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Thermal safety is one of the major issues for lithium‐ion batteries (LIBs) used in electric vehicles. The thermal runaway mechanism and process of LIBs have been extensively studied, but the thermal problems of LIBs remain intractable due to the flammability, volatility and corrosiveness of organic liquid electrolytes. To ultimately solve the thermal problem, all‐solid‐state LIBs (ASSLIBs) are considered to be the most promising technology. However, research on the thermal stability of solid‐state electrolytes (SEs) is still in its initial stage, and the thermal safety of ASSLIBs still needs further validation. Moreover, the specified reviews summarizing the thermal stability of ASSLIBs and all types of SEs are still missing. To fill this gap, this review systematically discussed recent progress in the field of thermal properties investigation for ASSLIBs, form levels of materials and interface to the whole battery. The thermal properties of three major types of SEs, including polymer, oxide, and sulfide SEs are systematically reviewed here. This review aims to provide a comprehensive understanding of the thermal stability of SEs for the benign development of ASSLIBs and their promising application under practical operating conditions. Thermal failure is a serious issue for liquid‐electrolyte‐based lithium‐ion batteries, and substituting liquid electrolytes with solid‐state electrolytes is expected to solve this problem. This review summarizes the thermal stability of polymers, oxides, sulfides, and other solid‐state electrolytes from the level of material, interface, and battery, and points out the limitations and future of thermal stability studies in solid‐state batteries.

All-solid-state batteries (ASSBs) with Li metal anodes or Si anodes are promising candidates to achieve high energy density and improved safety, but they suffer from undesirable lithium dendrite growth or huge volume expansion, respectively. Here we synthesize a hard-carbon-stabilized Li–Si alloy anode in which sintering of Si leads to the transformation of micro-metre particles into dense continuum. A 3D ionic-electronic-conductive network composed of plastically deformable Li-rich phases (Li 15 Si 4 and LiC 6 ) that enlarges active area and relieves stress concentration is created in the anode, leading to improved electrode kinetics and mechanical stability. With the hard-carbon-stabilized Li-Si anode, full cells using LiCoO 2 or LiNi 0.8 Co 0.1 Mn 0.1 O 2 cathodes and Li 6 PS 5 Cl electrolyte achieve favourable rate capability and cycle stability. In particular, the ASSB with LiNi 0.8 Co 0.1 Mn 0.1 O 2 at high loading of 5.86 mAh cm −2 delivers 5,000 cycles at 1 C (5.86 mA cm −2 ), demonstrating the potential of using hard-carbon-stabilized Li–Si alloy anodes for practical applications of ASSBs. Si anodes could be an alternative to Li anodes in the application of solid-state batteries, but they suffer from issues such as severe volume expansion and sluggish kinetics. Here the researchers develop a Li–Si alloy anode that is stabilized by hard carbon, which leads to exceptional high-performance solid-state batteries.

All‐solid‐state batteries (ASSBs) have been widely acknowledged as the key next‐generation energy storage technology/device, due to their high safety and energy density. Among all solid electrolytes (SEs) that have been studied for ASSBs, sulfide SEs represent the most promising technical route due to their ultra‐high ionic conductivity and desirable mechanical property. However, few results have been reported to study the thermal stability/safety issue of sulfide SEs and ASSBs. Herein, we develop the first‐of‐its‐kind theoretical paradigm and a new conceptual parameter Th to quantitatively calculate/predict the essential thermal stability of sulfide SEs. This theoretical paradigm takes all types of parameters (e.g. crystal structure, localized polyhedra configuration, bond energy, bond type, bond number, normalization factor, and the energy correction factor) into consideration, and more importantly, can be simplified into one straightforward equation for its convenient application in any crystalline systems. To prove its functionality, the typical experimental strategies (stoichiometric ratio control and elemental doping) are adopted for typical sulfide SEs (Li7P3S11, Li3PS4) to improve their thermal stabilities, based on the predictions obtained from the derived theory and equation. Moreover, the potential doping elements to improve thermal stability of sulfide SEs are screened throughout the whole periodic table, and the theoretically predicted trends correspond well with experimental evidence. This work may represent the most critical breakthroughs in the research field of thermal stability for sulfide SEs, not only because it fills the gap of this field, but also due to its precise and quantitative prediction based on a complete consideration of all parameters that determine their thermal stabilities. The handy model developed herein can also be applied to any crystalline materials. The first‐of‐its‐kind theoretical paradigm and new conceptual parameter Th to quantitatively calculate/predict the essential thermal stability of sulfide SEs are proposed for the first time and ed into the above figure. Their thermal stability and microscopic structure relationships are summarized as linear rules involving factors such as the structure, chemical bonding, and energy correction factor k. Moreover, the thermal stability of typical sulfide SEs (Li7P3S11, Li3PS4) is successfully improved through the typical experimental strategies (stoichiometric ratio control and elemental doping).

