What StudentsWant to Have in the Post-Pandemic?: A Study about Computing Science Study Preferences and Mode of Study in Southeast Asia

After two years of online learning, minor changes happened in some tiny places which we may not always notice. These changes may impact the school management, education arrangement, and curriculum design: what do students expect from their teachers, and the school? Are they expecting forever online learning, and getting their degree completely online? In this study, we examined 93 final-year students from the school of computing science which mainly used work-based learning applied to learn pedagogy. We analyze their viewpoint on how COVID-19 changed their understanding of teaching and learning: what is the role of teachers and students? And how do they see the arrangement for the internship program? We found that over 92% of students agree that a creditable degree can better secure a job;over 68% of the students believed that face-to-face teaching is still a better choice, but at the same time, over 73% wish to have the materials recorded so that they can access them at their convenience time. We also examined some of the course design elements, especially those related to the internship program, to achieve a possible curriculum improvement for the students in the Asia Pacific region. © 2022 ACM.

Air quality changes in Shijiazhuang during COVID-19 outbreak

[Background] The coronavirus disease 2019 (COVID-19) was first detected in December 2019. To combat the disease, a series of strict measures were adopted across the country, which led of improved air quality. This provides an opportunity to discuss the impact of human activities on air quality. [Objective] This study investigates the air quality changes in Shijiazhuang, and analyzes the impacts of epidemic prevention and control measures on air quality, so as to provide reference and ideas for further improving air quality and prevention and control measures. [Methods] The air quality data were collected online from https://www.zq12369.com/ and https://aqicn.org/city/shijiazhuang/cn/. Comparisons in air quality index (AQI) and the concentrations of air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3) were made between the period from December 2019 to June 2020 (reference) and the same period from 2016 to 2019 by t-test and chi-square test. [Results] The daily average AQI dropped by 25.38% in Shijiazhuang during the COVID-19 prevention and control compared with the some period from 2016 to 2019 (t=6.28, P < 0.05). The proportions of pollution days during the COVID-19 outbreak in Shijiazhuang were PM2.5 (44.56%), O3 (31.09%), PM10 (23.83%), and NO2 (2.59%) successively, the pollution days of PM10 decreased significantly (chi2=3.86, P < 0.05) compared with 2016-2019, but during traffic lockdown the numbers of pollution days of PM2.5 and in the mid stage of prevention the number of pollution days of O3 increased (P < 0.05). Compared with the control period, the concentrations of the six air pollutants decreased to varying degrees (P < 0.05), especially SO2 dropped by 55.36%. [Conclusion] The measures taken for COVID-19 control and prevention have reduced the pollution sources and emissions, which resulted in better general air quality of Shijiazhuang City, but have aggravated the pollution of O3 and other pollutants. It is necessary to further explore the causes for the aggravation of O3 pollution in order to formulate reasonable air quality control strategies.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

Research on the privacy concept of higher education groups in China under the COVID-19 epidemic situation

Since the outbreak and spread of COVID-19 all over the world, many countries, including China, are taking measures for epidemic prevention and control, and some measures require citizens to provide personal privacy information. In the era of big data, it is worth paying attention to how people view the collection of personal privacy data under the special background that China collects personal information to better fight against the COVID-19 epidemic. In particular, it is of great significance and value to explore the privacy concept of Chinese higher education groups, the most important participants in the era of big data in China. This study focuses on the privacy concept of Chinese higher education groups under the background of COVID-19 epidemic, and higher education groups from 19 provinces, 4 municipalities and 4 autonomous regions are selected as research samples. Through questionnaire survey and statistical analysis, individual privacy sensitivity, individual privacy deliver willingness, individual privacy security and other issues of Chinese higher education groups under the COVID-19 epidemic situation are discussed. And this study tries to explore the influencing factors behind it. It is found that Chinese higher education groups generally have high privacy sensitivity and high perception of privacy risk. However, in the special period of fighting against the COVID-19 epidemic, Chinese higher education groups generally have a high willingness to deliver private information and a high privacy security. In addition, education level, discipline background and parents' education level are important factors affecting the privacy concept of Chinese higher education groups. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

