The effect of the emergency shift to virtual instruction on student team dynamics

In spite of the sudden onset of the COVID-19 pandemic, many instructors who used team-based pedagogies shifted them online rather than suspending them entirely, but with limited time and resources. To examine the difference in team dynamics and outcomes for courses in Spring 2019 and Spring 2020 of over 1500 first-year engineering students per semester, Wilcoxon signed-rank tests and random forests method were used. Results show that students reported less improvement in team-member effectiveness, lower psychological safety, and less satisfaction in the semester with the emergency transition. However, students also reported lower conflict. The most important factor predicting project grades shifted from 'Interacting with teammates' to 'Having relevant knowledge, skills, and abilities' amid the emergency shift, accompanied by a reduction in team interdependence. In spite of the collection of data during an emergency transition, the foundation of face-to-face interaction before moving to virtual cooperation represents a useful contribution to research that has focused exclusively on virtual learning circumstances.

Analysis of Low Order Universal Portfolios Generated by Two and Three Parameters Distributions on Malaysia's Stocks During the Covid-19 Pandemic

Universal Portfolio is an investment strategy that enables investors to reallocate their wealth by up-dating the portfolio daily to achieve maximum wealth. There is no assumption of a stochastic model for the stock price in a universal portfolio. Instead, this paper will study the low order universal portfolio generated by selected two and three parameters' distributions such as Pareto, Loglogistic, Paralogistic, Burr, and Trans-formed Gamma. Three portfolios, each containing three different companies selected from Kuala Lumpur Stock Exchange (KLSE), will be used throughout the study. In addition, opening and closing stock prices for 500, 1000, 1500, 2000, 2500, and 3000 trading days. In order to study the performance of the universal portfo-lio generated with selected distributions during the economic downturn, the selected trading period included the Covid-19 pandemic. Different parameter values were applied in this study to identify the significant pa-rameter for each distribution, affecting the maximum wealth for each portfolio. The results obtained from each portfolio generated by selected distributions are compared with the best constant rebalanced portfolio (BCRP). The result shows that the Pareto distribution could generate wealth comparable to the BCRP with specific parameter values.

Preliminary Recommendations on the Timing of Lung Surgery after Novel Coronavirus Infection in Patients with Pulmonary Nodules and Lung Cancer.

In recent years, the corona virus disease 2019 (COVID-19) pandemic has had a huge impact on the global medical, political and economic fields. Since the beginning of the COVID-19 epidemic, our understanding of the impact of COVID-19 has grown exponentially. Recently, the COVID-19 epidemic has changed rapidly in China, and there has been controversy over how to carry out surgical operations for patients with lung neoplastic lesions. Some studies have shown that lung cancer patients undergoing surgery are more likely to experience respiratory failure and perioperative death after contract-ing COVID-19 than the general population, however, delays in cancer treatment are also associated with increased mortality among these patients. In particular, the novel coronavirus Omikron variant has a higher transmissibility and may escape the immunity obtained through the previous novel coronavirus infection and vaccination. In order to minimize the risk of novel coronavirus infection in surgical patients, it is necessary to develop new treatment guidelines, expert consensus and preventive measures. However, the current rapid change of the epidemic situation has led to insufficient time and evidence to develop guidelines and consensus. Therefore, thoracic surgeons need to evaluate specific patient populations at higher risk of severe complications before surgery and weigh the benefit of surgical treatment against the risk of novel coronavirus infection. We try to give some recommendations on lung surgery during the current domestic epidemic situation based on the guidelines and consensus of oncology and thoracic surgery organizations in different regions on lung surgery.Copyright © 2023, Chinese Journal of Lung Cancer. All rights reserved.

