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We present a prototype of an integrated reasoning environment for educational purposes. The presented tool is a fragment of a proof assistant and automated theorem prover. We describe the existing and planned functionality of the theorem prover and especially the functionality of the educational fragment. This currently supports working with terms of the untyped lambda calculus and addresses both undergraduate students and researchers. We show how the tool can be used to support the students' understanding of functional programming and discuss general problems related to the process of building theorem proving software that aims at supporting both research and education.
Manufacturing industries are undergoing a major paradigm shift towards more autonomy. Automated planning and scheduling then becomes a necessity. The Planning and Execution Competition for Logistics Robots in Simulation held at ICAPS is based on this scenario and provides an interesting testbed. However, the posed problem is challenging as also demonstrated by the somewhat weak results in 2017. The domain requires temporal reasoning and dealing with uncertainty. We propose a novel planning system based on Answer Set Programming and the Clingo solver to tackle these problems and incentivize robot cooperation. Our results show a significant performance improvement, both, in terms of lowering computational requirements and better game metrics.
Declarative languages for knowledge representation and reasoning provide constructs to define preference relations over the set of possible interpretations, so that preferred models represent optimal solutions of the encoded problem. We introduce the notion of approximation for replacing preference relations with stronger preference relations, that is, relations comparing more pairs of interpretations. Our aim is to accelerate the computation of a non-empty subset of the optimal solutions by means of highly specialized algorithms. We implement our approach in Answer Set Programming (ASP), where problems involving quantitative and qualitative preference relations can be addressed by ASPRIN, implementing a generic optimization algorithm. Unlike this, chains of approximations allow us to reduce several preference relations to the preference relations associated with ASP’s native weak constraints and heuristic directives. In this way, ASPRIN can now take advantage of several highly optimized algorithms implemented by ASP solvers for computing optimal solutions
The Amyloid-precursor-like protein 1 (APLP1) is a neuronal type I transmembrane protein which plays a role in synaptic adhesion and synaptogenesis. Past investigations indicated that APLP1 is involved in the formation of protein-protein complexes that bridge the junctions between neighboring cells. Nevertheless, APLP1-APLP1 trans interactions have never been directly observed in higher eukaryotic cells. Here, we investigate APLP1 interactions and dynamics directly in living human embryonic kidney (HEK) cells, using fluorescence fluctuation spectroscopy techniques, namely cross-correlation scanning fluorescence correlation spectroscopy (sFCS) and Number&Brightness (N&B). Our results show that APLP1 forms homotypic trans complexes at cell-cell contacts. In the presence of zinc ions, the protein forms macroscopic clusters, exhibiting an even higher degree of trans binding and strongly reduced dynamics. Further evidence from Giant Plasma Membrane Vesicles and live cell actin staining suggests that the presence of an intact cortical cytoskeleton is required for zinc-induced cis multimerization. Subsequently, large adhesion platforms bridging interacting cells are formed through APLP1-APLP1 direct trans interactions. Taken together, our results provide direct evidence that APLP1 functions as a neuronal zinc-dependent adhesion protein and provide a more detailed understanding of the molecular mechanisms driving the formation of APLP1 adhesion platforms. Further, they show that fluorescence fluctuation spectroscopy techniques are useful tools for the investigation of protein-protein interactions at cell-cell adhesion sites.
Pace-of-life syndromes
(2018)
This introduction to the topical collection on Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology, and life history provides an overview of conceptual, theoretical, methodological, and empirical progress in research on pace-of-life syndromes (POLSs) over the last decade. The topical collection has two main goals. First, we briefly describe the history of POLS research and provide a refined definition of POLS that is applicable to various key levels of variation (genetic, individual, population, species). Second, we summarise the main lessons learned from current POLS research included in this topical collection. Based on an assessment of the current state of the theoretical foundations and the empirical support of the POLS hypothesis, we propose (i) conceptual refinements of theory, particularly with respect to the role of ecology in the evolution of (sexual dimorphism in) POLS, and (ii) methodological and statistical approaches to the study of POLS at all major levels of variation. This topical collection further holds (iii) key empirical examples demonstrating how POLS structures may be studied in wild populations of (non) human animals, and (iv) a modelling paper predicting POLS under various ecological conditions. Future POLS research will profit from the development of more explicit theoretical models and stringent empirical tests of model assumptions and predictions, increased focus on how ecology shapes (sex-specific) POLS structures at multiple hierarchical levels, and the usage of appropriate statistical tests and study designs. Significance statement As an introduction to the topical collection, we summarise current conceptual, theoretical, methodological and empirical progress in research on pace-of-life syndromes (POLSs), a framework for the adaptive integration of behaviour, physiology and life history at multiple hierarchical levels of variation (genetic, individual, population, species). Mixed empirical support of POLSs, particularly at the within-species level, calls for an evaluation and refinement of the hypothesis. We provide a refined definition of POLSs facilitating testable predictions. Future research on POLSs will profit from the development of more explicit theoretical models and stringent empirical tests of model assumptions and predictions, increased focus on how ecology shapes (sex-specific) POLSs structures at multiple hierarchical levels and the usage of appropriate statistical tests and study designs.
Comparative text mining extends from genre analysis and political bias detection to the revelation of cultural and geographic differences, through to the search for prior art across patents and scientific papers. These applications use cross-collection topic modeling for the exploration, clustering, and comparison of large sets of documents, such as digital libraries. However, topic modeling on documents from different collections is challenging because of domain-specific vocabulary. We present a cross-collection topic model combined with automatic domain term extraction and phrase segmentation. This model distinguishes collection-specific and collection-independent words based on information entropy and reveals commonalities and differences of multiple text collections. We evaluate our model on patents, scientific papers, newspaper articles, forum posts, and Wikipedia articles. In comparison to state-of-the-art cross-collection topic modeling, our model achieves up to 13% higher topic coherence, up to 4% lower perplexity, and up to 31% higher document classification accuracy. More importantly, our approach is the first topic model that ensures disjunct general and specific word distributions, resulting in clear-cut topic representations.
Over the past few years, studying abroad and other educational international experiences have become increasingly highly regarded. Nevertheless, research shows that only a minority of students actually take part in
academic mobility programs. But what is it that distinguishes those students who take up these international opportunities from those who do not? In this
study we reviewed recent quantitative studies on why (primarily German) students choose to travel abroad or not. This revealed a pattern of predictive factors. These indicate the key role played by students’ personal and social background, as well as previous international travel and the course of studies they are enrolled in. The study then focuses on teaching students. Both facilitating and debilitating factors are discussed and included in a model illustrating the decision-making process these students use. Finally, we discuss the practical implications for ways in which international, studyrelated travel might be increased in the future. We suggest that higher education institutions analyze individual student characteristics, offering differentiated programs to better meet the needs of different groups, thus raising the likelihood of disadvantaged students participating in academic international travel.