Tool For Evaluation Research Articles

Cognitive phenomena measurement with time window-based multispectral brain mapping.

Cognitive neuroscience experiments require accurate and traceable methods of measuring cognitive phenomena, analyzing and processing data, and validating results, including measurement of impact of such phenomena on brain activity and consciousness. EEG measurement is the most widely used tool for evaluation of the experiment's progress. To extract more information from the EEG signal, continuous innovation is necessary to provide a broader range of information. This paper presents a new tool for measuring and mapping cognitive phenomena using time window-based multispectral brain mapping of electroencephalography (EEG) signals. The tool was developed using Python programming language and enables users to create brain maps images for six spectra (Delta, Theta, Alpha, Beta, Gamma, and Mu) of EEG signal. The system can accept an arbitrary number of EEG channels with standardized labels based on the 10-20 system, and users can select the channels, frequency bandwidth, type of signal processing, and time window length to perform the mapping. The key advantage of this tool is its ability to perform short-time brain mapping, which allows for the exploration and measurement of cognitive phenomena. The tool's performance was evaluated through testing on real EEG signals, and results demonstrated its effectiveness in accurately mapping cognitive phenomena. The developed tool can be used in various applications, including cognitive neuroscience research and clinical studies. Future work involves optimizing the tool's performance and expanding its capabilities.

Aleatoric and epistemic uncertainty extraction of patient-specific deep learning-based dose predictions in LDR prostate brachytherapy.

Objective.In brachytherapy, deep learning (DL) algorithms have shown the capability of predicting 3D dose volumes. The reliability and accuracy of such methodologies remain under scrutiny for prospective clinical applications. This study aims to establish fast DL-based predictive dose algorithms for low-dose rate (LDR) prostate brachytherapy and to evaluate their uncertainty and stability.Approach.Data from 200 prostate patients, treated with125I sources, was collected. The Monte Carlo (MC) ground truth dose volumes were calculated with TOPAS considering the interseed effects and an organ-based material assignment. Two 3D convolutional neural networks, UNet and ResUNet TSE, were trained using the patient geometry and the seed positions as the input data. The dataset was randomly split into training (150), validation (25) and test (25) sets. The aleatoric (associated with the input data) and epistemic (associated with the model) uncertainties of the DL models were assessed.Main results.For the full test set, with respect to the MC reference, the predicted prostateD90metric had mean differences of -0.64% and 0.08% for the UNet and ResUNet TSE models, respectively. In voxel-by-voxel comparisons, the average global dose difference ratio in the [-1%, 1%] range included 91.0% and 93.0% of voxels for the UNet and the ResUNet TSE, respectively. One forward pass or prediction took 4 ms for a 3D dose volume of 2.56 M voxels (128 × 160 × 128). The ResUNet TSE model closely encoded the well-known physics of the problem as seen in a set of uncertainty maps. The ResUNet TSE rectum D2cchad the largest uncertainty metric of 0.0042.Significance.The proposed DL models serve as rapid dose predictors that consider the patient anatomy and interseed attenuation effects. The derived uncertainty is interpretable, highlighting areas where DL models may struggle to provide accurate estimations. The uncertainty analysis offers a comprehensive evaluation tool for dose predictor model assessment.

Quality evaluation of physical education in colleges and universities based on fuzzy logic

This study aims to evaluate the quality of physical education in colleges and universities by using the evaluation method based on fuzzy logic. First, summarize the basic concept of fuzzy logic and its application in the evaluation process. Then, a physical education quality evaluation index system covering teaching quality and students’ physical quality, teachers’ team construction, sports facilities and management is constructed. Then, the evaluation object and evaluation level are determined, and the specific evaluation results and ranking are calculated by fuzzy comprehensive evaluation model. In the empirical analysis, use the simulation data for model application and result analysis, and further find the problems existing in college physical education. Finally, in view of these problems, a series of improvement and optimization suggestions are put forward. This study shows that the evaluation method of physical education quality based on fuzzy logic can effectively reflect the diversity and complexity of education quality, and provide a practical evaluation tool for colleges and universities. At the same time, this study also provides a reference for other universities to help them better understand their own problems, so that they can take effective measures to improve. In addition, this method can be applied to other fields of education quality evaluation in the future, so as to provide more useful information for education reform and development.

