This study was to determine the effects of a six-week program of dynamic weight training upon flexibility.

It is known that to pursuit end-to-end QoS of a class-based traffic flow is inefficient in Differentiated Service Networks. Therefore in this thesis, we propose an effective throughput-recovery mechanism to allow high-priority traffic flow to receive suitable resource allocation, and hence the end-to-end QoS is guaranteed. The proposed throughput-recovery mechanism assures a predefined minimum departure rate of low-latency EF dataflow. It consists of two parts. The first part is referred to as the feedback self-adaptive mechanism, where the egress node measures and monitors throughput of EF dataflow to decide whether to send the control messages to ingress node. When ingress node receives the control messages, it will reallocate the resources to improve EF throughput. The second part is referred to as the dynamic weight adjustment mechanism, which can prevent EF packets from dropping when congestion occurs in the core routers. For the purpose of demonstration, we build a mathematical model and use NS-2 simulator. We have proved our throughput-recovery mechanism is effective in improving the throughput of EF traffic flow. Finally, we modify the traditional WRR such that it can adjust weight based on the delay requirements.

Um bom modelo experimental deve contar com métodos de avaliação eficazes de seus parâmetros. Esta é uma observação importante quando se faz necessária a avaliação da nocicepção e da incapacitação articular em animais experimentais. O estabelecimento de novos critérios aos testes animais é fundamental para que processos inflamatórios articulares possam continuar sendo estudados, entendidos e resolvidos. Buscando contribuir neste sentido, este trabalho realizou a padronização do teste de incapacitação dinâmico (TID) para avaliação da incapacitação articular em modelos experimentais de artrite. Os resultados obtidos mostram que o TID é sensível na avaliação da incapacitação articular em modelos de artrite induzida por antígeno (AIA) ou por zimosana. Além disso é preditivo para o estudo do efeito farmacológico de drogas que interfiram na incapacitação articular como anti-inflamatórias ou analgésicas. Desde o início da década de 90, quando participação das células da glia na dor foi descrita, diversos trabalhos surgiram mostrando seu papel em diferentes modelos animais. A participação das células da glia espinais na dor e incapacitação em modelos experimentais de artrite e artrite reumatoide têm sido relatada, mas não há descrição desta participação em função do tempo de indução do processo inflamatório articular. Por meio de ferramentas farmacológicas e moleculares, este trabalho mostra que as células da glia, tanto espinais como do gânglio da raiz dorsal estão participando na gênese e manutenção da incapacitação inflamatória articular em modelo de AIA. A participação destas células ocorre por meio da liberação de IL-1? e TNF? em nível medular e pela primeira vez é mostrado que a ativação astrocítica parece preceder a ativação microglial neste modelo. / A good experimental model must rely on effective methods of evaluation of its parameters. This is an important observation when it is necessary to evaluate the articular nociception and disability in experimental animals. Establishing new criteria to test animals is essential for inflammatory joint can continue being studied, understood and resolved. Seeking help in this sense, this work constitutes a test dynamic weight bearing (DWB) standardization for assessment of articular incapacitation in experimental models of arthritis. The results show that the DWB is sensitive in assessing the impairment models articular antigen-induced arthritis (AIA) or zimosana. Furthermore is predictive for studying the pharmacological effects of drugs that interfere with articular incapacitation as antiinflammatory or analgesic. Since the early 90s, when participation of glial cells in pain was described, several studies have emerged showing its role in different animal models. The involvement of glial cells in the spinal pain and disability in experimental models of arthritis and rheumatoid arthritis have been reported, but no description of this contribution versus time of induction of joint inflammation. Through molecular and pharmacological tools, this work shows that the glial cells, both as the spinal dorsal root ganglio are participating in the genesis and maintenance of inflammatory joint incapacitation in AIA model. The participation of these cells occurs through the release of IL-1? and TNF? in the spinal cord and the first time it is shown that astrocytic activation appears to precede the microglial activation in this model.

