bluuebunny/crossref_metadata_2025_split huggingface dataset:
An efficient visual servo tracker for herd monitoring by UAV
Authors: Luo Wei , Zhang Guoqing , Shao Quanqin , Zhao Yongxiang , Wang Dongliang , Zhang Xiongyi , Liu Ke , Li Xiaoliang , Liu Jiandong , Wang Penggang , Li Lin , Wang Guanwu , Wang Fulong , Yu Zhongde 
Published: May 2024

AbstractIt is a challenging and meaningful task to carry out UAV-based livestock monitoring in high-altitude (more than 4500 m on average) and cold regions (annual average – 4 °C) on the Qinghai Tibet Plateau. The purpose of artificial intelligence (AI) is to execute automated tasks and to solve practical problems in actual applications by combining the software technology with the hardware carrier to create integrated advanced devices. Only in this way, the maximum value of AI could be realized. In this paper, a real-time tracking system with dynamic target tracking ability is proposed. It is developed based on the tracking-by-detection architecture using YOLOv7 and Deep SORT algorithms for target detection and tracking, respectively. In response to the problems encountered in the tracking process of complex and dense scenes, our work (1) Uses optical flow to compensate the Kalman filter, to solve the problem of mismatch between the target bounding box predicted by the Kalman filter (KF) and the input when the target detection in the current frame is complex, thereby improving the prediction accuracy; (2) Using a low confidence trajectory filtering method to reduce false positive trajectories generated by Deep SORT, thereby mitigating the impact of unreliable detection on target tracking. (3) A visual servo controller has been designed for the Unmanned Aerial Vehicle (UAV) to reduce the impact of rapid movement on tracking and ensure that the target is always within the field of view of the UAV camera, thereby achieving automatic tracking tasks. Finally, the system was tested using Tibetan yaks on the Qinghai Tibet Plateau as tracking targets, and the results showed that the system has real-time multi tracking ability and ideal visual servo effect in complex and dense scenes.
The solitary solutions for the stochastic fractional Chen Lee Liu model perturbed by multiplicative noise in optical fibers and plasma physics
Authors: Mohammed Wael W. , Iqbal Naveed , Sidaoui Rabeb , Alshammary Monirah W. 
Published: May 2024

AbstractIn this paper, we consider the stochastic fractional Chen Lee Liu model (SFCLLM). We apply the mapping method in order to get hyperbolic, elliptic, rational and trigonometric stochastic fractional solutions. These solutions are important for understanding some fundamentally complicated phenomena. The acquired solutions will be very helpful for applications such as fiber optics and plasma physics. Finally, we show how the conformable derivative order and stochastic term affect the exact solution of the SFCLLM.
A Markov network approach for reproducing purchase behaviours observed in convenience stores
Authors: Johansson Dan , Takayasu Hideki , Takayasu Misako 
Published: May 2024

AbstractThe convenience store industry in Japan holds immense significance, making a thorough comprehension of customer purchase behaviour invaluable for companies aiming to gain insights into their customer base. In this paper, we propose a novel application of a Markov network model to simulate purchases guided by stopping probabilities calculated from real data. Each node in the Markov network represents different product categories available for purchase. Additionally, we introduce the concept of a “driving force,” quantifying the influence of purchasing product A on the likelihood of purchasing product B, compared to random purchasing. For instance, our analysis reveals that the inclusion of nutrient bars in a purchase set leads to, on average, a 13% reduction in tobacco purchases compared to random patterns. To validate our approach, we compare the simulated macro-level purchase behaviours with real point of Sale (POS) data obtained from a prominent convenience store giant, 7-Eleven. The dataset is comprised of roughly 54 million receipts, in which we focus on the product categories existing in this dataset rather than individual products. Our model successfully replicates the purchase size distribution for 99.9% of all purchases and the purchase counts across various product categories, demonstrating its efficacy in capturing broad purchase patterns.
Recent advances in solid–liquid triboelectric nanogenerator technologies, affecting factors, and applications
Authors: Yuan Zhuochao , Guo Lin 
Published: May 2024

