Using data envelopment analysis to assess the efficiency of social security systems: the case of income protection in old age

As the number of pensioners in Europe rises relative to the number of people in employment, the gap between the contributions and the benefit levels increases, and consequently ensuring adequate pensions on a sustainable basis has become a major challenge. This study aims to explore the potential of using the Data Envelopment Analysis (DEA) technique in order to access the efficiency of the income protection in old age, one of the most important branches of Social Security. To this effect, we collected data from the 27 European Union Member States regarding this branch. Our results show important differences among the Member States and stress the importance of identifying best practices to achieve more adequate, sustainable and modernised pension systems. Our results also highlight the importance of using DEA as a decision support tool for policy makers.

Zonal prices analysis supported by a data mining based methodology

A methodology based on data mining techniques to support the analysis of zonal prices in real transmission networks is proposed in this paper. The mentioned methodology uses clustering algorithms to group the buses in typical classes that include a set of buses with similar LMP values. Two different clustering algorithms have been used to determine the LMP clusters: the two-step and K-means algorithms. In order to evaluate the quality of the partition as well as the best performance algorithm adequacy measurements indices are used. The paper includes a case study using a Locational Marginal Prices (LMP) data base from the California ISO (CAISO) in order to identify zonal prices.

Compositional analysis of archaeological glasses

At CoDaWork'03 we presented work on the analysis of archaeological glass composi- tional data. Such data typically consist of geochemical compositions involving 10-12 variables and approximates completely compositional data if the main component, sil- ica, is included. We suggested that what has been termed `crude' principal component analysis (PCA) of standardized data often identi ed interpretable pattern in the data more readily than analyses based on log-ratio transformed data (LRA). The funda- mental problem is that, in LRA, minor oxides with high relative variation, that may not be structure carrying, can dominate an analysis and obscure pattern associated with variables present at higher absolute levels. We investigate this further using sub- compositional data relating to archaeological glasses found on Israeli sites. A simple model for glass-making is that it is based on a `recipe' consisting of two `ingredients', sand and a source of soda. Our analysis focuses on the sub-composition of components associated with the sand source. A `crude' PCA of standardized data shows two clear compositional groups that can be interpreted in terms of di erent recipes being used at di erent periods, re ected in absolute di erences in the composition. LRA analysis can be undertaken either by normalizing the data or de ning a `residual'. In either case, after some `tuning', these groups are recovered. The results from the normalized LRA are di erently interpreted as showing that the source of sand used to make the glass di ered. These results are complementary. One relates to the recipe used. The other relates to the composition (and presumed sources) of one of the ingredients. It seems to be axiomatic in some expositions of LRA that statistical analysis of compositional data should focus on relative variation via the use of ratios. Our analysis suggests that absolute di erences can also be informative

Compositional analysis of bivariate discrete probabilities

A joint distribution of two discrete random variables with finite support can be displayed as a two way table of probabilities adding to one. Assume that this table has n rows and m columns and all probabilities are non-null. This kind of table can be seen as an element in the simplex of n · m parts. In this context, the marginals are identified as compositional amalgams, conditionals (rows or columns) as subcompositions. Also, simplicial perturbation appears as Bayes theorem. However, the Euclidean elements of the Aitchison geometry of the simplex can also be translated into the table of probabilities: subspaces, orthogonal projections, distances. Two important questions are addressed: a) given a table of probabilities, which is the nearest independent table to the initial one? b) which is the largest orthogonal projection of a row onto a column? or, equivalently, which is the information in a row explained by a column, thus explaining the interaction? To answer these questions three orthogonal decompositions are presented: (1) by columns and a row-wise geometric marginal, (2) by rows and a columnwise geometric marginal, (3) by independent two-way tables and fully dependent tables representing row-column interaction. An important result is that the nearest independent table is the product of the two (row and column)-wise geometric marginal tables. A corollary is that, in an independent table, the geometric marginals conform with the traditional (arithmetic) marginals. These decompositions can be compared with standard log-linear models. Key words: balance, compositional data, simplex, Aitchison geometry, composition, orthonormal basis, arithmetic and geometric marginals, amalgam, dependence measure, contingency table

