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To functionalize the NiTi alloy, multifunctional innovative nanocoatings of Ag-TiO2 and Ag-TiO2 doped with hydroxyapatite were engineered on its surface. The coatings were thoroughly characterized, focusing on surface topography and key functional properties, including adhesion, surface wettability, biocompatibility, antibacterial activity, and corrosion resistance. The electrochemical corrosion kinetics in a simulated body fluid and the mechanisms were analyzed. The coatings exhibited hydrophilic properties and were biocompatible with fibroblast and osteoblast cells while also demonstrating antibacterial activity against E. coli and S. epidermidis. The coatings adhered strongly to the NiTi substrate, with superior adhesion observed in the hydroxyapatite-doped layers. Conversely, the Ag-TiO2 layers showed enhanced corrosion resistance.

Medical support in crisis situations is a major challenge. Efficient implementation of the medical evacuation process especially in operations with limited human resources that may occur during armed conflicts can limit the loss of these resources. Proper evacuation of wounded soldiers from the battlefield can increase the chances of their survival and rapid return to further military operations. This paper presents the technical details of the decision support system for medical evacuation to support this process. The basis for the functioning of this system is the continuous measurement of vital signs of soldiers via a specialized measurement module with a set of medical sensors. Vital signs values are then transmitted via the communication module to the analysis and inference module, which automatically determines the color of medical triage and the soldier’s chance of survival. This paper presents the results of tests of our system to validate it, which were carried out using test vectors of soldiers’ vital signs, as well as the results of the system’s performance on a group of volunteers who performed typical activities of tactical operations. The results of this study showed the usefulness of the developed system for supporting military medical services in military operations.

Detecting instruments in a music signal is often used in database indexing, song annotation, and creating applications for musicians and music producers. Therefore, effective methods that automatically solve this issue need to be created. In this paper, the mentioned task is solved using mel-frequency cepstral coefficients (MFCC) and various architectures of artificial neural networks. The authors’ contribution to the development of automatic instrument detection covers the methods used, particularly the neural network architectures and the voting committees created. All these methods were evaluated, and the results are presented and discussed in the paper. The proposed automatic instrument detection methods show that the best classification quality was obtained for an extensive model, which is the so-called committee of voting classifiers.

The demand for digitizing manufacturing and controlling processes has been steadily increasing in recent years. Digitization relies on different techniques and equipment, which produces various data types and further influences the process of space understanding and area recognition. This paper provides an updated view of these data structures and high-level categories of techniques and methods leading to indoor environment segmentation and the discovery of its semantic meaning. To achieve this, we followed the Systematic Literature Review (SLR) methodology and covered a wide range of solutions, from floor plan understanding through 3D model reconstruction and scene recognition to indoor navigation. Based on the obtained SLR results, we identified three different taxonomies (the taxonomy of underlying data type, of performed analysis process, and of accomplished task), which constitute different perspectives we can adopt to study the existing works in the field of space understanding. Our investigations clearly show that the progress of works in this field is accelerating, leading to more sophisticated techniques that rely on multidimensional structures and complex representations, while the processing itself has become focused on artificial intelligence-based methods.

In this study, a series of four surface-active compounds—N-alkyl betaine ethyl ester chlorides, CnBetC2Cl—were synthesized and characterized in aqueous solutions. As with other alkyl betaines, these amphiphiles can be practically used, for example, as co-surfactants and/or solubility enhancers acting according to hydrotropic or micellar mechanisms, depending on the alkyl chain length in the amine. We focused on the representatives of the medium alkyl chain length (C6–C12) to find the dependence between the alkyl chain length in N-alkyl betaine ethyl ester chlorides and the surface, volumetric, acoustic, and viscometric properties of their solutions. Ethyl esters, the derivatives of amino acids, were chosen to increase functionality and take advantage of possible hydrolysis in solutions at higher pH, which is also a key parameter in biodegradability. The micellization parameters were calculated based on the physicochemical characteristics. We focused our interest on the ester with a dodecyl substituent since we can compare and discuss its properties with some other C12 representatives that are available in literature. Surprisingly, its micellization characteristic is almost temperature-independent in the investigated temperature range, t = (15–45) °C. Particularly interesting are the results of dynamic light scattering (DLS), which show that the changes in physicochemical parameters of the C12 homolog around the CMC are caused by the two types of micelles of different sizes present in solutions.

This paper addresses the problem of describing the complex linked coupling faults of memory devices and formulating the necessary and sufficient conditions for their detection. The main contribution of the proposed approach is based on using a new formal model of such faults, the critical element of which is the introduction of roles and scenarios performed by the cells involved in the fault. Three roles are defined such that the cells of the complex linked coupling faults perform, namely, the roles of the aggressor (A), the victim (V), and both (B), performed by two cells simultaneously in relation to each other. The memory march test and applied address sequence and background determine the scenario for implementing the roles of memory faulty cells. The necessary and sufficient conditions for detecting linked coupling faults are given based on a new formal model. Formally, the undetectable linked coupling faults are defined, and the conditions for their detection are formulated using multirun memory march tests. The experimental investigation confirmed the validity of the proposed formulated statements. Based on the example of a linked coupling fault, this study demonstrates the fulfillment of the necessary and sufficient conditions for its detection using a single march test. As demonstrated in this article, employing the approach proposed by the authors, a two-pass march C test, for instance, enables the attainment of 55.42% fault coverage for linked coupling faults, inclusive of undetectable faults identified by the single-pass march test.

