Directional DBS improves therapeutic window: from model prediction to human use

Deep brain stimulation of different targets has been shown to drastically improve symptoms of a variety of neurological conditions. However, the occurrence of disabling side effects may limit the ability to deliver adequate amounts of current necessary to reach the maximal benefit. Computed models have suggested that reduction in electrode size and the ability to provide directional stimulation could increase the efficacy of such therapies. This has never been demonstrated in humans. In the present study, we assess the effect of directional stimulation compared to omnidirectional stimulation.

The unstable CO2 feedback cycle on ocean planets

Ocean planets are volatile-rich planets, not present in our Solar system, which are thought to be dominated by deep, global oceans. This results in the formation of high-pressure water ice, separating the planetary crust from the liquid ocean and, thus, also from the atmosphere. Therefore, instead of a carbonate-silicate cycle like on the Earth, the atmospheric carbon dioxide concentration is governed by the capability of the ocean to dissolve carbon dioxide (CO2). In our study, we focus on the CO2 cycle between the atmosphere and the ocean which determines the atmospheric CO2 content. The atmospheric amount of CO2 is a fundamental quantity for assessing the potential habitability of the planet's surface because of its strong greenhouse effect, which determines the planetary surface temperature to a large degree. In contrast to the stabilizing carbonate-silicate cycle regulating the long-term CO2 inventory of the Earth atmosphere, we find that the CO2 cycle feedback on ocean planets is negative and has strong destabilizing effects on the planetary climate. By using a chemistry model for oceanic CO2 dissolution and an atmospheric model for exoplanets, we show that the CO2 feedback cycle can severely limit the extension of the habitable zone for ocean planets.

Relative abundance of pteropod species of the plankton pump samples in the surface water of the eastern North Atlantic Ocean (Table 4)

Plankton pump samples and plankton tows (size fractions between 0.04 mm and 1.01 mm) from the eastern North Atlantic Ocean contain the following shell- and skeleton-producing planktonic and nektonic organisms, which can be fossilized in the sediments: diatoms, radiolarians, foraminifers, pteropods, heteropods, larvae of benthic gastropods and bivalves, ostracods, and fish. The abundance of these components has been mapped quantitatively in the eastern North Atlantic surface waters in October - December 1971. More ash (after ignition of the organic matter, consisting mostly of these components) per cubic meter of water is found close to land masses (continents and islands) and above shallow submarine elevations than in the open ocean. Preferred biotops of planktonic diatoms in the region described are temperate shallow water and tropical coastal upwelling areas. Radiolarians rarely occur close to the continent, but are abundant in pelagic warm water masses, even near islands. Foraminifers are similar to the radiolarians, rarer in the coastal water mass of the continent than in the open ocean or off oceanic islands. Their abundance is highest outside the upwelling area off NW Africa. Molluscs generally outnumber planktonic foraminifers, implying that the carbonate cycle of the ocean might be influenced considerably by these animals. The molluscs include heteropods, pteropods, and larvae of benthic bivalves and gastropods. Larvae of benthic molluscs occur more frequently close to continental and island margins and above submarine shoals (in this case mostly guyots) than in the open ocean. Their size increases, but they decrease in number with increasing distance from their area of origin. Ostracods and fish have only been found in small numbers concentrated off NW Africa. All of the above-mentioned components occur in higher abundances in the surface water than in subsurface waters. They are closely related to the hydrography of the sampled water masses (here defined through temperature measurements). Relatively warm water masses of the southeastern branches of the Gulf Stream system transport subtropical and southern temperate species to the Bay of Biscay, relatively cool water masses of the Portugal and Canary Currents carry transitional faunal elements along the NW African coast southwards to tropical regions. These mix in the northwest African upwelling area with tropical faunal elements which are generally assumed to live in the subsurface water masses and which probably have been transported northwards to this area by a subsurface counter current. The faunas typical for tropical surface water masses are not only reduced due to the tongue of cool water extending southwards along the coast, but they are also removed from the coastal zone by the upwelling subsurface water masses carrying their own shell and skeleton assemblages. Tropical water masses contain much more shelland skeleton-producing plankters than subtropical and temperate ones. The climatic conditions found at different latitudes control the development and intensity of a separate continental coastal water mass with its own plankton assemblages. Extent of this water mass and steepness of gradients between the pelagic and coastal environment limit the occurrence of pelagic plankton close to the continental coast. A similar water mass in only weakly developed off oceanic islands.

