Holomorphic self-maps of singular rational surfaces

We give a new proof of the classification of normal singular surface germs admitting non-invertible holomorphic self-maps and due to J. Wahl. We then draw an analogy between the birational classification of singular holomorphic foliations on surfaces, and the dynamics of holomorphic maps. Following this analogy, we introduce the notion of minimal holomorphic model for holomorphic maps. We give sufficient conditions which ensure the uniqueness of such a model.Comment: 37 pages. To appear in Publicacions Matematiques

Laplace deconvolution and its application to Dynamic Contrast Enhanced imaging

In the present paper we consider the problem of Laplace deconvolution with noisy discrete observations. The study is motivated by Dynamic Contrast Enhanced imaging using a bolus of contrast agent, a procedure which allows considerable improvement in {evaluating} the quality of a vascular network and its permeability and is widely used in medical assessment of brain flows or cancerous tumors. Although the study is motivated by medical imaging application, we obtain a solution of a general problem of Laplace deconvolution based on noisy data which appears in many different contexts. We propose a new method for Laplace deconvolution which is based on expansions of the convolution kernel, the unknown function and the observed signal over Laguerre functions basis. The expansion results in a small system of linear equations with the matrix of the system being triangular and Toeplitz. The number $m$ of the terms in the expansion of the estimator is controlled via complexity penalty. The advantage of this methodology is that it leads to very fast computations, does not require exact knowledge of the kernel and produces no boundary effects due to extension at zero and cut-off at $T$. The technique leads to an estimator with the risk within a logarithmic factor of $m$ of the oracle risk under no assumptions on the model and within a constant factor of the oracle risk under mild assumptions. The methodology is illustrated by a finite sample simulation study which includes an example of the kernel obtained in the real life DCE experiments. Simulations confirm that the proposed technique is fast, efficient, accurate, usable from a practical point of view and competitive

Laplace deconvolution on the basis of time domain data and its application to Dynamic Contrast Enhanced imaging

In the present paper we consider the problem of Laplace deconvolution with noisy discrete non-equally spaced observations on a finite time interval. We propose a new method for Laplace deconvolution which is based on expansions of the convolution kernel, the unknown function and the observed signal over Laguerre functions basis (which acts as a surrogate eigenfunction basis of the Laplace convolution operator) using regression setting. The expansion results in a small system of linear equations with the matrix of the system being triangular and Toeplitz. Due to this triangular structure, there is a common number $m$ of terms in the function expansions to control, which is realized via complexity penalty. The advantage of this methodology is that it leads to very fast computations, produces no boundary effects due to extension at zero and cut-off at $T$ and provides an estimator with the risk within a logarithmic factor of the oracle risk. We emphasize that, in the present paper, we consider the true observational model with possibly nonequispaced observations which are available on a finite interval of length $T$ which appears in many different contexts, and account for the bias associated with this model (which is not present when $T\rightarrow\infty$). The study is motivated by perfusion imaging using a short injection of contrast agent, a procedure which is applied for medical assessment of micro-circulation within tissues such as cancerous tumors. Presence of a tuning parameter $a$ allows to choose the most advantageous time units, so that both the kernel and the unknown right hand side of the equation are well represented for the deconvolution. The methodology is illustrated by an extensive simulation study and a real data example which confirms that the proposed technique is fast, efficient, accurate, usable from a practical point of view and very competitive.Comment: 36 pages, 9 figures. arXiv admin note: substantial text overlap with arXiv:1207.223

Methodology for Carbon Footprint in Forestry Findings and Ways of Improvement

International audienceClassic methodologies for carbon footprint are made for conventional companies or territories. None is well adapted for entire sectors or parts of sectors, which usually contain numerous and very different companies, such in the forestry. In this work, we proposed a methodology to count GHG emissions for forestry in a region, from harvest preparation to the entrance of industries. We divided forestry in three steps: harvesting, forwarding and transport, for which we listed each GHG emitting process. Then, we applied this methodology in the Auvergne region (FR) and estimated GHG emissions to bring one cubic meter of wood to the industry to an average of 4.7 kgCe; with each step (harvesting, forwarding and transport) causing around a third of it. We also estimated related emissions for different types of wood (timber, industrial wood and fuelwood) and finally, we proposed 32 recommendations to reduce GHG emissions in forestry

Association between fetal DES-exposure and psychiatric disorders in adolescence/adulthood: evidence from a French cohort of 1002 prenatally exposed children

