119 resultados para parasitic network
Resumo:
In spite of its relative importance in the economy of many countriesand its growing interrelationships with other sectors, agriculture has traditionally been excluded from accounting standards. Nevertheless, to support its Common Agricultural Policy, for years the European Commission has been making an effort to obtain standardized information on the financial performance and condition of farms. Through the Farm Accountancy Data Network (FADN), every year data are gathered from a rotating sample of 60.000 professional farms across all member states. FADN data collection is not structured as an accounting cycle but as an extensive questionnaire. This questionnaire refers to assets, liabilities, revenues and expenses, and seems to try to obtain a "true and fair view" of the financial performance and condition of the farms it surveys. However, the definitions used in the questionnaire and the way data is aggregated often appear flawed from an accounting perspective. The objective of this paper is to contrast the accounting principles implicit in the FADN questionnaire with generally accepted accounting principles, particularly those found in the IVth Directive of the European Union, on the one hand, and those recently proposed by the International Accounting Standards Committees Steering Committeeon Agriculture in its Draft Statement of Principles, on the other hand. There are two reasons why this is useful. First, it allows to make suggestions how the information provided by FADN could be more in accordance with the accepted accounting framework, and become a more valuable tool for policy makers, farmers, and other stakeholders. Second, it helps assessing the suitability of FADN to become the starting point for a European accounting standard on agriculture.
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In this paper a p--median--like model is formulated to address theissue of locating new facilities when there is uncertainty. Severalpossible future scenarios with respect to demand and/or the travel times/distanceparameters are presented. The planner will want a strategy of positioning thatwill do as ``well as possible'' over the future scenarios. This paper presents a discrete location model formulation to address this P--Medianproblem under uncertainty. The model is applied to the location of firestations in Barcelona.
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We argue the importance both of developing simple sufficientconditions for the stability of general multiclass queueing networks and also of assessing such conditions under a range of assumptions on the weight of the traffic flowing between service stations. To achieve the former, we review a peak-rate stability condition and extend its range of application and for the latter, we introduce a generalisation of the Lu-Kumar network on which the stability condition may be tested for a range of traffic configurations. The peak-rate condition is close to exact when the between-station traffic is light, but degrades as this traffic increases.
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The Network Revenue Management problem can be formulated as a stochastic dynamic programming problem (DP or the\optimal" solution V *) whose exact solution is computationally intractable. Consequently, a number of heuristics have been proposed in the literature, the most popular of which are the deterministic linear programming (DLP) model, and a simulation based method, the randomized linear programming (RLP) model. Both methods give upper bounds on the optimal solution value (DLP and PHLP respectively). These bounds are used to provide control values that can be used in practice to make accept/deny decisions for booking requests. Recently Adelman [1] and Topaloglu [18] have proposed alternate upper bounds, the affine relaxation (AR) bound and the Lagrangian relaxation (LR) bound respectively, and showed that their bounds are tighter than the DLP bound. Tight bounds are of great interest as it appears from empirical studies and practical experience that models that give tighter bounds also lead to better controls (better in the sense that they lead to more revenue). In this paper we give tightened versions of three bounds, calling themsAR (strong Affine Relaxation), sLR (strong Lagrangian Relaxation) and sPHLP (strong Perfect Hindsight LP), and show relations between them. Speciffically, we show that the sPHLP bound is tighter than sLR bound and sAR bound is tighter than the LR bound. The techniques for deriving the sLR and sPHLP bounds can potentially be applied to other instances of weakly-coupled dynamic programming.
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We use network and correspondence analysis to describe the compositionof the research networks in the European BRITE--EURAM program. Our mainfinding is that 27\% of the participants in this program fall into one oftwo sets of highly ``interconnected'' institutions --one centered aroundlarge firms (with smaller firms and research centers providing specializedservices), and the other around universities--. Moreover, these ``hubs''are composed largely of institutions coming from the technologically mostadvanced regions of Europe. This is suggestive of the difficulties of attainingEuropean ``cohesion'', as technically advanced institutions naturally linkwith partners of similar technological capabilities.
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The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.
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The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.
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This work proposes novel network analysis techniques for multivariate time series.We define the network of a multivariate time series as a graph where verticesdenote the components of the process and edges denote non zero long run partialcorrelations. We then introduce a two step LASSO procedure, called NETS, toestimate high dimensional sparse Long Run Partial Correlation networks. This approachis based on a VAR approximation of the process and allows to decomposethe long run linkages into the contribution of the dynamic and contemporaneousdependence relations of the system. The large sample properties of the estimatorare analysed and we establish conditions for consistent selection and estimation ofthe non zero long run partial correlations. The methodology is illustrated with anapplication to a panel of U.S. bluechips.
