861 resultados para Network-based analysis


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Studies have revealed abnormalities in resting-state functional connectivity in those with major depressive disorder specifically in areas such as the dorsal anterior cingulate, thalamus, amygdala, the pallidostriatum and subgenual cingulate. However, the effect of antidepressant medications on human brain function is less clear and the effect of these drugs on resting-state functional connectivity is unknown. Forty volunteers matched for age and gender with no previous psychiatric history received either citalopram (SSRI; selective serotonergic reuptake inhibitor), reboxetine (SNRI; selective noradrenergic reuptake inhibitor) or placebo for 7 days in a double-blind design. Using resting-state functional magnetic resonance imaging and seed based connectivity analysis we selected the right nucleus accumbens, the right amygdala, the subgenual cingulate and the dorsal medial prefrontal cortex as seed regions. Mood and subjective experience were also measured before and after drug administration using self-report scales. Despite no differences in mood across the three groups, we found reduced connectivity between the amygdala and the ventral medial prefrontal cortex in the citalopram group and the amygdala and the orbitofrontal cortex for the reboxetine group. We also found reduced striatal-orbitofrontal cortex connectivity in the reboxetine group. These data suggest that antidepressant medications can decrease resting-state functional connectivity independent of mood change and in areas known to mediate reward and emotional processing in the brain. We conclude that hypothesis-driven seed based analysis of resting-state fMRI supports the proposition that antidepressant medications might work by normalising the elevated resting-state functional connectivity seen in depressed patients.

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Single-carrier (SC) block transmission with frequency-domain equalisation (FDE) offers a viable transmission technology for combating the adverse effects of long dispersive channels encountered in high-rate broadband wireless communication systems. However, for high bandwidthefficiency and high power-efficiency systems, the channel can generally be modelled by the Hammerstein system that includes the nonlinear distortion effects of the high power amplifier (HPA) at transmitter. For such nonlinear Hammerstein channels, the standard SC-FDE scheme no longer works. This paper advocates a complex-valued (CV) B-spline neural network based nonlinear SC-FDE scheme for Hammerstein channels. Specifically, We model the nonlinear HPA, which represents the CV static nonlinearity of the Hammerstein channel, by a CV B-spline neural network, and we develop two efficient alternating least squares schemes for estimating the parameters of the Hammerstein channel, including both the channel impulse response coefficients and the parameters of the CV B-spline model. We also use another CV B-spline neural network to model the inversion of the nonlinear HPA, and the parameters of this inverting B-spline model can easily be estimated using the standard least squares algorithm based on the pseudo training data obtained as a natural byproduct of the Hammerstein channel identification. Equalisation of the SC Hammerstein channel can then be accomplished by the usual one-tap linear equalisation in frequency domain as well as the inverse B-spline neural network model obtained in time domain. Extensive simulation results are included to demonstrate the effectiveness of our nonlinear SC-FDE scheme for Hammerstein channels.

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We are looking into variants of a domination set problem in social networks. While randomised algorithms for solving the minimum weighted domination set problem and the minimum alpha and alpha-rate domination problem on simple graphs are already present in the literature, we propose here a randomised algorithm for the minimum weighted alpha-rate domination set problem which is, to the best of our knowledge, the first such algorithm. A theoretical approximation bound based on a simple randomised rounding technique is given. The algorithm is implemented in Python and applied to a UK Twitter mentions networks using a measure of individuals’ influence (klout) as weights. We argue that the weights of vertices could be interpreted as the costs of getting those individuals on board for a campaign or a behaviour change intervention. The minimum weighted alpha-rate dominating set problem can therefore be seen as finding a set that minimises the total cost and each individual in a network has at least alpha percentage of its neighbours in the chosen set. We also test our algorithm on generated graphs with several thousand vertices and edges. Our results on this real-life Twitter networks and generated graphs show that the implementation is reasonably efficient and thus can be used for real-life applications when creating social network based interventions, designing social media campaigns and potentially improving users’ social media experience.