QUASAR Induction Study 1 Cumulative Response to Guselkumab in Patients With Moderately to Severely Active Ulcerative Colitis

Introduction: Guselkumab (GUS), an IL-23p19 antagonist, had greater efficacy than placebo (PBO) in achieving clinical response and clinical remission atWeek (Wk) 12 in the randomized, controlled Phase 2b QUASAR Induction Study 1 (NCT04033445) in patients with moderately to severely active ulcerative colitis (UC).1 Patients who were not in clinical response at Wk 12 received GUS treatment through Wk 24. Here, we report GUS cumulative efficacy and safety results for Induction Study 1. Method(s): Eligible patients had moderately to severely active UC (modified Mayo score of 5 to 9 with a Mayo endoscopy subscore >=2) at baseline. Patients were randomized 1:1:1 to IV GUS 200mg, 400mg, or PBO at Wks 0, 4, and 8. Patients who were not in clinical response to IV induction at Wk 12 received GUS treatment (PBO IV->GUS 200mg IV;GUS 200mg IV->GUS 200mg SC;GUS 400mg IV->GUS 200mg SC) at Wks 12, 16, and 20 and were evaluated at Wk 24 (Figure). Matching IV or SC PBO was administered to maintain the blind. Result(s): Three hundred thirteen patients were randomized and treated at baseline. Demographic and disease characteristics at baseline were similar among the treatment groups, and approximately 50% had a prior inadequate response or intolerance to advanced UC therapy. AtWk 12, clinical response was achieved by 61.4% (62/101) and 60.7% (65/107) of patients randomized to GUS 200mg and GUS 400mg IV vs 27.6 % (29/105) of patients randomized to PBO IV (both p< 0.001). Of the patients in the GUS groups who were not in clinical response at Wk 12, 54.3% (19/35) in the GUS 200mg IV->200mg SC group and 50.0% (19/38) in the GUS 400mg IV->200mg SC group achieved clinical response at Wk 24. Clinical response atWk 12 or 24 was achieved by 80.2% of patients who were randomized to GUS 200mg IV and 78.5% of patients who were randomized to GUS 400mg IV. For patients who received PBO IV->GUS 200mg IV, clinical response at Wk 24 (65.2%) was similar toWk 12 clinical response following GUS 200mg IV induction (61.4%). The most frequent adverse events among all GUS-treated pts (n=274) were anemia (7.7%), headache (5.1%), worsening UC (4.4%), COVID-19 (3.6%), arthralgia (2.9%) and abdominal pain (2.6%) which are consistent with Wk 12 results. Conclusion(s): Overall, approximately 80% of patients randomized to receive GUS achieved clinical response at Wk 12 or 24. Continued treatment with SC GUS allowed 50-54.3% of IV GUS Wk 12 clinical nonresponders to achieve clinical response at Wk 24. No new safety concerns for GUS were identified. (Figure Presented).

Cryopreservation for Allogeneic Hematopoetic Stem Cell Transplants Is Non-Inferior to Fresh Graft Products

