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Abstract Cytokinin Response Factors (CRFs) play a crucial role in plant growth and development, hormone signaling, and responses to biotic and abiotic stresses. However, there have been no reports on CRF genes in rice until now. We analyzed the CRF families in four rice subspecies: cultivated rice Oryza sativa Japonica Group, Oryza sativa Indica Group, and Oryza sativa (circum-Aus1 var. N22), as well as wild rice Oryza rufipogon. We identified 7, 6, 6, and 7 CRF in their genomes, respectively, distributed across different chromosomes. The protein motifs and gene structures of CRF in these four types of rice show high conservation. Cis-regulatory element analysis revealed that the promoter regions of the CRF contain numerous hormone and stress-related elements. The number of CRF in these four types of rice is not influenced by gene duplication. The expression pattern showed that OsCRF exhibit significant tissue-specific expression. The qRT-PCR results showed that OsCRF strongly responded to low-temperature stress and can be induced by melatonin and cytokinin to increase expression levels. In addition, the nuclear localisation of OsCRF4/5 was confirmed to be as predicted. The results above will provide a foundation for further and deeper investigation of CRFs.

BackgroundIn 2021, the United States experienced a 14% rise in fatal drug overdoses totaling 106,699 deaths, driven by harmful opioid use, particularly among individuals in the perinatal period who face increased risks associated with opioid use disorders (OUDs). Increased concerns about the impacts of escalating harmful opioid use among pregnant and postpartum persons are rising. Most of the current limited perinatal OUD studies were conducted using traditional methods, such as interviews and randomized controlled trials to understand OUD treatment, risk factors, and associated adverse effects. However, little is known about how social media data, such as X, formerly known as Twitter, can be leveraged to explore and identify broad perinatal OUD trends, disclosure and communication patterns, and public health surveillance about OUD in the perinatal period. ObjectiveThe objective is 3-fold: first, we aim to identify key themes and trends in perinatal OUD discussions on platform X. Second, we explore user engagement patterns, including replying and retweeting behaviors. Third, we investigate computational methods that could potentially streamline and scale the labor-intensive manual annotation effort. MethodsWe extracted 6 million raw perinatal-themed tweets posted by global X users during the opioid epidemic from May 2019 to October 2021. After data cleaning and sampling, we used 500 tweets related to OUD in the perinatal period by US X users for a thematic analysis using NVivo (Lumivero) software. ResultsSeven major themes emerged from our thematic analysis: (1) political views related to harmful opioid and other substance use, (2) perceptions of others’ substance use, (3) lived experiences of opioid and other substance use, (4) news reports or papers related to opioid and other substance use, (5) health care initiatives, (6) adverse effects on children’s health due to parental substance use, and (7) topics related to nonopioid substance use. Among these 7 themes, our user engagement analysis revealed that themes 4 and 5 received the highest average retweet counts, and theme 3 received the highest average tweet reply count. We further found that different computational methods excel in analyzing different themes. ConclusionsSocial media platforms such as X can serve as a valuable tool for analyzing real-time discourse and exploring public perceptions, opinions, and behaviors related to maternal substance use, particularly, harmful opioid use in the perinatal period. More health promotion strategies can be carried out on social media platforms to provide educational support for the OUD perinatal population.

Abstract The envelope (E) protein of the Japanese encephalitis virus (JEV) is a key protein for virus infection and adsorption of host cells, which determines the virulence of the virus and regulates the intensity of inflammatory response. The mutation of multiple aa residues in the E protein plays a critical role in the attenuated strain of JEV. This study demonstrated that the Asp to Gly, Ser, and His mutation of the E389 site, respectively, the replication ability of the viruses in cells was significantly reduced, and the viral neuroinvasiveness was attenuated to different degrees. Among them, the mutation at E389 site enhanced the E protein flexibility contributed to the attenuation of neuroinvasiveness. In contrast, less flexibility of E protein enhanced the neuroinvasiveness of the strain. Our results indicate that the mechanism of attenuation of E389 aa mutation attenuates neuroinvasiveness is related to increased flexibility of the E protein. In addition, the increased flexibility of E protein enhanced the viral sensitivity to heparin inhibition in vitro, which may lead to a decrease in the viral load entering brain. These results suggest that E389 residue is a potential site affecting JEV virulence, and the flexibility of the E protein of aa at this site plays an important role in the determination of neuroinvasiveness.

Abstract The advancement of laser-induced graphene (LIG) technology has streamlined the fabrications of flexible graphene devices. However, the ultrafast kinetics triggered by laser irradiation generates intrinsic amorphous characteristics, leading to high resistivity and compromised performance in electronic devices. Healing graphene defects in specific patterns is technologically challenging by conventional methods. Herein, we report the rapid rectification of LIG’s topological defects by flash Joule heating in milliseconds (referred to as F-LIG), whilst preserving its overall structure and porosity. The F-LIG exhibits a decreased I D/I G ratio from 0.84 – 0.33 and increased crystalline domain from Raman analysis, coupled with a 5-fold surge in conductivity. Pair distribution function and atomic-resolution imaging delineate a broader-range order of F-LIG with a shorter C-C bond of 1.425 Å. The improved crystallinity and conductivity of F-LIG with excellent flexibility enables its utilization in high-performance soft electronics and low-voltage disinfections. Notably, our F-LIG/polydimethylsiloxane strain sensor exhibits a gauge factor of 129.3 within 10% strain, which outperforms pristine LIG by 800%, showcasing significant potential for human-machine interfaces.

Abstract CuxO with flower‐like hierarchical structures has attracted significant research interest due to its intriguing morphologies and unique properties. The conventional methods for synthesizing such complex structures are costly and require rigorous experimental conditions. Recently, the X‐ray irradiation has emerged as a promising method for the rapid fabrication of precisely controlled CuxO shapes in large areas under environmentally friendly conditions. Nevertheless, the morphological regulation of the X‐ray‐induced synthesis of the CuxO is a multi‐parameter optimization task. Therefore, it is essential to quantitatively reveal the interplay between these parameters and the resulting morphology. In this work, we employed a high‐throughput experimental data‐driven approach to investigate the kinetics of X‐ray‐induced reactions and the impact of key factors, including sputtering power, film thickness, and annealing of precursor Cu thin films on the morphologies of CuxO. For the first time, the flower‐like CuxO nanostructures were synthesized using X‐ray radiation at ambient condition. This research proposes an eco‐friendly and cost‐effective strategy for producing CuxO with customizable morphologies. Furthermore, it enhances comprehension of the underlying mechanisms of X‐ray‐induced morphological modification, which is essential for optimizing the synthesis process and expanding the potential applications of flower‐like structures.

