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Abstract Advancements in cytometry technologies have enabled quantification of up to 50 proteins across millions of cells at single cell resolution. Analysis of cytometry data routinely involves tasks such as data integration, clustering, and dimensionality reduction. While numerous tools exist, many require extensive run times when processing large cytometry data containing millions of cells. Existing solutions, such as random subsampling, are inadequate as they risk excluding rare cell subsets. To address this, we propose SuperCellCyto, an R package that builds on the SuperCell tool which groups highly similar cells into supercells. SuperCellCyto is available on GitHub ( https://github.com/phipsonlab/SuperCellCyto ) and Zenodo ( https://doi.org/10.5281/zenodo.10521294 ).

Bacteriocins are ribosomally synthesized bacterial peptides endowed with antibacterial, antiprotozoal, anticancer and antiviral activities. In the present study, we evaluated the antiviral activities of two bacteriocins, enterocin DD14 (EntDD14) and lacticaseicin 30, against herpes simplex virus type 1 (HSV-1), human coronavirus 229E (HCoV-229E) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Vero, Huh7 and Vero E6 cells, respectively. In addition, the interactions of these bacteriocins with the envelope glycoprotein D of HSV-1 and the receptor binding domains of HCoV-229E and SARS-CoV-2 have been computationally evaluated using protein-protein docking and molecular dynamics simulations. HSV-1 replication in Vero cells was inhibited by EntDD14 and, to a lesser extent, by lacticaseicin 30 added to cells after virus inoculation. EntDD14 and lacticaseicin 30 had no apparent antiviral activity against HCoV-229E; however, EntDD14 was able to inhibit SARS-CoV-2 in Vero E6 cells. Further studies are needed to elucidate the antiviral mechanism of these bacteriocins. [ABSTRACT FROM AUTHOR]

New 2,6-bis(1,3-dihydroxy-2-(hydroxymethyl)propan-2-yl)pyrrolo[3,4-f]isoindole-1,3,5,7(2H,6H)-tetraone (2Tris@PMDA) and its polymeric hybrids with Anderson polyoxometalates (DiTA@PMDA) and with Lindquist polyoxometalates (DiTL@PMDA) have been synthesized and thoroughly characterized. Using dr. Blade's approach, TiO2 based thin films of 2Tris@PMDA, DiTA@PMDA, and DiTL@PMDA have been designed to explore the adsorption study, optical activity, and photocurrent generation. The calculated electrical conductivity values for 2Tris@PMDA, DiTA@PMDA and DiTL@PMDA were 2.8 × 103 S/m−1.90 × 103 S/m, 2.7 × 103 S/m−1.7 × 103 S/m, and 2 × 103 S/m−1.65 ×103 S/m, respectively. Furthermore, computational analysis for 2Tris@PMDA, DiTA@PMDA, and DiTL@PMDA has been studied at B3LYP using 6-31 G (d, p) and LanL2DZ level of density functional theory. It indicates that the conjugation of 2Tris@PMDA with polyoxometalates makes them a suitable candidate for dye sensitized solar cell due to the charge transfer process in DiTA@PMDA and DiTL@PMDA. [ABSTRACT FROM AUTHOR]

A mathematical model of skeletal muscle regeneration for immune-muscular cell interactions with a pro-inflammatory mediator is introduced and analyzed. The model is a multi-scale problem with discontinuities and numerically stiff. Thus, a nonstandard parametric stability analysis of the equilibria is carried out in order to investigate the potential muscular regeneration and the inflammation resolution. [ABSTRACT FROM AUTHOR]

Preserving the spatial characteristics of the built environments is a critical component for retaining historical cultural value. However, there is a lack of quantitative and systematic spatial analysis of Historic Chinese Built Environments (HCBE) in the literature especially at a medium scale. This study applies angular segment analysis (ASA) to analyse both the spatial structures and morphological changes of HCBEs. Four case studies exemplifying the core characteristics of HCBEs were selected for ASA (Pingyao, Lijiang, Kulangsu, and Wuzhen). The resulting knowledge yielded by this ASA provided three outcomes including the spatial structures, the morphological changes and the influence of traditional Chinese ideology on the design and planning principles of HCBE. While the ASA has provided insights into the inherent unique characteristics of the four HCBE cases, it has also illuminated specific spatial and morphological characteristics that should be acknowledged in any future heritage-conservation or -tourism renewal planning policies and projects. [ABSTRACT FROM AUTHOR]

Sialic acids are nine-carbon sugars that modify glycans on glycoconjugates and mediate important biological functions. While sialic acids have not been detected in insects (as it was considered that it is obtained from external sources), orthologs of sialic acid biosynthetic enzymes and insect ST6Gal sialyltransferases suggest ancestral sialylation pathways. Sialyltransferases contain conserved peptide regions called sialylmotifs (L, S, VS, III), participating in donor substrate binding and catalytic activity. We performed a computational analysis searching 27 insect proteomes for vertebrate sialylmotif sequences to identify putative novel insect sialyltransferases. Sialylmotif L sequences similar to mammalian ST3Gal IV and ST6GalNAc I were found in putative proteins from Galleria mellonella and Manduca sexta, respectively. Identifying sialyltransferase precursor genes in insects supports their evolutionary origin preceding vertebrate diversification. Despite the lack of sialic acid production, sialyltransferase genes in insects suggest an evolutionary perspective on conserved sialylation pathways. [ABSTRACT FROM AUTHOR]

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Atenolol β‐blocker drug (ATN) to treat hypertension and cardiovascular disorders such as angina pectoris is manufactured commercially in a racemic form, while only its (S)‐enantiomer shows selective β1‐blocking activity. Here, a new axially chiral thiolated naphthalene diimide derivatives (HS‐BIN‐NDI) for the rapid, simple, and sensitive detection of ATN enantiomers is presented. The Surface Plasmon Resonance (SPR) and Atomic Force Microscopy (AFM) experiments show that interactions between a chiral selector and a chiral analyte occur only when their configurations are opposite. The extensive computational simulations support this finding. The association coefficient determined by SPR is high (105‐106 M−1 s−1) and indicates that the interactions are electrostatic. The analytical utility of atropisomeric HS‐BIN‐NDIs is proven, and the voltammetric sensors designed to determine ATN enantiomers are constructed. The developed sensors are characterized by a wide analytical operating range from 5.0·10−3 to 1.0 µm, nanomolar detection limit, high selectivity, and a long lifetime. Several additives like urea, creatinine, glucose, human albumin, and hemoglobin do not affect ATN sensing. [ABSTRACT FROM AUTHOR]

