Automatic Small Bowel Tumor Diagnosis by Using Multi-Scale Wavelet-Based Analysis in Wireless Capsule Endoscopy Images

BACKGROUND: Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. METHOD: The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. RESULTS: The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Analysis and simulation of social unrest in Europe: towards understanding social unrest in Europe

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies

Analysis of output properties of the Peroxiredoxin/Thioredoxin/Thioredoxin reductase system

Dissertação de mestrado em Bioinformática

Composition of Greenhouse Gas Emissions in Spain: an Input-Output Analysis

Extending the traditional input-output model to account for the environmental impacts of production processes reveals the channels by which environmental burdens are transmitted throughout the economy. In particular, the environmental input-output approach is a useful technique for quantifying the changes in the levels of greenhouse emissions caused by changes in the final demand for production activities. The inputoutput model can also be used to determine the changes in the relative composition of greenhouse gas emissions due to exogenous inflows. In this paper we describe a method for evaluating how the exogenous changes in sectorial demand, such as changes in private consumption, public consumption, investment and exports, affect the relative contribution of the six major greenhouse gases regulated by the Kyoto Protocol to total greenhouse emissions. The empirical application is for Spain, and the economic and environmental data are for the year 2000. Our results show that there are significant differences in the effects of different sectors on the composition of greenhouse emissions. Therefore, the final impact on the relative contribution of pollutants will basically depend on the activity that receives the exogenous shock in final demand, because there are considerable differences in the way, and the extent to which, individual activities affect the relative composition of greenhouse gas emissions. Keywords: Greenhouse emissions, composition of emissions, sectorial demand, exogenous shock.

An input-output analysis of the "key" sectors in CO2 emissions from a production perspective: an application to the spanish economy

Here we present an approach that allows the identification of the "key" productive sectors responsible for CO2 emission. For this purpose, we develop an input–output methodology from a supply perspective. We focus on the impact of an increase in the value-added of the different productive sectors on total CO2 emissions and we identify the productive sectors responsible for the increase in CO2 emissions when there is an increase in the income of the economy. The approach shows the contribution of the various sectors to CO2 emission from a production perspective and allows us to identify the sectors that deserve more consideration for mitigation policies. This analysis is complementary to the input–output analysis from a demand perspective. The methodology is applied to the Spanish economy.

Economic impacts of alternative water policy scenarios in the Spanish production system: an input-output analysis

The objective of this paper is to analyse the economic impacts of alternative water policies implemented in the Spanish production system. The methodology uses two versions of the input-output price model: a competitive formulation and a mark-up formulation. The input-output framework evaluates the impact of water policy measures on production prices, consumption prices, intermediate water demand and private welfare. Our results show that a tax on the water used by sectors considerably reduces the intermediate water demand, and increases the production and consumption prices. On the other hand, according to Jevons' paradox, an improvement in technical efficiency, which leads to a reduction in the water requirements of all sectors and an increase in water production, increases the amount of water consumed. The combination of a tax on water and improved technical efficiency takes the pressure off prices and significantly reduces intermediate water demand. JEL Classification: C67 ; D57 ; Q25. Keywords: Production prices; Consumption prices; Water uses; Water policy; Water taxation.

Economic impact of alternative policy measures implemented on the energy activities of the Catalan production system: an input-output analysis

The aim of the paper is to analyse the economic impact of alternative policies implemented on the energy activities of the Catalan production system. Specifically, we analyse the effects of a tax on intermediate energy uses, a reduction in the final production of energy, and a reduction in intermediate energy uses. The methodology involves two versions of the input-output price model: a competitive price formulation and a mark-up price formulation. The input-output price framework will make it possible to evaluate how the alternative measures modify production prices, consumption prices, private welfare, and intermediate energy uses. The empirical application is for the Catalan economy and uses economic data for the year 2001.

An interregional input-output analysis of the pollution content of trade flows and environmental trade balances between five states in the US Mid-West

In this paper we attempt an empirical application of the multi-region input-output (MRIO) method in order to enumerate the pollution content of interregional trade flows between five Mid-West regions/states in the US –Illinois, Indiana, Iowa, Michigan and Wisconsin – and the rest of the US. This allows us to analyse some very important issues in terms of the nature and significance of interregional environmental spillovers within the US Mid-West and the existence of pollution ‘trade balances’ between states. Our results raise questions in terms of the extent to which authorities at State level can control local emissions where they are limited in the way some emissions can be controlled, particularly with respect to changes in demand elsewhere in the Mid-West and US. This implies a need for policy co-ordination between national and state level authorities in the US to meet emissions reductions targets. The existence of an environmental trade balances between states also raises issues in terms of net losses/gains in terms of pollutants as a result of interregional trade within the US and whether, if certain activities can be carried out using less polluting technology in one region relative to others, it is better for the US as a whole if this type of relationship exists.