Exploring educational simulation platform features for addressing complexity in Industry 4.0: a qualitative analysis of insights from logistics experts

IntroductionThis study explores the transformative impact of Industry 4.0 on industrial operations, emphasizing the integration of advanced technologies like AI, IoT, and Big Data Analytics to enhance process optimization, automation, and connectivity. Despite its potential for efficiency, Industry 4.0 introduces significant complexities, challenging existing operational and decision-making frameworks. Addressing these challenges, the research investigates the role of simulation platforms in logistics, seeking to identify their critical attributes for effective complexity management. It highlights the need for innovative tools in system evaluation, performance measurement, and skill development, aiming to equip the workforce with essential Industry 4.0 competencies. Through qualitative insights from logistics experts, the study aims to offer practical recommendations for educators and industry professionals, contributing to the design and implementation of educational simulations that align with the intricate demands of Industry 4.0 logistics.MethodsThis study employs a qualitative content analysis approach to develop an Industry 4.0-adapted logistics simulator, leveraging the Asteraceae framework for digital game co-design and pedagogical reflection. Data were collected from six industry and academia experts through semi-structured interviews, designed around the framework’s key steps to explore simulator design, decision-making, impact, and skill development. Utilizing convenience sampling, the research engaged participants with experience in educational logistics platforms and simulators. Interviews were conducted online, with ethical considerations including informed consent. Transcription used OpenAI’s API for accuracy, followed by manual review. The analysis combined qualitative content with frequency analysis, employing Atlas.ti software to identify and code key simulation features as informed by expert insights. This methodology underscores a comprehensive approach to understanding and innovating logistics education for Industry 4.0, aiming to equip learners with necessary competencies through targeted simulation tools.ResultsThe study’s findings emphasize the critical role of simulation tools in Industry 4.0 logistics for risk mitigation, operational planning, and decision-making. Experts pointed out the significant benefits of simulations in providing safe spaces for experimentation, especially valuable for SMEs with limited access to advanced technologies. They advocated for simulators to incorporate current technological and e-commerce trends, suggesting a customizable business model based on diverse logistics requirements. Key insights included the necessity for adaptable simulation architectures to handle various operational variables, the importance of integrating multidisciplinary competencies like data analytics and strategic management, and the role of performance metrics in evaluating simulations and logistics operations. The analysis revealed essential features for an educational logistics simulator, highlighting the importance of operational knowledge, predictive analytics, and the need for a comprehensive tool that integrates technology, strategy, operations, and data analysis. This approach aims to equip users with the skills necessary for navigating the complexities of modern logistics, promoting a deep understanding of systems thinking and complex reasoning skills.DiscussionThe discussion centers on the essential requirement for a multidisciplinary approach in creating an educational logistics simulator for Industry 4.0, emphasizing the need for technological adaptability and operational efficiency. It highlights the importance of integrating advanced technologies and collaborative paradigms to enhance logistics operations and improve decision-making processes. The utility of simulation-based learning as a pedagogical tool is acknowledged, with an emphasis on its role in developing complex thinking and practical skills relevant to the digital transformation of the logistics sector. The discussion suggests that educational simulations are poised to play a pivotal role in preparing the workforce for Industry 4.0 challenges by bridging technological advancements and pedagogical strategies. However, it also points to the limitations of the current study, such as its sampling method and regional focus, and calls for future research to explore broader applications and the integration of comprehensive strategies to ensure the educational simulator’s effectiveness and relevance in a global context.