This work investigates the use of Topology Optimization (TO) to support the design of femur prosthesis to obtain more efficient solutions from the point of view of material distribution and internal forces. Computational tests were performed by the Interior-Point OPTimizer (IPOPT) method, seeking to explore the elastic mechanical characteristics of three real scenarios of daily loads on the femur. Numerical examples are presented to verify the novelty of the proposed method. The results obtained indicate that it is possible to reduce the volume of material up to 30% of the customize human femoral prosthesis, respecting all the boundary conditions. [ABSTRACT FROM AUTHOR]

The framework of elementary probabilistic operations (EPO) explains the structure of elementary probabilistic reasoning tasks as well as people's performance on these tasks. The framework comprises three components: (a) Three types of probabilities: joint, marginal, and conditional probabilities; (b) three elementary probabilistic operations: combination, marginalization, and conditioning, and (c) quantitative inference schemas implementing the EPO. The formal part of the EPO framework is a computational level theory that provides a problem space representation and a classification of elementary probabilistic problems based on computational requirements for solving a problem. According to the EPO framework, current methods for improving probabilistic reasoning are of two kinds: First, reduction of Bayesian problems to a type of probabilistic problems requiring less conceptual and procedural competencies. Second, enhancing people's utilization competence by fostering the application of quantitative inference schemas. The approach suggests new applications, including the teaching of probabilistic reasoning, using analogical problem solving in probabilistic reasoning, and new methods for analyzing errors in probabilistic problem solving. [ABSTRACT FROM AUTHOR]

Recent years have seen a significant surge in the global popularity of Chinese webnovels as an emerging form of participatory transcultural storytelling. This research combines computational and interpretive textual analysis to map the cultural features embedded in webnovel content, aiming to identify the genre elements, common lexicon, and story themes of 4040 translated Chinese webnovels on global platforms. The analysis shows the hybridisation of Chinese cultures, digital cultures, and genre fiction elements in webnovel storytelling, contributing to the growing spectrum of diverse voices in international self-publishing. Simultaneously, webnovels depict a varied mosaic of imagined China, based on both cultural sharing and nonsharing within today's complex Chinese society and beyond the notion of 'Chineseness' rooted in common heritage or official values, amplifying diverse perspectives like subcultures and resistances in transcultural storytelling. While webnovels bear witness to China's cultural outreach and digital prowess converging in a new storytelling form, this research posits that their cultural production remains bound within a material process where borderless digital cultures collide with the imposed boundaries of platformed publishing and government control. [ABSTRACT FROM AUTHOR]

Six red-light-emitting Eu(III) complexes having a β-hydroxyketone as ligand and heterocyclic ring containing compounds as ancillary ligands were synthesized to explore their use in displays and optoelectronics. The coordinating behavior of complexes was determined by various techniques such as FTIR (Fourier transform infrared), 1H-NMR (Nuclear magnetic resonance), and 13C-NMR that establishes a bonding of ligand and ancillary ligand with the Eu(III) ion. Morphology and purity were investigated through XRD (X-ray diffraction), SEM (scanning electron microscopy) and EDS (energy-dispersive X-ray spectroscopy) analyses that suggest semicrystalline and pure complex formation. Thermal analysis of complexes by TGA/DTG (thermogravimetric/derivative thermogravimetric) indicates that complexes are stable upto 200 ºC temperature making them suitable for use in display devices. Analysis of the photophysical properties was carried out in both solid and solution states using PL (photoluminescence) studies, color parameters, J–O (Judd–Ofelt) analysis and bandgap. Most emissive transition (5D0 → 7F2) is responsible for the red emission in the complexes. The CIE (Commission International de I'Eclairage) coordinates of complexes also indicate the red emission on UV excitation. The bandgap which was obtained in the range of 2.54–3.02 eV reveals the semiconducting behavior of complexes. Values of J–O parameters and Ω2 in the complexes reflect asymmetric chemical environment around Eu (III) and less covalence and the Ω4 indicates that complexes are less rigid. Bandgap calculated through DFT (density function theory) for complexes is in range of 2.37–2.77 eV, and intensity parameters (J–O), energy transfer rates, and spherical coordinates were determined by LUMPAC software. The computational data are in good harmony with the experimental data. Further biological aspects of complexes were studied using antioxidant and antimicrobial studies. [ABSTRACT FROM AUTHOR]

To date, a growing body of second language (L2) research has investigated linguistic alignment as a pedagogical intervention, focusing on L2 learners' alignment behaviors in task-based interactions (e.g., Jung, YeonJoo, YouJin Kim & John Murphy. 2017. The role of task repetition in learning word-stress patterns through auditory priming tasks. Studies in Second Language Acquisition 39(2). 319–346; Kim, YouJin, YeonJoo Jung & Stephen Skalicky. 2019. Linguistic alignment, learner characteristics, and the production of stranded prepositions in relative clauses: Comparing FTF and SCMC contexts. Studies in Second Language Acquisition 41(5). 937–969). Linguistic alignment refers to a tendency where one speaker's utterances align with particular language features of those of the other speaker in dialogue. The current study investigated how L2 speakers' alignment behaviors differ in natural dialogues between L2-L1 and L2-L2 dyads in terms of language style (i.e., stylistic alignment) and the role of non-linguistic factors in the occurrence of stylistic alignment. The study analyzed a corpus of 360 texts using a computational tool. Results showed that stylistic alignment occurred to a greater extent in the L2-L2 dyad than in the L2-L1 dyad with respect to the word range, word frequency, word imageability, and proportion of bigrams proportion produced by the interlocutors. Furthermore, findings demonstrated the degree of stylistic alignment on each of the four selected lexical features was affected by numerous factors including age, group membership, nonnative speaker status, familiarity between interlocutors, and linguistic distance between L1 and L2. The effect of each factor on stylistic alignment in conversation is discussed in detail. [ABSTRACT FROM AUTHOR]