Efficacy of risankizumab by baseline clinical, biochemical, and endoscopic disease severity in moderately to severely active Crohn's disease

Background: Risankizumab (RZB), a p19-anti-interleukin-23 monoclonal antibody, has demonstrated efficacy as induction and maintenance therapy in patients with moderately to severely active Crohn's disease (CD). This post hoc analysis evaluates the efficacy of induction and maintenance RZB therapy by baseline clinical, biochemical, and endoscopic disease severity. Method(s): In the ADVANCE (NCT03105128) and MOTIVATE (NCT03104413) studies, patients with moderately to severely active CD and intolerance/inadequate response to >= 1 biologic (both studies) and/or conventional therapy (ADVANCE) were randomized to receive intravenous (IV) RZB induction therapy or placebo (PBO) for 12 weeks. Patients achieving stool frequency and/or abdominal pain score clinical response to 12 weeks of induction therapy were rerandomized in the FORTIFY (NCT03105102) study to receive subcutaneous (SC) maintenance RZB (180 mg or 360 mg) or PBO (withdrawal). Clinical and endoscopic endpoints were evaluated by baseline disease characteristics (Crohn's Disease Activity Index [CDAI: <= 300, > 300], highsensitivity C-reactive protein [hs-CRP: < 10 mg/L, >= 10 mg/L], and Simple Endoscopic Score for Crohn's Disease [SES-CD: 6-15, > 15]). Induction analyses included patients who received RZB 600 mg or PBO;data from the ADVANCE and MOTIVATE studies were pooled. Nonresponder imputation incorporating multiple imputation to handle missing data due to COVID-19 was used. Result(s): The induction analysis included 527 patients who received RZB 600 mg IV and 362 patients who received PBO. Patients treated with RZB 600 mg IV achieved significantly higher response rates vs PBO at week 12, regardless of subgroup (P < .05 for all;Figure 1). In the maintenance study, patients treated with SC RZB continued to achieve higher response rates vs the PBO (withdrawal) group at week 52 regardless of subgroup (P was not < .05 for all;Figure 2). Improvements in clinical and endoscopic outcomes were generally observed from weeks 12 to 52 with RZB treatment across all subgroups. Response rates were generally similar across subgroups in both induction and maintenance studies;endoscopic remission and ulcer-free endoscopy (resolution of ulcer) rates were numerically lower for patients with increased inflammation (hs-CRP > 10 mg/mL) and higher endoscopic activity (SES-CD > 15). Conclusion(s): RZB induction therapy resulted in higher response rates for clinical and endoscopic outcomes compared with PBO at week 12, regardless of baseline clinical, biochemical, and endoscopic disease severity. RZB also showed durable efficacy with continued RZB maintenance therapy, supporting the long-term use of RZB for patients across a range of baseline disease severity and activity.

Preliminary Recommendations on the Timing of Lung Surgery after Novel Coronavirus Infection in Patients with Pulmonary Nodules and Lung Cancer.

In recent years, the corona virus disease 2019 (COVID-19) pandemic has had a huge impact on the global medical, political and economic fields. Since the beginning of the COVID-19 epidemic, our understanding of the impact of COVID-19 has grown exponentially. Recently, the COVID-19 epidemic has changed rapidly in China, and there has been controversy over how to carry out surgical operations for patients with lung neoplastic lesions. Some studies have shown that lung cancer patients undergoing surgery are more likely to experience respiratory failure and perioperative death after contract-ing COVID-19 than the general population, however, delays in cancer treatment are also associated with increased mortality among these patients. In particular, the novel coronavirus Omikron variant has a higher transmissibility and may escape the immunity obtained through the previous novel coronavirus infection and vaccination. In order to minimize the risk of novel coronavirus infection in surgical patients, it is necessary to develop new treatment guidelines, expert consensus and preventive measures. However, the current rapid change of the epidemic situation has led to insufficient time and evidence to develop guidelines and consensus. Therefore, thoracic surgeons need to evaluate specific patient populations at higher risk of severe complications before surgery and weigh the benefit of surgical treatment against the risk of novel coronavirus infection. We try to give some recommendations on lung surgery during the current domestic epidemic situation based on the guidelines and consensus of oncology and thoracic surgery organizations in different regions on lung surgery.Copyright © 2023, Chinese Journal of Lung Cancer. All rights reserved.

Synthesis and enzymatic inhibition effects of thiazolidinedione 3C-like protease inhibitors

The 3C-like protease (also known as Mpro) plays a key role in SARS-CoV-2 replication and has similar substrates across mutant coronaviruses, making it an ideal drug target. We synthesized 19 thiazolidinedione derivatives via the Knoevenagel condensations and Mitsunobu reactions as potential 3C-like protease inhibitors. The activity of these inhibitors is screened in vitro by employing the enzymatic screening model of 3C-like protease using fluorescence resonance energy transfer. Dithiothreitol is included in the enzymatic reaction system to avoid non-specific enzymatic inhibition. Active inhibitors with diverse activity are found in this series of compounds, and two representative inhibitors with potent inhibitory activity are highlighted. © The Author(s) 2023.

