Derivation of an observer model adapted to irregular signals based on convolution channels.

Anthropomorphic model observers are mathe- matical algorithms which are applied to images with the ultimate goal of predicting human signal detection and classification accuracy across varieties of backgrounds, image acquisitions and display conditions. A limitation of current channelized model observers is their inability to handle irregularly-shaped signals, which are common in clinical images, without a high number of directional channels. Here, we derive a new linear model observer based on convolution channels which we refer to as the "Filtered Channel observer" (FCO), as an extension of the channelized Hotelling observer (CHO) and the nonprewhitening with an eye filter (NPWE) observer. In analogy to the CHO, this linear model observer can take the form of a single template with an external noise term. To compare with human observers, we tested signals with irregular and asymmetrical shapes spanning the size of lesions down to those of microcalfications in 4-AFC breast tomosynthesis detection tasks, with three different contrasts for each case. Whereas humans uniformly outperformed conventional CHOs, the FCO observer outperformed humans for every signal with only one exception. Additive internal noise in the models allowed us to degrade model performance and match human performance. We could not match all the human performances with a model with a single internal noise component for all signal shape, size and contrast conditions. This suggests that either the internal noise might vary across signals or that the model cannot entirely capture the human detection strategy. However, the FCO model offers an efficient way to apprehend human observer performance for a non-symmetric signal.

Bayesian Networks for the Age Classification of Living Individuals: a Study on Transition Analysis

Over the past few decades, age estimation of living persons has represented a challenging task for many forensic services worldwide. In general, the process for age estimation includes the observation of the degree of maturity reached by some physical attributes, such as dentition or several ossification centers. The estimated chronological age or the probability that an individual belongs to a meaningful class of ages is then obtained from the observed degree of maturity by means of various statistical methods. Among these methods, those developed in a Bayesian framework offer to users the possibility of coherently dealing with the uncertainty associated with age estimation and of assessing in a transparent and logical way the probability that an examined individual is younger or older than a given age threshold. Recently, a Bayesian network for age estimation has been presented in scientific literature; this kind of probabilistic graphical tool may facilitate the use of the probabilistic approach. Probabilities of interest in the network are assigned by means of transition analysis, a statistical parametric model, which links the chronological age and the degree of maturity by means of specific regression models, such as logit or probit models. Since different regression models can be employed in transition analysis, the aim of this paper is to study the influence of the model in the classification of individuals. The analysis was performed using a dataset related to the ossifications status of the medial clavicular epiphysis and results support that the classification of individuals is not dependent on the choice of the regression model.

How women and men project their gender prototypes on leader prototypes.

Both role incongruency theory (Eagly & Karau, 2002) and the lack of fit model by Heilman (1983) suggest that the underrepresentation of women in leadership positions can be explained by the male-typedness of leader prototypes. We examine how women and men project their gender prototypes onto leader prototypes. We found initially that men more so than women projected their gender prototypes on leader prototypes. For men there is more of an overlap between a prototypical men and a prototypical leader than there is an overlap between a prototypical woman and a prototypical leader. Women, however, do not engage in so called relative ingroup projection. In the current study, we further decompose this finding asking whether the gender difference in relative ingroup projection on leadership prototypes is driven by female prototypes, male prototypes, and/or leader prototypes. We further examine to what extent this gender difference is more manifested on positively valenced or negatively valenced attributes of prototypes. Our findings show that, while women and men have similar prototypes of leaders and men on both positively and negatively valenced attributes, men relative to women have less favorable prototypes of women but only on positively valenced attributes. An interesting implication is that efforts to address gender differences in the projection of gender prototypes onto leader prototypes should focus less on leader prototypes and more on the female prototypes. Theoretically, our findings allude to the importance of distinguishing between more subtle (evaluating the outgroup less positively on positive properties) and less subtle forms (evaluating the outgroup more negatively on negative properties) of outgroup derogation.

