High-temperature creep refers to the slow and continuous plastic deformation of materials under the effects of high temperatures and mechanical stress over extended periods, which can lead to the degradation or even failure of the components’ functionality. Al_xCr_0.2NbTiV (x = 0.2, 0.5, or 0.8) refractory high-entropy alloys were fabricated by arc melting. The effects of Al content on the microstructure of Al_xCr_0.2NbTiV alloys were studied using X-ray diffraction, scanning electron microscopy, and electron backscatter diffraction. The microhardness, compression properties, and nanoindentation creep properties of Al_xCr_0.2NbTiV alloys were also tested. The results show that the Al_xCr_0.2NbTiV series exhibits a BCC single-phase structure. As the Al content increases, the lattice constant of the alloys gradually decreases, and the intensity of the (110) crystal plane diffraction peak increases. Adding aluminum enhances the effect of solution strengthening; however, due to grain coarsening, the microhardness and room temperature compressive strength of the alloy are only slightly improved. Additionally, because the effect of solution strengthening is diminished at high temperatures, the compressive strength of the alloy at 1000 °C is significantly reduced. The creep mechanism of the alloys is predominantly governed by dislocation creep. Moreover, increasing the Al content helps to reduce the sensitivity of the alloy to the loading rate during the creep process. At a loading rate of 2.5 mN/s, the Al_0.8Cr_0.2NbTiV alloy exhibits the lowest creep strain rate sensitivity index (m), which is 0.0758. Full article

This study examined the multi-phase flow field for a single object and two parallel/series objects under different incoming angles of lateral flow. The volume of fluid model, the Sauer–Schnerr cavitation model, and the six degrees of freedom (DOF) method were adopted to consider simulations of multi-phase flow, phase change, and object movement, respectively. The results show that, for a single object, the degree of asymmetry in the cavity profile depends on the component (the z-component) of the lateral inflow velocity in the direction perpendicular to the initial velocity of the object. As this component increases, the asymmetry of the cavity increases. The cavity length is related to the relative axial speed between the object and the water. For parallel objects, the cavity asymmetry is determined by the superimposed influence of the z-component of the lateral incoming speed and the high-pressure zone induced by the nearby object. The object located downstream relative to the lateral flow has a stronger cavity asymmetry than that of the upstream object, and the trajectory of the downstream object is more easily deviated than that of the upstream object. For tandem objects, with the increase in the lateral incoming angle, the supercavity length increases after the rear object enters into the front cavity. With the increase in the z-component of the lateral flow velocity, the deviation speed increases. Full article

In order to improve the automation and safety of underground steel belt support in coal mines, a method for the intelligent identification and positioning of steel belt anchor holes in roadway support using inductive sensors is proposed. Using STM32F407ZGT6 as the main control chip, tasks such as data acquisition and processing, motor motion control, etc., are assigned based on the real-time operating system FreeRTOS. Using the XY mobile platform equipped with inductive sensors to detect steel belts, The collected data includes coordinate values and voltage values. Adaptive threshold generation and correction strategies are used for threshold segmentation and extraction of anchor hole boundary points. The principle of Hough circle transformation is used to fit the extracted boundary points into circles. The results show that this method can perform anchor hole positioning with a positioning error of within 5 mm, meeting the design requirements. Full article

Date palm (Phoenix dactylifera L.) fruit samples belonging to the ‘Mejhoul’ and ‘Boufeggous’ cultivars were harvested at the Tamar stage and used in our experiments. Before scanning, date samples were dried using convective drying at 60 °C and infrared drying at 60 °C with a frequency of 50 Hz, and then they were scanned. The scanning trials were performed for two hundred date palm fruit in fresh, convective-dried, and infrared-dried forms of each cultivar using a flatbed scanner. The image-texture parameters of date fruit were extracted from images converted to individual color channels in RGB, Lab, XYZ, and UVS color models. The models to classify fresh and dried samples were developed based on selected image textures using machine learning algorithms belonging to the groups of Bayes, Trees, Lazy, Functions, and Meta. For both the ‘Mejhoul’ and ‘Boufeggous’ cultivars, models built using Random Forest from the group of Trees turned out to be accurate and successful. The average classification accuracy for fresh, convective-dried, and infrared-dried ‘Mejhoul’ reached 99.33%, whereas fresh, convective-dried, and infrared-dried samples of ‘Boufeggous’ were distinguished with an average accuracy of 94.33%. In the case of both cultivars and each model, the higher correctness of discrimination was between fresh and infrared-dried samples, whereas the highest number of misclassified cases occurred between fresh and convective-dried fruit. Thus, the developed procedure may be considered an innovative approach to the non-destructive assessment of drying impact on the external quality characteristics of date palm fruit. Full article

