Plant Disease Detection using Deep Learning in Banana and Sunflower

In recent years plant disease detection and classification is finding a lot of scope in the field of agriculture. The use of image pre-processing along with deep learning techniques is making the role of farmers easy in the process of plant leaf disease detection. In this paper we propose a deep learning technique, ResNet-50 for the identification and classification of leaf diseases mainly in banana and sunflower. Images for the training and testing purpose are collected by visiting the farms and from village dataset for normal, leaf spot, leaf blight, powdery mildew, bunchy top, sigatoka, panama wilt. Pre-processing is done to remove eliminate the noise in the image by converting the RGB input to HSV image. Binary pictures are retrieved to separate the diseased and unaffected portions based on the hue and saturation components. A clustering method is utilized to separate the diseased region from the normal portion and the background. Classification of the disease is carried out using ResNet-50 algorithm. The experimental results obtained are compared with CNN, machine learning algorithms like SVM, KNN, DT and Ensemble algorithm like RF and XG booster. The proposed algorithm provided maximum efficiency compared to other algorithms

ANTIPROLIFERATIVE, ADME AND POTENTIAL IN SILICO G6PDH INHIBITORY ACTIVITY OF NOVEL 2-(1-BENZOFURAN-2-YL)-4-(5-PHENYL-4H-1, 2, 4-TRIAZOL-3-YL) QUINOLINE DERIVATIVES

Objectives: Synthesis of new 2-(1-benzofuran-2-yl)-4-(5-phenyl-4H-1, 2, 4-triazol-3-yl) quinoline and its derivatives for antiproliferative potential against cancer cells.Methods: The general methods were employed for the synthesis and the structures were confirmed by IR, 1H-NMR, 13C-NMR and mass spectral analysis. The antiproliferative activity was performed by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay and molecular docking study were performed by Auto Dock Tools. In silico Absorption-Distribution-Metabolism-Excretion-Toxicity (ADMET) study for the drug, likeliness was carried out on ACD/lab-2.Results: The compound 3l showed 44, 44, 38 and 37 % inhibition against MCF-7, HepG2, Colo205 and HeLa cell lines, respectively; whereas, the compounds 3i and 3j exhibited 49 and 42 % inhibition against MCF-7 cell line. The molecular docking study revealed that the compound 3i has the lowest binding energy (-8.60 Kcal mol-1), suggesting to be potentially best inhibitor of Glucose-6-phosphate dehydrogenase (G6PDH). The in silico ADME analysis also revealed that compound 3i does not violate any of the Lipinski rules of five and has the best stimulative human colonic absorption up to 95 %.Conclusion: The study reveals that the compounds containing benzofuran coupled nitrogen heterocycles are essential for activity as they possess excellent drug-like characteristics.Â

Search for multimessenger signals in NOvA coincident with LIGO/Virgo detections

Using the NOvA neutrino detectors, a broad search has been performed for any signal coincident with 28 gravitational wave events detected by the LIGO/Virgo Collaboration between September 2015 and July 2019. For all of these events, NOvA is sensitive to possible arrival of neutrinos and cosmic rays of GeV and higher energies. For five (seven) events in the NOvA Far (Near) Detector, timely public alerts from the LIGO/Virgo Collaboration allowed recording of MeV-scale events. No signal candidates were found

Search for multimessenger signals in NOvA coincident with LIGO/Virgo detections

Using the NOvA neutrino detectors, a broad search has been performed for any signal coincident with 28 gravitational wave events detected by the LIGO/Virgo Collaboration between September 2015 and July 2019. For all of these events, NOvA is sensitive to possible arrival of neutrinos and cosmic rays of GeV and higher energies. For five (seven) events in the NOvA Far (Near) Detector, timely public alerts from the LIGO/Virgo Collaboration allowed recording of MeV-scale events. No signal candidates were found

Measurement of neutrino-induced neutral-current coherent π⁰ production in the NOvA near detector

The cross section of neutrino-induced neutral-current coherent π⁰ production on a carbon-dominated target is measured in the NOvA near detector. This measurement uses a narrow-band neutrino beam with an average neutrino energy of 2.7 GeV, which is of interest to ongoing and future long-baseline neutrino oscillation experiments. The measured, flux-averaged cross section is σ = 13.8±0.9(stat)±2.3(syst)×10⁻⁴⁰ cm²/nucleus, consistent with model prediction. This result is the most precise measurement of neutral-current coherent π⁰ production in the few-GeV neutrino energy region

Supernova neutrino detection in NOvA

The NOvA long-baseline neutrino experiment uses a pair of large, segmented, liquid-scintillator calorimeters to study neutrino oscillations, using GeV-scale neutrinos from the Fermilab NuMI beam. These detectors are also sensitive to the flux of neutrinos which are emitted during a core-collapse supernova through inverse beta decay interactions on carbon at energies of O(10 MeV). This signature provides a means to study the dominant mode of energy release for a core-collapse supernova occurring in our galaxy. We describe the data-driven software trigger system developed and employed by the NOvA experiment to identify and record neutrino data from nearby galactic supernovae. This technique has been used by NOvA to self-trigger on potential core-collapse supernovae in our galaxy, with an estimated sensitivity reaching out to 10 kpc distance while achieving a detection efficiency of 23% to 49% for supernovae from progenitor stars with masses of 9.6 M_⊙ to 27 M_⊙, respectively

Measurement of neutrino-induced neutral-current coherent π⁰ production in the NOvA near detector

The cross section of neutrino-induced neutral-current coherent π⁰ production on a carbon-dominated target is measured in the NOvA near detector. This measurement uses a narrow-band neutrino beam with an average neutrino energy of 2.7 GeV, which is of interest to ongoing and future long-baseline neutrino oscillation experiments. The measured, flux-averaged cross section is σ = 13.8±0.9(stat)±2.3(syst)×10⁻⁴⁰ cm²/nucleus, consistent with model prediction. This result is the most precise measurement of neutral-current coherent π⁰ production in the few-GeV neutrino energy region