bluuebunny/crossref_metadata_2025_split huggingface dataset:
Multiple Constraints Source to K- Terminal Reliability Optimization under Common Cause Failures
Authors: Hazarika Kalpana , Bhadoria Vikas Singh , Khemaria Manish 
Published: August 2023

Abstract
Many systems like Gas pipelines, Irrigation systems, Fire Fighting Systems, etc., their satisfactory performance or reliability does not only depend on proper connectivity but also on delivering a required demand. Hence, reliability Optimization (RO) of such networks with Multiple Constraints i.e. Cost, Capacity, and Connectivity (CCC) is a complex decision. The common practices of RO are mostly observed as optimization at the component level compared to other alternative possibilities like right of way, feasibility of structural changes and capital investment for it etc. Till now extensive works have been proposed by many authors on the RO of SKT networks with single or multiple constraints using Exact and Approximate Methods. But RO of SKT Network with multiple constraints under Common Cause Failure (CCF) is a barely studied area. To demonstrate the proposed methodology, a single source to five terminals irrigation network is considered here. This paper is presented in three successive sections, Section A- Mathematical Modelling of SKT network applying Exhaustive Search Method to enumerate the successful paths with intended delivery capacity. Section B- Heuristic Approach is used for Reliability Optimization of SKT network with s-identical redundant components under cost constraints. Section C - Demonstrate the effect of CCFs using Poison Failure processes. In Conclusion Reliability of the SKT network with and without CCF is compared to show the significant effects of CCF. For its analysis, author has considered the irrigation network and assuming the common tendency of network optimization with s-identical components to explain how unknowingly the affect CCF get introduced due to selection of s-identical components especially in an identical operating conditions.
Microbial interaction between human skin and Nukadoko, a fermented rice bran bed for pickling vegetables
Authors: Niwa Ryo , Chen Dominique , Seong Young ah , Jo Kazuhiro , Ito Kohei 
Published: August 2023

Abstract
The skin microbiome, which varies widely between individuals, plays a crucial role in human health. It also interacts with the environment in various ways, including during the preparation of fermented food. Nukadokois a pickle and traditional fermented food in Japan that utilizes lactic acid bacteria to ferment vegetables. The microbial composition of Nukadoko contributes to the flavor of pickled products. However, the origin of the microbes present in the rice bran bed has yet to be determined and no studies have examined how the skin microbiome affects the quality of Nukadoko. In this study, the effects of interaction of microbes between Nukadoko and the human skin during Nukadokomaintenance were studied. Three participants were asked to stir commercially available late-stage Nukadoko for 14 days and not stir it for the remaining 14 days to examine microbial settlement and shedding. Microbiome analysis was performed on human skin and Nukadoko. We found that microorganisms from rice bran beds can temporarily settle on human skin but are shed quickly. Stirring rice bran beds by hand may have short-term effects on the skin microbiome. This study provides insights into the communication between human and food microbiomes in traditional Japanese fermented foods.
BlueEdge: Application Design for Big Data Cleaning Processing using Mobile Edge Computing Environments.
Authors: Elmobark Nagwa Elmobark Nagwa , El-ghareeb Haitham El-ghareeb Haitham , Elhishi Sara Elhishi Sara 
Published: August 2023

