Idiopathic pulmonary fibrosis [IPF] is a chronic progressive disease characterised by the accumulation of scar tissue in the lung parenchyma. It primarily occurs in middle-aged and elderly adults and results in significant morbidity and mortality worldwide. The disease occurs due to repetitive lung epithelial injury, subsequent fibroblast activation and myofibroblast differentiation, resulting in excessive extracellular matrix deposition. This leads to scar formation and subsequent loss of lung function. Current treatment options for patients with IPF include the two anti-fibrotic drugs, pirfenidone and nintedanib, which can slow disease progression; however, there are currently no known cures for the disease. As such, novel methods and drug targets are warranted. In this review, we provide an up-to-date account of the importance of specific cytokines and the potential role of regulatory immune cells. We discuss their role in the pathogenesis of IPF and address some of the key gaps in knowledge.

Butler matrix networks are well established as beam forming networks for phased antenna arrays. The challenge we address in this work is to cover the entire, (advanced 5G or 6G), FR3 band (7-24 GHz) with a single network, while retaining low losses and minimal size. The employed multilayer topology is also well established, however, the matching between the utilized hybrid couplers and the phase shifters constitutes a major challenge for such a wideband operation. This is achieved herein employing meander lines with appropriate curvature and introducing two distinct design methods for the Butler Matrix. The first method focuses on designing individual components separately, followed by their integration into the overall Butler Matrix structure. This approach is demonstrated through the design, prototyping, measurements and validation of an 8x8 Butler Matrix beamformer, which operates across the 6-16 GHz band (FR3 Low). The second method introduces a wideband matching technique, which simplifies the implementation process by designing the Butler Matrix as a single, unified structure. This technique is applied to both 4x4 and 8x8 Butler Matrices, which are implemented and simulated for the low FR3 band. Both design methods result in wideband operation, compact size, and meet the desired performance criteria.

The conformations of trifluoroacetyl triflate, CF3C(O)OSO2CF3, were investigated through vibrational experimental methods (gas-phase FTIR, liquid-phase Raman, and Ar-matrix FTIR spectroscopy) and Density Functional Theory (DFT) calculations. A potential energy surface was computed using the B3P86 /6-31+g(d) approximation as a function of the dihedral angles τ1 = CCOS and τ2 = COSC. The surface reveals three minima, which were further optimized using the B3LYP method with various basis sets (6-31++G(d), 6-311++G(d), tzvp and cc-pvtz). The global minimum corresponds to a syn-anti conformer (the CO double bound syn with respect the O−S single bond and the C−O single bond anti with respect to de S−C single bond). The other two minima represent enantiomeric syn-gauche forms. The Ar-matrix FTIR spectrum exhibited clear evidence of the presence of two conformers. Furthermore, the randomization process observed following broad-band UV-visible irradiation facilitated the identification of the IR absorption of each conformer. Based on the Ar-matrix FTIR experiments, the vapour phase of trifluoroacetyl triflate at room temperatures was composed of approximately 60-70% of the syn-anti conformer and 30-40% of the syn-gauche form.

The performance consistency of an RF MEMS switch matrix is a crucial metric, which directly impacts its operational lifespan. An improved crossbar-based RF MEMS switch matrix topology, the SR-Crossbar, was investigated in this article. An optimized port configuration scheme was proposed for the RF MEMS switch matrix. Both the utilization probability of individual switch nodes and path lengths in the switch matrix achieve best consistency simultaneously under the proposed port configuration scheme. One significant advantage of this scheme lies in that it only adjusts positions of input and output ports, with topology and individual switch nodes kept unchanged. This grants it a high level of generality and feasibility, and also introduces an additional degree of freedom for optimizations. The article also constructed a universal utilization probability function of single nodes, and formulated an optimization objective function for the SR-Crossbar RF MEMS switch matrix, which provides a convenient approach to directly solving the optimized port configuration scheme for practical applications.

Biofilm matrix is akin to bacterial abodes, primarily composed of proteins, polysaccharides, extracellular DNA, and lipids, providing essential structural support to bacteria. While some biofilm matrix offers significant benefits, such as engineered biofilm reactors that assist in water pollutant removal, others pose risks to human health, potentially leading to conditions like lung infections. Realizing the potential of advantageous biofilm matrix and mitigating the harmful effects of detrimental ones necessitates a comprehensive and systematic exploration of this intricate domain. To facilitate this examination, our study leveraged a dataset of the 1000 most pivotal papers in the field and conducted an exhaustive bibliographic review. This paper serves as a valuable resource for understanding the current progress in biofilm matrix research and delving into vital avenues for future exploration in this dynamic field.

(1) Background: Vitamin K deficiency is a common feature of chronic kidney disease (CKD), leading to impaired bone quality and increased risk of vascular calcifications. A method to indirectly measure Vitamin K status is measuring the blood level of Vitamin K dependent proteins (VKDP)- osteocalcin (OC) and matrix GLA protein (MGP). The aim of this study is to correlate the level of OC and MGP with markers of CKD mineral bone disorder (CKD-MBD). (2) Methods: We conducted a single-center cross-sectional study that included 45 CKD G5D patients and measured blood biochemistry, complete blood count and intact osteocalcin and matrix GLA protein. (3) Results: We found a strong statistically significant correlation of OC with the markers of CKD-MBD such as: iPTH , serum calcium and serum phosphorus and a strong indirect statistically significant correlation with abdominal circumference. There was also a statistically significant correlation of MGP with markers of inflammation (CRP). Higher levels of MGP were found in patients treated with vitamin K antagonists, non-calcium based phosphate binders and vitamin D receptor activator- paricalcitol. (4) Conclusions: In our study, we found that vitamin K deficiency, measured indirectly using the level of VKDP is associated to CKD-MBD. The use of medication such as phosphate binders, that reduce vitamin K absorbtion, Vitamin D that increases Vitamin K requirements and also vitamin K antagonists, seem to have an influence on the blood level of VKDPs.

Diminished ovarian reserve can be regarded as a sentinel indicator to foreshadow severe follicular loss and, ultimately, systemic aging. The negative slope of human ovulatory fidelity begins with a robust follicular endowment which gradually declines over time. In contrast, the youthful ovarian phenotype requires the coordinated work of endothelial, granulosa, immune, perivascular, stromal and possibly germline stem cells. Such a diverse tissue matrix can, in general, be influenced by platelet (PLT)-derived factors but this has not yet been specifically confirmed in the ovary after platelet-rich plasma (PRP). How could a comparable response be validated? Here a prospective, experimental study is proposed whereby eligible patients already undergoing scheduled laparoscopy provide ovarian tissue via biopsy submitted for co-culture with autologous Ca⁺² activated PRP. Recognizing the interlocking, central roles of nuclear factor κB (NF-κB) and tumor necrosis factor-α (TNF-α), incubated samples would be assessed for these in vitro before vs. after PRP exposure, in addition to stereomicroscopy. A mathematical model is available to track NF-κB oscillations and estimate gene expression, cell development, growth, apoptosis, and key immune and inflammatory actions. Since NF-κB and TNF-α are discharged in activated PLT releasate (or react to its cargo proteins) this audit permits extraction of response markers observed post-stimulus, thus linking discrete signals to transcriptional output, cellular fitness, and ovarian cytoarchitecture. From this, a hypothesis could emerge where intraovarian PRP is found to make no direct impact on follicles, although modified ovarian field function and curtailed local entropy incidentally favor optimized oocyte competence as a secondary effect.

Matrix Factorization is a long established method employed for analyzing and extracting valuable insight recommendations from complex networks containing user ratings. The execution time and computational resources demanded by these algorithms pose limitations when confronted with large datasets. Community detection algorithms play a crucial role in identifying groups and communities within intricate networks. To overcome the challenge of extensive computing resources, we present a novel parallel computation framework utilizing community information available in the rating network. Our proposed approach named as Community-based Matrix Factorization(CBMF), parallelizes matrix factorization technique by dividing the network into communities using existing community detection algorithms. We prove that this parallel approach not only increases the quality of recommendations in connection with Root Mean Square Error (RMSE), but also yields substantial performance improvement. We empirically evaluate our idea on diverse datasets and present comprehensive experimental results. These results serve as empirical evidence of the effectiveness and performance gains offered by our parallel computation framework.

In this study, the concentrations of metals (As, Cd, Co, Cr, Cu, Hg, Ni, Pb, and Zn) were deter-mined in two freshwater fish species. The same fish were also used to determine the content of fatty acids (FA), including saturated fatty acids (SFA), monounsaturated fatty acids (MUFA), and polyunsaturated fatty acids (PUFA). We investigated the species-specific relationship between bioaccumulation of metals and the content of FA. Roach and white bream were caught at two different sites in the Serbian part of the Danube. The measured metal concentrations were below the standard concentrations recommended in the guidelines of the EU and the Republic of Ser-bia. Among the non-essential metals, Ni had the highest concentration, ranging from 0.158 to 0.591 µg g-1. The muscle of the two fish species contained high concentrations of SFA, ranging from 36.31 to 51.79%, and MUFA, ranging from 33.56 to 43.70%. Polyunsaturated fatty acids were represented with the lowest percentage (5.32 - 27.18). Four of the nine metals studied (As, Hg, Ni and Pb) in one fish species and five of the nine metals studied (A, Cu, Ni, Pb and Zn) in the other fish species showed correlations with fatty acid content. These results help to reveal potential biomarkers of metal stress in lipid composition.

Novel tetragonal matrix Ba0.5Gd0.5-xNaxF2.5-x, where x = 0.05, doped by Yb3+, Ho3+, Er3+, was synthesized by molten salt synthesis (MSS) from nitrate flux. XRD data show that tetragonal phase with a = 4.122(1) Å, c = 17.672(1) Å is stable in argon atmosphere up to 960 °C. Luminescence spectra recorded in 500-900 nm and 1050-1700 nm upon 974 nm pumping demonstrated the characteristic luminescence at 1550 nm (4I13/2 → 4I15/2) for Er3+ and 1150 nm (5I6 → 5I8) for Ho3+. The relative thermal sensitivity (Sr) at 296-316 K were 0.3 %*K-1 and 5.5%*К-1 in shortwave infrared (SWIR) and visible range, respectively. Synthesized luminophores can be used as dual-range optical temperature sensors, which simultaneously operating in visible and SWIR ranges.

In estimating logistic regression models, convergence of the maximization algorithm is critical, however, this may fail. Numerous bias correction methods for maximum likelihood estimates of the parameters have been conducted for cases of complete data sets and also longitudinal models. For binary response fixed effects panel data model, the conditional logit estimator is consistent for balanced data. When faced with missing covariates problem, researchers opt for various imputation techniques to make the data complete and without loss of generality consistent estimates still suffice asymptotically. For maximum likelihood estimates of the parameters for logistic regression in cases of imputed covariates, the optimal choice of an imputation technique which yields the best estimates with minimum variance is still elusive. The main aim of this paper is to examine the behaviour of the Hessian matrix with optimal values of the imputed covariates vector which will make the Newton-Raphson algorithm to converge faster through a reduced absolute value of the product of the score function and the inverse fisher information component. We focus on a method used to modify the conditional likelihood function through partitioning of the covariate matrix. We also confirm from the moduli of the Hessian matrices that the log likelihood of a panel data logistic model has a global maximum as the parameter estimates. Simulation results reveal that model based simulation perform better than classical imputation techniques yielding estimates with smaller bias and higher precision for the conditional maximum likelihood estimation of nonlinear panel models with single fixed effects.

