bluuebunny/crossref_metadata_2025_split huggingface dataset:
Seismic hazard assessment for Iran in terms of macroseismic intensityy
Authors: Shabani Elham , Albarello Dario , Mahsuli Mojtaba , Eghbali Negar , Varzandeh Saeed Hosseini , Farnetani Federico 
Published: March 2024

Abstract
We present the results of probabilistic seismic hazard assessment for Iran based on a statistical procedure specifically developed to manage macroseismic intensity data. This procedure accounts for the unique characteristics of such data, which are ordinal, discrete, and confined within a finite interval, ensuring a logically coherent approach throughout the analysis. The results of our assessment are then compared with hazard maps generated using a standard approach, allowing for the illumination of significant differences observed both on a national scale and within individual cities. This comparative analysis will be useful in identifying areas of utmost concern, where further studies are strongly recommended to yield hazard estimates of greater robustness and reliability. By pinpointing these critical scenarios, we aim to guide future research endeavors towards providing more accurate and dependable seismic hazard estimates. Identifying these critical situations facilitates the prioritization of resources and interventions, ultimately enhancing seismic risk mitigation efforts across Iran.
Patients' Associations as Co-Creators of Knowledge: Tools and Insights into Stakeholders’ Engagement Process. The Experience of the ProSafe Project for Advancing Treatment Safety in Proximity Medicine
Authors: Moretti Francesca , Colpo Silvia , Montresor Sara , Facchinello Daniela , Robello Raffaella , Mazzi Mariangela , Tardivo Stefano , Stagi Lisa , De Stefano Luisa , Zotti Andrea Ilaria , Ambroso Luigi , Destro Cristina , Leone Salvo , Petruzzelli Davide , Moretti Ugo , Rimondini Michela 
Published: March 2024

Abstract

Background. Active involvement of stakeholders in research is crucial to validate findings and facilitate their practical application for enhancing the health of the participating community. Despite a growing body of evidence on the implementation of participatory research (PR) in various contexts, evidence on practical tools and strategies for translating PR principles into practice is limited. The main aim of the study is to provide a detailed description of the co-creation process of a Community-Based Participatory Research (CBPR) project, named ProSafe, emphasizing community engagement actions and proposing practical tools and strategies for fostering collaboration. The ProSafe project involves academic researchers, Presidents and members of four Patient Associations (Patient Safety Council, PSC), and a pharmaceutical company which supported the project and facilitated the partenership. The study involves the co-creation of a comprehensive survey exploring and comparing community and healthcare professional perspectives on therapeutic safety challenges arising from the territorial reorganization of the proximity network foreseen by Italian Resilience and Recovery Plan. Results: The structured and problem-oriented methodology of ProSafe identifies several practical tools and strategies for survey and project co-creation, including a SWOT analysis to systematically assess strengths, weaknesses, opportunities, and threats, and develop improvement strategies from the co-researchers’ perspective. A framework named OPERA-PACT (Opening a Participatory and Equitable Research Agreement based on Partnership, Awareness, Collaboration, and Trust) was co-created with the PSC to provide a structured way for sharing a formal agreement and commitment toward a set of principles, values, and attitudes that characterize a collaborative partnership. Within the framework, a commitment to continuous monitoring, verification, and feedback is valuable, as it plays a key role in promoting virtuous cycles of improvement and fostering partnership and involvement over the long-term. Conclusions: All instruments, strategies, and methodological insights proposed in the paper may serve as useful and practical support to ensure communities may have increasingly strong voices in research, contributing to producing valid and translational results. The process of partnership identity built with the implementation of OPERA-PACT may help synchronize team members to the right atmosphere and create the basis for future efficient collaboration.
Research on moving liquid level detection method of viscometer in dynamic scene
Authors: Liu Xia , Jing Rongyao , Zhang Kun , Zhao Qinjun , Sun Mingxu 
Published: March 2024