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Introduction. This paper studies the situation of research on Catalan literature between 1976 and 2003 by carrying out a bibliometric and social network analysis of PhD theses defended in Spain. It has a dual aim: to present interesting results for the discipline and to demonstrate the methodological efficacy of scientometric tools in the humanities, a field in which they are often neglected due to the difficulty of gathering data. Method. The analysis was performed on 151 records obtained from the TESEO database of PhD theses. The quantitative estimates include the use of the UCINET and Pajek software packages. Authority control was performed on the records. Analysis. Descriptive statistics were used to describe the sample and the distribution of responses to each question. Sex differences on key questions were analysed using the Chi-squared test. Results. The value of the figures obtained is demonstrated. The information obtained on the topic and the periods studied in the theses, and on the actors involved (doctoral students, thesis supervisors and members of defence committees), provide important insights into the mechanisms of humanities disciplines. The main research tendencies of Catalan literature are identified. It is observed that the composition of members of the thesis defence committees follows Lotka's Law. Conclusions. Bibliometric analysis and social network analysis may be especially useful in the humanities and in other fields which are lacking in scientometric data in comparison with the experimental sciences.
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A monoclonal antibody CC92 (IgM), raised against a fraction of rat liver enriched in Golgi membranes, recognizes a novel Endo H-resistant 74-kD membrane glycoprotein (gp74). The bulk of gp74 is confined to the cis-Golgi network (CGN). Outside the Golgi gp74 is found in tubulovesicular structures and ER foci. In cells incubated at 37 degrees C the majority of gp74 is segregated from the intermediate compartment (IC) marker p58. However, in cells treated with organelle perturbants such as low temperature, BFA, and [AIF4]- the patterns of the two proteins become indistinguishable. Both proteins are retained in the Golgi complex at 20 degrees C and in the IC at 15 degrees C. Incubation of cells with BFA results in relocation of gp74 to p58 positive IC elements. [AIF4]- induces the redistribution of gp74 from the Golgi to p58-positive vesicles and does not retard the translocation of gp74 to IC elements in cells treated with BFA. Disruption of microtubules by nocodazol results in the rapid disappearance of the Golgi elements stained by gp74 and redistribution of the protein into vesicle-like structures. The responses of gp74 to cell perturbants are in sharp contrast with those of cis/middle and trans-Golgi resident proteins whose location is not affected by low temperatures or [AIF4]-, are translocated to the ER upon addition of BFA, and stay in slow disintegrating Golgi elements in cells treated with nocodazol. The results suggest that gp74 is an itinerant protein that resides most of the time in the CGN and cycles through the ER/IC following the pathway used by p58.
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[cat] L’extensió de les activitats bancàries al segle XIX va ser liderat per alguns grups socials connectats amb el comerç, que van treure profit de la seva experiència i coneixement per estendre la seva influència al voltant del món del crèdit. A la historiografia espanyola, hi ha un conjunt de treballs que s’han centrat en aquesta gent, però en molts pocs casos s’ha fet una classificació que permeti detectar el conjunt de grups econòmics que han liderat el procés de modernització financera de l’Espanya de mitjans del segle XIX. El principal objectiu del treball és l’anàlisi dels grups socials que van formar el Banco de Barcelona entre 1844 i 1854. Aquesta institució va ser important per a la història financera i bancària d’Espanya per ser pionera en la seva activitat creditícia i d’emissió: a més, la seva experiència va servir com a base en la constitució d’un sistema financer modern a Espanya. En una societat com la catalana de mitjans del segle XIX, la confiança era un factor important per explicar la decisió d’invertir. L’aparició de noves companyies i les seves necessitats d’inversió van transformar el comportaments previs. Quin va ser el comportament dels inversors potencials? Va ser el grup que hi havia al voltant del banc el que va ascendir econòmicament en els anys centrals del segle XIX? La resposta és prou clara, els membres del consell d’administració del Banc de Barcelona formaven un grup apart dins dels grups que sorgeixen a l’economia catalana en el seu conjunt.
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The problem of searchability in decentralized complex networks is of great importance in computer science, economy, and sociology. We present a formalism that is able to cope simultaneously with the problem of search and the congestion effects that arise when parallel searches are performed, and we obtain expressions for the average search cost both in the presence and the absence of congestion. This formalism is used to obtain optimal network structures for a system using a local search algorithm. It is found that only two classes of networks can be optimal: starlike configurations, when the number of parallel searches is small, and homogeneous-isotropic configurations, when it is large.
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We propose a procedure for analyzing and characterizing complex networks. We apply this to the social network as constructed from email communications within a medium sized university with about 1700 employees. Email networks provide an accurate and nonintrusive description of the flow of information within human organizations. Our results reveal the self-organization of the network into a state where the distribution of community sizes is self-similar. This suggests that a universal mechanism, responsible for emergence of scaling in other self-organized complex systems, as, for instance, river networks, could also be the underlying driving force in the formation and evolution of social networks.