998 resultados para ORGANIC NETWORKS
Resumo:
This paper proposes a novel approach for the analysis of illicit tablets based on their visual characteristics. In particular, the paper concentrates on the problem of ecstasy pill seizure profiling and monitoring. The presented method extracts the visual information from pill images and builds a representation of it, i.e. it builds a pill profile based on the pill visual appearance. Different visual features are used to build different image similarity measures, which are the basis for a pill monitoring strategy based on both discriminative and clustering models. The discriminative model permits to infer whether two pills come from the same seizure, while the clustering models groups of pills that share similar visual characteristics. The resulting clustering structure allows to perform a visual identification of the relationships between different seizures. The proposed approach was evaluated using a data set of 621 Ecstasy pill pictures. The results demonstrate that this is a feasible and cost effective method for performing pill profiling and monitoring.
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A large proportion of the death toll associated with malaria is a consequence of malaria infection during pregnancy, causing up to 200,000 infant deaths annually. We previously published the first extensive genetic association study of placental malaria infection, and here we extend this analysis considerably, investigating genetic variation in over 9,000 SNPs in more than 1,000 genes involved in immunity and inflammation for their involvement in susceptibility to placental malaria infection. We applied a new approach incorporating results from both single gene analysis as well as gene-gene interactionson a protein-protein interaction network. We found suggestive associations of variants in the gene KLRK1 in the single geneanalysis, as well as evidence for associations of multiple members of the IL-7/IL-7R signalling cascade in the combined analysis. To our knowledge, this is the first large-scale genetic study on placental malaria infection to date, opening the door for follow-up studies trying to elucidate the genetic basis of this neglected form of malaria.
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Background: We address the problem of studying recombinational variations in (human) populations. In this paper, our focus is on one computational aspect of the general task: Given two networks G1 and G2, with both mutation and recombination events, defined on overlapping sets of extant units the objective is to compute a consensus network G3 with minimum number of additional recombinations. We describe a polynomial time algorithm with a guarantee that the number of computed new recombination events is within ϵ = sz(G1, G2) (function sz is a well-behaved function of the sizes and topologies of G1 and G2) of the optimal number of recombinations. To date, this is the best known result for a network consensus problem.Results: Although the network consensus problem can be applied to a variety of domains, here we focus on structure of human populations. With our preliminary analysis on a segment of the human Chromosome X data we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. These results have been verified independently using traditional manual procedures. To the best of our knowledge, this is the first recombinations-based characterization of human populations. Conclusion: We show that our mathematical model identifies recombination spots in the individual haplotypes; the aggregate of these spots over a set of haplotypes defines a recombinational landscape that has enough signal to detect continental as well as population divide based on a short segment of Chromosome X. In particular, we are able to infer ancient recombinations, population-specific recombinations and more, which also support the widely accepted 'Out of Africa' model. The agreement with mutation-based analysis can be viewed as an indirect validation of our results and the model. Since the model in principle gives us more information embedded in the networks, in our future work, we plan to investigate more non-traditional questions via these structures computed by our methodology.
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Little attention has been paid so far to the influence of the chemical nature of the substance when measuring δ 15N by elemental analysis (EA)-isotope ratio mass spectrometry (IRMS). Although the bulk nitrogen isotope analysis of organic material is not to be questioned, literature from different disciplines using IRMS provides hints that the quantitative conversion of nitrate into nitrogen presents difficulties. We observed abnormal series of δ 15N values of laboratory standards and nitrates. These unexpected results were shown to be related to the tailing of the nitrogen peak of nitrate-containing compounds. A series of experiments were set up to investigate the cause of this phenomenon, using ammonium nitrate (NH4NO3) and potassium nitrate (KNO3) samples, two organic laboratory standards as well as the international secondary reference materials IAEA-N1, IAEA-N2-two ammonium sulphates [(NH4)2SO4]-and IAEA-NO-3, a potassium nitrate. In experiment 1, we used graphite and vanadium pentoxide (V2O5) as additives to observe if they could enhance the decomposition (combustion) of nitrates. In experiment 2, we tested another elemental analyser configuration including an additional section of reduced copper in order to see whether or not the tailing could originate from an incomplete reduction process. Finally, we modified several parameters of the method and observed their influence on the peak shape, δ 15N value and nitrogen content in weight percent of nitrogen of the target substances. We found the best results using mere thermal decomposition in helium, under exclusion of any oxygen. We show that the analytical procedure used for organic samples should not be used for nitrates because of their different chemical nature. We present the best performance given one set of sample introduction parameters for the analysis of nitrates, as well as for the ammonium sulphate IAEA-N1 and IAEA-N2 reference materials. We discuss these results considering the thermochemistry of the substances and the analytical technique itself. The results emphasise the difference in chemical nature of inorganic and organic samples, which necessarily involves distinct thermochemistry when analysed by EA-IRMS. Therefore, they should not be processed using the same analytical procedure. This clearly impacts on the way international secondary reference materials should be used for the calibration of organic laboratory standards.
