323 research outputs found
Dirichlet Process Hidden Markov Multiple Change-point Model
This paper proposes a new Bayesian multiple change-point model which is based
on the hidden Markov approach. The Dirichlet process hidden Markov model does
not require the specification of the number of change-points a priori. Hence
our model is robust to model specification in contrast to the fully parametric
Bayesian model. We propose a general Markov chain Monte Carlo algorithm which
only needs to sample the states around change-points. Simulations for a normal
mean-shift model with known and unknown variance demonstrate advantages of our
approach. Two applications, namely the coal-mining disaster data and the real
United States Gross Domestic Product growth, are provided. We detect a single
change-point for both the disaster data and US GDP growth. All the change-point
locations and posterior inferences of the two applications are in line with
existing methods.Comment: Published at http://dx.doi.org/10.1214/14-BA910 in the Bayesian
Analysis (http://projecteuclid.org/euclid.ba) by the International Society of
Bayesian Analysis (http://bayesian.org/
On the Bounds of Function Approximations
Within machine learning, the subfield of Neural Architecture Search (NAS) has
recently garnered research attention due to its ability to improve upon
human-designed models. However, the computational requirements for finding an
exact solution to this problem are often intractable, and the design of the
search space still requires manual intervention. In this paper we attempt to
establish a formalized framework from which we can better understand the
computational bounds of NAS in relation to its search space. For this, we first
reformulate the function approximation problem in terms of sequences of
functions, and we call it the Function Approximation (FA) problem; then we show
that it is computationally infeasible to devise a procedure that solves FA for
all functions to zero error, regardless of the search space. We show also that
such error will be minimal if a specific class of functions is present in the
search space. Subsequently, we show that machine learning as a mathematical
problem is a solution strategy for FA, albeit not an effective one, and further
describe a stronger version of this approach: the Approximate Architectural
Search Problem (a-ASP), which is the mathematical equivalent of NAS. We
leverage the framework from this paper and results from the literature to
describe the conditions under which a-ASP can potentially solve FA as well as
an exhaustive search, but in polynomial time.Comment: Accepted as a full paper at ICANN 2019. The final, authenticated
publication will be available at https://doi.org/10.1007/978-3-030-30487-4_3
Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study
Background:
Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear.
Methods:
We obtained data from 3313 patients with established coronary heart disease in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. We tested associations of tertiles of lipoprotein(a) concentration in plasma and two LPA single-nucleotide polymorphisms ([SNPs] rs10455872 and rs3798220) with all-cause mortality and cardiovascular mortality by Cox regression analysis and with severity of disease by generalised linear modelling, with and without adjustment for age, sex, diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LDL-cholesterol concentration, and use of lipid-lowering therapy. Results for plasma lipoprotein(a) concentrations were validated in five independent studies involving 10 195 patients with established coronary heart disease. Results for genetic associations were replicated through large-scale collaborative analysis in the GENIUS-CHD consortium, comprising 106 353 patients with established coronary heart disease and 19 332 deaths in 22 studies or cohorts.
Findings:
The median follow-up was 9·9 years. Increased severity of coronary heart disease was associated with lipoprotein(a) concentrations in plasma in the highest tertile (adjusted hazard radio [HR] 1·44, 95% CI 1·14–1·83) and the presence of either LPA SNP (1·88, 1·40–2·53). No associations were found in LURIC with all-cause mortality (highest tertile of lipoprotein(a) concentration in plasma 0·95, 0·81–1·11 and either LPA SNP 1·10, 0·92–1·31) or cardiovascular mortality (0·99, 0·81–1·2 and 1·13, 0·90–1·40, respectively) or in the validation studies.
Interpretation:
In patients with prevalent coronary heart disease, lipoprotein(a) concentrations and genetic variants showed no associations with mortality. We conclude that these variables are not useful risk factors to measure to predict progression to death after coronary heart disease is established.
