I-line photolithographic metalenses enabled by distributed optical proximity correction with a deep-learning model.

High pattern fidelity is paramount to the performance of metalenses and metasurfaces, but is difficult to achieve using economic photolithography technologies due to low resolutions and limited process windows of diverse subwavelength structures. These hurdles can be overcome by photomask sizing or reshaping, also known as optical proximity correction (OPC). However, the lithographic simulators critical to model-based OPC require precise calibration and have not yet been specifically developed for metasurface patterning. Here, we demonstrate an accurate lithographic model based on Hopkin's image formulation and fully convolutional networks (FCN) to control the critical dimension (CD) patterning of a near-infrared (NIR) metalens through a distributed OPC flow using i-line photolithography. The lithographic model achieves an average ΔCD/CD = 1.69% due to process variations. The model-based OPC successfully produces the 260 nm CD in a metalens layout, which corresponds to a lithographic constant k1 of 0.46 and is primarily limited by the resolution of the photoresist. Consequently, our fabricated NIR metalens with a diameter of 1.5 mm and numerical aperture (NA) of 0.45 achieves a measured focusing efficiency of 64%, which is close to the calculated value of 69% and among the highest reported values using i-line photolithography.

Learning pathways composed of core subjects with features of reducing cognitive load have better learning outcomes.

BACKGROUND: Changing the course duration or timing of subjects in learning pathways would influence medical students' learning outcomes. Curriculum designers need to consider the strategy of reducing cognitive load and evaluate it continuously. Our institution underwent gradual curricular changes characterized by reducing cognitive load since 2000. Therefore, we wanted to explore the impact of this strategy on our previous cohorts. METHODS: This cohort study explored learning pathways across academic years of more than a decade since 2000. Eight hundred eighty-two medical students between 2006 and 2012 were included eventually. Learning outcomes included an average and individual scores of subjects in different stages. Core subjects were identified as those where changes in duration or timing would influence learning outcomes and constitute different learning pathways. We examined whether the promising learning pathway defined as the pathway with the most features of reducing cognitive load has higher learning outcomes than other learning pathways in the exploring dataset. The relationship between features and learning outcomes was validated by learning pathways selected in the remaining dataset. RESULTS: We found nine core subjects, constituting four different learning pathways. Two features of extended course duration and increased proximity between core subjects of basic science and clinical medicine were identified in the promising learning pathway 2012, which also had the highest learning outcomes. Other pathways had some of the features, and pathway 2006 without such features had the lowest learning outcomes. The relationship between higher learning outcomes and cognitive load-reducing features was validated by comparing learning outcomes in two pathways with and without similar features of the promising learning pathway. CONCLUSION: An approach to finding a promising learning pathway facilitating students' learning outcomes was validated. Curricular designers may implement similar design to explore the promising learning pathway while considering potential confounding factors, including students, medical educators, and learning design of the course.

Using machine learning to identify key subject categories predicting the pre-clerkship and clerkship performance: 8-year cohort study.

BACKGROUND: Medical students need to build a solid foundation of knowledge to become physicians. Clerkship is often considered the first transition point, and clerkship performance is essential for their development. We hope to identify subjects that could predict the clerkship performance, thus helping medical students learn more efficiently to achieve high clerkship performance. METHODS: This cohort study collected background and academic data from medical students who graduated between 2011 and 2019. Prediction models were developed by machine learning techniques to identify the affecting features in predicting the pre-clerkship performance and clerkship performance. Following serial processes of data collection, data preprocessing before machine learning, and techniques and performance of machine learning, different machine learning models were trained and validated using the 10-fold cross-validation method. RESULTS: Thirteen subjects from the pre-med stage and 10 subjects from the basic medical science stage with an area under the ROC curve (AUC) >0.7 for either pre-clerkship performance or clerkship performance were found. In each subject category, medical humanities and sociology in social science, chemistry, and physician scientist-related training in basic science, and pharmacology, immunology-microbiology, and histology in basic medical science have predictive abilities for clerkship performance above the top tertile. Using a machine learning technique based on random forest, the prediction model predicted clerkship performance with 95% accuracy and 88% AUC. CONCLUSION: Clerkship performance was predicted by selected subjects or combination of different subject categories in the pre-med and basic medical science stages. The demonstrated predictive ability of subjects or categories in the medical program may facilitate students' understanding of how these subjects or categories of the medical program relate to their performance in the clerkship to enhance their preparedness for the clerkship.

