Reciprocal associations between youth's responses to interpersonal stress and depression: the moderating role of sex

This study examined reciprocal associations between responses to interpersonal stress and depression in youth. Specifically, it tested the hypothesis that depression predicts fewer effortful, planful responses to peer stress and more involuntary, dysregulated responses over time, and that these types of responses then predict future depression. In addition, sex differences in these reciprocal associations were explored. Youth (M age = 12.41; SD = 1.19; 86 girls, 81 boys) and their maternal caregivers completed semi-structured interviews and questionnaires at three annual waves. Path analyses were conducted to examine associations between responses to stress and depression. Multi-group comparison analyses revealed sex differences in these associations; in girls, maladaptive interpersonal stress responses predicted depression, whereas in boys, depression predicted maladaptive interpersonal stress responses. These findings indicate that engaging in adaptive responses to stressful interpersonal situations may be more important for girls??? than boys??? psychological well-being, and that boys??? stress responses may be more susceptible than girls??? to their mood states. Findings are discussed with regard to interventions designed to prevent the onset and persistence of depression

Differential Evolution with Reversible Linear Transformations

Differential evolution (DE) is a well-known type of evolutionary algorithms (EA). Similarly to other EA variants it can suffer from small populations and loose diversity too quickly. This paper presents a new approach to mitigate this issue: We propose to generate new candidate solutions by utilizing reversible linear transformations applied to a triplet of solutions from the population. In other words, the population is enlarged by using newly generated individuals without evaluating their fitness. We assess our methods on three problems: (i) benchmark function optimization, (ii) discovering parameter values of the gene repressilator system, (iii) learning neural networks. The empirical results indicate that the proposed approach outperforms vanilla DE and a version of DE with applying differential mutation three times on all testbeds

Differential Evolution with Reversible Linear Transformations

Differential evolution (DE) is a well-known type of evolutionary algorithms (EA). Similarly to other EA variants it can suffer from small populations and loose diversity too quickly. This paper presents a new approach to mitigate this issue: We propose to generate new candidate solutions by utilizing reversible linear transformation applied to a triplet of solutions from the population. In other words, the population is enlarged by using newly generated individuals without evaluating their fitness. We assess our methods on three problems: (i) benchmark function optimization, (ii) discovering parameter values of the gene repressilator system, (iii) learning neural networks. The empirical results indicate that the proposed approach outperforms vanilla DE and a version of DE with applying differential mutation three times on all testbeds.Comment: Code: https://github.com/jmtomcza

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

Systems approaches and algorithms for discovery of combinatorial therapies

Effective therapy of complex diseases requires control of highly non-linear complex networks that remain incompletely characterized. In particular, drug intervention can be seen as control of signaling in cellular networks. Identification of control parameters presents an extreme challenge due to the combinatorial explosion of control possibilities in combination therapy and to the incomplete knowledge of the systems biology of cells. In this review paper we describe the main current and proposed approaches to the design of combinatorial therapies, including the empirical methods used now by clinicians and alternative approaches suggested recently by several authors. New approaches for designing combinations arising from systems biology are described. We discuss in special detail the design of algorithms that identify optimal control parameters in cellular networks based on a quantitative characterization of control landscapes, maximizing utilization of incomplete knowledge of the state and structure of intracellular networks. The use of new technology for high-throughput measurements is key to these new approaches to combination therapy and essential for the characterization of control landscapes and implementation of the algorithms. Combinatorial optimization in medical therapy is also compared with the combinatorial optimization of engineering and materials science and similarities and differences are delineated.Comment: 25 page

C\mathcal{C}-filtered modules and proper costratifying systems

In this paper we define and study the notion of a proper costratifying system, which is a generalization of the so-called proper costandard modules to the context of stratifying systems. The proper costandard modules were defined by V. Dlab in his study of quasi-hereditary algebras (see \cite{Dlab}).Comment: 23 page

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