Beta-lactam antibiotics have been a major climacteric in medicine for being the first bactericidal compound available for clinical use. They have continually been prescribed since their development in the 1940s, and their application has saved an immeasurable number of lives. With such immense use, the rise in antibiotic resistance has truncated the clinical efficacy of these compounds. Nevertheless, the synergism of combinational antibiotic therapy has allowed these drugs to burgeon once again. Here, the development of meropenem with vaborbactam—a recently FDA-approved beta-lactam combinational therapy—is reviewed in terms of structure rationale, activity gamut, pharmacodynamic/pharmacokinetic properties, and toxicity to provide insight into the future development of analogous therapies. Full article

A bioactive Pleurotus eryngii aqueous extract powder (SPAE) was obtained by spray drying and its performance in terms of physicochemical properties, in vitro digestion, inflammatory factors, and modulation of the intestinal microbiota was explored. The results indicated that the SPAE exhibited a more uniform particle size distribution than P. eryngii polysaccharide (PEP). Meanwhile, a typical absorption peak observed at 843 cm⁻¹ in the SPAE FTIR spectra indicated the existence of α-glycosidic bonds. SPAE exhibited higher antioxidant abilities and superior resistance to digestion in vitro. In addition, SPAE supplementation to mice significantly reduced the release of factors that promote inflammation, enhanced the secretion of anti-inflammatory factors, and sustained maximum production of short-chain fatty acids (SCFAs). Additionally, it significantly enhanced the relative abundance of SCFAs-producing Akkermansia and reduced the abundance of Ruminococcus and Clostridiides in intestines of mice. These results show the potential of SPAE as a novel material with prebiotic effects for the food and pharmaceutical industries. Full article

The purpose of this study was to investigate whether plasma biomarkers can help to diagnose, differentiate from Alzheimer disease (AD), and stage cognitive performance in patients with positron emission tomography (PET)-confirmed primary age-related tauopathy, termed tau-first cognitive proteinopathy (TCP) in this study. In this multi-center study, we enrolled 285 subjects with young-onset AD (YOAD; n = 55), late-onset AD (LOAD; n = 96), TCP (n = 44), and cognitively unimpaired controls (CTL; n = 90) and analyzed plasma Aβ42/Aβ40, pTau181, neurofilament light (NFL), and total-tau using single-molecule assays. Amyloid and tau centiloids reflected pathological burden, and hippocampal volume reflected structural integrity. Receiver operating characteristic curves and areas under the curves (AUCs) were used to determine the diagnostic accuracy of plasma biomarkers compared to hippocampal volume and amyloid and tau centiloids. The Mini-Mental State Examination score (MMSE) served as the major cognitive outcome. Logistic stepwise regression was used to assess the overall diagnostic accuracy, combining fluid and structural biomarkers and a stepwise linear regression model for the significant variables for MMSE. For TCP, tau centiloid reached the highest AUC for diagnosis (0.79), while pTau181 could differentiate TCP from YOAD (accuracy 0.775) and LOAD (accuracy 0.806). NFL reflected the clinical dementia rating in TCP, while pTau181 (rho = 0.3487, p = 0.03) and Aβ42/Aβ40 (rho = −0.36, p = 0.02) were significantly correlated with tau centiloid. Hippocampal volume (unstandardized β = 4.99, p = 0.01) outperformed all of the fluid biomarkers in predicting MMSE scores in the TCP group. Our results support the superiority of tau PET to diagnose TCP, pTau181 to differentiate TCP from YOAD or LOAD, and NFL for functional staging. Full article

