Programmed cell death protein 1 (PD-1) is a biomarker on the surface of cells that has a role in promoting self-tolerance by suppressing the inflammatory activity of T cells. In this work, one peptide of PD-1 was used as the template in molecular imprinting. The magnetic peptide-imprinted poly(ethylene-co-vinyl alcohol) composite nanoparticles (MPIP NPs) were characterized by dynamic light scattering (DLS), high-performance liquid chromatography (HPLC), Brunauer-Emmett-Teller (BET) analysis and superconducting quantum interference device (SQUID) analysis. Natural killer-92 (NK-92) cells were added to these composite nanoparticles and then incubated with human hepatoma (HepG2) cells. The viability and apoptosis pathway of HepG2 were then studied using cell counting kit-8 (CCK8) and the quantitative real-time polymerase chain reaction (qRT-PCR), respectively. These nanoparticles were found significantly enhance the activity of natural killer cells toward HepG2 cells by increasing expression of NK-kB, caspase 8 and especially caspase 3.

This study evaluated ground-level concentrations (GLCs) of aerosols and criteria pollutants using the Copernicus Atmosphere Monitoring Service (CAMS) reanalysis dataset over the Himawari-8 observational land area, including China, Indonesia, and Australia, for the past eight years. A square root transformation of the data was used to normalize and mitigate skewness. Monthly-hourly long-term averages were subtracted to determine abnormalities and identify significant pollution events. Geographic Weighted Regression (GWR) and the Jacobian matrix (dY/dX) methods were used to determine the spatial variability in pollutant concentrations and correlations with meteorological factors. The findings revealed complex interactions between atmospheric dynamics, such as wind components, specific humidity, and pollutant distribution. The analysis highlighted the limitations of traditional point monitoring methods and the need for incident-based spatiotemporal approaches to understand pollution dynamics. This comprehensive evaluation, covering roughly 10% of the globe, demonstrated CAMS's effectiveness in providing detailed insights into air quality trends, which can support targeted public health interventions and compliance with sustainability goals. Integrating CAMS data with high-resolution satellite data like Himawari-8 could revolutionize air quality monitoring by delivering dynamic, near real-time outputs with high spatiotemporal resolution.

The theory of heavy ion double charge exchange (DCE) reactions proceeding by effective rank–2 isotensor interactions is presented. Virtual pion–nucleon charge exchange interactions are investigated as the source for induced isotensor interactions, giving rise to the Majorana DCE (MDCE) reaction mechanism. MDCE is of a generic character, proceeding through pairs of complementary (π±,π∓) reactions in the projectile and target nucleus. The dynamics of the elementary processes is discussed where the excitation of pion–nucleon resonances are of central importance. Investigations of initial and final state ion–ion interactions show that these effects are acting as vertex renormalizations. In closure approximation, well justified by the finite pion mass, the second order transition matrix elements reduce to pion potentials and effective two–body isotensor DCE interactions, giving rise also to two–body correlations in either of the participating nuclei. Connections to neutrinoless Majorana double beta decay (MDBD) are elucidated at various levels of dynamics, from the underlying fundamental electro–weak and QCD scales to the physical scales of nuclear MDBD and MDCE physics. It is pointed out that heavy ion MDCE reactions may also proceed by competing electro–weak charge exchange processes, leading to lepton MDCE by electrons, positrons, and neutrinos.

Information geometry (IG) is a fascinating combination of differential geometry and statistics where a Riemannian manifold's structure is applied to a statistical model. It may find numerous fascinating uses in the domains of theoretical neurology, machine learning, complexity, and (quantum) information theory, among others. (IG) aims to provide a differential-geometric perspective on statistical geodesic models' structure. In this case, IG, KD, and J-divergence (JD) are used to define the manifold of the Generalised Brownian Motion (GBM). Consequently, the geodesic equations (GEs) are devised, and GB information matrix exponential (IME) is presented. Moreover, for first time ever, the necessary and sufficient mathematical requirement that characterizes the developability of Generalized Brownian Motion(GBM) manifold is devised. Also, a novel sufficient and necessary conditions which characterizes the regions where the surface describing GBM is minimal is determined. Also, it is shown that GBM has a non-zero 0-Gaussian and Ricci curvatures. Consequently, this advances the establishment of a unified GBM- Relativistic Info-Geometric based analysis.

Pathological aseptic calcification is the most common form of structural valvular degeneration (SVD), leading to premature failure of heart valve bioprostheses (BHVs). The processing methods used to obtain GA-fixed pericardium-based biomaterials determine the hemodynamic characteristics and durability of BHVs. This article presents a comparative study of the effects of several processing methods on the degree of damage to the ECM of GA-fixed pericardium-based biomaterials as well as on their biostability, biocompatibility, and resistance to calcification. Based on the assumption that preservation of the native ECM structure will enable the creation of calcinosis-resistant materials, this study provides a soft biomimetic approach for the manufacture of GA-fixed biomaterials using gentle decellularization and washing methods. It has been shown that the use of soft methods for preimplantation processing of materials, ensuring maximum preservation of the intactness of the pericardial ECM, radically increases the resistance of biomaterials to calcification. The data obtained are of interest for the development of new calcinosis-resistant biomaterials for the manufacture of BHVs.

Power converter technologies have become increasingly vital in various applications due to their efficient management of electrical energy. With the growing prominence of renewable energy sources like solar and wind, the high penetration of power electronic converters has been justified. However, ensuring power quality has emerged as a significant challenge for grid-connected power converters. The divergence from the ideal sinusoidal waveform in terms of magnitude and frequency impacts both grid-side currents and voltages. Several studies have proposed solutions to address power quality issues at the load side. The advancement of power converters has been fueled by the development of high-performance microprocessors and the emergence of high-speed switching devices, such as SiC-MOSFETs. This paper focuses on the design of voltage source converters, particularly those based on SiC-MOSFET semiconductor devices. The article presents the design of H-Bridge cells, discusses two-level voltage source converters based on cascade H-Bridge cells in parallel configuration with experimental fault analysis, addresses the seven-level voltage source converters topology, and explores the design and experimental results of the matrix converter. The findings underscore the importance of considering the entire converter design for improved performance at high switching frequencies. The article concludes by summarizing the main outcomes and implications of this research.

Compliant amplifying mechanisms are used widely in high-precision instruments driven by piezoelectric actuators, and the dynamic and static characteristics of these mechanisms are closely related to instrument performance. Although the majority of existing research has focused on analysis of their static characteristics, the dynamic characteristics of the mechanisms affect their response speeds directly. Therefore, this paper proposes a comprehensive theoretical model of compliant amplifying mechanisms based on the multi-body system transfer matrix method to analyze the dynamic and static characteristics of these mechanisms. The effects of the main amplifying mechanism parameters on the displacement amplification ratio and the resonance frequency are analyzed comprehensively using the control variable method. An iterative optimization algorithm is also used to obtain specific parameters that meet the design requirements. Finally, simulation analyses and experimental verification tests are performed. The results indicate the feasibility of using the proposed theoretical compliant amplifying mechanism model to describe the mechanism’s dynamic and static characteristics, which represents a significant contribution to the design and optimization of compliant amplifying mechanisms.

The following article presents an analysis of the determinants of diabetes using a dataset containing the surveys of 2000 patients from the Frankfurt Hospital in Germany. The data were analyzed using the following models, namely: Tobit, Probit, Logit, Multinomial Logit, OLS, WLS with heteroskedasticity. The results show that the presence of diabetes is positively associated with "Pregnancies", "Glucose", "BMI", "Diabetes Pedigree Function", "Age" and negatively associated with "Blood Pressure". A cluster analysis is realized using the fuzzy c-Means algorithm optimized with the Elbow method and three clusters were found. Finally a confrontation among eight different machine learning algorithms is realized to select the best performing algorithm to predict the probability of patients to develop diabetes.

Combining Matrix-Assisted Laser Desorption/Ionization Time-of-Flight (MALDI-TOF) spectra data and artificial intelligence (AI) has been introduced for rapid prediction on antibiotic susceptibility test (AST) of S. aureus. Based on the AI predictive probability, the cases with probabilities between low and high cut-offs are defined as “grey zone”. We aimed to investigate the underlying reasons of unconfident (grey zone) or wrong predictive AST. A total 479 S. aureus isolates were collected, analyzed by MALDI-TOF, and AST prediction, standard AST were obtained in a tertiary medical center. The predictions were categorized into the correct prediction group, wrong prediction group, and grey zone group. We analyzed the association between the predictive results and the demographic data, spectral data, and strain types. For MRSA, larger cefoxitin zone size was found in the wrong prediction group. MLST of the MRSA isolates in the grey zone group revealed that uncommon strain types composed 80%. Amid MSSA isolates in the grey zone group, the majority (60%) was composed of over 10 different strain types. In predicting AST based on MALDI-TOF AI, uncommon strains and high diversity would contribute to suboptimal predictive performance.

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disorder affecting 1 in 500 people in the general population. Although characterized by asymmetric left ventricular hypertrophy, cardiomyocyte disarray and cardiac fibrosis, HCM is in fact a highly complex disease with heterogenous clinical presentation, onset and complications. While HCM is generally accepted as a disease of the sarcomere, variable penetrance in families with identical genetic mutations challenges the monogenic origin of HCM and instead implies a multifactorial cause. Furthermore, large scale genome sequencing studies revealed that many genes previously reported as causative of HCM in fact have little or no evidence of disease association. These findings thus call for a re-evaluation of the sarcomere-centered view of HCM pathogenesis. Here, we summarize our current understanding of sarcomere-independent mechanisms of cardiomyocyte hypertrophy, highlight the role of extracellular signals in cardiac fibrosis, and propose an alternative but integrated model of HCM pathogenesis.

This is the first study to provide a systematic monetary benefit matrix, including greenhouse gas (GHG) emissions reduction benefits and air pollution reduction health co-benefits, for a change in on-the-road transport to low-carbon types. The benefit transfer method is employed to estimate the social cost of carbon and the health co-benefits via impact pathway analysis in Taiwan. Specifically, the total emissions reduction benefits from changing all internal combustion vehicles to either hybrid electric vehicles, plug-in hybrid electric vehicles, or electric vehicles would generate an average of US$760 million from GHG emissions reduction and US$2,091 million from health co-benefits based on air pollution reduction, for a total benefit of US$2,851 million annually. For a change from combustion scooters to light- or heavy-duty electric scooters, the average GHG emissions reduction benefits would be US$96.02 million, and the health co-benefits from air pollution reduction would be US$1,008.83 million, for total benefits of US$1,104.85 million annually.

In this paper, we provide some enlightening examples of the application of Clifford algebra in geometry, which show the concise representation, simple calculation and profound insight of this algebra. The definition of Clifford algebra implies geometric concepts such as vector, length, angle, area and volume, and unifies the calculus of scalar, spinor, vector and tensor, so that it is able to naturally describe all variables and calculus in geometry and physics. Clifford algebra unifies and generalizes real number, complex, quaternion and vector algebra, converts complicated relations and operations into intuitive matrix algebra independent of coordinate systems. By localizing the basis or frame of space-time and introducing differential and connection operators, Clifford algebra also contains Riemann geometry. Clifford algebra provides a unified, standard, elegant and open language and tools for numerous complicated mathematical and physical theories. Clifford algebra calculus is an arithmetic-like operation that can be well understood by everyone. This feature is very useful for teaching purposes, and popularizing Clifford algebra in high schools and universities will greatly improve the efficiency of students to learn fundamental knowledge of mathematics and physics. So Clifford algebra can be expected to complete a new big synthesis of scientific knowledge.

This paper discusses the computer-aided (CAD) classification between Hepatocellular Carcinoma (HCC), i.e., the most common type of liver cancer, and Liver Abscess, based on ultrasound image texture features and Support Vector Machine (SVM) classifier. Among 79 cases of liver diseases, with 44 cases of HCC and 35 cases of liver abscess, this research extracts 96 features of Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Run-Length Matrix (GLRLM) from the region of interests (ROIs) in ultrasound images. Three feature selection models, i) Sequential Forward Selection, ii) Sequential Backward Selection, and iii) F-score, are adopted to determine the identification of these liver diseases. Finally, the developed system can classify HCC and liver abscess by SVM with the accuracy of 88.875%. The proposed methods can provide diagnostic assistance while distinguishing two kinds of liver diseases by using a CAD system.

This study provides a detailed investigation into the pathways through which microplastics from urban sources are transported to marine ecosystems, their distribution across different environments, and their impacts on marine life. Utilizing a combination of water and sediment sampling across urban, riverine, and marine environments, the research quantitatively assesses the concentration and types of microplastics present, and evaluates the ecological consequences of their accumulation in marine ecosystems. The findings reveal a significant concentration of microplastics in all examined environments, with the highest levels detected in urban areas, closely linked to industrial activities and inadequate waste management practices. The study documents a variety of microplastic polymers, with polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET) being the most prevalent. A substantial impact on marine organisms was observed, including evidence of microplastic ingestion across a wide range of species and indications of stress and physical damage to coral reefs. Seasonal variations indicate that microplastic concentrations peak during periods of high rainfall, suggesting urban runoff as a critical pathway for microplastic transport. The study concludes with recommendations for improving waste management practices, enhancing public awareness and engagement in plastic recycling efforts, and implementing policies aimed at reducing the production and use of single-use plastics. This research underscores the urgent need for coordinated actions to mitigate the pervasive issue of microplastic pollution, highlighting the role of urban management and policy interventions in safeguarding marine ecosystems.

In this work, an evanescent Bragg grating sensor inscribed in a few-mode planar polymer waveguide was integrated in microchannel structures and characterized with various chemical applications. The planar waveguide and the microchannels consisted of epoxide-based polymers. The Bragg grating structure was post-processed using point-by-point direct inscription technology. By monitoring the central wavelength shift of the reflected Bragg signal, the sensor showed a temperature sensitivity of -47.75 pm/K. Moreover, the functionality of the evanescent field-based measurements is demonstrated with two application examples: refractive index sensing of different aqueous solutions and gas-phase hydrogen concentration detection. For the latter application, the sensor was additionally coated with a functional layer based on palladium nanoparticles. During the refractive index sensing measurement, the sensor achieved a sensitivity of 6.5 nm/RIU from air to 99.9% pure isopropyl alcohol. For the gas-phase hydrogen detection, the coated sensor achieved a reproducible concentration detection up to 4 vol% hydrogen. According to the reported experimental results, the integrated Bragg grating-based waveguide sensor demonstrates high potential for applications based on lab-on-a-chip concept.