HF spectrum activity prediction model based on HMM for cognitive radio applications

Although most of the research on Cognitive Radio is focused on communication bands above the HF upper limit (30 MHz), Cognitive Radio principles can also be applied to HF communications to make use of the extremely scarce spectrum more efficiently. In this work we consider legacy users as primary users since these users transmit without resorting to any smart procedure, and our stations using the HFDVL (HF Data+Voice Link) architecture as secondary users. Our goal is to enhance an efficient use of the HF band by detecting the presence of uncoordinated primary users and avoiding collisions with them while transmitting in different HF channels using our broad-band HF transceiver. A model of the primary user activity dynamics in the HF band is developed in this work to make short-term predictions of the sojourn time of a primary user in the band and avoid collisions. It is based on Hidden Markov Models (HMM) which are a powerful tool for modelling stochastic random processes and are trained with real measurements of the 14 MHz band. By using the proposed HMM based model, the prediction model achieves an average 10.3% prediction error rate with one minute-long channel knowledge but it can be reduced when this knowledge is extended: with the previous 8 min knowledge, an average 5.8% prediction error rate is achieved. These results suggest that the resulting activity model for the HF band could actually be used to predict primary users activity and included in a future HF cognitive radio based station.

Analysis of pixel-mapping rounding on geometric distortion as a prediction for view synthesis distortion

We analyze the performance of the geometric distortion, incurred when coding depth maps in 3D Video, as an estimator of the distortion of synthesized views. Our analysis is motivated by the need of reducing the computational complexity required for the computation of synthesis distortion in 3D video encoders. We propose several geometric distortion models that capture (i) the geometric distortion caused by the depth coding error, and (ii) the pixel-mapping precision in view synthesis. Our analysis starts with the evaluation of the correlation of geometric distortion values obtained with these models and the actual distortion on synthesized views. Then, the different geometric distortion models are employed in the rate-distortion optimization cycle of depth map coding, in order to assess the results obtained by the correlation analysis. Results show that one of the geometric distortion models is performing consistently better than the other models in all tests. Therefore, it can be used as a reasonable estimator of the synthesis distortion in low complexity depth encoders.

Supercritical Steam power cycle for Line-Focus Solar Power Plants

The supercritical Rankine power cycle offers a net improvement in plant efficiency compared with a subcritical Rankine cycle. For fossil power plants the minimum supercritical steam turbine size is about 450MW. A recent study between Sandia National Laboratories and Siemens Energy, Inc., published on March 2013, confirmed the feasibility of adapting the Siemens turbine SST-900 for supercritical steam in concentrated solar power plants, with a live steam conditions 230-260 bar and output range between 140-200 MWe. In this context, this analysis is focused on integrating a line-focus solar field with a supercritical Rankine power cycle. For this purpose two heat transfer fluids were assessed: direct steam generation and molten salt Hitec XL. To isolate solar field from high pressure supercritical water power cycle, an intermediate heat exchanger was installed between linear solar collectors and balance of plant. Due to receiver selective coating temperature limitations, turbine inlet temperature was fixed 550ºC. The design-point conditions were 550ºC and 260 bar at turbine inlet, and 165 MWe Gross power output. Plant performance was assessed at design-point in the supercritical power plant (between 43-45% net plant efficiency depending on balance of plantconfiguration), and in the subcritical plant configuration (~40% net plant efficiency). Regarding the balance of plant configuration, direct reheating was adopted as the optimum solution to avoid any intermediate heat exchanger. One direct reheating stage between high pressure turbine and intermediate pressure turbine is the common practice; however, General Electric ultrasupercritical(350 bar) fossil power plants also considered doubled-reheat applications. In this study were analyzed heat balances with single-reheat, double-reheat and even three reheating stages. In all cases were adopted the proper reheating solar field configurations to limit solar collectors pressure drops. As main conclusion, it was confirmed net plant efficiency improvements in supercritical Rankine line-focus (parabolic or linear Fresnel) solar plant configurations are mainly due to the following two reasons: higher number of feed-water preheaters (up to seven)delivering hotter water at solar field inlet, and two or even three direct reheating stages (550ºC reheating temperature) in high or intermediate pressure turbines. However, the turbine manufacturer should confirm the equipment constrains regarding reheating stages and number of steam extractions to feed-water heaters.

