Ecosystem size matters: The dimensionality of intralacustrine diversification in Icelandic stickleback is predicted by lake size

Cases of evolutionary diversification can be characterized along a continuum from weak to strong genetic and phenotypic differentiation. Several factors may facilitate or constrain the differentiation process. Comparative analyses of replicates of the same taxon at different stages of differentiation can be useful to identify these factors. We estimated the number of distinct phenotypic groups in threespine stickleback populations from nine lakes in Iceland and in one marine population. Using the inferred number of phenotypic groups in each lake, genetic divergence from the marine population, and physical lake and landscape variables, we tested if ecosystem size, approximated by lake size and depth, or isolation from the ancestral marine gene pool predict the occurrence and the extent of phenotypic and genetic diversification within lakes. We find intralacustrine phenotypic diversification to be the rule rather than the exception, occurring in all but the youngest lake population and being manifest in ecologically important phenotypic traits. Neutral genetic data further indicates non-random mating in four out of nine studied lakes, and restricted gene flow between sympatric phenotypic groups in two. Although neither the phenotypic variation nor the number of intralacustrine phenotypic groups were associated with any of our environmental variables, the number of phenotypic traits that were differentiated was significantly positively related to lake size, and evidence for restricted gene flow between sympatric phenotypic groups was only found in the largest lakes where trait specific phenotypic differentiation was highest.

EEG reactivity and EEG activity in never-treated acute schizophrenics, measured with spectral parameters and dimensional complexity

Our approaches to the use of EEG studies for the understanding of the pathogenesis of schizophrenic symptoms are presented. The basic assumptions of a heuristic and multifactorial model of the psychobiological brain mechanisms underlying the organization of normal behavior is described and used in order to formulate and test hypotheses about the pathogenesis of schizophrenic behavior using EEG measures. Results from our studies on EEG activity and EEG reactivity (= EEG components of a memory-driven, adaptive, non-unitary orienting response) as analyzed with spectral parameters and "chaotic" dimensionality (correlation dimension) are summarized. Both analysis procedures showed a deviant brain functional organization in never-treated first-episode schizophrenia which, within the framework of the model, suggests as common denominator for the pathogenesis of the symptoms a deviation of working memory, the nature of which is functional and not structural.

Virtual autopsy using imaging: bridging radiologic and forensic sciences. A review of the Virtopsy and similar projects

The transdisciplinary research project Virtopsy is dedicated to implementing modern imaging techniques into forensic medicine and pathology in order to augment current examination techniques or even to offer alternative methods. Our project relies on three pillars: three-dimensional (3D) surface scanning for the documentation of body surfaces, and both multislice computed tomography (MSCT) and magnetic resonance imaging (MRI) to visualise the internal body. Three-dimensional surface scanning has delivered remarkable results in the past in the 3D documentation of patterned injuries and of objects of forensic interest as well as whole crime scenes. Imaging of the interior of corpses is performed using MSCT and/or MRI. MRI, in addition, is also well suited to the examination of surviving victims of assault, especially choking, and helps visualise internal injuries not seen at external examination of the victim. Apart from the accuracy and three-dimensionality that conventional documentations lack, these techniques allow for the re-examination of the corpse and the crime scene even decades later, after burial of the corpse and liberation of the crime scene. We believe that this virtual, non-invasive or minimally invasive approach will improve forensic medicine in the near future.

Statistical shape analysis via principal factor analysis

Statistical shape analysis techniques commonly employed in the medical imaging community, such as active shape models or active appearance models, rely on principal component analysis (PCA) to decompose shape variability into a reduced set of interpretable components. In this paper we propose principal factor analysis (PFA) as an alternative and complementary tool to PCA providing a decomposition into modes of variation that can be more easily interpretable, while still being a linear efficient technique that performs dimensionality reduction (as opposed to independent component analysis, ICA). The key difference between PFA and PCA is that PFA models covariance between variables, rather than the total variance in the data. The added value of PFA is illustrated on 2D landmark data of corpora callosa outlines. Then, a study of the 3D shape variability of the human left femur is performed. Finally, we report results on vector-valued 3D deformation fields resulting from non-rigid registration of ventricles in MRI of the brain.

