Failure Prediction using Machine Learning in a Virtualised HPC System and application

YesFailure is an increasingly important issue in high performance computing and cloud systems. As large-scale systems continue to grow in scale and complexity, mitigating the impact of failure and providing accurate predictions with sufficient lead time remains a challenging research problem. Traditional existing fault-tolerance strategies such as regular check-pointing and replication are not adequate because of the emerging complexities of high performance computing systems. This necessitates the importance of having an effective as well as proactive failure management approach in place aimed at minimizing the effect of failure within the system. With the advent of machine learning techniques, the ability to learn from past information to predict future pattern of behaviours makes it possible to predict potential system failure more accurately. Thus, in this paper, we explore the predictive abilities of machine learning by applying a number of algorithms to improve the accuracy of failure prediction. We have developed a failure prediction model using time series and machine learning, and performed comparison based tests on the prediction accuracy. The primary algorithms we considered are the Support Vector Machine (SVM), Random Forest(RF), k-Nearest Neighbors (KNN), Classi cation and Regression Trees (CART) and Linear Discriminant Analysis (LDA). Experimental results indicates that the average prediction accuracy of our model using SVM when predicting failure is 90% accurate and effective compared to other algorithms. This f inding implies that our method can effectively predict all possible future system and application failures within the system.Petroleum Technology Development Fund (PTDF) funding support under the OSS scheme with grant number (PTDF/E/OSS/PHD/MB/651/14

Incidental finding of autosomal dominant polycystic kidney disease in a 52-year-old man: a case report.

Autosomal dominant polycystic kidney disease (ADPKD) also known as Adult Polycystic Kidney Disease (APKD) is one of the most common systemic hereditary diseases. The disease usually presents between 20 to 39 years of age, although milder forms may not present until over 60 years and absence of renal failure has been rarely observed in some patients up to 80 years of age. Three distinct gene defects have been implicated in the pathogenesis of APKD designated as PKD1, PKD2, and PKD3. Patients with APKD may be asymptomatic, or may usually present with hypertension (in 50-70% of cases), renal insufficiency, and the complications of multiple cysts (haematuria, pain and infection) or as an abdominal mass discovered on incidental clinical or imaging examination. APKD is said to be rare in Africans. Case report: We report a case of an incidental finding of autosomal dominant polycystic kidney disease (ADPKD) in a 52-year-old normotensive man with a normal renal function test. Haematuria, dysuria and low-grade fever were the presenting complaints. The role of radiology in the diagnosis and management of ADPKD was highlighted. Conclusion: Although APKD is rare in Africans, a high index of suspicion for the disease is essential for the diagnosis of the disease especially in elderly patients with a family history of APKD who present with haematuria associated with multiple renal cysts

Failure Analysis Modelling in an Infrastructure as a Service (Iaas) Environment

yesFailure Prediction has long known to be a challenging problem. With the evolving trend of technology and growing complexity of high-performance cloud data centre infrastructure, focusing on failure becomes very vital particularly when designing systems for the next generation. The traditional runtime fault-tolerance (FT) techniques such as data replication and periodic check-pointing are not very effective to handle the current state of the art emerging computing systems. This has necessitated the urgent need for a robust system with an in-depth understanding of system and component failures as well as the ability to predict accurate potential future system failures. In this paper, we studied data in-production-faults recorded within a five years period from the National Energy Research Scientific computing centre (NERSC). Using the data collected from the Computer Failure Data Repository (CFDR), we developed an effective failure prediction model focusing on high-performance cloud data centre infrastructure. Using the Auto-Regressive Moving Average (ARMA), our model was able to predict potential future failures in the system. Our results also show a failure prediction accuracy of 95%, which is good

Activation of coagulation and endothelium with concurrent impairment of anticoagulant mechanisms in patients with typhoid fever.

OBJECTIVES: Typhoid fever caused by Salmonella Typhi remains a major burden worldwide. Gastrointestinal bleeding can be seen in up to 10 percent of patients and may be fatal. The coagulopathy, which may be the driver of this severe complication in patients with typhoid fever, however is ill defined. The aim of this study was to evaluate the activation of coagulation, anticoagulation, and fibrinolysis in patients with acute typhoid fever. METHODS: Parameters of coagulation and fibrinolysis were measured in 28 hospitalized patients with culture-confirmed or PCR-confirmed typhoid fever and compared to 38 age- and sex-matched healthy volunteers. RESULTS: Patients demonstrated activation of the coagulation system, as reflected by elevated in vitro thrombin generation and high plasma levels of fibrinogen, D-dimer and prothrombin fragment F1 + 2 in concert with consumption of coagulation factors resulting in a prolonged prothrombin-time and activated-partial-thromboplastin-time. Concurrently, the anticoagulant proteins, protein C and antithrombin, were significantly lower in comparison to healthy controls. Patients also demonstrated evidence of activation and inhibition of fibrinolysis and a marked activation of endothelial cells. The extent of coagulation activation was associated with the course of the disease, repeated testing during convalescence showed a return toward normal values. CONCLUSIONS: Activation of coagulation is an important clinical feature of typhoid fever and is associated with severity of disease

