Open Coding Research Articles

Enhancing Fieldwork Supervision During Early Childhood Inclusive Practicum Placements

This manuscript outlines a collaborative initiative among four state universities to enhance practicum and field-based experiences for early childhood education (ECE) candidates. Grounded in research highlighting the impact of early childhood experiences, the collaboration addresses challenges in the ECCE workforce by fostering inclusive decision-making and engagement with ECCE partners. Through dialogue and partnership, the initiative aims to ensure comprehensive training and support for future early childhood educators. It highlights the evolution of practicum experiences, emphasizing collaborative relationships between novice teachers, mentor teachers, and university supervisors. Key components include the creation of universal training modules and an open-source platform to house training materials. The manuscript concludes with recommendations for enhancing practicum experiences and addressing workforce challenges, emphasizing ongoing collaboration and partnership in promoting high-quality early childhood education.

Single- and Multinozzle Plume Impingement to Detumble Space Debris

The management of space debris is increasingly crucial for ensuring the safety of space missions by mitigating collision risks. Most proposed debris management systems involve the capture and deorbiting of debris. However, it is also essential to eliminate any residual rotation and nutation of the debris to perform capture without accidents. The current work examines the effectiveness of thruster plume impingement for despinning space debris. A proof-of-concept study of plume impingement dynamics is conducted on a rectangular prism target using single- and multiple-nozzle arrangements for different target offsets and orientations. The three-dimensional simulation is carried out using the open-source Direct Simulation Monte Carlo code SPARTA. Staging and dynamic grid adaptation techniques are incorporated to obtain high-resolution results for the multiscale problem. It is observed that the plume–plume interaction in the multinozzle configuration leads to the beneficial formation of a relatively narrow beam of flow interacting with the target; that is, a multinozzle plume exerts a more concentrated directed force, which imparts greater countertorque across a broader spectrum of target orientations than a single-nozzle plume.

Role adaptation of nurses caring for older adults with terminal diseases in geriatric hospitals.

To understand the role adaptation process of nurses caring for older adult patients with terminal diseases in Chinese geriatric hospitals. The Chinese government has been encouraging the conversion of secondary general hospitals and some tertiary hospitals into specialized geriatric hospitals; however, research on nurses' adaptation to caring for older adult patients with terminal diseases in these hospitals is lacking. Individual in-depth interviews were conducted with 13 registered nurses with a minimum of two years of experience caring for older adults with terminal diseases. Following Glaserian grounded theory, open, selective, and theoretical coding were conducted for data analysis. The study followed the Consolidated Criteria for Reporting Qualitative Research checklist. "Guards of the shining sunset" emerged as the core category. Participants experienced three stages: "chaotic me," "rational me," and "inclusive me." They highlighted two causes, three contexts, two intervention conditions, three strategies, and two consequences. The study shows that nurses play a key role in "guarding the shining sunset" of older adult patients with terminal diseases. The observed role adaptation process provides theoretical support for interventions to assist nurses in becoming inclusive "guards of the shining sunset." Nurses play a unique role as guardians protecting the end-of-life quality of elderly patients. Their role needs to be expanded and strengthened via effective coping strategies and comprehensive legal, education, welfare, and professional promotion support policies. The substantive theory offered by this study may be applied by nurses, department leaders, geriatric hospital managers, and national-level institutions to underpin future interventions and improve role adaptation.

Towards maximizing geospatial data usage in north eastern India using open-source scalable user-centric applications

Abstract. The north eastern region of India is characterized by limited physical connectivity and challenging terrain, that requires innovative approaches for effective developmental planning and monitoring using geospatial data and user-centric applications. This paper focuses on leveraging space-based data and applications to address these challenges and enhance decision-making processes in governance. A unified framework for interoperable spatial data sharing has been developed, ensuring that data is easily discoverable, searchable, and consumable through metadata standards and OGC interoperable data services. A dedicated spatial data repository has been established, offering real-time access to over 1400 geospatial datasets and facilitating better decision-making and geo-analytics among diverse user groups. The repository operates on an open-source platform with integrated map viewers and geo-analytics tools, allowing for interactive exploration and visualization of geospatial data. Additionally, 35 user-centric geospatial applications have been operationalized, all developed using open-source geospatial tools and standards. Capacity building programs have been conducted to increase awareness and maximize the utilization of geospatial data services and applications across the region. The platform has boosted utilization of geospatial data services and applications in the region for overall planning and developmental activities for smart governance and societal benefits.

