Search Results (8,118)

Cotton’s susceptibility to low temperatures makes it a crucial raw resource for the world’s textile industry, yet its cultivation in temperate regions is severely limited. Although plant growth and stress responses depend on receptor-like kinases (RLKs), the functions of the MEDOS (MDS) gene family, which includes genes that encode RLK, are still poorly understood in cotton. In this study, we conducted a genome-wide analysis to systematically investigate the distribution of MDS gene family members in four cotton species. Phylogenetic analysis identified five evolutionary clades of the MDS gene family in cotton. The role of promoter cis-acting elements in hormone signaling and abiotic stress responses was suggested by analysis. Collinearity analysis demonstrated that segmental duplication was the primary driver of family expansion. Gene expression profiling showed that GhMDS11 was significantly upregulated under cold stress. Functional validation through silencing GhMDS11 compromised cold tolerance, confirming its role in stress adaptation. Comparative transcriptome study of silenced plants demonstrated substantial enrichment in pathways associated with hormone signal transduction and fatty acid breakdown. It is speculated that the chain of “hormone synthesis → signal transduction → secondary metabolism” completely presents the transcriptional regulation network and functional response of plants after receptor kinase VIGS. Silencing the GhMDS11 gene in cotton initiates regulatory effects through hormone synthesis, which is amplified via a signal transduction cascade, ultimately affecting secondary metabolism. This comprehensive pathway clearly demonstrates the downstream transcriptional reprogramming and functional changes. This work thoroughly examined the evolutionary traits of the MDS family across four cotton species and clarified the functional and molecular processes of GhMDS11 in improving low-temperature tolerance, laying a solid foundation for further clarifying multidimensional regulatory networks and breeding cold-resistant cotton materials. Simultaneously, our findings pave the way for future research to develop molecular markers, which could potentially shorten the breeding cycle and facilitate the targeted enhancement of cold tolerance in cotton. Full article

The replacement of polyvinylidene fluoride (PVDF) with environmentally friendly binders offers potential advantages in the development of aqueous lithium-ion batteries (ALIBs) and flow batteries (FBs) incorporating solid charge carriers (so-called solid boosters). This study investigates the electrochemical stability of ethyl cellulose and cross-linked gluten as substitutes for PVDF in LiMn₂O₄ (LMO) cathodes for aqueous Li-ion battery electrodes and solid boosters for FBs. The millimetre-scaled solid booster beads must be easily produced on a large scale, and at the same time, their charging and discharging must be reversible over long durations under electrolyte tank conditions. The binders were tested under standardized conditions for discharge capacity and cycling stability. Our results demonstrate that ethyl cellulose and cross-linked gluten can rival the electrochemical stability of PVDF, maintaining initial discharge capacities near 100 mAh g⁻¹ at 0.2 C for LMO cathodes and exhibiting reasonable capacity retention over hundreds of cycles. This work supports the feasibility of sustainable electrode processing, provides promising directions for scalable, eco-friendly electrode fabrication methods, and highlights promising binder candidates for use in aqueous energy storage systems. Full article

Crude oil emulsions continue to pose significant challenges across production, transportation, and refining due to their inherent stability and complex interfacial chemistry. Their persistence is driven by the synergistic effects of asphaltenes, resins, acids, waxes, and fine solids, as well as operational factors such as temperature, pH, shear, and droplet size. These emulsions increase viscosity, accelerate corrosion, hinder catalytic activity, and complicate downstream processing, resulting in substantial operational, economic, and environmental impacts—underscoring the necessity of effective demulsification strategies. This review provides a comprehensive examination of emulsion behavior, beginning with their formation, classification, and stabilization mechanisms and progressing to the fundamental processes governing destabilization, including flocculation, coalescence, Ostwald ripening, creaming, and sedimentation. Separation techniques are critically assessed across chemical, thermal, mechanical, electrical, membrane-based, ultrasonic, and biological domains, with attention to their efficiency, limitations, and suitability for industrial deployment. Particular emphasis is placed on hybrid and emerging methods that integrate multiple mechanisms to improve performance while reducing environmental impact. By uniting fundamental insights with technological innovations, this work highlights current progress and identifies future directions toward greener, more efficient oil–water separation strategies tailored to diverse petroleum operations. Full article

