Resolution prediction and optimization of temperature programme in comprehensive two-dimensional gas chromatography

A model is developed for predicting the resolution of interested component pair and calculating the optimum temperature programming condition in the comprehensive two-dimensional gas chromatography (GC x GC). Based on at least three isothermal runs, retention times and the peak widths at half-height on both dimensions are predicted for any kind of linear temperature-programmed run on the first dimension and isothermal runs on the second dimension. The calculation of the optimum temperature programming condition is based on the prediction of the resolution of "difficult-to-separate components" in a given mixture. The resolution of all the neighboring peaks on the first dimension is obtained by the predicted retention time and peak width on the first dimension, the resolution on the second dimension is calculated only for the adjacent components with un-enough resolution on the first dimension and eluted within a same modulation period on the second dimension. The optimum temperature programming condition is acquired when the resolutions of all components of interest by GC x GC separation meet the analytical requirement and the analysis time is the shortest. The validity of the model has been proven by using it to predict and optimize GC x GC temperature programming condition of an alkylpyridine mixture. (c) 2005 Elsevier B.V. All rights reserved.

Preparing students for interprofessional practice: exploring the intra-personal dimension

This paper appears in the Canadian-based, leading interprofessional education journal. Pre-qualification healthcare education can be viewed as having three inter-related components, intra-professional, interprofessional and intra-personal learning; the third of these underpinning the other two. Understanding more about personal learning needs can contribute to preparation for interprofessional interaction. A Studying and Learning Preferences Inventory (SALPI) was developed and validated for use with a range of healthcare professionals to assist in this process.

The EU Constitution of Social Governance in an Economic Crisis: in Defence of a Transnational Dimension to Social Europe

Conventional wisdom has it that the EU is unable to promote viable social integration, which contrasts with its commitments to improving working and living conditions and to social values and goals such as solidarity, social protection and social inclusion. This
article challenges two diff erent standpoints: on the one hand, competitive neoliberalism demands that the EU focuses on economic integration through legally binding internal market and competition rules even if Member States can only maintain a limited commitment to social inclusion, while authors defending the social models unique to the continent of Europe demand that the EU rescinds some of its established legal principles in order to make breathing space for Member States to maintain market correcting social policies. Both positions convene that there should be no genuine social policy at EU level.
This article uses scenarios of widely discussed rulings by the Court of Justice to illustrate that legally enforceable economic integration would prevent most Member States from achieving sustainable health services, labour relations and free university education on the basis of national closure. Since the EU has limited legislative competences to create EU level institutions to balance inequalities, it derives a Constitution of Social Governance from the EU’s values, proposing that the Court of Justice develops its urisprudence into an instrument for challenging European disunion induced by new EU economic governance

Perspectives on social citizenship in the EU – from status positivus to status socialis activus via two forms of transnational solidarity

Ever since the inauguration of EU citizenship, elements of social citizenship have been on the agenda of European integration. European level social benefits were proposed early on, and demands for collective labour rights have followed suit. This chapter uses the theoretical umbrella of transnational social citizenship in order to link transnational access to social benefits and collective labour rights. It promotes transnational rights as the best way to conceptualise EU social citizenship as an institution enabling the enjoyment of EU integration without being forced to forego social rights at other levels. Such a perspective sits well in a collection on EU citizenship and federalism, since it simultaneously challenges demands of renationalisation of social rights in the EU and pleas to reduce EU-level citizenship rights to a merely liberal dimension. Social citizenship as promoted here requires an interactive conceptualisation of regulatory and judicial powers at different levels of government as typical for federal systems.
In linking citizenship with human rights the chapter highlights different statuses of citizens. It argues that the rights constituted by social citizenship derive from a status positivus and a status socialis activus, expanding the time-honoured categories of Jellinek. This concept is developed further by linking the notions of receptive solidarity to the status positivus and the notion of participative solidarity to the status socialis activus. In relation to European Union citizenship it promotes a sustainable transnational social citizenship catering for receptive and participative solidarity.
These ideas contrast with most current discourses on EU citizenship. The stress on social citizenship takes issue with a retreat to mere liberalist notions of EU-level citizenship, and the stress on rights takes issue with conceptualising EU citizenship as a community bond with obligations, downplaying the empowering potential of rights. The difficulty of conceptualising transnational social citizenship is to avoid, on the one hand, taking up the tune of populist discourses imagining those moving beyond state borders as a threat to national social citizenship and, on the other hand, to reject the legitimate fears of those remaining at home of creating rupture in the social fabric of Europe’s society. Promoting transnational social citizenship rights based on receptive and participative solidarity the present chapter aims to contribute to avoiding these pitfalls.

