ProTect: a hybrid deep learning model for proactive detection of cyberbullying on social media.

The emergence of social media has given rise to a variety of networking and communication opportunities, as well as the well-known issue of cyberbullying, which is continuously on the rise in the current world. Researchers have been actively addressing cyberbullying for a long time by applying machine learning and deep learning techniques. However, although these algorithms have performed well on artificial datasets, they do not provide similar results when applied to real-time datasets with high levels of noise and imbalance. Consequently, finding generic algorithms that can work on dynamic data available across several platforms is critical. This study used a unique hybrid random forest-based CNN model for text classification, combining the strengths of both approaches. Real-time datasets from Twitter and Instagram were collected and annotated to demonstrate the effectiveness of the proposed technique. The performance of various ML and DL algorithms was compared, and the RF-based CNN model outperformed them in accuracy and execution speed. This is particularly important for timely detection of bullying episodes and providing assistance to victims. The model achieved an accuracy of 96% and delivered results 3.4 seconds faster than standard CNN models.

Clinical profile of patients infected with suspected SARS-CoV-2 Omicron variant of concern, Tamil Nadu, India, December 2021-January 2022.

Background & objectives: COVID-19 cases have been rising rapidly in countries where the SARS-CoV-2 variant of concern (VOC), Omicron (B.1.1.529) has been reported. We conducted a study to describe the epidemiological and clinical characteristics and outcomes of COVID-19 patients with 'S' gene target failure (SGTF, suspected Omicron). Furthermore, their clinical outcomes with COVID-19 patients with non-SGTF (non-Omicron) were also compared. Methods: This study was conducted in Tamil Nadu, India, between December 14, 2021 and January 7, 2022 among patients who underwent reverse transcription-PCR testing for SARS-CoV-2 in four laboratories with facilities for S gene screening. Consecutively selected COVID-19 patients with SGTF were telephonically contacted, seven and 14 days respectively after their date of positive result to collect information on the socio-demographic characteristics, previous history of COVID-19, vaccination status and clinical course of illness along with treatment details. To compare their outcomes with non-SGTF patients, one randomly suspected non-Omicron case for every two suspected Omicron cases from the line-list were selected, matching for the date of sample collection and the testing laboratory. Results: A total of 1175 SGTF COVID-19 patients were enrolled for this study. Almost 6 per cent (n=72) reported a history of previous infection. 141 (13.5%) suspected Omicron cases were non-vaccinated, while 148 (14.2%) and 703 (67.4%) had received valid one and two doses of COVID-19 vaccines, respectively. Predominant symptoms reported included fever (n=508, 43.2%), body pain (n=275, 23.4%), running nose (n=261, 22.2%) and cough (n=249, 21.2%). Five (0.4%) of the 1175 suspected Omicron cases required oxygen supplementation as compared to ten (1.6%) of the 634 suspected non-Omicron cases. No deaths were reported among omicron suspects, whereas there were four deaths among suspected non-Omicron cases. Interpretation & conclusions: Majority of the suspected Omicron cases had a mild course of illness. The overall severity of these cases was less compared to the suspected non-Omicron cases.

A detailed insight on fabricated porous chitosan in eliminating synthetic anionic dyes from single and multi-adsorptive systems with related studies.

Chitosan was fabricated via gelation method using CaBr2.xH2O/methanol solution and was studied as a potential adsorbent (MCh) in adsorbing anionic synthetic dyes like Bromophenol blue (BB), Direct blue 6 (DB) and Congo red (CR) from single (one dye species at a time) and multi (having two dyes; binary and all three dyes; tertiary) adsorptive systems. Physico-chemical modifications of MCh surface prior and post modification and dye adsorption were evaluated using scanning electron microscopy, Energy-dispersive X-ray spectroscopy, powder X-ray diffraction analysis, surface area analysis and Fourier-transformed infrared spectroscopy. Influential parameters influencing the adsorption process viz. initial pH of dye solution, MCh dosage, adsorption temperature and initial concentration of dye species were optimised. Adsorptive studies involving single adsorptive setups verified formation of sorbate's (dye species) monolayer over the sorbent's (MCh) surface via chemisorption; as established by Langmuir isotherm and pseudo-second order kinetics model analysis. Theoretical maximum adsorption capacities of MCh for BB, DB and CR was found to be 81.301 mg/g, 163.934 mg/g and 75.758 mg/g, respectively. Meanwhile, for all multi-adsorptive systems, competitive Langmuir isotherm model verified antagonistic behaviour of an individual dye over other dye adsorption over MCh surface in their respective adsorptive systems. Thermodynamics of the sorbate-sorbent interaction was exothermic, spontaneous, with elevated degree of disorderedness; concluding the interaction as thermodynamically favourable. Co-existing metal cations and anionic salts had minimal effect on MCh's adsorption efficiency. Phytotoxicity assay via germination of Vigna mungo seeds verified the efficacy of the adsorbent in eliminating the dye species from single and multi-adsorptive systems.