Using Google Earth Engine open-source code for land surface temperature estimation from Landsat data in Chuong My district, Hanoi city, Vietnam

Land surface temperature (LST) in association with urbanization has significantly influenced on local climates and terrestrial surface processes. By using multi-temporal Landsat data in the GEE platform, the study has found that there have been changes in land covers due to the main drivers of industrial development, urban and built-up expansion. This study estimated land surface temperature (LST) in Chuong My district from Landsat 5, 7, 8 and 9 thermal infrared sensors, using different surface emissivity sources. The Google Earth Engine (GEE), an advanced earth science data and analysis platform, offers the estimation of LST products, covering the time period from 2000 to 2024 in study site. RF algorithm for land cover classification and mapping is suggested to be applied in Chuong My district, with overall accuracy of land cover mapping in 2024 being 91.9% with Kappa coefficient of 0.89. The period 2000-2010 showed that 327.0 ha of land were converted to land for industrial development, urban and residential land, while the period 2010-2024 continued to witness a continued conversion of land to other land use purposes, with a decrease in agricultural land area (65.7 ha) and an increase in industrial land use (65.2 ha), but the rate of conversion was much lower than the previous period (2000-2024). The periods of 2000-2010 and 2010-2024 showed that there have been significant changes in land surface temperature. Most of the surface temperature in the entire region increased by over 20C, especially in the period 2003-2015 when a total area of 1424 ha had the temperature increased by above 30C. This is a consequence of the process of urbanization and industrialization, which began to take place in 2008, along with the process of changing the land cover status of the study area. Further studies are needed to better understand the thermal conductivity of surface materials and to plan how to reduce LST in such areas.

The Development of a 3D Magnetic Field Scanner Using Additive Technologies

Visualizing magnetic fields is essential for studying the operation of electromagnetic systems and devices that use permanent magnets or magnetic particles. However, commercial devices for this purpose are often expensive due to their complex designs, which may not always be necessary for specific research needs. This work presents a method for designing an automated laboratory setup for magnetic cartography, utilizing a 3D printer to produce structural plastic components for the scanner. The assembly process is thoroughly described, covering both the hardware and software aspects. Spatial resolution and mapping parameters, such as the number of data points and the collection time, were configured through software. Multiple tests were conducted on samples featuring flat inductive coils on a printed circuit board, providing a reliable model for comparing calculated and measured results. The scanner offers several advantages, including a straightforward design, readily available materials and components, a large scanning area (100 mm × 100 mm × 100 mm), a user-friendly interface, and adaptability for specific tasks. Additionally, the integration of a pre-built macro enables connection to any PC running Windows, while the open-source microcontroller code allows users to customize the scanner’s functionality to meet their specific requirements.

Characterizing structural features of two-dimensional particle systems through Voronoi topology

Abstract This paper introduces a new approach toward characterizing local structural features of two-dimensional particle systems. The approach can accurately identify and characterize defects in high-temperature crystals, distinguish a wide range of nominally disordered systems, and robustly describe complex structures such as grain boundaries. This paper also introduces two-dimensional functionality into the open-source software program VoroTop which automates this analysis. This software package is built on a recently-introduced multithreaded version of Voro++, enabling the analysis of systems with billions of particles on high-performance computer architectures.

ONIX: a unified open-source platform for multimodal neural recording and perturbation during naturalistic behavior.

