Search Results (647)

This study investigated into how different current input levels during cold metal transfer (CMT) welding affected the characteristics of the weld bead. For the current variation, three input values were taken: 80 A, 90 A, and 100 A. Weld beads fabricated from all three current inputs were compared by analysing their microstructure, microhardness, tensile strength, and residual stress. The microhardness of the weld bead decreased when the current parameter was increased from 80 A to 100 A. The average tensile strength increased from 80 A to 90 A. The lowest residual stress calculated was −135 MPa with 100 A current. Full article

Background: Charcot–Marie–Tooth (CMT) is a group of inherited diseases impairing the peripheral nervous system. CMT originates from genetic variants that affect proteins fundamental for the myelination of peripheral nerves and survival. Moreover, environmental and humoral factors can impact disease development and evolution. Currently, no therapy is available. Metabolomics is an emerging field of biomedical research that enables the development of novel biomarkers for neurodegenerative diseases by targeting metabolic pathways or metabolites. This study aimed to evaluate the metabolomics profile of CMT disease by comparing patients with healthy individuals. Methods: A total of 22 CMT patients (CMT) were included in this study and were demographically matched with 26 healthy individuals (C). Serum samples were analyzed through Nuclear Magnetic Resonance spectroscopy, and multivariate and univariate statistical analyses were subsequently applied. Results: A supervised model showed a clear separation (R²X = 0.3; R²Y = 0.7; Q² = 0.4; p-value = 0.0004) between the two classes of subjects, and nine metabolites were found to be significantly different (2-hydroxybutyrate, 3-hydroxybutyrate, 3-methyl-2-oxovalerate, choline, citrate, glutamate, isoleucine, lysine, and methyl succinate). The combined ROC curve showed an AUC of 0.94 (CI: 0.9–1). Additional altered metabolic pathways were also identified within the disease context. Conclusion: This study represents a promising starting point, demonstrating the efficacy of metabolomics in evaluating CMT patients and identifying novel potential disease biomarkers. Full article

New theologies developed in tandem with evolutionary biology during the nineteenth century, which have been called metaphysical evolutionisms and evolutionary theologies. A subset of these theologies analyzed here were developed by thinkers who accepted biological science but rejected both biblical creationism and materialist science. Tools from the cognitive science of religion, including conceptual metaphor theory (CMT) and blending theory, also known as conceptual integration theory (CIT), can help to explain the development of these systems and their transformation between the nineteenth and the twentieth centuries. The analysis focuses on several stable and popular blends of ideas, which have continued with some alteration into the twenty-first century. The three blends evaluated here are Progressive Soul Evolution, Salvation is Evolution, and Evolution is Therapy. Major contributors to these blends are the theosophist and theologian Helena P. Blavatsky and psychologist Frederic W. H. Myers, both influenced by the spiritualist movement, particularly the ideas of the spiritualist and biologist Alfred Russel Wallace. The influence of these blends can be seen in the twentieth-century “Aquarian Frontier,” a group of 145 thinkers and organizations identified in 1975 by counterculture historian Theodore Roszak. Part of the appeal of these blends may be seen in their use of metaphors, including the Great Chain of Being and A Purposeful Life is a Journey. The application of the polysemic term evolution in a sense that does much of the theological work of salvation in Christianity can in part be explained by applying the principles of blending theory, including the vital relation “achieve a human scale,” as well as compressions of time and identity. These blends have been successful because they meet the needs of a population who are friendly towards science but disenchanted with traditional religions. The blends provide a satisfying new theology that extends beyond death for a subset of adherents, particularly in the New Age and spiritual but not religious (SBNR) movements, who combine the agency of self-directed “evolution” with the religious concepts of grace and transcendence. Full article