In this paper, we propose one-step synthetic strategies for obtaining well-defined linear and star-shaped polyvinylpyrrolidone (linPVP and starPVP). The produced macromolecules and a commercial PVP K30 with linear topology were investigated as potential matrices for suppressing metronidazole (MTZ) crystallization. Interestingly, during the formation of binary mixtures (BMs) containing different polymers and MTZ, we found that linear PVPs exhibit maximum miscibility with the drug at a 50:50 weight ratio (w/w), while the star-shaped polymer mixes with MTZ even at a 30:70 w/w. To explain these observations, comprehensive studies of MTZ-PVP formulations with various contents of both components were performed using Fourier-transform infrared spectroscopy, differential scanning calorimetry, and X-ray diffraction. The obtained results clearly showed that the polymer’s topology plays a significant role in the type of interactions occurring between the matrix and MTZ. Additionally, we established that for MTZ-PVP 50:50 and 75:25 w/w BMs, linear polymers have the most substantial impact on inhibiting the crystallization of API. The star-shaped macromolecule turned out to be the least effective in stabilizing amorphous MTZ at these polymer concentrations. Nevertheless, long-term structural investigations of the MTZ-starPVP 30:70 w/w system (which is not achievable for linear PVPs) demonstrated its complete amorphousness for over one month.

Particle acceleration is a fundamental process arising in many astrophysical objects, including active galactic nuclei, black holes, neutron stars, gamma-ray bursts, accretion disks, solar and stellar coronae, and planetary magnetospheres. Its ubiquity means energetic particles permeate the Universe and influence the conditions for the emergence and continuation of life. In our solar system, the Sun is the most energetic particle accelerator, and its proximity makes it a unique laboratory in which to explore astrophysical particle acceleration. However, despite its importance, the physics underlying solar particle acceleration remain poorly understood. The SPARK mission will reveal new discoveries about particle acceleration through a uniquely powerful and complete combination of γ-ray, X-ray, and EUV imaging and spectroscopy at high spectral, spatial, and temporal resolutions. SPARK’s instruments will provide a step change in observational capability, enabling fundamental breakthroughs in our understanding of solar particle acceleration and the phenomena associated with it, such as the evolution of solar eruptive events. By providing essential diagnostics of the processes that drive the onset and evolution of solar flares and coronal mass ejections, SPARK will elucidate the underlying physics of space weather events that can damage satellites and power grids, disrupt telecommunications and GPS navigation, and endanger astronauts in space. The prediction of such events and the mitigation of their potential impacts are crucial in protecting our terrestrial and space-based infrastructure.

Orthoses are of critical importance in the field of medical biomechanics, particularly in the correction of spinal deformities. The objective of the current research was to improve the utility characteristics of the scoliosis brace without compromising its corrective capabilities. The orthotic shell of the Boston brace was used as the basis for this investigation. The finite element method (FEM) was used to evaluate the distribution of corrective forces through the device. The flow of force lines within the orthotic shell was determined by mapping the paths of maximum principal stresses. Areas of the device that had a negligible effect on overall stiffness were identified and material from these areas was eliminated. Minor modifications were then made to the redesigned shell to maintain its corrective stiffness. As a result of these changes, the weight of the braces was reduced without compromising its corrective stiffness. When subjected to corrective forces, the shell’s displacement patterns in the transverse plane showed minimal changes from the original model, confirming that its corrective capacity remained largely intact. This research presents an innovative methodology for orthotic design and demonstrates that structural optimization based on the mapping of maximum principal stress pathways can significantly improve device functionality. The approach outlined here holds promise for future advances in the design of various orthotic devices, thereby contributing to the advancement of the field.

Fluidic and non-fluidic surface plasmon resonance measurements were realized for the same type of sensory layer and using the same mouse IgG antibody and anti-mouse IgG antibody biomolecular system. A comparison of the thicknesses of the anti-mouse IgG antibody layers bound to the ligand at increasing analyte concentrations ranging from 0.0 μg mL−1 to 5.0 μg mL−1 in the non-fluidic and the fluidic variant showed that the thickness of the bound anti-mouse antibody layers in the fluidic variant was approximately 1.5–3 times larger than in the non-fluidic variant. The greater thicknesses of the deposited layers were also reflected in the larger increment of the resonant angle in the fluidic variant compared to the non-fluidic variant in the considered range of analyte concentrations. The choice between fluidic and non-fluidic surface plasmon resonance biosensors may be justified by the availability of analyte volume and the intended modulation technique. When working with limited analyte, non-fluidic biosensors with intensity modulation are more advantageous. For larger analyte quantities, fluidic biosensors with angular modulation are recommended, primarily due to their slightly higher sensitivity in this measurement mode.

Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead to high costs and substantial economic losses not only for the power plant but for consumers and the larger society. Therefore, the power production industry relies on a variety of approaches to maintenance tasks, ranging from traditional solutions and engineering know-how to smart, AI-based analytics to avoid potential downtimes. This review shows the evolution of maintenance approaches to support maintenance planning, equipment monitoring and supervision. We present older techniques traditionally used in maintenance tasks and those that rely on IT analytics to automate tasks and perform the inference process for failure detection. We analyze prognostics and health-management techniques in detail, including their requirements, advantages and limitations. The review focuses on the power-generation sector. However, some of the issues addressed are common to other industries. The article also presents concepts and solutions that utilize emerging technologies related to Industry 4.0, touching on prescriptive analysis, Big Data and the Internet of Things. The primary motivation and purpose of the article are to present the existing practices and classic methods used by engineers, as well as modern approaches drawing from Artificial Intelligence and the concept of Industry 4.0. The summary of existing practices and the state of the art in the area of predictive maintenance provides two benefits. On the one hand, it leads to improving processes by matching existing tools and methods. On the other hand, it shows researchers potential directions for further analysis and new developments.

Models of particle acceleration in solar eruptive events suggest that roughly equal energy may go into accelerating electrons and ions. However, while previous solar X-ray spectroscopic imagers have transformed our understanding of electron acceleration, only one resolved image of γ-ray emission from solar accelerated ions has ever been produced. This paper outlines a new satellite instrument concept—the large imaging spectrometer for solar accelerated nuclei (LISSAN)—with the capability not only to observe hundreds of events over its lifetime, but also to capture multiple images per event, thereby imaging the dynamics of solar accelerated ions for the first time. LISSAN provides spectroscopic imaging at photon energies of 40 keV–100 MeV on timescales of ≲10 s with greater sensitivity and imaging capability than its predecessors. This is achieved by deploying high-resolution scintillator detectors and indirect Fourier imaging techniques. LISSAN is suitable for inclusion in a multi-instrument platform such as an ESA M-class mission or as a smaller standalone mission. Without the observations that LISSAN can provide, our understanding of solar particle acceleration, and hence the space weather events with which it is often associated, cannot be complete.

This paper presents the photophysical and biological properties of eight 3-imino-1,8-naphthalimides. The optical properties of the compounds were investigated in the solvents that differed in their polarity (dichloromethane, acetonitrile, and methanol), including three methods of sample preparation using different pre-dissolving solvents such as dimethyl sulfoxide or chloroform. In the course of the research, it was found that there are strong interactions between the tested compounds and DMSO, which was visible as a change in the maximum emission band (λem) of the neat 3-imino-1,8-naphthalimides (λem = 470–480 nm) and between the compounds and DMSO (λem = 504–514 nm). The shift of the emission maximum that was associated with the presence of a small amount of DMSO in the sample was as much as 41 nm. In addition, the susceptibility of imines to hydrolysis in the methanol/water mixture with increasing water content and in the methanol/water mixture (v/v; 1:1) in the pH range from 1 to 12 was discussed. The studies showed that the compounds are hydrolysed in the CH3OH/H2O system in an acidic environment (pH in the range of 1 to 4). In addition, it was found that partial hydrolysis occurs in systems with an increased amount of water, and its degree may depend on the type of substituent on the imine bond. The compounds tended to quench the emission (ACQ) in the aggregated state and increase the emission related to the protonation of the imine bond. Moreover, it was found that the substituent in the imine bonds influenced a compound’s individual photophysical properties. Biological tests, including cytotoxicity studies and cellular localisation, were also performed for all of the molecules. All of the tested compounds exhibited green fluorescence in the MCF-7 cells and showed co-localisation in the mitochondria, endoplasmic reticulum, and lysosome. The obtained photophysical and biological results indicate the promising potential use of the tested compounds as cellular dyes.

We introduce a novel methodological framework based on additive value-based efficiency analysis. It considers inputs and outputs organized in a hierarchical structure. Such an approach allows us to decompose the problem into manageable pieces and determine the analyzed units’ strengths and weaknesses. We provide robust outcomes by analyzing all feasible weight vectors at different hierarchy levels. The analysis concerns three complementary points of view: distances to the efficient unit, ranks, and pairwise preference relations. For each of them, we determine the exact extreme results and the distribution of probabilistic results. We apply the proposed method to a case study concerning the performance of healthcare systems in sixteen Polish voivodeships (provinces). We discuss the results based on the entire set of factors (the root of the hierarchy) and three subcategories. They concern health improvement of inhabitants, efficient financial management, and consumer satisfaction. Finally, we show the practical conclusions that can be derived from the hierarchical decomposition of the problem and robustness analysis.

Information quality management (IQM) is crucial in critical Information and Communications Technology (ICT) systems since our lives and health often depend on the quality of information that the systems provide. Especially in the field of transport, we can speak about critical systems. Worldwide, a small number of scientists take on these problems. This is because information quality (IQ) measurement is a very complex process, and IQM is impossible without IQ measurement. In the article, the authors used a method for IQ measurement created by one of them. This method for IQ measurement makes it possible to create IQM and IQ assessment (IQA). This article proposes a method for IQA that makes IQM possible. The authors demonstrated the possibility of searching for IQ modelling imperfections and offered a computation example for a road traffic light power system. In the final section authors present simulation results for two models. The results of this research can be used to optimise information flow. Employing IQA to evaluate ICT systems will enable controlling the maintenance of adequate IQ, among others, after changes to an ICT system or locating the quality models’ weakest or improper elements. The novelty of the presented IQM method is using multi-layer IQA based on uncertainty modelling.

