Minimization of power loss in newfangled cascaded H-bridge multilevel inverter using in-phase disposition PWM and wavelet transform based fault diagnosis

AbstractNowadays multilevel inverters (MLIs) have been preferred over conventional two-level inverters due to reduced harmonic distortions, lower electromagnetic interference, and higher DC link voltages. However, the increased number of components, complex PWM control, voltage-balancing problem, and component failure in the circuit are some of the disadvantages. The topology suggested in this paper provides a DC voltage in the shape of a staircase that approximates the rectified shape of a commanded sinusoidal wave to the bridge inverter, which in turn alternates the polarity to produce an AC voltage with low total harmonic distortion and power loss. This topology requires fewer components and hence it leads to the reduction of overall cost and complexity particularly for higher output voltage levels. The component fault diagnostic algorithm is developed using wavelets transform tool. Finally an experimental prototype is developed and validated with the simulation results

Towards comprehensive annotation of Drosophila melanogaster enzymes in FlyBase.

The catalytic activities of enzymes can be described using Gene Ontology (GO) terms and Enzyme Commission (EC) numbers. These annotations are available from numerous biological databases and are routinely accessed by researchers and bioinformaticians to direct their work. However, enzyme data may not be congruent between different resources, while the origin, quality and genomic coverage of these data within any one resource are often unclear. GO/EC annotations are assigned either manually by expert curators or inferred computationally, and there is potential for errors in both types of annotation. If such errors remain unchecked, false positive annotations may be propagated across multiple resources, significantly degrading the quality and usefulness of these data. Similarly, the absence of annotations (false negatives) from any one resource can lead to incorrect inferences or conclusions. We are systematically reviewing and enhancing the functional annotation of the enzymes of Drosophila melanogaster, focusing on improvements within the FlyBase (www.flybase.org) database. We have reviewed four major enzyme groups to date: oxidoreductases, lyases, isomerases and ligases. Herein, we describe our review workflow, the improvement in the quality and coverage of enzyme annotations within FlyBase and the wider impact of our work on other related databases

Mould incidence and mycotoxin contamination in freshly harvested maize kernels originated from India

BACKGROUND: In this study, mould incidence and mycotoxin contamination were determined in freshly harvested maize samples collected from different agroclimatic regions of India. A total of 150 freshly harvested maize samples from major maize-growing areas of India (Karnataka, Andhra Pradesh and Tamilnadu) were collected during winter seasons 2010-2011 and 2011-2012 to determine their toxigenic fungal incidences, and mycotoxins were analyzed and quantified by high-perfomance liquid chromatography. A total of 288 fungal isolates comprising Fusarium, Aspergillus and Penicillium species were tested for aflatoxin B1 (AFB1), ochratoxin A (OTA), trichothecenes (deoxynivalenol (DON) and T-2 toxin) and fumonisin B1 (FB1). Chemotype determination of fungal isolates was carried out by molecular and chemical analysis through polymerase chain reaction (PCR) and high-performance thin layer chromatography respectively. The diversity and distribution of the mycoflora among the studied samples were recorded in terms of frequency, density, importance value index and diversity indices. RESULTS: A total of 288 fungal isolates were recovered from the 150 maize samples, of which 28 were positive for AFB1, 20 for OTA, 58 for FB1, 23 for DON and 11 for T-2 toxin chemotypes by PCR. Species-specific PCR assays were in line with morphological analysis. Toxigenic fungal incidences were found throughout the study region, and most of the toxins under study exceeded the maximum legal limits. The range of observed toxin concentrations were 48-58 &micro;g AFB1, 76-123 &micro;g FB1, 38-50 &micro;g T-2, 72-94 &micro;g DON and &lt;5 &micro;g OTA kg(-1) grain sample. CONCLUSION: Owing to the high incidences of toxigenic moulds and mycotoxins in the study area, there is a need for the creation of mycotoxin awareness among maize farmers of India to control the chronic adverse health effects on humans and livestock due to mycotoxins.</p

Enhancing Knee Osteoarthritis severity level classification using diffusion augmented images