Digitized Printed Strategic Intervention Material in Science in District I of Antipolo City: Basis for Enhancement Model

Digitization, technology, and scientific education are strong educational reform drivers. Modern educational institutions use computers and the Internet for all their activities. It’s everywhere now. Thus, digitally printed science intervention material is crucial in schools and society. Today, digitalized printed materials are the main teaching and learning channel. The Philippine Department of Education (DepEd) uses extracurricular activities to help students who struggle in science, technology, and other subjects. Educators, administrators, and curriculum planners use digitally enhanced printed materials and multimedia instructions to develop every aspect of teaching and learning. This study assessed the validity and acceptability of the Digitized Printed Strategic Intervention Material (DPSIM) in teaching Science as expected against evaluation. The respondents of the study were one (1) Technology Expert, five (5) Science Administrators, and one hundred (100) Science teachers who were described in terms of position, educational attainment, training attended in ICT, teaching experiences, and the ability to handle ICT. The validity is assessed in terms of content, manner of presentation, language and style, and evaluative tools. Acceptability is assessed in terms of clarity, usefulness, suitability, adequacy, and timeliness. Various resources such as books, published studies on the net, and other materials were gathered in the construction of the research questionnaire. Descriptive Statistics such as Mean and Frequency, T-test, and ANOVA were utilized to test the statistical significance of the variables presented. Results revealed that there is no significant difference in the assessment of the two groups (expected and evaluated responses) of respondents on the validity of the Digitized Printed Strategic Intervention Material (DPSIM), but there is a significant difference in the assessment of respondents in terms of acceptability of DPSIM. When respondents were grouped according to their profile in terms of position, educational attainment, training attended in Information Communication Technology (ICT), teaching experience, and the ability to handle ICT in Teaching, it was identified that differences in the responses for validity were brought about by the respondent’s difference in ICT training attended and their ability to handle ICT in teaching. The validity of DPSIM is perceived to be a high extent, with Application, Method of Presentation, Language and Style, and Evaluative Tools as the criteria that need further improvement. For the acceptability of DPSIM, there is a significant difference in the responses when grouped according to profile. However, it is worth noting that overall, no criteria were perceived to be needing improvement. Acceptability has also been categorized to a very high extent. It concluded that the Digitized Printed Strategic Intervention Material (DPSIM) is an effective tool in teaching Science. The study included that school administrators should evaluate the DPSIM whether its contents conform to the curriculum standards. Teachers should first examine the DPSIM use to determine the contents that align with the objective of the lesson. Parents should support children with technology materials that supplement the lesson; pupils can explore the DPSIM, which promotes independent learning; and future researchers can conduct similar studies that assess developed DPSIM if the same education will be conducted in the future. Keyword: Digitized Printed Strategic Intervention Material (DPSIM)

Two-dimensional and Doppler Echocardiographic Findings in Healthy Non-sedated Captive European Pond Turtles (Emys orbicularis)

Abstract Two-dimensional (2D) and Doppler echocardiography is considered the most practical diagnostic tool for antemortem evaluation of reptilian heart disease but has only been described in a limited number of chelonian species. Cardiac morphology and function were evaluated by ultrasonography in 35 clinically healthy, captive non-sedated European pond turtles (Emys orbicularis) using 2D-mode, M-mode, and pulsed wave spectral Doppler. Turtles were placed in a temperature-controlled water tank (24-26°C, 75.2-78.8°F) for cardiac examination through the right cervicobrachial window using water as coupling agent. Each echocardiogram included the evaluation of 19 variables, including 6 in 2D-mode, 7 in M-mode, and 6 in Doppler mode, and was performed in 5.64 minutes on average. Morphological and functional abnormalities were identified in eight turtles, including atrioventricular insufficiencies (n = 5), pericardial effusions (n = 4), increased velocity of the ventricular outflow tract (n = 1) and bradyarrhythmia (n = 2). Reference intervals could be established for the 19 parameters in the remaining individuals after excluding outliers (n = 25). Statistically significant positive correlations between weight and diastolic (0.61, P = 0.001) and systolic (0.46, P = 0.018) ventricular volumes, and diastolic ventricular diameter (0.35, P = 0.03) were identified. This study establishes an initial database for the evaluation of captive European pond turtle cardiovascular system by a simple and clinically applicable echocardiographic technique.