Drug abuse is a worldwide problem that leads to negative physical, mental, and economic consequences. Although pharmacological strategies for drug addiction management have been widely studied, therapeutic options with high efficacy and a low side-effects profile are still limited. Recently, there has been a growing interest in oxytocin (OT) and vasopressin (AVP) systems as potential therapeutic targets for the treatment of drug abuse. OT and AVP are hypothalamic neuropeptides involved in numerous physiological processes. Additionally, studies show that these neurohormones are highly implicated in the modulation of a wide range of behaviors. Interestingly, ample evidence has shown that both, OT and AVP are able to decrease the consumption of different drugs of abuse, as well as to ameliorate their rewarding and reinforcing effects. Furthermore, OT and AVP have been strongly involved in prosocial effects and social reward. In particular, OT has been shown to be able to shift drug-induced reward into social-induced reward, mainly due to its interaction with the dopaminergic system. This phenomenon is also reflected in the results of clinical trials where intranasal OT shows promising efficacy in managing substance use disorder. Therefore, the aim of this review is to comprehensively characterize the involvement of OT and AVP in the rewarding and other behavioral effects of drugs of abuse in animal models, with a particular highlight on the impact of social factors on the observed effects. Understanding this relationship may contribute to higher drug development success rates, as a result of a more profound and deliberate studies design.

In this paper, a novel auxetic structure with rotating squares with holes is investigated. The unit cell of the structure consists of four units in the shape of a square with cut corners and holes. Finally, the structure represents a kind of modified auxetic structure made of rotating squares with holes or sheets of material with regularly arranged diamond and square cuts. Effective and dynamic properties of these structures depend on geometrical properties of the structure. The structures are characterized by an effective Poisson’s ratio from negative to positive values (from about minus one to about plus one). Numerical analysis is made for different geometrical features of the unit cells. The simulations enabled the determination of the dynamic characteristic of the analyzed structures using vibration transmission loss, transmissibility, and mechanical impedance. Numerical calculations were conducted using the finite element method. In the analyzed cases of cellular auxetic structures, a linear elasticity model of the material is assumed. The dynamic characteristic of modified rotating square structures is strongly dependent not only on frequency. The dynamic behavior could also be enhanced by adjusting the geometric parameter of the structure. Auxetic and non-auxetic structures show different static and dynamic properties. The dynamic properties of the analyzed structures were examined in order to determine the frequency ranges of dynamic loads for which the values of mechanical impedance and transmissibility are appropriate.

Vascular endothelial growth factor receptor 2 (VEGF-R2) is a marker of angiogenesis and metastasis of cancer. Two biosensors for the determination of VEGF-R2 in plasma have been developed. One of them is based on a pure gold chip, and the other on a silver/gold bimetallic chip; both have the receptor, monoclonal rabbit antibody specific for human VEGF-R2, attached to the chip via a cysteamine linker. The biosensor with the gold chip exhibits linearity of the analytical signal between 0.03 and 2 ng/mL, a precision of 1.4% and recovery between 99% and 102%. The biosensor with the bimetallic chip exhibits linearity between 0.03 and 1 ng/mL, a precision of 2.2% and recovery between 99% and 103%. Both biosensors tolerate a 1:100 excess of VEGF, VEGF-R1 and VEGF-R3. Both biosensors were validated by parallel determination of VEGF-R2 in 27 different plasma samples using the ELISA immunosensor assay, with very good agreement of the results. Thermodynamic parameters of the interaction of VEGF-R2 with the antibody were determined by QCM (Quartz Crystal Microbalance) and SPRi (Surface Plasmon Resonance imaging) measurements.

Sulfide ores are a major source of noble (Au, Ag, and Pt) and base (Cu, Pb, Zn, Sn, Co, Ni, etc.) metals and will, therefore, be vital for the self-sustainment of future Mars colonies. Martian meteorites are rich in sulfides, which is reflected in recent findings for surface Martian rocks analyzed by the Spirit and Curiosity rovers. However, the only high-resolution (18 m/pixel) infrared (IR) spectrometer orbiting Mars, the Compact Reconnaissance Imaging Spectrometer for Mars (CRISM), onboard the Mars Reconnaissance Orbiter (MRO), is not well-suited for detecting sulfides on the Martian surface. Spectral interference with silicates impedes sulfide detection in the 0.4–3.9 μm CRISM range. In contrast, at least three common hydrothermal sulfides on Earth and Mars (pyrite, chalcopyrite, marcasite) have prominent absorption peaks in a narrow far-IR (FIR) wavelength range of 23–28 μm. Identifying the global distribution and chemical composition of sulfide ore deposits would help in choosing useful targets for future Mars exploration missions. Therefore, we have designed a new instrument suitable for measuring sulfides in the FIR range called the Martian far-IR Ore Spectrometer (MIRORES). MIRORES will measure radiation in six narrow bands (~0.3 µm in width), including three bands centered on the sulfide absorption bands (23.2, 24.3 and 27.6 µm), two reference bands (21.5 and 26.1) and one band for clinopyroxene interference (29.0 µm). Focusing on sulfides only will make it possible to adapt the instrument size (32 × 32 × 42 cm) and mass (

