bluuebunny/crossref_metadata_2025_split huggingface dataset:
Collaborative Optimization Model for Train Timetable and Stopping Plan in Intercity Railway
Authors: Wang Wenxian , Chen Hao , Zhang Liqing , Lv Qiuxia 
Published: October 2023

Abstract
In the organization of intercity passenger transport, train timetable is the basic document for train operation. A reasonable train timetable can improve the balance of train service at the station, thereby improving the service quality of railway passenger transport. In this paper, we define a quantitative calculation method for the balance of station service in the intercity railway. A collaborative optimization model of train timetable and stopping plan is develop, which aim to minimize dwelling time of trains and the imbalanced coefficient of train service at stations. So all trains could stop at their stations more evenly, and maximum waiting time for passengers is reduced. In order to solve this mixed integer nonlinear problem, an improved genetic algorithm is designed. Finally, taking Jiangmen-Zhanjiang Railway as an example, the proposed collaborative optimization model of train timetable and stopping plan is applied to a real scene. The case compares and analyzes the train service balance and the stopping time of each train at each station along the Jiangmen-Zhanjiang Railway in the original plan and the optimized plan. The results show that the optimized train departure plan can increase the station service balance by 24.6% (downlink direction) and 26.7% (uplink direction), and reduce the total dwelling time of all intercity trains by 24 minutes (downlink direction), 21 minutes (uplink direction) at the same time.
The mean temperatures of CME-related dimming masses
Authors: Thomson Emily , Hudson Hugh 
Published: October 2023

Abstract
Sun-as-a-star EUV spectroscopy from EVE (the Extreme-ultraviolet Variability Experiment, on board the Solar Dynamics Observatory) frequently shows striking irradiance reductions following major solar flares. These coincide with dimming events as seen in EUV and X-ray images, involving the evacuation of large volumes of the corona by the associated coronal mass ejections. The EVE view of the dimming process is precise and quantitative, whereas difference imaging in the EUV reveals the structures to be full of complicated detail due most likely to unrelated activity.We have studied a sample of 11 events, mostly GOES X-class flares, all of which were associated with coronal mass ejections. For a set of 9 lines of Fe ions at stages VIII - XIII, corresponding to nominal peak formation temperatures below log(T) = 6.3, we have compared the emission-measure-weighted temperatures of the dimming mass and the preflare global corona. We find similar temperatures by this measure, but with a distinctly narrower variation in the preflare samples. For higher ionization states weak emission commonly appears during the dimming intervals, consistent with residual late-phase flare late-phase development. The dimming depths do not appear to correlate with the preflare state of the global corona.
Pectoralis major activity prevents excessive horizontal abduction of the throwing arm in fastball pitching in baseball
Authors: L A.J.R. , Trigt B. van , Hoozemans M.J.M. , Veeger H.E.J. 
Published: October 2023

Abstract
Background: In baseball pitching, repetitive excessive horizontal abduction of the upper (throwing) arm, or hyperangulation, can cause internal impingement to become pathological when glenohumeral contact intensity repeatedly reaches a threatening level. The pectoralis major, positioned anatomically and functionally in horizontal adduction, may counteract the throwing arm's moment of inertia, limiting excessive horizontal abduction. This study aimed to evaluate whether the pectoralis major actively and passively produces force before maximal horizontal abduction during fastball pitching, to counteract the throwing arm's moment of inertia, thereby limiting excessive horizontal abduction.
Results: Moderate pectoralis major muscle activity was observed in the period preceding maximal horizontal abduction, indicating that the muscle actively generated force. The relative muscle length of the pectoralis major was approximately 125%, indicating that the muscle was stretched beyond its optimal muscle length, thereby also passively contributing to the force production. The relative muscle length of the pectoralis major increased in the period leading up to maximum horizontal abduction, which implies that the muscle provided an eccentric contraction.
Conclusion: The pectoralis major actively and passively contributes to the force generation required to counteract the throwing arm’s moment of inertia through eccentric contraction in the period preceding maximal horizontal abduction during fastball pitching, potentially preventing the throwing arm of reaching excessive values in horizontal abduction or hyperangulation.
The impact of surge capacity enhancement training for nursing managers on hospital disaster preparedness and response: An action research study
Authors: shafiei Alireza , Aslani Narges , Beyramijam Mehdi , Khankeh Hamidreza 
Published: October 2023

