Articles

Effective infection control requires a close fit between the mask and face to minimize gaps. This study investigated whether surgical mask performance varies with face shape and mask size. Three facial models were 3D-printed using head-related transfer function data. Two mask sizes were tested on each model, and 3D measurements were taken at five facial points: the nose, cheeks, and chin to assess mask-to-face gaps. To simulate droplet emission, an aqueous sodium chloride solution was released from a pseudo-oral cavity in the models, and air leakage was measured using a mask-fitting tester. A two-way analysis of variance (ANOVA) was used to examine the effects of face and mask size on leakage. Small face models showed significantly higher leakage than medium and large ones (p < 0.001), and S-sized masks leaked more than M-sized masks regardless of face size (p = 0.038).<b> </b>Linear regression showed a positive correlation between chin gaps and leakage when using S-sized masks (p < 0.05). These results suggest that medium-sized masks offer better overall performance. However, for small faces, fit—especially at the chin, requires particular attention.

Preference learning plays a crucial role in AI applications, particularly in recommender systems and personalized services. Traditional pairwise comparisons, while foundational, present scalability challenges in large-scale systems. This study explores alternative elicitation methods such as ranking, numerical ratings, and natural language feedback, alongside a novel hybrid framework that dynamically integrates these approaches. The proposed methods demonstrate improved efficiency, reduced cognitive load, and enhanced accuracy. Results from simulated user studies reveal that hybrid approaches outperform traditional methods, achieving a 40% reduction in user effort while maintaining high predictive accuracy. These findings open pathways for deploying user-centric, scalable preference learning systems in dynamic environments.

<b>Introduction:</b> Pain is considered as the fifth vital sign that should be considered in assessing patients. For clinicians to evaluate and determine the right pain interventions, there should be parameters such as pain scale. Our objective in this study is to determine factors affecting pain scale preferences in suburban and rural populations. The pain scales used in this study are FPS-R (Faces Pain Scale-Revised), VRS (Verbal Rating Scale), VAS (Visual Analogue Scale), and NRS (Numering Rating Scale). <b>Method:</b> This study uses observational design with an interview approach and a cross-sectional study. Areas covered are within Indonesia, which are marginal areas of Tangerang district border, and two rural areas in Serukam, West Kalimantan, and Soe, East Nusa Tenggara. Data collected will be analyzed using SPSS 25 software. <b>Result:</b> Populations within the suburban areas prefer NRS (52.08%) as their pain scale, and populations in rural areas prefer FPS-R 76.92%). Factors affecting pain scale preferences are location areas, as well as last education, with statistical significance of p<0.05. <b>Discussion:</b> Our study showed that the choice of several pain scales is not appropriate for specific demographics due to the complexity of these scales. Factors that should be considered are the location areas and education level, as some population in remote areas have better understanding of simpler pain scales. <b>Conclusion:</b> Complexity or simpler components may be an underlying reason for the preference of score selection to assess pain scales in some population. Therefore, the selection of pain scales should be adjusted to specific demographics so that clinicians can provide appropriate management with appropriate pain scales.

Over the past few decades, cardiovascular disease and related complications have surpassed all others as the important causes of death on a universal scale. At the moment, they are the important cause of mortality universal, including in India. It is important to know how to find cardiovascular problems early so that patients get better care and prices go down. This project utilizes the UCI Heart Disease Dataset to develop ML and DL models capable of detecting cardiac diseases. Heart illness was categorized using Convolutional Neural Network (CNN) models, which are able to detect intricate patterns in supplied data. A confusion matrix rating, an F1-score, a ROC curve, accuracy, precision, and recall were some of the measures used to grade the model. It did much better than the Neural Network, Deep Neural Network (DNN), and Gradient Boosted Trees (GBT) models, with 91.71% accuracy, 88.88% precision, 82.75% memory, and 85.70% F1-score. Comparative study showed that CNN was the most accurate model. Other models had different balances between accuracy and recall. The experiment results show that the optional CNN model is a decent way to identify cardiovascular disease. This means that it could be used in healthcare systems to find diseases earlier and treat patients better.

The initial omicron SARS-CoV-2 subvariants, BA.1 and BA.2 (BA.1.2), were progressively displaced by BA.5in Japan in 2022. In the BA.5-dominant period, there were significantly more healthcare staff infected by nosocomial contact with persons with confirmed SARS-CoV-2 infection than those infected by household contact, compared with the BA.1.2-dominant period. The staff infected via nosocomial contact included non-patient-facing staff, in the BA.5-dominant period, although they did not become infected by SARS-CoV-2 through nosocomial contact in the BA.1.2-dominant period. These data suggest the importance of infection control and care for non-patient-facing staff, in the same way as for patient-facing staff.