Why Women Rarely Rise to the Top: A Social Identity Model of Leader Prototypes.

Purpose We propose a social identity model of leader prototypes to address why the maleness of leader prototypes is more pronounced among men than among women (e.g., Schein, 2001). Specifically, we argue that individuals project their ingroup prototype (e.g., a male prototype) onto a valued other category (e.g., leaders) (e.g., Wenzel, Mummendey, Weber, & Waldzus, 2003) in order to maintain a positive ingroup (e.g., gender) identity. We hypothesized that both women and men engage in ingroup projection of their gender prototype on their leader prototype, and we expected this effect to be stronger for men than women. We also investigated intelligence as a moderator of ingroup projection. Methodology Participants (276 students, University of Lausanne) assessed to what extent attributes on a list of gender traits were characteristic of a successful leader. We computed relative ingroup similarity scores (e.g., Waldzus & Mummendey, 2004) representing the difference between how characteristic ingroup traits are for a successful leader, and how characteristic outgroup traits are for a successful leader. Results Results showed that men engaged in ingroup projection while women engaged in outgroup projection, and that men engaged in ingroup projection to a greater extent. We also found a small, but positive effect of intelligence on ingroup projection among men. Limitations The use of a student sample might limit the external validity of our findings. Implications Our findings contribute to research on the under-representation of women in managerial roles, and introduce intelligence as a predictor of ingroup projection. Value Our study allows for a more fine-grained understanding of the cognitive representations of leaders of men and women.

Classification models for neurocognitive impairment in HIV infection based on demographic and clinical variables

Objective: We used demographic and clinical data to design practical classification models for prediction of neurocognitive impairment (NCI) in people with HIV infection. Methods: The study population comprised 331 HIV-infected patients with available demographic, clinical, and neurocognitive data collected using a comprehensive battery of neuropsychological tests. Classification and regression trees (CART) were developed to btain detailed and reliable models to predict NCI. Following a practical clinical approach, NCI was considered the main variable for study outcomes, and analyses were performed separately in treatment-naïve and treatment-experienced patients. Results: The study sample comprised 52 treatment-naïve and 279 experienced patients. In the first group, the variables identified as better predictors of NCI were CD4 cell count and age (correct classification [CC]: 79.6%, 3 final nodes). In treatment-experienced patients, the variables most closely related to NCI were years of education, nadir CD4 cell count, central nervous system penetration-effectiveness score, age, employment status, and confounding comorbidities (CC: 82.1%, 7 final nodes). In patients with an undetectable viral load and no comorbidities, we obtained a fairly accurate model in which the main variables were nadir CD4 cell count, current CD4 cell count, time on current treatment, and past highest viral load (CC: 88%, 6 final nodes). Conclusion: Practical classification models to predict NCI in HIV infection can be obtained using demographic and clinical variables. An approach based on CART analyses may facilitate screening for HIV-associated neurocognitive disorders and complement clinical information about risk and protective factors for NCI in HIV-infected patients.

A feed-forward spiking model of shape-coding by IT cells

The ability to recognize a shape is linked to figure-ground (FG) organization. Cell preferences appear to be correlated across contrast-polarity reversals and mirror reversals of polygon displays, but not so much across FG reversals. Here we present a network structure which explains both shape-coding by simulated IT cells and suppression of responses to FG reversed stimuli. In our model FG segregation is achieved before shape discrimination, which is itself evidenced by the difference in spiking onsets of a pair of output cells. The studied example also includes feature extraction and illustrates a classification of binary images depending on the dominance of vertical or horizontal borders.

How to Model Heterogeneity in Costly Punishment: Insights from Responders' Response Times

We investigate what processes may underlie heterogeneity in social preferences. We address this question by examining participants' decisions and associated response times across 12 mini-ultimatum games. Using a finite mixture model and cross-validating its classification with a response time analysis, we identified four groups of responders: one group takes little to no account of the proposed split or the foregone allocation and swiftly accepts any positive offer; two groups process primarily the objective properties of the allocations (fairness and kindness) and need more time the more properties need to be examined; and a fourth group, which takes more time than the others, appears to take into account what they would have proposed had they been put in the role of the proposer. We discuss implications of this joint decision-response time analysis.

