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Vehicle-to-Everything (V2X) has become a key technology for addressing intelligent transportation challenges. Improving spectrum utilization and mitigating multi-user interference among V2X links are currently the primary focuses of research efforts. However, the time-varying nature of channel resources and the dynamic vehicular environment pose significant challenges to achieving high spectral efficiency and low interference. Numerous studies have demonstrated the effectiveness of deep reinforcement learning (DRL) in distributed resource allocation for vehicular networks. Nevertheless, in conventional distributed DRL frameworks, the independence of agent decisions often weakens cooperation among agents, thereby limiting the overall performance potential of the algorithms. To address this limitation, this paper proposes a state-aware communication resource allocation algorithm for vehicular networks. The proposed approach enhances the representation capability of observable data by expanding the state space, thus improving the utilization of available observations. Additionally, a conditional attention mechanism is introduced to strengthen the model’s perception of environmental dynamics. These innovative improvements significantly enhance each agent’s awareness of the environment and promote effective collaboration among agents. Simulation results verify that the proposed algorithm effectively improves agents’ environmental perception and inter-agent cooperation, leading to superior performance in complex and dynamic V2X scenarios.

With the integration of renewable energy into traction power supply systems at a high proportion and penetration level, the intermittency and randomness of renewable energy output significantly intensify the fluctuation characteristics of traction loads, posing severe challenges to the stable operation and precise dispatch of the system. To effectively address the dynamic tracking and anti-disturbance issues arising from the dual uncertainties of source and load, this paper proposes a dual-timescale two-layer optimization dispatch strategy based on Model Predictive Control (MPC). In the upper-layer optimization, with the objective of optimal system economic operation, a multi-step rolling optimization method is adopted to formulate a long-timescale baseline dispatch plan, fully considering the temporal correlation of photovoltaic and wind power outputs and the periodic characteristics of traction loads. In the lower-layer optimization, aimed at smoothing power fluctuations and correcting prediction deviations, the technical advantages of supercapacitors—high power density and fast response—are utilized to perform real-time tracking and dynamic compensation of the upper-layer baseline plan. This effectively reduces the impact of prediction errors on control accuracy, achieves smooth control of tie-line power, and enhances overall system stability. Case study results based on an actual railway traction power supply system demonstrate that the proposed method can fully leverage the coordinated and complementary characteristics of the hybrid energy storage system, effectively suppress power fluctuations from renewable energy output and traction loads, and achieve economic operation objectives while ensuring system disturbance rejection performance, thereby validating the effectiveness and practicality of the strategy.

Oat ( L.) is an important cereal crop grown worldwide for grain and forage, owing to its high adaptability to diverse environments. However, the genetic and genomics research of oat is lagging behind that of other staple cereal crops. In this study, a collection of 288 oat lines originating worldwide was evaluated using 2,213 single nucleotide polymorphism (SNP) markers obtained from an oat iSelect 6K-beadchip array to study its genetic diversity, population structure, and linkage disequilibrium (LD) as well as the genotype-phenotype association for hullessness and lemma color. The average gene diversity and polymorphic information content (PIC) were 0.324 and 0.262, respectively. The first three principal components (PCs) accounted for 30.33% of the genetic variation, indicating that the population structure of this panel of oat lines was stronger than that reported in most previous studies. In addition, accessions could be classified into two subpopulations using a Bayesian clustering approach, and the clustering pattern of accessions was closely associated with their region of origin. Additionally, evaluation of LD decay using 2,143 mapped markers revealed that the intrachromosomal whole-genome LD decayed rapidly to a critical r value of 0.156 for marker pairs separated by a genetic distance of 1.41 cM. Genome-wide association study (GWAS) detected six significant associations with the hullessness trait. Four of these six markers were located on the Mrg21 linkage group between 194.0 and 205.7 cM, while the other two significant markers mapped to Mrg05 and Mrg09. Three significant SNPs, showing strong association with lemma color, were located on linkage groups Mrg17, Mrg18, and Mrg20. Our results discerned relevant patterns of genetic diversity, population structure, and LD among members of a worldwide collection of oat landraces and cultivars proposed to be 'typical' of the Qinghai-Tibetan Plateau. These results have important implications for further studies on association mapping and practical breeding in high-altitude oat.

