Differential Responses of Herbivores and Herbivory to Management in Temperate European Beech

Forest management not only affects biodiversity but also might alter ecosystem processes mediated by the organisms, i.e. herbivory the removal of plant biomass by plant-eating insects and other arthropod groups. Aiming at revealing general relationships between forest management and herbivory we investigated aboveground arthropod herbivory in 105 plots dominated by European beech in three different regions in Germany in the sun-exposed canopy of mature beech trees and on beech saplings in the understorey. We separately assessed damage by different guilds of herbivores, i.e. chewing, sucking and scraping herbivores, gall-forming insects and mites, and leaf-mining insects. We asked whether herbivory differs among different forest management regimes (unmanaged, uneven-aged managed, even-aged managed) and among age-classes within even-aged forests. We further tested for consistency of relationships between regions, strata and herbivore guilds. On average, almost 80 of beech leaves showed herbivory damage, and about 6 of leaf area was consumed. Chewing damage was most common, whereas leaf sucking and scraping damage were very rare. Damage was generally greater in the canopy than in the understorey, in particular for chewing and scraping damage, and the occurrence of mines. There was little difference in herbivory among differently managed forests and the effects of management on damage differed among regions, strata and damage types. Covariates such as wood volume, tree density and plant diversity weakly influenced herbivory, and effects differed between herbivory types. We conclude that despite of the relatively low number of species attacking beech; arthropod herbivory on beech is generally high. We further conclude that responses of herbivory to forest management are multifaceted and environmental factors such as forest structure variables affecting in particular microclimatic conditions are more likely to explain the variability in herbivory among beech forest plots.

OCCUPATIONAL CAUSES OF LUNG CANCER IN NEW MEXICO'S ANGLOS AND HISPANICS

Although, elevated risk for lung cancer has been associated with certain industries and occupations in previous studies, the lack of cigarette smoking information in many of these investigations resulted in estimates that could not be adjusted for the effects of smoking. To determine lung cancer risk due to occupation and smoking, for New Mexico's Anglos and Hispanics, a population-based case-control study was conducted. Incident cases diagnosed 1980-1982, and controls from the general population, were interviewed for lifetime occupational and smoking histories. Specific high risk industries and occupations were identified in advance and linked with industrial and occupational codes for hypotheses-testings. Significantly elevated risks were found for welders (RR = 3.5) and underground miners (RR = 2.0) with adjustment for smoking. Because shipbuilding was the industry of employment for only five of the 18 cases who were welders, exposures other than asbestos could be causal agents. Among the underground for only five of the 18 cases who were welders, exposures other than asbestos could be causal agents. Among the underground miners, uranium, copper, lead and zinc, coal, and potash mining industries were represented. Low prevalence of employment in some of the industries and occupations of interest resulted in inconclusive results. ^

Cooperación y conflicto entre empresas, comunidades y gobierno : nuevos movimientos sociales en el caso de Cerro de San Pedro, México

El objetivo de este trabajo es analizar las relaciones de cooperación y conflicto entre una compañía minera y las comunidades, los Nuevos Movimientos Sociales y los tres niveles de gobierno involucrados. La compañía Minera inició operaciones para una mina a cielo abierto de oro y plata con el apoyo de los gobiernos locales, estatales y federal. Los habitantes de estas comunidades apoyados por grupos ambientalistas y Organizaciones No Gubernamentales argumentan que el proyecto contamina las Fuentes de agua fresca además de perturbar el medio ambiente y la ecología de la región. La metodología empleada consistió en un análisis histórico social para determinar, en un estudio exploratorio, las principales variables económicas, políticas, legales, sociales y culturales que inciden en el caso, sobre todo después de la firma del Tratado de Libre Comercio de América del Norte. Los hallazgos de esta investigación contribuyen a explicar las relaciones de cooperación y conflicto entre las empresas multinacionales que operan en las comunidades, a analizar el rol del gobierno en sus tres niveles y de los nuevos movimientos sociales en la conformación de las economías locales bajo procesos de integración económica regional. Los resultados también son de relevancia por sus contribuciones para el entendimiento de procesos de responsabilidad social corporativa de las empresas transnacionales y los procesos de contestación y acción colectiva de los nuevos movimientos sociales en el desarrollo económico y ambiental de las comunidades locales.