“Reminds Me How Much You Ought to be Thinking About”: Advancing History Teachers’ Vetting and Adaption of Digital Curriculum Materials

The digital revolution has widened the array of curriculum materials available to history teachers. Given the variable quality of these new materials and the deeply contextual nature of teaching, educators need better tools for selecting among the vast options available. This study aimed to validate a device designed for that purpose, called the Curriculum Materials Evaluation Tool (CMET). Using a questionnaire and think-aloud interview, the study examined how four social studies teachers evaluated a novel material set for potential classroom use, and how the CMET mediated their analysis. Findings showed that the teachers preferred when materials are readily accessible and adaptable for their specific teaching context, in contrast to “one-size-fits-all” resources that dominate the Web. The CMET appeared to foster a deeper and broader analysis of the given material set, especially regarding its political and cultural orientation. The study suggests that teachers’ role in vetting and adapting digital materials be recognized and embraced. The CMET can contribute to that end through its use in district adoption committees, teacher professional development, and collaborative curriculum research.

The power of the communicative approach: An investigation of classroom practices of English teachers working in vocational high schools

AbstractThis research examines classroom methodologies aligned with the communicative approach, gauging the perspectives of English teachers working within vocational high schools (VHSs). The study, employing a qualitative case study research design, engaged 10 teachers from diverse backgrounds. The participants volunteered for the study and were selected through a maximum diversity sampling technique, a purposeful sampling method. The research methodology encompassed data collection through interviews, observations, and document analysis. Content analysis was applied to scrutinize interview data, whereas observational and document‐based findings were subjected to descriptive analysis techniques. The study revealed a prevalent utilization of teacher‐controlled activities and a predominant teacher‐centric classroom layout among teachers. Notably, a considerable proportion of in‐class time was allocated to grammar instruction, whereas comparatively lesser emphasis was placed on fostering reading, speaking, writing, and listening skills. Moreover, it was found that multiple‐choice tests and alternative assessment formats such as performance evaluations and projects were exclusively employed; using other alternative assessment approaches like observations, interviews, learning diaries, and portfolios was rare. It is also found that English instruction in VHSs heavily relies on textbooks, supplemented by the occasional integration of audiovisual materials. Overall, teachers expressed a consensus that there exists a need for enhancement in curricular frameworks, teaching aids, as well as assessment and evaluation tools within the English instruction domain.

Energy Sustainability Indicators for the Use of Biomass as Fuel for the Sugar Industry

There are numerous analytical and/or computational tools for evaluating the energetic sustainability of biomass in the sugar industry. However, the simultaneous integration of the energetic–exergetic and emergetic criteria for such evaluation is still insufficient. The objective of the present work is to propose a range of indicators to evaluate the sustainability of the use of biomass as fuel in the sugar industry. For this purpose, energy, exergy, and emergy evaluation tools were theoretically used as sustainability indicators. They were validated in five variants of different biomass and their mixtures in two studies of technologies used in Cuba for the sugar industry. As a result, the energy method showed, for all variants, an increase in efficiency of about 5% in the VU-40 technology compared to the Retal technology. There is an increase in energy efficiency when considering AHRs of 2.8% or Marabu (Dichrostachys cinerea) (5.3%) compared to the V1 variant. Through the study of the exergetic efficiency, an increase of 2% was determined in both technologies for the case of the V1 variant, and an increase in efficiency is observed in the V2 variant of 5% and the V3 variant (5.6%) over the V1 variant. The emergetic method showed superior results for the VU-40 technology over the Retal technology due to higher fuel utilization. In the case of the V1 variant, there was a 7% increase in the renewability ratio and an 11.07% increase in the sustainability index. This is because more energy is produced per unit of environmental load.

Changes in biomarkers levels from gingival crevicular fluid in pre- and postmenopausal women undergoing orthodontic treatment : Asystematic review.