In the digital economy era, digital transformation is crucial for competitiveness in traditional industries, particularly in manufacturing. This study aimed to examine how digital transformation impacts the manufacturing environment, social responsibility, and corporate governance (ESG), with a focus on the role of senior executive teams. Using empirical analysis of Chinese A-share listed companies from 2010 to 2019, this study found that digital transformation promotes ESG performance in the manufacturing industry. The findings revealed that the educational level, CEO tenure, and professional background diversity of senior management teams moderate this relationship, enhancing ESG performance. This study enriches and expands the existing knowledge system on this topic by integrating theories related to the digital economy and resource-based theories. It provides methodological guidance for the manufacturing industry to improve its environmental, social, and governance performance and achieve rapid development. Additionally, it offers practical suggestions for the government, manufacturing enterprises, and senior executive teams on how to better play their performance in digital transformation and ESG governance. This will assist the manufacturing industry enhance its level of digital transformation and continuously improve its ESG management and governance. Full article

In this study, we demonstrate the direct preparation of dihalo-γ-lactams featuring two distinct halogens from dichloroamides using a novel atom exchange radical cyclization (AERC) procedure. This method integrates the established atom transfer radical cyclization (ATRC) with halogen exchange in solution. The technique operates under mild conditions and requires small amounts of metallic copper, serving as both a supplemental activator and reducing agent. Full article

With the increasing diversity and complexity of tasks assigned to unmanned aerial vehicles (UAVs), the demands on task assignment and sequencing technologies have grown significantly, particularly for large UAV tasks such as multi-target reconnaissance area surveillance. While the current exhaustive methods offer thorough solutions, they encounter substantial challenges in addressing large-scale task assignments due to their extensive computational demands. Conversely, while heuristic algorithms are capable of delivering satisfactory solutions with limited computational resources, they frequently struggle with converging on locally optimal solutions and are characterized by low iteration rates. In response to these limitations, this paper presents a novel approach: the probabilistic chain-enhanced parallel genetic algorithm (PC-EPGA). The PC-EPGA combines probabilistic chains with genetic algorithms to significantly enhance the quality of solutions. In our approach, each UAV flight is considered a Dubins vehicle, incorporating kinematic constraints. In addition, it integrates parallel genetic algorithms to improve hardware performance and processing speed. In our study, we represent task points as chromosome nodes and construct probabilistic connection chains between these nodes. This structure is specifically designed to influence the genetic algorithm’s crossover and mutation processes by taking into account both the quantity of tasks assigned to UAVs and the associated costs of inter-task flights. In addition, we propose a fitness-based adaptive crossover operator to circumvent local optima more effectively. To optimize the parameters of the PC-EPGA, Bayesian networks are utilized, which improves the efficiency of the whole parameter search process. The experimental results show that compared to the traditional heuristic algorithms, the probabilistic chain algorithm significantly improves the quality of solutions and computational efficiency. Full article

The spread of the FluA virus poses significant public health concerns worldwide. Fluorescent lateral flow immunoassay (LFIA) test strips have emerged as vital tools for the early detection and monitoring of influenza infections. However, existing quantitative virus-detection methods, particularly those utilizing smartphone-based sensing platforms, encounter accessibility challenges in resource-limited areas and among the elderly population. Despite their advantages in speed and portability, these platforms often lack user-friendliness for these demographics, impeding their widespread utilization. To address these challenges, this study proposes leveraging the optical pick-up unit (OPU) sourced from commercial optical drives as a readily available fluorescence excitation module for the quantitative detection of antibodies labeled with quantum-dot fluorescent microspheres. Additionally, we utilize miniaturized and high-performance optical components and 3D-printed parts, along with a customized control system, to develop an affordable point-of-care testing (POCT) device. Within the system, a stepping motor scans the test strip from the T-line to the C-line, enabling the calculation of the fluorescence-intensity ratio between the two lines. This simple yet effective design facilitates rapid and straightforward field or at-home testing for FluA. The proposed prototype platform demonstrates promising performance, achieving a limit of detection (LOD) of 2.91 ng/mL, a total detection time of no more than 15 min, and dimensions of 151 mm × 11.2 mm × 10.8 mm³. We believe that the proposed approach holds great potential for improving access to an accurate influenza diagnosis. Full article

