Barriers to Sustainable Waste Management in Mountain Tourism: Evidence from India

Goal 15 of the Sustainable Development Goals calls for efforts to protect fragile mountain ecosystems. Waste generated due to mountain tourism leads to environmental degradation, biodiversity loss, and poses a significant challenge to achieving this goal. Mountains which are characterized by uninhabitable terrain and remoteness, coupled with current tourism practices compound this challenge. The paper resolves this challenge by understanding barriers to sustainably manage waste using th Classical DEMATEL method. Based on data from 36 experts in India’s mountain tourism industry, barriers to sustainable management of non-biodegradable waste are analyzed. Results suggest that enforcement of regulations, waste collection infrastructure, and lack of transportation for waste transfer are the most prominent barriers that can be mitigated by collectively leveraging four tangible barriers: tourists’ motivation or achievement mentality, local government’s initiative, economic value of waste, and tourists’ lack of environmental awareness. Based on this, a policy intervention mandating certification standards for tourists is suggested before they embark on mountain tourism

A RANDOMIZED, DOUBLE-BLIND, PLACEBO-CONTROLLED, PARALLEL GROUP CLINICAL STUDY TO EVALUATE THE ANALGESIC EFFECT OF AQUEOUS EXTRACT OF TERMINALIA CHEBULA, A PROPRIETARY CHROMIUM COMPLEX, AND THEIR COMBINATION IN SUBJECTS WITH JOINT DISCOMFORT

Objective: To evaluate the analgesic effect of an aqueous extract of Terminalia chebula (TCE), a proprietary chromium complex (PCC), and theircombination in subjects with joint discomfort.Methods: A total of 100 patients with knee joint discomfort were randomized into five treatment groups - TCE 500 mg BID, TCE 500 mg BID+PCC400 µg OD, PCC 400 µg OD alone, placebo, and TCE 250 mg BID, for 12 weeks in a double-blinded manner. Assessment of symptoms of knee joint painand discomfort was done by modified Western Ontario and McMaster Universities Arthritis Index (mWOMAC) and knee swelling index (KSI); visualanalog scale (VAS) was used for subjective assessment of pain, stiffness, and disability. Statistical analysis was done with GraphPad Prism 6.Results: Absolute reduction in mWOMAC score in TCE 500 mg (19.82±8.35), TCE 500 mg+PCC 400 µg (13.10±5.69), PCC 400 µg (8.30±3.81), placebo(2.45±3.07), and TCE 250 mg (10.47±4.43), respectively, at the end of 12 weeks as compared to the baseline values. Absolute reduction in KSI inTCE 500 mg (28.95±16.82), TCE 500 mg+PCC 400 µg (19.14±9.50), PCC 400 µg (12.7±4.86), placebo (10.03±3.8), and TCE 250 mg (18.24±6.86),respectively, at the end of 12 weeks as compared to the baseline values (p<0.001). Similar results were seen with VAS assessments for pain, stiffness,and disability. All the treatments were well tolerated.Conclusion: TCE and PCC reduce joint discomfort.Keywords: Terminalia chebula extract, Proprietary chromium complex, Western Ontario and McMaster Universities Arthritis Index

Correlation of spirometry and six minute walk test in patients with chronic obstructive pulmonary disease from Sundargarh, Odisha, India

