Open Coding Research Articles

Living systematic review and comprehensive network meta-analysis of ALS clinical trials: study protocol.

Amyotrophic lateral sclerosis (ALS) is a fatal neurogenerative disease with no effective treatment to date. Despite numerous clinical trials, the majority of studies have been futile in their effort to significantly alter the course of the disease. However, these studies may still provide valuable information for identifying patient subgroups and generating new hypotheses for future research. Additionally, synthesising evidence from these studies may help overcome the limitations of individual studies. Network meta-analysis may refine the assessment of efficacy in specific patient subgroups, evaluate intervention characteristics such as mode of administration or biological mechanisms of action, and rank order promising therapeutic areas of interest. Therefore, we aim to synthesise the available evidence from ALS clinical trials. We will conduct a systematic review to identify all clinical trials that assessed disease-modifying pharmaceutical therapies, cell therapies, or supplements in patients with ALS. Outcomes of interest are clinical disease progression outcomes and survival. We will conduct this search in the period Q4 2024 in three databases: PubMed, Embase and ClinicalTrials.gov for studies from 1999 to 2023. Individual patient data and aggregate data will be collected and subsequentially synthesised in meta-analytical models. The final model will be presented as an open-source web application with biannual updates of the underlying data, thereby providing a 'living' overview of the ALS clinical trial landscape. No ethics approvals are required. Findings will be presented at relevant conferences and submitted to peer-reviewed journals. Data will be stored anonymously in secure repositories.

Exploring Factors Contributing to High Turnover Rate Among Digital Film Technicians: A Grounded Theory Approach

This study aimed to clarify the core elements affecting the turnover intention of grassroots employees in the digital film industry and to construct a model of the factors affecting the turnover rate in this industry. Adopting the grounded theory approach, which encompasses coding techniques such as open, axial, and selective coding, this research involved the participation of 21 grassroots practitioners to explore the causal and influencing factors of the turnover intention of grassroots practitioners in the digital film industry. The results show that determined by the unstable nature of the job and fierce market competition, interpersonal interaction is a core element that influences whether practitioners continue with or leave their jobs. The over-reliance on interpersonal skills leads to negative psychological outcomes and difficulties in career advancement for practitioners. The interpersonal interaction-focused influences model reflects the correlation between the willingness of individuals to leave and the market environment and organizational culture.

Playful programming, Social Resilience, and Persistent Actions as Drivers of Preservice Early Childhood Teachers’ Engagement in Computer Science

In this qualitative study, preservice early childhood education teachers created block-based code to control robots and used the robots in field experience at local preschools. The study is grounded in a conceptual framework that weaves together playful programing and resilience, interlocking concepts that can explain sustained engagement during times of challenge. We investigated how and why preservice early childhood teachers exhibit resilience during collaborative programing. We analyzed their debugging processes, reflections, and interviews using a phenomenological lens. We conducted open and axial coding and analysis of discourse and actions during debugging episodes. Results suggest that teachers exhibited resilience due to the following three reasons: through playful coding, preservice early childhood teachers (a) learned that computer science is approachable and fun, (b) engaged in adaptive attribution, and (c) engaged in joint celebration when they observed each other’s successes during collaborative tinkering. These findings provide potential insights for teacher learning of computing but also for novices learning to program.

Navigating Life: Delaware Families Experiencing Homelessness with Young Children.

This study explored the lived experience of Delaware families residing in homeless shelters and motels with young children. We focused on their daily experiences to gain understanding about their day-to-day living to foster understanding about optimal supports that can facilitate more permanent housing arrangements. We used qualitative approaches to obtain descriptions about the daily lives of families experiencing homelessness with young children. Semi-structured interviews were conducted between November 2022 and February 2023. This study analyzes data from three families using open and thematic coding methods. Families experiencing homelessness with young children discussed their struggle to locate housing, attend to day-to-day tasks, and maintain and obtain employment. Having access to conveniently located affordable and available child care and reliable transportation were discussed across the themes. Evidence building through gathering pertinent qualitative information is a critical step toward understanding the needs of families experiencing homeless. Findings from this study can inform state-level policy and state and non-profit agencies' practices. Current policies that support family homelessness could be adjusted to better address connecting families to resources (e.g., direct connection to landlords), transportation (e.g., increasing allotted bus passes, providing a "free" monthly bus pass), and child care (e.g., co-located care - shelter plus child care, funding enrollment slots left "open" specifically for families experiencing homelessness).