BackgroundAccording to the Morbidity and Mortality Weekly Report, polysubstance use among pregnant women is prevalent, with 38.2% of those who consume alcohol also engaging in the use of one or more additional substances. However, the underlying mechanisms, contexts, and experiences of polysubstance use are unclear. Organic information is abundant on social media such as X (formerly Twitter). Traditional quantitative and qualitative methods, as well as natural language processing techniques, can be jointly used to derive insights into public opinions, sentiments, and clinical and public health policy implications. ObjectiveBased on perinatal polysubstance use (PPU) data that we extracted on X from May 1, 2019, to October 31, 2021, we proposed two primary research questions: (1) What is the overall trend and sentiment of PPU discussions on X? (2) Are there any distinct patterns in the discussion trends of PPU-related tweets? If so, what are the implications for perinatal care and associated public health policies? MethodsWe used X’s application programming interface to extract >6 million raw tweets worldwide containing ≥2 prenatal health- and substance-related keywords provided by our clinical team. After removing all non–English-language tweets, non-US tweets, and US tweets without disclosed geolocations, we obtained 4848 PPU-related US tweets. We then evaluated them using a mixed methods approach. The quantitative analysis applied frequency, trend analysis, and several natural language processing techniques such as sentiment analysis to derive statistics to preview the corpus. To further understand semantics and clinical insights among these tweets, we conducted an in-depth thematic content analysis with a random sample of 500 PPU-related tweets with a satisfying κ score of 0.7748 for intercoder reliability. ResultsOur quantitative analysis indicates the overall trends, bigram and trigram patterns, and negative sentiments were more dominant in PPU tweets (2490/4848, 51.36%) than in the non-PPU sample (1323/4848, 27.29%). Paired polysubstance use (4134/4848, 85.27%) was the most common, with the combination alcohol and drugs identified as the most mentioned. From the qualitative analysis, we identified 3 main themes: nonsubstance, single substance, and polysubstance, and 4 subthemes to contextualize the rationale of underlying PPU behaviors: lifestyle, perceptions of others’ drug use, legal implications, and public health. ConclusionsThis study identified underexplored, emerging, and important topics related to perinatal PPU, with significant stigmas and legal ramifications discussed on X. Overall, public sentiments on PPU were mixed, encompassing negative (2490/4848, 51.36%), positive (1884/4848, 38.86%), and neutral (474/4848, 9.78%) sentiments. The leading substances in PPU were alcohol and drugs, and the normalization of PPU discussed on X is becoming more prevalent. Thus, this study provides valuable insights to further understand the complexity of PPU and its implications for public health practitioners and policy makers to provide proper access and support to individuals with PPU.

Abstract High‐performance soft magnetic materials are important for energy conservation and emission reduction. One challenge is achieving a combination of reliable temperature stability, high resistivity, high Curie temperature, and high saturation magnetization in a single material, which often comes at the expense of intrinsic coercivity–a typical trade‐off in the family of soft magnetic materials with homogeneous microstructures. Herein, a nanostructured FeCoNiSiAl complex concentrated alloy is developed through a hierarchical structure strategy. This alloy exhibits superior soft magnetic properties up to 897 K, maintaining an ultra‐low intrinsic coercivity (13.6 A m−1 at 297 K) over a wide temperature range, a high resistivity (138.08 µΩ cm−1 at 297 K) and the saturation magnetization with only a 16.7% attenuation at 897 K. These unusual property combinations are attributed to the dual‐magnetic‐state nature with exchange softening due to continuous crystal ordering fluctuations at the atomic scale. By deliberately controlling the microstructure, the comprehensive performance of the alloy can be tuned and controlled. The research provides valuable guidance for the development of soft magnetic materials for high‐temperature applications and expands the potential applications of related functional materials in the field of sustainable energy.

Background: Lung adenocarcinoma is a malignancy characterized by high mortality rates and unfavorable prognosis. However, the role of Leukotriene C4 Synthase (LTC4S) in lung cancer remains uninvestigated. Methods: The expression and prognostic value of LTC4S in LUAD were analyzed using the GEPIA online database. Subsequently, the function of LTC4S in lung cancer cells was examined through gain-of function experiments, using assays to evaluate tumor malignant behavior. Subcutaneous xenograft experiments in vivo was used for investigating the functions of LTC4S. Then, tumor hallmark pathways were analyzed by GSEA. Western blot assay was used to validate the impact of LTC4S on mTORC1 pathway. Finally, the correlation of mRNA and methylation of LTC4S were analyzed by cBioPortal. qRT-PCR, ChIP-qPCR and ChIP-Atlas were used to verify the regulation factors of LTC4S low expression in LUAD cells. Results: LTC4S presented significant decreased expression and favorable prognostic significance in LUAD. LTC4S was correlated with clinical stages in LUAD, which showed decreased expression gradually and significantly along with TNM stages. LTC4S-co-expressed genes were closely related to Ras signaling pathway, and MAPK signaling pathway. Overexpression of LTC4S inhibited cancer malignant phenotype and tumor growth in vitro and vivo. GSEA analysis and Western blot assay suggested low expression of LTC4S activated mTORC1 signaling pathway in LUAD. Moreover, the DNA methylation level of LTC4S in LUAD tissue was markedly elevated compared to normal tissue. The hypermethylation of the LTC4S promoter by DNMT3A leads to the decreased expression of LTC4S in LUAD. Conclusions: In conclusion, low expression of LTC4S serves as an unfavorable prognostic marker and the critical function of LTC4S in controlling the progression of LUAD. This highlights the promise for exploring the clinical benefits of manipulating LTC4S in LUAD targeted therapies.

Abstract In view of the current problems of low detection accuracy, poor stability and slow detection speed of intelligent vehicle violation detection systems, this article will use human–computer interaction and computer vision technology to solve the existing problems. First, the picture data required for the experiment is collected through the Bit Vehicle model dataset, and computer vision technology is used for preprocessing. Then, use Kalman filtering to track and study the vehicle to help better predict the trajectory of the vehicle in the area that needs to be detected; finally, use human–computer interaction technology to build the interactive interface of the system and improve the operability of the system. The violation detection system based on computer vision technology has an accuracy of more than 96.86% for the detection of the eight types of violations extracted, and the average detection is 98%. Through computer vision technology, the system can accurately detect and identify vehicle violations in real time, effectively improving the efficiency and safety of traffic management. In addition, the system also pays special attention to the design of human–computer interaction, provides an intuitive and easy-to-use user interface, and enables traffic managers to easily monitor and manage traffic conditions. This innovative intelligent vehicle violation detection system is expected to help the development of traffic management technology in the future.

