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Religiosity spirituality and nonreligious spiritual practices linked to anxiety and depressive symptoms
Continuum modeling of radiation-induced degradation in superconductors
Realizing the promise of nuclear fusion requires confining plasma at millions of degrees, a feat achievable only through high-field superconducting magnets. However, the fusion reaction itself generates a relentless flux of high-energy neutrons that degrades these critical and prohibitively expensive coils, limiting the operational lifetime of the reactor and compromising its economic viability. While radiation damage is well-documented experimentally, a predictive theoretical framework that links microscale defects to macroscopic magnetic failure has remained elusive. Here, we bridge this gap with a homogenized continuum damage model based on Ginzburg–Landau theory. By treating radiation-induced defects as “quantized” normal-phase inclusions, we map the degradation of the superconducting order parameter to an equivalent homogenization problem. This approach yields closed-form analytical expressions for the critical current as a function of neutron fluence, magnetic field, and temperature. We calibrate and validate the model against experimental data in the literature on rare-earth barium copper oxide (REBCO) tapes, demonstrating that the complex evolution of superconducting properties, including the counterintuitive “peak effect”, can be captured by a few effective material parameters that need to be calibrated just once. This work provides a design tool for engineering radiation-tolerant magnets, a critical step toward sustainable fusion energy.
Topographic modulation of soil functional indicators in shaded coffee agroforestry systems: a multivariate and network-based approach
Dual-frequency Doppler-free crossover resonance with suppressed magnetic-field sensitivity for compact optical clocks
We report the observation and characterization of a high-contrast dual-frequency Doppler-free ground-state crossover resonance in the D1 line of 87Rb. The crossover appears at the two-photon detuning δ exceeding the natural linewidth of the excited state and is formed by the hyperfine optical pumping. We show that the previously proposed resonance at zero two-photon detuning is sensitive to magnetic-field fluctuations due to residual ellipticity of the optical fields that produces the profile asymmetry and frequency shifts, while the crossover resonance is largely immune to this effect. Our theoretical analysis attributes the observed sensitivity to the dispersive contribution of ground-state coherences to absorption. Stability measurements under magnetic-field fluctuations demonstrate that using the crossover resonance at large δ provides more than an order-of-magnitude improvement, making it a promising reference for frequency stabilization in compact, field-deployable optical standards.
Immunophenotypic skewing of B cells toward IgD⁻CD27⁻IgG⁺ subtype and metabolic attenuation in colorectal cancer
Abstract Colorectal cancer (CRC) is the third most prevalent cancer and understanding its tumor microenvironment (TME) is crucial for the development of innovative therapies. Despite the presence of B cells in CRC infiltrate, their clinical significance is poorly understood. In this study, we observed an enrichment of double-negative (DN) B cells, a subset lacking surface IgD and CD27, in CRC biopsies. Typically underrepresented in physiological conditions, DN B cells expand in certain chronic infections, autoimmune diseases, and cancers. Within this subpopulation, low CD21 expression—a phenotypic hallmark of exhaustion—was observed. Consistently, DN B cells displayed low metabolic activity. Accordingly, total B cells infiltrating CRC tissues showed a diminished capacity to differentiate into antibody-secreting cells (ASCs) upon stimulation. In the murine setting, CRC organoids decreased the frequency of ASCs in co-cultured B cells and induced metabolic dysfunction, marked by altered glucose and fatty acid uptake and dysregulated expression of key metabolic proteins. Moreover, B cells displayed reduced glycolysis and mitochondrial respiration, despite increased mitochondrial dependence. This study provides evidence for DN B cell accumulation within CRC infiltrate and metabolic reprogramming of B cells, suggesting that targeting B cell metabolism may represent a promising strategy to potentiate anti-tumor immune responses.
