Search Results (4,893)

This study investigated the dynamic behavior of AA7075 plates joined by Friction Stir Welding (FSW), focusing on the influence of key process parameters, rotation, and traverse speeds, on the resulting dynamic characteristics. Experimental Modal Analysis (EMA) was performed under free boundary conditions to determine resonance frequencies, mode shapes, and damping ratios, revealing that an increase in traverse speed consistently led to a decrease in natural frequencies across most modes, thereby indicating reduced joint stiffness attributed to insufficient heat input. Furthermore, localized weld defects caused significant damping variations, particularly in low-order modes. To complement the experimental findings and enable simultaneous, multi-output prediction of these coupled dynamic parameters, a Co-Active Neuro-Fuzzy Inference System (CANFIS) model was developed. The CANFIS architecture utilized spindle speed and feed rate as inputs to predict natural frequency and damping ratio for multiple vibration modes as tightly coupled outputs. The trained model demonstrated strong agreement and high predictive accuracy against the EMA experimental data, with convergence analysis confirming its stable learning and excellent generalization capability. The successful integration of EMA and CANFIS establishes a robust hybrid framework for both physical interpretation and intelligent, coupled prediction of the dynamic behavior of FSW-welded AA7075 plates. Full article

The widespread panzootic of clade 2.3.4.4b highly pathogenic avian influenza (HPAI) H5N1 necessitates the development of vaccine platforms capable of rapid adaptation to emerging antigenic variants. Although commercial recombinant turkey herpesvirus (rHVT) vaccines are available, they often utilize heterologous inserts that may fail to optimally limit viral shedding of novel field strains. Here, we report the rapid construction of a homologous rHVT-H5 vaccine expressing the hemagglutinin (HA) gene of a representative clade 2.3.4.4b isolate via CRISPR/Cas9-mediated non-homologous end joining (NHEJ). In vitro characterization confirmed stable HA surface expression and growth kinetics comparable to the parental virus. In specific-pathogen-free (SPF) chickens, rHVT-H5 elicited robust hemagglutination inhibition (HI) antibody titers. Following lethal challenge with a homologous clade 2.3.4.4b H5N1 virus, the vaccine conferred 100% protection against mortality and clinical signs while significantly reduced oropharyngeal sheddings and completely inhibited viral shedding in cloacal samples. These findings demonstrate that an antigenically matched rHVT-H5 constitutes a promising strategy for mitigating the ongoing global threat posed by clade 2.3.4.4b HPAI H5N1. Full article

Background/Objectives: An impediment to successful drug discovery is the potential for off-target liabilities to eliminate otherwise promising candidates. As the drug discovery process is time-consuming and expensive, the use of artificial intelligence (AI) methods such as machine learning (ML) has drastically increased. It is invaluable to generate models that can quickly differentiate between successful and unsuccessful small-molecule drug candidates. Previous efforts established that molecular similarity could be used with other metrics to inform predictions of potential activity against a protein target. Similar methods were pursued here to combine similarity and machine learning for a collection of models called OPLE. Methods: Models were trained with proprietary and publicly available data to predict the likelihood of a given compound to be active against targets present in existing experimental SafetyScreen panels 18 and 44. Two-dimensional (2D) Tanimoto similarity from extended-connectivity fingerprints (ECFPs) and trained ML models were combined to obtain predictions. Results: Using all training data, a relationship between similarity and activity was established by fitting a probability assignment curve. Calibrated ML label assignment likelihoods were joined with the predictions from ECFP Tanimoto similarity to known active compounds using the belief theory formula, which maintains that activity prediction increases when both pieces of evidence support it. When assessing the performance of OPLE models for SafetyScreen 18 and 44 targets with external data from ChEMBL, more than 80% of the models had recall values greater than 0.8. This indicated favorable predictive ability to identify active molecules while limiting false negative predictions. Conclusions: Predicting and experimentally verifying safety liabilities is insightful at every stage of small-molecule drug discovery. This early detection tool can help project teams save resources that could be better deployed on series with no predicted or measured off-target liabilities. Full article

