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The family of ternary Chalcogenides systems has been investigated for their potential applications in optoelectronic devices. We present first-principles calculations of structural, elastic, magnetic, optical properties, and the effective mass of the Sulvanite compounds NbTu2S4 (Tu = Fe, Rh) is determined by GGA + U. The electronic band gaps are NbFe2S4 (2.4 eV (up)/1.8 eV (dn) and NbRh2S4 (2.07 eV (up)/1.6 Ev (dn), which are comparable to other computed results. Optical properties such as absorption coefficient, dielectric function, energy loss function, reflectivity function, refractive index, and extinction coefficient have been calculated for the first time. There is no difference between the materials regarding transparency in the visible range. The low hole effective mass and high valence band indicate a P-type material with photovoltaic applications. Plasma frequencies are observed around 13 eV for both investigated crystals. Sulvanite crystals have effective masses computed from high symmetry points varying non-linearly. The elastic parameter was used to study elastic properties. It is observed that both crystals show an anisotropic nature and ductility. The optical properties suggest that these crystals could be suitable for optoelectronic devices. [ABSTRACT FROM AUTHOR]

Hydrogen storage has garnered significant research attention in recent times due to the favorable qualities of hydrogen as a clean energy reservoir. We adorned hexagonal boron nitride (h-BN) with Fe and Mn to employ it for hydrogen storage purposes. Density functional theory (DFT) utilized to investigate diverse properties, encompassing the hydrogen storage capabilities of h-BN modified with both Fe and Mn. Simulation results revealed that, in its unaltered state, h-BN forms weak van der Waals interactions with H 2 molecules, leading to a binding energy within the range of 0.28 eV and a desorption temperature below 200 K. Furthermore, the study seeks to evaluate the structural stability, electronic characteristics, adsorption tendencies, binding energies, and hydrogen storage capacity. Adsorption energies of H 2 molecules on Fe- and Mn-decorated h-BN falls within the practical range of −0.20 to −0.20 eV for 1H 2 to 14H 2 molecules and −0.17 to −0.20 eV for 1H 2 to 17H 2 molecules respectively making them appropriate for H 2 storage applications. Additionally, hydrogen storing capacity values for Fe- and Mn-decorated h-BN are 6.77 wt % for 14H 2 molecules and 7.03 wt %, for 17H 2 molecules respectively. Hybridization was observed between the states of H 2 and the d states of the system. At elevated temperatures, the molecular dynamics simulations using AIMD techniques significantly enhanced the thermal stability of hydrogen (H 2) molecules when they were adsorbed onto h-BN surfaces decorated with both Fe and Mn, outperforming other experimental conditions or configurations. Based on desorption temperature prediction from the Van't Hoff equation, Fe- and Mn-decorated h-BN exhibit potential as substrate materials for H 2 storage by moderately high temperatures. The results of our current work make recognized that Fe/Mn decorated h-BN monolayers are strong eye-getting base material for hydrogen capacity exhibitions at high temperatures. • DFT study is performed in Fe/Mn decorated hexagonal BN for hydrogen storage. • Fe/Mn atoms revealed robust binding energy (−3.83 eV/3.03 eV) towards h-BN. • H 2 interacted with Fe decorated BN with adsorption energies −0.20 eV (n = 14H 2). • Adsorption energies are in the range of −0.17 to −0.20 eV for Mn decorated h-BN. • The hydrogen storage capacity of Fe/Mn decorated h-BN is 6.77 wt %/7.03 wt %. [ABSTRACT FROM AUTHOR]

Earthworms are economically and environmentally very beneficial and their correct identification is very vital. In this study, an attempt has been made to taxonomically identify earthworm species based on morphological characters. The earthworms were collected by simple random sampling from eighteen study sites of Poonch division Pakistan, between April through October 2019 by diging and hand sorting methods were fixed in 10% formaldehyde solution and studied by using a stereomicroscope. The samples were then identified with the help of identification keys provided by Julka (2008) and Chih-Han (2016). The data gathered by studying various external morphological characteristics was statistically assessed by using the one-factor analysis of variance (ANOVA). The research findings revealed that a total of eleven earthworm species classified under two families and six genera were recognized. Moreover, a significant statistical relationship (Tukey test, P < 0.05) was recorded between each of the morphological variables like length, weight and total number of segments. Eisenia fetida was the dominant species of Poonch division as it was reported from most of the sites, whereas Amynthus hupeiensis and Perionyx excavatus were not previously reported in the country. By keeping in mind the ecological significance of earthworms, the country’s research centers should focus on preparing an atlas for advance identification in the future. [ABSTRACT FROM AUTHOR]

[Display omitted] In recent years, enormous efforts have been made to identify and manipulate the exotic electrical and magnetic properties at a two-dimensional (2D) limit of various exciting materials. The spin–orbit coupling (SOC) in 2D van der Waals (vdW) heterostructures opens a fascinating and versatile platform to implement the intriguing quantum-engineered spintronic devices for practical applications. This review comprehensively outlines the modern-era progress of investigating the inherent magnetism of atomically thin 2D materials. Firstly, in this review, the most recent developments of synthesis, characterizations, functionalities, and spin textures in 2D magnetic materials are summarized in detail. Secondly, we conferred the well-known phenomena related to the proximity effect, spin–orbit torque (SOT), spin valve magnetic tunnel junction (MTJ), spin field effect transistor (FET) and magneto memristive-based applications. In addition, we also explored the possible interplay between 2D magnetic materials and associated band topology for spin caloritronics. Finally, we provided our perspective on the recent and upcoming challenges and goals of this promising research area, which leads the 2D magnetic materials to the modern era of energy-efficient quantum computing. [ABSTRACT FROM AUTHOR]

AbstractThe present study was designed with the aim to study morphometric characterization as well as phylogeny and diversity of the local Surguli goat at their breeding tract district Kohat through mitochondrial DNA region, i.e., Cytochrome C Oxidase Subunit One (CO1) gene. Morphometric data and blood samples were collected from thirty (30) pure goats. Morphometric analysis showed that sex had significant effect (p < 0.05) on body weight, body length, hearth girth and horn length while no significant effect (p > 0.05) was observed for other characteristics. The results also indicated that age had significant effect (p < 0.05) on height at rump, ear length, horn length and tail length while no significant effect (p > 0.05) was observed for other characteristics. The phylogenetic analysis through CO1 nucleotide sequences within nucleotide range 1–767 showed nine polymorphic sites segregating into eight haplotypes. The mean intraspecific diversity and mean interspecific diversity were calculated as 0.23 and 2.36%, respectively. Phylogenetic tree revealed that Capra Ibex and native Surguli goat have common ancestors. The morphometric and molecular results obtained from the present study can be exploited as a selection tool for breeding and overall improvement. [ABSTRACT FROM AUTHOR]

This paper discusses additive manufacturing (AM) and topology optimization (TO) and their relationship with industrial revolution 4.0. An overview of different AM techniques is given, along with the importance of design for manufacturing and assembly in progressing AM. The potential of AM to build complicated geometries with great precision has attracted a lot of interest in recent years. TO, one of the major enabling technologies in AM, has been essential in building compliant systems with improved performance across numerous industries. The development of hybrid mechanisms that integrate both compliant and stiff pieces because of improvements in "TO" algorithms has improved their usefulness and efficiency. Augmented realty and digital twins (DTs) have been used with "TO" to improve product design visualization and collaboration. Synergies between IN 4.0, TO, and AM have been discussed along with their cross-domain relevance. Machine learning involvement for more robust integration of IN 4.0 with TO and AM have also been discussed. The development of the Digital Triad, which combines DTs, digital threads, and digital trust to enable effective and secure data sharing and cooperation, is the result of the convergence of internet-of-things, cloud computing, and big data analytics. However, concerns about data privacy and cybersecurity still need to be resolved. The use of machine learning algorithms for cyberattack detection and mitigation as well as secure block chain-based frameworks for managing intellectual property rights are just a few of the frameworks and tactics that researchers have suggested to lower cybersecurity risks in AM systems. The establishment of new standards and guidelines for the cybersecurity of AM systems is anticipated to result from ongoing research in this area. [ABSTRACT FROM AUTHOR]

