Carbohydrate refeeding rapidly reverses the adaptive upregulation of human skeletal muscle pyruvate dehydrogenase kinase following a high fat diet

The time course for the reversal of the adaptive increase in pyruvate dehydrogenase kinase (PDK) activity following a 6d high fat diet (HP: 4.2 ± 0.2 % carbohydrate; 75.6 ± 0.4 % fat; 19.5 ± 0.8 % protein) was investigated in human skeletal muscle (vastus lateralis). HF feeding increased PDK activity by 44% (from 0.081 ± 0.025 min"' to 0.247 ± 0.025 mm\p < 0.05). Following carbohydrate re-feeding, (88% carbohydrate; 5% fat; 7% protein), PDK activity had returned to baseline (0.111 ± 0.014 min"') within 3h of re-feeding. The active fraction of pyruvate dehydrognease (PDHa) was depressed following 6d of the HF diet (from 0.89 ± 0.21 mmol/min/kg WW to 0.32 ± 0.05 mmol/min/kg ww,p <0.05) and increased to pre-HF levels by 45 min of post re-feeding (0.74 ±0.19 mmol/min/kg ww) and remained elevated for 3h. Western blotting analysis of the PDK isoforms, PDK4 and PDK2, revealed a 31% increase in PDK4 protein content following the HF diet, with no change in PDK2 protein. This adaptive increase in PDK4 protein content was reversed with carbohydrate re-feeding. It was concluded that the adaptive up-regulation in PDK activity and PDK4 protein content was fiilly reversed by 3h following carbohydrate re-feeding.

The practical application of a meta-analysis of deinstitutionalization : adaptive behaviour outcomes and the piloting of a transitional questionnaire for adults with intellectual disabilities

This investigation examined the effects of de institutionalization on the adaptive behaviour and adjustment of adults with intellectual disabilities (ID). In study 1, a meta-analysis was conducted with 23 studies on deinstitutionalization adaptive behaviour outcomes. Deinstitutionalization was associated with modest improvements in adaptive behaviour however outcomes varied across adaptive behaviour domains and other substantive variables. Clinical and service implications of these results were explicated. Noting the trends from the meta-analysis, study 2 used this information in refining and piloting an Agency Transition Survey used to evaluate community transitions for persons with ID. Information derived from the survey was found to be valuable and adequate for the effective evaluation of transitional success. Potential applications of the survey and meta-analysis results were illustrated.

Deinstitutionalization and its Effects on Social Inclusion, Choice-Making, Adaptive and Maladaptive Behavior for Individuals with Intellectual Disabilities: Case Studies Analysis

In the past three decades institutions for persons with intellectual disabilities (ID) have been downsizing and closing in Ontario, Canada. This trend is reflective of the changes that have occurred in society. As of March 2009 the last institution operated by the Ontario government for persons with ID closed, placing the remaining approximately 1000 persons into the community. The current study was an analysis of part of one study in a four-study research project, called the Facilities Initiative Study, to explore the impact of the closures on the lives of individuals who have been reintegrated into community settings. The goal of the current case study analysis was to describe the impact of changes in social inclusion, choice-making/autonomy, and adaptive/maladaptive functioning of four individuals prior to and following transition to the community. The results suggested that, in most cases, community integration was related to more social inclusion opportunities and autonomy in choice-making, a wider range of adaptive behaviors and fewer maladaptive behaviors. In some cases, the evidence suggested that some of these indices of quality of life were not improving. Overall, the study found that the differences observed were unique to each of the individuals who participated in the case study analysis. Some generalized themes were generated that can be applied to future deinstitutionalization endeavors.

Assessing the adaptive capacity of the Ontario wine industry to climate change: A case study

The global wine industry is experiencing the impacts of climate change. Canada’s major wine sector, the Ontario Wine Industry (OWI) is no exception to this trend. Warmer winter and summer temperatures are affecting wine production. The industry needs to adapt to these challenges, but their capacity for this is unclear. To date, only a limited number of studies exist regarding the adaptive capacity of the wine industry to climate change. Accordingly, this study developed an adaptive capacity assessment framework for the wine industry. The OWI became the case study for the implementation of the assessment framework. Data was obtained by means of a questionnaire sent to grape growers, winemakers and supporting institutions in Ontario. The results indicated the OWI has adaptive capacity capabilities in financial, institutional, political, technological, perceptions, knowledge, diversity and social capital resources areas. Based on the OWI case study, this framework provides an effective means of assessing regional wine industries’ capacity to adapt to climate change.

