A New Constructive Heuristic for the Fm|block|ST

This paper deals with the blocking flow shop problem and proposes new constructive procedures for the total tardiness minimization of jobs. The heuristic has three-phases to build the sequence; the first phase selects the first job to be scheduled, the second phase arranges the remaining jobs and the third phase uses the insertion procedure of NEH to improve the sequence. The proposed procedures evaluate the tardiness associated to the sequence obtained before and after the third phase in order to keep the best of both because the insertion phase can worsen the result. The computational evaluation of these procedures against the benchmark constructive procedures from the literature reveals their good performance.Postprint (published version

Evolution of opinions on social networks in the presence of competing committed groups

Public opinion is often affected by the presence of committed groups of individuals dedicated to competing points of view. Using a model of pairwise social influence, we study how the presence of such groups within social networks affects the outcome and the speed of evolution of the overall opinion on the network. Earlier work indicated that a single committed group within a dense social network can cause the entire network to quickly adopt the group's opinion (in times scaling logarithmically with the network size), so long as the committed group constitutes more than about 10% of the population (with the findings being qualitatively similar for sparse networks as well). Here we study the more general case of opinion evolution when two groups committed to distinct, competing opinions $A$ and $B$, and constituting fractions $p_A$ and $p_B$ of the total population respectively, are present in the network. We show for stylized social networks (including Erd\H{o}s-R\'enyi random graphs and Barab\'asi-Albert scale-free networks) that the phase diagram of this system in parameter space $(p_A,p_B)$ consists of two regions, one where two stable steady-states coexist, and the remaining where only a single stable steady-state exists. These two regions are separated by two fold-bifurcation (spinodal) lines which meet tangentially and terminate at a cusp (critical point). We provide further insights to the phase diagram and to the nature of the underlying phase transitions by investigating the model on infinite (mean-field limit), finite complete graphs and finite sparse networks. For the latter case, we also derive the scaling exponent associated with the exponential growth of switching times as a function of the distance from the critical point.Comment: 23 pages: 15 pages + 7 figures (main text), 8 pages + 1 figure + 1 table (supplementary info

Population uptake of antiretroviral treatment through primary care in rural South Africa

<p>Abstract</p> <p>Background</p> <p>KwaZulu-Natal is the South African province worst affected by HIV and the focus of early modeling studies investigating strategies of antiretroviral treatment (ART) delivery. The reality of antiretroviral roll-out through primary care has differed from that anticipated and real world data are needed to inform the planning of further scaling up of services. We investigated the factors associated with uptake of antiretroviral treatment through a primary healthcare system in rural South Africa.</p> <p>Methods</p> <p>Detailed demographic, HIV surveillance and geographic information system (GIS) data were used to estimate the proportion of HIV positive adults accessing antiretroviral treatment within northern KwaZulu-Natal, South Africa in the period from initiation of antiretroviral roll-out until the end of 2008. Demographic, spatial and socioeconomic factors influencing the likelihood of individuals accessing antiretroviral treatment were explored using multivariable analysis.</p> <p>Results</p> <p>Mean uptake of ART among HIV positive resident adults was 21.0% (95%CI 20.1-21.9). Uptake among HIV positive men (19.2%) was slightly lower than women (21.8%, P = 0.011). An individual's likelihood of accessing ART was not associated with level of education, household assets or urban/rural locale. ART uptake was strongly negatively associated with distance from the nearest primary healthcare facility (aOR = 0.728 per square-root transformed km, 95%CI 0.658-0.963, <it>P </it>= 0.002).</p> <p>Conclusions</p> <p>Despite concerns about the equitable nature of antiretroviral treatment rollout, we find very few differences in ART uptake across a range of socio-demographic variables in a rural South African population. However, even when socio-demographic factors were taken into account, individuals living further away from primary healthcare clinics were still significantly less likely to be accessing ART</p

Impact of the June 2018 Saddleworth Moor wildfires on air quality in northern England

The June 2018 Saddleworth Moor fires were some of the largest UK wildfires on record and lasted for approximately three weeks. They emitted large quantities of smoke, trace gases and aerosols which were transported downwind over the highly populated regions of Manchester and Liverpool. Surface observations of PM2.5 indicate that concentrations were 4–5.5 times higher than the recent seasonal average. State-of-the-art satellite measurements of total column carbon monoxide (TCCO) from the TROPOMI instrument on the Sentinel 5—Precursor (S5P) platform, coupled with measurements from a flight of the UK BAe-146–301 research aircraft, are used to quantify the substantial enhancement in emitted trace gases. The aircraft measured plume enhancements with near-fire CO and PM2.5 concentrations >1500 ppbv and >125 μg m−3 (compared to ~100 ppbv and ~5 μg m−3 background concentrations). Downwind fire-plume ozone (O3) values were larger than the near-fire location, indicating O3 production with distance from source. The near-fire O3:CO ratio was (ΔO3/ΔCO) 0.001 ppbv/ppbv, increasing downwind to 0.060–0.105 ppbv/ppbv, suggestive of O3 production enhancement downwind of the fires. Emission rates of CO and CO2 ranged between 1.07 (0.07–4.69) kg s−1 and 13.7 (1.73–50.1) kg s−1, respectively, similar to values expected from a medium sized power station

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

Bench-to-bedside review : targeting antioxidants to mitochondria in sepsis

Peer reviewedPublisher PD

Phosphoenolpyruvate carboxylase dentified as a key enzyme in erythrocytic Plasmodium falciparum carbon metabolism