Sexually Dimorphic Effect of the Val66Met Polymorphism of BDNF on Susceptibility to Alzheimer`s Disease: New Data and Meta-Analysis

Conflicting results have been reported as to whether genetic variations (Val66Met and C270T) of the brain-derived neurotrophic factor gene (RDNF) confer susceptibility to Alzheimer`s disease (AD). We genotyped these polymorphisms in a Japanese sample of 657 patients with AD and 525 controls, and obtained weak evidence of association for Val66Met (P = 0.063), but not for C270T. After stratification by sex, we found a significant allelic association between Val66Met and AD in women (P = 0.017), but not in men. To confirm these observations, we collected genotyping data for each sex from 16 research centers worldwide (4,711 patients and 4,537 controls in total). The meta-analysis revealed that there was a clear sex difference in the allelic association; the Met66 allele confers susceptibility to AD in women (odds ratio = 1.14, 95% CI 1.05-1.24, P = 0.002), but not in men. Our results provide evidence that the Met66 allele of BDNF has a sexually dimorphic effect on susceptibility to AD. (C) 2009 Wiley-Liss, Inc.

Responses to racism : a taxonomy of coping styles used by aboriginal Australians

The author takes up the challenge from social psychologists to explore the coping responses of those who experience racism. Previous attempts to provide taxonomies of responses to racism-discrimination-oppression are reviewed. An analysis of data derived from semistructured interviews conducted with 34 Indigenous Australians that explored experiences of racism and emotional and behavioral responses is reported, and a taxonomy of coping made up of 3 broad categories is presented. The defining feature of these categories is the purpose of the responses contained therein: to defend the self, to control or contain the reaction, or to confront the racism. It is argued that this may be a more useful way to understand responses to racism than taxonomies previously proposed.

Selected approaches and frameworks to carry out genomic data provision and analysis on the cloud

While High Performance Computing clouds allow researchers to process large amounts of genomic data, complex resource and software configuration tasks must be carried out beforehand. The current trend exposes applications and data as services, simplifying access to clouds. This paper examines commonly used cloud-based genomic analysis services, introduces the approach of exposing data as services and proposes two new solutions (HPCaaS and Uncinus) which aim to automate service development, deployment process and data provision. By comparing and contrasting these solutions, we identify key mechanisms of service creation, execution and data access required to support non-computing specialists employing clouds.

How calls from carers, friends and family members of someone affected by cancer differ from those made by people diagnosed with cancer; analysis of 4 years of South Australian Cancer Council Helpline data

PURPOSE: The purpose of this study is to determine how people diagnosed with cancer who call the Cancer Council Helpline in South Australia differ from carers/family/friends (caregivers) who call. METHOD: Descriptive, retrospective audit of calls from people who contacted Cancer Council Helpline in South Australia between 16 April 2009 and 16 April 2013 who were diagnosed with cancer (n&nbsp;=&nbsp;5766) or were the caregivers (n&nbsp;=&nbsp;5174) of a person with cancer. RESULTS: Caregivers were more likely to be female (p&nbsp;<&nbsp;0.001); younger in age (p&nbsp;<&nbsp;0.001); call regarding cancer that was metastasised/widespread/advanced, terminal or at an unknown stage (p&nbsp;<&nbsp;0.001) and phone requesting general cancer information or emotional support (p&nbsp;<&nbsp;0.001). This group was more distressed (p&nbsp;<&nbsp;0.001) but less likely (p&nbsp;=&nbsp;0.02) to be offered and/or accept referrals to counselling than people diagnosed with cancer who called. Follow-up care was required by 63.5&nbsp;% of caregivers and 73.1&nbsp;% of people with cancer according to distress management guidelines; 8.5 and 15.3&nbsp;%, respectively, accepted referrals to internal services. The most frequently discussed topic for both groups was emotional/psychological concerns. There were no differences in remoteness of residence or call length between groups. CONCLUSIONS: Caregivers represented different demographic groups than people diagnosed with cancer who called this helpline. The two groups phoned for different issues, at different stages of disease progression, displayed different levels of distress and, therefore, may benefit from services being tailored to meet their unique needs. These results also demonstrate the capacity of helplines to complement other health services and confirm that callers to cancer helplines exhibit high levels of distress.