The Internet of Vehicles plays a crucial role in advancing intelligent transportation systems, with In-Vehicle Ethernet serving as the fundamental backbone network of the new generation of in-vehicle communication. However, In-Vehicle Ethernet faces various network security threats, including data theft, data tampering, and malicious attacks. This study focuses on network intrusion and security issues in In-Vehicle Ethernet, by analyzing the data characteristics of Audio Video Transport Protocol and potential network attack means. We innovatively propose a network intrusion detection method based on a weighted histogram algorithm. This method aims to enhance the security of In-Vehicle Ethernet. Experimental results show that the anomaly detection rate of the proposed weighted histogram algorithm in this study is 99.7%, which shows an improvement of 15.8% compared with the traditional Bayesian algorithm, and 6.9% higher than the decision tree algorithm. Thus, our approach enhances the stability and anti-attack ability of In-Vehicle Ethernet, providing a solid network security for In-Vehicle Networks.

With the integration of an increasing number of outward-facing components in intelligent and connected vehicles, the open controller area network (CAN) bus environment faces increasingly severe security threats. However, existing security measures remain inadequate, and CAN bus messages lack effective security mechanisms and are vulnerable to malicious attacks. Although encryption algorithms can enhance system security, their high bandwidth consumption negatively impacts the real-time performance of intelligent and connected vehicles. Moreover, the message authentication mechanism of the CAN bus requires lengthy authentication codes, further exacerbating the bandwidth burden. To address these issues, we propose an improved dynamic compression algorithm that achieves higher compression rates and efficiency by optimizing header information processing during data reorganization. Additionally, we have proposed a novel dynamic key management approach, incorporating a dynamic key distribution mechanism, which effectively resolves the challenges associated with key management. Each Electronic Control Unit (ECU) node independently performs compression, encryption, and authentication while periodically updating its keys to enhance system security and strengthen defense capabilities. Experimental results show that the proposed dynamic compression algorithm improves the average compression rate by 2.24% and enhances compression time efficiency by 10% compared to existing solutions. The proposed security protocol effectively defends against four different types of attacks. In hardware tests, using an ECU operating at a frequency of 30 MHz, the computation time for the security algorithm on a single message was 0.85 ms, while at 400 MHz, the computation time was reduced to 0.064 ms. Additionally, for different vehicle models, the average CAN bus load rate was reduced by 8.28%. The proposed security mechanism ensures the security, real-time performance, and freshness of CAN bus messages while reducing bus load, providing a more efficient and reliable solution for the cybersecurity of intelligent and connected vehicles.

With the rapid development of intelligent driving technology, in-vehicle bus networks face increasingly stringent requirements for real-time performance and data transmission. Traditional bus network technologies such as LIN, CAN, and FlexRay are showing significant limitations in terms of bandwidth and response speed. In-Vehicle Ethernet, with its advantages of high bandwidth, low latency, and high reliability, has become the core technology for next-generation in-vehicle communication networks. This study focuses on bandwidth waste caused by guard bands and the limitations of Frame Pre-Emption in fully utilizing available bandwidth in In-Vehicle Ethernet. It aims to optimize TSN scheduling mechanisms by enhancing scheduling flexibility and bandwidth utilization, rather than modeling system-level vehicle functions. Based on the Time-Sensitive Networking (TSN) protocol, this paper proposes an innovative Adaptive Frame Segmentation (AFS) algorithm. The AFS algorithm enhances the performance of In-Vehicle Ethernet message transmission through flexible frame segmentation and efficient message scheduling. Experimental results indicate that the AFS algorithm achieves an average local bandwidth utilization of 94.16%, improving by 4.35%, 5.65%, and 30.48% over Frame Pre-Emption, Packet-Size Aware Scheduling (PAS), and Improved Qbv algorithms, respectively. The AFS algorithm demonstrates stability and efficiency in complex network traffic scenarios, reducing bandwidth waste and improving In-Vehicle Ethernet’s real-time performance and responsiveness. This study provides critical technical support for efficient communication in intelligent connected vehicles, further advancing the development and application of In-Vehicle Ethernet technology.

