bluuebunny/crossref_metadata_2025_split huggingface dataset:
Development of 3D-structured tilt capillary valve for lab-on-a-disc devices
Authors: Murano Yuito , Yamamoto Shoji , Matsuzawa Hayato , Morioka Kazuhiro , Hemmi Akihide , Nakajima Hizuru 
Published: November 2024

Abstract

Lab-on-a-disc (LoD) devices utilize centrifugal force to regulate fluid movement and are widely employed in biochemical applications. LoDs facilitate biochemical analysis by integrating different essential steps such as mixing samples and reagents, separating target components from the sample, and detecting analytes in a single platform. This integration on a single disc substrate enables the miniaturization and automation of various biochemical workflows. However, current LoD systems frequently rely on active valves, which increase complexity and limit versatility. To address these challenges, this study employed 3D printing technology to develop a 3D-structured tilt capillary valve acting as a passive control mechanism. Tilt capillary valves with inclination angles ranging from 50° to 80° were fabricated, and their burst rotational speeds and repeatability were compared with those of conventional capillary and slope valves. The tilt capillary valve demonstrated superior performance, achieving high-speed fluid control with relative standard deviations ranging from 1.5% to 2.1%. This improvement was attained by distributing the effects of centrifugal and gravitational forces along the inclined flow path. Additionally, the capillary structure stabilized the effects of surface tension, further enhancing reproducibility. These findings suggest that the developed tilt capillary valve enhances the LoD system performance, enabling more precise and rapid fluid control. The enhanced passive valve presented in this study can be incorporated in advanced microfluidic device designs, opening new possibilities for biochemical assays, particularly in resource-limited environments.
b-move: Faster Lossless Approximate Pattern Matching in a Run-Length Compressed Index
Authors: Depuydt Lore , Renders Luca , de Vyver Simon Van , Veys Lennart , Gagie Travis , Fostier Jan 
Published: November 2024

Abstract

Background: Due to the increasing availability of high-quality genome sequences, pan-genomes are gradually replacing single consensus reference genomes in many bioinformatics pipelines to better capture genetic diversity. Traditional bioinformatics tools using the FM-index face memory limitations with such large genome collections. Recent advancements in run-length compressed indices like Gagie et al.'s r-index and Nishimoto and Tabei's move structure, alleviate memory constraints but focus primarily on backward search for MEM-finding. Arakawa et al.'s br-index initiates complete approximate pattern matching using bidirectional search in run-length compressed space, but with significant computational overhead due to complex memory access patterns.
Results: We introduce b-move, a novel bidirectional extension of the move structure, enabling fast, cache-efficient, lossless approximate pattern matching in run-length compressed space. It achieves bidirectional character extensions up to 7 times faster than the br-index, closing the performance gap with FM-index-based alternatives. For locating occurrences, b-move performs φ and φ inverse operations up to 7 times faster than the br-index. At the same time, it maintains the favorable memory characteristics of the br-index, for example, all available complete E. coli genomes on NCBI's RefSeq collection can be compiled into a b-move index that fits into the RAM of a typical laptop.
Conclusions: b-move proves practical and scalable for pan-genome indexing and querying. We provide a C++ implementation of b-move, supporting efficient lossless approximate pattern matching including locate functionality, available at https://github.com/biointec/b-move under the AGPL-3.0 license.
Prevalence and Determinants of Still birth in Mothers Delivered by Cesarean Section in Orotta National Referral Maternity Hospital: A Cross Sectional Study
Authors: Gebremariam Hailemichael , Tesfai Berhe , Frezgi Okbu , Hussein Khalid , Asrat Kibreab , Kibreab Fitsum 
Published: November 2024

