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The Air Quality Index (AQI) in India is steadily deteriorating, leading to a rise in the mortality rate due to Lung Cancer. This decline in air quality can be attributed to various factors such as PM 2.5, PM 10, and Ozone (O3). To establish a relationship between AQI and Lung Cancer, several predictive models including Linear Regression, KNN, Decision Tree, ANN, Random Forest Regression, and XGBoost Regression were employed to estimate pollutant levels and Air Quality Index in India. The models relied on publicly available state-wise Air Pollution Dataset. Among all the models, the XGBoost Regression displayed the highest accuracy, with pollutant level estimations reaching an accuracy range of 81% to 98% during training and testing. The second-highest accuracy range was achieved by Random Forest. The paper also explores the impact of increasing pollution levels on the rising mortality rate among lung cancer patients in India., (© 2023. The Author(s).)

Air pollution is a central problem faced by industries during the production process. The control of this pollution is essential for the environment and living organisms as it creates harmful effects. Biofiltration is a current pollution management strategy that concerns removing odor, volatile organic compounds (VOCs), and other pollutants from the air. Recently, this approach has earned vogue globally due to its low-cost and straightforward technique, effortless function, high reduction efficacy, less energy necessity, and residual consequences not needing additional remedy. There is a critical requirement to consider sustainable machinery to decrease the pollutants arising within air and water sources. For managing these different kinds of pollutant reductions, biofiltration techniques have been utilized. The contaminants are adsorbed upon the medium exterior and are metabolized to benign outcomes through immobilized microbes. Biofiltration-based designs have appeared advantageous in terminating dangerous pollutants from wastewater or contaminated air in recent years. Biofiltration uses the possibilities of microbial approaches (bacteria and fungi) to lessen the broad range of compounds and VOCs. In this review, we have discussed a general introduction based on biofiltration and the classification of air pollutants based on different sources. The history of biofiltration and other mechanisms used in biofiltration techniques have been discussed. Further, the crucial factors of biofilters that affect the performance of biofiltration techniques have been discussed in detail. Finally, we concluded the topic with current challenges and future prospects., Competing Interests: The authors declare no competing financial interest., (© 2022 The Authors. Published by American Chemical Society.)

Carbon-based nanomaterials (CBNMs) have attracted significant alert due to the affluent science underpinning their implementations associated with a novel mixture of high aspect proportions, greater thermal and electrical performance, outstanding optical features, and high exterior area. CBNMs not only bear assurance in a broad range of implementations in medication, nano and microelectronics, and ecological remedies but may also be utilized in practical laboratory determinations. More specifically, CBNMs perform as an outstanding adsorbent in terminating heavy metal ions (HMI) from wastewater. There is presently a deficiency of powerful threat inspection instruments owing to their complex detection and related deficit in the health risk database. Therefore, our present review concentrates on spreading CBNMs to release pollutants from wastewater. The article wraps the effect of these contaminants and photocatalytic strategies towards treating these mixtures in wastewater, along with their restrictions and challenges, convincing resolutions, and possibilities of these approaches., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

MXenes are a quickly growing and extended group of two-dimensional (2D) substances that have earned unbelievable analysis credits for various application areas within different manufacturing areas. Due to novel essential architectural and physicochemical properties shows good properties, such as elevated exterior area, living adaptability, strong electrochemistry, and great hydrophilicity. Given the fast progress within the structure and synthesis of MBNs for water treatment, quick updates on this research field are required to remove toxic substances, such as production approaches and characterization methods for the advantages and constraints of MXenes for pollutant degradation. MXenes are determined as a proposed road toward atmosphere-clean-up machinery to identify and decrease a pattern of hazardous resistant pollutants from environmental forms. Here, in this review article, we have been focused on describing the overview, novel synthesis methods, and characteristics of the MXene-based nanomaterials (MBNs) in the field for removing hazardous contaminants from environmental conditions. In the last, the utilizations of MBNs in water sanitization, organic solvent filtration, antibiotics degradation, pesticide degradation, heavy metals degradation, ions removal, bacterial pathogens degradation, along with the conclusion, challenges, and prospects in this field, have been discussed., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

A viable electrochemical approach for the detection of dopamine (DA) in uric acid (UA) utilizing a silver nanoparticle-doped 2-aminodiphenylamine (AgNPs-2ADPA) electrode was invented. The electrochemical performance of DA showed that the incorporated electrode displayed outstanding electrocatalytic performance to the electrochemical oxidation of DA. In our study, the AgNPs-2ADPA exhibits remarkable catalytic activity, retaining high current value and resilience when employed as a working electrode component for electrocatalytic detection of DA. We have also utilized the bare and polymeric-2ADPA in DA detection for a comparison study. This method offers a facile route with extraordinary sensitivity, selectivity, and strength for the voltammetric detection of DA, even in the presence of UA and ascorbic acid (AA) as interferents, that can be employed for pharmaceutical and biological specimens.