Fit For Action: A Comparative Case Study of the Implementation of an Adaptive Fitness and Conditioning Program for Moderate Functioning Teens and Transition Age Youth with ASD

The purpose of my research was to develop and refine pedagogic approaches, and establish fitness baselines to adapt fitness and conditioning programs for Moderate-functioning ASD individuals. I conducted a seven-week study with two teens and two trainers. The trainers implemented individualized fitness and conditioning programs that I developed. I conducted pre and post fitness baselines for each teen, a pre and post study interview with the trainers, and recorded semi-structured observations during each session. I used multi-level, within-case and across case analyses, working inductively and deductively. My findings indicated that fundamental movement concepts can be used to establish fitness baselines and develop individualized fitness programs. I tracked and evaluated progressions and improvements using conventional measurements applied to unconventional movements. This process contributed to understanding and making relevant modifications to activities as effective pedagogic strategies for my trainers. Further research should investigate fitness and conditioning programs with lower functioning ASD individuals.

The Progressivity of Equalization Payments in Federations

We investigate the conditions under which an inequality averse and additively separable welfarist constitution maker would always choose to set up a progressive equalization payments scheme in a federation with local public goods. A progressive equalization payments scheme is defined as a list of per capita net (possibly negative) subsidies - one such net subsidy for every jurisdiction - that are decreasing with respect to jurisdictions per capita wealth. We examine these questions in a setting in which the case for progressivity is a priori the strongest, namely, all citizens have the same utility function for the private and the public goods, inhabitants of a given jurisdiction are all identical, and they are not able to move across jurisdictions. We show that the constitution maker favors a progressive equalization payments scheme for all distributions of wealth and all population sizes if and only if its objective function is additively separable between each jurisdiction’s per capita wealth and number of inhabitants. When interpreted as a mean of order r social welfare function, this condition is shown to be equivalent to additive separability of the individual’s indirect utility function with respect to wealth and the price of the public good. Some implications of this restriction to the case where the individual’s direct utility function is additively separable are also derived.

Federalism and Fiscal Equalization in Canada and the United States, 1990-1999.

Rapport de recherche

The effects of Motivation-Adaptive Skills-Trauma Resolution (MASTR) : Eye Movement Desensitization and Reprocessing (EMDR) on traumatized adolescents with conduct problems

Thèse numérisée par la Division de la gestion de documents et des archives de l'Université de Montréal

Analysis and Design of an Adaptive Polynomial Predistorter with the Loop Delay Estimator

Most adaptive linearization circuits for the nonlinear amplifier have a feedback loop that returns the output signal oj'tne eunplifier to the lineurizer. The loop delay of the linearizer most be controlled precisely so that the convergence of the linearizer should be assured lot this Letter a delay control circuit is presented. It is a delay lock loop (ULL) with it modified early-lute gate and can he easily applied to a DSP implementation. The proposed DLL circuit is applied to an adaptive linearizer with the use of a polynomial predistorter, and the simulalion for a 16-QAM signal is performed. The simulation results show that the proposed DLL eliminates the delay between the reference input signal and the delayed feedback signal of the linearizing circuit perfectly, so that the predistorter polynomial coefficients converge into the optimum value and a high degree of linearization is achieved

Energy Management in Wireless Sensor Networks: A Crosslayer,Channel Adaptive Approach Towards Performance Optimization

The proliferation of wireless sensor networks in a large spectrum of applications had been spurered by the rapid advances in MEMS(micro-electro mechanical systems )based sensor technology coupled with low power,Low cost digital signal processors and radio frequency circuits.A sensor network is composed of thousands of low cost and portable devices bearing large sensing computing and wireless communication capabilities. This large collection of tiny sensors can form a robust data computing and communication distributed system for automated information gathering and distributed sensing.The main attractive feature is that such a sensor network can be deployed in remote areas.Since the sensor node is battery powered,all the sensor nodes should collaborate together to form a fault tolerant network so as toprovide an efficient utilization of precious network resources like wireless channel,memory and battery capacity.The most crucial constraint is the energy consumption which has become the prime challenge for the design of long lived sensor nodes.

Speech sample estimation from composite zerocrossings and encoding via adaptive switching of transforms

This thesis investigates the potential use of zerocrossing information for speech sample estimation. It provides 21 new method tn) estimate speech samples using composite zerocrossings. A simple linear interpolation technique is developed for this purpose. By using this method the A/D converter can be avoided in a speech coder. The newly proposed zerocrossing sampling theory is supported with results of computer simulations using real speech data. The thesis also presents two methods for voiced/ unvoiced classification. One of these methods is based on a distance measure which is a function of short time zerocrossing rate and short time energy of the signal. The other one is based on the attractor dimension and entropy of the signal. Among these two methods the first one is simple and reguires only very few computations compared to the other. This method is used imtea later chapter to design an enhanced Adaptive Transform Coder. The later part of the thesis addresses a few problems in Adaptive Transform Coding and presents an improved ATC. Transform coefficient with maximum amplitude is considered as ‘side information’. This. enables more accurate tfiiz assignment enui step—size computation. A new bit reassignment scheme is also introduced in this work. Finally, sum ATC which applies switching between luiscrete Cosine Transform and Discrete Walsh-Hadamard Transform for voiced and unvoiced speech segments respectively is presented. Simulation results are provided to show the improved performance of the coder