Advances in nanomaterial-based immunosensors for prostate cancer screening

Prostate cancer is one of the most common health hazards for men worldwide, specifically in Western countries. Rapid prostate cancer screening by analyzing the prostate-specific antigen present in male serum has brought about a sharp decline in the mortality index of this disease. Immunoassay technology quantifies the target analyte in the sample using the antigen-antibody reaction. Immunoassays are now pivotal in disease diagnostics, drug monitoring, and pharmacokinetics. Recently, immunosensors have gained momentum in delivering better results with high specificity and lower limit of detection (LOD). Nanomaterials like gold, silver, and copper exhibit numerous exceptional features and their use in developing immunosensors have garnered excellent results in the diagnostic field. This review highlights the recent and different immunoassay techniques used to detect prostate-specific antigens and discusses the advances in nanomaterial-based immunosensors to detect prostate cancer efficiently. The review also explores the importance of specific biomarkers and nanomaterials-based biosensors with good selectivity and sensitivity to prostate cancer

Quality control and beam test of GEM detectors for future upgrades of the CMS muon high rate region at the LHC

Gas Electron Multipliers (GEM) are a proven position sensitive gas detector technology which nowadays is becoming more widely used in High Energy Physics. GEMs offer an excellent spatial resolution and a high particle rate capability, with a close to 100% detection efficiency. In view of the high luminosity phase of the CERN Large Hadron Collider, these aforementioned features make GEMs suitable candidates for the future upgrades of the Compact Muon Solenoid (CMS) detector. In particular, the CMS GEM Collaboration proposes to cover the high-eta region of the muon system with large-area triple-GEM detectors, which have the ability to provide robust and redundant tracking and triggering functions. In this contribution, after a general introduction and overview of the project, the construction of full-size trapezoidal triple-GEM prototypes will be described in more detail. The procedures for the quality control of the GEM foils, including gain uniformity measurements with an x-ray source will be presented. In the past few years, several CMS triple-GEM prototype detectors were operated with test beams at the CERN SPS. The results of these test beam campaigns will be summarised

ALCAM Regulates Motility, Invasiveness, and Adherens Junction Formation in Uveal Melanoma Cells

ALCAM, a member of the immunoglobulin superfamily, has been implicated in numerous developmental events and has been repeatedly identified as a marker for cancer metastasis. Previous studies addressing ALCAM’s role in cancer have, however, yielded conflicting results. Depending on the tumor cell type, ALCAM expression has been reported to be both positively and negatively correlated with cancer progression and metastasis in the literature. To better understand how ALCAM might regulate cancer cell behavior, we utilized a panel of defined uveal melanoma cell lines with high or low ALCAM levels, and directly tested the effects of manipulating these levels on cell motility, invasiveness, and adhesion using multiple assays. ALCAM expression was stably silenced by shRNA knockdown in a high-ALCAM cell line (MUM-2B); the resulting cells displayed reduced motility in gap-closure assays and a reduction in invasiveness as measured by a transwell migration assay. Immunostaining revealed that the silenced cells were defective in the formation of adherens junctions, at which ALCAM colocalizes with N-cadherin and ß-catenin in native cells. Additionally, we stably overexpressed ALCAM in a low-ALCAM cell line (MUM-2C); intriguingly, these cells did not exhibit any increase in motility or invasiveness, indicating that ALCAM is necessary but not sufficient to promote metastasis-associated cell behaviors. In these ALCAM-overexpressing cells, however, recruitment of ß-catenin and N-cadherin to adherens junctions was enhanced. These data confirm a previously suggested role for ALCAM in the regulation of adherens junctions, and also suggest a mechanism by which ALCAM might differentially enhance or decrease invasiveness, depending on the type of cadherin adhesion complexes present in tissues surrounding the primary tumor, and on the cadherin status of the tumor cells themselves

SPARC 2018 Internationalisation and collaboration : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2018 SPARC conference. This year we not only celebrate the work of our PGRs but also the launch of our Doctoral School, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 100 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to take up this great opportunity to engage with researchers working in different subject areas from your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Increasing access to integrated ESKD care as part of Universal Health Coverage

The global nephrology community recognizes the need for a cohesive strategy to address the growing problem of end-stage kidney disease (ESKD). In March 2018, the International Society of Nephrology hosted a summit on integrated ESKD care, including 92 individuals from around the globe with diverse expertise and professional backgrounds. The attendees were from 41 countries, including 16 participants from 11 low- and lower-middle–income countries. The purpose was to develop a strategic plan to improve worldwide access to integrated ESKD care, by identifying and prioritizing key activities across 8 themes: (i) estimates of ESKD burden and treatment coverage, (ii) advocacy, (iii) education and training/workforce, (iv) financing/funding models, (v) ethics, (vi) dialysis, (vii) transplantation, and (viii) conservative care. Action plans with prioritized lists of goals, activities, and key deliverables, and an overarching performance framework were developed for each theme. Examples of these key deliverables include improved data availability, integration of core registry measures and analysis to inform development of health care policy; a framework for advocacy; improved and continued stakeholder engagement; improved workforce training; equitable, efficient, and cost-effective funding models; greater understanding and greater application of ethical principles in practice and policy; definition and application of standards for safe and sustainable dialysis treatment and a set of measurable quality parameters; and integration of dialysis, transplantation, and comprehensive conservative care as ESKD treatment options within the context of overall health priorities. Intended users of the action plans include clinicians, patients and their families, scientists, industry partners, government decision makers, and advocacy organizations. Implementation of this integrated and comprehensive plan is intended to improve quality and access to care and thereby reduce serious health-related suffering of adults and children affected by ESKD worldwide