AbstractConverting dispersed mechanical energy into electrical energy can effectively improve the global energy shortage problem. The dispersed mechanical energy generated by liquid flow has a good application prospect as one of the most widely used renewable energy sources. Solid–liquid triboelectric nanogenerator (S–L TENG) is an inspiring device that can convert dispersed mechanical energy of liquids into electrical energy. In order to promote the design and applications of S–L TENG, it is of vital importance to understand the underlying mechanisms of energy conversion and electrical energy output affecters. The current research mainly focuses on the selection of materials, structural characteristics, the liquid droplet type, and the working environment parameters, so as to obtain different power output and meet the power supply needs of diversified scenarios. There are also studies to construct a theoretical model of S–L TENG potential distribution mechanism through COMSOL software, as well as to obtain the adsorption status of different kinds of ions with functional groups on the surface of friction power generation layer through molecular dynamics simulation. In this review, we summarize the main factors affecting the power output from four perspectives: working environment, friction power generation layer, conductive part, and substrate shape. Also summarized are the latest applications of S–L TENG in energy capture, wearable devices, and medical applications. Ultimately, this review suggests the research directions that S–L TENG should focus on in the future to enhance electrical energy output, as well as to expand the diversity of application scenarios.
Orbital learning: a novel, actively orchestrated decentralised learning for healthcare
Authors: Chakshu Neeraj Kavan , Nithiarasu Perumal 
Published: May 2024

AbstractA novel collaborative and continual learning across a network of decentralised healthcare units, avoiding identifiable data-sharing capacity, is proposed. Currently available methodologies, such as federated learning and swarm learning, have demonstrated decentralised learning. However, the majority of them face shortcomings that affect their performance and accuracy. These shortcomings include a non-uniform rate of data accumulation, non-uniform patient demographics, biased human labelling, and erroneous or malicious training data. A novel method to reduce such shortcomings is proposed in the present work through selective grouping and displacing of actors in a network of many entities for intra-group sharing of learning with inter-group accessibility. The proposed system, known as Orbital Learning, incorporates various features from split learning and ensemble learning for a robust and secure performance of supervised models. A digital embodiment of the information quality and flow within a decentralised network, this platform also acts as a digital twin of healthcare network. An example of ECG classification for arrhythmia with 6 clients is used to analyse its performance and is compared against federated learning. In this example, four separate experiments are conducted with varied configurations, such as varied age demographics and clients with data tampering. The results obtained show an average area under receiver operating characteristic curve (AUROC) of 0.819 (95% CI 0.784–0.853) for orbital learning whereas 0.714 (95% CI 0.692–0.736) for federated learning. This result shows an increase in overall performance and establishes that the proposed system can address the majority of the issues faced by existing decentralised learning methodologies. Further, a scalability demo conducted establishes the versatility and scalability of this platform in handling state-of-the-art large language models.
Synchronous profiling of mRNA N6-methyladenosine modifications and mRNA expression in high-grade serous ovarian cancer: a pilot study
Authors: Yang Li , Liu Jingfang , Jin Yanlu , Xing Jie , Zhang Jiejie , Chen Xin , Yu Aijun 
Published: May 2024

AbstractThis study aimed to synchronously determine epitranscriptome-wide RNA N6-methyladenosine (m6A) modifications and mRNA expression profile in high grade serous ovarian cancer (HGSOC). The methylated RNA immunoprecipitation sequencing (MeRIP-seq) was used to comprehensively examine the m6A modification profile and the RNA-sequencing (RNA-seq) was performed to analyze the mRNA expression profile in HGSOC and normal fallopian tube (FT) tissues. Go and KEGG analyses were carried out in the enrichment of those differentially methylated and expressed genes. MeRIP-seq data showed 53,794 m6A methylated peaks related to 19,938 genes in the HGSOC group and 51,818 m6A peaks representing 19,681 genes in the FT group. RNA-seq results revealed 2321 upregulated and 2486 downregulated genes in HGSOC. Conjoint analysis of MeRIP-seq and RNA-seq data identified differentially expressed genes in which 659 were hypermethylated (330 up- and 329 down-regulated) and 897 were hypomethylated (475 up- and 422 down-regulated). Functional enrichment analysis indicated that these differentially modulated genes are involved in pathways related to cancer development. Among methylation regulators, the m6A eraser (FTO) expression was significantly lower, but the m6A readers (IGF2BP2 and IGF2BP3) were higher in HGSOC, which was validated by the subsequent real-time PCR assay. Exploration through public databases further corroborated their possible clinical application of certain methylation regulators and differentially expressed genes. For the first time, our study screens the epitranscriptome-wide m6A modification and expression profiles of their modulated genes and signaling pathways in HGSOC. Our findings provide an alternative direction in exploring the molecular mechanisms of ovarian pathogenesis and potential biomarkers in the diagnosis and predicting the prognosis of the disease.
Aortic pulse wave analysis and functional capacity of heart transplantation candidates: a pilot study
Authors: Alcici-Moreira Adriana Marques , Vitarelli Marcela Oliveira , Velloso Tiago Abreu , Carvalho-Ribeiro Igor Antônio , Dario Daniella Moura , Polese Janaine Cunha , Guimarães Hélio Penna , Pena José Luiz Barros , Tuesta Marcelo , de Rezende Bruno Almeida , Rodrigues-Machado Maria da Glória 
Published: May 2024

