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Background Nurses have a primary role in providing palliative and end-of-life (EOL) care. Their knowledge of EOL care, attitudes toward care of the dying, and palliative care self-efficacy are important in care delivery. Little is known regarding palliative care preparedness among Mongolian nurses. This study examines palliative care knowledge, attitude towards death and dying, and self-efficacy among Mongolian nurses, and examines predictors of self-efficacy. Methods A cross-sectional descriptive study was conducted. Participants were 141 nurses employed at the National Cancer Center in Mongolia. Data was collected using a self-administered questionnaire. Results The median score for the knowledge of palliative care was 8.0/20. “Psychosocial and spiritual care” was the lowest score on the palliative care knowledge subscale. The mean score for attitude toward care of the dying was 69.1%, indicating positive attitudes. The mean score for the palliative care self-efficacy was 33.8/48. Nurses reported low self-efficacy toward communicating with dying patients and their families, and managing delirium. Palliative care knowledge and duration of experience as an oncology nurse significantly predicted self-efficacy toward palliative care, accounting for 14.0% of the variance. Conclusions Palliative education for nurses should address the knowledge gaps in EOL care and focus in increasing palliative care self-efficacy. Considering palliative care knowledge and nursing experience as an oncology nurse were significant predictors of self-efficacy toward palliative care, more effort is needed to fill the knowledge gaps in EOL care among nurses, especially for less experienced nurses.

Moving beyond the direct support all alone by a human teacher or an Artificial Intelligence (AI) system, optimizing the complementary strengths of the two has aroused great expectations and educational innovation potential. Yet, the conceptual guidance of how best to structure and implement teacher-AI collaboration (TAC) while ensuring teachers' instructional roles to support students learning remains limited. This study, therefore, aims what (1) curriculum, (2) teacher-AI interaction, (3) learning environment would be required as well as how TAC would evolve by reflecting teachers' views. Through in-depth interviews with 20 Chinese leading teachers in AI in Education (AIED), the study found that teachers aimed to improve students' subject-matter knowledge and build their capacity as the desired goals for TAC and these can be carried out by data-driven problem-based learning and case-based reasoning in tandem with growth-focused and reflective assessment. While teachers highlighted that developing teachers' data literacy and collegiality with AI are essential, they expected AI to be equipped with Technological Pedagogical and Content Knowledge (TPACK) knowledge and conflict resolution skills. In addition, teachers expressed that Internet of Things (IoT)-based classrooms, systematic AIED curriculum, school-based continuing professional development, research-practice-policy partnerships as well as creating a continuous learning and AI-ready culture are significant. Furthermore, teachers envision TAC would develop into three stages: (1) teachers as passive AI recipients, (2) teachers as active AI users (3) teachers-AI as constructive partners. These findings build a more holistic and in-depth understanding of the AIED and offer implications for the educational AI design and teachers' education.

It is necessary to identify factors that influence nurses' intention to care for coronavirus disease 2019 (COVID-19) patients to improve the quality of care during the pandemic. This study identifies factors that influence nurses' intention to care for COVID-19 patients, focusing on positive psychological capital and nursing professionalism. This study adopted a descriptive correlational design. Data were collected between August 16 and August 30, 2020, through self-administered questionnaires from 148 bedside nurses caring for COVID-19 patients, from four hospitals designated for COVID-19 treatment. Modified versions of the Nursing Intention Questionnaire for SARS Patient Care, Psychological Capital Questionnaire, and Hall's Professional Inventory were used. The collected data were analyzed using stepwise multiple regression. In total, 165 questionnaires were distributed, and 148 questionnaires (89.7%) were included in the final analysis. Factors influencing nurses' intention to care were: age (30<: β = .18, p = .026; ≥50: β = .23, p = .005), department (ICU: β = -.26, p = .001), sufficient clinical experience and skills to care for COVID-19 patients (sufficient: β = .18, p = .019), and positive psychological capital (β = .22, p = .044). The model's explanatory power (R2) was 48%. Strategies to increase nurses' positive psychological capital are necessary to improve nursing care quality by increasing intention to care when facing novel infectious diseases such as COVID-19. Furthermore, adequate education and training on managing novel infectious diseases should be implemented to provide nurses with relevant experience and skills regarding caring for patients infected with these diseases. Through various studies, strategies for improving nurses' positive psychological capital need to be suggested to improve the quality of care by increasing the nurses' intention to care during the emergence of a novel infectious disease, such as COVID-19. Additionally, adequate education and training on managing the novel infectious diseases, sufficient for the nurses to believe they have the experience and skills for caring for the infected patients, will be needed.