Abstract

Background: Stillbirth is a growing public health issues worldwide and accounts for majority of perinatal death. In resources limited countries, 40% of stillbirth occurs during labor and this loss could be avoided with improved monitoring and timely access to emergency obstetric care when required. The aim of this study was to determine the prevalence of stillbirth and identify its determinants among mothers delivered by cesarean section.
Methods: It was a hospital based retrospective unmatched case control study. Mothers who delivered by cesarean section with the outcome of still birth were cases and three consecutive cesarean section deliveries with live birth were controls. Data were collected using structured data extraction tool developed from literature related to stillbirth and modified according to the local context by the investigators. Variables with p<0.05 in the univariable logistic regression were entered to multivariable logistic regression and declared significant at p<0.05.
Results: A total of 380 sampled chart of mother’s delivered by cesarean section were included in study. Of those, 95 were stillbirth and 285 were live birth. The prevalence of still birth on cesarean section deliveries was 3.3% and 48% of stillbirth and 54% of live birth were in mother’s aged 25 to 34 years. Emergency cesarean section was performed in 93% of stillbirth and 71% of live birth. The major indications for cesarean section were antepartum hemorrhage (37%) for stillbirth and mal-presentation (21%) for live birth. Besides, 70% of stillbirth and 73% of live birth have birth weight of 2500-4000gram. The result showed that emergency cesarean section (AOR: 0.32; 95%CI: 0.14-0.75) and male newborn (AOR: 3.03; 95%CI: 1.78-5.19) were found to have a significant association with stillbirth.
Conclusion: Our study indicates emergency cesarean section for antepartum hemorrhage was associated with increased stillbirth rate. Focusing on causes of antepartum hemorrhage during antenatal care, appropriate intrapartum monitoring and early risk assessment for complications is paramount for early intervention and prevention of still birth.
A Novel Hybrid Particle Swarm Optimization-Simulated Annealing Algorithm for Maximizing Coverage in IoT-Enabled Wireless Sensor Networks
Authors: Benelhouri Abdelkader , IDRISSI-SABA Hafida , Antari Jilali 
Published: November 2024

Abstract

This paper presents a novel hybrid Particle Swarm Optimization-Simulated Annealing (PSO-SA)algorithm for optimizing coverage in IoT-enabled Wireless Sensor Networks (WSNs). We addressthe critical challenge of maximizing network coverage while considering computationalcomplexity. Our approach combines the global search capabilities of PSO with the local optimizationstrengths of SA to achieve superior performance across various network scales. Weconducted extensive simulations for networks ranging from 10 to 50 nodes. The proposed algorithmsignificantly improved network coverage, with improvements of up to 27.8% for smallernetworks (N=10) and 9.16% for larger networks (N=50). The optimized configurations consistentlyachieved coverage ratios above 95% for networks up to 20 nodes, and maintained coverageabove 75% for larger networks of 30-50 nodes. The algorithm demonstrated rapid convergence,typically achieving near-optimal solutions within 200-300 iterations. However, we observed anexponential increase in execution time as network size grew, from approximately 200ms for 10nodes to over 6000ms for 50 nodes. This highlights the trade-off between optimization qualityand computational cost for larger networks. Our results also show that the hybrid PSO-SAapproach maintains higher solution diversity for larger networks, allowing for more thoroughexploration of the solution space. The algorithm achieved a balance between coverage improvementand computational efficiency, with the number of function evaluations remaining relativelyconstant (around 1.8 ∗ 10^5) across all network sizes.
Rumen Metagenomic Sequencing Profiling Reveals the Differential Regulation of Microbial Related to Key Mutton Flavor 4-Alkyl-Branched-Chain Fatty Acids in the Longissimus Dorsi Muscle of Lamb Feeding Allium mongolicum Regel
Authors: Wang XiaoYuan , Bai Chen , Erdene Khas , Cao QiNa , Zheng YanKai , Han GuoLi , Ao ChangJin 
Published: November 2024