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We develop a new governance perspective on port–hinterland linkages and related port impacts. Many stakeholders in a port’s hinterland now demand tangible economic benefits from port activities, as a precondition for supporting port expansion and infrastructural investments. We use a governance lens to assess this farsighted contracting challenge. We find that most contemporary economic impact assessments of port investment projects pay scant attention to the contractual relationship challenges in port-hinterland relationships. In contrast, we focus explicitly on the spatial distribution of such impacts and the related contractual relationship issues facing port authorities or port users and their stakeholders in the port hinterland. We introduce a new concept, the Port Hinterland Impact (PHI) matrix, which focuses explicitly on the spatial distribution of port impacts and related contractual relationship challenges. The PHI matrix offers insight into port impacts using two dimensions: logistics dedicatedness, as an expression of Williamsonian asset specificity in the sphere of logistics contractual relationships, and geographic reach, with a longer reach typically reflecting the need for more complex contacting to overcome ‘distance’ challenges with external stakeholders. We use the PHI matrix in our empirical, governance-based analysis of contractual relationships between the port authorities in Antwerp and Zeebrugge, and their respective stakeholders.

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In humans, both language and fine motor skills are associated with left-hemisphere specialization, whereas visuospatial skills are associated with right-hemisphere specialization. Individuals with autism spectrum conditions (ASC) show a profile of deficits and strengths that involves these lateralized cognitive functions. Here we test the hypothesis that regions implicated in these functions are atypically rightward lateralized in individuals with ASC and, that such atypicality is associated with functional performance. Participants included 67 male, right-handed adults with ASC and 69 age- and IQ-matched neurotypical males. We assessed group differences in structural asymmetries in cortical regions of interest with voxel-based analysis of grey matter volumes, followed by correlational analyses with measures of language, motor and visuospatial skills. We found stronger rightward lateralization within the inferior parietal lobule and reduced leftward lateralization extending along the auditory cortex comprising the planum temporale, Heschl's gyrus, posterior supramarginal gyrus, and parietal operculum, which was more pronounced in ASC individuals with delayed language onset compared to those without. Planned correlational analyses showed that for individuals with ASC, reduced leftward asymmetry in the auditory region was associated with more childhood social reciprocity difficulties. We conclude that atypical cerebral structural asymmetry is a potential candidate neurophenotype of ASC

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Uncertainty in ocean analysis methods and deficiencies in the observing system are major obstacles for the reliable reconstruction of the past ocean climate. The variety of existing ocean reanalyses is exploited in a multi-reanalysis ensemble to improve the ocean state estimation and to gauge uncertainty levels. The ensemble-based analysis of signal-to-noise ratio allows the identification of ocean characteristics for which the estimation is robust (such as tropical mixed-layer-depth, upper ocean heat content), and where large uncertainty exists (deep ocean, Southern Ocean, sea ice thickness, salinity), providing guidance for future enhancement of the observing and data assimilation systems.

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P>1. Much of the current understanding of ecological systems is based on theory that does not explicitly take into account individual variation within natural populations. However, individuals may show substantial variation in resource use. This variation in turn may be translated into topological properties of networks that depict interactions among individuals and the food resources they consume (individual-resource networks). 2. Different models derived from optimal diet theory (ODT) predict highly distinct patterns of trophic interactions at the individual level that should translate into distinct network topologies. As a consequence, individual-resource networks can be useful tools in revealing the incidence of different patterns of resource use by individuals and suggesting their mechanistic basis. 3. In the present study, using data from several dietary studies, we assembled individual-resource networks of 10 vertebrate species, previously reported to show interindividual diet variation, and used a network-based approach to investigate their structure. 4. We found significant nestedness, but no modularity, in all empirical networks, indicating that (i) these populations are composed of both opportunistic and selective individuals and (ii) the diets of the latter are ordered as predictable subsets of the diets of the more opportunistic individuals. 5. Nested patterns are a common feature of species networks, and our results extend its generality to trophic interactions at the individual level. This pattern is consistent with a recently proposed ODT model, in which individuals show similar rank preferences but differ in their acceptance rate for alternative resources. Our findings therefore suggest a common mechanism underlying interindividual variation in resource use in disparate taxa.