Proposal for the Management of temporal and semantic components of Geographic Information

This poster raises the issue of a research work oriented to the storage, retrieval, representation and analysis of dynamic GI, taking into account The ultimate objective is the modelling and representation of the dynamic nature of geographic features, establishing mechanisms to store geometries enriched with a temporal structure (regardless of space) and a set of semantic descriptors detailing and clarifying the nature of the represented features and their temporality. the semantic, the temporal and the spatiotemporal components. We intend to define a set of methods, rules and restrictions for the adequate integration of these components into the primary elements of the GI: theme, location, time [1]. We intend to establish and incorporate three new structures (layers) into the core of data storage by using mark-up languages: a semantictemporal structure, a geosemantic structure, and an incremental spatiotemporal structure. Thus, data would be provided with the capability of pinpointing and expressing their own basic and temporal characteristics, enabling them to interact each other according to their context, and their time and meaning relationships that could be eventually established

Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data

Hoy en día, con la evolución continua y rápida de las tecnologías de la información y los dispositivos de computación, se recogen y almacenan continuamente grandes volúmenes de datos en distintos dominios y a través de diversas aplicaciones del mundo real. La extracción de conocimiento útil de una cantidad tan enorme de datos no se puede realizar habitualmente de forma manual, y requiere el uso de técnicas adecuadas de aprendizaje automático y de minería de datos. La clasificación es una de las técnicas más importantes que ha sido aplicada con éxito a varias áreas. En general, la clasificación se compone de dos pasos principales: en primer lugar, aprender un modelo de clasificación o clasificador a partir de un conjunto de datos de entrenamiento, y en segundo lugar, clasificar las nuevas instancias de datos utilizando el clasificador aprendido. La clasificación es supervisada cuando todas las etiquetas están presentes en los datos de entrenamiento (es decir, datos completamente etiquetados), semi-supervisada cuando sólo algunas etiquetas son conocidas (es decir, datos parcialmente etiquetados), y no supervisada cuando todas las etiquetas están ausentes en los datos de entrenamiento (es decir, datos no etiquetados). Además, aparte de esta taxonomía, el problema de clasificación se puede categorizar en unidimensional o multidimensional en función del número de variables clase, una o más, respectivamente; o también puede ser categorizado en estacionario o cambiante con el tiempo en función de las características de los datos y de la tasa de cambio subyacente. A lo largo de esta tesis, tratamos el problema de clasificación desde tres perspectivas diferentes, a saber, clasificación supervisada multidimensional estacionaria, clasificación semisupervisada unidimensional cambiante con el tiempo, y clasificación supervisada multidimensional cambiante con el tiempo. Para llevar a cabo esta tarea, hemos usado básicamente los clasificadores Bayesianos como modelos. La primera contribución, dirigiéndose al problema de clasificación supervisada multidimensional estacionaria, se compone de dos nuevos métodos de aprendizaje de clasificadores Bayesianos multidimensionales a partir de datos estacionarios. Los métodos se proponen desde dos puntos de vista diferentes. El primer método, denominado CB-MBC, se basa en una estrategia de envoltura de selección de variables que es voraz y hacia delante, mientras que el segundo, denominado MB-MBC, es una estrategia de filtrado de variables con una aproximación basada en restricciones y en el manto de Markov. Ambos métodos han sido aplicados a dos problemas reales importantes, a saber, la predicción de los inhibidores de la transcriptasa inversa y de la proteasa para el problema de infección por el virus de la inmunodeficiencia humana tipo 1 (HIV-1), y la predicción del European Quality of Life-5 Dimensions (EQ-5D) a partir de los cuestionarios de la enfermedad de Parkinson con 39 ítems (PDQ-39). El estudio experimental incluye comparaciones de CB-MBC y MB-MBC con los métodos del estado del arte de la clasificación multidimensional, así como con métodos comúnmente utilizados para resolver el problema de predicción de la enfermedad de Parkinson, a saber, la regresión logística multinomial, mínimos cuadrados ordinarios, y mínimas desviaciones absolutas censuradas. En ambas aplicaciones, los resultados han sido prometedores con respecto a la precisión de la clasificación, así como en relación al análisis de las estructuras gráficas que identifican interacciones conocidas y novedosas entre las variables. La segunda contribución, referida al problema de clasificación semi-supervisada unidimensional cambiante con el tiempo, consiste en un método nuevo (CPL-DS) para clasificar flujos de datos parcialmente etiquetados. Los flujos de datos difieren de los conjuntos de datos estacionarios en su proceso de generación muy rápido y en su aspecto de cambio de concepto. Es decir, los conceptos aprendidos y/o la distribución subyacente están probablemente cambiando y evolucionando en el tiempo, lo que hace que el modelo de clasificación actual sea obsoleto y deba ser actualizado. CPL-DS utiliza la divergencia de Kullback-Leibler y el método de bootstrapping para cuantificar y detectar tres tipos posibles de cambio: en las predictoras, en la a posteriori de la clase o en ambas. Después, si se detecta cualquier cambio, un nuevo modelo de clasificación se aprende usando el algoritmo EM; si no, el modelo de clasificación actual se mantiene sin modificaciones. CPL-DS es general, ya que puede ser aplicado a varios modelos de clasificación. Usando dos modelos diferentes, el clasificador naive Bayes y la regresión logística, CPL-DS se ha probado con flujos de datos sintéticos y también se ha aplicado al problema real de la detección de código