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ObjectiveThe objective of this scoping review was to explore, appraise and synthesize the current literature regarding the incidence, factors influencing, and prevention strategies related to suicide risk among nurses.MethodsAn extensive literature search was conducted using databases such as PubMed, Web of Science, Medline, and Embase from its formation to June 20, 2024, specifically focusing on the suicide-related behaviors of nurses written in Chinese or English. Two researchers independently screened the literature, and disagreements were debated until a consensus was reached. Data extraction was conducted for the studies that were included. The process of data synthesis was carried out using narrative analysis.ResultsThe study encompassed 40 papers from 15 different countries. This study found that nurses’ suicide ideation ranged from 4.3 to 44.58%, while suicide attempts ranged from 2.9 to 12.6%. Based on the stress-vulnerability model, factors influencing nurses’ suicide-related behaviors include vulnerability (personality traits, coping styles), stressors (mental disorders, workplace bullying, etc.) and protective factors (social support, resilience, etc.). The strategies for preventing nurse suicide encompass primary prevention (for all nurses), secondary prevention (for nurses at risk of suicide), and tertiary prevention (for nurses who have attempted suicide).ConclusionThe suicide rate among nurses exceeds that of the general population. Mental disorders and workplace bullying are significant stressors that contribute to nurse suicide. Suicide-related behaviors among nurses can be effectively prevented and managed through the implementation of the tertiary prevention strategies. Primary prevention is essential in reducing suicide. Cognitive exercises and schedule shifts reasonably are primary preventive measures tailored for nurses. This study addresses the gaps in influencing factors about suicide-related behaviors among nurses and the strategies for preventing suicide, and provides a complete review of the current situation of nurses’ suicide-related behaviors, providing references for the safe management of nurses’ suicide.

With the increasing demand for reducing CO2 emissions by the International Maritime Organization (IMO), controlling a ship's energy consumption at the design stage is crucial for proposing a 'greener' design. Some efforts have been made to consider the Energy Efficiency Design Index (EEDI) and the Energy Efficiency Operational Index (EEOI); however, the latter remains highly complex and contentious. In this study, a multistep optimization analysis method was developed to integrate EEDI and EEOI evaluations during the design stage to meet low emission requirements. Additionally, an Efficient Operational Scenario Analysis Method (EOSAM) was established to consider operational energy efficiency. This method was applied to optimize the hull and propulsor design of a pod-driven cruise ship. By accounting for operating conditions in both calm water and wave scenarios, and utilizing high-fidelity computational fluid dynamics simulations and model test validation, the delivered power was reduced by up to 7.1 % compared to the original design, and the EEOI decreased by an average of 16.7 %.

Traffic congestion prediction has become an indispensable component of an intelligent transport system. However, one limitation of the existing methods is that they treat the effects of spatio-temporal correlations on traffic prediction as invariable during modeling spatio-temporal features, which results in inadequate modeling. In this paper, we propose an attention-based spatio-temporal 3D residual neural network, named AST3DRNet, to directly forecast the congestion levels of road networks in a city. AST3DRNet combines a 3D residual network and a self-attention mechanism together to efficiently model the spatial and temporal information of traffic congestion data. Specifically, by stacking 3D residual units and 3D convolution, we proposed a 3D convolution module that can simultaneously capture various spatio-temporal correlations. Furthermore, a novel spatio-temporal attention module is proposed to explicitly model the different contributions of spatio-temporal correlations in both spatial and temporal dimensions through the self-attention mechanism. Extensive experiments are conducted on a real-world traffic congestion dataset in Kunming, and the results demonstrate that AST3DRNet outperforms the baselines in short-term (5/10/15 min) traffic congestion predictions with an average accuracy improvement of 59.05%, 64.69%, and 48.22%, respectively.

Abstract Vehicular edge computing (VEC) is emerging as a new computing paradigm to improve the quality of vehicular services and enhance the capabilities of vehicles. It enables performing tasks with low latency by deploying computing and storage resources close to vehicles. However, the traditional task offloading schemes only focus on one-shot offloading, taking less into consideration task dependency. Furthermore, the continuous action space problem during task offloading should be considered. In this paper, an efficient dependency-aware task offloading scheme for VEC with vehicle-edge-cloud collaborative computation is proposed, where subtasks can be processed locally or can be offloaded to an edge server, or a cloud server for execution. Specifically, first, the directed acyclic graph (DAG) is utilized to model the dependency of subtasks. Second, a task offloading algorithm based on Deep Deterministic Policy Gradient (DDPG) was proposed to obtain the optimal offloading strategy in a vehicle-edge-cloud environment, which efficiently solves the continuous control problem and helps reach fast convergence. Finally, extensive simulation experiments have been conducted, and the experimental results show that the proposed scheme can improve performance by about 13.62% on average against three baselines.

Temperature could change the migration characteristics of coastal groundwater. However, research on groundwater discharge processes under the influences of cut-off walls has been limited to isothermal conditions. This study built a two-dimensional numerical model coupling groundwater flow and salt transport in non-isothermal conditions at the site scale to investigate the impact of cut-off walls on groundwater discharge processes, considering the thermal effect. We focused on the dynamic characteristics of submarine groundwater discharge in non-isothermal conditions which are common in reality. This research quantitatively assessed the influence of seawater temperature on groundwater discharge flux (Q) and relative discharge flux (Q'). The results indicate that, under high-temperature seawater conditions, the timescale for Q' to reach equilibrium is significantly reduced. Specifically, higher freshwater temperatures and lower seawater temperatures could result in a greater Q'. However, when the seawater temperature exceeded the groundwater temperature by 15°C, reverse circulation is more likely to develop in the saltwater zone, which accelerates groundwater circulation and increases the total groundwater discharge into the sea, resulting in a corresponding rise in the Q' value. This study is significant for cut-off wall structure optimization and coastal groundwater sustainable utilization.

