Latest Publications

Abstract:
[Purpose of Review:] This paper provides an overview of integrating artificial intelligence (AI), particularly deep learning (DL), with ground-based LiDAR point clouds for forest monitoring. It identifies trends, highlights advancements, and discusses future directions for AI-supported forest monitoring.

[Recent Findings:] Recent studies indicate that DL models significantly outperform traditional machine learning methods in forest inventory tasks using terrestrial LiDAR data. Key advancements have been made in areas such as semantic segmentation, which involves labeling points corresponding to different vegetation structures (e.g., leaves, branches, stems), individual tree segmentation, and species classification. Main challenges include a lack of standardized evaluation metrics, limited code and data sharing, and reproducibility issues. A critical issue is the need for extensive reference data, which hinders the development and evaluation of robust AI models. Solutions such as the creation of large-scale benchmark datasets and the use of synthetic data generation are proposed to address these challenges. Promising AI paradigms like Graph Neural Networks, semi-supervised learning, self-supervised learning, and generative modeling have shown potential but are not yet fully explored in forestry applications.

[Summary:] The review underscores the transformative role of AI, particularly DL, in enhancing the accuracy and efficiency of forest monitoring using ground-based 3D point clouds. To advance the field, there is a critical need for comprehensive benchmark datasets, open-access policies for data and code, and the exploration of novel DL architectures and learning paradigms. These steps are essential for improving research reproducibility, facilitating comparative studies, and unlocking new insights into forest management and conservation.

Keywords:
Deep learning, Machine learning, Forest inventory, Tree characteristics, Open data, Precision forestry, LiDAR, TLS

Abstract:
The key to tactile sensors' sliding perception is the stick-slip modulation of the soft material through surface design. Herein, in-situ sliding tests were conducted on polydimethylsiloxane (PDMS) film/substrate bilayer structures (PF/SBS) with three surface adhesion characteristics tailored by crosslinking degrees of PDMS film. Microscopic damage mechanisms during Schallamach wave propagation were analyzed using mixed-mode cohesive contact models. Intermolecular interaction mechanisms at microscopic crack tips were also explored using PDMS-Silica (SiO2) molecular models with varying PDMS crosslinking degrees. The Schallamach waves and tangential force strongly depended on the crosslinking degree of PDMS film. The varying effects of crosslinking degree on normal and tangential separation mechanisms lead to a transition in Schallamach wave damage from mixed mode to Mode II during propagation.

Keywords:
Stick-slip,Film/substrate bilayer structures,Cohesive contact model,Intermolecular interaction

Abstract:
The urea oxidation reaction (UOR) is characterized by a lower overpotential compared to the oxygen evolution reaction (OER) during electrolysis, which facilitates the hydrogen evolution reaction (HER) at the cathode. Charge
distribution, which can be modulated by the introduction of a heterostructure, plays a key role in enhancing the adsorption and cleavage of chemical groups within urea molecules. Herein, a facile all-room temperature synthesis of functional heterojunction NiCo2 S4 /CoMo 2 S4 grown on carbon cloth (CC) is presented, and the as-prepared electrode served as a catalyst for simultaneous hydrogen evolution and urea oxidation reaction. The Density
Functional Theory (DFT) study reveals spontaneous transfer of charge at the heterointerface of NiCo 2 S4 /CoMo 2 S4 , which triggers the formation of localized electrophilic/nucleophilic regions and facilitates the adsorption of electron donating/electron withdrawing group in urea molecules during the UOR. The NiCo2 S4 /CoMo 2 S4 // NiCo 2 S4 /CoMo 2 S4 electrode pair required only a cell voltage of 1.17 and 1.18 V to deliver a current density of 10 and 100 mA cm−2 respectively in urea electrolysis cell and display very good stability. Tests performed in real urine samples show similar catalytic performance to urea electrolytes, making the work one of the best transition
metal-based catalysts for UOR applications, promising both efficient hydrogen production and urea decomposition.

Abstract:
Many real-world applications demand accurate and fast predictions, as well as reliable uncertainty estimates. However, quantifying uncertainty on high-dimensional predictions is still a severely under-investigated problem, especially when input–output relationships are non-linear. To handle this problem, the present work introduces an innovative approach that combines autoencoder deep neural networks with the probabilistic regression capabilities of Gaussian processes. The autoencoder provides a low-dimensional representation of the solution space, while the Gaussian process is a Bayesian method that provides a probabilistic mapping between the low-dimensional inputs and outputs. We validate the proposed framework for its application to surrogate modeling of non-linear finite element simulations. Our findings highlight that the proposed framework is computationally efficient as well as accurate in predicting non-linear deformations of solid bodies subjected to external forces, all the while providing insightful uncertainty assessments.

Keywords:
Surrogate modeling,Deep neural networks,Gaussian proces,Autoencoders,Uncertainty quantification,Finite element method

Abstract:
This article aims to explore the potential of using low-cost devices (iPhone and iPad) equipped with LiDAR scanners in the context of measuring the volume of concrete-plastic specimens with complex shapes. The goal was to assess whether these tools can support or even replace traditional metrology methods. For the purpose of the research program concrete-plastic columns with very complex cross-sections (based on different fractals) were harnessed. The research team was focused on analyzing the potential of using this technology to measure the volume of concrete-plastic structural elements created with the help of 3D printing. The tests were conducted under laboratory conditions. The effectiveness of the proposed approach was compared with results obtained using photogrammetry. The challenges of measurement accuracy, the impact of specimen shape, the impact of material and needed optimization of post-processing on the achieved results were also discussed.

Keywords:
3-D printing, LiDAR, Scanning, Fractals, Concrete

Abstract:
Background
Metrics evaluating the functional quality of red blood cells (RBCs) must consider their role in oxygen delivery. Whereas oxygen-carrying capacity is routinely reported using haemoglobin assays, the rate of oxygen exchange is not measured, yet also important for tissue oxygenation. Since oxygen-unloading depends on the diffusion pathlength inside RBCs, cell geometry offers a plausible surrogate.
Methods
We related the time-constant of oxygen-unloading (τ), measured using single-cell oxygen saturation imaging, with flow-cytometric variables recorded on a haematology analyser. Experiments compared freshly-drawn RBCs with stored RBCs, wherein metabolic run-down and spherical remodelling hinder oxygen unloading.
Findings
Multivariable regression related τ to a ratio of side- and forward-scatter, referred to herein as FlowScore. FlowScore was able to distinguish, with sensitivity and specificity >80%, freshly drawn blood from blood that underwent storage-related kinetic attrition in O2-handling. Moreover, FlowScore predicted τ restoration upon biochemical rejuvenation of stored blood. Since RBC geometry and metabolic state are related, variants of FlowScore estimated [ATP] and [2,3-diphosphoglycerate]. The veracity of FlowScore was confirmed by four blood-banking systems (Australia, Canada, England, Spain). Applying FlowScore to data from the COMPARE study revealed a positive association with the time-delay from sample collection to measurement, which was verified experimentally. The LifeLines dataset revealed age, sex, and smoking among factors affecting FlowScore.
Interpretation
We establish FlowScore as a widely-accessible and cost-effective surrogate of RBC oxygen-unloading kinetics. As a metric of a cellular process that is sensitive to storage and disease, we propose FlowScore as an RBC quality marker for blood-banking and haematology.

Keywords:
Haematology,Erythrocytes,Storage lesion,Assay,Oxygen transport,Transfusion

Abstract:
Silicon carbide and an aluminum alloy (SiC/AlSi12) composite are obtained during the pressurized casting process of the aluminum alloy into the SiC foam. The foam acts as a high-stiffness skeleton that strengthens the aluminum alloy matrix. The goal of the paper is to describe the behavior of the material, considering its internal structure. The composite’s structure is obtained by using X-ray computing tomography. The thorough computer tomography analysis allows for the high-precision identification of the shape and distribution of the pores in the matrix. The computational model prepared in the framework of the peridynamics method takes into account the pores and their shape. The pores in the structure appeared in the fabrication process. The impact of a steel ball is studied employing the peridynamics method. The sample without any porosity and a porous one were considered during the analyses. It has been found that the porosity of the matrix influences the plastic strain development, but the damage parameter in the skeleton is not affected significantly. The damage advancement in the skeleton during the process is practically identical in both cases. The equivalent plastic strain field is much smoother in a non-porous matrix than in a porous one. The porous matrix has high equivalent
plastic strain concentrations, much higher than the non-porous matrix. The shape of the sample is affected by the porosity of the matrix. The sample with a porous matrix tends to fragment, and it shows a tendency towards spallation when in close contact to the surface with the base.

Keywords:
interpenetrated composite, impact, damage, perydynamics

Abstract:
Cross-linking bonds adjacent polymer chains into a three-dimensional network. Cross-linked poly(vinyl alcohol) (PVA) turns into a hydrogel, insoluble structure exhibiting outstanding sorption properties. As an electrospinnable polymer, PVA enables the creation of nanofibrous hydrogels resembling biological tissues, thus ideal for nature-inspired platforms. PVA properties are easily adjustable through additives and an appropriate cross-linking method. Drawing inspiration from environmentally safe approaches, this work developed a new “green” method of low-temperature PVA cross-linking. Nanofibers were electrospun from a precursor solution of PVA dissolved in fresh lemon juice, stabilized by heating at 60 °C for 7 days, and thoroughly characterized. The obtained nanoplatform demonstrated long-term stability and enhanced mechanical properties. Its biocompatibility was confirmed, and its antibacterial and health-promoting effects were attributed to lemon juice-rich in vitamin C, a potent antioxidant with anti-inflammatory properties. The developed system has future potential for use in the biomedical engineering field as a dressing accelerating wound healing.

Abstract:
The tensile behavior and damage mechanisms of functionally graded (FG) Al-SiC composites are systematically investigated using molecular dynamics (MD) simulations. A comprehensive set of large-scale MD simulations is conducted on FG composites composed of three layers reinforced with different volume fractions of randomly distributed three-dimensional SiC particles. This work introduces a novel approach by modeling the reinforcement ceramic as three-dimensional particles, thereby more accurately representing the FG composite microstructure. Predictions of the model for Young's moduli of composites align with experimental data from the literature. The yield and ultimate tensile strength are overestimated due to the high applied strain rates and idealized crystal structures used in the simulations, which lack common defects such as vacancies and dislocations. The model is utilized to study the influence of reinforcement particle shape, size, orientation, and distribution on the tensile and damage behavior of composites. The FG composites reinforced with cubic particles demonstrate lower yield and tensile strength than those with spherical particles, primarily due to the high-stress concentrations around the corners of the cubic reinforcements. Reducing the size of SiC particles enhances the elastic modulus, yield, and tensile strength of the FG composites. It is shown that the stiffness of the FG composites reinforced with rectangular prisms can be effectively tailored by changing the orientation of the reinforcements. When SiC rectangular prisms are aligned along the tensile direction, the resulting FG composites exhibit higher yield and tensile strength. This work offers fundamental atomistic insights that help design FG composites with better mechanical performance.

Abstract:
In this paper, we demonstrate that torsional surface elastic waves can propagate along the curved surface of a metamaterial elastic rod (cylinder) embedded in a conventional elastic medium. The crucial parameter of the metamaterial rod is its elastic compliance s441(ω), which varies as a function of frequency ω analogously to the dielectric function ε(ω) in Drude’s model of metals. As a consequence, the elastic compliance s441(ω) can take negative values s441(ω)< 0 as a function of frequency ω. Negative elastic compliance s441(ω) enables the emergence of new surface states, i.e., new types of surface elastic waves. In fact, the proposed torsional elastic surface waves can be considered as an elastic analog of Surface Plasmon Polariton (SPP) electromagnetic (optical) waves propagating along a metallic rod (cylinder) embedded in a dielectric medium. Consequently, we developed the corresponding analytical equations, for the dispersion relation and group velocity of the new torsional elastic surface wave. The newly discovered torsional elastic surface waves exhibit virtually all extraordinary properties of their electromagnetic SPP counterparts, such as strong subwavelength concentration of the wave energy in the vicinity of the cylindrical surface (r = a ) of the guiding rod, very low phase and group velocities, etc. Therefore, the new torsional elastic surface waves can be used in: (a) nearfield subwavelength acoustic imaging (super-resolution), (b) acoustic wave trapping (zero group and phase velocity), etc. Importantly, the newly discovered torsional elastic surface waves can form a basis for the development of a new generation of ultrasonic sensors (e.g., viscosity sensors), biosensors, and chemosensors with a very high mass sensitivity.

Keywords:
torsional elastic waves,elastic metamaterials ,negative elastic compliance ,dispersion curves ,phase velocity ,group velocity ,mass sensitivity ,viscosity sensors

Abstract:
The suitability of a range of interatomic potentials for elemental tin was evaluated in order to identify an appropriate potential for modeling the stanene (2D tin) allotropes. Structural and mechanical features of the flat (F), low-buckled (LB), high-buckled (HB), full dumbbell (FD), trigonal dumbbell (TD), honeycomb dumbbell (HD), and large honeycomb dumbbell (LHD) monolayer tin (stanene) phases, were gained by means of the density functional theory (DFT) and molecular statics (MS) calculations with ten different Tersoff, modified embedded atom method (MEAM), and machine-learning-based (ML-IAP) interatomic potentials. A systematic quantitative comparison and discussion of the results is reported.

Keywords:
2D materials, DFT, interatomic potentials

Abstract:
This study focuses on the development and characterization of a bulk Ti-Al-N
multiphase composite enriched with BN addition and sintered through hot pressing. The
research aimed to create a material with optimized mechanical and corrosion-resistant
properties suitable for demanding industrial applications. The composite was synthesized using a powder metallurgy approach with a mixture of AlN, TiN, and BN powders, processed under a high temperature and pressure. Comprehensive analyses, including microstructural evaluation, hardness testing, X-ray tomography, and electrochemical corrosion assessments, were conducted. The results confirmed the formation of a multiphase microstructure consisting of TiN, Ti₂AlN and Ti₃AlN phases. The microstructure was uniform with minimal porosity, achieving a hardness within the range of 500–540 HV2. Electrochemical tests revealed the formation of a passive oxide layer that provided moderate corrosion resistance in chloride-rich environment. However, localized pitting corrosion was observed under extreme conditions. The study highlights the potential of a BN admixture to enhance mechanical and corrosion-resistant properties and suggests directions for further optimization in sintering processes and material formulations.

