Teclistamab in combination with daratumumab and lenalidomide in multiple myeloma (MajesTEC-2 study)

Introduction: Combination of daratumumab (Dara) and lenalidomide (Len) may enhance the function of teclistamab (Tec), potentially resulting in improved antimyeloma activity in a broader population. We present initial safety and efficacy data of Tec-Dara- Len combination in patients with multiple myeloma (MM) in a phase 1b study (MajesTEC-2;NCT04722146). Method(s): Eligible patients who received 1-3 prior lines of therapy (LOT), including a proteasome inhibitor and immune-modulatory drug, were given weekly doses of Tec (0.72-or- 1.5 mg/kg with step-up dosing) + Dara 1800 mg + Len 25 mg. Responses per International Myeloma Working Group criteria, adverse events (Aes) per CTCAE v5.0, and for cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) per ASTCT guidelines, were assessed. Result(s): 32 patients received Tec-Dara- Len (0.72 mg/kg, n = 13;1.5 mg/kg, n = 19). At data cut-off (11 July 2022), median follow-up (range) was 5.78 months (1.0-10.4) and median treatment duration was 4.98 months (0.10-10.35). Median age was 62 years (38-75);87.5% were male. Median prior LOT was 2 (1-3), 18.8% were refractory to Dara and 28.1% refractory to Len. CRS was most frequent AE (81.3% [n = 26], all grade 1/2), 95% occurred during cycle1. Median time to onset was 2 days (1-8), median duration was 2 days (1-22). No ICANS were reported. Frequent Aes (>=25.0% across both dose levels) were neutropenia (75.0% [n = 24];grade 3/4: 68.8% [n = 22]), fatigue (43.8% [n = 14];grade 3/4: 6.3% [n = 2]), diarrhoea (37.5% [n = 12];all grade 1/2), insomnia (31.3% [n = 10];grade 3/4: 3.1% [n = 1]), cough (28.1% [n = 9];all grade 1/2), hypophosphatemia (25.0% [n = 8];all grade 1/2), and pyrexia (25% [n = 8];grade 3/4: 6.3% [n = 2]). Febrile neutropenia frequency was 12.5% (n = 4). Infections occurred in 24 patients (75.0%;grade 3/4: 28.1% [n = 9]). Most common were upper respiratory infection (21.9% [n = 7]), COVID-19 (21.9% [n = 7]), and pneumonia (21.9% [n = 7]). Three (9.4%) had COVID-19 pneumonia. One (3.1%) discontinued due to COVID-19 infection and this patient subsequently died of this infection. Overall response rate (ORR, median follow-up) was 13/13 (8.61 months) at 0.72 mg/kg and 13/16 evaluable patients (less mature at 4.17 months) at 1.5 mg/kg. 12 patients attained very good/better partial response at 0.72 mg/kg dose, and response was not mature for 1.5 mg/kg group. Median time to first response was 1.0 month (0.7-2.0). Preliminary pharmacokinetic concentrations of Tec-Dara- Len were similar as seen with Tec monotherapy. Tec-Dara- Len- treatment led to proinflammatory cytokine production and T-cell activation. Conclusion(s): The combination of Tec-Dara- Len has no new safety signals beyond those seen with Tec or Dara-Len individually. Promising ORR supports the potential for this combination to have enhanced early disease control through the addition of Tec. These data warrant further investigation.

Framing blockchain-integrated digital twins for emergent healthcare management at local and city levels: A proof of concept

It has been witnessed that digital technology has the potential to improve the efficiency of emergent healthcare management in COVID-19, which however has not been widely adopted due to unclear definition and configuration. This research aims to propose a proof of concept of digital twins for emergent healthcare management through configuring the cyber and functional interdependencies of healthcare systems at local and city levels. Critical interdependencies of healthcare systems have been firstly identified at both levels, then the information and associated cyber and functional interdependencies embedded in seven critical hospital information systems (HISs) have been identified and mapped. The proposed conceptual digital twin-based approach has been then developed for information coordination amongst these critical HISs at both local and city levels based on permissioned blockchain to (1) integrate and manage the information from seven critical HISs, and further (2) predict the demands of medical resources according to patient trajectory. A case study has been finally conducted at three hospitals in London during the COVID-19 period, and the results showed that the developed framework of blockchain-integrated digital twins is a promising way to provide more accurate and timely procurement information to decision-makers and can effectively support evidence-based decisions on medical resource allocation in the pandemic. © 2023 ICE Publishing: All rights reserved.