malware, en el cual los nuevos ficheros recibidos deben ser continuamente clasificados en malware o goodware. Los resultados experimentales muestran que nuestro método es efectivo para la detección de diferentes tipos de cambio a partir de los flujos de datos parcialmente etiquetados y también tiene una buena precisión de la clasificación. Finalmente, la tercera contribución, sobre el problema de clasificación supervisada multidimensional cambiante con el tiempo, consiste en dos métodos adaptativos, a saber, Locally Adpative-MB-MBC (LA-MB-MBC) y Globally Adpative-MB-MBC (GA-MB-MBC). Ambos métodos monitorizan el cambio de concepto a lo largo del tiempo utilizando la log-verosimilitud media como métrica y el test de Page-Hinkley. Luego, si se detecta un cambio de concepto, LA-MB-MBC adapta el actual clasificador Bayesiano multidimensional localmente alrededor de cada nodo cambiado, mientras que GA-MB-MBC aprende un nuevo clasificador Bayesiano multidimensional. El estudio experimental realizado usando flujos de datos sintéticos multidimensionales indica los méritos de los métodos adaptativos propuestos. ABSTRACT Nowadays, with the ongoing and rapid evolution of information technology and computing devices, large volumes of data are continuously collected and stored in different domains and through various real-world applications. Extracting useful knowledge from such a huge amount of data usually cannot be performed manually, and requires the use of adequate machine learning and data mining techniques. Classification is one of the most important techniques that has been successfully applied to several areas. Roughly speaking, classification consists of two main steps: first, learn a classification model or classifier from an available training data, and secondly, classify the new incoming unseen data instances using the learned classifier. Classification is supervised when the whole class values are present in the training data (i.e., fully labeled data), semi-supervised when only some class values are known (i.e., partially labeled data), and unsupervised when the whole class values are missing in the training data (i.e., unlabeled data). In addition, besides this taxonomy, the classification problem can be categorized into uni-dimensional or multi-dimensional depending on the number of class variables, one or more, respectively; or can be also categorized into stationary or streaming depending on the characteristics of the data and the rate of change underlying it. Through this thesis, we deal with the classification problem under three different settings, namely, supervised multi-dimensional stationary classification, semi-supervised unidimensional streaming classification, and supervised multi-dimensional streaming classification. To accomplish this task, we basically used Bayesian network classifiers as models. The first contribution, addressing the supervised multi-dimensional stationary classification problem, consists of two new methods for learning multi-dimensional Bayesian network classifiers from stationary data. They are proposed from two different points of view. The first method, named CB-MBC, is based on a wrapper greedy forward selection approach, while the second one, named MB-MBC, is a filter constraint-based approach based on Markov blankets. Both methods are applied to two important real-world problems, namely, the prediction of the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors, and the prediction of the European Quality of Life-5 Dimensions (EQ-5D) from 39-item Parkinson’s Disease Questionnaire (PDQ-39). The experimental study includes comparisons of CB-MBC and MB-MBC against state-of-the-art multi-dimensional classification methods, as well as against commonly used methods for solving the Parkinson’s disease prediction problem, namely, multinomial logistic regression, ordinary least squares, and censored least absolute deviations. For both considered case studies, results are promising in terms of classification accuracy as well as regarding the analysis of the learned MBC graphical structures identifying known and novel interactions among variables. The second contribution, addressing the semi-supervised uni-dimensional streaming classification problem, consists of a novel method (CPL-DS) for classifying partially labeled data streams. Data streams differ from the stationary data sets by their highly rapid generation process and their concept-drifting aspect. That is, the learned concepts and/or the underlying distribution are likely changing and evolving over time, which makes the current classification model out-of-date requiring to be updated. CPL-DS uses the Kullback-Leibler divergence and bootstrapping method to quantify and detect three possible kinds of drift: feature, conditional or dual. Then, if any occurs, a new classification model is learned using the expectation-maximization algorithm; otherwise, the current classification model is kept unchanged. CPL-DS is general as it can be applied to several classification models. Using two different models, namely, naive Bayes classifier and logistic regression, CPL-DS is tested with synthetic data streams and applied to the real-world problem of malware detection, where the new received files should be continuously classified into malware or goodware. Experimental results show that our approach is effective for detecting different kinds of drift from partially labeled data streams, as well as having a good classification performance. Finally, the third contribution, addressing the supervised multi-dimensional streaming classification problem, consists of two adaptive methods, namely, Locally Adaptive-MB-MBC (LA-MB-MBC) and Globally Adaptive-MB-MBC (GA-MB-MBC). Both methods monitor the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a drift is detected, LA-MB-MBC adapts the current multi-dimensional Bayesian network classifier locally around each changed node, whereas GA-MB-MBC learns a new multi-dimensional Bayesian network classifier from scratch. Experimental study carried out using synthetic multi-dimensional data streams shows the merits of both proposed adaptive methods.

