Model For Evaluation Research Articles

Strategy to Identify Virulence-Related Genes of the Pathogenic Fungus Trichosporon asahii Using an Efficient Gene-Targeting System.

Trichosporon asahii is a pathogenic fungus that causes severe deep-seated mycosis in immunocompromised patients with neutropenia. Understanding the molecular mechanisms of T. asahii infection will facilitate the development of new therapeutic and preventive strategies. Two main obstacles have prevented the identification of virulence-related genes in T. asahii using molecular genetic techniques: the lack of experimental animal infection models for easy evaluation of T. asahii virulence and the lack of genetic recombination technology for T. asahii. To address these issues, we developed a silkworm infection model to quantitatively evaluate T. asahii virulence and a genetic recombination method to generate gene-deficient T. asahii mutants, enabling the identification of virulence factors of T. asahii. In this review, we propose a strategy for identifying virulence-related factors in T. asahii using a silkworm infection model and an efficient gene-targeting system.

Evaluasi Penilaian Kinerja Guru Untuk Meningkatkan Kualitas Pembelajaran

Teacher performance evaluation is essential to improving and maintaining the quality of education. Through these evaluations, teachers' strengths and weaknesses can be clearly identified, allowing for more appropriate professional development. When the quality of teachers' teaching improves, student achievement also tends to rise, showing the close relationship between teacher evaluation and student learning outcomes. The purpose of the study is to find out the various models and methods of teacher performance evaluation and the obstacles in implementation as well as strategies to improve teacher work assessment so that the quality of learning also increases. The research method used is library research. Based on the results of the research, it was found that there are various models of teacher performance evaluation and their impact on the quality of learning.

Study on Spatial Differentiation Characteristics and Driving Mechanism of Sustainable Utilization of Cultivated Land in Tarim River Basin

The sustainable utilization of cultivated land is a crucial prerequisite for ensuring food security and achieving sustainable socioeconomic development. This study employed a dataset to evaluate sustainable land use and utilized a combination of multi-factor comprehensive evaluation models, structural equation modeling, geographically weighted regression, and Pearson correlation analysis to systematically investigate the overall level, spatial differentiation characteristics, and driving mechanisms of sustainable cultivated land utilization in the Tarim River Basin. Additionally, we compared and tested three spatial interpolation methods using high-resolution data to address the modifiable areal unit problem (MAUP) and enhance the quality of spatial predictions for cultivated land utilization, ultimately identifying inverse distance weighting (IDW) as the optimal method. The results indicate the following: (1) The level of sustainable cultivated land utilization is moderately high, with an average index of 0.581, exhibiting a “U-shaped” trend from the upper to lower reaches of the Tarim River Basin. The highest levels are found in the Kashgar River–Yarkant River Basin, followed by the Hotan River Basin and the Kaidu–Peacock River Basin, while the mainstream area has the lowest levels. (2) The relationships among various cultivated land environmental systems and sustainability demonstrate distinct response characteristics and spatial differentiation patterns. Cultivated land use and management exert the most significant influence on sustainability, followed by soil quality and water resource systems, with climatic factors having the least impact. The effects of each system reveal inverted “U”, inverted “N”, “U”, and “W” patterns from the lower reaches to the upper reaches, respectively. (3) As the complexity of interactions and integrative mechanisms within the regional cultivated land system increases, the sensitivity and vulnerability of the system also rise, resulting in lower levels of sustainable utilization. (4) Based on the current challenges facing the cultivated land environmental system and the primary mechanisms influencing its sustainability, we propose regulatory measures focused on “suitable consolidation”, “suitable resting”, and “suitable planting”. These findings provide valuable insights for formulating differentiated land protection strategies, policies, and spatial planning initiatives.

Research on indoor POI salience evaluation model based on machine learning

Due to the lack of GNSS signals in indoor environments, landmarks are particularly important in orientation recognition and navigation. However, the salience evaluation models established by existing studies for extracting landmarks have deficiencies in dealing with indicator redundancy and nonlinear relationships. Therefore, this study adopts a data-driven approach. First, the indoor POI salience evaluation indicators system is established. Then, large shopping malls are selected to collect data, and the indicators are screened by Spearman’s correlation coefficient after preprocessing. Finally, the importance ranking of evaluation indicators is obtained, and based on this ranking, the model is trained and optimised using random forest and multilayer perceptron. The results show that the model established in this study has higher salience prediction accuracy and the best stability compared with the models established in previous studies.