The aim of this study was to investigate the mediating effects of health literacy on the relationship between frailty and health-related quality of life (HRQOL) among community-dwelling older adults. This study used the Korean Frailty and Aging Cohort Database (KFACD) for secondary data analysis. We selected data from 1,631 people without missing main variable values for analysis. Frailty was determined based on the modified Fried's phenotype [MFP], and HRQOL was measured using the Korean version of the 5-level EuroQol questionnaire (EQ-5D-5L). Health literacy was assessed using the questions on the Behavioral Risk Factor Surveillance System (BRFSS) used by the U.S. Center for Disease Control and Prevention. To examine the mediating role of health literacy in the relationship between frailty and HRQOL, Baron & Kenny's three-step mediating effect verification method was utilized. The participants had a mean frailty score of 1.37±1.02, health literacy score of 8.56±2.59, and HRQOL score of 0.84±0.10. Frailty was negatively correlated with health literacy (r = -0.27, p < .001) and HRQOL (r = -0.32, p < .001), while health literacy was positively correlated with HRQOL (r = 0.34, p < .001). We observed that health literacy played a partial mediating role in the relationship between frailty and HRQOL. To increase older adults' HRQOL, measures that directly prevent and manage frailty as well as interventions that target the enhancement of health literacy are needed.

We aimed to develop the Korean Hospital Frailty Risk Score (K-HFRS) by applying the International Classification of Diseases-10 codes to community-dwelling older adults' medical data. We selected data from 2,761 people with no missing main variable values from the Korean Frailty and Aging Cohort Data (KFACD) and National Health Insurance Database (NHID) for analysis. Frailty was determined based on modified Fried's phenotype [MFP] and Korean Frailty Index for Primary Care [KFI-PC] in the KFACD. A previously established method calculated the K-HFRS, verified by the area under the receiver operating characteristic (ROC) curve. The calculated cutoff value predicted the medical use. The respective K-HFRSs of the frailty group using the MFP and KFI-PC criteria ranged from 3.64 (±3.03) to 8.15 (±5.72) and 4.07 (±3.42) to 9.10 (±6.28), with 7.67 (±5.40) and 8.59 (±6.03) when four diagnoses were included. The K-HFRS of the frailty group using the KFI-PC criteria was higher than that using the MFP criteria. With four diagnoses included using the MFP criteria, the adjusted odds ratio (OR) for medical expenditures in the frailty group compared to the non-frailty group was 3.01 (95% confidence interval [CI] 2.52-3.60, p < .001); for the number of emergency room (ER) visits was 2.19 (95% CI 1.77-2.70, p < .001); for inpatient days was 2.48 (95% CI 2.08-2.96, p < .001). With four diagnoses included using the KFI-PC criteria, the adjusted OR value for medical expenditures was 2.77 (95% CI 2.35-3.27, p < .001); for the number of ER visits was 1.87 (95% CI 1.51-2.32, p < .001); for inpatient days was 2.07 (95% CI 1.75-2.45, p < .001). This study substantiated that the K-HFRS can measure frailty efficiently at a lower cost. Follow-up studies are needed for additional validity.

Presently, human papillomavirus (HPV)-based cervical cancer screening is commonly used and is replacing conventional cytology screening tests. The HPV genotyping assay is useful for triage in cervical cancer screening and the evaluation of HPV vaccination effects. In this study, we evaluated the clinical performance of two HPV genotyping assays, BD Onclarity HPV (Onclarity) and Seegene Anyplex II HPV28 (Anyplex) in the detection of relevant cervical lesions and for HPV genotyping concordance. Anyplex and Onclarity assays were performed on 920 consecutive liquid-based specimens. Anyplex, sensitivity, specificity, and genotyping concordance with Onclarity were optimal when restricted to ≥2+ (medium) viral loads. HPV genotyping agreement between the two assays ranged between 0.75 and 0.9 (excellent), except for HPV 33/58, which was 0.73 (good). With Onclarity as a reference, the relative sensitivity of Anyplex for the detection of ≥CIN 2 was 1.05 (95% CI: 0.99–1.1) and the relative specificity for detection of negative for intraepithelial lesion and malignancy (NILM) was 0.89 (95% CI: 0.85–0.93). For most ≥CIN 2 lesions, high-risk HPV was detected by Onclarity (66/72) and Anyplex (69/72) assays. For high-risk HPV negative ≥CIN 2 lesions, possible high-risk HPV genotypes were detected by Anyplex. In conclusion, the genotyping agreement between the tests was good to excellent. Full genotyping with Anyplex might confer additional benefits to patients with ≥CIN 2, although the difference is small. We also suggest an optimal cutoff value when reporting HPV infections using the Anyplex assay (≥2+; medium viral loads).

