Reliable and Automatic Recognition of Leaf Disease Detection using Optimal Monarch Ant Lion Recurrent Learning

Around 7.5 billion people worldwide depend on agriculture production for their livelihood, making it an essential component in keeping life alive on the planet. Negative impacts are being caused on the agroecosystem due to the rapid increase in the use of chemicals to combat plant diseases. These chemicals include fungicides, bactericides, and insecticides. Both the quantity and quality of the output are impacted when there is a high-scale prevalence of diseases in crops. Plant diseases provide a significant obstacle for the agricultural industry, which has a negative impact on the growth of plants and the output of crops. The problem of early detection and diagnosis of diseases can be solved for the benefit of the farming community by employing a method that is both quick and reliable regularly. This article proposes a model for the detection and diagnosis of leaf infection called the Automatic Optimal Monarch AntLion Recurrent Learning (MALRL) model, which attains a greater authenticity. The design of a hybrid version of the Monarch Butter Fly optimization algorithm and the AntLion Optimization Algorithm is incorporated into the MALRL technique that has been proposed. In the leaf image, it is used to determine acceptable aspects of impacted regions. After that, the optimal characteristics are used to aid the Long Short Term Neural Network (LSTM) classifier to speed up the process of lung disease categorization. The experiment's findings are analyzed and compared to those of ANN, CNN, and DNN. The proposed method was successful in achieving a high level of accuracy when detecting leaf disease for images of healthy leaves in comparison to other conventional methods

Performance evaluation of a common effluent treatment plant for tannery industries

Tannery is one of the oldest industries in the world and is one of the fastest developing industries in India. It is one of the problematic industries in India which generate high quantum of wastewater with high TDS and toxicity due to chromium. Hence, discharge of tannery effluent is a very serious issue. Many conventional treatment processes has been carried out in these industry before the discharge of effluent. One of the most common treatment process applied is biological treatment process by activated sludge process and upflow anaerobic sludge blanket process. Due to the high cost of installation for this treatment process, in many of the small scale tannery industries in India, the wastewater treatment is carried out in common effluent treatment plant (CETP). In the present study the performance of CETP for tannery effluent in terms of Biological oxygen demand (BOD),  Chemical oxygen demand (COD), Total suspended solids (TSS), Total dissolved solids (TDS), and by water tracer studies using Rhodamine. ETP showed a removal efficiency of BOD-66%, COD- 21%, TSS-21% and TDS-5%. The study revealed that ETP has to be redesigned based on the characteristics of influent wastewater in order to meet the Pollution Control Board prescribed standard limits for ETP.  &nbsp

Integrative determination of the atomic structure of mutant huntingtin exon 1 fibrils from Huntington's disease

Neurodegeneration in Huntington's disease (HD) is accompanied by the aggregation of fragments of the mutant huntingtin protein, a biomarker of disease progression. A particular pathogenic role has been attributed to the aggregation-prone huntingtin exon 1 (HttEx1) fragment, whose polyglutamine (polyQ) segment is expanded. Unlike amyloid fibrils from Parkinson's and Alzheimer's diseases, the atomic-level structure of HttEx1 fibrils has remained unknown, limiting diagnostic and treatment efforts. We present and analyze the structure of fibrils formed by polyQ peptides and polyQ-expanded HttEx1. Atomic-resolution perspectives are enabled by an integrative analysis and unrestrained all-atom molecular dynamics (MD) simulations incorporating experimental data from electron microscopy (EM), solid-state NMR, and other techniques. Visualizing the HttEx1 subdomains in atomic detail helps explaining the biological properties of these protein aggregates, as well as paves the way for targeting them for detection and degradation.</p

Two-pion Bose–Einstein correlations in central Pb–Pb collisions at √sNN=2.76 TeV

The first measurement of two-pion Bose–Einstein correlations in central Pb–Pb collisions at √sNN=2.76 TeV at the Large Hadron Collider is presented. We observe a growing trend with energy now not only for the longitudinal and the outward but also for the sideward pion source radius. The pion homogeneity volume and the decoupling time are significantly larger than those measured at RHIC

Inclusive J/ψ production in pp collisions at √s=2.76 TeV

The ALICE Collaboration has measured inclusive J/ψ production in pp collisions at a center-of-mass energy √s=2.76 TeV at the LHC. The results presented in this Letter refer to the rapidity ranges |y|<0.9 and 2.5<y<4 and have been obtained by measuring the electron and muon pair decay channels, respectively. The integrated luminosities for the two channels are Linte=1.1 nb−1 and Lintμ=19.9 nb−1, and the corresponding signal statistics are NJ/ψe+e−=59±14 and NJ/ψμ+μ−=1364±53. We present dσJ/ψ/dy for the two rapidity regions under study and, for the forward-y range, d2σJ/ψ/dydpt in the transverse momentum domain 0<pt<8 GeV/c. The results are compared with previously published results at s=7 TeV and with theoretical calculations