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Hydrogenation is an effective way to tune the property of metal oxides. It can conventionally be performed by doping hydrogen into solid materials with noble-metal catalysis, high-temperature/pressure annealing treatment, or high-energy proton implantation in vacuum condition. Acid solution naturally provides a rich proton source, but it should cause corrosion rather than hydrogenation to metal oxides. Here we report a facile approach to hydrogenate monoclinic vanadium dioxide (VO 2 ) in acid solution at ambient condition by placing a small piece of low workfunction metal (Al, Cu, Ag, Zn, or Fe) on VO 2 surface. It is found that the attachment of a tiny metal particle (~1.0 mm) can lead to the complete hydrogenation of an entire wafer-size VO 2 (>2 inch). Moreover, with the right choice of the metal a two-step insulator–metal–insulator phase modulation can even be achieved. An electron–proton co-doping mechanism has been proposed and verified by the first-principles calculations. Hydrogenation is an effective way to tune the property of metal oxides. Here, the authors report a simple approach to hydrogenate VO 2 in acid solution under ambient conditions by placing a small piece of low workfunction metal on VO 2 surface.

Background Type 2C protein phosphatase (PP2C) is a negative regulator of ABA signaling pathway, which plays important roles in stress signal transduction in plants. However, little research on the PP2C genes family of cucumber ( Cucumis sativus L.), as an important economic vegetable, has been conducted. Results This study conducted a genome-wide investigation of the CsPP2C gene family. Through bioinformatics analysis, 56 CsPP2C genes were identified in cucumber. Based on phylogenetic analysis, the PP2C genes of cucumber and Arabidopsis were divided into 13 groups. Gene structure and conserved motif analysis showed that CsPP2C genes in the same group had similar gene structure and conserved domains. Collinearity analysis showed that segmental duplication events played a key role in the expansion of the cucumber PP2C genes family. In addition, the expression of CsPP2Cs under different abiotic treatments was analyzed by qRT-PCR. The results reveal that CsPP2C family genes showed different expression patterns under ABA, drought, salt, and cold treatment, and that CsPP2C3 , 11 – 17 , 23 , 45 , 54 and 55 responded significantly to the four stresses. By predicting the cis-elements in the promoter, we found that all CsPP2C members contained ABA response elements and drought response elements. Additionally, the expression patterns of CsPP2C genes were specific in different tissues. Conclusions The results of this study provide a reference for the genome-wide identification of the PP2C gene family in other species and provide a basis for future studies on the function of PP2C genes in cucumber.

Background BRASSINAZOLE-RESISTANT (BZR) is a class of specific transcription factor (TFs) involved in brassinosteroid (BR) signal transduction. The regulatory mechanism of target genes mediated by BZR has become one of the key research areas in plant BR signaling networks. However, the functions of the BZR gene family in cucumber have not been well characterized. Results In this study, six CsBZR gene family members were identified by analyzing the conserved domain of BES1 N in the cucumber genome. The size of CsBZR proteins ranges from 311 to 698 amino acids and are mostly located in the nucleus. Phylogenetic analysis divided CsBZR genes into three subgroups. The gene structure and conserved domain showed that the BZR genes domain in the same group was conserved. Cis-acting element analysis showed that cucumber BZR genes were mainly involved in hormone response, stress response and growth regulation. The qRT-PCR results also confirmed CsBZR response to hormones and abiotic stress. Conclusion Collectively, the CsBZR gene is involved in regulating cucumber growth and development, particularly in hormone response and response to abiotic stress. These findings provide valuable information for understanding the structure and expression patterns of BZR genes.

Amid the escalating global climatic challenges, hydrological risks significantly influence human settlement patterns, underscoring the imperative for an in-depth comprehension of hydrological change’s ramifications on human migration. However, predominant research has been circumscribed to the national level. The study delves into the nonlinear effects of hydrological risks on migration dynamics in 46,776 global subnational units. Meanwhile, leveraging remote sensing, we procured globally consistent metrics of hydrological intrusion exposure, offering a holistic risk assessment encompassing hazard, exposure, and vulnerability dimensions, thus complementing previous work. Here, we show that exposure is the primary migration driver, surpassing socioeconomic factors. Surrounding disparities further intensified exposure’s impact. Vulnerable groups, especially the economically disadvantaged and elderly, tend to remain in high-risk areas, with the former predominantly migrating within proximate vicinities. The nonlinear analysis delineates an S-shaped trajectory for hydrological exposure, transitioning from resistance to migration and culminating in entrapment, revealing dependence on settlement resilience and adaptability. Hydrological risks drive migration more than socioeconomic factors. Vulnerable groups often stay in high-risk areas or migrate nearby. The study reveals an S-shaped migration pattern influenced by settlement resilience and adaptability.

