Domination number of a bipartite semigraph when it is a cycle

Semigraph is a generalization of graph, with two or more vertices on edges which allows multiplicity in every concept of graph when it comes to semigraph. When number of vertices on the edges are restricted to two the semigraph is a graph, so every graph is a semigraph. In this article we deal with the variety of bipartite semigraphs, namely bipartite, s-bipartite and e-bipartite and bounds for their domination number (adjacent domination number and end vertex adjacent domination number) in particular when the semigraph is a cycle and also about possible size of the bipartite sets when the bipartite semigraph is a cycle.Publisher's Versio

Proactive cloud service assurance framework for fault remediation in cloud environment

Cloud resiliency is an important issue in successful implementation of cloud computing systems. Handling cloud faults proactively, with a suitable remediation technique having minimum cost is an important requirement for a fault management system. The selection of best applicable remediation technique is a decision making problem and considers parameters such as i) Impact of remediation technique ii) Overhead of remediation technique ii) Severity of fault and iv) Priority of the application. This manuscript proposes an analytical model to measure the effectiveness of a remediation technique for various categories of faults, further it demonstrates the implementation of an efficient fault remediation system using a rule-based expert system. The expert system is designed to compute an utility value for each remediation technique in a novel way and select the best remediation technique from its knowledgebase. A prototype is developed for experimentation purpose and the results shows improved availability with less overhead as compared to a reactive fault management system

Prospective study of radiological and functional outcomes of humeral mid-shaft fractures by anterior bridge plating technique

Background: The humerus can be considered the most versatile bone in the human body. Can be successfully approached by a variety of methods for fracture fixation including functional bracing, plating (posterior, lateral, and anterior), and intramedullary nailing (antegrade and retrograde). Notably, many humeral fractures can be successfully managed conservatively due to the wide range of acceptability for reduction. Anterior bridge plating (ABP) which utilizes the minimally invasive approach popularly known as the minimally invasive percutaneous plate osteosynthesis (MIPPO) technique can be said to be the latest entrant in this list. The present study was undertaken to evaluate the efficacy of ABP. Methods: The study was carried out from July 2020 to July 2022 in DR. D. Y. Patil medical college and hospital, Nerul, Navi Mumbai, involving 32 patients who met the selection criteria and were operated at the tertiary care centre. Informed consent was obtained from all the patients for use of their clinical and imaging data. Ethical committee approval was taken. The assessment of the patients was done based on functional and radiological outcomes periodically. Results: Majority of patients belongs to age group 18-25 years (46.87%). Majority of side of injury were found right side (65.62%). In most of the cases, the extent of the displacement of fractures were 2-5 cm (71.87). Conclusions: In conclusion ABP is a very good technique in treating mid-shaft humeral fractures with minimal soft tissue dissection, smaller scars, and early return to overhead activities

Leak and Burst Detection in Water Distribution Network Using Logic- and Machine Learning-Based Approaches

Urban water systems worldwide are confronted with the dual challenges of dwindling water resources and deteriorating infrastructure, emphasising the critical need to minimise water losses from leakage. Conventional methods for leak and burst detection often prove inadequate, leading to prolonged leak durations and heightened maintenance costs. This study investigates the efficacy of logic- and machine learning-based approaches in early leak detection and precise location identification within water distribution networks. By integrating hardware and software technologies, including sensor technology, data analysis, and study on the logic-based and machine learning algorithms, innovative solutions are proposed to optimise water distribution efficiency and minimise losses. In this research, we focus on a case study area in the Sunbury region of Victoria, Australia, evaluating a pumping main equipped with Supervisory Control and Data Acquisition (SCADA) sensor technology. We extract hydraulic characteristics from SCADA data and develop logic-based algorithms for leak and burst detection, alongside state-of-the-art machine learning techniques. These methodologies are applied to historical data initially and will be subsequently extended to live data, enabling the real-time detection of leaks and bursts. The findings underscore the complementary nature of logic-based and machine learning approaches. While logic-based algorithms excel in capturing straightforward anomalies based on predefined conditions, they may struggle with complex or evolving patterns. Machine learning algorithms enhance detection by learning from historical data, adapting to changing conditions, and capturing intricate patterns and outliers. The comparative analysis of machine learning models highlights the superiority of the local outlier factor (LOF) in anomaly detection, leading to its selection as the final model. Furthermore, a web-based platform has been developed for leak and burst detection using a selected machine learning model. The success of machine learning models over traditional logic-based approaches underscores the effectiveness of data-driven, probabilistic methods in handling complex data patterns and variations. Leveraging statistical and probabilistic techniques, machine learning models offer adaptability and superior performance in scenarios with intricate or dynamic relationships between variables. The findings demonstrate that the proposed methodology can significantly enhance the early detection of leaks and bursts, thereby minimising water loss and associated economic costs. The implications of this study are profound for the scientific community and stakeholders, as it provides a scalable and efficient solution for water pipeline monitoring. Implementing this approach can lead to more proactive maintenance strategies, ultimately contributing to the sustainability and resilience of urban water infrastructure systems

Role of CYP1B1, MYOC, OPTN and OPTC genes in adult-onset primary open-angle glaucoma: predominance of CYP1B1 mutations in Indian patients

Mutations in the CYP1B1, MYOC, OPTN, and WDR36 genes result in glaucoma. Given its expression in the optic nerve, it is likely a mutation in the OPTC gene is also involved in initiating glaucoma. This study was designed to evaluate the involvement of the CYP1B1, MYOC, OPTN, and OPTC genes in the etiology of adult-onset primary open-angle glaucoma (POAG) found in 251 Indian patients

