Lehigh University

About: Lehigh University is a education organization based out in Bethlehem, Pennsylvania, United States. It is known for research contribution in the topics: Catalysis & Fracture mechanics. The organization has 12684 authors who have published 26550 publications receiving 770061 citations.

Improving Comprehension of Expository Text in Students With LD A Research Synthesis

Abstract: This article summarizes the findings of research studies designed to improve the comprehension of expository text for students with learning disabilities. Twenty-nine studies were located that met the inclusion criteria. Interventions gleaned from the review were categorized as content enhancement (i.e., advance and graphic organizers, visual displays, mnemonic illustrations, and computer-assisted instruction) or cognitive strategy instruction (i.e., text structure, main idea identification, summarization, questioning, cognitive mapping, reciprocal teaching). Treatment outcomes are discussed in relation to the various instructional approaches, student characteristics (e.g., grade, IQ), instructional features (e.g., materials, treatment length), methodological features, strategy maintenance, and generalization components. Implications for classroom practice and future research directions are provided.

Venture Capital Reputation, Post-IPO Performance, and Corporate Governance

Abstract: We examine the association of a venture capital (VC) firm’s reputation with the post-initial public offering (IPO) long-run performance of its portfolio firms. We find that VC reputation, measured by the past market share of VC-backed IPOs, has significant positive associations with long-run firm performance measures. While more reputable VCs initially select better-quality firms, more reputable VCs continue to be associated with superior long-run performance, even after controlling for VC selectivity. We find that more reputable VCs exhibit more active post-IPO involvement in the corporate governance of their portfolio firms, and this continued VC involvement positively influences post-IPO firm performance.

Crack problems in fgm layers under thermal stresses

Abstract: In this study an unconstrained elastic layer under statically self-equilibrating thermal or residual stresses is considered. The layer is assumed to be a functionally graded material (FGM), meaning that its thermo-mechanical properties are assumed to be continuous functions of the thickness coordinate. The layer contains an embedded or a surface crack perpendicular to its boundaries. Using superposition the problem is reduced to a perturbation problem in which the crack surface tractions are the only external forces. The dimensions, geometry, and loading conditions of the original problem are such that the perturbation problem may be approximated by a plane strain mode I crack problem for an infinite layer. After a general discussion of the thermal stress problem, the crack problem in the nonhomogeneous medium is formulated. With the application to graded coatings and interfacial zones in mind, the thickness variation of the thermo-mechanical properties is assumed to be monotonous. Thus, the functions suc...

A Multi-resolution Gaussian process model for the analysis of large spatial data sets

Abstract: We develop a multiresolution model to predict two-dimensional spatial fields based on irregularly spaced observations. The radial basis functions at each level of resolution are constructed using a Wendland compactly supported correlation function with the nodes arranged on a rectangular grid. The grid at each finer level increases by a factor of two and the basis functions are scaled to have a constant overlap. The coefficients associated with the basis functions at each level of resolution are distributed according to a Gaussian Markov random field (GMRF) and take advantage of the fact that the basis is organized as a lattice. Several numerical examples and analytical results establish that this scheme gives a good approximation to standard covariance functions such as the Matern and also has flexibility to fit more complicated shapes. The other important feature of this model is that it can be applied to statistical inference for large spatial datasets because key matrices in the computations are spars...