Domoic acid (DA), produced by Pseudo-nitzschia diatoms, is the one of the major toxin threats from harmful algal blooms (HABs) on the west coast of the United States. DA events vary in magnitude, timing, and duration, and elucidating drivers for individual events is a persistent challenge. Monterey Bay experiences near-annual DA events and hosts long-term HAB monitoring at the Santa Cruz Municipal Wharf (SCW). Here we characterize two toxin events, occurring in May 2023 and March 2024. The events were similar in magnitude and duration, but an exploration of physical, biological, and chemical dynamics revealed distinct environmental drivers. These differences resulted in a significant deviation in cellular DA (cDA) within the same species of Pseudo-nitzschia. In addition, opportunistic solid-phase adsorption toxin tracking (SPATT) was used for environmental metabolomics. The novel application of SPATT revealed 159 metabolites that were strongly correlated with DA in both events and produced a spectral match to a new marine natural product using Global Natural Products Social Molecular Networking (GNPS). This work takes a multivariable approach to understanding toxin drivers and lends proof of concept for the integration of environmental metabolomics in HAB monitoring. Full article

This paper introduces and validates a comprehensive instrument designed to measure financial literacy, its underlying determinants, and to assess how factors such as planning affect financial vulnerability and fraud in Brazil. This work represents a crucial step toward achieving several Sustainable Development Goals (SDGs). The study utilizes a two-fold methodology. First, Confirmatory Factor Analysis (CFA) is used to validate a six-component model consisting of Financial Literacy, Vulnerability, Fraud, Cognitive Reflection, Crypto Literacy, and Planning. This analysis is followed by the development and interpretation of a Random Forest model, which was identified as the best-performing predictor in a comparison of seven machine learning algorithms. The CFA results showed that Financial Planning has a stronger negative correlation with Financial Vulnerability (−0.642) and Fraud (−0.375) than Financial Literacy does. This evidence was further supported by the machine learning analysis; analyses using both SHAP and LIME identified Financial Planning as the strongest predictor of financial vulnerability and fraud. The analysis further showed significant social inequalities in the developed models and identified the gender variable (female) as an important predictor of enhanced financial vulnerability. Converging evidence from both CFA and machine learning confirms that sound planning practices are more important than financial knowledge in reducing financial distress. Our findings provide a solid foundation for the development of inclusive public policy that promotes behavioral change, aiming to reduce systemic inequalities (SDG 10) and achieve sustainable economic stability (SDG 8), thereby supporting social goals and the Sustainable Development Goals. Full article

A vector vortex beam (VVB) combines the phase singularity of a vortex beam (VB) with the anisotropic polarization of a vector beam, enabling the transmission of complex optical information and offering broad application prospects in optical sensing, high-capacity communication, and high-resolution imaging. In this work, we present a detailed theoretical analysis of the generation and detection of VVBs with Laguerre–Gaussian (LG) and Bessel–Gaussian (BG) forms. Particular emphasis is placed on the polarization characteristics of VVBs, the evolution of beam profiles after passing through polarizers with different orientations, and the interference features arising from the coaxial superposition of a VVB with a circularly polarized divergent spherical wave. To validate the theoretical analysis, LGVVBs were experimentally generated using a Mach–Zehnder interferometer by superposing two vortex beams with opposite topological charges and orthogonal circular polarizations. Furthermore, the introduction of an axicon enabled the direct conversion of LGVVBs into BGVVBs. The excellent agreement between theoretical predictions and experimental observations lays a solid foundation for beginners to systematically understand VVB characteristics and advance future research. Full article

The phase transformation of fayalite from copper slag during oxidation roasting was systematically studied in this work with an analysis using X-ray diffraction, X-ray photoelectron spectroscopy, vibrating sample magnetometer, scanning electronic microscope, and energy dispersive spectrometer. The results show that the oxidation of fayalite occurs at ≥300 °C. Fayalite is first oxidized into amorphous Fe₃O₄ and SiO₂ during oxidation roasting. The former then converts into Fe₂O₃ while the latter converts into cristobalite solid solution with increasing temperature. Meanwhile, the specific saturation magnetization of roasted products increases from 9.43 emu/g at 300 °C to 20.66 emu/g at 700 °C, and then decreases to 7.31 emu/g at 1100 °C. The migration of iron in fayalite is prior to that of silicon during oxidation roasting. Therefore, the thickness of the iron oxide layer on the particle surface steadily increases with roasting temperature, from about 1.0 μm at 800 °C to about 5.0 μm at 1100 °C. This study has guiding significance for the iron grain growth in copper slag during the oxidation-reduction roasting process. Full article