Matrix metalloproteinases (MMPs) are often considered biomarkers of skin fibrosis. At the early stages of the pathological process, an elevation of their enzymatic activity causes significant changes in the composition of the extracellular matrix. MMPs secreted by immune cells facilitate their migration to the site of damage. Then, the immune cells eliminate the affected cells and biomolecules. Moreover, bidirectional changes in the activity of proteolytic enzymes, including MMPs, accompany wound healing. This study aimed to assess changes in the expression of Mmp2, Mmp3, and Mmp9 after treating the mice with laser therapy using the experimental model of bleomycin-induced skin fibrosis. Using immunohistochemistry, we characterized the histological features of scarred skin. We also analyzed changes in the expression of MMPs using real-time polymerase chain reaction before and after the irradiation with laser. We showed that treatment of the mice with CO2 laser partially normalized the histological features of scarred skin. We also noticed a decrease in the expression of Mmp2, Mmp3 (both p < 0.05), and Mmp9 (p = 0.065) during scar healing. The obtained results suggest that normalization of skin homeostasis requires a control of MMPs activities via induction of their genes.

Cells actively sense differences in topology, matrix elasticity and protein composition of the extracellular microenvironment and adapt their function and morphology. In this study, we focus on the cross-talk between matrix stiffness and protein coating density that regulate morphology and proliferation dynamics of single myocytes. For this, C2C12 myocytes were monitored on L-DOPA functionalized hydrogels of 22 different elasticity and fibronectin density compositions. Static images were recorded and statistically analyzed to determine morphological differences and to identify the optimized extracellular matrix (ECM). Using that information, selected ECMs were used to study the dynamics before and after cell proliferation by statistical comparison of distinct cell states. We observed a fibronectin density independent increase of the projected cell area until 12 kPa. Additionally, changes in the fibronectin density led to an area optimum at about 2.6 μg/cm, which was confirmed by an independent F-actin analysis, revealing a maximum actin filament to cell area ratio of 7.5 %. The proliferation evaluation showed an opposite correlation between cell spreading duration and speed to the matrix elasticity and protein density, which did not affect the cell cycle duration. In summary, we identified an optimized ECM composition, while independent matrix properties regulate distinct cell characteristics.

There is need to address the challenges of organ shortage, through development of tissues and organs with alternatives to those of the allograft-kind. This illustrates the quest behind novel biofabrication strategies such as 3D bio-printing, which is necessary to create artificial multi-cellular tissues/organs. Several findings have been reported in this review. First, the role of ECM components in tissue regenerative medicine is presented. Different ECM components such as collagen, gelatin, elastin, fibronectin, laminins and glycosaminoglycans are concisely examined for their tissue regenerative medicine applications. Next, current state of research on extrusion-based 3D bio-printing techniques and their limitations are reviewed. For example, we show that cell viability is still a challenge with extrusion, while the use of natural polymers such as collagen in improving composites’ mechanical properties is limited. Lastly, we examine unresolved research questions necessary to advance the present state of research in the field.

Matrix metalloproteinases have been implicated in muscular dystrophy progression and recent studies described the role of MMP-10 in skeletal muscle pathology of young dystrophic mice. Nevertheless, its implication in dystrophin deficient hearts is still missing. Here, we aimed at investigating MMP-10 implication in severe muscular dystrophic progression and characterize MMP-10 loss in skeletal and cardiac muscles of aged dystrophic mice. We examined the histopathological effect of MMP-10 ablation in aged mdx mice, both in the hind limb muscles and heart tissues. We have found that MMP-10 loss compromises survival rates of aged mdx mice, with skeletal and cardiac muscles developing a chronic inflammatory response. Our findings indicate that MMP-10 is implicated in severe muscular dystrophy progression, identifying a new area of investigation that could lead to future therapies for dystrophic muscles.

A distributed bragg reflector is designed to get an optical reflectance on visible electromagnetic spectrum i.e. ~800 nm in this work. Device is realized based on Abele’s matrix for TE mode.

Studying various marine biomineralized ultrastructures reveals the appearance of common architectural designs and building blocks in materials with fascinating mechanical properties that match perfectly to their biological tasks. Advanced mechanical properties of biological materials are attributed to evolutionary optimized molecular architectures and structural hierarchy. One example which has not yet been structurally investigated in great detail is the shell of Mytilus edulis L. (Finnish blue mussel) found in the archipelago of SW-Finland. Through a combination of various state-of-the-art techniques such as high-resolution electron microscopy imaging, Fourier-transformed infrared spectroscopy, powder X-ray diffraction, synchrotron wide-angle X-ray diffraction, nanoindentation and protein analysis, both the inorganic mineralized components as well as the organic-rich matrix were extensively characterized. We found very similar ultra-architecture across the shell of M. edulis L. as compared to the widely studied and closely related M. edulis. However, we also found interesting differences, for instance in the thickness and degree of orientation of the mineralized layers indicating dissimilar properties and related alterations in the biomineralization processes. Our results show that the shell of M. edulis L. has a gradient of mechanical properties, with the increase in the stiffness and the hardness from anterior to the posterior region of the shell. The shell is made from distinct and recognizable mineralized layers each varying in thickness and microstructural features. At posterior regions of the shell, moving from dorsal to ventral side, these layers are an oblique prismatic layer, a prismatic layer and a nacreous layer, in which the oblique prismatic layer is found to be the main and thickest mineralized layer of the shell. Probing the calcified rods in the oblique prismatic layer using high resolution SEM imaging revealed opening of channels with a diameters of 40-50 nm and lengths up to a micrometer extending through the rods. The chitin and protein have been found to be the main component of the organic-rich interfacial matrix as expected. Protein analysis showed two abundant proteins with sizes around 100 kD and 45 kD which likely not only regulates biomineralization and adhesion of the crystals but also governing the intrinsic-extrinsic toughening in the shell. Overall, this detailed analysis provides new structural insights into biomineralization of marine shells in general.

The purpose of this study is to estimate the mean transitioning probabilities from a Healthy state to malaria positive uncomplicated state or to malaria positive severe state. It also classifies the various transitioning probabilities of moving through the various states based on some baseline characteristics. Malaria test results for 2019 over a 12-month period were collected from the University of Ghana school clinic. An H-U model for the study was developed and the transition rates from the cross-sectional data are indicated. With two states Healthy (H) and Uncomplicated (U) forming a state space, there were four possible transitions. The results show that the probability of transitioning from a Healthy state to a malaria positive state is 0.03% while the probability that an individual will remain at Healthy state (H) after the test is 99.73%. It was found that if an individual is already positive and has taken medication the probability that its second test came out negative is 6.45% while the chances that it will remain positive but uncomplicated is 93.55%. The study also showed that in the long run, about 95.98% of persons who visited the student clinic with malaria symptoms recorded negative tests for malaria parasite while about 4% recorded positive for malaria. In terms of disaggregation by gender, it was realized that the number of reported negative test results were higher for females (97.08%) than for males (96.13%). However, the infection rate is higher for males (3.87%) than females (2.92%). It is recommended that in as much as the University of Ghana has two health centers (a clinic and hospital), there should be a centralized system to track students’ health so research done would not be biased.

Milk and dairy foods are naturally rich sources of a wide range of nutrients, and when consumed according to recommended intakes contribute essential nutrients across all stages of the life cycle. Since then, seminal studies recommendations with respect to intake of saturated fat have been consistent and clear; limit total fat intake to 30% or less total dietary energy, with a specific recommendation for intake of saturated fat to less than 10% of total dietary energy. However, recent work has re-opened the debate on intake of saturated fat in particular, with suggestions that recommended intakes be considered not at a total fat intake within the diet, but at a food specific level. A large body of evidence exists examining the impact of dairy consumption on markers of metabolic health, both at a total dairy intake and also at a food level, with mixed findings to date, but suggests that the impact of saturated fat intake on health differs both across food groups and even between foods within the same good group such as dairy. Milk and dairy foods contain a range of nutrients and bioactive components in different levels, housed within very different food structures. The interaction of the overall food structure and the nutrients describes the concept of the ‘food matrix effect’ which has been well documented for dairy foods. Studies show that nutrients from different dairy food sources can have different effects on health and for this reason, they should be considered individually rather than grouped as a single food category in epidemiological research. This review examines the current evidence from randomised controlled trials and meta-analyses, with respect to dairy, milk, yoghurt and cheese on aspects of metabolic health, and summarises some of the potential mechanisms for these findings.

Viral protein 24 (VP24) from Ebola virus (EBOV) was first recognized as a minor matrix protein that associates with cellular membranes. However, more recent studies shed light on its roles in inhibiting viral genome transcription and replication, facilitating nucleocapsid assembly and transport, and interfering with immune responses in host cells through downregulation of interferon (IFN)-activated genes. Thus, whether VP24 is a peripheral protein with lipid binding ability for matrix layer recruitment has not been explored. Here we examined the lipid binding ability of VP24 with a number of lipid binding assays. The results indicated that VP24 lacked the ability to associate with lipids tested regardless of VP24 posttranslational modifications. We further demonstrate that the presence of the EBOV major matrix protein VP40 did not promote VP24 membrane association in vitro or in cells. Further, no protein-protein interactions between VP24 and VP40 were detected by co-immunoprecipitation. Confocal imaging and cellular membrane fractionation analyses in human cells suggested VP24 did not specifically localize at the plasma membrane inner leaflet. Overall, we provide evidence that EBOV VP24 is not a lipid binding protein and its presence in the viral matrix layer is likely not dependent on direct lipid interactions.

Metal matrix composite are used in such fields of technology, such as: aerospace, electronics, energy, industry, defense, automotive, aviation, shipbuilding, and more. Composite coatings of ceramic - metals is used primarily to enhance the durability of machine parts. Therefore, new materials are permanently looked for, what has resulted in the past in development of composite materials. The coatings dispersed are consisting of metallic matrix (metals and their alloys) and small non-metallic particles. The deposition of ceramic particles simultaneously with metallic matrix leads often to composite coatings possessing properties much better than those of metallic coating. The nickel and less often, other iron group elements are usually used as a matrix and Al2O3 as tough particles. The welding technology of applying alloy and composite coatings is widely used. The technology of infrasound thermal spraying of metal matrix composite coatings was presented. It is a simple technology and a very useful one in ship machinery regeneration during the cruise craft (e.g. internal combustion engines, torque pumps, separators). The metal matrix composite coatings must undergo finishing due to high surface roughness after application. In the article to used finishing by plastic working and machining of coatings nickel matrix composite was proposed.

Portfolio weights solely based on risk avoid estimation error from the sample mean, but they are still affected from the misspecification in the sample covariance matrix. To solve this problem, we shrink the covariance matrix towards the Identity, the Variance Identity, the Single-index model, the Common Covariance, the Constant Correlation and the Exponential Weighted Moving Average target matrices. By an extensive Monte Carlo simulation, we offer a comparative study of these target estimators, testing their ability in reproducing the true portfolio weights. We control for the dataset dimensionality and the shrinkage intensity in the Minimum Variance, Inverse Volatility, Equal-risk-contribution and Maximum Diversification portfolios. We find out that the Identity and Variance Identity have very good statistical properties, being well-conditioned also in high-dimensional dataset. In addition, the these two models are the best target towards to shrink: they minimise the misspecification in risk-based portfolio weights, generating estimates very close to the population values. Overall, shrinking the sample covariance matrix helps reducing weights misspecification, especially in the Minimum Variance and the Maximum Diversification portfolios. The Inverse Volatility and the Equal-Risk-Contribution portfolios are less sensitive to covariance misspecification, hence they benefit less from shrinkage.

The implementation of graphene-based electronics requires fabrication processes able to cover large device areas since exfoliation method is not compatible with industrial applications. Chemical vapor deposition of large-area graphene represents a suitable solution having the important drawback of producing polycrystalline graphene with formation of grain boundaries, which are responsible for limitation of the device performance. With these motivations, we formulate a theoretical model of graphene grain boundary by generalizing the graphene Dirac Hamiltonian model. The model only includes the long-wavelength regime of the particle transport, which provides the main contribution to the device conductance. Using symmetry-based arguments deduced from the current conservation law, we derive unconventional boundary conditions characterizing the grain boundary physics and analyze their implications on the transport properties of the system. Angle resolved quantities, such as the transmission probability, are studied within the scattering matrix approach. The conditions for the existence of preferential transmission directions are studied in relation with the grain boundary properties. The proposed theory provides a phenomenological model to study grain boundary physics within the scattering approach and represents per se an important enrichment of the scattering theory of graphene. Moreover, the outcomes of the theory can contribute in understanding and limiting detrimental effects of graphene grain boundaries also providing a benchmark for more elaborated techniques.