AbstractWe compared cardiovascular parameters obtained with the Mobil-O-Graph and functional capacity assessed by the Duke Activity Status Index (DASI) before and after Heart Transplantation (HT) and also compared the cardiovascular parameters and the functional capacity of candidates for HT with a control group. Peripheral and central vascular pressures increased after surgery. Similar results were observed in cardiac output and pulse wave velocity. The significant increase in left ventricular ejection fraction (LVEF) postoperatively was not followed by an increase in the functional capacity. 24 candidates for HT and 24 controls were also compared. Functional capacity was significantly lower in the HT candidates compared to controls. Stroke volume, systolic, diastolic, and pulse pressure measured peripherally and centrally were lower in the HT candidates when compared to controls. Despite the significant increase in peripheral and central blood pressures after surgery, the patients were normotensive. The 143.85% increase in LVEF in the postoperative period was not able to positively affect functional capacity. Furthermore, the lower values of LVEF, systolic volume, central and peripheral arterial pressures in the candidates for HT are consistent with the characteristics signs of advanced heart failure, negatively impacting functional capacity, as observed by the lower DASI score.
Measuring the prediction difficulty of individual cases in a dataset using machine learning
Authors: Kwon Hyunjin , Greenberg Matthew , Josephson Colin Bruce , Lee Joon 
Published: May 2024

AbstractDifferent levels of prediction difficulty are one of the key factors that researchers encounter when applying machine learning to data. Although previous studies have introduced various metrics for assessing the prediction difficulty of individual cases, these metrics require specific dataset preconditions. In this paper, we propose three novel metrics for measuring the prediction difficulty of individual cases using fully-connected feedforward neural networks. The first metric is based on the complexity of the neural network needed to make a correct prediction. The second metric employs a pair of neural networks: one makes a prediction for a given case, and the other predicts whether the prediction made by the first model is likely to be correct. The third metric assesses the variability of the neural network’s predictions. We investigated these metrics using a variety of datasets, visualized their values, and compared them to fifteen existing metrics from the literature. The results demonstrate that the proposed case difficulty metrics were better able to differentiate various levels of difficulty than most of the existing metrics and show constant effectiveness across diverse datasets. We expect our metrics will provide researchers with a new perspective on understanding their datasets and applying machine learning in various fields.
Evaluating the factor structure, reliability and validity of the Copenhagen Burnout Inventory-Student Survey (CBI-SS) among faculty of arts students of Ekiti State University, Ado-Ekiti, Nigeria
Authors: Oluwadiya Kehinde Sunday , Owoeye Omolara Kikelomo , Adeoti Adekunle Olatayo 
Published: May 2024

AbstractThe Copenhagen burnout inventory-student survey (CBI-SS) has shown promising psychometric properties in diverse student populations. This study aims to investigate the psychometric properties of the Nigerian version of the CBI-SS. This was a cross-sectional study of 635 students from Ekiti State University, Ado-Ekiti, Nigeria. Confirmatory factor analysis (CFA) was utilized to assess the CBI-SS validity. The reliability score of the CBI-SS was 0.957, ranging from 0.862 to 0.914 for the subscales. Correlation coefficients among the four CBI-SS factors ranged from 0.507 to 0.713. The CFA indicated an adequate goodness-of-fit for the four-factor model of the CBI-SS with the sample data. However, Item 10 was removed due to unacceptably low Average Variance Extracted score. The four factors demonstrated a negative correlation with both General Academic Self-Efficacy Scale and Cumulative Grade Point Average. Furthermore, both self-reported burnout and perceived course stress showed associations with the CBI-SS, where lower levels of burnout corresponded with lower median scores on the CBI-SS scales. This study underscores the significance of the CBI-SS in evaluating student burnout within our student population. The findings indicate that the CBI-SS is a highly reliable and valid instrument for assessing student burnout, suggesting its potential for effective utilization in the Nigerian academic context.
Respiratory pathogen and clinical features of hospitalized patients in acute exacerbation of chronic obstructive pulmonary disease after COVID 19 pandemic
Authors: Kim Soo Jung , Kim Taehee , Choi Hayoung , Shin Tae Rim , Kim Hwan Il , Jang Seung Hun , Hong Ji Young , Lee Chang Youl , Chung Soojie , Choi Jeong-Hee , Sim Yun Su 
Published: May 2024