Keywords:
AlN-TiN(BN) composite,hot-pressing,μCT,corrosion resistance

Abstract:
Correlation is the basic mechanism of every measurement model, as one never accesses the measured system directly. Instead, correlations are created, codifying information about the measurable property into the environment. Here, we address the problem of the emergence of physical reality from the quantum world by introducing a model that interpolates between weak and strong nonselective measurements for qudits. By utilizing Heisenberg-Weyl operators, our model suggests that independently of the interaction intensity between the system and the environment, full information about the observable of interest can always be obtained by making the system interact with many environmental qudits, following a quantum Darwinism framework.

Keywords:
zinc oxide (ZnO) nanoparticles, microwave hydrothermal method , microwave-assisted synthesis, near-band-edge (NBE) emission, deep-level emission (DLE), luminescent properties of ZnO, photoluminescence (PL), cathodoluminescence (CL), defect-related luminescence

Abstract:
Complete fractures of the third metacarpal bone (MC III) diaphysis pose a significant
clinical challenge, prompting advanced veterinary medicine to utilize constitutive and
biomechanical modeling to better understand bone behavior. This study aims to compare
the elastic modulus of the MC III cortical bone, supported by measurements of cortical
bone thickness and relative density, across the dorsal, lateral, medial, and palmar aspects of
the MC III, as well as to evaluate the cortical bone’s response to compressive forces applied
in different directions. Given the bone structure can exhibit sex-related differences, MC III
bones were isolated from six equine cadaver limbs collected exclusively from mares and
imaged using computed tomography (CT) to measure thickness and density. Cortical bone
samples were collected from the four aspects of the MC III and subjected to mechanical
testing followed by the elastic modulus calculation. Bone thickness and elastic modulus
varied across the MC III aspects. Thinner cortical bone on the palmar aspect coincided with
a lower sample reaction force-based elastic modulus in the externo-internal direction and a
lower axial compression force elastic modulus in the proximo-distal direction. Regardless
of the MC III aspect, the cortical bone demonstrated greater resistance to compressive forces
when loaded in the vertical plane than in the horizontal plane. The returning of different
values in mechanical tests depending on the direction of loading may be attributed to
the anisotropic behavior of the cortical bone, which may implicate the increased risk of
complete fractures of the MC III diaphysis due to a kick from another horse or a fall, rather
than from training or competition-related overload.

Keywords:
bone thickness, mechanical test, copression, bending, elastic modulus, equine

Abstract:
This study investigates the development and performance analysis of a supercapacitor using activated carbon synthesized from polyethylene oxide (PEO) as the electrode material, and a poly(vinylidene fluoride-co-hexafluoropropylene) (PVdF-HFP)-based polymer electrolyte, prepared using a solution-cast technique for dye-sensitized solar cell (DSSC) application. This paper deals with polyether-based electrochemical devices, where electrode material is developed by polyethylene oxide (PEO), while an electrolyte is prepared using PVdF-HFP. Detailed electrical and photoelectrochemical studies were carried out using various characterization tools, and the results are discussed in detail. Sandwich structure supercapacitors and DSSCs are developed using maximum conducting polymer electrolyte that has an ionic conductivity of (8.3 × 10−5) Scm−1, exhibiting a high specific capacitance of 395 Fg−1 and DSSC efficiency ranging from 1.6 to 3.5% under 1 sun condition. The findings underscore the capability of PEO-derived carbon and polymer electrolytes in improving the efficiency of energy storage and conversion systems.

Keywords:
Polyether, Activated carbon, Supercapacitor, Dye-sensitized solar cell

Abstract:
The paper examines the potential use of low-cost LiDAR for cave surveying. Mobile mapping using LiDAR complements traditional speleological surveying using a polygonal traverse. These methods assist each other, with one serving as an independent control measurement for the other, ultimately resulting in a more accurate 3D model. The testing results show that achieving high accuracy and detailed cave representation is possible using open hardware and open-source software. Both spacious and well-indented cave sections and narrow passages barely passable by humans were successfully mapped. The surveying process is significantly faster than traditional cave mapping, as drawing cave sketches by hand is unnecessary, being the most time-consuming task on site. This paper also presents a procedure for automated ground plan generation and profile generation from 3D point clouds, further expediting and simplifying the work for speleologists using scanning systems. Also, it is confirmed that the results are reproducible and do not depend on the subjective interpretation of the cartographer, as is the case with traditional speleological drawings.

Keywords:
cave mapping, mobile laser scanning, open hardware, open-source software, cave profiles

Abstract:
Tomonaga–Luttinger liquid (TLL) theory is a canonical formalism used to describe 1D metals, where the low-energy physics is determined by collective Bosonic excitations. Herein, a theoretical model to compute the parameters of Tomonaga–Luttinger liquid (TLL) in multiwalled nanotubes (MWNTs) is presented. MWNTs introduce additional complexity to the usual Fermionic chains due to interactions and hybridization between their multiple coaxial shells. A model in which conducting paths along the length of the MWNTs are randomly distributed among the shells is considered. Since the valley degree of freedom remains a good quantum number, the TLL description in addition to spin and charge contains also valley degree of freedom and hence four-mode description applies. The values of all four TLL parameters are obtained for this model. A surprising outcome is that the compressibility of the holon mode becomes a universal quantity, while the parameters of neutral modes will depend on the details of intershell coupling. Finally, experiments where predictions can be tested are proposed.

Abstract:
Taking into account energy demand a new highly conducting ionic liquid (IL) c (EmImTCM) mixed corn starch (CS) biopolymer electrolyte is synthesized for dual electrochemical application electric double layer capacitor (EDLC) and the dye-sensitized solar cell (DSSC) application. Electrical, structural, thermal, and optical studies are carried out in detail and presented in this communication. Maximum conducting IL-incorporated biopolymer electrolyte film has been sandwiched between electrodes to develop EDLC and DSSC. The sandwich-structured EDLC delivers a high specific capacitance of 250 F/gram while DSSC shows 1.44 % efficiency at one sun condition.

Keywords:
Corn starch, Biopolymer, XRD, TGA, EDLC, DSSC

Abstract:
The mechanical mismatch between microelectrode of brain–machine interfaces (BMIs) and soft brain tissue during electrophysiological investigations leads to inflammation, glial scarring, and compromising performance. Herein, a nanostructured, stimuli-responsive, conductive, and semi-interpenetrating polymer network hydrogel-based coated BMIs probe is introduced. The system interface is composed of a cross-linkable poly(N-isopropylacrylamide)-based copolymer and regioregular poly[3-(6-methoxyhexyl)thiophene] fabricated via electrospinning and integrated into a neural probe. The coating's nanofibrous architecture offers a rapid swelling response and faster shape recovery compared to bulk hydrogels. Moreover, the smart coating becomes more conductive at physiological temperatures, which improves signal transmission efficiency and enhances its stability during chronic use. Indeed, detecting acute neuronal deep brain signals in a mouse model demonstrates that the developed probe can record high-quality signals and action potentials, favorably modulating impedance and capacitance. Evaluation of in vivo neuronal activity and biocompatibility in chronic configuration shows the successful recording of deep brain signals and a lack of substantial inflammatory response in the long-term. The development of conducting fibrous hydrogel bio-interface demonstrates its potential to overcome the limitations of current neural probes, highlighting its promising properties as a candidate for long-term, high-quality detection of neuronal activities for deep brain applications such as BMIs.

Abstract:
The majority of the current cancer research is based on two-dimensional cell cultures and animal models. These methods have limitations, including different expressions of key factors involved in carcinogenesis and metastasis, depending on culture conditions. Addressing these differences is crucial in obtaining physiologically relevant models. In this manuscript we analyzed the plasticity of the expression of stem cell and epithelial/mesenchymal markers in breast cancer cells, depending on culture conditions. Significant differences in marker expression were observed in different growth models not
only between 2D and 3D conditions but also between two different 3D models. Differences observed in the levels of adherent junction protein E-cadherin in two different 3D models suggest that spatial parameters of cell growth and physical stress in the culture may affect
the expression of junction proteins. To provide an explanation of this phenomenon on the grounds of mechanobiology, these parameters were analyzed using a mathematical model of the 3D bioprinted cell culture. The finite element mechanical model generated in this study includes an extracellular matrix and a group of regularly placed cells. The single-cell model comprises an idealized cytoskeleton, cortex, cytoplasm, and nucleus. The analysis of the model revealed that the stress generated by external pressure is transferred between the cells, generating specific stress fields, depending on growth conditions. We have analyzed and compared stress fields in two different growth conditions, each corresponding to a different elasticity of extracellular matrix. We have demonstrated that soft matrix conditions produce more stress than a stiff matrix in the single cell as well as in cellular spheroids. The observed differences can explain the plasticity of E-cadherin expression in response to mechanical stress. These results should contribute to a better understanding of the differences between various growth models.

Keywords:
breast cancer, E-cadherin, mechanical stress, mathematical modeling, 3D bioprinting, complex systems, cell modeling, finite element method

Keywords:
zkSNARKs, Proof of Provenance, C2PA, Folding Schemes

Abstract:
AISI 304 steel experiences plastic flow instability during tension at room temperature if appropriate conditions are applied: a low strain rate and a sufficiently long gauge section of the sample. Then, propagation of the strain-localised band is activated. The electron backscattered diffraction (EBSD) research revealed that the reason is not only the difference in the content of the secondary phase – martensite α’ across the front face, but also the change in the volume fraction of austenite grains with Copper (Cu) and Goss-Brass (GB) orientation. Consequently, there is a division between two areas of high and limited deformation capacity. The tendency to maintain the continuity of deformation fields induces a massive rotation of austenite grains to Cu and GB orientations, which then undergo shearing and phase transformation. As a result, momentary strain accumulation leaves behind a stiffer zone. It is shown that the trapping of austenite grains prone to large deformations, inside the matrix with Cu and GB orientations, makes the formation of a plastic strain front possible. These features improve the ductility and strength of the 304 steel over 316L and 316LN at room temperature. The in-situ EBSD tension studies for the considered grades reveal three developing textures, with their comparison showing a gradual decrease in the preferences of the Cu and GB components. Thus, the appearing bands of the accumulated strains in 316L are limited by the Cu and GB areas, while such blockages do not occur in 316LN. The presented strengthening mechanism is confirmed by the digital image correlation (DIC) measurements. The root-mean-square (RMS) function of strains along the tensile direction, characterising the linear surroundings of the considered point, is introduced as a tool for linking the micro and macro scales. The experimental results provide a basis for explaining discontinuous front propagation at a temperature near 0 K.

Keywords:
Plastic flow instability, Martensitic transformation, Austenitic stainless steels, RMS strain amplitude

Abstract:
Mitochondrial proteins are transported and sorted to the matrix or inner mitochondrial membrane by the presequence translocase TIM23. In yeast, this essential and highly conserved machinery is composed of the core subunits Tim23 and Tim17. The architecture, assembly, and regulation of the human TIM23 complex are poorly characterized. The human genome encodes two paralogs, TIMM17A and TIMM17B. Here, we describe an unexpected role of the ovarian cancer immunoreactive antigen domain-containing protein 1 (OCIAD1) and the prohibitin complex in the biogenesis of human TIM23. Prohibitins were required to stabilize both the TIMM17A- and TIMM17B-containing variants of the translocase. Interestingly, OCIAD1 assembled with the prohibitin complex to protect the TIMM17A variant from degradation by the YME1L protease. The expression of OCIAD1 was in turn regulated by the status of the TIM23 complex. We postulate that OCIAD1 together with prohibitins constitute a regulatory axis that differentially regulates variants of human TIM23.

Keywords:
biogenesis, mitochondria, OCIAD1, prohibitin, TIM23 translocase

Abstract:
Plasmon-enhanced photo/electrocatalysis using hetero-nanostructures has emerged as a promising approach for boosting the efficiency and selectivity of photo/electrocatalytic reactions. Plasmonic nanostructures (PNSs), with their unique properties including localized surface plasmon resonance (LSPR), play a vital role in enhancing photo/electrocatalytic activities. By leveraging LSPR, PNSs can concentrate incident light, facilitate charge separation, and induce surface reactions, leading to improved catalytic performance. In this review, we provide a comprehensive analysis of the current state of knowledge in this field. We discuss the rational design and synthesis of hetero-nanostructures, focusing on the optimization of composition, size, shape, and interface properties. Furthermore, we explore various combinations of plasmonic sources with semiconductors of diverse morphologies to achieve enhanced photocatalytic activity. The reviewed research encompasses applications in water splitting, removal of organic pollutants, CO2 reduction, and energy conversion. We also address the challenges that need to be overcome, including optimization of materials, reproducibility, stability, band alignment, and understanding plasmon–material interactions in hetero-nanostructures. The review of future perspectives includes the integration of multiple functionalities, the exploration of novel plasmonic materials, and the translation of plasmon-enhanced photo/electrocatalysis into practical applications. The combination of plasmonics and nanotechnology can be used to advance green technologies and address pressing global issues.