In this article, bio-composites derived from starch-glycerol biodegradable matrix reinforced with jute fibers have been fabricated using the wet hand lay-up and compression moulding techniques. Samples having different weight percentages of jute fiber in the starch matrix have been analysed. The fibers surface was chemically treated by alkaline sodium hydroxide for improving the interphase bonding between fiber and matrix. Tensile test for the composites were done and the sample with highest tensile strength was selected for further tests that included water absorption, scanning electron microscopy and thermal analysis. It has been concluded that the ultimate tensile strength was found to be maximum for the composition of 15% fiber by weight composite as 7.547 MPa without epoxy coating and 10.43 MPa with epoxy coating. The major disadvantage of bio-composite is its high water absorption property, which in this study has been inhibited by the epoxy resin layer. Herein, the results of various tests done disclose a noteworthy improvement in the overall properties of bio-composite, in comparison to the neat biodegradable starch matrix.

Fatty acids (FAs) represent an important class of metabolites, impacting on membrane building blocks and cellular regulatory networks. In nature, prokaryotes are characterized with the most impressing FA structural diversity and the highest relative contents of free fatty acids (FFAs). Thereby, nitrogen-fixing bacteria (order Rhizobiales), often found in symbiosis with legumes, attract a special interest. Indeed, FAs impact on the structure of rhizobial nodulation factors, required for successful infection of plant root. Although the FA patterns can be addressed by GC- and LC-MS, these methods are time-consuming and suffer from compromised sensitivity, low stability of derivatives and artifacts. In contrast, MALDI-TOF-MS represents an excellent platform for high-efficient metabolite fingerprinting, also applicable to FFAs. Therefore, here we propose a simple and straightforward protocol for high-throughput relative quantification of FFAs in rhizobia by the combination of Langmuir technology and MALDI-TOF-MS, which is featured with high sensitivity, accuracy and precision of quantification. Here we propose a step by step procedure comprising rhizobia culturing, pre-cleaning, extraction, sample preparation, mass spectrometric analysis, data processing and post-processing. To demonstrate the analytical potential of the protocol we illustrate it by a case study – comparison the FFA metabolomes of two rhizobia species - Rhizobium leguminosarum and Sinorhizobium meliloti.

The primary purpose of this article is to provide a brief overview about the notion of the \textit{Mertens Function} $M(n)$ and \textit{Redheffer Matrices} $\mathbb{A}_{n}$ and, to derive specific order estimates for $M(n)$, in order to analyze the location of the non-trivial zeros of the \textit{Riemann Zeta function} $\zeta(s)$. A priori using the above concepts, the article aims at establishing a necessary and sufficient condition for the \textit{Riemann Hypothesis} to hold true.

The communication space allows for the exchange of information and ensures the movement of material flows and passenger flows. By communication space, we mean the movement of information and material flows of various natures based on transport systems, in this case, air transport systems. The direction and intensity of these flows to varying degrees reflect the main social and economic processes. Time series reflecting the intensity of passenger flows and cargo transportation over a given time horizon were selected as a source of information used for analysis. An information-theoretical measure based on the assessment of entropy transfer between time series elements is used as a research tool. Based on the obtained paired estimates of entropy transfer between the selected time series, an entropy transfer matrix is formed, which allows considering a set of time series as a communication system within the framework of system analysis. The resulting matrices are used to form entropy transfer graphs, which allow investigating the properties of time series based on directed graph analysis methods. The article examines examples of the analysis of the cognitive model of transportation, the analysis of the regional communication space, and the analysis of changes in the global communication field.

Modules composed of a resistance gene flanked by Xer site-specific recombination sites, the vast majority of which were found in Acinetobacter baumannii, are thought to behave as elements that facilitate horizontal dissemination. The A. baumannii xerC and xerD genes were cloned, and the recombinant clones used to complement the cognate Escherichia coli mutants. The complemented strains supported resolution of plasmid dimers, and, as is the case with E. coli and Klebsiella pneumoniae plasmids, the activity was enhanced when cells were growing in low osmolarity growth medium. Binding experiments showed that partially purified A. baumannii XerC and XerD proteins (XerC_Ab and XerD_Ab) bound synthetic Xer site-specific recombination sites, some of them with a nucleotide sequence deduced from existing A. baumannii plasmids. Incubation with suicide substrates resulted in covalent attachment of DNA to a recombinase, probably XerC_Ab, indicating that the first step in the recombination reaction took place. The results described show that XerC_Ab and XerD_Ab are functional proteins and support the hypothesis that they participate in horizontal dissemination of resistant genes among bacteria.

Surface initiated atom transfer radical polymerization (SI-ATRP) is one of the most versatile technique to modify the surface properties of material. Recent developed metal free SI-ATRP makes such technique more widely applicable. Herein photo-induced metal-free SI-ATRP of methacrylates, such as methyl methacrylate, N-isopropanyl acrylamide, and N,N- dimethylaminoethyl methacrylate, on the surface of SBA-15 was reported to fabricate organic-inorganic hybrid materials. SBA-15 based polymeric composite with adjustable graft ratio was obtained. The structure evolution during the SI-ATRP modification of SBA-15 was monitored and verified by FT-IR, XPS, TGA, BET, and TEM. The obtained polymeric composite showed enhanced adsorption ability for the model compound toluene in aqueous. This procedure provides a low cost, ready availability, and facile modification way to synthesize the polymeric composites without the contamination of metal.

Information geometry is a mathematical framework that analyses the structure of statistical models using concepts from differential geometry. It treats families of probability distributions as manifolds, where the parameters of each model determine the coordinate charts. By applying info-geometric tools, we can gain insights into the characteristics of these models. The approach involves characterizing the queueing system's manifold using information geometry and presenting the exponential of the information matrix. This integration of information geometry with queueing theory provides a novel perspective for analyzing the dynamics of queueing systems, incorporating relativistic and Riemannian concepts. Some applications to E-health are highlighted. Finally, closing remarks and the next phase of research.

The paper presents the results of experiments on measuring cross sections for the neutron transfer channels 9Be(3He,α)8Begs,3.03 in the reaction of the 3He (30 MeV) ions with the 9Be target. To describe the angular distributions, we use the Distorted Wave Born Approximation (DWBA) method (FRESCO code). The results of the theoretical analysis are in agreement with the experimental data. In addition, we perform calculations based on the solution of the time-dependent Schrödinger equation (TDSE) for the weakly bound neutron of the 9Be nucleus. The TDSE approach allows us to determine the dynamics of the neutron transfer process and calculate the probabilities for the transfer and removal of the neutron of the 9Be nucleus in the 3He+9Be reaction.

Generic text embeddings have demonstrated considerable success across a multitude of applications. However, these embeddings are typically derived by modeling the co-occurrence patterns within text-only corpora, which can limit their ability to generalize effectively across diverse contexts. In this study, we investigate methodologies that incorporate visual information into textual representations to overcome these limitations. Through extensive ablation studies, we introduce a novel and straightforward architecture named VisualText Fusion Network (VTFN). This architecture not only surpasses existing multimodal approaches on a range of well-established benchmark datasets but also achieves state-of-the-art performance on image-related textual datasets while utilizing significantly less training data. Our findings underscore the potential of integrating visual modalities to substantially enhance the robustness and applicability of text embeddings, paving the way for more nuanced and contextually rich semantic representations.

The parallel connection of multiple flexible rings in raceways can significantly improve the electrical conductivity of rolling conductive devices. Multiple flexible rings are generally separated by idlers to form ring-idler rolling pairs. In the present work, alumina (Al2O3), polytetrafluoroethylene (PTFE), polyether ether ketone (PEEK), and polyimide (PI) were used as idler materials. Rolling tests for four types of ring-idler contact pairs were carried out in the air at a rotating speed of 10 rpm and a current of 60 A. It was noticed that the voltage drop was the lowest when Al2O3 was incorporated as the idler material. The energy spectrum analysis indicated material transfer between the organic idlers and the flexible ring. Especially on the flexible ring surface, the transferred organic thin film covered the gold-plated layer of the flexible ring and affected the electrical contact of the flexible ring. The transfer of Al2O3 was not obvious, and the mass fraction of Au on the flexible ring surface after the rolling test was 93.1%. The above results could help in selecting the best idler material for high-power conductive rotary joints.

China has enacted a range of policies to improve its water ecosystem since the middle of the 20th Century. Some of these measures include the creation of Seven River Conservancy Commissions, the development (combination and recombination) of series of ministries and departments to address environmental pollution and degradation, and recently the implementation of the river chief system. To understand if the river chief system can transfer to other political jurisdictions the authors gathered data using key word searches of the Web of Science and Google Scholar, official government sites, media sites and key international organizations. Based on this the authors review the development of the river chief system in the context of broader ecological reforms, place the rise of the river chief in the context of potential lessons for future improvement, and speculate on the possibility that China could transfer the river chief to countries facing similar challenges in their water governance regimes.

Aging has been increasingly recognized as a global health burden. Current aging research suggests that preventative strategies may increase both lifespan and healthspan. Many natural compounds or natural products have demonstrated promising antiaging benefits and gained popularity in aging research. The present study evaluated two compositions comprised of nicotinamide mononucleotide, quercetin, alpha ketoglutarate, white button mushroom extract (standardized to spermidine), Transfer Factor (extracts from cow colostrum and chicken egg yolk) with or without milk thistle fruit extract (standardized to silybin) and apigenin for their antiaging effect in Caenorhabditis elegans. The active ingredients included in the two compositions were screened for their senolytic effects on cell viability of irradiated human umbilical vein endothelial cells. To further explore their potential molecular mechanisms of action, the two compositions were also tested for their binding activity to human sirtuin enzymes, and TF on natural killer cell activities in human peripheral blood mononuclear cells from both young and old donors. Both compositions significantly increased the lifespan and healthspan of C. elegans. Both compositions demonstrated significant dose-dependent inhibitory effect on several sirtuins. When treated with Transfer Factor, both younger and older human peripheral blood mononuclear cells bolstered natural killer cell activity. The present study suggested that these two compositions significantly improved both lifespan and healthspan of Caenorhabditis elegans likely by modulating sirtuin activity and rejuvenating senescent immune cells.

Companion cropping involves growing two or more species together, benefiting the conservation of natural resources and improving fertilization and nutrient cycling by balancing chemical and organic sources. Studies, as in the case of tree tomato and Hass avocado, have shown a significant increase in yield compared to monocultures, highlighting the viability of this practice. In addition to their environmental benefit, companion crops offer economic advantages to producers by obtaining multiple products in a single harvest, strengthening food security and the economy of rural families. This study evaluated three levels of fertilization and interactions between fruit trees at different altitudes, observing differential behavior in the variables evaluated. The combination of cape gooseberry and blackberry showed significantly positive results, with more leaves and fewer pests, demonstrating the benefits of companion plants. A trend towards the combined use of chemical and organic fertilizers was observed, a potential strategy to reduce costs and improve crop growth. The results were shared with producers interested in implementing companion cropping, encouraging the adoption of this more sustainable and profitable agricultural practice. Companion crop agriculture represents a viable and promising strategy for a more efficient and sustainable agriculture, with both environmental and economic benefits.

Time-of-Flight (ToF) cameras are subject to high levels of noise and errors due to Multi-Path-Interference (MPI). To correct these errors, algorithms and neuronal networks require training data. However, the limited availability of real data has led to the use of physically simulated data, which often involves simplifications and computational constraints. The simulation of such sensors is an essential building block for hardware design and application development. Therefore, the simulation data must capture the major sensor characteristics. This work presents a learning-based approach that leverages high-quality laser scan data to generate realistic ToF camera data. The proposed method employs MCW-Net (Multi-Level Connection and Wide Regional Non-Local Block Network) for domain transfer, transforming laser scan data into the ToF camera domain. Different training variations are explored using a real-world dataset. Additionally, a noise model is introduced to compensate for the lack of noise in the initial step. The effectiveness of the method is evaluated on reference scenes to quantitatively compare to physically simulated data.