Cryptococcosis is the third most common cause of invasive fungal infection in solid organ transplant recipients and cryptococcal meningitis (CM) its main clinical presentation. CM outcomes, as well as its clinical features and radiological characteristics, have not yet been considered on a large scale in the context of kidney transplantation (KT). We performed a nationwide retrospective study of adult patients diagnosed with cryptococcosis after KT between 2002 and 2020 across 30 clinical centers in France. We sought to describe overall and graft survival based on whether KT patients with cryptococcosis developed CM or not. Clinical indicators of CNS involvement and brain radiological characteristics were assessed. Eighty-eight cases of cryptococcosis were diagnosed during the study period, with 61 (69.3%) cases of CM. Mortality was high (32.8%) at 12 months (M12) but not significantly different whether or not patients presented with CM. Baseline hyponatremia and at least one neurological symptom were independently associated with CM (p < 0.001). Positive serum cryptococcal antigen at diagnosis was also significantly associated with CM (p < 0.001). On magnetic resonance imaging (MRI), three patterns of brain injury were identified: parenchymal, meningeal, and vascular lesions. Although CM does not affect graft function directly, it entails a grim prognosis.

One of the causes of mortality in bees is varroosis, a bee disease caused by the Varroa destructor mite. Varroa destructor mites may occur suddenly in beehives, spread across them, and impair bee colonies, which finally die. Edge IoT (Internet of Things) devices capable of processing video streams in real-time, such as the one we propose, may allow for the monitoring of beehives for the presence of Varroa destructor. Additionally, centralization of monitoring in the Cloud data center enables the prevention of the spread of this disease and reduces bee mortality through monitoring entire apiaries. Although there are various IoT or non-IoT systems for bee-related issues, such comprehensive and technically advanced solutions for beekeeping and Varroa detection barely exist or perform mite detection after sending the data to the data center. The latter, in turn, increases communication and storage needs, which we try to limit in our approach. In the paper, we show an innovative Edge-based IoT solution for Varroa destructor detection. The solution relies on Tensor Processing Unit (TPU) acceleration for machine learning-based models pre-trained in the hybrid Cloud environment for bee identification and Varroa destructor infection detection. Our experiments were performed in order to investigate the effectiveness and the time performance of both steps, and the study of the impact of the image resolution on the quality of detection and classification processes prove that we can effectively detect the presence of varroosis in beehives in real-time with the use of Edge artificial intelligence invoked for the analysis of video streams.

This article presents the results of numerical finite element method (FEM) simulations in the Ansys environment of a Boston orthopaedic brace. The geometric model was developed based on the results of digitisation performed by means of a three-dimensional (3D) optical scanner. A test stand for measurement of the brace’s field of displacements, utilising a laser electronic speckle pattern interferometer (ESPI), was used to experimentally verify the FEM model. During experimental testing, special attention was given to applying the loads and boundary conditions used in the numerical simulations. As a result, the relative difference between the experimentally and numerically determined displacements in the central part of orthoses amounted to approximately 0.6%. The experimentally verified FEM model was used to determine the force flow lines characteristic of the brace, indicating the general working method of the brace’s structure. The primary parts of the orthoses, carrying loads correcting the spine and the position of sites exerting little effort from the perspective of their participation in the orthoses’ essential therapeutic application were identified. The results obtained allow for the proposal of methods for mechanical optimisation of the brace’s design. The analysis conducted is universal in nature and can be adapted to other types of orthopaedic braces.

The aim of the study was to investigate the influence of addition of sodium alginate (SA) and chitosan (CH) on the properties of inulin hydrogels. Inulin hydrogels (20 g/100 g) containing various additions (0.0, 0.1, 0.3, and 0.5 g/100 g) of SA and CH were produced. The hydrogels’ properties were assessed based on the volumetric gel index, microstructure, yield stress, texture, stability, and color parameters. According to the findings, the inclusion of these polysaccharides had no influence on the gelation ability of the inulin solution. The physical properties of the hydrogels containing SA or CH differed from hydrogels containing only inulin (INU). The obtained microstructural pictures revealed that the addition of SA and CH resulted in the formation of hydrogels with a more compact, smooth, and cohesive structure. Consequently, they had higher yield stress, strength, and spreadability values than INU hydrogels. The addition of chitosan in comparison with sodium alginate also had a greater effect in strengthening the structure of hydrogels, especially at the level of 0.5 g/100 g. For example, the addition of this amount of SA increased the yield stress on average from 195.0 Pa (INU) to 493.6 Pa, while the addition of CH increased it to 745.3 Pa. In the case of the strength parameter, the addition of SA increased the force from 0.24 N (INU) to 0.42 N and the addition of CH increased it to 1.29 N. In the case of spreadability this increase was from 2.89 N * s (INU) to 3.44 N * s (SA) and to 6.16 N * s (CH). Chitosan also caused an increase in the stability of inulin hydrogels, whereas such an effect was not observed with the addition of sodium alginate. The gels with the addition of SA and CH also had significantly different values of color parameters. Inulin–alginate hydrogels were characterized by higher values of the color parameter a *, lower values of the color parameter b *, and in most concentrations higher values of the color parameter L * compared to inulin–chitosan hydrogels. Based on the collected data, it can therefore be concluded that through the addition of sodium alginate and chitosan, there is a possibility to modify the properties of inulin hydrogels and, consequently, to better adapt them to the characteristics of the pro-health food products in which they will be used.