Explaining the Family-Centred Care of Young People With Depressive Disorders and Suicidal Ideations: A Grounded Theory Study.

This study aimed to develop a theory to guide family members caring for young people with depressive disorders and suicidal ideations. Strauss and Corbin's Grounded Theory. Theoretical sampling was used to recruit primary family caregivers (aged 22-60) of young people experiencing depressive disorders and suicidal ideations from hospitals and psychiatric clinics in Taiwan. Data were collected using interviews (n = 23) in 2023. Data were analysed using Corbin & Strauss' analytical framework, including open, axial and selective coding until theoretical saturation was reached. A paradigm model was used to link the 13 categories and develop a substantive theory to help guide family members in the care of their young persons with depressive disorders and suicidal ideations. The core category that emerged was 'Struggling to contain the young person's life by adjusting, assisting, and protecting them from diving into depression'. Other key categories interconnected with this core category were-creating a nurturing environment, adjusting to changes, protecting the young person's safety and assisting with their medical treatment. Family caregivers could use this theory as a guide to enhance the care of young persons experiencing depressive disorders and suicidal ideations and accompany them alongside the healing process. Nursing professionals could provide psychoeducation to family caregivers on how to hold the young person gently and acquire compassion for the young persons' lived experience, thoughts and emotions, by creating a nurturing environment, adjusting to changes, protecting their safety and assisting with their medical treatment. This theory provides valuable guidance for future intervention research aimed at improving family caregivers' ability to care for young persons with depressive disorders and suicidal ideations. The COREQ guidelines were utilised. No patient or public contribution.

Interprofessional Management of (Risk of) Malnutrition and Sarcopenia: A Grounded Theory Study from the Perspective of Professionals.

As our global population ages, malnutrition and sarcopenia are increasingly prevalent. Given the multifactorial nature of these conditions, effective management of (risk of) malnutrition and sarcopenia necessitates interprofessional collaboration (IPC). This study aimed to understand primary and social care professionals' barriers, facilitators, preferences, and needs regarding interprofessional management of (risk of) malnutrition and sarcopenia in community-dwelling older adults. We conducted a qualitative, Straussian, grounded theory study. We collected data using online semi-structured focus group interviews. A grounded theory data analysis was performed using open, axial, and selective coding, followed by developing a conceptual model. We conducted five online focus groups with 28 professionals from the primary and social care setting. We identified five selective codes: 1) Information exchange between professionals must be smooth, 2) Regular consultation on the tasks, responsibilities, and extent of IPC is needed; 3) Thorough involvement of older adults in IPC is preferred; 4) Coordination of interprofessional care around the older adult is needed; and 5) IPC must move beyond healthcare systems. Our conceptual model illustrates three interconnected dimensions in interprofessional collaboration: professionals, infrastructure, and older adults. Based on insights from professionals, interprofessional collaboration requires synergy between professionals, infrastructure, and older adults. Professionals need both infrastructure elements and the engagement of older adults for successful interprofessional collaboration.

Development of venous thromboembolic event risk calculator for metabolic and bariatric surgery patients to reduce mortality

