Biochemical alterations of the tunica albuginea in impotence

PURPOSE: The objectives of this study were to quantify the immunohistochemical stainings of collagen types I, III and IV, and investigate the value of glycohistochemical staining with 3 lectin types specific to a particular glycan structure, Arachis hypogaea, Triticum vulgare and concanavalin A, as a method of defining possible changes in the collagen structure of the tunica albuginea in potent and impotent patients. MATERIALS AND METHODS: The study involved 4 normal men, 4 with pure venous leakage and 4 with pure arterial disease. Collagen types I, III and IV, and lectins Arachis hypogaea, Triticum vulgare and concanavalin A were studied using a cell image processor. The labeling index relates to the percentage of staining and mean optical density relates to the staining intensity. RESULTS: Mean labeling index values for the 3 types of collagen and lectins were similar (p > 0.05). Mean optical density value relating to collagen type I was significantly higher in the arteriogenic group than in the other groups (p < 0.05), while mean optical density value of collagen type IV was significantly higher in the venogenic group than in the 2 other groups (p < 0.05). Mean optical density values relating to the 3 lectin types were similar in the 3 clinical groups (p > 0.05). CONCLUSIONS: An alteration in the distribution and structure of the various collagen types and lectins in the tunica albuginea of impotent patients has been shown that may interfere with normal function and lead to impotence.     

Equi-affine Invariant Geometry for Shape Analysis

Traditional models of bendable surfaces are based on the exact or approximate invariance to deformations that do not tear or stretch the shape, leaving intact an intrinsic geometry associated with it. These geometries are typically defined using either the shortest path length (geodesic distance), or properties of heat diffusion (diffusion distance) on the surface. Both measures are implicitly derived from the metric induced by the ambient Euclidean space. In this paper, we depart from this restrictive assumption by observing that a different choice of the metric results in a richer set of geometric invariants. We apply equi-affine geometry for analyzing arbitrary shapes with positive Gaussian curvature. The potential of the proposed framework is explored in a range of applications such as shape matching and retrieval, symmetry detection, and computation of Voroni tessellation. We show that in some shape analysis tasks, equi-affine-invariant intrinsic geometries often outperform their Euclidean-based counterparts. We further explore the potential of this metric in facial anthropometry of newborns. We show that intrinsic properties of this homogeneous group are better captured using the equi-affine metric.     

Path Hitting in Acyclic Graphs

An instance of the path hitting problem consists of two families of paths, and ℋ, in a common undirected graph, where each path in ℋ is associated with a non-negative cost. We refer to and ℋ as the sets of demand and hitting paths, respectively. When p∈ℋ and share at least one mutual edge, we say that p hits q. The objective is to find a minimum cost subset of ℋ whose members collectively hit those of . In this paper we provide constant factor approximation algorithms for path hitting, confined to instances in which the underlying graph is a tree, a spider, or a star. Although such restricted settings may appear to be very simple, we demonstrate that they still capture some of the most basic covering problems in graphs. Our approach combines several novel ideas: We extend the algorithm of Garg, Vazirani and Yannakakis (Algorithmica, 18:3–20, 1997) for approximate multicuts and multicommodity flows in trees to prove new integrality properties; we present a reduction that involves multiple calls to this extended algorithm; and we introduce a polynomial-time solvable variant of the edge cover problem, which may be of independent interest. An extended abstract of this paper appeared in Proceedings of the 14th Annual European Symposium on Algorithms, 2006. This work is part of D. Segev’s Ph.D. thesis prepared at Tel-Aviv University under the supervision of Prof. Refael Hassin.     

B2B Procurement and Marketplace Transformation

Emerging web technologies and systems have started a revolutionary path that will have a profound impact on procurement processes and systems, especially in the area of indirect procurement and the management of operating resources. In fact, what started as more narrowly focused procurement systems only a couple of years ago, has transformed into a web of technologies, markets, and business strategies that have ramifications well beyond the purchasing function. The focus of this paper is on the marketplace structure, functionality and capabilities of systems, and key factors that buyers need to take into consideration when transforming their procurement processes. Contents management, markets, standards, and outsourcing are important problems that are discussed in this paper.     

A simple velocity-free controller for attitude regulation of a spacecraft with delayed feedback

In this note, we consider the application of a velocity-free controller for attitude regulation of a rigid spacecraft with gas jet actuators when the effects of time-delays in the feedback loop are taken into consideration. Simple sufficient conditions for exponential stability are presented. Some structural properties of the resulting closed-loop system are studied, and relevant design tools are demonstrated.     

LRA: Local Rigid Averaging of Stretchable Non-rigid Shapes

We present a novel algorithm for generating the mean structure of non-rigid stretchable shapes. Following an alignment process, which supports local affine deformations, we translate the search of the mean shape into a diagonalization problem where the structure is hidden within the kernel of a matrix. This is the first step required in many practical applications, where one needs to model bendable and stretchable shapes from multiple observations.     

Spider Silk-CBD-Cellulose Nanocrystal Composites: Mechanism of Assembly

The fabrication of cellulose-spider silk bio-nanocomposites comprised of cellulose nanocrystals (CNCs) and recombinant spider silk protein fused to a cellulose binding domain (CBD) is described. Silk-CBD successfully binds cellulose, and unlike recombinant silk alone, silk-CBD self-assembles into microfibrils even in the absence of CNCs. Silk-CBD-CNC composite sponges and films show changes in internal structure and CNC alignment related to the addition of silk-CBD. The silk-CBD sponges exhibit improved thermal and structural characteristics in comparison to control recombinant spider silk sponges. The glass transition temperature (Tg) of the silk-CBD sponge was higher than the control silk sponge and similar to native dragline spider silk fibers. Gel filtration analysis, dynamic light scattering (DLS), small angle X-ray scattering (SAXS) and cryo-transmission electron microscopy (TEM) indicated that silk-CBD, but not the recombinant silk control, formed a nematic liquid crystalline phase similar to that observed in native spider silk during the silk spinning process. Silk-CBD microfibrils spontaneously formed in solution upon ultrasonication. We suggest a model for silk-CBD assembly that implicates CBD in the central role of driving the dimerization of spider silk monomers, a process essential to the molecular assembly of spider-silk nanofibers and silk-CNC composites.     

An efficient algorithm for maximizing the expected profit from a serial production line with inspection stations and rework

In this paper, an unreliable serial production line in which nonconforming items are sent back for rework is studied. The line consists of existing machines and optional quality control stations (QCSs). The designer of such a production line needs to decide where to install the QCSs along the line and to determine the production rate, so as to maximize the expected operational profit rate obtained at a steady state. An efficient algorithm for solving this problem is presented; several extensions of the problem are discussed. An extensive simulation study proves the applicability of the model in realistic settings and is used to derive some insights about the nature of optimal solutions.     

Localization of function via lesion analysis

This article presents a general approach for employing lesion analysis to address the fundamental challenge of localizing functions in a neural system. We describe functional contribution analysis (FCA), which assigns contribution values to the elements of the network such that the ability to predict the network's performance in response to multilesions is maximized. The approach is thoroughly examined on neurocontroller networks of evolved autonomous agents. The FCA portrays a stable set of neuronal contributions and accurate multilesion predictions that are significantly better than those obtained based on the classical single lesion approach. It is also used for a detailed synaptic analysis of the neurocontroller connectivity network, delineating its main functional backbone. The FCA provides a quantitative way of measuring how the network functions are localized and distributed among its elements. Our results question the adequacy of the classical single lesion analysis traditionally used in neuroscience and show that using lesioning experiments to decipher even simple neuronal systems requires a more rigorous multilesion analysis.