Background: The use of cryopreservation for stem cell grafts for both autologous stem cell and allogeneic cord blood transplant has been utilized for years. For other allogeneic stem cell transplant sources, the use of fresh collected grafts has been preferred due to concerns that cryopreservation may result in impaired graft function. With the onset of the COVID-19 pandemic a shift was made at our institution to exclusive use of cryopreservation Methods: In this retrospective single-center analysis a total of 133 patients undergoing allogeneic stem cell transplant at the University of Minnesota between 1/2018-6/2021 for a variety of malignancies were included, with 62 patients receiving fresh stem cell product and 71 patients receiving frozen stem cell product. Univariate statistical analysis was performed. Result(s): There was no significant difference between the two groups with regards to product type, sex, age, diagnosis (acute leukemia vs other), disease risk index, conditioning regimen, Karnofsky score, co-morbidity index, or cell dose (Table 1). Donor type was notably different between the two groups (p<0.01): matched sibling grafts were more commonly used for fresh products than frozen (85% vs. 35%), while matched unrelated donors were used more frequently for frozen than for fresh products (54% vs. 6%). Use of frozen product was associated with delayed neutrophil and platelet engraftment compared to fresh (median days to engraftment 15 vs 12 for neutrophils, 23 vs 17 for platelets, p<0.01 for both). Two-year relapse rates were significantly lower for frozen products (4%) than fresh (24%) (Table 2). This may be partially attributable to differences in follow up between the groups, as fresh products had a total of 910 days of follow up vs 432 for frozen products (P<0.0001). The difference in follow up remained statistically significant if the data was censored at 730 days (P<0.0001). Of note, the use of frozen products was associated with a lower rate of chronic graft-versus-host disease at one year post-transplant (p<0.01). There was no significant difference in the rates of acute GVHD between the groups. There were significant differences in GVHD prophylaxis regimens between the fresh and frozen groups (p<0.01). (Figure Presented)Two-year overall survival did not differ between groups (p=0.96). Conclusion(s): Use of cryopreserved stem cell products is associated with similar efficacy and outcomes as those seen with the use of fresh stem cell products. Although the data presented here suggest novel finding of decreased risk of relapse and chronic GVHD with the use of frozen stem cell products, additional follow up may abrogate these differences. Regardless, the logistical benefits of cryopreservation make this an attractive option for continued use in allogeneic transplants and our data presented here suggests that cryopreserved products remain an appropriate option for allogeneic stem cell transplant.Copyright © 2023 American Society for Transplantation and Cellular Therapy

Predictive Information Workflow of Forecasting Number of COVID-19 Confirmed Cases

There are questions about how to accurately prepare with the correct number of resources for distribution in order to properly manage the healthcare resources (e.g., healthcare workers, Masks, ART-19 TestKit) required to tighten the grip on the COVID-19 pandemic. Mathematical and computational forecasting models have well served the means to address these questions, as well as the resulting advisories to governments. A workflow is proposed in this research, aiming to develop a forecasting simulation that makes accurate predictions on COVID-19 confirmed cases in Singapore. According to the analysis of the prior works, six candidate forecasting models are evaluated and compared in the workflow: polynomial regression, linear regression, SVM, Prophet, Holt's linear, and LSTM models. The study's goal is to determine the most suitable forecasting model for COVID-19 cases in Singapore. Two algorithms are also proposed to better compute the performance of two models: the order algorithm to determine optimal degree order for the polynomial regression model, and the optimizing algorithm for the Holt's linear model to calculate the optimal smoothing parameters. Observed from the experiment results with the COVID-19 dataset, the Prophet method model achieves the best performance with the lowest Root Mean Square Error (RMSE) score of 1557.744836 and Mean Absolute Percentage Error (MAPE) score of 0.468827, compared to the other five models. The Prophet method model achieving average accuracy range of 90% when forecasting the number of confirmed COVID-19 cases in Singapore for the next 87 days ahead. is chosen and recommended to be used as a system model for forecast the COVID-19 confirm cases in Singapore. The developed workflow will greatly assist the authorities in taking timely actions and making decisions to contain the COVID-19 pandemic. © 2022 IEEE.

[The predictive value of warning scores for intensive care unit admission in coronavirus disease 2019 patients].

To evaluate the predictive value of early warning scores for intensive care unit (ICU) admission in patients with coronavirus disease 2019 (COVID-19). For COVID-19 patients who were admitted to Shijiazhuang People's Hospital from January 2021 to February 2021, national early warning score (NEWS), national early warning score 2 (NEWS2), rapid emergency medicine score (REMS), quick sepsis-related organ failure (qSOFA), altered consciousness, blood urea nitrogen, respiratory rate, blood pressure, and age-65 (CURB-65) were used to evaluate the inpatient condition and the predictive value for ICU admission. A total of 368 patients were included, and 32 patients (8.7%) were transferred to the ICU. The median age was 49.0 (34.0,61.0) years. The scores of NEWS, NEWS2, REMS, and CURB-65 were 1 (0, 2), 1 (0, 2), 4 (2, 6) and 0 (0, 1), respectively. The receiver operating characteristic (ROC) cure (AUC) was used to evaluate the predictive value in detecting patients who are at risk of being transferred to the ICU. Area under the ROC AUC of NEWS was 0.756, sensitivity 65.6%, and specificity 71.3%. ROC AUC of NEWS2 was 0.732, sensitivity 62.5%, and specificity 61.3%. ROC AUC of REMS was 0.787, sensitivity 84.4%, and specificity 64.6%. ROC AUC of CURB-65 was 0.814, sensitivity 81.3%, and specificity 76.8%. The predictive value of NEWS and NEWS2 combined with age were significantly improved. The ROC AUC of NEWS combined with age was 0.885, sensitivity 85.1%, and specificity 75.0%. The ROC AUC of NEWS2 combined with age was 0.883, sensitivity 84.2%, and specificity 75.0%. NEWS and NEWS2 combined with age can be used as a predictive tool for whether COVID-19 patients will be admitted to the ICU.