IntroductionVenous thromboembolic events (VTEs) after Metabolic and Bariatric Surgery (MBS) result in significant morbidity and are the leading cause of mortality. The objective of this study was to identify patients who are at a high risk for developing VTE and who may benefit from extended chemoprophylaxis following MBS. MethodsUsing the 2015-2019 Metabolic and Bariatric Surgery Accreditation and Quality Improvement Program (MBSAQIP) participant user file (PUF), we identified 696,069 patients who completed 30-day follow-up data and met the inclusion criteria. Using logistic regression analysis, we identified preoperative and postoperative risk factors associated with VTE and validated our model externally using the MBSAQIP 2020-2021 datasets (N = 273,692). The Hosmer–Lemeshow test was used for goodness of fit and calibration. We also compared our model’s discriminatory capability with that of other VTE risk assessment tools. We then used these risk factors to create an online open source application. ResultsThe overall incidence of VTE after MBS in the 696,069 (MBSAQIP 2015-2019 database) patients included in our analysis was .40% (2759 patients). Our model had a good predictive capability, with a C-statistic of .66. Our model also demonstrated good fit with a Hosmer–Lemeshow chi-square of 11.06 (P = .198). A cut-off point of .4% resulted in a sensitivity of 48.28%, with 24% of patients having a VTE risk greater than .4% within the 2015-2019 MBSAQIP dataset. Among all the perioperative factors selected in the PUF, high risk for VTE included African American race (AOR 1.625, P < .0001), operation length in minutes (AOR: 1.003, P < .0001), preop functional status (AOR 1.012, P = .007), procedure type (RYGB; AOR .768, P < .0001 and RBS; AOR .758, P = .019 with respect to sleeve), preop body mass index (BMI) (AOR 1.012, P < .001), history of pre-op vein thrombosis requiring therapy (AOR 5.041, P < .0001), post-op superficial or organ space surgical site infection (AOR 2.713, P < .0001), preop venous stasis (AOR 1.425, P = .019),at least one readmission within 30 days(AOR 1.583, P < .0001), or at least one reoperation within 30 days (AOR 4.399, P < .0001). ConclusionVTE after MBS can result in increased mortality rates. High-risk patients might benefit from extended chemoprophylaxis. Our model suggests that patients with a VTE risk ≥ .4% in the first 30 days following surgery may benefit from extended chemoprophylaxis.

Devika AI: An Open-Source Revolution In AI-Powered Code Generation

Devika AI is an innovative open-source platform designed to revolutionize software development through AIpowered code generation. Leveraging advanced natural language processing (NLP), machine learning algorithms, and a modular architecture, Devika AI translates high-level human instructions into executable code across multiple programming languages. This paper presents a comprehensive overview of Devika AI's architecture, methodologies, and functionalities. We discuss its ability to improve developer productivity, reduce coding errors, and facilitate collaborative development. Experimental results demonstrate Devika AI's effectiveness in various coding tasks, highlighting its potential as a free and accessible alternative to proprietary AI coding assistants. The implications of Devika AI's adoption on the future of software development are also explored

Crown control in a pair of cavitation bubbles close to a free surface: A numerical study

When a cavitation bubble re-expands near the surface of a liquid, an axisymmetric crown forms around the jet that is initially produced. Controlling this crown is essential if the first jet is to be used in engineering applications such as laser-induced transfer (LIT). Herein, we introduce a second cavitation bubble to control the formation and growth of the crown. Numerical simulations were performed using the compressibleInterIsoFoam solver within the open-source platform OpenFOAM, incorporating a geometric volume-of-fluid approach for tracking interfaces. Detailed analysis showed that a reversal in curvature across the concave interface indicates the moment of crown formation, and this is induced by flow focusing during bubble contraction or momentum transfer from a second expansion. In the presence of the second bubble, the crown type can be classified as either enhanced or inhibited in comparison with a single-bubble scenario. The velocity of crown formation, vcf, is defined to describe the crown type, and a parametric study of crown types was conducted based on the dimensionless stand-off distances, γ1 and γ2. The findings of this study offer new insights into the field of LIT.

Management of experimental workflows in robotic cultivation platforms

In the last decades, robotic cultivation facilities combined with automated execution of workflows have drastically increased the speed of research in biotechnology. In this work, we present the design and deployment of a digital infrastructure for robotic cultivation platforms. We implement a Workflow Management System, using Directed Acyclic Graphs, based on the open-source platform Apache Airflow to increase traceability and the automated execution of experiments. We demonstrate the integration and automation of experimental workflows in a laboratory environment with a heterogeneous device landscape including liquid handling stations, parallel cultivation systems, and mobile robots. The feasibility of our approach is assessed in parallel E. coli fed-batch cultivations with glucose oscillations in which different elastin-like proteins are produced. We show that the use of workflow management systems in robotic cultivation platforms increases automation, robustness and traceability of experimental data.