Computation, prediction, and experimental tests of fitness for bacteriophage T7 mutants with permuted genomes

We created a simulation based on experimental data from bacteriophage T7 that computes the developmental cycle of the wild-type phage and also of mutants that have an altered genome order. We used the simulation to compute the fitness of more than 105 mutants. We tested these computations by constructing and experimentally characterizing T7 mutants in which we repositioned gene 1, coding for T7 RNA polymerase. Computed protein synthesis rates for ectopic gene 1 strains were in moderate agreement with observed rates. Computed phage-doubling rates were close to observations for two of four strains, but significantly overestimated those of the other two. Computations indicate that the genome organization of wild-type T7 is nearly optimal for growth: only 2.8% of random genome permutations were computed to grow faster, the highest 31% faster, than wild type. Specific discrepancies between computations and observations suggest that a better understanding of the translation efficiency of individual mRNAs and the functions of qualitatively “nonessential” genes will be needed to improve the T7 simulation. In silico representations of biological systems can serve to assess and advance our understanding of the underlying biology. Iteration between computation, prediction, and observation should increase the rate at which biological hypotheses are formulated and tested.

Contribution of Malic Enzyme, Pyruvate Kinase, Phosphoenolpyruvate Carboxylase, and the Krebs Cycle to Respiration and Biosynthesis and to Intracellular pH Regulation during Hypoxia in Maize Root Tips Observed by Nuclear Magnetic Resonance Imaging and Gas Chromatography-Mass Spectrometry1

In vivo pyruvate synthesis by malic enzyme (ME) and pyruvate kinase and in vivo malate synthesis by phosphoenolpyruvate carboxylase and the Krebs cycle were measured by 13C incorporation from [1-13C]glucose into glucose-6-phosphate, alanine, glutamate, aspartate, and malate. These metabolites were isolated from maize (Zea mays L.) root tips under aerobic and hypoxic conditions. 13C-Nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to discern the positional isotopic distribution within each metabolite. This information was applied to a simple precursor-product model that enabled calculation of specific metabolic fluxes. In respiring root tips, ME was found to contribute only approximately 3% of the pyruvate synthesized, whereas pyruvate kinase contributed the balance. The activity of ME increased greater than 6-fold early in hypoxia, and then declined coincident with depletion of cytosolic malate and aspartate. We found that in respiring root tips, anaplerotic phosphoenolpyruvate carboxylase activity was high relative to ME, and therefore did not limit synthesis of pyruvate by ME. The significance of in vivo pyruvate synthesis by ME is discussed with respect to malate and pyruvate utilization by isolated mitochondria and intracellular pH regulation under hypoxia.

Rock friction and its implications for earthquake prediction examined via models of Parkfield earthquakes.

The friction of rocks in the laboratory is a function of time, velocity of sliding, and displacement. Although the processes responsible for these dependencies are unknown, constitutive equations have been developed that do a reasonable job of describing the laboratory behavior. These constitutive laws have been used to create a model of earthquakes at Parkfield, CA, by using boundary conditions appropriate for the section of the fault that slips in magnitude 6 earthquakes every 20-30 years. The behavior of this model prior to the earthquakes is investigated to determine whether or not the model earthquakes could be predicted in the real world by using realistic instruments and instrument locations. Premonitory slip does occur in the model, but it is relatively restricted in time and space and detecting it from the surface may be difficult. The magnitude of the strain rate at the earth's surface due to this accelerating slip seems lower than the detectability limit of instruments in the presence of earth noise. Although not specifically modeled, microseismicity related to the accelerating creep and to creep events in the model should be detectable. In fact the logarithm of the moment rate on the hypocentral cell of the fault due to slip increases linearly with minus the logarithm of the time to the earthquake. This could conceivably be used to determine when the earthquake was going to occur. An unresolved question is whether this pattern of accelerating slip could be recognized from the microseismicity, given the discrete nature of seismic events. Nevertheless, the model results suggest that the most likely solution to earthquake prediction is to look for a pattern of acceleration in microseismicity and thereby identify the microearthquakes as foreshocks.

Safety consequences of raising the national speed limit from 55 mph to 60 mph. Technical report.

Mode of access: Internet.

Structural basis and prediction of substrate specificity in protein serine/threonine kinases

The large number of protein kinases makes it impractical to determine their specificities and substrates experimentally. Using the available crystal structures, molecular modeling, and sequence analyses of kinases and substrates, we developed a set of rules governing the binding of a heptapeptide substrate motif (surrounding the phosphorylation site) to the kinase and implemented these rules in a web-interfaced program for automated prediction of optimal substrate peptides, taking only the amino acid sequence of a protein kinase as input. We show the utility of the method by analyzing yeast cell cycle control and DNA damage checkpoint pathways. Our method is the only available predictive method generally applicable for identifying possible substrate proteins for protein serine/threonine kinases and helps in silico construction of signaling pathways. The accuracy of prediction is comparable to the accuracy of data from systematic large-scale experimental approaches.