Background: Burnout negatively impacts clinicians, patients, and healthcare systems. We examined the immediate and sustained effects of an evidence-based, multi-modal Stress Management and Resiliency Training (SMART) Program on clinician well-being. Methods: Clinicians who registered to participate in the SMART Program were invited to join an observational study and complete questionnaires before the program started, at two months (post-program), and at eight months (six months following program completion). Results: We found significant improvements in well-being, burnout, perceived stress, stress coping, resilience, and self-compassion at 2 months (all p < 0.001), with moderate-to-large effect sizes (d = 0.57 to 1.0). Significant benefits were maintained at 8 months, with small-to-moderate effect sizes (d = 0.41 to 0.65). Exploratory analyses found significant correlations between improvements in well-being from baseline to 8 months and the number of stress-management techniques used at 8 months (r = 0.53, p < 0.0001) and the number of days on which participants practiced meditation for at least 10 min (r = 0.28, p = 0.049). Conclusion: Participation in the SMART Program was associated with significant improvements in clinician well-being that persisted six months following program completion and was positively associated with the number of stress-management tools used and meditation practice. Full article

The performance of conventional precipitation-strengthened copper alloys drastically degrades at temperatures exceeding 500 °C, hindering their application under extreme conditions like those in nuclear fusion reactors. Oxide dispersion–strengthened copper (ODS–Cu) alloy surmounts these constraints by incorporating thermally stable, nanoscale oxide dispersoids that simultaneously confer strengthening, microstructural stabilization, and enhanced irradiation tolerance, while preserving high thermal conductivity. This review comprehensively examines the state of the art in ODS–Cu alloy from a “processing–microstructure–property” perspective. We critically assess established and emerging fabrication routes, including internal oxidation, mechanical alloying, wet chemical synthesis, reactive spray deposition, and additive manufacturing, to evaluate their efficacy in achieving uniform dispersions of coherent/semi-coherent nano-oxides at engineering-relevant scales. The underlying strengthening mechanisms and performance trade-offs are quantitatively analyzed. The review also outlines strategies for joining and manufacturing complex components, highlights key gaps in metrology and reproducibility, and proposes a roadmap for research and standardization to accelerate industrial deployment in plasma-facing components. Full article

Genomic instability caused by defective DNA double-strand break (DSB) repair is a key determinant of cellular radiosensitivity. The Long–Evans cinnamon (LEC) rat is a rare naturally occurring model with marked radiosensitivity, and a major quantitative trait locus, X-ray hypersensitivity 1 (xhs1), has been mapped to rat chromosome 4; however, the causal mechanism has remained unclear. Here, we investigated the cellular and molecular basis of xhs1-associated radiosensitivity using LEA and LEC rat-derived cells and human cultured cells. Exploratory RNA-seq of pre-hepatitic liver tissue identified a sequence variant within the Hmces transcript in LEC rats. Consistently, HMCES protein levels were markedly reduced in multiple tissues and liver-derived cell lines from LEC rats. Functional analyses showed that reduced HMCES activity prolonged γH2AX signaling after X-ray irradiation, indicating delayed DSB resolution. Clonogenic survival assays demonstrated increased radiosensitivity in HMCES-deficient cells, which was partially rescued by restoring HMCES expression in stable LEA/LEC lines. Moreover, pimEJ5GFP reporter assays revealed significantly decreased end-joining repair activity in HMCES-knockout human cells. Together, these results establish HMCES as a critical mediator of DSB repair and cellular radioresistance, identify HMCES dysfunction as a core genetic determinant underlying xhs1-associated radiosensitivity, and provide mechanistic insight into radiation response architecture in a naturally occurring radiosensitive model. Full article