Behavioral neuroscience faces two conflicting demands: long-duration recordings from large neural populations and unimpeded animal behavior. To meet this challenge we developed ONIX, an open-source data acquisition system with high data throughput (2 GB s-1) and low closed-loop latencies (<1 ms) that uses a 0.3-mm thin tether to minimize behavioral impact. Head position and rotation are tracked in three dimensions and used to drive active commutation without torque measurements. ONIX can acquire data from combinations of passive electrodes, Neuropixels probes, head-mounted microscopes, cameras, three-dimensional trackers and other data sources. We performed uninterrupted, long (~7 h) neural recordings in mice as they traversed complex three-dimensional terrain, and multiday sleep-tracking recordings (~55 h). ONIX enabled exploration with similar mobility as nonimplanted animals, in contrast to conventional tethered systems, which have restricted movement. By combining long recordings with full mobility, our technology will enable progress on questions that require high-quality neural recordings during ethologically grounded behaviors.

Open-Source Software for Building-Integrated Photovoltaic Tiling for Novelty Architecture

Novelty architecture buildings can be tiled with conventional rectangular solar photovoltaic (PV) modules with both close-packed cells or partially transparent modules, vastly increasing renewable energy, reducing carbon emissions, and allowing for positive energy buildings. To enable this potential, in this study, for the first time, two open-source programs were developed and integrated to provide a foundation for designing and coating real-life novelty architecture buildings and objects with solar PV modules. First, a tiling algorithm was proposed and integrated into Blender that can generate solar PV modules on the face of any 3D model, and an augmented Python version of SAM was developed to simulate the performance of the resultant irregularly shaped PV systems. The integrated open-source software was used to analyze the energy performance of seven different novelty BIPVs located across the globe. The buildings’ energy performance was compared to conventional ground-based PV systems, and the results showed that the conventional arrays generate more energy per unit power than the BIPVs. The analysis reveals that the more complex the building model geometry, the less energy the building generates; however, the novelty BIPV power and energy densities far surpass conventional ground-based PV. The real estate savings observed were substantial, reaching 170% in one case where the BIPV reached 750 m in height. The BIPVs’ energy production is optimized by orienting the building via rotation and only needs to be carried out a single time for replication anywhere globally. The results show that the energy yield of the BIPV increases as the building becomes more detailed while the total power and energy decrease, indicating the need for the careful balancing of priorities in building design. Finally, the energy simulations demonstrate the potential for net-positive energy buildings and contribute to net-zero-emission cities. The findings indicate that BIPVs are not only appropriate for conventional residential houses and commercial buildings, but also for historical building replicas or monuments in the future. Further studies are needed to investigate the structural, electrical, and socio-economic aspects of novelty-architecture BIPVs.

Evaluating ChatGPT Responses to Frequently Asked Questions Regarding Rhytidectomy

Importance: Patient education is vital during the assessment process. By informing patients, they are better equipped to make well-informed decisions, potentially leading to greater satisfaction after surgery. Objective: The study aimed to assess accuracy and readability, providing a robust evaluation of ChatGPT 3.5’s ability to address medical inquiries and improve the understanding of the facelift for interested patients. Method: On February 2, 2024, an investigation evaluated ChatGPT 3.5’s performance in answering facelift surgery queries. Four commonly asked questions were posed to the model. Responses were collected in an unguided manner and evaluated for accuracy via a literature review. The responses were evaluated for the accuracy with the senior author. Readability was assessed using the Flesch Reading Ease Score, Automated Readability Index, and Flesch-Kincaid Grade Level, calculated through an open-source platform. Result: The AI chatbot demonstrated its ability to generate comprehensive and accurate information, though some responses occasionally required clarification. The readability score and corresponding levels were consistently assessed at the college level. Conclusion: The study’s findings suggest that AI bots can serve as valuable tools for educating and preparing patients interested in getting a facelift.

