"It was hard to come to mutual understanding..." - Multidimensionality of social learning processes in natural resource use in India, Africa and Latin America

Sustainable natural resource use requires that multiple actors reassess their situation in a systemic perspective. This can be conceptualised as a social learning process between actors from rural communities and the experts from outside organisations. A specifically designed workshop oriented towards a systemic view of natural resource use and the enhancement of mutual learning between local and external actors, provided the background for evaluating the potentials and constraints of intensified social learning processes. Case studies in rural communities in India, Bolivia, Peru and Mali showed that changes in the narratives of the participants of the workshop followed a similar temporal sequence relatively independently from their specific contexts. Social learning processes were found to be more likely to be successful if they 1) opened new space for communicative action, allowing for an intersubjective re-definition of the present situation, 2) contributed to rebalance the relationships between social capital and social, emotional and cognitive competencies within and between local and external actors.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

Mutual Information for Testing Gene-Environment Interaction

Despite current enthusiasm for investigation of gene-gene interactions and gene-environment interactions, the essential issue of how to define and detect gene-environment interactions remains unresolved. In this report, we define gene-environment interactions as a stochastic dependence in the context of the effects of the genetic and environmental risk factors on the cause of phenotypic variation among individuals. We use mutual information that is widely used in communication and complex system analysis to measure gene-environment interactions. We investigate how gene-environment interactions generate the large difference in the information measure of gene-environment interactions between the general population and a diseased population, which motives us to develop mutual information-based statistics for testing gene-environment interactions. We validated the null distribution and calculated the type 1 error rates for the mutual information-based statistics to test gene-environment interactions using extensive simulation studies. We found that the new test statistics were more powerful than the traditional logistic regression under several disease models. Finally, in order to further evaluate the performance of our new method, we applied the mutual information-based statistics to three real examples. Our results showed that P-values for the mutual information-based statistics were much smaller than that obtained by other approaches including logistic regression models.

Symmetric inverse consistent nonlinear registration driven by mutual information.

A nonlinear viscoelastic image registration algorithm based on the demons paradigm and incorporating inverse consistent constraint (ICC) is implemented. An inverse consistent and symmetric cost function using mutual information (MI) as a similarity measure is employed. The cost function also includes regularization of transformation and inverse consistent error (ICE). The uncertainties in balancing various terms in the cost function are avoided by alternatively minimizing the similarity measure, the regularization of the transformation, and the ICE terms. The diffeomorphism of registration for preventing folding and/or tearing in the deformation is achieved by the composition scheme. The quality of image registration is first demonstrated by constructing brain atlas from 20 adult brains (age range 30-60). It is shown that with this registration technique: (1) the Jacobian determinant is positive for all voxels and (2) the average ICE is around 0.004 voxels with a maximum value below 0.1 voxels. Further, the deformation-based segmentation on Internet Brain Segmentation Repository, a publicly available dataset, has yielded high Dice similarity index (DSI) of 94.7% for the cerebellum and 74.7% for the hippocampus, attesting to the quality of our registration method.

Umriss der Entwicklungsgeschichte des jüdischen Rechts. Die Natur der Obligation

Leopold Auerbach

Reactive Co-Radicalization: Religious Extremism as Mutual Dicontent

Extremist rhetoric and behaviour, including violence, emanating from those fearing and opposed to Islamic extremism—and typically generalising that to Islam or Muslims—is undeniable. Equally, there is evidence of Muslim rhetoric that fires up fears of a threatening West and antipathy to religious ‘others’ as damned infidels, including Christians and Jews who are otherwise regarded as co-religionists—as ‘peoples of the Book’. Mutual discontent and antipathy abound. On the one hand, Islamic extremism provokes a reactionary extremism from parts, at least, of the non-Muslim world; on the other hand, Muslim extremism appears often in response to the perception of an aggressive and impositional colonising non-Muslim world. ‘Reactive Co-Radicalization’, I suggest, names this mutual rejection and exclusionary circle currently evident, in particular, with respect to many Muslim and non-Muslim communities. This article discusses reactive co-radicalization as a hermeneutical perspective on religious extremism with particular reference to two European cases.

The Framework of Trade in the Council for Mutual Economic Assistance

This paper establishes an overview of the variables and constraints that affected trade in the Council for Mutual Economic Assistance. It explores the origins of COMECON, the demographic and resource distribution of the member nations, and the role of trade in a centrally planned economy. The paper’s primary focus is on the emergence of a bilateral trade structure, the faulty price mechanism, and the nonconvertibility of currencies. The paper documents the origins and relationships between the constraints of trade within COMECON, and argues that ultimately, these constraints prevented COMECON from fully achieving its economic objectives.