Keywords:
Plasmons, Heterostructures, Energy conversion, Sustainable energy, Nanotechnology, Water-splitting, Interfacial properties, Photocatalysis, Surface reactions, Catalysts and Catalysis

Abstract:
Sialodacryoadenitis virus (SDAV) has been identified as the etiological agent responsible for the respiratory system and salivary gland infections in rats. The existing literature on SDAV infections is insufficient to address the topic adequately, particularly in relation to the central nervous system. In order to ascertain how SDAV gains access to neuronal cells and subsequently exits, our attention was focused on the small molecule valosin-containing protein (VCP), which is an ATPase. VCP is acknowledged for its function in the ubiquitin-mediated proteasomal degradation of proteins, including those of viral origin. To ascertain the potential influence of VCP on SDAV replication and egress, high-content screening was employed to determine the viral titer and protein content. Western blot analysis was employed to ascertain the relative expression of VCP. Real-time imaging of SDAV-infected cells and confocal imaging for qualitative morphological analysis were conducted. The Eeyarestatin I (EerI) inhibitor was employed to disrupt VCP involvement in the endoplasmic reticulum-associated protein degradation pathway (ERAD) in both pre- and post-incubation systems, with concentrations of 5 μM/mL and 25 μM/mL, respectively. We demonstrated for the first time that SDAV productively replicates in cultured primary neurons. VCP expression is markedly elevated during SDAV infection. The application of 5 μM/mL EerI in the post-treatment system yielded a statistically significant inhibition of the SDAV yield. It is likely that this modulates the efficacy of virion assembly by arresting viral proteins in the submembrane area.

Keywords:
SDAV,VCP,primary neurons,virion assembly,ERAD,eeyarestatin I

Abstract:
In metal single crystals, the observed formation of deformation banding pattern has been explained by greater latent hardening of slip systems than their self-hardening, which promotes spatial segregation of plastic slips and lamination towards single-slip domains. Numerical studies focusing on the formation of deformation bands usually involved initial imperfections, boundary-induced heterogeneity, or the postulate of minimal global energy expenditure which additionally promoted non-uniformity of deformation. This article analyses the case when no such mechanism enforcing locally non-uniform deformation is implemented in the finite element (FE) method, while the global system of equations of incremental equilibrium is solved in a standard way. The new finding in this paper is that the deformation banding pattern can appear spontaneously in FE simulations of homogeneous single crystals even in the absence of any mechanism favouring deformation banding in the numerical code. This has been demonstrated in several examples in the small strain formalism using a plane-strain model in which the twelve fcc slip systems are reduced to three effective plastic slip mechanisms. Incremental slips are determined at the Gauss-point level either by incremental work minimization in the rate-independent case or by rate-dependent regularization. In the rate-independent approach, the trust-region algorithm is developed for the selection of active slip systems with the help of the augmented Lagrangian method. Conditions under which a banding pattern appears spontaneously or is suppressed are discussed. In particular, a critical rate sensitivity exponent is identified.

Keywords:
Crystal plasticity, Small strain, Slip-system selection, Path instability, Microstructure formation, Finite element method

Abstract:
Hemoglobin (Hb) performs its physiological function within the erythrocyte. Extracellular Hb has prooxidative and proinflammatory properties and is therefore sequestered by haptoglobin and bound by the CD163 receptor on macrophages. In the present study, we demonstrate a novel process of Hb uptake by macrophages independent of haptoglobin and CD163. Unexpectedly, macrophages do not degrade the entire Hb, but instead transfer it to neighboring cells. We have shown that the phenomenon of Hb transfer from macrophages to other cells is mainly mediated by extracellular vesicles. In contrast to the canonical Hb degradation pathway by macrophages, Hb transfer has not been reported before. In addition, we have used the process of Hb transfer in anticancer therapy, where macrophages are loaded with a Hb-anticancer drug conjugate and act as cellular drug carriers. Both mouse and human macrophages loaded with Hb-monomethyl auristatin E (MMAE) effectively killed cancer cells when co-cultured in vitro.

Keywords:
Hemoglobin,Macrophages,CD163,Extracellular vesicles,Monomethyl auristatin E

Abstract:
Spatially-resolved modeling of deformation twinning and its interaction with plastic slip is achieved by coupling the phase- field method and crystal plasticity theory. The intricate constitutive relations arising from this coupling render the resulting computational model prone to inefficiencies and lack of robustness. Accordingly, together with the inherent limitations of the phase-field method, these factors may impede the broad applicability of the model. In this paper, our recent phase-field model of coupled twinning and crystal plasticity is the subject of study. We delve into the incremental formulation and computational treatment of the model and run a thorough investigation into its computational performance. We focus specifically on evaluating the efficiency of the finite-element discretization employing various element types, and we examine the impact of mesh density. Since the micromorphic regularization is an important part of the finite-element implementation, the effect of the micromorphic regularization parameter is also studied.

Keywords:
Deformation twinning, Microstructure, Phase-field method, Crystal plasticity, Finite element method

Abstract:
The presence and extent of metastatic disease in axillary lymph nodes (ALNs) in the setting of breast cancer (BC) are important factors for staging and therapy planning. The purpose of this study was to perform a multiparametric sonographic evaluation of ALNs to better differentiate between benign and metastatic nodes. Ninety-nine patients (mean age 54.1 y) with 103 BCs were included in this study, and 103 ALNs were examined sonographically. B-mode parameters, such as size in two dimensions, shape, cortical thickness and capsule outline, were obtained, followed by vascularity assessment via colour Doppler and microflow imaging and stiffness evaluation via shear wave elastography. Postoperative histopathological evaluation was the reference standard. In the statistical analysis, logistic regression and ROC analyses were conducted to search for feature patterns of both types of ALNs to evaluate the prediction qualities of the analysed variables and their combinations. For a cortex larger than 3 mm, without a circumscribed margin of the LN capsule and SWE (E max > 26 kPa), the AUC was 0.823. Multiparametric assessment, which combined conventional US, quantitative SWE and vascularity analysis, was superior to the single-parameter approach in the evaluation of ALNs.

Abstract:
Bone defects resulting from congenital anomalies and trauma pose significant clinical challenges for orthopedics surgeries, where bone tissue engineering (BTE) aims to address these challenges by repairing defects that fail to heal spontaneously. Despite numerous advances, BTE still faces several challenges, i.e., difficulties in detecting and tracking implanted cells, high costs, and regulatory approval hurdles. Biomaterials promise to revolutionize bone grafting procedures, heralding a new era of regenerative medicine and advancing patient outcomes worldwide. Specifically, novel bioactive biomaterials have been developed that promote cell adhesion, proliferation, and differentiation and have osteoconductive and osteoinductive characteristics, stimulating tissue regeneration and repair, particularly in complex skeletal defects caused by trauma, degeneration, and neoplasia. A wide array of biological therapeutics for bone regeneration have emerged, drawing from the diverse spectrum of gene therapy, immune cell interactions, and RNA molecules. This review will provide insights into the current state and potential of future strategies for bone regeneration.

Abstract:
Bone defects and fractures present significant clinical challenges, particularly in orthopedic and maxillofacial applications. While minor bone defects may be capable of healing naturally, those of a critical size necessitate intervention through the use of implants or grafts. The utilization of traditional methodologies, encompassing autografts and allografts, is constrained by several factors. These include the potential for donor site morbidity, the restricted availability of suitable donors, and the possibility of immune rejection. This has prompted extensive research in the field of bone tissue engineering to develop advanced synthetic and bio-derived materials that can support bone regeneration. The optimal bone substitute must achieve a balance between biocompatibility, bioresorbability, osteoconductivity, and osteoinductivity while simultaneously providing mechanical support during the healing process. Recent innovations include the utilization of three-dimensional printing, nanotechnology, and bioactive coatings to create scaffolds that mimic the structure of natural bone and enhance cell proliferation and differentiation. Notwithstanding the advancements above, challenges remain in optimizing the controlled release of growth factors and adapting materials to various clinical contexts. This review provides a comprehensive overview of the current advancements in bone substitute materials, focusing on their biological mechanisms, design considerations, and clinical applications. It explores the role of emerging technologies, such as additive manufacturing and stem cell-based therapies, in advancing the field. Future research highlights the need for multidisciplinary collaboration and rigorous testing to develop advanced bone graft substitutes, improving outcomes and quality of life for patients with complex defects.

Keywords:
bone regeneration, fractures, bone grafts, bone substitutes, bone implants

Abstract:
There exists a growing discourse around the domination of Big Tech on the landscape of artificial intelligence (AI) research, yet our comprehension of this phenomenon remains cursory. This paper aims to broaden and deepen our understanding of Big Tech's reach and power within AI research. It highlights the dominance not merely in terms of sheer publication volume but rather in the propagation of new ideas or memes. Current studies often oversimplify the concept of influence to the share of affiliations in academic papers, typically sourced from limited databases such as arXiv or specific academic conferences.
The main goal of this paper is to unravel the specific nuances of such influence, determining which AI ideas are predominantly driven by Big Tech entities. By employing network and memetic analysis on AI-oriented paper abstracts and their citation network, we are able to grasp a deeper insight into this phenomenon. By utilizing two databases: OpenAlex and S2ORC, we are able to perform such analysis on a much bigger scale than previous attempts.
Our findings suggest that while Big Tech-affiliated papers are disproportionately more cited in some areas, the most cited papers are those affiliated with both Big Tech and Academia. Focusing on the most contagious memes, their attribution to specific affiliation groups (Big Tech, Academia, mixed affiliation) seems equally distributed between those three groups. This suggests that the notion of Big Tech domination over AI research is oversimplified in the discourse.

Keywords:
Knowledge diffusion, Novelty, Affiliation influence, Big tech impact, Complex networks, Natural language processing

Abstract:
Bacterial infections can lead to severe complications that adversely affect wound healing. Thus, the development of effective wound dressings has become a major focus in the biomedical field, as current solutions remain insufficient for treating complex, particularly chronic wounds. Designing an optimal environment for healing and tissue regeneration is essential. This study aims to optimize a multi-functional 3D printed hydrogel for infected wounds. A dexamethasone (DMX)-loaded electrospun mat, incorporated with gold nanorods (AuNRs), is structured into short filaments (SFs). The SFs are 3D printed into gelatine methacrylate (GelMA) and sodium alginate (SA) scaffold. The photo-responsive AuNRs within SFs significantly enhanced DXM release when exposed to near-infrared (NIR) light. The material exhibits excellent photothermal properties, biocompatibility, and antibacterial activity under NIR irradiation, effectively eliminating Staphylococcus aureus and Escherichia coli in vitro. In vivo, material combined with NIR light treatment facilitate infectes wound healing, killing S. aureus bacteria, reduced inflammation, and induced vascularization. The final materials’ shape can be adjusted to the skin defect, release the anti-inflammatory DXM on-demand, provide antimicrobial protection, and accelerate the healing of chronic wounds.

Abstract:
This paper presents the results of research on the kinetics of transformations in the two-phase (α + β) Ti-6Al-4V alloy. The transformation start and end temperatures during heating at different rates were determined using a dilatometer. A modified dilatometer was employed, equipped with an acoustic emission measurement apparatus and software enabling the assessment of sample dimensional changes during heating and cooling. The results were obtained in the form of dilatometric curves. Additionally, the occurrence of the transformation was confirmed by acoustic emission signals. In the study of the Ti-6Al-4V alloy, acoustic emission refers to the application of this non-destructive technique to monitor the alloy’s behavior during thermal processes. As the temperature increased, regardless of the heating rate, the α→β transformation was observed to occur after exceeding 900 °C. Within the transformation range, acoustic emission signals were recorded. Moreover, it was found that the applied research methods enabled the identification of signal components originating from the transformation. The application of acoustic methods in the analysis of phase transformations opens new possibilities for their use in industry.

Keywords:
Ti-6Al-4V alloy, microstructure, dilatometric tests, acoustic emission (EA)

Abstract:
The study investigated the effect of the oxidation–reduction cycles on the structure and corrosion resistance of the Haynes 282 nickel superalloy at ambient and elevated temperatures. The comparative studies were performed on specimens produced by the Powder Bed Fusion-Laser Beam (PBF-LB) process and those in the as-received state. The microstructure of the PBF-LB specimens was studied using optical and scanning electron microscopy, whereas the chemical composition of the scale formed after isothermal oxidation in an air atmosphere at 750°C was analysed using energy-dispersive X-ray spectroscopy and X-ray Photoelectron Spectroscopy. The phase composition of the formed scale was determined by X-ray diffraction. Laboratory-induced hydrogen atmosphere was adopted through cathodic charging. A comparison of corrosion resistance was carried out on two types of Haynes 282 specimens, before and after the oxidation and cathodic charging processes. It was found that PBF-LB process could be effectively used to manufacture Haynes 282 nickel superalloy with low porosity and a fine crystalline microstructure. The low-porous, fine-crystalline microstructure of the tested specimens produced by the PBF-LB technique exhibited good resistance to electrochemical corrosion, slightly lower than wrought Haynes 282 nickel superalloy specimens.

Keywords:
corrosion, DMLS, haynes 282 nickel superalloy, hydrogen, oxidation

Abstract:
Artificial intelligence and machine learning (ML) approaches have recently been getting much of researchers’ attention. The growing interest in these methods results from the fast development of machine learning algorithms in the last few years, especially artificial neural networks. In this review, we pay attention to the need and benefits that ML approaches can bring to tissue engineering (TE). We critically evaluate the possibilities of using the ML approaches in the tissue engineering field. We consider various paths of its utility in the TE, such as scaffold design, predicting the biological response to the scaffold, optimizing drug delivery approaches, supporting image analysis, and modeling scaffold in vivo performance. The current status of ML implementation is presented and supported by many study examples. On the other hand, we analyze the present difficulties and challenges in implementing ML approaches to tissue engineering, including the quality of published data, databases and repositories availability, the need for experiment and results publishing standardization, and ethical issues. Additionally, we assess the available natural language processing tools that could support TE research.

Keywords:
ultrasound imaging,abdominal ultrasound,nonlinear propagation,tissue harmonic imaging,nonlinearity index

Abstract:
In this work, we explore the notions unextendible product basis and uncompletability for operators which remain positive under partial transpose. Then, we analyze their connections to the ensembles which are many-copy indistinguishable under local operations and classical communication (LOCC). We show that the orthogonal complement of any bipartite pure entangled state is spanned by product states which form a nonorthogonal unextendible product basis (nUPB) of maximum cardinality. This subspace has one to one correspondence with the maximum dimensional subspace where there is no orthonormal product basis. Due to these, the proof of indistinguishability of a class of ensembles under LOCC in many-copy scenario becomes simpler. Furthermore, it is now clear that there are several many-copy indistinguishable ensembles which are different construction-wise. But if we consider the technique of proving their indistinguishability property under LOCC, then, for many of them it can be done using the general notion of unextendible product basis. Explicit construction of the product states, forming nUPBs is shown. Thereafter, we introduce the notion of positive partial transpose uncompletability to unify different many-copy indistinguishable ensembles. We also report a class of multipartite many-copy indistinguishable ensembles for which local indistinguishability property increases with decreasing number of mixed states.