Background: Six‑Minute Walk Test (6MWT) is a simple, objective, reproducible test which correlated well with different spirometric indices, and thus able to predict severity of Chronic Obstructive Pulmonary Disease (COPD) and can replace spirometry in resource poor set‑up. Here, author evaluated the correlation of 6 minute walk distance (6MWD) with spirometric indices in COPD patients and the potential of 6MWT as an alternative to the assessment of severity of COPD.Methods: This cross-sectional observational study included a total of 80 COPD patients, diagnosed by GOLD criteria (Post bronchodilator FEV1/ FVC ratio <0.7). Modified Medical Research Council (mMRC) grading was used (age, weight, height, body mass index- BMI and breathlessness) and all the patients underwent spirometric measurement of FEV1, FVC and FEV1/ FVC ratio and tests were repeated after bronchodilation using 200-400 μg of salbutamol. 6MWT was performed following American Thoracic Society (ATS) protocol of 6MWT and distance was measured in meters.Results: Author found significant negative correlation of 6MWT with age (r=-0.384, p=0.00) and mMRC grading of dyspnea (r=-0.559, p=0.00) and significant positive correlation with height (r=0.267, p=0.019) and weight (r=0.293, p=0.008). Significant positive correlation of 6MWD was noted with post bronchodilator FEV1(r=0.608, p=0.00), FEV1% (r=0.429, p=0.00), FVC (r=0.514 p=0.00), FVC% (r=0.313 p=0.005), FEV1/FVC % (r=0.336, p=0.001). Positive correlation was also observed between 6MWT and BMI but statistically insignificant (r=0.177, p=0.116). There was significant negative correlation between 6MWT and GOLD staging (r=-0.536, p=0.00).Conclusions: This finding concludes that 6MWT can be used for the assessment of severity of disease in COPD patients in places where spirometry is not available

Correlation between endothelial dysfunction, inflammatory status, oxidative stress and total (nitrite/ nitrate) in subjects with diabetes mellitus type 2

Background: Diabetes Mellitus is a systemic metabolic disorder associated with Endothelial dysfunction and increased systemic inflammatory state with oxidative stress leading to increased Cardiovascular risk. This study planned to correlate the level of Endothelial dysfunction with oxidative stress and inflammatory status.Methods: Study was conducted in 60 Diabetes Mellitus subjects of both genders with duration of more than two years. Endothelial dysfunction assessed as Augmentation Pressure and Augmentation Index generated from Radial artery waveforms by tonometer using Spygmocor PWA system. Plasma Total Nitrite/ Nitrate, High sensitive C - Reactive Protein, Malondialdehyde and Glutathione were measured.Results: Out of total 60 Diabetes Mellitus subjects 16 subjects were with Coronary Artery Disease. There was no significant difference in High sensitive C - Reactive Protein, Glutathione, Malondialdehyde and Total Nitrite/ Nitrate between Diabetes Mellitus with Coronary Artery Disease and without Coronary Artery Disease, however significant difference (p=0.02) was observed Augmentation Pressure between Diabetic alone (12.8±5.19 mm of Mercury) and diabetics with Coronary Artery Disease (16.13±33.47 mm of Mercury) and Augmentation Index (p=0.04) between Diabetic alone (29.8±5.68 mm of Mercury) and diabetics with Coronary Artery Disease (40.01±5.74). As endothelial function is age dependent the subjects were divided into three age groups (20-40 years, 40-60 years and more than 60 years). High sensitive C - Reactive Protein, Glutathione, Malondialdehyde, Total Nitrite/ Nitrate and Augmentation Index did not differ in the three age groups while Augmentation Pressure (p=0.0096) showed significant difference between age group 20-40 years (10.59±3.24) and age group more than 60 years (15.83±3.92).Conclusions: There is significant endothelial dysfunction observed in Diabetes Mellitus subjects and Diabetes Mellitus with coronary artery disease showed greater endothelial dyfunction. Thereby concluding that Diabetes Mellitus subjects were at higher risk for development of coronary artery disease and as endothelial dysfunction is an early event, it may have some prognostic value

Thioridazine: a potential adjuvant in pharmacotherapy of drug resistant tuberculosis Ki

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. Despite advances in control strategies, inadequate treatment and failure to comply with drug regimens have resulted in TB to emerge as one of the most common and deadly infectious diseases worldwide. The emergence of drug-resistant TBhas evolved as a formidable obstacle for comprehensive TB control. Drug-resistant TB can be classified as multi-drug-resistant TB, extensively drug-resistant TB and totally drug resistant TB (TDR-TB). There is a paucity in the development of new drugs against drug-resistant mycobacteria. The focus has shifted to the exploration of anti-mycobacterial properties of drugs approved for other indications. Thioridazine, a drug approved for use in schizophrenia is one such potential agent, which has shown anti-mycobacterial activity. There is evidence of anti-mycobacterial action of Thioridazine in in-vitro and mouse models. There is a compelling need for new anti-mycobacterial drugs that are more effective and have less toxicity. Further clinical trials are advocated favoring the use of thioridazine as an adjuvant in the treatment of TB, especially TDR-TB