A novel approach is developed to improve the convergence of Physics-Informed Neural Networks (PINNs), aiming to employ them as real-time computational models within the framework of the digital twin for manufacturing processes. This method entails the weighting of physical equations, boundary conditions, and initial conditions to ensure their comparable magnitudes, with power being the chosen quantity in this study. The approach is applied to thermal problems, which are crucial for predicting manufacturing part defects. Different configurations, including complex boundary conditions and complex physics, were tested to assess the model’s robustness. The W-PINN demonstrates good predictions and strong stability compared to the classical PINN.

In this paper, we present a novel approach for text independent phone-to-audio alignment based on phoneme recognition, representation learning and knowledge transfer. Our method leverages a self-supervised model (wav2vec2) fine-tuned for phoneme recognition using a Connectionist Temporal Classification (CTC) loss, a dimension reduction model and a frame-level phoneme classifier trained thanks to forced-alignment labels (using Montreal Forced Aligner) to produce multi-lingual phonetic representations, thus requiring minimal additional training. We evaluate our model using synthetic native data from the TIMIT dataset and the SCRIBE dataset for American and British English, respectively. Our proposed model outperforms the state-of-the-art (charsiu) in statistical metrics and has applications in language learning and speech processing systems. We leave experiments on other languages for future work but the design of the system makes it easily adaptable to other languages.

Traditional image steganography conceals secret messages into unprocessed natural images by modifying the pixel value, causing the obtained stego different from the original image in terms of statistical distribution, thereby could be detected by a well-trained classifier for steganalysis. To ensure the steganography is imperceptible and in line with the trend of art images produced by Artificial Intelligence Generated Content (AIGC) becoming popular in social networks, this paper proposes to embed hidden information throughout the process of the generation of an art-style image by designing an image style transformation neural network with steganography function. The proposed scheme takes a content image, an art-style image, and messages to be embedded as inputs, processing them with an encoder-decoder model, and finally generates a styled image containing the secret messages at the same time. An adversarial training technique is applied to enhance the imperceptibility of the generated art-styled stego image with from plain style-transferred images. The lack of the original cover image makes it difficult for the opponent learning a steganalyzer to identify the stego. The recommended approach can successfully withstand existing steganalysis techniques and attain the embedding capacity of 3 bits per pixel for a color image, according to experimental results.

This paper proposes a position recognition method for the receiver coil by the secondary coil current. Based on the practical value of the current of the receiver coil, the position recognition of the receiver coil in the WPT system is realized. This paper proposes a 3×3 array multi-transmitter coil grouping and control logic. The mathematical model of mutual inductance between the receiver and transmitter coil at different positions on the X-Y plane is established. A method for identifying the position of the receiver coil according to the current of the receiver coil is proposed. Compared with the traditional position recognition method of the receiver coil, this method does not need to add a detection coil and position sensor and can realize the position recognition of the receiver coil on the 2D plane.

Registration of the flow pattern fine structure and the matter distribution of a free falling liquid drop in a target fluid at rest in the impact mode of coalescence, when the kinetic energy of the drop exceeds its available potential surface energy (APSE), was carried out by photo and video recording. The main attention was paid to the study of the flow structure at the initial stage of the cavity formation. To carry out color registration, the flow pattern was illuminated by several matrix LED and fiber optic sources of constant light. The planning of experiments and interpretation of the results were based on the properties of the complete solutions of the fundamental equations of fluid mechanics system, including the transfer and conversion of energy processes. Complete solutions of the system of equations describe large-scale flow components that are waves or vortices as well as thin jets (ligaments, filaments, fibers, trickles). In experiments, the jets are accelerated by the converted available potential surface energy (APSE) when the free surfaces of merging fluids were eliminated. The experiments were performed with the coalescence of water, solutions of alizarin ink, potassium permanganate, copper sulphate or iron sulphate drops in deep water. In all cases, at the initial contact, the drop begins to lose its continuity and breaks up into a thin veil and jets, the velocity of which exceeds the drop contact velocity. Small droplets, the size of which grows with time, are thrown into the air from spikes at the jet tops. On the surface of the liquid, the fine jets leave colored traces that form linear and reticular structures. Part of the jets penetrating through the bottom and wall of the cavity forms an intermediate covering layer. The forming layer jets are separated by interfaces of the target fluid. The processes of molecular diffusion equalize the density differences and form an intermediate layer with sharp boundaries in the target fluid. All noted structural features of the flow are also visualized when a fresh water drop isothermally spreads in the same tap water. The fast-changing and finely structured diffuse boundary of merging fluids, which at the initial stage has a complex and irregular shape, is gradually smoothed out by molecular diffusion processes. The similar flow patterns were observed in all performed experiments, however the geometric features of the flow depend on the individual thermodynamic and kinetic parameters of the contacting fluids.

The shortage of precooling equipment in litchi producing regions could lead to a high loss rate, poor quality of litchis. It is urgent to develop a portable precooling device for litchi producing regions. In this study, a novel spray hydrocooler with thermal energy storage (TES) were designed, fabricated, and tested. A simple mathematical model of TES capacity, ice coil thermal resistance and refrigeration system was employed to determine hydrocooler parameters. Then designed the structure of the spray hydrocooler. Maximum charging test was implemented with full TES capacity and litchi spray hydrocooling experiments were carried out at different charging times, spray flow rate, and litchi load with one-third TES capacity. Results showed that: (1) the spray hydrocooler allows for the rapid and effective precooling of litchis; (2) the hydrocooler can precool 299 kg litchis with one-third TES storage, meet the precooling requirements; (3) the effective TES capacity achieved 1.25×108 J at the maximum TES capacity of the hydrocooler, while the energy efficiency ratio (EER) is 2; (4) the precooling capacity was maximum and the average power consumption was minimum when the litchi load was 23 kg and the spray flow rate was 30 L min-1. Longer charging time is the most important factor in increasing precooling capacity and reducing average power consumption.

This study aimed to assess prescription transfer and medicines collection through Wasfaty, an electronic prescription service recently introduced in Saudi Arabia. A link to a cross-sectional online questionnaire was sent to all students and staff at the University of Jeddah, targeting beneficiaries who received e-prescriptions at the University Medical Centre (n = 2067). The questionnaire comprised 20 items under the following sections; demographics, patient perceptions and satisfaction with the Wasfaty service, and the availability of medicines. Of the 217 questionnaires received, the majority were filled by females (n = 125, 57.6%). Most were satisfied with the initial registration process of Wasfaty (n = 183, 84.1%). However, almost one-third of the participants reported that they could not find the prescribed medicines (n = 64, 29.7%), and most of them had to look for another pharmacy to obtain their treatment (n = 138, 63.9%). Respondents voiced their displeasure owing to the lack of access to certain pharmaceuticals, including anti-hypertensives and antidiabetics. This pilot study identified some challenges relating to the use of the Wasfaty service. Further attention to these challenges is required from the service providers, and a large-scale national study is warranted.

This study utilised an ensemble of pre-trained networks and digital mammograms to develop a supplementary diagnostic tool for radiologists. Digital mammograms and their associated information were collected from the department of radiology and pathology, Hospital Universiti Sains Malaysia. Thirteen pre-trained networks were selected and explored in this study. ResNet101V2 and ResNet152 had the highest mean PR-AUC, MobileNetV3Small and ResNet152 had the highest mean precision, ResNet101 had the highest mean F1 score, and ResNet152 and ResNet152V2 had the highest mean Youden J index. Subsequently, three ensemble models were developed using the top three pre-trained networks based on PR-AUC, precision, and F1 score. The final ensemble model had a mean precision, F1 score, and Youden J index of 0.82, 0.68, and 0.12, respectively. Additionally, the final model demonstrated a balanced performance across mammographic density. In conclusion, this study exhibited the good performance of the ensemble transfer learning on digital mammograms for the purpose of breast cancer risk estimation. This model can be utilised as a supplementary diagnostic tool for radiologists, thus, reducing their workloads.

The underlying assumption of the discourse about technology transfer is that government intervention is legitimate. Little scholarship has examined whether this assumption is valid or not and on what basis. Legitimacy is an important construct in the context of public policy. Government intervention can only be sustained if the public views such action as legitimate. The creation and transfer of technologies to the private sector is an area where there is significant government intervention. This paper reconceptualizes political legitimacy in the context of technology transfer policy. The analysis illuminates several concerns and challenges regarding the traditional approach to understanding whether specific government interventions in technology transfer are legitimate. It subsequently applies social constructionism and the notion of morality tales to describe an alternative conceptualization of political legitimacy that integrates aspects of other frameworks. In doing so, it reimagines political legitimacy as less of an unattainable normative principle of limited practical value to policymakers and more of a descriptively understood social phenomenon that policymakers can apply while formulating not only technology transfer policy, but other kinds of public policy as well. The paper demonstrates that there is a broader basis for claims of political legitimacy for government intervention in technology transfer, there is likely a more expansive range of technology transfer problems with which the government can rightly concern itself as well as possible solutions that policymakers can justifiably consider for addressing those problems, and that the political consequences of potential overreach in technology transfer policy are likely minimal.

Machine learning methods have widely been applied to detect anomalies in machine and cutting tool behavior during lathe or milling. However, detecting anomalies in the workpiece itself did not get the same attention by researchers. That is why in this article, the authors present a pub-licly available multivariate time series dataset which was recorded during milling of 16MnCr5. Due to artificially introduced, though realistic anomalies in the workpiece the dataset can be ap-plied for anomaly detection. By using a convolutional autoencoder as a first model good results in detecting the location of the anomalies in the workpiece were achieved. Furthermore, milling tools with two different diameters where used which led to a dataset eligible for transfer learn-ing. The objective of this article is to provide researchers with a real-world time series dataset of the milling process which is suitable for modern machine learning research topics like anomaly detection and transfer learning.

Segmentation is an important step in medical imaging. In particular, machine learning, especially deep learning, has been widely used to efficiently improve and speed up the segmentation process in clinical practice. Despite the acceptable segmentation results of multi-stage models, little attention was paid to the use of deep learning algorithms for brain image segmentation, which could be due to the lack of training data. Therefore, in this paper, we propose a Generative Adversarial Network (GAN) model that performs transfer learning to segment MRI brain images.Our model enables the generation of more labeled brain images from existing labeled and unlabeled images. Our segmentation targets brain tissue images, including white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF). We evaluate the performance of our GAN model using a commonly used evaluation metric, which is Dice Coefficient (DC). Our experimental results reveal that our proposed model significantly improves segmentation results compared to the standard GAN model. We observe that our model is 2.1–10.83 minutes faster than stat-of-the-art-models.

Horizontal transfer of transposons (HTT) is an important source of genomic evolution in eukaryotes. The HTT dynamics is well characterized in eukaryotes including insects however, but there is a huge gap of knowledge about HTT regarding many eukaryotes’ species. In this study we analyzed the events of the HTT between Rhus gall aphids (Hemiptera) and other insects. We analyzed the Mariner-like transposable elements (MLEs) belongs to Rhus gall aphids for the possible HT events. The MLEs have patchy distribution and have high similarity over the entire length of element with insects MLEs from different orders. We selected representative sequences from the Rhus gall MLEs and identified five events of HT between MLEs of Rhus gall aphids and other insects from five different orders. We also found multiple HTT events among the MLEs of insects from the five orders which demonstrate that these Mariner elements have been involved in recurrent HT between these six order of insects. Our current study closed the knowledge gap of HTT and reported the events between Rhus gall aphids and other insects for the first time. We believe that this study about HTT events will help to understand the evolution and spread of transposable elements in the genomes of Rhus gall aphids.

