Search Results (46,214)

This study presents a molecular dynamics (MD) investigation of water evaporation in copper nanochannels, with a focus on accurately modeling copper–water interactions through forcefield calibration. The TIP4P/2005 water model was coupled with the Modified Embedded Atom Method (MEAM) for copper, and the oxygen–copper Lennard–Jones (LJ) parameters were systematically tuned to match experimentally reported water contact angles (WCAs) on Cu (111) surfaces. Contact angles were extracted from simulation trajectories using a robust five-step protocol involving 2D kernel density estimation, adaptive thresholding, circle fitting, and mean squared error (MSE) validation. The optimized forcefield demonstrated strong agreement with experimental WCA values (50.2°–82.3°), enabling predictive control of wetting behavior by varying ε in the range 0.20–0.28 kcal/mol. Using this validated parameterization, we explored nanoscale evaporation in copper channels under varying thermal loads (300–600 K). The results reveal a clear temperature-dependent transition from interfacial-layer evaporation to bulk-phase vaporization, with evaporation onset and rate governed by the interplay between copper–water adhesion and thermal disruption of hydrogen bonding. These findings provide atomistically resolved insights into wetting and evaporation in metallic nanochannels, offering a calibrated framework for simulating phase-change heat transfer in advanced thermal management systems. Full article

Nucleobases play diverse structural and functional roles in biological systems. Understanding the fundamental properties of nucleobases is important for their applications as chemical probes of nucleic acid function. As the nucleobases are modified to tune their fluorescence or binding properties, their physical properties such as pK_a may also change. Unlike the canonical nucleobases, modified nucleobases are less well understood in terms of their acid-base properties. Previously, theoretical pK_a values of canonical, naturally modified, and aza-/deaza-modified nucleobases were determined. In this study, the theoretical pK_a values for 25 different fluorescent modified nucleobases (55 total pK_a values) were calculated by using an ab initio quantum mechanical method employing the B3LYP density functional with 6-31+G(d,p) basis set along with an implicit–explicit solvation model. The results of these computations are compared to known experimental pK_a values. The ability to estimate theoretical pK_a values will be beneficial for further development and applications of fluorescent nucleobases. Full article

We estimated, for the first time, the age of Diaphus watasei (Jordan & Starks, 1904) in the South China Sea (SCS) based on otolith microstructure. According to one-way ANOVA, differences were not observed between the sexes with regard to standard length, body mass, or age. Based on 137 specimens, the sex ratio and relationship between standard length and body mass was 1.32:1 (male/female) and W = 0.0000433L^2.78 (r² = 0.923), respectively. The von Bertalanffy model was fitted as L_t = 171.38 [1 − exp(−0.00206(t − 3.82))], r² = 0.645 (n = 92), which indicated a maximum growth rate of 0.356 mm/day. The speculated birth date of the 92 specimens of D. watasei occurred across almost all months of the year. Full article

This study presents a comparative performance analysis of three sensor technologies—microphone, magnetic pickup, and laser Doppler vibrometer—for capturing string vibration under varied excitation conditions: striking, plectrum plucking, and wire plucking. Two different magnetic pickups are included in the comparison. Measurements were taken at multiple excitation levels on a simplified electric guitar mounted on a stable platform with repeatable excitation mechanisms. The analysis focuses on each sensor’s capacity to resolve fine-scale waveform features during the initial attack while also taking into account its capability to measure general changes in instrument dynamics and timbre. We evaluate their ability to distinguish vibro-acoustic phenomena resulting from changes in excitation method and strength as well as measurement location. Our findings highlight the significant influence of sensor choice on observable string vibration. While the microphone captures the overall radiated sound, it lacks the required spatial selectivity and offers poor SNR performance 34 dB lower then other methods. Magnetic pickups enable precise string-specific measurements, offering a compelling balance of accuracy and cost-effectiveness. Results show that their low-pass frequency characteristic limits temporal fidelity and must be accounted for when analysing general sound timbre. Laser Doppler vibrometers provide superior micro-temporal fidelity, which can have critical implications for physical modeling, instrument design, and advanced audio signal processing, but have severe practical limitations. Critically, we demonstrate that the required optical target, even when weighing as little as 0.1% of the string’s mass, alters the string’s vibratory characteristics by influencing RMS energy and spectral content. Full article