Indian Classical Dance Action Identification and Classification with Convolutional Neural Networks

Extracting and recognizing complex human movements from unconstrained online/offline video sequence is a challenging task in computer vision. This paper proposes the classification of Indian classical dance actions using a powerful artificial intelligence tool: convolutional neural networks (CNN). In this work, human action recognition on Indian classical dance videos is performed on recordings from both offline (controlled recording) and online (live performances, YouTube) data. The offline data is created with ten different subjects performing 200 familiar dance mudras/poses from different Indian classical dance forms under various background environments. The online dance data is collected from YouTube for ten different subjects. Each dance pose is occupied for 60 frames or images in a video in both the cases. CNN training is performed with 8 different sample sizes, each consisting of multiple sets of subjects. The remaining 2 samples are used for testing the trained CNN. Different CNN architectures were designed and tested with our data to obtain a better accuracy in recognition. We achieved a 93.33% recognition rate compared to other classifier models reported on the same dataset

Challenges and opportunities in mixed method data collection on mental health issues of health care workers during COVID-19 pandemic in India

Background: The present paper describes the key challenges and opportunities of mixed method telephonic data collection for mental health research using field notes and the experiences of the investigators in a multicenter study in ten sites of India. The study was conducted in public and private hospitals to understand the mental health status, social stigma and coping strategies of different healthcare personnel during the COVID-19 pandemic in India.Methods: Qualitative and quantitative interviews were conducted telephonically. The experiences of data collection were noted as a field notes/diary by the data collectors and principal investigators.Results: The interviewers reported challenges such as network issues, lack of transfer of visual cues and sensitive content of data. Although the telephonic interviews present various challenges in mixed method data collection, it can be used as an alternative to face-to-face data collection using available technology.Conclusions: It is important that the investigators are well trained keeping these challenges in mind so that their capacity is built to deal with these challenges and good quality data is obtained

Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models

Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers. In this paper we discuss the SW/HW co-designed solution for high-performance distributed training of large-scale DLRMs. We introduce a high-performance scalable software stack based on PyTorch and pair it with the new evolution of Zion platform, namely ZionEX. We demonstrate the capability to train very large DLRMs with up to 12 Trillion parameters and show that we can attain 40X speedup in terms of time to solution over previous systems. We achieve this by (i) designing the ZionEX platform with dedicated scale-out network, provisioned with high bandwidth, optimal topology and efficient transport (ii) implementing an optimized PyTorch-based training stack supporting both model and data parallelism (iii) developing sharding algorithms capable of hierarchical partitioning of the embedding tables along row, column dimensions and load balancing them across multiple workers; (iv) adding high-performance core operators while retaining flexibility to support optimizers with fully deterministic updates (v) leveraging reduced precision communications, multi-level memory hierarchy (HBM+DDR+SSD) and pipelining. Furthermore, we develop and briefly comment on distributed data ingestion and other supporting services that are required for the robust and efficient end-to-end training in production environments

Factors associated with stigma and manifestations experienced by Indian health care workers involved in COVID-19 management in India: A qualitative study

Healthcare personnel who deal with COVID-19 experience stigma. There is a lack of national-level representative qualitative data to study COVID-19-related stigma among healthcare workers in India. The present study explores factors associated with stigma and manifestations experienced by Indian healthcare workers involved in COVID-19 management. We conducted in-depth interviews across 10 centres in India, which were analysed using NVivo software version 12. Thematic and sentiment analysis was performed to gain deep insights into the complex phenomenon by categorising the qualitative data into meaningful and related categories. Healthcare workers (HCW) usually addressed the stigma they encountered when doing their COVID duties under the superordinate theme of stigma. Among them, 77.42% said they had been stigmatised in some way. Analyses revealed seven interrelated themes surrounding stigma among healthcare workers. It can be seen that the majority of the stigma and coping sentiments fall into the mixed category, followed by the negative sentiment category. This study contributes to our understanding of stigma and discrimination in low- and middle-income settings. Our data show that the emergence of fear of the virus has quickly turned into a stigma against healthcare workers

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events