Introduction Cerebral venous sinus thrombosis (CVST) is an uncommon cerebrovascular disease with diverse predisposing factors. We report a case of CVST caused by a thyroid storm induced by traumatic brain injury. Case presentation A 29-year-old male patient with a history of Graves’ disease with hyperthyroidism presented to our hospital with head trauma of cerebral contusion and laceration in both frontal lobes confirmed by admission CT scan. He received mannitol to lower intracranial pressure, haemostatic therapy, and antiepileptic treatment. Eight days later, he presented with signs of thyroid storms, such as tachycardia, hyperthermia, sweating and irritation, and his thyroid function tests revealed high levels of TPO-Ab, TR-Ab, TG-Ab, FT3 and FT4. Then, he entered a deep coma. His brain CT showed a thrombosis of multiple venous sinuses, along with the opening of peripheral collateral vessels, congestive infarction with haemorrhage and brain swelling. He regained consciousness after treatment with antithyroid drugs, anticoagulants, respiratory support and a regimen of sedation/analgesia. After a half-year follow-up, most of the patient’s blocked cerebral venous sinuses had been recanalized, but there were still some sequelae, such as an impaired fine motor performance of the right hand and verbal expression defects. Conclusions CVST can be induced by thyroid storms, and trauma-related thyroid storms can develop on the basis of hyperthyroidism. The purpose of this case report is to raise clinicians’ awareness and improve their ability to diagnose CVST early in patients with traumatic brain injury complicating thyroid storms to improve the neurological prognosis among similar patients.

To understand the molecular mechanism controlling the size of barley grains, a number of traits were analyzed and RNA-seq was conducted on grains of two barley materials with a significant difference in thousand-grain weight (TGW) after flowering. The trait dataset delineates the dynamic changes in grain size after flowering, and it provides an understanding of the source of the difference in TGW. By comparing the transcripts of barley grains at several stages after flowering, we identified the gene expression characteristics and significantly enriched pathways in each stage. At the early stage of grain development, genes involved in fatty acid metabolism, plant hormone signal transduction, and pathways involved in cytoskeleton formation were significantly upregulated. At the later stage of grain development, genes involved in starch synthesis, glucose metabolism, and other pathways were significantly upregulated. Further, we used weighted gene coexpression network analysis (WGCNA) and correlation analysis of trait datasets to identify the coexpressed gene modules significantly associated with traits, such as grain length (GL), grain width (GW), and dry weight (DW). After comparing the modules with the differentially expressed gene (DEG) set, 12 candidate genes were selected, and among these, four genes were homologous to genes that regulate grain size in rice and other plants. The combined analysis identified many potential key regulatory factors that may control barley grain size and yield potential, thus providing new insights into the molecular mechanism of barley grain size.

A core collection reflects the diversity of the larger germplasm collection and makes the evaluation of genetic resources more effective. To improve barley germplasm management, we propose the construction of a core genetic collection derived from a set of 204 six-rowed hulless barley accessions (39 registered cultivars and 165 landraces) native to the Qinghai-Tibetan Plateau (QTP). A sampling percentage of 20% was predicted by the maximization strategy. Five different sampling strategies (Mstrat, Random, REMC, SBS, and SFS) were applied to establish 5 primary core collections from the original 204 accessions using 1750 single-nucleotide polymorphism (SNP) markers. After the evaluation and analysis of core collection representativeness, the Mstrat strategy was determined to be a valid method for developing a core collection. A total of 41 barley accessions were obtained, including 11 registered cultivars and 30 landraces. Genetic structure analysis of the 204 barley accessions showed that the core collection was evenly distributed throughout the initial collection, indicating that the core collection represented the larger germplasm well. A subset of 28 SNP markers were produced and used to distinguish all 204 barley accessions from each other. We believe the collection of 28 SNP markers will be incredibly helpful to barley breeders. Furthermore, the core collection ensures the long-term conservation of genetic resources and will support improvements to six-rowed hulless barley from the Qinghai-Tibetan Plateau.