Femtosecond ultrafast dynamics simulations of typical semiconductor materials under swift heavy ion irradiation
Swift heavy ion (SHI) irradiation has long been used to evaluate the performance of radiation-hard semiconductor devices. However, the in-depth insight into its microscopic processes and damage evolution remains unclear. In this work, the ultrafast microscopic processes within femtosecond timescales under SHI irradiation of four typical semiconductor materials (Si, 4H-SiC, GaN, β-Ga2O3) are investigated by the coupling ab initio and two-temperature model (TTM) methods. The ab initio method is utilized to systematically calculate the temperature-dependent electronic thermodynamic parameters of four semiconductor materials and then incorporated into the TTM to reveal the significance of the intrinsic thermodynamic properties on thermal spike evolution under SHI irradiation. The results demonstrate that stronger electron–phonon coupling accelerates femtosecond thermal processes and promotes more efficient energy transfer from the electronic to lattice subsystems. Lower thermal conductivity suppresses energy diffusion within subsystems, leading to more pronounced energy spikes. These energy spikes induced by the SHI produce instantaneous molten zones where radius variations are correlated with the material melting threshold energy. Under 430 MeV Kr ion irradiation, instantaneous molten zones with radii of 4.64 and 5.70 nm are formed within femtoseconds in GaN and β-Ga2O3, respectively, while no melting occurs in Si or SiC. This work provides essential data for understanding the behavior and microscopic damage processes of semiconductor materials under extreme irradiation conditions.
Exploring the optimal follow-up time for resectable colorectal cancer patients: a multicenter, five-year longitudinal cohort study
A triple-axis hybrid-linearity selective gradient field system design in magnetic hyperthermia: Providing a spheroidal shaped field-free region
Magnetic nanoparticles (MNPs) have emerged as transformative agents in precision oncology due to their tumor-targeting specificity, non-invasive nature, and biocompatibility, particularly in magnetic hyperthermia (MH). Conventional targeted MH systems rely on single-axis gradient selective fields to generate irregular field-free regions (FFRs). This leads to anisotropic heating and compromised targeting accuracy. To address these limitations, this study introduces a triple-axis hybrid-linearity gradient field system that applies a single-axis nonlinear adjustment field to a double-axis linear basement field. This configuration achieves approximate-isotropic gradient distribution, producing spheroidal FFRs with enhanced spatial symmetry. Finite-element simulations demonstrate an obvious reduction in heating zone volume compared to conventional single- or dual-axis systems, significantly reducing off-target heating effects. Experiment using Fe3O4 nanoparticles confirms selective MH efficacy, with FFR temperatures rising by 15.4 °C while unselected regions remain unheated (temperature rise less than 2 °C). An adaptive pre-mapping protocol further optimizes targeting precision, reducing FFR positioning errors to below 20% within a 50 mm workspace. This resolves anisotropic expansion issues inherent to purely linear systems. Despite requiring higher energy input (25 A DC current) than traditional setups, the system enables spatially confined energy deposition with reduced collateral tissue damage. These advancements highlight its clinical potential for tumor-specific therapy and controlled drug delivery. Future efforts should focus on enhancing power efficiency through coil geometry optimization. Integrating real-time field monitoring could also facilitate the real-time selective heating accuracy and operational stability. By proposing a possible system design, this work establishes a novel hybrid-linear modeling and design method for a precise magnetic hyperthermia system.
Functional connectivity in infants’ visual cortex and its links to motion processing and autism
Abstract In a previously published study, we found atypical visual cortical laterality patterns during global motion perception in 5-month-old infants who showed high levels of autistic symptoms in toddlerhood. Here, using data from a separate experiment within the same recording session, we examined whether these results could reflect altered visual cortical functional connectivity in theta, alpha, and gamma rhythms. We assessed this in a sample of 5-month- old infants ( n = 59; 39 elevated familial likelihood of autism) by means of electroencephalography (EEG) when they were watching videos showing social and non-social scenes. Gamma connectivity between midline and far-lateral visual cortex when viewing social scenes was linked to both later autism symptoms and global motion visual cortical laterality we reported in the previous study. This may indicate a shared integrative mechanism underlying social perception and global motion processing. Further, we found that higher midline-to-lateral theta connectivity in the visual cortex when perceiving non-social scenes in infancy was strongly associated with having more autistic symptoms at follow up, but uncorrelated with concurrent motion perception. Our study points to atypical functional connectivity in the visual cortex as a potential early marker of autistic symptoms and highlights a probable link between motion processing and social perception.
