In-material physical computing based on reconfigurable microwire arrays via halide-ion segregation.

Conventional computer systems based on the Von Neumann architecture rely on silicon transistors with binary states for information representation and processing. However, exploiting emerging materials' intrinsic physical properties and dynamic behaviors offers a promising pathway for developing next-generation brain-inspired neuromorphic hardware. Here, we introduce a stable and controllable photoelectricity-induced halide-ion segregation effect in epitaxially grown mixed-halide perovskite CsPbBrI microwire networks on mica, as confirmed by various in-situ measurements.

Deep generalizable prediction of RNA secondary structure via base pair motif energy.

Deep learning methods have demonstrated great performance for RNA secondary structure prediction. However, generalizability is a common unsolved issue on unseen out-of-distribution RNA families, which hinders further improvement of the accuracy and robustness of deep learning methods. Here we construct a base pair motif library that enumerates the complete space of the locally adjacent three-neighbor base pair and records the thermodynamic energy of corresponding base pair motifs through de novo modeling of tertiary structures, and we further develop a deep learning approach for RNA secondary structure prediction, named BPfold, which learns relationship between RNA sequence and the energy map of base pair motif.

DronePropA: Motion trajectories dataset for defective drones.

Unmanned aerial vehicles, or drones, are increasingly deployed in critical applications that demand exceptional safety and reliability. However, as drones become integral to industries such as logistics, agriculture, and public safety, reliability issues with core components like propellers can lead to serious safety risks and financial losses. Propellers typically have high failure rates, especially in harsh conditions, which has encouraged research into effective health monitoring techniques for early fault detection.

Synthesis of hexagonal boron arsenide nanosheets for low-power consumption flexible memristors.

Boron arsenide has recently attracted significant attention for its thermal and electronic properties. However, its lengthy growth process and bulk structure limit its application in advanced semiconductor systems. In this study, we introduce a method for synthesizing ultrathin crystalline hexagonal boron arsenide (h-BAs) nanosheets in large quantities via an in-situ chemical reaction of sodium borohydride with elemental arsenic in a low-pressure hydrogen atmosphere.

Fair ultrasound diagnosis via adversarial protected attribute aware perturbations on latent embeddings.

Deep learning techniques have significantly enhanced the convenience and precision of ultrasound image diagnosis, particularly in the crucial step of lesion segmentation. However, recent studies reveal that both train-from-scratch models and pre-trained models often exhibit performance disparities across sex and age attributes, leading to biased diagnoses for different subgroups. In this paper, we propose APPLE, a novel approach designed to mitigate unfairness without altering the parameters of the base model.

Soil Bacterial β-Diversity as a Key Determinant of Belowground Productivity in Warming Alpine Ecosystems.

Climate warming has profound effects on terrestrial ecosystems, with biodiversity playing a crucial role in modulating ecosystem productivity responses. While extensive studies have investigated how plant species richness (α-diversity) influences aboveground productivity under warming conditions, the contributions of plant and soil microbial β-diversity to belowground net primary productivity (BNPP) remain poorly understood. In this study, we conducted a 6-year warming experiment in an alpine meadow to investigate the response patterns and drivers of BNPP, as well as the α- and β-diversity of plant and soil microbial communities.

Atomic-scale self-rearrangement of hetero-metastable phases into high-density single-atom catalysts for the oxygen evolution reaction.

Maximizing metal-substrate interactions by self-reconstruction of coadjutant metastable phases can be a delicate strategy to obtain robust and efficient high-density single-atom catalysts. Here, we prepare high-density iridium atoms embedded ultrathin CoCeOOH nanosheets (CoCe-O-Ir) by the electrochemistry-initiated synchronous evolution between metastable iridium intermediates and symmetry-breaking CoCe(OH) substrates. The CoCe-O-Ir delivers an overpotential of 187 mV at 100 mA cm and a steady lifespan of 1000 h at 500 mA cm for oxygen evolution reaction.

Infrared In-Sensor Computing Based on Flexible Photothermoelectric Tellurium Nanomesh Arrays.