As artificial intelligence (AI) technology advances rapidly, its increasing involvement in military defense fosters intelligent air combat domain development. The Intelligent Flight Controller (IFC) is a crucial technology and foundation for intelligent air combat decision-making systems. Controlling 6 Degree-of-freedom (DOF) aircraft in close-to-real-world environments requires an adaptable and dynamic decision-making controller. Most IFC researches focus on simplistic flight trajectory design and validation, while air combat requires aircraft that can perform complex tactical maneuvers. Deep reinforcement learning (DRL) provides a suitable technical paradigm. However, DRL suffers from sparse rewards, insufficient supervisory signals, low sampling efficiency, and slow convergence. In contrast, Large Language Model (LLM) possesses abundant knowledge about the real world, contextual understanding, and reasoning capabilities. By leveraging this, LLM can serve as prior knowledge for DRL, thereby reducing DRL training time. This paper proposes an LLM-guided deep reinforcement learning framework for IFC, which utilizes LLM-guided deep reinforcement learning to achieve intelligent flight control under limited computational resources. LLM provides direct guidance during training based on local knowledge, which improves the quality of data generated in agent-environment interaction within DRL, expedites training, and offers timely feedback to agents, thereby partially mitigating sparse reward issues. Additionally, we present an effective reward function to comprehensively balance the aircraft coupling control to ensure stable, flexible control. Finally, simulations and experiments show that the proposed techniques have good performance, robustness, and adaptability across various flight tasks, laying a foundation for future research in the intelligent air combat decision-making domain.

Under the auspices of the national strategies for urban-rural integration and rural revitalization, a focus on the functional evolution and spatial reorganization mechanisms of urban agriculture is of great theoretical and practical significance. This paper analyzes research progress in urban agriculture functional transformation and presents key scientific issues in urgent need of attention in future research. This paper aims to promote high-quality, ecologically sound development of urban agriculture and provides a scientific basis for integrated development of urban and rural areas. We have found that: 1) Research into urban agriculture functional transformation mainly focuses on evaluation and division of urban agriculture development transformation into type models, including multi-functional transformation and sustainable development of urban agriculture, spatial organization and production organization pathways of urban agriculture, land use and bidding mechanisms applied to urban agriculture development, and problems arising from urban agriculture and its multi-dimensional effects. At present, research related to the functional transformation of urban agriculture is guided by the theories of agricultural development, agricultural multi-functionality, and agricultural product demand, focusing on land alienation, ownership security, and diversification of agricultural production subjects in the process of urbanization. 2) The development of urban agriculture presents complex characteristics (i.e., it is multi-subject, multi-linkage, and multi-objective), and coordination of mixed social relations based on the demands of different stakeholders can also pose difficulties. The process and results of the cooperative game of urban agricultural space rental competition and subject interests exert crucial impacts on the restructuring of urban agricultural production system and spatial organization. The dynamic mechanisms of functional evolution and spatial reorganization of regional urban agriculture systems need to be studied. An urgent need exists to strengthen research into land bidding, land tenure, and related stakeholders in urban agriculture development from the perspective of regional systems. It is necessary to clarify the basic and dominant factors influencing the evolution of urban agriculture systems based on different scales, subjects, and perspectives and to elucidate the rent competition mechanism underlying spatial reorganization and ecological and environmental effects. 3) Future research needs to solve key scientific issues regarding three aspects of urban agriculture functional transformation. First, from the perspective of the rural-urban continuum, to clarify the interaction linkage and coupling mechanism between endogenous and external forces driving regional functional evolution in urban agricultural systems. Second, to reveal the key mechanism of spatial restructuring of regional urban agricultural systems and clarify synergies among stakeholders and the logic of land bidding. Third, based on the ecological and environmental impacts of the functional evolution of regional urban agriculture systems and spatial reorganization, comparative studies on the ecological impact of regional functional transformation of agricultural systems at different locations on urban-rural spatial gradient transects are needed.

Abstract Li‐rich Mn‐based layered oxides (LLO) hold great promise as cathode materials for lithium‐ion batteries (LIBs) due to their unique oxygen redox (OR) chemistry, which enables additional capacity. However, the LLOs face challenges related to the instability of their OR process due to the weak transition metal (TM)‐oxygen bond, leading to oxygen loss and irreversible phase transition that results in severe capacity and voltage decay. Herein, a synergistic electronic regulation strategy of surface and interior structures to enhance oxygen stability is proposed. In the interior of the materials, the local electrons around TM and O atoms may be delocalized by surrounding Mo atoms, facilitating the formation of stronger TM─O bonds at high voltages. Besides, on the surface, the highly reactive O atoms with lone pairs of electrons are passivated by additional TM atoms, which provides a more stable TM─O framework. Hence, this strategy stabilizes the oxygen and hinders TM migration, which enhances the reversibility in structural evolution, leading to increased capacity and voltage retention. This work presents an efficient approach to enhance the performance of LLOs through surface‐to‐interior electronic structure modulation, while also contributing to a deeper understanding of their redox reaction.

In the extreme space environment, spacecraft endure dramatic temperature variations that can impair their functionality. A VO2-based smart radiator device (SRD) offers an effective solution by adaptively adjusting its radiative properties. However, current research on VO2-based thermochromic films mainly focuses on optimizing the emissivity tunability (Δε) of single-cycle sandwich structures. Although multi-cycle structures have shown increased Δε compared to single-cycle sandwich structures, there have been few systematic studies to find the optimal cycle structure. This paper theoretically discusses the influence of material properties and cyclic structure on SRD performance using Finite-Difference Time-Domain (FDTD) software, which is a rigorous and powerful tool for modeling nano-scale optical devices. An optimal structural model with maximum emissivity tunability is proposed. The BaF2 obtained through optimization is used as the dielectric material to further optimize the cyclic resonator. The results indicate that the tunability of emissivity can reach as high as 0.7917 when the BaF2/VO2 structure is arranged in three periods. Furthermore, to ensure a longer lifespan for SRD under harsh space conditions, the effects of HfO2 and TiO2 protective layers on the optical performance of composite films are investigated. The results show that when TiO2 is used as the protective layer with a thickness of 0.1 µm, the maximum emissivity tunability reaches 0.7932. Finally, electric field analysis is conducted to prove that the physical mechanism of the smart radiator device is the combination of stacked Fabry–Perot resonance and multiple solar reflections. This work not only validates the effectiveness of the proposed structure in enhancing spacecraft thermal control performance but also provides theoretical guidance for the design and optimization of SRDs for space applications.

Owing to the development issues of the Guangdong-Hong Kong-Macao Greater Bay Area in the new domestic and international situation, the content, challenges, and paths of innovation and development of the Greater Bay Area are explored from multiple dimensions, including economic, social, cultural, and institutional. The innovation and development of the Greater Bay Area should strengthen technological and industrial innovation capabilities, improve regional resilience to cope with external shocks, increase the mobility of intraregional factors, improve the well-being of the people's livelihood, enhance the capacity of spatial governance, promote integrated urban-rural development, and optimize the regional pattern of ecological security. The conclusion is that considering the innovation and development of the Greater Bay Area from a systemic and interconnected perspective is crucial for seeking innovations in various development fields and promoting coupling and coordination among them. Therefore, the region may acquire the agency that can continuously break through bottlenecks, resolve external shocks, and unlock new paths of development. We call for the strengthening of cross-field and cross-disciplinary collaborative research to contribute the power of geography to the realization of the development goals of the Guangdong-Hong Kong-Macao Greater Bay Area.