Introducing Aberrations into Human Eye Models with High Precision for Objective Visual Quality Evaluation

Objective visual quality evaluation using optical human eye models with actual eye aberration characteristics provides an important reference for clinical vision diagnosis and treatment. To ensure accurate evaluation, it is typically necessary to precisely introduce eye aberrations into the eye model by adjusting the model’s surface shape. However, the detailed relationship between eye aberrations and surface shapes is unclear, causing challenges in aberration introduction. In this paper, a method that enables the accurate introduction of target aberrations into an eye model for objective visual quality evaluation is proposed. The eye aberrations generated by the model’s surface are analyzed based on optical nodal aberration theory. The aberration calculation formulas are proposed and proved by a design example. Using the proposed method, the objective visual quality evaluation is conducted for the patients who underwent refractive surgery. The clinically measured postoperative eye aberrations are accurately introduced into the eye model with an error of less than 1.0 × 10−4 μm. The objective visual evaluation results are consistent with the statistical results of clinical contrast sensitivity tests. With the proposed method, it is expected to aid in clinical visual quality testing and assess the effect of refractive correction.

A Systematic Literature Review on Automatic Sexism Detection in Social Media

Sexist content has become increasingly prevalent on social media platforms, underscoring the critical need for the development of efficient Automatic Sexism Detection methods. Previous literature reviews have not encompassed the new advancements in Automatic Sexism Detection observed over the past three years. Hence, the present study conducted a Systematic Literature Review (SLR) that examined 48 primary studies published between 2014 and 17th Sept. 2024, retrieved from six bibliographic databases. This paper aims to present a comprehensive literature review on Automatic Sexism Detection, encompassing the datasets, preprocessing techniques, feature extraction methods, text representations, classification approaches, and evaluation models employed in Automatic Sexism Detection research. The paper includes a discussion of the findings, limitations, and future research directions of the chosen articles. Additionally, it provides an overview of the conclusions drawn from the conducted research. The performed analysis reveals a lack of corpus beyond the English and Spanish language encountered in datasets, with most of the latter being annotated for either misogyny or non-misogyny. Common preprocessing techniques analyzed in the current study include lowercase conversion, text removal, tokenization, stemming, and rewriting. Discrete representations, such as TF-IDF, N-grams, and BoW, are frequently utilized, while distributed representations, like Bert and GloVe, are prominent. Bert is the predominant classification model utilized while combining lexical features can enhance the results in the majority of the discussed scenarios. Accuracy (A) and F1 score (F1) are the most widely deployed evaluation metrics in this field.

Temporal dynamics of implicit moral evaluation: from empathy for pain to mentalizing processes

To understand how we evaluate harm to others, it is crucial to consider the offender’s intent and the victim’s suffering. Previous research investigating event-related potentials (ERPs) during moral evaluation has been limited by small sample sizes and a priori selection of electrodes and time windows that may bias the results. To overcome these limitations, we examined ERPs in 66 healthy human adults using a data-driven analytic approach involving cluster-based permutation tests. Participants performed an implicit moral evaluation task requiring to observe scenarios depicting intentional harm (IHS), accidental harm (AHS), and neutral actions (NAS) while judging whether each scenario was set indoors or outdoors. Our results revealed two distinct clusters, peaking at ∼170 and ∼250 ms, showing differences between harm scenarios (IHS and AHS) and NAS, suggesting rapid processing of the victim’s physical outcome. The difference between IHS and AHS scenarios emerged later, at ∼400 ms, potentially reflecting subsequent evaluation of the agent’s intentions. Source analysis showed that brain regions associated with empathy for pain were associated with the earlier peaks at ∼170 and ∼250 ms, while the modulation of the activity of the mentalizing network was presented at ∼250 and ∼400 ms. These findings advance our understanding of the neural mechanisms underlying implicit moral evaluation. Notably, they provide electrocortical new insights for models of implicit moral evaluation, suggesting an early neural response linked to empathy for pain, with subsequent integration of empathy response with mentalizing processes, followed by later cognitive evaluations, likely reflecting the assessment of the agent’s moral responsibility.

VA-Creator—A Virtual Appliance Creator based on adaptive Neural Networks to generate synthetic power consumption patterns

With the advent of the Smart Home domain and the increasingly widespread application of Machine Learning (ML), obtaining power consumption data is becoming more and more important. Collecting real-world energy data using sensors is time consuming, expensive, error-prone and in some situations not possible. Therefore, we present the VA-Creator, a framework to create Virtual Appliances (VAs). These VAs synthesize power consumption patterns (PCPs) based on Neural Networks (NNs) which adapt their architecture to the training data structure to simplify the creation of new VAs. To be able to generate all appliance types available in a typical household we use various kinds of NN, including Multilayer Perceptrons (MLPs), Long Short-Term Memorys (LSTMs) and a specific Generative Adversarial Network (GAN) as well as different ML techniques such as XGBoost, selecting the appropriate technique depending on each appliance’s characteristics. We then compare the results of the ML models against real data and evaluate them by using Dynamic time Warping (DTW) as well as the classification performance of an MLP descriminator as metrics. Additionally, to ensure that the VAs allow to meaningfully train ML models, we use them to generate synthetic data and then train Non intrusive Load Monitoring (NILM) models in an extensive evaluation. The presented evaluation provides evidence that the VA models produce realistic and meaningful results.

