Search Results (296)

Multi-hop routing over low-power wide-area networks (LPWANs) has emerged as a promising technology for extending network coverage. However, existing protocols face high transmission disruption risks due to factors such as dynamic topology driven by stochastic events, dynamic link quality, and coverage holes induced by imbalanced energy consumption. To address this issue, we propose a failure risk-aware deep Q-network-based multi-hop routing (FRDR) protocol, aiming to reduce transmission disruption probability. First, we design a power regulation mechanism (PRM) that works in conjunction with pre-selection rules to optimize end-device node (EN) activations and candidate relay selection. Second, we introduce the concept of routing failure risk value (RFRV) to quantify the potential failure risk posed by each candidate next-hop EN, which correlates with its neighborhood state characteristics (i.e., the number of neighbors, the residual energy level, and link quality). Third, a deep Q-network (DQN)-based routing decision mechanism is proposed, where a multi-objective reward function incorporating RFRV, residual energy, distance to the gateway, and transmission hops is utilized to determine the optimal next-hop. Simulation results demonstrate that FRDR outperforms existing protocols in terms of packet delivery rate and network lifetime while maintaining comparable transmission delay. Full article

Sarcomyxa edulis is a characteristic low-temperature, edible mushroom in Northeast China. It has a delicious taste and rich nutritional and medicinal value. S. edulis can undergo explosive fruiting, neat fruiting, and unified harvesting, making it suitable for factory production. The molecular mechanisms underlying fruiting body development in S. edulis remain poorly understood. This study employed transcriptome analysis to compare the post-ripening mycelium (NPM) and primordial fruiting bodies (PRMs) of the thermostable S. edulis strain PQ650759, which uniquely forms primordia under constant temperature. A total of 4862 differentially expressed genes (DEGs) (|log2(fold change)| ≥ 1) were identified and found to be predominantly enriched in biological processes such as cell wall organization, DNA replication, and carbohydrate metabolism. KEGG pathway analysis revealed significant enrichment in 20 metabolic pathways, including mismatch repair, yeast cell cycle, and starch/sucrose metabolism. Ten candidate genes (e.g., SKP1, MRE11, GPI) linked to cell cycle regulation, DNA repair, and energy metabolism were randomly selected and prioritized for functional analysis. Quantitative PCR validation confirmed the reliability of transcriptome data, with expression trends consistent across both methods. Our findings provide critical insights into the molecular regulation of fruiting body development in S. edulis and establish a foundation for future mechanistic studies and strain optimization in industrial cultivation. Full article

The Spodoptera litura, a Lepidopteran pest known for its high fecundity, undergoes a complete metamorphosis, including a distinctive process during which the male testes fuse from two separate organs into a single entity, significantly enhancing its fertility. To elucidate the molecular mechanisms underlying this testicular fusion, this study employed an integrated multi-omics approach to investigate concurrent changes at the transcriptomic and proteomic levels. We identified a series of synchronized alterations on the peritestic larval membrane, including heme binding, peptidase activity, hydrolase activity, metal ion transport, redox reactions, and chitin metabolism, all of which are substantially enriched at specific temporal points during testicular fusion. Nine genes/proteins co-expressed at the mRNA and protein levels were selected for targeted quantitative proteomics (PRM) and quantitative PCR (qPCR) validation, leading to the identification of five genes potentially involved in the testicular fusion process: Sl3030, ARCP, PSLRE, Obstructor-E, and Osris9B. Notably, the gene Sl3030, once knocked out, not only disrupted the normal fusion process but also resulted in reduced testis size, thickened peritestic membranes, and abnormal sperm development. Transcriptomic sequencing of the Sl3030 knockout mutant revealed its primary influence on the fusion process by affecting the assembly of the microtubule system and cytoskeleton. This research, for the first time, provides a multi-omics perspective on the response of key signaling pathways and molecular changes during the testicular fusion of S. litura and validates the role of the previously uncharacterized gene Sl3030 in this process, offering valuable insights into the complex mechanisms of testicular fusion in this species. Full article