Abstract Negative thermal expansion (NTE) alloys possess great practical merit as thermal offsets for positive thermal expansion due to its metallic properties. However, achieving a large NTE with a wide temperature range remains a great challenge. Herein, a metallic framework-like material FeZr2 is found to exhibit a giant uniaxial (1D) NTE with a wide temperature range (93-1078 K, $${\bar{\alpha }}_{l}=-34.01\times {10}^{-6}\,{{{{{{\rm{K}}}}}}}^{-1}$$ α ¯ l = − 34.01 × 10 − 6 K − 1 ). Such uniaxial NTE is the strongest in all metal-based NTE materials. The direct experimental evidence and DFT calculations reveal that the origin of giant NTE is the couple with phonons, flexible framework-like structure, and soft bonds. Interestingly, the present metallic FeZr2 excites giant 1D NTE mainly driven by high-frequency optical branches. It is unlike the NTE in traditional framework materials, which are generally dominated by low energy acoustic branches. In the present study, a giant uniaxial NTE alloy is reported, and the complex mechanism has been revealed. It is of great significance for understanding the nature of thermal expansion and guiding the regulation of thermal expansion.

Studying the flow behavior is critical to understand the deformation mechanism of amorphous solids. However, detecting the basic flow events in amorphous solids is challenging. Here, by simultaneous SAXS/WAXS, elementary flow carriers in wound metallic glasses are identified from flow-induced structural heterogeneities with a radius of gyration of 2.5∼3.5 nm. Their size increases and morphology changes from sphere-like to rod-like under flow. Moreover, the atomic structure exhibits an unusual change to a more disordered state during winding/annealing at the temperature of ∼0.8 Tg. This work provides an atomic-to-nanoscale description of the flow carriers of amorphous solids during deformation.Impact StatementThe elementary flow carriers in metallic glasses have a radius of gyration of 2.5∼3.5 nm. During flow, their size increases and morphology changes from sphere-like to rod-like.

Abstract Rechargeable lithium‐ion and sodium‐ion batteries (SIB) have dominated the energy storage fields such as electric vehicles and portable electronics due to their high energy density, long cycle life, and environmental friendliness. However, the critical bottleneck hindering the further improvement of their electrochemical performance is the unsatisfactory cathode materials, typically exhibiting inherent drawbacks such as low reversible capacity, initial capacity loss, fast capacity decay, and poor rate performance. These issues are mainly attributed to changes in the internal structure of cathode materials, such as irreversible transformation of particle morphology, evolution of crystal structure, and undesired physicochemical interfacial reactions during the electrochemical process. To address above obstacles, abundant research efforts have been devoted to stabilizing the structural evolution of cathode materials and enhancing their electrochemical performance. Herein, we reviewed the research progress on the cathode materials for lithium‐ion and SIBs. The typical cathodes and their structural characteristics, electrochemical behaviors, reaction mechanisms, and strategies for electrochemical performance optimization were summarized. This review aims to promote the understanding of the structure‐performance relationship in the cathode materials and provide some guidance for the design of advanced cathode materials for lithium‐ion and SIBs from the perspective of crystal structure.

ABSTRACTThe temperature dependence of the critical stress of R→B19’ transformation in NiTi shape memory alloys remains unclear due to the difficulties in precisely identifying the phase constitution and acquiring sole R phase. Here we investigate the thermally- and stress-induced martensitic transformation in a near-equiatomic nanocrystalline NiTi alloy. In situ synchrotron X-ray diffraction is used to identify the phase evolution such that the temperature window for sole R phase is firmly determined. We find that the temperature dependence of R→B19’ is negative (−0.2 MPa/K) in our alloy, in sharp contrast to 3–5 MPa/K reported. Possible reasons for the discrepancies are discussed.

Graphene can support surface plasmon polaritons (SPPs) in the terahertz band, and graphene SPP sensors are widely used in the field of terahertz micro- and nano-optical devices. In this paper, we propose an H-shaped graphene metasurface and investigate the plasmon-induced transparency (PIT) phenomenon in the proposed structure using the finite-difference time-domain (FDTD) method. Our results show that the Fermi energy levels, as well as certain shape parameters, can effectively modulate the PIT phenomenon in the proposed structure. Interestingly, changing some of these shape parameters can excite two dips into three. In terms of sensing performance, the maximum values of sensitivity and figure of merit (FOM) are 1.4028 THz/RIU and 17.97, respectively. These results offer valuable guidance for the use of terahertz optical graphene SPP sensors.

The low hardness and poor wear resistance of laser-cladding 316L stainless steel impose significant constraints on its practical applications. In this study, a strategy for strengthening laser-cladding 316L stainless steel with WMoTaNb refractory high-entropy alloy as a reinforcement material is proposed. The results confirm that the coating primarily comprises a body-centered cubic (BCC) Fe-based solid solution, a network-distributed hexagonal Fe2X (X = W, Mo, Ta, and Nb) Laves phase, and a diffusely distributed face-centered cubic (FCC) (Ta, Nb)C phase. The Fe-based solid solution distributes along columnar and fine dendrites, while the Laves phase and (Ta, Nb)C phase are in the inter-dendrites. The presence of a significant number of network Laves phases exhibiting high strength and hardness is the primary factor contributing to the enhancement of coating microhardness. The hardness of the composite coating is increased by nearly twice compared to that of the 316L coating, resulting in an improved wear resistance. The present work can shed light on designing and fabricating 316L stainless steel coating with enhanced hardness and wear resistance.

Few-shot object detection is a challenging task aimed at recognizing novel classes and localizing with limited labeled data. Although substantial achievements have been obtained, existing methods mostly struggle with forgetting and lack stability across various few-shot training samples. In this paper, we reveal two gaps affecting meta-knowledge transfer, leading to unstable performance and forgetting in meta-learning-based frameworks. To this end, we propose sample normalization, a simple yet effective method that enhances performance stability and decreases forgetting. Additionally, we apply Z-score normalization to mitigate the hubness problem in high-dimensional feature space. Experimental results on the PASCAL VOC data set demonstrate that our approach outperforms existing methods in both accuracy and stability, achieving up to +4.4 mAP@0.5 and +5.3 mAR in a single run, with +4.8 mAP@0.5 and +5.1 mAR over 10 random experiments on average. Furthermore, our method alleviates the drop in performance of base classes. The code will be released to facilitate future research.

Understanding high piezoelectricity in relaxors is challenging due to the heterogeneous structures. Here, the authors demonstrate that the competing local polar order-disorder state with balanced length and direction randomness is the key.