Optimization of hybridization chain reaction for imaging single RNA molecules in Drosophila larvae

ABSTRACT In situ hybridization techniques are powerful methods for exploring gene expression in a wide range of biological contexts, providing spatial information that is most often lost in traditional biochemical techniques. However, many in situ hybridization methods are costly and time-inefficient, particularly for screening-based projects that follow on from single-cell RNA sequencing data, which rely on of tens of custom-synthetized probes against each specific RNA of interest. Here we provide an optimized pipeline for Hybridization Chain Reaction (HCR)-based RNA visualization, including an open-source code for optimized probe design. Our method achieves high specificity and sensitivity with the option of multiplexing using only five pairs of probes, which greatly lowers the cost and time of the experiment. These features of our HCR protocol are particularly useful and convenient for projects involving screening several genes at medium throughput, especially as the method include an amplification step, which makes the signal readily visible at low magnification imaging.

Flow around triangular prisms with varying vertex angle at low Reynolds numbers

The present work investigates the unsteady flow around triangular prisms with vertex angles of 30°,45°,60°, and 90° for shedding Reynolds number between 50 and 150. The numerical simulations of flow around triangular prisms at different vertex angles and Reynolds number has been carried out using the open-source code OpenFOAM. The wake of the prisms in different cases has been examined using instantaneous and time-averaged velocity and vorticity fields. The energy dynamics in the wake are demonstrated using enstrophy. The paper explains the shedding around a prism and reports the differences in the wake due to the different vertex angles of the prisms employed in the present work. Strouhal number and force coefficients have been obtained and compared for different prisms. The coefficient of lift and drag phase plot indicates a higher spread for prisms with larger vertex angles at higher Reynolds number. The shedding frequency has a linear variation with Reynolds numbers for the prisms. The obtained results were compared with earlier works on square cylinders and 45° oriented square cylinder.

SimplySmart_v1, a new tool for the analysis of DNA damage optimized in primary neuronal cultures

BackgroundThe increased interest in research on DNA damage in neurodegeneration has created a need for the development of tools dedicated to the analysis of DNA damage in neurons. Double-stranded breaks (DSBs) are among the most detrimental types of DNA damage and have become a subject of intensive research. DSBs result in DNA damage foci, which are detectable with the marker γH2AX. Manual counting of DNA damage foci is challenging and biased, and there is a lack of open-source programs optimized specifically in neurons. Thus, we developed a new, fully automated application, SimplySmart_v1, for DNA damage quantification and optimized its performance specifically in primary neurons cultured in vitro.ResultsCompared with control neurons, SimplySmart_v1 accurately identifies the induction of DNA damage with etoposide in primary neurons. It also accurately quantifies DNA damage in the desired fraction of cells and processes a batch of images within a few seconds. SimplySmart_v1 was also capable of quantifying DNA damage effectively regardless of the cell type (neuron or NSC-34). The comparative analysis of SimplySmart_v1 with other open-source tools, such as Fiji, CellProfiler and a focinator, revealed that SimplySmart_v1 is the most ‘user-friendly’ and the quickest tool among others and provides highly accurate results free of variability between measurements. In the context of neurodegenerative research, SimplySmart_v1 revealed an increase in DNA damage in primary neurons expressing abnormal TAR DNA/RNA binding protein (TDP-43).ConclusionsThese findings showed that SimplySmart_v1 is a new and effective tool for research on DNA damage and can successfully replace other available software.

Deploying an IoT-based remote physics lab platform to enhance experimental physics education in remote regions

Abstract For several years, the educational gap in certain Latin American countries and around the world has become increasingly evident. The limited access to cutting-edge knowledge and technologies to strengthen student training processes has emerged as a significant problem, leading to increased inequality in job opportunities in these regions and progressive setbacks in social and economic development. One way to mitigate this problem has been to provide access to information through telecommunications. However, integration with educational processes has been deficient, especially in the areas of science, technology, engineering, and mathematics. This work proposes the development of a remote physics laboratory platform for experimental validation of models explaining certain physical phenomena. This platform is based on the Internet of Things (IoT) paradigm, allowing students and teachers to connect with these experiences coveringtopics in mechanics, electricity and magnetism, optics, and thermodynamics from remote regions. These laboratories utilize physical setups in educational institutions that have been modified to provide connectivity and remote control capabilities based on IoT. Finally, a framework for implementing new remote laboratories based on the IoT paradigm through an open-source platform is presented. The system has been tested and validated with high school and early university students to verify its usefulness, showing the potential to enhance educational processes by providing laboratory access to students and teachers from primary education to secondary education and university-level professional programs.