Labor Market Signaling and Self-Confidence: Wage Compression and the Gender Pay Gap

I extend Spence's signaling model by assuming that some workers are overconfident-they underestimate their marginal cost of acquiring education-and some are underconfident. Firms cannot observe workers' productive abilities and beliefs but know the fractions of high-ability, overconfident, and underconfident workers. I find that biased beliefs lower the wage spread and compress the wages of unbiased workers. I show that gender differences in self-confidence can contribute to the gender pay gap. If education raises productivity, men are overconfident, and women underconfident, then women will, on average, earn less than men. Finally, I show that biased beliefs can improve welfare.

Disease profiles of detainees in the Canton of Vaud in Switzerland: gender and age differences in substance abuse, mental health and chronic health conditions.

BACKGROUND: Literature on the disease profile of prisoners that differentiates by age and gender remains sparse. This study aimed to describe the health of correctional inmates in terms of substance abuse problems and mental and somatic health conditions, and compare it by gender and age. METHODS: This study examined cross-sectional data from the Canton of Vaud in Switzerland on the health conditions of detainees who were in prison on January 1, 2011 or entered prison in 2011. Health conditions validated by physician examination were reported using the International Classification of Diseases (ICD) version 10. The analyses were descriptive by groups of prisoners: the entire sample (All), Men, Older adults and Women. RESULTS: A total of 1,664 individuals were included in the analysis. Men comprised 91.5 % of the sample and had a mean age of 33 years. The other 8.5 % were women and had an average age of 39. Older adults (i.e., age 50 and older) represented 7 % of the total sample. Overall, 80 % of inmates were non-Swiss citizens, but the proportion of Swiss prisoners was higher among the older adults (51 %) and women (29 %). Overall, 41 % of inmates self-reported substance abuse problems. Of those, 27 % were being treated by psychiatrists for behavioral disorders related to substance abuse. Chronic infectious diseases were found in 9 % of the prison population. In addition, 27 % of detainees suffered from serious mental health conditions. Gender and age had an influence on the disease profile of this sample: compared to the entire prison population, the older inmates were less likely to misuse illegal drugs and to suffer from communicable infections but exhibited more problems with alcohol and a higher burden of chronic health conditions. Female prisoners were more disposed to mental health problems (including drug abuse) and infectious diseases. In terms of chronic diseases, women suffered from the same conditions as men, but the diseases were more prevalent in women. CONCLUSION: It is important to understand the different disease profiles of prisoners by gender and age, as it helps identify the needs of different groups and tailor age-and gender-specific interventions.

Classification of textures seen from different distances and under varying illumination direction

Changes in the angle of illumination incident upon a 3D surface texture can significantly alter its appearance, implying variations in the image texture. These texture variations produce displacements of class members in the feature space, increasing the failure rates of texture classifiers. To avoid this problem, a model-based texture recognition system which classifies textures seen from different distances and under different illumination directions is presented in this paper. The system works on the basis of a surface model obtained by means of 4-source colour photometric stereo, used to generate 2D image textures under different illumination directions. The recognition system combines coocurrence matrices for feature extraction with a Nearest Neighbour classifier. Moreover, the recognition allows one to guess the approximate direction of the illumination used to capture the test image

Using appearance and context for outdoor scene object classification

We propose a probabilistic object classifier for outdoor scene analysis as a first step in solving the problem of scene context generation. The method begins with a top-down control, which uses the previously learned models (appearance and absolute location) to obtain an initial pixel-level classification. This information provides us the core of objects, which is used to acquire a more accurate object model. Therefore, their growing by specific active regions allows us to obtain an accurate recognition of known regions. Next, a stage of general segmentation provides the segmentation of unknown regions by a bottom-strategy. Finally, the last stage tries to perform a region fusion of known and unknown segmented objects. The result is both a segmentation of the image and a recognition of each segment as a given object class or as an unknown segmented object. Furthermore, experimental results are shown and evaluated to prove the validity of our proposal

