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Biological wastewater treatment plants (BWWTPs) based on the activated sludge (AS) process have dramatically improved worldwide water sanitation despite increased urbanization and industrialization. However, current AS-based operations are considered economically and environmentally unsustainable. In this Perspective, we discuss our current understanding of microbial populations and their metabolic transformations in AS-based BWWTPs in view of developing more sustainable processes in the future. In particular, much has been learned over the course of the past 25 years about specialized microorganisms, which could be more comprehensively leveraged to recover energy and/or nutrients from wastewater streams. To achieve this, we propose a bottom-up design approach, focused around the concept of a wastewater biorefinery column, which would rely on the engineering of distinct ecological niches into a BWWTP in order to guarantee the targeted enrichment of specific organismal groups which in turn will allow the harvest of high-value resources from wastewater. This concept could be seen as a possible grand challenge to microbial ecologists and engineers alike at the centenary of the discovery of the AS process.

The study focused on analysing the eutrophication indicators of the Krishnagiri Reservoir Project (KRP) using the Water Quality Analysis Simulation Program (WASP). The reservoir was divided into six segments to simulate the indicators, and field measurements from 2015 to 2018 were used to calibrate the model while 2019 to 2022 were used to validate it. The results showed that the model predictions were in good agreement with the measured values, indicating the reliability of the model. The study assessed the impact of nutrient loads on dissolved oxygen, nitrate, phosphate, and chlorophyll-a. Four nutrient loading scenarios were simulated, and the most effective scenario (Scenario 4) involved a 75% reduction in nutrient load, which increased the reaeration rate by 1.47% and decreased chlorophyll-a concentrations by 88%. The study concluded that maintaining nitrates below 2.5 mg/L and phosphates below 0.75 mg/L could help restore the KRP reservoir's trophic status from hypereutrophic to mesotrophic. Overall, the study demonstrated the use of the WASP model in developing nutrient loading scenarios to manage reservoir water quality effectively. The findings could help policymakers and managers make informed decisions about reducing nutrient loads and restoring the trophic status of eutrophicated reservoirs. HIGHLIGHTS The study focused on the eutrophication management of the Krishnagiri Reservoir Project (KRP) using the Water Quality Analysis Stimulation Program (WASP) model with different nutrient load scenarios.; WASP is used to simulate the eutrophication indicators such as dissolved oxygen, chlorophyll-a, nitrate, and phosphate concentrations in the KRP reservoir.; Calibrated Eutro-model was used to develop scenarios for eutrophication management.;

Abstract The applications of the Internet of Things in different areas and the resources that demand these applications are on the increase. However, the limitations of the IoT devices such as processing capability, storage, and energy are challenging. Computational offloading is introduced to ameliorate the limitations of mobile devices. Offloading heavy data size to a remote node introduces the problem of additional delay due to transmission. Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. The proposed method uses a rank accuracy estimation model to decide the rank-1 value to be applied for the decomposition. Then canonical Polyadic decomposition-based attribute reduction is applied to the offload-able task to reduce the data size. Enhance hybrid genetic algorithm and particle Swarm optimization are developed to select the optimal device in either fog or cloud. The proposed algorithm improved the response time, delay, number of offloaded tasks, throughput, and energy consumption of the IoT requests. The simulation is implemented with iFogSim and java programming language. The proposed method can be applied in smart cities, monitoring, health delivery, augmented reality, and gaming among others.

