15 resultados para mutual mistake

em BORIS: Bern Open Repository and Information System - Berna - Suiça


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In this paper we propose a variational approach for multimodal image registration based on the diffeomorphic demons algorithm. Diffeomorphic demons has proven to be a robust and efficient way for intensity-based image registration. However, the main drawback is that it cannot deal with multiple modalities. We propose to replace the standard demons similarity metric (image intensity differences) by point-wise mutual information (PMI) in the energy function. By comparing the accuracy between our PMI based diffeomorphic demons and the B-Spline based free-form deformation approach (FFD) on simulated deformations, we show the proposed algorithm performs significantly better.

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In order to understand how nanoparticles (NPs <100 nm) interact with cellular systems, potentially causing adverse effects, it is important to be able to detect and localize them within cells. Due to the small size of NPs, transmission electron microscopy (TEM) is an appropriate technique to use for visualizing NPs inside cells, since light microscopy fails to resolve them at a single particle level. However, the presence of other cellular and non-cellular nano-sized structures in TEM cell samples, which may resemble NPs in size, morphology and electron density, can obstruct the precise intracellular identification of NPs. Therefore, elemental analysis is recommended to confirm the presence of NPs inside the cell. The present study highlights the necessity to perform elemental analysis, specifically energy filtering TEM, to confirm intracellular NP localization using the example of quantum dots (QDs). Recently, QDs have gained increased attention due to their fluorescent characteristics, and possible applications for biomedical imaging have been suggested. Nevertheless, potential adverse effects cannot be excluded and some studies point to a correlation between intracellular particle localization and toxic effects. J774.A1 murine macrophage-like cells were exposed to NH2 polyethylene (PEG) QDs and elemental co-localization analysis of two elements present in the QDs (sulfur and cadmium) was performed on putative intracellular QDs with electron spectroscopic imaging (ESI). Both elements were shown on a single particle level and QDs were confirmed to be located inside intracellular vesicles. Nevertheless, ESI analysis showed that not all nano-sized structures, initially identified as QDs, were confirmed. This observation emphasizes the necessity to perform elemental analysis when investigating intracellular NP localization using TEM.

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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.

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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.

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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.

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By switching the level of analysis and aggregating data from the micro-level of individual cases to the macro-level, quantitative data can be analysed within a more case-based approach. This paper presents such an approach in two steps: In a first step, it discusses the combination of Social Network Analysis (SNA) and Qualitative Comparative Analysis (QCA) in a sequential mixed-methods research design. In such a design, quantitative social network data on individual cases and their relations at the micro-level are used to describe the structure of the network that these cases constitute at the macro-level. Different network structures can then be compared by QCA. This strategy allows adding an element of potential causal explanation to SNA, while SNA-indicators allow for a systematic description of the cases to be compared by QCA. Because mixing methods can be a promising, but also a risky endeavour, the methodological part also discusses the possibility that underlying assumptions of both methods could clash. In a second step, the research design presented beforehand is applied to an empirical study of policy network structures in Swiss politics. Through a comparison of 11 policy networks, causal paths that lead to a conflictual or consensual policy network structure are identified and discussed. The analysis reveals that different theoretical factors matter and that multiple conjunctural causation is at work. Based on both the methodological discussion and the empirical application, it appears that a combination of SNA and QCA can represent a helpful methodological design for social science research and a possibility of using quantitative data with a more case-based approach.