Ecotoxicological assessment of micropollutant Diclofenac biosorption on magnetic sawdust: Phyto, Microbial and Fish toxicity studies.

Diclofenac (DCF), a persistent pharmaceutical micropollutant which occurs in the ecosystems causing adverse effects on aquatic as well as terrestrial organisms. In this study, magnetic sawdust (MSD) was prepared using co-precipitation method for biosorptive removal of DCF from water. The MSD was characterized using various analytical techniques like microscopic and spectroscopic analysis. Magnetometer study confirms the ferromagnetic behavior of the biosorbent which is a key advantage in the separation of MSD after biosorption. The effect of experimental parameters was optimized in batch mode with evaluated maximum efficiency of 86.12 % at pH 6, biosorbent dosage 25 mg for 50 mg/L of DCF. Ecotoxicological assessment has been performed for the treated and untreated sample using plant seeds, microbes and zebra fish to check the adverse effects of DCF on these organisms. Evaluation of toxicity studies revealed that inhibition concentration of DCF for various seeds (60.91 mg/L to 43.11 mg/L), E. coli (48.82 µg/mL) and B. subtilis (31.55 µg/mL). The lethal concentration of DCF on the Danio rerio was found to be 156.99 mg/L. In contrast, significant increase in both the concentration measures of DCF after biosorption was observed making this biosorbent a potent alternative to other available treatment measures.

Social determinants in access to tobacco prevention and cessation support services among migrant construction workers in Urban Chennai, India.

CONTEXT: In spite of the high burden of tobacco consumption among migrants, disparities in the awareness of tobacco-related harms, health-seeking behaviors, and intention to switch to lower risk alternatives remain understudied area. AIMS: Assess the social determinants in access to tobacco prevention and cessation support services among migrant construction workers in urban Chennai, India. SETTINGS AND DESIGNS: A community-based, cross-sectional study design. MATERIALS AND METHODS: A questionnaire adapted from GATS survey was used among migrants working across 13 construction sites of Chennai during May-September 2019. A counseling session was provided for the migrant workers who were willing to quit. STATISTICAL ANALYSIS USED: Data entered in MS Excel was analyzed using SPSS and multivariate analysis was performed. RESULTS: Among 345 migrants, 338 (98%) were currently using tobacco and smokeless tobacco (57.4%) consumers. In spite of awareness (84.6%) about tobacco ill-effects on health, only 48% care providers enquired of the tobacco use in the previous one year. Pictorial health warnings were seen by 315 migrants (91.3%) in the past one month, but only 110 migrants (34.9%) considered quitting. The majority (341 migrants, 98.4%) have not heard of the lower risk alternatives such as nicotine gums and lozenges and only 89 migrants (26.33%) agreed to try lower risk alternatives for tobacco on trial basis. Migrant construction workers who were using tobacco less than 5 years (P = 0.001) were more likely to try lower risk alternatives. CONCLUSIONS: Reappraising social determinants in access to tobacco prevention and cessation support services to migrant construction workers may be a promising strategy to reduce health harms of tobacco intake.

Significance of exploiting non-living biomaterials for the biosorption of wastewater pollutants.

Industrial effluents from various sectors have become a matter of major environmental concern. The treatment of wastewater in recent year plays a significant role in order to remove the pollutants and to safeguard the water resource. The conventional wastewater treatment is considered costlier and associated with problem of sludge generation. Biosorption methods are considered as the potential solution due to their economical efficiency, good adsorption capacity and eco-friendliness. In this review, an extensive list of biosorbents from algae, bacteria, fungi and agricultural byproducts have been compiled. The suitability of biosorbents towards the eradication of heavy metals, textile dyes and phenolic compounds were highlighted. It is evident from the literature survey of recently published research articles that the biosorbents have demonstrated outstanding removal potential towards the wastewater pollutants. Therefore, biosorbents from the source of dead microbial and agricultural byproduct can be viable alternatives to activated carbon for the wastewater treatment.