The perspective of energy poverty and 1st energy crisis of green transition

The role of energy transition amidst the energy crisis and how policymakers can drive down emissions while focusing on energy security are critical. Given the geo-political situation, energy crisis volatility, energy shortage and climate change all affect the green transition and the short-term priorities for energy companies and policymakers. Energy security is not an isolated issue but has widespread implications as various sectors depend on energy supply to function properly. Governments around the world are faced with this trilemma, how to balance energy security with energy sustainability while also considering energy affordability. Sustainability has been in focus for about a decade. However, energy security is suddenly becoming one of the most important priorities that policymakers need to consider. Unfortunately, the renewable energy infrastructure is not yet ready to replace the growing volume of energy demand from hydrocarbon, which the world has been dependent on. This means, for now, a surge in energy generation through hydrocarbon to meet the existing energy demand deficit. However, it is important not to lose focus on the challenge of energy sustainability and climate change adaption and mitigation. Where trends like carbon capture and storage;solar, wind, hydro, green hydrogen, etc.;renewable energy infrastructure and integrations, with supply chain and engineering services consideration [in aspect for the growing market in this space] need better attention with regards to investment and full-scale implementation. This paper aims to analyze this 1st energy crisis of green transition with a priori on energy poverty with consideration of major influences and associated impacts. Furthermore, it proposes a specific framework for inclusive investigations, which considers the entire energy ecosystem with consideration of major influences, to enable the policymakers to better drive the green transition. This involves formulating energy policies that are not entirely conservative towards renewable energy sources but instead promote investments in both green and relatively more environmentally benign energy sources compared to high emission hydrocarbons. In this regard, this paper renders exhaustive prospects and recommendations. © 2023 Elsevier Ltd

Comparative Efficacy of High Dose Dexamethasone (8 mgx TDS) vs Low Dose Methylprednisoslone (100 mgx BD) Therapy in Patients with Covid Pneumonia

Background: Around one and half years ago in the December of 2019 a flu like disease emerged in the city Wuhan located in China. This was termed by WHO as a global pandemic due to its rapid widespread. Aim: To compare the efficacy of high dose dexamethasone (8 mgx tds) vs low dose methylprednisoslone (100 mgx bd) therapy for two weeks, in resolution of acute inflammatory markers in patients with covid pneumonia. Study Design: Quasi experimental study. Methodology: Patients (n=72) with an age range of 18-70 years with Covid 19 PCR positive having Covid associated pneumonia were enrolled. Group 1 containing 36 patients receiving high dose dexamethasone (8 mgx TDS) and group 2 with 36 participants receiving low dose methylprednisolone (100 mgx BD). Inflammatory markers (CRP, ESR and Ferritin) were recorded on Day 1 (T1) on day 7 (T2) and day 14 (T3). Patients who required ventillatory support and those who died was also recorded.All this information was recorded on Performa. Data was analyzed using SPSS version 26. Results: Mean age of the patients was 50.11±11.7 years. When we compared the inflammatory markers among group 1 and group 2 at T1, T2 and T3 no statistically significant difference was obtained. Conclusion: It was concluded that high dose dexamethasone and low dose methylprednisoslone therapy for two weeks were equally effective in resolution of acute inflammatory markers in patients with covid pneumonia.

Gis-based vulnerability analysis of the United States to COVID-19 occurrence. (Special Issue: COVID-19 one year on.)

The outbreak of COVID-19 in the United States has resulted in over 11.2 million cases and over 240 thousand deaths. COVID-19 has affected the society in unprecedented way with its socioeconomic impact yet to be determined. This study aimed at assessing the vulnerability of the US at the county-level to COVID-19 using the pandemic data from January to June of the year 2020. The study considered the following critical factors: population density, elderly population, racial/ethnic minority population, diabetics, income, and smoking adults. Pearson's correlation analysis was performed to validate the independence of the factors. Spatial correlations between the COVID-19 occurrence and the factors were examined using Jaccard similarity analysis, which revealed relatively high correlation. A vulnerability to COVID-19 map with a five-level Likert scale was created using Logistic Regression Analysis in ArcGIS. The map showed close agreement in seven representative states, which were selected based on COVID-19 cases including NY, CA, FL, TX, OH, NC, and MT with R2 values between 0.684 and 0.731 with Root Mean Squared Error (RMSE) values between ..0.033 and ..0.057. Furthermore, vulnerability levels from 'High' to 'Very High' were obtained for the top ten counties with the highest COVID-19 cases with residual values less than or equal to 0.04. The method and resulted vulnerability map can aid in COVID-19 response planning, prevention programs and devising strategies for controlling COVID-19 and similar pandemics in the future.

