Causality and independence in systems of equations

The technique of causal ordering is used to study causal and probabilistic aspects implied by model equations. Causal discovery algorithms are used to learn causal and dependence structure from data. In this thesis, 'Causality and independence in systems of equations', we explore the relationship between causal ordering and the output of causal discovery algorithms. By combining these techniques, we bridge the gap between the world of dynamical systems at equilibrium and literature regarding causal methods for static systems. In a nutshell, this gives new insights about models with feedback and an improved understanding of observed phenomena in certain (biological) systems. Based on our ideas, we outline a novel approach towards causal discovery for dynamical systems at equilibrium. This work was inspired by a desire to understand why the output of causal discovery algorithms sometimes appears to be at odds with expert knowledge. We were particularly interested in explaining apparent reversals of causal directions when causal discovery methods are applied to protein expression data. We propose the presence of a perfectly adapting feedback mechanism or unknown measurement error as possible explanations for these apparent reversals. We develop conditions for the detection of perfect adaptation from model equations or from data and background knowledge. This can be used to reason about the existence of feedback mechanisms using only partial observations of a system, resulting in additional criteria for data-driven selection of causal models. This line of research was made possible by novel interpretations and extensions of the causal ordering algorithm. Additionally, we challenge a key assumption in many causal discovery algorithms; that the underlying system can be modelled by the well-known class of structural causal models. To overcome the limitations of these models in capturing the causal semantics of dynamical systems at equilibrium, we propose a generalization that we call causal constraints models. Looking beyond standard causal modelling frameworks allows us to further explore the relationship between dynamical models at equilibrium and methods for causal discovery on equilibrium data

Palaeoenvironmental signatures revealed from rare earth element (REE) compositions of vertebrate microremains of the Vesiku Bone Bed (Homerian, Wenlock), Saaremaa Island, Estonia

The Estonian Journal of Earth Sciences is an open access journal and applies the Creative Commons Attribution 4.0 International License CC BY to all its papers (http://creativecommons.org/licenses/by/4.0/). The attached file is the published version of the article

MOTIFATOR: detection and characterization of regulatory motifs using prokaryote transcriptome data

Summary: Unraveling regulatory mechanisms (e.g. identification of motifs in cis-regulatory regions) remains a major challenge in the analysis of transcriptome experiments. Existing applications identify putative motifs from gene lists obtained at rather arbitrary cutoff and require additional manual processing steps. Our standalone application MOTIFATOR identifies the most optimal parameters for motif discovery and creates an interactive visualization of the results. Discovered putative motifs are functionally characterized, thereby providing valuable insight in the biological processes that could be controlled by the motif.

Charge injection across a polymeric heterojunction

The charge injection across a polymeric heterojunction of a poly-p-phenylene vinylene derivative (injecting layer) and poly (9,9-dioctylfluorene) (accepting layer) is investigated. The electric field in the accepting layer is obtained after correcting the applied voltage for the voltage drop across the injecting layer due to the buildup of space charge. At high electric fields, the current across the polymeric heterojunction exhibits only a weak dependence on the field due to the absence of image force effects, in agreement with model predictions. The strong dependence at low fields can be explained by taking the increase of the Fermi level into account, which effectively modifies the barrier for charge carriers waiting for a jump across the heterojunction

Cognitive flexibility in children with Developmental Language Disorder: Drawing of nonexistent objects

Cognitive flexibility is the ability to adapt thoughts and behaviors to new environments. Previous studies investigating cognitive flexibility in children with Developmental Language Disorder (DLD) present contradictory findings. In the current study, cognitive flexibility was assessed in 5- and 6-year-old preschoolers with DLD (n = 23) and peers with typical development (TD; n = 50) using a nonexistent object drawing (NEOD) task. The children were asked to draw a nonexistent man and a nonexistent house. The children with DLD did not differ from their peers with TD on simple category changes, which were comprised of changes in the size or shape of parts of the object, change of the whole shape of the object, and deletion of parts of the object. Nevertheless, children with DLD made fewer more complex, high-level category changes, which included samecategory insertions, position exchange of object’s parts, and cross-category insertions. The difference between DLD and TD on high-level category changes was related to differences between the two groups in verbal short-term memory and inhibition. Furthermore, children with DLD made no changes to their original drawings of an existing man and house more often than their peers with TD. It is concluded that children with DLD aged 5–6 years show less flexibility on the NEOD task than age-matched children with TD. This difference in cognitive flexibility may be related to lower levels of verbal short-term memory and inhibition ability of children with DLD, or to different use of these cognitive skills on the NEOD task

ATK-ForceField: A New Generation Molecular Dynamics Software Package

ATK-ForceField is a software package for atomistic simulations using classical interatomic potentials. It is implemented as a part of the Atomistix ToolKit (ATK), which is a Python programming environment that makes it easy to create and analyze both standard and highly customized simulations. This paper will focus on the atomic interaction potentials, molecular dynamics, and geometry optimization features of the software, however, many more advanced modeling features are available. The implementation details of these algorithms and their computational performance will be shown. We present three illustrative examples of the types of calculations that are possible with ATK-ForceField: modeling thermal transport properties in a silicon germanium crystal, vapor deposition of selenium molecules on a selenium surface, and a simulation of creep in a copper polycrystal.Comment: 28 pages, 9 figure

Історія створення музею археології Волинського державного університету імені Лесі Українки

Purpose: This study investigated the comprehension of counterfactual conditionals in monolingual Turkish children with specific language impairment (SLI) and typically developing (TD) children. Comprehending counterfactuals requires a well-developed cognitive system (Beck, Riggs, & Gorniak, 2009). Children with SLI have impaired cognitive functioning (Im Bolter, Johnston, & Pascaul-Leone, 2006) and this impacts on their ability to comprehend counterfactuals. Method: The sample consisted of 13 children with SLI who were matched on age and nonverbal IQ with 13 TD children (mean age 6;9 [years; months] for both groups). Each group completed a sentence comprehension and repetition task with three sentence conditions: nonconditional, factual and counterfactual. Nonconditionals do not have if embedding whereas factual and counterfactual conditionals are morphosyntactically equivalent if-clauses, but only the latter is cognitively complex. Results: Conditionals were more difficult to comprehend than nonconditionals for both groups. Counterfactuals were more difficult to comprehend than the morphosyntactically equivalent factual counterparts for the SLI group. There was no discrepancy between the groups for repetition of counterfactuals and factuals. Conclusions: Children with SLI have difficulty processing counterfactuals due to morphosyntactic complexity (if-embedding) and the cognitive processes involved in comprehending counterfactuals. This indicates that cognitive complexity adds to sentence comprehension deficits in SLI