Abstract
In order to solve the problem of false detection of the moving liquid level caused by the vibration of the constant temperature water bath, this paper combines the Type-2 Fuzzy Gaussian Mixture Model (T2-FGMM) and Markov Random Field (MRF) to study a new background modeling method for detecting the moving liquid level in dynamic scenes. The method first considers the output of T2-FGMM as the initial labeling domain of MRF, and then combines the local energy of the labeling domain with the observation energy. The key of this method is to combine the spatiotemporal prior of T2-FGMM with the observation. Comparative experimental results show that the proposed algorithm has better dynamic background detection effect than traditional frame difference method and Vibe algorithm, and can effectively eliminate the influence of the vibration of the constant temperature water bath on the detection of the moving liquid level of the viscometer.
Characterization of the scale system and driving mechanism of wells canals settlement in Turpan oasis
Authors: liu bo , Huang Fojun , Ye Mao , Guo Jianghao , Sha Beining , Wang Wanying 
Published: March 2024

Abstract
Background
Rapid urbanization and industrialization have exacerbated the competition for water resources within the oasis, which has become a major problem for the oasis villages to achieve sustainable development .As a typical closed oasis, the relationship between water and settlement in the Turpan Basin is very sensitive.Therefore, this study is based on multi-period remote sensing imagery and economic data using the bit order-size law and geographic detector the characteristics of spatial and temporal variability of oasis village settlements within the basin and their influencing factors.
Results
The results show that (1) the number and area of oasis countryside settlements in the Turpan Basin have increased rapidly in the past 35 years, but the spatial distribution is uneven, presenting a trend of retrospective growth, forming the spatial characteristics of fewer north and south, and the central part of the countryside along the Flaming Mountains-Salt Mountain presenting the distribution of bead-like agglomerations.(2)The dominant position of larger settlements is obvious, and the number and size of low-grade settlements show rapid and disorderly expansion, resulting in the fragmentation of the size of settlement patches and the widening gap between the first and last settlements.(3) Height, slope, and groundwater are the main natural constraints for the formation of rural settlement scale patterns in the Turpan Basin, and distance to government, roads, artificial canals, and cultivated land area are key socio-humanistic drivers.(4) Settlement evolution in the Aragou-Baiyanghe basin and the Daheyan-Tarlang basin is driven by height and cultivated land area; while shifts in water resource utilization have had the most prominent impact on the formation of spatial patterns of settlement sizes in the Meiyaogou-Ertanggou basin, and in the Kekeya-Kanerqi basin.
Condusions
The research results are of great significance for optimizing the rural settlement structure and realizing the sustainable development of oasis villages in arid areas
Conjunctive effect of harvesting date and supplementary irrigation in different growth stages on peanut (Arachis hypogaea L.) under rainfed conditions
Authors: Charvadeh Mehrab Mehri , Rad Marefat Mostafavi , Zakerin Hamid Reza , Sayfzadeh Saeed , Valadabady Seyed Alireza 
Published: March 2024

Abstract

This experiment carried out as split factorial based on randomized complete block design with three replications in the experimental field of the Agricultural and Natural Resources Research and Education Center of Guilan Province, Astara, Iran. Four levels of irrigation including rain-fed condition (IR0), irrigation at the flowering stage (IRF), irrigation at the pod formation stage (IRP), and irrigation at the flowering stage + irrigation at the pod formation stage (IRF + IRp) in the main plot and three levels of harvesting date inclusive of August 22 (HD1), September 6 (HD2) and September 21 (HD3) in the sub plot, comprised experimental treatments. Result indicated that all measured physiological characteristics improved under supplementary irrigation conditions except unsaturated oleic acid and saturated palmitic acid. The greatest biological yield (8091.67 kg ha− 1), seed yield (2375 kg ha− 1), oil yield (1181.60 kg ha− 1), protein yield (458.33 kg ha− 1) and unsaturated linoleic acid (30.94%) were obtained in response to (IRf + IRp) × HD3 interaction. Hence, two stages of supplementary irrigation (IRf + IRp) and late harvesting date (HD3) increased biological yield by 64.26%, seed yield by 32.33%, oil yield by 76.88% and protein yield by 63.31%. Whereas, the greatest unsaturated oleic acid (58.35%) was achieved in the first harvesting date (HD1) and rainfed conditions and the quality of peanut oil enhanced in response to water deficit. Generally, the results revealed that the supplementary irrigation had great potential for increasing plant growth period and improving peanut yield under rainfed conditions. Hence, supplementary irrigation along with delay in harvesting date could be recommended to increase crop productivity and sustainability of peanut yield under rainfed conditions.
Mild SARS-CoV-2 infection with the Omicron variant mimicking metastatic cancer on whole body 18-F FDG PET/CT imaging
Authors: Helmsdal Gunnhild , Clemmensen Sissal , Mortensen Jann , Kristiansen Marnar Fríðheim , Petersen Maria Skaalum , Johannesen Herborg L 
Published: March 2024