Although the importance of the content of a webpage in retail business performance is widely recognized, there are few empirical studies on the importance of text and image information on the homepage in retailer performance. How will consumers sift through this information? Does text and image information affect consumers’ purchasing behavior? Using a data set of a Chinese convenience chain store, we attempt to clarify the influence of the brand in the title, the emotional atmosphere on the picture, and the product images of the homepage on the picture on retail business performance by employing a panel fixed-effects negative binomial regression model and a panel fixed-effect regression. Our results show that mentioning the product brand in the event title and presenting clear product images significantly enhance retailer performance in online community group buying. It is noteworthy that emotional descriptions have a greater impact on retailer performance compared to rational descriptions. In practice, this study provides a new perspective and reference for online community group buying platforms to better attract consumers and maintain sustainable development. Full article

In scientific computing, neural networks have been widely used to solve partial differential equations (PDEs). In this paper, we propose a novel RBF-assisted hybrid neural network for approximating solutions to PDEs. Inspired by the tendency of physics-informed neural networks (PINNs) to become local approximations after training, the proposed method utilizes a radial basis function (RBF) to provide the normalization and localization properties to the input data. The objective of this strategy is to assist the network in solving PDEs more effectively. During the RBF-assisted processing part, the method selects the center points and collocation points separately to effectively manage data size and computational complexity. Subsequently, the RBF processed data are put into the network for predicting the solutions to PDEs. Finally, a series of experiments are conducted to evaluate the novel method. The numerical results confirm that the proposed method can accelerate the convergence speed of the loss function and improve predictive accuracy. Full article

The term “viscoelastic pipe” refers to high polymer pipes that exhibit both elastic and viscoelastic properties. Owing to their widespread use in water transport systems, it is important to understand the transient flow characteristics of these materials for pipeline safety. Despite extensive research, these characteristics have not been sufficiently explored. This study evaluates the impact of friction models on the transient flow of viscoelastic pipes across various Reynolds numbers by employing an energy analysis approach. Given the complexity and computational demands of two-dimensional models, this paper compares the accuracy of one-dimensional and quasi-two-dimensional models. Notably, the superiority of the quasi-two-dimensional model in simulating viscoelastic pipelines is demonstrated. Owing to the interaction between pressure waves and fluid within viscoelastic pipes, fluid–structure coupling significantly attenuates pressure waves during transmission. These findings shed light on the constitutive properties of viscoelastic pipes and the influence of pipe wall friction models on transient hydraulic characteristics, building upon prior studies focused on elastic pipes. Nevertheless, numerous factors affecting transient flow in viscoelastic pipes remain unexplored. This paper suggests further analysis of strain effects, starting with temperature and pipe dynamics, to enhance the understanding of the coupling laws and flow mechanisms in viscoelastic pipelines. Full article

This paper introduces an iterative method with a remarkable level of accuracy, namely fourth-order convergence. The method is specifically tailored to meet the optimality condition under the Kung–Traub conjecture by linear combination. This method, with an efficiency index of approximately $1.5874$, employs a blend of localized and semi-localized analysis to improve both efficiency and convergence. This study aims to investigate semi-local convergence, dynamical analysis to assess stability and convergence rate, and the use of the proposed solver for systems of nonlinear equations. The results underscore the potential of the proposed method for several applications in polynomiography and other areas of mathematical research. The improved performance of the proposed optimal method is demonstrated with mathematical models taken from many domains, such as physics, mechanics, chemistry, and combustion, to name a few. Full article