Um bom modelo experimental deve contar com métodos de avaliação eficazes de seus parâmetros. Esta é uma observação importante quando se faz necessária a avaliação da nocicepção e da incapacitação articular em animais experimentais. O estabelecimento de novos critérios aos testes animais é fundamental para que processos inflamatórios articulares possam continuar sendo estudados, entendidos e resolvidos. Buscando contribuir neste sentido, este trabalho realizou a padronização do teste de incapacitação dinâmico (TID) para avaliação da incapacitação articular em modelos experimentais de artrite. Os resultados obtidos mostram que o TID é sensível na avaliação da incapacitação articular em modelos de artrite induzida por antígeno (AIA) ou por zimosana. Além disso é preditivo para o estudo do efeito farmacológico de drogas que interfiram na incapacitação articular como anti-inflamatórias ou analgésicas. Desde o início da década de 90, quando participação das células da glia na dor foi descrita, diversos trabalhos surgiram mostrando seu papel em diferentes modelos animais. A participação das células da glia espinais na dor e incapacitação em modelos experimentais de artrite e artrite reumatoide têm sido relatada, mas não há descrição desta participação em função do tempo de indução do processo inflamatório articular. Por meio de ferramentas farmacológicas e moleculares, este trabalho mostra que as células da glia, tanto espinais como do gânglio da raiz dorsal estão participando na gênese e manutenção da incapacitação inflamatória articular em modelo de AIA. A participação destas células ocorre por meio da liberação de IL-1? e TNF? em nível medular e pela primeira vez é mostrado que a ativação astrocítica parece preceder a ativação microglial neste modelo. / A good experimental model must rely on effective methods of evaluation of its parameters. This is an important observation when it is necessary to evaluate the articular nociception and disability in experimental animals. Establishing new criteria to test animals is essential for inflammatory joint can continue being studied, understood and resolved. Seeking help in this sense, this work constitutes a test dynamic weight bearing (DWB) standardization for assessment of articular incapacitation in experimental models of arthritis. The results show that the DWB is sensitive in assessing the impairment models articular antigen-induced arthritis (AIA) or zimosana. Furthermore is predictive for studying the pharmacological effects of drugs that interfere with articular incapacitation as antiinflammatory or analgesic. Since the early 90s, when participation of glial cells in pain was described, several studies have emerged showing its role in different animal models. The involvement of glial cells in the spinal pain and disability in experimental models of arthritis and rheumatoid arthritis have been reported, but no description of this contribution versus time of induction of joint inflammation. Through molecular and pharmacological tools, this work shows that the glial cells, both as the spinal dorsal root ganglio are participating in the genesis and maintenance of inflammatory joint incapacitation in AIA model. The participation of these cells occurs through the release of IL-1? and TNF? in the spinal cord and the first time it is shown that astrocytic activation appears to precede the microglial activation in this model.

Hydrologic and climate models predict variables through a simplification of the underlying complex natural processes. Model development involves minimising predictive uncertainty. Predictive uncertainty arises from three broad sources which are measurement error in observed responses, uncertainty of input variables and model structural error. This thesis introduces ways to improve predictive accuracy of hydroclimatic models by considering input and structural uncertainties. The specific methods developed to reduce the uncertainty because of erroneous inputs and model structural errors are outlined below. The uncertainty in hydrological model inputs, if ignored, introduces systematic biases in the parameters estimated. This thesis presents a method, known as simulation extrapolation (SIMEX), to ascertain the extent of parameter bias. SIMEX starts by generating a series of alternate inputs by artificially adding white noise in increasing multiples of the known input error variance. The resulting alternate parameter sets allow formulation of an empirical relationship between their values and the level of noise present. SIMEX is based on the theory that the trend in alternate parameters can be extrapolated back to the notional error free zone. The case study relates to erroneous sea surface temperature anomaly (SSTA) records used as input variables of a linear model to predict the Southern Oscillation Index (SOI). SIMEX achieves a reduction in residual errors from the SOI prediction. Besides, a hydrologic application of SIMEX is demonstrated by a synthetic simulation within a three-parameter conceptual rainfall runoff model. This thesis next advocates reductions of structural uncertainty of any single model by combining multiple alternative model responses. Current approaches for combining hydroclimatic forecasts are generally limited to using combination weights that remain static over time. This research develops a methodology for combining forecasts from multiple models in a dynamic setting as an improvement of over static weight combination. The model responses are mixed on a pair wise basis using mixing weights that vary in time reflecting the persistence of individual model skills. The concept is referred here as the pair wise dynamic weight combination. Two approaches for forecasting the dynamic weights are developed. The first of the two approaches uses a mixture of two basis distributions which are three category ordered logistic regression model and a generalised linear autoregressive model. The second approach uses a modified nearest neighbour approach to forecast the future weights. These alternatives are used to first combine a univariate response forecast, the NINO3.4 SSTA index. This is followed by a similar combination, but for the entire global gridded SSTA forecast field. Results from these applications show significant improvements being achieved due to the dynamic model combination approach. The last application demonstrating the dynamic combination logic, uses the dynamically combined multivariate SSTA forecast field as the basis of developing multi-site flow forecasts in the Namoi River catchment in eastern Australia. To further reduce structural uncertainty in the flow forecasts, three forecast models are formulated and the dynamic combination approach applied again. The study demonstrates that improved SSTA forecast (due to dynamic combination) in turn improves all three flow forecasts, while the dynamic combination of the three flow forecasts results in further improvements.