Turbulence and wind gusts pose significant risks to the safety and efficiency of UAVs (uncrewed aerial vehicles) in urban environments. In these settings, wind dynamics are strongly influenced by interactions with buildings and terrain, giving rise to small-scale phenomena such as vortex shedding and gusts. These wind speed oscillations generate unsteady forces that can destabilise UAV flight, particularly for small vehicles. Additionally, predicting their formation requires high-resolution Computational Fluid Dynamics (CFD) models, as current weather forecasting tools lack the resolution to capture these phenomena. However, such models require 3D representations of study areas with high geometric consistency and detail, which are not available for most cities. To address this issue, this work introduces an automated methodology for urban CFD mesh generation using open-source data. The proposed method generates error-free meshes compatible with OpenFOAM and includes tools for geometry modification, enhancing solver convergence and enabling adjustments to mesh complexity based on computational resources. Using this approach, CFD simulations are conducted for the city of Ourense, followed by an analysis of their impact on UAV operations and the integration of the system into a trajectory optimisation framework. The CFD model is also validated using experimental anemometer measurements. Full article

Terrestrial laser scanners (TLS) are widely used for deformation monitoring due to their ability to rapidly generate 3D point clouds. However, high-precision deliverables are increasingly required in TLS-based remote sensing applications to distinguish between measurement accuracies and actual geometric displacements. This study addresses the impact of atmospheric refraction, a primary source of systematic error in long-range terrestrial laser scanning, which causes laser beams to deviate from their theoretical path and intersect different object points on the target surface. A comprehensive study of two physical refractive index models (Ciddor and Closed Formula) is presented here, along with further developments on 3D spatial gradients of the refractive index. Field experiments were conducted using two long-range terrestrial laser scanners (Leica ScanStation P50 (Leica Geosystems, Heerbrugg, Switzerland) and Maptek I-Site 8820 (Maptek, Adelaide, Australia)) with reference back to a control network at two monitoring sites: a mine site for long-range measurements and a dam site for vertical angle measurements. The results demonstrate that, while conventional physical atmospheric models provide moderate improvement in accuracy, typically at the centimeter- or millimeter-level, the proposed advanced physical model—incorporating refractive index gradients—and the hybrid physical model—combining validated field results from the advanced model with a neural network algorithm—consistently achieve reliable millimeter-level accuracy in 3D point coordinates, by explicitly accounting for refractive index variations along the laser path. The robustness of these findings was further confirmed across different scanners and scanning environments. Full article

This study investigates the mechanical performance of squeezed branch piles under combined loads (horizontal combined with uplift/compression) in silty clay through model tests. Based on a systematic comparison of the mechanical responses among straight-shaft piles, single-plate piles, and double-plate piles, the load-dependent behavior of branched piles is revealed, and optimized design principles are proposed. The results demonstrate that under horizontal combined loads, squeezed branch piles effectively mobilize soil-arching effects via the bearing plates, leading to significant enhancements in both horizontal and vertical-bearing capacities compared to straight-shaft piles. Double-plate piles exhibit superior overall deformation resistance due to composite confinement; however, an adverse superposition effect at a plate spacing of 2 d may result in a marginally lower capacity. The horizontal capacity of single-plate piles increases with embedment depth, with the axial force peaking at a critical depth of 4 d (embedment depth of first plate). The upper plate plays a dominant role in resisting deformation, consistently carrying 75–105% higher axial force than the lower plate. This research provides important theoretical support and practical references for the design of pile foundations subjected to complex loading conditions. Full article