In the present study, linear novel polymer poly(1-(2-((3-amino-2-hydroxypropyl)amino)ethyl)-1'-ethyl-[4,4'-bipyridine]-1,1'-di-ium) (poly(AHAEBD)) and its complex with iron (ΙΙΙ) ([Fe(poly(AHAEBD)2].Na3) were synthesized and then their anticancer effects on A375 human malignant melanoma cells line were evaluated. The structure of the synthesized compounds was confirmed using Fourier transform infrared spectroscopy (FT-IR), nuclear magnetic resonance spectroscopy (1HNMR), field emission scanning electron microscopy (FE-SEM), X-ray energy diffraction analysis (EDS) and gel permeation chromatography (GPC). Also, the cytotoxicity of cisplatin as a reference, on A375 melanoma cell line was tested. The IC50 of polymer-complex [Fe(poly(AHAEBD)2].Na3 (0.71 µg/mL), cisplatin (4.58 µg/mL) and poly(AHAEBD) (1.73 µg/mL) were obtained. Our results revealed that the polymer-complex [Fe(poly(AHAEBD)2].Na3 exhibited better performance compared to cisplatin. Furthermore, the coordination with iron (III) enhanced the cytotoxicity levels of poly(AHAEBD). According to these findings, the synthesized polymer-complex demonstrates remarkable potential as an anti-cancer agent. This study could provide the basis for future research focused on employing this new polymer-complex for in vivo testing, highlighting its potential for therapeutic applications.

In this study organic bulk heterojunction (BHJ) solar cell along with the spiro OMeTAD as a hole transport layer (HTL) and the PDINO as an electron transport layer (ETL) was simulated through the Solar Capacitance Simulator, one dimensional (SCAPS-1D) software to examine the performance of this type of polymer thin film organic solar cells. As an active layer the blend of polymer donor PBDB-T and non-fullerene acceptor ITIC-OE was used. Numerical simulation was performed by varying the thickness of HTL and active layer. Firstly, the HTL layer thickness was optimized to 50 nm, after that the active layer thickness varied up to 80 nm. These results of simulation demonstrated that the HTL thickness has rather little impact on efficiency while in the case of active layer thickness improves efficiency significantly. The temperature effect on the performance of solar cells was considered, by the simulation performed for temperature from 300 K up to 400 K and the efficiency of solar cell decreases with increasing temperature. Generally, polymer films usually are full of traps and defects, the density of defects (Nt) value was also introduced to the simulation, and it was confirmed that with the increasing of defect density (Nt), the efficiency of solar cell decreases. After thickness, temperature and defect density optimization, the reflection coating was also applied on it. It turned out that by introducing the reflection coating on the back side of solar cell, the efficiency increases by 2.5 %. Additionally, the positive effect of HTL and ETL doping on efficiency of this type of solar cells was demonstrated.

The aim of the current study was to develop and evaluate the therapeutic potential of apocynin (APO) loaded pH-sensitive nanoparticles (NPs) based transdermal hydrogel for management of rheumatoid arthritis (RA). Slightly modified nanoprecipitation technique was used for preparation of polymeric nanoparticles. Optimization was done through design expert software. Optimized APO-NPs were loaded into carbopol-934 based hydrogel as final dosage form and further studied for physicochemical properties. Optimized APO-NPs formulation had a minimum particle size 63.44 nm, polydisperibility index 0.161, and zeta potential -15mV with a maximum encapsulation efficiency of 89%. In-vitro and ex-vivo studies of APO-NPs based hydrogel was performed at pH 5.5 (pH of normal skin) and 6.8 (pH of inflammed joint) showed a pH-responsive sustained drug release and increased penetration in comparison to free APO based hydrogel. The stability studies of APO-NPs based hydrogel were done to strengthen the potential use of the prepared formulation through transdermal route. Assessment and therapeutic efficacy of the prepared pH-sensitive nanocarriers system was evaluated in chronic inflammatory RA mice model. Parameters associated with chronic inflammation were investigated including behavioral changes and histopathological, and radiological x-rays images of joints of mice paws. In-vivo study depicts improvement in behavioral parameter, decline in synovial hyperplasia and bone structure restoration. In conclusion, APO loaded pH-sensitive NPs based transdermal is a promising carrier system that can effectively manage RA.

This research is completed in development of researches devoted to relations between elastic modulus (MoE) and thermal expansivity (CTe) of different materials. This study experimentally confirmed the relation of MoE and CTe for thermosetting polymers and FRPs both under normal and heating temperatures. As the thermosetting polymers, the epoxy compositions were used and glass fiber and mineral additives for FRP. The experiment was based on dilatometric and elastic deformations’ testing. Also, the relaxation model of MoE/CTe was proposed, that is based on physical properties of polymers’ supramolecular structures. The comparative analyzing of MoE/CTes’ different models is done. The most accurate models are determined, and the relaxation model has demonstrated the high accuracy.

Steel reinforcement in concrete has the tendency to corrode and this process can lead to structural damage. FRP reinforcement represents a viable alternative for structures exposed to aggressive environments and has many possible applications where superior corrosion resistance properties are required. The use of FRP rebars as internal reinforcements for concrete, however, is limited to specific structural elements and does not yet extend to the whole structure. The reasons for this relate to the limited availability of curved or shaped reinforcing elements on the market and their reduced structural performance. Various studies, in fact, have shown that the mechanical performance of bent portions of composite bars is reduced significantly under a multiaxial combination of stresses and that the tensile strength can be as low as 25% of the maximum tensile strength that can be developed in the straight part. In a significant number of cases, the current design recommendations for concrete structures reinforced with FRP, however, were found to overestimate the bend capacity of FRP rebar. This paper presents the state-of-the art review of the research works on the strength degradation in curved FRP composites and highlighted the performance of exiting predictive models for the bend capacity of FRP reinforcement. Recent practical predictive model based on the Tsai-Hill failure criteria by considering the material at marcromechanical level is also discussed and highlighted. The review also identifies the challenges and highlights the future directions of research to explore the use of shaped FRP composites in civil engineering applications and the trends for future research in this area.

Electrical properties of the thin films of poly(arylene ether ketone) copolymers (co-PAEKs) with the fraction of phthalide-containing units of 3, 5 and 50 mol% in the main chain were investigated by using radiation induced conductivity (RIC) measurements. Transient current signals and current-voltage (I-V) characteristics were obtained under exposing 20÷25 thick films of the co-PAEKs to monoenergetic electron pulses of the energy ranged from 3 to 50 keV in the electric field ranged from 5 to 40 V/μm. The Rose-Fowler-Vaisberg semi-empirical model based on a multiple trapping formalism was used for an analysis of the RIC data and the parameters of the highly dispersive charge carrier transport were evaluated. The analysis revealed that charge carriers moved in isolation from each other and the applied electric fields were below the threshold field triggering the switching effect (a reversible high-to-low resistivity transition) in the co-PAEK films. It was also found that the co-PAEK films due to the super-linear I-V characteristics are highly resistant to electrostatic discharges arising from the effects of ionizing radiation. This property is important for the development of protective coatings for electronic devices.

From a differential geometric perspective, information geometry (IG) aims to characterise the structure of statistical geodesic models. The research done for this paper offers a novel method for modelling the information geometry of a queuing system. From the perspective of IG, the manifold of the transient M/M/infinity queue is described in this context. The Fisher Information matrix (FIM) as well as the inverse of (FIM), (IFIM) of transient M/M/infinity QM are devised. In addition to that, new results that uncovered the significant impact of stability of QM on the existence of (IFIM) are obtained. Moreover, the Geodesic equations of motion of the coordinates of the underlying transient are obtained. Also, it is revealed that stable QM is developable (i.e., has a zero Gaussian curvature) and has a non-zero Ricci Curvature Tensor (RCT). Novel stability dynamics of transient M/M/iInfinity queue manifold is revealed by discovering the mutual dual impact between the behaviour of (RCT) and the stability(instability) phases of M/M/Infinity QM. Furthermore, a new discovery that presents the significant impact of stability of queue manifold and the continuity of the unique representation between M/G/1 queue manifold and Ricci Curvature Tensor (RCT). The information matrix exponential (IME) is devised. Also, it is shown that stability of the devised (IME) enforces the instability of M/M/ Infinity QM. More interestingly, novel relativistic info-geometric queueing theoretic links are revealed .

Nanling Mountain region is a typical southern hilly region, which plays an important ecological and environmental protection role in China's overall land protection pattern. Based on the remote sensing image data of Longnan City in Nanling Mountain in 2013, 2018 and 2023, this paper interpreted the land use type and analyzed the land use transfer situation by using Land use transfer flow, and Land use transfer matrix. At the same time, based on the remote sensing Ecological index (RSEI) model, the ecological environment quality of Longnan City from 2013 to 2023 was retrieved. The temporal and spatial response model of ecological environment quality to land use transfer in Longnan City from 2013 to 2023 was discussed based on Spatial autocorrelation and Geographic detector. The results show that from 2013 to 2023, the decrease of forest land (16.23km²) and the increase of construction land (13.25km²) were the main land use transfer in Longnan City. The ecological environment index of Longnan City in 2013, 2018 and 2023 was 0.789, 0.917 and 0.872, respectively, showing a trend of "first rising and then decreasing". The ecological environment quality in the north of Longnan City was significantly lower than that in the south, and the poor ecological quality area appeared in and around the northern main urban area, showing a trend of "inward contraction". Forest land, garden land, grassland, cultivated land and water area have a positive impact on ecological environment quality, while traffic land, construction land and other land have a negative impact on ecological environment quality. The response of ecological environment quality to different land use transfer modes is related to the change of the overall ecological environment quality. The interaction between LUCC and other factors had a great impact on the evolution of ecological environment quality in Longnan City.

In this paper, we obtain the existence and uniqueness theorem for solutions of Caputo type fractional stochastic delay differential systems (FSDDSs) with Poisson jumps by utilizing delayed perturbation of Mittag-Leffler function. Moreover, by using Burkholder-Davis-Gundy's inequality, Doob's martingale inequality and Holder inequality, we prove that the solution of the averaged FSDDSs converges to that of the standard FSDDSs in the sense of Lp. Some known results in the literature are extended.

In this paper, we introduce ResNetMF, a groundbreaking approach that harnesses the power of residual network matrix factorization to revolutionize recommendation systems. ResNetMF integrates residual networks, renowned for their ability to capture intricate patterns and features, with matrix factorization techniques that excel in modelling user-item interactions. This fusion presents a novel solution that surpasses the limitations of traditional recommendation systems. Through comprehensive experimentation and evaluation of diverse datasets, ResNetMF demonstrates remarkable enhancements in recommendation accuracy and efficiency. By effectively capturing both linear and nonlinear relationships in user-item interactions, ResNetMF provides superior recommendation quality. The outcomes from experiments unequivocally highlight the superiority of ResNetMF over existing state-of-the-art recommendation approaches, thereby validating its innovative nature and underscoring its potential to shape the future of recommendation systems. Through the integration of the deep residual network, ResNetMF approach facilitates the training of neural networks, enabling them to explore the underlying data layers more comprehensively. Extensive experimentation and evaluation across various datasets provide compelling evidence for the superiority of ResNetMF. Moreover, the proposed method utilized natural language processing (NLP) techniques for targeted information dissemination in recommendation systems, emphasizing the importance of personalized and relevant recommendations for user satisfaction and engagement.

Deep learning methods have been widely used in PolSAR image classification. To learn the polarimetric information, many deep learning methods expect to learn high-level semantic features from original PolSAR data. However, only original data cannot learn multiple scattering features and complex structures for extremely heterogeneous terrain objects. In addition, deep learning methods always cause edge confusion due to the high-level features. To overcome these shortages, we propose a double-channel CNN network combined with an edge-preserving MRF model(DCCNN-MRF) for PolSAR image classification. Firstly, to combine complex matrix data and multiple scattering features together, a double-channel convolution network(DCCNN) is developed, which consists of a Wishart-based complex matrix and multi-feature subnetworks. The Wishart-based complex matrix network can learn the statistical characteristics and channel correlation well, and the multi-feature network can learn high-level semantic features well. Then, a unified network framework is designed to fuse two kinds of features to enhance advantageous features and reduce redundant ones. Finally, an edge preserving MRF model is designed to combine with the DCCNN network. In the MRF model, a sketch map-based edge energy function is designed by defining adaptive weighted neighborhood for edge pixels. Experiments are conducted on four real PolSAR data sets with different sensors and bands. Experimental results demonstrate the effectiveness of the proposed DCCNN-MRF method.

Quantitative polymerase chain reaction (qPCR) has emerged as an important bioanalytical method for assessing the pharmacokinetics of human cell-based medicinal products after xenotransplantation into immunodeficient mice. A particular challenge in bioanalytical qPCR studies is that the different tissues of the host organism can affect amplification efficiency and amplicon detection to varying degrees, and ignoring these matrix effects can easily cause a significant underestimation of the true number of target cells in a sample. Here we describe the development and drug regulatory-compliant validation of a TaqMan® qPCR assay for quantification of mesenchymal stromal cells in the range of 125 to 20,000 cells/200 µl lysate by amplification of a human-specific, highly repetitive αsatellite DNA sequence of the chromosome 17 centromere region HSSATA17. Assessment of matrix effects in 14 different mouse tissues and blood revealed a wide range of spike recovery rates across the different tissue types from 11 to 174%. Based on these observations, we propose to perform systematic spike-and-recovery experiments during assay validation and to correct for the effects of the different tissue matrices on cell quantification in subsequent bioanalytical studies by multiplying the back-calculated cell number by tissue-specific factors derived from the inverse of the validated percent recovery rate.