Multi-Attentional U-Net for Medical Image Segmentation

Deep learning (DL) approaches for image segmentation have been gaining state-of-the-art performance in recent years. Particularly, in deep learning, U-Net model has been successfully used in the field of image segmentation. However, traditional U-Net methods extract features, aggregate remote information, and reconstruct images by stacking convolution, pooling, and up sampling blocks. The traditional approach is very inefficient due of the stacked local operators. In this paper, we propose the multi-attentional U-Net that is equipped with non-local blocks based self-attention, channel-attention, and spatial-attention for image segmentation. These blocks can be inserted into U-Net to flexibly aggregate information on the plane and spatial scales. We perform and evaluate the multi-attentional U-Net model on three benchmark data sets, which are COVID-19 segmentation, skin cancer segmentation, thyroid nodules segmentation. Results show that our proposed models achieve better performances with faster computation and fewer parameters. The multi-attention U-Net can improve the medical image segmentation results. © 2022 IEEE.

Successful ECMO course in an Acquired Immune Deficiency Syndrome (AIDS) patient with ARDS complicated by pneumocystis jirovecii pneumonia and COVID-19: A unique case

Objectives: Reviewing current literature and case reports of patients placed on Venous-Venous ECMO support for HIV and AIDS, with confection with Pneumocystis pneumonia and covid-19 pneumonia. The use of extracorporeal membrane oxygenation (ECMO) in patients who have acute respiratory distress syndrome has been shown to have very good outcomes. However, there is limited data to support the initiation of ECMO in patients who have human immunodeficiency virus infection with or without acquired immune deficiency syndrome. Method(s): We present a unique and challenging case of a 30 year old male, with no known past medical history, unvaccinated against covid-19, who presented with one week of progressive shortness of breath. On admission he was found with moderate bilateral infiltrates and was diagnosed with covid-19 pneumonia. Despite appropriate medical therapy, patient developed worsening hypoxic respiratory failure. Found to have elevated (1- 3)-7beta;-d-glucan and tested positive for HIV. CD4 count 11, HIV viral load 70,000. The patient remained severely hypoxemic despite mechanical ventilation, sedation, paralytics and proning. Venous venous extracorporeal membrane oxygenation was initiated. Considering his non improvement with variety of antivirals and antibiotics and with elevated (1-3)-7beta;-d-glucan in the setting of AIDS he was treated for presumed Pneumocystis pneumonia. The patient tolerated proning while on VV ECMO and his course was complicated with bilateral pneumothorax necessitating chest tube placement. Result(s): The patient successfully completed 64 days on VV ECMO, where he was treated for PCP pneumonia, covid pneumonia, CMV viremia and tolerated initiation of anti-retroviral therapy. Patient was successfully decannulated, and ultimately discharged from the hospital. Conclusion(s): VV-ECMO can be a beneficial intervention with successful outcomes in severely immunocomprimised patients with AIDS. This case highlights the importance of minimizing sedation and early mobilization on ECMO support. (Figure Presented).

Iterative Innovation Empowers the Training of High-level Interdisciplinary Medical Talents in the New Era: Experiences from School of Medicine, Zhejiang University

COVID-19 highlights the lack of interdisciplinary medical talents. The international history of medical education shows the urgent need of high-level interdisciplinary medical talents. Anchoring the goal to develop a global center of talents and highland of innovation, this article takes medical education of Zhejiang University as an example, focusing on and exploring the training mode of high-level interdisciplinary medical talents in the new era. It includes: Firstly, optimizing the training mode of eight-year program for medical doctors with non-medical bachelor degree followed with complete education for a medical doctorate that innovates the curriculum system of clinical medicine;secondly, creating the training system of postdoctor of clinical medicine and integrating medical resources that include high-quality talents and health care system, in order to build a high-quality teaching staff with a interdisciplinarity background and innovative bases. It not only strengthens the residents' competency and frontier creativity, but also ensures the sustainable development of interdisciplinary medical talents. The reform of training mode, curriculum system, teaching staff and clinical teaching bases all contribute to the goal of building a country with interdisciplinary talents that serve the frontier of science and technology in the world, the major needs of the country and people's health in the new era.Copyright © 2022, Peking Union Medical College Hospital. All rights reserved.