Background: Arsenic is viewed as a bizarre and frightful element in human history. Recent studies showed that even low levels of arsenic can cause neurological damage. Phyllanthus amarus is an important medicinal herb proved to have neuro protective effect in experimental animals. This pre-clinical study used an animal model of arsenic toxicity and screened the different neuroprotective mechanisms of Phyllanthus amarus ethanolic extract. Purpose: To assess the effect of Phyllanthus amarus ethanolic extract on various biochemical parameter's in the brain of arsenic administered Wistar albino rats. Methodology: The neuroprotective activity of P. amarus against arsenic induced toxicity was studied in Wistar albino rats. The experimental animals (n=24) were divided into four groups of 6 rats each. Rats in group I received distilled water, whereas rats in groups II, III, and IV received arsenic as sodium arsenite salt (40 mg/kg b.w) in drinking water daily for 28 days. In addition, rats from groups III, and IV also received P. amarus ethanolic extract 100 and 200 mg/kg b.w, by intragastric route, once daily for a period of 28 days. At the end of the experiment rats were subjected to various neurobehavioral tests such as Elevated plus maze, Light dark arena, Forced swim test and Tail suspension test. After 24 h of the last treatment, the animals were euthanized and brain tissue was assayed for various biochemical parameters. Results: ANOVA and Post hoc testing of behavioral and biochemical data (Dunnett's t-test and Student unpaired T test) showed co-administration of P. amarus ethanolic extract significantly reversed anxiety and depression-like behaviors in experimental animals. P. amarus ethanolic extract effectively reduced acetyl cholinesterase activity in the brain, and it also increased the levels of dopamine and serotonin in the brains of arsenic-treated animals as compared to only arsenic treated group. P. amarus ethanolic extract significantly decreased lipid peroxidase and increased brain catalase and super oxidase dismutase activities. Conclusion: Based on the pharmacological, and biochemical analysis the plant extracts of P. amarus have shown protective effects against arsenic induced neurotoxicity.

Abstract With the increasing level of IoT applications, computation offloading is now undoubtedly vital because of the IoT devices limitation of processing capability and energy. Computation offloading involves moving data from IoT devices to another processing layer with higher processing capability. However, the size of data offloaded is directly proportional to the delay incurred by the offloading. Therefore, introducing data reduction technique to reduce the offloadable data minimizes delay resulting from the offloading method. In this paper, two main strategies are proposed to address the enormous data volume that result to computation offloading delay. First, IoT Canonical Polyadic Decomposition for Deep Learning Algorithm is proposed. The main purpose of this strategy is to downsize the IoT offloadable data. In the study, the Kaggle-cat-and-dog dataset was used to evaluate the impact of the proposed data compression. The proposed method downsizes the data significantly and can reduce the delay due to network traffic. Secondly, Rank Accuracy Estimation Model is proposed for determining the Rank-1 value. The result of the proposed method proves that the proposed methods are better in terms of data compression compared to distributed deep learning layers. This method can be applied in smart city, vehicular networks, and telemedicine etc.

Aim: Using atenolol as a model active pharmaceutical and galactomannan from the seeds of Trigonella foenumgraecum as a mucoadhesive polymer, an effort was made to develop a gastroretentive bioadhesive floating delivery system to improve the residence time in the stomach. Materials and Methods: Different formulations were made with Hydroxypropyl Methyl Cellulose (HPMC) and galactomannan. Galactomannan was chosen because of its exceptional swelling properties in aqueous environments. In this investigation, citric acid and sodium bicarbonate were utilized as gas-producing components. Pre- and postcompression evaluations were performed on the manufactured tablets. The floating properties as well as the atenolol release pattern were investigated. Results: The extracted polymer was characterized using various techniques and found to be similar to literature. The results from GC analysis showed a residual acetone content of 0.127 ppm, indicating that the extracted polymer is safer to use in the formulation of gastroretentive tablets. The physicochemical properties of the manufactured tablets were satisfactory in terms of swelling index, release characteristics, and buoyancy pattern. All of the manufactured batches had adequate in vitro buoyancy. The gastroretentive tablet exhibited axial and radial swelling throughout the in vitro buoyancy test. According to the testing, the formulation remained buoyant for approximately 8 to 12 hr. Conclusion: According to the results of the evaluation, the manufactured tablet has a pleasing look, is heat stable, and is therapeutically efficient. F3 was determined to be the optimal formulation based on the data collected. [ABSTRACT FROM AUTHOR]

Rosai–Dorfman disease (RDD) with spinal cord involvement is a rare clinical entity. We report a case of RDD with paravertebral and intraspinal epidural involvement in a 24-year-old male Bangladeshi patient who presented with progressive bilateral lower limb weakness for 20 days duration associated with spasticity and muscle spasm. MRI demonstrated an enhancing paravertebral soft tissue lesion extending from C7 through T4 with intraspinal epidural extension encasing the spinal cord with focal cord oedema. Histopathology of the paraspinal-epidural lesion reported a finding consistent with RDD. The patient was initiated on high-dose steroids. Follow up after 2 months demonstrated symptomatic improvement as the patient was able to move on the crutch and repeated MRI showed lesion regression. Keywords: Rosai–Dorfman disease, Tuberculosis, Lymphoma, Spinal cord