Morphological stability of electromigration-driven vacancy islands

The electromigration-induced shape evolution of two-dimensional vacancy islands on a crystal surface is studied using a continuum approach. We consider the regime where mass transport is restricted to terrace diffusion in the interior of the island. In the limit of fast attachment/detachment kinetics a circle translating at constant velocity is a stationary solution of the problem. In contrast to earlier work [O. Pierre-Louis and T.L. Einstein, Phys. Rev. B 62, 13697 (2000)] we show that the circular solution remains linearly stable for arbitrarily large driving forces. The numerical solution of the full nonlinear problem nevertheless reveals a fingering instability at the trailing end of the island, which develops from finite amplitude perturbations and eventually leads to pinch-off. Relaxing the condition of instantaneous attachment/detachment kinetics, we obtain non-circular elongated stationary shapes in an analytic approximation which compares favorably to the full numerical solution.Comment: 12 page

Evidence for a Ru4+^{4+} Kondo Lattice in LaCu3_3Ru4_4O12_{12}

Rare $d$-electron derived heavy-fermion properties of the solid-solution series LaCu$_3$Ru$_x$Ti$_{4-x}$O$_{12}$ were studied for $1 \leq x \leq 4$ by resistivity, susceptibility, specific-heat measurements, and magnetic-resonance techniques. The pure ruthenate ($x = 4$) is a heavy-fermion metal characterized by a resistivity proportional to $T^2$ at low temperatures $T$. The coherent Kondo lattice formed by the localized Ru 4$d$ electrons is screened by the conduction electrons leading to strongly enhanced effective electron masses. By increasing titanium substitution the Kondo lattice becomes diluted resulting in single-ion Kondo properties like in the paradigm $4f$-based heavy-fermion compound Ce$_x$La$_{1-x}$Cu$_{2.05}$Si$_2$ [M. Ocko {\em et al.}, Phys. Rev. B \textbf{64}, 195106 (2001)]. In LaCu$_3$Ru$_x$Ti$_{4-x}$O$_{12}$ the heavy-fermion behavior finally breaks down on crossing the metal-to-insulator transition close to $x = 2$.Comment: 9 pages, 8 figure

Magnetic and vibrational properties of the covalent chain antiferromagnet RbFeS2

Ternary rubidium-iron sulfide, RbFeS2, belongs to a family of quasi-one-dimensional compounds with the general chemical composition AFeCh2 (where A – K, Rb, Cs, Tl; Ch – S, Se). Understanding the magnetic properties of these compounds is a challenge. The controversy concerning the spin-state of the iron ion needs to be resolved to build the proper model of magnetism. Single crystals of RbFeS2 were grown and characterized by powder x-ray diffraction. QD MPMS-5 SQUID magnetometry was used to measure the magnetic susceptibility, and specific heat was measured utilizing QD PPMS-9 setup. Above the transition to three-dimensional antiferromagnetic order at the Néel temperature of TN = 188 K, the susceptibility exhibits unusual quasi-linear increase up to the highest measured temperature of 500 K. The specific heat was measured in the temperature range 1.8 – 300 K. Ab initio phonon dispersion and density-of-states calculations were performed by means of density functional theory (DFT), and the calculated lattice specific heat was subtracted from the measured one giving the magnetic contribution to the specific heat. Our results suggest that the features of the magnetic specific heat are general for the whole family of the covalent chain ternary iron chalcogenides of the AFeCh2 structure and indicate an intermediate S = 3/2 spin state of the iron ion

Systematic Overestimation of Machine Learning Performance in Neuroimaging Studies of Depression

We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of more data, larger machine learning studies consistently show much weaker performance than the numerous small-scale studies. Here, we systematically investigated this effect focusing on one of the most heavily studied questions in the field, namely the classification of patients suffering from Major Depressive Disorder (MDD) and healthy controls. Drawing upon a balanced sample of $N = 1,868$ MDD patients and healthy controls from our recent international Predictive Analytics Competition (PAC), we first trained and tested a classification model on the full dataset which yielded an accuracy of 61%. Next, we mimicked the process by which researchers would draw samples of various sizes ($N=4$ to $N=150$) from the population and showed a strong risk of overestimation. Specifically, for small sample sizes ($N=20$), we observe accuracies of up to 95%. For medium sample sizes ($N=100$) accuracies up to 75% were found. Importantly, further investigation showed that sufficiently large test sets effectively protect against performance overestimation whereas larger datasets per se do not. While these results question the validity of a substantial part of the current literature, we outline the relatively low-cost remedy of larger test sets