Keywords:
Unextendibility, Uncompletability, Many-copy indistinguishability, LOCC, PPT-POVM

Abstract:
We consider the problem of existence and properties of pulse solutions to a system of equations modeling fast calcium waves in long cells. These waves have the speed up to 1000 μm/s. They propagate via the inflow of calcium ions from the extracellular space through the mechanically stimulated membrane channels. The channels open due to mechano-chemical interaction, in which stretching of the cell's membrane at a point opens the calcium channels at neighboring points due to the forces exerted by the actomyosin network. The existence of homoclinic solutions is based on the celebrated exchange lemma, which cannot be applied straightforwardly due to some specificities of the model equations.

Keywords:
calcium signaling, exchange lemma, homoclinic traveling waves

Abstract:
Human Respiratory Syncytial Virus (hRSV), a prevalent respiratory pathogen affecting various age groups, can trigger prolonged and intense inflammation in humans. The severity and outcome of hRSV infection correlate with elevated levels of pro-inflammatory agents, yet the underlying reasons for this immune system overstimulation remain elusive. We focused on the impact of hRSV non-structural proteins, NS1 and NS2, on immune response within epithelial cells. Available data indicates that these proteins impair the interferon pathway. We reinforce that NS1 and NS2 induce heightened secretion of the pro-inflammatory cytokines IL-6 and CXCL8. We also indicate that hRSV non-structural proteins provoke differential gene expression of human host FosB and long non-coding RNAs (MALAT1, RP11-510N19.5). It suggests an impact of NS molecules beyond IFN pathways. Thus, new light is shed on the interplay between hRSV and host cells, uncovering unexplored avenues of viral interference, especially the NS2 role in cytokine expression and immune modulation.

Keywords:
Human respiratory syncytial virus, Non-structural protein 1, Non-structural protein 2, Cytokines, MALAT1 long non-coding RNA

Abstract:
Mean-field modeling based on the Eshelby inclusion problem poses some difficulties when the non-linear Maxwell-type constitutive law is used for elasto–viscoplasticity. One difficulty is that this behavior involves different orders of time differentiation, which leads a long-term memory effect. One of the possible solutions to this problem is the additive interaction law. Generally, mean field models solely use the mean values of stress and strain fields per phase, while variational approaches consider the second moments of stresses and strains. It is seen that the latter approach improves model predictions allowing to account for stress fluctuation within the phases. However, the complexity of the variational formulations still makes them difficult to apply in the large scale finite element calculations and for non-proportional loadings. Thus, there is a need to include the second moments within homogenization models based on the additive interaction law. In the present study, the incorporation of the second moments of stresses into the formulation of the additive Mori–Tanaka model of two-phase elastic–viscoplastic material is discussed. A modified tangent linearization of the viscoplastic law is proposed, while the Hill–Mandel’s lemma is used to track the evolution of second moments of stresses. To study the model performance and efficiency, the results are compared to the full-field numerical calculations and predictions of other models available in the literature. Very good performance of the modified tangent linearization is demonstrated from these benchmarks for both monotonic and non monotonic loading responses.

Keywords:
Homogenization , Elasto-viscoplasticity, Non linear composites, Modified tangent linearization, Additive interaction law

Abstract:
Advanced flexible ionotronic devices have found excellent applications in the next generation of electronic skin (e-skin) development for smart wearables, robotics, and prosthesis. In this work, we developed transparent ionotronic-based flexible electrochemical capacitors using gel electrolytes and indium tin oxide (ITO) based transparent flexible electrodes. Different gel electrolytes were prepared using various salts, including NaCl, KCl, and LiCl in a 1:1 ratio with a polyvinyl alcohol (PVA) solution and compared its electrochemical performances. The interaction between gel electrolytes and ITO electrodes was investigated through the development of transparent electrochemical capacitors (TEC). The stable and consistent supply of ions was provided by the gel, which is essential for the charge storage and discharge within the TEC. The total charge contribution of the developed TECs is found from the diffusion-controlled mechanism and is measured to be 4.59 mC cm−2 for a LiCl/PVA-based gel. The prepared TEC with LiCl/PVA gel electrolyte exhibited a specific capacitance of 6.61 mF cm−2 at 10 μA cm−2. The prepared electrolyte shows a transparency of 99% at 550 nm and the fabricated TEC using LiCl/PVA gel exhibited a direct bandgap of 5.34 eV. The primary benefits of such ionotronic-based TEC development point to its potential future applications in the manufacturing of transparent batteries, electrochromic energy storage devices, ionotronic-based sensors, and photoelectrochemical energy storage devices.

Abstract:
Mobile devices such as smartphones, tablets or similar devices are becoming increasingly important as measurement devices in forestry due to their advanced sensors, including RGB cameras and LiDAR systems. This review examines the current state of applications of mobile devices for measuring biometric characteristics of individual trees and presents technologies, applications, measurement accuracy and implementation barriers. Passive sensors, such as RGB cameras have proven their potential for 3D reconstruction and analysing point clouds that improve single treelevel information collection. Active sensors with LiDAR-equipped smartphones provide precise quantitative measurements but are limited by specific hardware requirements. The combination of passive and active sensing techniques has shown significant potential for comprehensive data collection. The methods of data collection, both physical and digital, significantly affect the accuracy and reproducibility of measurements. Applications such as ForestScanner and TRESTIMATM have automated the measurement of tree characteristics and simplified data collection. However, environmental conditions and sensor limitations pose a challenge. There are also computational obstacles, as many methods require significant post-processing. The review highlights the advances in mobile device-based forestry applications and emphasizes the need for standardized protocols and cross-device benchmarking. Future research should focus on developing robust algorithms and cost-effective solutions to improve measurement accuracy and accessibility. While mobile devices offer significant potential for forest surveying, overcoming the above-mentioned challenges is critical to optimizing their application in forest management and protection.

Keywords:
mobile device, tree attributes , LiDAR, Photogrammetry

Abstract:
We employ pDyn (derived from ‘‘pandemics dynamics’’), an agent-based epidemiological model, to forecast the fourth wave of the SARS-CoV-2 epidemic, primarily driven by the Delta variant, in Polish society. The model captures spatiotemporal dynamics of the epidemic spread, predicting disease-related states based on pathogen properties and behavioral factors. We assess pDyn’s validity, encompassing pathogen variant succession, immunization level, and the proportion of vaccinated among confirmed cases. We evaluate its predictive capacity for pandemic dynamics, including wave peak timing, magnitude, and duration for confirmed cases, hospitalizations, ICU admissions, and deaths, nationally and regionally in Poland. Validation involves comparing pDyn’s estimates with real-world data (excluding data used for calibration) to evaluate whether pDyn accurately reproduced the epidemic dynamics up to the simulation time. To assess the accuracy of pDyn’s predictions, we compared simulation results with real-world data acquired after the simulation date. The findings affirm pDyn’s accuracy in forecasting and enhancing our understanding of epidemic mechanisms.

Keywords:
Epidemic dynamics , Epidemiology, Agent-based model, COVID-19

Abstract:
In this study, we introduce ‘‘instance loss functions’’, a new family of loss functions designed to enhance the
training of neural networks in the instance-level segmentation and detection of objects in biomedical image
data, particularly those of varied numbers and sizes. Intended to be utilized conjointly with traditional loss
functions, these proposed functions, prioritize object instances over pixel-by-pixel comparisons. The specific
functions, the instance segmentation loss (instance), the instance center loss (center), the false instance rate
loss (false), and the instance proximity loss (proximity), serve distinct purposes. Specifically, instance improves
instance-wise segmentation quality, center enhances segmentation quality of small instances, false minimizes
the rate of false and missed detections across varied instance sizes, and proximity improves detection quality
by pulling predicted instances towards the ground truth instances. Through the task of segmenting white
matter hyperintensities (WMH) in brain MRI, we benchmarked our proposed instance loss functions, both
individually and in combination via an ensemble inference models approach, against traditional pixel-level
loss functions. Data were sourced from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and the
WMH Segmentation Challenge datasets, which exhibit significant variation in WMH instance sizes. Empirical
evaluations demonstrate that combining two instance-level loss functions through ensemble inference models
outperforms models using other loss function on both the ADNI and WMH Segmentation Challenge datasets for
the segmentation and detection of WMH instances. Further, applying these functions to the segmentation of
nuclei in histopathology images demonstrated their effectiveness and generalizability beyond WMH, improving
performance even in contexts with less severe instance imbalance.

Keywords:
Instance-level segmentation loss, Instance-level detection loss, White matter hyperintensities, Brain lesions

Abstract:
This communication presents a comprehensive investigation into the impact of mixing on the synthesis of water-in-water Pickering emulsions. The approach employs commercial-grade oppositely charged nanoparticles within two distinct fluid phases, facilitating self-assembly and the formation of aggregates with variable sizes and compositions. Enhanced interfacial area, achieved through aggregate adsorption at the interface, elevates the Gibbs detachment energy of particles between the two aqueous phases, leading to stable emulsion formation. We further explore the effect of various mixing devices, including high-pressure and sonic wave mixing. Our findings reveal that mixing within the aqueous phase critically influences emulsion size, with sonicator-assisted mixing producing smaller droplets than homogenizer mixing. Both devices yield poly-dispersed droplet size distributions. Interestingly, the droplet size correlates well with the Hinze scale (hd), and the Kolmogorov length scale (ld) exhibits good correspondence within a specific operating range. The proposed method introduces a streamlined, one-step synthesis process for easy preparation, demonstrating excellent stability for a minimum of 30 days. This study pioneers the investigation of mixing effects within an aqueous two-phase system utilizing a Pickering emulsion template.

Abstract:
The synthesis of magnetically-active nickel-yttrium oxide (Ni-Y2O3) nanocomposite particles is described in this work. The investigated material is produced with a modified ultrasound spray pyrolysis (USP) device which differs from a common USP setup in terms of use of three independently heating zones. They provide a direct feed of H2 to the second reaction zone and allow controlling the formation of the nanocomposite particles and facilitating their post-reaction stabilization with polyvinylpyrrolidone (PVP). According to the morphological and structural studies, the Ni-Y2O3 material takes a form of nanoparticles whose sizes are not homogeneously distributed as well as shapes are not smooth due to the successful formation of composite material with two interpenetrating phases. Moreover, the organic layer is detected on the surface of the nanoparticles which confirms the presence of PVP stabilizer. The magnetic investigations confirm that the Ni-Y2O3 nanocomposite reveals a spin glass-like behavior in which a collective freezing of magnetic moments might occur due to the interparticle interactions between Ni nanocrystallites presented in the sample.

Abstract:
The dynamics of groups of non-touching particles settling under gravity in a crowded fluid medium are studied at the zero Reynolds number. It is assumed that the fluid velocity satisfies the Brinkman–Debye–Büche equations, and the particle dynamics are described in terms of the point-force model. The systems of particles at vertices of two or four horizontal regular polygons are considered that in the Stokes flow for a very long time do not destabilize, i.e., all the particles stay close to each other, performing periodic or quasiperiodic motions. It is known that such motions, as invariant manifolds, are essential for groups of particles at random initial positions to survive for a very long time and not destabilize. This work demonstrates that when the medium permeability is decreased, periodic motions cease to exist, and groups of particles split into smaller subgroups, moving away from each other. This mechanism seems to facilitate particle transport in a permeable medium.

Abstract:
Non-uniform distributions of various biological factors can be essential for tissue growth control, morphogenesis or tumor growth. The first model describing the emergence of such distributions was suggested by A. Turing for the explanation of cell differentiation in a growing embryo. In this model, diffusion-driven instability of the homogeneous in space solution appears due to the interaction of two or more morphogens described by a reaction–diffusion system of equations. In this work we suggest another mechanism of the emergence of spatial distributions in biological tissues based on local cell communication and global inhibition, and described by a nonlocal reaction–diffusion equation. Instability of the homogeneous in space solution leads to the emergence of stationary pulses and not of periodic solutions as in the case of Turing instability.

Keywords:
Nonlocal reaction–diffusion equation, Instability, Stationary pulses, Biological models

Abstract:
This paper shows the graphene and graphene oxide nanoflakes as the 0.1, 0.5, 1, 2, and 4 wt.% reinforcement of epoxy-resin matrix to enhance the thermal and mechanical characteristics of the composite. Experimental measurement of the glass transition temperature and thermal expansion coefficient indicated that the addition of nanostructural filler improving the glass transition temperature about ~12 oC for nanocomposite filled carbon-based nanoparticles for both heating and cooling cycles compared to the bare epoxy resin. Young's modulus measured by nanoindentation and the stress versus strain curves for different weight fractions of graphene nanoflakes additives during uniaxial compression and tension considered were obtained from the experiments. The distributions of strain field for the transverse, axial and shear components on the nanocomposites, during the uniaxial tension process for quasi-static strain rates, were analyzed. The tensile strengths show improvement for nanocomposites with less than 1 % weight fraction of carbon-based nanoparticles. The compressive yield stress increased to a maximal value (at the recorded peak on the curve) for an epoxy nanocomposite having 2 wt.% oxidized graphene flakes, where both parameters were enhanced with the oxidized form of graphene for the more effective dispersion in the epoxy resin matrix over the bare graphene filler.

Keywords:
epoxy resin, nanocomposite, carbon nanoparticles, tensile strength, compression strength, thermal stability

Abstract:
The superposition of causal orders shows promise in various quantum technologies. However, the fragility of quantum systems arising from environmental interactions, leading to dissipative behavior and irreversibility, demands a deeper understanding of the possible instabilities in the coherent control of causal orders. In this work, we employ a collisional model to investigate the impact of an open control system on the generation of interference between two causal orders. We present the environmental instabilities for the switch of two arbitrary quantum operations and examine the influence of environmental temperature on each potential outcome of control post-selection. Additionally, we explore how environmental instabilities affect protocol performance, including switching between mutually unbiased measurement observables and refrigeration powered by causal order superposition, providing insights into broader implications.