Educational strategies based on technological models that integrate the dimensions of prevention, screening, and treatment of diabetic foot ulcers are emerging as promising methods to improve nurses’ knowledge, skills, and clinical competencies in primary care. In this investigation, we evaluated the effectiveness of a digital education program, mediated by a virtual learning environment, in enhancing nurses’ clinical knowledge about diabetic foot ulcers. This quasi-experimental intervention study was conducted with 114 nurses, selected for convenience, from the five health districts that make up primary care in the municipality of Teresina, Brazil. Two stages, separated by the educational intervention, allowed us to measure their knowledge levels before and after the implementation of the digital technology. A characterization form and the Nurse Knowledge Assessment Questionnaire on Diabetic Foot were used to evaluate the outcomes. The McNemar test compared the pre- and post-intervention knowledge levels, while accuracy rate-based parameters allowed for the classification of results into performance categories. The intervention effect size was estimated using Cohen’s d test. Results showed substantial improvements in knowledge, particularly in domains related to definition (p = 0.002), risk factors (p < 0.001), associated complications (p < 0.001), signs and symptoms of neuropathies (p < 0.001), application of tests to assess protective sensation (p < 0.001) and foot biomechanics (p < 0.001), risk classification (p < 0.001), and prevention strategies (p < 0.001), with performance ratings predominantly “good” or “excellent” after the intervention. The effect size for paired samples was large (Cohen’s dz = 1.82), based on the total knowledge scores. Findings support the effectiveness signal of the virtual learning environment for knowledge improvement; however, without a control group, we cannot rule out testing effects. Controlled or stepped-wedge trials should confirm causality. Full article

As a contribution to our understanding of postglacial colonisation history of Anatolia, the Caucasus and the Middle East, we increased the existing phylogeographic coverage of the widespread Balkan short-tailed mouse Mus macedonicus. This added 92 new mitochondrial D-loop sequences (73 new haplotypes) from Anatolia and Thrace to generate a total dataset for the species of 221 sequences (174 haplotypes). We confirmed the previously described existence of a northern lineage (Anatolia, the southern Balkans, the Caucasus, Iran and Syria) and southern lineage (Israel and Lebanon) and generated Bayesian Skyline Plots to show demographic expansion after the Last Glacial Maximum (LGM) in the northern lineage but not the southern. We used haplotype networks to reveal haplotypes close to the ancestral condition of the northern lineage and to infer spread through its range, including colonisation of the southern Balkans. Our various phylogenetic reconstructions also show finer-scale geographic structuring. M. macedonicus likely occupied two separate glacial refugia in the vicinities of Israel and Lebanon (southern lineage) and Anatolia, Georgia and Iran (northern lineage) although further work is needed for precise localisation. M. macedonicus has become a well-worked model system for the phylogeography of a region deserving more attention. Full article

Coalbed-methane (CBM) extraction involves complex processes such as desorption, diffusion, and seepage, significantly increasing the difficulty of numerical simulation. To enable efficient CBM development, this study establishes an integrated simulation workflow for CBM, encompassing geological modeling, geomechanical modeling, hydraulic fracture simulation, and production dynamic simulation. Specifically, the unconventional fracture model (UFM), integrated within the Petrel commercial software, is applied for fracture simulation, with an unstructured grid constructing the CBM production model. Subsequently, based on the case study of well pad A in the Daning–Jixian block, the effects of well spacing and hydraulic fractures on gas production were analyzed. The results indicate that the significant stress difference between the coal seam and the top/bottom strata constrains fracture height, with simulated hydraulic fractures ranging from 169.79 to 215.84 m in length, 8.91 to 10.45 m in height, and 121.92 to 248.71 mD·m in conductivity. Due to the low matrix permeability, pressure drop and desorption primarily occur in the stimulated reservoir volume (SRV) region. The calibrated model predicts a 10-year cumulative gas production of 616 × 10⁴ m³ for the well group, with a recovery rate of 10.17%, indicating significant potential for enhancing recovery rates. Maximum cumulative gas production occurs when well spacing slightly exceeds fracture length. Beyond 200 mD·m, fracture conductivity has diminishing returns on production. Fracture length increases from 100 to 250 m show near-linear growth in production, but further increases yield smaller gains. These findings provide valuable insights for evaluating development performance and exploiting remaining gas resources for CBM. Full article