Traditional TCP when applied in wireless networks may encounter two limitations. The first limitation is the higher bit error rate (BER) due to noise, fading, and multipath interference. Because traditional TCP is designed for wired and reliable networks, packet loss is mainly caused by network congestions. As a result, TCP may decrease congestion window inappropriately upon detecting a packet loss. The second limitation is about the packet scheduling, which mostly does not consider wireless characteristics. In this Thesis, we propose a local retransmission mechanism to improve TCP throughput for wireless networks with higher BER. In addition, we measure the packet loss ratio (PLR) to adjust the queue weight such that the available bandwidth for each queue can be changed accordingly. In our mechanism, the queue length is used to determine whether there is a congestion in wireless networks. When the queue length exceeds a threshold, it indicates that the wireless networks may have congestion very likely. We not only propose the dynamic weight-adjustment mechanism, but also solve the packet out-of-sequence problem, which results form when a TCP flow changes to a new queue. For the purpose of demonstration, we implement the proposed weight-adjustment mechanisms on the Linux platform. Through the measurements and discussions, we have shown that the proposed mechanisms can effectively improve the TCP throughput in wireless networks.

Hydrologic and climate models predict variables through a simplification of the underlying complex natural processes. Model development involves minimising predictive uncertainty. Predictive uncertainty arises from three broad sources which are measurement error in observed responses, uncertainty of input variables and model structural error. This thesis introduces ways to improve predictive accuracy of hydroclimatic models by considering input and structural uncertainties. The specific methods developed to reduce the uncertainty because of erroneous inputs and model structural errors are outlined below. The uncertainty in hydrological model inputs, if ignored, introduces systematic biases in the parameters estimated. This thesis presents a method, known as simulation extrapolation (SIMEX), to ascertain the extent of parameter bias. SIMEX starts by generating a series of alternate inputs by artificially adding white noise in increasing multiples of the known input error variance. The resulting alternate parameter sets allow formulation of an empirical relationship between their values and the level of noise present. SIMEX is based on the theory that the trend in alternate parameters can be extrapolated back to the notional error free zone. The case study relates to erroneous sea surface temperature anomaly (SSTA) records used as input variables of a linear model to predict the Southern Oscillation Index (SOI). SIMEX achieves a reduction in residual errors from the SOI prediction. Besides, a hydrologic application of SIMEX is demonstrated by a synthetic simulation within a three-parameter conceptual rainfall runoff model. This thesis next advocates reductions of structural uncertainty of any single model by combining multiple alternative model responses. Current approaches for combining hydroclimatic forecasts are generally limited to using combination weights that remain static over time. This research develops a methodology for combining forecasts from multiple models in a dynamic setting as an improvement of over static weight combination. The model responses are mixed on a pair wise basis using mixing weights that vary in time reflecting the persistence of individual model skills. The concept is referred here as the pair wise dynamic weight combination. Two approaches for forecasting the dynamic weights are developed. The first of the two approaches uses a mixture of two basis distributions which are three category ordered logistic regression model and a generalised linear autoregressive model. The second approach uses a modified nearest neighbour approach to forecast the future weights. These alternatives are used to first combine a univariate response forecast, the NINO3.4 SSTA index. This is followed by a similar combination, but for the entire global gridded SSTA forecast field. Results from these applications show significant improvements being achieved due to the dynamic model combination approach. The last application demonstrating the dynamic combination logic, uses the dynamically combined multivariate SSTA forecast field as the basis of developing multi-site flow forecasts in the Namoi River catchment in eastern Australia. To further reduce structural uncertainty in the flow forecasts, three forecast models are formulated and the dynamic combination approach applied again. The study demonstrates that improved SSTA forecast (due to dynamic combination) in turn improves all three flow forecasts, while the dynamic combination of the three flow forecasts results in further improvements.

