Constraint Propagation in Presence of Arrays

We describe the use of array expressions as constraints, which represents a consequent generalisation of the "element" constraint. Constraint propagation for array constraints is studied theoretically, and for a set of domain reduction rules the local consistency they enforce, arc-consistency, is proved. An efficient algorithm is described that encapsulates the rule set and so inherits the capability to enforce arc-consistency from the rules.Comment: 10 pages. Accepted at the 6th Annual Workshop of the ERCIM Working Group on Constraints, 200

Towards More Precise Photometric Redshifts: Calibration Via CCD Photometry

We present the initial results from a deep, multi-band photometric survey of selected high Galactic latitude redshift fields. Previous work using the photographic data of Koo and Kron demonstrated that the distribution of galaxies in the multi-dimensional flux space U B R I is nearly planar. The position of a galaxy within this plane is determined by its redshift, luminosity and spectral type. Using recently acquired deep CCD photometry in existing, published redshift fields, we have redetermined the distribution of galaxies in this four-dimensional magnitude space. Furthermore, from our CCD photometry and the published redshifts, we have quantified the photometric-redshift relation within the standard AB magnitude system. This empirical relation has a measured dispersion of approximately 0.02 for z < 0.4. With this work we are reaching the asymptotic intrinsic dispersions that were predicted from simulated distributions of galaxy colors.Comment: submitted to the Astrophysical Journal Letter

The Computational Complexity of the Game of Set and its Theoretical Applications

The game of SET is a popular card game in which the objective is to form Sets using cards from a special deck. In this paper we study single- and multi-round variations of this game from the computational complexity point of view and establish interesting connections with other classical computational problems. Specifically, we first show that a natural generalization of the problem of finding a single Set, parameterized by the size of the sought Set is W-hard; our reduction applies also to a natural parameterization of Perfect Multi-Dimensional Matching, a result which may be of independent interest. Second, we observe that a version of the game where one seeks to find the largest possible number of disjoint Sets from a given set of cards is a special case of 3-Set Packing; we establish that this restriction remains NP-complete. Similarly, the version where one seeks to find the smallest number of disjoint Sets that overlap all possible Sets is shown to be NP-complete, through a close connection to the Independent Edge Dominating Set problem. Finally, we study a 2-player version of the game, for which we show a close connection to Arc Kayles, as well as fixed-parameter tractability when parameterized by the number of rounds played

A Multi-Scan Labeled Random Finite Set Model for Multi-object State Estimation

State space models in which the system state is a finite set--called the multi-object state--have generated considerable interest in recent years. Smoothing for state space models provides better estimation performance than filtering by using the full posterior rather than the filtering density. In multi-object state estimation, the Bayes multi-object filtering recursion admits an analytic solution known as the Generalized Labeled Multi-Bernoulli (GLMB) filter. In this work, we extend the analytic GLMB recursion to propagate the multi-object posterior. We also propose an implementation of this so-called multi-scan GLMB posterior recursion using a similar approach to the GLMB filter implementation

Jointly Optimal Channel and Power Assignment for Dual-Hop Multi-channel Multi-user Relaying

We consider the problem of jointly optimizing channel pairing, channel-user assignment, and power allocation, to maximize the weighted sum-rate, in a single-relay cooperative system with multiple channels and multiple users. Common relaying strategies are considered, and transmission power constraints are imposed on both individual transmitters and the aggregate over all transmitters. The joint optimization problem naturally leads to a mixed-integer program. Despite the general expectation that such problems are intractable, we construct an efficient algorithm to find an optimal solution, which incurs computational complexity that is polynomial in the number of channels and the number of users. We further demonstrate through numerical experiments that the jointly optimal solution can significantly improve system performance over its suboptimal alternatives.Comment: This is the full version of a paper to appear in the IEEE Journal on Selected Areas in Communications, Special Issue on Cooperative Networking - Challenges and Applications (Part II), October 201

Authentic, Dialogic Writing: The Case of a Letter to the Editor

This is the publisher's version, also found at http://search.proquest.com/docview/237320909?accountid=14556A teacher educator reflects on the educational value of an authentic writing assignment inspired by real-world local events

Structural correlates of semantic and phonemic fluency ability in first and second languages

Category and letter fluency tasks are commonly used clinically to investigate the semantic and phonological processes central to speech production, but the neural correlates of these processes are difficult to establish with functional neuroimaging because of the relatively unconstrained nature of the tasks. This study investigated whether differential performance on semantic (category) and phonemic (letter) fluency in neurologically normal participants was reflected in regional gray matter density. The participants were 59 highly proficient speakers of 2 languages. Our findings corroborate the importance of the left inferior temporal cortex in semantic relative to phonemic fluency and show this effect to be the same in a first language (L1) and second language (L2). Additionally, we show that the pre-supplementary motor area (pre-SMA) and head of caudate bilaterally are associated with phonemic more than semantic fluency, and this effect is stronger for L2 than L1 in the caudate nuclei. To further validate these structural results, we reanalyzed previously reported functional data and found that pre-SMA and left caudate activation was higher for phonemic than semantic fluency. On the basis of our findings, we also predict that lesions to the pre-SMA and caudate nuclei may have a greater impact on phonemic than semantic fluency, particularly in L2 speakers

To Adjust or Not to Adjust? Sensitivity Analysis of M-Bias and Butterfly-Bias

"M-Bias," as it is called in the epidemiologic literature, is the bias introduced by conditioning on a pretreatment covariate due to a particular "M-Structure" between two latent factors, an observed treatment, an outcome, and a "collider." This potential source of bias, which can occur even when the treatment and the outcome are not confounded, has been a source of considerable controversy. We here present formulae for identifying under which circumstances biases are inflated or reduced. In particular, we show that the magnitude of M-Bias in linear structural equation models tends to be relatively small compared to confounding bias, suggesting that it is generally not a serious concern in many applied settings. These theoretical results are consistent with recent empirical findings from simulation studies. We also generalize the M-Bias setting (1) to allow for the correlation between the latent factors to be nonzero, and (2) to allow for the collider to be a confounder between the treatment and the outcome. These results demonstrate that mild deviations from the M-Structure tend to increase confounding bias more rapidly than M-Bias, suggesting that choosing to condition on any given covariate is generally the superior choice. As an application, we re-examine a controversial example between Professors Donald Rubin and Judea Pearl.Comment: Journal of Causal Inference 201

An Introduction to Programming for Bioscientists: A Python-based Primer

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in the biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a 'variable', the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.Comment: 65 pages total, including 45 pages text, 3 figures, 4 tables, numerous exercises, and 19 pages of Supporting Information; currently in press at PLOS Computational Biolog