Computer-aided diagnosis of carotid atherosclerosis based on ultrasound image statistics, laws' texture and neural networks

Quantitative characterisation of carotid atherosclerosis and classification into symptomatic or asymptomatic is crucial in planning optimal treatment of atheromatous plaque. The computer-aided diagnosis (CAD) system described in this paper can analyse ultrasound (US) images of carotid artery and classify them into symptomatic or asymptomatic based on their echogenicity characteristics. The CAD system consists of three modules: a) the feature extraction module, where first-order statistical (FOS) features and Laws' texture energy can be estimated, b) the dimensionality reduction module, where the number of features can be reduced using analysis of variance (ANOVA), and c) the classifier module consisting of a neural network (NN) trained by a novel hybrid method based on genetic algorithms (GAs) along with the back propagation algorithm. The hybrid method is able to select the most robust features, to adjust automatically the NN architecture and to optimise the classification performance. The performance is measured by the accuracy, sensitivity, specificity and the area under the receiver-operating characteristic (ROC) curve. The CAD design and development is based on images from 54 symptomatic and 54 asymptomatic plaques. This study demonstrates the ability of a CAD system based on US image analysis and a hybrid trained NN to identify atheromatous plaques at high risk of stroke.

A computer-aided diagnostic system to characterize CT focal liver lesions: design and optimization of a neural network classifier

In this paper, a computer-aided diagnostic (CAD) system for the classification of hepatic lesions from computed tomography (CT) images is presented. Regions of interest (ROIs) taken from nonenhanced CT images of normal liver, hepatic cysts, hemangiomas, and hepatocellular carcinomas have been used as input to the system. The proposed system consists of two modules: the feature extraction and the classification modules. The feature extraction module calculates the average gray level and 48 texture characteristics, which are derived from the spatial gray-level co-occurrence matrices, obtained from the ROIs. The classifier module consists of three sequentially placed feed-forward neural networks (NNs). The first NN classifies into normal or pathological liver regions. The pathological liver regions are characterized by the second NN as cyst or "other disease." The third NN classifies "other disease" into hemangioma or hepatocellular carcinoma. Three feature selection techniques have been applied to each individual NN: the sequential forward selection, the sequential floating forward selection, and a genetic algorithm for feature selection. The comparative study of the above dimensionality reduction methods shows that genetic algorithms result in lower dimension feature vectors and improved classification performance.

Psychometric properties of the Swiss version of the Nursing Home Survey on Patient Safety Culture

The Nursing Home Survey on Patient Safety Culture (NHSPSC) was specifically developed for nursing homes to assess a facility’s safety climate and it consists of 12 dimensions. After its pilot testing, however, no fur- ther psychometric analyses were performed on the instrument. For this study of safety climate in Swiss nursing home units, the NHSPSC was linguistically adapted to the Swiss context and to address the unit as well as facility level, with the aim of testing aspects of the validity and reliability of the Swiss version before its use in Swiss nursing home units. Psychometric analyses were performed on data from 367 nurs- ing personnel from nine nursing homes in the German-speaking part of Switzerland (response rate = 66%), and content validity (CVI) examined. The statistical influence of unit membership on respondents’ answers, and on their agreement concerning their units’ safety climate, was tested using intraclass corre- lation coefficients (ICCs) and the rWG(J) interrater agreement index. A multilevel exploratory factor analysis (MEFA) with oblimin rotation was applied to examine the questionnaire’s dimensionality. Cronbach’s alpha and Raykov’s rho were calculated to assess factor reliability. The relationship of safety climate dimensions with clinical outcomes was explored. Expert feedback confirmed the relevance of the instru- ment’s items (CVI = 0.93). Personnel showed strong agreement in their perceptions in three dimensions of the questionnaire. ICCs supported a multilevel analysis. MEFA produced nine factors at the within-level (in comparison to 12 in the original version) and two factors at the between-level with satisfactory fit statis- tics. Raykov’s Rho for the single level factors ranged between 0.67 and 0.86. Some safety climate dimen- sions show moderate, but non-significant correlations with the use of bedrails, physical restraint use, and fall-related injuries. The Swiss version of the NHSPSC needs further refinement and testing before its use can be recommended in Swiss nursing homes: its dimensionality needs further clarification, particularly to distinguish items addressing the unit-level safety climate from those at the facility level.