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Tillage systems play a significant role in agricultural production throughout Iowa and the Midwest. It has been well documented that increased tillage intensities can reduce soil organic matter in the topsoil due to increased microbial activity and carbon (C ) oxidation. The potential loss of soil organic matter due to tillage operations is much higher for high organic matter soils than low organic matter soils. Tillage effects on soil organic matter can be magnified through soil erosion and loss of soil productivity. Soil organic matter is a natural reservoir for nutrients, buffers against soil erosion, and improves the soil environment to sustain soil productivity. Maintaining soil productivity requires an agriculture management system that maintains or improves soil organic matter content. Combining cropping systems and conservation tillage practices, such as no-tillage, strip-tillage, or ridge-tillage, are proven to be very effective in improving soil organic matter and soil quality.
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We examine the relationship between structural social capital, resource assembly, and firm performance of entrepreneurs in Africa. We posit that social capital primarily composed of kinship or family ties helps the entrepreneur to raise resources, but it does so at a cost. Using data drawn from small firms in Kampala, Uganda, we explore how shared identity among the entrepreneur's social network moderates this relationship. A large network contributed a higher quantity of resources raised, but at a higher cost when shared identity was high. We discuss the implications of these findings for the role of family ties and social capital in resource assembly, with an emphasis on developing economies.
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Evaluating the possible benefits of the introduction of genetically modified (GM) crops must address the issue of consumer resistance as well as the complex regulation that has ensued. In the European Union (EU) this regulation envisions the “co-existence” of GM food with conventional and quality-enhanced products, mandates the labelling and traceability of GM products, and allows only a stringent adventitious presence of GM content in other products. All these elements are brought together within a partial equilibrium model of the EU agricultural food sector. The model comprises conventional, GM and organic food. Demand is modelled in a novel fashion, whereby organic and conventional products are treated as horizontally differentiated but GM products are vertically differentiated (weakly inferior) relative to conventional ones. Supply accounts explicitly for the land constraint at the sector level and for the need for additional resources to produce organic food. Model calibration and simulation allow insights into the qualitative and quantitative effects of the large-scale introduction of GM products in the EU market. We find that the introduction of GM food reduces overall EU welfare, mostly because of the associated need for costly segregation of non-GM products, but the producers of quality-enhanced products actually benefit.
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Background: Mutism and dense retrograde amnesia are found both in organic and dissociative contexts. Moreover, dissociative symptoms may be modulated by right prefrontal activity. A single case, M.R., developed left hemiparesis, mutism and retrograde amnesia after a high-voltage electric shock without evidence of lasting brain lesions. M.R. suddenly recovered from his mutism following a mild brain trauma 2 years later. Methods: M.R.'s neuropsychological pattern and anatomoclinical correlations were studied through (i) language and memory assessment to characterize his deficits, (ii) functional neuroimaging during a standard language paradigm, and (iii) assessment of frontal and left insular connectivity through diffusion tractography imaging and transcranial magnetic stimulation. A control evaluation was repeated after recovery. Findings: M.R. recovered from the left hemiparesis within 90 days of the accident, which indicated a transient right brain impairment. One year later, neurobehavioral, language and memory evaluations strongly suggested a dissociative component in the mutism and retrograde amnesia. Investigations (including MRI, fMRI, diffusion tensor imaging, EEG and r-TMS) were normal. Twenty-seven months after the electrical injury, M.R. had a very mild head injury which was followed by a rapid recovery of speech. However, the retrograde amnesia persisted. Discussion: This case indicates an interaction of both organic and dissociative mechanisms in order to explain the patient's symptoms. The study also illustrates dissociation in the time course of the two different dissociative symptoms in the same patient.
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In this paper, we investigate how the gendered origin of migrant networks (i.e. matrilineal vs. patrilineal) is associated with aspirations to migrate and subsequent migration behavior. Using longitudinal data from the Mexican Family Life Survey (MxFLS), we follow 3,923 married couples across 139 municipalities over the 2002-2005 period. We find that the networks of both the individual and her/his spouse are associated with aspiring to migrate to the United States. However, one’s own network matters most (i.e. matrilineal networks for women and patrilineal networks for men). On the other hand, in terms of behavior, only matrilineal networks predict a subsequent move to the U.S. for men and women/couples, who are assessed jointly. These findings suggest that our understanding of the role of migrant networks in perpetuating male-centered, labor migration does not necessarily translate once a union has formed. We make the case that future work would do well to account for not only the presence and composition of networks, but also their origin, which in certain circumstances may be the most relevant factor.
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The role of albumin in tubular secretion of the organic anions p-aminohippurate (PAH, 21% albumin-bound at 1 microM) and methotrexate (MTX, 55% bound at 1 microM), and of the organic cation N1-methylnicotinamide (NMN, not bound), was investigated in isolated rabbit S2 proximal tubules. PAH or MTX secretory rates were low in the absence of colloids or in the presence of 1 g/dl dextran 40, and were reversibly two- to sevenfold stimulated by either 1 g/dl bovine (BSA, either regular, defatted, and/or dialyzed) or rabbit serum albumin, or by dialyzed native rabbit plasma. NMN secretion was not stimulated by either dextran or albumin. Luminal BSA had no effect, but stimulation of PAH secretion was observed when albumin was present in both lumen and bath. This secretion was BSA concentration-dependent up to a 1 g/dl BSA. Saturation experiments suggested that 1 g/dl BSA may increase PAH apparent affinity for secretion, with no change in its maximum velocity. Albumin appears therefore to facilitate organic anion proximal secretion by an effect unrelated to oncotic pressure or to the extent of organic anion binding.
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This paper lays down some theoretical framework for further research to be made on the subject of how identity of young Slovenian and Catalan users is forming within the social networking website Facebook. The author pursues his interest based on observation of how communicationand thus interaction between users is changing and how this is reflected in everyday practices. In so doing he tries to identify the connections between the individual, society and technology, asthese are more and more interwoven, and we cannot think one without the other in thecontemporary globalised world.
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Nuclear receptors are a major component of signal transduction in animals. They mediate the regulatory activities of many hormones, nutrients and metabolites on the homeostasis and physiology of cells and tissues. It is of high interest to model the corresponding regulatory networks. While molecular and cell biology studies of individual promoters have provided important mechanistic insight, a more complex picture is emerging from genome-wide studies. The regulatory circuitry of nuclear receptor regulated gene expression networks, and their response to cellular signaling, appear highly dynamic, and involve long as well as short range chromatin interactions. We review how progress in understanding the kinetics and regulation of cofactor recruitment, and the development of new genomic methods, provide opportunities but also a major challenge for modeling nuclear receptor mediated regulatory networks.
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Almost 30 years ago, Bayesian networks (BNs) were developed in the field of artificial intelligence as a framework that should assist researchers and practitioners in applying the theory of probability to inference problems of more substantive size and, thus, to more realistic and practical problems. Since the late 1980s, Bayesian networks have also attracted researchers in forensic science and this tendency has considerably intensified throughout the last decade. This review article provides an overview of the scientific literature that describes research on Bayesian networks as a tool that can be used to study, develop and implement probabilistic procedures for evaluating the probative value of particular items of scientific evidence in forensic science. Primary attention is drawn here to evaluative issues that pertain to forensic DNA profiling evidence because this is one of the main categories of evidence whose assessment has been studied through Bayesian networks. The scope of topics is large and includes almost any aspect that relates to forensic DNA profiling. Typical examples are inference of source (or, 'criminal identification'), relatedness testing, database searching and special trace evidence evaluation (such as mixed DNA stains or stains with low quantities of DNA). The perspective of the review presented here is not exclusively restricted to DNA evidence, but also includes relevant references and discussion on both, the concept of Bayesian networks as well as its general usage in legal sciences as one among several different graphical approaches to evidence evaluation.