Wind power forecasts using Gaussian processes and numerical weather prediction

Since wind at the earth's surface has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safe and economic use of wind energy. In this paper, we investigated a combination of numeric and probabilistic models: a Gaussian process (GP) combined with a numerical weather prediction (NWP) model was applied to wind-power forecasting up to one day ahead. First, the wind-speed data from NWP was corrected by a GP, then, as there is always a defined limit on power generated in a wind turbine due to the turbine controlling strategy, wind power forecasts were realized by modeling the relationship between the corrected wind speed and power output using a censored GP. To validate the proposed approach, three real-world datasets were used for model training and testing. The empirical results were compared with several classical wind forecast models, and based on the mean absolute error (MAE), the proposed model provides around 9% to 14% improvement in forecasting accuracy compared to an artificial neural network (ANN) model, and nearly 17% improvement on a third dataset which is from a newly-built wind farm for which there is a limited amount of training data. © 2013 IEEE.

Towards the prediction of mutations in genomic sequences

Bio-systems are inherently complex information processing systems. Furthermore, physiological complexities of biological systems limit the formation of a hypothesis in terms of behavior and the ability to test hypothesis. More importantly the identification and classification of mutation in patients are centric topics in today's cancer research. Next generation sequencing (NGS) technologies can provide genome-wide coverage at a single nucleotide resolution and at reasonable speed and cost. The unprecedented molecular characterization provided by NGS offers the potential for an individualized approach to treatment. These advances in cancer genomics have enabled scientists to interrogate cancer-specific genomic variants and compare them with the normal variants in the same patient. Analysis of this data provides a catalog of somatic variants, present in tumor genome but not in the normal tissue DNA. In this dissertation, we present a new computational framework to the problem of predicting the number of mutations on a chromosome for a certain patient, which is a fundamental problem in clinical and research fields. We begin this dissertation with the development of a framework system that is capable of utilizing published data from a longitudinal study of patients with acute myeloid leukemia (AML), who's DNA from both normal as well as malignant tissues was subjected to NGS analysis at various points in time. By processing the sequencing data at the time of cancer diagnosis using the components of our framework, we tested it by predicting the genomic regions to be mutated at the time of relapse and, later, by comparing our results with the actual regions that showed mutations (discovered at relapse time). We demonstrate that this coupling of the algorithm pipeline can drastically improve the predictive abilities of searching a reliable molecular signature. Arguably, the most important result of our research is its superior performance to other methods like Radial Basis Function Network, Sequential Minimal Optimization, and Gaussian Process. In the final part of this dissertation, we present a detailed significance, stability and statistical analysis of our model. A performance comparison of the results are presented. This work clearly lays a good foundation for future research for other types of cancer.^

Analyse multidimensionnelle de la persévérance aux études universitaires de premier cycle

L’abandon des études universitaires a attiré l’attention de plusieurs chercheurs. Toutefois, il est difficile de saisir la persévérance dans sa globalité à cause de sa complexité et le nombre important des facteurs associés. La persévérance aux études est liée aux facteurs individuels, aux facteurs contextuels et à la situation financière au cours des études. Ces facteurs ont été étudiés séparément et d’une manière isolée, et aucune étude n’a, à notre connaissance, tenté de mettre ces facteurs simultanément dans un même modèle. Dans cette thèse, nous identifions les principaux déterminants de la persévérance, tout en nous appuyant sur le modèle des attentes et des valeurs (Eccles et al., 1983), le modèle interactionnel de Tinto (1975) et les modèles d’impact financier (Paulsen & St. John, 1997; St. John, 1990; St. John et al., 1994). Cette thèse a pour objectif de valider un modèle de persévérance aux études universitaires de premier cycle. Celle-ci comporte deux études. Une étude rétrospective qui permet d’évaluer, à partir de l’expérience antérieure des étudiants (n = 731), les principaux facteurs qui ont joué un rôle sur le plan de la persévérance ou de l’abandon des études. Une étude prospective suivant sur une période de six mois (deux temps de mesure) des étudiants inscrits dans un programme de baccalauréat à l’Université Laval (n = 3 084). Pour les résultats de l’étude rétrospective, la situation financière, les performances scolaires antérieures et le fait d’avoir effectué des études préuniversitaires au Cégep prédisent la persévérance. Pour le premier temps de mesure de l’étude prospective, la perception de compétence, les attentes de succès et l’intérêt prédisent l’intention de persévérer. Deux facteurs interactionnels prédisent l’intention de persévérer à savoir : les interactions avec les pairs et l’engagement institutionnel et universitaire. En ce qui concerne le deuxième temps de mesure de l’étude prospective, l’intention de persévérer, la préoccupation de la Faculté par rapport à l’enseignement et au développement des étudiants, le développement intellectuel et académique ainsi que le fait d’avoir fait des études préuniversitaires au Cégep prédisent la persévérance. Les implications théoriques, méthodologiques et pratiques sont abordées et des pistes de recherches futures sont proposées.

