Imidacloprid impedes mitochondrial function and induces oxidative stress in cotton bollworm, Helicoverpa armigera larvae (Hubner: Noctuidae)

Neonicotinoids have high agonistic affinity to insect nicotinic acetylcholine receptors (nAChR) and are frequently used as insecticides against most devastating lepidopteran insect pests. Imidacloprid influenced dose-dependent decline in the state III and IV respiration, respiration control index (RCI), and P/O ratios, in vitro and in vivo. The bioassay indicated its LD50 value to be 531.24 μM. The insecticide exhibited a dose-dependent inhibition on F0F1-ATPase and complex IV activity. At 600 μM, the insecticide inhibited 83.62 and 27.13% of F0F1-ATPase and complex IV activity, respectively, and induced the release of 0.26 nmoles/min/mg protein of cytochrome c. A significant dose- and time-dependent increase in oxidative stress was observed; at 600 μM, the insecticide correspondingly induced lipid peroxidation, LDH activity, and accumulation of H2O2 content by 83.33, 31.51 and 223.66%. The stress was the maximum at 48 h of insecticide treatment (91.58, 35.28, and 189.80%, respectively). In contrast, catalase and superoxide dismutase were reduced in a dose- and time-dependent manner in imidacloprid-fed larvae. The results therefore suggest that imidacloprid impedes mitochondrial function and induces oxidative stress in H. armigera, which contributes to reduced growth of the larvae along with its neurotoxic effect

A Noval Hybrid SMOTE OverSampling Approach for Balancing Class Distribution on social media Text

Depression is a frequent and dangerous medical disorder that has an unhealthy effect on how a person feels, thinks, and behaves. Depression is also quite prevalent. Finding depression and treating it in its early stages is vital to prevent uncomfortable and perhaps life-threatening complications. An imbalance in the data creates several challenges, as a result of which the majority learners will have biases against the class that constitutes the majority, and in extreme situations, may completely dismiss the class that constitutes the minority. Traditional methods of machine learning have been widely used in the substantial research that has been conducted on class disparity over the last several decades. In addressing the challenge of imbalanced data in depression detection, the research aims to balance class distribution using Hybrid approach BI-LSTM along with synthetic minority over sampling tomek links and synthetic minority over sampling edited nearest neighbours’ techniques. This investigation presents a new approach that seeks to combine SMOTE with the Kalman filter to provide an innovative extension. The Kalman-SMOTE (KSMOTE) approach is used to filter out noisy samples in the final dataset, which consists of both the original data and the artificially created samples by SMOTE. This process effectively reduces the dataset's size. This approach enhances the accuracy of depression identification on social media, holding promise for healthcare applications. The outcomes demonstrate that the BI-LSTM classification framework is stronger to the other baseline models in the healthcare strategy for depression identification, for both balanced and unbalanced data

Microbial solubilization of heavy metals from soil using indigenous sulfur oxidizing bacterium: Effects of sulfur/soil ratio

680-683Present study assesses efficiency of bioleaching to decontaminate heavy metal laden soil affected by tannery effluent employing sulfur oxidizing bacterium, Acidithiobacillus thiooxidans. Concentrations of predominant heavy metals were Cd, 9; Cu, 95; Cr, 11800; Pb, 85; and Zn, 238 mg/kg. Irrespective of sulfur/soil ratio (0.14, 0.21, 0.29, 0.43 and 0.57), pH dropped from near neutral to below 1 over a period of 28 days; drop in pH was rapid when the ratio was 0.57 and it took only 6 days for pH to drop from 7.12 to 0.94. Production of sulphate (22-45 g/l) increased with rise in sulfur/soil ratio. Solubilization of heavy metals was: Cd, 44-57; Cu, 60-92; Cr, 72-81; Pb, 39-56; and Zn, 55-94%

Effect of pH on chromium biosorption by chemically treated Saccharomyces

675-679The effect of initial pH on biosorption by Saccharomyces cerevisiae of total chromium present in tannery effluent was investigated. Maximum biosorption efficiency was evident at neutral pH with a metal removal efficiency of 99 %. S. cerevisiae was then pretreated with NaOH and HCHO-HCOOH to study the role of proteins and amino acids, respectively, in biosorption. At pH 7, 9 and 11, biomass pretreated with NaOH exhibited significant biosorption as compared to raw biomass and that treated with HCHO-HCOOH. However, trend reversed at pH 2. At pH 4, untreated biomass exhibited maximum chromium sorption, when compared to that treated with NaOH and HCHO-HCOOH

Complex Events Processing on Live News Events Using Apache Kafka and Clustering Techniques

The explosive growth of news and news content generated worldwide, coupled with the expansion through online media and rapid access to data, has made trouble and screening of news tedious. An expanding need for a model that can reprocess, break down, and order main content to extract interpretable information, explicitly recognizing subjects and content-driven groupings of articles. This paper proposed automated analyzing heterogeneous news through complex event processing (CEP) and machine learning (ML) algorithms. Initially, news content streamed using Apache Kafka, stored in Apache Druid, and further processed by a blend of natural language processing (NLP) and unsupervised machine learning (ML) techniques.</jats:p