A Scientometric Review of Residential Segregation Research: A CiteSpace-Based Visualization

Residential segregation (RS) is a global phenomenon that has become an enduring and important topic in international academic research. In this review, using RS as the search term, 2520 articles from the period 1928–2022 were retrieved from the Scopus database and were visually analyzed using CiteSpace software. The results revealed the following: (1) The United States and its institutions have made outstanding contributions to RS research, while various scholars (e.g., Johnston, Massey, Forrest, Poulsen, and Iceland) have laid the foundation for RS research. (2) Mainstream RS research originates from three fields—psychology, education, and social sciences—while the trend of multidisciplinary integration is constantly increasing. (3) The research hotspots of RS include racial difference, sociospatial behavior, income inequality, mixed income communities, guest worker minorities, typical district segregation, occupational segregation, health inequalities, metropolitan ghetto, and migrant–native differential mobility. Furthermore, (4) gentrification, spatial analysis, school segregation, health disparity, immigrant, and COVID-19 have become new themes and directions of RS research. Future research should pay more attention to the impact of multi-spatial scale changes on RS as well as propose theoretical explanations rooted in local contexts by integrating multidisciplinary theoretical knowledge. © 2022 by the authors.

A dynamic pricing model of container liner shipping with overlapping legs on shipping network in a duopoly competition market

Container liner shipping is an important backbone for international trade marine transportation of industry products. After the 2008 financial crisis and especially with the recent COVID-19 pandemic, the international liner shipping has been at a low ebb. It has experienced an overall imbalance in the supply and demand of transportation capacity, prolonged recession periods, and low-level fluctuations in freight rates. Moreover, the imbalance between supply and demand has been extremely prominent and the operating cost has risen drastically. Therefore, competition between liner companies has grown fiercer. To reduce operating costs and increase their market share and shipping competitiveness, container liner companies have strengthened their cooperation and formed shipping liner alliances. With dominant ocean carriers and the merger of the carriers′ industry, the carrier competition exhibits an oligopolistic nature. The capital-intensive nature of regular shipping services has led to fierce competition between shipping lines. Low service differentiation in liner shipping implies that competition in this industry is mainly on a cost or price (freight rate) basis. Therefore, how to formulate reasonable container liner freight rates has become a core decision-making issue for shipping companies in an oligopolistic market. Furthermore, with the advent of online booking systems, such as the one operated by Maersk Line, adjusting realtime prices can become less costly, which will make a dynamic pricing strategy possible and necessary. In view of this, this paper focuses on the dynamic pricing strategy of container liner shipping in a duopoly market. This paper makes the following contributions to the literature. (1) It contributes to the literature by expanding the current literature by exploring the dynamic pricing problem that extends from a single origin-destination (OD) stream to multiple OD streams under a liner shipping network. (2) A time-phrased dynamic pricing game strategy is proposed to solve the pricing problem of liner shipping networks with overlapping legs based on the principle of discrete-time dynamic generalized Nash equilibrium. Shipping lines face two types of customer demands: long-term contractual demand and spot market demand. The price of the longterm demand is often fixed and contracted once a year, whereas the price of spot market demand may be agreed upon between shipping lines and shippers (or freight forwarders) dynamically on a daily or weekly basis. The regularity of liner shipping services indicates that liner services are perishable products, which means that unutilized vessel slots will lose the opportunity to generate revenue. Therefore, it is vital for a shipping line to seek an appropriate pricing strategy to maximize its revenue in the competitive and uncertain spot market. In addition, a container liner shipping network operates on multiple routes, and there are overlapping legs. The container freight rates of an OD that flows on different routes should be consistent without affecting the distribution ratio of the customer′s cargo transportation between the overlapping legs of each route. Therefore, from the perspective of customer classification, the focus of container liner shipping pricing decisions is mainly on the dynamic pricing of spot market customers. Based on the actual operation of liner shipping companies in multiple ports and the characteristics of customer classification, this paper studies the dynamic pricing problem of container liner shipping with overlapping legs on a shipping network in a duopoly competition market. The correlations between price sensitivity of customers and competition intensity with container shipping demand and freight rates in a spot market were analyzed. In accordance with the impact of a change in freight rate on freight flow distribution in overlapping segments of the shipping network, a time-phased dynamic pricing model for container liner shipping in a duopoly competition spot market was established while considering the factors of ma ket competition and the rival′s pricing strategy. The model has the essential feature of the generalized Nash equilibrium problem, that is, each participant′ s strategy is dependent on the competitor′s strategy. To prove the existence and uniqueness of the Nash equilibrium solution, the K-T method was employed to solve the discrete-time dynamic pricing model. The research results are as follows. (1) Adopting the dynamic pricing strategy will significantly increase the revenue of the two duopoly shipping companies. (2) The shipping company′s transportation revenue is negatively correlated with the intensity of market competition, and the container freight rate decreases as the intensity of competition in the duopoly market increases. (3) When the intensity of market competition is weak, the shipping company′s transportation revenue has a negative correlation with the customer′s price sensitivity. However, when the market competition is intense, the shipping company′s transportation revenue has a positive correlation with the customer′ s price sensitivity. The meaningful management implications of this paper are as follows. (1) To improve transportation revenue, shipping companies should adopt a flexible dynamic pricing strategy for customers in the duopoly competition spot market by dividing the canvassing period into several periods. (2) Shipping companies should strengthen cooperation by forming liner alliances. This will not only prevent price wars but also reduce the negative impact of market competition intensity on freight rates. (3) Shipping companies should adopt a time-phased pricing strategy to minimize the adverse impact of the price sensitivity of some urgent customers whose canvassing period is approaching on the demand for container transportation so that the shipping company′s transportation revenue would significantly improve © 2022, Journal of Industrial Engineering and Engineering Management. All Rights Reserved.

