Pilot scale inulin extraction from chicory roots assisted by pulsed electric fields

A pilot study for the pulsed electric fields (PEF) assisted countercurrent diffusion of inulin from chicory roots is presented. The influence of PEF parameters (electric field intensity E = 600 V cm^?1, treatment duration t_PEF = 10–50 ms) and diffusion temperature (varied between 30 and 80 °C) on soluble matter extraction kinetics, inulin content of juice, and pulp exhaustion are investigated. The draft (liquid to solid mass ratio) was fixed at 140%, similar to the industrial conditions. PEF treatment facilitates extraction of inulin at conventional diffusion temperature (70–80 °C), and diffusion temperature can even be reduced by 10–15 °C with comparable juice inulin concentration. Less energy consumption can be achieved by reducing PEF treatment duration to 10 ms, which is observed sufficient for effective extraction.     

Trade and convergence of per capita income in the Indian Ocean Zone, 1950–2008

This empirical study of per capita income convergence across the countries of the Indian Ocean Zone (IOZ) during 1950–2008 relies on a distribution dynamics approach that employs both stochastic kernels (stacked and high-density region plots) and a nonparametric estimator. During this period, no absolute convergence process of incomes occurs in the IOZ. Nevertheless, a bipolar situation emerges, such that countries with the weakest relative incomes in relation to the IOZ average remain in the same relative position—that is, the poorest countries remain poor. The relatively richest countries (i.e., Australia, Malaysia, Mauritius, Singapore, and Thailand) constitute a convergence club. Use of conditioned distributions shows that the dynamics of per capita gross domestic product (GDP) distributions can be explained both by the openness rate measured as trade/GDP ratio, or a proxy for trade policy, and by manufactured goods exports. However, this result likely confirms that the openness was accompanied by an increase in manufactured goods trade for many of these countries. In addition, openness defined following Sachs and Warner has a less explanatory power than traditional measure. Finally, bilateral trade and trade agreements have limited effects.     

Cold weldability of aluminium: Contribution of the mechanical loadings to the formation of metallic bonds

In solid-state welding, temperature generally has an important role (diffusion, recrystallization, etc.) however, a mechanical loading is also necessary for breaking down the thin oxide layer (Al₂O₃) which naturally covers aluminium alloys. As the oxide layers have a melting point of around 2000 °C meanwhile aluminium alloys generally melt at only 600 °C; the heat supply alone cannot lead to the welding and a mechanical loading is always needed. This work aims at understanding the influence of the mechanical loadings on the formation of metallic bonds. To this end a new weldability test has been introduced. A symmetric cyclic shear is run on the welding interface without external heat supply. A tube-shaped sample is cut through its cross-section and undergone both a compression and a cyclic torsion loading. The influence of some parameters has been studied. Among them, surface condition (roughness and cleanliness), torsion angle (low amplitude) and number of cycles are the most significant. The welded joints have been then mechanically tested and microscopically observed (FEG-SEM and EBSD): the joining is achieved on a 1.5 μm thick layer, as things stand, on about 50% of the welding interface. Moreover, a thermomechanical model concludes that the internal intrinsic heat involved in this experimental process is too low to imply a significant increase of temperature in the specimen; thus the joining is only achieved due to mechanical effects of elastoplastic type.     

Are memory self-efficacy and memory performance related? A meta-analysis.

The association between memory self-efficacy (MSE) and memory performance is highly documented in the literature. However, previous studies have produced inconsistent results, and there is no consensus on the existence of a significant link between these two variables. In order to evaluate whether or not the effect size of the MSE–memory performance relationship in healthy adults is significant and to test several theory-driven moderators, we conducted a meta-analysis of published and unpublished studies. A random-effects model analysis of data from 107 relevant studies (673 effect sizes) indicated a low but significant weighted mean correlation between MSE and memory performance, r = .15, 95% CI [.13, .17]. In addition, the mean effect size was significantly moderated by the way MSE was assessed. Memory performance was more strongly related to concurrent MSE (perceived current ability to perform a given task) than it was to global MSE (perceived usual memory ability in general). Furthermore, we found marginally larger MSE–memory performance correlations when the memory situations used to assess MSE involved familiar stimuli. No effect of the method used to assess global MSE or domain MSE (memory rating vs. performance predictions) was found. The results also show that the resource demands of the memory tasks have a moderator effect, as the MSE–performance correlation is larger with free-recall and cued-recall tasks than it is with recognition tasks. Limitations (generalization issues, moderators not considered) and implications for future research are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Functional Segmentation of Renal DCE-MRI Sequences Using Vector Quantization Algorithms

In dynamic contrast-enhanced magnetic resonance imaging, segmentation of internal kidney structures like cortex, medulla and cavities is essential for functional assessment. To avoid fastidious and time-consuming manual segmentation, semi-automatic methods have been recently developed. Some of them use the differences between temporal contrast evolution in each anatomical region to perform functional segmentation. We test two methods where pixels are classified according to their time–intensity evolution. They both require a vector quantization stage with some unsupervised learning algorithm (K-means or Growing Neural Gas with targeting). Three or more classes are thus obtained. In the first case the method is completely automatic. In the second case, a restricted intervention by an observer is required for merging. As no ground truth is available for result evaluation, a manual anatomical segmentation is considered as a reference. Some discrepancy criteria like overlap, extra pixels and similarity index are computed between this segmentation and a functional one. The same criteria are also evaluated between the reference and another manual segmentation. Results are comparable for the two types of comparisons, proving that anatomical segmentation can be performed using functional information.     

