bluuebunny/crossref_metadata_2025_split huggingface dataset:
Medical science students’ experiences of test anxiety: a phenomenological study
Authors: Badrian Majid , Bazrafkan Leila , Shakour Mahsa 
Published: July 2022

Abstract
Introduction
The studies show test anxiety is a common disorder in students that causes academic failure. There are not enough studies and specific theoretical background about test anxiety and ways to deal with it, so the purpose of this study was to do a qualitative study to fully understand the ways to deal with test anxiety in medical Sciences students.

Materials and methods
This is a qualitative study. The participants are the students of the last 2 years of pharmacy, medicine and dentistry at Isfahan University of Medical Sciences. Ten students were selected by purposeful sampling, and interviews continued until the data saturation stage and the lack of access to new data. The data were analyzed by seven-level Colaizzi method.

Findings
After analyzing data, about 50 codes were extracted. These codes divided into 16 subclasses, and among them, ultimately five main themes are extracted: “Prayer and Dialogue with God”, “Interaction and communication with friends and relatives”, “studying strategies”, “Finding ways to relax and self-care” and “Negative strategies” were extracted.

Conclusions
The result of this study showed that students often use positive strategies to overcome the test anxiety and try to use positive strategies, but some students are advised of undesirable strategies such as misuse of authorized drugs and writing cheating that that lead to a lot of complex problems. The educational system should do its utmost effort to empower students to manage the anxiety by learning the best strategies.
The impact of working capital management on credit rating
Authors: Abuhommous Ala’a Adden , Alsaraireh Ahmad Salim , Alqaralleh Huthaifa 
Published: July 2022

AbstractThis study investigates the possible nonlinear relationship between working capital and credit rating. Furthermore, it examines the relationship between the three components of working capital (inventory, accounts receivable, and accounts payable) and a firm’s credit rating. Employing data for U.S listed firms for the period between 1985 and 2017, the results of our ordered probit model show a nonlinear relationship between working capital and its components and credit rating. Finally, we find that the deviation from the optimal working capital adversely affects the credit rating. The results of this study are of significant importance for policy makers, managers, decision makers, and credit-rating agencies, as they help highlight the importance of working capital management for a firm’s credit rating.
Simulation translation differences between craft groups
Authors: Gard Jye , Duong Chi , Murtagh Kirsty , Gill Jessica , Lambe Katherine , Summers Ian 
Published: July 2022

Abstract
Background
Many simulation-based clinical education events (SBCEE) aim to prepare healthcare professionals with the knowledge, skills, and features of professionalism needed to deliver quality patient care. However, how these SBCEE learnings are translated into broader workplace practices by learners from different craft groups has not been described.

Objectives
To understand how learners from different craft groups (doctors and nurses) anticipate simulation-based learnings will translate to their workplaces and the process by which translation occurs.

Design
Qualitative descriptive study design using pre- and post-SBCEE questionnaires.

Settings
A large tertiary Australian hospital-based simulation centre that facilitates SBCEE for multi-professional graduate and undergraduate clinicians from 16 hospitals.

Methods
Participants who attended SBCEEs between May and October 2021 completed questionnaires at two touchpoints, on the day of attending a SBCEE and 6 weeks after. Based on a phenomenological approach, the study examined clinicians’ experiences in relation to simulation education, intended simulation learning use in the workplace, and perceived success in subsequently using these learnings to improve clinical outcomes. Qualitative inductive thematic data analysis was used to develop narratives for different learner cohorts.

Results
Three overarching themes were identified regarding simulation participants’ perceptions of the success of translating simulation learnings into the workplace. These were: scenario-workplace mirroring, self-assessment, and successful confidence. Doctor participants found it difficult to map SBCEE learnings to their workplace environments if they did not mirror those used in simulation. Nurses sought peer evaluation to analyse the effectiveness of their workplace translations, whereas doctors relied on self-assessment. Learners from both craft groups highly prized ‘confidence-building’ as a key indicator of improved workplace performance achieved through SBCEE learning.