Background Fusobacterium nucleatum ( F. nucleatum ) belongs to the genus Fusobacterium, which is a gram-negative obligate anaerobic bacterium. Bacteremia associated with F. nucleatum is a serious complication, which is not common in clinic, especially when it is combined with other intracranial pathogenic microorganism infection. We reported for the first time a case of F. nucleatum bacteremia combined with intracranial Porphyromonas gingivalis ( P. gingivalis ) and herpes simplex virus type 1 ( HSV-1 ) infection. Case presentation A 60-year-old woman was admitted to our hospital with a headache for a week that worsened for 2 days. Combined with history, physical signs and examination, it was characterized as ischemic cerebrovascular disease (ICVD). F. nucleatum was detected in blood by matrix-assisted laser desorption/ionization time-offight mass spectrometry (MALDI-TOF-MS). Meanwhile, P. gingivalis and HSV-1 in cerebrospinal fluid (CSF) were identified by metagenome next generation sequencing (mNGS). After a quick diagnosis and a combination of antibiotics and antiviral treatment, the patient recovered and was discharged. Conclusion To our knowledge, this is the first report of intracranial P. gingivalis and HSV-1 infection combined with F. nucleatum bacteremia.

Policy guidance plays a critical role in urban expansion and development patterns, and the scientific prediction of land use change trends and the assessment of the ecological benefits of future urban development are essential for effective policy-making. Different urban development policies not only shape the evolution of urban spatial patterns but also have a profound impact on the urban heat island effect (UHI) and cooling benefits. This study explores the impact of land use changes in Tianfu New District on the UHI and conducts multi-scenario simulations combined with different policy contexts. Focusing on Tianfu New District, four scenarios were selected: the Natural Development Scenario (ND), Economic Development Scenario (ED), Sustainable Development Scenario (SD), and Cropland Protection Scenario (CLP). To assess the impact of land use changes on the heat island effect, the study also used the InVEST urban cooling model (UCM) to evaluate the heat island mitigation effects under different scenarios. The results show that (1) the land use changes in Tianfu New District primarily went through three major stages: the natural ecological stage dominated by bare land, the rapid urbanization expansion stage, and the ecological restoration stage. (2) Under different scenarios, the land use changes differed significantly in their ability to mitigate the heat island effect. Both the Economic Development Scenario (ED) and Natural Development Scenario (ND) showed a weakening of cooling effects compared to the 2024 baseline, while the Sustainable Development Scenario (SD) and Cropland Protection Scenario (CLP) enhanced the region’s cooling capacity to some extent. Rational land use planning can promote economic development, and it can also play an important role in addressing climate change and mitigating the heat island effect. Future urbanization processes should pay more attention to integrating ecological protection and cooling strategies to ensure the achievement of sustainable development goals. This study provides scientific evidence for land use planning and policy-making in Tianfu New District and similar regions.

Plants have evolved sophisticated mechanisms to regulate gene expression to activate immune responses against pathogen infections. However, how the translation system contributes to plant immunity is largely unknown. The evolutionarily conserved thiolation modification of transfer RNA (tRNA) ensures efficient decoding during translation. Here, we show that tRNA thiolation is required for plant immunity in Arabidopsis . We identify a cgb mutant that is hyper-susceptible to the pathogen Pseudomonas syringae. CGB encodes ROL5, a homolog of yeast NCS6 required for tRNA thiolation. ROL5 physically interacts with CTU2, a homolog of yeast NCS2. Mutations in either ROL5 or CTU2 result in loss of tRNA thiolation. Further analyses reveal that both transcriptome and proteome reprogramming during immune responses are compromised in cgb . Notably, the translation of salicylic acid receptor NPR1 is reduced in cgb , resulting in compromised salicylic acid signaling. Our study not only reveals a regulatory mechanism for plant immunity but also uncovers an additional biological function of tRNA thiolation.

Neuromyelitis optica spectrum disorders (NMOSD) is a rare autoimmune disorder that causes severe inflammation in the central nervous system (CNS), primarily affecting the optic nerves, spinal cord, and brainstem. Aquaporin-4 immunoglobulin G antibodies (AQP4-IgG) are a diagnostic marker of the disease and play a significant role in its pathogenesis, though the exact mechanism is not yet fully understood. To develop rodent models that best simulate the in vivo pathological and physiological processes of NMOSD, researchers have been continuously exploring how to establish the ideal model. In this process, two key issues arise: 1) how the AQP4 antibody crosses the blood-brain barrier, and 2) the source of the AQP4 antibody. These two factors are critical for the successful development of rodent models of NMOSD. This paper reviews the current state of research on these two aspects.