Lluís Oliver i els components fonamentals de la matèria

Entrevista en Lluís Oliver, químic gironí

On the use of principal components in contemporany population genetics: a case study

In human Population Genetics, routine applications of principal component techniques are oftenrequired. Population biologists make widespread use of certain discrete classifications of humansamples into haplotypes, the monophyletic units of phylogenetic trees constructed from severalsingle nucleotide bimorphisms hierarchically ordered. Compositional frequencies of the haplotypesare recorded within the different samples. Principal component techniques are then required as adimension-reducing strategy to bring the dimension of the problem to a manageable level, say two,to allow for graphical analysis.Population biologists at large are not aware of the special features of compositional data and normally make use of the crude covariance of compositional relative frequencies to construct principalcomponents. In this short note we present our experience with using traditional linear principalcomponents or compositional principal components based on logratios, with reference to a specificdataset

Interpretation of wind components as compositional variables

The classical statistical study of the wind speed in the atmospheric surface layer is madegenerally from the analysis of the three habitual components that perform the wind data,that is, the component W-E, the component S-N and the vertical component,considering these components independent.When the goal of the study of these data is the Aeolian energy, so is when wind isstudied from an energetic point of view and the squares of wind components can beconsidered as compositional variables. To do so, each component has to be divided bythe module of the corresponding vector.In this work the theoretical analysis of the components of the wind as compositionaldata is presented and also the conclusions that can be obtained from the point of view ofthe practical applications as well as those that can be derived from the application ofthis technique in different conditions of weather

Adding new components to the knowledge plane GMPLS over WDM networks

A recent study defines a new network plane: the knowledge plane. The incorporation of the knowledge plane over the network allows having more accurate information of the current and future network states. In this paper, the introduction and management of the network reliability information in the knowledge plane is proposed in order to improve the quality of service with protection routing algorithms in GMPLS over WDM networks. Different experiments prove the efficiency and scalability of the proposed scheme in terms of the percentage of resources used to protect the network

I-SS: integrated supervision systems approach based on interactive components

Process supervision is the activity focused on monitoring the process operation in order to deduce conditions to maintain the normality including when faults are present Depending on the number/distribution/heterogeneity of variables, behaviour situations, sub-processes, etc. from processes, human operators and engineers do not easily manipulate the information. This leads to the necessity of automation of supervision activities. Nevertheless, the difficulty to deal with the information complicates the design and development of software applications. We present an approach called "integrated supervision systems". It proposes multiple supervisors coordination to supervise multiple sub-processes whose interactions permit one to supervise the global process

Estudi de la distribució de components i recobriment en comprimits farmacèutics mitjançant NIR-CI

La qualitat d’un producte elaborat és un factor important, tant pels consumidors, com pels òrgans reguladors que en defineixen normatives cada cop més estrictes. Iniciatives com la del PAT (Process Analytical Technology) en el sector farmacèutic, responen a aquestes necessitats. El PAT afavoreix la implantació de noves tècniques analítiques que facilitin el monitoratge i el control de paràmetres clau in-/on-line durant els processos de producció. En aquest sentit, el NIR-CI (Near Infrarred-Chemical Imaging) podria ser una eina molt útil en la millora de la qualitat de la indústria farmacèutica, ja que aprofita les avantatges del NIR com a tècnica analítica (ràpid, no invasiu, no destructiu) i les aplica a tota la superfície espacial de la mostra. És una tècnica capaç de proporcionar una gran quantitat d’informació, tant espectral com espacial, en una sola imatge. L’objectiu d’aquest treball és avaluar la capacitat de la tècnica NIR-CI, com a eina pel control de paràmetres de qualitat de comprimits farmacèutics. Concretament, s’han analitzat quantitativament la concentració i la distribució dels components (principi actiu i excipients) d’un comprimit farmacèutic amb i sense recobriment. A més, també s’ha determinat el gruix de la pel·lícula de laca de recobriment i la seva distribució a la superfície del comprimit. Per obtenir aquesta informació, es parteix d’imatges NIR-CI hiperespectrals dels comprimits. Per a l’extracció de les dades d’interès s’ha usat l’algoritme PLS en les diferents versions dels softwares Isys 5.0 i Unscrambler 9.8. La versió de l’Isys permet determinar la contribució de cada component pur a cada punt de la imatge, emprant únicament l’espectre del component en estudi. Amb la de l’Unscrambler, en canvi, es construeix un model de calibratge que, a partir d’unes mostres de referència, prediu la distribució del gruix de recobriment sobre la superfície del comprimit.