Singing voice detection or vocal detection is a classification task that determines whether there is a singing voice in a given audio segment. This process is a crucial preprocessing step that can be used to improve the performance of other tasks such as automatic lyrics alignment, singing melody transcription, singing voice separation, vocal melody extraction, and many more. This paper presents a survey on the techniques of singing voice detection with a deep focus on state-of-the-art algorithms such as convolutional LSTM and GRU-RNN. It illustrates a comparison between existing methods for singing voice detection, mainly based on the Jamendo and RWC datasets. Long-term recurrent convolutional networks have reached impressive results on public datasets. The main goal of the present paper is to investigate both classical and state-of-the-art approaches to singing voice detection.

In order to increase the quality of the products manufactured by injection molding, RTC technology can be used to achieve higher mold temperatures. As a result, the path of the injected melt can be extended, allowing the production of parts with more complex shapes and greater length. Induction heating allows heating only selected forming surfaces of the mold which increases the speed and efficiency of the process. This paper presents the concept of a detachable inductor integrated with sliders to enable the application of this technology in an injection mold with sliders, along with the theoretical model used to perform the tests. First, the effect of the magnetic concentrator shape on the process was analyzed. This was followed by a simulation study of the influence of process parameters: heating time, frequency, and electric current. An extensive analysis of the test results of the temperature distribution on the insert allowed for the selection of parameter sets that would enable obtaining the desired surface temperature without a major increase in process time. The results of simulation studies confirm the possible applications and present the range of parameters for obtaining the optimal process.

The use of selective induction heating of molding surfaces allows for better filling of molding cavities and has a positive effect on the properties of molded products. This is particularly important in the production of parts that include flexible hinges, which are thin plastic layers connecting two or more parts of the product. By using hinges, it is possible to expand the use of injection molding products and their capabilities. They are widely used in the production of parts for the electrical engineering industry and for packaging Fast Moving Consumer Goods (FMCG). The use of hinges also entails specific reductions in wall thickness. Increases in the shear rate can be expected, which can lead to the degradation of polymers and deterioration of mechanical properties of materials. This paper investigates injection molded flexible hinge parts manufactured with selective induction heating to improve their properties. To verify the efficiency of reduction of material degradation due to high shear rates, open/close tests of elastic hinges were performed. The linear relation between the number of cycles the hinges can withstand, mold temperature and injection time was identified, where mold temperature was the more significant factor.

Non-fluidic array SPR imaging (SPRi) with appropriate biosensors is a new tool for the determination of various biomarkers in body fluids. Numerous biomarkers can be determined without signal enhancement or preliminarily preconcentration. The introduction of a new material solution of the chip may increase the scope of the application of this technique. Solutions with adhesive separating foil and an Ag/Au chip were compared with the previously used two-paint separating polymer and pure gold chip. These solutions were tested using the example of a biosensor for cathepsin D (Cath D), which consisted of pepstatin A (a Cath D inhibitor) immobilized via a cysteamine linker using the NHS/EDC protocol. Four material versions of the Cath D biosensor proved adequate in terms of range of linearity, LOQ, precision and recovery. All four versions of the biosensor were used for the determination of Cath D in the blood serum patients with glioblastoma and control samples, producing very similar results and showing an elevated biomarker concentration in the case of cancer. Therefore, the problem of determining the correct level of Cath D in the serum of healthy individuals has been resolved, correcting literature data which ranged over three orders of magnitude.

In this study, we used publicly available data from the Centrum e-Zdrowia (CeZ) Polish Databank proposing a possible correlation between influenza vaccination and mortality due to COVID-19. We limited our search to the patients with positive COVID‑19 laboratory tests from 1 January 2020 to 31 March 2021 and who filled a prescription for any influenza vaccine during the 2019–2020 influenza season. In total, we included 116,277 patients and used a generalized linear model to analyze the data. We found out that patients aged 60+ who received an influenza vaccination have a lower probability of death caused by COVID-19 in comparison to unvaccinated, and the magnitude of this difference grows with age. For people below 60 years old, we did not observe an influence of the vaccination. Our results suggest a potential protective effect of the influenza vaccine on COVID-19 mortality of the elderly. Administration of the influenza vaccine before the influenza season would reduce the burden of increased influenza incidence, the risk of influenza and COVID‑19 coinfection and render the essential medical resources accessible to cope with another wave of COVID-19. To our knowledge, this is the first study showing a correlation between influenza vaccination and the COVID-19 mortality rate in Poland.

There is a growing body of scientific research showing the link between depression and dementia in Alzheimer’s disease (AD). The chronic stress contributes to the formation of oxidative stress in the parts of the brain involved in the development of depression and AD. The scientific literature reports the significant role of antioxidants, which are highly effective in treating these diseases. In this review, we have summarized the relationship between chronic stress, oxidative stress, and the changes in the brain they cause occurring in the brain. Among all the compounds showing antioxidant properties, the most promising results in AD treatment were observed for Vitamin E, coenzyme Q10 (CoQ10), melatonin, polyphenols, curcumin, and selenium. In case of depression treatment, the greatest potential was observed in curcumin, zinc, selenium, vitamin E, and saffron.