Proton-Exchange-Membrane Fuel Cell (PEMFC) systems are proving to be a promising solution for decarbonizing various means of transport, especially heavy ones. However, their reliability, availability, performance, durability, safety and operating costs are not yet fully competitive with industrial and commercial systems (actual systems). Predictive maintenance (PrM) is proving to be one of the most promising solutions for improving these critical points. In this paper, several PrM approaches will be developed considering the constraints of actual systems. The first approach involves estimating the overall State of Health (SOH) of a PEMFC operating under a dynamic load according to an FC-DLC (Fuel Cell Dynamic Load Cycle) profile, using a Health Indicator (HI). This section will also discuss the relevance of current End-of-Life (EoL) indicators by putting the performance, safety and economic profitability of PEMFC systems into perspective. The second approach involves predicting the voltage of the PEMFC while operating under this same profile in order to estimate its overall Remaining Useful Life (RUL). Finally, the last approach proposed will make it possible to estimate the time when it will be worthwhile, or even economically necessary, to replace a degraded PEMFC with a new one. Full article

In the context of coal mine operations, the assurance of work safety relies heavily on efficient autonomous navigation for rescue robots, yet traditional path planning algorithms such as A and RRT exhibit significant deficiencies in a coal mine environment. Traditional path planning algorithms (such as Dijkstra and PRM) have certain deficiencies in dynamic Spaces and narrow environments. For example, the Dijkstra algorithm has A relatively high computational complexity, the PRM algorithm has poor adaptability in real-time obstacle avoidance, and the A* algorithm is prone to generating redundant nodes in complex terrains. In recent years, research on underground mine scenarios has also pointed out that there are many difficulties in the integration of global planning and local planning. This paper proposes an enhanced A* algorithm in conjunction with the Dynamic Window Approach (DWA) to enhance the efficiency, search accuracy, and obstacle avoidance capability of path planning by optimizing the target function and eliminating redundant nodes. This approach enables path smoothing to be performed. In order to ensure that the requirement of multiple target point detection is realized, an RRT algorithm is proposed to reduce the element of randomness and uncertainty in the path planning process, leading to an increase in the convergence rate and overall performance of the algorithm. The solution to the problem of determining the global optimal path is proposed to be simplified by means of the optimal path planning algorithm based on the gradient coordinate rotation method. In this study, we not only focus on the efficiency of mobile robot path planning and real-time dynamic obstacle avoidance capabilities but also pay special attention to the symmetry of the final path. The findings of simulation experiments conducted within the MATLAB environment demonstrate that the proposed algorithm exhibits a substantial enhancement in terms of three key metrics: path planning time, path length, and obstacle avoidance efficiency, when compared with conventional methodologies. This study provides a theoretical foundation for the autonomous navigation of mobile robots in coal mines. Full article

Dengue virus (DENV) threatens public health, especially in regions with tropical and subtropical climates. In 2024, the World Health Organisation reported 3.4 million confirmed dengue cases, with 16,000 severe cases and 3000 dengue-associated fatalities. The first licensed dengue vaccine, CYD-TDV (Dengvaxia^®,Sanofi-Pasteur, Paris, France), is recommended by the WHO only for individuals aged 9–45 years with a prior history of dengue infection. However, being vaccinated with Dengvaxia^® increases the risk of developing severe dengue infections in seronegative individuals. Recently, a second licensed dengue vaccine, Qdenga^®,Takeda, Singen, Germany), was approved and recommended by the WHO to be administered only in highly dengue-endemic countries, as it was not shown to elicit a robust immune response against DENV-3 and DENV-4 serotypes in dengue seronegative individuals. Due to an imbalance in immune response against all four DENV serotypes, there is a higher risk of developing the antibody-dependent enhancement (ADE) effect, which could lead to severe dengue. This review has identified mutations throughout the DENV genome that were demonstrated to attenuate the virulence of DENV in either in vitro or in vivo studies. Several amino acid residues within the DENV prM and E proteins were identified to play important roles in ADE and modifying these ADE-linked residues is important in the rational design of novel live-attenuated dengue vaccine candidates. This review provides current insights to guide the development of a novel live-attenuated tetravalent dengue vaccine candidate that is effective against all DENV serotypes and safe from ADE. The efficacy and safety of the live-attenuated vaccine candidate should be further validated in in vivo studies. Full article