Abstract

Introduction: Hospitals as the main providers of healthcare services play an essential role in the management of disasters and emergencies. Nurses are one of the important and influential elements in increasing the surge capacity of hospitals. Accordingly, the present study aimed to assess the effect of surge capacity enhancement training for nursing managers on hospital disaster preparedness and response.
Methods: The participants in this action research intervention study were all nursing managers working in Motahari Hospital in Tehran, who were selected through the census sampling method and received hospital surge capacity training. The Iranian version of the “Hospital Emergency Response Checklist” was used to measure hospital disaster preparedness and response before and after the intervention.
Results: The overall hospital disaster preparedness and response score was 184 (medium level) before the intervention and 216 (high level) after the intervention. The intervention was effective in improving the dimensions of hospital disaster preparedness and response including command and control, triage, human resources, communication, surge capacity, logistics and supply management, safety and security, and post-disaster recovery, but had no significant impact on the continuity of essential services.
Conclusion: The study revealed that training nurses to enhance surge capacity and encouraging their proactive involvement in identifying hospital challenges related to surge capacity, along with implementing necessary measures, can enhance hospital disaster preparedness and response.
Molecularly Imprinted Electrochemical Sensor based on α- Cyclodextrin Dual-functional Monomers and MXene Nanosheets for Highly Sensitive and Selective Detection of Alkylresorcinols in Whole Wheat Foods
Authors: Wen Yangyang , Wang Mengyao , Zhao Shichao , Fan Haoran , Li Hongyan , Wang Jing , Sun Baoguo 
Published: October 2023

Abstract
To differentiate between whole wheat foods and refined wheat foods remains a significant challenge for both the grain industry and consumers. Alkylresorcinols serve as biomarkers for whole wheat grains, offering promising potential for authenticating whole wheat foods. In this study, we explored a novel molecularly imprinted electrochemical sensor with the modifications of MXene nanosheets and molecularly imprinted polymer (MIP) on the electrode surface, and for the first time applied it for the sensitive and selective detection of Alkylresorcinols. Specifically, α-cyclodextrin and acrylamide were used as dual-functional monomers, with 5-heneicosylresorcinol (AR21) as the template molecule, for the delicate synthesis of molecularly imprinted polymer. The alkyl chain of AR21 inserts into the hydrophobic cavity of α-cyclodextrin through hydrophobic effects, while hydroxyl groups of AR21 can form hydrogen-bonding interactions with acrylamide, resulting in significantly enhanced specificity towards AR21 compared to the MIP synthesized by single functional monomer and nonimprinted polymer. The fabricated sensor displayed a wide linear range of 0.005 µg·mL− 1 to 100 µg·mL− 1, with an ultralow detection limit of 2.52 ng·mL− 1. Moreover, the sensing assay displayed exceptional anti-interference performance, stability, and high reproducibility, owing to the unique cavities formed during the polymerization of bifunctional monomers. When applied to commercial whole wheat foods, the method achieved a satisfactory recovery between 96.3% and 103.5% with a relative standard deviation ranging from 0.65–2.87%. These results firmly validate the great efficiency of this analytical technique for accurately determining ARs and whole wheat foods.
Intelligent Surveillance Framework for Physical Abuse Detection
Authors: S Srividya M , R Anala M 
Published: October 2023

