Genetic algorithm optimization of adaptive multi-scale GLCM features

We introduce a new second-order method of texture analysis called Adaptive Multi-Scale Grey Level Co-occurrence Matrix (AMSGLCM), based on the well-known Grey Level Co-occurrence Matrix (GLCM) method. The method deviates significantly from GLCM in that features are extracted, not via a fixed 2D weighting function of co-occurrence matrix elements, but by a variable summation of matrix elements in 3D localized neighborhoods. We subsequently present a new methodology for extracting optimized, highly discriminant features from these localized areas using adaptive Gaussian weighting functions. Genetic Algorithm (GA) optimization is used to produce a set of features whose classification worth is evaluated by discriminatory power and feature correlation considerations. We critically appraised the performance of our method and GLCM in pairwise classification of images from visually similar texture classes, captured from Markov Random Field (MRF) synthesized, natural, and biological origins. In these cross-validated classification trials, our method demonstrated significant benefits over GLCM, including increased feature discriminatory power, automatic feature adaptability, and significantly improved classification performance.

How common is comorbidity and why does it occur?

Comorbidity is most generally defined as the co-occurrence of two or more mental health problems. Comorbidity between drug and other psychological disorders has emerged as a major clinical, public health and research issue over the past few decades. The reasons for comorbidity are complex. Furthermore, comorbidity is often associated with poor treatment outcome, severe illness course, and high service utilisation. This presents a significant challenge with respect to the identification, prevention and management of people with comorbid disorders. The unmet need for treatment within this group is considerable and the lack of research is unacceptable. This paper will give a brief overview of epidemiological research into comorbidity; and examine the reasons why comorbidity might occur.

Socioeconomic position, cognitive function, and clustering of cardiovascular risk factors in adolescence: Findings from the Mater University Study of Pregnancy and its outcomes

Objectives: The objectives of this study were to examine the extent of clustering of smoking, high levels of television watching, overweight, and high blood pressure among adolescents and whether this clustering varies by socioeconomic position and Cognitive function. Methods: This study was a cross-sectional analysis of 3613 (1742 females) participants of an Australian birth cohort who were examined at age 14. Results: Three hundred fifty-three (9.8%) of the participants had co-occurrence of three or four risk factors. Risk factors clustered in these adolescents with a greater number of participants than would be predicted by assumptions of independence having no risk factors and three or four risk factors. The extent of clustering tended to be greater in those from lower-income families and among those with lower cognitive function. The age-adjusted ratio of observed to expected cooccurrence of three or four risk factors was 2.70 (95% confidence interval [Cl], 1.80-4.06) among those from low-income families and 1.70 (95% Cl, 1.34-2.16) among those from more affluent families. The ratio among those with low Raven's scores (nonverbal reasoning) was 2.36 (95% Cl, 1.69-3.30) and among those with higher scores was 1.51 (95% Cl, 1.19-1.92); similar results for the WRAT 3 score (reading ability) were 2.69 (95% Cl, 1.85-3.94) and 1.68 (95% Cl, 1.34-2.11). Clustering did not differ by sex. Conclusion: Among adolescents, coronary heart disease risk factors cluster, and there is some evidence that this clustering is greater among those from families with low income and those who have lower cognitive function.

Family violence: Walking the tight rope between maternal alienation and child safety

Mothers are often alienated from their children when child abuse is suspected or confirmed, whether she is the primary abuser of the child or not. An abusive or violent partner often initiates the process of maternal alienation from children as a control mechanism. When the co-occurrence of maternal and child abuse is not recognised, nurses and health professionals risk further alienating a mother from her children, which can have detrimental effects in both the short and long term. Evidence shows that when mothers are supported and have the necessary resources there is a reduction in the violence and abuse she and her children experience; this occurs even in situations where the mother is the primary abuser of her children. The family-centred care philosophy, which is widely accepted as the best approach to nursing care for children and their families, creates tension for nurses caring for children who are the victims of abuse as this care generally occurs away from the context of the family. This fragmented approach to caring for abused children can inadvertently undermine the mother-child relationship and further contribute to maternal alienation. This paper discusses the complexity of family violence for nurses negotiating the 'tight rope' between the prime concern for the safety of children and further contributing to maternal alienation, within a New Zealand context. The premise that restoration of the mother-child relationship is paramount for the long-term wellbeing of both the children and the mother provides the basis for discussing implications for nursing practice.

