Programming Expertise Research Articles

Bringing Dance to Older Adults: Program Experts' Perspectives on the Role of Community Dance Classes to Support Older Adults.

Dancing offers several health and wellness benefits for older adults: it may promote physical literacy (PL) and positively influence the aging process. Yet, limited research considers the perspectives of those with experience working with older adults and in community dance programming. The purpose of this study was to understand program experts' perspectives on how older adult community dance can promote PL and contribute to age-friendly cities and community initiatives. Four themes were identified from semi-structured interviews with five program experts: (1) expert instructors tailor classes to participants' needs and interests; (2) the heart of what draws us to dancing: authentic experience and social connection; (3) elitist, ableist, and gendered assumptions of dance prevent social inclusion of older adults in dancing spaces; and (4) collaboration across sectors is needed to offer accessible, sustainable, and valued dance programming. Recommendations for developing and implementing older adult community dance programming are described.

Nanomagnetic chitosan/β-cyclodextrin for dispersive solid phase extraction of trace desipramine drug

In recent years, there has been an increase in the amount of pharmaceutical medication contamination of water sources. They are extremely difficult to detect since they are only present in trace amounts. In the presented study, the extraction method of dispersive solid phase was paired with HPLC as an easy, effective, and developed approach for preconcentration and measurement of desipramine drug, a depression medication, in aqueous and urine samples with nanomagnetic chitosan/β-cyclodextrin. The sorbent was produced from magnetic nanoparticles of (Fe3O4) in chitosan substrate modified with β-cyclodextrin (βCD) for increasing porosity, and then it was distinguished by several methods, containing X-ray diffraction, infrared spectroscopy, vibrating sample magnetometry, energy dispersive X-ray analysis, and field emission scanning electron microscopy. The significant elements affecting extraction effectiveness are optimized as pH, ionic strength of the solution, amount of adsorbent, the type of elution solvent, temperature and time adsorption, and elution solvent volume (in a multivariate method with the help of the Design Expert program). The results show the very good performance of this technique. The calibration curve of the method is a range of linear of 2–50 μg/L. The detection limit of the method is 0.39 μg/L, the 2.50% relative standard deviation in the method, and the correlation coefficient is 0.98. The maximum adsorbent capacity was recorded at 59.98 mg g−1.

Specific Features of a Fire Safety and Technical Expert Training

The paper examines a range of issues related to the influence of the level of training and competence of the expert on the quality and timeliness of forensic fire safety and technical expertise. The current state of the specifics of such a training in educational institutions at Forensic Expertise Programs (Engineering and Technical Expertise specialization) is analyzed. The authors propose some recommendations and ways to solve some problems in this regard. The authors believe that the current state of training of fire technical experts requires some changes. This is due to many factors, for example, an increase in the range of tasks to be solved, the emergence of new specializations (subtypes of forensic fire safety and technical examination), the introduction of new technologies and expert equipment, reengineering of scientific and methodological support for the activities of a fire safety and technical expert, etc. In the paper, the authors pay special attention to the criteria for selecting applicants to universities and the features of training future experts. It is proposed to make some changes to the regulatory documents for the preparation (training) of fire safety and technical experts at Forensic Expertise Programs (Engineering and Technical Expertise specialization).

Influence of Maintenance Funds on Improve Road Steadiness with the Curva Expert Program

Sustainable road construction is instrumental in improving connectivity among regions and economies while also offering road users a diverse range of options within the traffic network. To ensure optimal road performance for users, it becomes essential to allocate adequate maintenance funds that correlate with the planned service life. This necessity originates from a profound understanding of the significant influence maintenance funds have on road steadiness. Therefore, this study aims to establish a comprehensive road steadiness model, investigating the influence of toll roads as new routes and the impact on maintenance funds. The analysis included national roads across 15 cities in Central Java Province, Indonesia, covering a distance of 759.75 km from 2018–2023. Using a quantitative approach, the study adopted the Curva Expert program to evaluate the values of road steadiness and maintenance funds. The results showed a 5.78% enhancement in road steadiness over the period from 2018 to 2023, underscoring the positive impact of sustainable road construction practices and the allocation of adequate maintenance funds. The establishment of relationship between road steadiness and maintenance funds was established through a regression value of R2=0.94. This statistical correlation is represented by the equation y= 90.521 + 0.022x, providing a quantitative understanding of how maintenance funds influence road steadiness. The insights obtained from the outcomes of road steadiness modeling reiterate the significance of investing in additional routes and ensuring sufficient maintenance funds to improve performance. Doi: 10.28991/CEJ-2024-010-02-014 Full Text: PDF