Magnetic Properties of Chain Antiferromagnets RbFeSe2, TlFeSe2, and TlFeS2

Single crystals of ternary ion chalcogenides RbFeSe2, TlFeSe2, and TlFeS2 are studied by X-ray diffraction, SQUID magnetometry, and Mossbauer spectroscopy. Common structural units of these chalcogenides are tetrahedra of FeCh4 (chalcogen Ch = Se, S), arranged in chains by sharing an edge. It is found that RbFeSe2, TlFeSe2, and TlFeS2 undergo transition to a collinear antiferromagnetic state below temperatures TN = 248, 290, and 196 K, respectively. Their magnetic moments are oriented perpendicular to the axes of the chains of FeCh4 tetrahedra

Functional Connectivity Analyses in Imaging Genetics: Considerations on Methods and Data Interpretation

Functional magnetic resonance imaging (fMRI) can be combined with genotype assessment to identify brain systems that mediate genetic vulnerability to mental disorders (“imaging genetics”). A data analysis approach that is widely applied is “functional connectivity”. In this approach, the temporal correlation between the fMRI signal from a pre-defined brain region (the so-called “seed point”) and other brain voxels is determined. In this technical note, we show how the choice of freely selectable data analysis parameters strongly influences the assessment of the genetic modulation of connectivity features. In our data analysis we exemplarily focus on three methodological parameters: (i) seed voxel selection, (ii) noise reduction algorithms, and (iii) use of additional second level covariates. Our results show that even small variations in the implementation of a functional connectivity analysis can have an impact on the connectivity pattern that is as strong as the potential modulation by genetic allele variants. Some effects of genetic variation can only be found for one specific implementation of the connectivity analysis. A reoccurring difficulty in the field of psychiatric genetics is the non-replication of initially promising findings, partly caused by the small effects of single genes. The replication of imaging genetic results is therefore crucial for the long-term assessment of genetic effects on neural connectivity parameters. For a meaningful comparison of imaging genetics studies however, it is therefore necessary to provide more details on specific methodological parameters (e.g., seed voxel distribution) and to give information how robust effects are across the choice of methodological parameters

Effect of the G72 (DAOA) putative risk haplotype on cognitive functions in healthy subjects

<p>Abstract</p> <p>Background</p> <p>In the last years, several susceptibility genes for psychiatric disorders have been identified, among others <it>G72 </it>(also named D-amino acid oxidase activator, DAOA). Typically, the high-risk variant of a vulnerability gene is associated with decreased cognitive functions already in healthy individuals. In a recent study however, a positive effect of the high-risk variant of <it>G72 </it>on verbal working memory was reported. In the present study, we therefore examined the relationship between <it>G72 </it>genotype status and a broad range of cognitive functions in 423 healthy individuals.</p> <p>Methods</p> <p>The <it>G72 </it>carrier status was assessed by the two single nucleotide polymorphisms (SNPs) M23 and M24. Subjects were divided into three risk groups (low, intermediate and high risk).</p> <p>Results</p> <p><it>G72 </it>status influenced a number of cognitive functions, such as verbal working memory, attention, and, at a trend level, spatial working memory and executive functions. Interestingly, the high-risk allele carriers scored better than one or even both other groups.</p> <p>Conclusion</p> <p>Our data show that the putative high-risk haplotype (i.e. homozygote C/C-allele carriers in SNP M23 and homozygote T/T-allele carriers in SNP M24) is in healthy individuals not necessarily associated with worse performance in cognitive functions, but even with better performance in some domains. Further work is required to identify the mechanisms of <it>G72 </it>on brain functions.</p

Volume of subcortical brain regions in social anxiety disorder:mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = −0.077, pFWE = 0.037; right: d = −0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = −0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = −0.141, pFWE &lt; 0.001; right: d = −0.158, pFWE &lt; 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.</p

Volume of subcortical brain regions in social anxiety disorder:mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = −0.077, pFWE = 0.037; right: d = −0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = −0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = −0.141, pFWE &lt; 0.001; right: d = −0.158, pFWE &lt; 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.</p

Volume of subcortical brain regions in social anxiety disorder:mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = −0.077, pFWE = 0.037; right: d = −0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = −0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = −0.141, pFWE &lt; 0.001; right: d = −0.158, pFWE &lt; 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.</p