Diagnosing Patients Combining Principal Components Analysis and Case Based Reasoning

This paper addresses the application of a PCA analysis on categorical data prior to diagnose a patients data set using a Case-Based Reasoning (CBR) system. The particularity is that the standard PCA techniques are designed to deal with numerical attributes, but our medical data set contains many categorical data and alternative methods as RS-PCA are required. Thus, we propose to hybridize RS-PCA (Regular Simplex PCA) and a simple CBR. Results show how the hybrid system produces similar results when diagnosing a medical data set, that the ones obtained when using the original attributes. These results are quite promising since they allow to diagnose with less computation effort and memory storage

A chemical Hamiltonian approach study of the basis set superposition error changes on electron densities and one- and two-center energy components

A comparision of the local effects of the basis set superposition error (BSSE) on the electron densities and energy components of three representative H-bonded complexes was carried out. The electron densities were obtained with Hartee-Fock and density functional theory versions of the chemical Hamiltonian approach (CHA) methodology. It was shown that the effects of the BSSE were common for all complexes studied. The electron density difference maps and the chemical energy component analysis (CECA) analysis confirmed that the local effects of the BSSE were different when diffuse functions were present in the calculations

Passive modernization? the new human development index and its components in Italy’s regions (1871-2007)

The article presents and discusses estimates of social and economic indicators for Italy’s regions in benchmark years roughly from Unification to the present day: life expectancy, education, GDP per capita at purchasing power parity, and the new Human Development Index (HDI). A broad interpretative hypothesis, based on the distinction between passive and active modernization, is proposed to account for the evolution of regional imbalances over the long-run. In the lack of active modernization, Southern Italy converged thanks to passive modernization, i.e., State intervention: however, this was more effective in life expectancy, less successful in education, expensive and as a whole ineffective in GDP. As a consequence, convergence in the HDI occurred from the late XIX century to the 1970s, but came to a sudden halt in the last decades of the XX century.

Testing I(1) against I(d) alternatives in the presence of deteministic components

This paper discusses the role of deterministic components in the DGP and in the auxiliary regression model which underlies the implementation of the Fractional Dickey-Fuller (FDF) test for I(1) against I(d) processes with d ∈ [0, 1). This is an important test in many economic applications because I(d) processess with d & 1 are mean-reverting although, when 0.5 ≤ d & 1,, like I(1) processes, they are nonstationary. We show how simple is the implementation of the FDF in these situations, and argue that it has better properties than LM tests. A simple testing strategy entailing only asymptotically normally distributed tests is also proposed. Finally, an empirical application is provided where the FDF test allowing for deterministic components is used to test for long-memory in the per capita GDP of several OECD countries, an issue that has important consequences to discriminate between growth theories, and on which there is some controversy.

Modelos estadísticos y evaluación: tres estudios en educación

The educational system in Spain is undergoing a reorganization. At present, high-school graduates who want to enroll at a public university must take a set of examinations Pruebas de Aptitud para el Acceso a la Universidad (PAAU). A "new formula" (components, weights, type of exam,...) for university admission is been discussed. The present paper summarizes part of the research done by the author in her PhD. The context for this thesis is the evaluation of large-scale and complex systems of assessment. The main objectives were: to achieve a deep knowledge of the entire university admissions process in Spain, to discover the main sources of uncertainty and topromote empirical research in a continual improvement of the entire process. Focusing in the suitable statistical models and strategies which allow to high-light the imperfections of the system and reduce them, the paper develops, among other approaches, some applications of multilevel modeling.

Spanning tests in return and stochastic discount factor mean-variance frontiers: A unifying approach

We propose new spanning tests that assess if the initial and additional assets share theeconomically meaningful cost and mean representing portfolios. We prove their asymptoticequivalence to existing tests under local alternatives. We also show that unlike two-step oriterated procedures, single-step methods such as continuously updated GMM yield numericallyidentical overidentifyng restrictions tests, so there is arguably a single spanning test.To prove these results, we extend optimal GMM inference to deal with singularities in thelong run second moment matrix of the influence functions. Finally, we test for spanningusing size and book-to-market sorted US stock portfolios.

Testing I(1) against I(d) alternatives in the presence of deteministic components

This paper discusses the role of deterministic components in the DGP and in the auxiliaryregression model which underlies the implementation of the Fractional Dickey-Fuller (FDF) test for I(1) against I(d) processes with d [0, 1). This is an important test in many economic applications because I(d) processess with d < 1 are mean-reverting although, when 0.5 = d < 1, like I(1) processes, they are nonstationary. We show how simple is the implementation of the FDF in these situations, and argue that it has better properties than LM tests. A simple testing strategy entailing only asymptotically normally distributedtests is also proposed. Finally, an empirical application is provided where the FDF test allowing for deterministic components is used to test for long-memory in the per capita GDP of several OECD countries, an issue that has important consequences to discriminate between growth theories, and on which there is some controversy.