Comparative analysis of the survival and regeneration potential of juvenile and matured earthworm, Eudrilus eugeniae, upon in vivo and in vitro maintenance.

Eudrilus eugeniae is a clitellum-dependent earthworm that requires intact clitellum segments for its survival and regeneration. The present study aims to interconnect the survival and regeneration ability that varies between in vivo and in vitro maintenance upon different sites of amputation. The amputated portion of the worm that possesses intact clitellum (13th-18th segments) survived and had the potential to regenerate, whereas worms with partial or without clitellum segments only survived and were unable to regenerate.

Optimization of Process Variables in the Drilling of LM6/BC Composites through Grey Relational Analysis.

The objective of this investigational analysis was to study the influence of process variables on the response during the drilling of LM6/B4C composite materials. Stir casting was employed to produce the LM6/B4C composites. A Vertical Machining Center (VMC) with a dynamometer was used to drill the holes and to record the thrust force.

Blended Ensemble Learning Prediction Model for Strengthening Diagnosis and Treatment of Chronic Diabetes Disease.

Diabetes mellitus (DM), commonly known as diabetes, is a collection of metabolic illnesses characterized by persistently high blood sugar levels. The signs of elevated blood sugar include increased hunger, frequent urination, and increased thirst. If DM is not treated properly, it may lead to several complications.

Predicting the Growth of F. proliferatum and F. culmorum and the Growth of Mycotoxin Using Machine Learning Approach.

In distinct parts of the food web, Fusarium culmorum and Fusarium preserving the relationship can germinate and grow zearalenone (ZEA) and fumonisins (FUM), accordingly. Antimicrobial drugs used to combat these fungi and toxic metabolites raise the risk of hazardous residue in food products, as well as the development of fungus tolerance. For modeling fungal growth and pathogenicity under separate water action ( ) (0.

An Enhancement on Convolutional Artificial Intelligent Based Diagnosis for Skin Disease Using Nanotechnology Sensors.

Skin disease is the major health problem around the world. The diagnosis of skin disease remains a challenge to dermatologist profession particularly in the detection, evaluation, and management. Health data are very large and complex due to this processing of data using traditional data processing techniques is very difficult.

Current scenario of solid waste management techniques and challenges in Covid-19 - A review.

Annually, world generates 2.01 billion tonnes of solid wastes and it is expected to generate 2.2 billion tonnes of solid waste by 2025.

Visible light photocatalytic and magnetic properties of V doped α-FeO (VFO) nanoparticles synthesized by polyol assisted hydrothermal method.

Vanadium-doped α-FeO nanoparticles (VFO nanoparticles) were prepared by polyol-assisted hydrothermal method. The impact on the structure, optical, magnetic and photocatalytic properties of α-FeO nanoparticles were studied by varying the vanadium concentration from 1 to 5%. XRD analysis confirms the presence of hematite phase with hexagonal structure and estimates the nanocrystals size as ∼26-38 nm.

Optimal energy efficient path planning of UAV using hybrid MACO-MEA* algorithm: theoretical and experimental approach.

Autonomous mission capabilities with optimal path are stringent requirements for Unmanned Aerial Vehicle (UAV) navigation in diverse applications. The proposed research framework is to identify an energy-efficient optimal path to achieve the designated missions for the navigation of UAVs in various constrained and denser obstacle prone regions. Hence, the present work is aimed to develop an optimal energy-efficient path planning algorithm through combining well known modified ant colony optimization algorithm (MACO) and a variant of A*, namely the memory-efficient A* algorithm (MEA*) for avoiding the obstacles in three dimensional (3D) environment and arrive at an optimal path with minimal energy consumption.

Sustainable Smart Industry: A Secure and Energy Efficient Consensus Mechanism for Artificial Intelligence Enabled Industrial Internet of Things.

In recent years, the Internet of Things (IoT) has been industrializing in various real-world applications, including smart industry and smart grids, to make human existence more reliable. An overwhelming volume of sensing data is produced from numerous sensor devices as the Industrial IoT (IIoT) becomes more industrialized. Artificial Intelligence (AI) plays a vital part in big data analyses as a powerful analytic tool that provides flexible and reliable information insights in real-time.

Deep Learning-Based Privacy-Preserving Data Transmission Scheme for Clustered IIoT Environment.

The Industrial Internet of Things (IIoT) has received significant attention from several leading industries like agriculture, mining, transport, energy, and healthcare. IIoT acts as a vital part of Industry 4.0 that mainly employs machine learning (ML) to investigate the interconnection and massive quantity of the IIoT data.

The regime of constructed wetlands in greywater treatment.

There is an excellent need for supply-side threats due to the enhanced degradation and reclamation of existing water bodies in the present scenario. This led to the global water crisis. One of the easiest ways to fulfil the growing need for freshwater is the recycling of wastewater.

Metal-Doped Graphitic Carbon Nitride Nanomaterials for Photocatalytic Environmental Applications-A Review.

In the current world situation, population and industrial growth have become major problems for energy and environmental concerns. Extremely noxious pollutants such as heavy metal ions, dyes, antibiotics, phenols, and pesticides in water are the main causes behind deprived water quality leading to inadequate access to clean water. In this connection, graphite carbon nitride (GCN or g-CN) a nonmetallic polymeric material has been utilized extensively as a visible-light-responsive photocatalyst for a variety of environmental applications.