Funding:
Seventh Framework Programme for Research and Technical Development (AtheroRemo and RiskyCAD), INTERREG IV Oberrhein Programme, Deutsche Nierenstiftung, Else-Kroener Fresenius Foundation, Deutsche Stiftung für Herzforschung, Deutsche Forschungsgemeinschaft, Saarland University, German Federal Ministry of Education and Research, Willy Robert Pitzer Foundation, and Waldburg-Zeil Clinics Isny
From evolutionary computation to the evolution of things
Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering tasks ranging in outlook from the molecular to the astronomical. Today, the field is entering a new phase as evolutionary algorithms that take place in hardware are developed, opening up new avenues towards autonomous machines that can adapt to their environment. We discuss how evolutionary computation compares with natural evolution and what its benefits are relative to other computing approaches, and we introduce the emerging area of artificial evolution in physical systems
Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study
Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised
An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data
Citation: Shi, Z. Z., Chapes, S. K., Ben-Arieh, D., & Wu, C. H. (2016). An Agent-Based Model of a Hepatic Inflammatory Response to Salmonella: A Computational Study under a Large Set of Experimental Data. Plos One, 11(8), 39. doi:10.1371/journal.pone.0161131We present an agent-based model (ABM) to simulate a hepatic inflammatory response (HIR) in a mouse infected by Salmonella that sometimes progressed to problematic proportions, known as "sepsis". Based on over 200 published studies, this ABM describes interactions among 21 cells or cytokines and incorporates 226 experimental data sets and/or data estimates from those reports to simulate a mouse HIR in silico. Our simulated results reproduced dynamic patterns of HIR reported in the literature. As shown in vivo, our model also demonstrated that sepsis was highly related to the initial Salmonella dose and the presence of components of the adaptive immune system. We determined that high mobility group box-1, C-reactive protein, and the interleukin-10: tumor necrosis factor-a ratio, and CD4+ T cell: CD8+ T cell ratio, all recognized as biomarkers during HIR, significantly correlated with outcomes of HIR. During therapy-directed silico simulations, our results demonstrated that anti-agent intervention impacted the survival rates of septic individuals in a time-dependent manner. By specifying the infected species, source of infection, and site of infection, this ABM enabled us to reproduce the kinetics of several essential indicators during a HIR, observe distinct dynamic patterns that are manifested during HIR, and allowed us to test proposed therapy-directed treatments. Although limitation still exists, this ABM is a step forward because it links underlying biological processes to computational simulation and was validated through a series of comparisons between the simulated results and experimental studies
An update of the Worldwide Integrated Assessment (WIA) on systemic insecticides. Part 2: impacts on organisms and ecosystems
New information on the lethal and sublethal effects of neonicotinoids and fipronil on organisms is presented in this review, complementing the previous WIA in 2015. The high toxicity of these systemic insecticides to invertebrates has been confirmed and expanded to include more species and compounds. Most of the recent research has focused on bees and the sublethal and ecological impacts these insecticides have on pollinators. Toxic effects on other invertebrate taxa also covered predatory and parasitoid natural enemies and aquatic arthropods. Little, while not much new information has been gathered on soil organisms. The impact on marine coastal ecosystems is still largely uncharted. The chronic lethality of neonicotinoids to insects and crustaceans, and the strengthened evidence that these chemicals also impair the immune system and reproduction, highlights the dangers of this particular insecticidal classneonicotinoids and fipronil. , withContinued large scale – mostly prophylactic – use of these persistent organochlorine pesticides has the potential to greatly decreasecompletely eliminate populations of arthropods in both terrestrial and aquatic environments. Sublethal effects on fish, reptiles, frogs, birds and mammals are also reported, showing a better understanding of the mechanisms of toxicity of these insecticides in vertebrates, and their deleterious impacts on growth, reproduction and neurobehaviour of most of the species tested. This review concludes with a summary of impacts on the ecosystem services and functioning, particularly on pollination, soil biota and aquatic invertebrate communities, thus reinforcing the previous WIA conclusions (van der Sluijs et al. 2015)
Phase transitions in quantum chromodynamics
The current understanding of finite temperature phase transitions in QCD is
reviewed. A critical discussion of refined phase transition criteria in
numerical lattice simulations and of analytical tools going beyond the
mean-field level in effective continuum models for QCD is presented.
Theoretical predictions about the order of the transitions are compared with
possible experimental manifestations in heavy-ion collisions. Various places in
phenomenological descriptions are pointed out, where more reliable data for
QCD's equation of state would help in selecting the most realistic scenario
among those proposed. Unanswered questions are raised about the relevance of
calculations which assume thermodynamic equilibrium. Promising new approaches
to implement nonequilibrium aspects in the thermodynamics of heavy-ion
collisions are described.Comment: 156 pages, RevTex. Tables II,VIII,IX and Fig.s 1-38 are not included
as postscript files. I would like to ask the requestors to copy the missing
tables and figures from the corresponding journal-referenc
Automated Adaptation Strategies for Stream Learning
Automation of machine learning model development is increasingly becoming an established research area. While automated model selection and automated data pre-processing have been studied in depth, there is, however, a gap concerning automated model adaptation strategies when multiple strategies are available. Manually developing an adaptation strategy can be time consuming and costly. In this paper we address this issue by proposing the use of flexible adaptive mechanism deployment for automated development of adaptation strategies. Experimental results after using the proposed strategies with five adaptive algorithms on 36 datasets confirm their viability. These strategies achieve better or comparable performance to the custom adaptation strategies and the repeated deployment of any single adaptive mechanism
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