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An novel cloud task scheduling framework using hierarchical deep reinforcement learning for cloud computing

With the increasing popularity of cloud computing services, their large and dynamic load characteristics have rendered task scheduling an NP-complete problem.To address the problem of large-scale task scheduling in a cloud computing environment, this paper proposes a novel cloud task scheduling framework using hierarchical deep reinforcement learning (DRL) to address the challenges of large-scale task scheduling in cloud computing. The framework defines a set of virtual machines (VMs) as a VM cluster and employs hierarchical scheduling to allocate tasks first to the cluster and then to individual VMs. The scheduler, designed using DRL, adapts to dynamic changes in the cloud environments by continuously learning and updating network parameters. Experiments demonstrate that it skillfully balances cost and performance. In low-load situations, costs are reduced by using low-cost nodes within the Service Level Agreement (SLA) range; in high-load situations, resource utilization is improved through load balancing. Compared with classical heuristic algorithms, it effectively optimizes load balancing, cost, and overdue time, achieving a 10% overall improvement. The experimental results demonstrate that this approach effectively balances cost and performance, optimizing objectives such as load balance, cost, and overdue time. One potential shortcoming of the proposed hierarchical deep reinforcement learning (DRL) framework for cloud task scheduling is its complexity and computational overhead. Implementing and maintaining a DRL-based scheduler requires significant computational resources and expertise in machine learning. There are still shortcomings in the method used in this study. First, the continuous learning and updating of network parameters might introduce latency, which could impact real-time task scheduling efficiency. Furthermore, the framework’s performance heavily depends on the quality and quantity of training data, which might be challenging to obtain and maintain in a dynamic cloud environment.

Inflammatory cytokine interleukin-18 prevents murine miscarriage by inducing appropriate inflammation

M-ReDet: A mamba-based method for remote sensing ship object detection and fine-grained recognition

Ship object detection and fine-grained recognition of remote sensing images are hot topics in remote sensing image processing, with applications in fishing vessel operation command, merchant ship navigation route planning, and other fields. In order to improve the detection accuracy for different types of remote sensing ship objects, this paper proposes a ship object perception and feature refinement method based on the improved ReDet, called Mamba-ReDet (M-ReDet). First, this paper designs a ship object fine-grained feature extraction backbone (Mamba-ReResNet, M-ReResNet), which selects and reconstructs the unique features of different types of ship objects through the Mamba’s selective memory to improve the algorithm’s ability to extract fine-grained features. Secondly, the M-ReDet consists of the Ship Object Perception Module (SOPM) and the Ship Feature Refinement Module (SFRM), which can extract the ship’s spatial position information from the feature map, fuse different scales of spatial position information and use this information to refine the fine-grained features to improve the detection accuracy of the algorithm for different categories of ships. Finally, we use the KFIoU and Focal Loss as the regression loss and classification loss of the algorithm to improve the accuracy of the training. The experimental results show that the mAP0.5 of the M-ReDet algorithm on the FAIR1M(ship) and DOTAv1.0 visible light (RGB) remote sensing image datasets are 43.29% and 82.09%, respectively, which is 2.78% and 3.34% higher than that of the ReDet.

Disaster treatment and multisource monitoring of rockbursts in isolated island coal face under hard roof conditions

Analysis of blood screening strategies and their efficacy among voluntary blood donors in a region of East China

Objective In this study, we aimed to analyze the blood screening detection strategies employed for voluntary blood donation in a specific region of East China and evaluate the efficacy of the blood safety detection system. Donors and Methods A total of 539,117 whole blood samples were collected from voluntary blood donors between January 2018 and July 2021, as well as in 2023 and 2024. The samples were screened for hepatitis B surface antigen (HBsAg), hepatitis C virus (HCV) antibodies, human immunodeficiency virus antibodies/antigen (HIV Ab/Ag), and Treponema pallidum (TP) antibodies using enzyme-linked immunosorbent assay (ELISA). Alanine aminotransferase (ALT) levels were measured using a rapid method. Chemiluminescence immunoassay technology was used to detect five hepatitis B virus (HBV) markers. Polymerase chain reaction was employed to detect HBV DNA, HCV RNA, and HIV RNA. The reactivity rates of each marker were analyzed. Results The overall positivity rate for blood testing among donors in this region was 0.76% (4,078/539,117). The positivity rates for the individual markers were as follows: anti-TP (0.20%)> HBsAg (0.18%)> ALT (0.13%)> anti-HCV (0.085%)> nucleic acid testing (0.080%)> HIV antigen/anti-HIV (0.079%). No significant differences were observed (P > 0.05). Before 2023, the positivity rates for ALT and HBsAg exhibited occasional fluctuations, followed by a significant decline. Conversely, in 2024, a slight upward trend in the HIV positivity rate was noted. Conclusion The current multitiered blood screening and detection strategy in this region exhibits complementary advantages, ensuring effective blood safety. However, the observed slight upward trend in the HIV positivity rate among voluntary blood donors highlights the necessity for enhanced pre-donation counseling and risk assessment for key populations.