Abstract
With the rapid growth of the Internet of Things (IoT) and the emergence of big data, handling massive amounts of data has become a major challenge. Traditional approaches involve sending raw data to cloud data centers for cleaning, processing, and interpretation using data warehouse tools. However, this study introduces BlueEdge, a fog edge mobile application that aims to shift the cleaning and preprocessing tasks from the cloud to the edge. We compare BlueEdge with four popular data cleaning tools (WinPure, DoubleTake, WizSame, and DQGlobal) that operate within data warehouse architectures, such as Hadoop servers. The comparison considers criteria such as time consumption, resource utilization (memory and CPU), and tool performance. BlueEdge utilizes Natural Language Processing (NLP) techniques via the Natural Language Toolkit (NLTK) and Python packages to connect with a real-time database. Our results demonstrate that BlueEdge successfully performs the same cleaning services in real time on the fog edge (mobile). It excels in handling data duplication elimination services, including different spelling and pronunciation, misspellings, name abbreviations, honorific prefixes, common nicknames, and split names. BlueEdge achieves high accuracy percentages, ranging from 90% to 100%, surpassing data warehouse applications running on cloud servers. Additionally, BlueEdge significantly reduces memory consumption to 5,000 bytes per edge on mobile devices, while data warehouses range from 10,000 to 60,000 bytes on Hadoop servers. Moreover, BlueEdge minimizes the data cleaning time to 1 second per edge, compared to the typical 4 to 30 seconds for data warehouses. Notably, BlueEdge can be executed by users on mobile devices without permission, and it is available free of charge.
Prevention and therapy of orchestra musicians’ playing-related musculoskeletal disorders with transcranial direct current stimulation: a pilot study
Authors: Krumpöck Paul , Ebenbichler Gerold , Knosp Christina , Roiger-Simek Ricarda-Samantha , Margreiter-Neuwirth Nicoletta , Neuwirth Wolfgang , Kasprian Gregor , Nenning Karl-Heinz , Schmidbauer Victor , Benca Emir , Sterz Fritz 
Published: August 2023

Abstract
Background
Orchestra musicians and music students complain about painful playing-related musculoskeletal disorders (PRMDs) without receiving appropriate therapeutical support. The aim of this pilot study was to provide a proof of concept of a new treatment regimen for PRMDs based on a comprehensive assessment. This regimen consisted of transcranial direct current stimulation (tDCS) in addition to physiotherapeutic exercises and psychological coaching. As a part of the assessment, we tried to demonstrate the feasibility of multiple new diagnostic tools that could potentially investigate the efficacy of the treatment regimen and elucidate pathophysiological mechanisms of PRMDs.
Methods
Musicians from the Orchestra Academy of the Vienna Philharmonic Orchestra were asked for their voluntary participation. Seven participated in their choice of self-administered tDCS sessions with concurrent physiotherapeutic exercises, physiotherapeutic and psychological assessments, the pain questionnaire, and medical imaging or 3D motion capture acquisitions. The feasibility of these methods was determined through observation of the investigators and participant feedback, as well as a safety questionnaire and a checklist.
Results
All pilot trials (n = 10) were completed successfully without any major issues. Some minor problems, such as lack of electrode connectivity or tingling/burning sensations of the scalp, were encountered by the participants during the tDCS sessions (n = 2/2 participants), the physiotherapeutic assessments (n = 1/3) and exercises (n = 1/2), the psychological assessments (n = 1/2) and the medical imaging (n = 1/2).
Conclusions
The trials showed very promising results for all investigated study parts, therefore demonstrating the feasibility and safety of studying this new treatment regimen in a randomized clinical trial with a larger sample of musicians. Also, the medical imaging and 3D motion capture acquisitions encourage further investigation to evaluate their potential diagnostic applicability for musicians’ PRMDs.
Mobile monitoring system to detect the disease activity pattern and predict clinical outcomes in patients with newly diagnosed Crohn’s disease
Authors: Lee Yoo Jin , Kwak Sang Gyu , Kim Eun Soo , Kim Sung Kook , Lee Hyun Seok , Chung Yun Jin , Jang Byung Ik , Kim Kyeong Ok , Kim Jeongseok , Jo Hyeong Ho , Kim Eun Young 
Published: August 2023