Unveiling the Influence of Consumer Wine Appreciation Dimension on Purchasing Behavior

Consumption values and different usage situations have received extensive interest from scholars; however, there is a lack of understanding regarding how these two constructs interact when it comes to the purchase decisions of consumers. This study examines the relationship between consumption values, consumption situations, and consumers’ purchasing decisions in terms of their willingness to pay and the purchase quantity. First of all, my model proposes that all four consumption values and different situations have a positive effect on consumers’ willingness to pay as well as the quantity they purchase. It also proposes that varying usage situations moderate the effect of consumption values on consumers’ purchasing decisions. In my conceptual model, I have also integrated the epistemic and conditional values where there is a gap in the existing literature. Prior literature has isolated the consumption values when studying how they affect consumer behavior and has not examined how consumption situations moderate the relationship between consumption values and purchasing decisions. Also, the existing literature has mostly focused on how consumption values affect purchase intentions, brand loyalty, or satisfaction, whereas my study focuses on purchasing decisions. For my study, the participants were randomly chosen from the general wine consumer population and the age range was between 20 and 75, which included 83 male respondents and 119 female respondents. The data received from my respondents support my hypotheses for the model. In my final chapter, I discuss the theoretical and managerial implications as well as suggestions for future research.

La dimension humaine des enjeux environnementaux dans un bassin versant au Brésil

RÉSUMÉ La richesse en ressources naturelles est une source de développement économique et social, mais peut également constituer un facteur de dégradation environnementale et de problèmes pour la santé humaine. Les systèmes techniques de gestion des ressources naturelles ne sont pas suffisants pour apporter des solutions à tous les problèmes environnementaux. Mises à part les catastrophes naturelles, c'est l'intervention humaine qui cause la grande majorité des problèmes environnementaux. C'est pour comprendre cette dynamique entre les facteurs naturels et les facteurs économiques, sociaux, politiques, culturels et psychosociologiques que nous avons choisi de centrer cette thèse sur la dimension humaine des problèmes environnementaux – ce qui implique l'analyse des dimensions psychosociologiques et sociales entourant les problèmes environnementaux. Pour une gestion efficace des ressources naturelles, il nous faut donc comprendre l'action humaine, ses motivations et ses contraintes, ses orientations de valeurs et ses croyances, qui orientent les perceptions, les attitudes et les comportements humains par rapport à leur environnement. Pour ce faire, l’étude de valeurs, attitudes, croyances et comportements passe par l’examen attentif des concepts et de leurs définitions, ainsi que par l’analyse des diverses « dimensions » auxquelles chacun des concepts fait référence. Cette thèse porte justement sur les relations entre les valeurs, les croyances, les attitudes et les comportements humains par rapport aux problèmes environnementaux. Pour ce faire, nous avons utilisé un sondage auprès de 1800 répondants, habitants de la région du bassin versant de la Rio das Velhas, située dans la province du Minas Gerais, au Brésil.

Urban Detection From Hyperspectral Images Using Dimension-Reduction Model and Fusion of Multiple Segmentations Based on Stuctural and Textural Features

Ce mémoire de maîtrise présente une nouvelle approche non supervisée pour détecter et segmenter les régions urbaines dans les images hyperspectrales. La méthode proposée n ́ecessite trois étapes. Tout d’abord, afin de réduire le coût calculatoire de notre algorithme, une image couleur du contenu spectral est estimée. A cette fin, une étape de réduction de dimensionalité non-linéaire, basée sur deux critères complémentaires mais contradictoires de bonne visualisation; à savoir la précision et le contraste, est réalisée pour l’affichage couleur de chaque image hyperspectrale. Ensuite, pour discriminer les régions urbaines des régions non urbaines, la seconde étape consiste à extraire quelques caractéristiques discriminantes (et complémentaires) sur cette image hyperspectrale couleur. A cette fin, nous avons extrait une série de paramètres discriminants pour décrire les caractéristiques d’une zone urbaine, principalement composée d’objets manufacturés de formes simples g ́eométriques et régulières. Nous avons utilisé des caractéristiques texturales basées sur les niveaux de gris, la magnitude du gradient ou des paramètres issus de la matrice de co-occurrence combinés avec des caractéristiques structurelles basées sur l’orientation locale du gradient de l’image et la détection locale de segments de droites. Afin de réduire encore la complexité de calcul de notre approche et éviter le problème de la ”malédiction de la dimensionnalité” quand on décide de regrouper des données de dimensions élevées, nous avons décidé de classifier individuellement, dans la dernière étape, chaque caractéristique texturale ou structurelle avec une simple procédure de K-moyennes et ensuite de combiner ces segmentations grossières, obtenues à faible coût, avec un modèle efficace de fusion de cartes de segmentations. Les expérimentations données dans ce rapport montrent que cette stratégie est efficace visuellement et se compare favorablement aux autres méthodes de détection et segmentation de zones urbaines à partir d’images hyperspectrales.