Development of a Conceptual Model to Identify and Rank Environmental and Health Costs of Work-Related Diseases Using Delphi Study and Analytic Network Process

Introduction: Improving health and the environment is one of the components of development, social welfare, and economic growth. Another influential factor in increasing health costs and reducing social welfare is work-related accidents and diseases, which impose high costs on individuals, industries, and the national economies of countries. Therefore, using multi-criteria decision-making methods, the present study provided a conceptual model to identify and rank work-related diseases’ environmental and health costs. Material and Methods: The present study was conducted in 2023. A classification model for the economic evaluation of environmental and health costs of occupational diseases was developed to achieve the study’s aim. In the current research, the Delphi method was used to identify health and environmental criteria, and the Analytic Network Process (ANP) was used to weight the sub-criteria. Finally, the cost of health and the environment was estimated based on the available information. Naft Tehran Hospital (NSHT) was also selected as a case study site. Results: The results showed that the drug and medical equipment cost factor, with a weight of 0.312 in the treatment sector, and the particular and infectious waste cost factor, with a weight of 0.085, were the most critical factors in the economic evaluation. Also, the parametric model results showed that 99.84% of the total costs are related to health costs, and 0.16% are related to environmental costs. In general, the results of this research showed that 61.3% of the costs of the health sector are related to the two sectors of medicine and medical equipment and the cost of service personnel, and 91.7% of the costs of the environmental sector are related to wastewater treatment and the cost of electricity consumption. Conclusion: This study presented a semi-quantitative model to estimate health and environmental costs caused by occupational diseases. The results can create a novel scientific insight into implementing control measures using the optimal point of cost-benefit parameters. Implementing this integrated model can be a practical and effective step in allocating resources and prioritizing interventions.

Intelligent prediction and evaluation models for the seismic risk and vulnerability of reinforced concrete girder bridges in large-scale zones

Intelligent prediction and evaluation models for the seismic risk and vulnerability of reinforced concrete girder bridges in large-scale zones

Medical students’ perceptions of a community-engaged learning approach to community health in Ghana: the Students’ Community Engagement Programme (SCEP)

BackgroundRevitalizing primary health care requires that the health workforce, especially doctors, must appreciate the significance of the socio-cultural environment in health. To achieve this objective, training of medical students must emphasize greater understanding of the community and its role in health through community engagement using community-engaged learning. However, research on this learning method applied in a purely community engagement context is lacking. A medical school in Ghana adapted its fourth-year junior clerkship curriculum in Community Health to include a community-engagement programme. This study reports students’ perceptions of the said programme as a way of evaluating it and helping to improve upon its implementation.MethodsA cross-sectional survey using a Google form-based questionnaire with open- and closed-ended questions was conducted from May 2022 to December 2023 among 303 current and past medical students of the University of Health and Allied Sciences, Ghana who had experienced the said programme. Based on the first three levels of the Kirkpatrick’s four-level model of training evaluation, data was collected on participants’ socio-demographics, their assessment of the programme content and delivery, subsequent attitudinal changes and their application to practice. Descriptive statistics were performed on quantitative data and thematic content analysis done for responses to the open-ended questions.ResultsMore than half of participants were males (188/303). The mean (SD) participant age was 23.9 years (2.4). Over 90% indicated the programme was valuable to their training (277/297) and were satisfied with the facilitators (283/297) despite some anxieties expressed at the start of their clerkship. Participants noted that they acquired other skills including teamwork and leadership aside the reinforced academic content. At least 99% of participants noted they could conduct the processes of community entry and engagement with or without assistance.ConclusionAlthough there is room for improvement, the students’ community engagement programme may have some utility in the training of medical students to enable them better appreciate community interactions that influence health. Further research incorporating objective assessments of learning and behaviour change is needed to comprehensively assess the programme.