Benefiting from the advantageous features of structural diversity and resource renewability, organic electroactive compounds are considered as attractive cathode materials for aqueous Zn‐ion batteries (ZIBs). In this review, we discuss the recent developments of organic electrode materials for aqueous ZIBs. Although the proton (H+) storage chemistry in aqueous Zn‐organic batteries has triggered an overwhelming literature surge in recent years, this topic remains controversial. Therefore, our review focuses on this significant issue and summarizes the reported electrochemical mechanisms, including pure Zn2+ intercalation, pure H+ storage, and H+/Zn2+ co‐storage. Moreover, the impact of H+ storage on the electrochemical performance of aqueous ZIBs is discussed systematically. Given the significance of H+ storage, we also highlight the relevant characterization methods employed. Finally, perspectives and directions on further understanding the charge storage mechanisms of organic materials are outlined. We hope that this review will stimulate more attention on the H+ storage chemistry of organic electrode materials to advance our understanding and further its application. This review focuses on proton (H+) storage chemistry in aqueous Zn‐organic batteries and summarizes the reported electrochemical mechanisms as well as the impact of H+ storage on the electrochemical performance.

With the rise of big data and the Internet of Things, smart devices, especially autonomous driving systems, have become prime targets for information leakage and cyberattacks. This study presents the design and fabrication of a self-rectifying memristor utilizing a TiN/HfO x /Pt structure to enhance the security and reliability of autopilot systems. Following rapid thermal annealing treatment, the self-rectifying memristor demonstrates a recorded rectification ratio exceeding 10 8 and a nonlinearity of over 10 5 , coupled with minimal device-to-device (3.32%) and cycle-to-cycle variations (1.55%). We further extend the application of self-rectifying memristors into crossbar arrays for the real-time classification of autonomous driving datasets, showcasing their capability to execute artificial neural networks at the hardware level. The proposed crossbar arrays exhibit robust attack resilience, achieving classification accuracy (84.25%) comparable to those of software models (84.34%), particularly under complex attack scenarios. This work not only highlights the potential of self-rectifying memristors in bolstering the security of autonomous driving systems but also offers innovative strategies for safeguarding future intelligent transportation systems. This study presents a self-rectifying memristor (SRM) with high rectification ratio based on a TiN/HfO x /Pt structure. It demonstrates minimal device-to-device and cycle-to-cycle variations, enabling scalability and suitability for in-memory computing. SRM-based crossbar arrays achieve software-comparable accuracy and show promise to enhance autonomous driving security and reliability.

Background As the second largest leafy vegetable, cabbage ( Brassica oleracea L. var. capitata ) is grown globally, and the characteristics of the different varieties, forms, and colors of cabbage may differ. In this study, five analysis methods—variance analysis, correlation analysis, cluster analysis, principal component analysis, and comprehensive ranking—were used to evaluate the quality indices (soluble protein, soluble sugar, and nitrate), antioxidant content (vitamin C, polyphenols, and flavonoids), and mineral (K, Ca, Mg, Cu, Fe, Mn, and Zn) content of 159 varieties of four forms (green spherical, green oblate, purple spherical, and green cow heart) of cabbage. Results The results showed that there are significant differences among different forms and varieties of cabbage. Compared to the other three forms, the purple spherical cabbage had the highest flavonoid, K, Mg, Cu, Mn, and Zn content. A scatter plot of the principal component analysis showed that the purple spherical and green cow heart cabbage varieties were distributed to the same quadrant, indicating that their quality indices and mineral contents were highly consistent, while those of the green spherical and oblate varieties were irregularly distributed. Overall, the green spherical cabbage ranked first, followed by the green cow heart, green oblate, and purple spherical varieties. Conclusions Our results provide a theoretical basis for the cultivation and high-quality breeding of cabbage.

Below are the highlights of this review: This paper explores embedded RRAM development, parameters, and integration tech compatible with CMOS, highlighting advantages in embedded systems and its potential impact on chip process nodes. This paper introduces recent industry developments in embedded RRAM, featuring research from companies like Intel and TSMC, showcasing significant commercial application potential. This paper discusses embedded RRAM’s progress beyond storage, exploring potential applications in FPGA, MCU, CIM, and Neuromorphic Computing, along with challenges and future prospects. Embedded memory, which heavily relies on the manufacturing process, has been widely adopted in various industrial applications. As the field of embedded memory continues to evolve, innovative strategies are emerging to enhance performance. Among them, resistive random access memory (RRAM) has gained significant attention due to its numerous advantages over traditional memory devices, including high speed (<1 ns), high density (4 F 2 ·n −1 ), high scalability (∼nm), and low power consumption (∼pJ). This review focuses on the recent progress of embedded RRAM in industrial manufacturing and its potential applications. It provides a brief introduction to the concepts and advantages of RRAM, discusses the key factors that impact its industrial manufacturing, and presents the commercial progress driven by cutting-edge nanotechnology, which has been pursued by many semiconductor giants. Additionally, it highlights the adoption of embedded RRAM in emerging applications within the realm of the Internet of Things and future intelligent computing, with a particular emphasis on its role in neuromorphic computing. Finally, the review discusses the current challenges and provides insights into the prospects of embedded RRAM in the era of big data and artificial intelligence.