Cognitive disorders affect various cognitive functions that can have a substantial impact on individual’s daily life. Alzheimer’s disease (AD) is one of such well-known cognitive disorders. Early detection and treatment of cognitive diseases using artificial intelligence can help contain them. However, the complex spatial relationships and long-range dependencies found in medical imaging data present challenges in achieving the objective. Moreover, for a few years, the application of transformers in imaging has emerged as a promising area of research. A reason can be transformer’s impressive capabilities of tackling spatial relationships and long-range dependency challenges in two ways, i.e., (1) using their self-attention mechanism to generate comprehensive features, and (2) capture complex patterns by incorporating global context and long-range dependencies. In this work, a Bi-Vision Transformer (BiViT) architecture is proposed for classifying different stages of AD, and multiple types of cognitive disorders from 2-dimensional MRI imaging data. More specifically, the transformer is composed of two novel modules, namely Mutual Latent Fusion (MLF) and Parallel Coupled Encoding Strategy (PCES), for effective feature learning. Two different datasets have been used to evaluate the performance of proposed BiViT-based architecture. The first dataset contain several classes such as mild or moderate demented stages of the AD. The other dataset is composed of samples from patients with AD and different cognitive disorders such as mild, early, or moderate impairments. For comprehensive comparison, a multiple transfer learning algorithm and a deep autoencoder have been each trained on both datasets. The results show that the proposed BiViT-based model achieves an accuracy of 96.38% on the AD dataset. However, when applied to cognitive disease data, the accuracy slightly decreases below 96% which can be resulted due to smaller amount of data and imbalance in data distribution. Nevertheless, given the results, it can be hypothesized that the proposed algorithm can perform better if the imbalanced distribution and limited availability problems in data can be addressed. [ABSTRACT FROM AUTHOR]

Dicrocoelium lancet flukes cause significant production loss in ruminant livestock. Although co-infection with multiple Dicrocoelium species within a host is common, techniques for studying the composition of these complex parasite communities are lacking. The pathogenicity, epidemiology, and therapeutic susceptibility of different helminth species vary, and little is known about the interactions that take place between co-infecting species and their hosts. Here, we describe the first applicationof metabarcoding deep amplicon sequencing method to studythe Dicrocoelium species in sheep and goats. First, rDNA ITS-2 sequences of four Dicrocoelium species (Dicrocoelium dendriticum, Dicrocoelium hospes, Dicrocoelium orientalis, and Dicrocoelium chinensis) were extracted from the NCBI public database. Phylogenetic analysis revealed separate clades of Dicrocoelium species; hence, molecular differentiation between each species is possible in co-infections. Second, 202 flukes belonging to seventeen host populations (morphologically verified as belonging to the Dicrocoelium genus) were evaluated to determine the deep amplicon sequencing read threshold of an individual fluke for each of the four species. The accuracy of the method in proportional quantification of samples collected from single hosts was further assessed. Overall, 198 (98.01%) flukes were confirmed as D. dendriticum and 1.98% produced no reads. The comparison of genetic distances between rDNA ITS-2 revealed 86% to 98% identity between the Dicrocoelium species. Phylogenetic analysis demonstrated a distinct clustering of species, apart from D. orientalis and D. chinensis, which sit very close to each other in a single large clade whereas D. hospes and D. dendriticum are separated into their own clade. In conclusion each sample was identified as D. dendriticum based on the proportion of MiSeq reads and validated the presence of this group of parasites in the Gilgit Baltistan and Khyber Pakhtunkhwa provinces of Pakistan. The metabarcoding deep amplicon sequencing technology and bioinformatics pathway have several potential applications, including species interactions during co-infections, identifying the host and geographical distribution of Dicrocoelium in livestock, drug therapy response evaluation and understanding of the emergence and spread of drug resistance. [ABSTRACT FROM AUTHOR]

This study presents a method to enhance data processing by integrating a unidirectional analogue artificial neuromorphic memristor device with a piezoelectric nanogenerator, taking inspiration from biological information processing. A self‐powered unidirectional neuromorphic resistive memory device is proposed, comprising an ITO/ZnO/Yb2O3/Au structure combined with a high‐sensitivity piezoelectric nanogenerator (PENG) ITO/ZnO/Al. The memristor device is operated at a voltage sweep of ±4 V with a low operating current in a range of 1.4 µA. The filament formation is studied using a conductive mode atomic force microscope. The integration enables the creation of a self‐powered artificial sensing system that converts mechanical stimuli from the PENG into electrical signals, which are subsequently processed by analogue unidirectional neuromorphic device to mimic the functionality of a neuron without requiring additional circuitry. This emulation encompasses crucial functions such as potentiation, depression, and synaptic plasticity. Furthermore, this study highlights the potential for hardware implementations of neural networks with a weight change of memristor device with nonlinearity (NL) of potentiation and depression of 1.94 and 0.89, respectively, with an accuracy of 93%. The outcomes of this research contribute to the progress of next‐generation low‐power, self‐powered unidirectional neuromorphic perception networks with correlated learning and trainable memory capabilities. [ABSTRACT FROM AUTHOR]

This article examines the role of legal structure in explaining financial development in twenty-three emerging markets, which has not been explored in institutional economics literature before. This study relied on Pedroni, and Kao cointegration tests, which is followed by the renowned panel cointegration technique. The results of the Pedroni and Kao cointegration tests show that the variables understudy is cointegrated in the long-run. These findings are confirmed by the panel cointegration showing that legal structure (LS) has positive impact on financial development (FIND) in long-run that support Law and Finance, and New Institutional Economics theories in emerging markets. This study is the first to directly examine the long-run impact of LS on FIND in emerging markets, and the result remains consistent across alternative measure of FIND. The findings of this study have important policy implications for emerging markets. Policymakers should focus on creating a legal environment that is conducive to financial development. This includes strengthening the legal framework, improving regulatory regimes, and promoting market autonomy. Additionally, policymakers should work to attract foreign investment, which can help spur economic growth and development in emerging markets. The findings of the study are consistent across battery of robustness testing. [ABSTRACT FROM AUTHOR]

Pyrazinamide, an antituberculosis but documented toxic drug, is subjected to computational investigation along with the metal complexes via a DFT approach to predict the structure-activity and structure-toxicity relationship. 6-31G(d,p) basis set was used for Zn, Ni, Mn, Fe, and Co, while the SDD basis set was applied to Cu, Cr, Cd, and Hg. Several reactivity parameters and charge distribution were calculated and the reactivity profile was estimated. The complexes were found to be soft and polarizable which could be responsible for their binding with bacterial targets to inhibit their growth. In contrast, pyrazinamide which is found to be hard among all is susceptible to being toxic. Moreover, the electronegative nature of the complexes can endow them with a better antibacterial effect. Since metal complexes have been found to be less toxic and more biologically interactive by computational methods, they can be employed as potent drugs for the cure of tuberculosis. [ABSTRACT FROM AUTHOR]