Utilization of composite flour (red bean, catfish, oyster mushroom and tempeh formula flour) in making cookies

Local food ingredients can be used as alternative ingredients for cookie products to help ending hunger and overcome malnutrition are the objectives of SDG 2 and 3. This study aims to obtain the optimum cookie formula using composite flour from local food ingredients consisting of red bean flour, catfish flour, oyster mushrooms flour, and tempeh formula flour using the design expert program v.13 Response Surface Methodology (RSM) Box Behnken Design/BBD. Independent variables are different levels of red bean flour (20-45 g), catfish flour (10-45 g), oyster mushroom flour (5-25 g), and tempeh formula flour (5-35 g) with 29 (twenty-nine) different runs of 4 (four) similar center points. Using goal settings for each response based on proximate composition achieved from the best definition of each response to achieve high-quality cookies, an optimum formulation of cookies was obtained at 44.21% red bean flour, 34.39% catfish flour, 7.46% oyster mushroom flour, and 20.52% tempeh formula flour, with a desirability level of 1.00.

The Influence of Industrial Work Practice Experience on Entrepreneurial Interest in Students of Automotive Mechanical Engineering Expertise Program SMK Texmaco Pemalang

Prakerin or Industrial Work Practice is an educational, training, and learning activity for Vocational High School (SMK) students conducted in the business world or the industrial world related to student competence in accordance with the field mastered. The purpose of this study is to determine whether there is an effect of work experience in the industry (Prakerin) on interest in entrepreneurship and how much influence. The subjects of this study include only class students. Where there are 88 students (2 classes), of which 44 students are used as a test and 44 other students as a research sample.

Automated self-optimization, intensification, and scale-up of photocatalysis in flow.

The optimization, intensification, and scale-up of photochemical processes constitute a particular challenge in a manufacturing environment geared primarily toward thermal chemistry. In this work, we present a versatile flow-based robotic platform to address these challenges through the integration of readily available hardware and custom software. Our open-source platform combines a liquid handler, syringe pumps, a tunable continuous-flow photoreactor, inexpensive Internet of Things devices, and an in-line benchtop nuclear magnetic resonance spectrometer to enable automated, data-rich optimization with a closed-loop Bayesian optimization strategy. A user-friendly graphical interface allows chemists without programming or machine learning expertise to easily monitor, analyze, and improve photocatalytic reactions with respect to both continuous and discrete variables. The system's effectiveness was demonstrated by increasing overall reaction yields and improving space-time yields compared with those of previously reported processes.

INCREASING ACCESS TO INTERDISCIPLINARY IBD CARE FOR NEWLY DIAGNOSED IBD PATIENTS USING TELEMEDICINE: AN EXTENSION OF THE COMPASS-IBD PROGRAM