Compliance to iron folic acid consumption and factors associated among antenatal care attendant mothers in southern Ethiopia

Iron and folic acid (IFA) consumption is an important strategy for the prevention of birth defects and anemia during pregnancy. In Ethiopia, low proportion of pregnant mothers took an iron tablet for 90 plus days. Therefore, the aim of this study was to assess compliance to IFA consumption and its associated factors among mothers attending antenatal care in Southern Ethiopia, 2021. An institution-based cross-sectional study triangulated with qualitative methods was conducted. The data was collected data from 378 respondents selected by a simple random sampling technique and 21 in-depth interviews were conducted. Epi Data version 3.1 was used to enter data, which was then exported to Statistical Package for the social Science (SPSS) version 21 for further processing and analysis. Bivariable and multivariable logistic regression analyses were carried out to identify the significant association. Variables with a P-value of less than 0.05 were considered significant. The Open code software version 4.03 was used to code and categorize qualitative data, and then thematic analysis was employed to qualitative data. The compliance rate of IFA consumption was 66.58% 95% CI: 61.5-71.4%) Maternal education (AOR: 3.01, 95%CI:1.29, 6.35), knowledge about anemia (AOR: 2.63, 95% CI:1.29), 5.37), knowledge about IFA (AOR: 2.95, 95% CI (1.45, 6.02)), ANC visits (AOR: 2.70, 95% CI 1.17, 6.22), fear of side effect (AOR: 0.08, 95% CI:0.02, 0.24), registration time for initiation of ANC visits (AOR:4.63, 95% CI:1.50, 14.26), and counseling on IFA (AOR:3.95, 95% CI:1.57, 9.98) were significantly associated with compliance IFA consumption of the pregnant mothers. Supplement-related, pregnancy and experience-related, facility related, behavioral -related, perceived family support, and perceived cultural belief findings were identified from qualitative study. In this study, the compliance with IFA consumption was low and influenced by huge range factors. To improve compliance with IFA, health workers provide proper counseling and education for pregnant women on IFA and follow up supplementation.

Unpaid caregivers' process of collaborating with others during older adult hospital-to-home transitions: A grounded theory study.

Unpaid/family caregivers provide support critical to older adult hospital-to-home transitions, but lack time and preparation. There is limited evidence regarding important collaboration for caregivers during the transition. The objective was to examine caregivers' process of collaborating with others, including other family members, healthcare professionals, and community, social, and professional networks, during older adult hospital-to-home transitions. This study utilized grounded theory methodology. One-on-one interviews were conducted with unpaid/family caregivers of an older adult during a hospital-to-home transition. Data were analyzed using open, axial, and selective coding. Participants (N = 16) relationship to the older adult included: partners (n = 8), friends (n = 4), children (n = 3), and siblings (n = 1). Most were female (n = 14) and living with the older adult (n = 10). A conceptual model was developed which illustrates participants' process through 3 stages: 1) identifying and learning the caregiver role, 2) collaborating with others to provide care and support to the older adult, while supporting themselves, during the hospital-to-home transition, and 3) supporting the older adult's progress in recovering independence or planning to provide long-term care and support. Participants described multiple approaches to collaborating with others: caring on own, caring in network, caring with healthcare professionals, and caring with social and professional networks. Implications include the need to recognize and promote utilization of care networks, as it may help address negative outcomes associated with caregiving. We also identified opportunities to further leverage caregivers' social/professional networks and increase focus on caregiver needs in healthcare encounters.

Open-Source Telemedicine Platform Based on WebSockets for Management of Biosignals

Open-Source Telemedicine Platform Based on WebSockets for Management of Biosignals

Investigating on Humanistic Quality Education in Medical Schools in Shandong Province as Basis for Proposed Management Intervention Program