Digital entrepreneurial ecosystem embeddedness disrupts existing boundaries and content of innovative entrepreneurial activities, restructuring entrepreneurial landscape. However, how it drives the process and mechanisms of user entrepreneurial opportunity development remains underexplored. Based on entrepreneurial ecosystem theory and knowledge dynamic capability theory, this study examines the mediating role of knowledge dynamic capabilities in the relationship between digital entrepreneurial ecosystem embeddedness and user entrepreneurial opportunity development. Using a sample of 232 user entrepreneurial enterprises in China, hierarchical regression analysis and bootstrap methods are employed to investigate the mechanisms. The results reveal that digital entrepreneurial ecosystem embeddedness significantly promotes knowledge acquisition and sharing capabilities, which in turn facilitate entrepreneurial opportunity development. Moreover, under higher levels of entrepreneurial learning, the promotion of knowledge acquisition and sharing capabilities by digital entrepreneurial ecosystem embeddedness becomes more significant. Furthermore, knowledge dynamic capabilities, consisting of knowledge acquisition and sharing capabilities, significantly promote entrepreneurial opportunity development, partially mediating the relationship between digital entrepreneurial ecosystem embeddedness and entrepreneurial opportunity development. Additionally, knowledge sharing capability serves as the preferable pathway in the dual-driven process of digital entrepreneurial ecosystem embeddedness and entrepreneurial opportunity development. Our findings contribute to understanding the dynamics of user entrepreneurship in China in the digital environment, and offer practical insights for leveraging digital embeddedness to improve the quality and efficiency of opportunity development and promote the sustainability of the digital entrepreneurial ecosystem. Full article

Dairy is the largest sector of the agricultural industry in New Mexico, but the sector’s need for high quality forage in the face of ongoing drought and climate change causes concern. The economic merit of using guar to replace alfalfa under imposed constraints in irrigation water availability is evaluated. Nutritional quality of guar (Cyamopsis tetragonoloba L.) grown at the NMSU Agricultural Science Center at Clovis was estimated using Near Infrared Spectroscopy (NIRS) analysis. Results show that 45.6 percent of analyzed samples were comparable to Supreme or Premium alfalfa (Medicago sativa) hay using Relative Feed Value index, and 23.7% met this criteria using crude protein. While alfalfa uses 4.4 acre-feet of water (approximately 5400 cubic meters) per season, the guar sampled used 5 inches (500 cubic meters) of applied irrigation. Microsoft Excel Version 2404 LP Solver was used to identify an optimum crop mix of alfalfa and guar under different levels of irrigation water constraints. With increasing levels in modeled irrigation restrictions, the use of guar increased the potential forage production by 3% under a 0.4 acre-foot restriction up to almost 59% under a 1.5 acre-feet irrigation water limit. Our results merit additional research, including forage trials to determine the impact of guar forage on milk production and further agronomic research into growing guar to maximize forage yield. Full article

Composite polymers are an interesting class of materials with a wide range of applications. Among the properties of polymers which are currently being enhanced via the development of composite materials is their thermal stability, which is typically evaluated via thermogravimetric analysis (TGA). In this work, a paradox is recognized regarding the considered relationship between the polymer–filler interactions leading to a good dispersion of the filler and the improvement of thermal stability. Simulation of the TGA signal during isothermal measurements of composite polymers is performed along with experimental measurements. It is shown that there are at least three factors that can cause apparent alterations of the thermal stability of composite polymers, namely, the different buoyancy due to the different densities of the composites and the neat polymer, the different thermal diffusivity of the composites and the fact that the mass loss (or remaining mass) of the composites, conventionally, is expressed per overall mass of the composite and not per mass of polymer. The relative contributions of these factors are evaluated and it is found that the conventional expression of mass loss has the most profound effect. Furthermore, it is shown that it is proper to express and evaluate the TGA results of composite polymers per degradable (polymer) mass of the composite and not per overall mass of the composite. Full article