Abstract
We aimed to determine whether Crohn’s disease (CD) activity patterns depicted in a web-based symptom diary could help predict clinical outcomes in patients with newly diagnosed CD. Patients diagnosed with CD within 3 months were prospectively enrolled from four tertiary centres. They recorded their symptoms on a website using a smartphone at least once a week. The index outcomes were disease-related admissions and surgery during follow-up. The disease activity from enrolment to outcome or last follow-up was reviewed for pattern analysis. Cox regression was used to identify the predictors of disease outcomes. Among 135 patients with new CD, 102 were enrolled in the study. During a median follow-up period of 42 months, 25 (24.5%) and 6 (5.9%) patients required admission and surgery, respectively. Poor activity pattern was an independent predictor of disease-related hospitalisation (adjusted hazard ratio [aHR], 3.96; 95% confidence interval [CI], 1.5–10.45; p=0.005). A poor activity pattern (aHR, 19.48; 95% CI, 1.86–203.95; p=0.013) and female (aHR, 11.28; 95% CI, 1.49–85.01; p=0.018) were found to be independent predictors of bowel resection. CD disease activity patterns monitored through the mobile monitoring system could predict clinical outcomes, such as disease-related hospitalisation and surgery, in patients with newly diagnosed CD.
The Beauty Premium: Physicians’ Appearance and Patients’ Selection and Evaluation Behavior in Online Health Communities
Authors: Yang Yanbin , Ma Chengyu , Liu Haopeng 
Published: August 2023

Abstract
Background:With the development of information technology, online health communities (OHCs) are becoming an increasingly popular source of health information.
Objectives: While the impact of appearance has been extensively studied in various research fields, its role in online health communities has received little attention. This study aims to evaluate the effect of physicians’ appearance on patients’ selection and evaluation behavior in online health communities, and explore the difference in the beauty premium among different types of physicians.
Methods: Over 13,000 images of physicians and their relevant information were collected from Good Doctor website, which is now China’s leading OHC. We identified facial features in physicians’ photos based on deep learning and used Ordinary Least Squares (OLS) regression models to estimate the relationship between physicians’ appearance and patients’ behavior. We addressed the potential endogeneity issue by utilizing Propensity Score Matching (PSM) method.
Results:This study found that physicians’ appearance positively impacts patients’ selection and evaluation behavior. In addition, heterogeneity analysis showed that the appearance of male, high titles, longer service duration, and surgical diseases physicians have a greater influence on patients’ behaviors.
Conclusions: The beauty premium exists in online health communities. Therefore, this study provides new evidence on the impact of physicians’ facial appearance in online health communities, and provides useful insights for patients, physicians, and platforms about the relationship between physician’s structured or unstructured information and patients’ decision-making behaviors.
EuCARE-POSTCOVID Study: A Multicentre Cohort Study on Long-Term Post-COVID-19 Manifestations
Authors: Varisco Benedetta , Bai Francesca , De Benedittis Sara , Tavelli Alessandro , Cozzi-Lepri Alessandro , Sala Matteo , Miraglia Federica Gaia , Santoro Maria Mercedes , Ceccherini-Silberstein Francesca , Shimoni Yishai , Ravid Sivan , Kozlovski Tal , Köning Florian , Pfeifer Nico , Mommo Chiara , Marchetti Giulia 
Published: August 2023

Abstract
Background. Post-COVID-19 condition refers to persistent or new onset symptoms occurring three months after acute COVID-19, which are unrelated to alternative diagnoses. Symptoms include fatigue, breathlessness, palpitations, pain, concentration difficulties ("brain fog"), sleep disorders, and anxiety/depression. The prevalence of post-COVID-19 condition ranges widely across studies, affecting 10-20% of patients and reaching 50-60% in certain cohorts, while the associated risk factors remain poorly understood.
Methods. This multicentre cohort study, both retrospective and prospective, aims to assess the incidence and risk factors of post-COVID-19 condition in a cohort of recovered patients. Secondary objectives include evaluating the association between circulating SARS-CoV-2 variants and the risk of post-COVID-19 condition, as well as assessing long-term residual organ damage (lung, heart, central nervous system, peripheral nervous system) in relation to patient characteristics and virology (variant and viral load during the acute phase). Participants will include hospitalised and outpatient COVID-19 patients diagnosed between 01/03/2020 and 01/02/2025 from 8 participating centres. A control group will consist of hospitalised patients with respiratory infections other than COVID-19 during the same period.
Patients will be followed up at the post-COVID-19 clinic of each centre at 2-3, 6-9, and 12-15 months after clinical recovery. Routine blood exams will be conducted, and patients will complete questionnaires to assess persisting symptoms, fatigue, dyspnoea, quality of life, disability, anxiety and depression, and post-traumatic stress disorders.
Discussion. This study aims to understand post-COVID-19 syndrome's incidence and predictors by comparing pandemic waves, utilising retrospective data. Gender association, especially the potential higher prevalence in females, will be investigated. Symptom tracking via questionnaires and scales will monitor duration and evolution. Questionnaires will also collect data on vaccination, reinfections, and new health issues. Biological samples will enable future studies on post-COVID-19 sequelae mechanisms, including inflammation, immune dysregulation, and viral reservoirs.
Trial registration: This study has been registered with ClinicalTrials.gov under the identifier NCT05531773.
A novel, timely, cost-effective, and non-invasive photography-based technique for standard length measuring and individual identification of seahorses
Authors: Luzzatto Diego , Cussac Victor 
Published: August 2023

