Income distribution dependence of poverty measure:a theoretical analysis

Using a modified deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the 'global' mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reduction in poverty while an increase in the variance of the income distribution increases poverty. This altruistic view for a developing economy, however, is not tenable anymore once the poverty index is found to follow a pareto distribution. Here although a rising mean income indicates a reduction in poverty, due to the presence of an inflexion point in the poverty function, there is a critical value of the variance below which poverty decreases with increasing variance while beyond this value, poverty undergoes a steep increase followed by a decrease with respect to higher variance. Identifying this inflexion point as the poverty line, we show that the pareto poverty function satisfies all three standard axioms of a poverty index [N.C. Kakwani, Econometrica 43 (1980) 437; A.K. Sen, Econometrica 44 (1976) 219] whereas the log-normal distribution falls short of this requisite. Following these results, we make quantitative predictions to correlate a developing with a developed economy. © 2006 Elsevier B.V. All rights reserved.

The Rotational Evolution and Magnetospheric Emission of the Magnetic Early B-type Stars

How do the magnetic fields of massive stars evolve over time? Are their gyrochronological ages consistent with ages inferred from evolutionary tracks? Why do most stars predicted to host Centrifugal Magnetospheres (CMs) display no H$\alpha$ emission? Does plasma escape from CMs via centrifugal breakout events, or by a steady-state leakage mechanism? This thesis investigates these questions via a population study with a sample of 51 magnetic early B-type stars. The longitudinal magnetic field \bz~was measured from Least Squares Deconvolution profiles extracted from high-resolution spectropolarimetric data. New rotational periods $P_{\rm rot}$ were determined for 15 stars from \bz, leaving only 3 stars for which $P_{\rm rot}$ is unknown. Projected rotational velocities \vsini~were measured from multiple spectral lines. Effective temperatures and surface gravities were measured via ionization balances and line profile fitting of H Balmer lines. Fundamental physical parameters, \bz, \vsini, and $P_{\rm rot}$ were then used to determine radii, masses, ages, dipole oblique rotator model, stellar wind, magnetospheric, and spindown parameters using a Monte Carlo approach that self-consistently calculates all parameters while accounting for all available constraints on stellar properties. Dipole magnetic field strengths $B_{\rm d}$ follow a log-normal distribution similar to that of Ap stars, and decline over time in a fashion consistent with the expected conservation of fossil magnetic flux. $P_{\rm rot}$ increases with fractional main sequence age, mass, and $B_{\rm d}$, as expected from magnetospheric braking. However, comparison of evolutionary track ages to maximum spindown ages $t_{\rm S,max}$ shows that initial rotation fractions may be far below critical for stars with $M_*>10 M_\odot$. Computing $t_{\rm S,max}$ with different mass-loss prescriptions indicates that the mass-loss rates of B-type stars are likely much lower than expected from extrapolation from O-type stars. Stars with H$\alpha$ in emission and absorption occupy distinct regions in the updated rotation-magnetic confinement diagram: H$\alpha$-bright stars are found to be younger, more rapidly rotating, and more strongly magnetized than the general population. Emission strength is sensitive both to the volume of the CM and to the mass-loss rate, favouring leakage over centrifugal breakout.

A comprehensive study of multiplicative attribute graph model

Graphs are powerful tools to describe social, technological and biological networks, with nodes representing agents (people, websites, gene, etc.) and edges (or links) representing relations (or interactions) between agents. Examples of real-world networks include social networks, the World Wide Web, collaboration networks, protein networks, etc. Researchers often model these networks as random graphs. In this dissertation, we study a recently introduced social network model, named the Multiplicative Attribute Graph model (MAG), which takes into account the randomness of nodal attributes in the process of link formation (i.e., the probability of a link existing between two nodes depends on their attributes). Kim and Lesckovec, who defined the model, have claimed that this model exhibit some of the properties a real world social network is expected to have. Focusing on a homogeneous version of this model, we investigate the existence of zero-one laws for graph properties, e.g., the absence of isolated nodes, graph connectivity and the emergence of triangles. We obtain conditions on the parameters of the model, so that these properties occur with high or vanishingly probability as the number of nodes becomes unboundedly large. In that regime, we also investigate the property of triadic closure and the nodal degree distribution.