Abstract INTRODUCTION Interdisciplinary care is increasingly being recognized as important in the care of inflammatory bowel disease (IBD) patients. However, access to additional resources to do this are frequently only available in tertiary-care IBD centers. We piloted a telemedicine version of an interdisciplinary care program for recently diagnosed IBD patients. METHODS The Mount Sinai Health system has a well-established IBD center, located at the Mount Sinai Hospital in New York. Patients who were diagnosed with IBD in the last 18 months were identified by a primary gastroenterologist working at a community site within the Mount Sinai health system. Once identified, patients were referred electronically and enrolled in the Comprehensive Care for the Recently Diagnosed IBD Patient (COMPASS-IBD) program. This existing program provides interdisciplinary care to newly diagnosed IBD patients. IBD patients have access to a physician who works at the IBD Center, a nutritionist specializing in IBD diets, an experienced IBD clinical pharmacist and a licensed clinical social worker dedicated to the mental and social needs of patients with IBD. After an initial assessment, these patients were then provided access as needed to the program experts. All appointments were done virtually using telemedicine. After completing intake, recommendations were consolidated and provided to the patient and the patient’s primary gastroenterologist electronically. The patient then followed up with his/her primary gastroenterologist. RESULTS For this pilot study, twelve newly diagnosed inflammatory bowel disease patients were identified at community sites within the Mount Sinai health system. Enrolled patients met with all members of the COMPASS- IBD program team for their initial intake. The referring gastroenterologist received summary recommendations for all patients who completed the intake. Participating patients were overall satisfied with the intervention and use of telemedicine as a primary modality. No major barriers to virtual program implementation were identified. DISCUSSION We demonstrated the feasibility of providing interdisciplinary care via telemedicine for recently diagnosed IBD patients. This supports a “hub and spoke” model for IBD care. We believe our pilot study shows a simple way for health systems to increase access to interdisciplinary IBD care for patients with limited access to tertiary-care IBD Centers. This approach may also help in achieving health equity for underserved IBD patient populations.

CMD + V for chemistry: Image to chemical structure conversion directly done in the clipboard

AbstractWe present Clipboard‐to‐SMILES Converter (C2SC), a macOS application that directly converts molecular structures from the clipboard. The app focuses on seamlessly converting screenshots of molecules into a desired molecular representation. It supports a wide range of molecular representations, such as SMILES, SELFIES, InChI's, IUPAC names, RDKit Mol's, and CAS numbers, allowing effortless conversion between these formats within the clipboard. C2SC automatically saves converted molecules to a local history file and displays the last 10 entries for quick access. Additionally, it incorporates several SMILES operations, including canonicalization, augmentation, as well price‐searching molecules on chemical vendors for the cost‐effective purchasing option. Beyond the one‐click conversion from clipboard to molecular structures, the app offers continuous monitoring of the clipboard which automatically converts any supported representations or images detected into SMILES. The convenient interface, directly in the status bar, as well as availability as macOS application, makes C2SC useful for a broad community not requiring any programming expertise. Most conversions are performed locally, notably the image‐to‐SMILES conversion, with internet access only necessary for specific tasks like price lookups. In summary, C2SC provides a user‐friendly and efficient solution for converting molecular structures directly from the clipboard, offering seamless conversions between comprehensive chemical representations and can be directly downloaded from https://github.com/O-Schilter/Clipboard-to-SMILES-Converter.

IEEG-recon: A fast and scalable pipeline for accurate reconstruction of intracranial electrodes and implantable devices.

Clinicians use intracranial electroencephalography (iEEG) in conjunction with noninvasive brain imaging to identify epileptic networks and target therapy for drug-resistant epilepsy cases. Our goal was to promote ongoing and future collaboration by automating the process of "electrode reconstruction," which involves the labeling, registration, and assignment of iEEG electrode coordinates on neuroimaging. We developed a standalone, modular pipeline that performs electrode reconstruction. We demonstrate our tool's compatibility with clinical and research workflows and its scalability on cloud platforms. We created iEEG-recon, a scalable electrode reconstruction pipeline for semiautomatic iEEG annotation, rapid image registration, and electrode assignment on brain magnetic resonance imaging (MRI). Its modular architecture includes a clinical module for electrode labeling and localization, and a research module for automated data processing and electrode contact assignment. To ensure accessibility for users with limited programming and imaging expertise, we packaged iEEG-recon in a containerized format that allows integration into clinical workflows. We propose a cloud-based implementation of iEEG-recon and test our pipeline on data from 132 patients at two epilepsy centers using retrospective and prospective cohorts. We used iEEG-recon to accurately reconstruct electrodes in both electrocorticography and stereoelectroencephalography cases with a 30-min running time per case (including semiautomatic electrode labeling and reconstruction). iEEG-recon generates quality assurance reports and visualizations to support epilepsy surgery discussions. Reconstruction outputs from the clinical module were radiologically validated through pre- and postimplant T1-MRI visual inspections. We also found that our use of ANTsPyNet deep learning-based brain segmentation for electrode classification was consistent with the widely used FreeSurfer segmentations. iEEG-recon is a robust pipeline for automating reconstruction of iEEG electrodes and implantable devices on brain MRI, promoting fast data analysis and integration into clinical workflows. iEEG-recon's accuracy, speed, and compatibility with cloud platforms make it a useful resource for epilepsy centers worldwide.

