Multi-sensory treatment for children with developmental motor speech disorders

What this paper adds? What is already known on the subject? Multi-sensory treatment approaches have been shown to impact outcome measures positively, such as accuracy of speech movement patterns and speech intelligibility in adults with motor speech disorders, as well as in children with apraxia of speech, autism and cerebral palsy. However, there has been no empirical study using multi-sensory treatment for children with speech sound disorders (SSDs) who demonstrate motor control issues in the jaw and orofacial structures (e.g. jaw sliding, jaw over extension, inadequate lip rounding/retraction and decreased integration of speech movements). What this paper adds? Findings from this study indicate that, for speech production disorders where both the planning and production of spatiotemporal parameters of movement sequences for speech are disrupted, multi-sensory treatment programmes that integrate auditory, visual and tactile–kinesthetic information improve auditory and visual accuracy of speech production. The training (practised in treatment) and test words (not practised in treatment) both demonstrated positive change in most participants, indicating generalization of target features to untrained words. It is inferred that treatment that focuses on integrating multi-sensory information and normalizing parameters of speech movements is an effective method for treating children with SSDs who demonstrate speech motor control issues.

Abrupt transitions in the NAO control of explosive North Atlantic cyclone development

Explosive cyclones are intense extra-tropical low pressure systems featuring large deepening rates. In the Euro-Atlantic sector, they are a major source of life-threatening weather impacts due to their associated strong wind gusts, heavy precipitation and storm surges. The wintertime variability of the North Atlantic cyclonic activity is primarily modulated by the North Atlantic Oscillation (NAO). In this study, we investigate the interannual and multi-decadal variability of explosive North Atlantic cyclones using track density data from two reanalysis datasets (NCEP and ERA-40) and a control simulation of an atmosphere/ocean coupled General Circulation Model (GCM—ECHAM5/MPIOM1). The leading interannual and multi-decadal modes of variability of explosive cyclone track density are characterized by a strengthening/weakening pattern between Newfoundland and Iceland, which is mainly modulated by the NAO at both timescales. However, the NAO control of interannual cyclone variability is not stationary in time and abruptly fluctuates during periods of 20–25 years long both in NCEP and ECHAM5/MPIOM1. These transitions are accompanied by structural changes in the leading mode of explosive cyclone variability, and by decreased/enhanced baroclinicity over the sub-polar/sub-tropical North Atlantic. The influence of the ocean is apparently important for both the occurrence and persistence of such anomalous periods. In the GCM, the Atlantic Meridional Overturning Circulation appears to influence the large-scale baroclinicity and explosive cyclone development over the North Atlantic. These results permit a better understanding of explosive cyclogenesis variability at different climatic timescales and might help to improve predictions of these hazardous events.

Nox2 B-loop peptide, Nox2ds, specifically inhibits the NADPH oxidase Nox2

In recent years, reactive oxygen species (ROS) derived from the vascular isoforms of NADPH oxidase, Nox1, Nox2, and Nox4, have been implicated in many cardiovascular pathologies. As a result, the selective inhibition of these isoforms is an area of intense current investigation. In this study, we postulated that Nox2ds, a peptidic inhibitor that mimics a sequence in the cytosolic B-loop of Nox2, would inhibit ROS production by the Nox2-. but not the Noxl- and Nox4-oxidase systems. To test our hypothesis, the inhibitory activity of Nox2ds was assessed in cell-free assays using reconstituted systems expressing the Nox2-, canonical or hybrid Nox1- or Nox4-oxidase. Our findings demonstrate that Nox2ds, but not its scrambled control, potently inhibited superoxide (O(2)(center dot-)) production in the Nox2 cell-free system, as assessed by the cytochrome c assay. Electron paramagnetic resonance confirmed that Nox2ds inhibits O(2)(center dot-) production by Nox2 oxidase. In contrast, Nox2ds did not inhibit ROS production by either Nox1- or Nox4-oxidase. These findings demonstrate that Nox2ds is a selective inhibitor of Nox2-oxidase and support its utility to elucidate the role of Nox2 in organ pathophysiology and its potential as a therapeutic agent. (C) 2011 Elsevier Inc. All rights reserved.

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Open Issues in Control ofAutomotive R744 Air-ConditioningSystems

In this thesis, one of the current control algorithms for the R744 cycle, which tries tooptimize the performance of the system by two SISO control loops, is compared to acost-effective system with just one actuator. The operation of a key component of thissystem, a two stage orifice expansion valve is examined in a range of typical climateconditions. One alternative control loop for this system, which has been proposed byBehr group, is also scrutinized.The simulation results affirm the preference of using two control-loops instead of oneloop, but refute advantages of the Behr alternate control approach against one-loopcontrol. As far as the economic considerations of the A/C unit are concerned, usinga two-stage orifice expansion valve is desired by the automotive industry, thus basedon the experiment results, an improved logic for control of this system is proposed.In the second part, it is investigated whether the one-actuator control approach isapplicable to a system consisting of two parallel evaporators to allow passengers tocontrol different climate zones. The simulation results show that in the case of usinga two-stage orifice valve for the front evaporator and a fixed expansion valve forthe rear one, a proper distribution of the cooling power between the front and rearcompartment is possible for a broad range of climate conditions.