Abstract

This study aimed to develop a non-invasive and efficient method for measuring and identifying individual seahorses (Hippocampus patagonicus) in their natural habitat. A total of 976 seahorses were captured and photographed on a measuring board for standard length (Ls) measurements. Head photographs were also taken for individual recognition. Seahorses were tagged with visible implant elastomers (VIE) for calibration. The analysis showed no significant difference between left and right Ls measurements. The unique pattern of white dots on the heads served as individual fingerprints, consistent with VIE tagging. The recapture rate was 12%, with 89 individuals observed multiple times. Two distinct growth patterns were identified: males exhibited higher growth rates and a negative correlation with Ls compared to females. Released seahorses displayed different behaviors, with significant differences in Ls among these behaviors. Smaller seahorses tended to swim slowly towards nearby holdfasts, while larger seahorses escaped further or remained rigid before grasping a holdfast. The proposed methodology allowed for estimating individual seahorse growth rates, and the measurements were objective and precise. The results were obtained through quick and minimally invasive manipulation of the observed individuals.
VAPI: Vectorization of Algorithm for Performance Improvement
Authors: Yashar Mahmood , Rashid Tarik A. 
Published: August 2023

Abstract
This study presents the vectorization of metaheuristic algorithms as the first stage of vectorized optimization implementation. Vectorization is a technique for converting an algorithm, which operates on a single value at a time to one that operates on a collection of values at a time to execute rapidly. The vectorization technique also operates by replacing multiple iterations into a single operation, which improves the algorithm's performance in speed and makes the algorithm simpler and easier to be implemented. It is important to optimize the algorithm by implementing the vectorization technique, which improves the program's performance, which requires less time and can run long-running test functions faster, also execute test functions that cannot be implemented in non-vectorized algorithms and reduces iterations and time complexity. Converting to vectorization to operate several values at once and enhance algorithms' speed and efficiency is a solution for long running times and complicated algorithms. The objective of this study is to use the vectorization technique on one of the metaheuristic algorithms and compare the results of the vectorized algorithm with the algorithm which is non-vectorized.
Prevalence of high-risk HPV genotypes and associated factors among women living with HIV in Uganda: A facility-based cross-sectional study
Authors: Nakigozi Harriet , Ndejjo Rawlance , Bazeyo William , Nabaggala Annet , Achola Caroline , Iga Moses , Kalyesubula Simeon , Kanamwangi Ben , Mutungi Gerald , Batte Charles , Mukunya David , Sserwanga Lawrence , Gemageine Godfrey , Oyoo Charles Akiya , Nabadda Susan 
Published: August 2023