This study investigates the efficacy of machine learning techniques and correlation methods for predicting heat transfer performance in a dimpled tube under varying flow conditions, including the presence of nanoparticles. A comprehensive numerical analysis involving 120 cases was conducted to obtain Nusselt numbers and friction factors, considering different dimple depths and velocities for both pure water and water-Al2O3 nanofluid at 1%, 2%, and 3% volume concentrations. Utilizing the data acquired from the numerical simulations, a correlation equation, SVM ANN architectures were developed. The predictive capabilities of the statistical approach, ANN, and SVM models for Nusselt number distribution and friction factor were meticulously assessed through mean average percentage error (MAPE) and correlation coefficients (R 2). The research findings reveal that machine learning techniques offer a highly effective approach for accurately predicting heat transfer performance in a dimpled tube, with results closely aligned with Computational Fluid Dynamics (CFD) simulations. Particularly noteworthy is the superior performance of the ANN model, demonstrating the most precise predictions with an error rate of 2.54% and an impressive R 2 value of 0.9978 for Nusselt number prediction. In comparison, the regression model achieved an average error rate of 6.14% with an R 2 value of 0.8623, and the SVM model yielded an RMSE value of 2.984% with an R 2 value of 0.9154 for Nusselt number prediction. These outcomes underscore the ANN model's ability to effectively capture complex patterns within the data, resulting in highly accurate predictions. In conclusion, this research showcases the promising potential of machine learning techniques in accurately forecasting heat transfer performance in dimpled tubes. The developed ANN model exhibits notable superiority in predicting Nusselt numbers, making it a valuable tool for enhancing thermal system analyses and engineering design optimization. [ABSTRACT FROM AUTHOR]

Natural killer (NK) cells are central components of the innate immunity system against cancers. Since tumor cells have evolved a series of mechanisms to escape from NK cells, developing methods for increasing the NK cell antitumor activity is of utmost importance. It is previously shown that an ex vivo stimulation of patient‐derived NK cells with interleukin (IL)‐2 and Hsp70‐derived peptide TKD (TKDNNLLGRFELSG, aa450‐461) results in a significant upregulation of activating receptors including CD94 and CD69 which triggers exhausted NK cells to target and kill malignant solid tumors expressing membrane Hsp70 (mHsp70). Considering that TKD binding to an activating receptor is the initial step in the cytolytic signaling cascade of NK cells, herein this interaction is studied by molecular docking and molecular dynamics simulation computational modeling. The in silico results showed a crucial role of the heterodimeric receptor CD94/NKG2A and CD94/NKG2C in the TKD interaction with NK cells. Antibody blocking and CRISPR/Cas9–mediated knockout studies verified the key function of CD94 in the TKD stimulation and activation of NK cells which is characterized by an increased cytotoxic capacity against mHsp70 positive tumor cells via enhanced production and release of lytic granules and pro‐inflammatory cytokines. [ABSTRACT FROM AUTHOR]

In the Aerodynamic drag analysis, the predominant factor is pressure drag which reduces the vehicle speed and fuel efficiency. By delaying the flow separation at trailing edge in roof of the car body and creating turbulence in the vacuum region available at rear (of car body), the pressure difference between front and rear can be minimized, thus reducing the pressure drag. This study deals with the computational analysis of a simplified car model using Ansys FLUENT software at a Reynolds number of 3.281e5 based on the body length. To solve the Navier-stokes equations k - e turbulence model is used. A base car model and a car model with vortex generator (VG) placed at three different locations on either side of rear slant are developed using NX modelling software. By using ICEM meshing software, developed car models are meshed. For all model's coefficient of drag is analyzed using Ansys-FLUENT at different velocities such as 20m/s, 25m/s, 30m/s and 35m/s. From the computational analysis, a considerable reduction in the coefficient of drag is achieved in all three models. In particular, the model which had vortex generator placed at middle of rear slant of either side provides improved drag reduction comparing with other two models. While calculating the drag force using coefficient of drag, it is observed that for all velocities around 11% reduction in drag force are achieved in car model with vortex generator on comparing with the base car model. [ABSTRACT FROM AUTHOR]

The West Nile virus (WNV) is the causative agent of West Nile disease (WND), which poses a potential risk of meningitis or encephalitis. The aim of the study was to design an epitope-based vaccine for WNV by utilizing computational analyses. The epitope-based vaccine design process encompassed WNV sequence collection, phylogenetic tree construction, and sequence alignment. Computational models identified B-cell and T-cell epitopes, followed by immunological property analysis. Epitopes were then modeled and docked with B-cell receptors, MHC I, and MHC II. Molecular dynamics simulations further explored dynamic interactions between epitopes and receptors. The findings indicated that the B-cell epitope QINHHWHKSGSSIG, along with three T-cell epitopes (FLVHREWFM for MHC I, NPFVSVATANAKVLI for MHC II, and NAYYVMTVGTKTFLV for MHC II), successfully passed the immunological evaluations. These four epitopes were further subjected to docking and molecular dynamics simulation studies. Although each demonstrated favorable affinities with their respective receptors, only NAYYVMTVGTKTFLV displayed a stable interaction with MHC II during MDS analysis, hence emerging as a potential candidate for a WNV epitope-based vaccine. This study demonstrates a comprehensive approach to epitope vaccine design, combining computational analyses, molecular modeling, and simulation techniques to identify potential vaccine candidates for WNV. [Display omitted] • The WNV is responsible for causing West Nile disease (WND), which carries the potential for meningitis or encephalitis. • Computational predictions pinpointed B-cell and T-cell epitopes as potential candidates for the WNV epitope vaccine, followed by an in silico evaluation of their immunological characteristics. • The B-cell epitope QINHHWHKSGSSIG, along with three T-cell epitopes (FLVHREWFM for MHC I, NPFVSVATANAKVLI for MHC II, and NAYYVMTVGTKTFLV for MHC II), satisfactorily met the criteria of computational immunological assessments. • NAYYVMTVGTKTFLV consistently demonstrated binding with major histocompatibility complex II (MHC II) in the context of MDS analysis, thereby emerging as a potential candidate for a West Nile virus epitope-based vaccine. [ABSTRACT FROM AUTHOR]