Size selectivity of trammel nets in southern European small-scale fisheries

Trammel net size selectivity was studied for the most important metiers in four southern European areas: the Cantabrian Sea (Atlantic, Basque Country, Spain), the Algarve (Atlantic, southern Portugal), the Gulf of Cadiz (Atlantic, Spain) and the Cyclades Islands (Mediterranean, Aegean Sea, Greece). These metiers were: cuttlefish (Sepia officinalis) and soles (Solea senegalensis, Microchirus azevia, Synaptura lusitanica) in the Algarve and the Gulf of Cadiz, sole (Solea solea) in the Cantabrian Sea and mixed fin-fish in the Cyclades. In each area, experimental trammel nets of six different types (combinations of two large outer panel mesh sizes and three small inner panel meshes) were constructed. Fishing trials were carried out on a seasonal basis (four seasons in the Cantabrian Sea, Algarve and Cyclades and two seasons in the Gulf of Cadiz) with chartered commercial fishing vessels. Overall, size selectivity was estimated for 17 out of 28 species for which sufficient data were available. Trammel nets generally caught a wide size range of the most important species, with length frequency distributions that were skewed to the right and/or bi-modal. In many cases the length frequency distributions of the different nets were highly overlapped. The Kolmogorov-Smirnov test also showed that the large outer panel meshes generally had no effect in terms of size selectivity, while the opposite was true for the small inner panel ones. Six different selectivity models (normal scale, normal location, gamma, log-normal, bi-modal and gamma semi-Wileman) were fitted to data for the most abundant species in the four areas. For fish, the bi-modal model provided the best fits for the majority of the data sets, with the uni-modal models giving poor fits in most cases. For Sepia officinalis, where trammelling or pocketing was the method of capture in 100% of the cases, the logistic model fitted by maximum likelihood was judged to be more appropriate for describing the size selective properties of the trammel nets. Our results, which are among the first ones on trammel net selectivity in European waters, will be useful for evaluating the impacts of competing gear for the socio-economically important small-scale static gear fisheries. (c) 2006 Elsevier B.V All rights reserved.

Distribuição diamétrica de uma comunidade arbórea na Floresta Estadual do Amapá, Brasil.

A distribuição dos diâmetros é uma das análises mais empregadas para retratar o comportamento estrutural de um povoamento. Assim, este estudo objetivou avaliar a estrutura diamétrica da comunidade e das principais espécies lenhosas por meio das funções de densidade probabilísticas em uma floresta de terra firme no módulo IV da Floresta Estadual do Amapá (FLOTA/AP) no Município de Calçoene/AP. Os dados de diâmetro à altura do peito (DAP) foram obtidos de um inventário realizado em uma área de 1 hectare (100 x 100 m). A estrutura diamétrica foi analisada para toda a comunidade e para as quatro principais espécies ranqueadas segundo seus índices de valor de importância. Para avaliação dos ajustes das funções: Normal, Log-normal, Gamma e Weibull 3P foi utilizado o teste de Kolmogorov-Smirnov (a = 0,05). A maioria das espécies apresentaram assimetria positiva e curtose do tipo platicúrtica, o que demonstra o padrão típico de floresta nativa em forma de "J" invertido. A função Weibull 3P e Gamma foram aderentes no teste K-S aos dados das quatro espécies analisadas, sendo a primeira a mais indicada para descrever a distribuição diamétrica de três das quatro espécies de maior IVI, e também da referida floresta de terra firme. Conclui-se, ainda, que estudos como este devem ser realizados constantemente visando introduzir e avaliar a eficiência de outras funções densidade de probabilidade para a descrição da distribuição diamétrica de povoamentos em florestas inequiâneas.