A deflection prediction approach based on an adaptive MEC–RBF neural network was developed in this study. By dynamically optimizing the centres, widths, and weights of the RBF network, the proposed method substantially increases the prediction accuracy, and it achieves an R² of 0.9789 and an RMSE of 1.4978 on the training dataset. It effectively resolves the stability challenges that are associated with nonlinear construction conditions in traditional models. An orthogonal experimental design analysis revealed that the girder block length and the cantilever-to-span length ratio (d/L) were the most influential factors that affected deflection, whereas the effects of uniformly distributed loads and temperature were negligible, thereby providing a sound basis for parameter simplification. The application of the model to the Hannan Yangtze River Bridge yielded a maximum discrepancy of only 5.56 mm (17.7% error rate) between the predicted and measured values, thus demonstrating its practical engineering reliability. By innovatively integrating intelligent optimization techniques with neural networks, this approach overcomes the limitations in terms of real-time responsiveness and long-term stability of conventional methods and offers an efficient and reliable technical tool for the control of large-scale bridge construction. Full article

As a systematic project, corporate green innovation involves technological, organizational, and environmental dimensions. Therefore, its effective functioning is contingent on guidance from internal leadership. STEM represents an integration of science, technology, engineering, and mathematics education. A STEM CEO is a chief executive officer holding a degree in science, engineering, agriculture, or medicine. However, research on the impact of STEM CEOs on green innovation is limited. Using data from Chinese listed manufacturing firms from 2010 to 2023, panel fixed effects models reveal that STEM CEOs positively influence corporate green innovation. Further analysis indicates that alleviating financing constraints, fostering external collaboration, increasing R&D investment, and improving the efficiency of innovation resource allocation are key pathways through which STEM CEOs enhance green innovation output. Furthermore, this impact is positively moderated by the level of green finance development and the intensity of market competition. Finally, heterogeneity tests demonstrate that these positive effects are more pronounced for firms with high public environmental concern, in non-heavily polluting industries, with strong ESG performance, and in highly competitive industries. These findings underscore the role of STEM leaders in enhancing the output of green innovation systems, offering actionable insights into the interaction between STEM CEOs and the external environment. Full article

Yeast culture (YC) is widely used in dairy production to enhance milk yield and quality, yet effects vary due to differences in products, doses, and trial conditions. This meta-analysis evaluated the impact of YC supplementation on milk yield and composition in lactating Holstein cows, aiming to identify effective yeast culture types, dosages, and duration of use. A systematic search of PubMed, Web of Science, and CNKI for randomized controlled trials (RCTs) from 2000 to 2024 was conducted. Following PICOS criteria, 23 RCTs comprising 32 comparisons and over 3200 cows were included. Data were analyzed using RevMan 5.3 and Stata/MP 15.0 to compute standardized mean differences (SMD) and 95% confidence intervals with random-effects models. Subgroup and sensitivity analyses were performed. Results showed that YC supplementation significantly improved milk yield (SMD = 2.14), fat (SMD = 0.57), protein (SMD = 1.34), and lactose content (SMD = 0.61). Subgroup analysis revealed that supplementation with saccharomyces cerevisiae at a dosage of 10–50 g/d effectively increased milk yield during lactation 42–56 d. In contrast, during the lactation 21–30 d, different dosages of saccharomyces cerevisiae exerted differential effects on milk composition: supplementation at 60–120 g/d contributed to an increase in milk fat content, while supplementation at 10–50 g/d significantly enhanced milk protein level. Furthermore, lactose content was not significantly associated with the feeding period of saccharomyces cerevisiae; however, high-dose (>120 g/d) could significantly increase lactose content. Significant heterogeneity (I² = 70.7–89.6%) was observed, largely due to strain and dose variations. In conclusion, YC effectively enhances milk production and composition, with optimal outcomes depending on yeast type, dose, and duration, providing evidence-based recommendations for targeted supplementation strategies. Full article

