Service center location problems with decision dependent utilities and a pandemic case study

We study a service center location problem with ambiguous utility gains upon receiving service. The model is motivated by the problem of deciding medical clinic/service centers, possibly in rural communities, where residents need to visit the clinics to receive health services. A resident gains his utility based on travel distance, waiting time, and service features of the facility that depend on the clinic location. The elicited location-dependent utilities are assumed to be ambiguously described by an expected value and variance constraint. We show that despite a non-convex nonlinearity, given by a constraint specified by a maximum of two second-order conic functions, the model admits a mixed 0-1 second-order cone (MISOCP) formulation. We study the non-convex substructure of the problem, and present methods for developing its strengthened formulations by using valid tangent inequalities. Computational study shows the effectiveness of solving the strengthened formulations. Examples are used to illustrate the importance of including decision dependent ambiguity. An illustrative example to identify locations for Covid-19 testing and vaccination is used to further illustrate the model and its properties. © 2023 The Authors. Naval Research Logistics published by Wiley Periodicals LLC.

COVID-19 and Haters - A User Model Perspective

In this study, we present an in-depth analysis of users' propensity toward negative and hateful behavior during the COVID-19 pandemic. We analyze a large dataset extracted from Twitter from the months of January 2020 up until June 2020. The dataset includes 2,470,888 tweets from 3,269 users who are active over a period of six months. We model users' propensity toward hateful content over time by leveraging Random Forest regressor model and Long Short-Term Memory (LSTM) based many-to-one and Sequence2Sequence models for both short and long-term predictions. Our models leverage a set of features for each user, including the user's psychological traits. We also study the impact of external triggers, such as COVID-related news concurrent with the users' activities. To encode popular news, we propose using encoder states of a Sequence2Sequence model as features for a Tree-based regressor. The regressor, when combined with the vectorized news, results in an accurate prediction of tweeter's hateful behavior in the short (decoder size of four weeks) and long term (decoder size of 10 weeks) with a total training data of 15 weeks x 3269 users. We also show that our model accurately profiles selected groups of users, as they are defined by specific psychological traits. © 2022 IEEE.

A Framework of a User Interface Covid-19 Diagnosis Model

The world is facing the global challenge of COVID-19 pandemics, which is a topic of great concern.It is a contagious disease and infects others very fast.Artificial intelligence (AI) can assist healthcare professionals in assessing disease risks, assisting in diagnosis, prescribing medication, forecasting future well, and may be helpful in the current situation.Designing, a user-friendly Web application-based diagnosis model framework, is more useful in health care.The study focuses on a Web-based model for diagnosing the COVID-19 patients without direct contact with the patient.Chest CT scans have been important for the testing and diagnosing of COVID-19 disease.The Web-based model would take inputs, CT scan images, and users' symptoms and display classification results: NON-COVID-19 or COVID-19 infected. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

A Framework of a User Interface Covid-19 Diagnosis Model

The world is facing the global challenge of COVID-19 pandemics, which is a topic of great concern.It is a contagious disease and infects others very fast.Artificial intelligence (AI) can assist healthcare professionals in assessing disease risks, assisting in diagnosis, prescribing medication, forecasting future well, and may be helpful in the current situation.Designing, a user-friendly Web application-based diagnosis model framework, is more useful in health care.The study focuses on a Web-based model for diagnosing the COVID-19 patients without direct contact with the patient.Chest CT scans have been important for the testing and diagnosing of COVID-19 disease.The Web-based model would take inputs, CT scan images, and users’ symptoms and display classification results: NON-COVID-19 or COVID-19 infected. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Dealing with stress in new normal after the onset of COVID-19 – a study on public sector bank employees

The paper attempts to address issues related to occupational and personal stress faced by bank employees in new normal post-COVID-19, understand its impact on their mental and physical health, and how yoga and meditation can help them to develop self-care capabilities to manage stress in a eustress way. Structured questionnaires were used to collect first-hand data from employees working in public sector banks across India. Factor analysis was conducted on 21 statements which led to the creation of six factors. Using the clustering method, three clusters were identified to determine the profile of employees. This was followed by impact analysis and analysis of coping mechanisms. The study found that bank employees have been mainly grappling with mental health. The study recommends employees to adopt self-care tools to replace the script of fear, anxiety, depression, and insecurity with health, happiness, and joy. © 2021 Inderscience Enterprises Ltd.