How time and risk preferences affect glucose control in type 2 diabetes patients

Spatiotemporal characteristics and optimization strategies of land use and land resource carrying capacity in the three gorges reservoir region (1986–2020)

Studying land use changes caused by human economic activities is beneficial for sustainable growth, making it a global research hotspot. In this study, we used Landsat Thematic Mapper images and statistical yearbooks from 1986, 1995, 2000, 2007, 2010, and 2020 to obtain grid data on the land use status of the Three Gorges Reservoir Region (TGRR), from which vector data reflecting socioeconomic information were derived. We introduced models on land use quantitative changes, dynamic indicators, and degree index to investigate spatiotemporal variations in land use in the TGRR over the past 30 years. Classified maps were generated using ARCGIS 10.8, and Landsat TM images were processed for accuracy using supervised classification techniques. Based on the region’s status quo and the analytic hierarchy process, we constructed a land resource carrying ability evaluation indicator model considering social, economic, population, and ecological carrying abilities, introducing a mean-square mistake decision-making approach to determine indicator weights. Our results indicate significant changes in land types within the TGRR from 1986 to 2020, with decreases in arable land, forest land, and grassland, while water bodies, building land, and unused land increased. The change rates varied significantly among different land types, reflecting rapid development, especially between 1995 and 2000. Additionally, our analysis delves into the underlying mechanisms driving these changes, providing insights into how different factors influence spatial-temporal evolution of land use and land carrying capacity, crucial for developing optimization strategies aimed at promoting sustainable growth and efficient use of land resources in the TGRR. This study offers a comprehensive analysis of the TGRR’s land resource carrying ability, serving as a reference for sustainable land use.

Natural dual inhibitor isorhamnetin-3-O-neohespeidoside targets tyrosinase and MC1R for skin pigmentation management

BM-MSCs mitigate lung injury in a rat model of decompression sickness

Decompression sickness is a fatal disease worldwide. Therefore, to find a prophylactic modality for decompression sickness is urgently required. Bone marrow derived mesenchymal stem cells exhibit effectiveness in antioxidant, anti-inflammation, and decrease cell death; while its effects on decompression sickness remains unclear. This study aimed to further investigate the mechanisms of decompression sickness induced lung injury, as well as effects of bone marrow derived mesenchymal stem cells on decompression sickness induced lung injury and explore the role of oxidative stress, inflammation and cell death play in this disease. The study involved Sprague-Dawley rats age at 8−10 weeks weighting 350 ± 10g. Acute lung injury was induced by decompression hyperbaric chamber. A dose of bone marrow derived mesenchymal stem cells (2 × 106 cells) was given to rats one day prior to the start of decompression. Lung injury severity was estimated by determining lung damage scores, pulmonary oxidative, inflammatory factors and cell death. In bone marrow derived mesenchymal stem cells treated rats, the morbidity and mortality of decompression markedly decreased. The increases of protein IL-1 and IL-6 in BALF and lung wet/dry ratio and lung injury score were alleviated. The ROS, CAT, SOD, and MDA activities and GSH levels were significant attenuated (P < 0.05). The pyroptosis and nerroptosis were significant mitigate (P < 0.05). Based on the results, bone marrow derived mesenchymal stem cells is an potential efficient and safe prophylactic modality protect rats from decompression induced acute lung injury.

Subnucleosome preference of human chromatin remodeller SMARCAD1

Fault prediction method of large forging press based on a multi scale and multi model integrated method

Non-surgical treatments for post-burn scars: A network meta-analysis

Background and aim Post-burn scarring is a prevalent condition, and the existing non-surgical treatments exhibit varying degrees of efficacy. There is limited evidence available to determine the effective non-surgical treatment for post-burn scars. This study employs a multi-index network meta-analysis to conduct a comprehensive evaluation and comparative ranking of non-surgical treatments for post-burn scars. The aim is to identify the most effective treatment methods, thereby providing a robust, evidence-based foundation to guide clinical decision-making. Methods PubMed, Web of Science, Cochrane Library, PEDro, and Embase were systematically searched for eligible randomized controlled trial studies, and the network meta-analysis was performed via a frequentist approach. The primary outcomes assessed were Vancouver Scar Scale score, scar thickness and Visual Analogue Scale score. Results A total of 17 studies and 1,013 participants were included in this analysis. The treatment ranking revealed that massage therapy demonstrated the most significant efficacy in reducing Vancouver Scar Scale score (surface under the cumulative ranking curve [SUCRA] = 89.0%), CO2 laser therapy exhibited the highest efficacy in decreasing scar thickness (SUCRA = 96.8%), and extracorporeal shock wave therapy + routine treatment showed the most significant efficacy in reducing Visual Analogue Scale score (SUCRA = 58.6%). Conclusion This network meta-analysis illustrates that massage therapy, CO2 laser therapy and extracorporeal shock wave therapy + routine treatment are the most effective non-surgical treatments for reducing Vancouver Scar Scale score, scar thickness and Visual Analogue Scale score for post-burn scars, respectively. However, the findings reflect outcomes at a specific stage of scar maturation. And our conclusions must be interpreted with caution due to the limited number of studies included. In the future, well-designed randomized controlled trials with a large sample size are needed to validate these findings.