Concesión de explotación de granitos derivada del permiso de investigación “Honor de Miengo”

Este proyecto tiene por objeto el estudio de la viabilidad, tanto económica como técnica, de la apertura y explotación de una cantera de granito para su uso como roca ornamental. Para ello se ha seleccionado una zona de potencial interés en Santa Olalla del Cala (Huelva) debido a los afloramientos y la tonalidad de los mismos. En esta zona se ha realizado un estudio del medio físico y una investigación sobre los tipos de roca existentes en la superficie que comprende el Permiso de Investigación de la compañía minera Canteras Extremeñas S.L. Con todo ello, se han determinado varias áreas de interés en las que se podría realizar el emplazamiento de la cantera. Desde el punto de vista técnico, se ha definido el diseño de la cantera optando por un método de explotación combinando el Método Finlandés con el corte con hilo diamantado, proyectando a su vez una zona de emplazamiento para la futura escombrera temporal, teniendo en cuenta la realización de un estudio de impacto ambiental, plan de restauración, plan de vigilancia ambiental, explosivos y previsión de ejecución de las labores. El estudio realizado de los indicadores económicos nos muestra que el proyecto es rentable, con todo ello se concluye que, tanto técnica como económicamente, la explotación del recurso minero es viable. ABSTRACT This project aims to study the feasibility, both economic and technical, to the opening and operation of a granite quarry for use as an ornamental stone. For this we have selected an area of potential interest in Santa Olalla del Cala (Huelva) due to upwelling and tonality of these. In this area, it has made a study of the physical environment and an investigation into the types of rock on the surface comprising the Research Permit of the mining company Canteras Extremeñas SL. With all this, we have identified several areas of interest in which they could make the location of the quarry. From the technical point of view, we have defined the design of the quarry opting for a mining method combining the Finnish Method with the diamond wire cutting, projecting turn an area of the site for future temporal tip, taking into account the completion of an environmental impact, restoration plan, environmental monitoring plan, explosives and forecasting operations execution. The study of economic indicators shows that the project is profitable, yet it can be concluded that, both technically and economically, exploitation of mineral resources is viable.