In this work, the dynamic motion of a particle in an incompressible Newtonian fluid flow is investigated analytically. The shear and rotation effects on the lift and drag forces of the particle are considered for this problem. Also, the equations governing the motion of a particle are solved using the Temimi–Ansari technique. Analytical solutions for the horizontal and vertical velocities of this particle are obtained and analyzed in terms of time. The corresponding analytical findings are verified in comparison with numerical solutions. The obtained results showed very good accuracy of the solutions and the efficiency of this method in the whole time domain by employing the Padé approximation. [ABSTRACT FROM AUTHOR]

This research provides the first known solution to the nonlinear Hamiltonian amplitude equation using the combined Bernoulli sub-equation function and trigonometric-quintic-B-spline methods. While previous works have analyzed this model through limited linear approximations, an exact solution accounting for nonlinearity remains lacking. We address this gap by employing innovative techniques to reveal and scrutinize solitary wave solutions, elucidating complex behaviors inaccessible through linear methods. Our findings show the unequivocal effectiveness of our approach, comprising the first successful solution to this equation. This breakthrough fundamentally advances the comprehension of nonlinear physical systems across domains encompassing wave propagation, quantum mechanics, and optical phenomena. [ABSTRACT FROM AUTHOR]

In this day and age, there has been a discernible focus on and significant usage of Quantum machine learning (QML) models with the intention of predicting the toxicity of inconsequential compounds. The application of computational toxicity prediction provides considerable advantages in the early phases of pharmaceutical research. These benefits include the identification and removal of compounds that are likely to display poor effectiveness when tested in clinical trials. This trend has been easier to observe with the introduction of extensive toxicity databases. As a result of the fact that this field is still in its infancy, it is essential to acquire a more all-encompassing grasp of the range of QAI approaches and the contexts in which they might be used. Trials to harmonize principles from quantum mechanics, Quantum Machine learning algorithms with classical ML techniques, which leads towards enhancing the interpretability has been performed. In an attempt to achieve robust accuracy associated with the QML model, reach out of enriching insights from naïve Bayesian classification and recursive partitioning, through the merge of sophisticated computational techniques with complex biological phenomenon has been done, the present study not only moves towards enhancing the repertoire of tools available for early stage enhanced drug discovery & optimization but also moves towards revolutionary possibilities of quantum-infused methods in tackling persistent issues in the field of bioinformatics and toxicology. [ABSTRACT FROM AUTHOR]

Since the middle of the 17th century, scholars have been systematically describing numerous medieval manuscripts preserved in libraries and religious institutions that contain hagiographic texts, that is texts recounting the lives of saints. In this article, we apply quantitative tools to the resulting database to consider these codices from a new point of view. As such, we study their internal organization, that is the order in which their texts are arranged. We first present a visualization tool that allows to grasp this structure at a glance. Then, we describe a model to automatically classify manuscripts according to their internal organization, based on a constrained spline regression. The results of this classification task make it possible to identify the manuscripts that have a particular internal organization, called per circulum anni (following the course of the year), and thus to study their properties. Furthermore, they open the possibility to obtain clues regarding the origin of some codices and potential kinship links between them. [ABSTRACT FROM AUTHOR]

During the current worldwide pandemic, media coverage of COVID-19 influenced popular perceptions and provided guidance on how to deal with the crisis. However, prior research may have been limited by a singular approach and the portrayal of COVID-19 in mainstream newspapers in China has not been fully explored. This study utilised mixed-methods research, incorporating automated analysis (n = 308 articles) and manual (n = 52 articles) thematic analysis to unravel and illustrate the prominent topics and themes in China Daily. The results showed that although China Daily initially depicted COVID-19 as a "bane", it has since portrayed it as a relative "boon." Positive themes were identified, like prosociality, cooperation, pandemic recovery and informativeness, while themes of political tension emerged, like Occidentalism. The current study advances our understanding of COVID-19 news representations by harnessing mixed-methods research, which reduces subjective bias and offers a more complete picture. Moreover, it is significant in helping to understand journalistic practice and how China, a state-controlled and ideology-dominated mediascape, has depicted COVID-19 while facing international stigma, conspiracy and blame. [ABSTRACT FROM AUTHOR]

Background: Vehicle suspension systems are vital components necessary for ensuring passenger comfort, vehicle stability, and overall safety. The primary function of the suspension system is to mitigate shocks and vibrations resulting from irregular road conditions, guaranteeing a smooth and steady ride for passengers. The damping characteristics crucially depend on the design of the orifice and the fluid flow properties within the damping system. Purpose: This comprehensive research delves into modifications of orifices and fluid flow dynamics within automotive suspensions to enhance damping effectiveness. Methods: The review analyzes orifice designs, encompassing fixed, variable, and electronically controlled valves, and assesses their influence on damping efficiency. Additionally, it explores multiple damping fluids, such as hydraulic, magnetorheological, and electrorheological fluids, alongside emerging technologies like nanofluids and intelligent fluids. Furthermore, the paper delves into applying computational fluid dynamics (CFD) and numerical modelling techniques for simulating fluid flow within suspension dampers. Results: The paper emphasizes the significance of orifice design and fluid flow parameters in enhancing damping characteristics. The study offers insights on how various orifice types, geometries, and fluid technologies can improve damping efficiency. Advancements in computational fluid dynamics (CFD) and numerical modelling techniques enhance the prediction and optimization of damping behaviour. Conclusion: Engineers and researchers can enhance the creation of advanced suspension systems with improved ride comfort, stability, and performance by grasping the principles and recent progress in orifice and fluid flow adjustments. Considerations of cost-effectiveness, manufacturability, and dependability are essential for successfully incorporating these improvements into commercial vehicle suspensions. [ABSTRACT FROM AUTHOR]

