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Substrate temperature effects on structure and thermoelectric transport in DC-sputtered Bi2Te3 thin films
Abstract The thermoelectric performance of Bi₂Te₃ thin films is highly sensitive to deposition temperature because substrate heating simultaneously controls microstructure, stoichiometry, and charge transport. Here, ~ 450 nm Bi₂Te₃ films were deposited on glass by single-target DC magnetron sputtering while varying the substrate temperature from room temperature to 300 °C (RT, 100 °C, 200 °C, 300 °C). FESEM reveals progressive grain coarsening and improved grain connectivity with increasing temperature, while cross-sectional imaging confirms a comparable film thickness across all samples. EDS shows a monotonic Te-loss trend at elevated substrate temperatures, indicating increasing deviation from stoichiometric Bi₂Te₃. XRD confirms crystalline Bi₂Te₃ formation for all conditions and shows systematic peak shifts/lattice-spacing trends with temperature; no distinct elemental Bi or Te peaks are detected within measurement limits. Hall and transport measurements demonstrate that electrical conductivity increases with substrate temperature, whereas the Seebeck response decreases in magnitude, reflecting the expected conductivity–thermopower trade-off as composition and carrier transport evolve. The power factor ( $$PF = S^{2} \sigma$$ ) reaches a maximum of ~ 4 µW cm⁻¹ K⁻² for films deposited at 200 °C, identifying an intermediate-temperature window that optimizes the balance between conductivity and thermopower for this DC-sputtering route. UV–Vis reflectance analysis indicates a substrate-temperature-dependent increase in the apparent optical bandgap extracted from Kubelka–Munk/Tauc-type treatment in the 300–1100 nm window, which is reported as an apparent optical metric rather than the intrinsic Bi₂Te₃ bandgap. Overall, these results establish ~ 200 °C as the most favorable substrate temperature in this study for achieving high PF Bi₂Te₃ thin films on glass and provide practical processing guidance for thermoelectric thin-film optimization.
Editorial Note: Prevalence and factors associated with early resumption of sexual intercourse among postpartum women: Systematic review and meta-analysis
The prediction of the progressive deformation mode based on active waveguide-generated acoustic emission
Abstract Buildings on the slope are inevitably affected by the stability of the slope, and cracks and uneven settlement appear in the building structure during the landslide. The prediction of landslides is very important to the judgment of building safety. To investigate the precursor detection of landslide failures based on acoustic emission (AE) signal, a model test aiming at reproducing the shear surface deformation of typical landslide mode was designed. The evolution characteristics of the AE signals were analyzed in terms of AE count, cumulative AE count, AE correlation diagrams, and time-frequency properties. The test results show that for the progressive deformation mode, the AE count experiences a low-level period, an active period and a rapid increase period, and the distribution of the correlation diagram concentrates in a relatively small scale and then gradually scatters. There are high-frequency signals during the accelerating deformation stage. In laboratory experiments, the gray catastrophe analysis model can effectively predict sliding instability states. The comprehensive use of multiple AE features helps to more accurately identify landslide deformation, providing valuable references for subsequent research.
Scientific evidence does not support oyster farming as a marine carbon dioxide removal strategy for climate mitigation
Self-care needs among international migrants and travellers: A systematic review and meta-synthesis
International travellers and migrants perform self-care to maintain their health in their destination countries. The aim of this review was to determine the self-care needs of international travellers and temporary migrants, and to assess how these needs align with existing self-care frameworks. We conducted a systematic review and meta-synthesis, searching MEDLINE, Embase, International Pharmaceutical Abstracts, PsycINFO, and CINAHL for studies on self-care among international travellers or migrants without limiting date and language. Two reviewers performed title and abstract screening after deduplication, followed by full-text screening. Two reviewers used the Center for Evidence-Based Medicine’s (CEBM) Critical Appraisal of Qualitative Studies to assess the quality of selected articles. Discrepancies were resolved by consensus with a third reviewer. Thomas and Harden’s thematic synthesis was applied to synthesise the included literature. El-Osta’s Self-Care Matrix (SCM) was used as a sensitising concept and to map conceptual similarities of descriptive themes. The protocol was registered in PROSPERO (CRD42022372693). The searches retrieved 2,394 articles, of which 17 were considered acceptable quality and included in the meta-synthesis, totalling 769 participants. Two studies were conducted among travellers and 15 among migrants. Twenty-one descriptive themes were generated, and five analytical themes were synthesised. All descriptive themes, except social engagement, were mapped to the SCM, with partial convergences occurring for self-care products and medicines, self-treatment, and treatment adherence. This meta-synthesis identified five self-care needs: self-care empowerment, mutual understanding, healthcare challenges and opportunities, preventive self-care, and self-care facilitation. Travellers’ and migrants’ reduced social capital (resource-gaining from social networks) may impact their ability to self-care, and social engagement is a form of social capital important for their self-care.