Work-in-Progress: Using Latent Dirichlet Allocation to uncover themes in student comments from peer evaluations of teamwork

This work-in-process research paper investigates common themes in peer-to-peer comments of teamwork behavior effectiveness collected with peer evaluations in engineering student teams in three time horizons - prior to COVID-19 pandemic, early phase of pandemic, and mature phase of pandemic. Constructive feedback is imperative to maintaining healthy team climate and dynamic, which facilitates positive individual and team learning outcomes. Asking engineering students to provide self- and peer-evaluation feedback in comments accomplishes multiple objectives. Students reflect on teammates' behavior and performance rather than relying on (potentially biased) general perceptions to provide evidence-based comments for the assessment period. Repeated practice giving feedback also tends to improve students' ability to provide constructive and insightful evaluations. To better understand what and how engineering students provide feedback in teamwork, the Comprehensive Assessment of Team-Member Effectiveness (CATME) peer evaluation tool suite was used to provide a framework to teach students about effective team behaviors using a behavioral-anchored rating scale. Using CATME also provided a mechanism for collecting self- and peer- evaluation survey data in both structured (the behavioral scale) and open-ended (comments) ways. Latent Dirichlet Allocation (LDA) was used as the classic method for topic modeling to analyze first-year engineering students' self- and peer- comments in the introductory engineering foundation courses in a large Midwestern R1 university. Topic Coherence measure (c_v) for topic quality was used to determine the optimal number of topics to represent the comment data. The themes of each of the topics identified were interpreted by thematic analysis of the most commonly used words and responses associated with each topic identified by the LDA model. The preliminary results showed that pre-pandemic themes closely matched the five behavioral dimensions of the CATME instrument. Data collected in Spring 2020 required more themes to capture the complexity of the transition to online learning. Comments from Spring 2021 required an even larger number of themes to describe the experience of teamwork during a fully virtual class implementation. © American Society for Engineering Education, 2022.