Computational study on the asymmetric aminocatalysed Michael addition reaction of cyclohexanone to trans–β–nitrostyrene

Asymmetric organocatalysed reactions are one of the most fascinating synthetic strategies which one can adopt in order to induct a desired chirality into a reaction product. From all the possible practical applications of small organic molecules in catalytic reaction, amine–based catalysis has attracted a lot of attention during the past two decades. The high interest in asymmetric aminocatalytic pathways is to account to the huge variety of carbonyl compounds that can be functionalized by many different reactions of their corresponding chiral–enamine or –iminium ion as activated nucleophile and electrophile, respectively. Starting from the employment of L–Proline, many useful substrates have been proposed in order to further enhance the catalytic performances of these reaction in terms of enantiomeric excess values, yield, conversion of the substrate and turnover number. In particular, in the last decade the use of chiral and quasi–enantiomeric primary amine species has got a lot of attention in the field. Contemporaneously, many studies have been carried out in order to highlight the mechanism through which these kinds of substrates induct chirality into the desired products. In this scenario, computational chemistry has played a crucial role due to the possibility of simulating and studying any kind of reaction and the transition state structures involved. In the present work the transition state geometries of primary amine–catalysed Michael addition reaction of cyclohexanone to trans–β–nitrostyrene with different organic acid cocatalysts has been studied through different computational techniques such as density functional theory based quantum mechanics calculation and force–field directed molecular simulations.

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

Array-CGH testing in spontaneous abortions with normal karyotypes

In about 50% of first trimester spontaneous abortion the cause remains undetermined after standard cytogenetic investigation. We evaluated the usefulness of array-CGH in diagnosing chromosome abnormalities in products of conception from first trimester spontaneous abortions. Cell culture was carried out in short- and long-term cultures of 54 specimens and cytogenetic analysis was successful in 49 of them. Cytogenetic abnormalities (numerical and structural) were detected in 22 (44.89%) specimens. Subsequent, array-CGH based on large insert clones spaced at ~1 Mb intervals over the whole genome was used in 17 cases with normal G-banding karyotype. This revealed chromosome aneuplodies in three additional cases, giving a final total of 51% cases in which an abnormal karyotype was detected. In keeping with other recently published works, this study shows that array-CGH detects abnormalities in a further ~10% of spontaneous abortion specimens considered to be normal using standard cytogenetic methods. As such, array-CGH technique may present a suitable complementary test to cytogenetic analysis in cases with a normal karyotype.

Residuals for log-Burr XII regression models in survival analysis

In this paper, we compare three residuals to assess departures from the error assumptions as well as to detect outlying observations in log-Burr XII regression models with censored observations. These residuals can also be used for the log-logistic regression model, which is a special case of the log-Burr XII regression model. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and the empirical distribution of each residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended to the modified martingale-type residual in log-Burr XII regression models with censored data.

Log-modified Weibull regression models with censored data: Sensitivity and residual analysis

This paper proposes a regression model considering the modified Weibull distribution. This distribution can be used to model bathtub-shaped failure rate functions. Assuming censored data, we consider maximum likelihood and Jackknife estimators for the parameters of the model. We derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and we also present some ways to perform global influence. Besides, for different parameter settings, sample sizes and censoring percentages, various simulations are performed and the empirical distribution of the modified deviance residual is displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be straightforwardly extended for a martingale-type residual in log-modified Weibull regression models with censored data. Finally, we analyze a real data set under log-modified Weibull regression models. A diagnostic analysis and a model checking based on the modified deviance residual are performed to select appropriate models. (c) 2008 Elsevier B.V. All rights reserved.

A Log-Linear Regression Model for the Beta-Weibull Distribution

We introduce the log-beta Weibull regression model based on the beta Weibull distribution (Famoye et al., 2005; Lee et al., 2007). We derive expansions for the moment generating function which do not depend on complicated functions. The new regression model represents a parametric family of models that includes as sub-models several widely known regression models that can be applied to censored survival data. We employ a frequentist analysis, a jackknife estimator, and a parametric bootstrap for the parameters of the proposed model. We derive the appropriate matrices for assessing local influences on the parameter estimates under different perturbation schemes and present some ways to assess global influences. Further, for different parameter settings, sample sizes, and censoring percentages, several simulations are performed. In addition, the empirical distribution of some modified residuals are displayed and compared with the standard normal distribution. These studies suggest that the residual analysis usually performed in normal linear regression models can be extended to a modified deviance residual in the proposed regression model applied to censored data. We define martingale and deviance residuals to evaluate the model assumptions. The extended regression model is very useful for the analysis of real data and could give more realistic fits than other special regression models.