This study aims to understand the content, methods and effective implementation strategies of humanistic education in medical colleges in Shandong Province, to construct a process model of humanistic education in medical colleges in Shandong Province, and finally to propose a management intervention plan. This study adopted a multiple case study method, and semi-structured interviews were conducted with 4 humanistic education teachers, 3 medical students and 3 managers from three medical colleges in Shandong Province through purposive sampling and snowballing methods. This study used the basic ideas of grounded theory to conduct thematic analysis of the interview data. This study conducted open coding, screened typical sentences from the interviewees' answers, extracted keywords from the typical sentences; then the keywords were classified and sorted to further extract relevant information such as the content, methods, and implementation strategies of humanistic education in higher medical colleges. The research results show that the humanities education in medical schools in Shandong Province has a certain foundation, but there are still some shortcomings. In addition, the study proposed four (4) concepts, namely: humanistic leadership in medical schools, strengthening humanistic guidance, strengthening the humanistic development of medical students, and cultivating and nurturing students' humanistic qualities. Furthermore, the findings also indicated the positive impact of empathy, communication skills, and cultural awareness, which highlights the importance of integrating humanities into medical education to develop well-rounded, compassionate healthcare professionals of the future.Based on the findings, a management intervention plan is hereby proposed.

Development and performance of a high-resolution surface wave and storm surge forecast model: application to a large lake

Abstract. A real-time forecast model of surface hydrodynamics in Lake Ontario (Coastlines-LO) was developed to automatically predict storm surges and surface waves. The system uses a dynamically coupled Delft3D–SWAN model with a structured grid to generate 48 h predictions for the lake that are updated every 6 h. The lake surface is forced with meteorological data from the High Resolution Deterministic Prediction System (HRDPS). The forecast model has been running since May 2021, capturing a wide variety of storm conditions. Good agreement between observations and modelled results is achieved, with root mean squared errors (RMSEs) for water levels and waves under 0.02 and 0.26 m, respectively. During storm events, the magnitude and timing of storm surges are accurately predicted at nine monitoring stations (RMSE &lt;0.05 m), with model accuracy either improving or remaining consistent with decreasing forecast length. Forecast significant wave heights agree with observed data (1 %–12 % relative error for peak wave heights) at four wave buoys in the lake. Coastlines-LO forecasts for storm surge prediction for two consecutive storm events were compared to those from the Great Lakes Coastal Forecasting System (GLCFS) to further evaluate model performance. Both systems achieved comparable results with average RMSEs of 0.02 m. Coastlines-LO is an open-source wrapper code driven by open data and has relatively low computational requirements compared to GLCFS, making this approach suitable for forecasting marine conditions in other coastal regions.

Identities of Emerging Adult Men in Contemporary Gujarat

Emerging adulthood is considered a phase in which an individual is required to make choices that shape identity. It involves making major life decisions regarding occupation and relationships. This study focuses on understanding the identities of emerging adult men in the domains of career, relationship, and gender roles. Participants included 40 single emerging adult men, 18–29 years, from educated upper middle-class families in Vadodara city in Gujarat. In-depth interviews, including open-ended questions and hypothetical vignettes, were conducted to gather the data. The qualitative data was examined through open and axial coding, followed by identifying the common and salient themes across the identity domains. The results reveal that urban middle-class men are inclined to be gender sensitive and are resistant to stereotypical notions of masculinity. Assertion of individuality is clearly observed among the young men along with concern for family harmony.

River suspended-sand flux computation with uncertainty estimation using water samples and high-resolution ADCP measurements

Abstract. Measuring suspended-sand fluxes in rivers remains a scientific challenge due to their high spatial and temporal variability. To capture the vertical and lateral gradients of concentration in the cross-section, measurements with point samples are performed. However, the uncertainty related to these measurements is rarely evaluated, as few studies of the major sources of error exist. Therefore, the aim of this study is to develop a method to determine the cross-sectional sand flux and estimate its uncertainty. This SDC (for sand discharge computing) method combines suspended-sand concentrations from point samples with ADCP (acoustic Doppler current profiler) high-resolution depth and velocity measurements. The MAP (for multitransect averaged profile) method allows obtaining an average of several ADCP transects on a regular grid, including the unmeasured areas. The suspended-sand concentrations are integrated vertically by fitting a theoretical exponential suspended-sand profile to the data using Bayesian modeling. The lateral integration is based on the water depth as a proxy for the local bed shear stress to evaluate the bed concentration and sediment diffusion along the river cross-section. The estimation of uncertainty combines ISO standards and semi-empirical methods with a Bayesian approach to estimate the uncertainty due to the vertical integration. The new method is applied to data collected in four rivers under various hydro-sedimentary conditions: the Colorado, Rhône, Isère, and Amazon rivers, with computed flux uncertainties ranging between 18 % and 32 %. The relative difference between the suspended-sand flux in 21 cases calculated with the proposed SDC method compared to the International Organization for Standardization (ISO) 4363 standard method ranges between −40 % and +23 %. This method that comes with a flexible, open-source code is the first to propose an applicable uncertainty estimation that could be adapted to other flux computation methods.

