Positive Solutions to a Diffusive Logistic Equation with Constant Yield Harvesting

We consider a reaction diffusion equation which models the constant yield harvesting of a spatially heterogeneous population which satisfies a logistic growth. In particular, we study the existence of positive solutions subject to a class of nonlinear boundary conditions. We also provide results for the case of Neumann and Robin boundary conditions. We obtain our results via a quadrature method and Mathematica computations

CP Violation in Three-Body Chargino Decays

CP violation in supersymmetry can give rise to rate asymmetries in the decays of supersymmetric particles. In this work we compute the rate asymmetries for the three-body chargino decays \tilde\chi^\pm_2 \to \tilde\chi^\pm_1 HH, \tilde\chi^\pm_2 \to \tilde\chi^\pm_1 ZZ, \tilde\chi^\pm_2 \to \tilde\chi^\pm_1 W^+ W^- and \tilde\chi^\pm_2 \to tilde\chi^\pm_1 ZH. Each of the decays contains contributions mediated by neutral Higgs bosons that can possibly go on shell. Such contributions receive a resonant enhancement; furthermore, the strong phases required for the CP asymmetries come from the widths of the exchanged Higgs bosons. Our results indicate that the rate asymmetries can be relatively large in some cases, while still respecting a number of important low-energy bounds such as those coming from B meson observables and electric dipole moments. For the parameters that we consider, rate asymmetries of order 10% are possible in some cases.Comment: 17 pages, 4 figures, published versio

Machine learning for large-scale wearable sensor data in Parkinson disease:concepts, promises, pitfalls, and futures

For the treatment and monitoring of Parkinson's disease (PD) to be scientific, a key requirement is that measurement of disease stages and severity is quantitative, reliable, and repeatable. The last 50 years in PD research have been dominated by qualitative, subjective ratings obtained by human interpretation of the presentation of disease signs and symptoms at clinical visits. More recently, “wearable,” sensor-based, quantitative, objective, and easy-to-use systems for quantifying PD signs for large numbers of participants over extended durations have been developed. This technology has the potential to significantly improve both clinical diagnosis and management in PD and the conduct of clinical studies. However, the large-scale, high-dimensional character of the data captured by these wearable sensors requires sophisticated signal processing and machine-learning algorithms to transform it into scientifically and clinically meaningful information. Such algorithms that “learn” from data have shown remarkable success in making accurate predictions for complex problems in which human skill has been required to date, but they are challenging to evaluate and apply without a basic understanding of the underlying logic on which they are based. This article contains a nontechnical tutorial review of relevant machine-learning algorithms, also describing their limitations and how these can be overcome. It discusses implications of this technology and a practical road map for realizing the full potential of this technology in PD research and practice

Figure Once Removed Show Card

Show card for Figure Once removed, February 28 - April 2, 2003.https://digitalcommons.udallas.edu/figure_once_removed/1001/thumbnail.jp

Detection of CI in absorption towards PKS 1830-211 with the eSMA

We report the first science observations and results obtained with the "extended" SMA (eSMA), which is composed of the SMA (Submillimeter Array), JCMT (James Clerk Maxwell Telescope) and CSO (Caltech Submillimeter Observatory). Redshifted absorptions at z=0.886 of CI (^3P_1 - ^3P_0) were observed with the eSMA with an angular resolution of 0.55"x0.22" at 1.1 mm toward the southwestern image of the remarkable lensed quasar PKS 1830-211, but not toward the northeastern component at a separation of ~1". Additionally, SMA observations of CO, 13CO and C18O (all J=4-3) were obtained toward this object: CO was also detected toward the SW component, but none of the isotopologues were. This is the first time [CI] is detected in this object, allowing the first direct determination of relative abundances of neutral atomic carbon to CO in the molecular clouds of a spiral galaxy at z>0.1. The [CI] and CO profiles can be decomposed into two and three velocity components respectively. We derive C/CO column density ratios ranging from <0.5 (representative of dense cores) to ~2.5 (close to translucent clouds values). This could indicate that we are seeing environments with different physical conditions or that we are witnessing chemical evolution of regions where C has not completely been converted into CO.Comment: 6 pages using emulateapj, 3 tables, 2 figures ; accepted for publication in ApJ

