COVNET : A cooperative coevolutionary model for evolving artificial neural networks

This paper presents COVNET, a new cooperative coevolutionary model for evolving artificial neural networks. This model is based on the idea of coevolving subnetworks. that must cooperate to form a solution for a specific problem, instead of evolving complete networks. The combination of this subnetwork is part of a coevolutionary process. The best combinations of subnetworks must be evolved together with the coevolution of the subnetworks. Several subpopulations of subnetworks coevolve cooperatively and genetically isolated. The individual of every subpopulation are combined to form whole networks. This is a different approach from most current models of evolutionary neural networks which try to develop whole networks. COVNET places as few restrictions as possible over the network structure, allowing the model to reach a wide variety of architectures during the evolution and to be easily extensible to other kind of neural networks. The performance of the model in solving three real problems of classification is compared with a modular network, the adaptive mixture of experts and with the results presented in the bibliography. COVNET has shown better generalization and produced smaller networks than the adaptive mixture of experts and has also achieved results, at least, comparable with the results in the bibliography

Comparing the Penman-Monteith equation and a modified Jarvis-Stewart model with an artificial neural network to estimate stand-scale transpiration and canopy conductance

The responses of canopy conductance to variation in solar radiation, vapour pressure deficit and soil moisture have been extensively modelled using a Jarvis-Stewart (JS) model. Modelled canopy conductance has then often been used to predict transpiration using the Penman-Monteith (PM) model. We previously suggested an alternative approach in which the JS model is modified to directly estimate transpiration rather than canopy conductance. In the present study we used this alternative approach to model tree water fluxes from an Australian native forest over an annual cycle. For comparative purposes we also modelled canopy conductance and estimated transpiration via the PM model. Finally we applied an artificial neural network as a statistical benchmark to compare the performance of both models. Both the PM and modified JS models were parameterised using solar radiation, vapour pressure deficit and soil moisture as inputs with results that compare well with previous studies. Both models performed comparably well during the summer period. However, during winter the PM model was found to fail during periods of high rates of transpiration. In contrast, the modified JS model was able to replicate observed sapflow measurements throughout the year although it too tended to underestimate rates of transpiration in winter under conditions of high rates of transpiration. Both approaches to modelling transpiration gave good agreement with hourly, daily and total sums of sapflow measurements with the modified JS and PM models explaining 87% and 86% of the variance, respectively. We conclude that these three approaches have merit at different time-scales. © 2009 Elsevier B.V. All rights reserved

A modified Jarvis-Stewart model for predicting stand-scale transpiration of an Australian native forest

Rates of water uptake by individual trees in a native Australian forest were measured on the Liverpool Plains, New South Wales, Australia, using sapflow sensors. These rates were up-scaled to stand transpiration rate (expressed per unit ground area) using sapwood area as the scalar, and these estimates were compared with modelled stand transpiration. A modified Jarvis-Stewart modelling approach (Jarvis 1976), previously used to calculate canopy conductance, was used to calculate stand transpiration rate. Three environmental variables, namely solar radiation, vapour pressure deficit and soil moisture content, plus leaf area index, were used to calculate stand transpiration, using measured rates of tree water use to parameterise the model. Functional forms for the model were derived by use of a weighted non-linear least squares fitting procedure. The model was able to give comparable estimates of stand transpiration to those derived from a second set of sapflow measurements. It is suggested that short-term, intensive field campaigns where sapflow, weather and soil water content variables are measured could be used to estimate annual patterns of stand transpiration using daily variation in these three environmental variables. Such a methodology will find application in the forestry, mining and water resource management industries where long-term intensive data sets are frequently unavailable. © 2007 Springer Science+Business Media B.V

Impact of mental health problems on case fatality in male cancer patients

Background: Although mortality rates are elevated in psychiatric patients relative to their healthy counterparts, little is known about the impact of mental health on survival in people with cancer. / Methods and results: Among 16 498 Swedish men with cancer, survival was worse in those with a history of psychiatric hospital admissions: multiply-adjusted hazard ratio (95% confidence interval) comparing cancer mortality in men with and without psychiatric admissions: 1.59 (1.39, 1.83). / Conclusion: Survival in cancer patients is worse among those with a history of psychiatric disease. The mechanisms underlying this association should be further explored

Predicting Outcome in dogs with Primary Immune-Mediated Hemolytic Anemia: Results of a Multicenter Case Registry