Green Hydrogen (H 2 via renewable-driven electrolysis) is emerging as a vector to meet net-zero emission targets, provided it is produced with a low life cycle impact. While certification schemes for green H 2 have been introduced, they mainly focus on the embodied emissions from energy supply during electrolyser operation. This narrow focus on just operation is an oversight, considering that a complete green H 2 value chain also includes the electrolyser's manufacturing, transport/installation, and end-of-life. Each step of this chain involves materials and energy flows that impart impacts that undermine the clean and sustainable status of H 2. Therefore, holistic and harmonised assessments of the green H 2 production chain are required to ensure both economic and environmental deployment of H 2. Herein, we conduct an overarching environmental assessment encompassing the production chain described above, using Australia as a case study. Our results indicate that while the energy source has the most impact, material and manufacturing inputs associated with electrolyser production are increasingly significant as the scale of H 2 output expands. Moreover, wind power electrolysis has a greater chance of achieving green H 2 certification compared to solar powered, while increasing the amount of localised manufactured content and investment in end-of-life recycling of electrolyser components can reduce the overall life cycle impact of green H 2 production by 20%. • Life Cycle Assessment (LCA) approach for assessing the complete green H 2 value chain. • Application of the LCA of the Green H 2 in the Australian context. • End-Of-Life (EOL) included in LCA to explore trade-off of components recycling on life cycle impact. • Life cycle impact reduction of (up to 20%) estimated by localising manufacturing and adopting EoL. [ABSTRACT FROM AUTHOR]

AbstractPurposeMethodologyFindingsPractical implicationsOriginalityThe research on social media adoption and use is on the rise in Pakistan. However, researchers did not focus on investigating the risks associated with social media use for library services. So, this study examines perceived risks of library services through social media in the university libraries of Pakistan. Also, suggest possible solution to overcome the observed risks.Using a structured questionnaire, a national-level survey was conducted. Respondents of the study were professional librarians designated as Head or Chief or University librarian representing their organization. The study was conducted in an organizational perspective and required a single response from each organization. The questionnaire was distributed among 181 university librarians working both in public and private sector university libraries in Pakistan. However, valid responses were 124 (69%).The Pakistani university libraries are using social media platforms for library services. However, the research findings reveal that there are several risks to offering library services through social media. Among the responded libraries, the libraries that do not use social media platforms for service delivery feel riskier compared to the libraries that offer library services through social media. It is also found that there is no formal policy on social media usage in the libraries.The research findings provide valuable insight to university administration, library social media users, and developers on how to consider the identified risks while designing state-of-the-art library services through social media. Also, the study findings may be easily generalized at national level due to the coverage of the whole population.This is a novel study that explores the perceived social media risks associated with using social media to offer library services. Also, the study is first attempt that covers whole population through a census survey in an organizational perspective. [ABSTRACT FROM AUTHOR]

This study examines the relationship between board diversity, measured as cognitive (tenure, expertise, and education) and demographic (age, gender, and nationality) diversities, and idiosyncratic risk for 2000 Chinese non-financial firms from 2008 to 2020. This study highlights that cognitive board diversity has a more significant impact than demographic board diversity in mitigating idiosyncratic risk. After conducting sensitivity analysis and addressing endogeneity, the Capital Asset Pricing Model and Two-Stage-Least-Square findings confirm the robustness of results across different idiosyncratic risk measures, revealing a notable influence of board diversity on idiosyncratic risk. This study's findings provide valuable insights for practitioners that demographic and cognitive-oriented diversities should be perceived as an essential part of corporate governance in influencing overall corporate performance. [ABSTRACT FROM AUTHOR]

Objective: To determine the level of knowledge and practices of laboratory staff regarding COVID-19 infection. Materials and methods: It was a Multicenter, Cross-sectional Descriptive, Questionnaire-based study done in the Pathology laboratory of Khyber Teaching Hospital and Hayatabad Medical Complex Peshawar. The participants were asked to fill out proformas after obtaining consent. The data was analyzed by SPSS. The normality of data was determined by the Shapiro-Wilks test. The difference in scores between demographic characteristics was determined by the Whitney U test and the Kruskal Wallis test. Kendall Tau determined the correlation between scores and demographics. b, point biserial and Spearman rho tests. A p-value of less than 0.05 was considered statistically significant. Results: The age of 89 study participants ranged from 15-58 years (mean age of 34±9.6). The male-to-female ratio was 15.6:1. Mean knowledge and practice scores were 10.19±1.66 and 10.2±2.4. Knowledge and practices were good in all participants except that 42 (45%) participants denied avoiding going to crowded places. Mean knowledge score and practice score were higher in females (as compared to males) and in married participants (as compared to unmarried ones), but lower in undergraduates. There was no correlation between scores and demographic characteristics. Conclusion: The laboratory staff had good knowledge of COVID-19 and observed good practices. This shows the commitment of healthcare workers in Pakistan towards themselves and society in the crucial situation of COVID-19 infection. The scores were not associated with gender, marital status, or education level. [ABSTRACT FROM AUTHOR]

The aim of the study is to explore the relationship between marital satisfaction, emotion regulation, and self-efficacy in women experiencing Postpartum Depression. The sample size consisted of N=100 participants which were women with PPD symptoms who visited the OPD of gynecology ward of government hospitals. The selected population age average was 19 to 35 years. Urdu translated scales of Comprehensive Marital Satisfaction Scale, Depression Anxiety Stress Scale, Emotion Regulation Questionnaire and General Self-Efficacy Scale were used for data collection. The information was analyzed using Pearson Product Moment Correlation, Moderation Analysis and Multiple Regression via SPSS 21 version. The conclusion of this research has been demonstrated that there is weak positive correlation between Marital Satisfaction and severity of PPD in women. This study suggests that as Marital Satisfaction increases, the impact of PPD symptoms decreases. It also showed that Self-Efficacy has a strong and significant effect on PPD symptoms as a moderator. [ABSTRACT FROM AUTHOR]

Key Clinical Message: Successful management of cervical tuberculosis and severe kyphosis was achieved using a PEEK expandable cage and titanium plate, demonstrating favorable outcomes in restoring cervical alignment and stability. This approach represents a promising alternative for addressing complex cervical pathologies, highlighting the potential of PEEK‐based interventions in surgical management. Cervical tuberculosis can lead to severe vertebral destruction and kyphosis, posing challenges in surgical management. Recent advancements, including the use of polyetheretherketone (PEEK) expandable cages and titanium plates, show promise in addressing multilevel cervical pathologies. This report details the successful treatment of a 27‐year‐old male with cervical tuberculosis and severe kyphosis. Surgical intervention involved prevertebral abscess evacuation, C5‐C7 corpectomy, and insertion of a PEEK expandable cage with an anterior titanium plate. Postoperative care included a Philadelphia collar, and follow‐up demonstrated restored cervical alignment and stability. The use of PEEK‐based surgical interventions, as demonstrated in this case, represents a significant evolution in managing complex cervical conditions. The successful outcome highlights the potential benefits of PEEK expandable cages in addressing cervical tuberculosis and kyphosis. Further research is needed to validate these findings and establish PEEK‐based interventions as a viable alternative in such cases. [ABSTRACT FROM AUTHOR]

In the last two decades, structured light patterns with orbital angular momentum (OAM) have been extensively utilized in quantum cryptography or quantum key distribution (QKD), which is generally considered an unconditionally secure method of a secret key transmission between two distant communicating entities. High-dimensional encoding of quantum bits in quantum key distribution improves the security and information-carrying capability of a quantum signal. However, the free space optical channel significantly degrades the efficiency of such communication due to the aberration of OAM states under atmospheric turbulence. This paper focuses on analyzing the impact of atmospheric turbulence on QKD error-rates. These aid in analyzing the security of such communication over the quantum channel in the presence of an intruder (man-in-the-middle). Our results showed that the turbulence under normal conditions does not significantly affect the successful transmission of secret quantum bits between sender and receiver. Furthermore, our results show a unique pattern of variation in the quantum bit error rate, index transmission error rate and efficiency that helps to clearly detect the presence of an intruder as a result of medium-level turbulence. [ABSTRACT FROM AUTHOR]