Human activity impacts the natural environment. One example of such an impact is energy production, including energy from renewable sources. The aim of this study was to analyse and assess changes in the state of the environment in 2008, 2015 and 2023, resulting from the development and structure of renewable energy sources in EU countries. Three research questions were formulated: Question 1 (Q1). Is the state of the environment in most EU countries characterised by variability in terms of the level of renewable energy development? Question 2 (Q2). Has the composition of the group of EU countries with the highest environmental status changed? Question 3 (Q3). Is the group of EU countries with the highest environmental status characterised by a diverse structure of renewable energy sources used? The study covers three key periods: 2008, 2015 and 2023. This approach allows for the identification of the impact of crisis factors on the relationship between the energy transition and environmental status. The evaluation applied the TOPSIS, EDAS and Ward’s methods. Based on a substantive and formal analysis, diagnostic variables were selected: 18 describing the structure and level of RES development, 7 economic indicators and 11 reflecting the environmental status of EU countries. The selection criterion was data availability, with sources drawn from the EUROSTAT, IRENA and World Bank Group databases. The results show that the main leaders were Italy, Sweden, France and Germany, with Austria and Denmark maintaining high positions only in 2008. Italy took the lead in 2015 and retained it in 2023 thanks to extensive emission reductions, while Finland joined the top group. Poland and Lithuania ranked last in 2015 and 2023. A growing gap was also observed between the leaders and the lowest-performing countries. Among the highest-ranked countries, hydropower was the dominant RES, while in Germany and Denmark, wind energy and biofuels also played a key role. Cluster analysis using Ward’s method confirmed the diversity of environmental and energy profiles, as well as Belgium’s distinct position. The study confirms the instability of most EU countries’ positions, the persistence of a small group of leaders and widening disparities in sustainable environmental development within the EU. Full article

Refill Friction Stir Spot Welding (RFSSW) provides significant advantages over competing spot joining technologies, but detecting RFSSW’s often small and subtle defects remains challenging. In this study, kinematic feedback data from a RFSSW machine’s factory-installed sensors was used to successfully predict defect presence with 96% accuracy (F1 = 0.92) and preliminary multi-class defect diagnosis with 84% accuracy (F1 = 0.82). Thirty adverse treatments (e.g., contaminated coupons, worn tools, and incorrect material thickness) were carried out to create 300 potentially defective welds, plus control welds, which were then evaluated using profilometry, computed tomography (CT) scanning, cutting and polishing, and tensile testing. Various machine learning (ML) models were trained and compared on statistical features, with support vector machine (SVM) achieving top performance on final quality prediction (binary), random forest outperforming other models in classifying welds into six diagnosis categories (plus a control category) based on the adverse treatments. Key predictors linking process signals to defect formation were identified, such as minimum spindle torque during the plunge phase. In conclusion a framework is proposed to integrate these models into a manufacturing setting for low-cost, full-coverage evaluation of RFSSWs. Full article

Reliable joining of multi-layer aluminum foil current collectors is crucial for enhancing the performance and safety of high-capacity lithium-ion batteries. However, laser welding of such thin-thick aluminum combinations is often hindered by porosity, cracks and unstable weld-pool behavior. In this study, a ring-mode fiber laser combined with sinusoidal oscillation and linearly gradient power modulation was employed to achieve high-quality lap welding between 80 layers of 1060 aluminum foil (1 mm in total thickness) and a 1.5 mm thick aluminum plate. Welding experiments and thermo-mechanical simulations were conducted to investigate the effects of welding speed (15–45 mm/s) and central-power modulation parameters (−2, 0, +2, +4) on weld morphology, defect formation, and mechanical properties. The results indicate that increasing the welding speed can effectively suppress cracks and improve the shear strength from 249.8 N to 403.9 N, but it also leads to an increase in porosity from 5.78% to 12.26% and deterioration of the weld reinforcement. Higher central-power modulation (+2, +4) transformed the weld-pool geometry from an ω shape to U shape, effectively suppressing fusion-line cracks but leading to increased porosity (up to 8.41%) and deteriorated surface morphology. Overall, a low welding speed of 15 mm/s combined with an optimized power modulation strategy achieves effective crack suppression while maintaining controlled porosity, resulting in a welded joint with superior comprehensive performance. This research provides a robust process solution for high-quality laser welding of multi-layer aluminum foil current collectors in power battery manufacturing. Full article

The rise in electric vehicles (EVs) with lithium-ion batteries supports net-zero goals, but the increasing demand will inevitably generate more battery waste. Current pack designs often rely on permanent joining techniques, which hinder disassembly and thereby limit serviceability, reuse and recycling. A critical challenge is the removal of the battery lid, typically bonded to the pack frame with sealant adhesives. In the absence of design for disassembly requirements for OEMs, this study investigates a novel debonding strategy focused on the lid-to-frame bonding. A silane-based adhesive commonly used in battery packs is first characterised under tensile, shear and mode I conditions to establish the baseline performance in the range of flexible adhesive properties. Herein, a heat-activated primer is introduced as a debondable interfacial layer between the adhesive and the substrate. Upon activation at 150 ${}^{\circ }$C, the primer significantly reduces adhesion, around 98% of the initial joint strength, enabling room temperature debonding. The primer demonstrates strong compatibility with epoxy and polyurethane adhesives, but its performance with silane-based systems still needs to be improved in terms of the primer’s compatibility with silane-based adhesives. Finally, a small-scale testing apparatus is developed to evaluate primer effectiveness in the disassembly of battery lids. This approach represents a promising step toward more serviceable, recyclable and sustainable battery systems. Full article

