A Study on The Prevalence of Overweight and Associated Risk Factors in Urban Adult Women (19-49 Years) Of South 24 Parganas, West Bengal, India

The prevalence of overweight and obesity is escalating worldwide, and it has been acknowledged as a global issue by the World Health Organization (WHO). Even though India's overweight rates are comparatively lower than those of Western countries, they are steadily increasing. Therefore, it becomes crucial to understand the extent of overweight in cities like Kolkata. The main objective of this study was to determine the prevalence of overweight among urban adult women (aged 19-49 years) in the South 24 Parganas district of West Bengal, India. A cross-sectional survey was conducted, involving 130 subjects, and a pre-tested questionnaire was used to collect data on socio-economic details, physical activity, dietary patterns, and perceptions and knowledge related to overweight through interviews. The outcome variables measured were Body Mass Index (BMI) and waist circumference (WC). Univariate, bivariate, and logistic regression analyses were performed using MS Excel. There was a 54% overweight prevalence among urban adult women, and a 67.4% abdominal obesity prevalence. Several factors were significantly associated with being overweight (having a BMI over 25). These factors included women perceiving themselves as thinner than they actually are, being aged over 35 years, and having a husband who is self-employed. In urban West Bengal, overweight, obesity, and abdominal obesity levels are considerably high. This highlights the urgency of addressing the issue of overweight in this region and calls for targeted interventions to promote healthier lifestyles and combat the growing problem of overweight and obesity

Detecting transitions between collective motion regimes using functional hypothesis test of the time-varying persistence homology

In a system of many similar self-propelled entities such as flocks of birds, fish school, cells and molecules, the interactions with neighbors can lead to a "coherent state", meaning the formation of visually compelling aggregation patterns due to the local adjustment of speed and direction. In this study, we explore one of the open questions that arise in studying collective patterns. When such entities, considered here as particles, tend to assume a coherent state beginning from an incoherent (random) state, what is the time interval for the transition? Also, how do model parameters affect this transition time interval? Given the observations of particle migration over a given time period as a point cloud data sampled at discrete time points, we use Topological Data Analysis, specifically persistent homology, to infer the transition time interval in which the particles undergo regime change. The topology of the particle configuration at any given time instance is captured by the persistent homology specifically Persistence Landscapes. We localize (in time) when such a transition happens by conducting the statistical significance tests namely functional hypothesis tests on persistent homology outputs corresponding to subsets of the time evolution. This process is validated on a known collective behavior model of the self-propelled particles with the regime transitions triggered by changing the model parameters in time. As an application, the developed technique was ultimately used to describe the transition in cellular movement from a disordered state to collective motion when the environment was altered.Comment: 21 pages, 13 figure

Explainable and High-Performance Hate and Offensive Speech Detection

The spread of information through social media platforms can create environments possibly hostile to vulnerable communities and silence certain groups in society. To mitigate such instances, several models have been developed to detect hate and offensive speech. Since detecting hate and offensive speech in social media platforms could incorrectly exclude individuals from social media platforms, which can reduce trust, there is a need to create explainable and interpretable models. Thus, we build an explainable and interpretable high performance model based on the XGBoost algorithm, trained on Twitter data. For unbalanced Twitter data, XGboost outperformed the LSTM, AutoGluon, and ULMFiT models on hate speech detection with an F1 score of 0.75 compared to 0.38 and 0.37, and 0.38 respectively. When we down-sampled the data to three separate classes of approximately 5000 tweets, XGBoost performed better than LSTM, AutoGluon, and ULMFiT; with F1 scores for hate speech detection of 0.79 vs 0.69, 0.77, and 0.66 respectively. XGBoost also performed better than LSTM, AutoGluon, and ULMFiT in the down-sampled version for offensive speech detection with F1 score of 0.83 vs 0.88, 0.82, and 0.79 respectively. We use Shapley Additive Explanations (SHAP) on our XGBoost models' outputs to makes it explainable and interpretable compared to LSTM, AutoGluon and ULMFiT that are black-box models

Mood Responses to Various Exercise Types Using the Ontological Definitions of Exercise

Recently, a new ontological way of exploring sport and physical activity (PA) has been proposed: the type of PA performed is classified using the four ontological dimensions. This phenomenon has classified PA as individual (I-me), encounter (I-You), team (I-Society), and nature (I-Nature). There has only been one study that has examined how participating in these various types of PA influences moods; however, that study asked individuals to recall what types of PA were performed and how they felt more than 60 days before the commencement of the study. PURPOSE: To identify whether daily moods differ based on the four ontological dimensions of PA. METHODS: Subjects (n=144) were recruited from a small, private university in rural New York and asked to fill out the POMS-SF daily for 60 days. Participants (n=67) who completed 14 or more days of the survey were included in this study. Self-reported exercise type was classified based on the ontological dimension; however, if participants performed more than one type the day was classified as I-Multiple. Moods were scored using previously published methodology. Due to the non-normal distribution of data, a series of Kruskal-Wallis and post-hoc Dunn’s tests were used. RESULTS: On days participants performed I-society activities, they reported significantly lower feelings of depression (pCONCLUSION: The findings support the need for PA, as they suggest that performing PA increases feelings of energy. Interestingly, individual PA results in the greatest increase in feelings of energy. Findings also suggest that feelings of depression were lowest when performing PA with several people. The depression findings may be explained by the fact that data was collected during the COVID-19 pandemic where our participants were socially distancing on most days