Conclusion
A diverse range of factors influences healthcare workers’ experiences in translating simulation learnings to their workplace. To equip simulation learners to translate learnings from a SBCEE into their clinical practices, we suggest the following areas of focus: co-development of translation plans with learners during the delivery of an SBCEE including the indicators of success, above table discussions on the generalisability of learnings to different environments and contexts, smart investment in simulation outputs, and cautious championing of confidence-building.
Forming Student Teams to Incorporate Soft Skills and Commonality of Schedule
Authors: Bowers Andrew , Bowers Melissa R. , Bryan Nana , Letizia Paolo , Murphy Spencer 
Published: July 2022

It is widely recognized that students’ learning can be enhanced and facilitated when students have the opportunity to work together in teams. As a consequence, the pursuit of a methodology to form optimal student teams continues to challenge academics. Based on a review of related literature, we propose a model that includes new approaches to two team criteria. The first is a discrete optimization approach to commonality of schedule. To facilitate team meetings, we offer an exact formulation to ensure students on a given team share a minimum number of common time slots during which they are available. The second team criterion is sufficient soft skills. Using a unique text analysis approach, we ensure that each team includes students with adequate soft skills, such as leadership and interpersonal skills. Our analytic approach enhances the students’ learning experience and class performance and simplifies the faculty task of forming teams. History: This paper was refereed.
Microscopic Traffic Modeling Inside Intersections: Interactions Between Drivers
Authors: Zhao Jing , Knoop Victor L. , Wang Meng 
Published: July 2022

Microscopic traffic flow models enable predictions of traffic operations, which allows traffic engineers to assess the efficiency and safety effects of roadway designs. Modeling vehicle trajectories inside intersections is challenging because there is an infinite number of possible paths in a two-dimensional space, and drivers can simultaneously adapt their speeds as well. To date, human driver models for simultaneous longitudinal and lateral vehicle control based on the infrastructure characteristics and interactions with other drivers inside an intersection are still lacking. The contribution of this paper is threefold. First, it proposes an integrated microscopic traffic flow model to describe human-driven vehicle maneuvers under interactions. Drivers plan their heading and acceleration in the predicted future to minimize costs representing undesirable situations. The model works with a joint optimization for an interaction cost term. The weights associated with the interaction cost reflect how selfish or altruistic drivers are. Second, the proposed model endogenously gives the order of vehicles in case of crossing paths. Third, the paper develops a clustered validation method for microscopic traffic flow models with interacting vehicles, which account for interdriver variations. Results show that the model can accurately describe vehicle passing orders of interacting maneuvers, paths, and speeds against empirical data. The model can be applied to assess various intersection designs. Funding: This work was supported by the National Natural Science Foundation of China [Grants 71971140 and 52122215] and the Natural Science Foundation of Shanghai [Grant 20ZR1439300].
Model Kemitraan Pengembangan UKM Batik di Eks Lokalisasi Dolly
Authors: Ustazah Eri Naharani 
Published: July 2022

Level kesiapan masyarakat dalam menerima program pengembangan UKM Batik Dolly menjadi sebuah produk turunan adalah belum siap. Oleh karena itu dibutuhkan tenaga atau keahlian khusus. Sehubungan hal tersebut, pengabdian kegiatan ini bermaksud membantu pengembangan ekonomi lokal khususnya di kawasan Dolly-Jarak melalui upaya pemberdayaan masyarakat berbasis kewirausahaan pengembangan produk batik dan turunannya melalui kemitraan antar pelaku KM Batik dan partner desainer lain. Pengembangan yang dilakukan berupa pembuatan produk turunan batik yang disesuaikan dengan kompetensi pengabdi dipilih 3 (tiga) yang akan dikembangkan yaitu: baju to wear, baju rumahan, dan sajadah lipat. Skema kerjasama yang digunakan adalah melibatkan pelaku UKM Batik Dolly sebagai pemasok kain batik dan menggandeng partner Radiya Kinan, Zorey, dan Aghili sebagai produsen produk turunan batik. Kegiatan pengabdian yang diawali dengn pelatihan konsep dan desain sajadah lipat secara online. Tahapan dan urutan kerja dalam pengembangan produk dimulai dari tahap desain, pembuatan produk, proses Quality Control produk serta Proses Persiapan Pemasaran Produk harus disesuaikan dengan kasus Pandemi. Setiap tahapan dibagi ke dalam tim-tim khusus yang selalu diawasi dan didampingi, agar dihasilkan kualitas produk yang optimal. Upaya pengembangan produk turunan batik diharapkan berkesinambungan dan diminati masyarakat luas, sehingga sistem kemitraan yang dibangun adalah dengan melibatkan produsen lain dalam membuat produk turunan batik.
Supporting mental health and wellbeing of university and college students: A systematic review of review-level evidence of interventions
Authors: Worsley Joanne Deborah , Pennington Andy , Corcoran Rhiannon 
Published: July 2022