Two-dimensional supramolecular polymers: controlled formation and visualization on the surface

Self – assembly is a powerful tool for the construction of highly organized nanostructures. Therefore, the possibility to control and predict pathways of molecular ordering on the nanoscale level is a critical issue for the production of materials with tunable and adaptive macroscopic properties. 2D polymers are attractive objects for the field of material sciences due to their exceptional properties. [1] As shown before, amphiphilic oligopyrenotides (produced via automated solid-phase synthesis) form rod–like supramolecular polymers in water. [2] These assemblies form 1D objects. [3] By applying certain changes to the design of the oligopyrenotide units the dimensionality of the formed assemblies can be influenced. Herein, we demonstrate that Py3 (see Figure 1) forms defined supramolecular assemblies under thermodynamic conditions in water. To study Py3 self-assembly, we carried out whole set of spectroscopic (UV/vis, fluorescence, DLS) and microscopic experiments (AFM). The obtained results suggest that oligopyrenotides with the present type of geometry and linker length leads to formation of 2D supramolecular assemblies.

Testing for Measurement Equivalence in Surveys: Dimensions of Social Trust across Cultural Contexts

Our study evaluates the dimensionality and equivalence of social trust across cultural contexts, using new data from Switzerland and the World Values Survey 2005–2008. Whereas some scholars assert that trust should be regarded as a coherent concept, others claim that trust is better conceived of as a multidimensional concept. In contrast to the conventional dichotomy of the forms of social trust, we identify three distinct forms of trust, namely, particularized, generalized, and identity-based trust. Moreover, we dispute the view that respondents understand the wording of survey questions regarding social trust differently between different cultural contexts, which would imply that comparative research on trust is a pointless endeavor. Applying multiple-group confirmatory factor analysis to the various constructs of social trust, we conclude that one may study relationships among the three forms of trust and other theoretical constructs as well as compare latent means across cultural contexts. Our analyses therefore provide an optimistic outlook for future comparative analyses that investigate forms of social trust across cultural contexts.

Shaping frequency entangled qudits

We demonstrate the creation, characterization, and manipulation of frequency-entangled qudits by shaping the energy spectrum of entangled photons. The generation of maximally entangled qudit states is verified up to dimension d=4 through tomographic quantum-state reconstruction. Subsequently, we measure Bell parameters for qubits and qutrits as a function of their degree of entanglement. In agreement with theoretical predictions, we observe that for qutrits the Bell parameter is less sensitive to a varying degree of entanglement than for qubits. For frequency-entangled photons, the dimensionality of a qudit is ultimately limited by the bandwidth of the pump laser and can be on the order of a few millions.

ANALYTICAL MODELS OF EXOPLANETARY ATMOSPHERES. I. ATMOSPHERIC DYNAMICS VIA THE SHALLOW WATER SYSTEM

Within the context of exoplanetary atmospheres, we present a comprehensive linear analysis of forced, damped, magnetized shallow water systems, exploring the effects of dimensionality, geometry (Cartesian, pseudo-spherical, and spherical), rotation, magnetic tension, and hydrodynamic and magnetic sources of friction. Across a broad range of conditions, we find that the key governing equation for atmospheres and quantum harmonic oscillators are identical, even when forcing (stellar irradiation), sources of friction (molecular viscosity, Rayleigh drag, and magnetic drag), and magnetic tension are included. The global atmospheric structure is largely controlled by a single key parameter that involves the Rossby and Prandtl numbers. This near-universality breaks down when either molecular viscosity or magnetic drag acts non-uniformly across latitude or a poloidal magnetic field is present, suggesting that these effects will introduce qualitative changes to the familiar chevron-shaped feature witnessed in simulations of atmospheric circulation. We also find that hydrodynamic and magnetic sources of friction have dissimilar phase signatures and affect the flow in fundamentally different ways, implying that using Rayleigh drag to mimic magnetic drag is inaccurate. We exhaustively lay down the theoretical formalism (dispersion relations, governing equations, and time-dependent wave solutions) for a broad suite of models. In all situations, we derive the steady state of an atmosphere, which is relevant to interpreting infrared phase and eclipse maps of exoplanetary atmospheres. We elucidate a pinching effect that confines the atmospheric structure to be near the equator. Our suite of analytical models may be used to develop decisively physical intuition and as a reference point for three-dimensional magnetohydrodynamic simulations of atmospheric circulation.