The present study investigated the host cell response to EHV-8 infection in rabbit kidney (RK-13) cells through transcriptomic and proteomic approaches. At 24 h post-infection, a total of 2118 differentially expressed genes (DEGs) were identified, with 1338 upregulated and 780 downregulated. At 48 h, 7388 DEGs were detected, with 4342 upregulated and 3046 downregulated genes. Proteomic analysis revealed 932 differentially expressed proteins (DEPs) at 24 h (364 upregulated and 568 downregulated) and 3866 DEPs at 48 h (2285 upregulated and 1581 downregulated). Of these, 237 upregulated and 336 downregulated proteins were common across both time points. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that the majority of DEGs and DEPs were enriched in key inflammation-related pathways, notably the TNF and NF-κB signaling pathways. Validation of the transcriptomic and proteomic data was performed using RT-PCR and parallel reaction monitoring (PRM), respectively, and confirmed consistent trends for TNFR1, NF-κB p65, and MAP3K8, as reported in the transcriptomic and proteomic screening. These findings suggest that EHV-8 infection may modulate host immune responses by activating the TNF signaling pathway. However, given that RK-13 cells may not fully replicate viral–host interactions in equine species, further in vivo studies in horses and donkeys are required to provide a more comprehensive understanding of the viral pathogenesis in these animals. Full article

The shape parameters and energy spectra of the decoupled ${\mathrm{h}}_{11/2}$ bands in isotopes ${}^{99,101,103}\mathrm{Ru}$, ^{101,103,105,107}Pd and ^{101,103,105,107}Cd are analyzed using the particle-plus-rotor model and cranked shell model calculations. The quasiparticle-plus-rotor (PRM) model calculations are performed, considering both soft and rigid triaxial cores, using the constant-moment-of-inertia (CMI) and variable-moment-of-inertia (VMI) approaches. The asymmetry parameter $\gamma$ obtained from the PRM model calculations is found to be consistent with the results obtained from the cranked shell model calculations when the core exhibited CMI behavior. Full article

The increasing complexity of IT operations necessitates advanced automation to ensure system availability, resilience, continuity, performance, security, and maintainability. Traditional IT management frameworks, such as the Information Technology Infrastructure Library (ITIL), have standardized service management processes, while models like IBM’s Process Reference Model for IT (PRM-IT) have facilitated automation through structured workflows. However, critical tasks, such as incident resolution and problem management, still require significant human intervention. The adoption of development, security, and operations (DevSecOps) introduced standardized remediation playbooks, further enhancing automation. More recently, Generative AI (GenAI) has expanded automation possibilities, opening new avenues for hyper-automated IT operations. This study explored Agentic Artificial Intelligence for IT Operations (Agentic AIOps), an approach that integrates AI-driven agents to autonomously manage IT operations. Our methodology features a framework for designing and developing an Agentic AIOps system that proactively detects anomalies, classifies incidents, and autonomously executes resolution workflows across infrastructure, middleware, data, and applications in complex, heterogeneous Enterprise IT environments. Our findings suggest that such a system can significantly reduce incident response time, enhance predictive maintenance, and enable self-healing IT environments. By leveraging AI agents for real-time decision making, this approach enhances operational efficiency and reduces human workload. We conclude that this Agentic AIOps system represents a transformative step toward fully autonomous IT operations. We outline a framework for defining its architecture and planning its subsequent development, ensuring continuous evolution and adaptability in complex IT landscapes. Full article