Correction to: Letter by Lei et al Regarding Article, “A Randomized Controlled Trial of Thoracentesis in Acute Heart Failure”
A numerical simulation approach for inflatable asymmetric geometries of orthotropic fabrics
Abstract Inflatable structures are lightweight, easily transported, manufactured, and deployed. These advantages make them widely applicable in civil, aerospace, and recently in wind energy applications. They are also characterized by large deviations between the un-inflated and inflated geometries, making the design process of a structure with well specified target geometry under different loading conditions very challenging. This paper presents a comprehensive framework to predict the geometry of polyvinyl chloride coated polyester fabrics and their behavior under loads. The presented framework includes detailed characterization of the material properties to be fed to commercially available software for FEA of inflatable structures. The developed model is then used to predict the ability of the structure to withstand loads without failure or wrinkling. The framework is validated against 3D scanning of the inflated geometry of four different cases which are chosen to represent different levels of complexity including weld anisotropy, geometric nonlinearity in asymmetric forms, and the effect of internal reinforcements. Comparisons between numerical predictions and experimental outcomes demonstrate the framework’s ability to capture deformation and strain behavior for complex inflatable structures. The proposed workflow provides designers with a valuable tool to design and build inflatables with a higher level of dimensional accuracy and load-bearing capacity, enabling applications beyond current limitations.
Profile of David Baker, Demis Hassabis, and John Jumper: 2024 Nobel laureates in Chemistry
The 2024 Nobel Prize in Chemistry recognized revolutionary computational success in predicting protein structures from amino acid sequences and for designing amino acid sequences that fold into desired protein structures. The ultimate accomplishment emerged principally from two labs, applying distinct approaches, culminating four decades of effort by the community of protein scientists. The lab of David Baker at the University of Washington made protein design a reality by adapting methods of classical physical chemistry. Demis Hassabis and John Jumper in the Deep Mind division of Google applied co-evolution and AI methods to enable prediction of protein models remarkably close to experimentally determined structures and prediction of vast numbers of structures of proteins not yet experimentally studied.
Investment modeling for scalable agricultural learning
With the rise of information and communication technologies, localized farmer training can be transformed into scalable strategies applicable across diverse communities, cultures, and languages. However, the economic value of these approaches and the factors shaping their returns remain underexplored. This study presents a general framework for evaluating the economic impact of scalable agricultural learning initiatives, using multilingual instructional animations and YouTube dissemination as a case study. Systems modeling was used to simulate potential returns, assess key drivers of impact, and estimate the number of farmers required for economic viability. Sensitivity analysis shows that returns are most influenced by the cost to inform an individual, adoption rates, and income gains, and to a lesser degree, technique-sharing rates and adoption costs. When existing educational content is adapted and its lifespan extended, learning initiatives can be economically viable with few targeted farmers, making the linguistic adaption into minority or rarer languages an economically viable option. The wide variation in returns across scenarios highlights the importance of tailoring models to specific contexts to obtain more precise estimates of economic impact. These findings underscore the value of adaptable and durable learning materials and suggest that future research-for-development (R4D) investments could benefit from systems modeling to identify and prioritize high-impact agricultural solutions.
Calcific Aortopathy in Response to Aging and Injury
The arterial vasculature is the second most frequently calcified structure in the human body after the skeleton. Calcification of the aorta and aortic valves occurs in most individuals in westernized societies with advancing age, with abdominal aortic calcification generally preceding ascending thoracic aortic disease. In cardiac valves and the thoracic aorta, however, calcification often arises earlier in common disease contexts characterized by metabolic, mechanical, or inflammatory injury (eg, metabolic syndrome, chronic kidney disease, irradiation). In these settings, calcification frequently involves the arterial media as a histoanatomic feature, and is associated with accelerated neurocognitive decline and increased cardiovascular mortality, reflecting a form of precocious aging. The term arteriosclerosis was coined nearly 2 centuries ago to describe the calcium-mediated hardening of the aorta and conduit arteries observed at autopsy with aging. However, much of our understanding of the causes, characterization, and consequences of aortic calcium deposition has emerged only within the past decade. Features of disease biology, including engagement of innate immunity, senescence (inflammaging), and ectopic activation of osteogenic mechanisms, are consistently revealed. In this article, we briefly review the burgeoning literature, highlighting recent advances in clinical and discovery science with translational implications. Given the current trajectory, after 2 centuries of disease recognition, the next decade of innovation promises meaningful progress toward effective medical treatments to prevent and treat the clinical consequences of calcific aortopathy.