Résumé : Contrairement à ce que l'on pourrait croire, les douleurs chroniques ne constituent pas uniquement des symptômes, mais bien une pathologie à part entière. La pharmacopée actuelle ne permettant pas de les soulager efficacement, il y a maintenant un besoin de les considérer dans leur spécificité lors de la recherche de nouvelles thérapies. Dans cette optique, nous avons étudié le rôle des chimiokines et de leurs récepteurs dans le contrôle de la douleur. Connu pour leur rôle dans la réponse immunitaire, nous avons en particulier investigué le rôle du couple ligand-récepteur CCL2-CCR2 dans la régulation des douleurs d’origine arthritique. Nous avons d'abord évalué l'effet analgésique de notre molécule antagoniste du récepteur CCR2, l'INCB3344, dans un modèle de douleur inflammatoire où elle renverse d'environ 50% les douleurs provoquées et les douleurs spontanées lorsqu'administrée par voie spinale. Nous avons également pu observer que bloquer l'activation de CCR2 au niveau de la moelle épinière limite non seulement la neuroinflammation spinale, mais permet également de réduire la sévérité de l'atteinte inflammatoire périphérique en limitant le transport rétrograde de la substance P. Nous avons ensuite appliqué nos observations sur un modèle de douleur arthritique plus près de la réalité clinique des patients souffrant d'arthrite rhumatoïde. Nous y avons reproduit la majorité de nos effets analgésiques suite à une administration spinale. Le traitement est cependant demeuré sans effet sur l'œdème périphérique. Parallèlement à cela, l'administration périphérique du composé, sur une base de deux bolus par jour ou en libération continue par des mini-pompes osmotiques, n'a eu que de très faibles effets analgésiques, mais s'est révélé avoir un impact marquant sur l'œdème périphérique et le gain de poids des animaux. Finalement, c'est en combinant l'INCB3344 avec de l'ibuprofène qu'il a été possible d'avoir un impact positif sur le plus grand nombre de paramètres associés à la douleur chronique. Ces résultats suggèrent donc qu'un antagoniste du récepteur CCR2 possède un potentiel analgésique intéressant, d'autant plus lorsqu'il s'agit de douleur d'origine inflammatoire puisqu'il permet d'agir à la fois sur l'hypersensibilité nociceptive et sur la source même de la douleur inflammatoire. Ce potentiel devient d'autant plus intéressant que de le combiner à un anti-inflammatoire non-stéroïdien (l'ibuprofène) améliore l'efficacité des deux composés. // Abstract : Contrary to popular beliefs, chronic pain is not only a set of symptoms, but a bona fide pathology that the drugs currently available are not sufficient to efficiently relieve. There is thus a need to modify our approach to discover new analgesic agents, taking into consideration the specific physiopathology of chronic pain. With this in mind, we investigated the role of chemokines and their receptors in the modulation of pain. Also known for their participation in the immune response, we focused on the CCL2-CCR2 ability to regulate arthritic pain. We first evaluated the analgesic properties of INCB3344, a specific antagonist of the CCR2 receptor, in a model of inflammatory pain. It reverses both provoked and spontaneous pain by 50% when administered i.t. We also observed that spinally blocking CCR2 limited the expression of proinflammatory mediators. It also reduced peripheral inflammation by preventing peripheral transport of SP. We then translated our findings in a model of arthritic pain, closer to the clinical reality of patients with rheumatoid arthritis. Spinal administration of INCB3344 had similar analgesic actions, but did not altered peripheral inflammation. On the other hand, peripheral administration of INCB3344, either by subcutaneous injection or by continuous release assured by an osmotic pump, had almost no analgesic effects, but significantly reduced peripheral inflammation and reduced the weight loss. By combining INCB3344 with a daily administration of ibuprofen, we were however able to reduce both pain hypersensitivity and the severity of the peripheral inflammation. Taken together, these results suggest that CCR2 antagonism has promising analgesic properties; especially for inflammatory or arthritic pain as it can acts both on the sensibilized nociceptive network and on the peripheral source of the inflammatory pain. This become even more interesting as its mechanism is at least not completely redundant with those of classic non-steroidal anti-inflammatory drugs, which allow the combination of both class of molecule to yield even larger effect.