Validation Of Results Research Articles

Cultural adaptation and validation of the Sinhala version of the spiritual needs assessment for patients (S-SNAP) questionnaire

BackgroundSpiritual support for patients and caregivers of critically ill patients is associated with improved quality of life. This aspect, however, is not incorporated into the current care pathways in Sri Lanka. The Spiritual Needs Assessment for Patients (SNAP) questionnaire, comprised of 3 domains: psychosocial, spiritual and religious, gives a platform for clinicians to assess the spiritual needs of those patients. This study presents the results of validation of the Sinhala version of the SNAP (S-SNAP) questionnaire.MethodsThe SNAP was translated from English to Sinhala using the standard forward and backward translation process. After verifying the content validity, unambiguity and clarity of items in a focused group discussion, and a pilot study, the pre-final version was tested among 267 volunteers with cancer selected from three state-run cancer care institutions. Data were analysed for internal consistency and item-total correlations. Factor analysis was done using Varimax rotation with Kaiser normalization. A Scree plot was also made to determine the number of factors.ResultsThe mean (SD) age of subjects was 63.2 (11.4) years. The total S-SNAP score ranged from 22 to 88 (maximum 88). The overall Cronbach’s alpha was 0.94 while item-total correlations varied from 0.26 to 0.87. Total SNAP score showed inverse correlations with age, Charleson Comorbidity index and Barthel index while a positive correlation was seen with the Karnofsky performance status scale (p < 0.05). Kaiser-Meyer-Olkein value of 0.92 (P = < 0.001) for Bartlett’s test indicated adequate sampling and non-linearity of factors. The scree plot showed a four-factor structure explaining 76% variation. Meaning of life and relationship with a supernatural being and religious rituals are loaded as 2 different factors. Worries, fears and forgiveness are grouped as the third factor while relaxation, coping and sharing feelings are loaded separately.ConclusionsThe S-SNAP is a reliable and valid tool to assess spiritual suffering among patients with cancers conversant in the Sinhala language.

An Adaptive Combined Method for Lithium‐Ion Battery State of Charge Estimation Using Long Short‐Term Memory Network and Unscented Kalman Filter Considering Battery Aging

AbstractThe accurate estimation of battery state of charge (SOC) enables the reliable and safe operation of lithium‐ion batteries. Data‐driven SOC estimation is considered an emerging and effective solution. However, existing data‐driven SOC estimation methods typically involve direct estimation and lack effective feedback correction. Moreover, battery degradation poses additional challenges to accurate SOC estimation. Therefore, this study proposes an adaptive combined method for battery SOC estimation based on a long short‐term memory (LSTM) network and unscented Kalman filter (UKF) algorithm considering battery aging status. First, an LSTM model is constructed to characterize the battery's dynamic performance instead of traditional battery models. Then, the UKF algorithm is employed to perform SOC estimation through the feedback of terminal voltage prediction. To enhance estimation accuracy under different aging statuses, a proportional‐integral‐derivative controller is employed to correct the capacity fading during the SOC estimation process. Validation results indicate that the terminal voltage prediction model demonstrates exceptional robustness against interference from current and voltage noise. Compared to the traditional estimation method combining the deep learning model and Kalman filter algorithm, the proposed method demonstrates superior estimation accuracy under various complex operating conditions. Furthermore, the proposed method outperforms the traditional method in estimation performance during battery aging.

Development of electronic students’ worksheets based on problem-based learning on air pollution material

This research is development research with the aim to produce teaching material products in the form of PBL-based electronic student worksheets on air pollution sub-materials that will be used during the learning process, so that students can be more active and independent. This type of research is development research using the ADDIE model (analysis, design, development, implementation, evaluation), but this research is limited to the development stage. This research was conducted at State Senior High Schools in Palembang in the 2023/2024 school year. The sample in this study was class X students totaling 12 people. Sampling in this study using purposive sampling technique. electronic student worksheets are designed using the Canva and liveworksheets applications; after completing the design of electronic student worksheets, they are assessed by material and media validators using an instrument in the form of a validation questionnaire. After the electronic student worksheet is declared valid, the electronic student worksheet is applied to students in a small group trial. Based on the validation results with the Kappa calculation, the electronic student worksheets were declared valid with a Kappa value of 1. Electronic student worksheets also fall into the very practical category based on the teacher's practicality questionnaire which obtained a percentage of 100%, while the students' practicality questionnaire obtained an average percentage of 90.68%. Based on the results of the validation and practicality questionnaires of teachers and students, it can be concluded that PBL-based electronic student worksheets are valid and feasible to use during the learning process on air pollution sub-materials.