This study investigated the influence of patient-centeredness on patient safety perception among inpatients, with particular focus on the relationships between subfactors of patient-centeredness and patient safety perception. Data were collected from 122 inpatients in a university hospital from September 24 to October 8, 2019. Patient-centeredness was evaluated using the Patient-Centeredness Assessment Scale; patient safety perception was evaluated using the Korean version of the Patient Safety Perception Scale. Multiple linear regression analysis was conducted using SPSS for Windows 24.0. Average patient-centeredness score among inpatients was 77.14 ± 12.64 (range 0-100), and average patient safety perception score was 99.24 ± 15.90 (range 24-120). Patient-centeredness influenced patient safety perception (R2 = 70%, F = 27.75, p < .001). With respect to subfactors of patient safety perception, the medical team's activities to ensure safety was affected by the general treatment process and overall evaluation of patient-centeredness (R2 = 54%, F = 13.14, p < .001); patient safety practice was influenced only by the general treatment process (R2 = 39%, F = 7.02, p < .001); and trust in the medical system was affected by nurses' service, the general treatment process, and the hospital environment (R2 = 44%, F = 8.49, p < .001). To enhance patient safety perception, strategies should seek to strengthen patient-centeredness and its related subfactors, particularly the general treatment process, the hospital environment, and nurses' service.

We investigated the polarity dependence of a capacitive energy management circuit in a triboelectric nanogenerator (TENG) power system. In a half-wave rectifying circuit, the Simulation Program with Integrated Circuit Emphasis and analytical models show that the charge dump to the load varied depending on the polarity of the rectifying circuit even with the same charge output from TENG. Depending on the polarity of the rectifying circuit, a fast saturation of the direct current (DC) output voltage or a high DC output voltage was obtained. Experiments with a half-wave rectifier and Bennet doubler confirmed our simulation and theoretical results. The charge dump from the minimum capacitance of the separated TENG to the load capacitance and the charge dump from the maximum capacitance of the contacted TENG to the load resulted in asymmetric charging behavior. We concluded that it is necessary to analyze the TENG and the capacitive energy management circuit as a single system rather than considering them as independent units in the rectifying circuit of the TENG. This work can provide insights for the design of triboelectric energy harvesting systems.

Peroxisomes are highly metabolic, autonomously replicating organelles that generate reactive oxygen species (ROS) as a by-product of fatty acid β-oxidation. Consequently, cells must maintain peroxisome homeostasis, or risk pathologies associated with too few peroxisomes, such as peroxisome biogenesis disorders, or too many peroxisomes, inducing oxidative damage and promoting diseases such as cancer. We report that the PEX5 peroxisome import receptor binds ataxia-telangiectasia mutated (ATM) and localizes this kinase to the peroxisome. In response to ROS, ATM signalling activates ULK1 and inhibits mTORC1 to induce autophagy. Specificity for autophagy of peroxisomes (pexophagy) is provided by ATM phosphorylation of PEX5 at Ser 141, which promotes PEX5 monoubiquitylation at Lys 209, and recognition of ubiquitylated PEX5 by the autophagy adaptor protein p62, directing the autophagosome to peroxisomes to induce pexophagy. These data reveal an important new role for ATM in metabolism as a sensor of ROS that regulates pexophagy. Zhang et al. report that in response to ROS, ATM regulates peroxisome homeostasis through the phosphorylation of PEX5, which is then ubiquitylated and can be recognized by p62 to specifically activate pexophagy.

Deep learning approaches are widely employed for forecasting short-term travel demand to respond to real-time demand. Although it is critical for demand forecasting to be evenly distributed in the spatial and temporal views to support real-time mobility service operations, in related studies, the predictive performance of models has been evaluated only in terms of aggregated errors. Therefore, the present study was conducted to investigate the distribution of errors to explore spatiotemporal correlations. Six deep learning models with the same architecture, except for the base module, consisting of three stacked layers, were constructed. These models were used to forecast demands for a station-based bike-sharing service in Seoul, South Korea. To attain our goals, global and local Moran’s I of the errors was introduced to evaluate the spatial and temporal performances of the deep learning approaches. The results showed that the model with convolutional long short-term memory layers, which are effective at predicting spatiotemporal data, outperformed the other models in terms of aggregated performance. However, the global Moran’s I of the errors in the model reflects spatial dependency over the regions. This suggests that the best predictive performance of the model does not necessarily imply that it performs well in demand forecasting in all regions. Furthermore, cluster and outlier analyses of the errors indicated that excessive or insufficient predictions were clustered or dispersed throughout the regions. These results can be used to enhance the model by introducing the spatial correlation index into the loss function or by incorporating additional features for handling spatial correlations.