With the continuous development of 3D city modeling, traditional close-range photogrammetry is limited by complex processing procedures and incomplete 3D depth information, making it unable to meet high-precision modeling requirements. In contrast, the integration of LiDAR and camera in mobile measurement systems provides a new and highly effective solution. The LiDAR can quickly and accurately acquire the 3D spatial coordinates of target objects, while optical imagery contains abundant color information. If the two can be integrated, they can play an important role in multiple fields such as streetscape modeling, archaeology and digital city, etc. Currently, integrated mobile measurement systems commonly require cameras, lasers, POS and IMU, thus the hardware cost is relatively expensive and the system integration is complex. Therefore, in this paper we propose a simple ground mobile measurement system composed of a LiDAR and a GoPro camera without a POS system, providing a more convenient and reliable way to automatically obtain 3D point cloud data with spectral information. The automatic point cloud coloring based on video images mainly includes four aspects: (1) Establishing models for radial distortion and tangential distortion to correct video images. (2) Establishing a registration method based on normalized Zernike moments to obtain the exterior orientation elements. Normalized Zernike moments are region-based shape descriptors that can reflect the features of images in multiple dimensions even for low-quality video images. The results show that registration based on normalized Zernike moments provides a good result, with an error accuracy of 0.5-1 pixel, which is far higher than registration based on a collinearity equation. (3) Establishing adjacent video image relative orientation based on essential matrix decomposition and nonlinear optimization. This involves uniformly using the SURF algorithm with distance restriction and RANSAC to select corresponding points, which can improve the reliability of the corresponding points. The results indicate that the accuracy of the relative orientation method is high. Moreover, this method can converge to good results for stereo image pairs with large rotation angles and displacement amounts. Therefore, relative orientation based on essential matrix decomposition and nonlinear optimization has good applicability. (4) The video imagery suffers from significant motion blur and boundary distortion. Therefore, a point cloud coloring method based on Gaussian distribution with central region restriction is adopted. Only pixels within the central region are considered valid for coloring. Then, the point cloud is colored based on the mean of the Gaussian distribution of the color set. Experimental results show that the coloring accuracy between the video imagery and point cloud data is high, meeting the accuracy requirements of applications such as tunnel detection, street-view modeling and 3D urban modeling.

Work from the last years indicate that the extracellular matrix (ECM) plays a direct role in vari-ous cellular processes including proliferation, migration and differentiation. Besides homeostat-ic processes, its regulatory function in inflammation becomes more and more evident. In in-flammation like inflammatory bowel disease, the ECM composition is constantly remodeled which can result in a structuring of fistulizing disease course. Thus, tracking early ECM changes might bear the potential to predict the disease course. In this review, we will provide an over-view of relevant diagnostic methods focusing on ECM changes.

The peril of a 3-dimensional, robust and sustained myocardial restoration by means of Tissue Engineering is that it still remains a largely experimental approach. Prolific protocols have been developed and tested in small and large animals, but as clinical cardiac surgeons, we have not come to the privilege of utilizing any of them in our clinical practice. The question arises: why? The heart is a unique organ, anatomically and functionally. It is not an easy target to replicate with current techniques, or even to support its viability and function. Currently available therapies fail to reverse the loss of functional cardiac tissue, the fundamental pathology remains unaddressed and a heart transplantation is an ultima ratio treatment option. Owing to equivocal results of cell-based therapies, several strategies have been pursued to overcome limitations of the current treatment options. Preclinical data as well as first-in-human studies conducted to date have provided important insights into the understanding of injection-based approaches for myocardial restoration. In the light of the available data, injectable biomaterials suitable for transcatheteter delivery appear to have the highest translational potential,. This article presents a current state-of-the-art in the field of hydrogel-based myocardial restoration therapy.

There is a huge interest in developing novel hollow fiber (HF) membranes able to modulate neural differentiation to produce in vitro blood-brain barrier (BBB) models for biomedical and pharmaceutical research, due to the low cell-inductive properties of the polymer HFs used in current BBB models. In this work, poly(ε-caprolactone) (PCL) and composite PCL/graphene (PCL/G) HF membranes were prepared by phase inversion and were characterized in terms of mechanical, electrical, morphological, chemical, and mass transport properties. The presence of graphene in PCL/G membranes enlarged the pore size and the water flux and presented significantly higher electrical conductivity than PCL HFs. Biocompatibility assay showed that PCL/G HFs significantly increased C6 cells adhesion and differentiation towards astrocytes, may be attributed to their higher electrical conductivity in comparison to PCL HFs. On the other hand, PCL/G membranes produced a cytotoxic effect on the endothelial cell line HUVEC presumably related with a higher production of intracellular reactive oxygen species induced by the nanomaterial in this particular cell line. These results prove the potential of PCL HF membranes to grow endothelial cells and PCL/G HF membranes to differentiate astrocytes, the two characteristic cell types that could develop in vitro BBB models in future 3D co-culture systems.

Background: A significant proportion of SARS-CoV-2-infected patients develops respiratory failure. Thromboembolism is also prevalent in coronavirus disease 2019 (Covid-19). Vitamin K plays a role in coagulation and possibly also in lung diseases. We therefore hypothesized that vitamin K is implicated in Covid-19 pathogenesis. Methods: 134 Covid-19 patients and 184 controls were included. Inactive vitamin K-dependent matrix Gla protein (i.e.dp-ucMGP) and prothrombin (i.e. PIVKA-II) were measured, which are inversely related to respectively extrahepatic and hepatic vitamin K status. Desmosine was measured to quantify elastic fiber degradation. Lung involvement and arterial calcifications severity were assessed by computed tomography. Results Dp-ucMGP was elevated in Covid-19 patients compared to controls (P=0.001). Higher dp-ucMGP was found in Covid-19 patients with poor compared to better outcomes (P=0.002). PIVKA-II was normal in 81.8%, mildly elevated in 14.0% and moderately elevated in 4.1% of Covid-19 patients not using vitamin K antagonists. Dp-ucMGP in Covid-19 patients was correlated with desmosine (P<0.001), thoracic aortic calcification (P<0.001) but not with pneumonia severity. Conclusions: Extrahepatic vitamin K status was severely reduced in Covid-19 patients, as reflected by elevated inactive MGP, and related to poor outcome. Procoagulant prothrombin activity remained preserved in the majority of Covid-19 patients, which is compatible with the increased thrombogenicity that is frequently observed in severe Covid-19. Impaired MGP activation was linked to accelerated elastic fiber degradation and premorbid vascular calcifications. A trial should assess whether increasing MGP and protein S activity by vitamin K administration improves Covid-19 outcomes.

The current study assessed the influence of Anti Stripping Agents (ASA), Ground Tire Rubber (GTR) and waste polyethylene terephthalate (PET) on performance behavior of binder and Stone Matrix Asphalt (SMA) mixtures. Through this paper, the 85/100 penetration grade bitumen was utilized as original bitumen. Also, three liquid ASA’s (ASA (A), ASA (B), ASA (C)) were used as a mixture modifier. For this purpose, softening point, penetration, rotational viscosity, Dynamic Shear Rheometer, Multi Stress Creep Recovery (MSCR) and Linear Amplitude Sweep (LAS) tests were implemented to investigate the rheological properties of modified bitumen. For evaluating the behavior of modified mixtures several tests such as; Resilient Modulus, Tensile Strength, dynamic creep, wheel track and four-point beam fatigue tests were implemented. Based on MSCR test results, utilization of mentioned polymers enhanced the elasticity of bitumens and therefore the permanent deformation resistance of binders increases. Also by the addition of PET percentage, the rutting resistance improves. Results indicated that utilization of ASAs, PET and Crumb Rubber (CR) enhance the Resilient Modulus (Mr), Indirect Tensile Strength (ITS), rutting resistance, fatigue life and Fracture Energy (FE) of asphalt mixtures. Also based on results, modification of binder by PET/CR with a ratio of 50%/50% and ASA (B) have the highest fatigue life which indicates that this mixture has highest resistance against fatigue cracking.

The article shows materials to the question about algebraic features of the genetic code and about the dictatorial influence of the DNA and RNA molecules on the whole organism. Presented results testify in favor that the genetic code is an algebraic code related with a wide class of algebraic codes, which are a basis of noise-immune coding of information in communication technologies. Structural features of the genetic systems are associated with hypercomplex double (or hyperbolic) numbers and with bisymmetric doubly stochastic matrices. The received results confirm that represented matrix approaches are effective for modeling genetic phenomena and revealing the interconnections of structures of biological bodies at various levels of their organization. This allows one to think that living organisms are algebraically encoded entities where structures of genetic molecules have the dictatorial influence on inherited structures of the whole organism. New described algebraic approaches and results are discussed.

A predictive approach to the phase behavior of four-component poly-mer-water-surfactant-electrolyte systems is formulated, by viewing the four-component system as a binary polymer-pseudosolvent system, with the pseudosolvent representing water, surfactant, and the electrolyte. The phase stability of this binary system is examined using the framework of the lattice fluid model of Sanchez and Lacombe. In the lattice fluid model, a pure component is represented by three equation of state parameters, the hard-core volume of a lattice site ( ), the number of lattice sites occupied by the component (r) and its characteristic energy ( ). We in-troduce the extra thermodynamic postulate that r and for the pseudosolvent are the same as for water and all surfactant-electrolyte composition dependent characteristics of the pseudosolvent can be represented solely through its characteristic energy parameter. The key implication of the postulate is that the phase behavior of polymer-pseudosolvent systems will be identical for all pseudosolvents with equal values of the characteristic energy, despite their varying real compo-sitions. Based on the pseudosolvent model, illustrative phase diagrams have been computed for several four-component systems containing alkyl sulfonate/sulfate surfactants, electrolytes and anionic or nonionic polymers. The pseudosolvent model is shown to describe all important trends in experimentally observed phase behavior, pertaining to polymer and surfactant molecular characteristics. Most importantly, the pseudosolvent model allows one to construct a priori phase diagrams for any polymer-surfactant-electrolyte system, knowing just one experimental com-position data for a system at the phase boundary, using available thermodynamic data on sur-factants and electrolytes and without requiring any information on the polymer.

Theoretical and experimental approaches have been applied to study the polymer physics under-lying compaction of DNA in the bacterial nucleoid. Knowledge of the compaction mechanism is necessary to obtain a mechanistic understanding of the process of segregation of replicating chromosome arms (replichores) during the cell cycle. In the first part of this review light microscope observations are discussed that have demonstrated that the nucleoid has a lower refractive index and thus a lower density than the cytoplasm. A polymer-physical explanation for this phenomenon was given by the theory of Theo Odijk pro-posed in 1998. By assuming a phase separation between nucleoid and cytoplasm and by imposing equality of osmotic pressure and chemical potential between the two phases, a minimal energy situation is obtained in which soluble proteins are depleted from the nucleoid, thus explaining its lower density. The theory is compared with recent views for DNA compaction that are based on mere exclusion of polyribosomes from the nucleoid or on the transcriptional activity of the cell. These new views raise the question of whether they can still explain the lower refractive index or density of the nucleoid. In the second part of this review the question is discussed how DNA segregation occurs in Esche-richia coli, in the absence of the so-called active ParABS system, present in the majority of bacteria. How is entanglement prevented of nascent chromosome arms, generated at the origin in the pa-rental network of the E. coli nucleoid? The observations of the groups of Sherratt and Hansen in 2006, that the four nascent chromosome arms synthesized in the initial replication bubble, segre-gate to opposite halves of the sister nucleoids implies that extensive intermingling of daughter strands does not occur. Based on the hypothesis that leading and lagging replichores synthesized in the replication bubble, fold into micro-domains that do not intermingle, a passive "four-excluding-arms model" for segregation is proposed. This model implies that the key for seg-regation already lies in the structure of the replication bubble at the very start of DNA replication; it explains the different patterns of chromosome arms as well as the segregation distances between replicated loci as experimentally observed.

In view of the complexity of the pile foundation underpinning structure system and the stringent requirements of the construction process, this paper briefly describes the necessity of introducing epoxy resin reinforcing adhesive of planting rebar in the design of pile foundation underpinning beam structure to im-prove the mechanical properties of the underpinning beam new and old concrete joint surfaces and proposes a new type of pile foundation underpinning beam system construction method by “chiseling + prestressed reinforcement + epoxy resin reinforcing adhesive”. This paper uses an actual pile foundation underpinning project of an urban overpass as a prototype, designs and creates a model structure with a similarity ratio of 1/6, and performs repeated pro-gressive static loading tests to study the load carrying capacity, displacement change, and other properties of the underpinning structure, as well as analyses and distorts the overall working performance and failure mode of them. On this basis, the prototype structure's finite element analysis model was built, and the finite element analysis results were compared with the test results to get the mechanical properties and deformation characters of the actual pile foundation under-pinning structure system corresponding to the actual underpinning beam load. This paper's study can lay the theoretical and experimental foundation for the smooth development of similar projects.

Antibody-mediated targeting is an efficient strategy to enhance the specificity and selectivity of polymer nanomedicines towards the target site, typically a tumor. However, direct covalent coupling of an antibody with a polymer usually results in a partial damage of the antibody binding site accompanied with a compromised biological activity. Here, an original solution based on well-defined non-covalent interactions between tris-nitrilotriacetic acid (trisNTA) and hexahistidine (His-tag) groups, purposefully introduced to the structure of each macromolecule, is described. Specifically, trisNTA groups were attached along the chains of a hydrophilic statistical copolymer based on N-(2-hydroxypropyl)methacrylamide (HPMA), and at the end or along the chains of thermo-responsive di-block copolymers based on N-isopropylmethacrylamide (NIPMAM) and HPMA; His-tag was incorporated to the structure of a recombinant single chain fragment of an anti-GD2 monoclonal antibody (scFv-GD2). Static and dynamic light scattering analyses confirmed that mixing of polymer with scFv-GD2 led to the formation of polymer/scFv-GD2 complexes; those prepared from thermo-responsive polymers formed stable micelles at 37 °C. Flow cytometry and fluorescence microscopy clearly demonstrated antigen-specific binding of the prepared complexes to GD2 positive murine T-cell lymphoma cells EL-4 and human neuroblastoma cells UKF-NB3, while no interaction with GD2 negative murine fibroblast cells NIH-3T3 was observed. These non-covalent polymer protein complexes represent a new generation of highly specific actively targeted polymer therapeutics or diagnostics.

