Publications by authors named "Rajneesh Sharma"

Development of native microbial consortia is crucial for the sustainable management of plant diseases in modern agriculture. This study aimed to evaluate the antagonistic potential of various microbial isolates against , a significant soil-borne pathogen. A total of 480 bacteria, 283 fungi, and 150 actinomycetes were isolated and screened using in vitro dual plate assays.

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This work proposes a novel technique called Enhanced JAYA (EJAYA) assisted Q-Learning for the classification of pulmonary diseases, such as pneumonia and tuberculosis (TB) sub-classes using chest x-ray images. The work introduces Fuzzy lattices formation to handle real time (non-linear and non-stationary) data based feature extraction using Schrödinger equation. Features based adaptive classification is made possible through the Q-learning algorithm wherein optimal Q-values selection is done via EJAYA optimization algorithm.

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The study aimed to understand the dynamic interplay between plants and their associated microbes to develop an efficient microbial consortium for managing Fusarium wilt of cumin. A total of 601 rhizospheric and endophytic bacteria and fungi were screened for antagonistic activity against Fusarium oxysporum f.sp.

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Soil organic carbon (SOC) is a dynamic soil property (DSP) that represents the largest portion of terrestrial carbon. Its relevance to carbon sequestration and the potential effects of land use on SOC storage, make it imperative to map across both space and time. Most regional-scale studies mapping SOC give static estimates and train different models for different periods with varying accuracies.

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AKT and ERK 1/2 play a pivotal role in cancer cell survival, proliferation, migration, and angiogenesis. Therefore, AKT and ERK 1/2 are considered crucial targets for cancer intervention. In this study, we envisaged the role of AKT and ERK signaling in apoptosis regulation in presence of compound 4h, a novel synthetic derivative of quinoxalinone substituted spiropyrrolizines exhibiting substantial antiproliferative activity in various cancer cell lines.

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A computationally efficient statistical model for the prediction of the strength of mineralized collagen fibril (a basic building block of bone) is presented by taking into account the uncertainties associated with the geometrical and material parameters of collagen and mineral phases. The mineral plates have been considered as one-dimensional bar elements embedded in the two-dimensional plane stress collagen matrix. The mineral phase is considered as linear elastic and a hyperelastic material model is adopted for the collagen phase.

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In this work a fuzzy reinforcement learning (RL) based intelligent classifier for power transformer incipient faults is proposed. Fault classifiers proposed till date have low identification accuracy and do not identify all types of transformer faults. Herein, an attempt has been made to design an adaptive, intelligent transformer fault classifier that progressively learns to identify faults on-line with high accuracy for all fault types.

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A multiscale model for mineralized collagen fibril (MCF) is proposed by taking into account the uncertainties associated with the geometrical properties of the mineral phase and its distribution in the organic matrix. The asymptotic homogenization approach along with periodic boundary conditions has been used to derive the effective elastic moduli of bone's nanostructure at two hierarchical length scales, namely: microfibril (MF) and MCF. The uncertainties associated with the mineral plates have been directly included in the finite element mesh by randomly varying their sizes and structural arrangements.

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We propose a fuzzy reinforcement learning (RL) based controller that generates a stable control action by lyapunov constraining fuzzy linguistic rules. In particular, we attempt at lyapunov constraining the consequent part of fuzzy rules in a fuzzy RL setup. Ours is a first attempt at designing a linguistic RL controller with lyapunov constrained fuzzy consequents to progressively learn a stable optimal policy.

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Background: Dental restorative materials containing silver-mercury compounds have been known to induce oral lichenoid lesions.

Objectives: To determine the frequency of contact allergy to dental restoration materials in patients with oral lichenoid lesions and to study the effect of removal of the materials on the lesions.

Results: Forty-five patients were recruited in three groups of 15 each: Group A (lesions in close contact with dental materials), Group B (lesions extending 1 cm beyond the area of contact) and Group C (no topographic relationship).

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Objective: To determine the frequency of extraintestinal manifestations in patients with idiopathic ulcerative colitis.

Methods: 46 patients underwent detailed clinical, biochemical and radiological evaluation.

Results: One patient (2%) had peripheral arthritis and two patients (4%) had ocular involvement in the form of anterior uveitis.

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