A Schur complement approach to preconditioning sparse linear least-squares problems with some dense rows

The effectiveness of sparse matrix techniques for directly solving large-scale linear least-squares problems is severely limited if the system matrix A has one or more nearly dense rows. In this paper, we partition the rows of A into sparse rows and dense rows (A s and A d ) and apply the Schur complement approach. A potential difficulty is that the reduced normal matrix AsTA s is often rank-deficient, even if A is of full rank. To overcome this, we propose explicitly removing null columns of A s and then employing a regularization parameter and using the resulting Cholesky factors as a preconditioner for an iterative solver applied to the symmetric indefinite reduced augmented system. We consider complete factorizations as well as incomplete Cholesky factorizations of the shifted reduced normal matrix. Numerical experiments are performed on a range of large least-squares problems arising from practical applications. These demonstrate the effectiveness of the proposed approach when combined with either a sparse parallel direct solver or a robust incomplete Cholesky factorization algorithm

A Cross-Sectional Study of People with Epilepsy and Neurocysticercosis in Tanzania: Clinical Characteristics and Diagnostic Approaches.

Neurocysticercosis (NCC) is a major cause of epilepsy in regions where pigs are free-ranging and hygiene is poor. Pork production is expected to increase in the next decade in sub-Saharan Africa, hence NCC will likely become more prevalent. In this study, people with epilepsy (PWE, n=212) were followed up 28.6 months after diagnosis of epilepsy. CT scans were performed, and serum and cerebrospinal fluid (CSF) of selected PWE were analysed. We compared the demographic data, clinical characteristics, and associated risk factors of PWE with and without NCC. PWE with NCC (n=35) were more likely to be older at first seizure (24.3 vs. 16.3 years, p=0.097), consumed more pork (97.1% vs. 73.6%, p=0.001), and were more often a member of the Iraqw tribe (94.3% vs. 67.8%, p=0.005) than PWE without NCC (n=177). PWE and NCC who were compliant with anti-epileptic medications had a significantly higher reduction of seizures (98.6% vs. 89.2%, p=0.046). Other characteristics such as gender, seizure frequency, compliance, past medical history, close contact with pigs, use of latrines and family history of seizures did not differ significantly between the two groups. The number of NCC lesions and active NCC lesions were significantly associated with a positive antibody result. The electroimmunotransfer blot, developed by the Centers for Disease Control and Prevention, was more sensitive than a commercial western blot, especially in PWE and cerebral calcifications. This is the first study to systematically compare the clinical characteristics of PWE due to NCC or other causes and to explore the utility of two different antibody tests for diagnosis of NCC in sub-Saharan Africa

Assessing the Value of Recreational Divers for Censusing Elasmobranchs

BACKGROUND: Around the world, researchers are using the observations and experiences of citizens to describe patterns in animal populations. This data is often collected via ongoing sampling or by synthesizing past experiences. Since elasmobranchs are relatively rare, obtaining data for broad-scale trend analysis requires high sampling effort. Elasmobranchs are also relatively large and conspicuous and therefore it may be possible to enlist recreational divers to collect data on their occurrence and relative abundance from daily dive activities. For this, however, a good understanding of the value of data collected by recreational divers is essential. METHODOLOGY/PRINCIPAL FINDINGS: Here, we explore the value of recreational divers for censusing elasmobranchs using a diverse set of data sources. First, we use a simulation experiment to explore detection rates of the roving diver technique, used by recreational divers, across a range of fish densities and speeds. Next, using a field survey, we show that inexperienced recreational divers detect and count elasmobranchs as well as experienced recreational divers. Finally, we use semi-structured interviews of recreational dive instructors to demonstrate the value of their recollections in terms of effort and their descriptions of spatial and temporal distributions of sharks in Thailand. CONCLUSIONS/SIGNIFICANCE: Overall, this study provides initial ground-work for using recreational divers for monitoring elasmobranch populations. If used appropriately, citizen-collected data may provide additional information that can be used to complement more standardized surveys and to describe population trends across a range of spatial and temporal scales. Due to the non-extractive nature of this data, recreational divers may also provide important insight into the success of conservation initiatives, such as shark sanctuaries and no-take zones

Empowerment or Engagement? Digital Health Technologies for Mental Healthcare

We argue that while digital health technologies (e.g. artificial intelligence, smartphones, and virtual reality) present significant opportunities for improving the delivery of healthcare, key concepts that are used to evaluate and understand their impact can obscure significant ethical issues related to patient engagement and experience. Specifically, we focus on the concept of empowerment and ask whether it is adequate for addressing some significant ethical concerns that relate to digital health technologies for mental healthcare. We frame these concerns using five key ethical principles for AI ethics (i.e. autonomy, beneficence, non-maleficence, justice, and explicability), which have their roots in the bioethical literature, in order to critically evaluate the role that digital health technologies will have in the future of digital healthcare

Time spent with cats is never wasted: Lessons learned from feline acromegalic cardiomyopathy, a naturally occurring animal model of the human disease