COVID-19 has a severe risk of spreading rapidly, the quick identification of which is essential. In this regard, chest radiology images have proven to be a practical screening approach for COVID-19 affected patients. This study proposes a deep learning-based approach using Densenet-121 to detect COVID-19 patients effectively. We have trained and tested our model on the COVIDx dataset and performed both 2-class and 3-class classification, achieving 96.49% and 93.71% accuracy, respectively. By successfully utilizing transfer learning, we achieve comparable performance to the state-of-the-art method while using 15x fewer model parameters. Moreover, we performed an interpretability analysis using Grad-CAM to highlight the most significant image regions at test time. Finally, we developed a website that takes chest radiology images as input and detects the presence of COVID-19 or pneumonia and a heatmap highlighting the infected regions. Source code for reproducing results and model weights are available.

There is a crucial need for advancement in the online educational system due to the unexpected, forced migration of classroom activities to a fully remote format, due to the coronavirus pandemic. Not only this, but online education is the future, and its infrastructure needs to be improved for an effective teaching-learning process. One of the major concerns with the current video call-based online classroom system is student engagement analysis. Teachers are often concerned about whether the students can perceive the teachings in a novel format. Such analysis was involuntarily done in the offline mode, however, is difficult in an online environment. This research presents an autonomous system for analyzing the students' engagement in the class by detecting the emotions exhibited by the students. This is done by capturing the video feed of the students and passing the detected faces to an emotion detection mode. The emotion detection model in the proposed architecture was designed by finetuning VGG16 pre-trained image classifier model. Lastly, the average student engagement index is calculated. We received considerable performance setting reliability of the use of the proposed system in real-time giving a future scope to this research.

Semantically meaningless strings that are associated with affective attributes (US) can become emotionally valenced CS. Jurchiș et al (2020) recently demonstrated CS-US associations may influence evaluations towards previously-unseen letter strings if the latter share grammar construction rules with CS. We replicated those authors' findings in a modified extension (Experiment 1; N₁ = 108), where happy/angry faces (US) were differentially associated with letter strings (CS) constructed using familiar (English) or non-familiar (Phoenician) alphabets. CS-US sequences were sandwiched by evaluations of strings that never appeared as CS, but shared grammar construction rules. However, post-hoc tests indicated valence effects were restricted to participants classified as 'high awareness' or those who had been exposed to longer stimulus durations, suggesting resource-intense deliberations were central during evaluations. Qualitative awareness checks additionally showcased many participants had attributed valences to recurring elements across conditioned and evaluated exemplars. These limitations were collectively addressed in Experiment 2 (N₂ = 140), where participants viewed Phoenician (/English) CS during conditioning but viewed English (/Phoenician) strings during evaluations, meaning no strings nor elements recurred between phases. We found credible valence effects across English and Phoenician strings, with the latter observed across all awareness categories. Because participants were unable to consciously specify any evaluative strategies while evaluating Phoenician strings, we speculate grammar construction rules (organizing relations) may have been non-consciously acquired during conditioning.

Artificial Intelligence (AI) has seen increased application and widespread adoption over the past decade despite, at times, offering a limited understanding of its inner working. AI algorithms are, in large part, built on weights, and these weights are calculated as a result of large matrix multiplications. Computationally intensive processes are typically harder to interpret. Explainable Artificial Intelligence (XAI) aims to solve this black box approach through the use of various techniques and tools. In this study, XAI techniques are applied to chronic wound classification. The proposed model classifies chronic wounds through the use of transfer learning and fully connected layers. Classified chronic wound images serve as input to the XAI model for an explanation. Interpretable results can help shed new perspectives to clinicians during the diagnostic phase. The proposed method successfully provides chronic wound classification and its associated explanation. This hybrid approach is shown to aid with the interpretation and understanding of AI decision-making processes.

Using machine learning or deep learning to solve the problem of garbage recognition and classification is an important application in computer vision, but due to the incomplete establishment of garbage datasets and the poor performance of complex network models on smart terminal devices, the existing garbage classification models The effect is not good.This paper presents a waste classification and identification method base on transfer learning and lightweight neural network. By migrating the lightweight neural network MobileNetV2 and rebuild it, The reconstructed network is used for feature extraction, and the extracted features are introduced into the SVM to realize the identification of 6 types of garbage. The model was trained and verified by using 2527 pieces of garbage labeled data in the TrashNet dataset, which ultimately resulted in a classification accuracy of 98.4% of the method, which proves that the method can effectively improve the classification accuracy and time and overcome the problem of weak data and less labeling. The over-fitting phenomenon encountered by small data sets in deep learning makes the model robust.

The organo-catalyzed enantioselective benzylation reaction of α-trifluoromethoxy indanones afforded α-benzyl-α-trifluoromethoxy indanones with a tetrasubstituted stereogenic carbon center in excellent yield with moderate enantioselectivity (up to 57% ee). Cinchona alkaloid-based chiral phase transfer catalysts were found to be effective for this transformation, and both enantiomers of α-benzyl-α-trifluoromethoxy indanones were accessed, depended on the use of cinchonidine and cinchonine-derived catalyst. The method was extended to the enantioselective allylation reaction of α-trifluoromethoxy indanones to give the allylation products in moderate yield with good enantioselectivity (up to 76% ee).

Microbial symbioses exhibit astounding adaptations, yet all symbionts face the problem of how to reliably associate with host offspring every generation. A common strategy is vertical transmission, in which symbionts are directly transmitted from the female to her offspring. The diversity of symbionts and vertical transmission mechanisms is as expansive as the diversity of eukaryotic host taxa that house them. However, there are several common themes among these mechanisms based on the degree to which symbionts associate with the host germline during transmission. In this review, we detail three distinct vertical transmission strategies, starting with associations that are transmitted from host somatic cells to offspring somatic cells, either due to lacking a germline or avoiding it. A second strategy involves somatically-localized symbionts that migrate into the germline during host development. The third strategy we discuss is one in which the symbiont maintains continuous association with the germline throughout development. Unexpectedly, the vast majority of documented vertically inherited symbionts rely on the second strategy: soma-to-germline migration. Given that not all eukaryotes contain a sequestered germline and instead produce offspring from somatic stem cell lineages, this soma-to-germline migration is discussed in the context of multicellular evolution. Lastly, as recent genomics data have revealed an abundance of horizontal gene transfer events from symbiotic and non-symbiotic bacteria to host genomes, we discuss their impact on eukaryotic host evolution.

Hetero-nanomaterials constructed by plasmonic metals and functional semiconductors show enormous potential in photocatalytic applications, such as water splitting, hydrogen production, CO₂ reduction, pollutants treatment. Their photocatalytic performances can be better regulated through adjusting structure, ingredient, and components arrangement. Therefore, the reasonable design and synthesis of metal/semiconductor hetero-nanostructures is of vital significance. In this article, we briefly review the recent progress in efficiently establishing metal/semiconductor nanomaterials for improved photocatalysis. The defined photocatalysts mainly include traditional binary hybrids, ternary multi-metals/semiconductor and metal/multi-semiconductors heterojunctions. The underlying physical mechanism for the improved photocatalytic activity of the established photocatalysts are highlighted. At the end of this article, a brief summary and possible future perspectives for further development in this field are demonstrated.

We apply the stochastic thermodynamics formalism to describe the dynamics of systems of complex Langevin and Fokker-Planck equations. We provide in particular a simple and general recipe to calculate thermodynamical currents, dissipated and propagating heat for networks of nonlinear oscillators. By using the Hodge decomposition of thermodynamical forces and fluxes, we derive a formula for entropy production that generalises the notion of non-potential forces and makes transparent the breaking of detailed balance and of time reversal symmetry for states arbitrarily far from equilibrium. Our formalism is then applied to describe the off-equilibrium thermodynamics of a few examples, notably a continuum ferromagnet, a network of classical spin-oscillators and the Frenkel-Kontorova model of nano friction.

The future power equipment tends to take hydrogen or middle/low heat-value syngas as fuel for low emission. The heat transfer of film cooled turbine blade shall be influenced more by radiation. Its characteristic of conjugate heat transfer is studied experimentally and numerically in the paper by considering radiation heat transfer, multi-composition gas and TBC. The Weighted Sum of Gray Gases spectral model and Discrete Transfer Model are utilized to solve the radiative heat transfer in the multi-composition field, while validated against the experimental data for the studied cases. It is shown that the plate temperature increases significantly when considering the radiation and the temperature gradient of the film cooled plate becomes larger. It is also shown that increasing percentage of steam in gas composition results in increased temperature on the film-cooled plate. The normalized temperature of the film-cooled plate decreases about 0.02, as the total percentage of steam in hot gas increases per 7%. As for the TBC effect, it can smooth out the the temperature distribution and insulate the heat to a greater extent when the radiative heat transfer becomes significant.

A membrane ozonation contactor was built to investigate ozonation using tubular membranes and to inform computational fluid dynamics (CFD) studies. Non-porous tubular polydimethylsiloxane (PDMS) membranes of 1.0 – 3.2 mm inner diameter were tested at ozone gas concentrations of 110 – 200 g m−3 and liquid side velocities of 0.002 m s−1 – 0.226 m s−1. The dissolved ozone concentration could be adjusted to up to 14 mg O3 L−1 and increased with decreasing membrane diameter and liquid side velocity. Experimental mass transfer coefficients and molar fluxes of ozone were 1.1∙10−5 mol m−2 s−1 and 2.4∙10−6 m s−1, respectively, for the smallest membrane. CFD modelling could predict the final ozone concentrations but slightly overestimated mass transfer coefficients and molar fluxes of ozone. Model contaminant degradation experiments and UV absorption measurements of ozonated water samples in both ozone (O3) and peroxone (H2O2/O3) reaction systems in pure water, river water, wastewater effluent and solutions containing humic acid show that the contactor system can be used to generate information on the reactivity of ozone with different water matrices. Combining simple membrane contactors with CFD allows predicting ozonation performance under a variety of conditions leading to improved bubble-less ozone systems for water treatment.

In order to solve the problems of waveform distortion and signal delay by many physical and electrical systems with linear low-pass transfer characteristics with multiple complex poles, a general digital-signal-processing (DSP)-based method of real-time recovery of the original source waveform from the distorted output waveform is proposed. From the convolution kernel representation of a multiple-pole low-pass transfer function with an arbitrary denominator polynomial with real valued coefficients, it is shown that the source waveform can be accurately recovered in real time using a particular moving average algorithm with real-valued DSP computations only, even though some or all of the poles are complex. The proposed digital signal recovery method is DC-accurate and unaffected by initial conditions, transient signals, and resonant amplitude enhancement. This method can be applied to most sensors and amplifiers operating close to their frequency response limits or around their resonance frequencies to accurately deconvolute the multiple-pole characteristics and to improve the overall performances of data acquisition systems and digital feedback control systems.

Current education in biology is devoid of mathematics in many countries, probably because many relevant biological processes are explained from a qualitative point of view rather than addressing the quantitative aspects of these phenomena. Here, we employ a case study from the yeast physiology to illustrate the importance of numeracy skills for a deeper understanding of relevant biological problems. Yeast anaerobic growth on sugars is a widespread process as it is the basis for beer, bread, and winemaking and it is much akin to lactic acid fermentation in muscle cells in response to an increased energy demand. To study the physiology of yeasts under controlled conditions and being able to compare the results quantitatively, one ought to perform measurements and calculations involving concentrations of oxygen, biomass, and organic compounds. To set-up an “anaerobic” culture of Saccharomyces cerevisiae in a defined medium, one needs to calculate how much oxygen must enter the cultivation system, to meet the requirements for ergosterol and oleic acid biosyntheses, both of which require oxygen. Using basic physicochemical principles and simple mathematical skills, students will be able to compute the oxygen requirement for yeast growth under such “anaerobic” conditions.