This research presents a comprehensive investigation to enhance understanding of subsurface structural complexities within the Upper Cretaceous Pab Sandstone reservoir level in a gas-producing field within the Kirthar Fold Belt of the Southern Indus Basin, Pakistan. The seismic interpretation for accurate structural delineation and characterization of intricate fault systems is often challenging in Fold and Thrust Belt settings. The 3D structural maps of Upper Cretaceous Pab Sandstone at the reservoir level and the application of the ant-tracking attribute for fault extraction improve the structural understanding of the gas-producing field in the Kirthar Fold Belt in the Southern Indus Basin, Pakistan. Attributeassisted 3D seismic interpretation has revealed several subsurface structure elements, including a large thrusted anticline extended towards the north-south, the pattern of north-south oblique ramp thrusts on the southeastern flank, and a combination of easterly vergent thrusts with a counterback thrust creating a local pop-up structure in the area. A 3D structural model at the reservoir level was generated using horizon and fault framework volume-based modeling approach, serving as a structural model for Pab sandstone. The structural smoothing, variance and ant-tracking attribute were applied iteratively to get the best results and correlated with manual interpretation. 3D seismic interpretation and application of anttracking for fault extraction identifies discrete structural styles and revealed that all thrusting occurred due to compressional tectonics of the Plio- Pleistocene period. The apparent different styles result from the reactivation of earlier extensional fault systems and probably during phased periods of compression. The resulting 3D reservoir model can be used as an input to populate petrophysical properties and results can be extended for future field development plans. Integration of well and 3D seismic data interpretation and the application of automatic fault extraction techniques are highly recommended in structurally complex areas and have an equal implication for worldwide basins with similar conditions for reliable structural interpretation in Fold and Thrust Belts with structural complexity. [ABSTRACT FROM AUTHOR]

This document is a guest editorial for a special issue of the journal "Fluctuation & Noise Letters" on the topic of economic policy uncertainty and the energy stock market. The editorial highlights the importance of stable economic policies for consistent economic growth and discusses the negative correlation between economic policy uncertainty and the energy stock market. It also explores the integration of machine learning and artificial intelligence in finance and their potential to reduce economic policy uncertainty. The special issue includes 14 peer-reviewed papers that cover various aspects of energy economics, energy materials, energy stock market prediction, green energy commercialization, and renewable energy dynamics in society. [Extracted from the article]

This study explores the impact of axial conduction and viscous dissipation on heat transfer inside a tube by employing the Casson fluid model. A semianalytical approach is employed to handle the considered problem. The application of the separation of variable technique converts the heat equation into a set of ordinary differential equations. A built‐in function bvp4c in Matlab is adopted for numerical solutions in terms of eigenvalues and eigenfunctions. The obtained results are thoroughly discussed through pictorial representations. The finding shows that the Peclet and Brinkman numbers could not be ignored where an accurate temperature is essential for the final product. The both Peclet numbers and Brinkman numbers have a strong influence on the entrance temperature profile of the tube. In addition, the viscoplastic parameter raises the local Nusselt number in developing and fully developed regions of the tube. This analysis may be helpful in the advancement of thermal devices that are used to diagnose many diseases. [ABSTRACT FROM AUTHOR]

Semiconductors with direct band gaps are outstanding for their use in most optoelectronic devices specifically for solar cells. Here we studied the optoelectronic, thermodynamic, and thermoelectric features of novel MgACu3Se4 (A = Sc, Y) semiconductors. Cutting-edge computations that employs density functional theory is used. The predicted density of state plots validated the electronic band structure results. A direct type of energy gap with a semiconducting behavior was noticed from the electronic band profiles of both materials. The significant optical response for the incident photon energy range of 0–14 eV is also revealed and discussed in detail. By using the quasi-harmonic Debye model, we additionally examined the thermodynamic characteristics of these quaternary systems and analyzed how their cell volume, Debye temperature, heat capacity, thermal expansion coefficient, and Grüneisen constant change over the pressure and temperature range from 0 up to 20 GPa and 0 up to 1200 K, respectively. Furthermore, the important thermoelectric transport parameters were evaluated and discussed for their thermoelectric application. [ABSTRACT FROM AUTHOR]

The goal of this paper is to find exact solutions to the improved modified Korteweg-de Vries (mKdV) equation with a conformable derivative using the Jacobi elliptic function expansion method. The improved mKdV equation is a prominent mathematical model in the realm of nonlinear partial differential equations, with widespread applicability in diverse scientific and engineering domains. This study leverages the well-known effectiveness of the Jacobi elliptic function expansion method in solving nonlinear differential equations, specifically focusing on the intricacies of the improved mKdV problem. The investigation reveals innovative and explicit solutions, providing insight into the dynamics of the related physical processes. This paper provides a comprehensive examination of these solutions, emphasizing their distinct features and depictions using Jacobi elliptic functions. These findings are especially advantageous for specialists in the fields of nonlinear science and mathematical physics, providing significant insights into the behavior and development of nonlinear waves in various physical situations. This work also contributes to our knowledge of the improved mKdV equation and shows that the Jacobi elliptic function expansion method is a useful tool for solving complex nonlinear situations. The study is enhanced with graphical illustrations of various solutions, which further enhance its analytical complexity. [ABSTRACT FROM AUTHOR]

Concrete with fiber reinforcement is stronger and more ductile than concrete without reinforcement. Significant efforts have been made to demonstrate the properties and enhancements of concrete after reinforcement with various types and shapes of fibers. However, the issue of optimization in the reinforcement process is still unanswered. There is no academic study in the literature now available that can pinpoint the ideal fiber type, quantity, and shape and, more crucially, the overall technical viability of the reinforcement. The parametric analysis in this study determines the ideal shape, size, and proportion of fibers. The input and output parameters were separated from the optimization design variables. Input parameters included assessment of samples of fresh and mechanical concrete properties and the influence of type, length, and percentage of fiber on concrete performance. The aim was to establish the most efficient relationship between fiber dose and dimension to optimize the combined responses of workability and splitting tensile, flexural, and compressive strength. The mechanical and fresh properties of concrete reinforced with four different fibers, PFRC‐1, PFRC‐2, SFRC‐1, and SFRC‐2, were tested. The analysis showed that SFRC‐2‐20 mm‐1%, with compressive, split tensile, flexural, and workability values of 44.7 MPa, 3.64 MPa, 5.3 MPa, and 6.5 cm respectively, was the most effective combination among the materials investigated. The optimization technique employed in this study offers new, important insights into how input and output parameters relate to one another. [ABSTRACT FROM AUTHOR]

As the global climate continues to change, plants will increasingly experience abiotic stress(es). Stomata on leaf surfaces are the gatekeepers to plant interiors, regulating gaseous exchanges that are crucial for both photosynthesis and outward water release. To optimise future crop productivity, accurate modelling of how stomata govern plant–environment interactions will be crucial. Here, we synergise optical and thermal imaging data to improve modelled transpiration estimates during water and/or nutrient stress (where leaf N is reduced). By utilising hyperspectral data and partial least squares regression analysis of six plant traits and fluxes in wheat (Triticum aestivum), we develop a new spectral vegetation index; the Combined Nitrogen and Drought Index (CNDI), which can be used to detect both water stress and/or nitrogen deficiency. Upon full stomatal closure during drought, CNDI shows a strong relationship with leaf water content (r2 = 0.70), with confounding changes in leaf biochemistry. By incorporating CNDI transformed with a sigmoid function into thermal‐based transpiration modelling, we have increased the accuracy of modelling water fluxes during abiotic stress. These findings demonstrate the potential of using combined optical and thermal remote sensing‐based modelling approaches to dynamically model water fluxes to improve both agricultural water usage and yields. [ABSTRACT FROM AUTHOR]