This study aimed to verify whether there is adifference in biomarker levels in the gingival crevicular fluid between premenopausal and postmenopausal women undergoing orthodontic treatment. As eligibility criteria, prospective or retrospective observational studies evaluating women undergoing orthodontic treatment(P), comparing postmenopausal (E)and premenopausal(C) women, and analyzing differences in gingival crevicular fluid biomarkers (O)were included. An electronic search was conducted in seven databases (PubMed, Scopus, Web of Science, LILACS, The Cochrane Library, Embase, and EBSCO: Dentistry & Oral Science) and one grey literature source (Google Scholar). All databases were searched from September 2022 to March 2023. After duplicate exclusion and data extraction, the Newcastle-Ottawa scale was applied to assess the quality and risk of bias, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool was used to verify the certainty of evidence. Three case-control studies that analyzed receptor activator of nuclear factor kappa‑B ligand (RANKL), osteopontin (OPN), and interleukin (IL)-17A levels were included. One study reported asignificant difference for RANKL and another for OPN levels. A third study reported that there was a higher expression of IL17‑A in the postmenopausal group. However, the small number of articles limits our systematic review. The heterogeneity and imprecision in the study results cast doubt on the findings' internal validity. The studies reported alterations in biomarker levels but differed in their conclusions. Therefore, further studies must include other types of bone and inflammatory biomarkers in female patients who are pre- or postmenopausal and undergoing orthodontic treatment. The review was registered at the Open Science Framework ( https://doi.org/10.17605/OSF.IO/Q9YZ8 ).

Group Validation in Recommender Systems: Framework for Multi-layer Performance Evaluation

Evaluation of recommendation systems continues evolving, especially in recent years. There have been several attempts to standardize the assessment processes and propose replacement metrics better oriented toward measuring effective personalization. However, standard evaluation tools merely possess the capacity to provide a general overview of a system’s performance; they lack consistency and effectiveness in their use, as evidenced by most recent studies on the topic. Furthermore, traditional evaluation techniques fail to detect potentially harmful data on small subsets. Moreover, they generally lack explainable features to interpret how such minor variations could affect the system’s performance. This proposal focuses on data clustering for recommender evaluation and applies a cluster assessment technique to locate such performance issues. Our new approach, named group validation , aids in spotting critical performance variability in compact subsets of the system’s data and unravels hidden weaknesses in predictions where such unfavorable variations generally go unnoticed with typical assessment methods. Group validation for recommenders is a modular evaluation layer that complements regular evaluation and includes a new unique perspective to the evaluation process. Additionally, it allows several applications to the recommender ecosystem, such as model evolution tests, fraud/attack detection, and the capacity for hosting a hybrid model setup.

Regioselectively Carboxylated Cellulose Nanofibril Models from Dissolving Pulp: C6 via TEMPO Oxidation and C2,C3 via Periodate-Chlorite Oxidation.

Regioselective C6 and C2,C3 carboxylated cellulose nanofibrils (CNFs) have been robustly generated from dissolving pulp, a readily available source of unmodified cellulose, via stoichiometrically optimized 2,2,6,6-tetramethylpyperidine-1-oxyl (TEMPO)-mediated and sequential sodium periodate-sodium chlorite (PC) oxidation coupled with high-speed blending. Both regioselectively optimized carboxylated CNF series possess the widest ranges of comparable charges (0.72-1.48 mmol/g for T-CNFs vs. 0.72-1.10 mmol/g for PC-CNFs), but similar ranges of thickness (1.3-2.4 nm for T-CNF, 1.8-2.7 nm PC-CNF), widths (4.6-6.6 nm T-CNF, 5.5-5.9 nm PC-CNF), and lengths (254-481 nm T-CNF, 247-442 nm PC-CNF). TEMPO-mediated oxidation is milder and one-pot, thus more time and process efficient, whereas the sequential periodate-chlorite oxidation produces C2,C3 dialdehyde intermediates that are amenable to further chemical functionalization or post-reactions. These two well-characterized regioselectively carboxylated CNF series represent coherent cellulose nanomaterial models from a single woody source and have served as references for their safety study toward the development of a safer-by-design substance evaluation tool.

