1,721 research outputs found
Extracting Requirements for Ubiquitous Computing Technology-based IS Using Factor Analysis
The paper describes a methodology for extracting the requirements for ubiquitous computing technology-based information system (IS) using factor analysis. The early idea of ubiquitous computing was articulated by Mark Weiser in 1988 and since then has been constantly developed. However, so far there was no any or few research on application of ubiquitous computing to IS. Prior to the development of a ubiquitous computing-based IS model necessary requirements are to be identified. To derive the requirements we refer to conventional research on ubiquitous computing, ubiquitous service and ubiquitous environment, and hence, to their characteristics. Having specified those requirements using factor analysis technique it will be easier to develop a consistent ubiquitous computing-based IS
Luminescent properties of Bi-doped polycrystalline KAlCl4
We observed an intensive near-infrared luminescence in Bi-doped KAlCl4
polycrystalline material. Luminescence dependence on the excitation wavelength
and temperature of the sample was studied. Our experimental results allow
asserting that the luminescence peaked near 1 um belongs solely to Bi+ ion
which isomorphically substitutes potassium in the crystal. It was also
demonstrated that Bi+ luminescence features strongly depend on the local ion
surroundings
Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline
From medical charts to national census, healthcare has traditionally operated
under a paper-based paradigm. However, the past decade has marked a long and
arduous transformation bringing healthcare into the digital age. Ranging from
electronic health records, to digitized imaging and laboratory reports, to
public health datasets, today, healthcare now generates an incredible amount of
digital information. Such a wealth of data presents an exciting opportunity for
integrated machine learning solutions to address problems across multiple
facets of healthcare practice and administration. Unfortunately, the ability to
derive accurate and informative insights requires more than the ability to
execute machine learning models. Rather, a deeper understanding of the data on
which the models are run is imperative for their success. While a significant
effort has been undertaken to develop models able to process the volume of data
obtained during the analysis of millions of digitalized patient records, it is
important to remember that volume represents only one aspect of the data. In
fact, drawing on data from an increasingly diverse set of sources, healthcare
data presents an incredibly complex set of attributes that must be accounted
for throughout the machine learning pipeline. This chapter focuses on
highlighting such challenges, and is broken down into three distinct
components, each representing a phase of the pipeline. We begin with attributes
of the data accounted for during preprocessing, then move to considerations
during model building, and end with challenges to the interpretation of model
output. For each component, we present a discussion around data as it relates
to the healthcare domain and offer insight into the challenges each may impose
on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20
Pages, 1 Figur
HIF-Independent Regulation of Thioredoxin Reductase 1 Contributes to the High Levels of Reactive Oxygen Species Induced by Hypoxia
Cellular adaptation to hypoxic conditions mainly involves transcriptional changes in which hypoxia inducible factors (HIFs) play a critical role. Under hypoxic conditions, HIF protein is stabilized due to inhibition of the activity of prolyl hydroxylases (EGLNs). Because the reaction carried out by these enzymes uses oxygen as a co-substrate it is generally accepted that the hypoxic inhibition of EGLNs is due to the reduction in oxygen levels. However, several studies have reported that hypoxic generation of mitochondrial reactive oxygen species (ROS) is required for HIF stabilization. Here, we show that hypoxia downregulates thioredoxin reductase 1 (TR1) mRNA and protein levels. This hypoxic TR1 regulation is HIF independent, as HIF stabilization by EGLNs inhibitors does not affect TR1 expression and HIF deficiency does not block TR1 hypoxic-regulation, and it has an effect on TR1 function, as hypoxic conditions also reduce TR1 activity. We found that, when cultured under hypoxic conditions, TR1 deficient cells showed a larger accumulation of ROS compared to control cells, whereas TR1 over-expression was able to block the hypoxic generation of ROS. Furthermore, the changes in ROS levels observed in TR1 deficient or TR1 over-expressing cells did not affect HIF stabilization or function. These results indicate that hypoxic TR1 down-regulation is important in maintaining high levels of ROS under hypoxic conditions and that HIF stabilization and activity do not require hypoxic generation of ROS
Health-related quality of life in patients with a germline BRCA mutation and metastatic pancreatic cancer receiving maintenance olaparib
BACKGROUND: Patients with metastatic pancreatic cancer (mPC) often have a detriment in health-related quality of life (HRQoL). In the randomized, double-blind, Phase III POLO trial progression-free survival was significantly longer with maintenance olaparib, a poly(ADP-ribose) polymerase inhibitor, than placebo in patients with a germline BRCA1 and/or BRCA2 mutation (gBRCAm) and mPC whose disease had not progressed during first-line platinum-based chemotherapy. The prespecified HRQoL evaluation is reported here. PATIENTS AND METHODS: Patients were randomized to receive maintenance olaparib (300 mg bid; tablets) or placebo. HRQoL was assessed using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30-item module at baseline, every 4 weeks until disease progression, at discontinuation, and 30 days after last dose. Scores ranged from 0 to 100; a ≥ 10-point change or difference between arms was considered clinically meaningful. Adjusted mean change from baseline was analysed using a mixed model for repeated measures. Time to sustained clinically meaningful deterioration (TSCMD) was analysed using a log-rank test. RESULTS: Of 154 randomized patients, 89 of 92 olaparib-arm and 58 of 62 placebo-arm patients were included in HRQoL analyses. The adjusted mean change in Global Health Status (GHS) score from baseline was less than 10 points in both arms and there was no significant between-group difference (-2.47; 95% CI - 7.27, 2.33; P=0.31). Analysis of physical functioning scores showed a significant between-group difference (-4.45 points; 95% CI - 8.75, -0.16; P=0.04). There was no difference in TSCMD for olaparib versus placebo for GHS (P=0.25; HR 0.72; 95% CI 0.41, 1.27) or physical functioning (P=0.32; HR 1.38; 95%CI 0.73, 2.63). CONCLUSIONS: HRQoL was preserved with maintenance olaparib treatment with no clinically meaningful difference compared with placebo. These results support the observed efficacy benefit of maintenance olaparib in patients with a gBRCAm and mPC. CLINCALTRIALS.GOV NUMBER: NCT02184195