This paper presents a novel sound event detection (SED) system for rare events occurring in an open environment. Wavelet multiresolution analysis (MRA) is used to decompose the input audio clip of 30 seconds into five levels. Wavelet denoising is then applied on the third and fifth levels of MRA to filter out the background. Significant transitions, which may represent the onset of a rare event, are then estimated in these two levels by combining the peak-finding algorithm with the K-medoids clustering algorithm. The small portions of one-second duration, called 'chunks' are cropped from the input audio signal corresponding to the estimated locations of the significant transitions. Features from these chunks are extracted by the wavelet scattering network (WSN) and are given as input to a support vector machine (SVM) classifier, which classifies them. The proposed SED framework produces an error rate comparable to the SED systems based on convolutional neural network (CNN) architecture. Also, the proposed algorithm is computationally efficient and lightweight as compared to deep learning models, as it has no learnable parameter. It requires only a single epoch of training, which is 5, 10, 200, and 600 times lesser than the models based on CNNs and deep neural networks (DNNs), CNN with long short-term memory (LSTM) network, convolutional recurrent neural network (CRNN), and CNN respectively. The proposed model neither requires concatenation with previous frames for anomaly detection nor any additional training data creation needed for other comparative deep learning models. It needs to check almost 360 times fewer chunks for the presence of rare events than the other baseline systems used for comparison in this paper. All these characteristics make the proposed system suitable for real-time applications on resource-limited devices. [ABSTRACT FROM AUTHOR]

Dibenzyltoluene (H0-DBT), a Liquid Organic Hydrogen Carrier (LOHC), presents an attractive solution for hydrogen storage due to its enhanced safety and ability to store hydrogen in a concentrated liquid form. The utilization of machine learning proves essential for accurately predicting hydrogen storage classes in H0-DBT across diverse experimental conditions. This study focuses on the classification of hydrogen storage data into three classes, low-class, medium-class and high-class, based on the hydrogen storage capacity values. We introduce Hydrogen Storage Prediction with the Support Vector Machine (HSP-SVM) model to predict the hydrogen storage classes accurately. The performance of the proposed HSP-SVM model was investigated using various techniques, which included 5-Fold Cross Validation (5-FCV), Resubstitution Validation (RV), and Holdout Validation (HV). The accuracy of the HV approach for the low, medium, and high class was 98.5%, 97%, and 98.5%, respectively. The overall accuracy of HV approach reached 97% with a miss clarification rate of 3%, whereas 5-FCV and RV possessed an overall accuracy of 93.9% with a miss clarification rate of 6.1%. The results reveal that the HV approach is optimal for predicting the hydrogen storage classes accurately. [ABSTRACT FROM AUTHOR]

A number of coating techniques have been used to improve the processability of high explosives. These techniques are typically used for developing compositions, such as boosters and fillers. The most typically used technique is the "solvent–slurry coating". Several compositions of polymer-bonded explosives have been industrialized using this technique. The NUPC-6 polymer-bonded powder composition of hexahydro-1,3,5-trinitro-1,3,5-triazine is optimized using the solvent–slurry coating. It involved multiple processes, i.e., preparing a slurry of high explosives in an aqueous phase, dissolving the modified polymer binder in an organic solvent, maintaining both the solvent and slurry at controlled temperatures, introducing polymer binder solution and ingredients in the slurry, distilling the solvent, mixing contents homogeneously, filtering the polymer-coated hexahydro-1,3,5-trinitro-1,3,5-triazine composition, and drying in a vacuum oven. The phlegmatizing and hydrophobic agents enhance flowability and hydrophobicity. The mass flow rate, bulk density, tapped density, compressibility index, and Hausner ratio are determined to evaluate its flowability during filling operations. The results show that the composition is flowable using a filling funnel, with a 150 mm upper diameter, 25 mm flow diameter, and 136 mm total funnel height. The raw polymer binder was modified using diisooctylsebacate and SAE-10 oil. The additives in the composition enhance its flowability, and it might be used in underwater applications. [ABSTRACT FROM AUTHOR]

The unbalanced ratio of the environmental components adversely impacts the ecosystem because of dangerous gases at high levels. One of them, CO gas is the colourless, tasteless, and odourless gas that becomes difficult to identify by human sensory organs. Its accidental inhalation causes serious health problems. To overcome the dangerous and adverse effects of CO gas, the utilization of novel inorganic Al12As12 and Ga12As12 nanocages has not yet been thoroughly investigated. To fill this gap, a comparative investigation of the sensing capability of both nanocages is accomplished by employing first-principle DFT and TD-DFT computations. The calculated adsorption energy values manifest both nanocages' remarkable adsorption response. The explored molecular electronic properties: the energy gap (~ 2.21 eV), softness (~ 0.45 eV), hardness(~ 1.11 eV), electrophilicity index(~ 10.64 eV), electrical conductivity (~ 1.98 × 109), and recovery time (~ 1.63 × 10−12 s−1) values ascertain the comparatively high reactivity and sensing response of the Ga12As12 nanocage towards CO gas. NBO analysis explored the presence of more effective ICT network in Ga12As12 nanocage by showing the effective interactions towards CO gas. UV–Vis analysis and NCI analysis explored the comparative maximum absorbance wavelength (550.04 nm) along with minimum excitation energy (2.25 eV) and comparatively highest noncovalent interactions, respectively, by Ga12As12 nanocage complexes. The thermodynamic analysis explored the spontaneity of the interaction process for both the systems but comparatively highest values of ∆fH0 and ∆rG0 for Ga12As12 nanocage complexes that indicate the increased strength of the reaction mechanism. So, all the investigation parameters have proved the Ga12As12 nanocage and Al12As12 nanocage are helpful for environmental monitoring to detect CO gas, and the Ga12As12 nanocage is a promising influential sensing material and exhibits comparatively high sensitivity. [ABSTRACT FROM AUTHOR]

Recently, micro gas turbine (MGT) systems for combined heat and power (CHP) plants have attracted much attention due to their high combined energy efficiencies and low carbon emissions. Therefore, this study has focused on the performance and fuel flexibility analysis of a 5.5 kW MGT-CHP system coupled with a proton exchange membrane (PEM) electrolysis cell and a fuel cell unit for domestic applications. The simulation study includes an MGT unit that produces both heat and electricity, a low-temperature PEM electrolysis of H 2 O to produce H 2 fuel for the combustor, and a PEM fuel cell to generate electricity during system initialisation. The MGT unit in this study uses H 2 , hythane (20% H 2 + 80% C H 4), natural gas (NG) and methane (C H 4) fuels to investigate the thermal and electrical efficiency and C O 2 emission avoidance for each fuel utilisation. The result shows that the combustion of H 2 and hythane in the MGT combustor produces almost the same amount of nitrogen oxides (NOx) due to the lower reaction temperature of the combustor. Nearly 7% of C O 2 and C O emissions were avoided by replacing NG with hythane. C O 2 and C O emissions were avoided by burning H 2 instead of other fuels. Higher thermal efficiency was seen on the H 2 -fuelled MGT system. However, higher end-use costs were observed for the MGT system running on both H 2 and hythane fuels due to the higher purchase price of both fuels. The addition of a recuperator promoted lean combustion, which improved the overall efficiency of the proposed system. The outcome of the studied work achieved an efficiency of 82% for PEM electrolysis of H 2 O and an MGT-CHP combined efficiency of 96%. [Display omitted] • NG, CH 4 , hythane and H 2 fuelled MGT-CHP systems are introduced. • The electrolysis of H 2 O and H 2 fuel cell systems are proposed. • The hybrid system recorded low NOx and reduced carbon emissions. • The proposed system achieved an efficiency of 96% for the MGT unit. [ABSTRACT FROM AUTHOR]

