Teachers\u27 Read-Aloud Preferences: Perpetuating Sex-Role Stereotypes

Just what influence does children\u27s literature, sexist or not, have upon socialization of children

Effects of multiple-dose ponesimod, a selective SIP1 receptor modulator, on lymphocyte subsets in healthy humans

This study investigated the effects of ponesimod, a selective SIP1 receptor modulator, on T lymphocyte subsets in 16 healthy subjects. Lymphocyte subset proportions and absolute numbers were determined at baseline and on Day 10, after once-daily administration of ponesimod (10 mg, 20 mg, and 40 mg each consecutively for 3 days) or placebo (ratio 3: 1). The overall change from baseline in lymphocyte count was -1,292 +/- 340x10(6) cells/L and 275 +/- 486x10(6) cells/L in ponesimod- and placebo-treated subjects, respectively. This included a decrease in both T and B lymphocytes following ponesimod treatment. A decrease in naive CD4(+) T cells (CD45RA(+)CCR7(+)) from baseline was observed only after ponesimod treatment (-113 +/- 98x10(6) cells/L, placebo: 0 +/- 18x10(6) cells/L). The number of T-cytotoxic (CD3(+)CD8(+)) and T-helper (CD3(+)CD4(+)) cells was significantly altered following ponesimod treatment compared with placebo. Furthermore, ponesimod treatment resulted in marked decreases in CD4(+) T-central memory (CD45RA(-)CCR7(+)) cells (-437 +/- 164x10(6) cells/L) and CD4(+) T-effector memory (CD45RA(-)CCR7(-)) cells (-131 +/- 57x10(6) cells/L). In addition, ponesimod treatment led to a decrease of -228 +/- 90x10(6) cells/L of gut-homing T cells (CLA(-)integrin beta 7(+)). In contrast, when compared with placebo, CD8(+) T-effector memory and natural killer (NK) cells were not significantly reduced following multiple-dose administration of ponesimod. In summary, ponesimod treatment led to a marked reduction in overall T and B cells. Further investigations revealed that the number of CD4(+) cells was dramatically reduced, whereas CD8(+) and NK cells were less affected, allowing the body to preserve critical viral-clearing functions

Regular realizability problems and context-free languages

We investigate regular realizability (RR) problems, which are the problems of verifying whether intersection of a regular language -- the input of the problem -- and fixed language called filter is non-empty. In this paper we focus on the case of context-free filters. Algorithmic complexity of the RR problem is a very coarse measure of context-free languages complexity. This characteristic is compatible with rational dominance. We present examples of P-complete RR problems as well as examples of RR problems in the class NL. Also we discuss RR problems with context-free filters that might have intermediate complexity. Possible candidates are the languages with polynomially bounded rational indices.Comment: conference DCFS 201

The Computational Complexity of Generating Random Fractals

In this paper we examine a number of models that generate random fractals. The models are studied using the tools of computational complexity theory from the perspective of parallel computation. Diffusion limited aggregation and several widely used algorithms for equilibrating the Ising model are shown to be highly sequential; it is unlikely they can be simulated efficiently in parallel. This is in contrast to Mandelbrot percolation that can be simulated in constant parallel time. Our research helps shed light on the intrinsic complexity of these models relative to each other and to different growth processes that have been recently studied using complexity theory. In addition, the results may serve as a guide to simulation physics.Comment: 28 pages, LATEX, 8 Postscript figures available from [email protected]

The Computational Complexity of the Lorentz Lattice Gas

The Lorentz lattice gas is studied from the perspective of computational complexity theory. It is shown that using massive parallelism, particle trajectories can be simulated in a time that scales logarithmically in the length of the trajectory. This result characterizes the ``logical depth" of the Lorentz lattice gas and allows us to compare it to other models in statistical physics.Comment: 9 pages, LaTeX, to appear in J. Stat. Phy