Medical students' self-assessed efficacy and satisfaction with training on endotracheal intubation and central venous catheterization with smart glasses in Taiwan: a non-equivalent control-group pre- and post-test study

PURPOSE: Endotracheal intubation and central venous catheterization are essential procedures in clinical practice. Simulation-based technology such as smart glasses has been used to facilitate medical students' training on these procedures. We investigated medical students' self-assessed efficacy and satisfaction regarding the practice and training of these procedures with smart glasses in Taiwan. METHODS: This observational study enrolled 145 medical students in the 5th and 6th years participating in clerkships at Taipei Veterans General Hospital between October 2020 and December 2021. Students were divided into the smart glasses or the control group and received training at a workshop. The primary outcomes included students' pre- and post-intervention scores for self-assessed efficacy and satisfaction with the training tool, instructor's teaching, and the workshop. RESULTS: The pre-intervention scores for self-assessed efficacy of 5th- and 6th-year medical students in endotracheal intubation and central venous catheterization procedures showed no significant difference. The post-intervention score of self-assessed efficacy in the smart glasses group was better than that of the control group. Moreover, 6th-year medical students in the smart glasses group showed higher satisfaction with the training tool, instructor's teaching, and workshop than those in the control group. CONCLUSION: Smart glasses served as a suitable simulation tool for endotracheal intubation and central venous catheterization procedures training in medical students. Medical students practicing with smart glasses showed improved self-assessed efficacy and higher satisfaction with training, especially for procedural steps in a space-limited field. Simulation training on procedural skills with smart glasses in 5th-year medical students may be adjusted to improve their satisfaction.

A single-center, cross-sectional study of cross-professional faculties' perception to virtual class under different scenarios: A stepwise approach.

BACKGROUND: Virtual teaching in medical education is rising with the increased need caused by the recent pandemic. However, evaluations of the perception of clinical teachers across professions for setting a virtual class in different teaching scenarios are limited. This study aims to identify cross-professional clinical teachers' perception of virtual classes and the acceptability of the virtual class-specific checklist for setting a virtual class. METHODS: We conducted a cross-sectional study to investigate clinical teachers' need to set and teach a virtual class and then designed a virtual class-specific checklist with five essential steps and a related training program in July 2021. After the training, 186 participants were randomly enrolled in October 2021 to evaluate their perceptions about setting virtual classes and the acceptability of the virtual class-specific checklist using an online assessment questionnaire. RESULTS: In our institution, the number of faculty-led virtual classes has recently been on the increase. Our study revealed that most teachers agreed that virtual classes could break space and time limitations, but that the Internet environment could affect the fluency of the virtual class. They further agreed that the essential five steps in the checklist should vary depending on the type of teaching scenario. Most clinical teachers, with the exception of those who teach in the operating room, considered the operating room as the most difficult scenario for setting virtual classes. CONCLUSION: Faculty training for setting virtual classes is essential, and the essential virtual class-specific five steps are suitable for different teachers and teaching scenarios. However, the virtual class-specific checklist should be further adjusted according to the limitations caused by emerging innovative virtual teaching technology.

Airway function and respiratory resistance in Taiwanese coal workers with simple pneumoconiosis.

BACKGROUND: Occupational exposure to coalmine dust consisting of coal particles and free silica eventually results in massive lung fibrosis. However, clinical observations of patients with coal workers' pneumoconiosis (CWP) suggest that airway dysfunction may be a predominant feature in the initial development of the disease. METHODS: Forced expirogram, plethysmographic determination of lung volumes, and measurement of respiratory resistance (Rrs) by the forced oscillation technique at 3, 9, and 18 Hz were conducted in a sample of 71 coal miners with simple pneumoconiosis and 36 healthy subjects. RESULTS: The forced vital capacity (FVC) was well-preserved even in miners with category 2 and 3 CWP. There were no differences in the mean forced expiratory volume in 1 second (FEV1) values between healthy subjects and miners with category 1 disease. However, the level of airflow limitation in these miners increased with the transition from category 1 to category 2 and 3. The FEV1/FVC ratio fell below 70% in miners with category 2 and 3 disease, in both smokers and non-smokers. A consistent increase in the ratio of the residual volume to total lung capacity (RV/TLC) in the miners compared with that of the control workers was found. An abnormally high Rrs at 3 Hz (Rrs3) and frequency dependence in the flow resistance were also demonstrated in these subjects. There was an upward trend in the values of Rrs3 in the higher radiological categories. The correlation between respiratory conductance at this frequency (Grs3) and the RV/TLC ratio was good (r = - 0.763, p< 0.001). CONCLUSION: Simple CWP is not associated with a clinically apparent reduction in lung volume. The Rrs3 appears to be a sensitive parameter for detecting airway obstruction in patients with simple CWP associated or not with a reduced FEV1.

[Genetic diversity of AVR-pita alleles of rice blast fungus Magnaporthe grisea].

Rice blast, caused by fungus Magnaporthe grisea, is one of the most serious diseases of rice throughout the world and is also a classical system in which avirulence (AVR) genes in the pathogen show a functional correspondence with particular resistance (R) genes in rice. The interaction between AVR-pita gene in Magnaporthe grsiea and Pi-ta gene in rice is a classical gene-for-gene system. The genetic diversity of AVR-pita alleles was showed by 44 isolates from the fields in Sichuan and Chongqing. According to the published sequence of AVR-pita (GenBank Accession No. AF207841), the special primers were designed and a population analysis of AVR-pita occurrence in the field was conducted. The PCR negative isolates did not trigger host resistance responses and the disease might occur. The positive special PCR band in an isolate was not corresponding with its avirulence to the Pi-ta rice line. Among 11 sequenced A VR-pita alleles, six AVR-pita alleles encoded the same protein, four proteins differed from each other by one amino acid and one had nonsense mutation. The strategy of utilizing Pi-ta in rice breeding was also discussed.