PyF2F: a robust and simplified fluorophore-to-fluorophore distance measurement tool for Protein interactions from Imaging Complexes after Translocation experiments.

Structural knowledge of protein assemblies in their physiological environment is paramount to understand cellular functions at the molecular level. Protein interactions from Imaging Complexes after Translocation (PICT) is a live-cell imaging technique for the structural characterization of macromolecular assemblies in living cells. PICT relies on the measurement of the separation between labelled molecules using fluorescence microscopy and cell engineering. Unfortunately, the required computational tools to extract molecular distances involve a variety of sophisticated software programs that challenge reproducibility and limit their implementation to highly specialized researchers. Here we introduce PyF2F, a Python-based software that provides a workflow for measuring molecular distances from PICT data, with minimal user programming expertise. We used a published dataset to validate PyF2F's performance.

ExpoSeq: simplified analysis of high-throughput sequencing data from antibody discovery campaigns.

High-throughput sequencing (HTS) offers a modern, fast, and explorative solution to unveil the full potential of display techniques, like antibody phage display, in molecular biology. However, a significant challenge lies in the processing and analysis of such data. Furthermore, there is a notable absence of open-access user-friendly software tools that can be utilized by scientists lacking programming expertise. Here, we present ExpoSeq as an easy-to-use tool to explore, process, and visualize HTS data from antibody discovery campaigns like an expert while only requiring a beginner's knowledge. The pipeline is distributed via GitHub and PyPI, and it can either be installed as a package with pip or the user can choose to clone the repository.

Deciphering cancer genomes with GenomeSpy: a grammar-based visualization toolkit.

Visualization is an indispensable facet of genomic data analysis. Despite the abundance of specialized visualization tools, there remains a distinct need for tailored solutions. However, their implementation typically requires extensive programming expertise from bioinformaticians and software developers, especially when building interactive applications. Toolkits based on visualization grammars offer a more accessible, declarative way to author new visualizations. Yet, current grammar-based solutions fall short in adequately supporting the interactive analysis of large datasets with extensive sample collections, a pivotal task often encountered in cancer research. We present GenomeSpy, a grammar-based toolkit for authoring tailored, interactive visualizations for genomic data analysis. By using combinatorial building blocks and a declarative language, users can implement new visualization designs easily and embed them in web pages or end-user-oriented applications. A distinctive element of GenomeSpy's architecture is its effective use of the graphics processing unit in all rendering, enabling a high frame rate and smoothly animated interactions, such as navigation within a genome. We demonstrate the utility of GenomeSpy by characterizing the genomic landscape of 753 ovarian cancer samples from patients in the DECIDER clinical trial. Our results expand the understanding of the genomic architecture in ovarian cancer, particularly the diversity of chromosomal instability. GenomeSpy is a visualization toolkit applicable to a wide range of tasks pertinent to genome analysis. It offers high flexibility and exceptional performance in interactive analysis. The toolkit is open source with an MIT license, implemented in JavaScript, and available at https://genomespy.app/.

Prompt Literacy

Prompt literacy enables anyone to communicate with and direct generative AI systems without needing expertise in computer programming. Prompts are commands formulated in natural human language that unlock the capabilities of AI and guide its outputs. With prompt literacy, people can successfully interact with generative AI to achieve defined objectives, while exercising judgment and responsibility. Prompts serve as an accessible interface between users and automated systems, translating human intents into AI-compatible directives. Effectively crafted prompts are key to enabling generative AI to produce meaningful, targeted results. Just as traditional literacy involves mastering the written word, developing prompt literacy requires learning how to clearly formulate instructions for AI in its processing language. Command of this skill allows humans to reap benefits from AI, directing its open-ended potential to useful and ethical ends through targeted prompts.