An intrusion detection model for electric vehicle supply equipment based on multi-task learning and probability transfer mechanism
Abstract With the rapid development of new energy vehicles and Internet of Things technology, new energy vehicle users have an increasing demand for electric vehicle supply equipment (EVSE). However, a large number of EVSE are currently vulnerable to remote hacking due to the lack of effective security defense mechanisms. This not only leaks sensitive information of users, but also causes large-scale fluctuations in power grid energy. In addition, current research methods for intrusion detection in EVSE suffer from problems such as high false alarm rate, long detection time, and low detection accuracy. Therefore, in order to build a more effective EVSE intrusion detection method, this paper combines the multi-task learning architecture and proposes a deep learning detection model EVSEMTLIDS to conduct an in-depth analysis of the malicious intrusion behavior of EVSE. In order to shorten the intrusion detection time of this model for multiple tasks, EVSEMTLIDS integrates a multi-task learning architecture. At the same time, we propose a probability transfer mechanism to improve the prediction performance between multiple tasks. Experimental results show that compared with the baseline model, the proposed model improves the detection accuracy by up to 27.29% and shortens the detection time by 43.24%.
Correction: Dietary adherence among persons with type 2 diabetes: A concurrent mixed methods study
Clinical Spectrum of Children With Parvovirus B19–Associated Acute Myocarditis
BACKGROUND: Parvovirus B19 is a DNA virus transmitted via respiratory droplets, commonly causing erythema infectiosum in children but also implicated in acute myocarditis. In 2024, an outbreak of parvovirus B19 infections was reported across Europe and the United States. Despite growing awareness, data on the clinical features and outcomes of children with parvovirus B19–associated acute myocarditis remain limited. METHODS: This multicenter retrospective observational study reviewed medical records of pediatric patients (<18 years of age) admitted with acute myocarditis to 11 Italian tertiary pediatric cardiac centers between January 1, 2022, and October 31, 2024. Of 217 cases, 66 had confirmed parvovirus B19 DNA in plasma (PVB19 + ), whereas 82 with negative parvovirus B19 testing served as a comparator group (PVB19 − ). Population-based incidence trends of pediatric myocarditis were also evaluated in the Lombardy region from 2004 through 2024. RESULTS: Among PVB19 + acute myocarditis cases, 58 of 66 (87.9%) were admitted in 2024. The median age was 32 months, with 51 of 66 (77.2%) ≤7 years of age, and 36 of 66 (54.5%) were boys. Median plasma viral load was 34 411 copies/mL, whereas only 30 of 56 (53.6%) had immunoglobulin M (IgM) positivity. Among 26 of 66 (39.4%) with available histology, 23 (88.4%) had lymphocytic myocarditis, and parvovirus B19 DNA was identified in 84.0% of myocardial specimens. Among 25 of 65 (38.4%) who underwent genetic testing, none had pathogenic or likely pathogenic variants. Overall, 13 of 66 (19.7%) died, underwent heart transplantation, or received a durable left ventricular assist device (in total, there were 6 deaths, 5 durable left ventricular assist devices, and 5 transplantations) compared with 1 of 82 (1.2%) among PVB19 − acute myocarditis (one patient who received a durable left ventricular assist device and later underwent transplantation; P <0.001). A marked increase in regional and institutional myocarditis incidence in pediatric acute myocarditis was observed in 2024, predominantly in children ≤7 years of age, driven by PVB19 + cases. CONCLUSIONS: During the 2024 parvovirus B19 outbreak, pediatric PVB19 + acute myocarditis cases surged in Italy and were associated with severe outcomes. A high index of suspicion is required for diagnosis, and early virological testing is essential to guide management and potentially improve outcomes.