AbstractManufacturers confront considerable difficulties when machining titanium and nickel-based alloys due to concerns related to surface integrity, tool wear, cutting forces and temperature regulation. In order to tackle these difficulties, the prevailing method consists of utilizing cutting fluids to cool and lubricate the machining interface. Nevertheless, the persistent use of these fluids presents significant hazards to both human health and the environment. Hence, it is imperative to investigate novel methodologies that can reduce or eradicate the reliance on lubricants. Surface texturing has become a practical method in this situation since it improves the tribological properties of cutting inserts. The main factors that lead to the improvement of tribology are the capture of debris, decreased contact area, and increased lubricating capacity. These factors work together to lower cutting forces, tool deterioration and the surface roughness of the work material. This study provides an extensive analysis of the existing literature regarding the consequences of tool texturing in the process of machining titanium and nickel-based alloys. It scrutinizes techniques that utilize textured tools to enhance machining performance and assesses their influence on several machining parameters. The study explores various techniques for improving performance by analyzing the impact of textured tools on tool wear, thermal profiles, cutting dynamics and surface integrity in different scenarios. These scenarios include dry conditions, high-pressure cooling (HPC), the use of solid lubricants, the application of minimum quantity lubrication (MQL) with and without nanoparticles and the effectiveness of hybrid cryogenic/MQL techniques. This review also provides a comprehensive sustainability analysis, covering both the environmental and economic effects of using textured tools and lubricoolant techniques. Furthermore, this study provides valuable insights for future academic research, identifying areas that are ready for further investigation in this field. [ABSTRACT FROM AUTHOR]

The acquisition of clean drinking water in regions with limited power sources has been a challenge of paramount concern. Solar stills have emerged as a popular and sustainable option for obtaining clean water in such regions. This process involves employing solar radiation to heat up water, which is then condensed to obtain potable water. The present study introduces a solar still system that is both cost-effective and energy-efficient, while simultaneously ensuring sustainability. Fabric-coated polyurethane rollers with capillary action enhance evaporation area, leading to notable performance improvements. Water vapour condensed on the cooling chamber's inclined aluminium plate and collected in the distillate chamber within the solar still. The thermal, energetic, and economic performance and productivity of the proposed model were evaluated. The fabricated solar still boasted maximum instantaneous system efficiency and exergy efficiency of approximately 62.16% and 7.67%, respectively. This system's cost-effectiveness and performance improvements are particularly noteworthy. The daily average distillate productivity of the proposed still was estimated at 1.14 L/m2, resulting in an annual production rate of 416.54 L/year. The estimated cost of producing 1 L of distillate was 0.023 $. [ABSTRACT FROM AUTHOR]

In this research, a comparative study of four Quantum Machine Learning (QML) models was conducted for fraud detection in finance. We proved that the Quantum Support Vector Classifier model achieved the highest performance, with F1 scores of 0. 9 8 for fraud and nonfraud classes. Other models like the Variational Quantum Classifier (VQC), Estimator Quantum Neural Network (QNN), and Sampler QNN demonstrate promising results, propelling the potential of QML classification for financial applications. While they exhibit certain limitations, the insights attained pave the way for future enhancements and optimization strategies. However, challenges exist, including the need for more efficient quantum algorithms and larger and more complex datasets. This paper provides solutions to overcome current limitations and contributes new insights to the field of QML in fraud detection, with important implications for its future development. [ABSTRACT FROM AUTHOR]

Background and Aims Cress seeds release allelochemicals that over-stimulate the elongation of hypocotyls of neighbouring (potentially competing) seedlings and inhibit their root growth. The hypocotyl promoter is potassium, but the root inhibitor was unidentified; its nature is investigated here. Methods Low-molecular-weight cress-seed exudate (LCSE) from imbibed Lepidium sativum seeds was fractionated by phase partitioning, paper chromatography, high-voltage electrophoresis and gel-permeation chromatography (on Bio-Gel P-2). Fractions, compared with pure potassium salts, were bioassayed for effects on Amaranthus caudatus seedling growth in the dark for 4 days. Key Results The LCSE robustly promoted amaranth hypocotyl elongation and inhibited root growth. The hypocotyl inhibitor was non-volatile, hot acid stable, hydrophilic and resistant to incineration, as expected for K+. The root inhibitor(s) had similar properties but were organic (activity lost on incineration). The root inhibitor(s) remained in the aqueous phase (at pH 2.0, 6.5 and 9.0) when partitioned against butan-1-ol or toluene, and were thus hydrophilic. Activity was diminished after electrophoresis, but the remaining root inhibitors were neutral. They became undetectable after paper chromatography; therefore, they probably comprised multiple compounds, which separated from each other, in part, during fractionation. On gel-permeation chromatography, the root inhibitor co-eluted with hexoses. Conclusions Cress-seed allelochemicals inhibiting root growth are different from the agent (K+) that over-stimulates hypocotyl elongation and the former probably comprise a mixture of small, non-volatile, hydrophilic, organic substances. Abundant components identified chromatographically and by electrophoresis in cress-seed exudate fitting this description include glucose, fructose, sucrose and galacturonic acid. However, none of these sugars co-chromatographed and co-electrophoresed with the root-inhibitory principle of LCSE, and none of them (in pure form at naturally occurring concentrations) inhibited root growth. We conclude that the root-inhibiting allelochemicals of cress-seed exudate remain unidentified. [ABSTRACT FROM AUTHOR]

The application of interleukin-17 (IL-17) inhibitors, including secukinumab, ixekizumab, brodalumab, and bimekizumab, are associated with elevated risk of candidiasis. These medications interfere with the IL-17 pathway, which is essential for maintaining mucosal barriers and coordinating the immune response against Candida species. The observational data and clinical trials demonstrate the increased incidence of candidiasis in individuals treated with IL-17 inhibitors. Brodalumab and bimekizumab pose a greater risk than secukinumab in eliciting candidiasis, whereas the data regarding ixekizumab are equivocal. Higher doses and prolonged treatment duration of IL-17 inhibitors increase the risk of candidiasis by compromising the immune response against Candida species. Prior to prescribing IL-17 inhibitors, healthcare professionals should comprehensively evaluate patients' medical histories and assess their risk factors. Patients should be educated on the signs and symptoms of candidiasis to facilitate early detection and intervention. Future research should focus on identifying the risk factors associated with candidiasis in patients receiving IL-17 inhibitors. Prospective studies and long-term surveillance are required to explore the impact of specific inhibitors on the incidence and severity of candidiasis and to evaluate the effectiveness of combination therapies, such as concurrent use of IL-17 inhibitors and prophylactic antifungal agents. [ABSTRACT FROM AUTHOR]

This contemporary article examines the transfer of heat properties and the flow behavior of water‐based nanofluid suspended with silver nanoparticles. These silver nanoparticles have a very huge thermal conductivity and hence it is presumed that the resulting nanofluid shall have enhanced thermal conductance. This article is more focused on the study of Ag−H2O$Ag - {H}_2O$ nanofluid flowing past a cylinder that is modeled mathematically using the cylindrical coordinate system. The initial modeling is designed using a system of partial derivatives while at a later stage, this system is transformed into a nonlinear group of ordinary differential equations (ODEs). The equations in this system are solved to obtain the dual solutions by implementing the RKF‐45 method which has a greater rate of convergence and additionally, it is computationally very effective. The findings of the study are dealt by plotting graphs and the discussions are based on the appearance of graphs. It is further noticed that the critical point (λc)$({{\lambda }_c})$ remains constant at −42.58$ - 42.58$ for any changes made in the values of heat generation/absorption coefficient. Similarly, the critical value remains constant at −42.6$ - 42.6$ for any change made in the values of the Eckert number. Meanwhile, it is also observed that the increase in the Eckert number increases the temperature absorbed by the nanofluid whereas it decreases the Nusselt number. Furthermore, the higher values of the velocity slip reduce the skin friction coefficient. [ABSTRACT FROM AUTHOR]

