The Distribution of Fecal Contamination in an Urbanized Tropical Lake and Incidence of Acute Diarrheal Disease

Aquatic ecosystems of tropical countries are vulnerable to fecal contamination that could cause spikes in the incidences of acute diarrheal disease (ADD) and challenge public health management systems. Vembanad lake, situated along the southwest coast of India, was monitored for one year (2018-2019). Escherichia coli, an indicator of fecal contamination, was prevalent in the lake throughout the year. Multiple antibiotic resistance among more than 50% of the E. coli isolates adds urgency to the need to control this contamination. The high abundance of E. coli and incidence of ADD were recorded during the early phase of the southwest monsoon (June-July), prior to the once-in-a-century floods that affected the region in the later phase (August). The extent of inundation in the low-lying areas peaked in August, but E. coli in the water peaked in July, suggesting that contamination occurred even prior to extreme flooding. During the COVID-19-related lockdown in March-May 2021, fecal contamination in the lake and incidence of ADD reached minimum values. These results indicate the need for improving sewage treatment facilities and city planning in flood-prone areas to avoid the mixing of septic sewage with natural waters during extreme climate events or even during the normal monsoon.

Sanitization Using Autonomous Drone

Since the COVID -19 epidemic has nearly brought about global catastrophe, every chance to make things better must be considered. One such technique for improvement is airborne decontamination. Researching this method's efficacy in the pandemic is vital since it can be used for surface cleaning of bigger areas. There are numerous instances of using drones to disinfect areas affected by epidemics, but best practices and factors affecting effectiveness have not yet been found. The adaptable uses of agricultural drones are evident from reports about utilizing drones for disinfection during a pandemic. The authors of this study calculated the potential amount of disinfectant fluid per unit area using various parameters for fly speed, flight altitude, and flow rate. As a result, by adjusting the settings, a range of disinfectant concentrations per unit area can be provided. Even though the results create a lot of new queries, they can be used to determine appropriate flying characteristics based on various disinfection liquids. © 2022 IEEE.

The Distribution of Fecal Contamination in an Urbanized Tropical Lake and Incidence of Acute Diarrheal Disease

Aquatic ecosystems of tropical countries are vulnerable to fecal contamination that could cause spikes in the incidences of acute diarrheal disease (ADD) and challenge public health management systems. Vembanad lake, situated along the southwest coast of India, was monitored for one year (2018-2019). Escherichia coli, an indicator of fecal contamination, was prevalent in the lake throughout the year. Multiple antibiotic resistance among more than 50% of the E. coli isolates adds urgency to the need to control this contamination. The high abundance of E. coli and incidence of ADD were recorded during the early phase of the southwest monsoon (June-July), prior to the once-in-a-century floods that affected the region in the later phase (August). The extent of inundation in the low-lying areas peaked in August, but E. coli in the water peaked in July, suggesting that contamination occurred even prior to extreme flooding. During the COVID-19-related lockdown in March-May 2021, fecal contamination in the lake and incidence of ADD reached minimum values. These results indicate the need for improving sewage treatment facilities and city planning in flood-prone areas to avoid the mixing of septic sewage with natural waters during extreme climate events or even during the normal monsoon. © 2023 American Chemical Society.

Comprehensive review on consumers behavior towards sustainable fashion and its relativity in fast fashion

Sustainable fashion is clothing that is ethically produced and environmentally beneficial, whereas rapid fashion is the polar opposite in terms of sustainability. We know that circular business models can drive value by improving customer attention and possession. Due of its environmental impact, fashion experts believe that "there is no such thing as 100 percent sustainable fashion. "During the Covid-19 crisis, this trend became notably apparent, with two-thirds of surveyed European customers admitting that minimizing climate change impacts had become increasingly essential to them. The future of Sustainability in Fast Fashion concept and concern with the Consumers Behavior where circular business models are incorporated to increase the efficiencies of system to reduce inputs and decrease the amount or flow of material & garments in the system to reduce waste. The current study focuses on sustainability in fast fashion in the textile industry, with a focus on five imperatives: prioritize based on market segment, match the business model to the product, get the incentives right, make sustainable and pilot and experiment © 2022, Man Made Textiles in India. All rights reserved.

Comparative Study of CNN-Based Multi-Disease Detection Models Through X-Ray Images

Adaptation of computer-aided techniques in health care is continually improving diagnosis and treatment using chest X-ray images. Deep learning approaches are proving to be effective in offering more accurate disease detection However, there are still significant hurdles in medical imaging. In this paper, presented an experiential comparative analysis of popular deep learning-based convolutional neural networks (CNN’s) models such as ResNet50, Xception, VGG16, and VGG19 using transfer learning for multi-disease detection. Although experimented with several deep convolution architectures but presented here top most only. This paper addresses four classes (chest disease) classification using chest X-ray, namely COVID, Normal, Pneumonia, and Tuberculosis. All four models are trained, tested, and validated using the same chest X-ray dataset which consists of 700 images for each disease. The comparative result presented, accuracy, predict output, training and validation loss, confusion matrices, error rate, and F1-score. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Evaluation of Virtual Classes Teaching among first-year MBBS students during COVID-19 era in GMC Jammu

