2,807 research outputs found
Defining a baseline complexity model for ERP systems over SaaS
Our research investigates applying the Software as a Service (SaaS) model for hosted applications to more complex business systems such as an Enterprise Resource Management System (ERP). This application of the service model is still in its infancy and we present some challenges to the technology. We will initially be defining a measure of complexity for business systems and applying this as a baseline to complex business systems within a pure SaaS model on the cloud, considering the elements making up SaaS and inter-relating these with this definition of business complexity. In this research we will be applying elements of Complex Systems Theory, Network Complexity Theory and Programmatic Complexity Models, in extending these for our own application to this service model within this complex business context
Effect of convective and freeze-drying processes on galega kale quality
info:eu-repo/semantics/publishedVersio
Ontological analysis for dynamic data model exploration
Increasing access to data and computational resources allows use to use more expressive approaches to data analysis. We propose using established statistical metrics to assist the automatic analysis of free text transcripts. The meaningful concepts from a domain and their axiomatic relationships can be captured in an ontology. This provides an aggregate model which describes the domain. However, the fine detail from individual elements and their characteristics are subsumed by the whole. Keeping multiple 'micro models' of the data, along with meta information allows a range of different view points. This can be applied to free text documents that within a domain where significant information is carried by one or a few instances such as in the analysis of interview transcripts. This paper presents a framework that utilises ontological tools to create domain models in a way that it allows for a distributed and parallel implementation necessary for big data analysis
Multisubband ensemble Monte Carlo analysis of tunneling leakage mechanisms in ultrascaled FDSOI, DGSOI, and FinFET devices
Leakage phenomena are increasingly affecting the performance of nanoelectronic devices, and therefore, advanced device simulators need to include them in an appropriate way. This paper presents the modeling and implementation of direct source-to-drain tunneling (S/D tunneling), gate leakage mechanisms (GLMs) accounting for both direct tunneling and trap-assisted tunneling, and nonlocal band-to-band tunneling (BTBT) phenomena in a multissubband ensemble Monte Carlo (MS-EMC) simulator along with their simultaneous application for the study of ultrascaled fully depleted silicon-on-insulator, double-gate silicon-on-insulator, and FinFET devices. We find that S/D tunneling is the prevalent phenomena for the three devices, and it is increasingly relevant for short-channel lengths
Treating triple negative breast cancer cells with erlotinib plus a select antioxidant overcomes drug resistance by targeting cancer cell heterogeneity
Among breast cancer patients, those diagnosed with the triple-negative breast cancer (TNBC) subtype have the worst prog-nosis. TNBC does not express estrogen receptor-alpha, progesterone receptor, or the HER2 oncogene; therefore, TNBC lacks targets for molecularly-guided therapies. The concept that EGFR oncogene inhibitor drugs could be used as targeted treatment against TNBC has been put forth based on estimates that 30-60% of TNBC express high levels of EGFR. However, results from clinical trials testing EGFR inhibitors, alone or in combination with cytotoxic chemotherapy, did not improve patient outcomes. Results herein offer an explanation as to why EGFR inhibitors failed TNBC patients and support how combining a select antioxidant and an EGFR-specific small molecule kinase inhibitor (SMKI) could be an effective, novel therapeutic strategy. Treatment with CAT-SKL-a re-engineered protein form of the antioxidant enzyme catalase-inhibited cancer stem-like cells (CSCs), and treatment with the EGFR-specific SMKI erlotinib inhibited non-CSCs. Thus, combining the antioxidant CAT-SKL with erlotinib targeted both CSCs and bulk cancer cells in cultures of EGFR-expressing TNBC-derived cells. We also report evidence that the mechanism for CAT-SKL inhibition of CSCs may depend on antioxidant-induced downregulation of a short alternative mRNA splicing variant of the methyl-CpG binding domain 2 gene, isoform MBD2c
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Atomoxetine and Citalopram alter brain network organisation in Parkinson’s disease
Parkinson’s disease has multiple detrimental effects on motor and cognitive systems in the brain. In contrast to motor deficits, cognitive impairments in Parkinson’s disease are usually not ameliorated, and can even be worsened, by dopaminergic treatments. Recent evidence has shown potential benefits from restoring other neurotransmitter deficits, including noradrenergic and serotonergic transmission. Here, we study global and regional brain network organization using task-free imaging (also known as resting-state), which minimizes performance confounds and the bias towards predetermined networks. Thirty-three patients with idiopathic Parkinson’s disease were studied three times in a double-blind, placebo-controlled counter-balanced crossover design, following placebo, 40mg-oral atomoxetine (selective noradrenaline reuptake inhibitor) or 30mg-oral citalopram (selective serotonin reuptake inhibitor). Neuropsychological assessments were performed outside the scanner. Seventy-six controls were scanned without medication to provide normative data for comparison to the patient cohort. Graph theoretical analysis of task-free brain connectivity, with a random 500-node parcellation, was used to measure the effect of disease in placebo-treated state (versus unmedicated controls) and pharmacological intervention (drug versus placebo). Relative to controls, patients on placebo had executive impairments (reduced fluency and inhibitory control), which was reflected in dysfunctional network dynamics in terms of reduced clustering coefficient, hub degree and hub centrality. In patients, atomoxetine improved fluency in proportion to plasma concentration (p=0.006, r2=0.24), and improved response inhibition in proportion to increased hub eigen centrality (p=0.044, r2=0.14). Citalopram did not improve fluency or inhibitory control, but its influence on network integration and efficiency depended on disease severity: clustering (p=0.01, r2=0.22), modularity (p=0.043, r2=0.14) and path length (p=0.006, r2=0.25) increased in patients with milder forms of Parkinson’s disease, but decreased in patients with more advanced disease (UPDRS-III >30). This study supports the use of task-free imaging of brain networks in translational pharmacology of neurodegenerative disorders. We propose that hub connectivity contributes to cognitive performance in Parkinson’s disease, and that noradrenergic treatment strategies can partially restore the neural systems supporting executive function
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