bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of Real-time Ship Detection Strategy Based on Modified YOLOv7 Architecture
Authors: Xing Bowen , Wang Wei , xing Qingsong , Sun Yue , Han Jitao , Guan Lianwu 
Published: May 2024

Abstract

Ship detection is crucial in inland waterway shipping management, and it is not easy to balance accuracy and real-time performance in complex water conditions. This paper proposes a real-time ship detection method based on improved YOLOv7 to address the problem. Firstly, GhostNet is introduced into the backbone network for feature extraction, and then distribution shifting convolution is introduced into the feature fusion network to achieve a lightweight model. Secondly, an attention mechanism is introduced into the feature fusion network to compensate for the accuracy loss caused by the lightweight model. Finally, the loss function is improved to make the detection model more applicable to the ship dataset. Compared with the traditional YOLOv7 detection model, the experimental results of the HPRship dataset show that the computation volume is reduced by 3.88 × 10 10 , the model parameter volume is reduced by 5.7 × 10 6 , and the detection accuracy mAP0.5 is increased by 0.7% to 98.80%. YOLOv7-GDAW model achieves a good balance between lightweight and detection accuracy, allowing it to accurately and timely complete ship detection tasks. It is suitable for deployment on small devices with limited storage and computing capacity.
An Integrated Static and Dynamic Graph Fusion Approach for Traffic Flow Prediction
Authors: Che Xingliang , Xiong Wen , Zhang Xian , Zhang Xitong 
Published: May 2024

Abstract

The major challenge in accurate traffic flow prediction lies in effectively capturing the dynamic spatiotemporal correlations within the traffic system. In this paper, we propose a novel traffic flow prediction method based on the fusion of static and dynamic graphs. Firstly, a predefined graph structure is used as the initial static graph. Secondly, a temporal graph convolution module constructed in a data-driven manner is designed, further implementing a dynamic graph structure that varies with the input data, thoroughly constructing the spatial relations between traffic flow sequence data. Finally, specific spatial and temporal relations are modeled from the perspective of graphs, effectively merging static and dynamic spatial relations. The performance of our method was validated using two real public datasets, PEMS04 and PEMS08. Experimental results demonstrate that our model outperforms existing traffic flow prediction models by 9.32% in terms of prediction error when compared to 18 benchmark methods.
Effect of Faults and Fractures on Springwater Quality and Discharge of West Phaileng, Mizoram
Authors: Sailo Lalsangzela , Vanlalhruaia H. 
Published: May 2024

Abstract

The North Eastern part of India compromises of hilly slopes and ridges. The main source of water is of river, streams, rainfall and springs. Due to change in environmental variables, many springs and streams are drying up as discharge decreases. A lithological study shows the area to consist of clay, silt, shale, siltstone and sandstone where porosity is low leading to low yielding capacity. Hydrogeological and geochemical composition studied represents the water within this region as immature and major ions composition shows Na+>Mg2+>Ca2+>Mn2+>Fe2+>K+ in cations and anoins HCO3->Cl->SO42->NO3->PO43-. The mineral saturation indices constructed using PHREEQC showed supersaturation with dolomite, siderite and vivianite. The hydrogeochemical formation mechanism using Gibbs Diagram and Piper diagram suggested rock weathering type. Principal Component Analysis (PCA) was performed as a multivariate analysis to determine the correlation between different components of hydrogeochemistry. The assessment of springwater quality using water quality index (WQI) shows good quality for most of the samples. A conceptual recharge model was the constructed anticipating mountain front recharge as major recharge of spring water. The springwater hydrograph was modelled using Maillets. It was observed that two types of flow, firstly the initial larget slope corresponding to conduit flow and secondly smaller slope to the diffuse flow was system. Thus the main mechanism of recharge in the hilly regions of West Phaileng was attributed to the mountain front recharge which is influenced by faults and fractures.
Actual prestress force detection of tendons in prestressed beams based on static responses using genetic algorithm
Authors: Sharifi Mohamad , Mahmoudi Mussa , Sahab Mohamad Ghasem 
Published: May 2024

