Model-Checking the Higher-Dimensional Modal mu-Calculus

The higher-dimensional modal mu-calculus is an extension of the mu-calculus in which formulas are interpreted in tuples of states of a labeled transition system. Every property that can be expressed in this logic can be checked in polynomial time, and conversely every polynomial-time decidable problem that has a bisimulation-invariant encoding into labeled transition systems can also be defined in the higher-dimensional modal mu-calculus. We exemplify the latter connection by giving several examples of decision problems which reduce to model checking of the higher-dimensional modal mu-calculus for some fixed formulas. This way generic model checking algorithms for the logic can then be used via partial evaluation in order to obtain algorithms for theses problems which may benefit from improvements that are well-established in the field of program verification, namely on-the-fly and symbolic techniques. The aim of this work is to extend such techniques to other fields as well, here exemplarily done for process equivalences, automata theory, parsing, string problems, and games.Comment: In Proceedings FICS 2012, arXiv:1202.317

The Cat Is On the Mat. Or Is It a Dog? Dynamic Competition in Perceptual Decision Making

Recent neurobiological findings suggest that the brain solves simple perceptual decision-making tasks by means of a dynamic competition in which evidence is accumulated in favor of the alternatives. However, it is unclear if and how the same process applies in more complex, real-world tasks, such as the categorization of ambiguous visual scenes and what elements are considered as evidence in this case. Furthermore, dynamic decision models typically consider evidence accumulation as a passive process disregarding the role of active perception strategies. In this paper, we adopt the principles of dynamic competition and active vision for the realization of a biologically- motivated computational model, which we test in a visual catego- rization task. Moreover, our system uses predictive power of the features as the main dimension for both evidence accumulation and the guidance of active vision. Comparison of human and synthetic data in a common experimental setup suggests that the proposed model captures essential aspects of how the brain solves perceptual ambiguities in time. Our results point to the importance of the proposed principles of dynamic competi- tion, parallel specification, and selection of multiple alternatives through prediction, as well as active guidance of perceptual strategies for perceptual decision-making and the resolution of perceptual ambiguities. These principles could apply to both the simple perceptual decision problems studied in neuroscience and the more complex ones addressed by vision research.Peer reviewe

Matching Natural Language Sentences with Hierarchical Sentence Factorization

Semantic matching of natural language sentences or identifying the relationship between two sentences is a core research problem underlying many natural language tasks. Depending on whether training data is available, prior research has proposed both unsupervised distance-based schemes and supervised deep learning schemes for sentence matching. However, previous approaches either omit or fail to fully utilize the ordered, hierarchical, and flexible structures of language objects, as well as the interactions between them. In this paper, we propose Hierarchical Sentence Factorization---a technique to factorize a sentence into a hierarchical representation, with the components at each different scale reordered into a "predicate-argument" form. The proposed sentence factorization technique leads to the invention of: 1) a new unsupervised distance metric which calculates the semantic distance between a pair of text snippets by solving a penalized optimal transport problem while preserving the logical relationship of words in the reordered sentences, and 2) new multi-scale deep learning models for supervised semantic training, based on factorized sentence hierarchies. We apply our techniques to text-pair similarity estimation and text-pair relationship classification tasks, based on multiple datasets such as STSbenchmark, the Microsoft Research paraphrase identification (MSRP) dataset, the SICK dataset, etc. Extensive experiments show that the proposed hierarchical sentence factorization can be used to significantly improve the performance of existing unsupervised distance-based metrics as well as multiple supervised deep learning models based on the convolutional neural network (CNN) and long short-term memory (LSTM).Comment: Accepted by WWW 2018, 10 page

Analyzing large-scale DNA Sequences on Multi-core Architectures

Rapid analysis of DNA sequences is important in preventing the evolution of different viruses and bacteria during an early phase, early diagnosis of genetic predispositions to certain diseases (cancer, cardiovascular diseases), and in DNA forensics. However, real-world DNA sequences may comprise several Gigabytes and the process of DNA analysis demands adequate computational resources to be completed within a reasonable time. In this paper we present a scalable approach for parallel DNA analysis that is based on Finite Automata, and which is suitable for analyzing very large DNA segments. We evaluate our approach for real-world DNA segments of mouse (2.7GB), cat (2.4GB), dog (2.4GB), chicken (1GB), human (3.2GB) and turkey (0.2GB). Experimental results on a dual-socket shared-memory system with 24 physical cores show speed-ups of up to 17.6x. Our approach is up to 3x faster than a pattern-based parallel approach that uses the RE2 library.Comment: The 18th IEEE International Conference on Computational Science and Engineering (CSE 2015), Porto, Portugal, 20 - 23 October 201