The inherent limitations of traditional von Neumann architectures hinder the rapid development of internet of things technologies. Beyond conventional, complementary metal-oxide-semiconductor technologies, imaging sensors integrated with near- or in-sensor computing architectures emerge as a promising solution. In this study, the multi-scale van der Waals (vdWs) interactions in 1D tellurium (Te) atomic chains are explored, leading to the deposition of a photothermoelectric (PTE) Te nanomesh on a polymeric polyimide substrate.

Mpox: Global epidemic situation and countermeasures.

Mpox, is a zoonotic disease caused by the monkeypox virus and is primarily endemic to Africa. As countries gradually stop smallpox vaccination, resistance to the smallpox virus is declining, increasing the risk of infection with mpox and other viruses. On 14 August 2024, the World Health Organization announced that the spread of mpox constituted a public health emergency of international concern.

Overcoming Energy-Scaling Barriers: Efficient Ammonia Electrosynthesis on High-Entropy Alloy Catalysts.

Electrochemically converting nitrate (NO ) to value-added ammonia (NH) is a complex process involving an eight-electron transfer and numerous intermediates, presenting a significant challenge for optimization. A multi-elemental synergy strategy to regulate the local electronic structure at the atomic level is proposed, creating a broad adsorption energy landscape in high-entropy alloy (HEA) catalysts. This approach enables optimal adsorption and desorption of various intermediates, effectively overcoming energy-scaling limitations for efficient NH electrosynthesis.

Collective properties of Petitella georgiae in tube environments.

The movement of biological swarms is widespread in nature, and collective behavior enhances a swarm's adaptability to its environment. However, most research focuses on free swarm movement, overlooking the impact of environmental constraints such as tubes. This study examines the swimming behavior of Petitella georgiae through a tube.

Electrode-Dependent and Tunable Sub-to-Super-Linear Responsivity in Mott Material-Enabled Near-Infrared Photodetectors for Advanced Near-Sensor Image Processing.

Brain-like intelligence is ushering humanity into an era of the Internet of Perceptions (IoP), where the vast amounts of data generated by numerous sensing nodes pose significant challenges to transmission bandwidth and computing hardware. A recently proposed near-sensor computing architecture offers an effective solution to reduce data processing delays and energy consumption. However, a pressing need remains for innovative hardware with multifunctional near-sensor image processing capabilities.

IGU-Aug: Information-Guided Unsupervised Augmentation and Pixel-Wise Contrastive Learning for Medical Image Analysis.

Contrastive learning (CL) is a form of self-supervised learning and has been widely used for various tasks. Different from widely studied instance-level contrastive learning, pixel-wise contrastive learning mainly helps with pixel-wise dense prediction tasks. The counterpart to an instance in instance-level CL is a pixel, along with its neighboring context, in pixel-wise CL.

Nitrogen deposition differentially regulates the sensitivity of gross primary productivity to extreme drought versus wetness.

Global hydroclimatic variability is increasing with more frequent extreme dry and wet years, severely destabilizing terrestrial ecosystem productivity. However, what regulates the consequence of precipitation extremes on productivity remains unclear. Based on a 9-year field manipulation experiment on the Qinghai-Tibetan Plateau, we found that the responses of gross primary productivity (GPP) to extreme drought and wetness were differentially regulated by nitrogen (N) deposition.

Which images to label for few-shot medical image analysis?

The success of deep learning methodologies hinges upon the availability of meticulously labeled extensive datasets. However, when dealing with medical images, the annotation process for such abundant training data often necessitates the involvement of experienced radiologists, thereby consuming their limited time resources. In order to alleviate this burden, few-shot learning approaches have been developed, which manage to achieve competitive performance levels with only several labeled images.

An inorganic-blended p-type semiconductor with robust electrical and mechanical properties.

Inorganic semiconductors typically have limited p-type behavior due to the scarcity of holes and the localized valence band maximum, hindering the progress of complementary devices and circuits. In this work, we propose an inorganic blending strategy to activate the hole-transporting character in an inorganic semiconductor compound, namely tellurium-selenium-oxygen (TeSeO). By rationally combining intrinsic p-type semimetal, semiconductor, and wide-bandgap semiconductor into a single compound, the TeSeO system displays tunable bandgaps ranging from 0.