Naringenin is an essential precursor for all flavonoids, and effectively promoting naringenin production is crucial in metabolic engineering. The interaction between plant metabolic enzymes ensures metabolic flux. The effect can effectively improve the natural product synthesis of engineering microbial systems. In this study, chalcone isomerase genes in Allium fistulosum have been identified. The expression of AfCHIL is closely related to the accumulation of anthocyanins, and the expression of AfCHIL and AfCHS was highly synchronized. Yeast two-hybrid and firefly luciferase complementation imaging assay further confirmed AfCHIL physically interacted with AfCHS/AfCHI. The bioconversion experiment confirmed that AfCHIL reduced the derailment produced by AfCHS and increased the yield of naringenin. In addition, a system of biosynthesis naringenin involved in AfCHS was constructed, and these results suggested that the potential function between CHS with CHIL advanced naringenin production effectively. In conclusion, this study illustrated the function of AfCHIs in Allium fistulosum and provided new insight into improving the synthesis efficiency of naringenin.

Acetylserotonin methyltransferase (ASMT) in plant species, one of the most important enzymes in melatonin biosynthesis, plays a rate-limiting role in the melatonin production. In this study, based on the whole genome sequence, we performed a systematic analysis for the ASMT gene family in pepper (Capsicum annuum L.) and analyzed their expression profiles during growth and development, as well as abiotic stresses. The results showed that at least 16 CaASMT genes were identified in the pepper genome. Phylogenetic analyses of all the CaASMTs were divided into three groups (group I, group II, and group III) with a high bootstrap value. Through the online MEME tool, six distinct motifs (motif 1 to motif 6) were identified. Chromosome location found that most CaASMT genes were mapped in the distal ends of the pepper chromosomes. In addition, RNA-seq analysis revealed that, during the vegetative and reproductive development, the difference in abundance and distinct expression patterns of these CaASMT genes suggests different functions. The qRT-PCR analysis showed that high abundance of CaASMT03, CaASMT04, and CaASMT06 occurred in mature green fruit and mature red fruit. Finally, using RNA-seq and qRT-PCR technology, we also found that several CaASMT genes were induced under abiotic stress conditions. The results will not only contribute to elucidate the evolutionary relationship of ASMT genes but also ascertain the biological function in pepper plant response to abiotic stresses.

Transcriptome analysis is an efficient way to explore molecular markers in plant species, for which genome sequences have not been published. To address the limited number of markers published for the Welsh onion, this study found 6486 loci of genic simple sequence repeats (SSR), which consisted of 1–5 bp repeat motifs, based on next-generation sequencing (NGS) technology and the RNA-Seq approach. The most abundant motif was mononucleotide (52.33%), followed by trinucleotide (31.96%), and dinucleotide (14.57%). A total of 2525 primer pairs were successfully designed, and 91 out of 311 tested primers were polymorphisms. Overall, 38 genic SSR markers were randomly selected to further validate the degree of genetic diversity, and 22 genic SSR markers (57.89%) showed high levels of polymorphism. The average polymorphism information content (PIC) value and the number of alleles (Na) were 0.63 and 5.27, respectively, and the unweighted pair-group method with arithmetic average (UPGMA) cluster analysis grouped the 22 Allium accessions into three groups with Nei’s similarity coefficients ranging from 0.37 to 0.99. This result suggested that these genic SSR markers could be used to develop a higher resolution genetic map and/or to analyze the phylogenetic relationships among Allium plants in the near future.

The invertase gene family in plants is composed of two subfamilies of enzymes, namely, acid- and neutral/alkaline invertases (cytosolic invertase, CIN). Both can irreversibly cleave sucrose into fructose and glucose, which are thought to play key roles in carbon metabolism and plant growth. CINs are widely found in plants, but little is reported about this family. In this paper, a comparative genomic approach was used to analyze the CIN gene family in Solanum, including Solanum tuberosum, Solanum lycopersicum, Solanum pennellii, Solanum pimpinellifolium, and Solanum melongena. A total of 40 CINs were identified in five Solanum plants, and sequence features, phylogenetic relationships, motif compositions, gene structure, collinear relationship, and expression profile were further analyzed. Sequence analysis revealed a remarkable conservation of CINs in sequence length, gene number, and molecular weight. The previously verified four amino acid residues (D188, E414, Arg430, and Ser547) were also observed in 39 out of 40 CINs in our study, showing to be deeply conserved. The CIN gene family could be distinguished into groups α and β, and α is further subdivided into subgroups α1 and α2 in our phylogenetic tree. More remarkably, each species has an average of four CINs in the α and β groups. Marked interspecies conservation and collinearity of CINs were also further revealed by chromosome mapping. Exon−intron configuration and conserved motifs were consistent in each of these α and β groups on the basis of in silico analysis. Expression analysis indicated that CINs were constitutively expressed and share similar expression profiles in all tested samples from S. tuberosum and S. lycopersicum. In addition, in CIN genes of the tomato and potato in response to abiotic and biotic stresses, phytohormones also performed. Overall, CINs in Solanum were encoded by a small and highly conserved gene family, possibly reflecting structural and functional conservation in Solanum. These results lay the foundation for further expounding the functional characterization of CIN genes and are also significant for understanding the evolutionary profiling of the CIN gene family in Solanum.