Peak Separation by Derivative Spectroscopy Applied to FTIR Analysis of Hydrolized Silica

Reliable spectral analysis is only achieved if the spectrum is thoroughly investigated in regard to all hidden and overlapped peaks. This paper describes the steps undertaken to find and separate such peaks in the range of 3000 to 4000 cm(-1) in the case of three different infrared absorption spectra of the glass surface of hydrolyzed silica optical fibers. Peak finding was done by the analysis of the second and fourth derivatives of the digital data, coupled with the available knowledge of infrared spectroscopy of silica-water interaction in the investigated range. Peak separation was accomplished by curve fitting with four different models. The model with the best fit was described by a sum of pure Gaussian peaks. Shoulder limit and detection limit maps were used to validate the revealed spectral features.

Biometric relationship analysis of the wet weight by carapace width to the swimming crab Arenaeus-cribrarius (Lamarck, 1818) (Crustacea, Brachyura, Portunidae)

The biometric relationship between the weigth and the carapace width in the swimming crab A. cribrarius was compared with the results from other portunid crabs studied previously. During November/1988 to October/1989, a total of 403 specimens (189 males and 214 females) were collected with otter-trawl nets in north coast of the São Paulo State, Brazil. The animals were measured (carapace width excluding lateral spines = LC! and weighed (wet weight = PE). The empiric points of this relation were fit according to the power function (Y = a.X(b)) for each sex, maturation phases and total of individuals. The relation PE x LC indicates that the mole's growth changes during the ontogenesys from isometric (in juvenile phase) to allometric positive (in adult phase). For the females the growth is isometric in the two phases. The weight grows in a higher proportion than the carapace width variable (allometric positive growth). The data can be grouped in a single equation (PE = 7.85.10(-5).LC(3.14)) for the convertion between the variables there was a greater similarity between the equations obtained far each sex. In spite of this, the males present the fattening grade value (''a'') slightly higher than that of the females, possibly because of the greater size reached in its devellopment. The mean weight of the males is greater than the females one (p < 0.01). In the range 80 proves 90mm the males were more abundant, probably due to the females terminal ecdysis is near this size. The females only have the mean weight greater than the males in the 60 proves 70mm range (p < 0.01) when the puberty molt occurs and they present morphological changes in their reproductive system.

Applying spatial analysis of genetic and environmental data to predict connection corridors to the New World screwworm populations in South America

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Issues on the mean stress effect in fretting fatigue of a 7050-T7451 Al alloy posed by new experimental data

The aims of this work are: (i) to produce new experimental data for fretting fatigue considering the presence of a mean bulk stress and (ii) to assess two design methodologies against failure by fretting fatigue. Tests on a cylinder–flat contact configuration were conducted using a fretting apparatus mounted on a servo-hydraulic machine. The material used for both the pads and fatigue specimen was an aeronautical 7050-T7451 Al alloy. The experimental program was designed with all relevant parameters, apart from the mean bulk load (always applied before the contact loads), kept constant. The mean bulk stress varied from compressive to tensile values while maintaining a high peak pressure in order to encourage crack initiation. Two methodologies against fretting fatigue are proposed and confronted against the experimental data. The non-local stress-based methodology considers the evaluation of a critical plane fatigue criterion at the center of a process zone located beneath the contacting surfaces. The results showed that it correctly predicts crack initiation, but was not capable to provide successful prediction of the integrity of the specimens. Alternatively, we considered a crack arrest criterion which has the potential to provide a more complete description about the integrity of the specimens.