Abstract
We present a case with unusual findings on nuclear imaging after mild SARS-CoV-2 infection. 18F-Fluorodeoxyglucose Positron Emission Tomography-Computed Tomography showed activity in the lower thoracic spinal column, in portal lymph nodes, and in the terminal ileum and surrounding lymph nodes, all suspicious for metastatic cancer. Three months later, the findings had either disappeared or were considered reactive.
Loneliness and mental health issues among Vietnamese migrants in Japan: A cross-sectional study
Authors: Yamashita Tadashi , Quy Pham Nguyen , Nogami Emi , Yamada Chika , Kamiya Kuniyasu , Kato Kenji 
Published: March 2024

Abstract

Background: Loneliness is a major factor hindering the health of migrants. There is concern that social changes due to the COVID-19 pandemic, in addition to the acculturation gap with their host country, exacerbated loneliness among Vietnamese migrants in Japan.Therefore, this study aimed to clarify the prevalence of loneliness and examine the relationship between mental health and loneliness among Vietnamese migrants in Japan.
Methods: We used a cross-sectional study design using a self-administered questionnaire. The data were collected from May 2 to June 6, 2022. The target population for this study was Vietnamese migrants living in Japan, 213 of whom were included in the analysis. The questionnaire consisted of items regarding participants' characteristics, socioeconomic status, social support, Patient Health Questionnaire-9, Generalized Anxiety Disorder-7, and University of California Los Angeles 3-Item Loneliness Scale. Logistic regression analysis was performed with depressive (Patient Health Questionnaire-9 ≥ 10 points) and anxiety (Generalized Anxiety Disorder-7 ≥ 10 points) symptoms as dependent variables and loneliness (University of California Los Angeles 3-Item Loneliness Scale ≥ 6) and other socioeconomic factors as independent variables.
Results: The mean age of the participants was 26.8 ± 4.4 years. The study included 112 men (52.6%) and 101 women (47.4%). Their mean years of residence in Japan was 4.4 ± 2.5 years. 53 (24.9%) had a Patient Health Questionnaire-9 score ≥ 10. 30 (14.1%) had a Generalized Anxiety Disorder-7 score ≥ 10. 81 (38%) had a University of California Los Angeles 3-Item Loneliness Scale ≥ 6. Multivariate logistic regression analysis revealed that depressive symptoms were associated with loneliness (OR: 6.06; 95% CI: 2.84–12.90). Factors associated with anxiety disorders included loneliness (OR: 12.46; 95% CI: 3.93–39.51).
Conclusions: Loneliness can cause various mental disorders, and social changes due to the COVID-19 pandemic have increased loneliness over time. In this study, approximately 40% of Vietnamese migrants living in Japan were lonely, and loneliness was one of the factors contributing to their depressive and anxiety disorder symptoms. Currently, the number of Vietnamese migrants living in Japan is rapidly increasing, and reducing their loneliness may contribute to improving their mental health and wellbeing.
Improving CNC Turning Machine Precision through Vibration Analysis for Clamping Error Detection Employing Principal Component Analysis
Authors: Ullah Aman , Chan Tzu-Chi , Xie Zhong-Yan 
Published: March 2024