Bone tissue engineering has developed significantly in recent years as the increasing demand for bone substitutes due to trauma, cancer, arthritis, and infections. The scaffolds for bone regeneration need to be mechanically stable and have a 3D architecture with interconnected pores. With the advances in additive manufacturing technology, these requirements can be fulfilled by 3D printing scaffolds with controlled geometry and porosity using a low-cost multistep process. The scaffolds, however, must also be bioactive to promote the environment for the cells to regenerate into bone tissue. To determine if a low-cost 3D printing method for bespoke SiOC(N) porous structures can regenerate bone these structures were tested for osteointegration potential by using human mesenchymal stem cells (hMSCs). This includes checking the general biocompatibilities under the osteogenic differentiation environment (cell proliferation and metabolism). Moreover, cell morphology was observed by confocal microscopy and gene expressions on typical osteogenic markers at different stages for bone formation were determined by real-time PCR. The results of the study showed the pore size of the scaffolds had a significant impact on differentiation. A certain range of pore size could stimulate osteogenic differentiation, thus promoting bone regrowth and regeneration.

Abstract: We review the development and application of an organic polymer-gel capable of producing fixed, three-dimensional fluorescent images of complex radiation fields. The gel consists for more than 99% of γ-ray-polymerized (~15% conversion) tertiary-butyl acrylate (TBA) containing ~100 ppm of a fluorogenic compound, e.g. maleimido-pyrene (MPy). The radio-fluorogenic effect depends on copolymerization of the MPy into growing chains of TBA on radiation-induced polymerization. This converts the maleimido residue, which quenches the pyrene fluorescence, into a succinimido moeity (SPy), which doesn't. The intensity of the fluorescence is proportional to the yield of free-radicals formed and hence to the local dose deposited. Because the SPy moieties are built into the cross-linked polymer matrix the image is fixed. The method of preparing the gel and imaging the radiation-induced fluorescence are presented and discussed. The effect is illustrated with fluorescent images of the energy deposited in the gel by beams of X-rays, electrons and protons as well as a radioactive isotope.

We introduce optically clear and resilient free-form micro-optical of pure (non-photosensitized) organic-inorganic SZ2080 material made by femtosecond 3D laser lithography (3DLL). This is advantageous for rapid printing of 3D micro-/nanooptics, including their integration directly onto optical fibers. A systematic study on the fabrication peculiarities and quality of resultant structures is performed. Comparison of microlenses’ resiliency to CW and femtosecond pulsed exposure is determined. Experimental results prove that pure SZ2080 is ∼3 fold more resistant to high irradiance as compared with a standard photo-sensitized material and can sustain up to 1.91 GW/cm² intensity. 3DLL is a promising manufacturing approach for high-intensity micro-optics for emerging fields in astro-photonics and atto-second pulse generation. Additionally, pyrolysis is employed to shrink structures up to 40% by removing organic SZ2080 constituents. This opens a promising route towards downscaling photonic lattices and creation of mechanically robust glass-ceramic structures.

In Indonesia, types of meat are still identified manually due to increasing prices for beef and buf-falo ahead of Idul Fitri. Traders mix beef with pork to thwart the beef scam. Haar wavelet and GLCM, GLCM with angles of 0°, 45°, 90°, and 135°, as well as matrices using contrast, correlation, energy, homogeneity, and entropy, are used in feature extraction. The following are the results of meat image classification testing using k-NN, Haar wavelet, and GLCM: The k-NN algorithm shows superiority in identifying fresh (99%), frozen (99%), and rotten (96%) meat texture images with the most fantastic accuracy results in every situation. Meanwhile, GLCM routinely provides good results, especially regarding the texture image of fresh meat (183.21) and rotten meat (115.79). However, despite delivering less throughput than k-NN and GLCM, Haar wavelets are still helpful, especially when dealing with fresh meat texture images (89,96).

Manufacturing environments, characterized by rapid, unpredictable changes, uncertainties, risks, and uncontrollable fluctuations, pose significant challenges to minimizing disruptions in processes. This study introduces an innovative approach that prioritizes curbing risk propagation among processes to enhance robustness. It emphasizes the integration of engineering management principles and modular design within manufacturing. Adopting a system engineering perspective, all manufacturing process activities are viewed as interrelated components within a unified system. By employing Axiomatic Design (AD) theory and the Design Structure Matrix (DSM) method, manufacturing process architecture is modularized, yielding heightened robustness. The proposed mathematical model equips engineering and manufacturing managers with a potent tool for designing robust processes while adeptly managing system complexity. The study's outcomes underscore a substantial enhancement in modularization, leading to elevated overall robustness in manufacturing processes. To validate the methodology, the architectural design of manufacturing processes is examined in a real-case scenario, specifically the Barez Industrial Group in Iran. This verification substantiates the 'manufacturing processes' of the case, presenting an optimally modularized architecture. The results affirm the proposed approach's efficacy, demonstrating improved modularization that contributes to bolstered robustness in manufacturing processes.

The role of initial state (ISI) and final state (FSI) ion–ion interactions in heavy ion double charge exchange (DCE) reactions A(Z,N)→A(Z±2,N∓2) are studied in the context of double single charge exchange (DSCE) reactions given by sequential actions of the isovector nucleon–nucleon (NN) T–matrix. The second order DSCE reaction amplitude is investigated in momentum representation in a formulation, focused on the extraction of nuclear matrix elements under the conditions of strong initial state (ISI) and final state (FSI) interactions. In closure approximation and using the momentum representation, the reaction amplitude is finally separated into ISI/FSI distortion coefficients and reaction kernels and nuclear matrix elements. The ISI/FSI reaction kernels emerge as the result of the repeated scattering on the avoided volume, introduced by the imaginary parts of the ion–ion optical potential and acting as sinks for the quantal probability current. The closure approximation allows derive a set of induced effective two–body isotensor interactions, given by products of spin–scalar, spin–vector central and rank–2 spin–tensor interactions. The intermediate propagator plays a key role in establishing correlation between the DCE transitions in the projectile and target nucleus. The presented approach emphasizes the special features of DSCE reaction dynamics as proceeding like a system of two coupled isospin dipoles whose strengths are determined by the momentum-space form factors of the NN isovector interaction. The properties of the DSCE interaction form factors are investigated and the approach is applied to data.

A robust explicit model predictive control (EMPC)-based frequency adaptive grid voltage sensorless control is developed for a grid-connected inverter (GCI) via a linear matrix inequality (LMI) approach under the model parameter uncertainties and non-ideal grid environment. The control scheme is achieved by an enhanced prediction model rather than the conventional prediction model provided by fixed parameters to maintain the quality of grid currents injected into the grid when the model parameters are varied. Furthermore, an LMI-based observer is integrated with the disturbance observer to improve the reference tracking performance and reject disturbances. The proposed observer is employed for the grid frequency adaptive control without need of grid voltage sensors. The proposed current controller and observer employ the LMI scheme to maintain a stable and robust operation of the GCI. The discrete-time frequency response and pole-zero map analyses are used to investigate system stability and robustness against parameter uncertainties. Comprehensive simulation, experimental results and analyses clearly demonstrate the robustness of the proposed control scheme under various adverse test conditions with unexpected grid and system uncertainties.

Abstract Big datasets are becoming increasingly common and can be challenging to understand and apply in public health. One method for lowering the dimensionality of these datasets and improving interpretability while minimizing information loss is data reduction using principal component analysis (PCA). It achieves this by successively maximizing variance through the creation of new, uncorrelated variables. PCA is an adaptive data analysis technique because it simplifies the process of finding new variables, or principal components, by solving an eigenvalue or eigenvector problem. These new variables are determined by the dataset being used, rather than by the analyst starting from scratch. It is also adaptable in another way because varieties of the method have been designed to adjust to various data structures and types. However, there are serious problems in the theoretical understanding and practical application of PCA in public health researchers, whereas its application is becoming popular in developing countries. Therefore, this article, which concentrated on using PCA to reduce data, began by outlining the fundamental concepts of PCA and going over what it can and cannot do, as well as when and how to use it. We also discussed the fundamental assumptions, benefits, and drawbacks of PCA. Furthermore, this article demonstrated and resolved PCA practical application problems in public health that most scholars are unaware of, such as variable preparation, variable inclusion and exclusion criteria for PCA, iteration steps, wealth index analysis, interpretation, and ranking.

In this paper, experimental results about the performance of a Takagi-Sugeno Fuzzy Controller (TSFC) for an EV3 Ballbot Robotic System (EV3BRS) are reported. The physical configuration for the EV3BRS has the form of an inverted pendulum mounted on a ball. The EV3BRS is an underactuated robotic system with four outputs and two control torques. The Takagi-Sugeno Fuzzy Model (TSFM) design comes from linearization of the nonlinear model around two operation points near from the upright position of the EV3BRS's body. The Parallel Distributed Compensation (PDC) approach is used to the design of the TSFC. The Linear Matrix Inequalities (LMIs) approach is used to get the feedback gains for every local linear controller guaranteeing global asymptotically stability, via a more relaxed stability condition, of the overall fuzzy control system. Measurement and control data from and to the EV3BRS are transferred via telecontrol and telemetry.

In this paper, we demonstrate a useful interaction between the theory of clique partitions, edge clique covers of a graph, and the spectra of graphs. Using a clique partition and an edge clique cover of a graph we introduce the notion of a vertex-clique incidence matrix for a graph and produce new lower bounds for the negative eigenvalues and negative inertia of a graph. Moreover, utilizing these vertex-clique incidence matrices, we generalize several notions such as the signless Laplacian matrix, and develop bounds on the incidence energy and the signless Laplacian energy of the graph. %The tight upper bounds for the energies of a graph and its line graph are given. More generally, we also consider the set $S(G)$ of all real-valued symmetric matrices whose off-diagonal entries are nonzero precisely when the corresponding vertices of the graph are adjacent. An important parameter in this setting is $q(G)$, and is defined to be the minimum number of distinct eigenvalues over all matrices in $S(G)$. For a given graph $G$ the concept of a vertex-clique incidence matrix associated with an edge clique cover is applied to establish several classes of graphs with $q(G)=2$.

Vitamin K occupies a unique and often obscured place among its fellow fat-soluble vitamins. Evidence is mounting however, that vitamin K (VK) may play an important role in the visual system apart from the hepatic carboxylation of hemostatic related proteins. However, to our knowledge, no review covering the topic has appeared in the medical literature. Recent studies have confirmed that matrix Gla protein (MGP), a vitamin K-dependent protein (VKDP), is essential for the regulation of intraocular pressure in the mouse. The PREDIMED (Prevención con Dieta Mediterránea) study, a randomized trial involving 5860 adults at risk for cardiovascular disease, demonstrated a 29% reduction in the risk of cataract surgery in participants with the highest tertile of dietary vitamin K1 (PK) intake compared with the lowest tertile. However, the specific requirements of the eye and visual system (EVS) for VK, and what might constitute an optimized VK status, is currently unknown and largely unexplored. It is the intention therefore of this narrative review to provide an introduction concerning VK and the visual system, review ocular VK biology, and to provide some historical context to recent discoveries. Potential opportunities and gaps in current research efforts will be touched upon, in the hope of raising awareness, and encouraging continued VK related investigations in this important and highly specialized sensory system.

Various factors, such as uncertainty of component parameters and uncertainty of sensor meas-urement values, contribute to the difficulty of fault detection in the landing gear retrac-tion/extension hydraulic system. In this paper, we introduce linear fractional transformation technology and uncertainty analysis theory for the construction of the diagnostic bond graph of the landing gear retraction/extension hydraulic system. In this way, interval analytical redundancy relations and fault signature matrix can be derived. Using the fault signature matrix, existing faults of the system can be preliminarily detected and isolated. Additionally, interval analytical re-dundancy relations can be used to detect system faults in detail, and cases analysis can be carried out to determine if the actuator is externally or internally leaky, and if the landing gear selector valve is reversing stuck. Compared to the traditional analytical redundancy relations, this method takes into account the negative factors of uncertainty; and compared to the traditional absolute diagnostic threshold, the interval diagnostic threshold is more accurate and sensitive.

3D Zernike moments based on 3D Zernike polynomials have been successfully applied to the field of voxelized 3D shape retrieval and have attracted more attention in biomedical image processing. As the order of 3D Zernike moments increases, both computational efficiency and numerical accuracy decrease. Due to this phenomenon, a more efficient and stable method for computing high-order 3D Zernike moments was proposed in this study. The proposed recursive formula for computing 3D Zernike radial polynomials combines the recursive calculation of spherical harmonics to develop a voxel-based algorithm for the calculation of 3D Zernike moments. The algorithm was applied to the 3D shape Michelangelo's David with a size of 150×150×150 voxels. As compared to the method without additional acceleration, the proposed method uses a group action of order sixteen orthogonal group and saving unnecessary iterations, the factor of speed-up is 56.783±3.999 when the order of Zernike moments is between 10 and 450. The proposed method also obtained an accurate reconstructed shape with the error rate (normalized mean square error) of 0.00 (4.17×10^-3) when the reconstruction was computed for all moments up to order 450.

The notion of potential-growth indicator came to being in the field of matrix population models long ago, almost simultaneously with the pioneering Leslie model for age-structured population dynamics, albeit the term has been given and the theory developed only recent years. The indicator represents an explicit function, R(L), of matrix L elements and indicates the position of the spectral radius of L relative to 1 on the real axis, thus signifying the population growth, or decline, or stabilization. Some indicators turned out useful in theoretical layouts and practical applications prior to calculating the spectral radius itself. The most senior (1994) and popular indicator, R0(L), is known as the net reproductive rate, and we consider two more ones, R1(L) and RRT(A), developed later on. All the three are different in what concerns their simplicity and the level of generality, and we illustrate them with a case study of Calamagrostis epigeios, a long-rhizome perennial weed actively colonizing open spaces in the temperate zone. While the R0(L) and R1(L) fail respectively because of complexity and insufficient generality, the RRT(L) does succeed, justifying the merit of indication.