This study presents an analytical solution for static buckling and free vibration analysis of bi-dimensional functionally graded (2D-FG) metal-ceramic porous beams. To achieve this goal, equations of motion for the beam are derived by using Hamilton's principle and then the derived equations were solved in the framework of Galerkin's well-known analytical method for solution of equations. The material properties of the beam are variable along with thickness and length according to the power-law function. During the fabrication of functionally graded materials (FGMs), porosities may occur due to technical problems causing micro-voids to appear. Detailed mathematical derivations are presented and numerical investigations are performed, while emphasis is placed on investigating the effect of various parameters such as FG power indexes along both directions of thickness and length, porosity, and slenderness ratios (L/h), on the non-dimensional frequency and static buckling of the beam based on new higher deformation beam theory. The accuracy of the proposed model is validated based on comparisons of the results with the accepted studies. According to the result in both buckling and vibration analysis, the presented modified transverse shear stress along the thickness has shown closer consequences in comparison with TBT. [ABSTRACT FROM AUTHOR]

Abstract Radical S‐adenosyl‐L‐methionine (SAM) enzymes couple the reductive cleavage of SAM to radical‐mediated transformations that have proven to be quite broad in scope. DesII is one such enzyme from the biosynthetic pathway of TDP‐desosamine where it catalyzes a radical‐mediated deamination. Previous studies have suggested that this reaction proceeds via direct elimination of ammonia from an α‐hydroxyalkyl radical or its conjugate base (i.e., a ketyl radical) rather than 1,2‐migration of the amino group to form a carbinolamine radical intermediate. However, without a crystal structure, the active site features responsible for this chemistry have remained largely unknown. The crystallographic studies described herein help to fill this gap by providing a structural description of the DesII active site. Computational analyses based on the solved crystal structure are consistent with direct elimination and indicate that an active site glutamate residue likely serves as a general base to promote deprotonation of the α‐hydroxyalkyl radical intermediate and elimination of the ammonia group.

This study focuses on gene cloning, expression, biochemical and analytical characterization along with structural and functional characterization of collagenase followed with molecular docking, dynamics study and Molecular Mechanics Poisson-Boltzmann Surface Area (MMPBSA). The collagenase gene identified from the genome of the novel collagenase Bacillus siamensis strain Z1 is introduced into E.coli DH5α, subsequently expressed in E.coli BL21 (DE3) withisopropyl β −d – 1 − thiogalactopyranoside(IPTG) induction and further affinity purified yielding in ∼ 89.4 kDa recombinant collagenase which demonstrated alkali characteristics and thermostability determined by thermodynamic parameters. Recombinant collagenase revealed good stability when exposed to diverse biochemical components. The recombinant collagenase identity was confirmed through matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) showing specific mass peaks and via N-terminal sequence analysis as MTAVNQTISK. Moreover, the concluded N-terminal amino acid sequence from Edman degradation displayed significant resemblance. The structural and functional analysisof recombinant collagenase was analysed by Circular dichroism (CD), Proton nuclear magnetic resonance (1H NMR) spectrometry and Thermogravimetric analysis (TGA). The recombinant collagenase also showed gelatin liquefaction ability. The collagenase gene sequence is also assessed for structural and functional characterizations by using various computational tools and revealed its classification in U32 family peptidase. A Grand average of hydropathicity index (GRAVY) score of −0.295 and instability index of 37.22 was obtained. Homology model of collagenase gene was generated by employing SWISS-MODEL and structure analysis by Ramachandran plot. Molecular docking of modelled collagenase with four different substrates was carried out by PyRx and Autodocking. Highest docking score of −12.7 kcal/mol was obtained for Alaska pollock hydroxyproline containing marine collagen peptide (APHCP). Subsequently, Molecular dynamics and simulations for highest score docked complex was assessed using GROningenMAchine for Chemical Simulations (GROMACS).

Medicinal plants are used widely in the treatment of various infectious diseases. One of these medical plants is Moroccan plants such as Anacyclus pyrethrum. In this study, the essential oil isolated from the leaves of Anacyclus pyrethrum (APEO) by the hydrodistillation method was analyzed using (GC/MS) analysis. A total of forty-four compounds were identified form the oil and the oxygenated monoterpenes were the most abundant class of compounds. The major identified compound is santolina alcohol (40.7 %), followed by germacrene-D (8.9 %). The in-vitro assessment of the antimicrobial efficacy of APEO encompassed an investigation involving six microbial strains, including two Gram-positive bacteria, four Gram-negative bacteria, and three fungal strains. The findings revealed noteworthy antibacterial and antifungal properties against all examined microorganisms, with inhibitory zone diameters ranging from 25.67 ± 0.06 mm to 25.19 ± 0.03 mm for Gram-positive bacteria and from 22.34 ± 0.01 mm to 14.43 ± 0.02 mm for Gram-negative bacteria, as determined through the disc-diffusion assay. In the case of antifungal activity, inhibitory zones ranged from 24.57 ± 0.04 mm to 18.37 ± 0.06 mm. Further evaluation revealed that the MIC values of Gram-positive bacteria were at the concentration 0.25 % v/v, while MBC values ranged from 0.25 % to 1.0 % v/v. The Gram-negative bacteria exhibited MIC values spanning from 0.5 % to 2.0 % v/v, with MBC values in the range of 0.5 %–2.0 % v/v. For the fungal strains, MIC values ranged from 0.5 % to 1.0 % v/v, while the MFC consistently remained at 1.0 % for all tested fungal strains. The assessment of the MBC/MIC and MFC/MIC ratios collectively indicates that A. pyrethrum EO possesses bactericidal and fungicidal attributes. The in silico study of bioavailability predictions for compounds in APEO based on six physicochemical properties show optimal physiochemical properties including size, lipophilicity, solubility, flexibility, and saturation. α-Pinene, limonene, germacrene D, and (E)-β-farnesene are non-polar due to their lack of polar groups, and the ADME profile indicates desirable properties for considering these compounds in drug development. Molecular docking investigation indicates that all the compounds of APEO reside well into the binding site of the DNA gyrase B enzyme of Staphylococcus aureus by mediating a number of significant interactions with the binding site residues. The ADME analysis suggested that the major compounds APEO possess desirable properties for further consideration in drug development. In light of these findings, APEO could serve as a natural source for the elaboration of new and active antimicrobial drugs.

