A family resemblance? The regulation of marriage migration in Europe

This article analyses key aspects of the regulation of entry and stay of spousal migrants in EEA member states. It shows that there are differences of regulation, particularly between states in Eastern and Southern Europe and states in Northern and Western Europe but, in most cases, the amount of divergence is limited. The article connects this ‘family resemblance’ to a broad concept of Europeanisation. Even where there is no binding legal obligation, European legal norms and the practice in other European states largely circumscribe what is possible

Different coping strategies amongst individuals with grandiose and vulnerable narcissistic traits

OBJECTIVE: This study explored the relationships between coping with stress responses and grandiose and vulnerable narcissist traits. METHOD: A community sample of 170 adults (113 female) participated in this study. A cross-sectional design was employed that utilized self-report measures of trait anxiety, social desirability, coping with stress responses, and pathological narcissism. RESULTS: Regression models indicated that both grandiose and vulnerable narcissism traits are significantly associated with, in opposing directions, behavioural disengagement responses to stress when controlling for trait anxiety and social desirability. Vulnerable narcissism traits were significantly associated with the use of denial as coping with stress response when controlling for the same factors. CONCLUSION: These findings provide further evidence of the discriminant validity of the Pathological Narcissism Inventory and inform our understanding of the differences that grandiose and vulnerable narcissistic traits have on coping

Monte Carlo study of the evaporation/condensation transition on different Ising lattices

In 2002 Biskup et al. [Europhys. Lett. 60, 21 (2002)] sketched a rigorous proof for the behavior of the 2D Ising lattice gas, at a finite volume and a fixed excess \delta M of particles (spins) above the ambient gas density (spontaneous magnetisation). By identifying a dimensionless parameter \Delta (\delta M) and a universal constant \Delta_c, they showed in the limit of large system sizes that for \Delta < \Delta_c the excess is absorbed in the background (``evaporated'' system), while for \Delta > \Delta_c a droplet of the dense phase occurs (``condensed'' system). To check the applicability of the analytical results to much smaller, practically accessible system sizes, we performed several Monte Carlo simulations for the 2D Ising model with nearest-neighbour couplings on a square lattice at fixed magnetisation M. Thereby, we measured the largest minority droplet, corresponding to the condensed phase, at various system sizes (L=40, >..., 640). With analytic values for for the spontaneous magnetisation m_0, the susceptibility \chi and the Wulff interfacial free energy density \tau_W for the infinite system, we were able to determine \lambda numerically in very good agreement with the theoretical prediction. Furthermore, we did simulations for the spin-1/2 Ising model on a triangular lattice and with next-nearest-neighbour couplings on a square lattice. Again, finding a very good agreement with the analytic formula, we demonstrate the universal aspects of the theory with respect to the underlying lattice. For the case of the next-nearest-neighbour model, where \tau_W is unknown analytically, we present different methods to obtain it numerically by fitting to the distribution of the magnetisation density P(m).Comment: 14 pages, 17 figures, 1 tabl

Canonical Correlation Analysis and Partial Least Squares for identifying brain-behaviour associations: a tutorial and a comparative study

Canonical Correlation Analysis (CCA) and Partial Least Squares (PLS) are powerful multivariate methods for capturing associations across two modalities of data (e.g., brain and behaviour). However, when the sample size is similar or smaller than the number of variables in the data, CCA and PLS models may overfit, i.e., find spurious associations that generalise poorly to new data. Dimensionality reduction and regularized extensions of CCA and PLS have been proposed to address this problem, yet most studies using these approaches have some limitations. This work gives a theoretical and practical introduction into the most common CCA/PLS models and their regularized variants. We examine the limitations of standard CCA and PLS when the sample size is similar or smaller than the number of variables. We discuss how dimensionality reduction and regularization techniques address this problem and explain their main advantages and disadvantages. We highlight crucial aspects of the CCA/PLS analysis framework, including optimising the hyperparameters of the model and testing the identified associations for statistical significance. We apply the described CCA/PLS models to simulated data and real data from the Human Connectome Project and the Alzheimer's Disease Neuroimaging Initiative (both of n>500). We use both low and high dimensionality versions of each data (i.e., ratios between sample size and variables in the range of ∼1-10 and ∼0.1-0.01) to demonstrate the impact of data dimensionality on the models. Finally, we summarize the key lessons of the tutorial

TVL₁ Planarity Regularization for 3D Shape Approximation

The modern emergence of automation in many industries has given impetus to extensive research into mobile robotics. Novel perception technologies now enable cars to drive autonomously, tractors to till a field automatically and underwater robots to construct pipelines. An essential requirement to facilitate both perception and autonomous navigation is the analysis of the 3D environment using sensors like laser scanners or stereo cameras. 3D sensors generate a very large number of 3D data points when sampling object shapes within an environment, but crucially do not provide any intrinsic information about the environment which the robots operate within. This work focuses on the fundamental task of 3D shape reconstruction and modelling from 3D point clouds. The novelty lies in the representation of surfaces by algebraic functions having limited support, which enables the extraction of smooth consistent implicit shapes from noisy samples with a heterogeneous density. The minimization of total variation of second differential degree makes it possible to enforce planar surfaces which often occur in man-made environments. Applying the new technique means that less accurate, low-cost 3D sensors can be employed without sacrificing the 3D shape reconstruction accuracy