Using Multi-Objective Optimization To Maximize Multiple Benefits For Sustainable Drainage Design

For many years, drainage design was mainly about providing sufficient network capacity. This traditional approach had been successful with the aid of computer software and technical guidance. However, the drainage design criteria had been evolving due to rapid population growth, urbanisation, climate change and increasing sustainability awareness. Sustainable drainage systems that bring benefits in addition to water management have been recommended as better alternatives to conventional pipes and storages. Although the concepts and good practice guidance had already been communicated to decision makers and public for years, network capacity still remains a key design focus in many circumstances while the additional benefits are generally considered secondary only. Yet, the picture is changing. The industry begins to realise that delivering multiple benefits should be given the top priority while the drainage service can be considered a secondary benefit instead. The shift in focus means the industry has to adapt to new design challenges. New guidance and computer software are needed to assist decision makers. For this purpose, we developed a new decision support system. The system consists of two main components – a multi-criteria evaluation framework for drainage systems and a multi-objective optimisation tool. Users can systematically quantify the performance, life-cycle costs and benefits of different drainage systems using the evaluation framework. The optimisation tool can assist users to determine combinations of design parameters such as the sizes, order and type of drainage components that maximise multiple benefits. In this paper, we will focus on the optimisation component of the decision support framework. The optimisation problem formation, parameters and general configuration will be discussed. We will also look at the sensitivity of individual variables and the benchmark results obtained using common multi-objective optimisation algorithms. The work described here is the output of an EngD project funded by EPSRC and XP Solutions.

Model Prediction Control For Water Management Using Adaptive Prediction Accuracy

In the field of operational water management, Model Predictive Control (MPC) has gained popularity owing to its versatility and flexibility. The MPC controller, which takes predictions, time delay and uncertainties into account, can be designed for multi-objective management problems and for large-scale systems. Nonetheless, a critical obstacle, which needs to be overcome in MPC, is the large computational burden when a large-scale system is considered or a long prediction horizon is involved. In order to solve this problem, we use an adaptive prediction accuracy (APA) approach that can reduce the computational burden almost by half. The proposed MPC scheme with this scheme is tested on the northern Dutch water system, which comprises Lake IJssel, Lake Marker, the River IJssel and the North Sea Canal. The simulation results show that by using the MPC-APA scheme, the computational time can be reduced to a large extent and a flood protection problem over longer prediction horizons can be well solved.

A governança corporativa nos clubes de futebol : um estudo multi-caso baseado nas práticas de governança corporativa dos clubes cariocas

Esta dissertação objetiva mapear as estruturas e as práticas de governança adotadas pelos clubes de futebol profissional no Brasil, aprofundando em estudo de caso o Flamengo, o Vasco da Gama, o Fluminense e o Botafogo. A partir de levantamento da situação econômico-financeira dos clubes brasileiros e da literatura dedicada à governança de associações e de clubes de futebol, foi realizado levantamento de aspectos da governança dispostos no Estatuto dos clubes, e dirigentes anteriores dos clubes foram entrevistados sobre esses aspectos. Para a análise desse material, buscou-se identificar o tratamento vinculado a aspectos fundamentais da boa governança tratados em códigos nacionais e internacionais. Os resultados evidenciaram uma grande diferença entre as estruturas e as práticas de governança dos clubes e aquelas recomendadas pelos códigos, apontando a necessidade de melhorias, mas também de melhores identificação e definição de boas práticas de governança específica para os clubes.

Supply chain turbulence: the impact of a mid-range event in multi-tier, multi-dimension supply chains

Nota: A autora agradece à Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) pela concessão de bolsa de estudos para o desenvolvimento deste projeto de pesquisa.