Abstract

The vibration caused by mechanical manufacturing will lead to unpredictable changes in product quality, which will increase the manufacturing cost. Plenty of research is imposed to establish a normal vibration coefficient or to develop an accurate and efficient production process. Therefore, various health diagnosis methods and feedback mechanisms are obtained, such as dynamic feature Detection, machine tool state Detection, cutting chatter analysis, health state feedback of specific parts in the machine tool, and so on. This study analyzes the lathe and establishes the vibration analysis and health diagnosis method used for NC lathe or traditional machine tools through the vibration signals generated by different clamping states. Before the spindle speed reaches 2000 rpm, 5 experiments at an interval of 250- rpm and three clamping states are executed. Moreover, the vibration signal is obtained using the intelligent prediction and diagnosis performance system, analyzed in the frequency domain, matched with the root mean square result, and checked for the accuracy of the vibration signal data and vibration eigenvalues. Then, digital tools are used to filter the signal according to the filtered outliers and the matching results of feature extraction. Principal component analysis (PCA) and the projection matrix are used to evaluate 37 features and reduce the dimension of the data, to obtain the vibration data distribution map under different rotating speeds of each clamping state. It can identify the distribution range and tightness of the distribution map under each clamping state. In the above experiment, the signal data of each 250-rpm interval and three clamping states were collected and compared. The results show that it is feasible to use the PCA method to determine the change of vibration value in the CNC lathe and establish a health state feedback data set based on the vibration change mechanism.
Breastfeeding knowledge, attitudes and perceptions of breastfeeding education among undergraduate nursing students in mainland China: A cross-sectional study
Authors: Yang Yuanyuan , Liu Huijuan , Yang Jing , Li Bian , Shen Zhijuan , Zhou Xiaoling , Lu Hong 
Published: March 2024

Abstract
Background
China has the largest population in the world. While breastfeeding statistics have improved in the most recent decade, the exclusive breastfeeding rates remain low. Nurses with baccalaureate degrees are becoming the mainstay of China's nursing workforce and are an important force in supporting breastfeeding. To date, there is little evidence regarding breastfeeding education for undergraduate nursing students in mainland China. This study aims to explore the breastfeeding knowledge level and attitudes of undergraduate nursing students in mainland China, as well as their perceptions on breastfeeding education.
Methods
This was a descriptive cross-sectional study. An online questionnaire survey was conducted from October to December 2023 among 428 undergraduate nursing students from 22 medical universities/colleges in different regions of mainland China.
Results
Most student participants (96.96%) expressed supportive attitudes toward breastfeeding. The average correct response rate of the breastfeeding knowledge questionnaire was 54.80%. Students who reported having received breastfeeding education/training at school, or having obstetric or pediatric internship experience had significantly higher mean knowledge scores compared to others (p < 0.05). Overall, 92.99% (398/428) of students surveyed stated they would like more education on breastfeeding within the undergraduate nursing school curriculum. Case-based learning (CBL) and simulation were the most desired teaching methods for theoretical classes and practical classes, respectively.
Conclusions
The breastfeeding knowledge of undergraduate nursing students needs to be improved. Breastfeeding education included in the nursing curriculum should be strengthened, to adequately prepare students to support breastfeeding.
The development of a neutral buoyancy and virtual reality training system for training suborbital scientists
Authors: Seedhouse Erik L. 
Published: March 2024

Abstract
In 2021, 2022, 2023 and 2024 Blue Origin’s New Shepard and Virgin Galactic’s SpaceShipTwo (SS2) flew dozens of spaceflight participants (SFPs) on suborbital spaceflights. The SFPs, whether they were scientists or space tourists, each paid $450,000 or more for their ticket. With each flight providing between 180 and 240 seconds of microgravity time, this meant each second of microgravity time cost at least $2500 and the consequence of performing a task incorrectly could be extremely costly. In spaceflight, the tactile-kinesthetic and vestibular systems are affected by microgravity. While astronauts who visit the International Space Station (ISS) have time to adapt to microgravity, SFPs have little time to adapt because the time from rocket ignition to microgravity is less than 5 minutes. Compounding this lack of adaptation is the fact that suborbital SFPs may only have two or three days of preparation compared with many years training for an ISS astronaut. To evaluate the extent to which training in an analog environment can help scientist SFP’s prepare for their flights, this study evaluated the effectiveness of two spaceflight analog training modes, one that took that place in a neutral buoyancy environment (NBE) and one that took place in a virtual reality (VR) rendered environment (VRE). This study compared how much time was saved by practicing suborbital tasks in these environments across four groups. Results indicate that an analog-based learning environment positively affects the cognitive and affective domains of scientist SFPs thereby reducing training time and errors.
Small target detection in aerial images of road scenes based on improved YOLOv7
Authors: Liu Yang , Zhang Chuhan , Shi Fubin , Wei Yuning 
Published: March 2024