Measuring End-user Developers’ Episodic Experience of a Low-code Development Platform. A Preliminary Study

Background: As low-code development platforms (LCDPs) are becoming a trend, understanding how end-user developers think and feel as they work with such platforms is important. Particularly, assessing experiences during episodes of use can contribute to overall experience throughout long-term use. Aim: This paper aims to understand end-user developers’ episodic experience when they are building an application on a low-code platform and to provide guidance on how such experiences can be measured. Method: We designed the Episodic Developer Experience Questionnaire for LCDPs based on prior literature and refined it through expert Delphi sessions. The instrument contains 10 individual experience items, capturing various aspects of episodic experience. We further validated it through remote online tests on an LCDP. Results: The results showed significant differences in the relationships between items describing aspects of overall experience and items describing perceptions of tool quality and task difficulty. Programming expertise also affected end-user developers’ episodic experience. Conclusion: The study illustrates the design of questionnaire-based experience assessment in the context of development and identifies the importance of separating personal experience from assessment of tasks and tools since tool quality and task difficulty do not necessarily influence experience straightforwardly.

Design and two step process optimization of a reactive distillation column for improving production amount of ethyl acetate and water

In this study, two step optimization was performed for operating conditions of a reactive distillation (RD) column using simulation outputs. The effects of the operating parameters of the RD column, on the ethyl acetate (EtAc) amount as a result of the reaction between ethanol (EtOH) and acetic acid (HAc) were assessed. The response surface methodology (RSM) was applied to determine the optimum operating conditions for the RD column. The two step experimental design used in RSM was created with the Design Expert (DE) program. The Plackett-Burman (PB) design was used to determine the most important parameters affecting on the designed RD column for production of EtAc amount. The most important parameters were determined as HAc feed rate (kmol/h), EtOH feed rate (kmol/h), reflux ratio and temperature (°C). After PB design Central Composite Design (CCD) was applied to determine the optimum operating conditions of these most important parameters for the RD column. ANOVA was used to investigate the interaction between the response and independent variables with the obtained data and 3 dimensional (3D) plots created by the program were interpreted. A second order regression model according to the independent variables for the EtAc amount (response) was developed with DE program. The optimum operating conditions for the designed RD column were obtained as HAc feed rate 149.86 kmol/h, EtOH feed rate 99.99 kmol/h, feed temperature 70 °C and reflux ratio 2.50. The production of EtAc amount which determined with model coefficients and recommended by the program were compared and relative errors between the model results and the predicted values were less than 1%. The obtained results were showed that RSM may be a suitable method for optimization of operating parameters in RD columns.

Metabolic Syndrome and Positive Frailty Screening: A Cross-Sectional Study with Community-Dwelling Older Adults.

Metabolic Syndrome is a set of disorders that characterized by the association of three or more risk factors, like the obesity central, dyslipidemia, borderline blood pressure, hyperglycemia, and the increase of triglycerides. However, these factors also can be associated with pathophysiology of frailty. verifying whether the metabolic syndrome is associated to the positive frailty screening in the older people. Cross-sectional study. Participants: 443 older people living in Rio Branco, Brazil. Data collection was carried out in two stages: a personal interview and blood collection. The diagnosis of metabolic syndrome was based on the criteria of the Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults. The frailty screening was performed using subjective questions validated in a previous study. Descriptive statistics and multinomial logistic regression were used for data analyses. There was a predominance of female older people (69.07%), aged between 60 and 79 years (87.13%), with an income greater than or equal to one minimum wage (72.09%), no cognitive decline (75.94%) and depressive symptoms (63.31%), independent for BADL (86.46%) and dependent for IADL (51.69%). From the total sample, 56.88% of the older people were identified as frail, 34.09% pre-frail and 9.03% non frail. The prevalence of metabolic syndrome was 51.69%. After adjusting by the independent variables, an association between metabolic syndrome and pre-frailty was observed, and older people with metabolic syndrome were more likely to be prefrail (RRR=2.36; 95%CI=1.08-5.18). The metabolic syndrome was associated to the increase chance of screening for prefrailty in the older people evaluated, which reinforces the needy to establish preventive measures in relation to the metabolic syndrome to avoid frailty in the older people.