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Em redes de inovação baseadas em trocas de informação, o agente orquestrador se apropria das informações dos atores periféricos, gera inovação e distribui em forma de valor agregado. É sua função promover a estabilidade na rede fazendo com que a mesma tenha taxas não negativas de crescimento. Nos mercados de análise de crédito e fraude, por exemplo, ou bureaus funcionam como agentes orquestradores, concentrando as informações históricas da população que são provenientes de seus clientes e fornecendo produtos que auxiliam na tomada de decisão. Assumindo todas as empresas do ecossistema como agentes racionais, a teoria dos jogos se torna uma ferramenta apropriada para o estudo da precificação dos produtos como mecanismo de promoção da estabilidade da rede. Este trabalho busca identificar a relação de diferentes estruturas de precificação promovidas pelo agente orquestrador com a estabilidade e eficiência da rede de inovação. Uma vez que o poder da rede se dá pela força conjunta de seus membros, a inovação por esta gerada varia de acordo com a decisão isolada de cada agente periférico de contratar o agente orquestrador ao preço por ele estipulado. Através da definição de um jogo teórico simplificado onde diferentes agentes decidem conectar-se ou não à rede nas diferentes estruturas de preços estipuladas pelo agente orquestrador, o estudo analisa as condições de equilíbrio conclui que o equilíbrio de Nash implica em um cenário de estabilidade da rede. Uma conclusão é que, para maximizar o poder de inovação da rede, o preço a ser pago por cada agente para fazer uso da rede deve ser diretamente proporcional ao benefício financeiro auferido pela inovação gerada pela mesma. O estudo apresenta ainda uma simulação computacional de um mercado fictício para demonstração numérica dos efeitos observados. Através das conclusões obtidas, o trabalho cobre uma lacuna da literatura de redes de inovação com agentes orquestradores monopolistas em termos de precificação do uso da rede, servindo de subsídio de tomadores de decisão quando da oferta ou demanda dos serviços da rede.

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VALENTIM, R. A. M. ; MORAIS, A. H. F. ; SOUZA, V. S. V ; ARAUJO JUNIOR, H. B. ; BRANDAO, G. B. ; GUERREIRO, A. M. G. . Rede de Controle em Ambiente Hospitalar: um protocolo multiciclos para automação hospitalar sobre IEEE 802.3 com IGMP Snooping. Revista Ciência e Tecnologia, v. 11, p. 19, 2009

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The Wireless Sensor Networks (WSN) methods applied to the lifting of oil present as an area with growing demand technical and scientific in view of the optimizations that can be carried forward with existing processes. This dissertation has as main objective to present the development of embedded systems dedicated to a wireless sensor network based on IEEE 802.15.4, which applies the ZigBee protocol, between sensors, actuators and the PLC (Programmable Logic Controller), aiming to solve the present problems in the deployment and maintenance of the physical communication of current elevation oil units based on the method Plunger-Lift. Embedded systems developed for this application will be responsible for acquiring information from sensors and control actuators of the devices present at the well, and also, using the Modbus protocol to make this network becomes transparent to the PLC responsible for controlling the production and delivery information for supervisory SISAL

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In this paper artificial neural network (ANN) based on supervised and unsupervised algorithms were investigated for use in the study of rheological parameters of solid pharmaceutical excipients, in order to develop computational tools for manufacturing solid dosage forms. Among four supervised neural networks investigated, the best learning performance was achieved by a feedfoward multilayer perceptron whose architectures was composed by eight neurons in the input layer, sixteen neurons in the hidden layer and one neuron in the output layer. Learning and predictive performance relative to repose angle was poor while to Carr index and Hausner ratio (CI and HR, respectively) showed very good fitting capacity and learning, therefore HR and CI were considered suitable descriptors for the next stage of development of supervised ANNs. Clustering capacity was evaluated for five unsupervised strategies. Network based on purely unsupervised competitive strategies, classic "Winner-Take-All", "Frequency-Sensitive Competitive Learning" and "Rival-Penalize Competitive Learning" (WTA, FSCL and RPCL, respectively) were able to perform clustering from database, however this classification was very poor, showing severe classification errors by grouping data with conflicting properties into the same cluster or even the same neuron. On the other hand it could not be established what was the criteria adopted by the neural network for those clustering. Self-Organizing Maps (SOM) and Neural Gas (NG) networks showed better clustering capacity. Both have recognized the two major groupings of data corresponding to lactose (LAC) and cellulose (CEL). However, SOM showed some errors in classify data from minority excipients, magnesium stearate (EMG) , talc (TLC) and attapulgite (ATP). NG network in turn performed a very consistent classification of data and solve the misclassification of SOM, being the most appropriate network for classifying data of the study. The use of NG network in pharmaceutical technology was still unpublished. NG therefore has great potential for use in the development of software for use in automated classification systems of pharmaceutical powders and as a new tool for mining and clustering data in drug development

