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1.
Journal of Environmental Chemical Engineering ; 11(3), 2023.
Article in English | Scopus | ID: covidwho-2293894

ABSTRACT

Ciprofloxacin and ofloxacin belong to a class of antibiotics called Fluoroquinolones (FQs), which have a wide anti-bacterial activity against Gram-positive and Gram-negative bacteria. Since the recent Covid-19 pandemic witnessed a magnanimous rise in the use of antibiotics to prevent secondary bacterial infections, it led to vast production and use of such antibiotics. Ultimately the antibiotics get discharged into the municipal sewer pipes, thereby killing the useful microbial colony. In order to prevent environmental degradation a commercial scale-up of the adsorption of these antibiotics using raw sewage sludge is an absolute necessity. In this study, a continuous adsorption operation is conducted in a packed bed of semi-dried raw sewage sludge to remove the FQs from wastewater. Two transient convective-diffusion models are developed including pseudo-first and second-order kinetics driven depletion terms. The models are optimised using the data collected under various dynamic conditions in order to analyse the performance of the packed bed in terms of bed height, flow rate and initial concentration of the FQs. Damköhler numbers of the FQs are estimated to predict the breakthrough times of both the FQs. The ratios of Damköhler numbers of ciprofloxacin and ofloxacin do not change much with flow rate. In all the experiments, Das << 1 for both the FQs, indicating a faster diffusion process with respect to the rate of pseudo-reaction. Diffusion reaches an ‘equilibrium' well before the reaction achieves pseudo-chemical equilibrium. Ratios of the Damköhler numbers, meant to represent the first-order and second-order convective-diffusion models for ciprofloxacin to ofloxacin is < 1. © 2023 Elsevier Ltd

2.
22nd Annual Conference of the International Speech Communication Association, INTERSPEECH 2021 ; 6:4276-4280, 2021.
Article in English | Scopus | ID: covidwho-1535016

ABSTRACT

COVID-19 can be pre-screened based on symptoms and confirmed using other laboratory tests. The cough or speech from patients are also studied in the recent time for detection of COVID-19 as they are indicators of change in anatomy and physiology of the respiratory system. Along this direction, the diagnosis of COVID-19 using acoustics (DiCOVA) challenge aims to promote such research by releasing publicly available cough/speech corpus. We participated in the Track-1 of the challenge, which deals with COVID-19 detection using cough sounds from individuals. In this challenge, we use a few novel auditory acoustic cues based on long-term transform, equivalent rectangular bandwidth spectrum and gammatone filterbank. We evaluate these representations using logistic regression, random forest and multilayer perceptron classifiers for detection of COVID-19. On the blind test set, we obtain an area under the ROC curve (AUC) of 83.49% for the best system submitted to the challenge. It is worth noting that the submitted system ranked among the top few systems on the leaderboard and outperformed the challenge baseline by a large margin. Copyright © 2021 ISCA.

3.
Kesmas-National Public Health Journal ; 16(1):17-22, 2021.
Article in English | Web of Science | ID: covidwho-1524762

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is the causative agent of COVID-19 that began in Wuhan, Hubei Province, China. In Indonesia, the first two cases were reported on March 2, 2020;the first major response to block transmission of the virus was the declaration of large-scale social restrictions (LSSR) or Pembatasan Sosial Berskala Besar (PSBB). This study aimed to identify the epidemiology patterns and spatial distribution of the COVID-19 pandemic in five municipalities of DKI Jakarta. The research design comprised an ecological and case-series study uncovering the epidemiological trends and distribution of COVID-19 in DKI Jakarta based on secondary surveillance data. The results from the data analyzed between March-December 2020 showed an increasing epidemiological trend due to COVID-19, and Central Jakarta was the municipality most affected due to pandemic during this period. The implementation of the first PSBB in DKI Jakarta reduced the average number of daily cases during the first month, although the decrease was not statistically significant. There was a spatial autocorrelation of COVID-19 with the neighboring urban villages. There were fifteen COVID-19 hotspots all over DKI Jakarta based on the data analyzed in December 2020.

4.
International Journal of Computational Biology and Drug Design ; 14(1):43-63, 2021.
Article in English | Scopus | ID: covidwho-1190184

ABSTRACT

In view of the non-availability of any secure vaccine for COVID-19 caused by SARS-CoV-2, scientists around the world have been running to develop potential inhibitors against SARS-CoV-2. The present study helps us to identify and screen best phytochemicals (chemical drugs or plant based compounds) as potent inhibitors against COVID-19. In this study, we have measured the virtual interactions of COVID-19 main protease (PDB: 6LU7) with lung cancer, bronchitis and blood thinner drugs as well as some natural plant based compounds. Best docking results have been considered on the basis of disulfiram, tideglusib and shikonin. Absorption, distribution, metabolism and excretion (ADME) and toxicity are also predicted for these compounds. From this study, we will expect these drugs to undergo validation in human clinical trials to use as promising candidates for antiviral treatment with high potential to fight against COVID-19. © 2021 Inderscience Enterprises Ltd.. All rights reserved.

5.
Letters in Drug Design and Discovery ; 18(1):67-75, 2021.
Article in English | EMBASE | ID: covidwho-1110177

ABSTRACT

Background: Recently, novel coronavirus disease, COVID-19 caused the outbreak situation of global public health. In this pandemic situation, all the people's lives of 212 Countries and Territories have been affected due to partial or complete lockdown and also as a result of mandatory isolations or quarantines. This is due to the non-availability of any secure vaccine. Objective: The present study helps us to identify and screen the best phytochemicals as potent inhibitors against COVID-19. Methods: In this paper, we choose two standard drugs namely hamamelitannin and rosmarinic acid as a probable inhibitor of pandemic COVID-19 receptor as compared to antimalarial drugs hydroxychloroquine, anti-viral drug remdesivir, and also baricitinib. This study was done by taking into consideration of molecular docking study, performed with Auto Dock 4.0 (AD4.0). All chemical structures were optimized with the Avogadro suite by applying the MMFF94 force field and also hamamelitannin, rosmarinic acid was optimized using the Gaussian G16 suite of UB3LYP/6-311++G(d,p) basis set. Protein-ligand interaction was visualized by PyMOL software. Results: This work has provided an insightful understanding of protein-ligand interaction of ham-amelitannin and rosmarinic acid showing comparable binding energies than that of clinically applying probable COVID-19 inhibitors hydroxychloroquine (an anti-malarial drug) and remdesivir (an anti-viral drug). Conclusion: We will expect that if its anti-SARS-CoV-2 activity is validated in human clinical trials, these two drugs may be developed as an effective antiviral therapeutics towards infected patients in this outbreak and pandemic situation of COVID-19.

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