Abstract:
The paper examines the low-frequency reverberation sound field in coupled-room systems. In theoretical model, the modal expansion of sound pressure was applied, while in numerical procedure, the discrete Hilbert transform was used to determine the amplitude of decaying sound. Computer simulations were performed for a room system consisting of two connected rectangular rooms. Eigenfunctions and eigenfrequencies of this system were determined by the finite element method. Simulation results showed that for the hard-walled room system the sound decay is almost exponential for frequencies of modes localized in one of the subrooms. Acoustical treatment of the ceiling significantly reduced reverberation. However, due to beating effects and modal overlap, a large irregularity of sound decay curves has occurred. This makes it difficult to correctly qualify the sound decay, because in this case it is practically impossible to characterize the reverberation process with only one or at most two decay times.

Keywords:
room acoustics, coupled rooms, reverberant sound field, mode localization, sound decay

Abstract:
The long-term stability of alignment precision of microelectromechanical system accelerometers was evaluated. Four commercial biaxial accelerometers (two ADXL 202E and two ADXL 203 accelerometers by Analog Devices Inc.) were tested over a period of 20 and 15 years, respectively. The experimental studies were performed using a custom computer-controlled test rig and employing gravitational acceleration as the reference. Considerable changes in the existing misalignments were observed. It was found that not only misalignments between the sensitive axes changed over time, but due to some micro-movements within the mounting of the printed circuit board with the accelerometer chip, misalignments of the sensitive axes with respect to the mounting datum changed as well. Even though no bigger than 0.6°, the observed misalignments may considerably influence the accelerometer performance, especially in the case of tilt measurements. Some ways of increasing the considered long-term stability of printed circuit board mounting are proposed.

Keywords:
stability, aging, microelectromechanical systems (MEMS), misalignment

Abstract:
Introduction: Cognitive impairment (CI) is common in both end-stage kidney disease (ESKD) and alcohol-related liver cirrhosis. The aim of this study was to assess the prevalence and patterns of CI in patients awaiting kidney and liver transplantation, and to identify its determinants.

Methods: In this cross-sectional, prospective study, 31 consecutive patients with ESKD and 31 consecutive patients with alcohol-related liver cirrhosis, all currently on transplant waiting lists, were screened for cognitive decline using the Addenbrooke's Cognitive Examination. Medical history, demographics, and laboratory test results were also collected.

Results: The prevalence of CI among patients with ESKD and alcohol-related liver cirrhosis was 26% and 90%, respectively. In both groups, memory was the most affected cognitive domain, along with verbal fluency in patients with ESKD, and visuospatial abilities in patients with alcoholic cirrhosis. The most statistically significant increase in the prevalence of CI was found in patients with lower educational attainment, in both alcohol-related liver cirrhosis and ESKD populations as well as in older patients with alcoholic cirrhosis. Furthermore, better cognitive functioning in ESKD patients was associated with higher levels of total lymphocyte count and alanine transaminase (ALT), and in alcohol-related liver cirrhosis patients with higher levels of ALT and aspartate transaminase. A nonsignificant trend toward lower memory domain scores was also observed with increasing ammonia levels and increasing severity of liver disease (higher Child-Pugh scores). Finally, suboptimal performance on the screening test was correlated with the severity of liver disease as assessed by the Model for End-Stage Liver Disease Sodium (MELD-Na), but not at the statistically significant level.

Conclusions: The prevalence of CI, especially in patients with alcohol-related liver cirrhosis, is high and can be a significant clinical problem, negatively affecting the transplantation process. Routine screening tests in this group would contribute to the implementation of appropriate management, such as rehabilitation program or psychosocial treatments and facilitate the provision of specialized health care.

Keywords:
cognitive impairment, end‐stage kidney disease, end‐stage liver disease

Abstract:
The increasing groundwater pollution resulting from industrial dyes and pharmaceutical products, which come from various sources, requires urgent attention to implement effective remediation measures. We demonstrate that the rough particles studded with platinum (Pt) nanoparticles can be fabricated at room temperature straightforwardly and in a single step. These rough particles displayed a good catalytic power (100% removal efficiency) against a model industrial dye (methylene blue) and pharmaceutical residue (tetracycline) within a reasonable time scale. Characterization techniques such as X-ray diffraction (XRD), atomic force microscopy (AFM), and field emission scanning electron microscopy (FESEM) confirmed the uniform deposition of Pt nanoparticles on the surface of polystyrene particles, forming dense islands and the roughened surface. Further, we investigated the influence of particle size, concentration, and contact patterns on the performance of rough catalytic particles. The semi-batch conditions favoured the complete decomposition of tetracycline within 40 min, but the batch-wise operation offered a good contacting pattern for methylene blue, yielding a maximal output within 10 min. The kinetics of the heterogeneous catalytic process modelled by Langmuir-Hinshelwood kinetics (r = kKC/1 + KC) predicts that the given methylene blue decomposition reaction induced by the rough particles follows the pseudo-first-order kinetics. The rate constants for the reaction catalyzed by 0.6 and 1.0 m-sized rough particles are 0.048 and 0.032 min, respectively. Furthermore, we established the proof-of-concept using magnetically responsive nanoparticles for real-time applications, including decontamination and recovery of catalyst particles via an externally applied magnetic field in one cycle. Our proposed method helps achieve a near-100% degrading efficiency within 10 to 40 min at minimal catalytic particle concentration, i.e., 200 ppm. Since we can turn the rough particles into super-paramagnetic, we can recover and reuse them for several wastewater treatment cycles without incurring running costs.

Keywords:
Polystyrene (PS), Iron Oxide (IO), Plat- inum nanoparticles, Rough particles, Magnetically- responsive nanoparticles, Methylene blue, Tetracy- cline, Environmental remediation

Abstract:
With the rapid development and commercial interest in the organ-on-a-chip (OoC) field, there is a need for materials addressing key experimental demands and enabling both prototyping and large-scale production. Here, we utilized the gas-permeable, thermoplastic material polymethylpentene (PMP). Three methods were tested to prototype transparent PMP films suitable for transmission light microscopy: hot-press molding, extrusion, and polishing of a commercial, hazy extruded film. The transparent films (thickness 20, 125, 133, 356, and 653 µm) were assembled as the cell-adhering layer in sealed culture chamber devices, to assess resulting oxygen concentration after 4 days of A549 cell culture (cancerous lung epithelial cells). Oxygen concentrations stabilized between 15.6% and 11.6%, where the thicker the film, the lower the oxygen concentration. Cell adherence, proliferation, and viability were comparable to glass for all PMP films (coated with poly-L-lysine), and transparency was adequate for transmission light microscopy of adherent cells. Hot-press molding was concluded as the preferred film prototyping method, due to excellent and reproducible film transparency, the possibility to easily vary film thickness, and the equipment being commonly available. The molecular orientation in the PMP films was characterized by IR dichroism. As expected, the extruded films showed clear orientation, but a novel result was that hot-press molding may also induce some orientation. It has been reported that orientation affects the permeability, but with the films in this study, we conclude that the orientation is not a critical factor. With the obtained results, we find it likely that OoC models with relevant in vivo oxygen concentrations may be facilitated by PMP. Combined with established large-scale production methods for thermoplastics, we foresee a useful role for PMP within the OoC field.

Keywords:
polymethylpentene, gas permeability, organ-on-a-chip, prototyping thermoplastics, microfluidic device, microscopy

Abstract:
The objective of this examination was to test the aging resistance of the aluminous porcelain material C 130 type, when exposed to direct current (DC) high voltage. Long-term exposure to high DC voltages can potentially lead to various negative effects, in particular ionic current development in the porcelain material. This process may reduce the mechanical strength and, consequently, cause a failure. This problem has been noticed in the case of glass disc insulators. The samples were examined using the 3-point bending test, ultrasonic and microscopic analysis. No recordable degradation effects were found. Long-term impact of DC high voltage did not reduce the mechanical parameters or change the microstructure of the porcelain material.

Keywords:
DC high voltage, aluminous porcelain C 130, 3-point bending test, mechanical strength

Abstract:
The application of the acoustic emission (AE) method for the detection and recording of partial discharges (PD) occurring in a medium voltage switchgear model was presented in this paper. The results of AE measurements were presented in the form of spectrograms. The acoustic emission effect occurred when the applied voltage level reached values from 10 kV to 30 kV. The authors used devices and probes EA to record PD using the acoustic method. The presented equipment can also be intended for industrial applications. The original accomplishment of the presented work is the achievement of successful and repeatable results of partial discharge measurements using the acoustic method.

Keywords:
Partial Discharges (PD), Acoustic Emission (AE), Registration of Acoustic Emission signals

Abstract:
Hybrid-density-functional-theory calculations are used to evaluate the structural and electronic properties and formation energies of N-doped β-Ga2O3. Altogether, eleven interstitial (Ni) and three substitutional (NOI,II,III) impurity positions are investigated. Since direct evidence of N2 formation following the annealing of Ga2O3 and ZnO matrixes is revealed experimentally earlier, four complexes comprising two N atoms are also considered. It is determined that substitutional nitrogen defects act as deep acceptors, whereas the interstitial defects and N2-like complexes act as deep donors. Under Ga-rich growth conditions, substitutional nitrogen defects exhibit lower formation energies, with NOII defects being the most favorable. Under Ga-poor conditions, interstitial defects are more energetically desirable for a wide Fermi energy range, with Ni9 defect being the most favorable. The formation of the N2-like considered here at solely interstitial positions is energetically very expensive regardless of growth conditions. Finally, the Ni9–NOI complex is the most desirable one under Ga-rich conditions. This knowledge can serve as a basis for the development of optimal doping strategies, potentially leading to improved performance in future β-Ga2O3-based electronic devices.

Abstract:
This paper is devoted to multiscale modeling of cement composites. The need for this approach is due to the heterogeneous complex internal structure of the composite. A multiscale model of the composite was built and the results of computer simulations for the adopted parameters of the microstructure of the composite were presented, enabling a more detailed analysis of its mechanical and structural properties.

Keywords:
multiscale modeling,analysis of heterogeneity of cement composite structure,computer simulations

Abstract:
Thermoresponsive hydrogels provide a platform for sustained delivery of nanoparticles via nose-to-brain route by resisting mucociliary clearance to the enhanced mean residence time (MRT) of the formulation in the nasal cavity overcoming neurotoxicity induced by uncontrolled delivery of nanoparticles and accumulation in the brain when delivered alone. The reported study presents the synthesis of pullulan (PLN) based nanoparticles (PNP-EHBr) loaded with eletriptan hydrobromide (EHBr) via ionic gelation method having size between 26.65 nm and 29.59 nm after stability studies of 4 h incubation with an average zeta potential of 22.5 ± 0.1 mV and entrapment efficiency of 92.048%. F-127/F-68 based hyaluronic acid-co-pectin hydrogels of EHBr-loaded PLN nanoparticles thermoresponsive hydrogels (HAP-PNP-EHBr/T-Hg) were characterized via Fourier transform infrared spectroscopy (FTIR), X-ray diffraction, thermal analysis (TGA/DSC), and scanning electron microscopy and evaluated for their gelation time, gelation temperature, gel strength, cloud point, sol–gel fraction, ex-vivo permeation, etc. HAP-PNP-EHBr/T-Hg showed drug release in a controlled pattern in both phosphate-buffered saline (PBS) and simulated nasal fluid (SNF) i.e., 90.12 and 87.99, respectively, over 48 h, while PNP-EHBR, 99.44 and 97.53 in PBS and SNF, respectively, over 8 h. The controlled release and absorption of EHBr from HAP-PNP-EHBr/T-Hg and PNP-EHBr was estimated by an in-vivo pharmacokinetic study using high-performance liquid chromatography, MRT and area under the curve (AUC) were increased up to 11.337 ± 0.32 h and 3,104.73 ± 75.841 ng/mL*h, 11.088 ± 0.177 h and 3,906.64 ± 152.86 ng/mL*h in brain and blood respectively after IN administration. This work demonstrates the successful synthesis of a twofold drug delivery system with PLN-based nanoparticles (PNP-EHBr) loaded with EHBr laden F-127/F-68 based hyaluronic acid-co-pectin hydrogels (HAP-PNP-EHBr/T-Hg).

Keywords:
Biodegradable polymers, controlled delivery, nose-to-brain delivery, polymeric nanoparticles, self-assembling micelles, thermoresponsive hydrogels

Abstract:
Background. The coronavirus disease 2019 (COVID-19) pandemic has significantly accelerated the development and use of new healthcare technologies. While younger individuals may have been able to quickly embrace virtual advancements, older adults may still have different needs in terms of health communication.

Objectives. To identify areas of interest and preferred sources of information related to the COVID-19 pandemic among older adults and to verify their eHealth competencies.

Materials and methods. The study was conducted between February 2022 and July 2022. It included listeners from the University of the Third Age (U3A) and younger students. Both groups received information about the HealthBuddy+ chatbot, a questionnaire that addressed respondents’ interests about COVID-19, and the PL-eHEALS (eHealth Literacy Scale) questionnaire to measure their eHealth competencies.

Results. There were 573 participants in the study (U3A listeners – 303 participants, median age: 73 years (interquartile range (IQR): 69–77); young adult students – 270, median age: 24 years (IQR: 23–24). The primary source of information about COVID-19 for older adults was television (84.5%), and for younger adults, internet (84.4%). Among the older adults, only 17% ever interacted with a chatbot (younger adults – 78% respectively), and 19% considered it a trustworthy source of information on COVID-19 compared to 79% of younger respondents. Older adults and younger adults in our study were most interested in COVID-19 treatment methods (45.5% and 69.3%, respectively), symptoms of the disease (36.6% and 35.2%, respectively) and chronic diseases coexisting with COVID-19 (35.0% and 51.5%, respectively). However, their eHealth competencies were generally low (median (Me): 34; IQR: 30–39) compared to younger adults (Me: 42; IQR: 40–47).