Mental Health Status of Health Care Professionals during COVID-19 Pandemic at a Tertiary Care Hospital of Central Punjab

Introduction: Frontline medical workers are at risk of not just adverse physical outcomes from Corona Virus Disease 2019 (COVID-19) but psychological ones too. Healthcare workers might develop symptoms of Post-traumatic stress disorder, depression, anxiety and substance use disorders. Objective: To assess the mental health status of health care professionals during COVID-19 Pandemic at a tertiary care hospital of Central Punjab. Methodology: Study design: Cross-Sectional study. Study setting: Sheikh Zayed Medical College/Hospital, R.Y.Khan. Study Duration: 20th May 2020 to 20th August 2020. Study subjects: Healthcare professionals including medical and paramedical staff. Sample size: A total of 215 Subjects were included in the study. Sampling technique: Convenient sampling technique. Inclusion criteria: Male and female health care professionals of SZMC/H, R.Y.Khan present in a single working shift. Exclusion criteria: Subjects who refused to give informed verbal consent and those absent from the shift of data collection. Data collection method: Data was collected on pre-designed questionnaire. The questionnaire included information regarding age, sex, job title, working station, etc. Data analysis: Data was entered in and analyzed by using SPSS Version. 21. Numerical variables like age was presented as mean ± standard deviation. Categorical variables like sex, job title, working station were shown as percentages. Results: Our study shows that sex ratio was Male (41.4%) and Female (58.6%). We compared the subjects on variables of Sex, Job title and Ward/Department. The prevalence of depression among Males was Normal 69.7%, Borderline 18.0% and Abnormal 12.4% while in Females it was Normal 56.3%, Borderline 20.6% and Abnormal 23.0%. The prevalence of anxiety among Males was Normal 67.4%, Borderline 18.0% and Abnormal 14.6% while in Females it was Normal 38.1%, Borderline 28.6% and Abnormal 33.3%. Our study on the basis of Job title showed that Medical Staff has prevalence of depression of Normal 67.8%, Borderline 18.3% and Abnormal 13.9% while in Paramedical Staff it was Normal 31.4%, Borderline 25.7% and Abnormal 42.9%. The prevalence of anxiety among Medical Staff was Normal 55.6%, Borderline 22.8% and Abnormal 21.7% while in Paramedical Staff it was Normal 22.9%, Borderline 31.4% and Abnormal 45.7%. On the basis of Wards/Department, the prevalence of Depression in Medicine and Allied was Normal 62.7%, Borderline 23.9% and Abnormal 13.4%;in Surgery and Allied was Normal 67.2%, Borderline 22.4% and Abnormal 10.3%;in Paeds and Gynae/Obs. was Normal 63.5%, Borderline 11.5% and Abnormal 25.0%;in Flu Filter Clinic/Isolation Ward/ICU was Normal 50.0%, Borderline 18.4% and Abnormal 31.6%. The prevalence of Anxiety in Medicine and Allied was Normal 52.2%, Borderline 20.9% and Abnormal 26.9%;in Surgery and Allied was Normal 55.2%, Borderline 24.1% and Abnormal 20.7%;in Paeds and Gynae/Obs. was Normal 46.2%, Borderline 26.9% and Abnormal 26.9%;in Flu Filter Clinic/Isolation Ward/ICU was Normal 44.7%, Borderline 26.3% and Abnormal 28.9%. Conclusion: COVID-19 Pandemic has some major effects on the mental health status of health care professionals in terms of depression and anxiety that need to be addressed by providing better health care facilities, by arranging awareness seminars and counseling sessions.

Assessment of gap between knowledge and practice of PPES among healthcare professionals during Covid-19"

Objective: To assess the gap between knowledge and practice of PPEs among healthcare professionals during COVID-19. Study design: Cross-Sectional study. Study setting: Sheikh Zayed Medical College/Hospital, Rahim Yar Khan. Study Duration: May-August 2020. Methodology: A total of 214 Healthcare professionals (including medical and paramedical staff) were included in this study using convenient sampling technique. Data was collected on pre-designed questionnaire. The questionnaire included information regarding age, sex, job title, working station, etc. then data was entered in and analyzed by using SPSS Version. 21. Numerical variables like age was presented as mean ± standard deviation. Categorical variables like sex, job title, working station were shown as percentages. Results: Our study included the subjects with 88 (41.1%) males and 126 (58.9%) females. Mean age of study subjects came out to be 26.6±3.954 years. It is observed that only 95 (44.4%) of the subjects have PPEs;only 85 (39.7%) were provided PPEs from their respective healthcare authorities and 137 (64%) can afford purchasing PPEs on their own. And there is a major gap seen between the knowledge about PPEs/appreciation of their effectiveness and the practice of PPEs by these healthcare professionals. Regarding PPEs (which include gown, surgical mask, N-95 mask, gloves, goggles, head cover, shoe cover, social distancing, hand sanitizer and hand washing), this lag is seen majorly among the healthcare professionals working in general wards;less among emergency staff and least among the subjects working at flu filter clinic or isolation wards. Conclusion: Majority of healthcare professionals appreciate the effectiveness of PPEs against corona virus but don't bring them into practice;either due to non-availability of PPEs or they have some attitude problem towards it.