Background: Charcot–Marie–Tooth disease (CMT) is a genetically and phenotypically heterogeneous hereditary neuropathy. Axonal CMT type 2 (CMT2) subtypes often exhibit overlapping clinical features, which makes molecular genetic analysis essential for accurate diagnosis and subtype differentiation. Methods: This retrospective study included five pediatric patients who presented with gait disturbance, muscle weakness, and foot deformities and were subsequently diagnosed with axonal forms of CMT. Clinical data, electrophysiological studies, neuroimaging, and genetic analyses were evaluated. Whole exome sequencing (WES) was performed in three sporadic cases, while targeted CMT gene panel testing was used for two siblings. Variants were interpreted using ACMG guidelines, supported by public databases (ClinVar, HGMD, and VarSome), and confirmed by Sanger sequencing when available. Results: All had absent deep tendon reflexes and distal muscle weakness; three had intellectual disability. One patient was found to carry a novel homozygous frameshift variant (c.2568_2569del) in the IGHMBP2 gene, consistent with CMT2S. Other variants were identified in the NEFH (CMT2CC), DYNC1H1 (CMT2O), and MPV17 (CMT2EE) genes. Notably, a previously unreported co-occurrence of MPV17 mutation and congenital heart disease was observed in one case. Conclusions: This study expands the clinical and genetic spectrum of pediatric axonal CMT and highlights the role of early physical examination and molecular diagnostics in detecting rare variants. Identification of a novel IGHMBP2 variant and unique phenotypic associations provides new insights for future genotype–phenotype correlation studies. Full article

The adoption of predictive maintenance in public transportation has gained increasing attention in the context of Industry 4.0. However, many urban bus fleets remain in early digital transformation stages, with limited historical data and fragmented infrastructures that hinder the implementation of data-driven strategies. This study proposes a reproducible Machine Learning pipeline tailored to such data-scarce conditions, integrating domain-informed feature engineering, lightweight and interpretable models (Linear Regression, Ridge Regression, Decision Trees, KNN), SMOGN for imbalance handling, and Leave-One-Out Cross-Validation for robust evaluation. A scheduled batch retraining strategy is incorporated to adapt the model as new data becomes available. The pipeline is validated using real-world data from hybrid diesel buses, focusing on the prediction of time spent in critical soot accumulation zones of the Diesel Particulate Filter (DPF). In Zone 4, the model continued to outperform the baseline during the production test, indicating its validity for an additional operational period. In contrast, model performance in Zone 3 deteriorated over time, triggering retraining. These results confirm the pipeline’s ability to detect performance drift and support predictive maintenance decisions under evolving operational constraints. The proposed framework offers a scalable solution for digitally emerging fleets. Full article

The anode assembly, as a key component in the electrolytic aluminum process, is composed of steel claws and aluminum guide rods. The connection quality between the steel claws and guide rods directly affects the current conduction efficiency, energy consumption, and operational stability of equipment. Achieving high-quality joining between the aluminum alloy and steel has become a key process in the preparation of the anode assembly. To join the guide rods and steel claws, this work uses Cold Metal Transfer (CMT) technology to clad aluminum on the steel surface and employs machine vision to detect surface forming defects in the cladding layer. The influence of different currents on the interfacial microstructure and mechanical properties of aluminum alloy cladding on the steel surface was investigated. The results show that increasing the cladding current leads to an increase in the width of the fusion line and grain size and the formation of layered Fe₂Al₅ intermetallic compounds (IMCs) at the interface. As the current increases from 90 A to 110 A, the thickness of the Al-Fe IMC layer increases from 1.46 μm to 2.06 μm. When the current reaches 110 A, the thickness of the interfacial brittle phase is the largest, at 2 ± 0.5 μm. The interfacial region where aluminum and steel are fused has the highest hardness, and the tensile strength first increases and then decreases with the current. The highest tensile strength is 120.45 MPa at 100 A. All the fracture surfaces exhibit a brittle fracture. Full article