Inulin supplementation improves some inflammatory indices, clinical outcomes, and quality of life in rheumatoid arthritis patients

Association between household second-hand smoke and low birth weight in sub-Saharan Africa

Background The reduction of maternal and child morbidity and mortality is essential for achieving the Sustainable Development Goals (especially goal 3 – wellbeing of mothers and children) in sub-Saharan Africa (SSA). Exposure to household second-hand smoke (SHS) has been linked to adverse birth outcomes, yet limited evidence exists on its impact on low birth weight (LBW) in SSA. This study examines the association between household SHS exposure and LBW across ten SSA countries using recent national survey data. Methods A cross-sectional study was conducted using data from the Demographic and Health Surveys (DHS) from ten SSA countries collected between 2020 and 2024. The sample included 45,684 women aged 15–49 who had given birth in the five years preceding the surveys. The primary outcome variable was LBW, defined as birth weight <2500 grams. SHS exposure was determined based on household smoking behavior. Bivariate analysis was conducted using Chi-square tests, and multivariate logistic regression models were employed to estimate adjusted odds ratios (AOR) with 95% confidence intervals (CI), controlling for maternal, household, and reproductive health factors. Results Overall, 6.3% of women reported exposure to SHS, and 11.9% of births were classified as LBW. After adjusting for potential confounders, SHS exposure was significantly associated with increased odds of LBW (AOR = 1.28; 95% CI: 1.12–1.46, p < 0.01). The association was particularly pronounced in urban areas (AOR = 1.39; 95% CI: 1.17–1.65, p < 0.01). Other significant predictors of LBW included maternal age < 20 years, lower educational attainment, low antenatal care (ANC) attendance, and socioeconomic status. Conclusion Household SHS exposure is an independent risk factor for LBW in SSA. Given the significant burden of LBW on neonatal health, policies targeting SHS reduction—such as household smoking bans and integrating SHS awareness into prenatal care—should be prioritized. Future longitudinal studies should explore causal mechanisms in greater detail.

Geospatial distribution of heavy metals in rice soils of northwestern Peru

The effect of telerehabilitation on activity performance and participation in daily life in children with developmental coordination disorder: A randomized controlled trial

Background Developmental Coordination Disorder (DCD) is a neurodevelopmental condition that adversely impacts motor skills, sensory processing, and daily activity participation. Telerehabilitation has recently emerged as a promising method to improve therapy access and foster family involvement. This study investigated the effects of integrating telerehabilitation with sensory-based intervention on motor performance, sensory processing, and participation in children with DCD. Methods This randomized controlled trial included 20 children aged 3–7 years with a confirmed diagnosis of DCD. Participants were randomly assigned to either a sensory-based intervention (SBI) group or a telerehabilitation sensory-based intervention (TBSI) group. Both groups received weekly face-to-face sensory-based therapy for eight weeks. Additionally, the TBSI group participated in 30-minute weekly home-based telerehabilitation sessions. Outcome measures included the Canadian Occupational Performance Measure (COPM), the Functional Independence Measure for Children (WeeFIM), and the Dunn Sensory Profile. Results Both groups demonstrated statistically significant improvements; however, the TBSI group showed greater gains in WeeFIM motor, cognitive, and total scores as well as COPM performance and satisfaction scores (p < 0.01). Furthermore, larger improvements and greater effect sizes were observed in the sensory processing subdomains of the TBSI group. Parental training and active participation appeared to enhance the effectiveness of the telerehabilitation program. Conclusions Telerehabilitation is an effective intervention for improving motor and cognitive functions, sensory processing, and daily life participation in children with DCD. The findings support the integration of telerehabilitation into sensory-based approaches as part of a holistic model of care in occupational therapy practice. Trial registration Clinicaltrials.gov NCT06977256.