Abstract
Physical abuse is a societal problem irrespective of whether the society is rich, educated or so. Mostly physically weaker section like children, women and old age people are most vulnerable to it especially in cases of domestic violence or workplace aggression. If the abuser and victim share a relationship then reporting the abuse becomes all the more challenging. Hence an intelligent surveillance system is the need of the hour. In this paper we propose a hybrid deep learning framework for physical abuse detection and prevention through human action recognition. 3D convolution neural network (CNN) based deep learning model is built to analyze this complex human action. Using transfer learning ResNet-18 and GoogleNet model are trained for publicly available UBI fight and UCF crime dataset for detecting physical abuse in the video. The 2D kernels are converted to 3D kernels for both temporal and spatial feature extraction in the video. A layer of bilinear LSTM is added to gather long term temporal information, so that there is improvement in capturing the human action information. This hybrid model used for physical abuse detection is the novel approach and the results show that the performance parameters such as precision, accuracy, specificity and sensitivity score improved as we moved from 2D kernels to 3D, and there is remarkable improvement when bilinear LSTM was added to the deep learning model.
Chinese EFL Teachers' cognition of Coping strategies for language learners' Foreign Language anxiety: Scale development, Status Quo and investigating the impact of teacher training workshop
Authors: Que Jun , Alibakhshi Goudarz , Taghizadeh Nayreh 
Published: October 2023

Abstract
Language anxiety is a significant concern for applied linguists and English language teachers. As an affective variable, foreign language anxiety can potentially harm learners' language learning and performance. While the impacts of language anxiety on EFL learners' academic achievement have been extensively studied, little research has investigated EFL teachers' coping strategies to address learners' anxiety. This study examined the Chinese EFL teachers’ cognition of coping strategies for EFL learners’ language anxiety. More particularly, it aimed at developing a scale, assessing the Chinese EFL teachers’ status quo of cognitions and practices of the coping strategies, and assessing the effectiveness of teacher training workshops. A multi-phase quantitative research design was employed. 384 Chinese EFL learners were selected through convenience sampling. An adopted questionnaire was validated and used as a data collection tool. The researchers also selected a sub-group of participants and invited them to a teacher training workshop. Results revealed that Chinese EFL teachers use three macro and 24 micro-strategies to reduce language anxiety. Results also showed that attending teacher training workshops significantly affects the teachers’ cognition and use of coping strategies. These findings have theoretical and practical significance for teachers, educators, and managers.
Game-based Learning in Eye Health Education - The Developmental Challenges of E-learning Games
Authors: Maseedupalli Srikanth , Prakasam Ruby Kala , Vaidyanathan Kartic , Varada Sreelakshmi , Bollam Yamuna , Madhukuri Sitaramanjaneyulu , Singdha Snigdha , Pathengay Avinash 
Published: October 2023

Abstract
Purpose
To demonstrate the developmental challenges encountered at various stages of making e-learning game prototypes.
Methods
Structured focus-group discussions (FGD) were conducted involving all the stakeholders of game-development, the subject experts, and the technical experts. The four phases of FGDs were i) Ideation and team development, ii) Identifying the competencies and mapping these with cognition, iii) Concept to prototype development - a. Defining questions and data points; b. Accumulation of content, and iv) Prototype testing and game packaging. The FGDs were audio recorded, the descriptive data transcribed verbatim, and thematically analyzed.
Results
The challenges differed in every phase of game development. Data on the strengths and weaknesses of game development were collected by participant recall. Throughout the project, the technical team had to understand the requirements of the subject experts and vice-versa. Participant understanding of e-learning games varied across the teams. Choosing appropriate topics for game development, identifying and mapping underlying cognition to exit competency, data generation, problematic translation of concepts into game building, the role of communication in maintaining team dynamics, and the mandate to seek early feedback from end-users, were some of the challenges encountered.
Conclusion
The lessons learnt in overcoming procedural challenges may be widely applied when developing game-based educational tools for eye health education.
Hypergeometric Series, Lemniscate Functions, Q−xtensions and Jacobi Elliptic Functions
Authors: Cantarini Marco 
Published: October 2023

Abstract
In this paper, we provide a solution to an open problem posed by Campbell
and Chu \cite{CamChu} concerning the explicit evaluation of a constant known
as the 'lemniscate-like constant.' We demonstrate that by utilizing tools related
to the primary Jacobi elliptic functions, we can derive a closed-form expression
in terms of $q-$generalizations of Zeta and Polylogarithm functions and
well-known mathematical constants. Lastly, we establish that our primary outcome
establishes a non-obvious connection between various and disparate mathematical
entities.
The Elusive S Cells: Reevaluating Enteroendocrine Cell Classification
Authors: Klingenspor Martin , Hysenaj Franc , Lauber Michael , Bast-Habersbrunner Andrea , List Markus 
Published: October 2023