Influence of Socio-Cultural Attributes on Stigmatizing Public Transport in Saudi Arabia

Several factors over the years have contributed to stigma in public transport. Many studies have highlighted the need to make the transport system more equitable both from economic and gender perspectives. This study attempts to demonstrate how the perceptions of public transport users and non-users are stigmatized from social and cultural standpoints. Thus, it identifies the social and cultural stigma-induced barriers embedded with the use and people's general perception about the public bus service, taking SAPTCO (Saudi Public Transport Company) as a case study. The study results suggest that privacy concern is the primary cause of stigma. Most of the users are unwilling to ride with their families as SAPTCO does not account for gender needs (e.g., privacy, travel convenience, safety, comfort, etc.). Moreover, people from the high-income classes are more stigmatized against this ridership. A fuzzy inference system (FIS) model is used to analyze the survey questionnaire responses and understand what stigma means for the public bus service. Expert opinions are employed to generate "if-then " rules of the FIS models. Sensitivity of the defined fuzzy model is conducted to different aspects of the ridership. The study results further suggest that "inconvenience " poses the highest impact while "feeling safe ", "privacy ", "fare ", "timing ", and "comfort " are found to be the medium impact-making variables for stigma. The stigma-defining variables would be critical for the public bus service to improve its service quality and help (re-)design the policies that would attract a high amount of ridership. Some solutions are suggested in the end that would complement, strengthen, and promote the current SAPTCO service. The demonstrated methodology of this study would be relevant and adaptive to any relevant context to improve public transportation service and pertaining policies.

Does the stringency of government interventions for COVID19 reduce the negative impact on market growth? Evidence from Pacific and South Asia

The objective of this study is to empirically assess the effect of government decisions on market growth in response to social distancing initiatives, government reactions, economic support provision, and containment and health responses, to name a few. A panel dataset of daily stock market returns is analysed in this study, changes in COVID-19 cases, and government responses to 17 countries in the Pacific and South Asia from 1st January 2020 to 31st December 2020. Findings indicate that social distancing policies have a significant negative effect on stock returns but a substantial positive impact on market growth when new cases' growth rate declines after accounting for country characteristics and systematic risk due to foreign factors. A direct negative effect is seen almost immediately, and a subsequently indirect positive effect is noted. As expected, policies regarding social distancing have an immediate negative impact, attributed mainly to the expected negative effect on economic activity. Subsequently, we see an indirect positive effect on market return because social distancing measures reduced the growth of confirmed COVID-19 cases. Both awareness, containment, and health index (ACHI) and Income Support and Debt Relief Index (ISDRI) positively affect market growth, as they are perceived to support individuals' socio-economic well-being and mainly result in positive market returns. © 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Segmentation of COVID-19 pneumonia lesions: A deep learning approach

Background: Lung CT scan has a pivotal role in diagnosis and monitoring of COVID-19 patients, and with growing number of affected individuals, the need for artificial intelligence (AI)-based systems for interpretation of CT images is emerging. In current investigation we introduce a new deep learning-based automatic segmentation model for localization of COVID-19 pulmonary lesions. Methods: A total of 2469 CT scan slices, containing 1402 manually segmented abnormal and 1067 normal slices form 55 COVID-19 patients and 41 healthy individuals, were used to train a deep convolutional neural network (CNN) model based on Detectron2, an open-source modular object detection library. A dataset, including 1224 CT slices of 18 COVID-19 patients and 9 healthy individuals, was used to test the model. Results: The accuracy, sensitivity, and specificity of the trained model in marking a single image slice with COVID-19 lesion were 0.954, 0.928, and 0.961, respectively. Considering a threshold of 0.4% for percentage of lung involvement, the model was capable of diagnosing the patients with COVID-19 pneumonia, with a sensitivity of 0.982% and a specificity of 88.5%. Furthermore, the mean Intersection over Union (IoU) index for the test dataset was 0.865. Conclusion: The deep learning-based automatic segmentation method provides an acceptable accuracy in delineation and localization of COVID-19 lesions, assisting the clinicians and researchers for quantification of abnormal findings in chest CT scans. Moreover, instance segmentation is capable of monitoring longitudinal changes of the lesions, which could be beneficial to patients’ follow-up. Copyright© Iran University of Medical Sciences