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.

Okun’s law – A meta analysis

This paper seeks to identify whether there is a representative empirical Okun’s Law coefficient (OLC) and to measure its size. We carry out a meta regression analysis on a sample of 269 estimates of the OLC to uncover reasons for differences in empirical results and to estimate the ‘true’ OLC. On statistical (and other) grounds, we find it appropriate to investigate two separate subsamples, using respectively (some measure of) unemployment or output as dependent variable. Our results can be summarized as follows. First, there is evidence of type II publication bias in both sub-samples, but a type I bias is present only among the papers using some measure of unemployment as the dependent variable. Second, after correction for publication bias, authentic and statistically significant OLC effects are present in both sub-samples. Third, bias-corrected estimated true OLCs are significantly lower (in absolute value) with models using some measure of unemployment as the dependent variable. Using a bivariate MRA approach, the estimated true effects are -0.25 for the unemployment sub-sample and -0.61 for the output-sub sample; with a multivariate MRA methodology, the estimated true effects are -0.40 and -1.02 for the unemployment and the output-sub samples respectively.

Modular analysis of gene expression data with R.

SUMMARY: Large sets of data, such as expression profiles from many samples, require analytic tools to reduce their complexity. The Iterative Signature Algorithm (ISA) is a biclustering algorithm. It was designed to decompose a large set of data into so-called 'modules'. In the context of gene expression data, these modules consist of subsets of genes that exhibit a coherent expression profile only over a subset of microarray experiments. Genes and arrays may be attributed to multiple modules and the level of required coherence can be varied resulting in different 'resolutions' of the modular mapping. In this short note, we introduce two BioConductor software packages written in GNU R: The isa2 package includes an optimized implementation of the ISA and the eisa package provides a convenient interface to run the ISA, visualize its output and put the biclusters into biological context. Potential users of these packages are all R and BioConductor users dealing with tabular (e.g. gene expression) data. AVAILABILITY: http://www.unil.ch/cbg/ISA CONTACT: sven.bergmann@unil.ch

Necessary and sufficient conditions for robust stability using modal intervals

In this paper, robustness of parametric systems is analyzed using a new approach to interval mathematics called Modal Interval Analysis. Modal Intervals are an interval extension that, instead of classic intervals, recovers some of the properties required by a numerical system. Modal Interval Analysis not only simplifies the computation of interval functions but allows semantic interpretation of their results. Necessary, sufficient and, in some cases, necessary and sufficient conditions for robust performance are presented

Analysis of GPCR properties of Frizzled receptors and establishment of the "in vitro" platform for screening of Frizzled agonists/antagonists as potential therapeutic agents