Plant height as an indicator for alpine carbon sequestration and ecosystem response to warming.

Growing evidence indicates that plant community structure and traits have changed under climate warming, especially in cold or high-elevation regions. However, the impact of these warming-induced changes on ecosystem carbon sequestration remains unclear. Using a warming experiment on the high-elevation Qinghai-Tibetan Plateau, we found that warming not only increased plant species height but also altered species composition, collectively resulting in a taller plant community associated with increased net ecosystem productivity (NEP).

Fertilizer response to climate change: Evidence from corn production in China.

Corn is the third most cultivated food crop in the world, and climate change has important effects on corn production and food security. China is the top user of chemical fertilizer in the world, and analyzing how to effectively manage fertilizer application in such a developing country with resource constraints is crucial. We present empirical evidence from China to demonstrate the nonlinear impact of temperature on fertilizer usage in corn production based on a panel dataset that shows 2297 corn-growing counties during 1998-2016.

Pulse irradiation synthesis of metal chalcogenides on flexible substrates for enhanced photothermoelectric performance.

High synthesis temperatures and specific growth substrates are typically required to obtain crystalline or oriented inorganic functional thin films, posing a significant challenge for their utilization in large-scale, low-cost (opto-)electronic applications on conventional flexible substrates. Here, we explore a pulse irradiation synthesis (PIS) to prepare thermoelectric metal chalcogenide (e.g.

Multiscale Confinement Engineering for Boosting Overall Water Splitting by One-Step Stringing of a Single Atom and a Janus Nanoparticle within a Carbon Nanotube.

Enzyme-mimicking confined catalysis has attracted great interest in heterogeneous catalytic systems that can regulate the geometric or electronic structure of the active site and improve its performance. Herein, a liquid-assisted chemical vapor deposition (LCVD) strategy is proposed to simultaneously confine the single-atom Ru sites onto sidewalls and Janus Ni/NiO nanoparticles (NPs) at the apical nanocavities to thoroughly energize the N-doped carbon nanotube arrays (denoted as Ni/NiO@Ru-NC). The bifunctional Ni/NiO@Ru-NC electrocatalyst exhibits overpotentials of 88 and 261 mV for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) at 100 mA cm in alkaline solution, respectively, all ranking the top tier among the carbon-supported metal-based electrocatalysts.

Accelerating the speed of innovative anti-tumor drugs to first-in-human trials incorporating key de-risk strategies.

Pharmaceutical companies have recently focused on accelerating the timeline for initiating first-in-human (FIH) trials to allow quick assessment of biologic drugs. For example, a stable cell pool can be used to produce materials for the toxicology (Tox) study, reducing time to the clinic by 4-5 months. During the coronavirus disease 2019 (COVID-19) pandemic, the anti-COVID drugs timeline from DNA transfection to the clinical stage was decreased to 6 months using a stable pool to generate a clinical drug substrate (DS) with limited stability, virus clearance, and Tox study package.

Opposing effects of warming on the stability of above- and belowground productivity in facing an extreme drought event.

Climate warming, often accompanied by extreme drought events, could have profound effects on both plant community structure and ecosystem functioning. However, how warming interacts with extreme drought to affect community- and ecosystem-level stability remains a largely open question. Using data from a manipulative experiment with three warming treatments in an alpine meadow that experienced one extreme drought event, we investigated how warming modulates resistance and recovery of community structural and ecosystem functional stability in facing with extreme drought.

Controlling Surface Chemical Inhomogeneity of Ni P/MoNiP /MoP Heterostructure Electrocatalysts for Efficient Hydrogen Evolution Reaction.

Crystalline/amorphous phase engineering is demonstrated as a powerful strategy for electrochemical performance optimization. However, it is still a considerable challenge to prepare transition metal-based crystalline/amorphous heterostructures because of the low redox potential of transition metal ions. Herein, a facile H -assisted method is developed to prepare ternary Ni P/MoNiP /MoP crystalline/amorphous heterostructure nanowires on the conductive substrate.