Using comparative genomics to reorder the human genome sequence into a virtual sheep genome

Using BAC-end sequences, a sparse marker map and the sequences of the human, dog and cow genomes, an accurate and detailed sub-gene level map of the sheep genome has been constructed

Genome sequence of the necrotrophic plant pathogen Pythium ultimum reveals original pathogenicity mechanisms and effector repertoire

Background: Pythium ultimum (P. ultimum) is a ubiquitous oomycete plant pathogen responsible for a variety of diseases on a broad range of crop and ornamental species. Results: The P. ultimum genome (42.8 Mb) encodes 15,290 genes and has extensive sequence similarity and synteny with related Phytophthora species, including the potato blight pathogen Phytophthora infestans. Whole transcriptome sequencing revealed expression of 86% of genes, with detectable differential expression of suites of genes under abiotic stress and in the presence of a host. The predicted proteome includes a large repertoire of proteins involved in plant pathogen interactions although surprisingly, the P. ultimum genome does not encode any classical RXLR effectors and relatively few Crinkler genes in comparison to related phytopathogenic oomycetes. A lower number of enzymes involved in carbohydrate metabolism were present compared to Phytophthora species, with the notable absence of cutinases, suggesting a significant difference in virulence mechanisms between P. ultimum and more host specific oomycete species. Although we observed a high degree of orthology with Phytophthora genomes, there were novel features of the P. ultimum proteome including an expansion of genes involved in proteolysis and genes unique to Pythium. We identified a small gene family of cadherins, proteins involved in cell adhesion, the first report in a genome outside the metazoans. Conclusions: Access to the P. ultimum genome has revealed not only core pathogenic mechanisms within the oomycetes but also lineage specific genes associated with the alternative virulence and lifestyles found within the pythiaceous lineages compared to the Peronosporaceae

Tumor Biology and Immune Infiltration Define Primary Liver Cancer Subsets Linked to Overall Survival After Immunotherapy

Primary liver cancer is a rising cause of cancer deaths in the US. Although immunotherapy with immune checkpoint inhibitors induces a potent response in a subset of patients, response rates vary among individuals. Predicting which patients will respond to immune checkpoint inhibitors is of great interest in the field. In a retrospective arm of the National Cancer Institute Cancers of the Liver: Accelerating Research of Immunotherapy by a Transdisciplinary Network (NCI-CLARITY) study, we use archived formalin-fixed, paraffin-embedded samples to profile the transcriptome and genomic alterations among 86 hepatocellular carcinoma and cholangiocarcinoma patients prior to and following immune checkpoint inhibitor treatment. Using supervised and unsupervised approaches, we identify stable molecular subtypes linked to overall survival and distinguished by two axes of aggressive tumor biology and microenvironmental features. Moreover, molecular responses to immune checkpoint inhibitor treatment differ between subtypes. Thus, patients with heterogeneous liver cancer may be stratified by molecular status indicative of treatment response to immune checkpoint inhibitors

Genetics and Pathogenesis of Diffuse Large B-Cell Lymphoma.

BACKGROUND: Diffuse large B-cell lymphomas (DLBCLs) are phenotypically and genetically heterogeneous. Gene-expression profiling has identified subgroups of DLBCL (activated B-cell-like [ABC], germinal-center B-cell-like [GCB], and unclassified) according to cell of origin that are associated with a differential response to chemotherapy and targeted agents. We sought to extend these findings by identifying genetic subtypes of DLBCL based on shared genomic abnormalities and to uncover therapeutic vulnerabilities based on tumor genetics. METHODS: We studied 574 DLBCL biopsy samples using exome and transcriptome sequencing, array-based DNA copy-number analysis, and targeted amplicon resequencing of 372 genes to identify genes with recurrent aberrations. We developed and implemented an algorithm to discover genetic subtypes based on the co-occurrence of genetic alterations. RESULTS: We identified four prominent genetic subtypes in DLBCL, termed MCD (based on the co-occurrence of MYD88L265P and CD79B mutations), BN2 (based on BCL6 fusions and NOTCH2 mutations), N1 (based on NOTCH1 mutations), and EZB (based on EZH2 mutations and BCL2 translocations). Genetic aberrations in multiple genes distinguished each genetic subtype from other DLBCLs. These subtypes differed phenotypically, as judged by differences in gene-expression signatures and responses to immunochemotherapy, with favorable survival in the BN2 and EZB subtypes and inferior outcomes in the MCD and N1 subtypes. Analysis of genetic pathways suggested that MCD and BN2 DLBCLs rely on "chronic active" B-cell receptor signaling that is amenable to therapeutic inhibition. CONCLUSIONS: We uncovered genetic subtypes of DLBCL with distinct genotypic, epigenetic, and clinical characteristics, providing a potential nosology for precision-medicine strategies in DLBCL. (Funded by the Intramural Research Program of the National Institutes of Health and others.).This research was supported by the Intramural Research Program of the NIH, Center for Cancer Research, National Cancer Institute and by a National Cancer Institute Strategic Partnering to Evaluate Cancer Signatures (SPECS II) grant (5U01CA157581-05). R.S. was supported by the Dr Mildred Scheel Stiftung für Krebsforschung (Deutsche Krebshilfe). D.J.H. was a Kay Kendall Leukaemia Fund Intermediate research fellow. M.K. was supported by the National Institutes of Health Oxford-Cambridge Scholars Program and the Washington University in St. Louis Medical Scientist Training Progra