Reinforcement Learning Informed Evolutionary Search for Autonomous Systems Testing

Evolutionary search (ES)-based techniques are commonly used for testing autonomous robotic systems. However, these approaches often rely on computationally expensive simulator-based models for test scenario evaluation. To improve the computational efficiency of the search-based testing, we propose augmenting the ES with a reinforcement learning (RL) agent trained using surrogate rewards derived from domain knowledge. In our approach, known as RIGAA (Reinforcement learning Informed Genetic Algorithm for Autonomous systems testing), we first train an RL agent to learn useful constraints of the problem and then use it to produce a certain part of the initial population of the search algorithm. By incorporating an RL agent into the search process, we aim to guide the algorithm towards promising regions of the search space from the start, enabling more efficient exploration of the solution space. We evaluate RIGAA on two case studies: maze generation for an autonomous “Ant” robot and road topology generation for an autonomous vehicle lane-keeping assist system. In both case studies, RIGAA reveals more failures of a high level of diversity than the compared baselines. RIGAA also outperforms the state-of-the-art tools for vehicle lane-keeping assist system testing, such as AmbieGen, CRAG, WOGAN, and Frenetic in terms of the number of revealed failures in a two-hour budget.

Application of Environmental Protection Agency (EPA) Model in Occupational Hazard Evaluation of UV-Curable Coating Production Project

This paper applies the EPA inhalation risk evaluation model—which has the advantage of the high safety margin value of the RfC value and considers long-term contact exposure to chemical toxicants for all protected populations—to objectively assess the risk level of acute and chronic occupational poisoning and tumors caused by respiratory exposure to chemical toxicants in a UV-curable coating production project, which is of guiding significance. The results reveal that the hazardous chemical elements in the air in the workshop of this UV-curable coating production project have no substantial influence on worker health; therefore, no further design is required.

Farmers' credit risk evaluation with an explainable hybrid ensemble approach: A closer look in microfinance

Artificial intelligence stimulates the vitality of microcredit by reshaping credit risk evaluation models, especially targeting the group of farmers. Therefore, the paper aims to establish a new interpretable hybrid ensemble model for evaluating the credit risk of microfinance for farmers, which is called ADASYN (Adaptive Synthetic Sampling)-LCE (Local Cascade Ensemble)-Shapash. It integrates the advantages of three ensemble models: bagging, boosting, and local cascading, including reducing model variance, reducing model bias, and simplifying complex problems by learning different parts of the training data. And it alleviates the problem of low generalization performance of traditional ensemble models caused by imbalanced loan data of farmers. Through the empirical analysis of the data of farmers' loans of China poverty alleviation agency “CHONGHO BRIDGE”, it is found that its average rank is 2.1, which is better than other integrated models in the credit risk evaluation of farmers' microfinance. Finally, the global and local interpretation of our model is preliminarily explored.

Power Loss and Electrothermal Characterization of Hybrid Power Integrated Modules for Industrial Servo Motor Drives

This study aims to facilitate the assessment of the electromagnetic-electrical-thermal coupled response of a developed 30 kHz/12 kW silicon carbide (SiC)/silicon (Si) hybrid power-integrated module (hPIM) during load operation. To achieve this goal, an efficient electromagnetic-circuit-thermal coupling (ECTC) analysis methodology is introduced. This ECTC methodology incorporates a fully integrated electromagnetic-circuit coupling (EMCC) analysis model for parasitic extraction in order to addressing their effects on power losses, and a simplified electrothermal coupling (SETC) analysis model for temperature evaluation in order to consider the coupling influence of the instantaneous junction temperature on instantaneous power losses. The SETC model couples a simple lookup table that maps the power loss (P) in terms of the temperature (T) constructed using the developed EMCC model, and an equivalent Foster thermal network model established through three-dimensional (3D) computational fluid dynamics (CFD) thermal flow analysis. This PT lookup table, replacing the tedious and time-consuming EMCC simulation, is responsible for fast estimation of temperature-dependent power losses. The proposed analysis models, namely the CFD, EMCC, and SETC analysis models, are validated through thermal experiments and detailed modeling. Finally, the influence of various operation conditions on the power losses of the hPIM during the power conversion operation is explored through parametric analysis.

Analysis on Evaluation Method of Mechanically-Induced Hemolysis of Medical Devices

Mechanically-induced hemolysis is an important index for evaluating the blood compatibility of medical devices. It mainly evaluates the risk of mechanical hemolysis under simulated clinical use conditions of medical devices. The existing hemolysis test standards mainly evaluate the risk of material-induced hemolysis and cannot evaluate the risk of mechanically-induced hemolysis. Although some institutions have conducted research on mechanically-induced hemolysis caused by medical devices, systematic evaluation standards have not yet been established. This study mainly summarizes the evaluation process, selection of evaluation models, and steps for assessing mechanically-induced hemolysis, providing a reference for relevant evaluations and standard establishment.