A microscopic understanding of the magnetism in Fe3GeTe2 with mono-atomic vacancies
Fe3GeTe2 (FGT) is a promising two-dimensional van der Waals magnet known for its metallic conductivity and relatively high Curie temperature (Tc). Structural defects, particularly mono-atomic vacancies, are inevitably introduced in FGT during material fabrication and have been observed to significantly modulate Tc and coercivity. However, the underlying mechanisms of these modifications require systematic exploration. In this work, by first-principles calculations, we investigate the effect of various mono-atomic vacancies on the magnetic properties of FGT. We find that magnetic anisotropy is reduced by all kinds of vacancies by a local density approximation method, and the main reason is the diminished contributions from Te atoms, which possess strong spin–orbital coupling. Furthermore, by examining the vacancy-induced changes in the magnetic exchange coupling (MEC), a deeper understanding of magnetism in FGT can be achieved. For instance, the enhanced MEC among the Fe1up–Fe1up pair by Te vacancies confirms the competition between superexchange coupling and Ruderman–Kittel–Kasuya–Yosida interactions. These insights are instrumental for guiding future applications of FGT.
Low power reprogrammable DNA basecaller with an efficient HMM accelerator for real time nanopore sequencing
Analyzing sustainable cotton production in Türkiye through the water energy carbon nexus framework
Human values and physical activity before and during COVID-19 restrictions in Hungary
Abstract Physical inactivity is a major public health challenge in Hungary. Drawing on Schwartz’s Theory of Basic Human Values, we exploit a natural experiment created by temporary population-wide restrictions to examine how value orientations relate to physical activity across contrasting contexts. In a nationally representative survey of 1,031 adults, respondents reported frequency of structured exercise training (SET) and light daily physical activity (LDPA) for the period before the restrictions and during them. Generalized ordered logistic models linked activity categories to self-transcendence, conservation, openness to change, and self-enhancement, controlling for sociodemographic and health factors. Self-transcendence predicted higher participation in both SET and LDPA under usual conditions; during restrictions, its association with SET attenuated, whereas the link with LDPA remained robust. Conservation values consistently predicted lower SET, with avoidance intensifying under constraints; associations with LDPA were weaker. Openness to change and self-enhancement showed no independent effects after adjustment. Age, gender, education, self-rated health, BMI, smoking and alcohol use were associated with activity. Findings indicate that values shape activity differently depending on context: self-transcendence is associated with greater persistence in daily activity, whereas conservation corresponds to declines in structured exercise. Aligning interventions with motivational profiles may improve adherence when opportunities to be active are disrupted.
Synthesis of the porous Co–N-doped carbon catalysts as a durable cathode for zinc–air battery
Abstract Due to the exceptional ORR catalytic activity and stability, cobalt and nitrogen-doped carbon (Co–N–C) catalysts are regarded as highly promising candidates for cathode catalysts in zinc–air batteries. However, it remains a challenge to expose more stable and more efficient active sites. Therefore, this work focuses on the design and preparation of Co–N–C catalysts with a robust and porous structure. The results revealed that the robust and porous structure could be easily achieved by the template (SiO 2 )-assisted hydrothermal method. Moreover, the Co-900-50 catalyst has the highest half-wave potential, and the Co-900-100 catalyst has the highest limiting current density. Both individuals are chosen for further examination regarding their potential use in zinc–air batteries. The battery with Co-900-100 catalyst demonstrated exceptional stability across the current densities (5–20 mA cm − 2 ). Specifically, the voltage rose by 0.04 V following a 100 h discharge at a rate of 5 mA cm − 2 , while the discharge voltage remained nearly constant at 1.24 V throughout 300 charge/discharge cycles at 5 mA cm − 2 .