Exploring the link between sustainability reporting and sustainability management: a conceptual framework.

Sustainability managementand Sustainability Reporting (SR) practices have dramatically increased during the last two decades, raising important questions about the relationship between internal practices and external communication. Previous literature on SR has almost exclusively highlighted the role of institutional and stakeholder pressures in driving its adoption. However, as surveys among reporters also identify internal benefits of SR, its full role for company-level sustainability management remains unclear. In order to address this question, we develop a framework accounting for four SR configurations, stemming from different levels of relative importance of external and internal motives for SR. A multiple case study involving four large Spanish companies serves to illustrate the framework and to identify company-level factors that act both as enablers and barriers of SR internal relevance. We conclude that motivations for SR, along with such internal factors, decisively influence its contribution to sustainability management.

Changes in global gene expression patterns during development and maturation of the rat kidney

We set out to define patterns of gene expression during kidney organogenesis by using high-density DNA array technology. Expression analysis of 8,740 rat genes revealed five discrete patterns or groups of gene expression during nephrogenesis. Group 1 consisted of genes with very high expression in the early embryonic kidney, many with roles in protein translation and DNA replication. Group 2 consisted of genes that peaked in midembryogenesis and contained many transcripts specifying proteins of the extracellular matrix. Many additional transcripts allied with groups 1 and 2 had known or proposed roles in kidney development and included LIM1, POD1, GFRA1, WT1, BCL2, Homeobox protein A11, timeless, pleiotrophin, HGF, HNF3, BMP4, TGF-α, TGF-β2, IGF-II, met, FGF7, BMP4, and ganglioside-GD3. Group 3 consisted of transcripts that peaked in the neonatal period and contained a number of retrotransposon RNAs. Group 4 contained genes that steadily increased in relative expression levels throughout development, including many genes involved in energy metabolism and transport. Group 5 consisted of genes with relatively low levels of expression throughout embryogenesis but with markedly higher levels in the adult kidney; this group included a heterogeneous mix of transporters, detoxification enzymes, and oxidative stress genes. The data suggest that the embryonic kidney is committed to cellular proliferation and morphogenesis early on, followed sequentially by extracellular matrix deposition and acquisition of markers of terminal differentiation. The neonatal burst of retrotransposon mRNA was unexpected and may play a role in a stress response associated with birth. Custom analytical tools were developed including “The Equalizer” and “eBlot,” which contain improved methods for data normalization, significance testing, and data mining.

Evaluation of the usability and benefits of twist wire GMAW and FACW narrow gap welding /

"March 1988."

Weston-Waterville, Havre-Waterville and Waterville-Canso cables repair expeditions for the Commercial Cable Coy. : 1901-1903 : C.S.S. "Buccaneer".

On cover: no. 6.

USCG group control and communications system study /

Final report; January 1979.

Report to the President by the Emergency Board created June 23, 1948 by Executive order 9971 pursuant to Section 10 of the Railway Labor Act : to investigate and report upon a dispute between the Grand Trunk Western Railroad Co., Chesapeake and Ohio Railway Co., Wabash Railroad and the Ann Arbor Railroad Co. and certain of its employees represented by the National Maritime Union of America, N.M.B. cases A-2801, A-2802, A-2803, A-2804, Detroit, Michigan, July 20, 1948.

Signed: Robert G. Simmons, chairman, Thomas F. Gallagher, member, Joseph L. Miller, member.

Troy and Greenfield Railroad : speech of Hon. Alvah Crocker, on the bill for the more speedy completion of the Troy and Greenfield Railroad, in the Senate of Massachusetts, April 15, 1862.

At head of title: Troy and Greenfield Railroad.

Report on the Brunswick canal and rail road, Glynn County, Georgia. With an appendix containing the charter and commissioners's report.

Mode of access: Internet.

Report of Messrs. Benj. Wright and J. L. Sullivan, engineers, engaged in the survey of the route of the proposed canal,

Pages [57]-70 contain: "An act to incorporate the president, managers and company, of the Delaware and Hudson Canal Company.