A new series of 1,8-naphtalimides containing an imine bond at the 3-position of the naphthalene ring was synthesized using 1H, 13C NMR, FTIR, and elementary analysis. The impact of the substituent in the imine linkage on the selected properties and bioimaging of the synthesized compounds was studied. They showed a melting temperature in the range of 120–164 °C and underwent thermal decomposition above 280 °C. Based on cyclic and differential pulse voltammetry, the electrochemical behavior of 1,8-naphtalimide derivatives was evaluated. The electrochemical reduction and oxidation processes were observed. The compounds were characterized by a low energy band gap (below 2.60 eV). Their photoluminescence activities were investigated in solution considering the solvent effect, in the aggregated and thin film, and a mixture of poly(N-vinylcarbazole) (PVK) and 2-tert-butylphenyl-5-biphenyl-1,3,4-oxadiazole (PBD) (50:50 wt.%). They demonstrated low emissions due to photoinduced electron transport (PET) occurring in the solution and aggregation, which caused photoluminescence quenching. Some of them exhibited light emission as thin films. They emitted light in the range of 495 to 535 nm, with photoluminescence quantum yield at 4%. Despite the significant overlapping of its absorption range with emission of the PVK:PBD, incomplete Förster energy transfer from the matrix to the luminophore was found. Moreover, its luminescence ability induced by external voltage was tested in the diode with guest–host configuration. The possibility of compound hydrolysis due to the presence of the imine bond was also discussed, which could be of importance in biological studies that evaluate 3-imino-1,8-naphatalimides as imaging tools and fluorescent materials for diagnostic applications and molecular bioimaging.

The array SPR imaging (SPRi) technique is well suited to the determination of biomarkers in body fluids, called liquid biopsy. No signal enhancement or analyte preconcentration is required. With the aim of achieving signal enhancement and lowering the cost of a single determination, the replacement of gold-covered chips by silver–gold chips was investigated. The aim of this work was to investigate the analytical characteristics of a biosensor formed on a Ag/Au chip and to compare them with those of a biosensor formed on a gold chip. A biosensor for the determination of cathepsin S (Cath S) was chosen as an example. The biosensor consisted of the linker cysteamine and an immobilized rat monoclonal antibody specific for cathepsin S. Both biosensors exhibited a Langmuirian response to Cath S concentration, with linear response ranging from LOQ to 1.5 ng mL−1. The LOQ is 0.1 ng mL−1 for the biosensor formed on the Ag/Au chip, and 0.22 ng mL−1 for that formed on the gold chip. Recoveries and precision for medium and high Cath S concentrations were acceptable for both biosensors, i.e., precision better than 10% and recoveries within the range 102–105%. However, the results for the lowest Cath S concentration were better for the biosensor formed on the Ag/Au chip (9.4 and 106% for precision and recovery, respectively). Generally, no significant differences in analytical characteristics were observed between the Ag/Au and Au chips. The two biosensors were also compared in the determination of Cath S in real samples. Nine plasma samples from healthy donors and nine from patients with ovarian cancer were analyzed for Cath S concentration with the biosensors formed on Ag/Au and Au chips. The results obtained with the two biosensors were very similar and show no significant differences on the Bland–Altman plot. The Cath S concentration in the blood plasma of ovarian cancer patients was elevated by one order of magnitude as compared with the control (12.6 ± 3.6 vs. 1.6 ± 1.2 ng mL−1).

One of the methods of converting thermal energy into electricity is the use of thermoelectric generators (TEG). The method can be used in low-temperature waste heat conversion systems from industrial installations, but its serious limitation is the low efficiency of thermolectric generators and the relatively low power of the electric waveforms obtained. Increasing the obtained power values is done by multiplying the number of TEGs used, grouped into modules (MTEG). In such systems, the design of the module is extremely important, as it should ensure the best possible heat transfer between both sides of the TEG (hot and cold), and thus obtaining maximum electrical power. The article presents an analysis of a two-section flat plate heat hot side exchanger MTEG. The key parameters like effectiveness of exchange and MTEG efficiency and their impact on the efficiency of heat use and generated electric power were indicated. The tests showed an improvement in these main system parameters for the mixed cycle (co-current and countercurrent—inward direction) of the hot side heat exchanger, compared to the countercurrent flow in both sections of this exchanger.

An important achievement in the functional diagnostics of memory devices is the development and application of so-called transparent testing methods. This is especially important for modern computer systems, such as embedded systems, systems and networks on chips, on-board computer applications, network servers, and automated control systems that require periodic testing of their components. This article analyzes the effectiveness of existing transparent tests based on the use of the properties of data stored in the memory, such as changing data and their symmetry. As a new approach for constructing transparent tests, we propose to use modified address sequences with duplicate addresses to reduce the time complexity of tests and increase their diagnostic abilities.