Diversité microbienne associée au cycle du méthane dans les mares de fonte du pergélisol subarctique

La fonte et l’effondrement du pergélisol riche en glace dans la région subarctique du Québec ont donné lieu à la formation de petits lacs (mares de thermokarst) qui émettent des gaz à effet de serre dans l’atmosphère tels que du dioxyde de carbone et du méthane. Pourtant, la composition de la communauté microbienne qui est à la base des processus biogéochimiques dans les mares de fonte a été très peu étudiée, particulièrement en ce qui concerne la diversité et l’activité des micro-organismes impliqués dans le cycle du méthane. L’objectif de cette thèse est donc d’étudier la diversité phylogénétique et fonctionnelle des micro-organismes dans les mares de fonte subarctiques en lien avec les caractéristiques de l’environnement et les émissions de méthane. Pour ce faire, une dizaine de mares ont été échantillonnées dans quatre vallées situées à travers un gradient de fonte du pergélisol, et disposant de différentes propriétés physico-chimiques. Selon les vallées, les mares peuvent être issues de la fonte de palses (buttes de tourbe, à dominance organique) ou de lithalses (buttes de sol à dominance minérale) ce qui influence la nature du carbone organique disponible pour la reminéralisation microbienne. Durant l’été, les mares étaient fortement stratifiées; il y avait un fort gradient physico-chimique au sein de la colonne d’eau, avec une couche d’eau supérieure oxique et une couche d’eau profonde pauvre en oxygène ou anoxique. Pour identifier les facteurs qui influencent les communautés microbiennes, des techniques de séquençage à haut débit ont été utilisées ciblant les transcrits des gènes de l’ARNr 16S et des gènes impliqués dans le cycle du méthane : mcrA pour la méthanogenèse et pmoA pour la méthanotrophie. Pour évaluer l’activité des micro-organismes, la concentration des transcrits des gènes fonctionnels a aussi été mesurée avec des PCR quantitatives (qPCR). Les résultats montrent une forte dominance de micro-organismes impliqués dans le cycle du méthane, c’est-à-dire des archées méthanogènes et des bactéries méthanotrophes. L’analyse du gène pmoA indique que les bactéries méthanotrophes n’étaient pas seulement actives à la surface, mais aussi dans le fond de la mare où les concentrations en oxygène étaient minimales; ce qui est inattendu compte tenu de leur besoin en oxygène pour consommer le méthane. En général, la composition des communautés microbiennes était principalement influencée par l’origine de la mare (palse ou lithalse), et moins par le gradient de dégradation du pergélisol. Des variables environnementales clefs comme le pH, le phosphore et le carbone organique dissous, contribuent à la distinction des communautés microbiennes entre les mares issues de palses ou de lithalses. Avec l’intensification des effets du réchauffement climatique, ces communautés microbiennes vont faire face à des changements de conditions qui risquent de modifier leur composition taxonomique, et leurs réponses aux changements seront probablement différentes selon le type de mares. De plus, dans le futur les conditions d’oxygénation au sein des mares seront soumises à des modifications majeures associées avec un changement dans la durée des périodes de fonte de glace et de stratification. Ce type de changement aura un impact sur l’équilibre entre la méthanogenèse et la méthanotrophie, et affectera ainsi les taux d’émissions de méthane. Cependant, les résultats obtenus dans cette thèse indiquent que les archées méthanogènes et les bactéries méthanotrophes peuvent développer des stratégies pour survivre et rester actives au-delà des limites de leurs conditions d’oxygène habituelles.