Purpose: To primarily compare surgically induced astigmatism (SIA), total and posterior corneal curvature, pachymetry, and their stabilization after 2.2 and 2.8 mm clear corneal incision in phacoemulsification., Methods: A randomized, prospective interventional study of 130 patients (130 eyes) of either sex having senile cataract (>40 years) divided randomly into two groups. The patients underwent uncomplicated phacoemulsification surgery with foldable intraocular lens implantation using 2.2 mm (group 1) and 2.8 mm incisions (group 2). The patients were evaluated preoperatively and followed-up at first, third, and sixth weeks., Results: Mean SIA was less in group 1 at all the follow-up visits which was not statistically significant (P value - 0.507 (at week 1), 0.626 (at week 3), and 0.312 (at week 6). Mean SIA decreased from week 1 to week 6 in both the groups. Both the groups showed an increase in SIA with the increase in the hardness of cataract. Posterior keratometry (k1 and k2) showed statistically significant steepening in the first postoperative week, followed by gradual flattening which continued till the sixth week postoperatively. Posterior astigmatism increased in both the groups at week 1 (not statistically significant). Thereafter, it decreases and does not change significantly after 3 weeks. Pachymetry increased significantly (P value < 0.001 in both the groups) in the first week in both the groups and thereafter stabilizing at 3 weeks., Conclusion: Reducing the incision size does not result in any significant reduction in SIA. We observed that the posterior corneal curvature majorly stabilized by 3 weeks, but some stabilization continued till 6 weeks., Competing Interests: None

Component-based software engineering is currently a development strategy used to improve complex embedded systems. The engineers have to deal with a large number of quality requirements (e.g. safety, security, availability, reliability, maintainability, portability, performance, and temporal correctness requirements), hence the development of complex embedded systems is becoming a challenging task. Enhancement of the quality prediction in component-based software engineering systems using soft computing techniques is the foremost intention of the research. Therefore, this paper proposes an extreme learning machine (ELM) classifier with the ant colony optimization algorithm and Nelder-Mead (ACO-NM) soft computing approach for component quality prediction. To promote efficient software systems and the ability of the software to work under several computer configurations maintainability, independence, and portability are taken as three core software components metrics for measuring the quality prediction. The ELM uses AC-NM for updating its weight to transform the quality constraints into objective functions for providing a global optimum quality prediction. The experimental results have shown that the proposed work gives an improved performance in terms of Sensitivity, Precision, Specificity, Accuracy, Mathews correlation coefficient, false positive rate, negative predictive value, false discovery rate, and rate of convergence., (© Springer Nature B.V. 2020.)

The present case shows a remarkable long-term response of the choroidal neovascular membrane and serous retinal detachment associated with choroidal osteoma to two injections of ranibizumab which is an anti-vascular endothelial growth factor (anti-VEGF) agent., Competing Interests: Competing interests: None declared., (© BMJ Publishing Group Limited 2020. No commercial re-use. See rights and permissions. Published by BMJ.)

Context: "Integrated Management of Neonatal and Childhood Illnesses" (IMNCI) needs regular supportive supervision (SS)., Aims: The aim of this study was to find suitable SS model for implementing IMNCI., Settings and Design: This was a prospective interventional study in 10 high-focus districts of Haryana., Subjects and Methods: Two methods of SS were used: (a) visit to subcenters and home visits (model 1) and (b) organization of IMNCI clinics/camps at primary health center (PHC) and community health center (CHC) (model 2). Skill scores were measured at different time points. Routine IMNCI data from study block and randomly selected control block of each district were retrieved for 4 months before and after the training and supervision., Statistical Analysis Used: Change in percentage mean skill score difference and percentage difference in median number of children were assessed in two areas., Results: Mean skill scores increased significantly from 2.1 (pretest) to 7.0 (posttest 1). Supportive supervisory visits sustained and improved skill scores. While model 2 of SS could positively involve health system officials, model 1 was not well received. Outcome indicator in terms of number of children assessed showed a significant improvement in intervention areas., Conclusions: SS in IMNCI clinics/camps at PHC/CHC level and innovative skill scoring method is a promising approach., Competing Interests: There are no conflicts of interest.