Conclusions. Health education for older adults should be appropriately tailored to their current needs and differentiated. The level of eHealth competencies of older adults suggests that much work remains to narrow the gap between the eHealth competencies of the younger and older generations.

Keywords:
health education,older adults,information seeking,COVID-19

Abstract:
The tests were carried out for the selected 27MnCrB5-2 alloy steel with the addition of boron. The paper presents the kinetics of the ferritic transformation occurring under continuous cooling conditions. The temperatures of the beginning and end of the transformation of supercooled austenite were determined using a dilatometer. In addition, a waveguide and an acoustic sensor were installed in the device to receive acoustic emission signals. The results in the form of dilatometric curves were additionally confi rmed by the obtained acoustic emission signals. Based on the obtained microstructural results, it can be concluded that in the hardening process of 27MnCrB5-2 steel at the applied temperatures, complex transformations of austenite into ferrite and bainite occur. The use of acoustic methods in the fi eld of phase transformation issues creates the possibility of their application in industry.

Keywords:
Steel 27MnCrB5, dilatometric tests, acoustic emission (AE), microstructure

Abstract:
Research on the durability of structural concrete requires careful selection of aggregates, particularly considering their reactivity to alkali-silica reaction (ASR). The Miniature Concrete Prism Test (MCPT) allows for shortened testing time
and eliminates the need for aggregate crushing, making it a practical alternative to other methods. The aim of the research is to evaluate the reactivity of aggregate mixtures with varying mineral compositions. Research results confirm
the significant impact of fine aggregates on concrete expansion in the MCPT method in NaOH solution at 60°C. The observed expansion correlates with a reduction in concrete’s elastic modulus.
Badania nad trwałością betonu konstrukcyjnego wymagają starannej selekcji kruszyw, szczególnie uwzględniającej ich reaktywność na reakcję alkalia-krzemionka (ASR). Metoda Miniature Concrete Prism Test (MCPT) pozwala na skrócenie
czasu badania i eliminację konieczności rozdrabniania kruszywa, co czyni ją praktyczną alternatywą dla innych metod. Celem badań jest ocena reaktywności mieszaniny kruszyw o zróżnicowanym składzie mineralnym. Wyniki badań potwierdzają
znaczący wpływ kruszywa drobnego na ekspansję betonu w metodzie MCPT w roztworze NaOH w temp. 60°C. Obserwowana ekspansja koreluje z redukcją modułu sprężystości betonu.

Keywords:
alkali-silica reaction (ASR), concrete expansion, MCPT method, fine aggregate, durability, reakcja alkalia-krzemionka (ASR), ekspansja betonu, metoda MCPT, kruszywo drobne, trwałość

Abstract:
Context
SARS-CoV-2, responsible for COVID-19, has led to over 500 million infections and more than 6 million deaths globally. There have been limited effective treatments available. The study aims to find a drug that can prevent the virus from entering host cells by targeting specific sites on the virus’s spike protein.

Method
We examined 13,397 compounds from the Malaria Box library against two specific sites on the spike protein: the receptor-binding domain (RBD) and a predicted cryptic pocket. Using virtual screening, molecular docking, molecular dynamics, and MMPBSA techniques, they evaluated the stability of two compounds. TCMDC-124223 showed high stability and binding energy in the RBD, while TCMDC-133766 had better binding energy in the cryptic pocket. The study also identified that the interacting residues are conserved, which is crucial for addressing various virus variants. The findings provide insights into the potential of small molecules as drugs against the spike protein.

Keywords:
SARS-CoV-2, Molecular docking, Spike protein, Cryptic pocket, MMPBSA

Abstract:
The marine environment is a rich source of microorganisms producing bioactive compounds, like biosurfactant-producing bacteria that exhibit unique characteristics and functionalities. In this study, we examined glycolipid biosurfactants produced by bacteria that live commensally with marine organisms. We isolated a biosurfactant-producing strain identified as Cobetia marina strain F1, which displayed high hemolytic activity (27 mm), oil spreading ability (4 mm), emulsification index (40%), and decreasing surface tension to 31.3 (mN·m−1). Fourier transform infrared (FT-IR) spectroscopy revealed the glycolipid composition of the biosurfactant. Furthermore, elemental analysis utilizing CHNS and energy-dispersive X-ray spectroscopy (EDS) confirmed the biosurfactant contained carbon, hydrogen, nitrogen, sulfur, chlorine, potassium, oxygen, and additional elements. The critical micelle concentration (CMC) of the crude biosurfactant was determined to be 350 mg·L−1, at which concentration, a decrease in surface tension was observed when the biosurfactant was dissolved in distilled water. Given the presence of impurities in the biosurfactant composition, this observed CMC is considered acceptable. Furthermore, the biosurfactant exhibited significant antimicrobial activity against both Gram-positive and Gram-negative bacterial strains, with the largest zone of inhibition (ZOI) of 27 mm against Pseudomonas aeruginosa. This demonstrates the potential of the biosurfactant to serve as an alternative to novel antibiotic agents. The biosurfactant exhibited considerable inhibition of biofilm formation, disruption of preformed biofilms, and reduced enzymatic activity in bacterial cells following treatment. Moreover, the combination of the biosurfactant and F1 bacterial strain enhanced the degradation of crude oil by 86%, indicating its potential application in environmental remediation. These findings highlight the importance of investigating commensal strains capable to produce biosurfactants for applications in hydrocarbon remediation, overcoming antibiotic resistance, and biofilm disruption.

Abstract:
The variability in vestibular schwannoma growth rates greatly complicates clinical treatment. Management options are limited to radiological observation, surgery, radiotherapy and, in specific cases, bevacizumab therapy. As such, there is a pressing requirement for growth restricting drugs for vestibular schwannoma. This study explored potential predictors of vestibular schwannoma growth in depth, highlighting differences between static and growing vestibular schwannoma to identify potential therapeutic targets. High-dimensional imaging was used to characterize the tumour micro-environment of four static and five growing vestibular schwannoma (indicated by volumetric change < 20% or ≥ 20% per year, respectively). Single-cell spatial information and protein expression data from a panel of 35 tumour immune-targeted antibodies identified specific cell populations, their expression profiles and their spatial localization within the tumour micro-environment. Growing vestibular schwannoma contained significantly more proliferative and non-proliferative alternatively activated tumour-associated macrophages per millimetre square compared with static vestibular schwannoma. Furthermore, two additional proliferative cell types were identified in growing and static vestibular schwannoma: transitioning monocytes and programmed cell death ligand 1 (PD-L1+) Schwann cells. In agreement, growing vestibular schwannoma was characterized by a tumour micro-environment composed of immune-enriched, proliferative neighbourhoods, whereas static vestibular schwannoma were composed of tumour-enriched, non-proliferative neighbourhoods. Finally, classically activated macrophages significantly colocalized with alternatively activated macrophages in static vestibular schwannoma, but this sequestration was reduced in growing vestibular schwannoma. This study provides a novel, spatial characterization of the immune landscape in growing vestibular schwannoma, whilst highlighting the need for new therapeutic targets that modulate the tumour immune micro-environment.

Keywords:
tumour-associated macrophage, inflammation, tumour micro-environment, vestibular schwannoma, acoustic neuroma

Abstract:
We calculated the structural, electronic, and magnetic properties of FeSe within density-functional theory at
the generalized gradient approximation level. First, we studied how the bandwidth of the d-bands at the Fermi
energy is renormalized by adding simple corrections: Hubbard U , Hund’s J, and by introducing long-range
magnetic orders. We found that introducing either a striped or a staggered dimer antiferromagnetic order brings
the bandwidths—which are starkly overestimated at the generalized gradient approximation level—closer to
those experimentally observed. Second, for the ferromagnetic, the striped, checkerboard, and staggered dimer
antiferromagnetic order, we investigate the change in magnetic formation energy with local magnetic moment
of Fe at a pressure up to 6 GPa. The bilinear and biquadratic exchange energies are derived from the Heisenberg
model and noncollinear first-principles calculations, respectively. We found a nontrivial behavior of the spin-
exchange parameters on the magnetization, and we put forward a field-theory model that rationalizes these results
in terms of two-dimensional spin and orbital fluctuations. The character of these fluctuations can be either that
of a standard density wave or a topological vortex. Topological vortices can result in mesoscopic magnetization
structures.

Abstract:
The study introduces a methodology that integrates a novel velocity estimation approach with the Particle Filter for accurately estimating the position of an object navigating within a magnetic anomaly field. To accurately determine position in GPS-denied environments, the acceleration measurements obtained from the Inertial Measurement Unit are augmented with magnetic field measurements and a previously designed magnetic anomaly map. Then, Bayesian statistics are employed to fuse information from the Inertial Measurement Unit and magnetometer, enabling accurate estimation of the object's velocity. The estimated velocity serves as input for the propagation model within the Particle Filter, which accurately predicts the object's position. This study showcases the efficacy of Bayesian-based velocity estimation in enhancing the classical Particle Filter approach, resulting in an approximate 40-55% reduction in the mean trajectory error. This refined methodology holds promise for applications across diverse domains, including GPS-independent navigation for vehicles

Abstract:
The majority of the current cancer research is based on 2D cell cultures and animal models. These methods have limitations, including different expression of key factors involved in carcinogenesis and metastasis, depending on culture conditions. Addressing these differences is crucial in obtaining physiologically relevant results. Stemness and epithelial-mesenchymal transition (EMT) is linked to the increased invasive potential and metastasis, thus exploring the expression of this markers in a different growth conditions is essential. We report plasticity of expression of selected stem cell and EMT markers in different culture conditions, pointing to the importance of spatial parameters. The most significant difference is the expression of adherent cell junction protein E-cadherin, which changes dramatically between standard 2D culture, floating spheroid culture and matrigel scaffolded culture. As a step towards understanding the reasons causing these discrepancies, we have created a mathematical model of tensions within the 3D bioprinted culture.

Abstract:
This paper shows the results of a semi autonomous mobile robot tested in inspection missions during ENRICH 2023 and ELROB 2024. After successful ENRICH 2023 we decided to improve our system by adding LiDAR (Light Detection and Ranging) motion compensation with IMU (Inertial Measurement Unit). Our goal is to provide an affordable robotic solution as open source project available at https://github.com/JanuszBedkowski/msas_enrich_2023. Everything was fine till realistic test during ELROB 2024. Our system works well in 2D scenarios. It is not robust against large slopes. In this paper we show system overview and elaborate its limitations. We demonstrated the use of our open source project https://github.com/MapsHD/HDMapping for 3D map building with the mobile mapping system attached to the robot.

Keywords:
mobile robot, semi autonomous, real world task, LiDAR

Abstract:
This contribution discusses a semi-active control technique intended for mitigation of structural vibrations. The control law is implemented using the machine learning technique of reinforcement learning, that is in a repeated trial-and-error interaction between the control agent and a simulated environment. Such an approach allows to omit the stage of deriving the optimal control in an analytic way, which is often difficult in nonlinear, semi-actively controlled systems. A specific implementation of the Deep Q Learning (DQN) approach is applied, which promotes control robustness with respect to structural damages. A dedicated network architecture allows the network to be damage-aware, and a specific training procedure involves not only the observations, control actions, and rewards, but also the current health status of the structure.

A numerical example is provided involving a shear-type building model subjected to a seismic excitation. The actuator takes the form of a tuned mass damper (TMD), which is semi-actively controlled by changing the level of viscous damping. The optimally tuned classical passive TMD is used as the baseline reference damping system.

Abstract:
Additive manufacturing (AM) is revolutionizing production with its ability to rapidly create complex designs while minimizing material waste. The influence of the SLM parameters on mechanical properties of two sets of open cell lattices (Set A and Set B) made of IN718 was investigated. The purpose of using the modified parameters was to reduce the cost/time of manufacturing as well as to reduce microporosity in ligaments by increased exposure time (reduced laser scanning speed) or higher energy density based on increased exposure time. The researchers investigate ligament deformation and collapse in porous lattices, its impact on overall behavior, and how microstructure influences hardening under varying strain rates.

Keywords:
highly porous random open-cell lattice, additive manufacturing, direct impact Hopkinson pressure bar technique, Inconel 718

Abstract:
The analysis of nanostructures at the atomic level requires knowledge of interatomic interactions. There is a lot of data available in the literature for potentials, but it is often necessary to adjust the parameters of interatomic interactions for unusual structures, e.g. two dimensional materials. The aim of this work is to present a method for the optimal selection of interatomic parameters using machine learning techniques. Reinforced learning is one of the groups of methods that allow the use of artificial intelligence in the selection of parameters or models of real systems. The article uses the Monte Carlo Tree Search method [1,2] combined with local and global optimization algorithms for the optimal selection of silicon potential parameters for two dimensional structures.
The research used Molecular Dynamics (MD) to simulate nanostructures, and based on the results, nanostructure parameters were determined and compared with standard data from the literature. The aim of the optimization was to ensure the greatest possible compliance of the nanostructure parameters with the reference data. MD analyses were performed using the LAMMPS package [3].
The full article presents a description of the method as well as numerical examples for the two dimensional structure of silicon – silicene.

Keywords:
Reinforced Learning, Optimization, Interatomic potential, Nanostructure

Abstract:
The aim of this work is to present a method for optimizing the mechanical properties of a nanostructure based on Silicene. Optimization is carried out using a parallel evolutionary algorithm and parallel Molecular Dynamics analyses used to determine material properties. Due to high computational costs, optimization was carried out using one of the fastest supercomputers in the world – LUMI installed in CSC in Kajaani, Finland.

Keywords:
Methods of computational intelligence, 2D nanostructures, Molecular dynamics

Abstract:
Additive manufacturing, widely called 3d printing, allows to create new quality of metal products. A microstructure of 3d printed AlSi10Mg alloy can be described as an eutectic area surrounded by Si-network. Eutectic, fine-grain microstructure improves durability of material in comparison to cast, dendritic aluminium alloys. The presence of Si particles is challenging for electrochemical surface treatments, for instance to anodizing. In this study, Plasma Electrolytic Oxidation (PEO) – the most environmentally-friendly kind of anodizing – was performed on the cast AlSi10Mg and on the 3d printed AlSi10Mg specimens.