In recent years, deep learning (DL) has been demonstrated remarkable capabilities in hyperspectral unmixing (HU) due to its powerful feature representation ability. Convolutional neural networks (CNNs) are effective in capturing local spatial information, but limited in modeling long-range dependencies. In contrast, transformer architectures extract global contextual features via multi-head self-attention (MHSA) mechanisms. However, most existing transformer-based HU methods focus only on spatial or spectral modeling at a single scale, lacking a unified mechanism to jointly explore spatial and channel-wise dependencies. This limitation is particularly critical for multiscale contextual representation in complex scenes. To address these issues, this article proposes a novel Spatial-Channel Multiscale Transformer Network (SCMT-Net) for HU. Specifically, a compact feature projection (CFP) module is first used to extract shallow discriminative features. Then, a spatial multiscale transformer (SMT) and a channel multiscale transformer (CMT) are sequentially applied to model contextual relations across spatial dimensions and long-range dependencies among spectral channels. In addition, a multiscale multi-head self-attention (MMSA) module is designed to extract rich multiscale global contextual and channel information, enabling a balance between accuracy and efficiency. An efficient feed-forward network (E-FFN) is further introduced to enhance inter-channel information flow and fusion. Experiments conducted on three real hyperspectral datasets (Samson, Jasper and Apex) and one synthetic dataset showed that SCMT-Net consistently outperformed existing approaches in both abundance estimation and endmember extraction, demonstrating superior accuracy and robustness. Full article

Neuroactive steroids (NAS) have long been recognized for their hypnotic and anesthetic properties in both clinical and preclinical settings. While sex differences in NAS sensitivity are acknowledged, the underlying mechanisms remain poorly understood. Here, we examined sex-specific responses to an endogenous NAS epipregnanolone (EpiP) in wild-type mice using behavioral assessment of hypnosis (loss of righting reflex, LORR) and in vivo electrophysiological recordings. Specifically, local field potentials (LFPs) were recorded from the central medial thalamus (CMT) and electroencephalogram (EEG) signals were recorded from the barrel cortex. We found that EpiP-induced LORR exhibited clear sex differences, with females showing increased sensitivity. Spectral power analysis and thalamocortical (TC) and corticocortical (CC) phase synchronization further supported enhanced hypnotic susceptibility in female mice. Our findings reveal characteristic sex-dependent effects of EpiP on the synchronized electrical activity in both thalamus and cortex. These results support renewed exploration of endogenous NAS as clinically relevant anesthetic agents. Full article

This study investigated the enhancement of Cu₂MnSnS₄ (CMTS) thin films’ photocatalytic properties through potassium (K) doping for rhodamine B degradation under visible light. K-doped CMTS films synthesized using spray pyrolysis technology achieved a 98% degradation efficiency within 120 min. The physical property improvements were quantitatively validated through X-ray diffraction (XRD) analysis, which confirmed enhanced crystallinity. Scanning electron microscopy (SEM) revealed significant modifications in surface morphology as a function of potassium content, highlighting its influence on film growth dynamics. Optical characterization demonstrated a pronounced reduction in transmittance, approaching negligible values at 7.5% potassium doping, and a narrowed optical band gap of 1.41 eV, suggesting superior light absorption capabilities. Photocatalytic performance was significantly enhanced, achieving a Rhodamine B degradation efficiency of up to 98% at 7.5% doping. These enhancements collectively improved the material’s light-harvesting capabilities and charge separation efficiency, positioning K-doped CMTS as a highly effective photocatalyst compared to other ternary and quaternary materials. Full article