A categorical data analysis approach to estimation of demographic characteristics for Texas county populations

The need for timely population data for health planning and Indicators of need has Increased the demand for population estimates. The data required to produce estimates is difficult to obtain and the process is time consuming. Estimation methods that require less effort and fewer data are needed. The structure preserving estimator (SPREE) is a promising technique not previously used to estimate county population characteristics. This study first uses traditional regression estimation techniques to produce estimates of county population totals. Then the structure preserving estimator, using the results produced in the first phase as constraints, is evaluated.^ Regression methods are among the most frequently used demographic methods for estimating populations. These methods use symptomatic indicators to predict population change. This research evaluates three regression methods to determine which will produce the best estimates based on the 1970 to 1980 indicators of population change. Strategies for stratifying data to improve the ability of the methods to predict change were tested. Difference-correlation using PMSA strata produced the equation which fit the data the best. Regression diagnostics were used to evaluate the residuals.^ The second phase of this study is to evaluate use of the structure preserving estimator in making estimates of population characteristics. The SPREE estimation approach uses existing data (the association structure) to establish the relationship between the variable of interest and the associated variable(s) at the county level. Marginals at the state level (the allocation structure) supply the current relationship between the variables. The full allocation structure model uses current estimates of county population totals to limit the magnitude of county estimates. The limited full allocation structure model has no constraints on county size. The 1970 county census age - gender population provides the association structure, the allocation structure is the 1980 state age - gender distribution.^ The full allocation model produces good estimates of the 1980 county age - gender populations. An unanticipated finding of this research is that the limited full allocation model produces estimates of county population totals that are superior to those produced by the regression methods. The full allocation model is used to produce estimates of 1986 county population characteristics. ^

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

A method to incorporate the effect of taxonomic uncertainty on multivariate analyses of ecological data

Researchers in ecology commonly use multivariate analyses (e.g. redundancy analysis, canonical correspondence analysis, Mantel correlation, multivariate analysis of variance) to interpret patterns in biological data and relate these patterns to environmental predictors. There has been, however, little recognition of the errors associated with biological data and the influence that these may have on predictions derived from ecological hypotheses. We present a permutational method that assesses the effects of taxonomic uncertainty on the multivariate analyses typically used in the analysis of ecological data. The procedure is based on iterative randomizations that randomly re-assign non identified species in each site to any of the other species found in the remaining sites. After each re-assignment of species identities, the multivariate method at stake is run and a parameter of interest is calculated. Consequently, one can estimate a range of plausible values for the parameter of interest under different scenarios of re-assigned species identities. We demonstrate the use of our approach in the calculation of two parameters with an example involving tropical tree species from western Amazonia: 1) the Mantel correlation between compositional similarity and environmental distances between pairs of sites, and; 2) the variance explained by environmental predictors in redundancy analysis (RDA). We also investigated the effects of increasing taxonomic uncertainty (i.e. number of unidentified species), and the taxonomic resolution at which morphospecies are determined (genus-resolution, family-resolution, or fully undetermined species) on the uncertainty range of these parameters. To achieve this, we performed simulations on a tree dataset from southern Mexico by randomly selecting a portion of the species contained in the dataset and classifying them as unidentified at each level of decreasing taxonomic resolution. An analysis of covariance showed that both taxonomic uncertainty and resolution significantly influence the uncertainty range of the resulting parameters. Increasing taxonomic uncertainty expands our uncertainty of the parameters estimated both in the Mantel test and RDA. The effects of increasing taxonomic resolution, however, are not as evident. The method presented in this study improves the traditional approaches to study compositional change in ecological communities by accounting for some of the uncertainty inherent to biological data. We hope that this approach can be routinely used to estimate any parameter of interest obtained from compositional data tables when faced with taxonomic uncertainty.