203 research outputs found

    Exhaust particle number of a non-road diesel engine fuelled by methyl esters with different fatty acid compositions

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    ArticleThe main aim of this study was to find out how methyl esters with different fatty acid compositions affect the exhaust particle numbers. Along with fossil diesel fuel oil (DFO) and renewable diesel (HVO), a high-speed non-road diesel engine was fuelled by rapeseed (RME) and soybean (SME) methyl esters. Particle numbers within the size range of 5.6–560 nm were measured by means of an engine exhaust particle sizer (EEPS). The exhaust smoke, gaseous emissions and the basic engine performance were also determined. During the measurements, the 4-cylinder, turbocharged, intercooled engine was run according to the non-road steady cycle. Methyl esters reduced particles within the size range of 70 to 200 nm. For RME and SME, both positive and significant correlations were found between the sum of the particle numbers detected above the size category of 23 nm and methyl palmitate (C16:0), methyl stearate (C18:0) and methyl linoleate (C18:2) contents at 10% load at rated speed. In terms of nitrogen oxide (NOx) and hydrocarbon (HC) emissions, HVO was beneficial while carbon monoxide (CO) emission was the lowest with DFO. The level in smoke emission was negligible

    Associations of cognitive reserve and psychological resilience with cognitive functioning in subjects with cerebral white matter hyperintensities

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    Background and purpose Cerebral small vessel disease is characterized by progressive white matter hyperintensities (WMH) and cognitive decline. However, variability exists in how individuals maintain cognitive capabilities despite significant neuropathology. The relationships between individual cognitive reserve, psychological resilience and cognitive functioning were examined in subjects with varying degrees of WMH. Methods In the Helsinki Small Vessel Disease Study, 152 subjects (aged 65-75 years) underwent a comprehensive neuropsychological assessment, evaluation of subjective cognitive complaints and brain magnetic resonance imaging with volumetric WMH evaluation. Cognitive reserve was determined by education (years) and the modified Cognitive Reserve Scale (mCRS). Psychological resilience was evaluated with the Resilience Scale 14. Results The mCRS total score correlated significantly with years of education (r = 0.23, p < 0.01), but it was not related to age, sex or WMH volume. Together, mCRS score and education were associated with performance in a wide range of cognitive domains including processing speed, executive functions, working memory, verbal memory, visuospatial perception and verbal reasoning. Independently of education, the mCRS score had incremental predictive value on delayed verbal recall and subjective cognitive complaints. Psychological resilience was not significantly related to age, education, sex, WMH severity or cognitive test scores, but it was associated with subjective cognitive complaints. Conclusions Cognitive reserve has strong and consistent associations with cognitive functioning in subjects with WMH. Education is widely associated with objective cognitive functioning, whereas lifetime engagement in cognitively stimulating leisure activities (mCRS) has independent predictive value on memory performance and subjective cognitive complaints. Psychological resilience is strongly associated with subjective, but not objective, cognitive functioning.Peer reviewe

    Anduril 2: Upgraded large-scale data integration framework

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    aSummary: Anduril is an analysis and integration framework that facilitates the design, use, parallelization and reproducibility of bioinformatics workflows. Anduril has been upgraded to use Scala for pipeline construction, which simplifies software maintenance, and facilitates design of complex pipelines. Additionally, Anduril's bioinformatics repository has been expanded with multiple components, and tutorial pipelines, for next-generation sequencing data analysis.Peer reviewe

    Comprehensive evaluation of coding region point mutations in microsatellite-unstable colorectal cancer

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    Microsatellite instability (MSI) leads to accumulation of an excessive number of mutations in the genome, mostly small insertions and deletions. MSI colorectal cancers (CRCs), however, also contain more point mutations than microsatellite-stable (MSS) tumors, yet they have not been as comprehensively studied. To identify candidate driver genes affected by point mutations in MSI CRC, we ranked genes based on mutation significance while correcting for replication timing and gene expression utilizing an algorithm, MutSigCV. Somatic point mutation data from the exome kit-targeted area from 24 exome-sequenced sporadic MSI CRCs and respective normals, and 12 whole-genome-sequenced sporadic MSI CRCs and respective normals were utilized. The top 73 genes were validated in 93 additional MSI CRCs. The MutSigCV ranking identified several well-established MSI CRC driver genes and provided additional evidence for previously proposed CRC candidate genes as well as shortlisted genes that have to our knowledge not been linked to CRC before. Two genes, SMARCB1 and STK38L, were also functionally scrutinized, providing evidence of a tumorigenic role, for SMARCB1 mutations in particular. © 2018 The Authors. Published under the terms of the CC BY 4.0 licensePeer reviewe