Coordenação e governança no Programa Territórios da Cidadania: uma análise multi-level a partir do Vale do Ribeira-SP

Poverty in Brazil has been gradually reduced. Among the main reasons, there are public policies for universalization of rights. On the other hand, the municipalities' Human Development Index indicates scenarios of growing inequality. In other words, some regions, basically of rural character, were left behind in that process of development. In 2008, the “Territórios da Cidadania” (Territories of Citizenship) Program was launched by the federal government, under high expectations. It was proposed to develop those regions and to prioritize the arrival of ongoing federal public policies where they were most demanded. The program has shown an innovative arrangement which included dozens of ministries and other federal agencies, state governments, municipalities and collegialities to the palliative management and control of the territory. In this structure, both new and existing jurisdictions came to support the program coordination. This arrangement was classified as an example of multi-level governance, whose theory has been an efficient instrument to understand the intra- and intergovernmental relations under which the program took place. The program lasted only three years. In Vale do Ribeira Territory – SP, few community leaderships acknowledge it, although not having further information about its actions and effects. Against this background, the approach of this research aims to study the program coordination and governance structure (from Vale Territory, considered as the most local level, until the federal government), based on the hypothesis that, beyond the local contingencies in Vale do Ribeira, the layout and implementation of the Territories of Citizenship Program as they were formulated possess fundamental structural issues that hinder its goals of reducing poverty and inequality through promoting the development of the territory. Complementing the research, its specific goal was to raise the program layout and background in order to understand how the relations, predicted or not in its structure, were formulated and how they were developed, with special attention to Vale do Ribeira-SP. Generally speaking, it was concluded that the coordination and governance arrangement of the Territories of Citizenship Program failed for not having developed qualified solutions to deal with the challenges of the federalist Brazilian structure, party politics, sectorized public actions, or even the territory contingencies and specificities. The complexity of the program, the poverty problem proposed to be faced, and the territorial strategy of development charged a high cost of coordination, which was not accomplished by the proposal of centralization in the federal government with internal decentralization of the coordination. As the presidency changed in 2011, the program could not present results that were able to justify the arguments for its continuation, therefore it was paralyzed, lost its priority status, and the resources previously invested were redirected.

Organic acids and/or compound with defined microorganisms to control Salmonella enterica serovar Enteritidis experimental infection in chickens

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

Análise e desenvolvimento de controladores preditivos multivariáveis baseados em multi-modelos bilineares

This work addresses issues related to analysis and development of multivariable predictive controllers based on bilinear multi-models. Linear Generalized Predictive Control (GPC) monovariable and multivariable is shown, and highlighted its properties, key features and applications in industry. Bilinear GPC, the basis for the development of this thesis, is presented by the time-step quasilinearization approach. Some results are presented using this controller in order to show its best performance when compared to linear GPC, since the bilinear models represent better the dynamics of certain processes. Time-step quasilinearization, due to the fact that it is an approximation, causes a prediction error, which limits the performance of this controller when prediction horizon increases. Due to its prediction error, Bilinear GPC with iterative compensation is shown in order to minimize this error, seeking a better performance than the classic Bilinear GPC. Results of iterative compensation algorithm are shown. The use of multi-model is discussed in this thesis, in order to correct the deficiency of controllers based on single model, when they are applied in cases with large operation ranges. Methods of measuring the distance between models, also called metrics, are the main contribution of this thesis. Several application results in simulated distillation columns, which are close enough to actual behaviour of them, are made, and the results have shown satisfactory

Controlador preditivo generalizado multi-modelo aplicado ao controle de pressão arterial

Postsurgical complication of hypertension may occur in cardiac patients. To decrease the chances of complication it is necessary to reduce elevated blood pressure as soon as possible. Continuous infusion of vasodilator drugs, such as sodium nitroprusside (Nipride), would quickly lower the blood pressure in most patients. However, each patient has a different sensitivity to infusion of Nipride. The parameters and the time delays of the system are initially unknown. Moreover, the parameters of the transfer function associated with a particular patient are time varying. the objective of the study is to develop a procedure for blood pressure control i the presence of uncertainty of parameters and considerable time delays. So, a methodology was developed multi-model, and for each such model a Preditive Controller can be a priori designed. An adaptive mechanism is then needed for deciding which controller should be dominant for a given plant

Experience generalization for multi-agent reinforcement learning

On-line learning methods have been applied successfully in multi-agent systems to achieve coordination among agents. Learning in multi-agent systems implies in a non-stationary scenario perceived by the agents, since the behavior of other agents may change as they simultaneously learn how to improve their actions. Non-stationary scenarios can be modeled as Markov Games, which can be solved using the Minimax-Q algorithm a combination of Q-learning (a Reinforcement Learning (RL) algorithm which directly learns an optimal control policy) and the Minimax algorithm. However, finding optimal control policies using any RL algorithm (Q-learning and Minimax-Q included) can be very time consuming. Trying to improve the learning time of Q-learning, we considered the QS-algorithm. in which a single experience can update more than a single action value by using a spreading function. In this paper, we contribute a Minimax-QS algorithm which combines the Minimax-Q algorithm and the QS-algorithm. We conduct a series of empirical evaluation of the algorithm in a simplified simulator of the soccer domain. We show that even using a very simple domain-dependent spreading function, the performance of the learning algorithm can be improved.