Development of Canva-Based Science Infographic Learning Media to Improve Students’ Learning Outcomes

The aim of this research is to develop, test the feasibility, and effectiveness of Canva-based infographic learning media. This type of research and development (R&amp;D) development research with the ADDIE development model, namely analysis, design, development, implementation, and evaluation). The research subjects were fourth grade students totaling 25 students, data collection techniques with observation, interviews, questionnaires, and documentation data. The results of media expert validation show a percentage value of 88.3% very feasible category, material experts with a percentage value of 86.66% very feasible category. Based on the pretest-posttest results, it is known that Canva-based infographic media is effective in improving student learning outcomes, which is indicated by an increase in the average pretest score from 52 to 80 on the posttest, with an N-Gain test result of 0.58 in the moderate category. Based on the response questionnaire distributed, a very positive response was obtained from teachers and students. From these results, it can be concluded that Canva-based infographic learning media is effective in improving student learning outcomes and is feasible and practical to use in IPAS learning on respiratory system material in grade V SD Negeri Tambakaji 05.

Framework for Microdosing Odors in Virtual Reality for Psychophysiological Stress Training.

To better cope with stress in emergencies, emergency personnel undergo virtual reality (VR) stress training. Such training typically includes visual, auditory and sometimes tactile impressions, whereas olfactory stimuli are mostly neglected. This concept paper therefore examines whether odors might be beneficial for further enhancing the experience of presence and immersion into a simulated environment. The aim is to demonstrate the benefits of VR civilian stress training for emergency personnel and to investigate the role of odors as stressors by manipulating the degree of perceived psychophysiological stress via olfactory impressions. Moreover, the current paper presents the development and validation of a convenient and portable fragrance dosing system that allows personalized odor presentation in VR. The presented system can transport reproducible small quantities of an air-fragrance mixture close to the human nose using piezoelectric stainless steel micropumps. The results of the fluidic system validation indicate that the micropump is suitable for releasing odors close to the nose with constant amounts of odor presentation. Furthermore, the theoretical background and the planned experimental design of VR stress training, including odor presentation via olfactory VR technology, are elucidated.

The development of elema 2.0 for the invertebrate zoology course on the phylum arthropoda topic

Currently, technology has become an inseparable part of education and learning. Various digital learning tools have been developed and widely used in the classroom. eLEMA (electronic learning materials) was developed as a mobile application that supports learning in the Invertebrate Zoology courses at the Biology Education Program, University of Palangka Raya. At that time, eLEMA was developed to meet the need for electronic learning materials for online learning during the COVID-19 pandemic. Along with the rapid development of technology in recent years, eLEMA needs to be developed further for updates. This research aims to develop eLEMA 2.0 for the Invertebrate Zoology course. This study is a research and development (R &amp; D) using Hannafin &amp; Peck development model to develop eLEMA 2.0 for the Invertebrate Zoology course on the Phylum Arthropoda topic. The development product is the eLEMA 2.0 application for lectures on the Phylum Arthropoda topic in the Invertebrate Zoology course with improvements to the user interface and additional features that support participatory learning and student-centered learning. The results of trials and validation show that all pages and content in this application were successfully opened without any disturbing errors. These results indicate that the development product is feasible to be implemented in the classroom.