Mediating role of psychological resilience in relationship between stress and anxiety symptoms of medical students in post COVID-19 period

[Background] In the post-pandemic period, attention has been paid to the study of psychological stage changes in various groups. Under the stress of pandemics, how to control negative emotions such as anxiety symptoms will have an important impact on medical students' professional identity and future professional competence. [Objective] This study is designed to explore the characteristics of stress and anxiety symptoms of medical students in different stages of the post COVID-19 period, and potential mediating role of psychological resilience in the relationship between stress and anxiety symptoms. [Methods] By convenience sampling method, 3 000 medical students from three medical colleges in Shaanxi Province were selected and completed an online survey reporting the Self-Rating Anxiety Scale (SAS), Stress Scale for College Student (SSCS), and Resilience Scale of Adults (RSA) to assess their stress, psychological resilience, and anxiety symptoms in September and November 2020. SPSS 25.0 software was used to perform dependent-sample t test, variance analysis, Pearson correlation analysis, and mediating effect test (hierarchical regression analysis). [Results] A total of 2 894 valid questionnaires were recovered and the valid recovery rate was 96.5%. The overall scores of stress, psychological resilience, and anxiety symptoms of selected medical students were 56.61+/-17.17, 166.88+/-28.55, and 40.45+/-9.67, respectively in the post COVID-19 period. The positive rate of high stress was 72.2%, and the positive rate of anxiety symptoms was 16.0%. There were significant differences in anxiety symptoms scores between the high and the low stress level groups (42.16+/-9.92, 35.99+/-7.30) (P < 0.01). There were significant differences in scores of stress, psychological resilience, and anxiety symptoms among different grade groups (P < 0.01). The pearson correlation analysis results showed that the stress score was positively correlated with the anxiety symptom score (r=0.417, P < 0.01) and negatively correlated with the psychological resilience score (r=-0.344, P < 0.01);the psychological resilience score was negatively correlated with the anxiety symptom score (r=-0.495, P < 0.01). The hierarchical regression analysis results found that stress had a positive effect on anxiety symptoms (b=0.280, P < 0.01), and a negative effect on psychological resilience (b=-0.344, P < 0.01);psychological resilience negatively affected anxiety symptoms (b=-0.398, P < 0.01), and played a partial mediating role in the relationship between stress and anxiety symptoms (effect value was 0.137) that accounted for 32.8% of the total effect. [Conclusion] In the post COVID-19 period, medical students have a superposition of high stress and high anxiety symptoms. Psychological resilience is a protective factor for anxiety symptoms and plays a partial mediating role in the relationship between stress and anxiety symptoms.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

Long-Term Efficacy and Safety of Upadacitinib in Patients with Psoriatic Arthritis Refractory to Biologic Therapies: 2-Year Results from the Phase 3 Select-Psa 2 Study