Life cycle assessment, LCA is one of the tools that is used to measure the environmental impacts of a process or an operation. Various studies have mentioned the benefits of mass timber in building construction. This study presents an evaluation of the LCA of certain mass timber in relation to concrete-based materials. Using Athena impact estimator for buildings, the study compared the results of an LCA study for a house that is designed with concrete beams, concrete columns, and concrete walls with brick in the envelope category (Material group 1) with those that are made with glulam beams, glulam columns, CLT walls with spruce wood bevel siding (Material group 2), and another building with LVL columns, LVL beams, CLT walls with spruce wood bevel siding (Material group 3). The results are in line with those that were reported by the majority of previous researchers. For the location that is being reviewed (Calgary, Alberta), the designs showed that construction with wood materials having mass timber components will have a better environmental performance than that for a building design with more concrete-based materials. The building design with more concrete-based material (group 1) showed 242% and 60% higher global warming and acidification potential respectively than the building with glulam beams and columns (material group 2). Except for ozone depletion potential, material group 2 (with glulam beams and columns) has a lower impact than material group 3 (with LVL/PSL beams and columns). The differences in impacts are more pronounced when the comparison is with design with more concrete-based products. This report further shows that LCA can be helpful during the preliminary design to evaluate the expected environmental impacts of the choice of different materials. This study recommends that material manufacturers and building contractors pay attention to LCA results to evaluate areas for continuous improvement.

Hand hygiene is crucial in preventing healthcare-associated infections. In this study, we aimed to quantify the accuracy of subjective evaluation of hand washing through visual inspection and objective evaluation through images. The participants were 24 consenting nursing students, and the study used black light and fluorescent paint to generate sketches and captured images of the unwashed areas, which were processed. Handwashing training was conducted once a week for four consecutive weeks. We collected data in the first and fourth training sessions. We found that the percentage of the unwashed palmar areas was significantly higher in the images than in the sketches (p<0.05). The percentage of the uncleaned area as recognized visually significantly increased for sketches (p=0.01) and decreased for images (p=0.009) in the fourth session. The difference between the percentages of the image and sketch area notably decreased in the fourth session (p=0.002). When we checked the recognition percentage of the unwashed area by dividing the right-hand palmar side into six areas, the fingertips had the highest percentage, and the ball of the thumb had the lowest percentage. The recognition of the unwashed areas was low when comparing the subjective visual assessment with the objective imagery assessment. In addition, the percentage of the unwashed areas decreased with repeated training, indicating a decrease in the difference between the subjective and objective ratings.

From 2020 to 2022 the Covid-19 was spread and many people died. Death is near to everyone. The aim of the study was to investigate differences of concept of good death and view of life and death cross cultural. Participants were 92 Japanese, 110 Korean and 100 American who were ordinary people. We used the Good Death questionnaire to measure desirable death and the Death Attitude Inventory to measure view of life and death. Participants completed both questionnaires. As for Good Death, Japanese and Korean regarded “not being burden to others” as important the most, and American regarded “feeling that one’s life is worth living” as important. The scores of “unawareness of death” and “religious and spiritual comfort” of Korean were the highest, following American, and Japan. As for the Death Attitude Inventory, the score of American was higher than Japanese and Korean totally. The scores of “Death as release” or “Death Avoidance” of American were the highest. These results suggest that although Japanese and Korean regard “Not being burden to others” as important in common, Korean regard religious and spiritual comfort as important. American may avoid to think of death and regard it as release. We can make use of these cultural differences in clinical situation.

Ever since the idea of sustainable development was proposed, how to achieve it has always been the focus of researchers and policymakers. At the same time, in the letters of sustainable development, two approaches of weak sustainability and strong sustainability have been mentioned; Two approaches with different assumptions suggest different policies and will have different consequences. On the other hand, with the increase of environmental concerns in recent decades, the concept of natural capital and physical, human, and social capital has been added to the common literature of economics. Recently, with the collection of data related to the natural capital of nations by the World Bank, the possibility of statistical studies in this field has been provided. In the form of several regression models and at the international level, the present study will analyze the most fundamental difference between the two approaches of weak sustainability and strong sustainability, i.e., the possibility or impossibility of replacing physical capital instead of natural capital. The study results show that natural capital has a direct, positive, and independent role in explaining sustainable development indicators. Even the addition of physical, human, and social capital indicators does not threaten the significant coefficient of natural capital. Therefore, it can be concluded that under the assumption of a strong sustainability model, other types of capital can not replace natural capital.