Factors influencing motivation to perform mental and physical tasks during the initial lockdown period of the COVID-19 pandemic

International Journal of Exercise Science 15(5): 1600-1615, 2022. Drastic changes to lifestyles have occurred during the COVID-19 pandemic. An unintended consequence of stay at home orders is increased isolation and less social interaction for many people. For overall wellbeing it is important to stay both physically and mentally active; however, for many individual’s motivation may be a barrier. There are non-modifiable (e.g. sex, age, personality, infection rates in the area) and modifiable factors (e.g. physical activity, diet, sleep) that may be associated with motivation to perform physical and mental tasks. We collected data from 794 subjects using an online survey between April 13th to May 3rd of 2020. Survey questionnaires included demographics, personality traits, diet, sleep, physical activity levels, mental workload and motivation to perform mental and physical tasks. Multiple linear regression analyses were used to assess the association between non-modifiable and modifiable variables on motivation to perform mental and physical tasks. The results of our analyses suggest that those who reported a higher quality of diet (REAP-S score), exercised vigorously, and reduced their sedentary time, reported higher motivation to perform both mental and physical tasks. Those who were employed and had higher grit were more motivated to perform physical tasks. Lower trait physical energy was associated with greater motivation to perform mental tasks. Our findings support that during challenging times, such as the COVID-19 pandemic, it is important for healthcare practitioners to emphasize the importance healthy lifestyle behaviors to prevent individuals from experiencing a lack of motivation to perform both mental and physical tasks. Future research should focus on trying to determine the directionality of the relationship between specific healthy lifestyle behaviors and motivation

Factors Influencing Motivation to Perform Mental and Physical Tasks during the Initial Lockdown Period of the COVID-19 Pandemic

Drastic changes to lifestyles have occurred during the COVID-19 pandemic. A consequence of non-pharmaceutical interventions (NPIs) used against this health crisis, such as stay-at-home orders, has been increased isolation and less social interaction for a majority of people. For overall wellbeing, it is important to stay both physically and mentally active. However, for many individuals motivation may be a barrier. There are non-modifiable (e.g., sex, age) and modifiable factors (e.g., physical activity, diet) that may be associated with motivation to perform physical/mental tasks. PURPOSE: To explore if there is an association between non-modifiable and modifiable variables on motivation to perform mental/physical tasks under COVID-19 NPIs. METHODS: We collected data from 794 subjects using Qualtrics and each subject completed our survey once each week during April 1st to May 3rd of 2020. This is an ongoing study that will terminate when the COVID-19 pandemic ends. Survey questionnaires included demographics, personality traits, diet, physical activity levels, and motivation to perform mental/physical tasks. Multiple linear regression analyses were used for statistical analysis. RESULTS: Significant results include: a) those who reported a higher quality of diet (REAP-S score) (β=.015, p\u3c0.05; β=0.000, p\u3c0.001), exercised vigorously (β=0.005, p\u3c0.01; β=0.000, p\u3c0.001), and reduced their sedentary time (β=.000, p\u3c0.01; β=.000, p\u3c0.001), reported higher motivation to perform both mental and physical tasks, respectively; b) those who were employed (β=.043, p\u3c0.05) and had higher grit (β=.041, p\u3c0.05) were more motivated to perform physical tasks; and c) lower trait physical energy was associated with greater motivation to perform mental tasks (β=.027, p\u3c0.05). CONCLUSION: Our findings indicate that living a healthy lifestyle is associated with motivation to perform both mental and physical tasks during the initial lockdown period of the COVID-19 pandemic. These preliminary results support the continuation of data collection. Future research should focus on trying to determine the directionality of the relationship between healthy lifestyle behaviors and motivation

Utilizing logistic regression to compare risk factors in disease modeling with imbalanced data: a case study in vitamin D and cancer incidence