Photoreceptor Cell Death, Proliferation and Formation of Hybrid Rod/S-Cone Photoreceptors in the Degenerating STK38L Mutant Retina

A homozygous mutation in STK38L in dogs impairs the late phase of photoreceptor development, and is followed by photoreceptor cell death (TUNEL) and proliferation (PCNA, PHH3) events that occur independently in different cells between 7–14 weeks of age. During this period, the outer nuclear layer (ONL) cell number is unchanged. The dividing cells are of photoreceptor origin, have rod opsin labeling, and do not label with markers specific for macrophages/microglia (CD18) or Müller cells (glutamine synthetase, PAX6). Nestin labeling is absent from the ONL although it labels the peripheral retina and ciliary marginal zone equally in normals and mutants. Cell proliferation is associated with increased cyclin A1 and LATS1 mRNA expression, but CRX protein expression is unchanged. Coincident with photoreceptor proliferation is a change in the photoreceptor population. Prior to cell death the photoreceptor mosaic is composed of L/M- and S-cones, and rods. After proliferation, both cone types remain, but the majority of rods are now hybrid photoreceptors that express rod opsin and, to a lesser extent, cone S-opsin, and lack NR2E3 expression. The hybrid photoreceptors renew their outer segments diffusely, a characteristic of cones. The results indicate the capacity for terminally differentiated, albeit mutant, photoreceptors to divide with mutations in this novel retinal degeneration gene

Gene Expression Signature of Normal Cell-of-Origin Predicts Ovarian Tumor Outcomes

The potential role of the cell-of-origin in determining the tumor phenotype has been raised, but not adequately examined. We hypothesized that distinct cells-of-origin may play a role in determining ovarian tumor phenotype and outcome. Here we describe a new cell culture medium for in vitro culture of paired normal human ovarian (OV) and fallopian tube (FT) epithelial cells from donors without cancer. While these cells have been cultured individually for short periods of time, to our knowledge this is the first long-term culture of both cell types from the same donors. Through analysis of the gene expression profiles of the cultured OV/FT cells we identified a normal cell-of-origin gene signature that classified primary ovarian cancers into OV-like and FT-like subgroups; this classification correlated with significant differences in clinical outcomes. The identification of a prognostically significant gene expression signature derived solely from normal untransformed cells is consistent with the hypothesis that the normal cell-of-origin may be a source of ovarian tumor heterogeneity and the associated differences in tumor outcome

Influence of Blood-Brain Barrier Integrity on Brain Protein Biomarker Clearance in Severe Traumatic Brain Injury: A Longitudinal Prospective Study.

Brain protein biomarker clearance to blood in traumatic brain injury (TBI) is not fully understood. The aim of this study was to analyze the effect that a disrupted blood-brain barrier (BBB) had on biomarker clearance. Seventeen severe TBI patients admitted to Karolinska University Hospital were prospectively included. Cerebrospinal fluid (CSF) and blood concentrations of S100 calcium binding protein B (S100B) and neuron-specific enolase (NSE) were analyzed every 6-12 h for ∼1 week. Blood and CSF albumin were analyzed every 12-24 h, and BBB integrity was assessed using the CSF:blood albumin quotient (QA). We found that time-dependent changes in the CSF and blood levels of the two biomarkers were similar, but that the correlation between the biomarkers and QA was lower for NSE (ρ = 0.444) than for S100B (ρ = 0.668). Because data were longitudinal, we also conducted cross correlation analyses, which indicated a directional flow and lag-time of biomarkers from CSF to blood. For S100B, this lag-time could be ascribed to BBB integrity, whereas for NSE it could not. Upon inferential modelling, using generalized least square estimation (S100B) or linear mixed models (NSE), QA (p = 0.045), time from trauma (p < 0.001), time from trauma2 (p = 0.023), and CSF biomarker levels (p = 0.008) were independent predictors of S100B in blood. In contrast, for NSE, only time from trauma was significant (p < 0.001). These findings are novel and important, but must be carefully interpreted because of different characteristics between the two proteins. Nonetheless, we present the first data that indicate that S100B and NSE are cleared differently from the central nervous system, and that both the disrupted BBB and additional alternative pathways, such as the recently described glymphatic system, may play a role. This is of importance both for clinicians aiming to utilize these biomarkers and for the pathophysiological understanding of brain protein clearance, but warrants further examination

Deep sequencing of the zebrafish transcriptome response to mycobacterium infection

Animal science