Background: The Covid-19 era has caused the shifting of medical teaching into an Online podium. This has provided us with an excellent opportunity to recognize MBBS-students’ preferences of these Online classes which otherwise did not form a significant part of the traditional medical teaching. We have undertaken online classes for theory & practical for the first time in our medical college at GMC Jammu. So the current study was conducted to assess & analyze the preference of first-year MBBS students between online classes & traditional classroom teaching. Objectives: To evaluate the predilection/inclination of first-year MBBS students between online classes and traditional classroom teaching. Materials & Methods: An institution-based descriptive cross-sectional study was performed on 180 MBBS students of 2020-21 batch at the Department of Physiology in GMC Jammu, after receiving Institutional ethics committee (IEC) clearance who have attended online classes for a minimum of 1 hour per day or 6 hours per week for 1-month duration using zoom or other video-based learning platforms. A pre-structured questionnaire-based feedback study was conducted after obtaining written consent from the first-year MBBS students. We designed a total of 24 questions related to their theory & practical classes, for assessing their preference for Online classes in comparison to traditional classroom teaching with multiple-choice options. Results: In our study, we found that overall, 61.11% of MBBS students prefer traditional classroom teaching over Online classes and 60% of students prefer traditional teaching methods over online learning for practical classes. However, 50% of students reported that accessibility to stable internet was causing difficulty in following Online classes. Moreover, 53.89% of students reported that they get distracted at home during Online classes. Further, 66.11% of students mentioned a lack of personal interaction & lonely experience on the Online platform. Conclusion: In our study, we found that medical students prefer the traditional teaching method to the Online platform for learning as well as examination. For better understanding and learning, the first phase of MBBS students prefers that traditional classroom teaching should be followed by Online classes that can be easily accessed by students at their convenient time. In this study, the majority of medical students reported limited access to stable internet, distractions & disturbances in the domestic environment, & lack of personal interaction as the barriers to Online learning.

A Covid-19 Safety Web Application to Monitor Social Distancing and Mask Detection

Covid-19 Pandemic dipped entire world in sorrow and grief, people are fighting for their lives. Vaccines are being given to people based on priority such as frontline workers, old age, etc. In this situation, the only way to prevent ourselves from getting infected is to follow precautionary measures like social distancing, wearing masks and more. To make everyone follow the precautionary measures effectively, an idea is proposed to monitor social distancing and mask detection. The system is designed using pre-trained models such as DSFD, Mobilenetv2, Resnet50 and YOLOv3 weights and also adding few layers on top of pre-trained models. This helps in detecting people wearing masks or not and calculate the distance between people in a single model by indicating in different colored bounding boxes. It is further made interesting by collaborating the proposed design with the Streamlit framework resulting in a fine Web Application. © 2021 IEEE.

Assisted Telemedicine Model for Rural Healthcare Ecosystem

A project involving study and field trials to analyze and validate the relevance and feasibility of an "Assisted Telemedicine"model towards addressing the accessibility gaps in the rural primary healthcare ecosystem. The work also involved designing a blue-print of an Assisted Telemedicine app for catering to the healthcare consultation needs during and beyond Covid-19 in a participatory design model. A customized app was created for "assisted telemedicine"model and features were incrementally added based on observations and inputs received from various stakeholders. Initial studies indicate that this model of health care delivery can benefit a range of demographics and can find acceptance among the different stakeholders. The potential impact of this intervention is also studied from the perspective of Capability Approach. © 2021 ACM.

COVID-19 cardiovascular epidemiology, cellular pathogenesis, clinical manifestations and management.

Coronavirus Disease 2019 (COVID-19) is a rapidly progressing global pandemic that may present with a variety of cardiac manifestations including, but not limited to, myocardial injury, myocardial infarction, arrhythmias, heart failure, cardiomyopathy, shock, thromboembolism, and cardiac arrest. These cardiovascular effects are worse in patients who have pre-existing cardiac conditions such as coronary artery disease, hypertension, diabetes mellitus, and coagulation abnormalities. Other predisposing risk factors include advanced age, immunocompromised state, and underlying systemic inflammatory conditions. Here we review the cellular pathophysiology, clinical manifestations and treatment modalities of the cardiac manifestations seen in patients with COVID-19.

A Guide to Facial Trauma Triage and Precautions in the COVID-19 Pandemic.

COVID-19 is an emerging viral illness that has rapidly transmitted throughout the world. Its impact on society and the health care system has compelled hospitals to quickly adapt and innovate as new information about the disease is uncovered. During this pandemic, essential medical and surgical services must be carried out while minimizing the risk of disease transmission to health care workers. There is an elevated risk of COVID-19 viral transmission to health care workers during surgical procedures of the head and neck due to potential aerosolization of viral particles from the oral cavity/naso-oropharynx mucosa. Thus, patients with facial fractures pose unique challenges to the variety of injuries and special considerations, including triaging injuries and protective measures against infection. The proximity to the oral cavity/naso-oropharyngeal mucosa, and potential for aerosolization of secretions containing viral particles during surgical procedures make most patients undergoing operative interventions for facial fractures high risk for COVID-19 transmission. Our proposed algorithm aims to balance patient care with patient/medical personnel protection as well as judicious health care utilization. It stratifies facial trauma procedures by urgency and assigns a recommended level of personal protective equipment, extreme or enhanced, incorporating current best practices and existing data on viral transmission. As this pandemic continues to evolve and more information is obtained, the protocol can be further refined and individualized to each institution.