With the continuous advancement of urban renewal, innovative and creative spaces in the urban village have attracted much attention as a new model of space restoration. In the process of material space transformation, the emotional identity and place identity of innovative and creative spaces in urban villages are reconstructed. However, communities and residents in the urban village remain often been neglected in previous studies, most of which focused on the material and economic perspectives. In other words, the emotional mechanisms and spatial influences of relevant subjects in innovative and creative spaces have not received sufficient attention. By focusing on the innovative and creative spaces of Huangpu village in Guangzhou as an example, this study employed in-depth interviews, network text analysis, and other methods to explore the impact of innovative and creative spaces on residents' sense of place and their role in creating a local emotional identity within the context of urban renewal from the perspective of emotional geography. The innovative and creative spaces of the urban villages exerted a different impact on the local emotion and space identity of multiple subjects through the reshaping of the material environment, culture, and social relations. The improvement of the material environment of the innovative and creative spaces in the urban villages enhanced the emotional identity and local attachment of residents. The cultural values of modern industrial forms were not able to shape the local and cultural identities of residents but increased the level of makers. The local identity of the tenant group was based on creativity and cultural atmosphere. The innovative and creative spaces of the urban villages formed a social network relationship with industry as the link by strengthening the interaction and connection between the subjects, establishing a common emotional attachment and local identity, and transforming the original traditional living space into a multi-dimensional space with consumption, production, and leisure attributes. The emotion and atmosphere of the innovative and creative spaces were displayed during the interaction between makers and residents and during the production of creative products and made different subjects participate in the process of space-remodeling. Not only did this process strengthen the perception and recognition of innovative and creative elements and rural areas, but it also established the recognition of a common local value. Given the current emphasis on the reuse of stock space resources, such as industrial heritage and historical buildings, it is particularly important to focus on the emotional connection between humans and the environment. From the perspective of emotional geography, it is of great significance that the emotional effect and meaning of constructing innovative and creative spaces on rural development are elucidated. This study provides not only a theoretical perspective for a deeper understanding of the relationship between the innovative and creative spaces and the locality of urban villages but also insights into promoting culturally oriented urban renewal.

Rice direct seeding has the significant potential to save labor and water, conserve environmental resources, and reduce greenhouse gas emissions tremendously. Therefore, rice direct seeding is becoming the major cultivation technology applied to rice production in many countries. Identifying and utilizing genes controlling mesocotyl elongation is an effective approach to accelerate breeding procedures and meet the requirements for direct-seeded rice (DSR) production. This study used a permanent mapping population with 144 recombinant inbred lines (RILs) and 2 828 bin-markers to detect quantitative trait loci (QTLs) associated with mesocotyl length in 2019 and 2020. The mesocotyl lengths of the rice RILs and their parents, Lijiangxintuanheigu (LTH) and Shennong 265 (SN265), were measured in a growth chamber at 30°C in a dark environment. A total of 16 QTLs for mesocotyl length were identified on chromosomes 1(2), 2(4), 3(2), 4, 5, 6, 7, 9, 11(2), and 12. Seven of these QTLs, including qML1a, qML1b, qML2d, qML3a, qML3b, qML5, and qML11b, were reproducibly detected in both years via the interval mapping method. The major QTL, qML3a, was reidentified in two years via the composite interval mapping method. A total of 10 to 413 annotated genes for each QTL were identified in their smallest genetic intervals of 37.69 kb to 2.78 Mb, respectively. Thirteen predicted genes within a relatively small genetic interval (88.18 kb) of the major mesocotyl elongation QTL, qML3a, were more thoroughly analyzed. Finally, the coding DNA sequence variations among SN265, LTH, and Nipponbare indicated that the LOC_Os03g50550 gene was the strongest candidate gene for the qML3a QTL controlling the mesocotyl elongation. This LOC_Os03g50550 gene encodes a mitogen-activated protein kinase. Relative gene expression analysis using qRT-RCR further revealed that the expression levels of the LOC_Os03g50550 gene in the mesocotyl of LTH were significantly lower than in the mesocotyl of SN265. In conclusion, these results further strengthen our knowledge about rice's genetic mechanisms of mesocotyl elongation. This investigation's discoveries will help to accelerate breeding programs for new DSR variety development.

Abstract Background Pyrroloquinoline quinone (PQQ), a cofactor for bacterial dehydrogenases, is associated with biological processes such as mitochondriogenesis, reproduction, growth, and aging. Due to the extremely high cost of chemical synthesis and low yield of microbial synthesis, the election of effective strains and the development of dynamic fermentation strategies for enhancing PQQ production are meaningful movements to meet the large-scale industrial requirements. Results A high-titer PQQ-producing mutant strain, Hyphomicrobium denitrificans FJNU-A26, was obtained by integrating ARTP (atmospheric and room‑temperature plasma) mutagenesis, adaptive laboratory evolution and high-throughput screening strategies. Afterward, the systematic optimization of the fermentation medium was conducted using a one-factor-at-a-time strategy and response surface methodology to increase the PQQ concentration from 1.02 to 1.37 g/L. The transcriptional analysis using qRT-PCR revealed that the expression of genes involved in PQQ biosynthesis were significantly upregulated when the ARTP-ALE-derived mutant was applied. Furthermore, a novel two-stage pH control strategy was introduced to address the inconsistent effects of the pH value on cell growth and PQQ production. These combined strategies led to a 148% increase in the PQQ concentration compared with that of the initial strain FJNU-6, reaching 1.52 g/L with a yield of 40.3 mg/g DCW after 144 h of fed-batch fermentation in a 5-L fermenter. Conclusion The characteristics above suggest that FJNU-A26 represents an effective candidate as an industrial PQQ producer, and the integrated strategies can be readily extended to other microorganisms for the large-scale production of PQQ.

Bi0.5Na0.5TiO3BaTiO3 (BNT–100xBT) ceramics are promising candidates for piezoelectric applications. The correlation between their structure and piezoelectric properties has attracted considerable interest. Herein, the structures of 6BT and 7BT with distinct piezoelectricity are investigated via in-situ synchrotron X-ray diffraction and transmission electron microscopy. It is found that although both compositions present morphotropic phase boundary (MPB) features with coexisting R3c and P4bm phases, their refined structures are significantly different. 6BT is composed of the R3c phase with a small P4bm fraction after electrical poling, while 7BT presents comparable fractions of the two phases. Less pronounced structure distortion and oxygen octahedral tilting occur in 7BT, which favor the phase transformation, resulting in an enhanced piezoelectricity. This enhancement driven by structural flexibility is elucidated by phenomenological analysis. These results demonstrate that the design of high piezoelectricity at MPBs should consider not only the phase-coexisting states but also the refined crystal structure.