Aims
The review of reviews had three aims: (i) to synthesize the available evidence on interventions to improve college and university students’ mental health and wellbeing; (ii) to identify the effectiveness of interventions, and (iii) to highlight gaps in the evidence base for future study.

Methods
Electronic database searches were conducted to identify reviews in English from high-income OECD countries published between 1999 and 2020. All review-level empirical studies involving post-secondary students attending colleges of further education or universities that examined interventions to improve general mental health and wellbeing were included. Articles were critically appraised using an amended version of the AMSTAR 2 tool. Evidence from the included reviews were narratively synthesized and organised by intervention types.

Results
Twenty-seven reviews met the review of reviews inclusion criteria. The quality of the included reviews varied considerably. Intervention types identified included: mindfulness-based interventions, psychological interventions, psychoeducation interventions, recreation programmes, relaxation interventions, setting-based interventions, and stress management/reduction interventions. There was evidence that mindfulness-based interventions, cognitive behavioural therapy (CBT), and interventions delivered via technology were effective when compared to a passive control. Some evidence suggested that the effects of CBT-related interventions are sustained over time. Psychoeducation interventions do not appear to be as effective as other forms of intervention, with its effects not enduring over time.

Conclusions
The review of reviews located a sizeable body of evidence on specific interventions such as mindfulness and cognitive-behavioural interventions. The evidence suggests that these interventions can effectively reduce common mental health difficulties in the higher education student body. Gaps and limitations in the reviews and the underlying body of evidence have been identified. These include a notable gap in the existing body of review-level evidence on setting-based interventions, acceptance and commitment training, and interventions for students attending colleges in UK settings.
Assessing breast cancer awareness on reproductive age women in West Badewacho Woreda, Hadiyya Zone, South Ethiopia; Community based cross- sectional study
Authors: Funga Mengistu Lodebo , Dilebo Zerihun Damissie , Shuramo Anebo Getachewu , Bereku Tessema 
Published: July 2022

Introduction
Breast cancer is the most commonly diagnosed cancer in women worldwide, in both high- and low-income countries. Individual and community awareness of breast cancer can be extremely beneficial. However, breast cancer awareness is extremely low among Ethiopian women, particularly in rural areas. Thus, the aim of this study was assessing awareness of breast cancer on reproductive-aged women in West Badewacho Woreda, Hadiya Zone, South Ethiopia, 2020.

Method
A community-based-cross sectional study was employed from April 18 to May 16, 2020. To obtain data, a pre-tested structured interviewer-administered questionnaire was employed. A multistage random sampling technique was employed to select reproductive-aged women from Woreda. Data was entered into a computer using Epi data version 3.1, and edited, cleaned and analyzed using SPSS windows version 20. Bivariable and multivariable analyses were used to identify determinants related to awareness of breast cancer.

Result
A total of 578 reproductive-age women participated in this study. Only 364 women of reproductive-age (63%) had heard about breast cancer. 234 (64.3%) of the respondents were aware of breast cancer. After adjusting for other variables, husbands’ educational status [AOR = 0.262; 95% CI (0.076, 0.900)], family history of breast cancer [AOR = 0.281; 95% CI (0.132, 0.594)] and having TV/Radio [AOR = 0.489; 95% CI (0.246, 0.972)] were significant predictors for awareness of breast cancer.

