Factors influencing malaria control policy-making in Kenya, Uganda and Tanzania.

BACKGROUND: Policy decisions for malaria control are often difficult to make as decision-makers have to carefully consider an array of options and respond to the needs of a large number of stakeholders. This study assessed the factors and specific objectives that influence malaria control policy decisions, as a crucial first step towards developing an inclusive malaria decision analysis support tool (MDAST). METHODS: Country-specific stakeholder engagement activities using structured questionnaires were carried out in Kenya, Uganda and Tanzania. The survey respondents were drawn from a non-random purposeful sample of stakeholders, targeting individuals in ministries and non-governmental organizations whose policy decisions and actions are likely to have an impact on the status of malaria. Summary statistics across the three countries are presented in aggregate. RESULTS: Important findings aggregated across countries included a belief that donor preferences and agendas were exerting too much influence on malaria policies in the countries. Respondents on average also thought that some relevant objectives such as engaging members of parliament by the agency responsible for malaria control in a particular country were not being given enough consideration in malaria decision-making. Factors found to influence decisions regarding specific malaria control strategies included donor agendas, costs, effectiveness of interventions, health and environmental impacts, compliance and/acceptance, financial sustainability, and vector resistance to insecticides. CONCLUSION: Malaria control decision-makers in Kenya, Uganda and Tanzania take into account health and environmental impacts as well as cost implications of different intervention strategies. Further engagement of government legislators and other policy makers is needed in order to increase funding from domestic sources, reduce donor dependence, sustain interventions and consolidate current gains in malaria.

Assessment of toxicity and biodistribution of recombinant AAV8 vector-mediated immunomodulatory gene therapy in mice with Pompe disease.

A preclinical safety study was conducted to evaluate the short- and long-term toxicity of a recombinant adeno-associated virus serotype 8 (AAV2/8) vector that has been developed as an immune-modulatory adjunctive therapy to recombinant human acid α-glucosidase (rhGAA, Myozyme) enzyme replacement treatment (ERT) for patients with Pompe disease (AAV2/8-LSPhGAApA). The AAV2/8-LSPhGAApA vector at 1.6 × 10(13) vector particles/kg, after intravenous injection, did not cause significant short- or long-term toxicity. Recruitment of CD4(+) (but not CD8(+)) lymphocytes to the liver was elevated in the vector-dosed male animals at study day (SD) 15, and in group 8 animals at SD 113, in comparison to their respective control animals. Administration of the vector, either prior to or after the one ERT injection, uniformly prevented the hypersensitivity induced by subsequent ERT in males, but not always in female animals. The vector genome was sustained in all tissues through 16-week postdosing, except for in blood with a similar tissue tropism between males and females. Administration of the vector alone, or combined with the ERT, was effective in producing significantly increased GAA activity and consequently decreased glycogen accumulation in multiple tissues, and the urine biomarker, Glc4, was significantly reduced. The efficacy of the vector (or with ERT) was better in males than in females, as demonstrated both by the number of tissues showing significantly effective responses and the extent of response in a given tissue. Given the lack of toxicity for AAV2/8LSPhGAApA, further consideration of clinical translation is warranted in Pompe disease.

Similar prevalence and magnitude of auditory-evoked and visually evoked activity in the frontal eye fields: implications for multisensory motor control.

Saccadic eye movements can be elicited by more than one type of sensory stimulus. This implies substantial transformations of signals originating in different sense organs as they reach a common motor output pathway. In this study, we compared the prevalence and magnitude of auditory- and visually evoked activity in a structure implicated in oculomotor processing, the primate frontal eye fields (FEF). We recorded from 324 single neurons while 2 monkeys performed delayed saccades to visual or auditory targets. We found that 64% of FEF neurons were active on presentation of auditory targets and 87% were active during auditory-guided saccades, compared with 75 and 84% for visual targets and saccades. As saccade onset approached, the average level of population activity in the FEF became indistinguishable on visual and auditory trials. FEF activity was better correlated with the movement vector than with the target location for both modalities. In summary, the large proportion of auditory-responsive neurons in the FEF, the similarity between visual and auditory activity levels at the time of the saccade, and the strong correlation between the activity and the saccade vector suggest that auditory signals undergo tailoring to match roughly the strength of visual signals present in the FEF, facilitating accessing of a common motor output pathway.