Modified Block Adaptive Predictive Coder For Speech Processing

This thesis investigated the potential use of Linear Predictive Coding in speech communication applications. A Modified Block Adaptive Predictive Coder is developed, which reduces the computational burden and complexity without sacrificing the speech quality, as compared to the conventional adaptive predictive coding (APC) system. For this, changes in the evaluation methods have been evolved. This method is as different from the usual APC system in that the difference between the true and the predicted value is not transmitted. This allows the replacement of the high order predictor in the transmitter section of a predictive coding system, by a simple delay unit, which makes the transmitter quite simple. Also, the block length used in the processing of the speech signal is adjusted relative to the pitch period of the signal being processed rather than choosing a constant length as hitherto done by other researchers. The efficiency of the newly proposed coder has been supported with results of computer simulation using real speech data. Three methods for voiced/unvoiced/silent/transition classification have been presented. The first one is based on energy, zerocrossing rate and the periodicity of the waveform. The second method uses normalised correlation coefficient as the main parameter, while the third method utilizes a pitch-dependent correlation factor. The third algorithm which gives the minimum error probability has been chosen in a later chapter to design the modified coder The thesis also presents a comparazive study beh-cm the autocorrelation and the covariance methods used in the evaluaiicn of the predictor parameters. It has been proved that the azztocorrelation method is superior to the covariance method with respect to the filter stabf-it)‘ and also in an SNR sense, though the increase in gain is only small. The Modified Block Adaptive Coder applies a switching from pitch precitzion to spectrum prediction when the speech segment changes from a voiced or transition region to an unvoiced region. The experiments cont;-:ted in coding, transmission and simulation, used speech samples from .\£=_‘ajr2_1a:r1 and English phrases. Proposal for a speaker reecgnifion syste: and a phoneme identification system has also been outlized towards the end of the thesis.

An adaptive cluster based routing scheme for mobile wireless sensor networks

Clustering schemes improve energy efficiency of wireless sensor networks. The inclusion of mobility as a new criterion for the cluster creation and maintenance adds new challenges for these clustering schemes. Cluster formation and cluster head selection is done on a stochastic basis for most of the algorithms. In this paper we introduce a cluster formation and routing algorithm based on a mobility factor. The proposed algorithm is compared with LEACH-M protocol based on metrics viz. number of cluster head transitions, average residual energy, number of alive nodes and number of messages lost

Channel Adaptive MAC Protocol with Traffic-Aware Distributed Power Management in Wireless Sensor Networks-Some Performance Issues

In Wireless Sensor Networks (WSN), neglecting the effects of varying channel quality can lead to an unnecessary wastage of precious battery resources and in turn can result in the rapid depletion of sensor energy and the partitioning of the network. Fairness is a critical issue when accessing a shared wireless channel and fair scheduling must be employed to provide the proper flow of information in a WSN. In this paper, we develop a channel adaptive MAC protocol with a traffic-aware dynamic power management algorithm for efficient packet scheduling and queuing in a sensor network, with time varying characteristics of the wireless channel also taken into consideration. The proposed protocol calculates a combined weight value based on the channel state and link quality. Then transmission is allowed only for those nodes with weights greater than a minimum quality threshold and nodes attempting to access the wireless medium with a low weight will be allowed to transmit only when their weight becomes high. This results in many poor quality nodes being deprived of transmission for a considerable amount of time. To avoid the buffer overflow and to achieve fairness for the poor quality nodes, we design a Load prediction algorithm. We also design a traffic aware dynamic power management scheme to minimize the energy consumption by continuously turning off the radio interface of all the unnecessary nodes that are not included in the routing path. By Simulation results, we show that our proposed protocol achieves a higher throughput and fairness besides reducing the delay

Short-Term Load Forecast Of A Low Loadfactor Power System For Optimization Of Merit Order Dispatch Using Adaptive Learning Algorithm

Short term load forecasting is one of the key inputs to optimize the management of power system. Almost 60-65% of revenue expenditure of a distribution company is against power purchase. Cost of power depends on source of power. Hence any optimization strategy involves optimization in scheduling power from various sources. As the scheduling involves many technical and commercial considerations and constraints, the efficiency in scheduling depends on the accuracy of load forecast. Load forecasting is a topic much visited in research world and a number of papers using different techniques are already presented. The accuracy of forecast for the purpose of merit order dispatch decisions depends on the extent of the permissible variation in generation limits. For a system with low load factor, the peak and the off peak trough are prominent and the forecast should be able to identify these points to more accuracy rather than minimizing the error in the energy content. In this paper an attempt is made to apply Artificial Neural Network (ANN) with supervised learning based approach to make short term load forecasting for a power system with comparatively low load factor. Such power systems are usual in tropical areas with concentrated rainy season for a considerable period of the year