As the world races toward carbon neutrality—think Japan's 2050 goal and global bans on gas-guzzling cars by 2035-2040—electric vehicles (EVs) are surging ahead, slashing emissions and transforming transportation. But this boom in lithium-ion batteries (LIBs), the high-energy hearts of EVs, smartphones, and more, brings a hidden danger: counterfeit or low-quality non-OEM batteries slipping into the mix. Reports highlight fires and explosions from these shady substitutes, especially in e-bikes and cameras, where overcharging or degradation turns them into ticking time bombs. Traditional safeguards like barcodes or IC chips? Easily faked or swapped. Enter a game-changing idea: harnessing the invisible magnetic fields generated by the batteries themselves during charge-discharge cycles. Building on prior nondestructive tech for spotting battery faults, this research pioneers magnetic analysis to authenticate LIBs right onboard vehicles, ensuring safety without invasive checks and paving the way for trustworthy EV adoption worldwide.

The sorghum salt tolerant gene SbTEF1 was identified by genome-wide association study (GWAS) and the PAV284 which located in the promoter region of SbTEF1 was the key regulatory locus governing the salt tolerant ability.

In an era where electric vehicles (EVs) are accelerating toward mainstream adoption, the global push for sustainable transportation is undeniable. With fossil fuels dwindling and climate concerns mounting, EVs promise cleaner roads and reduced emissions. However, this surge in EV popularity is straining our existing power grids, especially at charging stations where unpredictable fleets of vehicles plug in and out randomly. This creates imbalances in power demand, leading to issues like voltage drops, harmonic distortions, and overall poor power quality that could hinder widespread EV integration. Enter the innovative solution explored in this research: using a device called D-STATCOM (Distribution Static Compensator) to dynamically balance loads and supply reactive power right at the charging station. By addressing these local challenges, the study paves the way for more reliable, efficient EV infrastructure, making electric mobility not just viable but truly attractive for everyday users.

This study aimed to investigate the impact of Jinfeng Pills on the receptivity of a thin endometrium in rats and elucidate its mechanism of action. A thin endometrial model was established in female Sprague–Dawley rats. The rats were randomly assigned to the control, model, estradiol valerate, and Jinfeng Pill groups. Histological evaluation using hematoxylin and eosin staining was performed to assess morphological changes in the endometrium under light microscopy. Enzyme-linked immunosorbent assay was used to measure vascular endothelial growth factor (VEGF), estrogen, and progesterone levels in rat serum. Immunohistochemical analysis was used to examine morphological alterations in the endometrium. Immunofluorescence and quantitative polymerase chain reaction were employed to analyze the expression of VEGF, platelet endothelial cell adhesion molecule (CD31), β-catenin, leukemia inhibitory factor (LIF), and homeobox gene A10 (HOXA10) proteins and mRNA in endometrial tissue.

In the realm of secure information storage, optical encryption has emerged as a vital technique, particularly with the miniaturization of encryption devices. However, many existing systems lack the necessary reconfigurability and dynamic functionality. This study presents a novel approach through the development of dynamic optical-to-chemical energy conversion metamaterials, which enable enhanced steganography and multilevel information storage. We introduce a micro-dynamic multiple encryption device that leverages programmable optical properties in coumarin-based metamaterials, achieved through a direct laser writing grayscale gradient strategy. This methodology allows for the dynamic regulation of photoluminescent characteristics and cross-linking networks, facilitating innovative steganographic techniques under varying light conditions. The integration of a multi-optical field control system enables real-time adjustments to the material’s properties, enhancing the device’s reconfigurability and storage capabilities. Our findings underscore the potential of these metamaterials in advancing the field of microscale optical encryption, paving the way for future applications in dynamic storage and information security.

Sustainable water, energy and food (WEF) supplies are the bedrock upon which human society depends. Solar-driven interfacial evaporation, combined with electricity generation and cultivation, is a promising approach to mitigate the freshwater, energy and food crises. However, the performance of solar-driven systems decreases significantly during operation due to uncontrollable weather. This study proposes an integrated water/electricity cogeneration–cultivation system with superior thermal management. The energy storage evaporator, consisting of energy storage microcapsules/hydrogel composites, is optimally designed for sustainable desalination, achieving an evaporation rate of around 1.91 kg m⁻² h⁻¹. In the dark, heat released from the phase-change layer supported an evaporation rate of around 0.54 kg m⁻² h⁻¹. Reverse electrodialysis harnessed the salinity-gradient energy enhanced during desalination, enabling the long-running WEC system to achieve a power output of ~0.3 W m⁻², which was almost three times higher than that of conventional seawater/surface water mixing. Additionally, an integrated crop irrigation platform utilized system drainage for real-time, on-demand wheat cultivation without secondary contaminants, facilitating seamless WEF integration. This work presents a novel approach to all-day solar water production, electricity generation and crop irrigation, offering a solution and blueprint for the sustainable development of WEF.

In a paper published in aBIOTECH, the authors developed APTES—a deep learning system for automated segmentation of individual Arabidopsis leaves and siliques, coupled with the calculation of 128 phenotypic traits. The extracted traits are readily applicable to genome-wide association studies (GWAS) and other genetic analyses. Using this tool, the authors identified 1,042 trait-associated SNPs in their GWAS.