The Solar and Lunar Variations in Barometric Pressure at Glasgow and Ben Nevis

Abstract Not Provided

The identification of a novel, high frequency variant in the Cytochrome b gene in an isolated population of a rare fish, Spined Loach Cobitis taenia, in England: A population worth protecting?

The spined loach Cobitis taenia, is listed as a protected species under Appendix 3 of the Bern Convention and Annex II of the European Council Directive (92/43/EEC) on the conservation of natural habitats and of wild fauna and flora. It is desirable therefore to understand the genetic diversity within European populations. In a molecular genetic analysis of the cytochrome b gene in Cobitis taenia from three sites in the upper reaches of the River Trent catchment, a novel high frequency variant was identified which has not been previously reported in any European or Non-European population

Multi-Objective Big Data Optimization with jMetal and Spark

Big Data Optimization is the term used to refer to optimization problems which have to manage very large amounts of data. In this paper, we focus on the parallelization of metaheuristics with the Apache Spark cluster computing system for solving multi-objective Big Data Optimization problems. Our purpose is to study the influence of accessing data stored in the Hadoop File System (HDFS) in each evaluation step of a metaheuristic and to provide a software tool to solve these kinds of problems. This tool combines the jMetal multi-objective optimization framework with Apache Spark. We have carried out experiments to measure the performance of the proposed parallel infrastructure in an environment based on virtual machines in a local cluster comprising up to 100 cores. We obtained interesting results for computational e ort and propose guidelines to face multi-objective Big Data Optimization problems.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Petascale Simulation Initiative Tech Base: FY2007 Final Report

The Petascale Simulation Initiative began as an LDRD project in the middle of Fiscal Year 2004. The goal of the project was to develop techniques to allow large-scale scientific simulation applications to better exploit the massive parallelism that will come with computers running at petaflops per second. One of the major products of this work was the design and prototype implementation of a programming model and a runtime system that lets applications extend data-parallel applications to use task parallelism. By adopting task parallelism, applications can use processing resources more flexibly, exploit multiple forms of parallelism, and support more sophisticated multiscale and multiphysics models. Our programming model was originally called the Symponents Architecture but is now known as Cooperative Parallelism, and the runtime software that supports it is called Coop. (However, we sometimes refer to the programming model as Coop for brevity.) We have documented the programming model and runtime system in a submitted conference paper [1]. This report focuses on the specific accomplishments of the Cooperative Parallelism project (as we now call it) under Tech Base funding in FY2007. Development and implementation of the model under LDRD funding alone proceeded to the point of demonstrating a large-scale materials modeling application using Coop on more than 1300 processors by the end of FY2006. Beginning in FY2007, the project received funding from both LDRD and the Computation Directorate Tech Base program. Later in the year, after the three-year term of the LDRD funding ended, the ASC program supported the project with additional funds. The goal of the Tech Base effort was to bring Coop from a prototype to a production-ready system that a variety of LLNL users could work with. Specifically, the major tasks that we planned for the project were: (1) Port SARS [former name of the Coop runtime system] to another LLNL platform, probably Thunder or Peloton (depending on when Peloton becomes available); (2) Improve SARS's robustness and ease-of-use, and develop user documentation; and (3) Work with LLNL code teams to help them determine how Symponents could benefit their applications. The original funding request was $296,000 for the year, and we eventually received$252,000. The remainder of this report describes our efforts and accomplishments for each of the goals listed above

Service Oriented Big Data Management for Transport

International audienceThe increasing power of computer hardware and the sophistication of computer software have brought many new possibilities to information world. On one side the possibility to analyse massive data sets has brought new insight, knowledge and information. On the other, it has enabled to massively distribute computing and has opened to a new programming paradigm called Service Oriented Computing particularly well adapted to cloud computing. Applying these new technologies to the transport industry can bring new understanding to town transport infrastructures. The objective of our work is to manage and aggregate cloud services for managing big data and assist decision making for transport systems. Thus this paper presents our approach to propose a service oriented architecture for big data analytics for transport systems based on the cloud. Proposing big data management strategies for data produced by transport infra‐ structures, whilst maintaining cost effective systems deployed on the cloud, is a promising approach. We present the advancement for developing the Data acquisition service and Information extraction and cleaning service as well as the analysis for choosing a sharding strategy

Failure analysis of parameter-induced simulation crashes in climate models

Simulations using IPCC (Intergovernmental Panel on Climate Change)-class climate models are subject to fail or crash for a variety of reasons. Quantitative analysis of the failures can yield useful insights to better understand and improve the models. During the course of uncertainty quantification (UQ) ensemble simulations to assess the effects of ocean model parameter uncertainties on climate simulations, we experienced a series of simulation crashes within the Parallel Ocean Program (POP2) component of the Community Climate System Model (CCSM4). About 8.5% of our CCSM4 simulations failed for numerical reasons at combinations of POP2 parameter values. We applied support vector machine (SVM) classification from machine learning to quantify and predict the probability of failure as a function of the values of 18 POP2 parameters. A committee of SVM classifiers readily predicted model failures in an independent validation ensemble, as assessed by the area under the receiver operating characteristic (ROC) curve metric (AUC > 0.96). The causes of the simulation failures were determined through a global sensitivity analysis. Combinations of 8 parameters related to ocean mixing and viscosity from three different POP2 parameterizations were the major sources of the failures. This information can be used to improve POP2 and CCSM4 by incorporating correlations across the relevant parameters. Our method can also be used to quantify, predict, and understand simulation crashes in other complex geoscientific models