To determine the association between postoperative delirium (POD) and cognitive outcomes at least 1 month after surgery in elderly patients, and synthesize the dynamic risk trajectory of cognition impairment after POD. Meta-analysis searching PubMed, Cochrane and EMBASE from inception to November 1, 2020. The terms postoperative delirium, delirium after surgery, postsurgical delirium, postoperative cogniti*, postoperative cognitive dysfunction, postoperative cognition decline, cognitive decline, cognitive impair* and dement* were searched alone or in combination. Inclusion criteria were prospective cohort studies investigating the association between POD and cognitive outcomes in patients aged ≥60 years underwent surgery. The primary outcome was the association between POD and cognitive outcomes at 1 or more months after surgery. We considered cognitive outcomes measured up to 12 months after surgery as short-term and beyond 12 months as long-term. Two authors performed the study screening, data extraction and quality assessments. Effect sizes were calculated as Hedges g or Odds ratio (OR) based on random- and fixed-effects models. Meta-regression was conducted to analyze the role of potential contributors to heterogeneity. Eighteen studies were included. Our result showed a significant and medium association between POD and cognitive outcomes after at least 1 month postoperatively (g = 0.61 95% CI 0.43–0.79; I2 = 65.1%), indicating that patients with POD were associated with worse cognitive outcomes. The association of POD with short- and long-term cognitive impairment were also both significant (short-term: g = 0.46 95% CI 0.24–0.68; I2 = 53.1%; and long-term: g = 0.82 95% CI 0.57–1.06; I2 = 57.1%). A multivariate meta-regression suggested that age and measure of delirium were significant sources of heterogeneity. POD was also associated with the significant risk for dementia (OR = 6.08 95% CI 3.80–9.72; I2 = 0) as well as attention (OR = 1.74 95% CI 1.13–2.68; I2 = 0), executive (OR = 1.33 95% CI 1.00–1.80; I2 = 0) and memory impairment (OR = 1.59 95% CI 1.20–2.10; I2 = 43.0%). Additionally, our results showed that the risk trajectory for cognitive decline associated with POD within five years after surgery revealed exponential growth. This is the first meta-analysis quantifying the association between POD and cognitive outcomes. Our results showed that POD was significantly associated with worse cognitive outcomes, including short- and long-term cognitive outcomes following surgery. •POD was significantly associated with worse short- and long-term cognitive outcomes.•POD was associated with dementia as well as attention, execution and memory damage.•The relation between POD and cognitive impairment was time- and dose-dependent.

Tumor necrosis factor receptor‐associated factor (TRAF) proteins play crucial roles in plant development and response to abiotic stress. Here, we present genetic evidence that SEVEN IN ABSENTIA 2 (SINA2), a TRAF‐like family protein, is involved in abscisic acid (ABA)‐related drought stress signaling in Arabidopsis. Gene expression, protein subcellular localization, protein–protein interaction, and a transient transcription dual‐luciferase assay were performed. The drought tolerance of SINA2 loss‐of‐function mutants and SINA2‐overexpressing plants was investigated. In Arabidopsis, SINA2 was significantly induced by ABA and drought treatment. The SINA2‐YFP fusion protein was predominately localized in the nuclei and cytoplasm. Loss of function of SINA2 (sina2) reduced drought tolerance, whereas overexpression of SINA2 increased stomatal closure, decreased water loss, and therefore improved drought resistance in transgenic plants. Upon ABA treatment, expression of some key ABA‐ and stress‐responsive genes decreased in the sina2 mutant, but increased in SINA2‐overexpressing plants. Furthermore, SINA2 was induced in the ABA‐deficient mutant by ABA, but not by drought stress. Thus, the drought response of SINA2 was ABA‐dependent. ProSINA2::LUC expression in Arabidopsis protoplasts further revealed that ABA‐responsive element (ABRE) binding (AREB) protein 1 (AREB1) AREB2 and ABRE‐binding factor 3 (ABF3) might regulate SINA2 expression at the transcriptional level. Our results indicate that SINA2 functions as a positive molecular link between drought tolerance and ABA signaling in Arabidopsis.