Keywords:
3d printing, Laser Powder Bed Fusion Process,Plasma Electrolytic Oxidation, aluminium

Abstract:
The work presents a comprehensive approach to the design and modelling of acoustic materials based on labyrinth structures filled with fibres. It has recently been shown that exceptionally favourable acoustic properties can be obtained in labyrinthine materials due to their extreme tortuosity. Such materials, typically produced by methods such as 3D printing, exhibit high sound absorption values at lower frequencies. The next step in the development of this type of acoustic treatment (explored here) involves introducing fibres into labyrinthine channels. Such acoustic composite designs can have a beneficial effect of shifting the absorption peak to even lower frequencies and also widening its efficiency range. Two samples of slotted labyrinth materials, designed using analytical acoustic modelling, were 3D printed, and their slits were filled with selected fibrous materials, such as biofibres, cotton wool, acrylic yarn, etc. They were tested in an impedance tube to confirm the predicted improvement, but also to show a dramatic change in sound absorption.

Abstract:
Selective laser sintering and binder jetting are two additive manufacturing technologies that use loose powder as a feedstock. In the case of binder jetting, the printout walls are essentially permeable and need to be additionally impregnated to be fully air-tight. The permeability of sintered objects, on the other hand, can be controlled to some extent by the amount of laser energy, among other things, provided to the exposed layer. Exploring these two technologies, several single- and double-porosity samples were additively manufactured, examined and acoustically measured in an impedance tube. Moreover, the normal incidence sound absorption spectra resulting from these structures were predicted employing multi-scale methods. The values of porosity and permeability of permeable printed materials were determined and utilised in the applied modelling. It is observed that making the skeleton microporous and permeable enables effective sound absorption even in primitive 3D printed acoustic treatments.

Abstract:
In this work, slotted acoustic materials based on a space filling curve called the Peano-Gosper curve are proposed and investigated. The slits in such materials form a complex pattern because they are divided by walls built along lines generated by the Gosper curve algorithm. The pattern can be twisted around an axis normal to its surface to increase the tortuosity inside the material, and therefore, modify its acoustic properties, which can be controlled by the turning angle or pitch of the twist. A highly efficient semi-analytical model has been developed to accurately predict the acoustic properties, in particular the sound absorption of such materials. It only requires a representative part of the pattern, or better, scanning the surface of the fabricated material so that the actual geometry and dimensions (in particular slit widths) are well reproduced in a two-dimensional finite element mesh generated on a representative fluid domain. The mesh is used to solve a dedicated Poisson problem and determine a few key parameters, and the rest of the modelling is based on analytical formulas. Material samples with straight and twisted slit patterns were 3D printed and then measured in an impedance tube to confirm semi-analytical sound absorption predictions.

Keywords:
Air-drop Capsule, Impact Mitigation, Adaptable Airbag, Discharge Valve

Abstract:
The contribution presents a numerical and experimental investigation of a novel control method developed
to adaptively mitigate impact loading of unknown characteristics. The adaptivity of the method relies on on-
line tracking of system kinematics and application of kinematic optimality condition utilizing actual values of
system displacements and accelerations. The original kinematics-based approach enables the determination
of the optimal force vs time dependency, optimizing system response under dynamic loading. The control
process is executed using piezoelectric valve with embedded strain gauge, which allows for proportional
control of the actual gas flow rate between two chambers of the damper. The conducted investigation proves
that integrating the kinematics-based control with a proportional piezoelectric valve results in a novel self-
adaptive system capable to adjust to unknown dynamic loads of unpredictable characteristics.

Abstract:
Mixture of Experts (MoE) models have emerged as a primary solution for reducing the computational cost of Large Language Models. In this work, we analyze their scaling properties, highlighting certain arbitrary assumptions present in the existing literature. In particular, we introduce a new hyperparameter, granularity, the modification of which allows for the optimal adjustment of the size of experts. Subsequently, we present scaling laws for fine-grained MoE, taking into account the number of training tokens, model size, and granularity. Using these scaling laws, we derive the optimal training configuration for a given computational budget. Furthermore, in contrast with previous works, we demonstrate that the gap in efficiency between dense and MoE models grows as we scale up the model size and training budget.

Abstract:
State Space Models (SSMs) have become serious contenders in the field of sequential modeling, challenging the dominance of Transformers. At the same time, Mixture of Experts (MoE) has significantly improved Transformer-based Large Language Models, including recent state-of-the-art open models. We propose that to unlock the potential of SSMs for scaling, they should be combined with MoE. We showcase this on Mamba, a recent SSM-based model that achieves remarkable performance. Our model, MoE-Mamba, outperforms Mamba and matches the performance of Transformer-MoE. In particular, MoE-Mamba reaches the same performance as Mamba in 2.35x fewer training steps while preserving the inference performance gains of Mamba against Transformer.

Abstract:
A new breed of gated-linear recurrent neural networks has reached state-of-the-art performance on a range of sequence modeling problems. Such models naturally handle long sequences efficiently, as the cost of processing a new input is independent of sequence length. Here, we explore another advantage of these stateful sequence models, inspired by the success of model merging through parameter interpolation. Building on parallels between fine-tuning and in-context learning, we investigate whether we can treat internal states as task vectors that can be stored, retrieved, and then linearly combined, exploiting the linearity of recurrence. We study this form of fast model merging on Mamba-2.8b, a pretrained recurrent model, and present preliminary evidence that simple linear state interpolation methods suffice to improve next-token perplexity as well as downstream in-context learning task performance.

Abstract:
Mixture of Experts (MoE) models based on Transformer architecture are pushing the boundaries of language and vision tasks. The allure of these models lies in their ability to substantially increase the parameter count without a corresponding increase in FLOPs. Most widely adopted MoE models are discontinuous with respect to their parameters - often referred to as sparse. At the same time, existing continuous MoE designs either lag behind their sparse counterparts or are incompatible with autoregressive decoding. Motivated by the observation that the adaptation of fully continuous methods has been an overarching trend in Deep Learning, we develop Mixture of Tokens (MoT), a simple, continuous architecture that is capable of scaling the number of parameters similarly to sparse MoE models. Unlike conventional methods, MoT assigns mixtures of tokens from different examples to each expert. This architecture is fully compatible with autoregressive training and generation. Our best models not only achieve a 3× increase in training speed over dense Transformer models in language pretraining but also match the performance of state-of-the-art MoE architectures. Additionally, a close connection between MoT and MoE is demonstrated through a novel technique we call transition tuning.

Abstract:
Background, Motivation and Objective
Flexible ultrasound (US) arrays are a promising technology that may further democratize US technology — e.g. in wearable US. Flexible transducers also pose challenges in image reconstruction, as they require adaptable beamforming delays due to a changing geometry of the probe. Various approaches have been proposed for flexible array shape estimation and beamforming, e.g. external sensors, deep learning and optimization. In this work, we propose a deep reinforcement learning (DRL) approach, where a software agent is responsible for tracking the array shape to properly reconstruct US B-mode image.

Statement of Contribution/Methods
Here we considered a reinforcement learning environment as a setup consisting of a US system with the flexible array and point targets phantom. The environment was simulated using j-Wave software. The environment’s state consisted of the current shape of the array, modeled as a sinusoid s = a sin(bx + c), and the current model of the array assumed by the beamformer: s’ = a’ sin(b’x + c’) (single-element STA scheme). A single episode consisted of
7 steps; the parameters a, b, c could vary from step to step (within bounds of physical constraints). The agent observed the current B-mode, could modify the current values of a’, b’ and c’ (action) and received a reward equal to the linear combination of the coherence factor and structural similarity index measure (SSIM) between the current and reference image. We trained our agent using TD3 approach and tested it for various settings of a, b and c.

Results/Discussion
Our agent achieved an average SSIM of 0.73 per episode step. Figure 1 shows the sequence of states and images within an example episode; the agent was able to correctly react to the change of the array shape. The DRL approach has the following advantages compared to other methods: the agent can be trained to operate in an environment with a changing state; and the agent can be trained to maximize expected return (dependent on beamforming quality metric), which does not have to be differentiable.

Fig. 1. (Top) B-mode images, estimated array shape (red) and actual shape (black) within an example episode. (Bottom) Coherence factor and SSIM achieved by the agent during the episode

Keywords:
Vibration Damping, Particle Impact Damper, Adaptive Pneumatic Damper

Abstract:
Kompozytowe podwozie samolotu Skyleader GP ONE poddane zostało obciążeniom symulującym warunki przyziemienia podczas lądowania samolotu, a także próbie niszczącej. Zweryfikowano możliwość wskazania lokalizacji obszarów maksymalnej koncentracji naprężeń zredukowanych przy zastosowaniu uproszczonego modelowania, wykonanego przy założeniu izotropowości materiału podwozia. Do przeprowadzenia testów laboratoryjnych posłużyło unikalne stanowisko z wieżą zrzutową, posiadające pionowy i poziomy układ łożysk liniowych.

Keywords:
zrzutownik, podwozie samolotu ultralekkiego, model izotropowy

Abstract:
Breast cancer is the most common cancer in women, and ultrasound
(US) imaging is important for breast mass assessment. Accurate automatic
breast mass segmentation facilitates mass characterization. Traditional deep
learning methods, such as convolutional networks and transformers, have
achieved high performance in breast mass segmentation. Recently, implicit
neural representations, which use continuous, nonlinear, coordinate-based
approximations through multi-layer perceptrons, have shown promise
in various fields, including medical image segmentation. In this work, we
present an implicit network for breast mass segmentation in US. We train a
coordinate-based implicit network to jointly output the US image pixel values
and the segmentation pixel scores. The network is conditioned using latent
codes, effectively associating the regression and segmentation tasks with the
mass type (benign/malignant) and BI-RADS category. Additionally, a trainable
image-specific code is used. During inference, given a US image, we fix the
weights of the network and use the backpropagation algorithm to determine
the latent codes, facilitating the image regression task. This process, due to the learned associations, also provides the segmentation mask. Our results
confirm the feasibility of using implicit networks for breast mass segmentation
and other tasks leveraging learned associations between latent codes and
image/mask appearances.

Keywords:
leśnictwo, sztuczna inteligencja, uczenie maszynowe

Abstract:
Segmentation of biomedical images is often ambiguous and complicated by noise, varying
contrasts, and imaging artifacts. We address the challenge of segmenting images of brain
tissue in which gene expression has been localized using in situ hybridization. Since gene
expression patterns differ widely between genes, it can be difficult to correctly discriminate
pixels positive for gene expression. In testing different segmentation networks, we observed
that each network had its own trade-offs between sensitivity and precision. To exploit
the benefits of all trained networks, we developed a meta-network that learns to combine
multiple segmentation maps from diverse segmentation architectures to generate a final
segmentation that best matches the ground-truth label. In our experiments, the meta-
network outperforms ensembles that simply average segmentation maps.

Keywords:
meta-learning, segmentation, gene expression

Abstract:
Accurate estimation of the speed-of-sound (SoS) is important for ultrasound (US) image reconstruction techniques and tissue characterization. Various approaches have been proposed to calculate SoS, ranging from tomography-inspired algorithms like CUTE to convolutional networks, and more recently, physics-informed optimization frameworks based on differentiable beamforming. In this work, we utilize implicit neural representations (INRs) for SoS estimation in US. INRs are a type of neural network architecture that encodes continuous functions, such as images or physical quantities, through the weights of a network. Implicit networks may overcome the current limitations of SoS estimation techniques, which mainly arise from the use of non-adaptable and oversimplified physical models of tissue. Moreover, convolutional networks for SoS estimation, usually trained using simulated data, often fail when applied to real tissues due to out-of-distribution and data-shift issues. In contrast, implicit networks do not require extensive training datasets since each implicit network is optimized for an individual data case. This adaptability makes them suitable for processing US data collected from varied tissues and across different imaging protocols. We evaluated the proposed SoS estimation method based on INRs using data collected from a tissue-mimicking phantom containing four cylindrical inclusions, with SoS values ranging from 1480 m/s to 1600 m/s. The inclusions were immersed in a material with an SoS value of 1540 m/s. In experiments, the proposed method achieved strong performance, clearly demonstrating the usefulness of implicit networks for quantitative US applications.

Keywords:
beamforming, deep learning, implicit neural representations, speed-of-sound, quantitative ultrasound

Keywords:
Ni-free shape memory alloys, interstitials atoms, stress-induced phase transformation, acoustic emission

Keywords:
High entropy alloys, high entropy nitrides, nitriding, nanoindentation, ion implantation

Keywords:
composite, coating, metal matrix, wear, interfacial strength

Keywords:
nanoindentation, micropillars compression, high entropy alloys, nitriding, ion implantation

Keywords:
Detonation, Detonation damping, Flow control

Keywords:
Deformation-induced martensitic transformation, Austenitic Stainless Steel, Additive Manufacturing, DIC, Cryogenic temperatures

Keywords:
Phase transformation, Deformation-induced martensitic transformation, 316L, Fused Deposition Modelling

Abstract:
he Institute of Fundamental Technological Research's Microfluidic Laboratory
is focused on enhancing the accuracy and practical use of microfluidic methods for chemical
and biological studies, as well as creating tailored microfluidic instruments to address
specific biological research needs. In this document, we present a few of our latest projects.