Androgen receptor phosphorylation at serine 515 by Cdk1 predicts biochemical relapse in prostate cancer patients

<br>Background:Prostate cancer cell growth is dependent upon androgen receptor (AR) activation, which is regulated by specific kinases. The aim of the current study is to establish if AR phosphorylation by Cdk1 or ERK1/2 is of prognostic significance.</br> <br>Methods: Scansite 2.0 was utilised to predict which AR sites are phosphorylated by Cdk1 and ERK1/2. Immunohistochemistry for these sites was then performed on 90 hormone-naive prostate cancer specimens. The interaction between Cdk1/ERK1/2 and AR phosphorylation was investigated in vitro using LNCaP cells.</br><br>Results:Phosphorylation of AR at serine 515 (pAR(S515)) and PSA at diagnosis were independently associated with decreased time to biochemical relapse. Cdk1 and pCdk1(161), but not ERK1/2, correlated with pAR(S515). High expression of pAR(S515) in patients with a PSA at diagnosis of ≤20 ng ml(-1) was associated with shorter time to biochemical relapse (P=0.019). This translated into a reduction in disease-specific survival (10-year survival, 38.1% vs 100%, P<0.001). In vitro studies demonstrated that treatment with Roscovitine (a Cdk inhibitor) caused a reduction in pCdk1(161) expression, pAR(S515)expression and cellular proliferation.</br> <br>Conclusion: In prostate cancer patients with PSA at diagnosis of ≤20 ng ml(-1), phosphorylation of AR at serine 515 by Cdk1 may be an independent prognostic marker.</br&gt

TIGIT can inhibit T cell activation via ligation-induced nanoclusters, independent of CD226 co-stimulation

TIGIT is an inhibitory receptor expressed on lymphocytes and can inhibit T cells by preventing CD226 co-stimulation through interactions in cis or through competition of shared ligands. Whether TIGIT directly delivers cell-intrinsic inhibitory signals in T cells remains unclear. Here we show, by analysing lymphocytes from matched human tumour and peripheral blood samples, that TIGIT and CD226 co-expression is rare on tumour-infiltrating lymphocytes. Using super-resolution microscopy and other techniques, we demonstrate that ligation with CD155 causes TIGIT to reorganise into dense nanoclusters, which coalesce with T cell receptor (TCR)-rich clusters at immune synapses. Functionally, this reduces cytokine secretion in a manner dependent on TIGIT’s intracellular ITT-like signalling motif. Thus, we provide evidence that TIGIT directly inhibits lymphocyte activation, acting independently of CD226, requiring intracellular signalling that is proximal to the TCR. Within the subset of tumours where TIGIT-expressing cells do not commonly co-express CD226, this will likely be the dominant mechanism of action

Using a realist approach to evaluate smoking cessation interventions targeting pregnant women and young people

Background This paper describes a study protocol designed to evaluate a programme of smoking cessation interventions targeting pregnant women and young people living in urban and rural locations in Northeast Scotland. The study design was developed on so-called 'realist' evaluation principles, which are concerned with the implementation of interventions as well as their outcomes. Methods/design A two-phased study was designed based on the Theory of Change (TOC) using mixed methods to assess both process and outcome factors. The study was designed with input from the relevant stakeholders. The mixed-methods approach consists of semi-structured interviews with planners, service providers, service users and non-users. These qualitative interviews will be analysed using a thematic framework approach. The quantitative element of the study will include the analysis of routinely collected data and specific project monitoring data, such as data on service engagement, service use, quit rates and changes in smoking status. Discussion The process of involving key stakeholders was conducted using logic modelling and TOC tools. Engaging stakeholders, including those responsible for funding, developing and delivering, and those intended to benefit from interventions aimed at them, in their evaluation design, are considered by many to increase the validity and rigour of the subsequent evidence generated. This study is intended to determine not only the components and processes, but also the possible effectiveness of this set of health interventions, and contribute to the evidence base about smoking cessation interventions aimed at priority groups in Scotland. It is also anticipated that this study will contribute to the ongoing debate about the role and challenges of 'realist' evaluation approaches in general, and the utility of logic modelling and TOC approaches in particular, for evaluation of complex health interventions

Experiences Marketing: A Cultural Philosophy for Contemporary Hospitality Marketing Studies

This article explores the landscape of contemporary hospitality marketing. It is argued that the teaching and academic discussions that surround the subject area adopt a predominantly positivistic approach; although important, that does not adequately reflect the nature of the industry or the products offered. Such a metrics-oriented position, although significant in the formulation of marketing strategy, does not reflect the complex experiential, nontangible nature of the hospitality product. This article presents a culturally located philosophy that reflects the multifaceted nature of the industry. The philosophy is underpinned by three precepts that draw from a multidisciplinary theoretical framework to create a more subject-specific approach to marketing, that when woven with traditional approaches can create a more effective and informed contemporary approach