To address limitations such as cleaning difficulties or secondary contamination/damage of cultural relics caused by the uncontrollable diffusion of water/cleaning agent/dirty liquids during the cleaning process in traditional cleaning methods, this study, using cotton textiles as an example, systematically investigated the cleaning efficacy of four in situ methods (blank gel, cleaning gel, ultrasonic emulsification, and gel + ultrasonic emulsification synergistic cleaning) on eight types of stains, including sand, clay, rust, blood, ink, oil, and mixed solid/liquid stains. Building upon this, this study proposed an efficient, targeted, in situ, and controllable cleaning strategy tailored for fragile, stained textile relics. Results demonstrated that, regardless of the stain type, the synergistic cleaning method of G+U (gel poultice + ultrasonic emulsification) consistently outperformed the cleaning methods of blank gel poultice, cleaning gel poultice, and ultrasonic emulsification. Furthermore, the gel loaded with cleaning agents was always more effective than the blank gel (unloaded cleaning agents). The poultice methods of blank gel and cleaning gel were better suited for solid stains, while the ultrasonic emulsification cleaning method was more effective for liquid stains. Meanwhile, it was also found that the optimal cleaning method proposed in this study (the G+U synergistic cleaning method) was a cleaning method that restricted the cleaning agent within the gel network/emulsion system, and utilized the porous network physical structure of gel, the chemical action of emulsion’s wetting/dissolving dirt, and the cavitation synergistic effect of ultrasound to achieve the targeted removal of contaminants from relics’ surfaces. Crucially, the cleaning process of G+U also had the characteristics of controlling the cleaning area at the designated position and effectively regulating the diffusion rate of the cleaning solution within the treatment zone, as well as the reaction intensity. Therefore, the proposed optimal (the synergistic cleaning method of G+U) cleaning method conforms to the significant implementation of the “minimal intervention and maximal preservation” principle in modern cultural heritage conservation. Consequently, the synergistic cleaning method of G+U holds promise for practical application in artifact cleaning work. Full article

Computation modeling for large thermoplastic deformation of plastic solids is critical for industrial applications like non-invasive assessment of engineering components. While deep learning-based methods have emerged as promising alternatives to traditional numerical simulations, they often suffer from systematic errors caused by geometric mismatches between predicted and ground truth meshes. To overcome this limitation, we propose a novel boundary geometry-constrained neural framework that establishes direct point-wise mappings between spatial coordinates and full-field physical quantities within the deformed domain. The key contributions of this work are as follows: (1) a two-stage strategy that separates geometric prediction from physics-field resolution by constructing direct, point-wise mappings between coordinates and physical quantities, inherently avoiding errors from mesh misalignment; (2) a boundary-condition-aware encoding mechanism that ensures physical consistency under complex loading conditions; and (3) a fully mesh-free approach that operates on point clouds without structured discretization. Experimental results demonstrate that our method achieves a 36–98% improvement in prediction accuracy over deep learning baselines, offering a efficient alternative for high-fidelity simulation of large thermoplastic deformations. Full article

This study investigates the mechanisms of hazardous gas outbursts in geologically complex non-coal tunnels. This is a critical safety concern during excavation, particularly at specific locations and during time-sensitive periods. To address this, a gas–solid coupled numerical model is established to simulate gas seepage processes under such conditions. The simulations systematically reveal the spatiotemporal evolutionary patterns of the velocity and direction of the gas seepage and elucidate the migration mechanism driven by excavation-induced pressure gradients. The model specifically analyzes how geological structures, such as rock joints and fractures, control the seepage pathways. The model also demonstrates the dynamic variations in and enrichment behavior of the gas escape velocities near these discontinuities. Field measurements obtained from the Hongdoushan Tunnel validated the simulated emission patterns along jointed fissures. The findings clarify the intrinsic relationships between the outburst dynamics and key factors that include pressure differentials, geological structures, and temporal effects. This work provides a crucial theoretical foundation and practical strategy for the prediction and prevention of hazardous gas disasters in analogous tunnel engineering projects, thereby enhancing overall construction safety. Full article

The dehydration of fructose and glucose to 5-hydroxymethylfurfural (HMF) in water solution was carried out in the presence of functionalized heteropolyanion-based heterogeneous catalysts. Two catalysts were prepared by immobilizing the Keggin polyoxometalate H₃PW₁₂O₄₀ (PW₁₂) onto nanoSiO₂ by the use of imidazoline and -SO₃⁻ surface species through acid–base reactions. The catalysts were characterized by N₂ adsorption–desorption isotherms, XRD, TGA, FTIR, solid-state NMR, SEM, and acidity–basicity measurements. Catalytic reactions in batch conditions were performed at 165 °C in the presence of suspended catalysts, and the yield of furfural and 5-hydroxymethylfurfural (5-HMF) was determined. The catalytic activity of the materials was tested for sugars at 1M concentration in a water solution. The valorization of sugars (fructose and glucose) was found to be more effective in the case of fructose. Furthermore, the two catalysts in which the heteropolyacid was immobilized showed activity similar to that observed for naked PW₁₂ (reaction in homogeneous phase), despite the heterogeneous nature of the process, but with the advantage of easier separation at the end of the reaction by simple filtration. The material’s substantial stability was demonstrated through three consecutive catalytic test cycles, in which the same catalyst was recovered after each experiment and washed several times with hot water. Finally, tests devoted to the valorization of sugars contained in wastewater from the brewing industry provided a poor yield in 5-HMF, indicating that the catalysts prepared here were, unfortunately, not suitable for this transformation under the conditions tested. This was because the catalysts prepared in this work showed a low capacity to transform glucose (the most present sugar in the carbohydrate fraction of this biomass) into furans. Full article