Background/Aims Upadacitinib (UPA), an oral Janus kinase (JAK) inhibitor, demonstrated efficacy and safety in patients (pts) with psoriatic arthritis (PsA) and prior inadequate response or intolerance to >=1 biologic disease modifying antirheumatic drug (bDMARD) at week (wk) 56 in the phase 3 SELECT-PsA 2 study. We aimed to evaluate the efficacy and safety of UPA at wk 104 from the ongoing long-term extension of SELECTPsA 2. Methods Pts were randomized to UPA 15mg (UPA15), UPA 30mg (UPA30), or placebo (PBO) for 24 wks;PBO pts were then switched to UPA15 or UPA30. For continuous UPA treatment groups, efficacy endpoints at wk 104 were analyzed using non-responder imputation (NRI) and as observed (AO) (binary endpoints) or mixed-effect model repeated measures (MMRM) and AO (continuous endpoints). Treatmentemergent adverse events (TEAEs) were summarized for pts who received >=1 dose of study drug using visit-based cut-off at wk 104. Results A total of 641 pts received >=1 dose of study drug. At wk 104, 38.4% of all patients had discontinued study drug, with the highest discontinuation observed in patients randomized to PBO at baseline (all PBO: 46.7%). The most common reasons for discontinuation were lack of efficacy (UPA15: 12.3%, UPA30: 8.7%, all PBO: 21.7%) and adverse event (UPA15: 10.9%, UPA30: 13.3%, all PBO: 12.7%). The proportion of UPA pts that achieved ACR20/50/70, MDA, PASI75/90/100, and resolution of dactylitis and enthesitis were generally similar, or further improved, with 104 wks of treatment vs 56 wks. Similarly, mean change from baseline in HAQ-DI, patient's assessment of pain, BASDAI, and ASDAS was improved with UPA treatment. At 104 wks of therapy, clinical responses were largely similar with UPA15 and UPA30. Generally, safety data at wk 104 were consistent with that reported at wk 56. Rates of serious infection, herpes zoster, hepatic disorder, anemia, neutropenia, lymphopenia, and CPK elevation remained numerically higher with UPA30 vs UPA15, while rates of malignancies, MACE, and VTE were similar for both UPA groups. One death was reported with UPA15 (unexplained due to lack of information;however, the patient had recently been diagnosed with ovarian cancer) and two with UPA30 (pancytopenia and COVID-19 pneumonia). Conclusion In PsA pts with prior inadequate response or intolerance to>=1 bDMARD, clinical responses were maintained with UPA15 and UPA30 up to two years of treatment. No new safety signals were identified in this long-term extension.

Comparison of the Effectiveness of Different Covid-19 Vaccines among Plwh

Background: Previous studies have demonstrated promising serologic responses in PLWH receiving a third dose of vaccine against SARS-CoV-2. However, real-world clinical effectiveness, especially during the pandemic caused by B.1.1.529 variant, remains less investigated. Method(s): PLWH seeking HIV care at our hospital from 2021/6 to 2022/6 were included and advised to receive the third dose of COVID-19 vaccine. Individuals were excluded from this study if they had been previously diagnosed with COVID-19. Different types of COVID-19 vaccines were available in the vaccination program, including BNT162b2, mRNA-1273 (either 50 or 100 mug), MVC-COV1901 and NVX-CoV2373 vaccines. PLWH were screening for the occurrence of COVID-19 through the reporting system of notifiable diseases of Taiwan CDC, and were tested for anti-nucleocapsid (anti-N) IgG every 1 to 3 months. Participants were followed for 180 days until the fourth dose of COVID-19 vaccination, occurrence of SARS-CoV-2 infection, seroconversion of anti-N IgG, death, or loss to follow-up, whichever occurred first. Result(s): 1,496 PLWH were included: 631 (42.2%) receiving 100 mug mRNA-1273 vaccine, 468 (31.3%) 50 mug mRNA-1273 vaccine, and 328 (21.9%) BNT162b2 vaccine, 65 (4.3%) MVC-COV1901 vaccine, and 4 (0.3%) NVX-CoV2373 vaccine for the third dose of SARS-CoV-2 vaccination. 297 (19.9%) PLWH were diagnosed with COVID-19 during the follow-up period, including 92 (14.6%) who received 100 mug mRNA-1273, 111 (23.7%) 50 mug mRNA-1273, 79 (24.1%) BNT162b2 and 15 (21.7%) either MVC-COV1901 or NVX-CoV2373;in addition, 98 PLWH had seroconversion of anti-N IgG during follow-up, including 23, 50, 19 and 6 PLWH who received 100 mug mRNA-1273, 50 mug mRNA-1273, BNT162b2, and either MVC-COV1901 or NVX-CoV2373, respectively. Similar rates of new infection with SARS-CoV-2 or seroconversion of anti-N IgG were demonstrated regardless the vaccine type of the third dose (log-rank test, p=0.46). Factors associated with a diagnosis of SARS-CoV-2 infection and seroconversion of anti-N IgG included an age >50 years (aOR, 0.67;95% CI, 0.49-0.91) and newly infected with hepatitis C virus (HCV) (aOR, 1.41;95% CI, 1.09-1.83). Conclusion(s): Our study demonstrated that clinical effectiveness of the third dose of different vaccines available to PLWH was similar in preventing SARSCoV- 2 infection or seroconversion of anti-N IgG Taiwan. PLWH aged less than 50 years and those with newly diagnosed HCV infection were at higher risk of acquiring COVID-19. Kaplan-Meier survival curve for acquiring COVID-19 or seroconversion of anti-N IgG in PLWH receiving different COVID-19 vaccination of the third dose (log-rank test, 4 groups, p = 0.46).