Abstract
Background: Women living with HIV are at risk for cervical dysplasia and cancer worldwide. In 2015, the World Health Organization (WHO) recommended that testing for high-risk HPV (hrHPV) infection be incorporated into cervical cancer screening programs using molecular nucleic acid tests (NATs) but this has not previously been done in Uganda. The country’s coverage for Human Papilloma Virus (HPV) screening remains low at less than 10% for women aged 25 - 49 years. This study determined the prevalence and associated factors of high-risk Human Papilloma Virus genotypes among women living with HIV in Uganda.
Methods: A descriptive cross-sectional study was conducted in 15 selected health facilities among participants who were on Antiretroviral therapy (ART). Participants who consented to participate were instructed on how to collect their own high vaginal swabs using a cervical brush for HPV molecular testing (HPV DNA or HPV RNA) and their demographics data was collected using a standard questionnaire. Laboratory diagnosis for HPV molecular testing was done using Gene xpert machines and Hologic Aptima Machine. Modified Poisson regression analysis was conducted to determine the associated factors.
Results: This study involved 5856 HIV positive participants on ART. A total of 2006 out of 5856 (34.3%) participants had high risk HPV genotypes. The prevalence of the individual genotypes were: HPV16 317(15.8%), HPV 18-45 308 (15.4%) and other high-risk HPV 1381 (68.8%). The independent factors associated with all hrHPV, and the individual genotypes (16, 18=45 and other hrHPV) were parity, education level, having more than one partner, and engaging in early sex. Smoking was associated with HPV 16, HPV 18-45 and other hrHPV. Age was associated with all hrHPV and HPV 18-45, marital status with all hrHPV and HPV 16, and occupation with HPV 16.
Conclusions. The prevalence of high-risk HPV genotypes among HIV positive women attending ART clinics in public facilities in Uganda was high. Other hrHPV genotype was the commonest compared to 18-45 and HPV 16. The integration of cervical cancer screening in ART programmes remains paramount to support the early detection of cervical cancer and Non-invasive self-collected urine and vaginal sampling for cervical cancer screening present an opportunity.
Dynamics analysis and image encryption application of Hopfield neural network with a novel multistable and highly tunable memeristor
Authors: Yao Wei , Liu Jiapei , Sun Yichuang , Zhang Jin , Yu Fei , Cui Li , Lin Hairong 
Published: August 2023

Abstract
Building neural network models and studying their dynamic behaviours is extremely important from both a theoretical and practical standpoint due to the rapid advancement of artificial intelligence. In addition to its engineering applications, this article concentrates primarily on the memristor model and chaotic dynamics of the asymmetric memristive neural network. First, we develop a novel-multistable, highly-tunable memristor model. Using this memristor model to build an asymmetric memristive neural network (AMNN), the chaotic dynamics of the proposed AMNN are investigated and analyzed using fundamental dynamics techniques such as equilibrium stability, bifurcation diagrams, and Lyapunov exponents. According to the findings of this study, the proposed AMNN possesses a number of complex dynamic properties, including scaling amplitude hyperchaos with coupling strength control, and coexisting unusual chaotic attractors with initial control and coupling strength control. Significantly, the neural networks demonstrate for the first time the phenomenon of infinitely persisting uncommon chaotic attractors. In the interim, a system for image encryption based on the proposed AMNN is constructed utilizing hyperchaotic attractors. By analyzing correlation, information entropy, and key sensitivity, the devised ciphering method reveals a number of benefits. The feasibility of the encryption system is validated through FPGA hardware experiments, and the proposed memristor and AMNN models have been translated into a Simulink model.
Method for Setting Speed Limit Value of Extra Long Tunnel
Authors: Zhaoyou MA , Zhigang DU , Junhua Wang , WANG Xiaoyan 
Published: August 2023

Abstract
Based on the feature analysis of the visual environment constituent elements of the urban expressway extra-long tunnel, the model test of the visual illusion effect of the driver on the visual information of the extra-long tunnel was designed to study the effect of different visual information conditions of the extra-long tunnel on the driver's illusion of speed. Through the simulation test of the operation safety and traffic efficiency comparison of the extra-long tunnel, the effect of different speed limit values on the operation safety and efficiency of the extra-long tunnel under different traffic flow conditions is compared. Comprehensively considering the driving environment of the extra-long tunnel and the driving needs of the driver, a method and process for determining the speed limit value based on the functional positioning of the extra-long tunnel and the linear technical indicators, legal speed limit requirements, the driver's speed perception needs, and the dynamic balance of operational safety and efficiency are proposed. Standardize and guide the setting of speed limit values for extra-long tunnels, and create a good driving environment and speed law enforcement environment.