This paper explores the agentic capacities of inanimate objects and their role in shaping the affective atmospheres of women's markets in a post-conflict setting. To analyse this material affectivity, I draw on women's markets of Swat in Pakistan and the role of four selected objects including posters/notices, bras, mannequins and curtains in the generation, transmission and manipulation of affect. I ask, how objects matter in shaping the affectivity of women's markets during and after Swat's conflict? To answer this question, I draw on 36 semi-structured interviews with men traders (N = 18) and women customers (N = 18) along with my field notes. I found that centring our analyses upon gendered materiality of mundane objects allow us to capture nuances of unruly capacities and gendered affectivities of objects in the context of war and post-conflict environments. Moreover, my findings suggest that focussing on agentic capacities of objects enhance our understanding of the affective materiality of women's markets in the post-conflict setting. [ABSTRACT FROM AUTHOR]

In this paper, we present an innovative approach to acquire the exact solutions of the Shynaray-IIA equations (S-IIAE), by using the improved modified Sardar sub-equation method (IMSSEM). The S-IIAE are nonlinear and coupled partial differential equations that arise in various fields of physics and engineering such as optical fibers and ferromagnetic materials. The IMSSEM is applied to S-IIAE; we successfully derived exact solutions that accurately described the wave propagation behavior of the system under consideration. The obtained solutions include rational, trigonometric, and trigonometric hyperbolic function solutions. The obtained solutions are concise and offer a deeper insight into the dynamics and characteristics of the S-IIAE. Moreover, some of the new solutions to S-IIAE are plotted in different dimensions through which bright, anti-kink and bright solitary wave structures are established. The results of the study also indicated that the proposed method is a valuable approach for achieving analytical solutions to a wide range of nonlinear partial differential equations. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are essential in many areas, from healthcare to environmental monitoring. However, WSNs are vulnerable to routing attacks that might jeopardize network performance and data integrity due to their inherent vulnerabilities. This work suggests a unique method for enhancing WSN security through the detection of routing threats using feed-forward artificial neural networks (ANNs). The proposed solution makes use of ANNs' learning capabilities to model the network's dynamic behavior and recognize routing attacks like black-hole, gray-hole, and wormhole attacks. CICIDS2017 is a heterogeneous dataset that was used to train and test the proposed system in order to guarantee its robustness and adaptability. The system's ability to recognize both known and novel attack patterns enhances its efficacy in real-world deployment. Experimental assessments using an NS2 simulator show how well the proposed method works to improve routing protocol security. The proposed system's performance was assessed using a confusion matrix. The simulation and analysis demonstrated how much better the proposed system performs compared to the existing methods for routing attack detection. With an average detection rate of 99.21% and a high accuracy of 99.49%, the proposed system minimizes the rate of false positives. The study advances secure communication in WSNs and provides a reliable means of protecting sensitive data in resource-constrained settings. [ABSTRACT FROM AUTHOR]

Glipizide, a poor water-soluble drug belongs to BCS class II. The proposed work aimed to enhance the solubility of glipizide by preparing solid dispersions, using polyvinyl pyrrolidone (PVP) and polyethylene glycol (PEG). Solvent evaporation method was used for the preparation of glipizide solid dispersions. Solid dispersions were prepared in four different drug-to-polymer ratios i.e. 1:1, 1:2, 1:3 and 1:4. Mainly effect of three polymers (PVP K30, PVP K90 and PEG 6000) was evaluated on the solubility and dissolution of glipizide. The in-vitro dissolution of all prepared formulations was performed under pH 6.8 at 37°C using USP type II apparatus. In-vitro dissolution results revealed that the formulations having high concentrations of the polymer showed enhanced solubility. Enhancements in the solubility and rate of dissolution of the drug were noted in solid dispersion formulations compared to the physical blends and pure drug. Solid dispersions containing polyvinyl pyrrolidone exhibited a more favorable pattern of drug release compared to the corresponding solid dispersions with PEG. An increase in the maximum solubility of the drug within the solid dispersion systems was observed in all instances. Two solid dispersion formulations were optimized and formulated into immediate-release tablets, which passed all the pharmacopoeial and non-pharmacopoeial tests. Fourier transformed Infrared (FTIR) spectroscopy X-ray diffraction (XRD) and Differential scanning calorimetry (DSC) were used to indicate drug: polymer interactions in solid state. Analysis of the solid dispersion samples through characterization tests indicated the compatibility between the drug and the polymer. [ABSTRACT FROM AUTHOR]

This paper presents a model of a doubly clamped electrically actuated microbeam, which is a commonly used structure in microelectromechanical systems (MEMS). The model is based on Euler–Bernoulli beam theory and includes the effect of electrostatic forces on the beam's deflection. The electric field is modeled using the parallel plate capacitor model, and the deflection of the beam is calculated using the Galerkin method. The behavior of a microbeam subjected to the van der Waals force, which is a weak intermolecular force that arises from the interaction between the beam and a nearby surface. The microbeam is modeled using the Euler–Bernoulli beam theory, and the van der Waals force is modeled using the Lennard–Jones potential. At the last we study the model of MEMS based on multi-walled carbon nanotubes (MWCNTs). MWCNTs have unique mechanical, thermal, and electrical properties, which make them ideal for use in MEMS applications. The approximate solution of the developed models is found by using homotopy perturbation based Aboodh transformation (HPATM). HPATM is a mathematical method used to solve nonlinear equations by converting them into linear forms. This approach involves introducing a small parameter and applying perturbation theory to obtain a solution in a series form. The method's accuracy is defined based on the existing literature because its solution matched the variation iteration-based Laplace method. Also, we compared its results with the finite difference method. The validity of the stability analysis is further established by examining the stability in the vicinity of the fixed points. Sketches are made of the phase portraits close to the equilibrium points. [ABSTRACT FROM AUTHOR]

Simple Summary: In the context of increasing global meat consumption, the meat production industry is facing significant challenges as it strives to enhance attributes related to livestock and meat quality. This is of paramount importance. Vertebral traits are among the factors influencing the overall body size and carcass weight of animals, with profound implications for both meat quality and quantity. This issue is particularly prominent in the livestock breeding sector, especially in China, where the augmentation of body size traits has become a central objective due to its consequential impact on carcass quality. Vertebral traits in livestock are complex, polygenic characteristics, and numerous genetic markers and pathways associated with vertebral development, size, and length have already been identified. This review article emphasizes the significant genes linked to vertebral traits in animals such as pigs, sheep, and donkeys based on the existing literature. It further underscores the importance of exploring deeper into molecular mechanisms to gain a more comprehensive understanding of the relationship between vertebral traits and genes, facilitating their effective utilization in successful breeding programs. In livestock breeding, the number of vertebrae has gained significant attention due to its impact on carcass quality and quantity. Variations in vertebral traits have been observed across different animal species and breeds, with a strong correlation to growth and meat production. Furthermore, vertebral traits are classified as quantitative characteristics. Molecular marker techniques, such as marker-assisted selection (MAS), have emerged as efficient tools to identify genetic markers associated with vertebral traits. In the current review, we highlight some key potential genes and their polymorphisms that play pivotal roles in controlling vertebral traits (development, length, and number) in various livestock species, including pigs, donkeys, and sheep. Specific genetic variants within these genes have been linked to vertebral development, number, and length, offering valuable insights into the genetic mechanisms governing vertebral traits. This knowledge has significant implications for selective breeding strategies to enhance structural characteristics and meat quantity and quality in livestock, ultimately improving the efficiency and quality of the animal husbandry industry. [ABSTRACT FROM AUTHOR]