In inertial confinement fusion, the sub-atmospheric purging through microcapillaries is of great importance to the high gas purity inside the cryogenic target and the low failure rate of experiments. In this study, a non-continuous flow model is developed for this sub-atmospheric purging process and verified through National Ignition Facility experiments to study the evolution of parameters such as pressure and gas composition that are not possible to measure directly. The effects of microcapillary structures and sizes on the transient evacuation–filling behaviors are analyzed, and the periodic purging scheme is optimized. The results show that the extension of evacuation and filling time caused by the elongated microtube can be described as a linear function of microtube length or an exponential decay function of microtube diameter, and the change of the inner diameter has a more drastic effect. The conical-straight composite can effectively reduce the evacuation and filling time while meeting the thermal and mechanical requirements. The overall performance of the purging process exhibits a strong dependence on the cycle trough pressure. The total purging time firstly decreases and then increases with the increase in the trough pressure, and the optimal trough pressure falls at around 20% of the filling pressure where the evacuation and filling times are almost evenly balanced. These results can provide theoretical guidance for the selection of microtubes and the design of the filling–evacuating scheme in the experiments. Full article

Electromagnetic interference poses a significant challenge to the reliability and performance of electronic equipment, particularly in the aerospace and aviation sectors where the demand for high-performance electromagnetic shielding materials is paramount. This study introduces an innovative solution: a lightweight nickel-plated carbon fiber composite chassis, designed to meet these stringent requirements. Through comparative analysis, we prove that this composite chassis is not only comparable to traditional metal chassis in terms of time-domain shielding effect, but also close to traditional metal chassis in terms of heat dissipation capability. Notably, it achieves a substantial weight reduction of 71.43% to 76.25% compared to its metal counterparts, addressing the critical need for lighter materials in aerospace applications. The superior heat dissipation feature of the nickel-plated carbon fiber composite, quantitatively superior to conventional materials, indicates its potential to enhance the operational efficiency and safety of aerospace electronics. This research underscores the viability of nickel-plated carbon fiber composites as a groundbreaking material for electromagnetic shielding, promising significant advancements in aerospace and beyond. Full article

Disposable sensors are inexpensive, user-friendly sensing tools designed for rapid single-point measurements of a target. Disposable sensors have become more and more essential as diagnostic tools due to the growing demand for quick, easy-to-access, and reliable information related to the target. Dopamine (DA), a prevalent catecholamine neurotransmitter in the human brain, is associated with central nervous system activities and directly promotes neuronal communication. For the sensitive and selective estimation of DA, an enzyme-free amperometric sensor based on polyaniline-doped multi-walled carbon nanotubes (PANI-MWCNTs) drop-coated disposable screen-printed carbon electrodes (SPCEs) was fabricated. This PANI-MWCNTs-2/SPCE sensor boasts exceptional accuracy and sensitivity when working directly with ex vivo mouse brain homogenates. The sensor exhibited a detection limit of 0.05 μM (S/N = 3), and a wide linear range from 1.0 to 200 μM. The sensor’s high selectivity to DA amidst other endogenous interferents was recognized. Since the constructed sensor is enzyme-free yet biocompatible, it exhibited high stability in DA detection using ex vivo mouse brain homogenates extracted from both Parkinson’s disease and control mice models. This research thus presents new insights into understanding DA release dynamics at the tissue level in both of these models. Full article

The genus Purpureocillium is renowned for its role in biocontrol and biotechnological applications. The identification of new species within this genus is crucial for broadening our understanding of its ecological roles and potential utility in sustainable agriculture. This study aimed to characterize a new species of Purpureocillium, isolated from soil in eastern China, and to evaluate its bioactivity against Ostrinia furnacalis (corn moth) and Galleria mellonella (greater wax moth). We utilized morphological characterization; molecular phylogenetic analysis employing ITS, nrLSU, and tef1 genes; and bioactivity assays to identify and characterize the new species. The newly identified species, Purpureocillium jiangxiense sp. nov., displays unique morphological and genetic profiles compared to known species. Bioactivity tests showed that this species exhibits inhibitory effects against O. furnacalis and G. mellonella, highlighting its potential in biocontrol applications. By the ninth day at a spore concentration of 1 × 10⁸ spores/mL, the mortality rate of the corn moth and greater wax moth reached 30% to 50% respectively. The discovery of P. jiangxiense sp. nov. adds to the genetic diversity known within this genus and offers a promising candidate for the development of natural biocontrol agents. It underscores the importance of continued biodiversity exploration and the potential for natural solutions in pest and disease management. Full article