The Development and Implementation of Online Video-based Simulation Training on Strengthening Pre-service Teachers' Competence in Bullying Intervention

COVID-19 has severely impacted the world since December 2019, and because of its highly infectious nature, many countries around the world have taken lockdown measures to prevent the virus from spreading unchecked, resulting in ramifications for higher education as many institutions have been forced to implement distance education. The question of how to develop a teaching method suitable for teacher education programs that place particular importance on practice in classroom settings warrants particular concern. Online video-based simulation training (OVST) as a teacher training method holds promise for addressing this issue by allowing learners to increase their opportunities to apply theory-based knowledge in real educational practice, reducing the theory-practice gap. OVST can also be distributed through online learning environments that offer easily repeated large-scale usage at lower cost to a variety of introvert/extravert learners through individual learning trajectories. In this vein, this study aims to introduce a method for developing OVST used to enhance pre-service teacher competence (by immediately intervening during school bullying, or CIISB) and clarifying the efficacy of types of OVST (with and without debriefing) on strengthening pre-service teachers' CIISB skills. A total of 98 pre-service teachers from four Taiwanese universities and colleges participated in this study that adopted a quasi-experimental design approach. Each of these pre-service teachers was assigned to one of three groups: OVST with debriefing, OVST without debriefing, and an OVST control condition, with a video-based instrument used to map pre-service teachers' CIISB-related perception, interpretation, and decision-making skills (PID skills). The results of a mixed-model two-way ANOVA analysis indicated that both types of OVST were more effective than the control condition in improving pre-service teachers' CIISB. OVST with debriefing was also more effective than the OVST without debriefing, suggesting that OVST with debriefing is a promising way to develop pre-service teachers' clinical competencies, while also offering a valuable resource for teacher education training methods, particularly when conducted under pandemic conditions.

NF-Heart: A Near-field Non-contact Continuous User Authentication System via Ballistocardiogram

The increasingly remote workforce resulting from the global coronavirus pandemic has caused unprecedented cybersecurity concerns to organizations. Considerable evidence has shown that one-pass authentication fails to meet security needs when the workforce work from home. The recent advent of continuous authentication (CA) has shown the potential to solve this predicament. In this paper, we propose NF-Heart, a physiological-based CA system utilizing a ballistocardiogram (BCG). The key insight is that the BCG measures the body's micro-movements produced by the recoil force of the body in reaction to the cardiac ejection of blood, and we can infer cardiac biometrics from BCG signals. To measure BCG, we deploy a lightweight accelerometer on an office chair, turning the common chair into a smart continuous identity "scanner". We design multiple stages of signal processing to decompose and transform the distorted BCG signals so that the effects of motion artifacts and dynamic variations are eliminated. User-specific fiducial features are then extracted from the processed BCG signals for authentication. We conduct comprehensive experiments on 105 subjects in terms of verification accuracy, security, robustness, and long-term availability. The results demonstrate that NF-Heart achieves a mean balanced accuracy of 96.45% and a median equal error rate of 3.83% for CA. The proposed signal processing pipeline is effective in addressing various practical disturbances.