Background/Objectives: The cannabinoid type 2 receptor (CB₂ receptor) has been extensively studied in recent years due to the benefits associated with its modulation, including the regulation of the inflammatory response, neuroimmunomodulatory properties, and antitumor effects, all with the advantage of lacking significant psychoactive effects. Herein, we report the design, synthesis, characterization, biological assays, and molecular modelling analyses of novel (5/6-chloro-2-aryl-1H-benzo [d]imidazol-1-yl)(4-methoxyphenyl)methanone and 5/6-chloro-1-(4-methoxybenzyl)-2-aryl-1H-benzo [d]imidazole regioisomers as potential cannabinoid type 2 receptor ligands. Methods: The compounds were evaluated for their presumed CB₂ agonist activity using an indirect receptor-dependent apoptotic cell death assay exerted by cannabinoids, using the cell lines HEK293 (low CB₁/CB₂ expression), U-87 MG (high CB₁ expression), and HL-60 (exclusive CB₂ expression), and including the known cannabinoid ligands WIN-55,212-2 and AM630 as reference ligands. Flow cytometry was performed to assess apoptosis. Molecular docking and molecular dynamics simulations were used to explore ligand-receptor interactions at the CB₂ active site. Results: Compounds 3a, 3b’, 3c, and 4b selectively reduced HL-60 cell viability, similar to WIN-55,212-2, while showing no toxicity toward HEK293 or U-87 MG cells. Flow cytometry indicated that compounds 3a and 3c induced apoptosis in HL-60 cells comparable to WIN-55,212-2. Computational studies suggested that both compounds bind within the CB₂ receptor active site predominantly through π–π and hydrophobic interactions involving their benzo [d]imidazole cores, 2-aryl moieties, and 4-methoxybenzoyl scaffolds, resembling the binding patterns of established CB₂ ligands. Conclusions: Compounds 3a and 3c exert selective cytotoxicity against HL-60 cells, likely via a CB₂ agonist-mediated apoptotic mechanism. The applied combined experimental and computational approach provides a rapid, informative strategy for preliminary evaluation of CB₂ ligands and guides subsequent detailed pharmacological studies. Full article

Arsenic (As) toxicity drives the evolution of resistance mechanisms in environmental microorganisms. Bacteria of the Bacillus genus are frequently identified in isolates from arsenic-contaminated sites, highlighting the importance of understanding the molecular mechanisms related to this bacterial genus. Bacillus subtilis, a soil microorganism and Gram-positive model paradigm, employs multiple strategies to counteract As toxicity, including biosorption, redox transformation, active efflux, and inducible genetic regulation. This review provides a comprehensive analysis of the physiological and molecular mechanisms involved in arsenic response in B. subtilis and related species, focusing on the ars and ase operons. The ars operon, located within the mobile SKIN element, encodes a reductase (ArsC), an Acr3-type efflux pump (ArsB), a carbon–arsenic lyase (ArsI/YqcK), and a transcriptional repressor (ArsR), all co-regulated in response to arsenic. In turn, the ase operon contributes to resistance via an ArsB-type efflux system (AseA) and its own regulatory protein (AseR) but lacks an arsenate reductase. Additionally, genes such as aioAB, arrAB, and arsD are discussed, along with evidence for extracellular detoxification and cell surface immobilization of As. Studies on environmental Bacillus species are examined, pointing out the evolutionary implications of As resistance and the biotechnological potential for remediation of contaminated sites. Full article