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In this work a modification on ANFIS (Adaptive Network Based Fuzzy Inference System) structure is proposed to find a systematic method for nonlinear plants, with large operational range, identification and control, using linear local systems: models and controllers. This method is based on multiple model approach. This way, linear local models are obtained and then those models are combined by the proposed neurofuzzy structure. A metric that allows a satisfactory combination of those models is obtained after the structure training. It results on plant s global identification. A controller is projected for each local model. The global control is obtained by mixing local controllers signals. This is done by the modified ANFIS. The modification on ANFIS architecture allows the two neurofuzzy structures knowledge sharing. So the same metric obtained to combine models can be used to combine controllers. Two cases study are used to validate the new ANFIS structure. The knowledge sharing is evaluated in the second case study. It shows that just one modified ANFIS structure is necessary to combine linear models to identify, a nonlinear plant, and combine linear controllers to control this plant. The proposed method allows the usage of any identification and control techniques for local models and local controllers obtaining. It also reduces the complexity of ANFIS usage for identification and control. This work has prioritized simpler techniques for the identification and control systems to simplify the use of the method

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In the past few years the interest is accomplishing a high accuracy positioning increasing. One of the methods that has been applied by the scientific community is the network based on positioning. By using multiple reference station data, it is possible to obtain centimetric positioning in a larger coverage area, in addition to gain in reliability, availability and integrity of the service. Besides, using this concept, it is possible to model the atmospheric effects (troposphere refraction and ionosphere effect). Another important question concerning this topic is related to the transmission of the network corrections to the users. There are some possibilities for this fact and an efficient one is the Virtual Reference Station (VRS) concept. In the VRS concept, a reference station is generated near to the rover receiver (user). This provides a short baseline and the user has the possibility of using a single frequency receiver to accomplish the relative positioning. In order to test this kind of positioning method, a software has been developed at São Paulo State University. In this paper, the methodology applied to generate the VRS data is described and the VRS quality is analyzed by using the Precise Point Positioning (PPP) method.

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The literature has shown a relation between periodontics and the removable partial denture (RPD), with progressive destruction observed in the support structures. The aim of this study was to clinically assess periodontal condition in users of removal partial denture (RPD), and compare right abutments teeth, indirect abutments and controls before installation and after 1 year, in addition to comparing tooth-supported and tooth mucosa-supported abutments. A total of 50 patients, 32 women and 18 men, mean age of 45 years, took part in the study. The patients were examined by a single examiner at prosthesis installation and after 3, 6, 9 and 12 months. The following were verified at each examination: Probe Depth (PD), Plaque Index (PI), Gingival Index (GI), the amount of Keratinized Mucosa (KM), Gingival Recession (GR) and Dental Mobility (DM); in addition patients received oral hygiene orientation, accompanied by prophylaxis, periodontal scaling and root planing (PSRP), when necessary. Analysis of Variance (ANOVA) with Tukey-Kramer post test was used to assess the dependent variables (PD, PI, KM, GR) of the three groups over time while Friedman s test was used for GI. To assess the outcomes of prosthesis type in the right abutment group, a confidence interval-based analysis was performed. The results showed that the control group was the least compromised in all the variables studied. With respect to development of the groups over time, it was verified that the measures for GR, PD, GI and KM increased from initial examination to 1 year of use in all the groups, but only PI showed a significant increase. There was a non-discriminatory low prevalence of dental mobility. The tooth mucosa-supported prosthesis had significantly higher values for GR, GI and PI and significantly lower ones for KM when compared to tooth-supported. Over time, both types of prostheses showed no significant differences from initial to final examination for the variables GR, PD, KM and GI, with PI significant only for tooth-supported. The results showed that the teeth most involved in RPD design had greater potential of periodontal damage, probably because of greater dental biofilm accumulation. Abutments elements adjacent to the free extremities had less favorable periodontal condition than those adjacent to interpolated spaces, but the use of RPD did not worsen the initial condition

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)