Impact assessment of COVID-19 on digital payment: an Indian perspective

The psychological and socioeconomic impact of the COVID-19 pandemic is significant and has changed the global order. Strict confinement has changed our everyday life and our buying behaviour. The purpose of this paper is to examine the impact of COVID-19 on the behaviour of digital payments in the Indian context. The cluster analysis technique is used to classify the types of customers according to their payment behaviour. The first group of clients may be described as ‘late majority’ and the second group of clients as ‘early majority’. The results suggest that fear of COVID-19 has contributed to digital initiatives by banks. The findings of this paper can be used by private and public sector banks or other small banks to understand the future implications of it in their payment operations and future policy to optimise the operational cost. © 2021 Inderscience Enterprises Ltd.

Challenges to Mental Well-being, Perceived Resources, and Felt Needs During COVID-19 Among College Youth in India

COVID-19 has significantly impacted the mental health and well-being of college youth across the world. An online survey using checklists and open-ended questions was shared across various institutions in India to capture information about challenges faced, internal and external resources utilized to deal with the stress, existing support systems and suggestions for additional support for maintaining well-being by college youth. Thematic analysis was conducted to understand the emergent themes. Findings suggested that the most challenging aspect of the pandemic was worry about academics, career, and health of loved ones. The most useful self-management strategies to deal with stress were pursuing hobbies, learning new things, spending time with family, sharing concerns and positive self-talks. The students suggested more robust academic as well as mental health support mechanisms at the university level. At the community level students highlighted the need for community based mental health programs and more support from families. This is one of the very first exploratory studies on the potential mental health impact of the pandemic on Indian university students. © This work is licensed under a Creative Commons Attribution-No Derivative Works 2.5 India License

The relationship between symptoms and functional physiological outcomes in survivors of severe COVID-19 pneumonia

P136 Table 1Results of correlation analysis Correlation analysis 4MGS 1STSreps SpO2% desaturation Results r p-value r p-value r p-value Pre-COVID mMRC dyspnoea score 0(0–1) -0.267** <0.001 -0.285** <0.001 -0.108 0.094 Post-COVID mMRC dyspnoea score 1(0–2) -0.442** <0.001 -0.457** <0.001 -0.143* 0.025 NRS breathlessness 3(0–5) -0.287** <0.001 -0.406** <0.001 -0.490 0.445 NRS fatigue 3(0–5) -0.315** <0.001 -0.379** <0.001 -0.190* 0.003 NRS cough 0(0–2) -0.660 0.292 -0.153* 0.017 0.083 0.194 NRS pain 1(0–4) -0.278** <0.001 -0.346** <0.001 -0.188* 0.003 NRS sleep difficulty 2(0–5) -0.246** <0.001 -0.386** <0.001 -0.122 0.057 Data are presented as median (interquartile range) or frequency (proportion%;95% confidence interval). SpO2% desaturation = SpO2% desaturation from baseline during 1 minute sit to stand test;1STSreps = repetitions per minute during 1 minute sit to stand test;4MGS = 4 metre gait speed;mMRC = modified Medical Research Council;NRS = 0 – 10 numerical rating scale;r = Spearman correlation coefficient. *indicates statistical significance at 0.05 level. **indicates statistical significance at 0.001 level.ConclusionRespiratory symptoms were not strong predictors of 4-metre gait speed and 1-minute sit-to-stand test performance. These data highlight the importance of face-to-face testing to objectively assess functional limitation in patients recovering from severe COVID pneumonia.