Morphogens of the Wnt protein family are the secreted lipoglycoprotein ligands which initiate several pathways heavily involved in the coordination of various developmental stages of organisms in the majority of animal species. Deregulation of these pathways in the adult leads to formation and sustaining of multiple types of cancer. The latter notion is reinforced by the fact that the very discovery of the first Wnt ligand was due to its role as the causative factor of carcinogenic transformation (Nusse and Varmus, 1982). Nowadays our knowledge on Wnt signaling has "moved with the times" and these pathways were identified to be often crucial for tumor formation, its interactions with the microenvironment, and promotion of the metastases (Huang and Du, 2008; Zerlin et al., 2008; Jessen, 2009). Thus the relevance of the pathway as the target for drug development has further increased in the light of modern paradigms of the complex cancer treatments which target also spreading and growth- promoting factors of tumors by specific and highly efficient substances (Pavet et al., 2010). Presently the field of the Wnt-targeting drug research is almost solely dominated by assays based on transcriptional activation induced by the signaling. This approach resulted in development of a number of promising substances (Lee et al., 2011). Despite its effectiveness, the method nevertheless suffers from several drawbacks. Among the major ones is the fact that this approach is prone to identify compounds targeting rather downstream effectors of the pathway, which are indiscriminately used by all the subtypes of the Wnt signaling. Additionally, proteins which are involved in several signaling cascades and not just the Wnt pathway turn out as targets of the new compounds. These issues increase risks of side effects due to off-target interactions and blockade of the pathway in healthy cells. In the present work we put forward a novel biochemical approach for drug development on the Wnt pathway. It targets Frizzleds (Fzs) - a family of 7-transmbembrane proteins which serve as receptors for Wnt ligands. They offer unique properties for the development of highly specific and effective drugs as they control all branches of the Wnt signaling. Recent advances in the understanding of the roles of heterotrimeric G proteins downstream from Fzs (Katanaev et al., 2005; Liu et al., 2005; Jernigan et al., 2010) suggest application of enzymatic properties of these effectors to monitor the receptor-mediated events. We have applied this knowledge in practice and established a specific and efficient method based on utilization of a novel high-throughput format of the GTP-binding assay to follow the activation of Fzs. This type of assay is a robust and well-established technology for the research and screenings on the GPCRs (Harrison and Traynor, 2003). The conventional method of detection involves the radioactively labeled non-hydrolysable GTP analog [35S]GTPyS. Its application in the large-scale screenings is however problematic which promoted development of the novel non-radioactive GTP analog GTP-Eu. The new molecule employs phenomenon of the time-resolved fluorescence to provide sensitivity comparable to the conventional radioactive substance. Initially GTP-Eu was tested only in one of many possible types of GTP-binding assays (Frang et al., 2003). In the present work we expand these limits by demonstrating the general comparability of the novel label with the radioactive method in various types of assays. We provide a biochemical characterization of GTP-Eu interactions with heterotrimeric and small GTPases and a comparative analysis of the behavior of the new label in the assays involving heterotrimeric G protein effectors. These developments in the GTP-binding assay were then applied to monitor G protein activation by the Fz receptors. The data obtained in mammalian cultured cell lines provides for the first time an unambiguous biochemical proof for direct coupling of Fzs with G proteins. The specificity of this interaction has been confirmed by the experiments with the antagonists of Fz and by the pertussis toxin-mediated deactivation. Additionally we have identified the specificity of Wnt3a towards several members of the Fz family and analyzed the properties of human Fz-1 which was found to be the receptor coupled to the Gi/o family of G proteins. Another process playing significant role in the functioning of every GPCR is endocytosis. This phenomenon can also be employed for drug screenings on GPCRs (Bickle, 2010). In the present work we have demonstrated that Drosophila Fz receptors are involved in an unusual for many GPCRs manifestation of the receptor-mediated internalization. Through combination of biochemical approaches and studies on Drosophila as the model organism we have shown that direct interactions of the Fzs and the α-subunit of the heterotrimeric G protein Go with the small GTPase Rab5 regulate internalization of the receptor in early endosomes. We provide data uncovering the decisive role of this self-promoted endocytosis in formation of a proper signaling output in the canonical as well as planar cell polarity (PCP) pathways regulated by Fz. The results of this work thus establish a platform for the high-throughput screening to identify substances active in the cancer-related Wnt pathways. This methodology has been adjusted and applied to provide the important insights in Fz functioning and will be instrumental for further investigations on the Wnt-mediated pathways.

Economic and environmental effects of the CO2 taxation: an input-output analysis for Spain

CO2 emissions induced by human activities are the major cause of climate change; hence, strong environmental policy that limits the growing dependence on fossil fuel is indispensable. Tradable permits and environmental taxes are the usual tools used in CO2 reduction strategies. Such economic tools provide incentives to polluting industries to reduce their emissions through market signals. The aim of this work is to investigate the direct and indirect effects of an environmental tax on Spanish products and services. We apply an environmentally extended input-output (EIO) model to identify CO2 emission intensities of products and services and, accordingly, we estimate the tax proportional to these intensities. The short-term price effects are analyzed using an input-output price model. The effect of tax introduction on consumption prices and its influence on consumers’ welfare are determined. We also quantify the environmental impacts of such taxation in terms of the reduction in CO2 emissions. The results, based on the Spanish economy for the year 2007, show that sectors with relatively poor environmental profile are subjected to high environmental tax rates. And consequently, applying a CO2 tax on these sectors, increases production prices and induces a slight increase in consumer price index and a decrease in private welfare. The revenue from the tax could be used to counter balance the negative effects on social welfare and also to stimulate the increase of renewable energy shares in the most impacting sectors. Finally, our analysis highlights that the environmental and economic goals cannot be met at the same time with the environmental taxation and this shows the necessity of finding other (complementary or alternative) measures to ensure both the economic and ecological efficiencies. Keywords: CO2 emissions; environmental tax; input-output model, effects of environmental taxation.

The Impact of Industry Collaboration on Academic Research Output: A Dynamic Panel Data Analysis

The aim of this paper is to analyse the impact of university knowledge and technology transfer activities on academic research output. Specifically, we study whether researchers with collaborative links with the private sector publish less than their peers without such links, once controlling for other sources of heterogeneity. We report findings from a longitudinal dataset on researchers from two engineering departments in the UK between 1985 until 2006. Our results indicate that researchers with industrial links publish significantly more than their peers. Academic productivity, though, is higher for low levels of industry involvement as compared to high levels.