Applicability of electromyography (EMG) as a prospective technique for textural evaluation of different types of biscuits

Bakery industry is an important segment of the food industry, worldwide, and texture is an important determinant in the consumer acceptability of baked products especially biscuits. In this study, six different textured biscuits namely, whole wheat flour biscuit, chocolate biscuit, cumin biscuit, cardamom biscuit, pistachio biscuit and cashew biscuit, procured from local bakery, were analyzed for their proximate composition and color characteristics. The biscuits were having significantly (p ≤ 0.05) different values for proximate composition and color parameters. This study primarily aimed at investigating the application of electromyography (EMG) as a prospective technique for texture evaluation of these different types of biscuits. EMG is an upcoming technique for in vivo food texture evaluation which gives real-time information about the dynamic textural changes occurring during mastication of a food product. The EMG study was conducted on ten human subjects who were served six samples of biscuits in duplicate. To eliminate subject factor variance, two-way ANOVA was applied on the relative values of EMG variables. Two recordings of same subject in an EMG session for a biscuit sample showed significant (p ≤ 0.05) degree of similarity indicating that human mastication behavior is reproducible. Initially, twenty-eight EMG parameters were obtained which were reduced to five representative parameters using cluster analysis. Principal component analysis further classified these five masticatory parameters into two independent principal components (PC1 and PC2) for explaining the data variance. Cumulative proportions for PC1 and PC2 were 37.6% and 70.8%, respectively. The results showed that mastication time obtained from electromyographic analysis can evaluate sensory fracturability, hardness and chewiness. While middle interburst duration can effectively evaluate sensory cohesiveness and instrumental flexural strength. The study concluded that EMG can serve as a comprehensive texture evaluation tool in the bakery industry.

Social Media Metrics as Predictors of Publishers’ Website Traffic

The relationship between legacy media and social media has become a crucial topic in the discussions about new media. The debate intensified after Facebook announced a reduction in news posts in user timelines in 2018. In the era of the “Like economy”, social media holds significant economic value, prompting media outlets to adopt a “let’s try and see” approach to reach new audiences and increase their online advertising share. The present study, based on a large-scale survey of 50 publishers’ websites, Facebook pages, and Twitter accounts, deepens our understanding of the relationship between legacy and social media as indicators of audience feedback. Through the lens of network gatekeeping and reciprocal journalism theories, it contributes to the development of new evaluation tools that predict publishers’ website traffic based on social media metrics. Results show that Facebook and Twitter metrics can predict publishers’ website traffic indicators at a rate exceeding 60%. This study underscores the importance of social media metrics in evaluating media practices and the need to shift research toward specific indicators to understand the relationship between legacy and social media.

Keratinocyte-derived circulating microRNAs in extracellular vesicles: a novel biomarker of psoriasis severity and potential therapeutic target

BackgroundPsoriasis is a chronic inflammatory disorder characterized by pathogenic hyperproliferation of keratinocytes and immune dysregulation. Currently, objective evaluation tools reflecting the severity of psoriasis are insufficient. MicroRNAs in extracellular vesicles (EV miRNAs) have been shown to be potential biomarkers for various inflammatory diseases. Our objective was to investigate the possibility of plasma-derived EV miRNAs as a marker for the psoriasis disease severity.MethodsEVs were extracted from the plasma of 63 patients with psoriasis and 12 with Behçet’s disease. We performed next-generation sequencing of the plasma-derived EV miRNAs from the psoriasis patients. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to validate the level of EV miRNA expression. In situ hybridization was used to discern the anatomical location of miRNAs. qRT-PCR, western blotting, and cell counting kits (CCKs) were used to investigate IGF-1 signaling in cells transfected with miRNA mimics.ResultsWe identified 19 differentially expressed EV miRNAs and validated the top three up-and down-regulated EV miRNAs. Among these, miR-625-3p was significantly increased in patients with severe psoriasis in both plasma and skin and most accurately distinguished moderate-to-severe psoriasis from mild-to-moderate psoriasis. It was produced and secreted by keratinocytes upon stimulation. We also observed a significant intensification of IGF-1 signalling and increased cell numbers in the miR-625-3p mimic transfected cells.ConclusionsWe propose keratinocyte-derived EV miR-625-3p as a novel and reliable biomarker for estimating the severity of psoriasis. This biomarker could objectively evaluate the severity of psoriasis in the clinical setting and might serve as a potential therapeutic target.Trial registration None.