On Topological Solitons in The Faddeev-Skyrme Model and its Extensions

The topological solitons of two classical field theories, the Faddeev-Skyrme model and the Ginzburg-Landau model are studied numerically and analytically in this work. The aim is to gain information on the existence and properties of these topological solitons, their structure and behaviour under relaxation. First, the conditions and mechanisms leading to the possibility of topological solitons are explored from the field theoretical point of view. This leads one to consider continuous deformations of the solutions of the equations of motion. The results of algebraic topology necessary for the systematic treatment of such deformations are reviewed and methods of determining the homotopy classes of topological solitons are presented. The Faddeev-Skyrme and Ginzburg-Landau models are presented, some earlier results reviewed and the numerical methods used in this work are described. The topological solitons of the Faddeev-Skyrme model, Hopfions, are found to follow the same mechanisms of relaxation in three different domains with three different topological classifications. For two of the domains, the necessary but unusual topological classification is presented. Finite size topological solitons are not found in the Ginzburg-Landau model and a scaling argument is used to suggest that there are indeed none unless a certain modification to the model, due to R. S. Ward, is made. In that case, the Hopfions of the Faddeev-Skyrme model are seen to be present for some parameter values. A boundary in the parameter space separating the region where the Hopfions exist and the area where they do not exist is found and the behaviour of the Hopfion energy on this boundary is studied.

Gender diversity and innovation in manufacturing and service firms

Traditionally, researchers have considered the innovation process as being gender neutral. However, recently some studies have begun to take gender diversity into account as a determinant of firms’ innovation. This paper aims to analyse how the effect of gender diversity on innovation output at firm level is sensitive to team size. Using the Spanish PITEC (Panel de Innovación Tecnológica) from 2007 to 2012 for innovative manufacturing and service firms, we estimate a multivariate probit model to analyse how gender diversity both in R&D teams and in the total workforce affect product, process, marketing and organizational innovations. Our results show that gender-diverse teams increase the probability of innovating, and this capacity is positively related team size. Gender diversity, in both the R&D department and the total workforce, has a larger positive impact on the probability of carrying out product and organizational innovations in larger teams than it does in smaller teams. This effect is less clear-cut in the case of marketing and process innovation, where the impact is only significant for micro and small firms. Finally, size effects are of greater importance when we distinguish between the manufacturing and service sectors. JEL Code: O30, O31, J16

Classification, comorbidity, heredity, and risk factors of female sexual dysfunctions