Sudden onset of log-periodicity and superdiffusion in non-Markovian random walks with amnestically induced persistence: exact results

Random walks can undergo transitions from normal diffusion to anomalous diffusion as some relevant parameter varies, for instance the L,vy index in L,vy flights. Here we derive the Fokker-Planck equation for a two-parameter family of non-Markovian random walks with amnestically induced persistence. We investigate two distinct transitions: one order parameter quantifies log-periodicity and discrete scale invariance in the first moment of the propagator, whereas the second order parameter, known as the Hurst exponent, describes the growth of the second moment. We report numerical and analytical results for six critical exponents, which together completely characterize the properties of the transitions. We find that the critical exponents related to the diffusion-superdiffusion transition are identical in the positive feedback and negative feedback branches of the critical line, even though the former leads to classical superdiffusion whereas the latter gives rise to log-periodic superdiffusion.

Spectral peak resolution and speech recognition in quiet: Normal hearing, hearing impaired and cochlear implant listeners

Spectral peak resolution was investigated in normal hearing (NH), hearing impaired (HI), and cochlear implant (CI) listeners. The task involved discriminating between two rippled noise stimuli in which the frequency positions of the log-spaced peaks and valleys were interchanged. The ripple spacing was varied adaptively from 0.13 to 11.31 ripples/octave, and the minimum ripple spacing at which a reversal in peak and trough positions could be detected was determined as the spectral peak resolution threshold for each listener. Spectral peak resolution was best, on average, in NH listeners, poorest in CI listeners, and intermediate for HI listeners. There was a significant relationship between spectral peak resolution and both vowel and consonant recognition in quiet across the three listener groups. The results indicate that the degree of spectral peak resolution required for accurate vowel and consonant recognition in quiet backgrounds is around 4 ripples/octave, and that spectral peak resolution poorer than around 1–2 ripples/octave may result in highly degraded speech recognition. These results suggest that efforts to improve spectral peak resolution for HI and CI users may lead to improved speech recognition

A rapid PCR protocol for marker assisted detection of heterozygotes in segregating generations involving 1BL/1RS translocation and normal wheat lines

A rapid and reliable polymerase chain reaction (PCR)-based protocol was developed for detecting zygosity of the 1BL/1RS translocation in hexaploid wheat. The protocol involved a multiplex PCR with 2 pairs of oligonucleotide primers, rye-specific Ris-1 primers, and consensus 5S intergenic spacer (IGS) primers, and digestion of the PCR products with the restriction enzyme, MseI. A small piece of alkali-treated intact leaf tissue is used as a template for the PCR, thereby eliminating the necessity for DNA extraction. The test is simple, highly sensitive, and rapid compared with the other detection systems of 1BS1RS heterozygotes in hexaploid wheat. PCR results were confirmed with AFLP analyses. Diagnostic tests for 1BL/1RS translocation based on Sec-1-specific ELISA, screening for chromosome arm 1RS controlled rust resistance locus Yr9, and the PCR test differed in their ability to detect heterozygotes. The PCR test and rust test detected more heterozygotes than the ELISA test. The PCR test is being used to facilitate S1 family recurrent selection in the Germplasm Enhancement Program of the Australian Northern Wheat Improvement Program. A combination of the PCR zygosity test with other markers currently being implemented in the breeding program makes this test economical for 1BL/1RS characterisation of S1 families.

Improving the environmental performance of bedding products by using life cycle assessment at the design stage

Improvement of the environmental performance of processes and products is a common objective in industry, and has been receiving increased attention in recent years. The main objective of this work is to evaluate the potential environmental impact of two bedding products, a polyurethane foam mattress (PFM) and a pocket spring mattress (PSM). These two types are the most common mattresses used in Europe. A Life Cycle Assessment (LCA) shows that the PFM has a higher environmental impact than the PSM. For both products the main cause of environmental impact is the manufacturing process, respectively the polyurethane foam block moulding process for the PFM, and the pocket spring nucleus process for the PSM. A scenario analysis shows the possibility of reducing the environmental impact of the products’ life cycle using an alternative End-of-Life scenario, resorting to incineration rather than landfill. Two strategies were also studied in order to reduce the environmental impact of the PFM: (1) reutilization of foam that was sent to the waste system management, and (2) a 20% weight reduction of the polyurethane foam. The second strategy has proven to be the most effective.