Conclusion
This study emphasized the importance of raising breast cancer awareness among women in the study area.
Vaccine discourse during the onset of the COVID-19 pandemic: Topical structure and source patterns informing efforts to combat vaccine hesitancy
Authors: Hwang Juwon , Su Min-Hsin , Jiang Xiaoya , Lian Ruixue , Tveleneva Arina , Shah Dhavan 
Published: July 2022

BackgroundUnderstanding public discourse about a COVID-19 vaccine in the early phase of the COVID-19 pandemic may provide key insights concerning vaccine hesitancy. However, few studies have investigated the communicative patterns in which Twitter users participate discursively in vaccine discussions.ObjectivesThis study aims to investigate 1) the major topics that emerged from public conversation on Twitter concerning vaccines for COVID-19, 2) the topics that were emphasized in tweets with either positive or negative sentiment toward a COVID-19 vaccine, and 3) the type of online accounts in which tweets with either positive or negative sentiment were more likely to circulate.MethodsWe randomly extracted a total of 349,979 COVID-19 vaccine-related tweets from the initial period of the pandemic. Out of 64,216 unique tweets, a total of 23,133 (36.03%) tweets were classified as positive and 14,051 (21.88%) as negative toward a COVID-19 vaccine. We conducted Structural Topic Modeling and Network Analysis to reveal the distinct topical structure and connection patterns that characterize positive and negative discourse toward a COVID-19 vaccine.ResultsOur STM analysis revealed the most prominent topic emerged on Twitter of a COVID-19 vaccine was “other infectious diseases”, followed by “vaccine safety concerns”, and “conspiracy theory.” While the positive discourse demonstrated a broad range of topics such as “vaccine development”, “vaccine effectiveness”, and “safety test”, negative discourse was more narrowly focused on topics such as “conspiracy theory” and “safety concerns.” Beyond topical differences, positive discourse was more likely to interact with verified sources such as scientists/medical sources and the media/journalists, whereas negative discourse tended to interact with politicians and online influencers.ConclusionsPositive and negative discourse was not only structured around distinct topics but also circulated within different networks. Public health communicators need to address specific topics of public concern in varying information hubs based on audience segmentation, potentially increasing COVID-19 vaccine uptake.
Prácticas heterodoxas ysantidad queer: “El proceso de fe” (s. XVII) de las monjas clarisas de Trujillo
Authors: Paz Torres Margarita , Ruiz Tresgallo Silvia 
Published: July 2022

ResumenLos testimonios de Luisa Benítez y Ana Núñez, dos jóvenes monjas del Convento de Santa Clara de Trujillo (Perú), proveen información relativa al proceso de fe que el tribunal inquisitorial de Lima llevó a cabo en el siglo XVII. La heterodoxia religiosa y política de estas monjas criollas, presente tanto en el lenguaje de sus declaraciones inquisitoriales como en su performance de santidad, transgrede los roles de género femeninos según expectativas patriarcales y a la vez, como proponemos, abre el espacio para que estos sujetos femeninos desarrollen lo que llamamos una santidad queer que reorienta la ideología de la cultura imperial española.
La articulación entre los niveles de definición de la política educativa en Argentina. La experiencia del plan de capacitación docente Escuelas de Innovación (2011–2015)
Authors: Marchetti Braian , Porta Luis 
Published: July 2022

Los niveles de definición macro, meso y micro de las políticas educativas se articulan en el marco del federalismo argentino para alcanzar su puesta en acto. En el caso de las políticas de inclusión digital y las acciones de formación docente en ejercicio, esta articulación significa una de las cuestiones fundamentales para que pueda desarrollarse.
Recuperamos en este trabajo algunos de los hallazgos de una investigación mayor realizada sobre las políticas públicas de formación docente con inclusión de medios digitales, en la cual hemos profundizado sobre la experiencia del Plan Nacional de Capacitación Escuelas de Innovación (2011–2015) y su articulación con las jurisdicciones provinciales. Desde una metodología cualitativa e interpretativa, el trabajo de campo de esta investigación se centró principalmente en la realización de entrevistas en profundidad a integrantes del plan Escuelas de Innovación.
STRUCTURAL EQUATION MODELING FOR ANALYZING THE TECHNOLOGY ACCEPTANCE MODEL OF STUDENTS IN ONLINE TEACHING DURING THE COVID-19 PANDEMIC
Authors: Annas Suwardi , Ruliana Ruliana , Sanusi Wahidah 
Published: July 2022