Abstract
The nomenclature of enteroendocrine cells (EECs), established in 1977, applies the ”one cell - one hormone” dogma, which distinguishes subpopulations based on the secretion of a specific hormone. These hormone-specific subpopulations include S cells for secretin, K cells for glucose-dependent insulinotropic polypeptide, N cells producing neurotensin (NTS), I cells producing cholecystokinin (CCK), D cells producing
somatostatin (SST), and others. Our study challenges this doctrine, showing that the expression of certain hormones is not confined to their designated cell type. Moreover, our findings do not confirm the presence of S cells or any cell population that exhibits significantly elevated secretin expression compared to other cell populations, despite the common attribution of secretin to S cells in existing literature. Instead, our investigation indicates that secretin is not synthesized by S cells; rather, its secretion is realized jointly by other enteroendocrine subpopulations.
NGS-Assisted Diagnosis of Clear Cell Sarcoma in the Inguinal Region of a Child: A Case Report
Authors: Zhang Xinyue , Cheng Haiyan , Fu Libin , Yang Wei , Qin Hong , Feng Jun , Han Jianyu , Yang Shen , Ren Qinghua , Wang Huanmin 
Published: October 2023

Abstract
Transparent cell sarcoma has an extremely low incidence rate, and children are not a high-risk age group. This study reported a case of recurrent tumor in the inguinal region of an 11-year-old boy. The pathological report of the puncture showed vascular epithelioid cell tumor. After treatment, the effect was not obvious. After surgical resection, NGS detection was performed on the gross specimen, and the EWSR1-ATF1 gene was found. Combined with the pathological features, the final diagnosis was CCS. This article emphasizes the importance of NGS in the auxiliary diagnosis of rare malignant tumors and the necessity of accurate diagnosis and treatment.
VKH-like syndrome in the setting of Dabrafenib and Trametinib therapy for BRAF mutant metastatic melanoma: A case report
Authors: Gunaratnam Cadric , Sivagurunathan Premala , FRANZCO Michael Hogden 
Published: October 2023

Abstract

Background: To report a unique case of Vogt‒Koyanagi‒Harada (VKH)-like uveitis
in a patient with BRAF mutant metastatic melanoma associated with concurrent use of BRAF and MEK inhibitors.
Case presentation: A 49-year-old woman with stage IV metastatic cutaneous melanoma developed bilateral acute pan-uveitis with multifocal serous retinal detachments, four months after starting combined dabrafenib and trametinib therapy. Clinical assessment, together with fluorescein angiography, optical coherence tomography, and serology, to exclude other key differential diagnoses led to the diagnosis of VKH-like uveitis. Prompt systemic corticosteroids and modification of the dosing schedule of the suspected offending agents resulted in the resolution of intraocular inflammation and serous retinal detachments.
Currently, systematic reviews reporting ocular adverse effects of combined dabrafenib and trametinib therapy are limited, although a retrospective study by Mettler et al. reported an odds ratio of 21.8 for VKH-like disease. Management of VKH in reported cases involves discontinuation of offending agents and initiation of intravenous corticosteroids for three days, followed by tapering oral corticosteroid treatment.
Conclusion: Both ophthalmologists and oncologists should be aware of the potential association between VKH-like uveitis and BRAF and MEK inhibitors, as these medications are becoming more common in the management of metastatic malignancies. Early and prompt recognition of this condition and treatment can be sight saving without compromising treatment for metastatic malignancy.
Experimental study on the coefficient of internal frictional resistance in the annular gap during plunger gas lifting process
Authors: Shi Haowen , Chen Zhong , Liao Ruiquan , Liu Jie , Li Junliang , Jin Shan 
Published: October 2023