SARS-CoV-2 was empirically and computationally found to be of a specific but peculiar evolution. Shell disorder models found that the outer shell (M protein) of SARS-CoV-2 to be among the hardest in its CoV family. The hard outer shell (low M percentage of disorder (PID)) is likely to be related to the SARS-CoV-2 resistance to the antimicrobial enzymes in saliva and mucus, and be responsible for the high-level of viral shedding which has been observed clinically. Experimental studies have also shown that SARS-CoV-2 is more resilient in the environment than many other CoVs, including SARS-CoV-1. Another aspect of the shell disorder models predicts that SARS-CoV-1 is more virulent than SARS-CoV-2 because of higher inner shell disorder (N PID) that helps SARS-CoV-1 replicate faster in vital organs despite being of lesser viral loads in the saliva and mucus, unlike SARS-CoV-2. This has been reaffirmed experimentally, where higher levels (50 folds) of infectious particles were detected in the SARS-CoV-1 samples in comparison with those of SARS-CoV-2. The hard outer shell of SARS-CoV-2 has been found to be associated with burrowing animals, particularly pangolins, which are often in contact with buried feces. For these reasons, the M protein is highly conserved among close relatives of SARS-CoV-2. The phylogenetic tree using M, unlike the genome-wide one, shows that pangolin-CoVs are more closely related to SARS-CoV-2 than bat-RaTG13. Previous phylogenetic studies may have been confused by recombinations that are usually poorly handled. According to the shell disorder models based on the N PID, an attenuated COVID-19 strain is likely to have entered humans via pangolins in 2017 or before, which provides the virus enough time to adapt to humans. This could explain why the SARS-CoV-2 S protein is highly adapted to the human ACE-2. The specific but peculiar evolution has a wide range of clinical, immunological, and epidemiological implications.

We construct admissible circulant Laplacian matrix functions as generators for strictly increasing random walks on the integer line. These Laplacian matrix functions refer to a certain class of Bernstein functions. The approach has connections with biased walks on digraphs. Within this framework, we introduce a space-time generalization of the Poisson process as a strictly increasing walk with discrete Mittag-Leffler jumps subordinated to a (continuous-time) fractional Poisson process. We call this process ‘space-time Mittag-Leffler process’. We derive explicit formulae for the state probabilities which solve a Cauchy problem with a Kolmogorov-Feller (forward) difference-differential equation of general fractional type. We analyze a “well-scaled” diffusion limit and obtain a Cauchy problem with a space-time convolution equation involving Mittag-Leffler densities. We deduce in this limit the ‘state density kernel’ solving this Cauchy problem. It turns out that the diffusion limit exhibits connections to Prabhakar general fractional calculus. We also analyze in this way a generalization of the space-time fractional Mittag-Leffler process. The approach of construction of good Laplacian generator functions has a large potential in applications of space-time generalizations of the Poisson process and in the field of continuous-time random walks on digraphs.

The method for quantitative analysis is based on the direct measurement of the analyte using differential pulse voltammetry (DPV), exploiting its oxidation peak. Calibration curves are set up to evaluate the figures of merit of the analytical method (LOD, LOQ, linear range). The application of the sensor for the dosing of GA in real matrices is carried out by analyzing non-alcoholic and alcoholic beverages and comparing the results with those reported in the literature and with the content of total polyphenols determined by the Folin-Ciocalteu method. In all cases, concentrations of GA align with those previously found in the literature for the beverages examined. Moreover, the values are always lower than the total polyphenols content; this demonstrates the good selectivity of the sensor that can discriminate the target molecule from other polyphenols present.

Recent simulation studies have revealed a wealth of distinct crystal polymorphs encountered in the self-organization of polymer systems driven by entropy or free energy. The present analysis, based on the concept of self-avoiding random walks on crystal lattices, is useful to calculate upper bounds for the entropy difference of the crystals that are formed during polymer crystallization and thus provide predictions on polymorph thermodynamic stability. Here, we compare two pairs of crystals sharing the same coordination number, ncoord: hexagonal close packed (HCP) and face centered cubic (FCC), both having ncoord = 12 and the same packing density, and the less dense hexagonal (HEX) and body centered cubic (BCC) lattices, with ncoord = 8. In both cases, once a critical step length is reached, one of the crystals shows a higher number of SAWs compatible with the crystal. We explain the observed trends in terms of the bending and torsion angles corresponding to the different chain geometry as imposed by the geometric constraints of the crystal lattice.

The present article addresses the long-standing problem of the polymer brush bilayers under stationary shear flow at non-linear response regime where the system gets a non-Newtonian fluid. The main idea behind this research would be the fact that the immense lubricity of the polymer brush bilayers originates from a global restructuring that takes place at large shear rates. It is shown here that physical quantities like, stress tensor, viscosity tensor, the friction coefficient and the chain extensions could become dependent on the shear rate at non-Newtonian regime. Apparently, the sub-linear scaling of the physical quantities at large shear rates is solely due to the fact that the chains stretch in the shear direction.

The self-assembly is an intriguing process of great importance in general soft matter and thus re-ceives an ever-growing scientific interest. Its most trivial example is the entropy-driven crystalli-zation of hard spheres. Past works have established the similarities and differences in the phase behavior of monomers and chains made of hard spheres. In the present work, inspired by the dif-ference in the melting points of the pure components, we study, through Monte Carlo simulations, the phase behavior of athermal mixtures composed of fully flexible polymers and individual monomers of uniform size. We analyze how the relative number fraction and the packing density affect crystallization and the established ordered morphologies. A synergetic effect is observed in the crystallization leading to synchronous crystallization of the two species. Structural analysis of the resulting ordered morphologies shows perfect mixing and thus no phase separation, which could split the system into polymer-rich and monomer-rich domains. Due to the constraints imposed by chain connectivity, the local environment of the individual spheres is systematically more spherical and more symmetric compared to the one of spheres belonging to chains. In general, increasing polymer content leads to reduction of the degree of crystallinity. According to the present findings, relative concentration is another determining factor to control the phase behavior of hard colloidal systems based on polymers.

Water electrolysis provides efficient and cost-effective production of hydrogen from renewable energy. Currently, the oxidation half-cell reaction relies on noble-metal catalysts, impeding widespread application. In order to adopt water electrolyzers as the main hydrogen production systems, it is critical to develop inexpensive and earth-abundant catalysts. This review discusses the proton exchange membrane (PEM) water electrolysis (WE) and the progress in replacing the noble-metal catalysts with earth-abundant ones. Researchers within this field are aiming to improve the efficiency and stability of earth-abundant catalysts (EACs), as well as to discover new ones. The latter is particularly important for the oxygen evolution reaction (OER) under acidic media, where the only stable and efficient catalysts are noble-metal oxides, such as IrO_x and RuO_x. On the other hand, there is significant progress on EACs for the hydrogen evolution reaction (HER) in acidic conditions, but how many of these EACs have been used in PEM WEs and tested under realistic conditions? What is the current status on the development of EACs for the OER? These are the two main questions this review addresses.

This study examined the patterns of epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1) deposition in the small intestine and colon to evaluate the association between histopathological severity of EFEMP1 deposition and constipation and determine if amyloid transthyretin (ATTR) and EFEMP1 deposits can colocalize. In 40 older cases (≥80 years of age), EFEMP1 deposition in the small intestine initiated in the submucosal and subserous vessels, subserous interstitium, and serosa (early stage); progressing to the muscularis propria and peri-Auerbach plexus area (intermediate stage); and finally, spreading diffusely to areas, excluding the mucosa and muscularis mucosa (advanced stage). The colon had a similar pattern of progression. During the middle-to-advanced stages, amyloid formation was observed in some vascular and serous deposits. We identified a subgroup of cases in which EFEMP1 deposition was the only presumed cause of constipation. Additionally, we demonstrated the colocalization of ATTR and EFEMP1 deposition. Apple-green birefringence was detected under polarized light only in approximately one-half of the cases in the small intestine and one-third of the cases in the colon. These findings emphasize that EFEMP1 deposits may be associated with lower gastrointestinal pathological conditions. Given the challenges of histopathological diagnosis on Congo red-stained specimens, we recommend the combined use of elastic fiber staining and immunohistochemistry for EFEMP1 to prevent overlooking this deposition.

Candidiasis is one of the global public health problems. In fluconazole resistant Candida spp. (FRCS), mutations in ergosterol biosynthesis gene 11 (ERG 11) have been commonly found. This study aimed to determine the profile of FRCS isolates and to detect mutations in part of ERG 11 gene in fluconazole resistant Candida albicans (FRCA) isolates. Study was conducted on 150 isolates of FRCS obtained from patients admitted in a tertiary care hospital, South India from September 2019 to December 2021. Candida spp. was identified by MALDI-TOF MS and fluconazole resistance was detected by VITEK 2 system. Following which a part of the ERG 11 gene of the FRCA isolates were amplified, purified, sequenced and a phylogenetic tree was constructed. Out of the 150 FRCS, the most common FRCS was C. auris followed by C. glabrata, C. krusei, C. parapsilosis, C. albicans, C. tropicalis and C. guilliermondii. Sequencing of amplicons detected a single missense mutation and 44 silent mutations. We opined that fluconazole resistance in FRCA isolates may be due to mecha-nisms other than the studied one in our region. Phylogenetic analysis of amplified sequences of 12 FRCA isolates observed three clusters and all 12 sequences showed relatedness to Malaysian 2019 isolates.

Chronic kidney disease (CKD) is a progressive condition of kidney dysfunction due to diverse causes of injury. In healthy kidneys, protein-bound uremic toxins (PBUTs) are cleared from the systemic circulation by proximal tubule cells through the concerted action of plasma membrane transporters that facilitate their urinary excretion, but the endogenous metabolites are hardly removed with kidney dysfunction and may contribute to CKD progression. Accumulating evidence suggests that senescence of kidney tubule cells influences kidney fibrosis, the common endpoint for CKD with an excessive accumulation of extracellular matrix (ECM). Senescence is a special state of cells characterized by permanent cell cycle arrest and limitation of proliferation, which promotes fibrosis by releasing senescence-associated secretory phenotype (SASP) factors. The accumulation of PBUTs in CKD causes oxidative stress and increases the production of inflammatory (SASP) factors that could trigger fibrosis. Recent studies provide some clues that PBUTs may also promote senescence in kidney tubular cells. This review provides an overview on how senescence contributes to CKD and the involvement of PBUTs in this process, and how kidney senescence can be studied, Finally, some suggestions for future therapeutic options for CKD while targeting senescence are given.

In light of the current situation where no testing equipment is available for measuring thermal deformation of objects, this paper proposes a novel method for accurate and precise measurement. The method overcomes the limitations of previous approaches that relied on pitch angle. By utilizing the principle of biplane multiple reflections, a bivariate laser spot displacement analysis algorithm is devised to attain highly precise measurements of bivariate angles. Additionally, a temperature gradient comparison algorithm is introduced to calculate the indicator test results under specific temperature conditions. To validate the effectiveness and reliability of this method, a testing system is constructed and utilized. The results demonstrate that the thermal deformation angle change test achieves an impressive accuracy of 0.015″ and a rate of thermal deformation angle change of 0.3247″/°C. These values are in close agreement with the previously simulated analysis result of 0.359″/°C, with only a relative error of 9.55%. Therefore, the test results confirm the efficacy and reliability of this testing method along with the feasibility of the algorithm processing.

The extracellular matrix (ECM) is earning an increasingly relevant role in many disease states and the process of aging. Analyzing these disease states is possible with GWAS and PheWAS methodology, and through our analysis, we aimed to explore the relationships between polymorphisms in the compendium of ECM genes (i.e., matrisome genes) in various disease states. A significant contribution on the part of the ECM polymorphisms is evident in many varying types of diseases, particularly those in the core matrisome genes. Our results confirm previous links to connective tissue disorders, but also unearth new and underexplored relationships with neurological, psychiatric, and age-related disease states. Upon analysis of drug indications for gene-disease relationships, we identified numerous targets that may be repurposed for age-related pathology. The identification of ECM polymorphisms and their contribution to disease plays an integral role in future therapeutic developments, drug repurposing, precision medicine, and personalized care.

Galectins are β-galactosyl-binding proteins that fulfill essential physiological functions. Recently, we introduced galectin-1 (Gal-1) and galectin-3 (Gal-3) as fusion proteins of a His6-tag, a SNAP-tag, and a fluorescent protein. We characterized their binding in ELISA-type assays and their application in cell-surface binding. In the present study, we have constructed further fusion proteins of galectins with fluorescent protein color code. The fusion proteins of Gal-1, Gal-3, and Gal-8 were purified by affinity chromatography. For this, we have prepared glycoprotein affinity resins based on asialofetuin (ASF) and fetuin and combined this in a two-step purification with Immobilized Metal Affinity chromatography (IMAC) to get pure and active galectins. Purified galectin fractions were analyzed by size-exclusion chromatography. The binding characteristics to ASF of solely His6-tagged galectins and galectin fusion proteins were compared. As an example, we demonstrate a 1.6-3-fold increase in binding efficiency for HSYGal-3 (His6-SNAP-yellow fluorescent protein-Gal-3) compared to the HGal-3 (His6-Gal-3). Our results reveal an apparent higher binding efficiency for galectin SNAP-tag fusion proteins compared to His6-tagged galectins which are independent of the purification mode. This is also demonstrated by the binding of galectin fusion proteins to extracellular glycoconjugates laminin, fibronectin, and collagen IV. Our results indicate the probable involvement of the SNAP-tag in apparently higher binding signals, which we discuss in this study.