Ambient PM2.5 and cardiopulmonary mortality in the oldest-old people in China: A national time-stratified case-crossover study

Evidence on the associations of fine particulate matter (PM2.5) with cardiopulmonary mortality in the oldest-old (aged 80+ years) people remains limited. We conducted a time-stratified case-crossover study of 1,475,459 deaths from cardiopulmonary diseases in China to estimate the associations between short-term exposure to ambient PM2.5 and cardiopulmonary mortality among the oldest-old people. Each 10μg/m3 increase in PM2.5 concentration (6-day moving average [lag05]) was associated with higher mortality from cardiopulmonary diseases (excess risks [ERs]= 1.69%, 95% confidence interval [CI]: 1.54%, 1.84%), cardiovascular diseases (ER= 1.72%, 95% CI: 1.54%, 1.90%), and respiratory diseases (ER= 1.62%, 95% CI: 1.33%, 1.91%). Compared to the other groups, females (ER= 1.94%, 95% CI: 1.73%, 2.15%) (p for difference test= 0.043) and those aged 95-99 years (ER= 2.31%, 95% CI: 1.61%, 3.02%) (aged 80-85 years old was the reference, p for difference test= 0.770) presented greater mortality risks. We found 14 specific cardiopulmonary causes associated with PM2.5, out of which emphysema (ER= 3.20%, 95% CI: 1.57%, 4.86%) had the largest association. Out of the total deaths, 6.27% (attributable fraction [AF], 95% CI: 5.72%, 6.82%) were ascribed to short-term PM2.5 exposure. This study provides evidence of PM2.5-induced cardiopulmonary mortality and calls for targeted prevention actions for the oldest-old people. This work was supported by the National Key Research and Development Program of China, the National Natural Science Foundation of China, the Foreign Expert Program of the Ministry of Science and Technology, the Natural Science Foundation of Guangdong, China, and the Science and Technology Program of Guangzhou.

Analysis of the Effect of Entrepreneurship Education and Entrepreneurial Mindset on Entrepreneurial Skills using use of Social Media as a Mediator Variable at SMKN & SMKS with Marketing Expertise Programs in Mojokerto Regency

Business is often discussed in all forums and media, as evidenced by many teaching methods, and business is now a required course in many higher and basic universities (Lockma & Schirm, 2020). In this research, we use several methods using partial least squares equation modeling (PLS-SEM) to estimate and confirm the given hypotheses. This study uses Google Forms to collect information on employment and secondary school students in Mojokerto Regency. The respondents to this study are 346 respondents from three schools targeted for this study. Entrepreneurship education has therefore been shown to be incapable of explaining social media use or entrepreneurial skills. However, theories of entrepreneurship can explain social media use and entrepreneurial skills. Additionally, market perception will have a greater impact on the market if it is improved using social media as an indicator. At the same time, although business education is strong using social media as an intermediary, it does not appear to have a greater impact on the ability to do business.

DOES INDUSTRIAL WORK PRACTICE EXPERIENCE AND VOCATIONAL COMPETENCE STRENGTHEN WORK READINESS THROUGH EMPLOYABILITY SKILLS?

This study was conducted to determine the effect of industrial work practice experience and vocational competence on job readiness through employability skills at State Vocational High School 3 Depok. The research method used is quantitative research method with a descriptive approach. The population used in this study were students of State Vocational High School 3 Depok in all expertise programs, namely Construction and Property Business, Computer and Network Engineering, Online Business and Marketing, Accounting and Institutional Finance, Islamic Banking and Office Management Automation consisting of 450 students with a sample of 212 students. This research model uses a path analysis model and the data analysis technique used is SEM (Structural Equation Modeling) using the SmartPLS version 3 application. This shows that industrial work practice experience and vocational competence have a positive and significant direct effect on work readiness, and also have indirect effect through employability skills.