This paper presents a rule-based negation and litotes detection system for Modern Standard Arabic. Unlike purely statistical approaches, the proposed pipeline leverages linguistic structures, lexical resources, and dependency parsing to identify negated expressions, exception clauses, and instances of litotic inversion, where rhetorical negation conveys an implicit positive meaning. The system was applied to a large-scale subset of the Arabic OSCAR corpus, filtered by sentence length and syntactic structure. The results show the successful detection of 5193 negated expressions and 1953 litotic expressions through antonym matching. Additionally, 200 instances involving exception prepositions were identified, reflecting their syntactic specificity and rarity in Arabic. The system is fully interpretable, reproducible, and well-suited to low-resource environments where machine learning approaches may not be viable. Its ability to scale across heterogeneous data while preserving linguistic sensitivity demonstrates the relevance of rule-based systems for morphologically rich and structurally complex languages. This work contributes a practical framework for analyzing negation phenomena and offers insight into rhetorical inversion in Arabic discourse. Although coverage of rarer structures is limited, the pipeline provides a solid foundation for future refinement and domain-specific applications in figurative language processing. Full article

This study investigates premature fatigue failure in rocker arm gears of large-mining-height shearers operating at alternating ±45° working angles, where insufficient lubrication generates non-uniform thermal -stress fields. In this study, an integrated multiphysics framework combining transient thermal–fluid–structure coupling simulations with fatigue life prediction is proposed. Transient thermo-mechanical coupling analysis simulated dry friction conditions, capturing temperature and stress fields under varying speeds. Fluid–thermal–solid coupling analysis modeled wet lubrication scenarios, incorporating multiphase flow to track oil distribution, and calculated convective heat transfer coefficients at different immersion depths (25%, 50%, 75%). These coupled simulations provided the critical time-varying temperature and thermal stress distributions acting on the gears (Z6 and Z7). Subsequently, these simulated thermo-mechanical loads were directly imported into ANSYS 2024R1 nCode DesignLife to perform fatigue life prediction. Simulations demonstrate that dry friction induces extreme operating conditions, with Z6 gear temperatures reaching over 800 °C and thermal stresses peaking at 803.86 MPa under 900 rpm, both escalating linearly with rotational speed. Lubrication depth critically regulates heat dissipation, where 50% oil immersion optimizes convective heat transfer at 8880 W/m²·K for Z6 and 11,300 W/m²·K for Z7, while 25% immersion exacerbates thermal gradients. Fatigue life exhibits an inverse relationship with speed but improves significantly with cooling. Z6 sustains a lower lifespan, exemplified by 25+ days at 900 rpm without cooling versus 50+ days for Z7, attributable to higher stress concentrations. Based on the multiphysics analysis results, two physics-informed engineering optimizations are proposed to reduce thermal stress and extend gear fatigue life: a staged cooling system using spiral copper tubes and an intelligent lubrication strategy with gear-pump-driven dynamic oil supply and thermal feedback control. These strategies collectively enhance gear longevity, validated via multiphysics-driven topology optimization. Full article

In complex working environments where early fault diagnosis of mechanical equipment is required, interference signals such as ambient vibrations and motor noise can significantly affect the acquisition and analysis of vibration signals and meshing force signals, making it difficult to capture early fault features. This paper provides a method for fault diagnosis and identification of typical gear tooth faults by analyzing the influence of meshing stiffness on dynamic transmission error in the gear transmission process. Three-dimensional models of both normal and faulty gear pairs were built using SolidWorks 2021 software and imported into Adams for dynamic simulation to obtain the system’s dynamic transmission error and meshing force data. By training and identifying these two different types of data, the experimental results demonstrate that the identification accuracy using dynamic transmission error is higher than that based on meshing force. Full article

Indoor housed cattle, particularly those housed in slatted floor barns, may develop specific types of lameness associated with their housing environment. Previous studies have demonstrated that cattle raised on slats that are fitted with rubber perform better than cattle that are on concrete slats alone; however, lameness continues to be a problem even with this modification. This project investigated the feasibility of adding additional commercially available solid mats to the rubber-coated slatted floor barn and observing animal behavior and outcomes in a group setting. The objective was to determine if creating an improved lying area through a relatively simple management change could positively impact the outcome of these animals. Commercial mats were simple to install and were used immediately and extensively by the cattle. However, the outcome provided mixed results. The additional mats provided challenges with cleanliness. Steer calves became dirty faster and more severely than heifers. Forty-three percent of the heifer calves and 19% of the steers were culled early. More work is needed to better understand and provide solutions for this welfare issue. Full article