Ongoing COVID-19 Pandemic has resulted into massive damage to various platforms of global economy which has caused disruption to human livelihood. Natural Language Processing has been extensively used in different organizations to categorize sentiments, perform recommendation, summarizing information and topic modelling. This research aims to understand the non-medical impact of COVID-19 on global economy by leveraging the natural language processing methodology. This methodology comprises of text classification which includes topic modelling on unstructured COVID-19 media articles dataset provided by Anacode. Like other Natural Language Processing algorithms, Latent Dirichlet allocation (LDA) and Non-negative matrix factorization (NMF) has been proposed to classify the media articles dataset in order to analyze COVID-19 pandemic impacts in the different sectors of global economy. Model Accuracy was examined based on the coherence and perplexity score which came out to be 0.51 and -10.90 using LDA algorithm. Both the LDA and NMF algorithm identified similar prevalent topics that was impacted by COVID-19 pandemic in multiple sectors of economy. Through intertopic distance map visualization produced by LDA algorithm, it can be reciprocated that general industries which includes children schooling, parental care, and family gatherings had the major impact followed by business sector and the financial industry.

Matrix metalloproteinase 3 (MMP3) plays multiple roles in pro-tumorigenic proteolysis and in intracellular transcription. These include inducing connective tissue growth factor [CTGF, also known as cellular communication network factor 2 (CCN2)] and prompting a new definition of MMP3 as a moonlighting metalloproteinase. Members of the MMP family have been found within tumor-derived extracellular vesicles (EVs) such as oncosomes or exosomes. We here investigated the roles of MMP3-rich oncosomes in tumor progression, molecular transmission, and gene regulation. MMP3 and CCN2/CTGF were significantly co-expressed in tumor samples derived from patients suffering from colorectal adenocarcinoma. We found that oncosomes derived from a rapidly metastatic colon cancer cells (LuM1) were enriched in MMP3 and a C-terminal half fragment of CCN2/CTGF. MMP3-rich oncosomes were highly transmissive into recipient cells and were pro-tumorigenic in an allograft mouse model. Oncosome-derived MMP3 was transmissive into recipient cell nuclei, trans-activated CCN2/CTGF promoter, and induced CCN2/CTGF production at 1 to 6 hours after the addition of oncosomes to culture media. In addition, CRISPR/Cas9-mediated knockout of MMP3 showed significant anti-tumor effects, including inhibition of migration and invasion of LuM1 cells in vitro, inhibition of tumor growth in vivo, and reduction of CCN2/CTGF and its promoter activity in vitro. These data newly demonstrate that the oncosome-derived moonlighting metalloproteinase promotes metastasis and is pro-tumorigenic at distant sites as well as a transmissive trans-activator for the cellular communication network gene.

In computer networks, loss of data packets is inevitable, in particular, because of the buffer memory overflow of at least one of the nodes located on the path from the source to the receiver, including the latter. Such losses associated with overflows are hereinafter referred to as congestion of network nodes. There are many ways to prevent and eliminate overloads; these methods, in the majority, are based on the management of data flows. A special place is taken by the maintenance of packages, taking into account their priorities. The article considers a number of original technical solutions to improve the quality of control and reduce the required amount of buffer memory of network nodes. The ideas of these solutions are quite simple for their implementation in the development of appropriate software and hardware for telecommunication devices.

Detecting volatile organic compounds (VOCs) emitted from different plant species and their or-gans can provide valuable information about plant health and environmental factors that affect them. For example, limonene emission can be a biomarker to monitor plant health and detect stress. Traditional methods for VOC detection encounter challenges, prompting the proposal of novel approaches. In this study, we proposed integrating electrospinning, molecular imprinting, and conductive nanofibers to fabricate limonene sensors. In detail, polyvinylpyrrolidone (PVP) and polyacrylic acid (PAA) served here as fiber and cavity formers, respectively, with multi-walled carbon nanotubes (MWCNT) enhancing conductivity. We developed one-step monolithic molecularly imprinted fibers, where S(-)-limonene was the target molecule using electrospinning technique. The functional cavities were fixed using UV curing method, followed by a target mol-ecule washing. This procedure enabled the creation of recognition sites for limonene within the nanofiber matrix, enhancing sensor performance and streamlining manufacturing. Humidity was crucial for sensor working, with optimal conditions at about 50% RH. The sensors rapidly re-sponded to S(-)-limonene, reaching a plateau within 200 seconds. Enhancing fiber density im-proved sensor performance, resulting in a lower limit of detection (LOD) of 137 ppb. However, excessive fiber density decreased accessibility to active sites, thus reducing sensitivity. Remarka-bly, the thinnest mat on the fibrous sensors created provided the highest selectivity to limonene (Selectivity Index: 72%) compared to other VOCs, such as EtOH (used as a solvent in nanofiber development), aromatic compounds (toluene), and two other monoterpenes (α-pinene and linalo-ol) with similar structure. These findings underscored the potential of the proposed integrated approach for selective VOC detection in applications such as precision agriculture and environ-mental monitoring.

In the present study, the efficiency of a biomimetic approach by coating demineralized bone matrix (DBM) amorphous calcium phosphate (DBM+CaP), including its combination with serum albumin (DBM+CaP+BSA), was investigated. The intact structure of DBM promotes the transformation of amorphous calcium phosphate (CaP) into DPCD with a characteristic plate shape and particle size of 5–35 µm. The inclusion of BSA in the coating resulted in a better and more uniform distribution of CaP on the surface of DBM trabeculae. MG63 cells showed that both the obtained forms of CaP and its complex with BSA did not exhibit cytotoxicity up to a concentration of 10 mg/ml in vitro. Ectopic (subcutaneous) implantation in rats revealed pronounced biocompatibility, as well as strong osteoconductive, osteoinductive, and osteogenic effects for both DBM+CaP and DBM+CaP+BSA, but more pronounced effects for DBM+CaP+BSA. In addition, for the DBM+CaP+BSA samples, a pronounced full physiological intrafibrillar biomineralization and proangiogenic effect with the formation of bone-morrow-like niches, accompanied by pronounced processes of intramedullary hematopoiesis, indicating a powerful osteogenic effect of this composite have been achieved.

Magnetic resonance elastography (MRE) has revealed sexual dimorphism in brain stiffness in healthy individuals and multiple sclerosis (MS) patients. In the animal model of MS, experimental autoimmune encephalomyelitis (EAE), we showed previously that inflammation-induced brain softening was associated with alterations of the extracellular matrix (ECM). However, it remained unclear whether the brain ECM presents sex-specific properties that can be visualized by MRE. Therefore, we aimed here at quantifying sexual dimorphism in brain viscoelasticity in association with ECM changes in healthy and inflamed brains. Multifrequency MRE was applied to the midbrain of healthy and EAE mice of both sexes to quantitatively map regional stiffness. To define differences in brain ECM composition, gene expression of the key basement membrane components laminin (Lama4, Lama5), collagen (Col4a1, Col1a1) and fibronectin (Fn1) was investigated by RT-qPCR. We showed that the healthy male cortex expressed less Lama4, Lama5, Col4a1 but more Fn1 (all p < 0.05) than the healthy female cortex, which was associated with 9% softer properties (p = 0.044) in that region. At peak EAE, cortical softening was similar in both sexes compared to healthy tissue, with an 8% difference remaining between males and females during EAE (p < 0.001). Cortical Lama4, Lama5 and Col4a1 expression increased 2 to 3-fold in EAE in both sexes while Fn1 decreased only in males (all p < 0.05). No significant sex differences in stiffness were detected in other brain regions. In conclusion, sexual dimorphism in the ECM composition of cortical tissue in the mouse brain is reflected by in vivo stiffness measured with MRE and should be considered in future studies by sex-specific reference values.

This paper presents an approach to the Timoshenko beam theory (TBT) using the finite difference method (FDM). The Timoshenko beam theory covers cases associated with small deflections based on shear deformation and rotary inertia considerations. The FDM is an approximate method for solving problems described with differential equations. It does not involve solving differential equations; equations are formulated with values at selected points of the structure. In addition, the boundary conditions and not the governing equations are applied at the beam’s ends. The model developed in this paper consisted of formulating differential equations with finite differences and introducing additional points at the beam’s ends and at positions of discontinuity (concentrated loads or moments, supports, hinges, springs, brutal change of stiffness, spring-mass system, etc.). The introduction of additional points allowed us to apply the governing equations at the beam’s ends. Moreover, grid points with variable spacing were considered, the grid being uniform within beam segments. First-order, second-order, and vibration analyses of structures were conducted with this model. Furthermore, tapered beams were analyzed (element stiffness matrix, second-order analysis, vibration analysis). Finally, a direct time integration method (DTIM) was presented; the FDM-based DTIM enabled the analysis of forced vibration of structures, with damping taken into account. The results obtained in this paper showed good agreement with those of other studies, and the accuracy was increased through a grid refinement. Especially in the first-order analysis of uniform beams, the results were exact for uniformly distributed and concentrated loads regardless of the grid.

The early embryonic heart is a multi-layered tube consisting of (1) an outer myocardial tube; (2) an inner endocardial tube; and (3) an extracellular matrix layer interposed between myocardium and endocardium, called “cardiac jelly” (CJ). During the past decades, research on CJ has mainly focused on its molecular and cell biological aspects. This review focuses on the morphological and biomechanical aspects of CJ. Special attention is given to (1) the spatial distribution and fiber architecture of CJ; (2) the morphological dynamics of CJ during the cardiac cycle; and (3) the removal/remodeling of CJ during advanced heart looping stages, which leads to the formation of ventricular trabeculations and endocardial cushions. CJ acts as a hydraulic skeleton displaying striking structural and functional similarities with the mesoglea of jellyfish. CJ not only represents a filler substance, facilitating end-systolic occlusion of the embryonic heart lumen. Its elastic components antagonize the systolic deformations of the heart wall and thereby power the refilling phase of the ventricular tube. Non-uniform spatial distribution of CJ generates non-circular cross sections of the opened endocardial tube (initially elliptic, later deltoid), which seem to be advantageous for valveless pumping. Endocardial cushions arise from non-removed remnants of the original CJ.

The performance in terms of minimal Bayes’ error probability for detection of a high-dimensional random tensor is a fundamental under-studied difficult problem. In this work, we consider two Signal to Noise Ratio (SNR)-based detection problems of interest. Under the alternative hypothesis, i.e., for a non-zero SNR, the observed signals are either a noisy rank-R tensor admitting a Q-order Canonical Polyadic Decomposition (CPD) with large factors of size Nq  R, i.e, for 1  q  Q, where R, Nq ! ¥ with R1/q/Nq converge towards a finite constant or a noisy tensor admitting TucKer Decomposition (TKD) of multilinear (M1, . . . ,MQ)-rank with large factors of size Nq  Mq, i.e, for 1  q  Q, where Nq,Mq ! ¥ with Mq/Nq converge towards a finite constant. The detection of the random entries (coefficients) of the core tensor in the CPD/TKD is hard to study since the exact derivation of the error probability is mathematically intractable. To circumvent this technical difficulty, the Chernoff Upper Bound (CUB) for larger SNR and the Fisher information at low SNR are derived and studied, based on information geometry theory. The tightest CUB is reached for the value minimizing the error exponent, denoted by s?. In general, due to the asymmetry of the s-divergence, the Bhattacharyya Upper Bound (BUB) (that is, the Chernoff Information calculated at s? = 1/2) can not solve this problem effectively. As a consequence, we rely on a costly numerical optimization strategy to find s?. However, thanks to powerful random matrix theory tools, a simple analytical expression of s? is provided with respect to the Signal to Noise Ratio (SNR) in the two schemes considered. A main conclusion of this work is that the BUB is the tightest bound at low SNRs. This property is, however, no longer true for higher SNRs.

Ice formation on aircraft surfaces poses significant safety risks, and current detection systems often struggle to provide accurate, real-time predictions. This paper presents the development and comprehensive evaluation of a smart ice control system using a suite of machine learning models. The system utilizes various sensors to detect temperature anomalies and signal potential ice formation. We trained and tested supervised learning models (Logistic Regression, Support Vector Machine, Random Forest), unsupervised learning models (K-means clustering), and neural networks (Multi-Layer Perceptron) to predict and identify ice formation patterns. Experimental results demonstrate that our smart system, driven by machine learning, accurately predicts ice formation in real-time, optimizes de-icing processes, and enhances safety while reducing power consumption. This solution holds the potential for improving ice detection accuracy in aviation and other critical industries requiring robust predictive maintenance.

Hexakis(2-alkoxy-1,5-phenyleneimine) macrocycles were synthesized using a simple one−pot procedure through by precipitation−driven cyclization. The acetal−protected AB−type monomers, 2-alkoxy-5-aminobenzaldehyde diethyl acetals, underwent polycondensation in water or acid−containing tetrahydrofuran. The precipitation−driven cyclization based on imine dynamic covalent chemistry and π−stacked columnar aggregation played a decisive role in the one−pot synthesis. The progress of the reaction was analyzed by MALDI−TOF mass spectrometry. The macrocycles with alkoxy chains were soluble in specific organic solvents such as chloroform, allowing their structures to be analyzed by NMR. The shape−anisotropic, nearly planar, and persistent macrocycles aggregated into columnar assemblies in polymerization solvents, driven by aromatic π−stacking. The octyloxylated macrocycle OcO−Cm6 exhibited an enantiotropic columnar liquid crystal−like mesophase between 165°C and 197°C. In the SEM image of (S)-(−)-3,7-dimethyloctyloxylated macrocycle (−)BCO-Cm6, columnar substances with a diameter of 100−200 nm were observed. The polymerization solution for 2-(2-methoxyethoxy)ethoxy)ethoxylated macrocycle (TEGO−Cm6) gelled and showed thixotropic properties by forming a hydrogen bond network.

We present results on the spontaneous crystallization of freely-jointed polymers of hard spheres obtained in an unprecedentedly long Monte Carlo (MC) simulation on a system of 54 chains of 1000 monomers. Starting from a purely amorphous configuration and after a transitory dominance of the hexagonal closed packed (HCP) polymorph, the system crystallizes in a final, stable, face centered cubic (FCC) crystal of very high perfection. Through refined metrics we gauge the degree of ordering and identify the regions of the phase transition and the corresponding morphologies. An analysis of chain conformational characteristics, of the spatial distribution of monomers and of the volume accessible to them shows that the phase transition is caused by an increase in translational entropy that is larger than the loss of conformational entropy of the chains in the crystal compared to the amorphous state. Polymer chains in the crystal adopt ideal random walk statistics as their great length renders local conformational details, imposed by the geometry of the FCC crystal, irrelevant.