BACKGROUND: Outcome prediction in dogs with immune‐mediated hemolytic anemia (IMHA) is challenging and few prognostic indicators have been consistently identified. OBJECTIVES: An online case registry was initiated to: prospectively survey canine IMHA presentation and management in the British Isles; evaluate 2 previously reported illness severity scores, Canine Hemolytic Anemia Score (CHAOS) and Tokyo and to identify independent prognostic markers. ANIMALS: Data from 276 dogs with primary IMHA across 10 referral centers were collected between 2008 and 2012. METHODS: Outcome prediction by previously reported illness‐severity scores was tested using univariate logistic regression. Independent predictors of death in hospital or by 30‐days after admission were identified using multivariable logistic regression. RESULTS: Purebreds represented 89.1% dogs (n = 246). Immunosuppressive medications were administered to 88.4% dogs (n = 244), 76.1% (n = 210) received antithrombotics and 74.3% (n = 205) received packed red blood cells. Seventy‐four per cent of dogs (n = 205) were discharged from hospital and 67.7% (n = 187) were alive 30‐days after admission. Two dogs were lost to follow‐up at 30‐days. In univariate analyses CHAOS was associated with death in hospital and death within 30‐days. Tokyo score was not associated with either outcome measure. A model containing SIRS‐classification, ASA classification, ALT, bilirubin, urea and creatinine predicting outcome at discharge was accurate in 82% of cases. ASA classification, bilirubin, urea and creatinine were independently associated with death in hospital or by 30‐days. CONCLUSIONS AND CLINICAL IMPORTANCE: Markers of kidney function, bilirubin concentration and ASA classification are independently associated with outcome in dogs with IMHA. Validation of this score in an unrelated population is now warranted

Turning the tables : regions shaping university performance

[EN] This paper straddles the systems of innovation and the economic geography theories that conceptualize universities as engines of regional development and drivers of growth. However, these approaches overlook the heterogeneity of universities in the process of engagement, assuming their equal capacity to contribute to their region. In the view proposed here, not only does the university influence the surrounding region, but also regional characteristics shape university performance. The paper puts into perspective differences between university profiles in Spain based on their strategies and performance, and the scale and scope of the capabilities to contribute to their regionsThis research was supported by the Spanish Ministry of Education through the Formación de Profesorado Universitario (FPU) programme.Sánchez-Barrioluengo, M. (2014). Turning the tables : regions shaping university performance. Regional Studies Regional Science. 1(1):276-285. doi:10.1080/21681376.2014.964299S2762851

Izlučivanje razumljivih logičkih pravila iz neuronskih mreža. Primjena TREPAN algoritma u bioinformatici i kemoinformatici

TREPAN is an algorithm for the extraction of comprehensible rules from trained neural networks. The method has been applied successfully to biological sequence (bioinformatics) problems. It has now been extended to handle chemoinformatics (QSAR) datasets. The method has been shown to have advantages over traditional symbolic rule induction methods such as C5. Results obtained for bioinformatics and chemoinformatics problems using the TREPAN algorithm are presented.TREPAN je algoritam za izlučivanje razumljivih pravila iz neuronskih mreža nakon provedenoga postupka učenja. Metoda je uspješno primjenjivana na probleme u bioinformatici, za analizu bioloških sekvencija. Primjena TREPAN metode sada se proširuje i na analizu skupova podataka u kemoinformatici (QSAR). Pokazano je da metoda ima prednosti u odnosu na uobičajene postupke koji se rabe za indukciju simboličkih pravila poput metode C5. Prikazani su rezultati koji su dobiveni u analizi bioinformatičkih i kemoinformatičkih problema s pomo}u algoritma TREPAN

ACVIM consensus statement on the treatment of immune-mediated hemolytic anemia in dogs

Immune‐mediated hemolytic anemia (IMHA) causes severe anemia in dogs and is associated with considerable morbidity and mortality. Treatment with various immunosuppressive and antithrombotic drugs has been described anecdotally and in previous studies, but little consensus exists among veterinarians as to the optimal regimen to employ and maintain after diagnosis of the disease. To address this inconsistency and provide evidence‐based guidelines for treatment of IMHA in dogs, we identified and extracted data from studies published in the veterinary literature. We developed a novel tool for evaluation of evidence quality, using it to assess study design, diagnostic criteria, explanation of treatment regimens, and validity of statistical methods. In combination with our clinical experience and comparable guidelines for humans afflicted with autoimmune hemolytic anemia, we used the conclusions of this process to make a set of clinical recommendations regarding treatment of IMHA in dogs, which we refined subsequently by conducting several iterations of Delphi review. Additionally, we considered emerging treatments for IMHA in dogs and highlighted areas deserving of future research. Comments were solicited from several professional bodies to maximize clinical applicability before the recommendations were submitted for publication. The resulting document is intended to provide clinical guidelines for management of IMHA in dogs. These guidelines should be implemented pragmatically, with consideration of animal, owner, and veterinary factors that may vary among cases