Abstract

Background Three key branched-chain fatty acids (4-methyloctanoic acid, 4-ethyloctanoic acid, 4-methylnonanoic acid) (KBCFAs) have been identified as the primary contributors to the formation of mutton odor. Given the potential of Allium mongolicum regel in regulating mutton flavor (MF) and the regulation of rumen microbiota, it is hypothesized that Allium mongolicum regel may alter the structure of the gastrointestinal microbiota, subsequently affecting pathways related to odor synthesis, thus improving the flavor of lamb meat.
Methods A total of twenty lambs (Small-tailed Han sheep × Dorper sheep) were randomly selected and divided into two experimtetal groups. (1) basal diet as control group (CON); (2) basal diet supplement with 15 g/lamb/day Allium mongolicum regel powder as treatment group (AMR). The experimental period lasted for a total of 75 days. The effects of dietary AMR supplementation on lamb rumen fermentation, the three branched-chain fatty acids in the longissimus dorsi (LD) muscle, and rumen microbiota were evaluated.
Reasults. A comparison of the two groups revealed that the AMR group exhibited a notable reduction in the concentration of propionate and total volatile fatty acids (P < 0.05), while the AMR group demonstrated a significant decline in the concentration of KBCFAs in the LD muscle (P < 0.05). The relative abundance of Prevotellaat the genus level was found to be significantly reduced in the AMR group (P< 0.05), as was the relative abundance of Prevotella sp. Rep29 at the species level is significantly reduced in the AMR group (P < 0.05). The GH94 showed the positive correlation with MOA (R = 0.88, P < 0.05), while GT2 showed a negative correlation with EOA (R = -0.92, P = 0.03 ). The influential heatmap revealed that MNA demonstrated significantly negative correlations with Eubacterium callanderi, Intestinibaculum porci, Collinsella aerofaciens, and Serratia marcescens (P < 0.05). MOA showed significantly positive correlations with Prevotella sp. Rep29, and Chamaesiphon minutus, and showed significantly negative correlations with Eubacterium callanderi (P < 0.05). EOA were positively correlated with Prevotella sp. Rep29 and Pyramidobacter piscolens (P < 0.05). The co-occurrence networks indicate that bacterial stability in the rumen surpasses that of archaea, which in turn exceeds that of fungi. The KEGG pathways K01579, K17723, and K18933 are significantly upregulated in the AMR group in the pantothenate and CoA biosynthesis pathway (P < 0.05).
Balancing Performance and Cost in EC2 Instance Selection for Energy-Efficient Cloud Computing
Authors: Mishra Abheelash , B Ida Seraphim 
Published: November 2024

Abstract

This paper introduces a dynamic decision-making framework designed to optimize cloud resource allocation through the selection of the most suitable Amazon EC2 instance types based on specific workload demands. The system categorizes workloads into general-purpose, memory-intensive, and compute-intensive types, allowing user input to be translated into detailed technical requirements, such as the necessary virtual CPUs, RAM, expected usage duration, and performance needs. Leveraging a cost-performance scoring algorithm, the system filters and evaluates various EC2 instances to recommend optimal configurations that balance computational performance with budgetary constraints. This method not only maximizes cost-effectiveness but also reduces unnecessary resource utilization, minimizing operational inefficiencies and environmental impact associated with cloud over-provisioning. The proposed framework is particularly relevant in the context of scalable, energy-efficient cloud computing environments, as it aligns infrastructure usage with specific application requirements, thereby supporting more sustainable cloud operations. By helping users effectively match their cloud investment to workload necessities, this system offers a valuable solution for organizations looking to achieve both economic and ecological benefits in their cloud deployments.
Design and research of business processor of electricity consumption information collection system
Authors: CHENG Xingliang , Mingli ZHOU , LI Xiaojun , Tongyang ZOU , Siyu MEN , Lin CHEN 
Published: November 2024

Abstract

In order to improve the electricity consumption information collection system, this research designed a new type of business processor, which can realize the information collection of the user's electricity collection environment, and realize the collection of different information on the surrounding environment to detect the data information of the surrounding environment. Through the marketing and utilization of smart IoT, it realizes the operation of electricity data collection, parameter issuance, electricity statistics and line loss calculation for residential users, special transformer users, and substation gateways, which improves the intelligence and automation capabilities of electricity information collection. When designing the front-end processor, the power consumption information collection function is improved by establishing a connection with the front-end processor. The research also designed an active queue management (Active Queue Management, AQM) algorithm model, which can improve the power consumption information data transmission and application capabilities. Through experiments, the method of this research has greatly improved the business capability of the electricity consumption information collection system with high accuracy.
Stacking multi-timescale graph attention network and bidirectional gated recurrent units for traffic flow prediction
Authors: Liu Yizhi , Zou Zhengbiao , Tang Jingxin , Liao Zhuhua , Liu Yuxuan , Fang Zhixiong 
Published: November 2024