Imbalanced data, a common challenge encountered in statistical analyses of clinical trial datasets and disease modeling, refers to the scenario where one class significantly outnumbers the other in a binary classification problem. This imbalance can lead to biased model performance, favoring the majority class, and affecting the understanding of the relative importance of predictive variables. Despite its prevalence, the existing literature lacks comprehensive studies that elucidate methodologies to handle imbalanced data effectively. In this study, we discuss the binary logistic model and its limitations when dealing with imbalanced data, as model performance tends to be biased towards the majority class. We propose a novel approach to addressing imbalanced data and apply it to publicly available data from the VITAL trial, a large-scale clinical trial that examines the effects of vitamin D and Omega-3 fatty acid to investigate the relationship between vitamin D and cancer incidence in sub-populations based on race/ethnicity and demographic factors such as body mass index (BMI), age, and sex. Our results demonstrate a significant improvement in model performance after our undersampling method is applied to the data set with respect to cancer incidence prediction. Both epidemiological and laboratory studies have suggested that vitamin D may lower the occurrence and death rate of cancer, but inconsistent and conflicting findings have been reported due to the difficulty of conducting large-scale clinical trials. We also utilize logistic regression within each ethnic sub-population to determine the impact of demographic factors on cancer incidence, with a particular focus on the role of vitamin D. This study provides a framework for using classification models to understand relative variable importance when dealing with imbalanced data

Inhibition of the epidermal growth factor receptor by erlotinib prevents immortalization of human cervical cells by Human Papillomavirus type 16

AbstractThe Human Papillomavirus type-16 (HPV-16) E6 and E7 oncogenes are selectively retained and expressed in cervical carcinomas, and expression of E6 and E7 is sufficient to immortalize human cervical epithelial cells. Expression of the epidermal growth factor receptor (EGFR) is often increased in cervical dysplasia and carcinoma, and HPV oncoproteins stimulate cell growth via the EGFR pathway. We found that erlotinib, a specific inhibitor of EGFR tyrosine kinase activity, prevented immortalization of cultured human cervical epithelial cells by the complete HPV-16 genome or the E6/E7 oncogenes. Erlotinib stimulated apoptosis in cells that expressed HPV-16 E6/E7 proteins and induced senescence in a subpopulation of cells that did not undergo apoptosis. Since immortalization by HPV E6/E7 is an important early event in cervical carcinogenesis, the EGFR is a potential target for chemoprevention or therapy in women who have a high risk for cervical cancer

Measuring the impact of student success retention initiatives for engineering students at a private research university

IntroductionStudent success in Science, Technology, Engineering, and Mathematics (STEM) is a national concern. To increase engineering retention and graduation rates at a small private institution, a university council developed a binary classifier to identify high-risk students and proposed interventions that included decoupling first-year Physics and Calculus courses, support in introductory Calculus, and Spatial Visualization (SV) training. This paper aims to validate the binary classifier used to identify the under-prepared students entering their first year and assess the impact of the interventions. We provide a comparative analysis of student success metrics for high-risk engineering students across a decade of cohorts, including 5 years before (2006–2010) and 5 years after (2011–2015) implementation of intentional strategies.MethodsWe validated the binary classifier using an accuracy measure and Matthews Correlation Coefficient (MCC). We used the 2-population proportion test to compare STEM retention and 4- and 6-year graduation rates of High-Risk engineering students before and after interventions and compare student performance in early foundation STEM courses across the same time frame.ResultsThe binary classification model identified High-Risk students with an accuracy of 63–70% and an MCC of +0.28 to +0.30. In addition, we found statistically significant improvement (p < 0.001) in the STEM retention rates, 6-year graduation rates, and first part of Physics, Calculus, and Chemistry sequences after the interventions.DiscussionThe methodology and strategies presented may provide effective guidance for institutions seeking to improve the overall performance of undergraduate students who otherwise might struggle in their first-year engineering curriculum

Trait Energy and Fatigue Modify Acute Ingestion of an Adaptogenic-Rich Beverage on Neurocognitive Performance

Background: Psychological research considers traits as a long-standing pre-disposition to an individual’s mood, whereas short-term feelings are categorized as states. We previously reported similar overall acute mental performance benefits between an adaptogen-rich, caffeine-containing energy shot (e+Energy Shot–e+Shot; Isagenix International, LLC) and a caffeine-matched placebo Since the publication of that study, multiple studies have reported that trait mental and physical energy (TME/TPE), and trait mental and physical fatigue (TMF/TPF) status modify the effect of various interventions on neurocognitive performance. Therefore, we reevaluated our previously published work and accounted for the four traits. Methods: Participants (n = 30) completed a series of questionnaires to determine baseline trait energy and fatigue measures. Then, participants performed a 27 min battery of neurocognitive tasks before and three times after consuming the study beverages with 10 min breaks between each post-consumption battery of tests. Data from the previous study were re-analyzed using linear mixed-effects models. Results: We now report that the adaptogen product significantly improved mood and cognitive test responses in individuals stratified by initial TME, TPE, TMF, and TPF status. Moreover, this reevaluation also indicated that the caffeine placebo significantly increased heart rate and blood pressure in those subjects initially characterized by low physical and mental energy. Conclusions: In summary, a post-hoc re-analysis of our initial study suggests that consumption of the adaptogen-rich, caffeine-containing product preferentially benefited individuals with initial low TME/TPE and high TMF status when compared to caffeine alone. These findings also support our previous study suggesting that adaptogens may promote mental and physical performance benefits while modulating potentially negatively associated responses to caffeine