Developing strategies to study reactivity and selectivity in flexible catalyst systems has become an important topic of research. Herein, we report a combined experimental and computational study aimed at understanding the mechanistic role of an achiral DABCOnium cofactor in a regio- and enantiodivergent bromocyclization reaction. It was found that electron-deficient aryl substituents enable rigidified transition states via an anion-π interaction with the catalyst, which drives the selectivity of the reaction. In contrast, electron-rich aryl groups on the DABCOnium result in significantly more flexible transition states, where interactions between the catalyst and substrate are more important. An analysis of not only the lowest-energy transition state structures but also an ensemble of low-energy transition state conformers via energy decomposition analysis and machine learning was crucial to revealing the dominant noncovalent interactions responsible for observed changes in selectivity in this flexible system.

The profound impacts of global changes on biodiversity necessitate a more comprehensive documentation, particularly at the microscale level. To achieve precise and rapid insights into this unique diversity, the choice of an ideal species candidate is crucial. Neurospora crassa, a well-established organism in the field of biology, emerges as a promising candidate for this purpose. In our study, we explore the potential of the Carboxypeptidase A1 (CPA1) enzyme as a valuable tool for profiling global diversity. Our investigation has revealed that CPA1 possesses distinctive characteristics, notably its conserved solvent accessibility. This unique feature makes CPA1 an invaluable asset for microscale studies of global changes. The insights presented in our study serve as a practical blueprint, showcasing the application of structural biology in understanding diversity and global changes within microscale environments.

Introduction. At the present stage of industrial development, the electromagnetic field is widely used in various technological processes. The force effect of an electromagnetic field on conductive materials is used in a class of technological operations called electromagnetic forming. Problem. Under the conditions of electromagnetic forming, the main element of the technological equipment – the inductor – is simultaneously subjected to the force impact with the workpiece. At certain levels of the electromagnetic field, the deformation of the inductor becomes so significant that it can lead to a loss of its efficiency. Goal. Computational analysis of a thin-walled curved workpiece and a two-turn inductor under the conditions of electromagnetic processing of the workpiece corner zone. Determining the distribution of quantitative characteristics of the electromagnetic field and the stress-strain state and conducting assessments based on them regarding the efficiency of the technological operation. Methodology. Computational modeling using the finite element method as a method of numerical analysis. The results on the distribution of quantitative characteristics of the electromagnetic field and components of the stress-strain state for a thin-walled workpiece and an inductor are obtained. It is shown that for the specified characteristics of the technological operation, the inductor remains operational, and plastic deformations occur in the workpiece. A series of calculations were carried out, in which some parameters of the technological system were varied. Originality. For the first time, the results of the calculation analysis of the quantitative characteristics distribution of the electromagnetic field of the deformation process for the «inductor – thin-walled curved workpiece» system are presented. Practical value. The presented design scheme of a curved thin-walled workpiece and a two-turn inductor, the method of calculation analysis and some obtained results can be used in the analysis of electromagnetic processing of thin-walled structures that contain curved elements.

For various daunting physical world structural optimization design problems, a novel multi-objective water strider algorithm (MOWSA) is proposed, and its non-dominated sorting (NDS) framework is explored. This effort is inspired by the recent proposals for the Water Strider Algorithm, a population-based mathematical paradigm focused on the lifespan of water strider insects. The crowding distance characteristic is integrated into MOWSA to improve the exploration and exploitation trade-off behavior during the advancement of the quest. Furthermore, the suggested a posteriori approach exercises the NDS technique to maintain population diversity, a key issue in meta-heuristics, especially for multi-objective optimization. Structural mass reduction and nodal deflection maximization are two diverse objectives for the posed design problems. At the same time, stress on the components and discrete cross-sectional areas are imposed on safety and side constraints, respectively. Eight planar and spatial truss design problems demonstrate the utility of the proposed MOWSA approach for solving complex problems where the performance analysis is based on ten globally accepted metrics. Moreover, MOWSA outcomes were compared with four state-of-the-art optimization techniques to measure the viability of the suggested algorithm. MOWSA outperforms other considered algorithms concerning computational run to achieve optimal solutions and their qualitative behavior over Pareto fronts. The Matlab code for MOWSA can be obtained from https://github.com/kanak02/MOWSA.

The operation of vertical axis wind turbines (VAWTs) to generate low-carbon electricity is growing in popularity. Their advantages over the widely used horizontal axis wind turbine (HAWT) include their low tip speed, which reduces noise, and their cost-effective installation and maintenance. A Farrah turbine equipped with 12 blades was designed to enhance performance and was recently the subject of experimental investigation. However, little research has been focused on turbine configurations with more than three blades. The objective of this study is to employ numerical methods to analyse the performance of the Farrah wind turbine and to validate the findings in comparison with experimental results. The investigated blade pitch angles included both positive and negative angles of 7, 15, 20 and 40 degrees. The k-ω SST model with the sliding mesh technique was used to perform simulations of a 14.4 million element unstructured mesh. Comparable trends of power output results in the experimental investigation were obtained and the assumptions of mechanical losses discussed. Wake recovery was determined at an approximate distance of nine times the turbine diameter. Two large complex quasi-symmetric vortical structures were observed between positive and negative blade pitch angles, located in the near wake region of the turbine and remaining present throughout its rotation. It is demonstrated that a number of recognised vortical structures are transferred towards the wake region, further contributing to its formation. Additional notable vortical formations are examined, along with a recirculation zone located in the turbine’s core, which is described to exhibit quasi-symmetric behaviour between positive and negative rotations.