A rapid and accurate transfer alignment method using inertial instrument measurement information

The rapidity and precision of transfer alignment impacts the response speed and working precision of inertial navigation system (INS) directly, and flexural deformation is a critical constraint on transfer alignment performance. However, transfer alignment performance of the traditional modeling estimation method is easily degraded by the effect of model mismatch. Therefore, a rapid and accurate transfer alignment method using inertial instrument measurements is proposed in this paper. The relative attitude of main/sub INSs is roughly estimated by angular velocity measurements. Then, a novel transfer alignment filter model is established by relative attitude error model, and measurements of inertial instrument are used to construct angular increment matching and specific force matching quantities. This approach improves both the rapidity and precision of sub INS’s alignment. The performance validation results indicate that compared with traditional methods, the proposed method can improve alignment accuracy by more than 70% and significantly shorten alignment time, thus realizing rapid and accurate alignment.

Development of Augmented Reality-Based Learning Media

One of the essential aspects of the learning process is instructional media. An instructional media that can be utilized is Augmented Reality (AR)-based instructional media. This research aims to assess the feasibility of AR-based instructional media on the digestive system. The stages involved in this research include gathering information through literature review, designing AR-based instructional media, validating AR-based instructional media, and revising AR-based instructional media based on validator feedback. The validation results of AR-based instructional media, with four assessment aspects including linguistic, illustration, attractiveness, and quality, obtained a score of 1.00, indicating a very high rating. AR-based instructional media can visualize digestive system material that cannot be directly observed through the presentation of illustrations such as images and videos that resemble real conditions, thereby reducing misconceptions about the digestive system material. It is concluded that AR-based instructional media is suitable for instructional media on the digestive system topic.

Validitas Modul Sistematika Invertebrata sebagai Media Pembelajaran bagi Mahasiswa

The aim of this research is to determine the validity of the invertebrate systematics module. This type of research is development research. The research and development model used is a 4D model modified to 3D, namely Define, Design and Develop. The research instrument used was a validation sheet. The data collection technique uses validation by validators consisting of content/material experts, display experts and language experts. The data analysis technique used is the percentage technique. Based on the results of module validation by validators, it was found that 87.5% of language experts, 87.5% of material experts, and 90% of display experts, with an average of 88.3%. Thus, the module is declared very valid and suitable to be used as a reference source for teaching materials for Invertebrate Systematics.

Meningkatkan Potensi Kampung Wisata Pengolahan Susu Samar sebagai Destinasi Wisata Digital melalui Pemanfaatan Aset MOOC

The aim of this community service is to develop the Samar Milk Processing Tourism Village as a digital tourism destination through the use of Massive Open Online Courses (MOOC) assets. This implementation focuses on efforts to utilize MOOCs as an important tool to improve education, development and marketing of dairy farming-based tourist destinations in Samar Village through the Asset Based Community Development (ABCD) method. Media expert validation results show an approval level of 89.5% for the concept of using MOOCs in marketing tourist destinations. Meanwhile, the material expert validation results reached an agreement level of 92.5%, indicating that this approach was received positively by experts in the field of milk processing. Furthermore, the implementation of this activity also recorded a significant increase in the learning outcomes of participants who took part in the MOOC related to the dairy industry. This confirms that the use of MOOCs in digital tourism destination-based education and training can provide real benefits. Keywords: MOOC; Asset; Tourism; Digital; Samar’s Milk

Parameter-coupled state space models based on quasi-Gaussian fuzzy approximation

The accuracy of a fuzzy system’s approximation is closely tied to the performance of fuzzy control systems design, while this system’s interpretability depends on the description of a mechanical model using human language. This research introduces a quasi-Gaussian membership function characterized by a pair of parameters to achieve the sensitivity of a triangular membership function along with the interpretability of Gaussian membership functions. Consequently, a two-dimensional (2-D) quasi-Gaussian membership function is derived, and a method for establishing quasi-Gaussian fuzzy systems (QGFS) using a rectangular grid is proposed. After validating the approximation properties using the sine function for the one-dimensional (1-D) and 2-D QGFS, the systems are applied to approximate the depyrogenation tunnel, a significant piece of equipment in the pharmaceutical industry with various mechanical designs. Validation results indicate that the 1-D and 2-D QGFS can achieve an approximation error varying within a ± 5% range. Meanwhile, the 1-D and 2-D QGFSs are applied to mechanical models of the depyrogenation tunnel with satisfactory final approximation results. Lastly, the 2-D QGFS is capable of demonstrating an excellent description of models with coupled parameters.