Barefoot Walking (Earthing) Craze and Policy Support Among Community-Dwelling Older Adults in South Korea: A Grounded Theory Analysis

Barefoot walking is currently a craze in South Korean communities. In particular, the elderly are participating in barefoot walking (earthing) to improve their physical and mental health due to their increasing desire for a healthy life. The purpose of this study was to analyze causes, processes, and consequences of the barefoot walking craze among the elderly in Korean society. The research method used was the grounded theory method. Thirty-five elderly people participating in barefoot walking were selected as participants. Data were analyzed according to open coding, axial coding, and selective coding proposed by Strauss and Corbin. First, an open coding phase yielded 61 concepts, 18 subcategories, and 7 categories through continuous questioning and comparative analysis. Second, in the axial coding stage, causal, contextual, and mediating conditions, action/interaction strategies, and consequences were presented, centering on the phenomenon. Causal conditions and contextual conditions contributing to the phenomenon of barefoot walking were identified as “motivation to participate” and “barefoot walking environment,” respectively. “Participating in barefoot walking” was identified as a phenomenon in the axial coding paradigm. The intervening condition was analyzed as “information about barefoot walking.” The action/interaction strategy was analyzed as “spreading the value of barefoot walking.” In the axial coding paradigm, consequences that emerged through the action/interaction strategy were “restoring physical and mental health” and “community spread and nuisance.” Third, in the selective coding stage, “barefoot walking as a daily routine” was derived as the core category, and the narrative outline was presented. To create a sustainable barefoot walking environment in Korea, it is necessary to have a healthy civic consciousness that coexists and harmonizes with nature.

CovSTATIS: A multi-table technique for network neuroscience

Similarity analyses between multiple correlation or covariance tables constitute the cornerstone of network neuroscience. Here, we introduce covSTATIS, a versatile, linear, unsupervised multi-table method designed to identify structured patterns in multi-table data, and allow for the simultaneous extraction and interpretation of both individual and group-level features. With covSTATIS, multiple similarity tables can now be easily integrated, without requiring a priori data simplification, complex black-box implementations, user-dependent specifications, or supervised frameworks. Applications of covSTATIS, a tutorial with Open Data and source code are provided. CovSTATIS offers a promising avenue for advancing the theoretical and analytic landscape of network neuroscience.

Quantifying traffic emission reductions and traffic congestion alleviation from high-capacity ride-sharing

Despite the promising benefits that ride-sharing offers, there has been a lack of research on the benefits of high-capacity ride-sharing services. Prior research has also overlooked the relationship between traffic volume and the degree of traffic congestion and emissions. To address these gaps, this study develops an open-source agent-based simulation platform and a heuristic algorithm to quantify the benefits of high-capacity ride-sharing with significantly lower computational costs. The simulation platform integrates a traffic emission model and a speed-density traffic flow model to characterise the interactions between traffic congestion levels and emissions. The experiment results demonstrate that ride-sharing with vehicle capacities of 2, 4, and 6 passengers can alleviate total traffic congestion by approximately 3%, 4%, and 5%, and reduce traffic emissions of a ride-sourcing system by approximately 30%, 45%, and 50%, respectively. This study can guide transportation network companies in designing and managing more efficient and environment-friendly mobility systems.