QUASAR Induction Study 1 Cumulative Response to Guselkumab in Patients With Moderately to Severely Active Ulcerative Colitis

Background: Guselkumab (GUS), an IL-23p19 antagonist, had greater efficacy than placebo (PBO) in achieving clinical response and clinical remission at Week (Wk) 12 in the randomized, controlled Phase 2b QUASAR Induction Study 1 (NCT04033445) in patients with moderately to severely active ulcerative colitis (UC).1 Patients who were not in clinical response at Wk 12 received GUS treatment through Wk 24. Here, we report GUS cumulative efficacy and safety results for Induction Study 1. Method(s): Eligible patients had moderately to severely active UC (modified Mayo score of 5 to 9 with a Mayo endoscopy subscore >=2) at baseline. Patients were randomized 1:1:1 to IV GUS 200mg, 400mg, or PBO at Wks 0, 4, and 8. Patients who were not in clinical response to IV induction at Wk 12 received GUS treatment (PBO IVGUS 200mg IV;GUS 200mg IV->GUS 200mg SC;GUS 400mg IV->GUS 200mg SC) at Wks 12, 16, and 20 and were evaluated at Wk 24 (Figure 1). Matching IV or SC PBO was administered to maintain the blind. Result(s): Three hundred thirteen patients were randomized and treated at baseline. Demographic and disease characteristics at baseline were similar among the treatment groups, and approximately 50% had a prior inadequate response or intolerance to advanced UC therapy. At Wk 12, clinical response was achieved by 61.4% (62/101) and 60.7% (65/107) of patients randomized to GUS 200mg and GUS 400mg IV vs 27.6% (29/105) of patients randomized to PBO IV (both p<0.001). Of the patients in the GUS groups who were not in clinical response at Wk 12, 54.3% (19/35) in the GUS 200mg IV->200mg SC group and 50.0% (19/38) in the GUS 400mg IV->200mg SC group achieved clinical response at Wk 24. Clinical response at Wk 12 or 24 was achieved by 80.2% of patients who were randomized to GUS 200mg IV and 78.5% of patients who were randomized to GUS 400mg IV. For patients who received PBO IV->GUS 200mg IV, clinical response at Wk 24 (65.2%) was similar to Wk 12 clinical response following GUS 200mg IV induction (61.4%). The most frequent adverse events among all GUS-treated pts (n=274) were anemia (7.7%), headache (5.1%), worsening UC (4.4%), COVID-19 (3.6%), arthralgia (2.9%) and abdominal pain (2.6%) which are consistent with Wk 12 results. Conclusion(s): Overall, approximately 80% of patients randomized to receive GUS achieved clinical response at Wk 12 or 24. Continued treatment with SC GUS allowed 50-54.3% of IV GUS Wk 12 clinical nonresponders to achieve clinical response at Wk 24. No new safety concerns for GUS were identified.