Abstract
Small target detection in aerial road images is challenging, and the existing detection models are not suitable for small targets with dense, complicated background and occlusion in aerial images. Therefore, a new small target detection model based on YOLOv7 model is used for small target detection in UAV road scenes. We have made four improvements: (i) a new head for detection is added to the original YOLOv7 model to detect tiny-scale targets. (ii) we use the SimAM attention to focus on areas with small-scale targets. (iii) In the downsampling stage, SPD-Conv model is added to replace the original CNN model to improve the capacity to identify small targets of low resolution in aerial road images. (iv) CARAFE model is introduced to enhance feature fusion and reduce information loss. To demonstrate the feasibility of the model, the first set of contrast experiments were first performed on the Drone dataset, the mAP0.5 value is increased by 8.8% compared with that of the original YOLOv7. Then, experiments are also carried out on the VisDrone2019 dataset. In comparison with the original YOLOv7, the mAP0.5 value of the improved YOLOv7 is increased by 7.2%. This model is equally effective for dense and obscured small targets, our detection performance of the improved YOLOv7 is superior to that of recent methods.
Pan-cancer analysis identifies AL365181.3 as a novel prognostic biomarker for lung adenocarcinoma
Authors: Liu Xiaoying , Liu Jinlong , Zeng Yingou , Qiao Di , Wang Qiang 
Published: March 2024

Abstract
As a lncRNA, AL365181.3 is aberrantly expressed in multiple cancer types, including lung adenocarcinoma (LUAD). However, the biological process underlying the ability of AL365181.3 to promote the progression of LUAD is unclear. Here, the pancancer expression level of AL365181.3 was analyzed using the TCGA and GTEx databases, as well as its clinical characteristics and prognostic value. Finally, the in vitro and in vivo biological functions of AL365181.3 in LUAD were revealed by using various functional assays. We found that AL365181.3 was significantly more highly expressed in many types of cancer tissues, including LUAD tissues, than in adjacent normal tissues. LUAD patients with high AL365181.3 expression had poor prognoses. Functional enrichment analyses indicated that AL365181.3 is involved in the regulation of metabolism, MAPK signaling and other tumor regulatory signaling pathways.Finally, we found that knockdown of AL365181.3 reduced the proliferation and migratory capacity of LUAD cells, and knockdown of AL365181.3 resulted in a reduced in vivo tumorigenic capacity of LUAD cells. These findings provide a comprehensive understanding of the role of AL365181.3 in LUAD.
CausNet-partial : `Partial Generational Orderings' based search for optimal sparse Bayesian networks via dynamic programming with parent set constraints
Authors: Sharma Nand , Millstein Joshua 
Published: March 2024

Abstract

Background: In our recent work, we developed a novel dynamic programming algorithm to find optimal Bayesian networks (BNs) with parent set constraints. This ‘generational orderings’ based dynamic programming search algorithm - CausNet - efficiently searches the space of possible BNs given the possible parent sets. The algorithm supports both continuous and categorical data, as well as continuous, binary and survival outcomes. In the present work, we develop a variant of CausNet - CausNet-partial - which searches the space of ‘partial generational orderings’, which further reduces the search space and is suited for finding smaller sparse optimal Bayesian networks; and can be applied to 1000s of variables.
Results: We test this method both on synthetic and real data. Our algorithm performs better than three state-of-art algorithms that are currently used extensively to find optimal BNs. We apply it to simulated continuous data and also to a benchmark discrete Bayesian network ALARM, a Bayesian network designed to provide an alarm message system for patient monitoring. We first apply the original CausNet and then CausNet-partial varying the partial order from 5 to 2. CausNet-partial discovers small sparse networks with drastically reduced runtime as expected from theory.
Conclusions: Our partial generational orderings based search for small optimal networks, is both an efficient and highly scalable approach for finding optimal sparse and small Bayesian Networks and can be applied to 1000s of variables. Using specifiable parameters - correlation, FDR cutoffs, in-degree, and partial order - one can increase or decrease the number of nodes and density of the networks. Availability of two scoring option - BIC and Bge - and implementation for survival outcomes and mixed data types makes our algorithm very suitable for many types of high dimensional data in a variety of fields.