Predictive Current Control of Doubly Fed Induction Generators

This paper presents a predictive current control strategy for doubly-fed induction generators (DFIG). The method predicts the DFIG’s rotor current variations in the synchronous reference frame fixed to the stator flux within a fixed sampling period. This is then used to directly calculate the required rotor voltage to eliminate the current errors at the end of the following sampling period. Space vector modulation is used to generate the required switching pulses within the fixed sampling period. The impact of sampling delay on the accuracy of the sampled rotor current is analyzed and detailed compensation methods are proposed to improve the current control accuracy and system stability. Experimental results for a 1.5 kW DFIG system illustrate the effectiveness and robustness of the proposed control strategy during rotor current steps and rotating speed variation. Tests during negative sequence current injection further demonstrate the excellent dynamic performance of the proposed PCC method.

Improved Nonlinear PCA for Process Monitoring Using Support Vector Data Description

Nonlinear principal component analysis (PCA) based on neural networks has drawn significant attention as a monitoring tool for complex nonlinear processes, but there remains a difficulty with determining the optimal network topology. This paper exploits the advantages of the Fast Recursive Algorithm, where the number of nodes, the location of centres, and the weights between the hidden layer and the output layer can be identified simultaneously for the radial basis function (RBF) networks. The topology problem for the nonlinear PCA based on neural networks can thus be solved. Another problem with nonlinear PCA is that the derived nonlinear scores may not be statistically independent or follow a simple parametric distribution. This hinders its applications in process monitoring since the simplicity of applying predetermined probability distribution functions is lost. This paper proposes the use of a support vector data description and shows that transforming the nonlinear principal components into a feature space allows a simple statistical inference. Results from both simulated and industrial data confirm the efficacy of the proposed method for solving nonlinear principal component problems, compared with linear PCA and kernel PCA.

Rift Valley Fever Epidemiology, Surveillance, and Control: What Have Models Contributed?

Background: Rift Valley fever (RVF) is an emerging vector-borne zoonotic disease that represents a threat to human health, animal health, and livestock production, particularly in Africa. The epidemiology of RVF is not well understood, so that forecasting RVF outbreaks and carrying out efficient and timely control measures remains a challenge. Various epidemiological modeling tools have been used to increase knowledge on RVF epidemiology and to inform disease management policies.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

Prospective control of manual interceptive actions:comparative simulations of extant and new model constructs

Two prospective controllers of hand movements in catching-both based on required velocity control-were simulated. Under certain conditions, this required velocity control led to overshoots of the future interception point. These overshoots were absent in pertinent experiments. To remedy this shortcoming, the required velocity model was reformulated in terms of a neural network, the Vector Integration To Endpoint model, to create a Required Velocity Integration To Endpoint model. Addition of a parallel relative velocity channel, resulting in the Relative and Required Velocity Integration To Endpoint model, provided a better account for the experimentally observed kinematics than the existing, purely behavioral models. Simulations of reaching to intercept decelerating and accelerating objects in the presence of background motion were performed to make distinct predictions for future experiments.

A predictive maintenance system for integral type faults based on support vector machines:An application to ion implantation

In semiconductor fabrication processes, effective management of maintenance operations is fundamental to decrease costs associated with failures and downtime. Predictive Maintenance (PdM) approaches, based on statistical methods and historical data, are becoming popular for their predictive capabilities and low (potentially zero) added costs. We present here a PdM module based on Support Vector Machines for prediction of integral type faults, that is, the kind of failures that happen due to machine usage and stress of equipment parts. The proposed module may also be employed as a health factor indicator. The module has been applied to a frequent maintenance problem in semiconductor manufacturing industry, namely the breaking of the filament in the ion-source of ion-implantation tools. The PdM has been tested on a real production dataset. © 2013 IEEE.