Development of ranking alternatives of micro-cup production from directionally rolled copper rods using the Intuitionistic Fuzzy MARCOS method
Multi-axial strain mapping to characterise structure and material properties of the human hip capsule
The biological composition and spatial arrangement of the tissue’s constituents are directly related to its condition and function. Conventional inspection techniques such as optical microscopy and exogenous staining have limited ability to capture the heterogeneity and anisotropy of biological tissues. Here, we apply a commercial 2D digital image correlation (DIC) system integrated with a biaxial testing machine to quantitatively characterise the fibrous structure of biological materials. The approach applies a homogeneous biaxial stress field across the tissue and uses optical measurement of the resulting strain field to identify load-bearing collagen architecture. Under this loading condition, collagen bundles deform less than the surrounding matrix, so low-strain bands and their principal directions indicate ligament locations and orientations. The method was validated using an artificial anisotropic material and ex vivo skin, and was then applied to the human hip joint capsule to demonstrate its ability to characterise complex collagen networks. Testing of nine excised hip capsule specimens revealed the collagenous network and the confluence between its fibrous structures. The locations and orientations of seven ligamentous regions were detected and matched to previously published anatomical descriptions. Using strain as a quantitative measure of ligament anatomy further enabled extraction of local mechanical properties, including the tangent modulus, across the entire tissue in a single test. By combining a biaxial testing machine with a commercial 2D DIC system, this study demonstrates a practical and scalable approach for quantifying tissue structure-function relationships across whole tissues.
CXCR6 <sup>+</sup> T Cells Drive Immune Checkpoint Inhibitor Myocarditis
BACKGROUND: Myocarditis is a severe complication of immune checkpoint inhibitors (ICIs). The major risk factor for ICI myocarditis is the use of combination ICI treatment, especially when relatlimab, a novel anti–LAG-3 (lymphocyte-activation gene 3) antibody, is combined with anti–PD-1 (programmed cell death protein 1) therapy. Although pathogenic T cells are necessary for ICI myocarditis, the specific signaling and T-cell populations that drive cardiac infiltration have not been fully elucidated, especially in setting of anti–LAG-3/PD-1 treatment. METHODS: We used VigiBase, an international pharmacovigilance database, to assess the risk of myocarditis with anti–LAG-3 compared with other ICI treatment regimens. We identified a mouse model of LAG-3/PD-1–associated ICI myocarditis through genetic deletion of immune checkpoints LAG-3 and PD-1 ( Lag3 -/ - , Pdcd1 -/ - mice) and performed rigorous cardiac phenotyping using histology, flow cytometry, electrocardiography, single-cell RNA sequencing, and antibody-induced cellular depletion. RESULTS: We found an increased risk of myocarditis with anti–LAG-3 combination treatment clinically, confirming early clinical trial data. Lag3 -/ - , Pdcd1 -/ - mice were found to develop severe cardiac inflammation by histology with increased cardiac macrophages and clonal T cells, which was associated with the development of spontaneous arrhythmias leading to premature death by 6 to 8 weeks. We identified CXCR6 (C-X-C motif chemokine receptor 6) as a key marker of activated cardiac T cells in this model, along with analogous signals in other preclinical models and patient data. CXCR6 marked a heterogenous group of cardiac T cells, including distinct clusters of Gzmk , Gzmb , Cd4 , and actively dividing T cells. CXCL16 (C-X-C motif chemokine ligand 16), the sole known ligand for CXCR6, was similarly upregulated in the cardiac macrophage population. Treatment with anti-CXCR6 antibody prevented premature lethality, attenuated arrhythmias, and reduced the histological severity of myocarditis, demonstrating that CXCR6 + T cells are necessary for disease pathogenesis. CONCLUSIONS: Our findings suggest that ICI myocarditis is driven by an expansion of CXCR6 + T cells and identifies CXCR6 as a putative therapeutic target for this highly morbid condition.
Effects of compression legwear on knee biomechanics and inter-joint coordination during depth jumps: a randomized cross-over study
Task–technology fit and digital textbook usage outcomes: The mediating role of positive emotion within an S–O–R framework
Digital textbooks are now an integral component of EFL learning environments, yet the underlying psychological mechanisms that influence digital textbook usage outcomes are still clearly unknown. This study constructs a model using the Stimulus–Organism–Response (S–O–R) theory to show how task-technology fit (TTF), which is an external stimulus variable, affects the outcomes of digital textbook usage (DTUO) by influencing the mediating role of positive emotion (POE). In this model, DTUO is defined as a second-order construct consisting of learning effectiveness (LEE) and continuance intention (COI). Using cross-sectional questionnaire data from 259 undergraduates in China, the paper employed structural equation modeling (SEM) for empirical investigation. Findings indicated that TTF positively predicted both POE and DTUO. Furthermore, POE was found to be positively associated with DTUO and played a significant mediating role in the relationship between TTF and DTUO. These findings confirm that the S-O-R theory is applicable in digital textbook learning and underscore the significance of a task-technology fit and emotional engagement. Theoretical and empirical contributions are offered for educational content developers and policymakers.