Hierarchical Multi-agent Model for Reinforced Medical Resource Allocation with Imperfect Information

With the advent of the COVID-19 pandemic, the shortage in medical resources became increasingly more evident. Therefore, efficient strategies for medical resource allocation are urgently needed. However, conventional rule-based methods employed by public health experts have limited capability in dealing with the complex and dynamic pandemic-spreading situation. In addition, model-based optimization methods such as dynamic programming (DP) fail to work since we cannot obtain a precise model in real-world situations most of the time. Model-free reinforcement learning (RL) is a powerful tool for decision-making;however, three key challenges exist in solving this problem via RL: (1) complex situations and countless choices for decision-making in the real world;(2) imperfect information due to the latency of pandemic spreading;and (3) limitations on conducting experiments in the real world since we cannot set up pandemic outbreaks arbitrarily. In this article, we propose a hierarchical RL framework with several specially designed components. We design a decomposed action space with a corresponding training algorithm to deal with the countless choices, ensuring efficient and real-time strategies. We design a recurrent neural network-based framework to utilize the imperfect information obtained from the environment. We also design a multi-agent voting method, which modifies the decision-making process considering the randomness during model training and, thus, improves the performance. We build a pandemic-spreading simulator based on real-world data, serving as the experimental platform. We then conduct extensive experiments. The results show that our method outperforms all baselines, which reduces infections and deaths by 14.25% on average without the multi-agent voting method and up to 15.44% with it.

Exploration of Potential Biomarkers and Mechanisms for COVID-19 and Asthma Based on Microarray Analysis

Aims: The aim of this study is to investigate the potential mechanisms of coronavirus disease (COVID-19) and asthma comor-bidities.Methods: GSE147507 and GSE143303 datasets were obtained from the Gene Expression Omnibus (GEO) database, the differ-ential expressed genes (DEGs) were identified, and the overlapping DEGs were obtained by determining the DEG intersection between the two datasets. A series of analyses of the shared DEGs were performed, including enrichment analysis, protein -protein interaction (PPI) network construction, construction of transcription factor (TF)/microRNA (miRNA)-gene interaction networks, drug-gene and disease-gene interactions, and receiver operating characteristic curve (ROC) analysis.Results: A total of 135 overlapping DEGs were obtained by determining the DEGs intersection between the GSE147507 and GSE143303 datasets. These overlapped DEGs were significantly enriched in the regulation of DNA-templated transcription, initi-ation, clathrin-sculpted gamma-aminobutyric acid transport vesicle, DNA binding, and eight KEGG (kyoto encyclopedia of genes and genomes) pathways. The PPI network revealed that HSPA8, SRSF1, NDUFAB1, PTEN, CCT8, HIST1H2BK, HIST2H2BE, DLAT, EIF3G, and WAC, with high scores, were the hub genes. In addition, 65 TFs (transcription factors) and 369 miRNAs tar-geted overlapping DEGs. Finally, these overlapped DEGs were also related to other diseases, such as hyperglycemia, metabolic acidosis, and lung neoplasm, and the top 10 drugs with the most significant potential included lanatoside C, digoxin, GW-8510, doxorubicin, daunorubicin, proscillaridin, anisomycin, helveticoside, ouabain, and bisacodyl. The ROC analysis results shown that these hub genes had good diagnostic performance.Conclusions: HSPA8, SRSF1, NDUFAB1, PTEN, CCT8, HIST1H2BK, HIST2H2BE, DLAT, EIF3G, WAC, FOXC1, GATA2, hsa-miR-93-5p, and hsa-miR-17-5p may play vital roles in COVID-19 (corona virus disease-2019)/asthma comorbidity. Lanatoside C, digoxin, GW-8510, doxorubicin, daunorubicin, proscillaridin, anisomycin, helveticoside, ouabain, and bisacodyl may serve as drug targets against COVID-19/asthma comorbidity.

Enhancing service quality of rural public transport during the COVID-19 pandemic: a novel fuzzy approach

In order to encourage the use of public transportation, it is necessary to make it more appealing to commuters by conducting frequent Service Quality (SQ) evaluations and modifications. Understanding passengers' expectations of public transportation are important, and evaluating the SQ is an essential tool for assessing the overall performance of the public transportation system. The purpose of the present study was to examine the expectations and perceptions of core passengers regarding SQ in public bus transportation. By surveying 598 passengers in rural public transportation in India, the study results are illustrated and further discussed to guide possible bus SQ improvements in rural areas. In addition, the impact of these expectations and perceptions on satisfaction levels of rural public bus transportation services are explored by applying the Interval-Valued Pythagorean Fuzzy (IVPF). The outcomes of the survey indicated significant disparities among expectations and perceptions of passengers, as well as widespread dissatisfaction with the delivery of bus services in rural areas as a whole. The dependability and adaptiveness of the bus service have been critical in describing the overall quality of bus services in rural areas, and best practices from around the world were used to develop a set of recommendations for transportation operators and local officials. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Research on the time-varying effects among green finance markets in China: A fresh evidence from multi-frequency scale perspective

