Analysis and modeling of changes in online shopping behavior due to Covid-19 pandemic: A Florida case study

Classification of chronic ankle instability using machine learning technique based on ankle kinematics during heel rise in delivery workers

Objective

Ankle injuries in delivery workers (DWs) are often caused by trips, and high recurrence rates of ankle sprains are related to chronic ankle instability (CAI). Heel rise requires joint angles and moments similar to those of the terminal stance phase of walking that the foot supinates. Thus, our study aimed to develop, determine, and compare the predictive performance of statistical machine learning models to classify DWs with and without CAI using ankle kinematics during heel rise.

Methods

In total, 203 DWs were screened for eligibility. Seven predictors were included in our study (age, work duration, body mass index, calcaneal stance position angle [CSPA] in the initial and terminal positions during heel rise, calcaneal movement during heel rise [CMHR], and plantar flexion angle during heel rise). Six machine learning algorithms, including logistic regression, decision tree, AdaBoost, Extreme Gradient boosting machines, random forest, and support vector machine, were trained.

Results

The random forest model (area under the curve [AUC], 0.967 [excellent]; F1, 0.889; accuracy, 0.925) confirmed the best predictive performance in the test datasets among the six machine learning models. For Shapley Additive Explanations, old age, low CMHR, high CSPA in the initial position, high PFA, long work duration, low CSPA in the terminal position, and high body mass index were the most important predictors of CAI in the random forest model.

Conclusion

Ankle kinematics during heel rise can be considered in the classification of DWs with and without CAI.

Prevalence of pharmaceuticals and personal care products, microplastics and co-infecting microbes in the post-COVID-19 era and its implications on antimicrobial resistance and potential endocrine disruptive effects

The COVID-19 (coronavirus disease 2019) pandemic's steady condition coupled with predominance of emerging contaminants in the environment and its synergistic implications in recent times has stoked interest in combating medical emergencies in this dynamic environment. In this context, high concentrations of pharmaceutical and personal care products (PPCPs), microplastics (MPs), antimicrobial resistance (AMR), and soaring coinfecting microbes, tied with potential endocrine disruptive (ED) are critical environmental concerns that requires a detailed documentation and analysis. During the pandemic, the identification, enumeration, and assessment of potential hazards of PPCPs and MPs and (used as anti-COVID-19 agents/applications) in aquatic habitats have been attempted globally. Albeit receding threats in the magnitude of COVID-19 infections, both these pollutants have still posed serious consequences to aquatic ecosystems and the very health and hygiene of the population in the vicinity. The surge in the contaminants post-COVID also renders them to be potent vectors to harbor and amplify AMR. Pertinently, the present work attempts to critically review such instances to understand the underlying mechanism, interactions swaying the current health of our environment during this post-COVID-19 era. During this juncture, although prevention of diseases, patient care, and self-hygiene have taken precedence, nevertheless antimicrobial stewardship (AMS) efforts have been overlooked. Unnecessary usage of PPCPs and plastics during the pandemic has resulted in increased emerging contaminants (i.e., active pharmaceutical ingredients and MPs) in various environmental matrices. It was also noticed that among COVID-19 patients, while the bacterial co-infection prevalence was 0.2-51%, the fungi, viral, protozoan and helminth were 0.3-49, 1-22, 2-15, 0.4-15% respectively, rendering them resistant to residual PPCPs. There are inevitable chances of ED effects from PPCPs and MPs applied previously, that could pose far-reaching health concerns. Furthermore, clinical and other experimental evidence for many newer compounds is very scarce and demands further research. Pro-active measures targeting effective waste management, evolved environmental policies aiding strict regulatory measures, and scientific research would be crucial in minimizing the impact and creating better preparedness towards such events among the masses fostering sustainability.

The Application of Biometric Approaches in Agri-Food Marketing: A Systematic Literature Review

A challenge in social marketing studies is the cognitive biases in consumers' conscious and self-reported responses. To help address this concern, biometric techniques have been developed to obtain data from consumers' implicit and non-verbal responses. A systematic literature review was conducted to explore biometric applications' role in agri-food marketing to provide an integrated overview of this topic. A total of 55 original research articles and four review articles were identified, classified, and reviewed. It was found that there is a steady growth in the number of studies applying biometric approaches, with eye-tracking being the dominant method used to investigate consumers' perceptions in the last decade. Most of the studies reviewed were conducted in Europe or the USA. Other biometric techniques used included facial expressions, heart rate, body temperature, and skin conductance. A wide range of scenarios concerning consumers' purchase and consumption behaviour for agri-food products have been investigated using biometric-based techniques, indicating their broad applicability. Our findings suggest that biometric techniques are expanding for researchers in agri-food marketing, benefiting both academia and industry.

Investigating influencing factors for ICT adoption that changes travel behavior in response to the COVID-19 outbreak in Indonesia

Mobility and out-of-home activities restrictions from the COVID-19 pandemic have forced people to maximize their in-home activities. Considering the increase in Information and Communication Technology (ICT) adoption during the outbreak, this paper tries to shed light on the factors that influence changing travel behavior. For these purposes, the study uses data collected through an online questionnaire during the outbreak in Indonesia, which was then analyzed using cluster and discriminant analyses. The study found that online adaptation during the outbreak was affected by income level, whereby high-income individuals are associated with high online adaptation. Residential location also influences ICT adaptation during the outbreak. Cities with higher access to the internet and ICT platforms as well as higher income per capita tend to have higher ICT adoption. People with more experience with online platforms or services also record higher online in-home activity adoption during the outbreak. Furthermore, while the lower-income group tends to reduce their travel, the higher-income group still continues to travel to fulfil their household needs during the outbreak, such as in-store shopping. Since the lower-income group and less accessible areas tend to have difficulty in accessing ICT as a substitute for travel, this study recommends that the government and ICT stakeholders ensure equal access to ICT to support physical distancing and to limit mobility in order to flatten the peak of the pandemic.

COVID-19 outbreak: Impact on global economy

COVID-19 has been considered the most significant threat since World War II and the greatest global health disaster of the century. Wuhan City, Hubei Province, China, reported a new infection affecting residents in December 2019. The Coronavirus Disease 2019 (COVID-19) has been named by the World Health Organization (WHO). Across the globe, it is spreading rapidly, posing significant health, economic, and social challenges for everyone. The content of this paper is solely intended to provide a visual overview of COVID-19 global economic impact. The Coronavirus outbreak is causing a global economic collapse. Most countries have implemented full or partial lockdown measures to slow the spread of disease. The lockdown has slowed global economic activity substantially, many companies have reduced operations or closed down, and people are losing their jobs at an increasing rate. Service providers are also affected, in addition to manufacturers, agriculture, the food industry, a decline in education, the sports industry, and of entertainment sector also observed. The world trade situation is expected to deteriorate substantially this year.