CHR Grammars

A grammar formalism based upon CHR is proposed analogously to the way Definite Clause Grammars are defined and implemented on top of Prolog. These grammars execute as robust bottom-up parsers with an inherent treatment of ambiguity and a high flexibility to model various linguistic phenomena. The formalism extends previous logic programming based grammars with a form of context-sensitive rules and the possibility to include extra-grammatical hypotheses in both head and body of grammar rules. Among the applications are straightforward implementations of Assumption Grammars and abduction under integrity constraints for language analysis. CHR grammars appear as a powerful tool for specification and implementation of language processors and may be proposed as a new standard for bottom-up grammars in logic programming. To appear in Theory and Practice of Logic Programming (TPLP), 2005Comment: 36 pp. To appear in TPLP, 200

Lineage-specific gene expression and the regulative capacities of the sea urchin embryo: a proposed mechanism

Three aspects of early sea urchin development are reviewed, and conclusions derived that lead to a unified concept of how the initial specifications of differential gene activity may occur in this embryo. i. The embryo has an invariant cell lineage, and the lineage founder cells can be considered as regulatory spatial domains. That is, from each of these cells descend clones of progeny the members of which express the same set of lineage-specific genes. ii. From the extensive classical literature on blastomere plasticity, and some key modern experiments, are derived a system of inductive blastomere interactions, which accounts for the conditionality of lineage founder cell specification. That is, the fates of many of the lineage founder cells can apparently be altered if the normal spatial interrelationships within the embryo are perturbed. iii. Recent studies have been carried out by gene transfer, and are supported by in vitro analyses of DNA-protein interactions in the regulatory regions of two genes that are expressed in a lineage- specific manner. Expression of both of these markers of cell fate specification is controlled by diffusible DNA-binding factors (i.e. within each nucleus). A molecular mechanism is proposed, based on inductive effects on gene regulatory factors, which in principle provides a specific explanation of the regulative capacities for which this embryo is famous

Subtree power analysis finds optimal species for comparative genomics

Sequence comparison across multiple organisms aids in the detection of regions under selection. However, resource limitations require a prioritization of genomes to be sequenced. This prioritization should be grounded in two considerations: the lineal scope encompassing the biological phenomena of interest, and the optimal species within that scope for detecting functional elements. We introduce a statistical framework for optimal species subset selection, based on maximizing power to detect conserved sites. In a study of vertebrate species, we show that the optimal species subset is not in general the most evolutionarily diverged subset. Our results suggest that marsupials are prime sequencing candidates.Comment: 16 pages, 3 figures, 3 table

Semi Automated Partial Credit Grading of Programming Assignments

The grading of student programs is a time consuming process. As class sizes continue to grow, especially in entry level courses, manually grading student programs has become an even more daunting challenge. Increasing the difficulty of grading is the needs of graphical and interactive programs such as those used as part of the UNH Computer Science curriculum (and various textbooks). There are existing tools that support the grading of introductory programming assignments (TAME and Web-CAT). There are also frameworks that can be used to test student code (JUnit, Tester, and TestNG). While these programs and frameworks are helpful, they have little or no no support for programs that use real data structures or that have interactive or graphical features. In addition, the automated tests in all these tools provide only “all or nothing” evaluation. This is a significant limitation in many circumstances. Moreover, there is little or no support for dynamic alteration of grading criteria, which means that refactoring of test classes after deployment is not easily done. Our goal is to create a framework that can address these weaknesses. This framework needs to: 1. Support assignments that have interactive and graphical components. 2. Handle data structures in student programs such as lists, stacks, trees, and hash tables. 3. Be able to assign partial credit automatically when the instructor can predict errors in advance. 4. Provide additional answer clustering information to help graders identify and assign consistent partial credit for incorrect output that was not predefined. Most importantly, these tools, collectively called RPM (short for Rapid Program Management), should interface effectively with our current grading support framework without requiring large amounts of rewriting or refactoring of test code

Effect of short-term probiotic Enterococcus faecium SF68 dietary supplementation in overweight and obese cats without comorbidities

Obesity in cats is associated with metabolic abnormalities and increased susceptibility to diseases such as diabetes mellitus. Studies in mouse models and human beings have shown that probiotics can reduce food intake, promote weight loss and improve metabolic profile. Studies assessing the effects of probiotics on these same parameters are absent in cats. Therefore, the aim of this study was to determine if probiotic Enterococcus faecium strain SF68 dietary supplementation reduces food intake, promotes weight loss and improves metabolic profile in overweight and obese cats without comorbidities. Twenty overweight and obese specific pathogen-free cats without comorbidities were acclimatised to a dry diet for four weeks. After exclusion of four cats for unrelated reasons, eight cats received a daily oral probiotic for eight weeks and eight control cats received no probiotic. All cats were fed ad libitum with food intake measured daily and bodyweight weekly. Blood was collected at three time points: after four weeks of acclimatisation to the diet, after eight weeks of intervention and after six weeks of washout for measurement of glucose, triglyceride, cholesterol, fructosamine, insulin, leptin, total adiponectin and deuterium oxide for body composition. There were no differences in food intake, metabolic parameters and body composition between the probiotic and control groups after eight weeks of intervention and six weeks of washout (P≥0.050). Short-term use of E faecium SF68 dietary supplementation had no significant effect on food intake, bodyweight, body composition or metabolic parameters in overweight and obese specific pathogen-free cats without comorbidities