Development of a Connecting Web as an Information Media for Parents of VIP Pesawat Wates Junior High School Kulon Progo

This study aims to assess the feasibility and practicality of a connecting website as an information medium for parents of VIP Pesawat Junior High School students. The Research and Development (R&amp;D) process followed the ADDIE model (Analysis, Design, Development, Implementation, and Evaluation). A total of 92 parents of VIP Pesawat Wates Junior High School class VII students were selected through Simple Random Sampling. Data collection involved validation questionnaires for media and material experts, and practicality surveys for parents. The data was analyzed using quantitative descriptive methods.The results show that: (1) The media validation scored 79% on two aspects—design usage and visual communication—indicating the website is feasible as an information medium. (2) The material experts' validation results were 75% for the content/material aspect, 85% for language, 75% for implementation, and 80% for usability, affirming its suitability for use. (3) In terms of practicality, user tests showed a 90% score for usefulness, 77% for ease of use, 86% for ease of learning, and 86% for satisfaction. These scores demonstrate that the connecting website is practical and effective as an information source for parents of students at VIP Pesawat Wates Junior High School

Bringing interactive elements into classes: Augmented reality-based learning media development for electrical measurement subjects in vocational education

This study aims to develop and evaluate Augmented Reality (AR)-based learning media to improve student interest at SMKN 1 Kuantan Mudik. AR, which integrates virtual objects into the real world, is expected to enrich the learning experience through innovative visual and interactive elements. This research employs a Research and Development (R&amp;D) which includes preliminary research, prototype creation, student response assessment, and systematic reflection. The AR-based learning media prototype was developed using Assemblr Edu software and evaluated by media experts, content specialists, and students. The validation results indicate that the media is highly viable, receiving a score of 92.7% from content experts and media specialists. Student trials produced ratings of 88.9% for effectiveness and 90.3% for engagement. The findings demonstrate that AR-based learning media significantly enhance student interest and involvement in the learning process. This study concludes that augmented reality learning media substantially improve educational experiences in vocational settings, showing potential for broader implementation across various subjects. However, this research is limited to expert validation processes and primarily focuses on student responses rather than measuring learning outcomes. This study is anticipated to provide a foundation for developing more comprehensive and effective learning media.

Predicting the Duration of Forest Fires Using Machine Learning Methods

For thousands of years forest fires played the role of a regulator in the ecosystem. Forest fires contributed to the ecological balance by destroying old and diseased plant material; but in the modern era fires are a major problem that tests the endurance not only of government agencies around the world, but also have an effect on climate change. Forest fires have become more intense, more destructive, and more deadly; these are known as megafires. They can cause major economic and ecological problems, especially in the summer months (dry season). However, humanity has developed a tool that can predict fire events, to detect them in time, but also to predict their duration. This tool is artificial intelligence, specifically, machine learning, which is one part of AI. Consequently, this paper briefly mentions several methods of machine learning as used in predicting forest fires and in early detection, submitting an overall review of current models. Our main overall objective is to venture into a new field: predicting the duration of ongoing forest fires. Our contribution offers a new way to manage forest fires, using accessible open data, available from the Hellenic Fire Service. In particular, we imported over 72,000 data from a 10-year period (2014–2023) using machine learning techniques. The experimental and validation results are more than encouraging, with Random Forest achieving the lowest value for the error range (8–13%), meaning it was 87–92% accurate on the prediction of forest fire duration. Finally, some future directions in which to extend this research are presented.

Identification of Key Genes Related to Immune-Lipid Metabolism in Skin Barrier Damage and Analysis of Immune Infiltration.