Hepatitis B, a liver disease caused by the hepatitis B virus (HBV), poses a significant public health burden. The virus spreads through the exchange of bodily fluids between infected and susceptible individuals. Hepatitis B is a complex health challenge for individuals. In this research, we propose a nonlinear HBV mathematical model comprising seven compartments: susceptible, latent, acutely infected, chronically infected, carrier, recovered, and vaccinated individuals. Our model investigates the dynamics of HBV transmission and the impact of vaccination on disease control. Using the next-generation matrix approach, we derive the basic reproduction number R0{R}_{0} and determine the disease-free equilibrium points. We establish the global and local stability of the model using the Lyapunov function. The model is numerically solved using the higher-order Galerkin time discretization technique, and a comprehensive sensitivity analysis is carried out to investigate the impact of all physical parameters involved in the proposed nonlinear HBV mathematical model. A comparison was made of the accuracy and dependability with the findings produced using the Runge–Kutta fourth-order (RK4) approach. The findings highlight the critical need for vaccination, particularly among the exposed class, to facilitate rapid recovery and mitigate the spread of HBV. The results of this study provide valuable insights for public health policymakers and inform strategies for hepatitis B control and elimination.

Background: Gliomas are neoplasms of the central nervous system that originate in glial cells. The genetic characteristics of this type of neoplasm are the loss of function of tumor suppressor genes such as TP53 and somatic mutations in genes such as IDH1/2. Additionally, in clinical cases, de novo single nucleotide polymorphisms (SNP) are reported, of which their pathogenicity and their effects on the function and stability of the protein are known. Methodology: Non-synonymous SNPs were analyzed for their structural and functional effect on proteins using a set of bioinformatics tools such as SIFT, PolyPhen-2, PhD-SNP, I-Mutant 3.0, MUpro, and mutation3D. A structural comparison between normal and mutated residues for disease-associated coding SNPs was performed using TM-aling and the SWISS MODEL. Results: A total of 13 SNPs were obtained for the TP53 gene, 1 SNP for IDH1, and 1 for IDH2, which would be functionally detrimental and associated with disease. Additionally, these changes compromise the structure and function of the protein; the A161S SNP for TP53 that has not been reported in any databases was classified as detrimental. Conclusions: All non-synonymous SNPs reported for TP53 were in the region of the deoxyribonucleic acid (DNA) binding domain and had a great impact on the function and stability of the protein. In addition, the two polymorphisms detected in IDH1 and IDH2 genes compromise the structure and activity of the protein. Both genes are related to the development of high-grade gliomas. All the data obtained in this study must be validated through experimental approaches.

A novel series of seventeen 2‐(4‐chlorophenyl)‐1H‐benzo[d]imidazole‐N‐aryl acetamides derivatives 3(a–q) were synthesized by nucleophilic substitution of 2‐chloro‐N‐(aryl)‐acetamides 2(a–q) with 2‐(4‐chlorophenyl)‐1H‐benzo[d]imidazole (1) in N,N‐Dimethylformamide. The literature indicates that the primary compound, 2‐(4‐chlorophenyl)‐1H‐benzo[d]imidazole (1), not only serves as a synthetic precursor but also exhibit anthelmintic, antiviral, and antifungal activities. The synthesized compounds were estimated for their structures through elemental analysis and spectral data examination. All the compounds be subjected to evaluation for their antibacterial activity against Bacillus subtilis (NCIM 2920), Staphylococcus aureus (NCIM 2901), Escherichia coli (NCIM 2810), Pseudomonas aeruginosa (NCIM 5223), and antimycobacterial activity against Mycobacterium smegmatis (ATCC607). Compound 3 m, exhibit the highest antibacterial activity with a MIC value of 1.562 μg/ml against all tested bacterial strains and compound 3 k, exhibited the highest antimycobacterial activity with a MIC value of 3.96 μg/ml. Additionally, we performed docking investigations of the most active compounds within the active binding site of the co‐crystallized structure of Glucosamine‐6‐phosphate synthase (PDB ID: 2VF5) and Mycobacterium tuberculosis (PDB ID: 2X22). [ABSTRACT FROM AUTHOR]

AbstractAs part of this study, we used three-dimensional numerical simulations to look into mixed thermal convection in a nanofluid that flows in a partially heated cylindrical channel without being able to be compressed. Our study specifically focused on two distinct configurations: the investigation of mixed thermal convection in the laminar regime using a hybrid nanofluid under both porous and nonporous conditions. The study adds to the scientific understanding of heat transfer processes in complex fluid–solid systems and contributes to the ongoing advancement of knowledge in the fields of thermal engineering and nanofluid research. This research involved investigations into varying nanoparticle volume fractions (0%–4%), Reynolds numbers within the range of 200–800, Richardson numbers between 1 and 2, and a fixed Darcy number of Da=10−8. Our analytical methodology involved a thorough assessment of temperature, velocity, and heat distributions within the hybrid nanofluid. The study we did showed that adding nanoparticles made the base fluid’s effective thermal conductivity much better. This made the transfer rate go up. Specifically, the thermal conductivity of the Al2O3-CuO-water hybrid nanofluid displayed noteworthy improvement. Furthermore, the incorporation of a porous matrix substantially enhanced the overall efficiency of the heat transfer process. [ABSTRACT FROM AUTHOR]

Electrospray ionization mass spectrometry (ESI-MS) analysis is frequently associated with noncovalent adduct formation, both in positive and negative modes. Anion binding and sensing by mass spectrometry, notably more challenging compared to cation binding, will have major research potential with the development of appropriate sensors. Here, we demonstrated identification of stable bisquaternary dication adducts with trifluoroacetate (TFA−), Cl− and HSO4− in positive-mode ESI-MS analysis. The observed adducts were stable in MS/MS mode, leading to the formation of characteristic fragment ions containing a covalently bound anion, which requires bond reorganization. This phenomenon was confirmed by computational methods. Furthermore, given that anion detection and anion sensor chemistry have gained significant prominence in chemistry, we conducted an analysis of the fluorescent properties of bisquaternary ammonium compound as a potential anion sensor. [ABSTRACT FROM AUTHOR]