Abstract
Plunger gas lift process technology is an economical solution to the problem of gas well liquid buildup. However, in-house simulation experiments revealed that the high-speed movement of the plunger may lead to fluid leakage and generate annular gap frictional resistance. To address this issue, a detailed experimental study was conducted to comparatively analyze five existing frictional resistance models, which were found to have significant deviations. Therefore, we propose a new model of annular gap frictional resistance and validate it with experimental data, and the results show that the new model is more accurate and reliable. We also conducted a comparative analysis of production site examples by using VB programming and found that when considering the annular gap frictional resistance, the upward travel time of the plunger was delayed, the difference between the upper and lower end face pressures was significant, and the difference in speed was 1.73 m/s. This indicates that the annular gap frictional resistance cannot be ignored and is crucial for optimizing the plunger gas lift process technology and improving the drainage efficiency of gas wells.
Artificial Intelligence in Medicine: A Systematic Review of Guidelines on Reporting and Interpreting Studies
Authors: Zrubka Zsombor , Kovács Levente , Nezhad Hossein Motahari , Czere János , Gulácsi László , Péntek Márta 
Published: October 2023

Abstract

Background
Reporting guidelines developed for medical artificial intelligence (AI) studies are structured tools that address general and/or AI-specific methodological and reporting issues. We aimed to systematically review published medical AI reporting guidelines and checklists and evaluate aspects that can support the choice of the tool in a particular research context.
Methods
We searched PubMed, Scopus, and Web of Science until February 2023. Citations and Google were searched in addition. We included peer reviewed articles of reporting guidelines or checklists applicable for medical AI research. Screening, article selection and data extraction was performed in duplicate. We extracted publication details, the guidelines’ aims, target audiences, development process, focus area, structure, number of items and recorded the number of Google Scholar citations as a proxy to usage.
Results
From 821 records, and additional sources, 24 guidelines were included (4 narrative guidelines, 7 general reporting checklists, 4 study design specific checklists, 9 clinical area specific checklists). 13 studies reported the guideline development methods, 10 guidelines were registered in the Enhancing the QUAlity and Transparency Of health Research (EQUATOR) Network. In 224 sections, the guidelines contained 704 items in total. The number of items per checklist varied between 10 and 66. Nine guidelines broadly followed the Introduction, Methods, Results, and Discussion (IMRAD) structure, 12 the machine learning pipeline method (i.e., sequential steps from data processing to model training and evaluation) and 3 had other structure.
Conclusions
Currently there is no consensus about the structure and format about AI reporting guidelines. The guidelines’ structure and level of detail varied significantly which makes difficult for researchers to follow how detailed and standardized a medical AI study report should be. The robustness of development process and support from the literature suggests CONSORT-AI as the most established tool. Such AI extensions of clinical study guidelines may not cover all the application fields of AI in medicine. In certain research contexts, an established checklist for main study types, and a general AI-based checklist may be used in parallel to provide most useful guidance in designing, writing and interpreting medical AI studies.
Management of COVID-19 Pandemic by Immunity-modulating Ayurvedic
Interventions: A Bright Panacea
Authors: Sharma Ruchi , Rai Shalini , Saini Heena , Rochlani Dimpal , Singh Varnika , Tripathi Richa 
Published: October 2023

Abstract:
COVID-19, or SARS-CoV-2 or novel coronavirus 2019 (nCoV-2019), first reported
in Wuhan, China, has become a global pandemic due to human-to-human transmission with no
specific treatment available. This review highlights the history of coronavirus, its diagnosis,
treatment, and prevention by immunity-modulating Ayurvedic interventions to manage the disease during the early chaotic days of the COVID-19 outburst. Immunity modulation is a documented mode of action for many Ayurvedic drugs, including Tinospora cordifolia, Withania
somnifera, Andrographis paniculata, Glycerrhiza glabra, Boerhaevia diffusa, Ocimum sanctum,
Tribulus terrestris, Curcuma longa, Emblica officinalis, Terminalia chebula, Terminalia bellirica,
etc. Several studies have been performed, and many trials have been registered to evaluate the
effects of these herbal drugs to combat infectious diseases like COVID-19. Studies have also
shown that Ayurvedic drugs, healthy diet, good lifestyle, and psychological aspects all have been
researched over the years and found to have a significant role in increasing immunity and decreasing the number of comorbidities; hence, they should be considered in designing a module
for the prevention and treatment of COVID-19 infection.