കരിമീന്‍ കൃഷി സാധ്യതകള്‍

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The Egr transcription factor family: From signal transduction to kidney differentiation

Extracellular “signals” in the form of neurotransmitters, growth factors, hormones, and matrix are known to be key modulators of cellular phenotype. These agents lead to the generation of second messenger signals in the plasma membrane and cytosol. In turn, these biochemical events modulate the expression of a set of so-called immediate-early genes (IEG), whose induction does not require de novo protein synthesis. Several years ago, we and others identified several IEGs [reviewed in 1 and 2]. Of particular interest to our laboratory has been a subset of IEGs that encode transcription factors, since as such they might: (1) be the targets for second messenger events, and (2) activate or repress the transcription of critical genes required to effect a particular cellular phenotype. Thus, immediate-early transcription factors (IETF) should couple short-term responses in the form of second messenger events to long-term changes in gene expression instrumental in altering phenotype

DeepSolarEye: Power Loss Prediction and Weakly Supervised Soiling Localization via Fully Convolutional Networks for Solar Panels

The impact of soiling on solar panels is an important and well-studied problem in renewable energy sector. In this paper, we present the first convolutional neural network (CNN) based approach for solar panel soiling and defect analysis. Our approach takes an RGB image of solar panel and environmental factors as inputs to predict power loss, soiling localization, and soiling type. In computer vision, localization is a complex task which typically requires manually labeled training data such as bounding boxes or segmentation masks. Our proposed approach consists of specialized four stages which completely avoids localization ground truth and only needs panel images with power loss labels for training. The region of impact area obtained from the predicted localization masks are classified into soiling types using the webly supervised learning. For improving localization capabilities of CNNs, we introduce a novel bi-directional input-aware fusion (BiDIAF) block that reinforces the input at different levels of CNN to learn input-specific feature maps. Our empirical study shows that BiDIAF improves the power loss prediction accuracy by about 3% and localization accuracy by about 4%. Our end-to-end model yields further improvement of about 24% on localization when learned in a weakly supervised manner. Our approach is generalizable and showed promising results on web crawled solar panel images. Our system has a frame rate of 22 fps (including all steps) on a NVIDIA TitanX GPU. Additionally, we collected first of it's kind dataset for solar panel image analysis consisting 45,000+ images.Comment: Accepted for publication at WACV 201

The Repurposing Drugs in Oncology (ReDO) Project

The Repurposing Drugs in Oncology (ReDO) Project seeks to repurpose well-known and well-characterised non-cancer drugs for new uses in oncology. The rationale for this project is presented, examining current issues in oncological drug development, challenges for health systems, and existing and future patient needs. In addition to discussing the advantages of repurposing, the paper also outlines some of the characteristics used in the selection of drug candidates by this project. Challenges in moving candidate drugs into clinical trial and subsequent practice are also discussed

Hemolytic and DNA binding studies of divalent transition metal ion based macrocyclic complexes

529-535New tetra-azamacrocyclic complexes of Ni (II) and Cu(II) have been synthesized by template methodology leading to the formation of complex of type [MLX2] where L is a macrcocyclic ligand obtained from the condensation of 4-Methyl-o-phenylenediamine (DAT) and 1,3-diphenylpropane-1,3-dione (DBM)and X= NO3-, Cl-, and CH3COO-. Characterization of newly prepared complexes has been  done by using various physico-analytical techniques like UV-visible, IR, ESR, CHN, Magnetic susceptibilities and PXRD.The non-electrolytic nature of the complexes was elucidated by lower value of molar conductance. The data received from various techniques give an indication towards the octahedral geometry of the complexes. The macrocyclic ring is present at the equatorial position whereas the axial positions are occupied by the ligands Cl-, NO3- and CH3COO-. Screening of all the complexes has been performed against the pathogenic strains of microbes in order to check their antimicrobial potential. Invitro-hemolytic activity reveals about the extent to which lyses of hemoglobin takes place. The Herring fish sperm DNA interaction studies are carried out with the help of UV-absorption spectra. Molecular modeling was done through the assistance of  software Chem 3D Ultra that gives the energy calculation and their quantum chemical parameter