In the human race, Fatigue may contribute to a decline in efficiency. Fatigue is a risk factor for health and a component of quality degradation. The effects of Fatigue include sleep disorders, depression, and worry, all of which can lead to life-threatening issues. This project uses machine learning and deep learning techniques to identify a person's degree of Fatigue and its effects. The developed deep learning network can accurately distinguish between normal and exhausted states. This detection device uses physiological characteristics to guarantee high detection rates and accuracy. The project aims to recognize fatigue levels by examining the features extracted from the batch of images and classifying them into their respective class labels, such as Alert, Non-Vigilant, and Fatigued. To implement the detection procedures using deep structured learning that will yield very accurate image recognition and classification results, a large-scale image dataset is transported through efficient algorithm strategies and is processed to transform the data by labelling the patterns, tracking the correlations, and producing supreme results. The images will be diagnosed by employing the pre-trained models of the Convolutional Neural Networks (CNN), convolving through the hidden layers, applying the filters, and sharing the weights. Alex Net, Resnet50, and MobilenetV2 are the potential classifiers that will expand, filter, train, compress, and test through the neurons of the subjects. The layers and the non-linear functionalities are designed in the wake of the structured embedding of the model to deliver efficient metrics. The proposal offers the best accuracy for the established MobilenetV2 model with 99.8% accuracy and validates it with high-performance results. [ABSTRACT FROM AUTHOR]

This study examines the remarkable effectiveness of Withaferin-A (WA), a withanolide obtained from Withania somnifera (Ashwagandha), in encountering the mortiferous breast malignancy, a global peril. The predominant objective is to investigate WA's intrinsic target proteins and hedgehog (Hh) pathway proteins in breast cancer targeting through the application of in silico computational techniques and network pharmacology predictions. The databases and webtools like Swiss target prediction, GeneCards, DisGeNet and Online Mendelian Inheritance in Man were exploited to identify the common target proteins. The culmination of the WA network and protein–protein interaction network were devised using Stitch and String web tools, through which the drug–target network of 30 common proteins was constructed employing Cytoscape-version 3.9. Enrichment analysis was performed by incorporating Gprofiler, Metascape and Cytoscape plugins. David compounded the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and enrichment was computed through bioinformatics tools. The 20 pivotal proteins were docked harnessing Glide, Schrodinger Suite 2023-2. The investigation was governed by docking scores and affinity. The shared target proteins underscored the precise Hh and WA network roles with the affirmation enrichment P -value of <0.025. The implications for hedgehog and cancer pathways were profound with enrichment (P  < 0.01). Further, the ADMET and drug-likeness assessments assisted the claim. Robust interactions were noticed with docking studies, authenticated through molecular dynamics, molecular mechanics generalized born surface area scores and bonds. The computational investigation emphasized WA's credible anti-breast activity, specifically with Hh proteins, implying stem-cell-level checkpoint restraints. Rigorous testament is imperative through in vitro and in vivo studies. [ABSTRACT FROM AUTHOR]

This paper introduces the Julia programming language as a dynamic, cost-effective, and efficient framework for implementing structural analysis packages. To achieve this, the finite element method was implemented for plane frames addressing the elastic instability problem through the Finite Element Method (FEM). Julia is a language open source, multiplatform, high-level and high-performance for technical and scientific computing, its compiler allows you to achieve speeds comparable to languages such as C and FORTRAN, but with more productive development dynamics due to its programming flexibility. Benchmarks between Julia and MATLAB are employed to discuss the processing costs, the programming techniques and paradigms used for computational performance. The results demonstrate that Julia performed the same analysis as the language used for comparison in 88.40% of the time, in addition to the fact that in loops comparisons case it reached 41.7% of the time for iteration, confirming its significant potential as a development tool of computational packages for structural analysis and scientific computing in general. [ABSTRACT FROM AUTHOR]

With the rising population and urbanization in developing countries, the building sector must contribute to sustainable construction. To achieve this, it must consider suitable design methodology, circular financial models, and holistic processes like information modeling, as collaboration is the fundamental tool for producing better outcomes. In the present study, different design alternatives, one conventional and the other with the proposed materials and methods were analyzed computationally for their cost and environmental impacts with the help of a residential building case. The results show that sustainable construction practices, such as low cost and less carbon-emitting materials reduced the overall cost by 25% and carbon emissions by 20%. Moreover, vital practices are recommended to meet the circular economy's objectives in building construction. [ABSTRACT FROM AUTHOR]

Introduction. At the present stage of industrial development, the electromagnetic field is widely used in various technological processes. The force effect of an electromagnetic field on conductive materials is used in a class of technological operations called electromagnetic forming. Problem. Under the conditions of electromagnetic forming, the main element of the technological equipment – the inductor – is simultaneously subjected to the force impact with the workpiece. At certain levels of the electromagnetic field, the deformation of the inductor becomes so significant that it can lead to a loss of its efficiency. Goal. Computational analysis of a thin-walled curved workpiece and a two-turn inductor under the conditions of electromagnetic processing of the workpiece corner zone. Determining the distribution of quantitative characteristics of the electromagnetic field and the stress-strain state and conducting assessments based on them regarding the efficiency of the technological operation. Methodology. Computational modeling using the finite element method as a method of numerical analysis. The results on the distribution of quantitative characteristics of the electromagnetic field and components of the stress-strain state for a thin-walled workpiece and an inductor are obtained. It is shown that for the specified characteristics of the technological operation, the inductor remains operational, and plastic deformations occur in the workpiece. A series of calculations were carried out, in which some parameters of the technological system were varied. Originality. For the first time, the results of the calculation analysis of the quantitative characteristics distribution of the electromagnetic field of the deformation process for the «inductor – thin-walled curved workpiece» system are presented. Practical value. The presented design scheme of a curved thin-walled workpiece and a two)turn inductor, the method of calculation analysis and some obtained results can be used in the analysis of electromagnetic processing of thin-walled structures that contain curved elements. References 16, table 1, figures 6. [ABSTRACT FROM AUTHOR]