Myocardial infarction (MI), including ST-elevation MI (STEMI) and non-ST-elevation MI (NSTEMI), has been the leading cause of hospitalization and death. Exosomes participate in many physiological and pathological processes and have important effects on cell communication and function. This study analyzed the proteomic characteristics of plasma exosomes with the discovery of exosomal differentially expressed proteins (DEPs) in MI patients. Proteomics technology was used to identify the plasma exosomal DEPs in 41 patients in STEMI, NSTEMI, unstable angina, and CONTROL groups, and 406 exosomal DEPs were discovered. Further, 36 selected exosomal DEPs were validated with parallel reaction monitoring (PRM) in a new cohort of STEMI, NSTEMI, and CONTROL groups, and 7 were successfully verified. There were three (F13A1, TSPAN33, and YWHAZ) in the STEMI group and six (F13A1, TSPAN33, ITGA2B, GP9, GP5, and PPIA) in the NSTEMI group, and all were down-regulated compared to the CONTROL group with high sensitivity and specificity in MI that may be developed as biomarkers for MI and may become possible therapeutic targets for MI. Bioinformatics analysis revealed that these seven exosomal DEPs are of great significance in the molecular mechanism of MI. Therefore, the present study has provided insights to further explore the pathological mechanism and possible therapeutic targets in MI. Full article

With the evolution of the power market and the increase in the new energy penetration rate, the power industry will present diversified characteristics. The continuous development of the electric energy market (EEM) and the peak regulation market (PRM) is also affecting the economic benefits of cascade hydropower stations, in which the EEM, as a market for electric energy trading in the power market, develops synergistically with the PRM and creates the conditions for the consumption of new energy sources; for this reason, this paper, while considering the benefits of cascade hydropower stations in the EEM in different time scales and the impact of the spot market, combines the compensation mechanism and apportionment principle of the PRM. This paper proposes an optimal economic scheduling strategy for cascade hydropower stations. Specifically, firstly, the strategy adopts multi-objective optimization. The objective function takes into account the generation capacity of the cascade hydropower stations, the benefits of the EEM, the influence of the spot market, the compensatory benefits of peaking, and the sharing expenses of peaking; secondly, the constraints at the level of the power grid, the level of the cascade hydropower stations, and the level of the market are taken into account comprehensively, and the Harris Hawk Algorithm is used to solve the model; lastly, by comparing different schemes, it is observed that under varying inflow conditions, the proposed dispatch strategy in this paper yields slightly lower revenue in the EEM than other schemes. However, due to its comprehensive consideration of the synergy between the PRM and the EEM, its overall economic benefits surpass those of other schemes. This fully validates the effectiveness and economic efficiency of the proposed dispatch strategy. Full article

Clostridium ljungdahlii is a model acetogenic bacterium utilized for ethanol production from syngas, with its growth and ethanol synthesis being profoundly influenced by fermentation pH. However, the mechanistic basis of this pH-dependent regulation remains poorly understood. In this study, we systematically investigated the impact of pH on the growth and metabolic profile of C. ljungdahlii under controlled pH conditions using CO as the sole carbon and energy source. At pH 6.0, C. ljungdahlii consumed around 6.0 M carbon monoxide, producing 413 ± 43 mM acetate, 288 ± 35 mM ethanol, and 17 ± 2 mM 2,3-butanediol, with a maximum optical density (OD) of 15.9. In contrast, at pH 5.3, the strain exhibited enhanced metabolic activity, consuming around 9.6 M carbon monoxide and generating 235 ± 24 mM acetate, 756 ± 26 mM ethanol, 38 ± 4 mM 2,3-butanediol, and 28 ± 7 mM lactate, achieving a maximum OD of 30. This represents an approximate twofold increase in both ethanol production and biomass accumulation compared to pH 6.0. Proteomic and parallel reaction monitoring (PRM) analyses demonstrated that the expression levels of key enzymes in central metabolic pathways were marginally higher at pH 6.0 than at pH 5.3, indicating that the observed physiological enhancements were not attributable to differential enzyme expression but likely stemmed from variations in ATP synthesis efficiency. Further optimization experiments revealed that the optimal pH for growth and ethanol production by C. ljungdahlii under CO-sufficient and nutrient-replete conditions is approximately 5.3. These findings provide critical insights into the pH-dependent metabolic regulation of C. ljungdahlii and establish essential parameters for scaling up syngas fermentation for ethanol production. Additionally, this study offers a foundation for further exploration of the unique proton motive force-driven ATP synthesis system in C. ljungdahlii and its broader implications for metabolic network regulation. Full article