Green finance is an essential instrument for achieving sustainable development. Objectively addressing correlations among different green finance markets is conducive to the risk management of investors and regulators. This paper presents evidence on the time-varying correlation effects and causality among the green bond market, green stock market, carbon market, and clean energy market in China at multi-frequency scales by combining the methods of Ensemble Empirical Mode Decomposition Method (EEMD), Dynamic Conditional Correlation (DCC) GARCH model, Time-Varying Parameter Vector Autoregression with Stochastic Volatility Model (TVP-VAR-SV), and Time-varying Causality Test. In general, the significant negative time-varying correlations among most green finance markets indicate a prominent benefit of risk hedging and portfolio diversification among green financial assets. In specific, for different time points and lag periods, the green finance market shock has obvious time-varying, positive and negative alternating effects in the short-term scales, while its time delay and persistence are more pronounced in the medium-term and long-term scales. Interestingly, a positive event shock will generate positive connectivity among most green finance markets, whereas a negative event including the China/U.S. trade friction and the COVID-19 pandemic may exacerbate the reverse linkage among green finance markets. Furthermore, the unidirectional causality of "green bond market - carbon market - green stock and clean energy markets” was established during 2018–2019. © 2023

A Data-Driven Context-Aware Health Inference System for Children during School Closures

Many countries have implemented school closures due to the outbreak of the COVID-19 pandemic, which has inevitably affected children's physical and mental health. It is vital for parents to pay special attention to their children's health status during school closures. However, it is difficult for parents to recognize the changes in their children's health, especially without visible symptoms, such as psychosocial functioning in mental health. Moreover, healthcare resources and understanding of the health and societal impact of COVID-19 are quite limited during the pandemic. Against this background, we collected real-world datasets from 1,172 children in Hong Kong during four time periods under different pandemic and school closure conditions from September 2019 to January 2022. Based on these data, we first perform exploratory data analysis to explore the impact of school closures on six health indicators, including physical activity intensity, physical functioning, self-rated health, psychosocial functioning, resilience, and connectedness. We further study the correlation between children's contextual characteristics (i.e., demographics, socioeconomic status, electronic device usage patterns, financial satisfaction, academic performance, sleep pattern, exercise habits, and dietary patterns) and the six health indicators. Subsequently, a health inference system is designed and developed to infer children's health status based on their contextual features to derive the risk factors of the six health indicators. The evaluation and case studies on real-world datasets show that this health inference system can help parents and authorities better understand key factors correlated with children's health status during school closures. © 2023 ACM.

Correlation between glycocalyx and diseases, and progress in its degradation mechanism

With the burgeoning development of glycobiology, a growing body of research shows a significant relationship between the development of various diseases and polysaccharides. Glycocalyx, an important component of the vascular endothelium, has a villi-like structure and plays a highly crucial role in maintaining vascular homeostasis. In-depth multidisciplinary studies have further revealed that the biological functions of glycocalyx are not only limited to vascular homeostasis, but are also closely related to various diseases in vivo. Foundations of glycocalyx composition and biological function, this paper reviews the latest research of glycocalyx biodegradation mechanism from the perspective of biological relevance of glycocalyx main components [heparan sulfate (HS), chondroitin sulfate (CS), hyaluronic acid (HA) and core protein] to cancer, corona virus disease 2019 (COVID-19), trauma surgery and other diseases by visualization and molecular biology experimental methods, and intends to provide new thoughts for clinical development of novel diagnostic methods and therapeutic targets.