AbstractRespiratory infections are common causes of acute exacerbation of chronic obstructive lung disease (AECOPD). We explored whether the pathogens causing AECOPD and clinical features changed from before to after the coronavirus disease 2019 (COVID-19) outbreak. We reviewed the medical records of patients hospitalized with AECOPD at four university hospitals between January 2017 and December 2018 and between January 2021 and December. We evaluated 1180 patients with AECOPD for whom medication histories were available. After the outbreak, the number of patients hospitalized with AECOPD was almost 44% lower compared with before the outbreak. Patients hospitalized with AECOPD after the outbreak were younger (75 vs. 77 years, p = 0.003) and more often stayed at home (96.6% vs. 88.6%, p < 0.001) than patients of AECOPD before the outbreak. Hospital stay was longer after the outbreak than before the outbreak (10 vs. 8 days. p < 0.001). After the COVID-19 outbreak, the identification rates of S. pneumoniae (15.3 vs. 6.2%, p < 0.001) and Hemophilus influenzae (6.4 vs. 2.4%, p = 0.002) decreased, whereas the identification rates of P. aeruginosa (9.4 vs. 13.7%, p = 0.023), Klebsiella pneumoniae (5.3 vs. 9.8%, p = 0.004), and methicillin-resistant Staphylococcus aureus (1.0 vs. 2.8%, p = 0.023) increased. After the outbreak, the identification rate of influenza A decreased (10.4 vs. 1.0%, p = 0.023). After the outbreak, the number of patients hospitalized with AECOPD was lower and the identification rates of community-transmitted pathogens tended to decrease, whereas the rates of pathogens capable of chronic colonization tended to increase. During the period of large-scale viral outbreaks that require quarantine, patients with AECOPD might be given more consideration for treatment against strains that can colonize chronic respiratory disease rather than community acquired pathogens.
Clinico-epidemiological evaluation of pharmaceutical/non-pharmaceutical poisoning in a referral poisoning emergency in the Central part of Iran
Authors: Eizadi-Mood Nastaran , Sanjari Hamed , Feizi Awat , Yazdi Razieh , Dorostkar Amin , Mahvari Razieh , Mirmoghtadaee Parisa , Meamar Rokhsareh 
Published: May 2024

AbstractThe pattern of poisoning varies in different societies. In this study, we investigated the clinical-epidemiological features and outcomes of poisoned patients based on the substances involved, whether pharmaceutical or non- pharmaceutical toxins. This cross-sectional study involved a retrospective chart review of all poisoned patients who presented to the poisoning emergency hospital in the center of Iran between January 2015 and December 2019. We collected data on socio-demographics, the nature of the poisoning, and the outcomes. Backward stepwise binary regression analysis was conducted to predict the mortality. Throughout the study period, 5777 patients with acute poisoning met the inclusion criteria. Of these, 3524 cases (61%) were attributed to pharmaceutical, and 2253 cases (39%) were due to non-pharmaceutical poisoning. The majority of pharmaceutical poisonings (82.9%) were intentional, whereas non-pharmaceutical poisonings accounted for 46.2% of intentional exposures (P < 0.001). Patients with non-pharmaceutical poisoning were predominantly men, older in age, and had a history of addiction compared to those with pharmaceutical poisoning (P < 0.001). In binary logistic regression analysis, patients poisoned by non-pharmaceutical substances had a significantly higher risk of mortality [Odds ratio, 3.14; (95% CI 1.39–7.10); P = 0.006] compared to those poisoned by pharmaceutical substances (P < 0.001). The pattern of poisoning differs in terms of age and gender when comparing pharmaceutical to non-pharmaceutical poisoning. Patients poisoned by non-pharmaceutical may have a worse outcome compared to those poisoned by pharmaceutical substances.
Sexual dimorphism of the human fetal pelvis exists at the onset of primary ossification
Authors: Kanahashi Toru , Matsubayashi Jun , Imai Hirohiko , Yamada Shigehito , Otani Hiroki , Takakuwa Tetsuya 
Published: May 2024