    Large-scale data integration framework provides a comprehensive view on glioblastoma multiforme

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    Background: Coordinated efforts to collect large-scale data sets provide a basis for systems level understanding of complex diseases. In order to translate these fragmented and heterogeneous data sets into knowledge and medical benefits, advanced computational methods for data analysis, integration and visualization are needed.Methods: We introduce a novel data integration framework, Anduril, for translating fragmented large-scale data into testable predictions. The Anduril framework allows rapid integration of heterogeneous data with state-of-the-art computational methods and existing knowledge in bio-databases. Anduril automatically generates thorough summary reports and a website that shows the most relevant features of each gene at a glance, allows sorting of data based on different parameters, and provides direct links to more detailed data on genes, transcripts or genomic regions. Anduril is open-source; all methods and documentation are freely available.Results: We have integrated multidimensional molecular and clinical data from 338 subjects having glioblastoma multiforme, one of the deadliest and most poorly understood cancers, using Anduril. The central objective of our approach is to identify genetic loci and genes that have significant survival effect. Our results suggest several novel genetic alterations linked to glioblastoma multiforme progression and, more specifically, reveal Moesin as a novel glioblastoma multiforme-associated gene that has a strong survival effect and whose depletion in vitro significantly inhibited cell proliferation. All analysis results are available as a comprehensive website.Conclusions: Our results demonstrate that integrated analysis and visualization of multidimensional and heterogeneous data by Anduril enables drawing conclusions on functional consequences of large-scale molecular data. Many of the identified genetic loci and genes having significant survival effect have not been reported earlier in the context of glioblastoma multiforme. Thus, in addition to generally applicable novel methodology, our results provide several glioblastoma multiforme candidate genes for further studies. Anduril is available at http://csbi.ltdk.helsinki.fi/anduril/ The glioblastoma multiforme analysis results are available at http://csbi.ltdk.helsinki.fi/anduril/tcga-gbm

    Towards a framework for work package allocation for GSD

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    Proceeding of: Proceeding of: OTM 2011 Workshops: Confederated International Workshops and Posters: EI2N+NSF ICE, ICSP+INBAST, ISDE, ORM, OTMA, SWWS+MONET+SeDeS, and VADER 2011, Hersonissos, Crete, Greece, October 17-21, 2011Global software development is an inexorable trend in the software industry. The impact of the trend in conventional software development can be found in many of its aspects. One of them is task or work package allocation. Task allocation was traditionally driven by resource competency and availability but GSD introduces new complexities to this process including time-zones differences, costs and cultural differences. In this work a report on the construction of a framework for work-package allocation within GSD projects is presented. This framework lies on three main pillars: individual and organizational competency, organizational customization and sound assessment methods.This work is supported by the Spanish Centro para el Desarrollo Tecnológico Industrial (CDTI) under the Eureka Project E! 6244 PROPS-Tour and the national cooperation project SEM-IDi (IDI-20091150)

    Overview : Integrative and Comprehensive Understanding on Polar Environments (iCUPE) - concept and initial results

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    The role of polar regions is increasing in terms of megatrends such as globalization, new transport routes, demography, and the use of natural resources with consequent effects on regional and transported pollutant concentrations. We set up the ERA-PLANET Strand 4 project "iCUPE - integrative and Comprehensive Understanding on Polar Environments" to provide novel insights and observational data on global grand challenges with an Arctic focus. We utilize an integrated approach combining in situ observations, satellite remote sensing Earth observations (EOs), and multi-scale modeling to synthesize data from comprehensive long-term measurements, intensive campaigns, and satellites to deliver data products, metrics, and indicators to stakeholders concerning the environmental status, availability, and extraction of natural resources in the polar areas. The iCUPE work consists of thematic state-of-the-art research and the provision of novel data in atmospheric pollution, local sources and transboundary transport, the characterization of arctic surfaces and their changes, an assessment of the concentrations and impacts of heavy metals and persistent organic pollutants and their cycling, the quantification of emissions from natural resource extraction, and the validation and optimization of satellite Earth observation (EO) data streams. In this paper we introduce the iCUPE project and summarize initial results arising out of the integration of comprehensive in situ observations, satellite remote sensing, and multi-scale modeling in the Arctic context.Peer reviewe
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