Elucidating the aetiology of human Campylobacter coli infections

Peer reviewedPublisher PD

Precompetitive data sharing as a catalyst to address unmet needs in Parkinson's disease

Parkinson's disease is a complex heterogeneous disorder with urgent need for disease-modifying therapies. Progress in successful therapeutic approaches for PD will require an unprecedented level of collaboration. At a workshop hosted by Parkinson's UK and co-organized by Critical Path Institute's (C-Path) Coalition Against Major Diseases (CAMD) Consortiums, investigators from industry, academia, government and regulatory agencies agreed on the need for sharing of data to enable future success. Government agencies included EMA, FDA, NINDS/NIH and IMI (Innovative Medicines Initiative). Emerging discoveries in new biomarkers and genetic endophenotypes are contributing to our understanding of the underlying pathophysiology of PD. In parallel there is growing recognition that early intervention will be key for successful treatments aimed at disease modification. At present, there is a lack of a comprehensive understanding of disease progression and the many factors that contribute to disease progression heterogeneity. Novel therapeutic targets and trial designs that incorporate existing and new biomarkers to evaluate drug effects independently and in combination are required. The integration of robust clinical data sets is viewed as a powerful approach to hasten medical discovery and therapies, as is being realized across diverse disease conditions employing big data analytics for healthcare. The application of lessons learned from parallel efforts is critical to identify barriers and enable a viable path forward. A roadmap is presented for a regulatory, academic, industry and advocacy driven integrated initiative that aims to facilitate and streamline new drug trials and registrations in Parkinson's disease

Prospectus, September 10, 1980

ARE YOU A \u27REAL STUDENT\u27?; Parkland People; Gamut challenges you; Emergency course offered; Oops!; Stugo hopefuls list qualifications; Kinks wow U of I fans; Coates announces student audtions; Country music is moving up; Women\u27s Program offers self-series; Classifieds; Students are....well, just students; Student disappointed; Correction; Science You Can See: Ask not what Cable T.V. can do for you, ask what you can do for Cable T.V.; B-ball deadline is Sept. 22; Football and tennis are IM openers; PC Datebook; Golfers begin season with win over Danville; After some surprises last week, Fast Freddy is ready; LaBadie confident of his runners; Fast Freddy Contest; Bench Warmer: Cobras show talenthttps://spark.parkland.edu/prospectus_1980/1022/thumbnail.jp

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease

Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children

Genetic factors are important determinants of overweight. We examined whether there are differential effect sizes depending on children's body composition. We analysed data of n = 4,837 children recorded in the Avon Longitudinal Study of Parents and Children (ALSPAC), applying quantile regression with sex- and age-specific standard deviation scores (SDS) of body mass index (BMI) or with body fat mass index and fat-free mass index at 9 years as outcome variables and an "obesity-risk-allele score" based on eight genetic variants known to be associated with childhood BMI as the explanatory variable. The quantile regression coefficients increased with increasing child's BMI-SDS and fat mass index percentiles, indicating larger effects of the genetic factors at higher percentiles. While the associations with BMI-SDS were of similar size in medium and high BMI quantiles (40th percentile and above), effect sizes with fat mass index increased over the whole fat mass index distribution. For example, the fat mass index of a normal-weight (50th percentile) child was increased by 0.13 kg/m(2) (95% confidence interval (CI): 0.09, 0.16) per additional allele, compared to 0.24 kg/m(2) per allele (95% CI: 0.15, 0.32) in children at the 90th percentile. The genetic associations with fat-free mass index were weaker and the quantile regression effects less pronounced than those on fat mass index. Genetic risk factors for childhood overweight appear to have greater effects on fatter children. Interaction of known genetic factors with environmental or unknown genetic factors might provide a potential explanation of these findings