Impact of pH-Shifting and Autoclaving on the Allergenic Potential of Red Kidney Bean (Phaseolus vulgaris L.) Lectins.

The ingestion of red kidney bean products is hindered by the persistent allergenicity of lectins, even after autoclaving. This study examined the modification of lectin allergenicity in red kidney beans by pH-shifting and autoclaving treatments, utilizing BALB/c mouse sensitization, in situ recirculating perfusion, and a bone marrow-derived dendritic cell (BMDC) model for allergenicity evaluation. Compared to autoclaving alone, combined pH-shifting and autoclaving reduced allergic symptoms in BALB/c mice, as evidenced by lower serum IgE, mMCPT-1, GM-CSF, HIS, IL-2, IL-4, IL-9, IL-13, and IL-17 levels and higher IgG1, IgG2a, IL-10, IFN-γ, and IFN-α cytokine release. Moreover, lectin continued to affect intestinal permeability and damaged the barrier despite undergoing pH-shifting and autoclaving treatments. Additionally, the uptake of lectin by BMDCs through mannose receptor-mediated endocytosis was diminished, with an increased susceptibility to endolysosomal degradation. The T-cell polarization was consistent with the mouse experiments, where the balance of Th1 and Th2 cells remained in lectin with pH-shifting and autoclaving treatments though the decreased abundance ratios of peptide YKYDSNAHT and increased abundance ratios of peptide ITKGNVETN in endolysosomal degradation. Therefore, the immunogenicity of lectins could be decreased by pH-shifting and autoclaving treatments, offering insights into the development of hypoallergenic legume products.

Assessing the effectiveness of feature film and television series in university teaching through evaluation quadrangulation and action learning

ABSTRACT Multimedia technologies such as feature films and television series (FF/TV) are increasingly used by university lecturers to stay relevant in contemporary media-saturated society. However, institutional guidance on how to evaluate the teaching effectiveness and thus optimise the pedagogical integration of these materials is scarce: most institutional Student Evaluation of Teaching (SET) questionnaires do not directly cover multimedia use in the classroom. Lecturers therefore have been self-reliant in implementing a range of different evaluation practices to assess pedagogies with FF/TV. Using the four-quadrant model of evaluation and action learning, this study examines the advantages and shortcomings of various evaluation practices (e.g., SET questionnaires, observation, peer review) used by lecturers across disciplines who use FF/TV in their teaching. The study identified objectives and areas of evaluation that are specific to the context of teaching with FF/TV to guide the development of new SET questions and the integration of various TE practices into the full teaching cycle.

How Malaysian Adolescents Navigate Sexual Health Information on the Internet.

Significant sociocultural barriers to sexual and reproductive health (SRH) information influence what is acceptable to discuss and learn within the Malaysian community. To address gaps in their knowledge, adolescents routinely turn to the Internet. This study identifies the ways they navigate SRH information found online. One-on-one interviews were conducted with 17 Malaysian adolescents. The data were analysed with reflexive thematic analysis. Participants navigate SRH information using intuitive strategies, known locally as pandai-pandai. This important cultural concept involves balancing between adherence to social norms and resourcefulness in problem-solving. Pandai-pandai strategies were observed in three domains: (1) navigating SRH sources, (2) evaluating and verifying SRH information, and (3) processing SRH information. Malaysian adolescents' strategies for evaluating SRH information extend beyond traditional critical evaluation models and are driven by emotional, social, and cultural criteria, requiring a reconsideration of what constitutes critical evaluation in this context.

A three-dimensional analytical model for performance evaluation of thermoelectric generators

A three-dimensional (3D) theoretical model for thermoelectric generators (TEGs) has been developed in this paper, yielding analytical solutions for power output and energy conversion efficiency. The model comprehensively considers convective heat transfer between the thermoelectric legs and their ambient environment, as well as 3D heat conduction within the ceramic substrates. Numerical results reveal the significant influence of convective heat loss from the legs' surfaces on efficiency, especially for taller legs or higher heat convection coefficient, while having a minimal impact on power output for the constant temperature boundaries. It is shown that neglecting 3D heat conduction within the ceramic substrates leads to a substantial overestimation of TEG performance. Additionally, the complex 3D heat conduction problem for TEGs can be simplified into a more manageable 1D model with only minor adjustments to classical TEG theory. This is achieved by introducing analytical expressions for a dimensionless impact factor to quantify convective heat loss from the legs’ surfaces and the effective thermal conductance of the ceramic substrates. The proposed model serves as a valuable tool for simplifying the modeling process and optimizing the design of actual TEGs.