Design And Implementation Of Dual Input Single Output Converter For Real World Applications

With the adding integration of renewable energy sources such as solar, hydro, wind for household energy systems, the need for effective power operation results has come pivotal. In addition to this, battery is used as energy storehouse system to give provisory power when oscillations happen due to renewable sources. This integration helps to manage inflow of power supply without disturbances in real world operations. The present system concentrates on Dual Input Single Output DC- DC converter. It enhances the connection and distribution of energy from binary energy sources. It maximizes the effectiveness while maintaining a steady and reliable energy force through innovative power inflow operation. This work incorporates with basic and improved level of voltage management systems. Initially system is validated for both simulations and hardware with two battery sources of 12 V connected to converters which provides stable output voltage of 12V without fluctuations. Later, the system is improved by considering solar as one input source and battery as another input source. This system showcases effectiveness of dual inputs to converters by providing 150V of AC voltage which suits for real world applications. This work is validated by MATLAB simulations and Hardware implementations, by providing regulated output voltage. It suits for Domestic grid applications when fluctuations occur thorough renewable sources. In order to implement this esp32 Microcontroller and PIC Microcontroller was utilized. The experimental results satisfy with simulation results, verifying the converter’s ability to efficiently manage energy flow while minimizing waste. This DC DC conversion approach provides a cost-effective and scalable solution for integrating renewable energy into real world applications. By smartly balancing energy sources, the Dual Input Single Output converter enhances overall efficiency and sustainability. Further, contributes to the higher aim of reducing dependency on nonrenewable fossil fuel based power generation and distribution

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Genetic analysis of groundnut (Arachis hypogaea L.) genotypes for yield and oil quality parameters

Genetic variability is a foundation for advancing crop improvement programs. The effectiveness of selection is influenced by the characteristics, scope, and degree of genetic variability found in the material, as well as the extent to which this variability is heritable. This study assessed fifteen traits, including yield and oil quality parameters, in 55 groundnut accessions from diverse origins. The analysis of genetic parameters, including phenotypic coefficient of variation (PCV), genotypic coefficient of variation (GCV), heritability, genetic advance as a percentage of the mean (GAM), skewness, and kurtosis revealed significant genetic variation for several key traits. Notably, the traits viz., the number of branches(NB)/plant, hundred pod weight, shelling percentage(SP), oil yield/plant, and oleic acid(OA) content exhibited high PCV, GCV, heritability, and GAM. The analysis showed significant genetic variability and a predominance of additive gene effects, suggesting phenotypic selection as an effective approach for groundnut improvement. Association analysis revealed positive genotypic and phenotypic correlations of single plant yield(SPY) with traits like days to first flowering(DFiF), NB per plant, number of pods(NP) per plant, hundred pod weight, oil yield per plant (OYPP), and OA content. Principal component analysis (PCA) identified five principal components with eigenvalues greater than 1, explaining 75.13% of the total variation. A biplot constructed using the first two PCs visually represented the importance of NP/plant, NB/plant, oil yield/plant, and OA content for yield improvement strategies. Cluster analysis efficiently grouped the 55 genotypes into five distinct clusters. The high OA lines "Girnar 4" and "Girnar 5" were clustered together. This information suggests that selecting accessions from clusters with greater genetic distance can be a valuable strategy to maximize genetic variability within breeding programs

Immune-complex deposits in “pauci-immune” glomerulonephritis: a case report and brief review of recent literature

Anti-neutrophil cytoplasmic antibody (ANCA)-associated glomerulonephritis is considered a “pauci-immune” disease, characterized by absent or mild glomerular tuft staining for immunoglobulin and/or complement. We describe a 72-year-old man with progressive renal failure over five months who was found to have P-ANCA associated crescentic glomerulonephritis. Renal biopsy also revealed immunofluorescence staining for Immunoglobulin G and C3. Treatment comprised corticosteroids, cyclophosphamide, and plasmapheresis but unfortunately kidney function did not recover, likely due to substantial interstitial fibrosis at diagnosis. This case illustrates that serologic evaluation for ANCAs should not be discounted when immune deposits are present. Prompt diagnosis is warranted

Comparative multimodal statistical analysis for Yield Stability in Mutant populations of Rice (Oryza sativa L.) var. ADT (R) 47

Rice is an important staple food for half of the world’s population. Genetic erosion was caused by the development of high-yielding cultivars and the extensive cultivation of these kinds. Mutation breeding is promising not only for creating and utilizing the new variability but also an indispensable approach through which yield might be improved without altering the existing desirable characters. Induced mutations, have offered a single and short alternative to conventional breeding that includes isolation, screening, selection and testing generation after generation. A multi-model approach employing BLUP-based simultaneous selection, to assess the stability and performance of ADT 47 mutants genotypes with respect to the grain yield was performed. All members of the AMMI (Additive Main Effects and Multiplicative Interaction) family were less accurate than BLUP (Best linear unbiased prediction). BLUP approach involved the estimation of Harmonic mean of genotypic values (HMGV) which is used to infer both yield and stability, Relative performance of genotypic values (RPGV) involved in the estimation of mean yield and genotypic adaptability), harmonic mean of the relative performance of genotypic values (HMRPGV) tangled to evaluate stability, adaptability, and yield simultaneously. Comparing all the calculated indices, mutants viz., 160-39-1, 200-30-3, 250-36-1, 200-69-1 were highly stable for plant yield along with ADT47 control variety

Isolation of DNA sequences on human chromosome 21 by application of a recombination-based assay to DNA from flow-sorted chromosomes

By merging two efficient technologies, bivariate flow sorting of human metaphase chromosomes and a recombination-based assay for sequence complexity, we isolated 28 cloned DNA segments homologous to loci on human chromosome 21. Subregional mapping of these DNA segments with a somatic cell hybrid panel showed that 26 of the 28 cloned DNA sequences are distributed along the long arm of chromosome 21, while the other 2 hybridize with sequences on the short arm of both chromosome 21 and other chromosomes. This new collection of probes homologous to chromosome 21 should facilitate molecular analyses of trisomy 21 by providing DNA probes for the linkage map of chromosome 21, for studies of nondisjunction, for chromosome walking in clinically relevant subregions of chromosome 21, and for the isolation of genes on chromosome 21 following the screening of cDNA libraries.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47623/1/439_2004_Article_BF00366237.pd