Bounding The Hochschild Cohomological Dimension

Ce mémoire a deux objectifs principaux. Premièrement de développer et interpréter les groupes de cohomologie de Hochschild de basse dimension et deuxièmement de borner la dimension cohomologique des k-algèbres par dessous; montrant que presque aucune k-algèbre commutative est quasi-libre.

A unified framework for the comprehension of software's time dimension

Les logiciels sont de plus en plus complexes et leur développement est souvent fait par des équipes dispersées et changeantes. Par ailleurs, de nos jours, la majorité des logiciels sont recyclés au lieu d’être développés à partir de zéro. La tâche de compréhension, inhérente aux tâches de maintenance, consiste à analyser plusieurs dimensions du logiciel en parallèle. La dimension temps intervient à deux niveaux dans le logiciel : il change durant son évolution et durant son exécution. Ces changements prennent un sens particulier quand ils sont analysés avec d’autres dimensions du logiciel. L’analyse de données multidimensionnelles est un problème difficile à résoudre. Cependant, certaines méthodes permettent de contourner cette difficulté. Ainsi, les approches semi-automatiques, comme la visualisation du logiciel, permettent à l’usager d’intervenir durant l’analyse pour explorer et guider la recherche d’informations. Dans une première étape de la thèse, nous appliquons des techniques de visualisation pour mieux comprendre la dynamique des logiciels pendant l’évolution et l’exécution. Les changements dans le temps sont représentés par des heat maps. Ainsi, nous utilisons la même représentation graphique pour visualiser les changements pendant l’évolution et ceux pendant l’exécution. Une autre catégorie d’approches, qui permettent de comprendre certains aspects dynamiques du logiciel, concerne l’utilisation d’heuristiques. Dans une seconde étape de la thèse, nous nous intéressons à l’identification des phases pendant l’évolution ou pendant l’exécution en utilisant la même approche. Dans ce contexte, la prémisse est qu’il existe une cohérence inhérente dans les évènements, qui permet d’isoler des sous-ensembles comme des phases. Cette hypothèse de cohérence est ensuite définie spécifiquement pour les évènements de changements de code (évolution) ou de changements d’état (exécution). L’objectif de la thèse est d’étudier l’unification de ces deux dimensions du temps que sont l’évolution et l’exécution. Ceci s’inscrit dans notre volonté de rapprocher les deux domaines de recherche qui s’intéressent à une même catégorie de problèmes, mais selon deux perspectives différentes.

Influence of pre-plant densities of Meloidogyne incognita on growth and root infestation of spinach (Spinacia oleracea L.) (Amaranthaceae) – an important dimension towards enhancing crop production

Vegetables represent a main source of micro-nutrients which can improve the health status of malnourished poor in the world. Spinach (Spinacia oleracea L.) is a popular leafy vegetable in many countries which is rich with several important micro-nutrients. Thus, consuming Spinach helps to overcome micro-nutrient deficiencies. Pests and pathogens act as major yield constraints in food production. Root-knot nematodes, Meloidogyne species, constitute a large group of highly destructive plant pests. Spinach is found to be highly susceptible for these nematode attacks. Though agricultural production has largely benefited from modern technologies and innovations, some important dimensions which can minimize the yield losses have been neglected by most of the growers. Pre-plant or initial nematode density in soil is a crucial biotic factor which is directly responsible for crop losses. Hence, information on preplant nematode densities and the corresponding damage is of vital importance to develop successful control procedures to enhance crop production. In the present study, effect of seven initial densities of M. incognita, i.e., 156, 312, 625, 1250, 2,500, 5,000 and 10,000 infective juveniles (IJs)/plant (equivalent to 1000cm3 soil) on the growth and root infestation on potted spinach plants was determined in a screen house. In order to ensure a high accuracy, root infestation was ascertained by the number of galls formed, the percentage galled-length of feeder roots and galled-feeder roots, and egg production, per plant. Fifty days post-inoculation, shoot length and weight, and root length were suppressed at the lowest IJs density. However, the pathogenic effect was pronounced at the highest density at which 43%, 46% and 45% reduction in shoot length and weight, and root length, respectively, was recorded. The highest reduction in root weight (26%) was detected at the second highest density. The Number of galls and percentage galled-length of feeder roots/per plant showed significant progressive increase across the increasing IJs density with the highest mean value of 432.3 and 54%, respectively. The two shoot growth parameters and root length showed significant inverse relationship with the increasing gall formation. Moreover, the shoot and root length were shown to be mutually dependent on each other. Suppression of shoot growth of spinach greatly affects the grower’s economy. Hence, control measures are essentially needed to ensure a better production of spinach via reducing the pre-plant density below the level of 0.156 IJs/cm3.