Abstract

The determination and monitoring of prestress force in tendons of prestressed concrete (PC) structures have become a key focus for researchers in recent years. While modern structures are equipped with sensors to track prestress losses, older structures require non-destructive testing methods to assess these forces. This paper introduces a novel approach for detecting actual prestress force in tendons of a prestressed concrete beam using static displacement data under experimental loads. The method eliminates the need for pre-installed sensors or destructive tests, offering a more cost-effective solution. An algorithm based on genetic algorithm (GA) is developed to accurately determine the prestress force of tendons. Laboratory testing demonstrates that the proposed algorithm can detect prestress losses with high accuracy, even in the presence of intentional measurement errors up to ten percent.
Myanmar XNLI: Building a Dataset and Exploring Low-resource Approaches to Natural Language Inference with Myanmar
Authors: Htet Aung Kyaw , Dras Mark 
Published: May 2024

Abstract

Despite dramatic recent progress in NLP, it is still a major challenge to apply Large Language Models (LLM) to low-resource languages. This is made visible in benchmarks such as Cross-Lingual Natural Language Inference (XNLI), a key task that demonstrates cross-lingual capabilities of NLP systems across a set of 15 languages.
In this paper, we extend the XNLI task for one additional low-resource language, Myanmar, as a proxy challenge for broader low-resource languages, and make three core contributions. First, we build a dataset called Myanmar XNLI (myXNLI) using community crowd-sourced methods, as an extension to the existing XNLI corpus. This involves a two-stage process of community-based construction followed by expert verification; through an analysis, we demonstrate and quantify the value of the expert verification stage in the context of community-based construction for low-resource languages. We make the myXNLI dataset available to the community for future research. Second, we carry out evaluations of recent multilingual language models on the myXNLI benchmark, as well as explore data-augmentation methods to improve model performance. Our data-augmentation methods improve model accuracy by up to 2 percentage points for Myanmar, while uplifting other languages at the same time.Third, we investigate how well these data-augmentation methods generalise to other low-resource languages in the XNLI dataset.
As a prognostic biomarker for malignant tumors, DUXAP8 can mediate the proliferation and migration of prostate cancer
Authors: Wen Yaoan , Wang Shenfan , Zhan Shuyuan , Zheng Song 
Published: May 2024

Abstract

Background: The prognostic value of lncRNA double homeobox A pseudogene 8 (DUXAP8) remains inconsistent. Moreover, the role of DUXAP8 in prostate cancer (PCa) is poorly understood. We performed a meta-analysis to elucidate the clinical value of DUXAP8 in malignancies and evaluated the effect of DUXAP8 in PCa in this study.
Methods: PubMed, Embase, and Web of Science were searched to identify eligible studies. Hazard ratios (HR) with 95% confidence interval (95%CI) and clinicopathological factors were extracted. Subgroup analysis according to sample size, cancer type, cancer morphology and HRs source were conducted. The DUXAP8 expression in PCa tissues, and the relationship between DUXAP8 expression and clinical parameters were performed using TCGA dataset. Then transwell, wound healing and EdU assays were used for cells migration and proliferation analysis. In vivo xenograft assay was also employed to evaluate the DUXAP8 role in PCa.
Results: A total of 20 eligible studies involving 1226 patients were incorporated in the meta-analysis. We found that DUXAP8 overexpression was significantly associated with poor overall survival (HR = 2.50, 95%CI: 1.90-3.28), lymph node metastasis (OR = 2.76, 95%CI: 1.71-4.46) , histological grade (OR = 2.20, 95%CI: 1.42–3.40) and TNM staging (OR = 2.60, 95%CI 1.96-3.46) in malignancies. By analyzing the TCGA databases, and confirming in cell lines, we found that DUXAP8 was overexpressed in PCa. its overexpression was associated with poor biochemical recurrence (p = 0.04), pathological stage (p = 0.035), Gleason score (p = 0.009), T stage (p = 0.003) and lymph node metastasis (p = 0.024). DUXAP8 knockdown inhibited the PCa cell migration and invasion in vitro, and cell growth both in vitro and vivo.
Conclusion: These results indicate that DUXAP8 may be a potential predictor for poor prognosis and therapeutic target in tumor including PCa.
‘Everyone needs to be educated’: pupil’s voices on menstrual education
Authors: Brown Natalie , Forrest Laura J , Williams Rebekah , Piasecki Jessica , Bruinvels Georgie 
Published: May 2024