AbstractHuman adolescent and adult skeletons exhibit sexual dimorphism in the pelvis. However, the degree of sexual dimorphism of the human pelvis during prenatal development remains unclear. Here, we performed high-resolution magnetic resonance imaging-assisted pelvimetry on 72 human fetuses (males [M]: females [F], 34:38; 21 sites) with crown-rump lengths (CRL) of 50–225 mm (the onset of primary ossification). We used multiple regression analysis to examine sexual dimorphism with CRL as a covariate. Females exhibit significantly smaller pelvic inlet anteroposterior diameters (least squares mean, [F] 8.4 mm vs. [M] 8.8 mm, P = 0.036), larger subpubic angle ([F] 68.1° vs. [M] 64.0°, P = 0.034), and larger distance between the ischial spines relative to the transverse diameters of the greater pelvis than males. Furthermore, the sacral measurements indicate significant sex-CRL interactions. Our study suggests that sexual dimorphism of the human fetal pelvis is already apparent at the onset of primary ossification.
A non-canonical role of the inner kinetochore in regulating sister-chromatid cohesion at centromeres
Authors: Yan Lu , Yuan Xueying , Liu Mingjie , Chen Qinfu , Zhang Miao , Xu Junfen , Zeng Ling-Hui , Zhang Long , Huang Jun , Lu Weiguo , He Xiaojing , Yan Haiyan , Wang Fangwei 
Published: May 2024

AbstractThe 16-subunit Constitutive Centromere-associated Network (CCAN)-based inner kinetochore is well-known for connecting centromeric chromatin to the spindle-binding outer kinetochore. Here, we report a non-canonical role for the inner kinetochore in directly regulating sister-chromatid cohesion at centromeres. We provide biochemical, X-ray crystal structure, and intracellular ectopic localization evidence that the inner kinetochore directly binds cohesin, a ring-shaped multi-subunit complex that holds sister chromatids together from S-phase until anaphase onset. This interaction is mediated by binding of the 5-subunit CENP-OPQUR sub-complex of CCAN to the Scc1-SA2 sub-complex of cohesin. Mutation in the CENP-U subunit of the CENP-OPQUR complex that abolishes its binding to the composite interface between Scc1 and SA2 weakens centromeric cohesion, leading to premature separation of sister chromatids during delayed metaphase. We further show that CENP-U competes with the cohesin release factor Wapl for binding the interface of Scc1-SA2, and that the cohesion-protecting role for CENP-U can be bypassed by depleting Wapl. Taken together, this study reveals an inner kinetochore-bound pool of cohesin, which strengthens centromeric sister-chromatid cohesion to resist metaphase spindle pulling forces.
Secure transmission design in cooperative NOMA networks: Orienting toward user requirements
Authors: Jiang Dan , Gao Yuanyuan , Li Guoxin , Sha Nan , Cai Jihao , Ding ChengFei 
Published: May 2024

AbstractThis paper presents a full‐duplex and multi‐antenna relay‐aided transmission scheme for the user‐oriented perspective in cooperative non‐orthogonal multiple access (NOMA) systems. Relying on the service requirements, two legitimate users with security demands (SU) and quality of service (QoS) demands (QU) are paired for NOMA execution. The security of SU is enhanced through inverse power allocation of the conventional NOMA. The QoS requirements for QU are guaranteed, simultaneously. Then, the precoding design at the multi‐antenna relay has been exploited to improve the reliability demands of SU. Closed‐form expressions for SU's outage probability (OP) and intercepted probability, as well as QU's OP, are derived. The security–reliability trade‐off is also presented. Additionally, performance analysis under the half‐duplex and multi‐antenna scheme is provided as a benchmark for comparison. Finally, numerical simulations are performed to confirm the accuracy of the theoretical derivations under different schemes. Results demonstrate the superiority of the proposed scheme over benchmark schemes in terms of improving the security and reliability of SU, as well as saving power consumption of the system.