Development of a high-speed planetary gearbox for an electric vehicle
Threshold-based artefact correction methods influence heart rate variability measurements in individuals with type 2 diabetes mellitus
Impact of sedentary behavior and physical activity on stroke risk in a cohort of patients with silent brain infarction
Linking lipid profile alterations to antibiotic tolerance and natural product synergy in drug-resistant Mycobacterium tuberculosis clinical isolates
Abstract Despite global control efforts, tuberculosis remains the leading infectious cause of death, with rising incidence, pediatric cases, and drug-resistant strains posing major public health challenges. Mycobacteria, including Mycobacterium tuberculosis , possess a lipid-rich, dual-membrane cell envelope that contributes to their impermeability, drug resistance, and unique pathogenic mechanisms. Some lipids play key roles in modulating host immune responses, enabling survival within macrophages, and promoting granuloma formation. Since it is known that lipid remodeling of the cell envelope is correlated with the antibiotics tolerance in mycobacteria we used liquid chromatography coupled to mass spectrometry to analyze the lipid profiles of M. tuberculosis clinical isolates with diverse drug-resistance characteristics in order to investigate if there is any link between Mtb lipids composition, its drugs susceptibility and the antimycobacterial activity of natural small molecules used in combination with first line antibiotics. The results showed that among cross combinations of antibiotics and natural products (piperine and thymoquinone) the potentiation of antimycobacterial activity was obtained in all strains only for rifampicin. Drug-resistant isolates presented the shift in glycerophospholipids building the inner membrane towards molecules with shorter acyl chains, but the decreased membrane hydrophobic thickness was compensated in some strains by increased membrane rigidity. The pXDR/XDR isolates accumulated mycobactins loaded iron and showed dysregulation in the production of phthiocerol/phthiodiolone dimycocerosates and triacylglycerols.
Blasting ore size detection based on efficient dehazing network and multi-dimensional feature fusion
Abstract Ore particle size distribution is an important metric for evaluating blasting outcomes and affects the energy consumption of ore crushing equipment. Faced with dense accumulation of ore, nonuniform size distributions, dust occlusion, and target loss due to motion, using computer vision methods, we propose a blasting ore size detection method based on efficient dehazing network and multi-dimensional feature fusion, which is an improvement to YOLOv8. Firstly, we constructs an efficient defogging backbone network that combines feature attention and composite scalable backbone so that the model can efficiently extract the features of ore images and enhance the robustness of the model to dust interference in the ore crushing process. Secondly, we introduces a new feature fusion network that combines the convolution model and the Vmamba sequence model as well as cross-layer fusion of multi-scale features so that the model can effectively adapt to the dramatic scale change of blasting ore, capture fine ore and large-size ore, avoid ore omission, and improve the accuracy of particle size statistics. Finally, the multi-dimensional feature fusion ability of Dynamic Head was introduced to optimize the target detection head, and the feature fusion was further optimized so that the feature tensor obtained from the ore image was adapted to the detection and positioning task of ore, and the discrimination ability of the model for ore was improved. Experiments were conducted on a manually labeled jaw fracture ore dataset. Compared to the YOLOv8n algorithm, the average precision ( $$\overline{P}$$ ) for detecting eight size categories of ore increased by 7%. On datasets containing interference such as smoke, dust, and wet conditions, the mean average precision at the IoU threshold of 0.5 (mAP50) improved by 7.6%. For fine ores below D5 (72 mm), the detection precision ( $$\overline{P}$$ ) increased by 18.8%, while the recall rate ( $$\overline{R}$$ ) rose by 13.8%. On the total one-class dataset, the recall rate ( $$\overline{R}$$ ) and mAP50 reached 84% and 88.1%, respectively.