Psychometric Properties of the Persian Version of Student Evaluation of Online Teaching Effectiveness (SEOTE) questionnaire Among Medical Sciences’ Students

Background: Due to the increasing number of online educations, traditional methods for evaluation of different on-line education methods are not suitable and there is a need for a valid and reliable tool in this field. This study aimed to examine the validity and reliability of the Student Evaluation of Online Teaching Effectiveness (SEOTE) questionnaire among Medical Sciences’ students in Tabriz, Iran.
 Methods: Using convenience sampling method, the present study included 230 students of Medical Sciences (e.g., mean age of 21.96 ±3.47 years) in Tabriz, Iran. The SEOTE questionnaire was used to collect the data. Forward–backward translation, construct validity and content validity were utilized to check the validity of the questionnaire. In addition, temporal stability was calculated using the test-retest method and Internal Consistency Coefficient (ICC).
 Results: It was confirmed that the SEOTE has appropriate content validity using the content validity index (CVI) of 0.80 and content validity ratio CVR of 0.70. Exploratory factor analysis (EFA) identified the following two factors for domain identification of “communication” and “learning”. A Cronbach’s alpha of 0.97 was obtained for the questionnaire’s reliability, and ICC was used to confirm the temporal stability of the questionnaire (95% Confidence Interval [CI]: 0.966-0.977).
 Conclusion: This study confirms that the Persian version of SEOTE questionnaire is a valid and reliable tool for evaluation of on-line teaching among Medical Sciences’ students.

Integration of a facile sustainable resonance Rayleigh scattering switchable-based system for feasible determination of centrophenoxine, a nootropic and antioxidant agent; application to crude materials and dosage forms

The proposed research adheres to a certain methodology to ensure that the technique used for analyzing the centrophenoxine drug is sustainable and green. It is important to highlight that several tools that have been recently developed were utilized as potential indicators of environmental sustainability and applicability. The present research presents a novel and entirely innovative method utilizing ultrasensitive spectrofluorimetry for the detection of centrophenoxine (CPX) drug. The employed methodology in this study involved the utilization of one-step, one-pot, and direct spectrofluorimetric technique, which was found to be both efficient and environmentally sustainable in the validation and assessment of the drug. Simply, when CPX and erythrosine B reagent were combined in an acidic environment, the highly resonance Rayleigh scattering product was immediately produced. The sensitivity limits were observed to be within the range of 15–47 ng mL−1, whereas the linearity was assessed to be in the range of 50–2000 ng mL−1. The optimal settings for all modifiable parameters of the system were ascertained through an analysis of centrophenoxine-erythrosine B complexes. Moreover, the system demonstrated compliance with International Council for Harmonization (ICH) specifications without encountering any issues. The suggested process was then rated on different recent environmental safety measuring metrics to see how good it was for the environment. Fortunately, the WAC standards that combine ecological and functional elements utilizing the Green/Red/Blue (RGB 12) design also acclaimed the current analytical technique as a white one. Additionally, a new applicability evaluation tool (BAGI) was employed to estimate the practicability of the planned method in the analytical chemistry field.

Development of a novel machine learning-based approach for brain function assessment and integrated software solution

Industry 5.0 emphasizes human-centered solutions. However, bridging the gap between human conditions and engineering systems remains a challenge in this era. Promoting the development of cybernetics applications in the field of rehabilitation is imperative. In the healthcare sector, the evaluation of rehabilitation products’ ergonomics and the dynamic assessment of the human body are of utmost importance. Amid the burgeoning prominence of data-driven product design concepts, ergonomics methods have emerged as indispensable evaluative tools. Nevertheless, the integration of data from multiple sources remains a contemporary challenge; one must extract meaningful information from diverse data sets while enhancing data analysis and fusion techniques. In this study, we collect multimodal neurobiological signals using electroencephalogram (EEG) and functional near-infrared spectroscopy (fNIRS) to devise a robust multimodal rehabilitation data fusion method based on graph convolutional network (GCN), particularly focusing on the motor imagery (MI) task. To achieve a more holistic evaluation, we incorporate granger causality (GC) and brain region adjacency matrix as supplementary features, integrating electrophysiological and hemodynamic perspectives. This integration aims to enhance information complementarity and foster a comprehensive understanding of the neural processes involved in MI. Our results demonstrate the superiority of the multimodal fusion method: it achieves higher average accuracy and improved stability, as indicated by the reduced standard deviation of accuracy. This enhanced performance suggests its potential regarding broader research applications. Building upon our successful findings, we establish an intelligent algorithmic rehabilitation platform based on multimodal neural data. This platform not only holds significant clinical value, facilitating precision and personalized medicine, but also propels the advancement of medical practices, paving the way for a more tailored and effective approach to patient care. Our research makes progresses in the areas of rehabilitation modeling, equipment design, intelligence, and interdisciplinary collaboration through the in-depth study and extension of cybernetic principles and techniques.