REAL WORLD DATA SUPPORTS POST-PANDEMIC CONTINUATION OF TELEMEDICINE SURVEILLANCE VISITS FOLLOWING RESECTION OF COLORECTAL LIVER METASTASES

INTRODUCTION The purpose of surveillance after resection of colorectal liver metastases (CLM) is to detect and treat recurrence using axial imaging, biomarker measurement, and a history/physical examination. In response to COVID-19 pandemic, telemedicine was used as a risk mitigation strategy to replace in-person visits, including for cancer surveillance. The objective of the study was to measure the uptake of telemedicine for cancer surveillance and outcomes following telemedicine surveillance after resection of CLM. METHODS Data from a prospective database was combined with real world data obtained from electronic health records using a cloud-based, data integration tool (Palantir Foundry) to identify patients in active surveillance following first surgical resection for CLM between April 2017 and April 2021. Telemedicine surveillance visit was defined as a follow-up visit >90 days following surgery using video or telephone. Recurrence was defined as detection of a new lesion. Bivariate statistical testing was performed using Student's t-test or chi-squared test. Retrospective chart review was used to validate identification of recurrence using the Foundry platform (100% interobserver agreement). RESULTS A total of 1,057 surveillance visits (306 patients) met our inclusion criteria. Prior to April 2020, 0% (0/686) visits utilized telemedicine. After April 2020, an average of 47.3% of visits per month utilized telemedicine (range 33.0 – 69.0%). The overall rate of identifying a recurrence during surveillance visit was 18.1% (191/1,057). There was no difference when comparing detection of recurrence using in-person (17.6%, 154/872) versus telemedicine visits (20.0%, 37/185, P=.371). The management of recurrence did not differ whether it was identified with an in-person or telemedicine visit;surgery, 36 (23%) vs. 10 (27%);ablation, 26 (17%) vs. 8 (22%);systemic therapy, 83 (54%) vs. 16 (43%);other, 9 (6%) vs. 3 (8%), respectively (P=.699). CONCLUSION Telemedicine was used in almost half of surveillance visits for CLM during the COVID- 19 pandemic. Detection and treatment of recurrence was similar for both telemedicine and in-person visits. Telemedicine-based follow-up is a safe and effective approach for surveillance after resection of CLM, supporting continued utilization beyond the pandemic.

Spatio-temporal Transmission of COVID-19 Pandemic in Susceptible-exposed of Small-world Network Model

This paper proposes the Susceptible-exposed of Small-world Network Model (SSEM) by combining the Susceptible-Exposed-Infectious-Recovered (SEIR) model with the Small-world Network (SN) model. The scenarios of COVID-19 propagation in urban public transport network was set by the specific model parameters. A study area, Huicheng District, Huizhou City, Guangdong Province, China, was selected to estimate the temporal and spatial distribution characteristics of COVID-19 within 12 hours based on SSEM. The results show that, without taking protective measures, if the two infectious source were in a bus, after 12 hours, 324 bus stations, 762 infected people and 68.85km2 were covered in the study area. The results of this study will provide a reference for the future study of COVID-19 virus transmission mechanism in the small enclosed environment. © 2021 IEEE.

FACTORS CONTRIBUTING TO BED BLOCK AND EMERGENCY DEPARTMENT RAMPING: A PROSPECTIVE AUDIT ON PROPORTION OF MEDICAL INPATIENTS AT SIR CHARLES GAIRDNER HOSPITAL NOT REQUIRING TERTIARY CARE