The poor impact resistance of carbon fiber reinforced composites limits their application in broader fields. In this study, a toughened epoxy resin (E2) modified with toughening agents and a micron-sized toughening particle (TP) were developed. Standard epoxy resin (E1), toughened epoxy resin (E2), and TP-toughened E2 resin (E3) were prepared into prepregs with SYT55-12K carbon fiber and ultimately fabricated into carbon fiber reinforced composites. The mechanical properties of the resins and the composites, particularly the compression properties, were characterized. The failure morphology of the composites and the distribution of toughening particles were observed using scanning electron microscopy (SEM), ultrasonic C-scan testing, and metallographic microscopy. It was found that the toughening agents improved the bending strength of the resin by approximately 12%, while the incorporation of TP enhanced the impact performance of the resin by 122%. Further characterization of the mechanical properties of the carbon fiber reinforced composites revealed that, with the addition of toughening agents, the resin increased the 0° bending strength of the composites by 29.9% and the 0° compressive strength by 34.3%. Additionally, significant enhancements were observed in interlaminar shear strength and open-hole compressive strength. After the addition of TP, the compressive strength of EC3 compared to EC2 increased by 74.3% after impact, while the mode I interlaminar fracture toughness increased by 34.8% and the mode II interlaminar fracture toughness improved by 67.9%. C-scan analysis indicated that the damage area of EC3 decreased by 60.7% compared to EC2, demonstrating that the particle toughening significantly enhanced the impact resistance of the composites. The compression failure of the TP-toughened EC3 exhibited typical characteristics of kink band failure, and the micron-sized particles were able to significantly balance and absorb loads. The findings of this study indicate that resin toughening can significantly improve the 0° compressive strength of carbon fiber reinforced composites, and that the use of micron-sized toughening particles can markedly enhance the post-impact compressive strength of the composites through interlaminar toughening. This research provides insights for improving the compressive and impact resistance performance of carbon fiber reinforced composites, with implications for industrial application and guidance for further industrialization trials.

Premature skin aging, also known as photoaging, refers to the changes of the structure and function of the skin caused by chronic sun exposure. The ultraviolet radiation in the sunlight is one of the key factors that causes photoaging. Thus, MMPs, TGFB1, and NF-κB signaling can be an effective therapeutic strategy for UVB exposure. In this study, we used human dermal fibroblast and mouse macrophage cells to identify the mediators of skin photoaging. Quercitrin isolated from ‘Green Ball’ apple peel was treated to UVB-irradiated fibroblast cell and lipopolysaccharide (LPS)-induced macrophages to identify photoaging prevention effect of quercitrin. Genes that are associated with photoaging was determined by using ELISA, western blot, and qPCR. Quercitrin increased collagen biosynthesis in UVB-irradiated fibroblast cell via regulating MMPs, TIMP-1, TGFB1, HAS2, and COL1A2. In addition, quercitrin regulated p-65, iNOS, COX-2, and mediators (PGE2 and NO), in the NF-κB signaling process, and inhibited the production of cytokines in LPS-induced macrophages. These results indicates that quercitrin can improve photoaging damaged skin by regulating MMPs, TGFβ, and NF-κB signaling pathway modulators.

Chronic wounds are a major health problem because of delayed healing and cause hardships for the patient. The infection present in these wounds plays a role in delayed wound healing. Silver wound dressings have been used for decades, beginning in the 1960s with silver sulfadiazine for infection prevention for burn wounds. Since that time, there has been a large number of commercial silver dressings that have cleared FDA approval. In this review, we examine the literature involving in vitro, in vivo, and clinical studies with commercial silver dressings and attempt to glean the important characteristics of these dressings in treating infected wounds. The primary presentation of the literature is in the form of detailed tables. The narrative part of the review focuses on the different types of silver dressings, including the supporting matrix, the release characteristics of the silver into the surroundings, and their toxicity. Though there are many clinical studies of chronic and burn wounds using silver dressings that we discuss, it is difficult to compare the performances of the dressings directly because of the differences in the study protocols. We conclude that silver dressings can assist in wound healing, though it is difficult to provide general treatment guidelines.

Vitronectin is a glycoprotein, present in plasma and extracellular matrix, implicated in cell migration. The high amount of vitronectin found in neuroblastoma biopsies was associated with poor prognosis. However, there are almost no studies of vitronectin levels in neuroblastoma cell culture media nor in plasma of neuroblastoma patients. Vitronectin concentration in culture media of four neuroblastoma cell lines grown in monolayer and in 3D-models, and in plasma of 114 neuroblastoma patients, was quantified using ELISA. Three of the neuroblastoma cell lines secreted vitronectin to culture media when cultured in monolayer and 3D-models. Vitronectin release was higher by neuroblastoma cells cultured in 3D-models than in monolayer, and was still great when cells grown in 3D-scaffolds with cross-linked vitronectin. Vitronectin secretion occurred independently of cell numbers in cultures. Its concentration in plasma of neuroblastoma patients ranged between 52.4 and 870µg/mL (median, 218µg/mL). A ROC curve was used to establish a cutoff of 361µg/mL, above which patients over 18-months-old had worse prognosis (p=0.0018). Vitronectin could be considered a new plasma prognostic biomarker in neuroblastoma, and warrants confirmation in collaborative studies. Drugs inhibiting vitronectin interaction with cells and/or extracellular matrix could represent a significant improvement in survival for neuroblastoma patients.

Polymeric composites are prone to undergo damage, such as microcracks, during their operation, that can ultimately lead to catastrophic failure. To contradict such problem, effort has been put, by the scientific community, towards developing self-healing composites that, by mimicking biological systems, can autonomously and prematurely repair flaws, extending durability and improving security of materials. The present review explores the progress being made in such area, focusing on extrinsic self-healing methods, considering that they can be employed to a variety of materials. Reservoir-based techniques, that resort to capsules, hollow fibers or microvascular networks, and thermoplastic-based ones are overviewed, prioritizing innovative approaches made in recent years. At last, promising practical applications for self-healing composites are highlighted and future challenges and opportunities are pointed out.

Wound healing is a complex, dynamic process involving the coordinated interaction of diverse cell types, growth factors, cytokines, and extracellular matrix components. Despite emerging evidence highlighting their importance, dermal sheath cells remain a largely overlooked aspect of wound healing research. This review explores the multifunctional roles of dermal sheath cells in various phases of wound healing, including modulating inflammation, aiding in proliferation, and contributing to extracellular matrix remodeling. Special attention is devoted to the paracrine effects of dermal sheath cells and their role in fibrosis, highlighting their potential in improving healing outcomes, especially in differentiating between hairy and non-hairy skin sites. By drawing connections between dermal sheath cells activity and wound healing outcomes, this work proposes new insights into the mechanisms of tissue regeneration and repair, marking a step forward in our understanding of wound healing processes.

Several types of guided bone regeneration materials are available with various properties and clinical indications. Among them, dentin-derived matrix from extracted teeth is an excellent alternative to traditional graft materials, such as allografts and xenografts. Different clinical preparation protocols exist: block form versus powder form, demineralized versus non-demineralized form. Out of these methods, demineralization protocols for dentin-derived matrix from extracted teeth have been noted for a wide range of successful clinical outcomes. The purpose of this animal study was to find out the most effective method of demineralizing dentin-derived matrix to result in the highest regenerative ability in the bone graft material in rabbit calvaria. The study conducted a comparative histomorphometric analysis of four groups in distinguished matrix conditions: a control group without graft placement, a non-demineralized dentin-derived matrix graft placement group, a 15-minute demineralized dentin-derived matrix graft placement group, and a 30-minute demineralized dentin-derived matrix graft placement group. Regenerative processes were evaluated three times at 2, 4, and 8 weeks post-graft placement. These groups of rabbits were evaluated randomly in a blinded setting to prevent bias. Among the four groups compared, the group with a 15-minute demineralized dentin-derived matrix graft showed the most efficient bone regeneration in the histomorphometric analysis. Based on this animal study, it was apparent that a 15-minute demineralization of dentin-derived matrix is the preferred preparation protocol to maximize the regenerative potential in the matrix.

For some persistent pollutants, such as recalcitrant pesticides, the polluted water (urban, agricultural and/or industrial) treated by conventional wastewater treatment plants is in some cases insufficient to achieve the legally required level of purity. This issue is of particular concern in areas where low rainfall does not provide sufficient water resources to meet the needs of agriculture, requiring increased reuse of water from wastewater treatment plants. In this context, Advanced Oxidation Processes (AOPs) hold great promise for the removal of organic pollutants. This study first evaluates the effectiveness of UV/S2O8= compared to heterogeneous photocatalysis using UV/TiO2 processes on the degradation of two commonly used herbicides (terbutylazine and isoproturon) in aqueous solutions using a photoreactor. In addition. the effect of UV wavelength on the degradation efficiency of both herbicides was investigated. Although degradation rate was higher under UV-254/S2O8= nm than under UV-365/S2O8= nm, complete degradation of the herbicides (0.2 mg L-1) was achieved within 30 min under UV-366 nm using a Na2S2O8 dosage of 250 mg L-1 in the absence of inorganic anions. To assess the impact of water matrix, the individual and combined effects of sulphate, bicarbonate and chloride were evaluated. They can react with hydroxyl and sulphate radicals formed during AOPs to form new radicals with a lower redox potential. The results showed negligible effects of sulphate, while the combination of bicarbonate and chloride seemed to be the key for the decrease in herbicide removal efficiency found when working with complex matrices. Finally, the main intermediates detected during the photodegradation process were identified and the likely pathways are proposed and discussed.

In this paper, we establish the necessary and sufficient conditions for solving a dual split quaternion matrix equation AXB=C, and present the general solution expression when solvability is achieved. As an application, we delve into the necessary and sufficient condition for the existence of Hermitian solution to this equation by using a newly defined real representation method. Furthermore, we obtain the solutions for the dual split quaternion matrix equations AX=C and XB=C. Finally, we provide a numerical example to demonstrate the findings of this paper.

Thin people who undergo implant insertion into the chest wall face a high risk of implant exposure to the external environment. Five months after an 8-year-old boy underwent implantable cardioverter-defibrillator (ICD) implantation in a subcutaneous pocket in the left anterolateral chest wall to manage long QT syndrome, ICD replacement became necessary owing to exposure risk from distal and lateral thinning of the ICD pocket. Pocket rupture and exposure would increase the risk of infection; therefore, we performed ICD removal and primary pocket closure. Two weeks later, a new suprafascial pocket was created, acellular dermal matrix (ADM) was attached to the inner wall to prevent ICD protrusion, and a new ICD was inserted. One year postoperatively, the ADM was engrafted, and no complications were observed. A thin subcutaneous layer increases the risk of ICD implantation complications. Inner wall strengthening with ADM can help prevent pocket rupture.

This investigation mainly focused on the microstructural analysis of Al based hybrid metal matrix composites. Aluminium as base metal and reinforced with 2% B4 C, ZrO2 (2%,4%,6%), SiC (4%,8%,12%). Specimens were manufactured by using conventional stir casting technique. Hybrid metal matrix composites were examined by using Scanning electron microscope. This research explained XRD, EDS and Fractography analysis. This investigation shows the reinforced material has given better results in all aspects than pure Al6061 alloy and homogeneous dispersion of particles inside the matrix. Porosity, delamination, cracks, particle distributions were observed through microstructural analysis. Additionally determined the crystal size of pure Aluminium 6061 alloy and hybrid composites.

This work proposes a physics-based identification technique based on genetic algorithms. The main objective is to obtain a parametric matrix A that describes the time-invariant linear model of the longitudinal dynamics of an aircraft. This is achieved by proposing a fitness function based on the properties of the transition matrix and taking advantage of some of the capabilities of the genetic algorithm, mainly those of restricting the search ranges of the unknowns. In this case, such unknowns are related to the type of aircraft and flight conditions that are considered during the identification process. The proposed identification method is validated with a reliable nonlinear model that can be found in the literature, as well as with the calculation of the trim condition and linearization generally used in aircraft dynamics. In summary, this study suggests the genetic algorithm provided with the adequate fitness function, could be an appealing alternative for aircraft model identification, even when only a limited amount of data is available. Furthermore, in some cases, linearization using genetic algorithm can be more efficient than classical methods.

