3-D vertical ray shooting and 2-D point enclosure, range searching, and arc shooting amidst convex fat objects

We present a new data structure for a set of n convex simply-shaped fat objects in the plane, and use it to obtain efficient and rather simple solutions to several problems including (i) vertical ray shooting—preprocess a set of n non-intersecting convex simply-shaped flat objects in 3-space, whose xy-projections are fat, for efficient vertical ray shooting queries, (ii) point enclosure—preprocess a set C of n convex simply-shaped fat objects in the plane, so that the k objects containing a query point p can be reported efficiently, (iii) bounded-size range searching— preprocess a set C of n convex fat polygons, so that the k objects intersecting a “not-too-large” query polygon can be reported efficiently, and (iv) bounded-size segment shooting—preprocess a set C as in (iii), so that the first object (if exists) hit by a “not-too-long” oriented query segment can be found efficiently. For the first three problems we construct data structures of size O(λ_s(n)log³n), where s is the maximum number of intersections between the boundaries of the (xy-projections) of any pair of objects, and λ_s(n) is the maximum length of (n, s) Davenport-Schinzel sequences. The data structure for the fourth problem is of size O(λ_s(n)log²n). The query time in the first problem is O(log⁴n), the query time in the second and third problems is O(log³n + klog²n), and the query time in the fourth problem is O(log³n).

We also present a simple algorithm for computing a depth order for a set as in (i), that is based on the solution to the vertical ray shooting problem. (A depth order for , if exists, is a linear order of , such that, if K₁, K₂ and K₁ lies vertically above K₂, then K₁ precedes K₂.) Unlike the algorithm of Agarwal et al. (1995) that might output a false order when a depth order does not exist, the new algorithm is able to determine whether such an order exists, and it is often more efficient in practical situations than the former algorithm.     

Mod 2 cohomology of combinatorial Grassmannians

Matroid bundles, introduced by MacPherson, are combinatorial analogues of real vector bundles. This paper sets up the foundations of matroid bundles. It defines a natural transformation from isomorphism classes of real vector bundles to isomorphism classes of matroid bundles. It then gives a transformation from matroid bundles to spherical quasifibrations, by showing that the geometric realization of a matroid bundle is a spherical quasifibration. The poset of oriented matroids of a fixed rank classifies matroid bundles, and the above transformations give a splitting from topology to combinatorics back to topology. A consequence is that the mod 2 cohomology of the poset of rank k oriented matroids (this poset classifies matroid bundles) contains the free polynomial ring on the first k Stiefel-Whitney classes.     

Dendrimers as scaffolds for multifunctional reversible addition–fragmentation chain transfer agents: Syntheses and polymerization

The synthesis and characterization of novel first‐ and second‐generation true dendritic reversible addition–fragmentation chain transfer (RAFT) agents carrying 6 or 12 pendant 3‐benzylsulfanylthiocarbonylsulfanylpropionic acid RAFT end groups with Z‐group architecture based on 1,1,1‐hydroxyphenyl ethane and trimethylolpropane cores are described in detail. The multifunctional dendritic RAFT agents have been used to prepare star polymers of poly(butyl acrylate) (PBA) and polystyrene (PS) of narrow polydispersities (1.4 < polydispersity index < 1.1 for PBA and 1.5 < polydispersity index < 1.3 for PS) via bulk free‐radical polymerization at 60 °C. The novel dendrimer‐based multifunctional RAFT agents effect an efficient living polymerization process, as evidenced by the linear evolution of the number‐average molecular weight (M_n) with the monomer–polymer conversion, yielding star polymers with molecular weights of up to M_n = 160,000 g mol^?1 for PBA (based on a linear PBA calibration) and up to M_n = 70,000 g mol^?1 for PS (based on a linear PS calibration). A structural change in the chemical nature of the dendritic core (i.e., 1,1,1‐hydroxyphenyl ethane vs trimethylolpropane) has no influence on the observed molecular weight distributions. The star‐shaped structure of the generated polymers has been confirmed through the cleavage of the pendant arms off the core of the star‐shaped polymeric materials. © 2004 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 42: 5877–5890, 2004     

Cognitive Demands and Second-Language Learners: A Framework for Analyzing Mathematics Instructional Contexts

The issues involved in teaching English language learners mathematics while they are learning English pose many challenges for mathematics teachers and highlight the need to focus on language-processing issues related to teaching mathematical content. Two realistic-type problems from high-stakes tests are used to illustrate the complex interactions between culture, language, and mathematical learning. The analyses focus on aspects of the problems that potentially increase cognitive demands for second-language learners. An analytical framework is presented that is designed to enable mathematics teachers to identify critical elements in problems and the learning environment that contribute to increased cognitive demands for students of English as a second language. The framework is proposed as a cycle of teacher reflection that would extend a constructivist model of teaching to include broader linguistic, cultural, and cognitive processing issues of mathematics teaching, as well as enable teachers to develop more accurate mental models of student learning.