Improving Elementary Students’ Computational Thinking Skills through an Educational Robot Intervention: A Quasi-Experimental Study

Globally, many educational institutions recognize the importance of computational thinking and have begun incorporating it into primary education. Educators cultivate students’ computational thinking skills through block-based programming; however, a lack of digital learning tools that offer real interaction may negatively impact students’ computational thinking learning performances. This study proposes a cost-effective, block-based, programmable computational thinking educational robot developed using the open-source Arduino platform, combined with Android application development. This robot is specifically designed for use in elementary computational thinking education. To assess the impact of the proposed approach on elementary students’ learning achievement, motivation, and attitudes towards computational thinking education, a quasi-experimental design with control and experimental groups was implemented in the computational thinking curriculum at an elementary school. The experiment was conducted over a period of three weeks and involved two classes of students and one teacher. The control group engaged in computational thinking learning activities using computers, while the experimental group completed computational thinking learning activities using the computational thinking educational robot and application developed in this study. Data were collected through prior knowledge tests of computational thinking, learning motivation and attitude questionnaires, and computational thinking achievement tests completed by the students. The results indicate that the experimental group outperformed the control group in learning achievement, motivation, and attitudes, demonstrating that physical interaction in learning can effectively enhance learning performances.

Digital data collection protocols and template design for an oral health survey of elite athletes in Ireland

AimTo design a digital template for form building, data collection and data management to assess the diet and oral health of elite athletes.Subject and methodsA web-based open-source platform, KoboToolbox (KBTB), was used to aid design and manufacture of a digital data collection form for use in oral health surveys. KBTB frontend form builder was used to create a customised questionnaire. Dental charting systems for the chosen indices were designed using XLSForms, converted to XForm and uploaded to the KBTB interface to create a single form for digital data input. This template was used to collect data for a cross-sectional study investigating the diet and oral health of a convenience sample of elite athletes in Ireland.ResultsA digital data collection (DDC) form was designed for use in oral health surveys. The customised form was then used to collect data for a survey of 88 elite athletes on the KBTB platform. Dietary behaviours were recorded by the participants using KBTB. Following data collection, the dataset was downloaded from KBTB and cleaned for subsequent analysis.ConclusionThe design of a versatile form and oral health questionnaire template using digital tools customised for elite athletes was useful for efficient, comprehensive field data collection. DDC tools are convenient for data form design, collection, and storage. This template can be easily modified for use by other researchers planning oral health surveys.

중학생의 사이버불링에 대한 학교상담사의 대처 경험과 성장에 관한 연구

The purpose of this study is to deeply explore the coping experiences of school counselors regarding cyberbullying among middle school students and their subsequent growth. To achieve this research objective, in-depth interviews were conducted with 20 school counselors who have experience in dealing with cyberbullying. The raw data was conceptualized and categorized using a continuous comparison method. In this study, data were analyzed using the method of grounded theory. As a result of open coding, 79 concepts, 21 subcategories, and 9 categories were derived and arranged in a paradigm model. The central phenomenon experienced by school counselors regarding cyberbullying among middle school students is ‘facing crisis situations,’ which includes ‘recognizing the limitations of the school counselor's role and the unfamiliarity of cyberspace.’ The analysis went through four stages, and the relationships between the categories were confirmed to classify participants into ‘complete rebirth growth type,’ ‘experiential growth type,’ ‘infrastructure-building rebirth type,’ and ‘incomplete rebirth growth type.’ This study is significant in that it provides educational and counseling implications for coping with cyberbullying by deeply exploring and concretizing the practical characteristics and actual appearances of school counselors' coping experiences with cyberbullying among middle school students.

The requirements of providing health education for rural people through electronic methods: the experiences and perspectives of community health workers.

