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Robust biodegradable synapse with sub-biological energy and extended memory for intelligent reflexive system
Improved deformation reconstruction of composite material structures based on optical fiber sensing
Integrating machine learning algorithms and remote sensing for High-Resolution mapping of soil crusting in agricultural lands
Highly efficient current-induced domain wall motion in a room temperature van der Waals magnet
Abstract Two-dimensional van der Waals magnets are highly promising for next-generation spintronics. The ferromagnetic material Fe 3 GaTe 2 is especially interesting due to its high Curie temperature. Here we demonstrate highly efficient current-induced domain wall motion in Fe 3 GaTe 2 racetracks via spin-transfer torque that gives rise to the highest domain wall velocity yet reported for any van der Waals magnet. The spin polarization of the conduction electrons was measured via superconducting point-contact measurements revealing that 100% of their spin angular momentum is transferred to the domain walls. The very low threshold current density plus the very high mobility of the domain walls is attributed to the structural perfection of the two-dimensional magnet. We further demonstrate an electrically readable memristive racetrack device with more than four data bits, via precise domain wall positioning. Our work demonstrates that van der Waals magnets are compelling for emerging spintronic applications from room temperature to cryogenic temperatures.
Insecticidal efficiency of selected essential oils against stored pests Sitophilus orzyae and Callosobruchus maculatus by using GC–MS analysis
Fibrinogen alpha and beta chains as non-invasive predictors of hepatocellular carcinoma progression
Hierarchical folding-upon-binding of an intrinsically disordered protein
Abstract Intrinsically disordered proteins (IDPs) often undergo folding-upon-binding to their partners via short linear motifs, typically 5-15 amino acids in length. However, a significant proportion of IDPs do not adhere to this paradigm but fold upon binding through extended regions comprising multiple molecular recognition elements. For these IDPs, the binding mechanisms and the structural characteristics of their folding intermediates remain poorly understood. Here we unveil hierarchical folding of an IDP as it binds to its partner, exemplified by the disordered signaling effector POSH and the small GTPase Rac1. By combining nuclear magnetic resonance (NMR) spectroscopy and X-ray crystallography, we resolve at atomic resolution how POSH transitions from a fully disordered state to a highly ordered, Rac1-bound conformation through two structurally distinct folding intermediates. The folding of each element is contingent on the successful structuring of the preceding element, highlighting a hierarchical folding-upon-binding mechanism. Our work highlights the potential of targeting folding intermediates and conformational transitions to unlock therapeutic opportunities for IDPs.
From ‘Me’ to ‘We’: the psychology behind future collective action for wetland sustainability
Economic and reliability assessment of intermediate charging ports for EV stations
Abstract The widespread adoption of electric vehicles (EVs) poses significant challenges to distribution system operations. When electric vehicle charging stations (EVCS) are installed without proper planning, they can negatively impact voltage stability and reliability in distribution systems leading to reduced customer satisfaction. To enhance distribution system charging station reliability, a novel 36-port design has been developed, incorporating identical and non-identical port configurations. This system operates within a 50–350 kW distribution network. The research employs failure rate analysis based on MILHDBK217F standards, while port probability functions for failure rate and reliability are assessed according to MILHBK-338B guidelines. The study introduces an evaluation process to determine charging station success rates based on individual port failure rates. The failure rate analysis for the charging station with 36-port configuration utilizes binomial distribution method. Additionally, the research includes a price assessment framework for the 36-port system, considering both failure rates and individual port maintenance success rates. The study evaluates distribution station voltage stability by examining individual port failure rates and the overall reliability of the 36-port configuration. Results demonstrate that the proposed design achieves reduced failure rates and maintenance costs while maintaining superior port arrangement reliability and voltage stability.
Non-invasive ultrasonic neuromodulation of the human nucleus accumbens impacts reward sensitivity
Abstract Precisely neuromodulating deep brain regions could bring transformative advancements in both neuroscience and treatment. We demonstrate that non-invasive transcranial ultrasound stimulation (TUS) can selectively modulate deep brain activity and affect learning and decision making, comparable to deep brain stimulation (DBS). We tested whether TUS could causally influence neural and behavioural responses by targeting the nucleus accumbens (NAcc) using a reinforcement learning task. Twenty-six healthy adults completed a within-subject TUS–fMRI experiment with three conditions: TUS to the NAcc, dorsal anterior cingulate cortex (dACC), or Sham. After TUS, participants performed a probabilistic learning task during fMRI. TUS-NAcc altered BOLD responses to reward expectation in the NAcc and surrounding areas. It also affected reward-related behaviours, including win–stay strategy use, learning rate following rewards, learning curves, and repetition rates of rewarded choices. DBS-NAcc perturbed the same features, confirming target engagement. These findings establish TUS as a viable approach for non-invasive deep-brain neuromodulation.
Excess 40Ar retention in metamorphosed amphibole complicates 40Ar/39Ar geochronological interpretation of diabase
Regularized ensemble Kalman inversion for robust and efficient gravity data modeling to identify mineral and ore deposits
Abstract Modeling mineral and ore bodies from gravity anomalies remains challenging in geophysical exploration due to the ill-posed and non-unique nature of the inverse problem, particularly under conditions of noisy or sparse data. Established inversion methods, including local optimization and metaheuristic algorithms, often require extensive parameter tuning and may yield unstable or poorly constrained solutions. This study proposes a regularized ensemble Kalman inversion (EKI) framework enhanced by Tikhonov regularization to improve numerical stability and mitigate sensitivity to ensemble degeneracy, thereby enabling efficient uncertainty quantification through ensemble statistics. Controlled numerical experiments show that the ensemble size is larger than $$\:100$$ with moderate regularization, we can achieve an optimal balance between convergence stability and model resolution. Benchmarking against established metaheuristic algorithms (PSO, VFSA, and BA) suggests superior computational efficiency and stable convergence. Synthetic and real gravity data inversion (chromite, Pb-Zn, sulphide, and Cu-Au deposits) suggests that the regularized EKI yields stable, geologically consistent results with prior interpretations and drilling data. These results highlight the regularized EKI framework as a robust and efficient tool for mitigating mining risks and supporting strategic decision-making in mineral exploration.