Phospoenolpyruvate carboxylase (PEPC) is absent from humans but encoded in thePlasmodium falciparum genome, suggesting that PEPC has a parasite-specific function. To investigate its importance in P. falciparum, we generated a pepc null mutant (D10Δpepc), which was only achievable when malate, a reduction product of oxaloacetate, was added to the growth medium. D10Δpepc had a severe growth defect in vitro, which was partially reversed by addition of malate or fumarate, suggesting that pepc may be essential in vivo. Targeted metabolomics using 13C-U-D-glucose and 13C-bicarbonate showed that the conversion of glycolytically-derived PEP into malate, fumarate, aspartate and citrate was abolished in D10Δpepc and that pentose phosphate pathway metabolites and glycerol 3-phosphate were present at increased levels. In contrast, metabolism of the carbon skeleton of 13C,15N-U-glutamine was similar in both parasite lines, although the flux was lower in D10Δpepc; it also confirmed the operation of a complete forward TCA cycle in the wild type parasite. Overall, these data confirm the CO2 fixing activity of PEPC and suggest that it provides metabolites essential for TCA cycle anaplerosis and the maintenance of cytosolic and mitochondrial redox balance. Moreover, these findings imply that PEPC may be an exploitable target for future drug discovery

A Functional Variant in MicroRNA-146a Promoter Modulates Its Expression and Confers Disease Risk for Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with a strong genetic predisposition, characterized by an upregulated type I interferon pathway. MicroRNAs are important regulators of immune homeostasis, and aberrant microRNA expression has been demonstrated in patients with autoimmune diseases. We recently identified miR-146a as a negative regulator of the interferon pathway and linked the abnormal activation of this pathway to the underexpression of miR-146a in SLE patients. To explore why the expression of miR-146a is reduced in SLE patients, we conducted short parallel sequencing of potentially regulatory regions of miR-146a and identified a novel genetic variant (rs57095329) in the promoter region exhibiting evidence for association with SLE that was replicated independently in 7,182 Asians (Pmeta = 2.74×10−8, odds ratio = 1.29 [1.18–1.40]). The risk-associated G allele was linked to reduced expression of miR-146a in the peripheral blood leukocytes of the controls. Combined functional assays showed that the risk-associated G allele reduced the protein-binding affinity and activity of the promoter compared with those of the promoter containing the protective A allele. Transcription factor Ets-1, encoded by the lupus-susceptibility gene ETS1, identified in recent genome-wide association studies, binds near this variant. The manipulation of Ets-1 levels strongly affected miR-146a promoter activity in vitro; and the knockdown of Ets-1, mimicking its reduced expression in SLE, directly impaired the induction of miR-146a. We also observed additive effects of the risk alleles of miR-146a and ETS1. Our data identified and confirmed an association between a functional promoter variant of miR-146a and SLE. This risk allele had decreased binding to transcription factor Ets-1, contributing to reduced levels of miR-146a in SLE patients

Opinion leaders and changes over time: a survey

<p>Abstract</p> <p>Background</p> <p>Opinion leaders represent one way to disseminate new knowledge and influence the practice behaviors of physicians. This study explored the stability of opinion leaders over time, whether opinion leaders were polymorphic (<it>i.e.</it>, influencing multiple practice areas) or monomorphic (<it>i.e.</it>, influencing one practice area), and reach of opinion leaders in their local network.</p> <p>Methods</p> <p>We surveyed surgeons and pathologists in Ontario to identify opinion leaders for colorectal cancer in 2003 and 2005 and to identify opinion leaders for breast cancer in 2005. We explored whether opinion leaders for colorectal cancer identified in 2003 were re-identified in 2005. We examined whether opinion leaders were considered polymorphic (nominated in 2005 as opinion leaders for both colorectal and breast cancer) or monomorphic (nominated in 2005 for only one condition). Social-network mapping was used to identify the number of local colleagues identifying opinion leaders.</p> <p>Results</p> <p>Response rates for surgeons were 41% (2003) and 40% (2005); response rates for pathologists were 42% (2003) and 37% (2005). Four (25%) of the surgical opinion leaders identified in 2003 for colorectal cancer were re-identified in 2005. No pathology opinion leaders for colorectal cancer were identified in both 2003 and 2005. Only 29% of surgical opinion leaders and 17% of pathology opinion leaders identified in the 2005 survey were considered influential for both colorectal cancer and breast cancer. Social-network mapping revealed that only a limited number of general surgeons (12%) or pathologists (7%) were connected to the social networks of identified opinion leaders.</p> <p>Conclusions</p> <p>Opinion leaders identified in this study were not stable over a two-year time period and generally appear to be monomorphic, with clearly demarcated areas of expertise and limited spheres of influence. These findings may limit the practicability of routinely using opinion leaders to influence practice.</p

General Analysis of Antideuteron Searches for Dark Matter

Low energy cosmic ray antideuterons provide a unique low background channel for indirect detection of dark matter. We compute the cosmic ray flux of antideuterons from hadronic annihilations of dark matter for various Standard Model final states and determine the mass reach of two future experiments (AMS-02 and GAPS) designed to greatly increase the sensitivity of antideuteron detection over current bounds. We consider generic models of scalar, fermion, and massive vector bosons as thermal dark matter, describe their basic features relevant to direct and indirect detection, and discuss the implications of direct detection bounds on models of dark matter as a thermal relic. We also consider specific dark matter candidates and assess their potential for detection via antideuterons from their hadronic annihilation channels. Since the dark matter mass reach of the GAPS experiment can be well above 100 GeV, we find that antideuterons can be a good indirect detection channel for a variety of thermal relic electroweak scale dark matter candidates, even when the rate for direct detection is highly suppressed.Comment: 44 pages, 15 Figure