Evaluation of unsupervised semantic mapping of natural language with Leximancer concept mapping

The Leximancer system is a relatively new method for transforming lexical co-occurrence information from natural language into semantic patterns in an unsupervised manner. It employs two stages of co-occurrence information extraction-semantic and relational-using a different algorithm for each stage. The algorithms used are statistical, but they employ nonlinear dynamics and machine learning. This article is an attempt to validate the output of Leximancer, using a set of evaluation criteria taken from content analysis that are appropriate for knowledge discovery tasks.

Some like it wet - biological characteristics underpinning tolerance of extreme water stress events in Antarctic bryophytes

Antarctic bryophyte communities presently tolerate physiological extremes in water availability, surviving both desiccation and submergence events. We investigated the relative ability of three Antarctic moss species to tolerate physiological extremes in water availability and identified physiological, morphological, and biochemical characteristics that assist species performance under such conditions. Tolerance of desiccation and submergence was investigated using chlorophyll fluorescence during a series of field- and laboratory-based water stress events. Turf water retention and degree of natural habitat submergence were determined from gametophyte shoot size and density, and delta C-13 signatures, respectively. Finally, compounds likely to assist membrane structure and function during desiccation events (fatty acids and soluble carbohydrates) were determined. The results of this study show significant differences in the performance of the three study species under contrasting water stress events. The results indicate that the three study species occupy distinctly different ecological niches with respect to water relations, and provide a physiological explanation for present species distributions. The poor tolerance of submergence seen in Ceratodon purpureus helps explain its restriction to drier sites and conversely, the low tolerance of desiccation and high tolerance of submergence displayed by the endemic Grimmia antarctici is consistent with its restriction to wet habitats. Finally the flexible response observed for Bryum pseudotriquetrum is consistent with its co-occurrence with the other two species across the bryophyte habitat spectrum. The likely effects of future climate change induced shifts in water availability are discussed with respect to future community dynamics.

Towards user profiling for web recommendation

Collaborative recommendation is one of widely used recommendation systems, which recommend items to visitor on a basis of referring other's preference that is similar to current user. User profiling technique upon Web transaction data is able to capture such informative knowledge of user task or interest. With the discovered usage pattern information, it is likely to recommend Web users more preferred content or customize the Web presentation to visitors via collaborative recommendation. In addition, it is helpful to identify the underlying relationships among Web users, items as well as latent tasks during Web mining period. In this paper, we propose a Web recommendation framework based on user profiling technique. In this approach, we employ Probabilistic Latent Semantic Analysis (PLSA) to model the co-occurrence activities and develop a modified k-means clustering algorithm to build user profiles as the representatives of usage patterns. Moreover, the hidden task model is derived by characterizing the meaningful latent factor space. With the discovered user profiles, we then choose the most matched profile, which possesses the closely similar preference to current user and make collaborative recommendation based on the corresponding page weights appeared in the selected user profile. The preliminary experimental results performed on real world data sets show that the proposed approach is capable of making recommendation accurately and efficiently.

Grumbling, voting, demonstrating, and rioting: ''Rationality'' and decision-making in intergroup conflict

An individual faced with intergroup conflict chooses A from a vast array of possible actions, ranging from grumbling among ingroup friends to voting and demonstrating to rioting and revolution. The present paper conceptualises these intergroup choices as rationally shaped by perceptions of the benefits and costs associated with the action (expectancy-value processes). However, in presenting a model of agentic normative influence, it is argued that in intergroup contexts group-level costs and benefits play a critical role in individuals' decision-making. In the context of English-French conflict in Quebec, in Canada, four studies provide evidence that group-level costs and benef influence individuals' decision-making in intergro conflict; that the individual level of analysis need mediate the group level of analysis; that group-level co and benefits mediate the relationship between soc identity and intentions to engage in collective action; a that perceptions of outgroup and ingroup norms for inte group behaviours are relatively invariant and predictal related to perceptions of the group- and individual-le, benefits and costs associated with individualistic vers collective actions. By modelling the relationship betwe group norms and group-level costs and benefits, soc psychologists may begin to address the processes th underlie identity-behaviour relationships in collecti action and intergroup conflict.