Filtration Performance and Fiber Shedding Behavior in Common Respirator and Face Mask Materials

Wearing respirators and face masks is effective for protecting the public from COVID-19 infection. Thus, there is a need to evaluate the performance of the commonly used respirators and face masks. Two experimental systems were developed to investigate seven different mask materials, which have a fiber size range from 0.1 µm (100 nm) to 20 µm (20,000 nm). One of the systems is a computer-controlled setup for measuring the filtration performance, including size-dependent filtration efficiency and pressure drop, while the other system is for testing the fiber shedding behavior of the materials. The technique of scanning electron microscope (SEM) was applied to observe the dimensions and structures of those materials, which are made of nonwoven-fabrics electret-treated media, cotton woven fabrics, or nanofiber media. The study indicated that the 3M N95 respirator has the best overall filtration performance with over 95% efficiency and low pressure drop of 74.1 Pa. The two commercial cotton face masks have the worst filtration performance in general, with a filtration efficiency of around 25%. No broken fibers from by the seven tested respirator and face mask materials were discovered;however, dendrite structures likely shed by the SHEMA97 face mask with a size comparable to its nanoscale fibers were identified. The reason for this phenomena is presented. © 2023, AAGR Aerosol and Air Quality Research. All rights reserved.

MepoGNN: Metapopulation Epidemic Forecasting with Graph Neural Networks

Epidemic prediction is a fundamental task for epidemic control and prevention. Many mechanistic models and deep learning models are built for this task. However, most mechanistic models have difficulty estimating the time/region-varying epidemiological parameters, while most deep learning models lack the guidance of epidemiological domain knowledge and interpretability of prediction results. In this study, we propose a novel hybrid model called MepoGNN for multi-step multi-region epidemic forecasting by incorporating Graph Neural Networks (GNNs) and graph learning mechanisms into Metapopulation SIR model. Our model can not only predict the number of confirmed cases but also explicitly learn the epidemiological parameters and the underlying epidemic propagation graph from heterogeneous data in an end-to-end manner. Experiment results demonstrate our model outperforms the existing mechanistic models and deep learning models by a large margin. Furthermore, the analysis on the learned parameters demonstrates the high reliability and interpretability of our model and helps better understanding of epidemic spread. Our model and data have already been public on GitHub https://github.com/deepkashiwa20/MepoGNN.git. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Experts proposal and frequently asked questions of rapid screening and prevention of novel coronavirus pneumonia in children.

The outbreak of novel coronavirus pneumonia (NCP) has become the most severe public health issue at the moment, threatening people's lives. Pediatricians in Shanghai have recently launched a discussion on the focused questions of NCP, including the incidence situation, epidemiological features, essentials of early screening, treatment and nosocomial infection prevention of children's novel coronavirus infection (2019-nCoV), and further put forward the experts proposal upon the patterns of disease occurrence, development, diagnosis and control, for the reference of frontline pediatricians.Copyright © 2020 by the Chinese Medical Association.

Micro-level social structures and the success of COVID-19 national policies

Similar policies in response to the COVID-19 pandemic have resulted in different success rates. Although many factors are responsible for the variances in policy success, our study shows that the micro-level structure of person-to-person interactions—measured by the average household size and in-person social contact rate—can be an important explanatory factor. To create an explainable model, we propose a network transformation algorithm to create a simple and computationally efficient scaled network based on these micro-level parameters, as well as incorporate national-level policy data in the network dynamic for SEIR simulations. The model was validated during the early stages of the COVID-19 pandemic, which demonstrated that it can reproduce the dynamic ordinal ranking and trend of infected cases of various European countries that are sufficiently similar in terms of some socio-cultural factors. We also performed several counterfactual analyses to illustrate how policy-based scenario analysis can be performed rapidly and easily with these explainable models. © 2022, The Author(s), under exclusive licence to Springer Nature America, Inc.