This research paper explores the classification of knee osteoarthritis (OA) severity levels using advanced computer vision models and augmentation techniques. The study investigates the effectiveness of data preprocessing, including Contrast-Limited Adaptive Histogram Equalization (CLAHE), and data augmentation using diffusion models. Three experiments were conducted: training models on the original dataset, training models on the preprocessed dataset, and training models on the augmented dataset. The results show that data preprocessing and augmentation significantly improve the accuracy of the models. The EfficientNetB3 model achieved the highest accuracy of 84\% on the augmented dataset. Additionally, attention visualization techniques, such as Grad-CAM, are utilized to provide detailed attention maps, enhancing the understanding and trustworthiness of the models. These findings highlight the potential of combining advanced models with augmented data and attention visualization for accurate knee OA severity classification.Comment: Paper has been accepted to be presented at ICACECS 2023 and the final version will be published by Atlantis Highlights in Computer Science (AHCS) , Atlantis Press(part of Springer Nature

The Reactome pathway Knowledgebase

The Reactome Knowledgebase (www.reactome.org) provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations-an extended version of a classic metabolic map, in a single consistent data model. Reactome functions both as an archive of biological processes and as a tool for discovering unexpected functional relationships in data such as gene expression pattern surveys or somatic mutation catalogues from tumour cells. Over the last two years we redeveloped major components of the Reactome web interface to improve usability, responsiveness and data visualization. A new pathway diagram viewer provides a faster, clearer interface and smooth zooming from the entire reaction network to the details of individual reactions. Tool performance for analysis of user datasets has been substantially improved, now generating detailed results for genome-wide expression datasets within seconds. The analysis module can now be accessed through a RESTFul interface, facilitating its inclusion in third party applications. A new overview module allows the visualization of analysis results on a genome-wide Reactome pathway hierarchy using a single screen page. The search interface now provides auto-completion as well as a faceted search to narrow result lists efficiently

The Reactome pathway knowledgebase

Reactome (http://www.reactome.org) is a manually curated open-source open-data resource of human pathways and reactions. The current version 46 describes 7088 human proteins (34% of the predicted human proteome), participating in 6744 reactions based on data extracted from 15 107 research publications with PubMed links. The Reactome Web site and analysis tool set have been completely redesigned to increase speed, flexibility and user friendliness. The data model has been extended to support annotation of disease processes due to infectious agents and to mutation

Reactome: a database of reactions, pathways and biological processes

Reactome (http://www.reactome.org) is a collaboration among groups at the Ontario Institute for Cancer Research, Cold Spring Harbor Laboratory, New York University School of Medicine and The European Bioinformatics Institute, to develop an open source curated bioinformatics database of human pathways and reactions. Recently, we developed a new web site with improved tools for pathway browsing and data analysis. The Pathway Browser is an Systems Biology Graphical Notation (SBGN)-based visualization system that supports zooming, scrolling and event highlighting. It exploits PSIQUIC web services to overlay our curated pathways with molecular interaction data from the Reactome Functional Interaction Network and external interaction databases such as IntAct, BioGRID, ChEMBL, iRefIndex, MINT and STRING. Our Pathway and Expression Analysis tools enable ID mapping, pathway assignment and overrepresentation analysis of user-supplied data sets. To support pathway annotation and analysis in other species, we continue to make orthology-based inferences of pathways in non-human species, applying Ensembl Compara to identify orthologs of curated human proteins in each of 20 other species. The resulting inferred pathway sets can be browsed and analyzed with our Species Comparison tool. Collaborations are also underway to create manually curated data sets on the Reactome framework for chicken, Drosophila and rice

The Gene Ontology resource: enriching a GOld mine

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations

Minimization of power loss in newfangled cascaded H-bridge multilevel inverter using in-phase disposition PWM and wavelet transform based fault diagnosis

Nowadays multilevel inverters (MLIs) have been preferred over conventional two-level inverters due to reduced harmonic distortions, lower electromagnetic interference, and higher DC link voltages. However, the increased number of components, complex PWM control, voltage-balancing problem, and component failure in the circuit are some of the disadvantages. The topology suggested in this paper provides a DC voltage in the shape of a staircase that approximates the rectified shape of a commanded sinusoidal wave to the bridge inverter, which in turn alternates the polarity to produce an AC voltage with low total harmonic distortion and power loss. This topology requires fewer components and hence it leads to the reduction of overall cost and complexity particularly for higher output voltage levels. The component fault diagnostic algorithm is developed using wavelets transform tool. Finally an experimental prototype is developed and validated with the simulation results. Keywords: Field programmable gate array (FPGA), In-phase disposition (IPD) PWM, Least number of switching devices, Multi level inverter, Total harmonic distortion, Wavelet transform too