Background: During the last financial year, 101 internal emergencies were declared in West Australian (WA) hospitals due to inadequate capacity. This number is predicted to increase as the WA borders open. Observational experience at our hospital suggests that a significant number of general medical patients are occupying beds for prolonged periods of time for non-acute reasons. These include: awaiting placement to aged care facilities or transitional care placement (TCP), transfer to mental health units and National Disability Insurance Scheme (NDIS) for further discharge planning. Aim: To quantify the amount of acute medical beds that are occupied by patients who do not require a tertiary hospital bed for management of their condition. So as to assess the impact on patient flow and justify the need for a step-down unit at a secondary facility. Methods: This was a non-blinded prospective study whereby general medical units were audited every 8 days over a 5-week period to capture variation across different days of the week. A General Physician trainee assessed all general medical patients and concluded whether a tertiaryhospital bed was required. Criteria for non-tertiary beds includes patients who were awaiting permanent placement, respite, NDIS or mental health unit beds. Primary outcome measured was the daily proportion of patients not requiring acute tertiary care. Secondary outcomes measured were the reasons for ongoing hospital stay, patient factors contributing to this and the length of stay attributable to non-acute care. Results: The average daily proportion of general medical inpatients that do not warrant tertiary care was 21.5% (range 16% - 23%). Those awaiting placement to residential aged care facilities, TCP or respite contributed the most to ongoing hospital admissions (55.9%). Other reasons included awaiting NDIS approval (17.6%), mental health unit admission (17.6%) and transfer to rural residences (8%). More than half of the patients were over 65 years of age (64.7%). 58.8% of these patients were independent with activities of daily living, while the remaining 41.2% required assistance. Most common presenting complaints includes falls (23.5%) and infection;pneumonia, urinary tract infection, cellulitis and sepsis of unclear source (23.5%). Dementia with behavioural and psychological disturbance contributed 11.8%, mental health was 8.8%, neurological presentations (CVA, TIA, seizures) was 8.8%, gastrointestinal issues contributed 5.9%, and other reasons totaled 8.8%. More than half of the patients had a psychiatric comorbidity (58.8%) and close to half had cognitive impairment (41.2%). Average length of stay for non-acute care was 19.2 days. Proportion of patients with lengths of stay less than 10 days and 10-20 days was equal (35.3%), 5.9% for 20-30 days, 8.8% for 30-40 days, 2.9% for 40-50 days and 11.8% for more than 50 days. Conclusion: This study highlights the factors contributing to the burden faced by WA Health including lack of available beds, disruption in patient flow, and ramping. To address this, we have identified a significant proportion of general medical inpatients that could be stepped down to an alternate facility. In the context of the COVID-19 pandemic, efficient bed flow is paramount to ensure timely patient care and appropriate allocation of resources.

The impact of COVID-19 on the attention to sustainable clothing consumption: Analysis of Baidu indexes on old clothes recycling, old clothes renovation and old clothes donation

The COVID-19 epidemic has exerted tremendous impact on the public lifestyle. Due to the shortage of living materials, people have consciously saved the necessities of life, indirectly cultivating the environmental protection awareness and sustainability awareness. However, the public attention to clothing sustainability has been inclined. To explore the impact degree, the Baidu indexes on old clothes recycling, old clothes renovation and old clothes donation were analyzed. The STL algorithm was used for the decomposition of the time series of the public attention to isolate the trend components that can reflect the change trend;the index weights of the specific behaviors of sustainable clothing consumption before and after the COVID-19 epidemic were calculated using entropy method. The results have shown that the COVID-19 epidemic has increased the public attention to sustainable clothing consumption;during the post-epidemic period, the public have paid more attention to the sustainable behavior of old clothes recycling, and the attention to old clothes renovation and donation has declined. Therefore, according to the trend of change, targeted suggestions were proposed on the implementation of sustainable clothing consumption behaviors during the post-epidemic period. © 2021 China Silk Association. All rights reserved.

Intelligent System for Distributed Social Governance Based on Big Data

In recent years, promoting the synergy and intelligence of social governance, and improving the social governance system of co-construction, co-governance and sharing are important development directions for the country. As a production factor, data plays an increasingly critical role in social governance. How to realize the secure query, collaborative management, and intelligent analysis of multi-party massive data is the key issue to improve the effectiveness of social governance. In major public events such as the prevention and control of the COVID-19, distributed social governance faces low computing efficiency, poor multi-party credible coordination, and difficult decision-making for complex tasks. In response to the above challenges, this study proposes on big data based distributed social governance intelligent system based on secure multi-party computing, blockchain technology, and precise intelligence theory. The proposed system can support various applications of social governance that provide decision-making support for the improvement of social governance in the new era. © Copyright 2022, Institute of Software, the Chinese Academy of Sciences. All rights reserved.

Revisiting Meta-Heuristic Optimization Method in solving Stochastic System Design Problem

Optimization is an important issue in the real world, and most problems can be transformed into optimization problems. However, such stochastic optimization problems are always accompanied by uncertainty, especially in the industries of innovative technologies (i.e., wearable devices and sensors on healthcare), integrated supply chain, and sustainable operations management. Due to the outbreak of COVID-19 pandemics last year, it has become quite difficult for industries to quickly obtain their supplies and optimize their operations. Therefore, a Particle Swarm Optimization Retrospective Approximation (PSORA) algorithm is proposed to solve and validate the problem using a unimodal example and sensitivity analysis. PSORA uses the framework of Retrospective approximation (RA) to iteratively solve a sequence of sample path approximation problems with increasing sample sizes;each sample path problem is solved by the improved PSO algorithm. When the sample size approaches infinite, the improved PSO algorithm solves the sample path problem to approximately identify the real objective function. Our simulation results show that PSORA is robust, and converges quickly. The result of the developed optimal model can provide marginal insights to decision-makers in problem-solving. © 2021 IEEE.