Clinical, functional and psychological characteristics of survivors of severe COVID-19 pneumonia: a comparison of outcomes from the first and second waves

P135 Table 1Patient demographics, self-reported scores and functional test results by wave 1st wave 2nd wave p-value Demographics n=167 n=141 Age 59±13 58±12 0.564 Female 60 (35.93;28.94–43.40) 62 (43.97;35.97–52.22) 0.15 BMI (kg/m2) 30.5 (26.6–35.2) 32.1 (28.5–37.9) 0.009 ** BAME 115 (69.7;62.39–76.32) 72 (59.5;50.62–67.94) 0.073 Number of comorbidities 2 (1–3) 2 (1–3) 0.144 Patients Receiving Drugs Dexamethasone 11 (6.63;3.57–11.17) 138 (97.87;94.43–99.40) <0.001 *** Remdesivir 18 (10.84;6.79–16.24) 81 (57.45;49.20–65.39) <0.001 *** Other Immunomodulator 2 (1.20;0.25–3.81) 31 (21.99;15.76–29.35) <0.001 *** Questionnaire Scores n=164 n=132 NRS Breathlessness 2 (0–5) 3 (0–5) 0.153 ≥4 56 (34.78;27.75–42.36) 52 (37.14;29.47–45.34) 0.67 NRS Cough 0 (0–2) 0 (0–3) 0.439 ≥4 17 (10.56;6.52–16.00) 18 (13.64;8.59–20.26) 0.419 NRS Fatigue 3 (0–5) 3 (0–5) 0.867 ≥4 65 (40.63;33.24–48.35) 48 (36.92;28.99–45.43) 0.52 NRS Pain 0 (0–5) 1 (0–3) 0.682 ≥4 44 (27.50;21.03–34.78) 30 (23.08;16.48–30.86) 0.39 NRS Sleep disturbance 2 (0–5) 2 (0–5) 0.558 ≥4 52 (32.50;25.61–40.02) 49 (37.40;29.47–45.89) 0.382 Pre-COVID-19 mMRC 1 (0–2) 1 (1–2) 0.478 Post-COVID-19 mMRC 0 (0–1) 0 (0–1) 0.329 Post-COVID-19 mMRC ≥2 66 (40.99;33.61–48.70) 49 (38.58;30.45–47.23) 0.678 PCFS 2 (0–3) 1 (0–2) 0.055 PCFS ≥2 80 (50.00;42.31–57.69) 51 (42.15;33.62–51.05) 0.191 PHQ-9 ≥10 32 (20.38;14.66–27.19) 29 (23.02;16.33–30.92) 0.592 GAD-7 ≥10 34 (21.38;15.56–28.24) 16 (12.80;7.81- 19.49) 0.059 TSQ ≥6 43 (27.56;21.01–34.94) 27 (22.31;15.60–30.33) 0.319 Functional Tests n=160 n=139 4MGS <0.8 (ms-1) 67 (42.41;34.89–50.19) 47 (35.07;27.38–43.40) 0.201 1STS repetitions 18 (12–23) 17 (12–21) 0.460 <2.5 percentile 96 (60.00;52.29–67.36) 108 (77.70;70.25–84.00) 0.011 * Desaturation ≥4% 52 (34.67;27.40–4 .52) 42 (32.31;24.73–40.67) 0.677 Parametric data are presented as mean ± standard deviation, non-parametric data are presented as median (interquartile range) or frequency (proportion;95% confidence interval). Statistical significance indicated by * (p<0.05), ** (p<0.01), *** (p<0.001). BMI = Body mass index, BAME = Black, Asian or minority ethnic, NRS = Numerical rating scale (0–10), mMRC = modified Medical Research Council for dyspnoea (0–4), PCFS = Post-COVID-19 functional status scale (0–4), PHQ-9 = Patient health questionnaire 9 (0–27), GAD-7 = General Anxiety Disorder-7 scale (0–21), TSQ = Trauma screening questionnaire (0–10), 4MGS = 4-metre gait speed, 1STS = 1-minute sit-to-stand.ConclusionDespite shorter admission duration, and less frequent IMV, the burden of symptoms and functional limitation experienced post-hospitalisation for severe COVID-19 pneumonia was at least as severe during Wave 2 as in Wave 1. Identification of contributing factors and impact on post-COVID rehabilitation outcomes requires further study.

A privacy-enabled platform for COVID-19 applications: Poster abstract

We present our experiences in adapting and deploying TIPPERS1, a novel privacy-enabled IoT data collection and management system for smart spaces, to facilitate the monitoring of adherence to COVID-19 regulations in a university campus and a military facility. © 2020 Owner/Author.