International audienceIn utero diethylstilbestrol (DES) exposure has been demonstrated to be associated with somatic abnormalities in adult men and women. Conversely, the data are contradictory regarding the association with psychological or psychiatric disorders during adolescence and adulthood. This work was designed to determine whether prenatal exposure to DES affects brain development and whether it is associated with psychiatric disorders in male and female adolescents and young adults. HHORAGES Association, a national patient support group, has assembled a cohort of 1280 women who took DES during pregnancy. We obtained questionnaire responses from 529 families, corresponding to 1182 children divided into three groups: Group 1 (n = 180): firstborn children without DES treatment, Group 2 (n = 740): exposed children, and Group 3 (n = 262): children born after a previous pregnancy treated by DES. No psychiatric disorders were reported in Group 1. In Group 2, the incidence of disorders was drastically elevated (83.8%), and in Group 3, the incidence was still elevated (6.1%) compared with the general population. This work demonstrates that prenatal exposure to DES is associated with a high risk of psychiatric disorders in adolescence and adulthood

Comparative Recruitment Dynamics of Alewife and Bloater in Lakes Michigan and Huron

The predictive power of recruitment models often relies on the identification and quantification of external variables, in addition to stock size. In theory, the identification of climatic, biotic, or demographic influences on reproductive success assists fisheries management by identifying factors that have a direct and reproducible influence on the population dynamics of a target species. More often, models are constructed as one‐time studies of a single population whose results are not revisited when further data become available. Here, we present results from stock recruitment models for Alewife Alosa pseudoharengus and Bloater Coregonus hoyi in Lakes Michigan and Huron. The factors that explain variation in Bloater recruitment were remarkably consistent across populations and with previous studies that found Bloater recruitment to be linked to population demographic patterns in Lake Michigan. Conversely, our models were poor predictors of Alewife recruitment in Lake Huron but did show some agreement with previously published models from Lake Michigan. Overall, our results suggest that external predictors of fish recruitment are difficult to discern using traditional fisheries models, and reproducing the results from previous studies may be difficult particularly at low population sizes.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141414/1/tafs0294.pd

L'Université de Salamanque

Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2009-201

Something to Say: Writing for Publication

Publication, if successful, is exhilarating! Aspiring academic scholars recognize the contribution that peer-reviewed publications make to their careers. It identifies their engagement with their discipline. For students, the benefits of publishing a paper include bolstering their levels of confidence and knowledge and demonstrating to them how they can contribute to their chosen profession. However, inexperience can cause trepidations of the unknown or negative emotions when the writing and publication process goes amiss (Devitt, Coad, & Hardicre, 2007; Rew, 2012). Described in this paper is the background, structure, and limitations of a writing workshop the authors initiated during a recent conference. The purpose of the workshop was to aid both academic colleagues and students in publishing articles in peer-reviewed journals. Participants shared their experiences of writing and identified challenges with the writing for publication process. Finally, strategies that could help participants successfully meet their publications goals were identifie

The Effect of Smoking on Kentucky’s Workforce

Excerpt from the Executive Summary: Smoking has been estimated to increase health care costs in the United States by $167.5 billion annually (Xu et al. 2015). In Kentucky, smoking adds$2.5 billion in health care expenditures each year. Most of these costs were paid by public programs such as Medicaid and Medicare. While these costs are significant, they represent only a portion of the costs that smoking imposes on society. Smoking also leads to poorer labor market outcomes. Smokers are more likely to be unemployed, earn lower wages, and die prematurely than non-smokers. These negative labor market effects reduce economic activity and lower tax revenues, adding to the social costs and fiscal impact that smoking imposes. Past research shows that smokers generally earn four to eleven percent less than similar nonsmokers. Some of this wage penalty is due to the negative health consequences of smoking. Smoking can reduce workers’ health, causing them to be less productive, have higher health insurance costs, and incur greater rates of absenteeism. As a result, smokers tend to earn lower wages. However, the wage penalty might also reflect differences between those who decide to smoke and those who do not rather than being caused directly by smoking

The Economic Impact of Diabetes in Kentucky

Excerpt from the Executive Summary: The Kentucky Department of Public Health is responsible for improving the health and safety of Kentucky’s residents by preventing disease and injuries and encouraging healthy lifestyles. The department administers nearly 150 programs that address critical health issues affecting Kentuckians. These programs screen newborns for health problems, prevent the spread of infectious diseases, promote oral health, and provide numerous other services. Diabetes represents a growing health concern for the nation and Kentucky. It is a chronic condition that causes blood sugar levels to rise and contributes to other serious health conditions such as heart and kidney disease. The U.S. Centers for Disease Control and Prevention lists diabetes as the 7th leading cause of death in the nation. The disease imposes significant costs on the country’s economy. The American Diabetes Association estimates that the U.S. spends $237 billion annually on diabetes-related health care. In addition, diabetes also adversely affects the nation’s workforce. As the disease progresses, individuals may find it more difficult to work. This can reduce employment, productivity, wages, and tax revenue. To better understand how diabetes affects Kentucky residents, the Kentucky Department of Public Health contracted with the University of Kentucky’s Center for Business and Economic Research to study the economic impacts of the disease. This study has three main goals: estimate the effect diabetes has on Kentucky’s workforce; estimate the short-run and long-run effects diabetes has on state tax revenues; and examine how prevention and education programs could affect the health of those with diabetes and how they could potentially affect the state’s workforce and tax revenues