Online teaching can be a solution in the learning process during the pandemic to stop the spreading of the Covid-19 infection. Universitas Negeri Makassar (UNM) as an educational institution provided a Learning Management System (LMS) to support the online teaching and learning process with the platform name SYAM-OK. In this research, we examine the behavioral model of a student's acceptance of the use of an information system SYAM-OK in online teaching. 120 students in the sample used online teaching fully during the pandemic. The data was obtained from an online questionnaire using a google form whose contents were based on Technology Acceptance Model (TAM). The variable of TAM consists of Perceived Ease of Use, Perceived Usefulness, Attitude Towards, Behavioral Intention, and Actual Use. The Structural Equation Modeling (SEM) PLS method was used in this research for modeling the relationship between TAM variables. Based on the results of the SEM we obtained that Perceived Usefulness significantly affects the Attitude Towards and Attitude Towards significantly affects the behavioral intention. By using the bootstrapping and T statistics, we conclude that SEM has identified the significant effects between variables of TAM.
GANs for generation of synthetic ultrasound images from small datasets
Authors: Maack Lennart , Holstein Lennart , Schlaefer Alexander 
Published: July 2022

Abstract
The task of medical image classification is increasingly supported by algorithms. Deep learning methods like convolutional neural networks (CNNs) show superior performance in medical image analysis but need a high-quality training dataset with a large number of annotated samples. Particularly in the medical domain, the availability of such datasets is rare due to data privacy or the lack of data sharing practices among institutes. Generative adversarial networks (GANs) are able to generate high quality synthetic images. This work investigates the capabilities of different state-of-the-art GAN architectures in generating realistic breast ultrasound images if only a small amount of training data is available. In a second step, these synthetic images are used to augment the real ultrasound image dataset utilized for training CNNs. The training of both GANs and CNNs is conducted with systematically reduced dataset sizes. The GAN architectures are capable of generating realistic ultrasound images. GANs using data augmentation techniques outperform the baseline Style- GAN2 with respect to the Frechet Inception distance by up to 64.2%. CNN models trained with additional synthetic data outperform the baseline CNN model using only real data for training by up to 15.3% with respect to the F1 score, especially for datasets containing less than 100 images. As a conclusion, GANs can successfully be used to generate synthetic ultrasound images of high quality and diversity, improve classification performance of CNNs and thus provide a benefit to computer-aided diagnostics.
Does the 3D Feature Descriptor Impact The Registration Accuracy in Laparoscopic Liver Surgery?
Authors: Krames Lorena , Suppa Per , Nahm Werner 
Published: July 2022

Abstract
In laparoscopic liver surgery (LLS) image-guided navigation systems could support the surgeon by providing subsurface information such as the positions of tumors and vessels. For this purpose, one option is to perform a registration of preoperative 3D data and 3D surface patches reconstructed from laparoscopic images. Part of an automatic 3D registration pipeline is the feature description, which takes into account various geometric and spatial information. Since there is no leading feature descriptor in the field of LLS, two feature descriptors are compared in this paper: The Fast Point Feature Histogram (FPFH) and Triple Orthogonal Local Depth Images (TOLDI). To evaluate their performance, three perturbations were induced: varying surface patch sizes, spatial displacement, and Gaussian deformation. Registration was performed using the RANSAC algorithm. FPFH outperformed TOLDI for small surface patches and in case of Gaussian deformations in terms of registration accuracy. In contrast, TOLDI showed lower registration errors for patches with spatial displacement. While developing a 3D-3D registration pipeline, the choice of the feature descriptor is of importance, consequently a careful choice suitable for the application in LLS is necessary.