Friction stir spot welding (FSSW) is a novel variant of Friction Stir welding (FSW), developed by Mazda Motors and Kawasaki Heavy Industries to join similar and dissimilar materials in a solid state. It is an economic and environmentally friendly alternative to resistance spot welding (RSW). The FSSW technique, however, includes some structural defects imbedded within the weld joint, such as keyhole formation, hook crack, and bond line oxidation challenging the joint strength. The unique properties of nanomaterials in the reinforcement of metal matrices motivated researchers to enhance the FSSW joints’ strength. Previous studies successfully fabricated nano-reinforced FSSW joints. At different volumetric ratios of nano-reinforcement, nanoparticles may agglomerate due to inefficient stirring of the welding tool pin, forming stress concentration sites and brittle phases, affecting tensile and fatigue strength under static and cyclic loading conditions, respectively. This work investigated how the welding tool pin affects stirring efficiency by controlling the distribution of a nano-reinforcing material within the joint stir zone (SZ), and thus the tensile and fatigue strength of the FSSW joints. Sheets of AA6061-T6 of 1.8 mm thickness were used as a base material. In addition, graphene nanoplatelets (GNPs) with lateral sizes of 1–10 µm and thicknesses of 3–9 nm were used as nano-reinforcements. GNP-reinforced FSSW specimens were prepared and successfully fabricated. Optical microscope (OM) and field emission scanning electron microscope (FE-SEM) methods were employed to visualize the GNPs’ incorporation into the SZs of the FSSW joints. Micrographs of as-welded specimens showed lower formations of scattered, clustered GNPs achieved by the threaded pin tool compared to continuous agglomerations observed when the cylindrical pin tool was used. Tensile test results revealed a significant improvement of about 30% exhibited by the threaded pin tool compared to the cylindrical pin tool, while fatigue test showed an improvement of 46–24% for the low- and high-cycle fatigue, respectively. Full article

Mycoplasma synoviae (MS) is a major pathogen threatening China’s poultry industry, causing severe economic losses, and clarifying its epidemiology is pivotal for disease control and flock purification. In this study, a total of 3215 chicken samples collected from 643 broiler farms across 15 provinces in China in 2024 were analyzed. PCR detected 14% positivity (450 samples), and 18 isolates obtained from these positive samples (4.0% isolation rate). Multilocus sequence typing (MLST, 7 housekeeping genes) and neighbor-joining phylogenetic analysis (integrating 425 reference sequences from public databases) identified 13 distinct sequence types (STs), demonstrating considerable genetic diversity among circulating MS strains. Pathogenicity assessment of the five isolates revealed that the infected chickens exhibited varying degrees of infectious synovitis, while no respiratory signs were observed. In addition, antimicrobial susceptibility testing against 10 commonly used antibiotics was conducted on the 18 strains, providing urgently needed guidance for rational drug use in the clinical treatment of both breeder and broiler flocks. This large-scale epidemiological study yields crucial insights into the current prevalence and genetic diversity of MS in China and lays a scientific foundation for formulating targeted prevention strategies and optimizing management practices. Full article