A multiscale crystal plasticity model accounting for temperature-dependent mechanical behaviors without introducing a larger number of unknown parameters was developed. The model was implemented in elastic-plastic self-consistent (EPSC) and crystal plasticity finite element (CPFE) frameworks for grain-scale simulations. A computationally efficient EPSC model was first employed to estimate the critical resolved shear stress and hardening parameters of the slip and twin systems available in a hexagonal close-packed magnesium alloy, ZEK100. The constitutive parameters were thereafter refined using the CPFE. The crystal plasticity frameworks incorporated with the temperature-dependent constitutive model were used to predict stress–strain curves in macroscale and lattice strains in microscale at different testing temperatures up to 200 °C. In particular, the predictions by the crystal plasticity models were compared with the measured lattice strain data at the elevated temperatures by in situ high-energy X-ray diffraction, for the first time. The comparison in the multiscale improved the fidelity of the developed temperature-dependent constitutive model and validated the assumption with regard to the temperature dependency of available slip and twin systems in the magnesium alloy. Finally, this work provides a time-efficient and precise modeling scheme for magnesium alloys at elevated temperatures.

We experimentally demonstrate the intensity and angle control of interference image during all-optical logic (AOL) gate carrying orbital angular momentum (OAM) in a hot atomic ensemble. The variation of output signal intensity has been discovered by changing the detuning of input field. By changing the angle of reference light, we can also get obvious output signal modulation effects. Moreover, the transition of the interference pattern from parallel shape to spiral shape by changing the small angle is observed. This novel method of controlling AOL gate carrying OAM will further promoting the construction of all-optical networks with atomic ensembles.

Objectives Identification of endometrial cancers (EC) with mismatch repair deficiency (dMMR) or microsatellite instability-high (MSI-H) is essential for Lynch syndrome screening and treatment stratification. We aimed to assess the utility of immunohistochemistry (IHC) staining for MMR protein expression and polymerase chain reaction (PCR)-based MSI assays in EC and the correlation between MMR/MSI status and various clinicopathological parameters. Methods We reviewed the clinical and pathological information of 333 patients with EC. MMR protein expression was assessed as retained or lost to determine MMR status by IHC staining, and MSI status was identified by PCR capillary electrophoresis (PCR-CE) testing with a National Cancer Institute (NCI) panel. The correlation of MMR/MSI status with clinicopathological features was determined by statistical analysis. Discrepant results were further analyzed using an alternative PCR-CE MSI (Promega panel) method, MLH1 promoter methylation assays, and next-generation sequencing (NGS). Results Among the EC patients, the overall percentage of dMMR was 25.2%, and the overall percentage of MSI-H was 24%. Among the dMMR patients, 50 (59.5%) showed loss of MLH1 and PMS2 expression, 19 (22.6%) loss of MSH2 and MSH6 expression, and seven (8.3%) and eight (9.5%) loss of PMS2 and MSH6 expression, respectively. The dMMR subgroup was significantly younger than the pMMR subgroup, especially for

The Feixianguan Formation reservoirs in northeastern Sichuan are mainly a suite of carbonate platform deposits. The reservoir types are diverse with high heterogeneity and complex genetic mechanisms. Pores, vugs and fractures of different genetic mechanisms and scales are often developed in association, and it is difficult to classify reservoir types merely based on static data such as outcrop observation, and cores and logging data. In the study, the reservoirs in the Feixianguan Formation are grouped into five types by combining dynamic and static data, that is, karst breccia-residual vuggy type, solution-enhanced vuggy type, fractured-vuggy type, fractured type and matrix type (non-reservoir). Based on conventional logging data, core data and formation microscanner image (FMI) data of the Qilibei block, northeastern Sichuan Basin, the reservoirs are classified in accordance with fracture-vug matching relationship. Based on the principle of cluster analysis, K-Nearest Neighbor (KNN) classification templates are established, and the applicability of the model is verified by using the reservoir data from wells uninvolved in modeling. Following the analysis of the results of reservoir type discrimination and the production of corresponding reservoir intervals, the contributions of various reservoir types to production are evaluated and the reliability of reservoir type classification is verified. The results show that the solution-enhanced vuggy type is of high-quality sweet spot reservoir in the study area with good physical property and high gas production, followed by the fractured-vuggy type, and the fractured and karst breccia-residual vuggy types are the least promising.

NiTiCu-based shape memory alloys have been considered as ideal materials for solid-state refrigeration due to their superb cycling stability for elastocaloric effect. However, the embrittlement and deterioration caused by secondary phase and coarse grains restrict their applications, and it is still challenging since the geometric components are required. Here, bulk NiTiCuCo parts with excellent forming quality were fabricated by laser powder bed fusion (LPBF) technique. The as-fabricated alloy exhibits refined three-phases hierarchical microcomposite formed based on the rapid cooling mode of LPBF, composed of intricate dendritic Ti _2 Ni–NiTi composite and nano Ti _2 Cu embedded inside the NiTi-matrix. This configuration endows far superior elastocaloric stability compared to the as-cast counterpart. The low fatigue stems from the strong elastic coupling between the interphases with reversible martensite transformation, revealed by in-situ synchrotron high-energy x-ray diffraction. The fabrication of NiTiCuCo alloy via LPBF fills the bill of complex geometric structures for elastocaloric NiTiCu alloys. The understanding of interphase micro-coupling could provide the guide for designing LPBF fabricated shape memory-based composites, enabling their applications for special demands on other functionalities.

Abstract Nowadays, LiCoO2 has dominated the cathode technology of lithium‐ion batteries (LIBs) for 3C digital devices, but the sluggish electrochemical kinetics and severe structure destruction limit its further application under extreme temperatures. Herein, we design a synergetic strategy including La, Mg co‐doping and LiAlO2@Al2O3 surface coating. Typically, the La3+ increases the interlayer distance and significantly enhances the ionic conductivity, the Mg2+ improves electronic conductivity, and the LiAlO2@Al2O3 coating layer improves the interfacial charge transfer and suppresses the polarization. The co‐modified LiCoO2 (CM‐LCO) shows excellent temperature adaptability with remarkable electrochemical performance in a wide temperature range (−40–70°C). Remarkably, the CM‐LCO also exhibits excellent cycle stability and high‐rate performance at extreme temperatures. The synergistic effects of this co‐modification strategy are demonstrated by investigating the electrochemical reaction kinetics and structure evolution of CM‐LCO. This work proposes a promising strategy for the application of the high‐voltage LCO in a wide temperature range.