Keywords:
Micro-, Nano- and Bio-flows, Multi-phase Flows, Droplets

Abstract:
Ceramic materials are commonly used in plungers due to high resistance to wear, abrasion, and low coefficient of thermal expansion. Also, they are commonly used in dry conditions without permanent damage, ceasing of pump head and better corrosion resistance than metals due to their inert characteristics. Zirconia (ZrO2) ceramic is used due to its high strength whereas, alumina (Al2O3) is commonly used in industries for high pressure pumps. The toughness of zirconia ceramics is higher than alumina ceramics as it overcomes the inherent brittleness of ceramic materials. It also has higher wear resistance and extends the life of the product. Whereas alumina has better mechanical characteristics such as hardness compared to Zirconia. In this research work tribological behavior of Alumina and Zirconia ceramics used in high pressure pumps have been studied. The wear test using end face wear testing apparatus has been conducted under flat contact for both alumina and ceramic material considering a mean contact pressure of 10 N, 20 N, 30 N and 40 N and sliding velocity of 40 mm/s. The wear test was conducted for 30 min considering a total sliding distance of 1500 m and 3000 m. The wear test results indicate that both alumina and ceramic exhibit lower wear factors and superior mechanical properties. The findings also reveal that the wear rates of Al2O3 and ZrO2 are influenced by friction forces, subsequently impacting the overall wear rate. Also, as the load increases the surface contact area also increases which in turn increases the wear rate. However, zirconia could be a potential substitute for alumina due to its high strength and fracture toughness.

Keywords:
Ceramics, Composites, Alumina, Zirconia, Wear rate, Toughness

Keywords:
anning electron microscopy, in-situ mechanical tests, hot-pressing

Abstract:
The problem of safe, impact loads absorption is present in a wide class of applications, and particularly where direction of the object's movement is well-defined, for example: precise docking systems, rail car buffers or landing gear shock absorbers. In those applications the objective is to absorb gradually impact energy, minimizing the deceleration peak. For safety reasons, the class of drop-caps (eg. in delivery business) or bigger airdrops from airplanes or from stratospheric airships (space debris) becomes a challenge for next decades. However, knowing the dropping mass and estimating the touchdown velocity, our SAI shock-absorbers (cf. [1]) made of multi-layered, "delaminable" panels, can be adapted to the expected impact. Therefore, let us concentrate on the SAI concept based on the following steps: -- design a multi-layer structure capable of semi-active "delamination" control along the contact infrastructure (slipping lines). -- apply an actuator realizing the on/off type of semi-active control for slipping lines' activation, playing the role of structural clutch (cf. the actuator in the so-called PAR vibration suppression technique, [2-3]), -- apply various characteristics for the contact interfaces (friction coefficient), -- apply various control strategies for the slipping lines activation (and releasing of the pre-stress effect), depend on the case study and identified on-line impact parameters. The effectiveness of the proposed, adaptive approach to impact absorption (so-called Depress Dampers) will be compared versus traditional shock-absorbers, based on passive honeycomb panels (cf. also adaptive pneumatic shock-absorber concept).

Abstract:
In breast cancer diagnosis, early detection of tumors and accurate differentiation of malignant and benign breast lesions are key demands. Tumor size, as a measure of tumor progression, is related to recurrence rate and patient survival. This study aims to determine which sonographic features al- low the differentiation of small breast lesions into benign and malignant. Inclusion criteria for the analysis were tumors with the longest diameter of less than or equal to 10 mm and tumors with confirmed classification by follow-up care or core needle biopsy result. Following the criteria, 1515 cases were analyzed, including 365 carcinomas and 1150 benign lesions. To quantitatively evaluate the images, 383 ultrasound parameters
(BI-RADS features, morphological features, fractal features, his- togram features, and texture parameters) were used. Univariate and multiple logistic regression analyses were used to assess the significance of various diagnostic features and their combinations. The combined classifier (based on 19 quantitative features) yields an area under the ROC curve of 0.91.

Keywords:
Ultrasound imaging, Breast cancer, Small lesion, Feature extraction

Abstract:
This paper presents a novel low cost 3D mapping system designed for fulfilling the gap between existing solutions and constantly growing end-users’ expectations. Firstly, the cost was reduced to minimum by providing an open-source, open-hardware projects. Secondly, the ergonomic, light weight, reconfigurable approach enables a wearable approach to maximize the mobility of the end user. It allows among other things the freedom to walk, crawl and climb. Those are necessities in extreme mobile mapping applications such as cave mapping, construction site survey, search and rescue missions and other unexplored yet applications such as mobile mapping with K9s (trained dogs equipped with 3D mobile mapping systems). The significance of this research is to provide cost effective mobile mapping solution for as large audience as it is possible. Thus, our software is constantly improved for covering more applications e.g. air + ground + underground mapping.

Keywords:
Mobile mapping system, SLAM, LiDAR odometry, Normal Distributions Transforms, Gaussians

Abstract:
The topic of smart civil infrastructure has attracted significant attention. An important component of such structural systems is the network of sensors used to monitor the structure and deliver information about its current health status. The task of optimal sensor placement is not trivial due to the discrete, combinatorial nature of the problem. The brute force search is unfeasible for large structures, which calls for approximate and heuristic approaches. This problem has been investigated for several decades, beginning probably with the landmark 1978 paper of Shah [1]. A recent review can be found in [2].

The criteria typically used for assessing candidate placements are based either on Kammer’s Effective Independence (EFI) and the Fisher Information Matrix (FIM) [3], and quantify the amount of information provided by sensors, or on covariance matrices obtained within the Kalman filtering procedure used to quantify the uncertainty of the unknown response of interest being estimated [4]. However ingenious, most of the proposed procedures are computationally costly in large-scale problems.

This talk will discuss two optimal placement methods that have been recently developed with the objective of computational efficiency [5, 6]. One of them is based on Kalman filter covariance matrices and has—instead of typically quadratic—a linear complexity in the number of potential sensor locations. The other method uses the technique of convex relaxation to represent the problem in a computationally tractable continuous form and speed up the solution procedure even further. The presented application examples will use models of bridge structures.

[1] P.C. Shah, F.E. Udwadia, A methodology for optimal sensor locations for identification of dynamic systems, J. Appl. Mech. 45(1), 188–196 (1978)
[2] Y. Tan, L. Zhang, Computational methodologies for optimal sensor placement in structural health monitoring: A review, Struct. Health Monit. 19(4), 1287–1308 (2020)
[3] D.C. Kammer, Sensor placement for on-orbit modal identification and correlation of large space structures, J. Guid. Control Dyn. 14(2), 251–259 (1991)
[4] C. Zhang, Y.-L. Xu, Optimal multi-type sensor placement for response and excitation reconstruction, J. Sound Vib. 360, 112–128 (2016)
[5] B. Błachowski, A. Świercz A., M. Ostrowski, P. Tauzowski, P. Olaszek, L. Jankowski, Convex relaxation for efficient sensor layout optimization in large-scale structures subjected to moving loads, Comput.-Aided Civ. Inf. 35(10), 1085–1100 (2020)
[6] B. Błachowski, A. Świercz, P. Olaszek, Ł. Jankowski, Implementation of multi-type sensor placement strategy for large-scale engineering structures, 10th ECCOMAS Thematic Conference on Smart Structures and Materials (SMART 2023), July 3–5, 2023, Patras, Greece, pp. 498–506 (2023)

Keywords:
eight-node (hexahedron) solid-shell elements, standard or partial Hu-Washizu functionals, reduced representations of assumed stress/strain, EAS for the thickness strain, skew coordinates

Abstract:
The very serious problem connected with long distance transport of gaseous fuels is connected with the fact that detonation may occur inside the duct if some air leaks into it. Detonation is particularly dangerous for compressors which “push” the gas through pipelines. It is therefore necessary to use some “detonation dampers” to protect these compressors. The commonly used detonation damper has a form of a matrix of narrow channels, placed across the pipe transporting gas. Detonation wave is supposed to be extinguished due to cooling by cold walls of these channels. To achieve efficient damping the channels should be very narrow. Our earlier simulations (Walenta et al. in Central European Journal of Energetic Materials. 1:49–59, 2004; Walenta Z.A., Slowicka A.M.: Extinguishing detonation in pipelines—optimization of the process, In: K. Kontis (ed.), Proceedings of 22nd Int. Shock Interaction Symposium, Glasgow, pp. 202–206. (2016).; Walenta Z.A., Slowicka A.M.: Detonation Waves in Narrow Channels of Various Shapes, Proceedings of 23rd Int. Shock Interaction Symposium, Skukuza, Kruger National Park, South Africa, pp. 135–140 (2018).) indicate, that preferable widths should be of the order of 0.005 mm. This is not acceptable for practical reasons—in real applications it is close to 0.5 mm. In such channels cooling the gas by heat transfer is inefficient and cannot extinguish the flame (cooling effect is proportional to perimeter of the channel cross-section and amount of gas to be cooled to cross-section surface). Rarefaction wave generated behind sharp increase of channel cross-section is an alternative phenomenon, which may be used to cool the burning gas (Walenta et al. in Central European Journal of Energetic Materials. 1:49–59, 2004). In our earlier papers we tested several channel shapes with increase of cross-section (Walenta Z.A., Slowicka A.M.: Extinguishing detonation in pipelines—optimization of the process, In: K. Kontis (ed.), Proceedings of 22nd Int. Shock Interaction Symposium, Glasgow, pp. 202–206. (2016).; Walenta Z.A., Slowicka A.M.: Detonation Waves in Narrow Channels of Various Shapes, Proceedings of 23rd Int. Shock Interaction Symposium, Skukuza, Kruger National Park, South Africa, pp. 135–140 (2018).). Here we compare channels 0.5 mm wide, without and with sharp increases and decreases of cross-section. Such channels were found to be the best for practical applications.

Keywords:
shock waves, shock interactions, fluid dynamics

Abstract:
Świeżo upieczony student studiów doktoranckich często jest wrzucany na głęboką wodę-
– nowe środowisko, nowi ludzie, masa wyzwań i trudności. Niejednokrotnie ma on wrażenie, że brakuje mu odpowiednich umiejętności i wsparcia ze strony
promotora, co bezpośrednio wpływa na jakość procesu naukowego. Czy to jednak głównie kwestia wadliwego systemu, postawy promotora, czy może podejścia samego studenta? Szczerze mówiąc, problem
leży zapewne pośrodku.

Abstract:
A newly admitted doctoral student is often simply thrown in at the deep end, facing
a whole new environment, unfamiliar faces, and
a multitude of challenges. More often than not, they
feel ill-equipped and insufficiently supported by their
supervisor – the person who is ostensibly their closest
ally. This, in turn, affects the overall experience and
success of their academic path. But is this primarily
due to a flawed system, the supervisor’s attitude, or
perhaps the student’s own approach? The truth likely
lies somewhere in between.

Abstract:
A dense packing of the Voronoi polygons (VP) was created by the Centroidal Voronoi (CV) iteration. It includes VPs with 5, 6 or 7 sides. VPs are represented in a dual triangular representation. In this way, a polycrystal containing grains made of hexagons is formed. The grains are separated by lines of 5/7 pairs. To emphasize the orientation of the grains, we colour the edges of triangles according to a saturated colour circle (CC). The colouring depends on the edge direction modulo 60 degrees. Thanks to this, the colour of edges of an equilateral triangle is the same. Since the colours give the direction of the edges, the colours of the edges of the pentagon go in the opposite direction to the colours of the edges of the heptagon. Thus the CV iteration leads to uniform packing and to the famous hexatic phase transition.

Keywords:
Voronoi’s polygon, duality, Colour Circle, 5/7 dislocation, film

Abstract:
Wieże Hanoi są znaną łamigłówką matematyczną, która mimo swej pozornej prostoty jest ważna w różnych dziedzinach nauki. Przypominamy łamigłówkę i dyskutujemy najprostszy algorytm jej rozwiązania, podany przez polskiego matematyka Andrzeja Lissowskiego. Zgodnie z tym algorytmem w każdym kroku korzystamy z dwu pól: pole, z którego bierzemy krążek, i pole, na które krążek kładziemy. Trzecie pole w tym kroku nie pełni żadnej roli. Nazywamy je polem nieruszonym. Na przykład, jeżeli przekładamy krążek z pola A na pole B, to pole C nie jest ruszone. Patrząc na kolejność pól nieruszonych, zauważamy, że pola nieruszone przesuwają się po okręgu. Omawiamy związek algorytmu z innymi zadaniami matematycznymi, takimi jak drzewo Lindenmayera, krzywa smoka i trójkąty Sierpińskiego.

Keywords:
okresowość, pole nieruszone, rekurencja, trójkąty Sierpińskiego

Abstract:
An experimental botanical fact is the spiral growth of leaves and flowers, and in general of plant buds. Each new shoot in the meristem is formed at an angular distance from the previous one equal to the angle of the golden ratio, i.e. 137.5 degrees. What is most astonishing is that the theory of the golden ratio and its connection with Fibonacci numbers also finds its expression in botany. Each bud produces 5, 6 or 7 diagonals. Adding a new point in the middle of the bud system (in the meristem) pushes the existing points apart so that on each dislocation circle there is an exchange of contacts, i.e. the so-called one flip. The article concludes with a proposal to apply the DISCHARGING procedure (used by Heesch to solve the four-color problem) to precisely determine the geometric curvature of the divided tissue. An appendix is also provided, which explains in more detail the lesser-known concepts from mathematics and crystallography used in the article.

Keywords:
remodeling of biological tissue, parastichies, Fibonacci-Lucas numbers, leaf buds

Abstract:
The chapter is discussing meaning of energy and entropy in some equilibrium and non-equilibrium processes of thermodynamics. We pay an attention to the paradox arising between the description of the adiabatic transformation and the result of the Gay-Lusac experiment. According to the known formula for the adiabatic transformation of an ideal gas, the expansion of the gas should be accompanied by a decrease in temperature. Meanwhile, in the Gay-Lusac experiment, the expansion caused by the sudden removal of the plug does not cause a change in the temperature of an ideal gas. Sudden removal does not cause the phenomenon that occurs with slow expansion. Next, we compared the introduction of entropy in phenomenological thermodynamics and in statistical thermodynamics. Further we discuss the entropy change in the diffusion process. It turns out that while the total entropy of the diffusion process increases monotonically with time, the entropy density has local maxima with the value 1/e. We have given the formula for the efficiency of a Brownian engine operating in two phases, at two different temperatures. In the appendices we recall the similarity given by R. Emden for energy and entropy, and we provide a sketch of the history of heat.

Keywords:
Gas expansion, ideal gas, van der Waals gas, diffusion, caloric