It is known that the elastic characteristics of polyamides change with increasing temperature, in particular, the Young's modulus decreases significantly. This fact is practically not taken into account in design calculations of metal-polymer plain (MP) bearings, operating under conditions of the boundary and dry friction. The purpose of the study is the analysis of the effect of temperature on the change of the Young's modulus and, accordingly, the contact strength and triboresource according to the developed method of calculating MP bearings. MP bearings with a bushing made of polyamide PA6 reinforced with glass or carbon dispersed fibers were investi-gated. Quantitative and qualitative regularities of change of the maximum contact pressures and resource of the bearings at temperature increase under conditions of boundary and dry friction are established. The pressures in the bearing bushing made of PA6+30GF will be lower than for the bushing made of PA6+30CF. The resource of the bushing made of PA6+30CF will be significantly greater than for PA6+30GF. For thermoplastic polymers, the increase in temperature will have a useful practical effect due to the decrease in the rigidity of the polymer composites of the bearing bushing.

We discuss two queueing-inventory systems with catastrophes in the warehouse. Catastrophes occur according to Poisson process and upon arrival of a catastrophe all inventory in the system is instantly destroyed. But consumer customers in the system (in the server or in the buffer) continue still waiting for the replenishment of the stock. The arrivals of the consumer customers follow a Markovian Arrival Process (MAP) and they can be queued in an infinite buffer. Service time of a consumer customer follows a phase-type distribution. The system receives negative customers whose have Poisson flows to service facility and upon arrival of a negative customer one consumer customer is pushed out from the system, if any. One of two replenishment policies can be used in the system: either (s,S) or (s,Q). If upon arrival of the consumer customer, the inventory level is zero, then according to the Bernoulli scheme, this customer is either lost (lost sale scheme) or join the queue (backorder sale scheme). The system is formulated by a four-dimensional continuous-time Markov chain. Steady state distribution is obtained using the matrix-geometric method. A comprehensive numerical study is performed on the performance measures under various replenishment policies. Finally, an optimization study is presented.

Lately Silicon Carbide (SiC) and Galium Nitride (GaN) based high frequency power conversion has gained immense popularity which stems from relatively low switching energy, robustness to high temperature operation, wide-band gap and superior thermal limits. While this aspect inherently results in a high-density power stage design, the design of adjoining passive components, particularly magnetics, needs careful attention. This is especially true if the compatibility of core and winding options and their performance is limited with the use of higher switching frequency. In this regard, this paper presents a brief review of existent research conducted in materials, optimization and integration of magnetics for single and three phase applications, ranging from filters, resonant inductors to isolation transformers. Design knobs pertaining to medium voltage (MV) applications, low-voltage (LV) applications, e-mobility sector such as more electric aircrafts (MEAs) and electric vehicles (EVs) are discussed. Guidelines for magnetics design are summarized for each application with a projected roadmap on future trend for magnetics.

Examining the similarity of event environments or surroundings, more precisely settings, provides additional insight in analyzing event sequences as it provides information about the context and potential common factors that may have influenced them. This article proposes a new similarity measure for event setting sequences, which involve the space and time in which events occur. While similarity measures for spatiotemporal event sequences have been studied, the settings and setting sequences have not yet been studied. While modeling event setting sequences we consider spatial and temporal scales to define the bounds of the setting and incorporates dynamic variables alongside static variables. Using a matrix-based representation and an extended Jaccard index we developed new similarity measures that allow for the use of all variable data types. We successfully used these similarity measures coupled with other multivariate statistical analysis approaches in a case study involving setting sequences and pollution event sequences associated with the same monitoring stations, which validate the hypothesis that more similar spatial-temporal settings or setting sequences may generate more similar events or event sequences. In conclusion, these similarity measures have many potential real-world applications, and offer researchers a powerful tool for understanding different factors and their dynamics corresponding to occurrences of spatiotemporal event sequences.

This paper presents work done as part of a transformation effort towards a greener and more sustainable Aluminium manufacturing plant. The effort includes reducing the carbon footprint by minimising waste and increasing operational efficiency. The contribution of this work includes the reduction of waste through the implementation of autonomous, real-time quality measurement and classification at an Aluminium casthouse. Data is collected from the MV20/20 which uses ultrasound pulses to detect molten Aluminium inclusions, which degrade the quality of the metal and cause subsequent metal waste. The sensor measures cleanliness, inclusion counts and distributions from 20 - 160 microns. The contribution of this work is in the development of business analytics to implement condition-based monitoring through anomaly detection, and to classify inclusion types for samples that failed. For anomaly detection, multivariate K-Means and DBSCAN algorithms are compared as they have been proven to work in a wide range of datasets. For classification, a two-stage classifier is implemented. The first stage classifies the success or failure of the sample, while the second stage classifies the inclusion responsible for the failed sample. The algorithms considered include logistic regression, support vector machine, multi-layer perceptron and radial basis function network. The multi-layer perceptron offers the best performance using k-fold cross-validation, and is further tuned using grid search to explore the possibility of an even better performance. The results reveal that the model has achieved a global maximum in performance. Recommendations include the integration of additional sensor systems and the improvements in quality assurance practices.

Introduction: A plethora of biological molecules regulate chondrogenesis in the epiphyseal growth plate. Disruptions of quantity and function of these molecules can manifest clinically as stature abnormalities of various etiologies. Traditionally, the growth hormone/insulin-like growth factor 1 (IGF1) axis represents the etiological center of final stature attainment. Of note, little is known about the molecular events that dominate the growth of the craniofacial complex and its correlation with somatic stature. Aim: Given the paucity of the relevant data, this review discusses available information regarding potential applications of lateral cephalometric radiography as a potential clinical indicator of genetic short stature in children. Materials and Methods: A literature search was conducted in the PubMed electronic database using the key words: cephalometric analysis and short stature; cephalometric analysis and achondroplasia; cephalometric analysis and hypochondroplasia; cephalometric analysis and skeletal abnormalities; cephalometr* and SHOX; cephalometr* and CNP; cephalometr* and ACAN; cephalometr* and CNVs; cephalometr* and IHH; cephalometr* and FGFR3; cephalometr* and Noonan syndrome; cephalometr* and “Turner syndrome”; cephalometr* and achondroplasia. Results: In individuals with genetic syndromes causing short stature, linear growth of the craniofacial complex is confined, following the pattern of somatic short stature regardless of its etiology. The angular cephalometric measurements differ from the average height normal individuals and are suggestive of a posterior placement of the jaws and a vertical growth pattern of the face. Conclusion: The greater part of the existing literature regarding cephalometric measurements in short statured children with genetic syndromes provides qualitative data. Furthermore, cephalometric data for individuals affected with specific rare genetic conditions causing short stature, should be the focus of future studies. These quantitative data are required to potentially establish cut-off values to refer for genetic testing based on craniofacial phenotypes.

We describe a new approach for integrating multiple views of data into a common latent space using non-negative tensor factorization (NTF). This approach, which we refer to as the "Integrated Sources Model" (ISM), consists of two main steps: embedding and analysis. In the embedding step, each view is transformed into a matrix with common non-negative components. In the analysis step, the transformed views are combined into a tensor and decomposed using NTF. Noteworthy, ISM can be extended to process multi-view data sets with missing views. We illustrate the new approach using two examples: the UCI digit dataset and a public cell type gene signatures dataset, to show that multi-view clustering of digits or marker genes by their respective cell type is better achieved with ISM than with other latent space approaches. We also show how the non-negativity and sparsity of the ISM model components enable straightforward interpretations, in contrast to latent factors of mixed signs. Finally, we present potential applications to single-cell multi-omics and spatial mapping, including spatial imaging and spatial transcriptomics, and computational biology, which are currently under evaluation. ISM relies on state-of-the-art algorithms invoked via a simple workflow implemented in a Jupyter Python notebook.

In Geo Polymer bricks (GPB), fly ash content which is a waste from power plants is converted into bricks by chemical treatment. GPB can be dried by using appropriate curing methods. Conven-tionally electric oven curing is one of the prominent methods. Using solar dryer instead of elec-trical oven gives added advantage of saving high grade electrical energy. So in this work solar dryer with PCM (Phase Change materials) Paraffin Wax and without PCM is used for curing ap-plication. GPB are gaining added advantage when compared to conventional bricks like cement and sand bricks in terms of strength. GPB has been taken as specimen for comparing the com-pressive, tensile split strength and flexural strength by electrical energy based curing and solar energy based curing. It is experimentally observed that solar energy based curing with PCM and without PCM exhibits higher compressive strength, higher tensile split strength and flexural strength when compared to electrical energy based curing. Solar curing with PCM shows higher compressive strength, higher tensile split strength and flexural strength when compared to Solar curing without PCM. Open solar curing is a traditional technique but nowadays aggressive cli-matic conditions can lead to severe damage of Geo polymers. The novelty of this work is to suggest to study the effect of PCM like paraffin wax in solar drying on curing time, mechanical properties of GPB.

High-Level Synthesis (HLS) tools have revolutionized FPGA application development by providing a more efficient and streamlined approach, significantly impacting digital design methodologies. Despite the capability of FPGAs to customize numerical representations in data paths, most HLS projects have focused on fixed-point precision, while floating-point representations remain limited to vendor-provided single, double, and half-precision formats. This paper proposes a customized floating-point library compatible with HLS to address these limitations. This library allows programmers to define the number of exponent and mantissa bits at compile time, providing greater flexibility and enabling the use of mixed precision. Moreover, this library includes optimized implementations of common components such as vector summation (VSUM), dot-product (DP), and matrix-vector multiplication (MVM). Results demonstrate that the proposed library reduces latency and resource utilization compared to vendor IP blocks, particularly in VSUM, DP, and MVM operations. For example, the MVM operation involving a 32x32 matrix, using vendor IP requires 22 clock cycles, whereas CuFP completes the same task in just 7 clock cycles, using approximately 60% fewer DSPs, 10% fewer LUTs, and 60% fewer FFs.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI–TOF MS) is a commonly used technique for analyzing large biomolecules. However, the utilization of organic matrices limits the small-molecule analysis because of the interferences in the low-mass region and reproducibility issues. To overcome these limitations, a surface-assisted laser desorption/ionization (SALDI), which utilizes nanostructured metallic surfaces, has been developed. Herein, a novel approach for SALDI–MS was proposed using nanoengineered gold shell with nanogaps on the silica core (SiO2@Au NGS), which is an emerging material due to its excellent heat-generating capabilities. The gold shell thickness was controlled by adjusting the concentration of gold precursor for the growth of gold nanoparticles. SALDI-MS measurements were performed on a layer formed by drop-casting a mixture of SiO2@Au NGS and analytes. At the optimized process, the gold shell thickness was observed to be 17.2 nm, which showed the highest absorbance. The ion desorption efficiency was confirmed with a survival yield upon fragmentation. Based on the enhanced SALDI capability, SiO2@Au NGS was utilized to detect various small molecules including amino acids, sugars, and flavonoids. The limits of detection, reproducibility, and salt tolerance of SiO2@Au NGS demonstrate its potential as an effective and reliable SALDI material for small-molecule analyses.

A model to predict the relative levels of respiratory and fecal-oral transmission potentials of coronaviruses (CoVs) by measuring the percentage of protein intrinsic disorder (PID) of the M (Membrane) and N (nucleoprotein) proteins in their outer and inner shells, respectively, was built before the MERS-CoV outbreak. Application of this model to the 2003 SARS-CoV indicated that this virus with M_PID = 8.6% and N_PID = 50.2% falls into group B, which consists of CoVs with intermediate levels of both fecal-oral and respiratory transmission potentials. Further validation of the model came with MERS-CoV (M_PID = 9%, N_PID = 44%) and SARS-CoV-2 (M_PID = 5.5%, N_PID = 48%) falling into the groups C and B, respectively. Group C contains CoVs with higher fecal-oral but lower respiratory transmission potentials. Unlike SARS-CoV, SARS-CoV-2 with M_PID = 5.5% has one of the hardest outer shells among CoVs. This shell hardness is believed to be responsible for high viral loads in the mucus and saliva making it more contagious than SARS-CoV. The hard shell is able to resist the anti-microbial enzymes in body fluids. Further searches have found that high rigidity of outer shell is characteristic for the CoVs of burrowing animals, such as rabbits (M_PID = 5.6%) and pangolins (M_PID = 5-6%), which are in contact with the buried feces. A closer inspection of pangolin-CoVs from 2017-19 reveals that these animals provided a unique window of opportunity for the entry of an attenuated SARS-CoV-2 precursor into the human population in 2017 or earlier, with the subsequent slow and silent spread as a mild cold that followed by its mutations into the current more virulent form. Evidence of this lies in the similarity of shell disorder and genetic proximity of the pangolin-CoVs to SARS-CoV-2 (~90%). A 2017 pangolin-CoV strain shows evidence of higher levels of attenuation and higher fecal-oral transmission associated with lower human infectivity via having lower N_PID (44.8%). Our shell disorder analysis also revealed that lower inner shell disorder is associated with the lesser virulence in a variety of viruses.