Comparative analysis of the sensitivity of two surface plasmon resonance (SPR) biosensors was conducted on a single-metallic Au sensor and bimetallic Ag–Au sensor, using a cathepsin S sensor as an example. Numerically modeled resonance curves of Au and Ag–Au layers, with parameters verified by the results of experimental reflectance measurement of real-life systems, were used for the analysis of these sensors. Mutual relationships were determined between ∂Y/∂n components of sensitivity of the Y signal in the SPR measurement to change the refractive index n of the near-surface sensing layer and ∂n/∂c sensitivity of refractive index n to change the analyte’s concentration, c, for both types of sensors. Obtained results were related to experimentally determined calibration curves of both sensors. A characteristic feature arising from the comparison of calibration curves is the similar level of Au and Ag–Au biosensors’ sensitivity in the linear range, where the signal of the AgAu sensor is at a level several times greater. It was shown that the influence of sensing surface morphology on the ∂n/∂c sensitivity component had to be incorporated to explain the features of calibration curves of sensors. The shape of the sensory surface relief was proposed to increase the sensor sensitivity at low analyte concentrations.

Injection molding is a polymer processing technology used for manufacturing parts with elastic hinges. Elastic hinges are widely used in FMCG (Fast Moving Consumer Goods) packaging (e.g., bottle closures of shampoos, sauces) and in the electrical engineering industry. Elastic hinge is a thin film that connect two regions of the injection molded part, where significant shear rates are present, which can lead to the degradation of polymers and the decrease in mechanical properties. Selective induction heating is the method that improves the flow of the polymer melt through thin regions by the local increase in mold temperature. In this study, selective induction heating was used to improve mechanical properties of elastic hinges by the reduction of material degradation due to high shear rates. To verify the change of shear rates, selective induction heating simulation and injection molding simulations were performed. The linear relation between mold temperature and maximum shear rate in the cross-section was identified and the mechanical tests showed significant differences in hinge stiffness, tensile strength and elongation at break.

In recent years, carbon nanomaterials have been intensively investigated for their possible applications in biomedical studies, especially as drug delivery vehicles. Several surface modifications can modulate the unique molecular structure of [60]fullerene derivatives, as well as their physicochemical properties. For this reason, covalent modifications that would enable a greater water solubilization of the fullerene buckyball have been rapidly investigated. The most exciting applications of fullerene nanomaterials are as drug delivery vectors, photosensitizers in photodynamic therapy (PDT), astransfection or MRI contrast agents, antimicrobials and antioxidants. From these perspectives, the glucose derivatives of [60]fullerene seem to be an interesting carbon nanomaterial for biological studies. It is well-known that cancer cells are characterized by an increased glucose uptake and it has also been previously reported that the glucose transporters (GLUTs) are overexpressed in several types of cancers, which make them attractive molecular targets for many drugs. This study explored the use of a highly water-soluble glycofullerene (called Sweet-C60) in pancreatic cancer studies. Here, we describe the PANC-1 cell proliferation, migration, metabolic activity and glycolysis rate after incubations with different concentrations of Sweet-C60. The final results did not show any influence of the Sweet-C60 on various cancer cellular events and glycolysis, suggesting that synthesized glycofullerene is a promising drug delivery vehicle for treating pancreatic cancer.

To solve the problem of human diseases caused by a combination of genetic and environmental factors or by microorganisms, intense research to find completely new materials is required. One of the promising systems in this area is the silver-silica nanocomposites and their derivatives. Hence, silver and silver oxide nanoparticles that were homogeneously distributed within a silica carrier were fabricated. Their average size was d = (7.8 ± 0.3) nm. The organic polymers (carboxymethylcellulose (CMC) and sodium alginate (AS)) were added to improve the biological features of the nanocomposite. The first system was prepared as a silver chlorine salt combination that was immersed on a silica carrier with coagulated particles whose size was d = (44.1 ± 2.3) nm, which coexisted with metallic silver. The second system obtained was synergistically interacted metallic and oxidized silver nanoparticles that were distributed on a structurally defective silica network. Their average size was d = (6.6 ± 0.7) nm. Physicochemical and biological experiments showed that the tiny silver nanoparticles in Ag/SiO2 and Ag/SiO2@AS inhibited E. coli, P. aeruginosa, S. aureus, and L. plantarum’s cell growth as well as caused a high anticancer effect. On the other hand, the massive silver nanoparticles of Ag/SiO2@CMC had a weaker antimicrobial effect, although they highly interacted against PANC-1. They also generated reactive oxygen species (ROS) as well as the induction of apoptosis via the p53-independent mechanism.

The main method to improve the filling of the cavity by the polymer melt is to increase the mold temperature. Rapid temperature cycling (RTC) technologies have been used around the world for several years, improving the quality of injection molded parts with a slight extension of production time. The present work focuses on the application of induction heating technology in the injection molding process since it is the most effective and most intensively developing method of heating in modern RTC technologies. In this research, the application of the induction heating process for selected surfaces was investigated with particular emphasis on the dynamics of the process. The numerical simulations were used to study the influence of the number of coils, the distance between coils and cavity surface and the mold material was examined with and without the presence of a magnetic concentrator. According to the obtained results, several crucial conclusions were made: the efficiency of heating is directly correlated with the distance between the inductor and the mold surface, the presence of magnetic flux concentrator significantly improves the homogeneity of temperature distribution and heating efficiency, application of aluminum mold lowers the obtained surface temperature.