Observation of Coherent Elastic Neutrino-Nucleus Scattering
The coherent elastic scattering of neutrinos off nuclei has eluded detection
for four decades, even though its predicted cross-section is the largest by far
of all low-energy neutrino couplings. This mode of interaction provides new
opportunities to study neutrino properties, and leads to a miniaturization of
detector size, with potential technological applications. We observe this
process at a 6.7-sigma confidence level, using a low-background, 14.6-kg
CsI[Na] scintillator exposed to the neutrino emissions from the Spallation
Neutron Source (SNS) at Oak Ridge National Laboratory. Characteristic
signatures in energy and time, predicted by the Standard Model for this
process, are observed in high signal-to-background conditions. Improved
constraints on non-standard neutrino interactions with quarks are derived from
this initial dataset
Quantitative analysis of single bacterial chemotaxis using a linear concentration gradient microchannel
A microfluidic device to quantify bacterial chemotaxis has been proposed, which generates a linear concentration gradient of chemoattractant in the main channel only by convective and molecular diffusion, and which enables the bacteria to enter the main channel in a single file by hydrodynamic focusing technique. The trajectory of each bacterium in response to the concentration gradient of chemoattractant is photographed by a CCD camera and its velocity is acquired by a simple PTV (Particle Tracking Velocimetry) algorithm. An advantage of this assay is to measure the velocity of a single bacterium and to quantify the degree of chemotaxis by analyzing the frequency of velocities concurrently. Thus, the parameter characterizing the motility of wild-type Escherichia coli strain RP437 in response to various concentration gradients of L-aspartate is obtained in such a manner that the degree of bacterial chemotaxis is quantified on the basis of a newly proposed Migration Index
Detection and molecular characterisation of bovine corona and toroviruses from Croatian cattle
Prevalence of neck pain in subjects with metabolic syndrome - a cross-sectional population-based study
<p>Abstract</p> <p>Background</p> <p>Metabolic syndrome (MetS) is increasingly common. Obesity has been suggested to associate with neck pain but prevalence of neck pain in subjects with MetS has not been studied. Aim of this study was to analyse the association between MetS and neck pain.</p> <p>Methods</p> <p>The study population consisted of 1294 middle-aged subjects in Pieksämäki, Finland. A total of 399 males and 500 females participated (69%). The mean age of both males and females was 46 years. Clinical and biochemical measurements were taken. The participants filled out a standard questionnaire. Psychological distress was assessed with the 12-item General Health Questionnaire (GHQ-12). Neck pain was defined as neck pain perceived daily. MetS was defined using National Cholesterol Education Program (NCEP) criteria. Statistical comparisons between the groups were performed using a bootstrap-type t-test or Chi-Square test. Risk ratios of having neck pain were calculated using generalised linear models with age, smoking, alcohol use, exercise and GHQ-12 score as covariates.</p> <p>Results</p> <p>The prevalence of MetS was 33% in males and 29% in females. Neck pain was present in 11% (N = 42) of males and 19% (N = 93) of females (P < 0.001). The prevalence of neck pain was 7.9% (95% CI, 4.9% to 12%) among male subjects without MetS and 16% (95% CI, 10% to 23%) among those with MetS. The respective proportions among females were 16% (95% CI, 12% to 20%) and 25% (95% CI, 18% to 33%). The multivariate analysis showed an increased risk of neck pain in males with MetS (RR 2.1, 95% CI, 1.2 to 3.7, P = 0.010) and in females with MetS (RR 1.5, 95% CI, 1.0 to 2.1, P = 0.040).</p> <p>Conclusions</p> <p>MetS was associated with neck pain. This association was stronger in males, but the prevalence of neck pain was higher in females. Prospective studies should explore the potential causal association between neck pain and MetS and the potential common background factors of neck pain and MetS.</p
Evolutionary and pulsational properties of white dwarf stars
Abridged. White dwarf stars are the final evolutionary stage of the vast
majority of stars, including our Sun. The study of white dwarfs has potential
applications to different fields of astrophysics. In particular, they can be
used as independent reliable cosmic clocks, and can also provide valuable
information about the fundamental parameters of a wide variety of stellar
populations, like our Galaxy and open and globular clusters. In addition, the
high densities and temperatures characterizing white dwarfs allow to use these
stars as cosmic laboratories for studying physical processes under extreme
conditions that cannot be achieved in terrestrial laboratories. They can be
used to constrain fundamental properties of elementary particles such as axions
and neutrinos, and to study problems related to the variation of fundamental
constants.
In this work, we review the essentials of the physics of white dwarf stars.
Special emphasis is placed on the physical processes that lead to the formation
of white dwarfs as well as on the different energy sources and processes
responsible for chemical abundance changes that occur along their evolution.
Moreover, in the course of their lives, white dwarfs cross different
pulsational instability strips. The existence of these instability strips
provides astronomers with an unique opportunity to peer into their internal
structure that would otherwise remain hidden from observers. We will show that
this allows to measure with unprecedented precision the stellar masses and to
infer their envelope thicknesses, to probe the core chemical stratification,
and to detect rotation rates and magnetic fields. Consequently, in this work,
we also review the pulsational properties of white dwarfs and the most recent
applications of white dwarf asteroseismology.Comment: 85 pages, 28 figures. To be published in The Astronomy and
Astrophysics Revie
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