To study behavioral and productive factors to detect changes that may indicate and predict clinical mastitis cure, Holstein dairy cows (n = 60), in an automatic milking system (AMS) and equipped with behavioral monitoring collar, were monitored from the diagnosis of clinical mastitis (D0) until clinical cure. The parameters collected through sensors were feeding activity, milk electrical conductivity (EC), milk yield, Mastitis Detection Index (MDi), milk flow, and number of gate passages. Clinical mastitis cases (n = 22) were monitored and divided into cured cases (n = 14) and non-cured cases within 30 days (n = 8), paired with a control case group (n = 28). Cows were assessed three times per week, and cure was determined when both clinical assessment and California Mastitis Test (CMT) results were negative in three consecutive evaluations. Mixed generalized linear regression was used to assess the relationship between parameters and clinical mastitis results. Mixed generalized logistic regression was used to create a predictive model. The average clinical cure time for cows with clinical mastitis was 11 days. Feeding activity, gate passages, milk yield, milk flow, EC, and the MDi were associated with cure. The predictive model based on data from D0 showed an Area Under the Curve of 0.89 (95% CI = 0.75–1). Sensitivity and specificity were 1 (95% CI = 1–1) and 0.63 (95% CI = 0.37–0.91), respectively. The predictive model demonstrated to have good internal sensitivity and specificity, showing promising potential for predicting clinical mastitis cure within 14 days based on data on the day of clinical mastitis diagnosis. Full article

Background: Charcot-Marie-Tooth (CMT) disease is a hereditary motor and sensory neuropathy that affects foot morphology and gait patterns, potentially leading to abnormal plantar pressure distribution. This systematic review synthesizes the existing literature examining plantar pressure characteristics in CMT patients. Methods: A comprehensive search was conducted across PubMed, Scopus, and Web of Science databases. Risk of bias was assessed using the Newcastle–Ottawa Scale. Results: Six studies comprising 146 patients were included. Four studies employed dynamic baropodometry, and two used in-shoe pressure sensors to evaluate the main plantar pressure parameters. The findings were consistent across different populations and devices, with a characteristic plantar-pressure profile of marked midfoot off-loading with peripheral overload at the forefoot and rearfoot, often accompanied by a lateralized center-of-pressure path and a prolonged pressure–time exposure. These alterations reflect both structural deformities and impaired neuromuscular control. Interventional studies demonstrated a load redistribution of pressure after corrective surgery, though residual lateral overload often persists. Conclusions: Plantar pressure mapping seems to be a valuable tool to identify high-pressure zones of the foot in order to personalize orthotic treatment planning, to objectively monitor disease progression, and to evaluate therapeutic efficacy. Further longitudinal studies with standardized protocols are needed to confirm these results. Full article

Subclinical mastitis (SCM) is a stealthy but devastating challenge in the dairy industry, leading to economic losses and hindering efforts to achieve milk self-sufficiency. This study investigated the prevalence of SCM, antimicrobial resistance, and virulence profiles of Escherichia coli. A total of 174 milk samples were analyzed using the California mastitis test (CMT), somatic cell counts (SCCs), bacteriological culture, MALDI-TOF MS, and polymerase chain reaction (PCR). The findings revealed that the SCM prevalence was 68/174 (39.08%) based on CMT and SCC. Among SCM-positive samples, 60/68 (88.23%) were identified as E. coli, confirmed by MALDI-TOF MS and PCR assay. The most frequently detected serogroups were 0113 (11.6%) and 0113 (3.3%). Additionally, the genes for Stx1 and Stx2 were also detected in nine (15%) and one (1.7%), respectively. Antimicrobial susceptibility tests showed widespread resistance, with E. coli isolates demonstrating resistance to penicillin in 43 (71.6%), followed by ciprofloxacin in 42 (70%) and gentamicin in 18 (30%). A larger proportion of the E. coli strains (100%) harbored the bla_VIM gene, while 23 (38.3%), 20%, 20%, and 1.47% contained bla_KPC, bla_NMD, suli1, and msrA. Thirty (50%) isolates were considered multidrug-resistant (MDR). These findings underscore the urgent need for enhanced surveillance and antibiotic stewardship in dairy farming. The presence of MDR E. coli in SCM poses a dual threat of potential transmission to humans and treatment failures in mastitis management. This study highlights the importance of proactive control strategies to mitigate the spread of antimicrobial resistance in livestock and beyond. Full article