Robust Spatial-Spectral Squeeze-Excitation AdaBound Dense Network (SE-AB-Densenet) for Hyperspectral Image Classification.

Increasing importance in the field of artificial intelligence has led to huge progress in remote sensing. Deep learning approaches have made tremendous progress in hyperspectral image (HSI) classification. However, the complexity in classifying the HSI data using a common convolutional neural network is still a challenge.

Integrated Approach to Interaction Studies of Pyrene Derivatives with Bovine Serum Albumin: Insights from Theory and Experiment.

This work aimed to investigate the interaction of bovine serum albumin with newly synthesized potent new pyrene derivatives (PS1 and PS2), which might prove useful to have a better antibacterial character as found for similar compounds in the previous report [Low et al. 2014, 12, 2269-2284]. However, to date, binding studies with plasma protein are still unknown.

ABC Fractional Order Vaccination Model for Covid-19 with Self-Protective Measures.

A mathematical model delineating the control strategies in transference of Covid-19 pandemic is examined through Atangana-Baleanu Caputo type fractional derivatives. The total count of people under observation is classified into Susceptible, Vaccinated, Infected and Protected groups (SVIP). The designed model studies the efficiency of vaccination and personal precautions incorporated qualitatively by every individual via fixed point theorem.

Application of waste eggshell as a source of calcium in bacterial bio-cementation to enhance the engineering characteristics of sand.

A technique to produce bio-cementation in sandy soil using the microbially induced calcium carbonate precipitation (MICP) process and calcium ions generated from eggshell is presented in this research. This research also focused on the application of S. pasteurii bacteria and L.

Retinopathy grading with deep learning and wavelet hyper-analytic activations.

Recent developments reveal the prominence of Diabetic Retinopathy (DR) grading. In the past few decades, Wavelet-based DR classification has shown successful impacts and the Deep Learning models, like Convolutional Neural Networks (CNN's), have evolved in offering the highest prediction accuracy. In this work, the features of the input image are enhanced with the integration of Multi-Resolution Analysis (MRA) and a CNN framework without costing more convolution filters.

AdaBoost Ensemble Methods Using K-Fold Cross Validation for Survivability with the Early Detection of Heart Disease.

As a result of technology improvements, various features have been collected for heart disease diagnosis. Large data sets have several drawbacks, including limited storage capacity and long access and processing times. For medical therapy, early diagnosis of heart problems is crucial.

Semenogelin, a coagulum macromolecule monitoring factor involved in the first step of fertilization: A prospective review.

Human male infertility affects approximately 1/10 couples worldwide, and its prevalence is found more in developed countries. Along with sperm cells, the secretions of the prostate, seminal vesicle and epididymis plays a major role in proper fertilization. Many studies have proven the functions of seminal vesicle secretions, especially semenogelin protein, as an optimiser for fertilization.

Highly economic and waste valorization strategy for multicomponent and Knoevenagel reactions using water extract of tamarind seed ash.

The application of solid organic waste-originated products in the preparation of synthetically and biologically significant compounds in aqueous media or pure water is a highly desired task in chemical synthesis that shows an effective solution to the circular economy and sustainable environment. In this article, we describe our research on the development of highly economic and sustainable protocols for the synthesis of biologically important oxygen-heterocycles (using a multicomponent reaction) and synthetically important olefins (via the Knoevenagel condensation reaction) using water extract of tamarind seed ash (WETS) as catalyst and aqueous reaction medium. The reactions are carried out at room temperature (RT) under toxic/problematic/volatile organic solvent-free conditions.

Classification of Myopathy and Amyotrophic Lateral Sclerosis Electromyograms Using Bat Algorithm and Deep Neural Networks.

Electromyograms (EMG) are a recorded galvanic action of nerves and muscles which assists in diagnosing the disorders associated with muscles and nerves. The efficient discrimination of abnormal EMG signals, myopathy and amyotrophic lateral sclerosis, engage crucial role in automatic diagnostic assistance tools, since EMG signals are nonstationary signals. Hence, for computer-aided identification of abnormalities, extraction of features, selection of superlative feature subset, and developing an efficient classifier are indispensable.

Hybridization Effect on Mechanical Properties of Basalt/Kevlar/Epoxy Composite Laminates.

The present work investigates the fabrication of Kevlar/epoxy and basalt/epoxy and Kevlar/basalt/epoxy hybrid composite laminates and compares their mechanical properties. Mechanical characterization tests, including tension, flexural, impact and hardness tests, as per ASTM standards, were conducted on coupons cut out from the fabricated composite panels. A hand layup fabrication technique was used to fabricate composite panels with seven layers in them.

Modeling and optimization of photovoltaic serpentine type thermal solar collector with thermal energy storage system for hot water and electricity generation for single residential building.

Increasing surface temperature has a significant effect on the electrical performance of photovoltaic (PV) panels. A closed-loop forced circulation serpentine tube design of cooling water system was used in this study for effectively management of the surface temperature of PV panels. A real-time experiment was first carried out with a PV panel with a cooling system at heat transfer fluid (HTF) flow rates of 60 kg h, 120 kg h, and 180 kg h.

Energy recovery of waste plastics into diesel fuel with ethanol and ethoxy ethyl acetate additives on circular economy strategy.

The widespread use of plastic goods creates huge disposal issues and environmental concerns. Increasing emphasis has been paid to the notion of a circular economy, which might have a significant impact on the demand for plastic raw materials. Post-consumer plastics recycling is a major focus of the nation's circular economy.