Female sexual dysfunctions, including desire, arousal, orgasm and pain problems, have been shown to be highly prevalent among women around the world. The etiology of these dysfunctions is unclear but associations with health, age, psychological problems, and relationship factors have been identified. Genetic effects explain individual variation in orgasm function to some extent but until now quantitative behavior genetic analyses have not been applied to other sexual functions. In addition, behavior genetics can be applied to exploring the cause of any observed comorbidity between the dysfunctions. Discovering more about the etiology of the dysfunctions may further improve the classification systems which are currently under intense debate. The aims of the present thesis were to evaluate the psychometric properties of a Finnish-language version of a commonly used questionnaire for measuring female sexual function, the Female Sexual Function Index (FSFI), in order to investigate prevalence, comorbidity, and classification, and to explore the balance of genetic and environmental factors in the etiology as well as the associations of a number of biopsychosocial factors with female sexual functions. Female sexual functions were studied through survey methods in a population based sample of Finnish twins and their female siblings. There were two waves of data collection. The first data collection targeted 5,000 female twins aged 33–43 years and the second 7,680 female twins aged 18–33 and their over 18–year-old female siblings (n = 3,983). There was no overlap between the data collections. The combined overall response rate for both data collections was 53% (n = 8,868), with a better response rate in the second (57%) compared to the first (45%). In order to measure female sexual function, the FSFI was used. It includes 19 items which measure female sexual function during the previous four weeks in six subdomains; desire, subjective arousal, lubrication, orgasm, sexual satisfaction, and pain. In line with earlier research in clinical populations, a six factor solution of the Finnish-language version of the FSFI received supported. The internal consistencies of the scales were good to excellent. Some questions about how to avoid overestimating the prevalence of extreme dysfunctions due to women being allocated the score of zero if they had had no sexual activity during the preceding four weeks were raised. The prevalence of female sexual dysfunctions per se ranged from 11% for lubrication dysfunction to 55% for desire dysfunction. The prevalence rates for sexual dysfunction with concomitant sexual distress, in other words, sexual disorders were notably lower ranging from 7% for lubrication disorder to 23% for desire disorder. The comorbidity between the dysfunctions was substantial most notably between arousal and lubrication dysfunction even if these two dysfunctions showed distinct patterns of associations with the other dysfunctions. Genetic influences on individual variation in the six subdomains of FSFI were modest but significant ranging from 3–11% for additive genetic effects and 5–18% for nonadditive genetic effects. The rest of the variation in sexual functions was explained by nonshared environmental influences. A correlated factor model, including additive and nonadditive genetic effects and nonshared environmental effects had the best fit. All in all, every correlation between the genetic factors was significant except between lubrication and pain. All correlations between the nonshared environment factors were significant showing that there is a substantial overlap in genetic and nonshared environmental influences between the dysfunctions. In general, psychological problems, poor satisfaction with the relationship, sexual distress, and poor partner compatibility were associated with more sexual dysfunctions. Age was confounded with relationship length but had over and above relationship length a negative effect on desire and sexual satisfaction and a positive effect on orgasm and pain functions. Alcohol consumption in general was associated with better desire, arousal, lubrication, and orgasm function. Women pregnant with their first child had fewer pain problems than nulliparous nonpregnant women. Multiparous pregnant women had more orgasm problems compared to multiparous nonpregnant women. Having children was associated with less orgasm and pain problems. The conclusions were that desire, subjective arousal, lubrication, orgasm, sexual satisfaction, and pain are separate entities that have distinct associations with a number of different biopsychosocial factors. However, there is also considerable comorbidity between the dysfunctions which are explained by overlap in additive genetic, nonadditive genetic and nonshared environmental influences. Sexual dysfunctions are highly prevalent and are not always associated with sexual distress and this relationship might be moderated by a good relationship and compatibility with partner. Regarding classification, the results supports separate diagnoses for subjective arousal and genital arousal as well as the inclusion of pain under sexual dysfunctions.

CLASSIFICATION OF FOREST ROADS AND DETERMINATION OF ROUTE USING GEOGRAPHIC INFORMATION SYSTEM

ABSTRACT Geographic Information System (GIS) is an indispensable software tool in forest planning. In forestry transportation, GIS can manage the data on the road network and solve some problems in transportation, such as route planning. Therefore, the aim of this study was to determine the pattern of the road network and define transport routes using GIS technology. The present research was conducted in a forestry company in the state of Minas Gerais, Brazil. The criteria used to classify the pattern of forest roads were horizontal and vertical geometry, and pavement type. In order to determine transport routes, a data Analysis Model Network was created in ArcGIS using an Extension Network Analyst, allowing finding a route shorter in distance and faster. The results showed a predominance of horizontal geometry classes average (3) and bad (4), indicating presence of winding roads. In the case of vertical geometry criterion, the class of highly mountainous relief (4) possessed the greatest extent of roads. Regarding the type of pavement, the occurrence of secondary coating was higher (75%), followed by primary coating (20%) and asphalt pavement (5%). The best route was the one that allowed the transport vehicle travel in a higher specific speed as a function of road pattern found in the study.