Non-homologous end joining (NHEJ) is a critical DNA double-strand break (DSB) repair pathway that operates throughout the cell cycle to maintain the genomic stability of the cell. Unlike homologous recombination (HR), NHEJ is capable of repairing DSBs without the need for a homologous template, making it a rapid response mechanism, but potentially prone to errors. Central to NHEJ function and essential for the ligation through the recruitment and activation of additional repair factors, such as Artemis, XRCC4, and DNA ligase IV, is the DNA-dependent protein kinase (DNA-PK) complex. Dysregulation in the NHEJ pathway contributes to genomic instability, oncogenesis, and resistance to genotoxic therapies. Consequently, inhibitors of DNA-PK have emerged as promising therapeutic agents to sensitize tumor cells to radiation and DNA-damaging chemotherapeutics. Inhibiting the DNA-PK ability to recruit the protein complex needed for successful DSB repair promotes cell death through apoptosis or mitotic catastrophe. While inhibitors of DNA-PK can be used to enhance the effects of genotoxic therapies, the field still struggles to address critical problems: how to best exploit the differential DNA repair capacities among tumor subtypes, how to maximize radiosensitization of cancerous cells while sparing normal tissues, and how to translate preclinical studies into clinical benefits. Given that NHEJ constitutes the primary line of defense against radiation-induced damage, rapidly repairing the majority of double-strand breaks throughout the cell cycle, this review concentrates on targeting the DNA-PK complex, as the master regulator of this rapid-response mechanism, highlighting why its inhibition represents a strategic action to overcome intrinsic radioresistance. The implementation of DNA-PK inhibitors into medical practice can enable the stratification of oncologic patients into two categories, based on the tumors’ vulnerability to NHEJ disruptions. Thus, the therapeutic pathways of patients with NHEJ tumors could branch, combining traditional genotoxic therapies (radiation and DNA-damaging chemotherapeutics) with DNA-PK inhibitors to achieve an enhanced effect and improved survival outcomes. Full article

The global shipping industry is surging ahead, and with it, a quiet revolution is taking place on the water: marine lithium-ion batteries have emerged as a crucial clean energy carrier, powering everything from ferries to container ships. When these vessels dock, they increasingly rely on shore power charging systems to refuel—essentially, plugging in instead of idling on diesel. But predicting how much power they will need is not straightforward. Think about it: different ships, varying battery sizes, mixed charging technologies, and unpredictable port stays all come into play, creating a load profile that is random, uneven, and often concentrated—a real headache for grid planners. So how do you forecast something so inherently variable? This study turned to the Monte Carlo method, a probabilistic technique that thrives on uncertainty. Instead of seeking a single fixed answer, the model embraces randomness, feeding in real-world data on supply modes, vessel types, battery capacity, and operational hours. Through repeated random sampling and load simulation, it builds up a realistic picture of potential charging demand. We ran the numbers for a simulated fleet of 400 vessels, and the results speak for themselves: load factors landed at 0.35 for conventional AC shore power, 0.39 for high-voltage DC, 0.33 for renewable-based systems, 0.64 for smart microgrids, and 0.76 when energy storage joined the mix. Notice how storage and microgrids really smooth things out? What does this mean in practice? Well, it turns out that Monte Carlo is not just academically elegant, it is practically useful. By quantifying uncertainty and delivering load factors within confidence intervals, the method offers port operators something precious: a data-backed foundation for decision-making. Whether it is sizing infrastructure, designing tariff incentives, or weighing the grid impact of different shore power setups, this approach adds clarity. In the bigger picture, that kind of insight matters. As ports worldwide strive to support cleaner shipping and align with climate goals—China’s “dual carbon” ambition being a case in point—achieving a reliable handle on charging demand is not just technical; it is strategic. Here, probabilistic modeling shifts from a simulation exercise to a tangible tool for greener, more resilient port energy management. Full article

The reliable joining of dissimilar stainless steel and carbon steel remains a critical challenge in Metal Inert Gas (MIG) welding due to complex thermal–metallurgical interactions and the formation of brittle phases at the weld interface. In this study, a Taguchi-based design of experiments was employed to systematically optimize MIG welding parameters for SUS201/S20C dissimilar joints using a SUS201 filler wire, with particular attention to the welding current, voltage, travel speed, and electrode stick-out. The welding process was performed using an automatic welding robot. Tensile specimens were tested on a universal testing machine. Microstructural analysis was performed using a metallurgical microscope. The microstructure reveals that the development of the carbon side’s large ferrite and the stainless steel side’s δ-ferrite both significantly degrade joint quality. Among all process parameters, electrode stick-out is identified as the most influential parameter governing both tensile and bending performance, highlighting a critical process sensitivity that has received limited attention in prior studies. Optimized parameter combinations are required to maximize tensile and flexural responses. The highest tensile strength is 450.96 MPa. These findings advance the understanding of parameter–microstructure–property relationships in dissimilar MIG welding. Future work applying numerical welding simulations and advanced evaluation techniques is recommended. Full article