Several physical and chemical factors regulate skin barrier function. Skin barrier dysfunction causes many inflammatory skin diseases, such as atopic dermatitis and psoriasis. Activation of the immune response may lead to damage to the epidermal barrier. Abnormal lipid metabolism is defined as abnormally high or low values of plasma lipid components such as plasma cholesterol and triglycerides. The mouse skin barrier damage model was used for RNA sequencing. Bioinformatics analysis and validation were performed. Differently expressed genes (DEGs) related to immune and lipid metabolism were screened by differentially expressed gene analysis, and the enriched biological processes and pathways of these genes were identified by GO-KEGG. The interactions between DEGs were confirmed by constructing a PPI network. GSEA, transcription factor regulatory network, and immune infiltration analyses were performed for the 10 genes. Expression validation was performed by public datasets. The expression of key genes in mouse skin tissue was detected by qPCR. The expression of differentially expressed immune cell markers in the skin was detected by immunofluorescence. Based on the trans epidermal water loss (TEWL) score, the expression of key genes was detected by qPCR before skin barrier injury, at 4h and 7d, and at recovery from injury. Il17a, Il6, Tnf, Itgam, and Cxcl1 were immune-related key genes. Pla2g2f, Ptgs2, Plb1, Pla2g3, and Pla2g2d were key genes for lipid metabolism. Database validation and experimental results revealed that the expression trends of these genes were consistent with our analyses. The research value of these genes has been demonstrated through mouse datasets and experimental validation, and future therapeutic approaches may be able to mitigate the disease by targeting these genes to modulate the function of the skin barrier.

Systematic evaluation of Rutongshu oral liquid based on chromatographic fingerprinting and nontargeted metabolomic analysis

AbstractBased on chromatographic fingerprinting combined with quantitative analysis on characteristic chemical constituents as well as hierarchical cluster analysis, an easy and sensitive approach utilizing high performance liquid chromatography (HPLC) was developed for the identification and quality evaluation of Rutongshu oral liquid (ROL). What is more, nontargeted metabolomic analysis was conducted to gain a global view in terms of its chemical profile. In this study, 16 peaks from different batches (S1–S10) of ROL samples produced by Taihe Hospital of Chinese Medicine were selected as common peaks for the evaluation of their similarity whose values of all tested 10 batches exceeded 0.90 when compared with the control fingerprints. Meanwhile, simultaneous quantification of five markers in the oral solution, including albiflorin, paeoniflorin, chlorogenic acid, quercetin and ferulic acid was performed, and standard curves established for respective reference substances showed good regression in the linear range (r2 &gt; 0.999) with recoveries in the range of 98.96–102.35%. The ultra-high performance liquid chromatography (UHPLC) combined with Orbitrap Exploris 120 mass spectrometer resulted in 88 identified compounds. The results of validation showed that the established method was reproducible, precise and stable. This study offers an effective, dependable and useful approach for the systematic evaluation of the hospital formulation ROL.

Predictive Models for Sustained, Uncontrolled Hypertension and Hypertensive Crisis Based on Electronic Health Record Data: Algorithm Development and Validation.

Assessing disease progression among patients with uncontrolled hypertension is important for identifying opportunities for intervention. We aim to develop and validate 2 models, one to predict sustained, uncontrolled hypertension (≥2 blood pressure [BP] readings ≥140/90 mm Hg or ≥1 BP reading ≥180/120 mm Hg) and one to predict hypertensive crisis (≥1 BP reading ≥180/120 mm Hg) within 1 year of an index visit (outpatient or ambulatory encounter in which an uncontrolled BP reading was recorded). Data from 142,897 patients with uncontrolled hypertension within Atrium Health Greater Charlotte in 2018 were used. Electronic health record-based predictors were based on the 1-year period before a patient's index visit. The dataset was randomly split (80:20) into a training set and a validation set. In total, 4 machine learning frameworks were considered: L2-regularized logistic regression, multilayer perceptron, gradient boosting machines, and random forest. Model selection was performed with 10-fold cross-validation. The final models were assessed on discrimination (C-statistic), calibration (eg, integrated calibration index), and net benefit (with decision curve analysis). Additionally, internal-external cross-validation was performed at the county level to assess performance with new populations and summarized using random-effect meta-analyses. In internal validation, the C-statistic and integrated calibration index were 0.72 (95% CI 0.71-0.72) and 0.015 (95% CI 0.012-0.020) for the sustained, uncontrolled hypertension model, and 0.81 (95% CI 0.79-0.82) and 0.009 (95% CI 0.007-0.011) for the hypertensive crisis model. The models had higher net benefit than the default policies (ie, treat-all and treat-none) across different decision thresholds. In internal-external cross-validation, the pooled performance was consistent with internal validation results; in particular, the pooled C-statistics were 0.70 (95% CI 0.69-0.71) and 0.79 (95% CI 0.78-0.81) for the sustained, uncontrolled hypertension model and hypertensive crisis model, respectively. An electronic health record-based model predicted hypertensive crisis reasonably well in internal and internal-external validations. The model can potentially be used to support population health surveillance and hypertension management. Further studies are needed to improve the ability to predict sustained, uncontrolled hypertension.