Fronts from complex two-dimensional dispersal kernels: theory and application to Reid's paradox

Bimodal dispersal probability distributions with characteristic distances differing by several orders of magnitude have been derived and favorably compared to observations by Nathan [Nature (London) 418, 409 (2002)]. For such bimodal kernels, we show that two-dimensional molecular dynamics computer simulations are unable to yield accurate front speeds. Analytically, the usual continuous-space random walks (CSRWs) are applied to two dimensions. We also introduce discrete-space random walks and use them to check the CSRW results (because of the inefficiency of the numerical simulations). The physical results reported are shown to predict front speeds high enough to possibly explain Reid's paradox of rapid tree migration. We also show that, for a time-ordered evolution equation, fronts are always slower in two dimensions than in one dimension and that this difference is important both for unimodal and for bimodal kernels

A finite difference scheme for steady, supersonic, two-dimensional, compressible flow of real gases

A finite difference scheme is presented for the solution of the two-dimensional equations of steady, supersonic, compressible flow of real gases. The scheme incorparates numerical characteristic decomposition, is shock-capturing by design and incorporates space-marching as a result of the assumption that the flow is wholly supersonic in at least one space dimension. Results are shown for problems involving oblique hydraulic jumps and reflection from a wall.

The power of NMR.: in two and three dimensions

Soon after its discovery in the 1950s, NMR had become an indispensable tool fr chemists. In the 1970s and 1980s, the power of the technique was extended from one dimension to two and even three dimensions, opening up exciting applkications in both chemistry and biochemistry. the success of one dimensional. high-resolution NMR stems from the unique insights that it can provide about molecular structure. The chemical shift of a nucleus gives invaluable information abut the chemical environment in which that nucleus is located, Coupling interactions between hydorgen nuclei, as revealed by characteristic splitting patterns inthe 1H-NMR spectrum, provide informaton about the loaction of one group of hydorgen atoms relative to others inthe molecule. And the nuclearf Overhauser effect (nOe) can shed light on molecular stereochemistry.

Extensivity of two-dimensional turbulence

This study is concerned with how the attractor dimension of the two-dimensional Navier–Stokes equations depends on characteristic length scales, including the system integral length scale, the forcing length scale, and the dissipation length scale. Upper bounds on the attractor dimension derived by Constantin, Foias and Temam are analysed. It is shown that the optimal attractor-dimension estimate grows linearly with the domain area (suggestive of extensive chaos), for a sufficiently large domain, if the kinematic viscosity and the amplitude and length scale of the forcing are held fixed. For sufficiently small domain area, a slightly “super-extensive” estimate becomes optimal. In the extensive regime, the attractor-dimension estimate is given by the ratio of the domain area to the square of the dissipation length scale defined, on physical grounds, in terms of the average rate of shear. This dissipation length scale (which is not necessarily the scale at which the energy or enstrophy dissipation takes place) can be identified with the dimension correlation length scale, the square of which is interpreted, according to the concept of extensive chaos, as the area of a subsystem with one degree of freedom. Furthermore, these length scales can be identified with a “minimum length scale” of the flow, which is rigorously deduced from the concept of determining nodes.

A comparative review of dimension reduction methods in approximate Bayesian computation

Approximate Bayesian computation (ABC) methods make use of comparisons between simulated and observed summary statistics to overcome the problem of computationally intractable likelihood functions. As the practical implementation of ABC requires computations based on vectors of summary statistics, rather than full data sets, a central question is how to derive low-dimensional summary statistics from the observed data with minimal loss of information. In this article we provide a comprehensive review and comparison of the performance of the principal methods of dimension reduction proposed in the ABC literature. The methods are split into three nonmutually exclusive classes consisting of best subset selection methods, projection techniques and regularization. In addition, we introduce two new methods of dimension reduction. The first is a best subset selection method based on Akaike and Bayesian information criteria, and the second uses ridge regression as a regularization procedure. We illustrate the performance of these dimension reduction techniques through the analysis of three challenging models and data sets.