Air quality changes in Shijiazhuang during COVID-19 outbreak

[Background] The coronavirus disease 2019 (COVID-19) was first detected in December 2019. To combat the disease, a series of strict measures were adopted across the country, which led of improved air quality. This provides an opportunity to discuss the impact of human activities on air quality. [Objective] This study investigates the air quality changes in Shijiazhuang, and analyzes the impacts of epidemic prevention and control measures on air quality, so as to provide reference and ideas for further improving air quality and prevention and control measures. [Methods] The air quality data were collected online from https://www.zq12369.com/ and https://aqicn.org/city/shijiazhuang/cn/. Comparisons in air quality index (AQI) and the concentrations of air pollutants (PM2.5, PM10, SO2, CO, NO2, and O3) were made between the period from December 2019 to June 2020 (reference) and the same period from 2016 to 2019 by t-test and chi-square test. [Results] The daily average AQI dropped by 25.38% in Shijiazhuang during the COVID-19 prevention and control compared with the some period from 2016 to 2019 (t=6.28, P < 0.05). The proportions of pollution days during the COVID-19 outbreak in Shijiazhuang were PM2.5 (44.56%), O3 (31.09%), PM10 (23.83%), and NO2 (2.59%) successively, the pollution days of PM10 decreased significantly (χ2=3.86, P < 0.05) compared with 2016-2019, but during traffic lockdown the numbers of pollution days of PM2.5 and in the mid stage of prevention the number of pollution days of O3 increased (P < 0.05). Compared with the control period, the concentrations of the six air pollutants decreased to varying degrees (P < 0.05), especially SO2 dropped by 55.36%. [Conclusion] The measures taken for COVID-19 control and prevention have reduced the pollution sources and emissions, which resulted in better general air quality of Shijiazhuang City, but have aggravated the pollution of O3 and other pollutants. It is necessary to further explore the causes for the aggravation of O3 pollution in order to formulate reasonable air quality control strategies. © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.

Interactive Virtual Reality Game for Online Learning of Science Subject in Primary Schools

Education plays an important role in nurturing children. COVID-19 pandemic brings challenges or disruptions to school education, due to school closures in some countries. Science subject in primary schools is unique as hands-on experiments are important learning components. Its learning process may be affected, as a new norm of online learning or home-based learning. This research project creates a serious game on science subject for primary school students aging within 10 to 11 years old using virtual reality (VR) technology. It consists of three virtual learning phases. Phase 1 explains theories of science topics on electricity and electric circuits. Phase 2 provides interactive hands-on experiment exercises where students can practice theory knowledge learned in the previous phase. An interactive quiz session is offered to reinforce the learning in Phase 3. Interactive VR features enable primary school students learning science concepts in an interesting way compared to conventional classroom settings. Meticulous design attentions have been placed in the details such as visual instructions, voice instructions, speech tempo, animations, and colorful graphics to create a sense of realism and keep students actively engaged. Preliminary case study has been conducted with 10 students at primary schools in Singapore to evaluate learning effectiveness in this research. © 2021 IEEE.

Connecting cancer research and communities: Assessing barriers and facilitators to the implementation of a community scientist program

Introduction: Community Scientist (CS) programs - often referred to as Citizen Scientist programs - that facilitate direct engagement between scientific researchers and community members have emerged as effective strategies for building community trust in scientists and better informing research design and dissemination to address true community needs. While population health research has increasingly incorporated community stakeholders into the research continuum, basic and translational sciences struggle to do the same and may contribute to cancer disparities. We designed and implemented a virtual CS program at the Robert H. Lurie Comprehensive Cancer Center of Northwestern University (LCC). We report barriers, facilitators, and lessons learned. Methods: Translational scientists (TSs) were recruited from among LCC investigators, and CSs were identified for participation from among LCC community networks. We sought to recruit a CS cohort representing LCC's catchment area and a TS cohort whose research focuses on cancers most impacting LCC catchment. CS program interactions included monthly meetings between two CSs and one TS wherein the CS-TS triad discuss TS research in lay terms and work together to co-create educational infographics suitable for dissemination to the catchment and LCC scientists. Virtual attendance was tracked and meeting recordings retroactively reviewed to identify and create product development. Results: Six CSs and three TSs agreed to participate in the CS program. The CS cohort includes cancer survivors, patient advocates, community organization leaders, a nurse, and an educator, while the TS cohort includes breast, prostate, and lung cancer researchers. Currently, 11 of 18 triad meetings have been completed, with attendance averaging 97%. Barriers to program implementation have included technological difficulties, restrictions on in-person meeting, scheduling conflicts, time limitation, and language barriers, while facilitators have included small group meetings to promote comfortable group-member contribution, presence of a trained facilitator, articulation of achievable meeting goals and mission for product creation, and clear assignment of team roles. Conclusion: The COVID-19 pandemic has illuminated pre-existing needs for improved connectivity between communities impacted by cancer disparities and cancer researchers. By identifying current barriers and facilitators to successful virtual CS program implementation, our findings can be used to guide development and implementation of similar programs at LCC and other cancer centers that are aimed at mitigating cancer health disparities.