Theoretically Efficient Parallel Graph Algorithms Can Be Fast and Scalable

There has been significant recent interest in parallel graph processing due to the need to quickly analyze the large graphs available today. Many graph codes have been designed for distributed memory or external memory. However, today even the largest publicly-available real-world graph (the Hyperlink Web graph with over 3.5 billion vertices and 128 billion edges) can fit in the memory of a single commodity multicore server. Nevertheless, most experimental work in the literature report results on much smaller graphs, and the ones for the Hyperlink graph use distributed or external memory. Therefore, it is natural to ask whether we can efficiently solve a broad class of graph problems on this graph in memory. This paper shows that theoretically-efficient parallel graph algorithms can scale to the largest publicly-available graphs using a single machine with a terabyte of RAM, processing them in minutes. We give implementations of theoretically-efficient parallel algorithms for 20 important graph problems. We also present the optimizations and techniques that we used in our implementations, which were crucial in enabling us to process these large graphs quickly. We show that the running times of our implementations outperform existing state-of-the-art implementations on the largest real-world graphs. For many of the problems that we consider, this is the first time they have been solved on graphs at this scale. We have made the implementations developed in this work publicly-available as the Graph-Based Benchmark Suite (GBBS).Comment: This is the full version of the paper appearing in the ACM Symposium on Parallelism in Algorithms and Architectures (SPAA), 201

Natural Complexity, Computational Complexity and Depth

Depth is a complexity measure for natural systems of the kind studied in statistical physics and is defined in terms of computational complexity. Depth quantifies the length of the shortest parallel computation required to construct a typical system state or history starting from simple initial conditions. The properties of depth are discussed and it is compared to other complexity measures. Depth can only be large for systems with embedded computation.Comment: 21 pages, 1 figur

Parallel Algorithm and Dynamic Exponent for Diffusion-limited Aggregation

A parallel algorithm for ``diffusion-limited aggregation'' (DLA) is described and analyzed from the perspective of computational complexity. The dynamic exponent z of the algorithm is defined with respect to the probabilistic parallel random-access machine (PRAM) model of parallel computation according to $T \sim L^{z}$, where L is the cluster size, T is the running time, and the algorithm uses a number of processors polynomial in L\@. It is argued that z=D-D_2/2, where D is the fractal dimension and D_2 is the second generalized dimension. Simulations of DLA are carried out to measure D_2 and to test scaling assumptions employed in the complexity analysis of the parallel algorithm. It is plausible that the parallel algorithm attains the minimum possible value of the dynamic exponent in which case z characterizes the intrinsic history dependence of DLA.Comment: 24 pages Revtex and 2 figures. A major improvement to the algorithm and smaller dynamic exponent in this versio

The Parallel Complexity of Growth Models

This paper investigates the parallel complexity of several non-equilibrium growth models. Invasion percolation, Eden growth, ballistic deposition and solid-on-solid growth are all seemingly highly sequential processes that yield self-similar or self-affine random clusters. Nonetheless, we present fast parallel randomized algorithms for generating these clusters. The running times of the algorithms scale as $O(\log^2 N)$, where $N$ is the system size, and the number of processors required scale as a polynomial in $N$. The algorithms are based on fast parallel procedures for finding minimum weight paths; they illuminate the close connection between growth models and self-avoiding paths in random environments. In addition to their potential practical value, our algorithms serve to classify these growth models as less complex than other growth models, such as diffusion-limited aggregation, for which fast parallel algorithms probably do not exist.Comment: 20 pages, latex, submitted to J. Stat. Phys., UNH-TR94-0

Dental attendance, restoration and extractions in adults with intellectual disabilities compared with the general population: a record linkage study

Background: Oral health may be poorer in adults with intellectual disabilities (IDs) who rely on carer support and medications with increased dental risks. Methods: Record linkage study of dental outcomes, and associations with anticholinergic (e.g. antipsychotics) and sugar‐containing liquid medication, in adults with IDs compared with age–sex–neighbourhood deprivation‐matched general population controls. Results: A total of 2933/4305 (68.1%) with IDs and 7761/12 915 (60.1%) without IDs attended dental care: odds ratio (OR) = 1.42 [1.32, 1.53]; 1359 (31.6%) with IDs versus 5233 (40.5%) without IDs had restorations: OR = 0.68 [0.63, 0.73]; and 567 (13.2%) with IDs versus 2048 (15.9%) without IDs had dental extractions: OR = 0.80 [0.73, 0.89]. Group differences for attendance were greatest in younger ages, and restoration/extractions differences were greatest in older ages. Adults with IDs were more likely prescribed with anticholinergics (2493 (57.9%) vs. 6235 (48.3%): OR = 1.49 [1.39, 1.59]) and sugar‐containing liquids (1641 (38.1%) vs. 2315 (17.9%): OR = 2.89 [2.67, 3.12]). Conclusion: Carers support dental appointments, but dentists may be less likely to restore teeth, possibly extracting multiple teeth at individual appointments instead