Abstract

Accurately predicting traffic flow becomes more and more important to intelligent transportation systems in the age of autonomous driving. Some existing methods extract spatial and temporal features of road networks respectively via graph convolutional network and recurrent neural network for traffic flow prediction. However, there are still threefold challenge of spatiotemporal coupling interrelations, dynamic spatial correlations, and the impact of periodic patterns and external factors. Addressing at these challenges, this paper proposes a novel approach of stacking multi-timescale graph attention network (GAT) and bidirectional gated recurrent units (BiGRU) for traffic flow prediction, called SMGAT-BiGRU. Firstly, a GAT feature extraction module is explored to capture the dynamic spatial correlation of different road segments, and then a multi-timescale feature fusion module is constructed to mine hidden periodic patterns and to capture the impact of external factors by extracting fine-grained spa-tiotemporal features and external dynamic time-varying features. Secondly, a BiGRU module with attention is proposed to capture temporal dependencies from dynamic spatial dependency sequences. Furthermore, a GAT-BiGRU module is presented to be stacked to fully capture the spatiotemporal coupling interrelations. Experimental results on two PeMS datasets show that SMGAT-BiGRU 1 can remarkably improve the performance of traffic flow prediction and outper-forms many state-of-the-art methods (such as T-GCN, STGCN, STSGCN, and DMSTGCN).
The effect of psychological capital on athlete burnout: the mediating role of coping strategies and the moderating effect of perceived stress
Authors: YU Xiaomei , XING Suxuan , YANG Yang 
Published: November 2024

Abstract

Athlete burnout represents a critical concern in sports psychology, significantly affecting athletes' well-being and performance. This study investigated the relationships among psychological capital, coping strategies, perceived stress, and athlete burnout. A cross-sectional survey was conducted among 344 athletes, and data were analyzed using SPSS Statistics 25.0 and PROCESS Macro v4.1 for hierarchical stepwise regression and moderated mediation analysis. Control variables included age, gender, sport type, and competitive experience. The results revealed that psychological capital negatively predicted burnout both directly ( β = -0.539, p <0.01) and indirectly (a*b = -0.803, p < 0.01) through coping strategies. Furthermore, perceived stress moderated both the relationship between psychological capital and coping strategies and the indirect effect of psychological capital on burnout via coping strategies. Notably, under high-stress conditions, the protective effect of psychological capital was more pronounced, with a more substantial indirect effect compared to low-stress conditions (β = -1.020, p < 0.01 vs. β = -0.299, p < 0.01). These findings underscore the importance of cultivating psychological resources and adaptive coping mechanisms to mitigate burnout, offering valuable insights for targeted interventions aimed at enhancing the well-being of athletes, particularly those experiencing elevated stress levels.
The Mediating Role of the Care Factor in the Effect of Nomophobia on Job Satisfaction in Nurses: a cross-sectional study
Authors: ÖNER Uğur , ASLAN Sinan , EKİNGEN Erhan 
Published: November 2024

Abstract

Background: This study aimed to reveal the mediating role of the Care Factor in the effect of nomophobia on job satisfaction in nurses.
Methods: The population of this descriptive, cross-sectional study consisted of nurses working in a province in the Southeastern Anatolia region of Turkey. A total of 1,083 nurses participated in the study, and the data were collected between May and September 2024. The data were gathered using the "Descriptive Form," "Fırat Nomophobia Scale (FNS)," "Care Factor Scale (CFS)," and the "Nurse Job Satisfaction Scale (JSSN)." Data were analyzed using the SPSS 25 program, with descriptive statistics, Pearson correlation, and regression analyses applied. Additionally, analysis was conducted using PROCESS macro version 4.0 (Model 4).
Results: It was observed that the Care Factor Scale—Caring for Self (CFS-CS) (-.063) and the Care Factor Scale—Caring of Manager (CFS-CM)(-.096) have a moderate mediating role in the effect of the Fırat Nomophobia Scale on the Job Satisfaction Scale for Nurses (JSSN).When the parallel mediation role was tested, the effect size increased to (-.159) and remained moderate.
Conclusion: In this study, a significant negative relationship was found between nomophobia and both job satisfaction and the Care Factor, while a significant positive relationship was found between the Care Factor and job satisfaction. Furthermore, the Care Factor was found to mediate the relationship between nomophobia and job satisfaction.
Still safe; still respectful: a mixed methods study exploring the early experiences of a rural community hospice in providing voluntary assisted dying
Authors: Auret Kirsten , Pikora Terri , Briand Beatriz Cuesta 
Published: November 2024