A model that predicts levels of coronavirus (CoV) respiratory/fecal-oral transmission potentials based on the outer shell hardness has been built using neural network (artificial intelligence, AI) analysis of the percentage of disorder (PID) in the nucleocapsid, N, and membrane, M, proteins of the inner and outer viral shells, respectively. Based mainly on the PID of N, SARS-CoV-2 is categorized as having intermediate levels of both respiratory and fecal oral transmission potential. Related to this, other studies have found strong positive correlations between virulence and inner shell disorder among numerous viruses, including Nipah, Ebola, and Dengue viruses. There is some evidence that this is also true for SARS-CoV-2 and SARS-CoV, which have N PIDs of 48% and 50%, and are characterized by case-fatality rates of 7.1% and 10.9%, respectively. The link between levels of respiratory transmission and virulence lies in viral load of body fluids and organ respectively. A virus can be infectious via respiratory modes only if the viral loads in saliva and mucus exceed certain minima. Likewise, a person may die, if the viral load is too high especially in viral organs. Inner shell proteins of viruses play important roles in the replication of viruses, and structural disorder enhances these roles by providing greater efficiency in protein-protein/DNA/RNA/lipid binding. This paper outlines a novel strategy in attenuating viruses involving comparison of disorder patterns of inner shells of related viruses to identify residues and regions that could be ideal for mutation. The M protein of SARS-CoV-2 has one of the lowest M PID values (6%) in its family, and therefore this virus has one of the hardest outer shells, which makes it resistant to antimicrobial enzymes in body fluid. While this is likely responsible for its contagiousness, the risks of creating an attenuated virus with a more disordered M are discussed.

As people grow a custom to effortless outdoor navigation there is a rising demand for similar possibility indoors as well. Unfortunately, indoor localization, being one of the necessary requirements for navigation, continues to be problem without a clear solution. In this article we are proposing a method for an indoor positioning system using a single image. This is made possible using small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with SIFT algorithm we can look through the database and find image which is the most similar to the image taken by user. Pair of images is then used to find coordinates of database image using PnP problem. Furthermore, projection and essential matrices are determined allowing for the user image localization ~ determining the position of the user in indoor environment. Benefits of this approach lies in the single image being the only input from user and no requirements for new onsite infrastructure and thus enables a simpler realization for the building management.

The classical Rotational Isomeric State (RIS) model, originally proposed by Flory, has been used to rationalize a wide range of physicochemical properties of neutral polymers. However, many weak polyelectrolytes of interest are able to regulate their charge depending on the conformational state of the bonds. Recently, it has been shown that the RIS model can be coupled with the Site Binding (SB) model, for which the ionizable sites can adopt two states: protonated or deprotonated. The resulting combined scheme, the SBRIS model, allows to analyse ionization and conformational equilibria on the same foot. In the present work this approach is extended to include pH-dependent electrostatic Long Range (LR) interactions, ubiquitous in weak polyelectrolytes at moderate and low ionic strengths. With this aim the original LR interactions are taken into account by defining effective Short Range (SR) and pH-dependent parameters, such as effective microscopic protonation constants and rotational bond energies. The new parameters are systematically calculated using variational methods. The machinery of statistical mechanics for SR interactions, including the powerful and fast transfer matrix methods, can then be applied. The resulting technique, to which we will refer as Local Effective Interaction Parameters (LEIP) method, is illustrated with a minimal model of a flexible linear polyelectrolyte containing only one type of rotating bonds. LEIP reproduces very well the pH dependence of the degree of protonation and bond probabilities obtained by semi-grand canonical Monte Carlo simulations, where LR interactions are taken explicitly into account. The reduction in the computational time in several orders of magnitude suggests that the LEIP technique could be useful in a range of areas involving linear weak polyelectrolytes, allowing direct fitting of the relevant physical parameters to the experimental quantities.

This paper presents an approach to the Euler-Bernoulli beam theory (EBBT) using the finite difference method (FDM). The EBBT covers the case of small deflections, and shear deformations are not considered. The FDM is an approximate method for solving problems described with differential equations. The FDM does not involve solving differential equations; equations are formulated with values at selected points of the structure. Generally, the finite difference approximations are derived based on fourth-order polynomial hypothesis (FOPH) and second-order polynomial hypothesis (SOPH) for the deflection curve; the FOPH is made for the fourth and third derivative of the deflection curve while the SOPH is made for its second and first derivative. In addition, the boundary conditions and not the governing equations are applied at the beam’s ends. In this paper, the FOPH was made for all of the derivatives of the deflection curve, and additional points were introduced at the beam’s ends and positions of discontinuity (concentrated loads or moments, supports, hinges, springs, etc.). The introduction of additional points allowed us to apply the governing equations at the beam’s ends and to satisfy the boundary and continuity conditions. Moreover, grid points with variable spacing were also considered, the grid being uniform within beam segments. First-order analysis, second-order analysis, and vibration analysis of structures were conducted with this model. Furthermore, tapered beams were analyzed (element stiffness matrix, second-order analysis). Finally, a direct time integration method (DTIM) was presented. The FDM-based DTIM enabled the analysis of forced vibration of structures, with damping taken into account. The results obtained in this paper showed good agreement with those of other studies, and the accuracy was increased through a grid refinement. Especially in the first-order analysis of uniform beams, the results were exact for uniformly distributed and concentrated loads regardless of the grid. Further research will be needed to investigate polynomial refinements (higher-order polynomials such as fifth-order, sixth-order…) of the deflection curve; the polynomial refinements aimed to increase the accuracy, whereby non-centered finite difference approximations at beam’s ends and positions of discontinuity would be used.

This study presents an exact solution to the free vibration analysis of a uniform Timoshenko beam, with a harmonic vibration being assumed. The Timoshenko beam theory covers cases associated with small deflections based on shear deformation and rotary inertia considerations. In this paper, a moment-shear force-circular frequency-curvature relationship was presented. The complete study was based on this relationship and closed-form expressions of efforts and deformations were derived. The free vibration response of single-span systems and spring-mass systems was analyzed; closed-form formulations of matrices expressing the boundary conditions were presented and the natural frequencies were determined by solving the eigenvalue problem. Systems with intermediate mass, spring, or spring-mass system were also analyzed. Furthermore, first-order dynamic stiffness matrices in local coordinates were derived. Finally, a second-order analysis of beams resting on an elastic Winkler foundation was conducted. The results obtained in this paper were in good agreement with those of other studies.

Protein immobilization for the functionalization of particles is used in various applications, including biosensors, lateral-flow immunoassays (LFIA), bead-based assays, and others. Common methods for the quantification of bound protein are measuring protein in the supernatant before and after coating and calculating the difference. This popular approach has the potential for a significant overestimation of the amount of immobilized protein since layers not directly bound to the surface (soft protein corona) are usually lost during washing and handling. Only the layer directly bound to the surface (hard corona) can be used in subsequent assays. A simplified amino acid analysis method based on acidic hydrolysis and RP-HPLC-FLD of tyrosine and phenylalanine (aromatic amino acid analysis, AAAA) is proposed to directly quantify protein bound to the surface of gold nano- and latex microparticles. The results are compared with indirect methods such as colorimetric protein assays, such as Bradford, bicinchoninic acid (BCA), as well as AAAA of the supernatant. For both particle types, these indirect quantification techniques show a protein overestimation of up to 1700% compared to the direct AAAA measurements. In addition, protein coating on latex particles was performed both passively through adsorption and covalently through EDC/sulfo-NHS chemistry. Our results showed no difference between the immobilization methodologies. This finding suggests that usual protein determination methods are no unambiguous proof of a covalent conjugation on particles or beads.

A novel stationary phase for affinity separations is presented. This material is based on sintered borosilicate glass readily available as semi-finished filter plates with defined porosity and surface area. The material shows fast binding kinetics and excellent long-term stability under real application conditions due to lacking macropores and high mechanical rigidity. The glass surface can be easily modified with standard organosilane chemistry to immobilize selective binders or other molecules used for biointeraction. In this paper, the manufacturing of the columns and their respective column holders by 3D printing is shown in detail. The model system protein A/IgG was chosen as an example to examine the properties of such monolithic columns under realistic application conditions. Several specifications, such as (dynamic) IgG capacity, pressure stability, long-term performance, productivity, non-specific binding, and peak shape, are presented. It could be shown that due to the very high separation speed, 250 mg antibody per hour and column can be collected, which surpasses the productivity of most standard columns of the same size. The total IgG capacity of the shown columns is around 4 mg (5.5 mg/mL), which is sufficient for most tasks in research laboratories. The cycle time of an IgG separation can be less than 1 minute. Due to the glass material's excellent pressure resistance, these columns are compatible with standard HPLC systems. This is usually not the case with standard affinity columns, limited to manual use or application in low-pressure systems. The use of a standard HPLC system also improves the ability for automation, which enables the purification of hundreds of cell supernatants in one day. The sharp peak shape of the elution leads to an enrichment effect, which might increase the concentration of IgG by a factor of 3. The final concentration of IgG can be around 7.5 mg/mL without the need for an additional nanofiltration step. The purity of the IgG was > 95% in one step and nearly 99% with a second polishing run.

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.

Nonporous corundum powder, known as an abrasive material in the industry, was functionalized covalently with protein binders to isolate and enrich specific proteins from complex matrices. The materials based on corundum were characterized by TEM, ESEM, BET, DLS, and zeta potential measurements. The strong Al-O-P bonds between the corundum surface and amino phosphonic acids are used to introduce functional groups for further conjugations. The common crosslinker glutaraldehyde was compared with a hyperbranched polyglycerol (PG) of around 10 kDa. The latter is oxidized with periodate to generate aldehyde groups that can covalently react with the amines of the surface and the amino groups from the protein via a reductive amination process. The amount of bound protein was quantified via aromatic amino acid analysis (AAAA). This work shows that oxidized polyglycerol can be used as an alternative to glutaraldehyde. With polyglycerol, more of the model protein bovine serum albumin (BSA) could be attached to the surface under the same conditions, and lower nonspecific binding (NSB) was observed. As a proof of concept, IgG was extracted with protein A from crude human plasma. The purity of the product was examined by SDS-PAGE. A binding capacity of 1.8 mg IgG per g of corundum powder was achieved. The advantages of corundum are the very low price, extremely high physical and chemical stability, pressure resistance, favorable binding kinetics, and flexible application.

A particular challenge in the conceptual design of direct-from orbit delivery systems is the seemingly well-known kinematics retain fallacies whose efficacies are reduced over great distances. Rotation about the local wing of an aerospace vehicle is almost never the pitch angle, yet modern application of kinematics often assumes such (with accompanying angular error). The same assertion is usually true about the nature of roll and yaw angles. Expressing motion in coordinates of rotating reference frames necessitates transformation between reference frames, and one such transformation is embodied in the Direction Cosine Matrices (DCM) formed by a sequence of three successive frame rotations. One of two ubiquitous sequences of three rotations used to construct the DCM involves first a rotation around the inertial z-axis, then intermediate y-axis, then finally about the body’s x-axis; a sequence commonly called the “aerospace sequence” or the a “3-2-1 rotation sequence”. The second ubiquitous sequence is the so-called “orbital sequence” or “3-1-3 rotation sequence” with rotations about the inertial z axis first, then about the intermediate x-axis, then finally about the body z-axis. This manuscript evaluates which sequence is the most advantageous for an object starting in space and then travels through the atmosphere to a target on the Earth’s surface. Six degrees of freedom of vehicle motion were simulated starting in orbit with a given thrust and commanded maneuver. The simulation performs all twelve possible rotation sequences (transforming inertial coordinates to body coordinates) with comparison by computational burden and error representing rotations about body axes (roll, pitch, and yaw respectively). Simulation precision is validated using the quaternion normalization condition indicating near machine precision (0.9\times{10}^{-15}) and reveals the so-called 132 rotation is the most accurate with an average error of 0.14° and a computational time of 0.013 seconds: resulting in a 97.95% increase in accuracy over the so-called 321 rotation and a 99.84% increase over the so-called 313 rotation.

In the present work we revise and extend the Characteristic Crystallographic Element (CCE) norm, an algorithm used to simultaneously detect radial and orientational similarity of computer-generated structures with respect to specific reference crystals and local symmetries. Based on the identification of point group symmetry elements, the CCE descriptor is able to gauge local structure with high precision and finely distinguish between competing morphologies. As test cases we use computer-generated monomeric and polymer systems of spherical particles interacting with the hard-sphere and square-well attractive potentials. We demonstrate that the CCE norm is able to detect and differentiate, between others, among: hexagonal close packed (HCP), face centered cubic (FCC), hexagonal (HEX) and body centered cubic (BCC) crystals as well as non-crystallographic fivefold (FIV) local symmetry in bulk 3-D systems; triangular (TRI), square (SQU) and honeycomb (HON) crystals, as well as pentagonal (PEN) local symmetry in thin films of one-layer thickness (2-D systems). The descriptor is general and can be applied to identify the symmetry elements of any point group for arbitrary atomic or particulate system in two or three dimensions, in the bulk or under confinement.

Objectives: Multicentric Osteolysis, Nodulosis, and Arthropathy (MONA) syndrome is a rare genetic skeletal dysplasia. Its diagnosis can be deceptively similar to childhood-onset genetic skeletal dysplasias and juvenile idiopathic arthritis. We aimed to report the syndrome’s clinical and radiologic features with emphasis on skeletal manifestations. And establish relevant phenotype-genotype correlations. Methods: We evaluated two boys, 4-and-7-years-old with MONA syndrome. Both patients had consanguineous parents. We verified the diagnosis by correlating the outcomes of clinical, radiologic and molecular analysis. We specifically evaluated the craniofacial morphology and clinical and radiographic skeletal abnormalities. We contextualized the resultant phenotype-genotype correlations to publications on MONA and its differential diagnosis. Results: Skeletal manifestations were the presenting symptoms and mostly restricted to hands and feet in terms of fixed extension deformity of the metacarpophalangeal and flexion deformity of the interphalangeal joints with extension deformity of big toes. There were arthritic symptoms in the older patient especially of the wrists and minute pathologic fractures. The skeletal radiographs showed osteopenia/dysplastic changes of hands and feet. Both patients had variants in the matrix metalloproteinase2 gene which conformed to phenotype of previously reported literature in one patient while the other had a novel variant which conformed to MONA phenotype. Craniofacial abnormalities were present. However, minimal extra-skeletal manifestations. Conclusion: Overall, there is an emerging distinctive skeletal pattern of involvement in terms of both clinical and radiographic features. This includes age of onset and location of presenting skeletal manifestations, chronological order of joint affection, longitudinal disease progression, specifics of skeletal radiographic pathology and craniofacial features. Nevertheless, physicians are cautioned against differential diagnosis of similar genetic skeletal dysplasias and juvenile idiopathic arthritis.