Reliance solely on traditional approaches in health education is no longer considered sufficient, and electronic/digital education can be a complementary approach. Implementing electronic methods in health education requires identifying the requirements from the perspective of the service providers. Therefore, this study aimed to elucidate the experiences and perspectives of community health workers (Behvarzan) regarding the requirements for providing health education for rural people through electronic/digital means. This descriptive qualitative study was conducted in 2022 at Alborz University of Medical Sciences. Data were collected through semi-structured interviews with 14 Behvarzan from Health Houses (HH) in Karaj City. The data were analyzed using the inductive Elo & Kyngas approach and conventional content analysis facilitated with MAXQDA software. After analyzing the results, we extracted 139 open codes, and by merging them for more precise coding and to facilitate the research process, we formed three main themes and ten subthemes. The themes included Technology (technical infrastructure, content production, content delivery methods, and content delivery channels), Facilities and equipment (communication equipment and electronic content repositories), and Stakeholders (training of providers, motivating providers, persuading learners and target groups, and reference groups). From the perspective of rural healthcare workers, the implementation of electronic education requires necessary technology, equipment, facilities, processes, and content should be pursued and provided through specialized working groups, extending from the Ministry of Health and Medical Education to local HHs. These resources should be available to the healthcare workers and their target populations. Concurrently, educational programs and incentives should be defined and offered at the university level and within health networks for rural healthcare workers and their populations.

P-TIMA: a framework of T witter threat intelligence mining and analysis based on a prompt-learning NER model

Abstract Open-source information platforms such as Twitter continuously provide the latest threat intelligence, including new vulnerabilities and in-the-wild exploitations of advanced persistent threat (APT) groups. Automated extraction of threat intelligence from Twitter has become crucial for defenders to access up-to-date threat knowledge. However, existing studies mainly rely on supervised learning methods to extract threat intelligence knowledge, such as entities, which require a large amount of annotated data. This paper presents Threat Intelligence Mining and Analysis based on Prompt Learning (P-TIMA), a framework specifically crafted for extracting and analyzing threat intelligence from Twitter. P-TIMA employs our innovative few-shot entity recognition method, SecEntPrompt (SEP), built on prompt learning, to extract vulnerability intelligence from Twitter. Additionally, P-TIMA analyzes and profiles the overarching vulnerability intelligence obtained from Twitter, along with in-the-wild exploitation intelligence of APT groups. The SEP improves the average entity recognition F1 score by 3.62-4.40 compared with the best-performing comparison model and outperforms the method based on the large language model on recognition performance and inference time. To validate our framework, we apply P-TIMA to extract vulnerability-related threat intelligence from real Twitter data. Through case studies, we then analyze trends in vulnerability threats and the exploitation capabilities of APT groups. In conclusion, our framework provides a more efficient and accurate method for extracting threat intelligence from Twitter, enabling defenders to stay up-to-date with the latest threat trends and helping them improve their defense strategies against cyber attacks.

Designing the Model of Human Resources Analytics in Health System with Grounded Theory

Background: Given the necessity of attracting, retaining, and developing human capital within the health system, the process of human resources analytics in this context is of paramount importance, and it plays a significant role in evidence-based decision-making and policy formulation. Therefore, the aim of the present study was to design a model for human resources analytics in the health system. Methods: This research is practical in nature and utilized a qualitative approach based on grounded theory. In 2023, semi-structured interviews were conducted with 14 experts and managers from Kerman University of Medical Sciences, using purposive sampling until theoretical saturation was achieved. Throughout the process, interviews were continuously compared, and notes were taken during and after the interviews. The collected data from each interview were then analyzed using open, axial, and selective coding with the assistance of MaxQDA20 software. Through categorizing the open codes, axial categories were identified and in the final step, relationships among core categories were established through selective coding. Additionally, the validity and reliability of the findings were assessed and confirmed based on the four criteria of credibility, dependability, confirmability and transferability. Results: In identifying the codes and categories related to human resources analytics, a total of 370 open codes, 61 subcategories, and 24 main categories were generated. These were ultimately examined across 6 main axes, including the central phenomenon, causal conditions, contextual conditions, intervening conditions, strategies and consequences. Conclusion: It is recommended that in order to enhance and develop the human resources analytics process within the health system, attention be paid to the extracted model and its dimensions and components, particularly the identified causal conditions, contextual conditions, and strategies