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The development of an accurate, non-invasive method for the diagnosis of peripheral artery disease (PAD) from accelerometer contact microphone (ACM) recordings of the cardiac system.Mel frequency cepstral coefficients (MFCCs) are initially extracted from ACM recordings. The extracted MFCCs are then used to fine-tune a pre-trained ResNet50 network whose middle layers provide streams of high-level-of-abstraction coefficients (HLACs) which could provide information on blood pressure backflow caused by arterial obstructions in PAD patients. A vision transformer is finally integrated with the feature extraction layer to detect PAD, and stratify the severity level. This architecture is coined multi-stream-powered vision transformer (MSPViT). The performance of MSPViT is evaluated on 74 PAD and 21 healthy subjects.Sensitivity, specificity, F1 score, and area under the curve (AUC) of 99.45%, 98.21%, 99.37%, and 0.99, respectively, are reported for the binary classification which ensures accurate detection of PAD. Furthermore, MSPViT suggests average sensitivity, specificity, F1 score, and AUC of 96.66%, 97.34%, 96.29%, and 0.96, respectively, for the classification of subjects into healthy, mild-PAD, and severe-PAD classes. The silhouette score is calculated to assess the separability of clusters formed for classes in the penultimate layer of MSPViT. An average silhouette score of 0.66 and 0.81 demonstrate excellent cluster separability in PAD detection and severity classification, respectively.The achieved performance suggests that the proximal ACM-driven framework can replace state-of-the-art techniques for PAD detection.This study presents a fundamental step towards prompt and accurate diagnosis of PAD and stratification of its severity level.

COVID-19 pandemic has disrupted schooling globally. Affecting millions of students, the conventional face-to-face (F2F) education system has been replaced by e-learning overnight. As the advantages, disadvantages, and technical challenges of this abrupt transformation were already well-documented, this study aimed to intensely scrutinize university students' experiences of e-learning practices in this new normal situation. Methods: Adopting the Interpretative Phenomenological Analysis (IPA), a smaller sample of respondents (N=25) was observed to gain deeper insights using semi-structured interviews. Data were analyzed and interpreted through thematic analysis. Findings revealed that most of the students have had unfavorable experiences with e-learning. The majority of students feel that e-learning has ruined their social relationships by isolating them from their peers and instructors. A significant number of students were observed to be anxious about their future due to unstable financial status, poor learning outcomes, and unfair evaluation processes. Moreover, poor self-esteem, anxiety, and depressive symptoms have been observed among a significant portion of the students. The overall findings of this study are meant to assist stakeholders in taking the necessary steps to address the aforementioned issues and ensure an improved learning experience, particularly in an e-learning environment.

OBJECTIVE: This study sought to evaluate the utility of the Global Health Security (GHS) index in predicting the launch of COVID-19 vaccine rollout by Organization for Economic Cooperation and Development (OECD) member countries. METHODS: Country-level data on the preparedness to respond to infectious disease threats through vaccination rollout were collected using the GHS index. OECD member countries were rank-ordered based on the percentage of their populations fully vaccinated against COVID-19. Rank-ordering was conducted from the lowest to the highest, with each country assigned a score ranging from 1 to 33. Spearman's rank correlation between the GHS index and the percentage of the population that is fully vaccinated was also performed. RESULTS: Israel, ranked 34th in the world on the GHS index for pandemic preparedness, had the highest percentage of the population that was fully vaccinated against COVID-19 within 2 months of the global vaccine rollout. The Spearman rank correlation coefficient between GHS index and the percentage of population fully vaccinated was -0.1378, with a p-value of 0.43. CONCLUSION: The findings suggest an absence of correlation between the GHS index rating and the COVID-19 vaccine rollout of OECD countries, indicating that the preparedness of OECD countries for infectious disease threats may not be accurately reflected by the GHS index.

Neurofibromatosis-1 (NF-1) is a genetic neuro-cutaneous disorder that is associated with an increased prevalence of pheochromocytoma (PHEO). However, this association may not be commonly anticipated by physicians, as patients may be normotensive. In addition, NF-1 patients can be asymptomatic and/or normotensive. These factors can result in a delayed or missed diagnosis of pheochromocytoma leading to catastrophic complications. Currently, it is recommended to perform annual blood pressure monitoring in patients with NF-1 and to test for pheochromocytoma only if found to be hypertensive. However, recent studies show that this practice may lead to underdiagnosis of pheochromocytoma. Therefore, suggesting routine biochemical testing for pheochromocytoma in all patients with NF-1. In this case report, we discuss the factors which can lead to a delayed diagnosis of pheochromocytoma in a patient with known NF-1 and hypertension.