Abstract

Background Physical, affective and behavioural symptoms associated with the menstrual cycle can significantly impair the daily lives of individuals. Within school, the menstrual cycle has been reported to affect attendance, behaviour and participation in physical activity. However, investigations have lacked understanding why the menstrual cycle negatively influences these aspects of schools to create recommendations for change. Through obtaining the pupil voice, this study aimed to understand young people’s perceptions and experiences of menstrual education received in schools, this included perceived gaps in their own understanding. A secondary aim was to explore first-hand how girls felt their periods affected participation in physical education (PE) in school.Methods To address the aims of this study, a qualitative descriptive study was conducted. Nine focus groups with female pupils were completed across six school locations in England and Wales, including primary and secondary schools. A range of elements relating to the menstrual cycle, education at school and PE were discussed by pupils.Results Similarities were reflected across focus groups in terms of current (lacking) education, lesson style and preferences, comfort of conversations, lack of school support and impact on school and PE. Four main themes were developed a) Education preferences, b) Period positive environment c) Personal experiences and d) Impact on school.Conclusion The findings highlight the lack of menstrual education received and subsequent impact on menstruation and menstrual-related symptoms in school and PE participation. The abundance of information requested by pupils highlights the deficit in information provided to young people to understand and manage periods in school and in relation to staying physically active. Schools can utilise information from the current study to create period positive environments, with consideration given to lesson content and format, but also specifically in PE to help support girls stay physically active.
Effects of a static and an magnetic field electron beam on the linear propagation of dust acoustic mode
Authors: El-Shorbagy Kh. H. , Mahassen Hania , Elbendary A. A. 
Published: May 2024

Abstract

Dusty plasma consist of electron, ions, electron beam as a separate component and charged dust grains observed in several astrophysical and space environments such as nebulas, planetary rings, and planetary ionosphere. The physical and optical properties of plasma are depend on dynamic of species in the discharge volume, then the presence of an electron beam and external static magnetic field in a dusty plasma can modify the plasma structure. In this study, we proved the linear propagation in the non-collision dusty plasma. The results revealed that the propagation of acoustic waves in the dusty plasma can be controlled by adjusting the electron number density of the electron beam and the external magnetic field.
Perspectives of substance use disorder counselors on the benefits and drawbacks of medications for opioid use disorder
Authors: Cardamone Nicholas C. , Stewart Rebecca E. , Kampman Kyle M. , Marcus Steven C. 
Published: May 2024

Abstract

Background:
Medications for opioid use disorder (MOUD) are among the best tools we have to combat the opioid epidemic. Yet, use of MOUD among people with opioid use disorder (OUD) remains low. Interventions to increase MOUD access in the United States have largely focused on improving organizational capacity and addressing funding barriers, yet stigma toward MOUD may inhibit uptake even where MOUD is readily available. Substance use disorder (SUD) treatment counselors likely have considerable influence on a client’s choice to initiate and adhere to MOUD, but beliefs that counselors convey about MOUD in interaction with clients are understudied. The current study explores what advantages and disadvantages that SUD treatment counselors communicate about buprenorphine, methadone, and naltrexone.
Methods:
From June to December 2021, we surveyed counselors from publicly-funded SUD treatment agencies under a municipality-wide mandate to offer MOUD to all clients with OUD. Counselors were asked to describe, in a free-response format, the most important advantages and disadvantages to communicate to their clients about taking buprenorphine, methadone, and naltrexone. Counselor responses were coded for one or more advantage and disadvantage.
Results:
A total of 271 SUD counselors from 29 agencies completed the survey, generating 1,995 advantages and disadvantages across three types of MOUD. The most frequently reported advantage across all three types of MOUD was their ability to reduce cravings and illicit drug use. The most frequently reported disadvantage related to the potential for some types of MOUD to develop long-term medication dependence.
Conclusions:
As the availability and variety of MOUD treatment options continue to expand, it is important that SUD counselors are equipped with evidence-based recommendations for OUD care. We identified misalignments with the MOUD-prescribing evidence base and stigmatizing language toward MOUD within counselors’ responses, highlighting the potential to refine training materials for MOUD and mitigate stigmatizing beliefs.
Surface fluxes and flow structure for stably stratified near-calm conditions
Authors: Mahrt Larry 
Published: May 2024