A Geospatial Analysis of Tweets During Post-circuit Breaker in Singapore

Since 19 July 2020, Singapore entered Phase 2 of re-opening after one and half month’s “Circuit Breaker” measures to curb the spread of COVID 19. Although most businesses and public places have resumed operation at a reduced capacity, individuals were strongly advised to practice social distancing and avoid crowds. Both implicit and explicit measures to prevent overcrowding had impacted on how people visit places in Singapore. The current study used geotagged Twitter data between September to October in 2020 to examine the spatial and temporal patterns of residents’ locations in Singapore and explored the service amenities which remain “attractive” to residents. Random Forest Supervised Machine Learning Model was used to train and predict spatial distribution of activities during off-work recreational hours using service amenities point of interests (POIs) and land use merge. Five explanatory variables used were parks, public links between parks and malls, taxi stands, residential areas, and shopping malls which had the strongest influence in driving the model prediction of spatial distribution of activities in off-work recreational hours. While distinct temporal patterns of tweets were expected during office hour, this analysis revealed no such statistically significant clusters. The regression analysis showed that distances to service amenities did not provide strong explanations for tweeting patterns. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Spatiotemporal Characteristics and Resilience of Urban Network Structure during the Spring Festival Travel Rush: A Case Study of Urban Agglomeration in the Middle Reaches of Yangtze River in China

With the increasing trend of globalization, large-scale and diffuse population flow have become vital carriers characterizing users' spatial behaviors. Network analysis provides a new perspective to uncover the topology and evolution of the population flow and understand its influence on regional development. By gathering the Autonavi migration index during the Spring Festival travel rush (SFTR) in 2019, 2020, and 2021, the population flow networks among 31 cities of urban agglomeration in the middle reaches of the Yangtze River were constructed to analyze spatiotemporal dynamic characteristics and explore the structure resilience. Results show that although the changing trends of population flow during the 40-day SFTR of 2019, 2020, and 2021 are consistent, the population floating scale in 2020 and 2021 shows remarkable abnormalities before and after the Spring Festival due to the need for prevention and control of COVID-19. The intensity of population floating of the regional urban network in 2020 was the weakest, and Changsha became the focus of most population flow, while Wuhan was the most advantageous city in 2019 and 2021. As the third core city in the regional network, the siphon effect of Nanchang was still weak. A situation of tripartite confrontation in the region is formed. However, the higher intensity of population flow in 2021 increased the instability of the regional urban network, potentially exposing the region to higher risks and pressures. Therefore, it is necessary to pay more attention to the peripheral cities to improve regional resilience. © 2021 Shimei Wei and Jinghu Pan.

Consumer Stockpiling Across Cultures During the COVID-19 Pandemic

On March 11, 2020, the World Health Organization declared the COVID-19 (coronavirus) outbreak a pandemic. In the following days, media reports showed that consumers increasingly stockpiled groceries and household supplies. Interestingly, behavioral data show that this stockpiling exhibited considerable heterogeneity across countries. Building on cultural dimension theory, the authors theorize that this heterogeneity can be explained by countries’ cultural values: consumer stockpiling after the World Health Organization's announcement was more pronounced in countries whose residents show high uncertainty avoidance, low long-term orientation, low indulgence, and high individualism. The authors confirm these propositions using global mobility data from Google matched with country-level data on cultural values, pandemic reaction policies, and other key variables. This research note thereby integrates the previously disconnected literature on cultural dimension theory and consumer stockpiling in general, as well as provides new and significant knowledge about cross-cultural consumer behavior in crises. Furthermore, the authors provide actionable insights for international policy makers and business managers who aim to predict or control consumer stockpiling in future global crises to enhance consumer well-being. © The Author(s) 2021.