Improving computational drug repositioning through multi-source disease similarity networks

Facilitators and barriers of Community Case management of Malaria implementation in Homabay, Busia and Kakamega Counties, Kenya

Background Community Case management of malaria (CCMm) is a strategy used in malaria-endemic areas to reduce malaria morbidity and mortality. CCMm involves providing malaria diagnosis and treatment within the community by trained community health volunteers (CHVs). While evidence suggests CCMm is effective in combating the disease burden at the community level, it isn’t without challenges. This study assesses facilitators of and barriers to uptake of CCMm. Methods This cross-sectional study employed a mixed methods approach. Quantitative data was collected using a household questionnaire targeting 528 participants, while qualitative data was collected using 4 focused group discussions and 20 key informant interviews. Quantitative data was cleaned, coded, and analyzed using STATA version 14. Qualitative data was transcribed, and the data was analyzed using NVIVO version 10. Results The study found that 72% of households had received a service on Malaria, and this was consistent across all counties (Busia 75%, Homabay 72%, Kakamega 71%). 62% of respondents considered CHVs a regular source of healthcare, with approximately 85% of the population being satisfied with the services offered by CHVs. Key initiatives that improved the effectiveness of CCMm included sensitization on malaria causes and preventive measures, training of CHVs on the management of malaria, and empowerment of CHVs who can utilize rapid tests to diagnose malaria at the household level. The facilitators of CCMm included the availability of malaria commodities, a functional referral system, and support supervision from the Community Health Assistants (CHA) and Health Management Teams. Barriers that hindered the implementation of CCMm included myths and misconceptions surrounding the use of mosquito nets, stock outs of malaria commodities such as the Malaria Rapid Diagnostic Test (mRDT) kits and antimalarials, and inaccessible roads into the communities. Conclusion In spite of great strides in CCMm initiatives to reduce malaria-related Morbidity and mortality, some of the barriers underpinning its effectiveness remain unaddressed. Continuous training for CHVs, sustained availability of commodities for testing and treating malaria, and incentives are essential for the success and sustainability of CCMm initiatives.

Research and design of TiN/TiAlN coated integral cemented carbide reamers under high cutting-speed and high feed-rate machining conditions

Abstract The development of high-performance reamers made of Cemented carbide and coating materials is an important direction in mechanical finishing. Due to the complex structure of reamers, it is difficult to manufacture reamers with good performance in practice. This paper takes the high cutting- speed and high feed-rate mechanical finishing of 45 steel as the experimental condition and the production site machining as the background to scientifically investigate the factors affecting the performance of the TiN/TiAlN coated Integral Cemented carbide reamer. Firstly, the TiN/TiAlN coated cemented carbide reamer was designed and manufactured. During the experimental processing, shrinkage hole over-tolerance problems occurred rapidly. By analyzing the cutting characteristics of the reamer, the mechanical model of the cutting edge of the reamer was established, and the principle of chipping was analyzed. The results were consistent with the magnified fracture morphology of the cutting edge. In response to the accelerated wear caused by poor cooling and lubrication, an internal cooling reamer structure was adopted, and the fluid mechanics model of the Integral reamer was constructed. The important structural parameters were determined, and the importance of adequate cooling and lubrication was clarified. By clarifying the factors affecting the processing performance, the machining capacity of this type of reamer was maximized.

Factors associated with SARS-CoV-2 RNAemia development at COVID-19 diagnosis

Objectives SARS-CoV-2 RNAemia at diagnosis is associated with mortality. The aims were to identify factors associated with the development of RNAemia. Methods Multicenter COVID-19 cohort study was conducted between January 2020 and May 2023. Demographics, chronic underlying diseases, symptoms and signs, analytical and radiological variables, cytokines, and neutralizing antibodies were evaluated on admission. RNAemia was the primary endpoint. Results We included 1011 patients, 392 (38.8%) immunocompromised and 619 (61.2%) immunocompetent. RNAemia occurred in 49.7% and 18.7% (p < 0.001), respectively, being independently associated with 30-day all-cause mortality. In immunocompromised patients, factors independently associated with RNAemia were Alpha and Omicron VOC periods (OR: 1.95 [1.01–3.79]), pneumonia (OR: 1.96 [1.10–3.50]), LDH > 300 UI/L (OR: 1.64 [1.02–2.63]) and neutralizing antibodies absence (OR: 2.51 [1.57–4.00]). In immunocompetent patients, the factors associated with RNAemia were Delta and Omicron VOC periods (OR: 2.27 [1.46–3.52]), lymphocyte count < 1000/µL (OR: 1.81 [1.16–2.80]) and LDH levels > 300 IU/L (OR: 3.99 [2.51–6.36]). Conclusions Immunodeficiency almost tripled SARS-CoV-2 RNAemia. Omicron VOC period, LDH as inflammatory biomarker, and a lower immune response in all patients, neutralizing antibodies absence in immunocompromised and lymphopenia in immunocompetent, and pneumonia in immunocompromised patients were associated with RNAemia.