Medical management of mesothelioma

Mesothelioma is a malignant tumour of pleura and other serosal tissues. It arises many years after asbestos exposure. There is currently no highly effective therapy and the median survival is approximately 10-12 months from diagnosis. Most patients cannot be treated surgically due to the advanced stage of the disease at diagnosis or are unfit for radical surgery. New antifolate drugs (pemetrexed or raltitrexed) in combination with platinum are associated with longer median survival than platinum alone, an increase which averages about three months. Radiation therapy is limited by its toxicity to the underlying lung, but newer field and dose planning methods are under investigation. Mesothelioma presents major challenges for the palliative management of dyspnoea, pain, and cancer cachexia syndrome

Nature and occurence of yeasts in Haryana grapes and wines

More than one hundred isolates of yeasts were taken from juice, must (at different stages of fermentation) and wine prepared from seven different grape varieties grown in Haryana. The isolates fell into 6 genera and 14 species. Saccharomyces yeasts were the most frequently encountered species during the fermentation, and all but one were identified as S. cerevisiae, S. cerevisiae var. ellipsoideus, S. steineri, S. carlsbergensis and S. mellis. Schizosaccharomyces pombe, Debaryomyces vini, Candida pulcherrima, C. guilliermondii, Endomycopsis fibuliger, E. fibuliger var. monospora and E. fibuliger var. bispora were the other strains isolated.The occurrence of Schizosaccharomyces pombe and strains of Endomocopsis fibuliger is of interest in this connection when it is considered that Kloeckera apiculata and Saccharomyces oviformis have been significantly absent in Haryana grapes and musts

PCN: A Deep Learning Approach to Jet Tagging Utilizing Novel Graph Construction Methods and Chebyshev Graph Convolutions

Jet tagging is a classification problem in high-energy physics experiments that aims to identify the collimated sprays of subatomic particles, jets, from particle collisions and tag them to their emitter particle. Advances in jet tagging present opportunities for searches of new physics beyond the Standard Model. Current approaches use deep learning to uncover hidden patterns in complex collision data. However, the representation of jets as inputs to a deep learning model have been varied, and often, informative features are withheld from models. In this study, we propose a graph-based representation of a jet that encodes the most information possible. To learn best from this representation, we design Particle Chebyshev Network (PCN), a graph neural network (GNN) using Chebyshev graph convolutions (ChebConv). ChebConv has been demonstrated as an effective alternative to classical graph convolutions in GNNs and has yet to be explored in jet tagging. PCN achieves a substantial improvement in accuracy over existing taggers and opens the door to future studies into graph-based representations of jets and ChebConv layers in high-energy physics experiments. Code is available at https://github.com/YVSemlani/PCN-Jet-Tagging.Comment: 13 pages, 2 figures, and 4 table

A Brief Review on Plant Leaf Disease Detection Using Auto Adaptive Approach

This proposal is regarding automatic detection of diseases and pathological part present within the leaf pictures of plants and even within the agriculture Crop production it is through with advancement of technology that helps in farming to extend the production. Primarily there is downside of detection accuracy and in neural network approach support vector machine (SVM) is exist already. During this analysis proposal, a completely unique approach can design to extend accuracy victimization KNN. During this analysis work, we are going to work upon the advancement of the plant diseases prediction techniques and going to propose a completely unique approach for the detection rule