Abstract

The dependence of fluxes on the wind speed near the surface of the stable nocturnal boundary layer can be organized in terms of a threshold wind speed. When the wind speed is smaller than the threshold speed (near calm conditions), the eddies at the observational level tend to be decoupled from the surface. When the wind speeds are larger than the threshold value, the main eddies tend to directly interact with the underlying surface. As an example, the threshold wind speed at the 2-m observational level is typically 1 m s-1 Investigation of the heat flux as a function of the wind speed is straightforward. The dependence of the friction velocity u* on the wind speed requires somewhat different strategies. The friction velocity is derived from the momentum flux averaged in different ways. For near calm conditions, the stress vector and wind vector are often not aligned. The wind direction frequently varies rapidly with height near the surface for near-calm conditions, and meandering of the wind vectors can sweep out a range of wind directions over a short period of time. Individual time series for near-calm wind speeds are often erratic. Considerable averaging of records is required for emergence of the relation between u* and the mean flow.
Tip-Over Stability Estimation and Simulation of a Manipulator using the Mean Normal Ground Reaction criterion.
Authors: García-Hernández Juan Carlos , Gonzalez-Villela Victor Javier , Souza-Jimenez Jose Antonio , Meda-Campaña Jesús Alberto 
Published: May 2024

Abstract

The possibility of a robot failing to perform its task can be influenced by factors related to its movement and the load it carries. This concern is particularly important in mobile robots where these factors are more noticeable. Many researchers have conducted studies to quantify the loss of stability in different types of robots. However, these studies often require expensive and complex equipment for replication. Therefore, this research proposes an alternative approach to estimate tip-over stability using MATLAB/Simulink.
The methodology involves using a 3-degree-of-freedom serial manipulator placed on an Angular Positioning Table. The stability measure is determined by applying a criterion based on the average normal reactions at the base of the manipulator. Case studies are conducted to simulate operating conditions and assess the potential for tipping over based on the trajectory between two desired points. Finally, a case is presented where the obtained stability values are used to mitigate this effect by adjusting the manipulator’s trajectory.
The Impact of Sleep Duration and Dietary Patterns on the Risk of Metabolic Syndrome in Middle-Aged and Elderly Adults: A Decision Tree Analysis
Authors: Zhu Hao , Zhang Li , Zhu Tongying , Jia Linlin , Zhang Jiaye , Shu Li 
Published: May 2024