In view of the problem that the recommendation system is not good at integrating multi-source information and user sentiment, this paper proposes a BERT-LSTM Dual-Tower Recommendation Method for Sequential Feature Extraction (BLDRM-SFE). This method uses BERT to extract semantic features from user reviews and item details and obtains vector representations of item IDs and their groups through embedding. The user tower combines user review features with item group features to generate a user vector, while the item tower integrates item detail features with item ID vectors to generate an item vector. The outputs of the two towers are processed by LSTM to handle item ID sequence information, uncover potential sequence relationships, and generate rating predictions, thereby constructing a personalized recommendation list. The experimental results show that this method significantly outperforms four baseline models—BERT4Rec, PRM, BST, and ComiRec—on the Amazon Review Data and Yelp datasets. On the Amazon dataset, BLDRM-SFE improves by 10.39%, 8.08%, 10.78%, 10.59%, and 5.49% across five metrics compared to the baseline models; on the Yelp dataset, the improvements are 10.95%, 10.06%, 13.04%, 12.59%, and 10.8%, respectively. In addition, ablation experiments confirmed the positive impact of item ID sequence information on the method’s performance. The results show that the incorporation of sequence information significantly enhanced the recommendation performance. Full article

Background: Dengue virus type 2 (DENV2) is endemic to hyperendemic in the French territories of the Americas (FTAs), including French Guiana, Guadeloupe, Martinique, Saint-Barthelemy, and Saint-Martin. In 2023–2024, French Guiana, Martinique, and Guadeloupe experienced unprecedented dengue epidemics partly associated with this serotype. In response, we conducted a retrospective study of the diversity of DENV2 strains circulating in the FTAs from 2000 to 2024. Methods: To this end, we selected DENV2 samples from the collection at the National Research Center for Arboviruses in French Guiana (NRCA-FG) and sequenced them using Oxford Nanopore Technologies (ONT)-based next-generation sequencing (NGS). Results: Phylogenetic analysis revealed that (i) the 77 DENV2 sequences from the FTAs belong to two distinct genotypes—Asian American and Cosmopolitan; (ii) from the 2000s up to the 2019 epidemic in French Guiana, all sequenced strains belonged to the Asian American genotype; (iii) and from 2019 to 2020, strains circulating in Martinique and Guadeloupe belonged to the Cosmopolitan genotype, specifically the Indian subcontinent sublineage, while (iv) strains from the 2023–2024 outbreak in Martinique, Guadeloupe, and French Guiana fall within a distinct sublineage of the same genotype—Other Cosmopolitan. Additionally, we analyzed amino acid (AA) changes in FTA sequences compared to the Dengvaxia^® and Qdenga^® vaccines. The analysis of amino acid changes in FTA sequences compared to the vaccines (Dengvaxia^® and Qdenga^®) identified 42 amino acid changes in the prM/E regions (15 in the prM region and 27 in the E region) relative to CYD-2 Dengvaxia^® and 46 amino acid changes in the prM/E regions relative to Qdenga^®, including 16 in the prM region and 30 in the E region. Some of these AA changes are shared across multiple genotypes and sublineages, with 8 substitutions in the prM region and 18 in the E region appearing in both analyses. This raises questions about the potential impact of these changes on vaccine efficacy. Conclusion: Overall, these findings provide a current overview of the genomic evolution of DENV2 in the FTA, which is crucial for developing more effective prevention and control strategies and for selecting future vaccines tailored to circulating strains. Full article

Triazole pesticides are widely used throughout the world, but their abuse causes toxic effects in non-targeted organisms. In the present study, the cytotoxic effect of the triazole ipconazole was evaluated in porcine and ram spermatozoa. Ipconazole significantly reduced sperm viability, increased ROS levels, altered catalase and SOD enzyme activity, and caused alterations in the molecular mRNA expression of structural biomarkers (PRM1, ODF2, AKAP4, THEG, SPACA3 and CLGN) related to fertility in males, as well as the overexpression of BAX (cell death) and ROMO1 (oxidative stress) mRNA. Our results indicate that the fungicide triazole is involved in cellular, enzymatic and molecular alteration of porcine and ram spermatozoa, and is possibly a factor in the development of infertility in male mammals. Full article