BackgroundLow birthweight (LBW) is a leading cause of neonatal mortality in the United States and a major causative factor of adverse health effects in newborns. Identifying high-risk patients early in prenatal care is crucial to preventing adverse outcomes. Previous studies have proposed various machine learning (ML) models for LBW prediction task, but they were limited by small and imbalanced data sets. Some authors attempted to address this through different data rebalancing methods. However, most of their reported performances did not reflect the models’ actual performance in real-life scenarios. To date, few studies have successfully benchmarked the performance of ML models in maternal health; thus, it is critical to establish benchmarks to advance ML use to subsequently improve birth outcomes. ObjectiveThis study aimed to establish several key benchmarking ML models to predict LBW and systematically apply different rebalancing optimization methods to a large-scale and extremely imbalanced all-payer hospital record data set that connects mother and baby data at a state level in the United States. We also performed feature importance analysis to identify the most contributing features in the LBW classification task, which can aid in targeted intervention. MethodsOur large data set consisted of 266,687 birth records across 6 years, and 8.63% (n=23,019) of records were labeled as LBW. To set up benchmarking ML models to predict LBW, we applied 7 classic ML models (ie, logistic regression, naive Bayes, random forest, extreme gradient boosting, adaptive boosting, multilayer perceptron, and sequential artificial neural network) while using 4 different data rebalancing methods: random undersampling, random oversampling, synthetic minority oversampling technique, and weight rebalancing. Owing to ethical considerations, in addition to ML evaluation metrics, we primarily used recall to evaluate model performance, indicating the number of correctly predicted LBW cases out of all actual LBW cases, as false negative health care outcomes could be fatal. We further analyzed feature importance to explore the degree to which each feature contributed to ML model prediction among our best-performing models. ResultsWe found that extreme gradient boosting achieved the highest recall score—0.70—using the weight rebalancing method. Our results showed that various data rebalancing methods improved the prediction performance of the LBW group substantially. From the feature importance analysis, maternal race, age, payment source, sum of predelivery emergency department and inpatient hospitalizations, predelivery disease profile, and different social vulnerability index components were important risk factors associated with LBW. ConclusionsOur findings establish useful ML benchmarks to improve birth outcomes in the maternal health domain. They are informative to identify the minority class (ie, LBW) based on an extremely imbalanced data set, which may guide the development of personalized LBW early prevention, clinical interventions, and statewide maternal and infant health policy changes.

Enhancing the stability of positive electrodes at thermally-abused conditions is vital for next-generation lithium-based batteries. Here, the authors report in situ physicochemical characterizations to improve the fundamental understanding of the degradation mechanism in polycrystalline Ni-rich cathodes.

The use of Mn-rich layered cathodes in Na-based batteries is hindered by inadequate cycling reversibility and sluggish anionic redox kinetics. Here, the authors report a strategy to stabilize the structure and promote anionic redox via configurational entropy and ion-diffusion structural tuning.

The coordinated development of jobs and housing spaces is of great importance for the rational allocation of urban functions and residents' quality of life. We focus on the measurement of the spatial relationship between working and living space in a mountainous city and the impact of industrial and topographic factors, with the main city of Chongqing as the study area. Using the employed population and residential population as identified by Baidu Huiyan, this paper analyzes the relationship between jobs and housing spaces in the central city of Chongqing by calculating the degree of job-housing deviation, dividing the study area into three groups: the Employment-Dominant Area (EDA), the Balanced Area (BA), and the Residential-Dominant Area (RDA). Factor analysis and window analysis are then applied to explore the impact of industrial and topographic factors on job-housing space based on the Fourth National Economic Census. We find that, first, the spatial distributions of employment and the residential population in the central city of Chongqing are basically the same, showing the characteristics of "high in the middle and low around" and a polycentric spatial structure; there is spatial overlap between the areas with the densest employment and residential population, such as Jiefangbei, Qixinggang, and Nanping. Second, the job-housing space in Chongqing is basically balanced; the deviation of work and residence in most suburban districts is not obvious. The sub-districts with the highest Standard Deviation (SD) are mainly concentrated in the employment-dominant areas within the outer ring, while a few are distributed in the residential-dominant areas. The multi-center structure shows a low job-housing balance in the main center (Jiefangbei) and a high job-housing balance in the four sub-centers. Third, industrial factors and relief amplitude have a great impact on job-housing balance in Chongqing's main urban area. Using SD as the dependent variable can better explain the influencing factors. The integrated service industry factor and the production service industry factor exacerbate the separation of jobs and residences because of their ability to attract the employment population. In the meantime, the social service industry factor, manufacturing factor, and relief amplitude reduce the difference between jobs and residences. In addition, urban spatial structure, traffic patterns, government planning, and residents' attributes are important factors shaping the job-housing space in the Chongqing main area.

Under the background of rural revitalization strategy, art intervention in rural areas, as a new way of rural construction in China, is attracting more and more attention since various art practices have appeared in Chinese villages during the last decade. Art intervention in rural areas has multi-dimensional benefits such as improving rural landscape, promoting villagers' income, enhancing community connections, and promoting cultural inheritance. On the basis of clarifying the connotation and typical modes of art intervention in rural areas in China, this paper constructs and analyzes the benefit hierarchy of art intervention in rural areas based on Maslow's hierarchy of needs theory, and selects Xiaozhou and Fenghe villages in Guangzhou as typical cases to identify the benefit characteristics and problems of two modes of artist-led and capital-led art intervention through field investigation. Although previous studies have focused more on specific cases of art intervention in rural areas, which have revealed the work procedure and achievements in detail, the comparison of their differences and a systematic construction of the influence are still worth discussing. The research results show that: (1) Art intervention in rural areas is a typical mode of rural revitalization in which the government, capital, artists and cultural groups realize multi-level benefits such as rural landscape beautification, tourism economic benefits, community creation and governance, and local cultural inheritance through art practice in the context of rural revitalization. According to different driving subjects, the art intervention in rural areas can be divided into two types: artist-led and capital-led. (2) Art intervention in rural areas has four levels of benefits: material, economic, social and cultural, showing the characteristics of progression by level. (3) The artist-led type plays a significant role in realizing high-level benefits, while the low-level benefits are lacking; the capital-led type plays a significant role in realizing low-level benefits, while the high-level benefits are lacking. (4) Building a multi-party cooperation model with the collaboration of capital and artists, government support, and villagers' participation can combine the advantages of the benefits of the two modes and make the rural practice of art intervention more replicable. In summary, this study divides the practices of art intervention in rural China into two types: artist-led and capital-led, constructs the four-level benefits hierarchy based on Maslow's hierarchy of needs theory, compares the four-level benefits between Xiaozhou village and Fenghe village, and summarizes the benefit differences between the artist-led mode and the capital-led mode. For its contributions, it innovatively applies Maslow's hierarchy of needs theory into the study of art intervention from a theoretical perspective and enriches the case study of art intervention in rural China and explores the characteristics from a practical perspective.

Unraveling the structural origin of liquid anomalies remains a challenging topic. Xu et al. propose a folded-network structural model for molten tin and provide insights into the observed second-order-like structural transition.

Native crystallographic defects are often introduced during synthesis of battery materials, but has been overlooked. Here, using in situ synchrotron X-ray probes and electron microscopy, the authors have revealed their adverse effect during battery operation.