Optimal control and numerical optimization applied to epidemiological models

A relação entre a epidemiologia, a modelação matemática e as ferramentas computacionais permite construir e testar teorias sobre o desenvolvimento e combate de uma doença. Esta tese tem como motivação o estudo de modelos epidemiológicos aplicados a doenças infeciosas numa perspetiva de Controlo Ótimo, dando particular relevância ao Dengue. Sendo uma doença tropical e subtropical transmitida por mosquitos, afecta cerca de 100 milhões de pessoas por ano, e é considerada pela Organização Mundial de Saúde como uma grande preocupação para a saúde pública. Os modelos matemáticos desenvolvidos e testados neste trabalho, baseiam-se em equações diferenciais ordinárias que descrevem a dinâmica subjacente à doença nomeadamente a interação entre humanos e mosquitos. É feito um estudo analítico dos mesmos relativamente aos pontos de equilíbrio, sua estabilidade e número básico de reprodução. A propagação do Dengue pode ser atenuada através de medidas de controlo do vetor transmissor, tais como o uso de inseticidas específicos e campanhas educacionais. Como o desenvolvimento de uma potencial vacina tem sido uma aposta mundial recente, são propostos modelos baseados na simulação de um hipotético processo de vacinação numa população. Tendo por base a teoria de Controlo Ótimo, são analisadas as estratégias ótimas para o uso destes controlos e respetivas repercussões na redução/erradicação da doença aquando de um surto na população, considerando uma abordagem bioeconómica. Os problemas formulados são resolvidos numericamente usando métodos diretos e indiretos. Os primeiros discretizam o problema reformulando-o num problema de optimização não linear. Os métodos indiretos usam o Princípio do Máximo de Pontryagin como condição necessária para encontrar a curva ótima para o respetivo controlo. Nestas duas estratégias utilizam-se vários pacotes de software numérico. Ao longo deste trabalho, houve sempre um compromisso entre o realismo dos modelos epidemiológicos e a sua tratabilidade em termos matemáticos.

Parallel implementation of an adaptive generalized predictive control algorithm

The Adaptive Generalized Predictive Control (GPC) algorithm can be speeded up using parallel processing. Since the GPC algorithm needs to be fed with knowledge of the plant transfer function, the parallelization of a standard Recursive Least Squares (RLS) estimator and a GPC predictor is discussed here.

Promise for plant pest control: root-associated pseudomonads with insecticidal activities.

Insects are an important and probably the most challenging pest to control in agriculture, in particular when they feed on belowground parts of plants. The application of synthetic pesticides is problematic owing to side effects on the environment, concerns for public health and the rapid development of resistance. Entomopathogenic bacteria, notably Bacillus thuringiensis and Photorhabdus/Xenorhabdus species, are promising alternatives to chemical insecticides, for they are able to efficiently kill insects and are considered to be environmentally sound and harmless to mammals. However, they have the handicap of showing limited environmental persistence or of depending on a nematode vector for insect infection. Intriguingly, certain strains of plant root-colonizing Pseudomonas bacteria display insect pathogenicity and thus could be formulated to extend the present range of bioinsecticides for protection of plants against root-feeding insects. These entomopathogenic pseudomonads belong to a group of plant-beneficial rhizobacteria that have the remarkable ability to suppress soil-borne plant pathogens, promote plant growth, and induce systemic plant defenses. Here we review for the first time the current knowledge about the occurrence and the molecular basis of insecticidal activity in pseudomonads with an emphasis on plant-beneficial and prominent pathogenic species. We discuss how this fascinating Pseudomonas trait may be exploited for novel root-based approaches to insect control in an integrated pest management framework.

Connexin-36 contributes to control function of insulin-producing cells.

Connexin-36 (Cx36) is a gap junction protein expressed by the insulin-producing beta-cells. We investigated the contribution of this protein in normal beta-cell function by using a viral gene transfer approach to alter Cx36 content in the insulin-producing line of INS-1E cells and rat pancreatic islets. Transcripts for Cx43, Cx45, and Cx36 were detected by reverse transcriptase-PCR in freshly isolated pancreatic islets, whereas only a transcript for Cx36 was detected in INS-1E cells. After infection with a sense viral vector, which induced de novo Cx36 expression in the Cx-defective HeLa cells we used to control the transgene expression, Western blot, immunofluorescence, and freeze-fracture analysis showed a large increase of Cx36 within INS-1E cell membranes. In contrast, after infection with an antisense vector, Cx36 content was decreased by 80%. Glucose-induced insulin release and insulin content were decreased, whether infected INS-1E cells expressed Cx36 levels that were largely higher or lower than those observed in wild-type control cells. In both cases, basal insulin secretion was unaffected. Comparable observations on basal secretion and insulin content were made in freshly isolated rat pancreatic islets. The data indicate that large changes in Cx36 alter insulin content and, at least in INS-1E cells, also affect glucose-induced insulin release.