<div><p>Background</p><p>In humans, acromegaly due to a pituitary somatotrophic adenoma is a recognized cause of increased left ventricular (LV) mass. Acromegalic cardiomyopathy is incompletely understood, and represents a major cause of morbidity and mortality. We describe the clinical, echocardiographic and histopathologic features of naturally occurring feline acromegalic cardiomyopathy, an emerging disease among domestic cats.</p><p>Methods</p><p>Cats with confirmed hypersomatotropism (IGF-1>1000ng/ml and pituitary mass; n = 67) were prospectively recruited, as were two control groups: diabetics (IGF-1<800ng/ml; n = 24) and healthy cats without known endocrinopathy or cardiovascular disease (n = 16). Echocardiography was performed in all cases, including after hypersomatotropism treatment where applicable. Additionally, tissue samples from deceased cats with hypersomatotropism, hypertrophic cardiomyopathy and age-matched controls (n = 21 each) were collected and systematically histopathologically reviewed and compared.</p><p>Results</p><p>By echocardiography, cats with hypersomatotropism had a greater maximum LV wall thickness (6.5mm, 4.1–10.1mm) than diabetic (5.9mm, 4.2–9.1mm; Mann Whitney, p<0.001) or control cats (5.2mm, 4.1–6.5mm; Mann Whitney, p<0.001). Left atrial diameter was also greater in cats with hypersomatotropism (16.6mm, 13.0–29.5mm) than in diabetic (15.4mm, 11.2–20.3mm; Mann Whitney, p<0.001) and control cats (14.0mm, 12.6–17.4mm; Mann Whitney, p<0.001). After hypophysectomy and normalization of IGF-1 concentration (n = 20), echocardiographic changes proved mostly reversible. As in humans, histopathology of the feline acromegalic heart was dominated by myocyte hypertrophy with interstitial fibrosis and minimal myofiber disarray.</p><p>Conclusions</p><p>These results demonstrate cats could be considered a naturally occurring model of acromegalic cardiomyopathy, and as such help elucidate mechanisms driving cardiovascular remodeling in this disease.</p></div

Cigarette, cigar and pipe smoking, passive smoke exposure, and risk of pancreatic cancer: a population-based study in the San Francisco Bay Area

Abstract Background To examine the influence of cigarette, cigar and pipe smoking, cessation of cigarette smoking and passive smoke exposure on the risk of pancreatic cancer. Methods Exposure data were collected during in-person interviews in a population-based case-control study of pancreatic cancer (N = 532 cases, N = 1701 controls) in the San Francisco Bay Area. Odds ratios (ORs) were adjusted for potential confounders. Results The adjusted odds ratio (OR) of pancreatic cancer among current smokers was 1.9 (95% confidence interval (CI), 1.4-2.7). A significant, positive trend in risk with increasing pack-years of smoking was observed (P-trend &lt;0.0001). Compared with participants who continued to smoke, former smokers had no statistically significant elevation in risk of pancreatic cancer 10 years after smoking cessation, with risk reduced to that of never smokers regardless of prior smoking intensity. Both men and women experienced similar increased risk of pancreatic cancer with increasing smoking duration. Cigar and pipe smoking and exposure to passive smoke were not associated with pancreatic cancer. Conclusions Cigarette smoking is associated with an increased risk of pancreatic cancer. Smokers who had quit for ≥10 years no longer experienced an increased risk. Future work will help to determine the effect of declining smoking rates on pancreatic cancer incidence

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures

The Main Belt Comets and ice in the Solar System

We review the evidence for buried ice in the asteroid belt; specifically the questions around the so-called Main Belt Comets (MBCs). We summarise the evidence for water throughout the Solar System, and describe the various methods for detecting it, including remote sensing from ultraviolet to radio wavelengths. We review progress in the first decade of study of MBCs, including observations, modelling of ice survival, and discussion on their origins. We then look at which methods will likely be most effective for further progress, including the key challenge of direct detection of (escaping) water in these bodies

Impact of exposure measurement error in air pollution epidemiology: effect of error type in time-series studies

<p>Abstract</p> <p>Background</p> <p>Two distinctly different types of measurement error are Berkson and classical. Impacts of measurement error in epidemiologic studies of ambient air pollution are expected to depend on error type. We characterize measurement error due to instrument imprecision and spatial variability as multiplicative (i.e. additive on the log scale) and model it over a range of error types to assess impacts on risk ratio estimates both on a per measurement unit basis and on a per interquartile range (IQR) basis in a time-series study in Atlanta.</p> <p>Methods</p> <p>Daily measures of twelve ambient air pollutants were analyzed: NO₂, NO_x, O₃, SO₂, CO, PM₁₀mass, PM_2.5mass, and PM_2.5components sulfate, nitrate, ammonium, elemental carbon and organic carbon. Semivariogram analysis was applied to assess spatial variability. Error due to this spatial variability was added to a reference pollutant time-series on the log scale using Monte Carlo simulations. Each of these time-series was exponentiated and introduced to a Poisson generalized linear model of cardiovascular disease emergency department visits.</p> <p>Results</p> <p>Measurement error resulted in reduced statistical significance for the risk ratio estimates for all amounts (corresponding to different pollutants) and types of error. When modelled as classical-type error, risk ratios were attenuated, particularly for primary air pollutants, with average attenuation in risk ratios on a per unit of measurement basis ranging from 18% to 92% and on an IQR basis ranging from 18% to 86%. When modelled as Berkson-type error, risk ratios per unit of measurement were biased away from the null hypothesis by 2% to 31%, whereas risk ratios per IQR were attenuated (i.e. biased toward the null) by 5% to 34%. For CO modelled error amount, a range of error types were simulated and effects on risk ratio bias and significance were observed.</p> <p>Conclusions</p> <p>For multiplicative error, both the amount and type of measurement error impact health effect estimates in air pollution epidemiology. By modelling instrument imprecision and spatial variability as different error types, we estimate direction and magnitude of the effects of error over a range of error types.</p

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT