940 resultados para Complex network. Optimal path. Optimal path cracks


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Enhanced Recovery After Surgery (ERAS) is a multimodal, standardized and evidence-based perioperative care pathway. With ERAS, postoperative complications are significantly lowered, and, as a secondary effect, length of hospital stay and health cost are reduced. The patient recovers better and faster allowing to reduce in addition the workload of healthcare providers. Despite the hospital discharge occurs sooner, there is no increased charge of the outpatient care. ERAS can be safely applied to any patient by a tailored approach. The general practitioner plays an essential role in ERAS by assuring the continuity of the information and the follow-up of the patient.

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Graph theory has provided a key mathematical framework to analyse the architecture of human brain networks. This architecture embodies an inherently complex relationship between connection topology, the spatial arrangement of network elements, and the resulting network cost and functional performance. An exploration of these interacting factors and driving forces may reveal salient network features that are critically important for shaping and constraining the brain's topological organization and its evolvability. Several studies have pointed to an economic balance between network cost and network efficiency with networks organized in an 'economical' small-world favouring high communication efficiency at a low wiring cost. In this study, we define and explore a network morphospace in order to characterize different aspects of communication efficiency in human brain networks. Using a multi-objective evolutionary approach that approximates a Pareto-optimal set within the morphospace, we investigate the capacity of anatomical brain networks to evolve towards topologies that exhibit optimal information processing features while preserving network cost. This approach allows us to investigate network topologies that emerge under specific selection pressures, thus providing some insight into the selectional forces that may have shaped the network architecture of existing human brains.

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In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.

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Historical data about ancient avalanches are scarce in the Pyrenees. Dendrochronology can provide new data about past avalanches and their return period, but up to now little research has been carried out with this purpose. The Aludex project aims to obtain information about the frequency and extent of extreme avalanches, using a dendrochronological and a nivo-meteorological approach. In this paper, we present the results of a dendrochronological study of the Canal del Roc Roig avalanche path which was affected by two extreme avalanches in February 1996. This first dendrochronological study has permitted us to assess the tree-ring signals due to avalanche events in 53 out of 132 dated trees. The trees presented a variety of responses to the 1996 avalanche events. It is shown that the type of tree-ring signal depends on tree age. The methodology has proved successful in detecting the 1996 and 1972 documented avalanche events, and provided outstanding evidence of undocumented past events such as one in 1930.

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Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.

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Tässä työssä tarkastellaan projektiin liittyvää toiminnanohjausta. Tutkimusongelmana on, kuinka toiminnanohjausta voitaisiin kehittää aikataulutuksen avulla. Työn yhtenä tavoitteena on luoda kokonaiskuva aikataulutuksen nykytilanteesta. Toisena tavoitteena on kartoittaa ajankohtaiset ongelmat. Kolmantena tavoitteena on luoda malli aikataulun laatimiselle kalanterin valmistuksessa.Kirjallisuustutkimuksen perusteella luotiin kuva projektiliiketoiminnasta ja projektinhallintaan sisältyvästä aikataulunhallinnasta. Haastattelututkimuksen perusteella luotiin kokonaiskuva projektin aikataulutuksesta ja siihen liittyvistä ongelmista. Tutkimusta täydennettiin analysoimalla erään projektin suunniteltua aikataulua ja toteutunutta aikataulua. Toiminnanohjauksen aikataulutustehtävä on muuttumassa yhä tarkeämmäksi toimittaessa resurssien äärirajoilla. Ajankohtaisia kysymyksiä ovat: toteutusaikataulun laatimistekniikka, projektin osittaminen, optimi suunnittelujärjestys ja kriittinen polku.Tutkimuksen perusteella kehitettiin toteutusaikataulun suunnittelun malli ja malliaikataulu. Mallin keskeiset osat ovat: projektin osittaminen tehtäviin, tärkeimpien tehtävien määrittäminen tarkempaa ohjausta varten, tehtävien välisten riippuvuuksien määrittäminen, tehtävien limitysmahdollisuuksien ja ajallisen keston arviointi, aikataulun esittäminen janakaaviona ja ulkoisten tekijöiden, kuten hankinnan asettamien vaatimusten huomioiminen malliaikataulussa. Malliaikataulua tullaan soveltamaan seuraavaan sopivaan toimitusprojektiin.

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Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

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PURPOSE: Small cell carcinomas of the bladder (SCCB) account for fewer than 1% of all urinary bladder tumors. There is no consensus regarding the optimal treatment for SCCB. METHODS AND MATERIALS: Fifteen academic Rare Cancer Network medical centers contributed SCCB cases. The eligibility criteria were as follows: pure or mixed SCC; local, locoregional, and metastatic stages; and age ≥18 years. The overall survival (OS) and disease-free survival (DFS) were calculated from the date of diagnosis according to the Kaplan-Meier method. The log-rank and Wilcoxon tests were used to analyze survival as functions of clinical and therapeutic factors. RESULTS: The study included 107 patients (mean [±standard deviation, SD] age, 69.6 [±10.6] years; mean follow-up time, 4.4 years) with primary bladder SCC, with 66% of these patients having pure SCC. Seventy-two percent and 12% of the patients presented with T2-4N0M0 and T2-4N1-3M0 stages, respectively, and 16% presented with synchronous metastases. The most frequent curative treatments were radical surgery and chemotherapy, sequential chemotherapy and radiation therapy, and radical surgery alone. The median (interquartile range, IQR) OS and DFS times were 12.9 months (IQR, 7-32 months) and 9 months (IQR, 5-23 months), respectively. The metastatic, T2-4N0M0, and T2-4N1-3M0 groups differed significantly (P=.001) in terms of median OS and DFS. In a multivariate analysis, impaired creatinine clearance (OS and DFS), clinical stage (OS and DFS), a Karnofsky performance status <80 (OS), and pure SCC histology (OS) were independent and significant adverse prognostic factors. In the patients with nonmetastatic disease, the type of treatment (ie radical surgery with or without adjuvant chemotherapy vs conservative treatment) did not significantly influence OS or DFS (P=.7). CONCLUSIONS: The prognosis for SCCB remains poor. The finding that radical cystectomy did not influence DFS or OS in the patients with nonmetastatic disease suggests that conservative treatment is appropriate in this situation.

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This study aimed to determine the number of measurements necessary to evaluate physical and chemical characteristics of peach fruits, study the relationships between them and their direct and indirect effects on the content of ascorbic acid and total carotenoids. The characteristics skin and pulp color, fruit weight, suture, equatorial and polar diameters, firmness, soluble solids (SS), titratable acidity (TA), SS/TA ratio, ascorbic acid and total carotenoids were evaluated in 39 cultivars of peach and 3 cultivars of nectarine from the orchard of the Universidade Federal de Viçosa. The repeatability coefficient was estimated by ANOVA and CPCOR. Phenotypic correlation coefficients (rf) were estimated and, after the multicollinearity diagnostics, they were unfolded to direct and indirect effects of the explanatory variables on the response variable using path analysis. There was agreement on the magnitude of repeatability coefficients obtained by the two methods; however, they varied among the 14 characteristics. The highest correlations were found between FW, SD, ED and PD. Seven fruits are sufficient to evaluate the physical and chemical characteristics of peach with a correlation coefficient of 90%. The characteristics considered in the path diagrams (b* skin, hº skin, b* pulp, hº pulp, ED, PD, FIR, SS, SS/AT and TC) are not the main determinants of the ascorbic acid. The yellow hue of the pulp (hº pulp) has the potential to be used in indirect selection for total carotenoids.

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ABSTRACT The present study aimed at evaluating the heterotic group formation in guava based on quantitative descriptors and using artificial neural network (ANN). For such, we evaluated eight quantitative descriptors. Large genetic variability was found for the eight quantitative traits in the 138 genotypes of guava. The artificial neural network technique determined that the optimal number of groups was three. The grouping consistency was determined by linear discriminant analysis, which obtained classification percentage of the groups, with a value of 86 %. It was concluded that the artificial neural network method is effective to detect genetic divergence and heterotic group formation.

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Motivated by the Chinese experience, we analyze a semi-open economy where the central bank has access to international capital markets, but the private sector has not. This enables the central bank to choose an interest rate different from the international rate. We examine the optimal policy of the central bank by modelling it as a Ramsey planner who can choose the level of domestic public debt and of international reserves. The central bank can improve savings opportunities of credit-constrained consumers modelled as in Woodford (1990). We find that in a steady state it is optimal for the central bank to replicate the open economy, i.e., to issue debt financed by the accumulation of reserves so that the domestic interest rate equals the foreign rate. When the economy is in transition, however, a rapidly growing economy has a higher welfare without capital mobility and the optimal interest rate differs from the international rate. We argue that the domestic interest rate should be temporarily above the international rate. We also find that capital controls can still help reach the first best when the planner has more fiscal instruments.

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Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.

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The second scientific meeting of the European systems genetics network for the study of complex genetic human disease using genetic reference populations (SYSGENET) took place at the Center for Cooperative Research in Biosciences in Bilbao, Spain, December 10-12, 2012. SYSGENET is funded by the European Cooperation in the Field of Scientific and Technological Research (COST) and represents a network of scientists in Europe that use mouse genetic reference populations (GRPs) to identify complex genetic factors influencing disease phenotypes (Schughart, Mamm Genome 21:331-336, 2010). About 50 researchers working in the field of systems genetics attended the meeting, which consisted of 27 oral presentations, a poster session, and a management committee meeting. Participants exchanged results, set up future collaborations, and shared phenotyping and data analysis methodologies. This meeting was particularly instrumental for conveying the current status of the US, Israeli, and Australian Collaborative Cross (CC) mouse GRP. The CC is an open source project initiated nearly a decade ago by members of the Complex Trait Consortium to aid the mapping of multigenetic traits (Threadgill, Mamm Genome 13:175-178, 2002). In addition, representatives of the International Mouse Phenotyping Consortium were invited to exchange ongoing activities between the knockout and complex genetics communities and to discuss and explore potential fields for future interactions.