The growing population requires higher crop yields, and one promising approach is growing crops in less fertile lands. To do this successfully, we must understand how well different crops can tolerate salt stress. In this study, we evaluated the salt tolerance potential of five commercial Brassica cultivars (Westar, Faisal canola, Punjab canola, Nifa Gold, and Aari canola) under controlled conditions. We grew these cultivars in a medium with varying levels of NaCl (ranging from 0 to 300 mM). We measured different growth parameters and their root architecture using an automated root scanner. Salt stress affected the growth of all cultivars. However, one cultivar, Aari canola, showed remarkable resilience. It showed up to 1.4-fold higher germination, up to 9-fold higher germination index, up to 7.7-fold fresh weight, and 2.4-fold dry biomass than the rest of the cultivars under the stress conditions. While other cultivars demonstrated reductions of up to 31% in root volume, 20% in root surface area, and 19% in the number of root tips under salt stress, Aari canola displayed minimal changes in these parameters. Aari canola, however, exhibited a substantial reduction in root diameter (up to 60%). The cultivar's unique morphological adaptations in root architecture to salt stress, characterized by noticeable increases in root volume, surface area, and root tips at the cost of reduced root diameter, imply the presence of an intrinsic defensive mechanism against salinity, making it a good candidate for cultivation in saline terrains. [ABSTRACT FROM AUTHOR]

Due to damage to the network of nerves that regulate the muscles and feeling in the shoulder, arm, and forearm, brachial plexus injuries (BPIs) are known to significantly reduce the function and quality of life of affected persons. According to the World Health Organization (WHO), a considerable share of global disability-adjusted life years (DALYs) is attributable to upper limb injuries, including BPIs. Telehealth can improve access concerns for patients with BPIs, particularly in lower-middle-income nations. This study used deep reinforcement learning (DRL)-assisted telepresence robots, specifically the deep deterministic policy gradient (DDPG) algorithm, to provide in-home elbow rehabilitation with elbow flexion exercises for BPI patients. The telepresence robots were used for a six-month deployment period, and DDPG drove the DRL architecture to maximize patient-centric exercises with its robotic arm. Compared to conventional rehabilitation techniques, patients demonstrated an average increase of 4.7% in force exertion and a 5.2% improvement in range of motion (ROM) with the assistance of the telepresence robot arm. According to the findings of this study, telepresence robots are a valuable and practical method for BPI patients' at-home rehabilitation. This technology paves the way for further research and development in telerehabilitation and can be crucial in addressing broader physical rehabilitation challenges. [ABSTRACT FROM AUTHOR]

This study presents an integrated framework of machine learning models (Artificial Neural Network, Ensembled Learning Tree, Support Vector Machine, and Gaussian Process Regression) and particle swarm optimization (PSO) to predict and optimize hydrogen production from SCWG using sewage sludge characteristics and process parameters. According to the results, ELT-PSO is preferred for forecasting hydrogen yield (Coefficient of determination (R2) = 0.997, Root Mean Square Error (RMSE) = 0.093), and it is highly suggested for handling complex variable-target correlation. However, Support Vector Machine (SVM) performed poorly, with R2 = 0.83 and RMSE = 2.28. According to SHAP feature importance Temperature, Carbon, Hydrogen, and Pressure are among the parameters that have strong impact. In addition, by adjusting the ML hyperparameters, optimization method (PSO) was used to maximize H2 yield. The optimized ELT-PSO model was utilized to establish a Graphical User Interface that made it simple to calculate H2 yield. [Display omitted] • ML with PSO used for prediction and analysis of H2 yield from SCWG. • PCC show temperature, oxygen, hydrogen, and volatile matter impact significantly. • ELT-PSO performed better than other machine learning optimization integrated model. • GUI is developed for H2 yield prediction for ease in the process. [ABSTRACT FROM AUTHOR]

This article discusses the challenges and effectiveness of early post-discharge follow-up for patients hospitalized with heart failure (HF). While guidelines recommend early follow-up visits after discharge, the evidence supporting their effectiveness is limited. A study from France found that combined follow-up with a general practitioner and cardiologist was associated with a lower risk of death or rehospitalization, but a higher risk of HF readmission. The article emphasizes the importance of optimizing guideline-directed medical therapy (GDMT) during these visits and initiating GDMT prior to discharge to improve outcomes for HF patients. However, the article acknowledges the limitations of the study and the need for further research in this area. [Extracted from the article]

The article discusses the underutilization of guideline-directed medical therapy (GDMT) for heart failure with reduced ejection fraction (HFrEF). It highlights the findings of the CHAMP-HF registry, which revealed that many eligible patients did not receive GDMT. The article explores various reasons for this, including patient out-of-pocket costs, poor tolerability, patient preference, and clinical inertia. The authors present the results of the HELP-HF registry, which examined the reasons for non-prescription or non-titration of GDMT. However, the study faced limitations due to missing data and the subjective nature of reasons provided. The article emphasizes the need for definitive data to understand the barriers to GDMT utilization and improve patient care. [Extracted from the article]

The utilization of hexagonal structures in nano ferrites has been employed for absorption because of their dielectric, attenuation characteristics, and reflection losses. Electromagnetic pollution is one of the significant issues in cleaning the environment. Electronic devices produce pollution and are hazardous to human health. Therefore, ferrite materials have been used for absorption purposes. In this study, the impact of chromium substitution on the structural and dielectric specifications of the Barium-strontium-based W-type hexagonal ferrites has been investigated and used for microwave absorption application. The sol-gel auto-ignition process prepared w-type hexagonal ferrites with Ba 0.5 Sr 0.5 Mg 2 Cr x Fe 16-x O 27 (x = 0.0, 0.1, 0.2, 0.3, and 0.4). According to XRD examination, the formation of single-phase W-type hexagonal ferrites was proven. The synthesized composition is confirmed to be nanocrystalline because the calculated crystallite size value is in the nanometer range. FTIR analysis confirmed the structure of W-type hexagonal ferrite. Raman spectroscopic study examined the vibrational and rotational modes of molecules. Survey spectra of XPS, which include Ba, Sr, Mg, Fe, Cr, and O, confirmed the presence of all constituent elements. SEM analysis confirmed that the sample contains grains with a hexagonal platelet shape. The results showed that increasing chromium concentration reduced the dielectric permittivity, tan loss, and ac conductivity. At x = 0.4, the reflection loss value is very low. The recorded value is −79.62 dB, corresponding to a frequency of 5.92 GHz, with a thickness of 1.75 mm. Because of this, W-type hexagonal ferrites are suitable for a wide range of electronic applications, including microwave absorbers, high-density recording media, and multilayer chip inductors. These applications have made it possible to functionalize these materials in order to enhance device performance and lower the size, weight, and cost of devices while also fostering the development of new technologies that have significantly improved the quality of our daily lives. [ABSTRACT FROM AUTHOR]

Background: Severe burns patients are in danger of intra-abdominal hypertension and its sequelae including organ failure, abdominal compartment syndrome and death. This study aimed to find the frequency and occurrence of intra-abdominal hypertension and abdominal compartment syndrome in patients with major burn injuries characteristics. Methods: All patients brought to the Burn Care Center whose burn size exceeded 20% total body surface area were included in the study. Intra-abdominal pressure monitoring was done at the intensive care unit via an intra-vesical pressure monitoring system. Resuscitation was done using the modified Brookes formula. Results: One hundred thirty two patients were included in this study. Intra-abdominal hypertension was noted in 52% of patients and abdominal compartment syndrome in 29%. Intra-abdominal hypertension was noted in 95.7% of patients who received more than 7000 ml of resuscitation fluids. Abdominal compartment syndrome was noted in 94.8% of patients who received more than 9500 ml of resuscitation fluids. Mortality of patients with intra-abdominal hypertension was 63.8% and with abdominal compartment syndrome 100%. Conclusion: In the current study, patients with circumferential abdominal burns with total body surface area more than 40% frequently develop intra-abdominal hypertension and abdominal compartment syndrome, and patient mortality is significant. Burn patients must be constantly monitored for intra-abdominal hypertension, and measurements of intra-abdominal hypertension should be taken in all severe burns to prevent fatal complications. Level of evidence: Level V, Risk/Prognostic [ABSTRACT FROM AUTHOR]