Abstract

The aim of this study was to investigate the relationship between sleep duration and dietary patterns and the prevalence of metabolic syndrome (MetS) in middle-aged and elderly adults in Bengbu city. This study, a cross-sectional analysis, utilized information from the “Community-based Cardiovascular and Health Promotion Study 2019” (COCHPS 2019), carried out in Bengbu, Anhui Province, China. The definition of MetS adhered to the criteria of Guidelines for the Prevention and Treatment of Dyslipidemia in Chinese Adults (2016 Revision). Dietary information was collected from 24-hour dietary records spanning three successive days. Principal component analysis (PCA) served to identify dominant dietary patterns. Logistic regression model was used to analyze the associations of sleep duration and dietary patterns with MetS, and decision tree model was used to analyze the influencing factors of MetS. The prevalence rate of MetS was 13.4% among the 9132 middle-aged and elderly adults over 45 years of age. Participants were divided into short (< 6 h/d), normal (6–8 h/d), and long (> 8 h/d) groups based on their daily sleep duration. Three dietary patterns were identified by PCA, namely fruit-milk pattern, tubers-meat pattern and vegetable-cereal pattern. After adjusting for covariates, logistic regression analysis showed that long sleep duration had statistically significant negative effects on MetS. Fruit-milk pattern and vegetable-cereal pattern were negatively associated with MetS, while tubers-meat pattern showed a positive correlation with MetS. The results of decision tree model analysis showed that vegetable-cereal pattern is the most important influencing factor for MetS, followed by marital status, tubers-meat pattern, fruit-milk pattern, exercise, sleep duration and gender. In addition, the decision tree model also screened out five types of high-risk groups of MetS. The results of our study indicate that normal sleep duration and consumption of either a fruit-milk or vegetable-cereal diet may lower the likelihood of Mets in middle-aged and elderly adults.
Development of a Loop-Mediated Isothermal Amplification Technique for Sex Detection in Cervidae Species
Authors: Zorkóczy Orsolya Krisztina , Gyurcsó Adrienn , Ózsvári László , Lehotzky Pál , Raveendranathanpillai Sanil , Zenke Petra 
Published: May 2024

Abstract

Determining sex in Cervidae species is crucial for wildlife management, conservation, breeding programs, disease surveillance, and forensic investigations. While existing genetic sexing methods have proven effective, they often involve time-consuming and resource-intensive processes. In response to the growing need for a more efficient and cost-effective technique, this study aimed to develop a novel loop-mediated isothermal amplification (LAMP) method for sex detection in various deer species. We designed LAMP primers specific to Cervidae based on sex chromosome-located genes, AmelogeninX, and SRY. Analytical specificity was confirmed using 108 samples from red deer, roe deer, and fallow deer, and species specificity was also tested in other deer and mammal species. Sex determination results were fast (40 minutes) and accurate (100% reliability). This technique has the advantage of allowing researchers to identify the sex of different deer species using the same method. Using the isothermal amplification properties of LAMP, this new method provides a simple, quick, and accurate tool to help researchers, wildlife managers, and forensic investigators with important sex-related questions in cervid populations.
Integrating Agglomerative Clustering with Temporal Deep Learning Models for System Failure Detection
Authors: Pithode Kamiya , patheja Pushpinder Singh 
Published: May 2024

Abstract

This research introduces a pioneering approach to system failure detection by integrating agglomerative clustering with temporal deep learning models, leveraging hierarchical log analysis. Traditional methods of log analysis for failure detection heavily rely on manual inspection or straightforward machine learning models that often overlook the rich temporal dynamics and inherent structures within log data. Recognizing this gap, our study proposes a novel methodology that employs agglomerative clustering to preprocess system logs, grouping similar log messages based on content and temporal characteristics. This preprocessing step not only aids in uncovering common patterns and anomalies within the logs but also optimizes the input feature space for subsequent deep-learning analysis. We further enhance the predictive capabilities of our models by incorporating interpolated timestamps into Recurrent Neural Networks (RNN) and Convolutional Neural Networks (CNN), capturing the nuanced temporal behaviors indicative of system health. The integration of cluster-based features with temporal deep learning models presents a dual advantage: it significantly improves the accuracy of failure detection and offers deeper insights into the underlying causes of system anomalies. Through rigorous evaluation of the Hadoop Distributed File System (HDFS) log dataset, our approach demonstrates superior performance compared to existing methods, achieving noteworthy advancements in precision, recall, and F1 score. This research not only contributes to the field of automated system monitoring and diagnosis by introducing an effective method for analyzing complex log data but also paves the way for further exploration into the integration of hierarchical clustering techniques with deep learning for enhanced interpretability and predictive performance in various domains.