Hydrological streamflow modeling at the inlet of Gilgel Gibe III dam of Ethiopia using soil and water assessment tool

AbstractComprehensive approach is a pre‐requisite to improve the estimation of variability in streamflow data for designing water supply systems, generating hydropower, determining environmental flows, allocating water, and conducting pollution studies that need a comprehensive approach. There is a need to model streamflow data to develop effective water policy plans when sufficient data are unavailable. This study aims at assessing the accuracy and applicability of the Soil and Water Assessment Tool (SWAT) model in predicting streamflow at the inlet of the Gilgel Gibe III dam watershed in Ethiopia. Historical meteorological data from nine available stations between 1987 and 2017 were used to predict the streamflow. The SWAT model was calibrated and validated for two different time periods (1997–1999 and 2003–2004) using SWATCUP program and SUFI‐2 technique. Calibration and validation were based on monthly observed discharges at the Abelti and Gojeb stations. The results showed acceptable values of R2, Nash–Sutcliffe modeling efficiency (NSE), and percent bias (PBIAS). At the Abelti station and Gojeb station, the calibration and validation results were 0.82, 0.79, and −10.1%; 0.88, 0.84, and −14.4%; and 0.86, 0.79, and 14.1% for calibration and 0.88, 0.8, and 11.1% for validation, respectively. The prediction uncertainty of 95% was consistent with the observed discharge. The mean annual runoff was 440.08 m3/s, demonstrating the model's effectiveness in simulating streamflow at the dam's inlet. The calibrated and validated model can be used to study the effects of climate and land use changes; analyze water quality and sediment yield; and inform future water policy plans, dam construction planning, and flood disaster risk management.

Development augmented reality assisted teaching modules human sensory system to improve student learning outcomes

In the era of digital transformation, the use of technology to improve the quality of learning is very important. This research aimed to develop a teaching module for human sensory system material assisted by augmented reality media to improve students' biology learning outcomes. This research uses research and development methods. The subjects of this research were 22 Biology Education students at the University of Papua. Data collection instruments include validation sheets and questionnaires to determine the validity and responses of students to teaching modules as well as providing multiple choice questions to measure learning outcomes. The data analysis technique is descriptive by calculating validation results, analyzing student response questionnaires and student learning outcomes. The research results show that media and material expert validation test results obtained a percentage of 93.33% with a very valid category. The results of assessing student responses in the trial obtained an average percentage of 85.13% in the very good category. Student biology learning results show an average of 61.36 in the sufficient category. The conclusion of the research on Augmented Reality-assisted teaching modules meets the criteria of being valid, practical and effective and improving students' biology learning outcomes.

Improving Critical Thinking Skills of Elementary Students Through Science Learning with Interactive Teaching Materials and Problem Based Learning

This study aims to evaluate the effectiveness of interactive multimedia-based learning with Problem Based Learning (PBL) model in improving critical thinking skills of elementary school students in Natural and Social Sciences subjects. This research uses a development method with quantitative and qualitative approaches. The results of validation from the aspects of material, media, and language showed high ratings, and the product was declared practical by teachers and students. Students were actively involved in learning, and the results of statistical analysis showed significant differences between the control group and the experimental group in learning activities. This shows that this method is effective in improving students' critical thinking skills. Nonetheless, this study has limitations in terms of generalization of the results. Future research is expected to expand the scope of the study and consider additional factors for the development of more effective learning methods.