Bipedal walking gait generation based on the Sequential Method of Analytical Potential (SMAP)

This paper presents a method we have called the Sequential Method of Analytical Potential (SMAP). By taking account of a system’s actual capabilities via Dynamic Propulsion Potentials (DPP), this method aims to generate dynamic walking gaits for bipedal robots. The objective is to move the robot by acting directly on the actuator forces. The various accelerations governing the movements of the robot are controlled by direct, precise modification of its own dynamic effects, taking account of the robot’s intrinsic dynamics as well as the capabilities of the actuators moving the joints.     

A unified short-channel compact model for cylindrical surrounding-gate MOSFET

For the first time, a continuous and explicit model valid in all operating regions, for undoped short-channel cylindrical gate-all-around (GAA) MOSFETs, is presented in this study. From a two-dimensional analysis, the threshold voltage roll-off, the drain-induced barrier lowering (DIBL) and the subthreshold swing are explicitly modeled. Short-channel effects are then implemented into a continuous drain-current model based on an effective surface potential approach using the gradual channel approximation. Improving the model behavior in the saturation operating region by accounting the channel pinch-off displacement, channel length modulation is studied and implemented as well. Analytical results are compared to TCAD-Atlas numerical simulations and validate the short-channel model in all operating modes making it suitable for circuit design simulations.     

Thirty years of urban regeneration in Britain,Germany and France: The importance of context and path dependency

It is a little over 30 years since Jim Callaghan's Labour Government passed the 1978 Inner Urban Areas Act. The following year marked a shift in power to Margaret Thatcher's Conservative Government and a very different approach to urban regeneration. These developments established and shaped the approach to urban regeneration in England for a generation. The economic context and the urban changes of the 1970s and 1980s and the nature of these responses put England at the forefront of the evolution of this type of urban policy in Europe. It is therefore timely to reflect on 30 years of urban regeneration and to do so from a comparative perspective, setting the English experience alongside that of Germany and France. In this paper the authors compare the experiences of these three countries. The great benefit of international comparison is that it allows the observer to step outside their own institutions and context, to compare with other countries and to look back at their own country from a new, foreign, perspective. The emphasis of this paper is on the contingent and contextualised nature of actions designed to foster urban regeneration. This reinforces the rationale for studying the evolution of this policy field in different nation-state settings.     

A new energy and natural resources investigation method: Geneva case studies

The Praille–Acacias–Vernets suburb, located in Geneva, Switzerland, is today considered as an outworn city area (2.3 km²). It consists of parking lots, industries, businesses and marshalling yards. The Geneva Government decided to remodel this suburb to effectively allow for city growth while complying with the highest energy efficient and environmental standards in urban development. A masterplan was accepted in spring 2007. It did not take into account the various energy and natural resources of the area at that stage.BG Consulting Engineers was thus mandated to assess a set of resources related to energy and environment, such as geothermal power or roundwater. For this purpose, a new investigation method was tested. It integrated the Deep City approach (Swiss Federal Institute of Technology, Lausanne), which promotes the sustainable use of urban underground resources.The BG method consisted in (1) establishing a geodatabase regrouping all available data (Geographic Information System), (2) identifying, localising and quantifying the different resources and (3) identifying and discussing all synergies and conflicts that might arise during their exploitation. This third step constitutes a real improvement allowing for anticipated decision making, thus avoiding future compatibility issues.Results of this study consisted in lists and maps of (1) raw resources, (2) technical and economical opportunities and constraints of exploitation, and (3) practical synergies and conflicts of exploitation. In addition, further necessary studies were identified along with synthetic scopes of work.Results were convincing and highly considered by the Geneva Government. For example, geothermal power resources were localised along with possible exploitation technologies and quantified extractable power. Synergies like combined exploitation of geothermal power and groundwater were also identified while conflicts such as spatial occupation were localised and discussed. These examples, among many others, validate this BG innovative method integrating the Deep City concept.     

Artificial intelligence tools and inverse methods for estimating the thermal diffusivity of building materials

The actual European energy context highlights the building sector as one of the largest sectors of energy consumption. Consequently, the “Energy Performance of Buildings Directive”, adopted in 2002 and focusing on energy use in buildings, requires all the EU members to enhance their building regulations and to introduce energy certification schemes, with the aim of both reducing energy consumption and improving energy efficiency. That is why carrying out an energy performance diagnosis is mandatory, notably when buying or selling properties. Indeed, invisible defaults, like, for example, non-emerging cracks or delaminations, could have a detrimental effect on insulating qualities. Esimaing in situ thermo-physical properties allowing locating these defaults, the present work focuses on proposing new and efficient approaches based on the use of both artificial intelligence tools (artificial neural networks and neuro-fuzzy systems) and inverse methods for characterizing building materials i.e. for estimating their thermal diffusivity using thermograms obtained thanks to a non-destructive photothermal method.