This work was supported by the National Institute of Neurological Disorders and Stroke of the National Institutes of Health under award number P50NS108676 and Moore Foundation

The increasingly remote workforce resulting from the global coronavirus pandemic has caused unprecedented cybersecurity concerns to organizations. Considerable evidence has shown that one-pass authentication fails to meet security needs when the workforce work from home. The recent advent of continuous authentication (CA) has shown the potential to solve this predicament. In this paper, we propose NF-Heart, a physiological-based CA system utilizing a ballistocardiogram (BCG). The key insight is that the BCG measures the body's micro-movements produced by the recoil force of the body in reaction to the cardiac ejection of blood, and we can infer cardiac biometrics from BCG signals. To measure BCG, we deploy a lightweight accelerometer on an office chair, turning the common chair into a smart continuous identity "scanner". We design multiple stages of signal processing to decompose and transform the distorted BCG signals so that the effects of motion artifacts and dynamic variations are eliminated. User-specific fiducial features are then extracted from the processed BCG signals for authentication. We conduct comprehensive experiments on 105 subjects in terms of verification accuracy, security, robustness, and long-term availability. The results demonstrate that NF-Heart achieves a mean balanced accuracy of 96.45% and a median equal error rate of 3.83% for CA. The proposed signal processing pipeline is effective in addressing various practical disturbances. © 2023 ACM.

Epidemiological characteristics and disease spectrum analysis of outpatients in the dermatology department of a hospital in Wuhan during the COVID-19 epidemic.

Objective: To investigate epidemiological characteristics of outpatients and disease spectrum in the dermatology department during the COVID-19 epidemic Methods: A retrospective comparison of outpatient visits, gender, age and disease types in the dermatology department of Wuhan No.1 Hospital was performed between COVID-19 epidemic period (from 23th January 2020 to 15th April 2020) and the same period in 2019. Enumeration data were analyzed by Pearson's chi-square test. Result(s): During the COVID-19 epidemic, the number of outpatient visits to the dermatology department of the hospital decreased markedly, and the average daily number of outpatient visits (236 visits/day) was only 8.81% of that during the same period in 2019 (2 678 visits/day) ;the ratio of male to female patients was reversed from 1:1.37 in 2019 to 1.16:1 in 2020;the proportions of patients aged 0-6, 7-12, 13-17 and 18-45 years significantly decreased compared with those in 2019 (all P < 0.001), and the proportions of patients aged 46-69 and > 69 years significantly increased (both P < 0.001). During the COVID-19 epidemic, there were 171 types of skin diseases in the dermatology outpatient department, and the number of disease categories decreased compared with that during the same period in 2019 (442 types) ;the number of patient visits for allergic skin diseases, erythematous papulosquamous skin diseases, viral infectious skin diseases and bacterial infectious skin diseases significantly increased compared with that during the same period in 2019 (all P < 0.001), while the number of patient visits for sebaceous and sweat gland disorders, pigmented skin diseases and physical skin diseases significantly decreased (all P < 0.001). Conclusion(s): Compared with the same period in 2019, the number of outpatient visits, patient sex ratio, age distribution and disease types in the dermatology department have undergone marked changes during the COVID-19 epidemic, and this study provides a reference for healthcare workers in dermatology department to respond to various epidemics and natural disasters in the future.Copyright © 2021 by the Chinese Medical Association.

A systematic review of factors influencing student interest in online homework

Online homework has been emerging with the popularity of online learning. The significance of online homework has been recognised, especially during the outbreak of COVID-19. Although it is regarded as one homework format, studies explicitly targeted at online homework are limited till now, particularly in student interest. As interest is defined as the driver of student learning, it is important to explore the factors influencing student interest in online homework to promote this technology use. Thus, a systematic review of the literature was conducted to identify studies on student interest in online homework with the guide of PRISMA. Based on 23 selected studies, this study unveiled the included studies' characteristics and the informed factors influencing student interest in the online homework system or the homework assigned or completed online. The findings of this study showed that background variables, adult guidance and monitoring, and the role of students in the process impact student interest in online homework. As online homework is delivered via technology, other factors, such as content design, the ability of technology use and homework submission methods, are also associated with student interest in online homework. Relevant educational implications are elaborated. Further studies and limitations are also included in this study. © The Author(s).