This article shows how to establish expansion formulas for calculating the mixed operations $(A^{\dag})^{\#}$, $(A^{\#})^{\dag}$, $((A^{\dag})^{\#})^{\dag}$, $((A^{\#})^{\dag})^{\#}$, $\ldots$ of generalized inverses, where $(\cdot)^{\dag}$ denotes the Moore--Penrose inverse of a matrix and $(\cdot)^{\#}$ denotes the group inverse of a square matrix. As applications of the formulas obtained, the author constructs and classifies some groups of matrix equalities involving the above mixed operations, and derives necessary and sufficient conditions for them to hold.

Cerebral palsy (CP) is the most common movement disorder in children with a prevalence rang-ing from 1.5 to 4 per 1000 live births. CP is caused by a non-progressive lesion of the developing brain, leading to progressive alterations of the musculoskeletal system, including spasticity, often leading to the development of fixed contractures, necessitating tendon lengthening surgery. Total RNA-sequencing analysis was performed on semitendinosus tendons from diplegic and tetraple-gic CP patients subjected to tendon lengthening surgery compared to control patients undergoing anterior cruciate ligament reconstructive surgery. Tetraplegic CP patients showed increased ex-pression of genes implicated in collagen synthesis and extracellular matrix (ECM) turnover, while only minor changes were observed in diplegic CP patients. In addition, tendons from tetra-plegic CP patients showed an enrichment for upregulated genes involved in vesicle-mediated transport and downregulated genes involved in cytokine and apoptotic signaling. Overall, our results indicate increased ECM turnover with increased net synthesis of collagen in tetraplegic CP patients without activation of inflammatory and apoptotic pathways similar to observations in athletes where ECM remodeling results in increased tendon stiffness and tensile strength. Never-theless, the resulting increased tendon stiffness is an important issue in clinical practice, where surgery is often required to restore joint mobility.

In this study we assessed the electrical and optical behavior of semiconductor hybrid films fabricate from octaethyl-21H,23H-porphine copper (CuP), embedded in polymethylmethacrylate (PMMA), and polystyrene (PS). The hybrid films were characterized structurally and morphologically by means of Infrared spectroscopy (IR), atomic force microscopy (AFM), scanning electron microscopy (SEM) and X-ray diffraction (XRD). Subsequently, the PMMA:CuP and PS:CuP hybrid films were evaluated optically by UV-vis spectroscopy, as well as electrically, with the four-point collinear method. Hybrid films present a homogeneous and low roughness morphology, besides; the PS matrix allows the crystallization of the porphin, while the PMMA promotes the amorphous structure in CuP. The polymeric matrix also has an effect on the optical behavior of the films, since the smallest optical gap (2.16 eV) and onset gap (1.89 eV) and the highest transparency are obtained in the film with a PMMA matrix. Finally, the electrical behavior in hybrid films is also affected by the matrix: the largest amount of current carried is around 0.01 A for PS:CuP film, while for PMMA:CuP film it is 0.0015 A. Thanks to the above properties, hybrid films are promising candidates for use in optoelectronic devices.

Nonnegative matrix factorization (NMF) has been shown to be a strong data representation technique, with applications in text mining, pattern recognition, image processing, clustering and other fields. In this paper, we propose a hypergraph regularized Lp smooth nonnegative matrix factorization (HGSNMF), by incorporating hypergraph regularization and Lp smoothing constraint terms into the standard NMF. The hypergraph regularization term can capture the intrinsic geometry structure of the high dimension space data more comprehensively than simple graph, the Lp smoothing constraint may yield a smooth and more accurate solution to the optimization problem. The updating rules are given using multiplicative update techniques, and the convergence of HGSNMF is theoretically investigated. The experimental results on four different data sets show that the proposed method has better clustering effect than the related state-of-the-art methods in the vast majority of cases.

Through the arrow decomposition of the Mueller matrix, respective sets of sixteen independent polarimetric images of biological tissues are obtained for enpolarizing, retarding and depolariz-ing descriptors. In addition to the mean intensity coefficient and the three indices of polarimetric purity, the absolute values and Poincaré orientations of diattenuation, polarizance, entrance re-tardance and exit retardance vectors are considered. In this work we use for the first time this set of polarimetric observables for the visualization of biological structures, both of animal and vege-tal origin. Results show images with enhanced visualization derived from the spatial variation of such significant polarimetric properties. The experimental results are discussed, showing the suit-ability of such set of observables for applications in biophotonics imaging, providing not only ex-cellent visualization of biological tissues, but also showing structures not visible in non-polarimetric images.

The use of tungsten fiber-reinforced tungsten composites (Wf/W) has been demonstrated to significantly enhance the mechanical properties of tungsten (W) by incorporating W-fibers into the W-matrix. However, prior research has been restricted by the usage of single fiber-based textile fabrics, consisting of 150 µm warp and 50 µm weft filaments, with limited homogeneity, reproducibility, and mechanical properties in bulk structures due to the rigidity of the 150 µm fibers. To overcome this limitation, two novel textile preforms were developed utilizing radial braided yarns with 7 core- and 16 sleeve filaments (R.B. 16+7) as the warp material. In this study, bulk composites of two different fabric types were produced via a layer-by-layer CVD-process, utilizing single 50 µm filaments (type 1) and R.B. 16+7 yarns (type 2) as weft materials. The produced composites were sectioned into KLST-type specimen based on DIN EN ISO 179-1:2000 using electrical discharge machining (EDM), and subjected to three-point bending tests. Both composites demonstrated enhanced mechanical properties with pseudo-ductile behavior at room temperature and endured over 10,000 load cycles between 50-90 % of their respective maximum load without sample fracture. Composites based on fabric type 1 demonstrated superior manufacturing performance and mechanical properties, a high relative average density (>97 %), and high fiber volume fraction (14-17 %). Furthermore, a novel approach to predict the fatigue behavior of the material under cyclic loading was developed based on the high reproducibility of the mechanical properties of type 1, providing a new benchmark for upscaling endeavors.

Fibreglass composite plates are used for applications ranging from aerospace and automotive industries to construction industry. Vibroacoustic properties of the fibreglass plate has been investigated for different boundary conditions. The theory of the plate vibration and sound radiation has been used to determine the deflection of the composite plate at different locations on its surface. 3-Dimentional (3D) deformations and their corresponding contour velocities of plate have been computed for a range of frequencies. It has been shown that clamping the plate at four edges delayed first resonance of the plate by 15 Hz and second resonance of the plate by 30 Hz. Vibroacoustic indicators and the radiation impedance matrix of the plate have also been calculated. The results of this study show that fibreglass plate could be used in building industry to dampen the vibration of machine and structural vibration of buildings, and to sandwich building structures to form panels in order to attenuate airborne sound and to lower noise transmission of structural borne sound

In the era of big data with increasingly complex data structures and ever-larger data scales, matrix-type data are becoming highly valued and their applications in the fields of medicine, industry, education, geography, and astronomy are growing in extent. In recent years, significant progress has been made in the practical use of matrix variable t-distribution finite mixture models for handling data in order to address the issues of multi-subgroup structures and long data tails. In this paper, the expectation-maximization (EM) algorithm with penalized maximum likelihood is proposed to resolve the problem of the unbounded nature of the likelihood function applied to the model by considering the degeneracy of the variance-covariance matrix of this model. Our data were analyzed through simulations and real data, and the results demonstrate that our model is effective in both preventing the likelihood function from being unbounded and in ensuring the accuracy of the estimated parameters of the EM algorithm.

This study investigated and classified typical structures in rural village and analyzed the vulnerability of various typical types of structures. Based on the statistics of earthquake damages with magnitudes above 5 from 1996 to 2013 in China, the damage matrixes of different types of structures in rural village are obtained. And The vulnerability index and the vulnerability equation of structure are crucial to assess the earthquake losses of typical structures under different magnitudes earthquakes. According to the seismic loss of different types of structures under different earthquake magnitudes, there are possible to improve the seismic resilience of the buildings in rural village. Moreover, the regional vulnerability is analyzed by β probability distribution function, and the comprehensive seismic performance index of different types of agricultural buildings in the region is obtained. The main research is to predict the loss of different types of structures under different earthquake magnitudes in the future, and to provide technical support for different types of building in rural village reinforcement.

Various studies have addressed the role of neutrophils in cancer wherein the focus has been drawn on the elevated neutrophil count in blood or at tumor loci. However, cancer has a systemic impact which targets various organs thus challenging the overall physiology of the host. So, it is worthwhile to explore whether and how neutrophils contribute to systemic deterioration in cancer. To discern the systemic role of neutrophils, we monitored their number and function at different stages of tumor growth in Dalton’s lymphoma mice model. Notably, we observed a gradual increase in neutrophil count in blood and their infiltration in vital organs of tumor bearing mice. In parallel, we observed damaged histoarchitecture with significant alterations in biochemical parameters that aggravated with tumor progression. We next examined systemic impact of neutrophil by assessing neutrophil elastase, myeloperoxidase, and matrix metalloproteinases (MMP-8 and MMP-9) wherein we found their upregulated expression and activity in tumor condition. Taken together, our results demonstrate high infiltration and hyperactivation of neutrophils which possibly account for gradual systemic deterioration during cancer progression. Our findings thus implicate neutrophils as a potential therapeutic target that may help to reduce the overall fatality rate of cancer.

Recently, we have witnessed a booming development of composites and multi-dopant metal oxides to be employed as novel photocatalysts. Yet the practical application of photocatalysis for environmental purposes is still elusive. Concerns about the unknown fate and toxicity of nanoparticles, unsatisfactory performance in real conditions, mass transfer limitations and durability issues have so far discouraged investments in full-scale applications of photocatalysis. Herein, we provide a critical overview of the main challenges that are limiting large-scale application of photocatalysis in air and water/wastewater purification. We then discuss the main approaches reported in the literature to tackle these shortcomings, such as the design of photocatalytic reactors that retain the photocatalyst, the study of degradation of micropollutants in different water matrices, and the development of gas-phase reactors with optimized contact time and irradiation. Furthermore, we provide a critical analysis of research-practice gaps such as treatment of real water and air samples, degradation of pollutants with actual environmental concentrations, photocatalyst deactivation, and cost and environmental life-cycle assessment.

The diffusion process of water molecules within a polyetherimide (PEI) glassy matrix has been analyzed by combining the experimental analysis of water sorption kinetics performed by FTIR spectroscopy with theoretical information gathered from Molecular Dynamics simulations and with the expression of water chemical potential provided by a non-equilibrium lattice fluid model able to describe the thermodynamics of glassy polymers. This approach allowed to construct a convincing description of the diffusion mechanism of water in PEI providing molecular details of the process related to the effects of the cross- and self-hydrogen bondings established in the system on the dynamics of water mass transport.

This study presents an in–depth analysis and strategic planning techniques for approaching a situation or achieving progress related to information technology services of Nueva Ecija University of Science and Technology, particularly the San Isidro Campus. As an educational organization and one in the region excellence providers in education, the University has so much vital information to manage and services to offer to provide the student's needs through the Management Information System department, application of IT services as a competing instrument to combat tedious tasks such as online admission, grade release, enrollment information, and online learning, university announcement, and possible students’ internship. The objective of this study is to determine the influence of information technology in day–to–day activities of the organization and strategy applied to streamline processes more conveniently. The researchers develop a conceptual model that would analyze the IT services' impact by identifying its strengths, weaknesses, opportunities, and threats and cleverly act on it using the TOWS Matrix in generating strategic decisions. The overall results were beneficial to the University and MIS as a basis for formulating competitive strategies and integrating it in an extended development plan.

