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Evidence of air-induced surface transformation of atomic step-engineered sapphire in relation to epitaxial growth of 2D semiconductors
A dynamic simulation approach to optimize thrust regulation in electric pump-fed rocket engines
Spin Hall and Edelstein effects in chiral non-collinear altermagnets
Abstract Altermagnets are a newly discovered class of magnetic phases that combine the spin polarization behavior of ferromagnetic band structures with the vanishing net magnetization characteristic of antiferromagnets. Initially proposed for collinear magnets, the concept has since been extended to include certain non-collinear structures. A recent development in Landau theory for collinear altermagnets incorporates spin-space symmetries, providing a robust framework for identifying this class of materials. Here, we expand on that theory to identify altermagnetic multipolar order parameters in non-collinear chiral materials. We demonstrate that the interplay between non-collinear altermagnetism and chirality allows for spatially odd multipole components, leading to non-trivial spin textures on Fermi surfaces and unexpected transport phenomena, even in the absence of SOC. This makes such chiral altermagnets fundamentally different from the well-known SOC-driven Rashba-Edelstein and spin Hall effects used in 2D spintronics. Choosing the chiral topological magnetic material Mn 3 IrSi as a case study, we apply toy models and first-principles calculations to predict experimental signatures, such as large spin Hall and Edelstein effects, that have not been previously observed in altermagnets. These findings pave the way for a new realm of spintronics applications based on the spin-transport properties of chiral altermagnets.
Effects of resveratrol on inflammatory and hormonal disorders induced by Helicobacter pylori OMVs in pregnant mice
Mechanical control of cell fate decisions in the skin epidermis
Reflectance spectroscopy reveals mineralogy and preservation of ceramics from the Bidong Shipwreck
Puzzle-like molecular assembly of non-flammable solid-state polymer electrolytes for safe and high-voltage lithium metal batteries
White matter neural substrates in alcohol dependence with genetic risk and their role in pathological reward process
Abstract Studies have revealed significant evidence of white matter (WM) microstructural and network connectome abnormalities in alcohol use disorder (AUD). However, the neuroimaging characteristics of alcohol dependence (AD) patients with a family history of AUD and the role of these changes in pathological craving remain unclear. Investigating the heritability of AUD is crucial for identifying genetic predispositions and informing targeted prevention strategies. The study recruited 51 patients for AD, 21 patients with a family history positive (FHP), 30 patients with a family history negative (FHN), and 25 healthy controls (HC). We compared fractional anisotropy (FA) and mean diffusivity (MD) of striatal circuits and topological properties of the reward system between the three groups. Then, covariates of alcohol use characteristics (duration and severity of AD) were controlled between FHP and FHN. We found abnormal topological properties of hippocampus in AD with FHP compared to HC. After controlling for covariates, there were still disruptions of topology organization in FHP compared to FHN, such as lower nodal betweenness, nodal degree and higher shortest path of right hippocampus. The nodal topological properties of right hippocampus were significantly correlated with self-reported craving in AD. Our findings provide robust evidence for WM neural abnormalities in AD with high genetic risk. We also found the disrupted topological properties of the right hippocampus associated with craving level.
Physiologic Homeostasis in a Living Human after Pig Kidney Xenotransplantation
Research on topology optimization and case application of power tunnel structure based on variable density method
Structural basis of antiphage defence by an ATPase-associated reverse transcriptase
HDLCA: hunger driven lion clustering algorithm, a novel energy efficient and scalable clustering approach for underwater wireless sensor nodes
Abstract Underwater Wireless Sensor Networks (UWSNs), a subset of traditional WSNs, face critical challenges due to their reliance on non-rechargeable, irreplaceable power sources, making energy-efficient communication essential. This paper proposes a novel meta-heuristic clustering-based routing protocol inspired by the hunger-driven hunting and territorial behaviour of lions, termed the Hunger Driven Lion Clustering Algorithm (HDLCA). Unlike other approaches, HDLCA directly maps lion behaviour to sensor node dynamics, enabling adaptive cluster head selection and efficient sub-cluster formation based on energy levels and node proximity. The algorithm is evaluated using key performance metrics including residual energy, dead node count per round, first and last node death, and throughput. Simulation results show that HDLCA optimizes these metrics effectively compared to EERBLC, EECMR, LEACH, and K-Means Clustering. Specifically, HDLCA achieves improvements in network longevity by 23.3%, 14.37%, 34.04%, and 59.91% when compared to EECMR, EERBLC, K-Means Clustering, and LEACH respectively. Additionally, HDLCA exhibits strong scalability, noise resilience, and consistent throughput, making it a robust and efficient solution for underwater deployments.
High expression of Rex-orf-I and HBZ mRNAs and bronchiectasis in lung of HTLV-1A/C infected macaques
Abstract HTLV-1 type-A rarely causes lung disease in humans, whereas HTLV-1 type-C is more frequently associated with respiratory failure and premature death. We investigated the genetic basis of HTLV-1C morbidity by constructing a chimeric HTLV-1A/C oI-L encompassing the highly divergent type C orf-I. We demonstrate that systemic infectivity of HTLV-1A and HTLV-1A/C oI-L is equivalent in macaques, but viral expression in lungs is significantly higher in HTLV-1A/C oI-L infection. In addition, bronchoalveolar-lavage immune cell dynamics differs greatly with neutrophils and monocytes producing TNF-α in HTLV-1A/C oI-L , but producing IL-10 in HTLV-1A infection. Animals infected with HTLV-1A/C oI-L develops bronchiectasis at 10 months from infection, but at the same timepoint those infected with HTLV-1A do not. HTLV-1A/C oI-L expressed a 16 kDa fusion protein (p16C) via a doubly spliced, Rex-orf-IC, mRNA able to shield T-cells from efferocytosis, a monocyte function that mitigates inflammation via clearance of apoptotic cells. The Rex-orf-IC mRNA is expressed as more frequent in the lung of HTLV-1A/C oI-L than HTLV-1A infected animals. Since defective efferocytosis is associated with lung obstructive pathologies, the data raise the hypothesis that p16C may contribute to the lung morbidity observed in HTLV-1C infection.
Leveraging hybrid deep learning with starfish optimization algorithm based secure mechanism for intelligent edge computing in smart cities environment
Parallel neuronal structural plasticity with memory trace formation in the orbitofrontal cortex
Collaborative optimization strategy for urban highways and roads based on electronic toll collection lane regulation
Effects of individual variation and seasonal vaccination on disease risks
Abstract Estimates of the risk of a large outbreak resulting from pathogen introduction into a population are valuable for planning interventions. Two key factors affecting outbreak risks are variation in transmission between individuals (e.g., superspreading individuals) and change over time (e.g., through seasonality or changing population immunity due to vaccination). Here, we develop an outbreak risk estimation framework that accounts for both features simultaneously. To demonstrate the real-world application of our framework, we consider the design of annual COVID-19 booster vaccination campaigns, using a multi-scale approach incorporating an individual-level model of vaccine-induced antibody dynamics. Near the start of annual vaccine distribution, when population immunity is low, a high outbreak risk is possible; this can be mitigated by distributing vaccines over a longer period. We show that longer distribution periods are particularly beneficial if vaccine coverage and/or effectiveness is high, and if seasonality in transmission is limited.