Abstract

Background
Voluntary assisted dying has become available as an end-of-life choice in many countries, including Australia. There is evidence on the mixed impact of voluntary assisted dying legislation on palliative care healthcare professionals, however, less is known about the interface between palliative care and voluntary assisted dying in smaller rural settings. This study explored the experiences of staff at a hospice in rural Western Australia in the two years following the implementation of voluntary assisted dying legislation.
Methods
A mixed-methods research methodology was used, with data collected via a brief anonymous survey and semi-structured interviews conducted with hospice staff in one rural location in Western Australia. Survey data was exported into SPSS and descriptive statistics were performed. Interviews were audio recorded and after deidentification, the transcripts were analysed thematically.
Results
A total of 30 participants took part in the survey and 10 were interviewed. The majority (n = 19) of survey respondents had been involved in voluntary assisted dying, yet only seven reported that their day-to-day role had changed. Supporting patient choice and autonomy were the most cited benefits of the introduction of voluntary assisted dying. Analysis of the qualitative data yielded three main themes: everyone is involved with patients accessing VAD; nothing changes but everything changes; and perceived support, education and training needs.
Conclusions
This study has described day-to-day work and experiences of those working in a small rural hospice which has integrated VAD into the care offered within the facility, observing there are subtle changes in the organisational atmosphere when VAD occurs. The education and support activities in place and the noted gaps may be a useful checklist for other hospices in the early phases of integrating VAD into their facility. Recommendations for future research are made.
Investigating miRNA-Driven DNA Methylation: Statistical Evidence of Gene-Specific Modulation
Authors: Jeon Seyeon , Jun Ha Ra , Lee Ji-Young , Sung Chang Ohk , CHUN SUNG-MIN 
Published: November 2024

Abstract

DNA methylation plays a crucial role in the epigenetic regulation of gene expression and is closely associated with the development of cancer. Abnormal regulation of gene expression due to changes in DNA methylation patterns of specific genes has been frequently observed in tumor cells. However, the specific mechanisms underlying the induction of DNA methylation in certain genes have not been fully elucidated. This study aimed to investigate the potential of microRNAs (miRNAs) as statistically significant regulators guiding promoter methylation of specific genes. MiRNAs are known to specifically recognize DNA sequences and exhibit various degrees of complementarity. We performed Spearman's rank correlation between the expression levels of 734 microRNAs and the CpG island methylation levels of 20,587 genes, collected from 813 cell lines in the Cancer Cell Line Encyclopedia (CCLE) database. Subsequently, we validated the dependent relationship between the selected target microRNAs and gene clusters using linear regression analysis. We identified 25 target genes in which promoter methylation was induced by the expression of four target miRNAs (hsa-miR-200a, hsa-miR-200b, hsa-miR-200c, and hsa-miR-141) with statistically significant values. The correlations of the target pairs between methylation level of target genes and matched miRNAs were most pronounced in colorectal, gastric, lung, and ovarian cancers. Cancer-related genes, including ST14, OVOL1, and EPCAM, were identified as the target genes, confirming the possibility that promoter methylation of these genes is regulated by miRNA. Using bioinformatics-based screening analysis, we discovered target pairs that exhibited statistically significant changes in promoter methylation patterns due to specific miRNA expression. Furthermore, we confirmed the potential for miRNAs to regulate the expression of cancer-related genes through miRNA-induced promoter methylation. This expands our understanding of the mechanism underlying tumor development through methylation and provides a new perspective on the utilization of microRNAs in the field of cancer treatment.