Robust Institutional Support and Collaboration Between Summer Training Programs in Cancer and Biomedicine Drive the Pivot to a Virtual Format in Response to the COVID Pandemic.

Summer internships serve important roles in training the next generation of biomedical researchers and healthcare providers through laboratory and clinical experiences that excite trainees about these fields and help them make informed decisions about career paths. The SARS-CoV-2 (COVID) pandemic and associated physical distancing restrictions precluded implementation of traditional in-person summer curricula and led to the cancellation of many internships across the USA. COVID-related disruptions also created opportunities for trainees to engage in remote research, become proficient in online learning platforms, and explore multidisciplinary topics. These skills are highly relevant to trainees as virtual interfaces occupy an increasingly mainstream role in their professional paths. The response to the COVID pandemic required real-time adaptations at all levels for major biomedical institutions including the University of Maryland Baltimore (UMB). Pivoting summer programs to a virtual format as part of this response provided a "teachable moment" to expose trainees to the innovation and resilience that are essential components of the biomedical profession. UMB summer programs, which span diverse biomedical disciplines from cancer research to diabetes, consolidated resources and identified mentors with online research projects to develop a robust virtual curriculum. Herein, data from a cancer-focused internship illustrate the collaborative adaptations to established components and creation of new learning modules in the transition to, and implementation of, online training. Outcomes are presented in the context of the COVID pandemic and significant societal issues that arose in the summer of 2020. The utility of virtual components and their impact on future programs is discussed.

Research on Digital Transformation of Construction Industry

As one of the pillars that support national economy, construction industry makes remarkable contribution in building our country's economy. However, despite being larger in size, the industry is weak in general and companies often lack core competencies. Meanwhile, COVID-19 has major influence on industry development and social governance such that the traditional extensive management method can no longer satisfy the needs of core business in this new era. Transformation and advancement of construction industry through digitalization is an inevitable trend. This paper first analyzes the current development situation of construction industry and main problems associated with digitalization during the 10 years. We move on to discuss the significance of transforming construction industry through digitalization and propose the concrete pathway to realize the advancement. © ASCE.

Study on droplet dispersion influenced by ventilation and source configuration in classroom settings using low‐cost sensor network

The COVID‐19 virus can transmit through airborne expiratory droplets and thus, the viral transmission can take place between the occupants in the isolated room. With the school re-opening under the current COVID‐19 pandemic, it is urgent to improve the classroom ventilation system to mitigate the risk of virus transmission. The present study developed a particle concentration monitoring network (PCMN) using low‐cost sensors and deployed it to explore the dispersion of the droplet particles under different ventilation settings and aerosol configurations. Our experiment shows the advance of using a low‐cost sensor network on spatiotemporal air monitoring and demonstrates indoor particle concentration level and distribution are strongly impacted by the ventilation setting and source location. Two recommendations on reducing the viral risk in the classroom were derived from the study. The first is the respiratory droplet source, e.g., the instructor, should be in the location such that the particle dispersion opposes the ventilation flow. The second is the air handling unit (AHU) and fan coil unit (FCU) should be both turned on during class hours despite whether there is a need for thermal comfort, as it allows higher and more uniform ventilation flow to resolve the issue of the dead air zone. © The Author(s).

An experimentally validated analytical model for aerosol number concentration reduction in classrooms

To predict the aerosol number concentration decay in modern classrooms, this study derived an analytical model that addresses various indoor factors, viz., the filtration efficiency of air ventilation systems, effects of indoor air cleaners, particle deposition on walls, and particle emission from occupants. We also conducted experimental measurements to determine the wall-loss coefficient and the occupants’ particle generation rate, and the modeling results agreed with the experimental data reasonably well. Additionally, we investigated the behavior of the particle concentration decay in different ventilation scenarios. The model has been incorporated into web-based software that is freely available to the public. © The Author(s).