Summary: Tuberculous meningitis (TBM) is the most severe and deadly manifestation of tuberculosis. Neurological complications are observed in up to 50% of patients affected. Here, attenuated Mycobacterium bovis are injected into the cerebellum of mice, and histopathological images and cultured colonies confirm successful brain infection. Then, whole-brain tissue is dissected for 10X Genomics single-cell sequencing, and we acquire 15 cell types. Transcriptional changes of inflammation processes are found in multiple cell types. Specifically, Stat1 and IRF1 are shown to mediate inflammation in macrophages and microglia. For neurons, decreased oxidative phosphorylation activity in neurons is observed, which corresponds to TBM clinical symptoms of neurodegeneration. Finally, ependymal cells present prominent transcriptional changes, and decreased FERM domain containing 4A (Frmd4a) may contribute to TBM clinical symptoms of hydrocephalus and neurodegeneration. This study shows a single-cell transcriptome of M. bovis infection in mice and improves the understanding of brain infection and neurological complications in TBM.

Lactoferrin (Lf), existing widely in human and mammalian milk, is a multifunctional glycoprotein with many functions, such as immune regulation, anti-inflammation, antibacterial, antiviral, and antioxidant. These extensive functions largely attribute to its ability to chelate iron and interfere with the cellular receptors of pathogenic microorganisms and their hosts. Moreover, it is non-toxic and has good compatibility with other supplements. Thus, Lf has been widely used in food nutrition, drug carriers, biotechnology, and feed development. Although Lf has been continuously explored and studied, a more comprehensive and systematic compendium is still required. This review presents the recent advances in the structure and physicochemical properties of Lf as well as clinical studies on human diseases, with the aim of providing a reference for further research of Lf and the development of its related functional products.

Mechanical integrity issues are one of the main causes of limited long-term cycle stability for Ni-rich cathode materials. Here the authors analyse the roles of cobalt and manganese and utilise a concentration gradient design to mitigate these issues.

BackgroundVaping or e-cigarette use has become dramatically more popular in the United States in recent years. e-Cigarette and vaping use–associated lung injury (EVALI) cases caused an increase in hospitalizations and deaths in 2019, and many instances were later linked to unregulated products. Previous literature has leveraged social media data for surveillance of health topics. Individuals are willing to share mental health experiences and other personal stories on social media platforms where they feel a sense of community, reduced stigma, and empowerment. ObjectiveThis study aimed to compare vaping-related content on 2 popular social media platforms (ie, Twitter and Reddit) to explore the context surrounding vaping during the 2019 EVALI outbreak and to support the feasibility of using data from both social platforms to develop in-depth and intelligent vaping detection models on social media. MethodsData were extracted from both Twitter (316,620 tweets) and Reddit (17,320 posts) from July 2019 to September 2019 at the peak of the EVALI crisis. High-throughput computational analyses (sentiment analysis and topic analysis) were conducted. In addition, in-depth manual content analyses were performed and compared with computational analyses of content on both platforms (577 tweets and 613 posts). ResultsVaping-related posts and unique users on Twitter and Reddit increased from July 2019 to September 2019, with the average post per user increasing from 1.68 to 1.81 on Twitter and 1.19 to 1.21 on Reddit. Computational analyses found the number of positive sentiment posts to be higher on Reddit (P

Direction of arrival (DOA) estimation is an effective method for detecting various active interference signals during the satellite navigation process. It can be utilized for both interference detection and anti-interference applications. This paper proposes a DOA estimation algorithm for satellite interference sources based on frequency domain covariance matrix reconstruction (FDCMR) to address various types of active interference that may occur in the satellite navigation positioning process. This algorithm can estimate the DOA of coherent signals from multiple frequency points under low signal-to-noise ratio (SNR) conditions. The signals received from the array are transformed from the time domain to the frequency domain using a fast Fourier transform (FFT). The data corresponding to the frequency point of the target signal is extracted from the signal in the frequency domain. The frequency domain covariance matrix of the received array signals is reconstructed by utilizing its covariance matrix property. The spatial spectrum search method is used for the final DOA estimation. Simulation experiments have shown that the proposed algorithm performs well in the DOA estimation under low SNR conditions and also resolves coherency. Moreover, the algorithm’s effectiveness is verified through comparison with three other algorithms. Finally, the algorithm’s applicability is validated through simulations of various interference scenarios.

Electrochemical degradation is the most critical challenge for Li-rich materials. Here, the authors reveal that manganese related phase reaction inhomogeneity coupling with transition metal rearrangement triggers electrochemical degradation in lithium-rich layered cathode.

The role of the lithiated graphite anode in battery thermal runaway failure remains under intense investigation. In this work, with multiple in situ synchrotron X-ray characterizations, the phase evolution, gas release, and lithium leaching of lithiated graphite anode are illustrated in detail.

Advanced screening strategies for the design of high-entropy alloys are highly desirable. Here the authors use the project-oriented design strategy and CALPHAD-based high-throughput calculation tool to rapidly screen promising Al-Cr-Fe-Mn-Ti structural HEAs for high-temperature applications.

Zinc metal has a hexagonal close packing hcp structure with an unusual axial ratio c/a. This work presents the local atomic structure analysis of elemental zinc using the x-ray atomic pair distribution function (PDF) method and total synchrotron x-ray scattering in the temperature range of 100–300 K. In this PDF study, we determined the evolution of local bonding in zinc structure in the temperature range of 100–300 K by fitting the first two peaks in the radial distribution function (RDF), R(r), with two Gaussian peaks. Our local structure results reveal a piece of evidence for unusual bond length behavior at low temperatures. The PDF analysis revealed that the a-axis varies linearly from 300 to 160 K and remains constant below 160 K. This local structural result indicates that at temperatures below 160 K, the Zn–Zn bonds are no longer thermally contractible in the ab plane, in agreement with standard crystallographic analysis [J. Nuss et al., Z. Anorg. Allg. Chem. 636, 309 (2010)]. Another significant observation is that the local thermal expansion for the a-axis was found to be three times larger than the one obtained using conventional crystallographic methods [U. Wedig et al., Z. Anorg. Allg. Chem. 639, 2036 (2013)]. This PDF result shows the advantage of total scattering PDF methods in studying the local structural features in elemental zinc, which cannot be captured by the crystallographic model. In addition, this PDF study demonstrates that multiple RDF-peak fitting is a useful approach for interpreting the local structural features of such a non-ideal hcp structure.

Drought is the main abiotic stress limiting soybean production worldwide and seriously limits the reproductive growth of soybean. To elucidate the molecular mechanisms of drought stress response in soybean seed developmental stages, transcriptome analysis was performed on five seed developmental stages under drought stress and control conditions. Thousands of genes were found to change in expression level under drought stress, GO and KEGG enrichment analysis showed that differentially expressed genes (DEGs) were involved in drought resistance at every stage or tissue, but there were very few DEGs at the primary stage of seed development, which indicated that the seeds at the primary developmental stage were influenced little by drought stress. There was no shared DEG among all five stages or tissues, this indicated that they have different mechanisms to resist drought stress. Furthermore, we investigated DEGs associated with drought response at different stages to identify candidate regulators of drought stress response during soybean seed development. These genes are associated with metabolic and regulatory networks, among others. Taken together, the results will expand our understanding of the adaptation of soybean to drought stress and provide new insights into the molecular mechanisms of soybean drought tolerance development.