The EARLY MATURITY 8 (EAM8) gene of barley is homologous to the EARLY FLOWERING 3 (ELF3) gene in Arabidopsis, as loss-of-function mutations in this circadian clock gene promote rapid flowering. A previous study demonstrated that the early flowering phenotype of a hulless barley, Lalu, was due to allele eam8.l carrying an alternative splicing mutation in intron 3 that led to intron retention. In the present study, we verified that eam8.l encoded a truncated protein. Although EAM8 was expressed at a higher level in Lalu than in other barley lines with a longer growth period, it did not negatively regulate flowering time. This result further proved that the eam8.l protein was nonfunctional in regulating flowering in barley. The early flowering phenotype of Lalu plants was strongly dependent on the biosynthesis of gibberellin (GA). The eam8.l mutation stopped the suppression of GA biosynthesis, and Lalu accumulated excessive GA, especially in leaves. This was achieved through the upregulated expression of genes in the GA pathway, including GA20ox2, LFY1, SOC1, PAP2, and FPF3. The mutation of the EAM8 gene also abolished the inhibition of FLOWERING LOCUS T-like (FT1) gene expression at night. During the night, expression levels of the FT1 gene were higher than those during the day in Lalu. However, the GA-dependent pathway and FT1 gene mechanism are two independent pathways that promote flowering in Lalu. Alleles of EAM8, therefore, demonstrated an important breeding value in barley, which is probably effective in many other day-length-sensitive crop plants as well; thus, they could be used to tune adaptation in different geographic regions and climatic conditions, a critical issue in times of global warming.

Avena chinensis is recognized as one of the cereals with high nutritional value in the world. In this study, the complete chloroplast (cp) genome sequence of A. chinensis was reported. The complete cp genome of A. chinensis was 135,899 bp in length with a GC content of 38.51%, including a large single copy (LSC) region of 80,117 bp, a small single copy (SSC) region of 12,576 bp, and a pair of inverted repeated regions of 21,603 bp. The A. chinensis cp genome encoded 128 functional genes, including 82 protein-coding genes, 38 tRNAs, and eight rRNAs. The phylogenetic analysis showed that A. chinensis was closely related to Avena hybrid and Avena occidentalis.

Key message Three computationally efficient algorithms of GP including RHBK, RHDK, and RHPK were developed in approximate genome-based kernel model. The drastically growing amount of genomic information contributes to increasing computational burden of genomic prediction (GP). In this study, we developed three computationally efficient algorithms of GP including RHBK, RHDK, and RHPK in approximate genome-based kernel model, which reduces dimension of genomic data via Nyström approximation and decreases the computational cost significantly thereby. According to the simulation study and real datasets, our three methods demonstrated predictive accuracy similar to or better than RHAPY, GBLUP, and rrBLUP in most cases. They also demonstrated a substantial reduction in computational time compared to GBLUP and rrBLUP in simulation. Due to their advanced computing efficiency, our three methods can be used in a wide range of application scenarios in the future.

Understanding the local adaptation of crops has long been a concern of evolutionary biologists and molecular ecologists. Identifying the adaptive genetic variability in the genome is crucial not only to provide insights into the genetic mechanism of local adaptation but also to explore the adaptation potential of crops. This study aimed to identify the climatic drivers of naked barley landraces and putative adaptive loci driving local adaptation on the Qinghai-Tibetan Plateau (QTP). To this end, a total of 157 diverse naked barley accessions were genotyped using the genotyping-by-sequencing approach, which yielded 3123 high-quality SNPs for population structure analysis and partial redundancy analysis, and 37,636 SNPs for outlier analysis. The population structure analysis indicated that naked barley landraces could be divided into four groups. We found that the genomic diversity of naked barley landraces could be partly traced back to the geographical and environmental diversity of the landscape. In total, 136 signatures associated with temperature, precipitation, and ultraviolet radiation were identified, of which 13 had pleiotropic effects. We mapped 447 genes, including a known gene HvSs1. Some genes involved in cold stress and regulation of flowering time were detected near eight signatures. Taken together, these results highlight the existence of putative adaptive loci in naked barley on QTP and thus improve our current understanding of the genetic basis of local adaptation.