One of the main challenges for autonomous learning in virtual environments is finding the right material that fits students’ needs and supports their learning process. Personalized recommender systems partially solve this problem by suggesting online educational resources to students based on their preferences. However, in educational environments (which need a proper characterization of both users and educational resources), most existing recommendation algorithms either fail to include all the available information or use hybrid processes that do not exploit possible relationships between users and item features. This article presents a personalized recommender system for educational resources aimed at combining user and item information into a single mathematical model based on matrix factorization. As a result, estimated latent factors can provide insight into possible interactions between users and item features, improving the quality of the information retrieval process. We validated the proposed model on a real dataset that contains the ratings assigned by students from Universidad Nacional de Colombia and Universidade Feevale to educational resources in the Colombian Federation of Learning Object Repositories (FROAC in Spanish). User characterization included learning style and educational level, whereas item characterization (obtained from the objects’ metadata), included interactivity level, aggregation level and type, and resource format. These results, compared to those obtained when not all the available information is included, show that our method can improve the recommendation process.

Magnesium is one of the lightest structural metal used in different industrial sector and many works are present in literature about the study of its reinforcement by fillers addition. Basalt fibres are natural fillers with good mechanical properties, excellent resistance to high temperature and lower cost than carbon fibres. For these aspects, in the last years they are increasingly used in the production of composite materials with polymeric matrices. However, very few information are presents in literature about the use of basalt fibres as reinforcement in metal matrix composite materials. It is well known that the impregnation of fibres reinforcement affects the mechanical behavior of composites materials. The aim of this study is to investigate the impregnation and the behavior of basalt fibres in a magnesium alloy composite material manufactured by a centrifugal casting technique.

High density polyethylene (HDPE) and poly(lactic) acid (PLA) blends with different ratios of both polymers, namely 30:70, 50:50 and 70:30, were produced. Polyethylene grafted maleic anhydride and a random copolymer of ethylene and glycidyl methacrylate, were also proposed as compatibilizers to modify HDPE-PLA optimal blends and were added in the amounts of 1, 3 and 5 wt.%. Blends properties have been evaluated through different aspects by performing tensile tests, scanning electron microscopy to analyze blend morphology and interfaces, and thermomechanical analysis through differential scanning calorimetry, thermo-gravimetric analyses and infrared spectroscopy. The second blend, the one with equal amounts of HDPE and PLA seems to represent a good balance between high amount of bio-derived charge and acceptable mechanical properties. This suggests a good potential of these blends, which would be a good starting point for the production of composites with lingo-cellulosic fillers.

An accumulating body of evidence suggests that physiological reactive oxygen species (ROS) generated by NADPH oxidases act as a redox signal to re-establish homeostasis, a capacity that progressively declines during aging, but is maintained in long-lived animals to promote healthy aging. In the model organism Caenorhabditis elegans, ROS generated by dual oxidases (Duox) are important for extracellular matrix integrity, pathogen defense, oxidative stress resistance, and longevity. The Duox enzymatic activity is tightly regulated and under cellular control. Developmental molting cycles, pathogen infections, toxins, mitochondrial-derived ROS, drugs, and small GTPases (RHO-1) can activate Duox (BLI-3) to generate ROS, whereas NADPH oxidase inhibitors and negative regulators, such as MEMO-1, can inhibit Duox to generate ROS. Three mechanisms-of-action have been discovered for the Duox/BLI-3-generated ROS: 1) enzymatic activity to catalyze cross-linking of free tyrosine ethyl ester in collagen bundles to stabilize extracellular matrices, 2) high ROS bursts/levels to kill pathogens, and 3) Redox signaling activating downstream kinase cascades to transcription factors orchestrating oxidative stress- and immunity responses to re-establish homeostasis. Although Duox function at the cell surface is well established, recent genetic and biochemical data also suggests a novel role for Duoxs at the endoplasmic reticulum membrane to control redox signaling. Evidence underlying these mechanisms initiated by ROS from NADPH oxidases and their relevance for human aging are discussed in this review. Appropriately controlling NADPH oxidase activity for local and physiological redox signaling to maintain cellular homeostasis might be a therapeutic strategy to promote healthy aging.

This paper presents a new methodology that provides the analysis of surface texture changes in areas adjacent to the volcano and its impact product of volcanic activity. To do this, algorithms from digital image processing such as the co-occurrence matrix and the wavelet transform are used. These methods are working on images taken by the Landsat satellite platform sensor 5 TM and Landsat 7 ETM + sensor, and implemented with the purpose of evaluating superficial changes that can warn of surface movements of the volcano. The results were evaluated by similarity metrics for grayscale images, and validated in two different scenarios that have the same type of eruption, but differ, essentially, in climate and vegetation. Finally, the proposed algorithm is presented, setting the parameters and constraints for implementation and use.

Linear regression is a basic tool in mobile robotics, since it enables accurate estimation of straight lines from range-bearing scans or in digital images, which is a prerequisite for reliable data association and sensor fusing in the context of feature-based SLAM. This paper discusses, extends and compares existing algorithms for line fitting applicable also in case of strong covariances between the coordinates at each single data point, which must not be neglected if range-bearing sensors are used. Besides, particularly the determination of the covariance matrix is considered, which is required for stochastic modeling. The main contribution is a new error model of straight lines in closed form for calculating fast and reliably the covariance matrix dependent on just a few comprehensible and easily obtainable parameters. The model can be applied widely in any case when a line is fitted from a number of distinct points also without a-priori knowledge of the specific measurement noise. By means of extensive simulations the performance and robustness of the new model in comparison to existing approaches is shown.

High-performance poly(1,4-butylene terephthalate (PBT) nanocomposites have been developed via the consideration of phosphorus-containing agents and amino-carbon nanotube (A-CNT). One-pot functionalization method has been adopted to prepare functionalized CNTs via the reaction between A-CNT and different oxidation state phosphorus-containing agents, including chlorodiphenylphosphine (DPP-Cl), diphenylphosphinic chloride (DPP(O)-Cl), and diphenyl phosphoryl chloride (DPP(O3)-Cl). These functionalized CNTs, DPP(Ox)-A-CNTs (x = 0, 1, 3), were respectively mixed with PBT to obtain the CNTs-based polymer nanocomposites through a melt blending method. SEM observations demonstrated that DPP(Ox)-A-CNT nano-additives were homogeneously distributed within PBT matrix compared to A-CNT. The incorporation of DPP(Ox)-A-CNT improved the thermal stability of PBT. Moreover, PBT/DPP(O3)-A-CNT showed the highest crystallization temperature and tensile strength, due to the superior dispersion and interfacial interactions between DPP(O3)-A-CNT and PBT. PBT/DPP(O)-A-CNT exhibited the best flame retardancy resulting from the excellent carbonization effect. The radicals generated from decomposed polymer were effectively trapped by DPP(O)-A-CNT, leading to the reduction of heat release rate, smoke production rate, carbon dioxide and carbon monoxide release during cone calorimeter tests.

The extracellular matrix of most bacterial biofilms contains polysaccharides, proteins, and nucleic acids. These biopolymers have been shown to mediate fundamental biofilm-related phenotypes including surface attachment, intercellular adhesion, and biocide resistance. Enzymes that degrade polymeric biofilm matrix components, including glycoside hydrolases, proteases, and nucleases, are useful tools for studying the structure and function of biofilm matrix components and are also being investigated as potential antibiofilm agents for clinical use. Dispersin B is a well-studied, broad spectrum antibiofilm glycoside hydrolase produced by Aggregatibacter actinomycetemcomitans. Dispersin B degrades poly-N-acetylglucosamine, a biofilm matrix polysaccharide that mediates biofilm formation, stress tolerance, and biocide resistance in numerous Gram-negative and Gram-positive pathogens. Dispersin B has been shown to inhibit biofilm and pellicle formation; detach pre-formed biofilms; disaggregate bacterial flocs; sensitize pre-formed biofilms to detachment by enzymes, detergents, and metal chelators; and sensitize pre-formed biofilms to killing by antiseptics, antibiotics, bacteriophages, macrophages, and predatory bacteria. This review summarizes the results of nearly 100 in vitro and in vivo studies that have been carried out on dispersin B since it’s discovery 20 years ago. These include investigations into the biological function of the enzyme, it’s structure and mechanism of action, and its in vitro and in vivo antibiofilm activities against numerous bacterial species. Also discussed are potential clinical applications of dispersin B.

In the paper, the authors establish two identities to express the generating function of the Chebyshev polynomials of the second kind and its higher order derivatives in terms of the generating function and its derivatives each other, deduce an explicit formula and an identities for the Chebyshev polynomials of the second kind, derive the inverse of an integer, unit, and lower triangular matrix, present several identities of the Catalan numbers, and give some remarks on the closely related results including connections of the Catalan numbers respectively with the Chebyshev polynomials, the central Delannoy numbers, and the Fibonacci polynomials.

In this paper, comprehensive analysis of combined effect of major influencing parameters on heat transfer in the single U-tube BHE (sBHE) and double U-tube BHE (dBHE) with two independent circuits was performed by using validated numerical heat transfer model. Geometrical parameters, such as shank spacing (with maximum, average and minimum values) and borehole diameter (large, medium and small borehole sizes) and borehole depth (shallow, average and deep borehole depths) as well as thermal conductivity of soil and grout which ranges from minimum to high value were considered. The combined impact of these parameters was included under four major cases: 1) combined effect of borehole depth, borehole size and shank spacing; 2) combined effect of borehole depth, and soil and grout thermal conductivity; 3) combined effect of soil and grout thermal conductivity and borehole size; and 4) combined effect of soil thermal conductivity, borehole size and shank spacing. Each of these major cases has nine different design options of both sBHE and dBHE. Series of results of heat transfer per unit borehole depth were generated for all the considered various cases. With the given parameters, the BHE case that provides highest heat transfer among the various cases of sBHE and dBHE were obtained.

The adaptive implementation of the Monte Carlo Method (AMCM) has been applied to optimize the calibration uncertainty of a positive displacement meter against a standard tank in an ISO 17025 accredited volume laboratory. These meters are used for custody transfer in liquid hydrocarbon logistics where any reduction in the uncertainty estimation may have an important economic impact. Several innovations are proposed when applying AMCM; regulation of AMCM convergence by applying the Student's t-distribution, validation of repeatability and filtering of outliers by performing 50 iterations of the AMCM, and characterization of the measurand's Probability Density Function (PDF) which results in a Flatten Gaussian. This work proves that GUM method does not assign the correct PDF. The uncertainty estimation is reduced 7.1 % compared to GUM method.

Background: The aim of this systematic review was to evaluate diagnostic accuracy of molecular-based LTPs serum IgE for the diagnosis of food allergies in patients with suspected allergy to one of the LTPs-containing food. Methods: cohort, prospective or retrospective cross- sectional studies were considered for inclusion in the review. Oral food challenge (both open and double-blind placebo-controlled) was the reference standard for the diagnosis. Pubmed (MEDLINE), Web of Science, Scopus, and ClinicalTrial.org were searched for relevant papers. Risk of bias was assigned by QUADAS-2 tool. Data were reported as sensitivity and specificity. Study protocol was registered in the PROSPERO database (CRD42022321985). Results: Fifteen articles, including 2395 individuals, were included. Sensitivity of Ara h 9 for peanut allergy diagnosis ranged from 6 to 61%; specificity ranged from 57 to 100%. Cor a 8 sensitivity ranged from 11 to 43%, with specificity ranging from 59 to 94%. Conclusions: Ara h9 and Cor a 8 serum IgE may be useful to confirm diagnosis of peanut and hazelnut allergy in symptomatic patients, although diagnostic accuracy is limited by low sensitivity. More investigation on other LTPs and in adult population may be important to define the clinical role of this test in food allergies diagnostics.

In order to solve the problem of structure damage location and degree identification, the weighted mean of vectors algorithm (INFO), a high-performance optimization one, was first introduced to identify structure damage. The genetic algorithm (GA) are improved to obtain a refined genetic algorithm (RGA). An objective function is constructed by combining the dynamic response transfer-ratio without modal analysis. INFO and RGA algorithms are used to optimize the objective function for damage identification. Though simulations, the INFO, RGA, GA algorithms were used to identify the damage on a simply supported beam and cantilevered plate with different levels of noise and different frequency spacing of pickup points. The simulations verify the effectiveness of the three damage identification methods, and the INFO algorithm has the highest damage identification accuracy, the RGA is second and the GA is the worst.