Responsibility for regional waste generation: A single region extended input-output analysis with uni-directional trade flows

The paper uses a regional input-output (IO) framework and data derived on waste generation by industry to examine regional accountability for waste generation. In addition to estimating a series of industry output-waste coefficients, the paper considers two methods for waste attribution but focuses first on one (trade endogenised linear attribution system (TELAS)) that permits a greater focus on private and public final consumption as the main exogenous driver of waste generation. Second, the paper uses a domestic technology assumption (DTA) to consider a regional ‘waste footprint’ where local consumption requirements are assumed to be met through domestic production.

An HEI-Disaggregated Input-Output Table for Scotland

This paper describes how the education sector of the Scottish Input-Output tables is disaggregated to identify a separate sector for each of Scotland’s twenty Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input- Output table provides a useful descriptive snapshot of the Scottish economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multi-sectoral, HEI disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.

An HEI-Disaggregated Input-Output Table for Wales

This paper describes how the education sector of the Welsh Input-Output tables is disaggregated to identify a separate sector for each of Wales’s twelve Higher Education Institutions (HEIs). The process draws on accounting and survey data to accurately determine the incomes and expenditures of each institution. In particular we emphasise determining the HEIs incomes source of origin to inform their treatment, as endogenous or exogenous, in subsequent analyses. The HEI-disaggregated Input-Output table provides a useful descriptive snapshot of the Welsh economy and the role of HEIs within it for a particular year, 2006. The table can be used to derive multipliers and conduct various impact studies of each institution or the sector as a whole. The table is furthermore useful to calibrate other multi-sectoral, HEI-disaggregated models of regional economies, including Social Accounting Matrix (SAM) and computable general equilibrium (CGE) models.

Reconocimiento de objetos multi-clase basado en descriptores de forma

Este trabajo presenta un sistema para detectar y clasificar objetos binarios según la forma de éstos. En el primer paso del procedimiento, se aplica un filtrado para extraer el contorno del objeto. Con la información de los puntos de forma se obtiene un descriptor BSM con características altamente descriptivas, universales e invariantes. En la segunda fase del sistema se aprende y se clasifica la información del descriptor mediante Adaboost y Códigos Correctores de Errores. Se han usado bases de datos públicas, tanto en escala de grises como en color, para validar la implementación del sistema diseñado. Además, el sistema emplea una interfaz interactiva en la que diferentes métodos de procesamiento de imágenes pueden ser aplicados.

A multi-purpose grammar generating a multi-scale integrated analysis of Laos

In this study we propose an application of the MuSIASEM approach which is used to provide an integrated analysis of Laos across different scales. With the term “integrated analysis across scales” we mean the generation of a series of packages of quantitative indicators, characterizing the performance of the socioeconomic activities performed in Laos when considering: (i) different hierarchical levels of organization (farming systems described at the level of household, rural villages, regions of Laos, the whole country level); and (ii) different dimensions of analysis (economic dimension, social dimension, ecological dimension, technical dimension). What is relevant in this application is that the information carried out by these different packages of indicators is integrated in a system of accounting which establishes interlinkages across these indicators. This is a essential feature to study sustainability trade-offs and to build more robust scenarios of possible changes. The multi-scale integrated representation presented in this study is based on secondary data (gathered in a three year EU project – SEAtrans and integrated by other available statistical sources) and it is integrated in GIS, when dealing with the spatial representation of Laos. However, even if we use data referring to Laos, the goal of this study is not that of providing useful information about a practical policy issue of Laos, but rather, to illustrate the possibility of using a multipurpose grammar to produce an integrated set of sustainability indicators at three different levels: (i) local; (ii) meso; (iii) macro level. The technical issue addressed is the simultaneous adoption of two multi-level matrices – one referring to a characterization of human activity over a set of different categories, and another referring to a characterization of land uses over the same set of categories. In this way, it becomes possible to explain the characteristics of Laos (an integrated set of indicators defining the performance of the whole country) in relation to the characteristics of the rural Laos and urban Laos. The characteristics of rural Laos, can be explained using the characteristics of three regions defined within Laos (Northern Laos, Central Laos and Southern Laos), which in turn can be defined (using an analogous package of indicators), starting from the characteristics of three main typologies of farming systems found in the regions.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Protein recovery, separation and purification: selection of optimal techniques using an expert system

The paper discusses the utilization of new techniques ot select processes for protein recovery, separation and purification. It describesa rational approach that uses fundamental databases of proteins molecules to simplify the complex problem of choosing high resolution separation methods for multi component mixtures. It examines the role of modern computer techniques to help solving these questions.

Large multi-gene phylogenetic trees of the grasses (Poaceae): progress towards complete tribal and generic level sampling.