This paper analyzes the control strategy for urban battery-swapping stations by optimizing the charging policy based on real-time battery demand and the time required for a full charge. The energy stored in available batteries serves as an electricity buffer, allowing energy to be drawn from the grid when costs or equivalent ${\mathrm{CO}}_2$ emissions are low. An optimized charging policy is derived using dynamic programming (DP), assuming average battery demand and accounting for both the costs and emissions associated with electricity consumption. The proposed algorithm uses a prediction of the expected traffic in the area as well as the expected cost of electricity on the net. Battery tests were conducted to assess charging time variability, and traffic density measurements were collected in the city of Valencia across multiple days to provide a realistic scenario, while real-time data of the electricity cost is integrated into the control proposal. The results show that incorporating traffic and electricity price forecasts into the control algorithm can reduce electricity costs by up to 11% and decrease associated ${\mathrm{CO}}_2$ emissions by more than 26%. Full article

Background: This scoping review aims to map and summarise physical therapy interventions specifically targeting gait and balance in individuals with Charcot-Marie-Tooth disease (CMT), highlighting commonly applied strategies, methodological limitations, and clinical implications. Charcot-Marie-Tooth disease (CMT) is a hereditary neuropathy characterised by progressive motor and sensory impairment, often resulting in reduced mobility, muscle weakness, balance deficits, and fatigue. Although pharmacological options remain limited, rehabilitation is increasingly recognised as a key component of disease management. However, the scope, type, and effectiveness of rehabilitative interventions in CMT remain poorly mapped. Methods: This scoping review was conducted in accordance with the Joanna Briggs Institute (JBI) methodology and the PRISMA-ScR guidelines. Five databases (PubMed, Cochrane, PEDro, Scopus, and Web of Science) were systematically searched up to March 2024. Studies were eligible if they involved participants with CMT undergoing rehabilitation interventions aimed at improving functional outcomes. Data extraction focused on study characteristics, methods, outcome measures, and results. Results: Eleven studies met inclusion criteria, comprising case reports, cohort studies, and two randomised controlled trials. Interventions included aerobic training, strength and balance exercises, videogame-based home programmes, and multidisciplinary rehabilitation. Most studies reported improvements in walking capacity (e.g., 6MWT, 10MWT), postural balance (e.g., BBS), and lower limb strength (e.g., MRC, dynamometry). Some also showed positive changes in fatigue and quality of life, though data were limited. Methodological heterogeneity and small sample sizes limited comparability and generalisability. Conclusions: Rehabilitation appears to yield meaningful improvements in key functional domains in people with CMT. Tailored, multimodal interventions show promise, though long-term benefits remain underexplored. Future research should adopt standardised protocols and outcome measures to better define best practices and optimise patient care. Full article

Canine mammary tumors (CMTs) are the common tumors in female dogs, and approximately 50% of CMTs are malignant tumors, with abnormal regulation of non-coding RNAs being a critical factor in disease progression. Currently, research on long non-coding RNAs (lncRNAs) regulating CMT development remains limited. This study identified a novel lncRNA, aiming to explore the role of lncRNA LOC610012 in CMTs. In this study, immunofluorescence and Western blot analyses were employed to detect protein expression. LncRNA LOC610012 is downregulated in CMT tissues and cells. Stable cells of LOC610012 were constructed by the lentivirus technique. Through a variety of experimental methods, LOC610012 inhibited the proliferation, invasion, and metastasis of CMT cells in in vitro and in vivo experiments conducted using cell culture and mouse models. Mechanistically, LOC610012 regulated the expression of EP3 and GSK-3β by targeting PTGS2, resulting in excessive production of reactive oxygen species (ROS), which inhibited cell viability. Similarly, through transmission electron microscopy, mitochondrial damage caused by LOC610012 was observed in CMT cells, which was manifested as mitochondrial swelling, membrane rupture, and mitochondrial ridge disappearance. PTGS2 could partially restore the inhibition of LOC610012 on cell activity. LOC610012 acts as a tumor suppressor gene in CMTs and as a potential biomarker for the disease. Full article