China’s 2060 carbon neutrality agenda requires implementation of policies that can decouple its economic growth from environmental pollution. Consequently, establishing green growth in the Chinese economy is of utmost significance. Against this milieu, this study questions whether the depth of Chinese financial markets matters for establishing green growth in China. Besides, the green growth effects of renewable energy use, technological innovation, and urbanization are also examined. Accordingly, quarterly frequency data from 1990Q1 to 2020Q4 are utilized to perform econometric tests that accommodate structural break concerns in data. Overall, the findings reveal that the depth of the Chinese financial markets facilitates the prospects of greening the Chinese economy. Notably, deepening of financial markets is seen to initially inhibit green growth while stimulating it later on; thus, the financial markets’ depth-green growth nexus is evidenced to depict a U-shape. On the other hand, green growth in China is also found to be catalyzed by the renewable transformation of the Chinese energy sector and through technological innovation in the long-run. Conversely, urbanization is witnessed to inflict anti-green growth impacts. Furthermore, the causality analysis verifies bi-directional causal associations between renewable energy use and green growth while unidirectional causalities running from financial markets' deepening, technological innovation, and urbanization to green growth are also discovered. Therefore, it is recommended that China should try to persistently develop its stock and debt markets so that clean investment can be boosted to decouple economic growth and environmental pollution. Besides, it is also important to undergo renewable energy transition, develop clean technologies, and design low-energy urbanization strategies.

Bangladesh has recently pledged at the 26th Conference of Parties (COP26) to reduce its carbon dioxide emission figures by 22% at the end of 2030. However, since this South Asian country has always turned to fossil fuels for electricity generation purposes, achieving this emission reduction goal is a challenging task for the Bangladesh government. Nevertheless, considering the negative environmental implications associated with the generation and consumption of unclean energy, particularly electricity, it is critically important for Bangladesh to expedite the process of clean transformation of its traditional pollution-intensive power system. Hence, the objective of this study is to dissect the repercussions of hydroelectricity use on Bangladesh’s fossil fuel consumption-related carbon dioxide As opposed to the traditional method of quantifying environmental quality using total carbon dioxide emissions, this study considers Bangladesh’s annual carbon dioxide emissions generated from the combustion of gas, oil, and coal. Besides, novel Fourier-based econometric methods that effectively handle structural break problems in data are utilized in this study. Based on the results, it is found that up-scaling hydroelectricity consumption levels exert emission-inhibiting effects while greater economic globalization activities are witnessed to boost the emissions. More importantly, hydroelectricity consumption and economic globalization are observed to jointly curb fossil fuel consumption-based emissions of carbon dioxide. Additionally, the results verify the environmental Kuznets curve hypothesis for Bangladesh. Furthermore, financial sector development is found to be effective in reducing the natural gas consumption-related carbon dioxide emissions while urbanization is held responsible for amplifying emissions generated from all three types of fossil fuels. Therefore, considering these findings, the Bangladesh government needs to particularly emphasize scaling up production and consumption of hydroelectricity to decarbonize its economy.

Background: Given the relatively modest benefit of currently available treatments in improving COVID-19 clinical outcomes, there is an urgent need for novel therapeutic strategies, especially in reversing associated lung inflammation. Attention has focused on repurposing existing agents with immune modulatory properties to accelerate their incorporation into clinical practice. Recent evidence has demonstrated that the cholesterol-lowering agents, statins, are associated with reduced mortality in patients with influenza, sepsis, community-acquired pneumonia, and chronic obstructive pulmonary diseases (COPD). We sought to investigate the relationship between statin use and COVID-19 disease severity in hospitalized patients. Methods: A retrospective analysis of COVID-19 patients admitted to the Johns Hopkins Medical Institutions between March 1, 2020 and June 30, 2020 was performed. The outcomes of interest were mortality and severe COVID-19 infection, as defined by prolonged hospital stay (≥ 7 days) and/ or invasive mechanical ventilation. Logistic regression, Cox proportional hazards regression and propensity score matching were used to obtain both univariable and multivariable associations between covariates and outcomes in addition to the average treatment effect of statin use. Results: Of the 4,447 patients who met our inclusion criteria, 594 (13.4%) patients were exposed to statins on admission, of which 340 (57.2%) were male. The mean age was higher in statin users compared to non-users [64.9 ± 13.4 vs. 45.5 ± 16.6 years, p

BackgroundThere is an urgent need for novel therapeutic strategies for reversing COVID-19-related lung inflammation. Recent evidence has demonstrated that the cholesterol-lowering agents, statins, are associated with reduced mortality in patients with various respiratory infections. We sought to investigate the relationship between statin use and COVID-19 disease severity in hospitalized patients.MethodsA retrospective analysis of COVID-19 patients admitted to the Johns Hopkins Medical Institutions between March 1, 2020 and June 30, 2020 was performed. The outcomes of interest were mortality and severe COVID-19 infection, as defined by prolonged hospital stay (≥ 7 days) and/ or invasive mechanical ventilation. Logistic regression, Cox proportional hazards regression and propensity score matching were used to obtain both univariable and multivariable associations between covariates and outcomes in addition to the average treatment effect of statin use.ResultsOf the 4,447 patients who met our inclusion criteria, 594 (13.4%) patients were exposed to statins on admission, of which 340 (57.2%) were male. The mean age was higher in statin users compared to non-users [64.9 ± 13.4 vs. 45.5 ± 16.6 years, p ConclusionStatin use was not associated with altered mortality, but with an 18% increased risk of severe COVID-19 infection.