In this paper we included a very broad representation of grass family diversity (84% of tribes and 42% of genera). Phylogenetic inference was based on three plastid DNA regions rbcL, matK and trnL-F, using maximum parsimony and Bayesian methods. Our results resolved most of the subfamily relationships within the major clades (BEP and PACCMAD), which had previously been unclear, such as, among others the: (i) BEP and PACCMAD sister relationship, (ii) composition of clades and the sister-relationship of Ehrhartoideae and Bambusoideae + Pooideae, (iii) paraphyly of tribe Bambuseae, (iv) position of Gynerium as sister to Panicoideae, (v) phylogenetic position of Micrairoideae. With the presence of a relatively large amount of missing data, we were able to increase taxon sampling substantially in our analyses from 107 to 295 taxa. However, bootstrap support and to a lesser extent Bayesian inference posterior probabilities were generally lower in analyses involving missing data than those not including them. We produced a fully resolved phylogenetic summary tree for the grass family at subfamily level and indicated the most likely relationships of all included tribes in our analysis.

Gestión de recursos en nodos multi-core de memoria compartida

La gestión de recursos en los procesadores multi-core ha ganado importancia con la evolución de las aplicaciones y arquitecturas. Pero esta gestión es muy compleja. Por ejemplo, una misma aplicación paralela ejecutada múltiples veces con los mismos datos de entrada, en un único nodo multi-core, puede tener tiempos de ejecución muy variables. Hay múltiples factores hardware y software que afectan al rendimiento. La forma en que los recursos hardware (cómputo y memoria) se asignan a los procesos o threads, posiblemente de varias aplicaciones que compiten entre sí, es fundamental para determinar este rendimiento. La diferencia entre hacer la asignación de recursos sin conocer la verdadera necesidad de la aplicación, frente a asignación con una meta específica es cada vez mayor. La mejor manera de realizar esta asignación és automáticamente, con una mínima intervención del programador. Es importante destacar, que la forma en que la aplicación se ejecuta en una arquitectura no necesariamente es la más adecuada, y esta situación puede mejorarse a través de la gestión adecuada de los recursos disponibles. Una apropiada gestión de recursos puede ofrecer ventajas tanto al desarrollador de las aplicaciones, como al entorno informático donde ésta se ejecuta, permitiendo un mayor número de aplicaciones en ejecución con la misma cantidad de recursos. Así mismo, esta gestión de recursos no requeriría introducir cambios a la aplicación, o a su estrategia operativa. A fin de proponer políticas para la gestión de los recursos, se analizó el comportamiento de aplicaciones intensivas de cómputo e intensivas de memoria. Este análisis se llevó a cabo a través del estudio de los parámetros de ubicación entre los cores, la necesidad de usar la memoria compartida, el tamaño de la carga de entrada, la distribución de los datos dentro del procesador y la granularidad de trabajo. Nuestro objetivo es identificar cómo estos parámetros influyen en la eficiencia de la ejecución, identificar cuellos de botella y proponer posibles mejoras. Otra propuesta es adaptar las estrategias ya utilizadas por el Scheduler con el fin de obtener mejores resultados.

The ubiquitin-proteasome system in prostate cancer and its transition to castration resistance.

Prostate cancer is the most common carcinoma in the male population. In its initial stage, the disease is androgen-dependent and responds therapeutically to androgen deprivation treatment but it usually progresses after a few years to an androgen-independent phase that is refractory to hormonal manipulations. The proteasome is a multi-unit protease system that regulates the abundance and function of a significant number of cell proteins, and its inhibition results in cancer cell growth inhibition and apoptosis and is already exploited in the clinic with the use of proteasome inhibitor bortezomib in multiple myeloma. In order to be recognized by the proteasome, a target protein needs to be linked to a chain of the small protein ubiquitin. In this paper, we review the role of ubiquitin-proteasome system (UPS) in androgen receptor-dependent transcription as well as in the castration resistant stage of the disease, and we discuss therapeutic opportunities that UPS inhibition offers in prostate cancer.

Structural decomposition analysis and input-output subsystems: An application to Spanish CO2 emissions

Analysis of gas emissions by the input-output subsystem approach provides detailed insight into pollution generation in an economy. Structural decomposition analysis, on the other hand, identifies the factors behind the changes in key variables over time. Extending the input-output subsystem model to account for the changes in these variables reveals the channels by which environmental burdens are caused and transmitted throughout the production system. In this paper we propose a decomposition of the changes in the components of CO2 emissions captured by an input-output subsystems representation. The empirical application is for the Spanish service sector, and the economic and environmental data are for years 1990 and 2000. Our results show that services increased their CO2 emissions mainly because of a rise in emissions generated by non-services to cover the final demand for services. In all service activities, the decomposed effects show an increase in CO2 emissions due to a decrease in emission coefficients (i.e., emissions per unit of output) compensated by an increase in emissions caused both by the input-output coefficients and the rise in demand for services. Finally, large asymmetries exist not only in the quantitative changes in the CO2 emissions of the various services but also in the decomposed effects of these changes. Keywords: structural decomposition analysis, input-output subsystems, CO2 emissions, service sector.

Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation

This paper presents the Juste-Neige system for predicting the snow height on the ski runs of a resort using a multi-agent simulation software. Its aim is to facilitate snow cover management in order to i) reduce the production cost of artificial snow and to improve the profit margin for the companies managing the ski resorts; and ii) to reduce the water and energy consumption, and thus to reduce the environmental impact, by producing only the snow needed for a good skiing experience. The software provides maps with the predicted snow heights for up to 13 days. On these maps, the areas most exposed to snow erosion are highlighted. The software proceeds in three steps: i) interpolation of snow height measurements with a neural network; ii) local meteorological forecasts for every ski resort; iii) simulation of the impact caused by skiers using a multi-agent system. The software has been evaluated in the Swiss ski resort of Verbier and provides useful predictions.

Molecular Genetic Analysis of Multi-drug Resistance in Indian Isolates of Mycobacterium tuberculosis

A total of 116 isolates from patients attending the out-patient department at the All India Institute of Medical Sciences, New Delhi and the New Delhi Tuberculosis Centre, New Delhi, India were collected. They were analyzed for resistance to drugs prescribed in the treatment for tuberculosis. The drug resistance was initially determined by microbiological techniques. The Bactec 460TB system was employed to determine the type and level of resistance in each isolate. The isolates were further characterized at molecular level. The multi-drug loci corresponding to rpo b, gyr A, kat G were studied for mutation(s) by the polymerase chain reaction-single strand conformational polymorphism (PCR-SSCP) technique. The SSCP positive samples were sequenced to characterize the mutations in rpo b, and gyr A loci. While previously reported mutations in the gyr A and rpo b loci were found to be present, several novel mutations were also scored in the rpo b locus. Interestingly, analysis of the gyr A locus showed the presence of point mutation(s) that could not be detected by PCR-SSCP. Furthermore, rifampicin resistance was found to be an important marker for checking multi-drug resistance (MDR) in clinical isolates of Mycobacterium tuberculosis. This is the first report on molecular genetic analysis of MDR tuberculosis one from India, highlights the increasing incidence of MDR in the Indian isolates of M. tuberculosis.

Multi-segment foot kinematics after total ankle replacement and ankle arthrodesis during relatively long-distance gait.

This study aimed to investigate the influence of ankle osteoarthritis (AOA) treatments, i.e., ankle arthrodesis (AA) and total ankle replacement (TAR), on the kinematics of multi-segment foot and ankle complex during relatively long-distance gait. Forty-five subjects in four groups (AOA, AA, TAR, and control) were equipped with a wearable system consisting of inertial sensors installed on the tibia, calcaneus, and medial metatarsals. The subjects walked 50-m twice while the system measured the kinematic parameters of their multi-segment foot: the range of motion of joints between tibia, calcaneus, and medial metatarsals in three anatomical planes, and the peaks of angular velocity of these segments in the sagittal plane. These parameters were then compared among the four groups. It was observed that the range of motion and peak of angular velocities generally improved after TAR and were similar to the control subjects. However, unlike AOA and TAR, AA imposed impairments in the range of motion in the coronal plane for both the tibia-calcaneus and tibia-metatarsals joints. In general, the kinematic parameters showed significant correlation with established clinical scales (FFI and AOFAS), which shows their convergent validity. Based on the kinematic parameters of multi-segment foot during 50-m gait, this study showed significant improvements in foot mobility after TAR, but several significant impairments remained after AA.

Application of control measures for infections caused by multi-resistant gram-negative bacteria in intensive care unit patients

Multi-resistant gram-negative rods are important pathogens in intensive care units (ICU), cause high rates of mortality, and need infection control measures to avoid spread to another patients. This study was undertaken prospectively with all of the patients hospitalized at ICU, Anesthesiology of the Hospital São Paulo, using the ICU component of the National Nosocomial Infection Surveillance System (NNIS) methodology, between March 1, 1997 and June 30, 1998. Hospital infections occurring during the first three months after the establishment of prevention and control measures (3/1/97 to 5/31/97) were compared to those of the last three months (3/1/98 to 5/31/98). In this period, 933 NNIS patients were studied, with 139 during the first period and 211 in the second period. The overall rates of infection by multi-resistant microorganisms in the first and second periods were, respectively, urinary tract infection: 3.28/1000 patients/day; 2.5/1000 patients/day; pneumonia: 2.10/1000 patients/day; 5.0/1000 patients/day; bloodstream infection: 1.09/1000 patients/day; 2.5/1000 patients/day. A comparison between overall infection rates of both periods (Wilcoxon test) showed no statistical significance (p = 0.067). The use of intervention measures effectively decreased the hospital bloodstream infection rate (p < 0.001), which shows that control measures in ICU can contribute to preventing hospital infections.