Gamma-enhancement of reflected light images as a routine method for assessment of compositional heterogeneity in common low-reflectance Fe-bearing minerals

Abstract Incorporation of impurity elements into minerals impacts on their physical properties (e.g., reflectance, hardness, and electrical conductivity) but the quantitative relationships between these features and compositional variation remain inadequately constrained. Prior work has shown that gamma-enhancement of reflected light images represents a simple yet powerful tool to assess the compositional heterogeneity of single pyrite crystals as it can enhance subtle differences in reflectance between distinct domains with different minor element concentrations. This study extends the gamma correction method to several other common Fe-bearing minerals, magnetite, garnet, wolframite, and tetrahedrite-tennantite, which all have far lower reflectance than pyrite. Gamma-enhanced optical images reveal clear variations in reflectance that are either systematic with increased minor element concentration as the change in gray value on backscatter electron (BSE) images (in the case of magnetite, garnet, and tetrahedrite-tennantite) or contrasting (as in pyrite), yielding a convincing linkage between reflectance variation and compositional heterogeneity. Reflectance variation is an expression of the distribution of the average effective number of free electrons on the mineral surface that can re-emit light when excited by visible light. Gamma-enhanced images can reveal compositional heterogeneity in minerals such as wolframite where small atomic mass differences between substituting elements (Mn and Fe, in the case of wolframite) are virtually impossible to observe as a variation of gray values on BSE images. Results also demonstrate that Fe-rich domains in these minerals can be expected to have higher reflectance than Fe-poor domains whenever Fe is a major constituent. The greater reflectance is attributed to Fe ions having a greater effective number of free electrons than many other elements (e.g., Co, Ni, Si, Ca, Al, Mg, Mn, and As). The research highlights the utility of gamma correction as an inexpensive tool for routine evaluation of compositional heterogeneity in common Fe-bearing minerals, potentially obviating the necessity of a microbeam platform to correlate textures and composition.

Development and testing of a post competency scale for traditional Chinese medicine physicians undergoing standardized training

ObjectiveTo develop and test a post competency scale for traditional Chinese medicine (TCM) physicians undergoing standardized training to provide an applicable tool for scientific evaluation. MethodsBased on literature analysis, behavioral event interviews, and expert consultations, measurement questions were formulated and the initial scale was designed. A questionnaire survey was conducted from July 2022 to May 2023 among TCM physicians undergoing standardized training in China. The rationality of the scale was confirmed through item purification, factor analysis, and tests of reliability and validity. ResultsThe post competency scale consisted of three dimensions (TCM fundamentals and research abilities, TCM thinking and skill abilities, and personal traits and communication abilities) with 21 items. Exploratory factor analysis identified three common factors, accounting for a cumulative variance contribution rate of 62.165%. Confirmatory factor analysis demonstrated that the fit indices of the three-factor model fell within a relatively ideal level. The Cronbach's alpha coefficient of the scale was 0.885. Through convergent validity analysis, the standardized loading coefficients of the 21 items were >0.5, and the average extracted variance (AVE) of the three factors was also >0.5. Moreover, the square roots of the AVE values for each dimension exceeded the correlation coefficients between it and the other dimensions. ConclusionsThe findings suggest that the post competency scale of TCM physicians undergoing standardized training can provide a reliable scientific basis for training and assessment within China.