The rise and fall of word retrieval across the lifespan.

Picture-naming performance for 48 black-and-white drawings was investigated in 1,145 Hebrew speakers, ages 5–86. Both a linear and a curvilinear quadratic model fit the data, reflecting an increase in ability with age as well as an increase followed by a decrease beyond that linear rise. Late-life performance was more affected by access difficulty than was early-life performance, with children's responses limited by lexicon size. Immigrants performed more poorly than nonimmigrants, but an identical correlation between participant age and naming scores was found in both groups. We discuss the role of vocabulary funds and controlled access in naming pictures throughout life. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Microstructural pattern of palatable food intake from weaning to adulthood in male and female OLETF rats.

Ontogenetic trajectories from weaning to adulthood and sex differences in feeding patterns were examined in the Otsuka Long-Evans Tokushima Fatty (OLETF) rat, an animal model of early onset overeating-induced obesity, and a natural cholecystokinin-1 receptor knockout. Overnight patterns of licking a palatable liquid diet (Ensure) were analyzed on Postnatal Days 22, 38, 60, and 90. Because different microstructure profiles may reflect alterations in the influence of positive and negative signals, we examined meal parameters to uncover developing mechanisms underlying eating behavior in this strain. OLETF rats displayed significantly greater caloric intake, larger meals (in number of licks), and more (within-meal) clusters of feeding (which were shorter in duration and contained fewer licks per cluster) than did Long-Evans Tokushima Ohtsuka (LETO) strain controls. OLETF rats also had significantly lower satiety ratios than LETO rats. Moreover, we identified sex differences in the age of emergence of microstructural patterns of obesity-related overeating, suggesting that systems other than cholecystokinin may be disrupted, possibly worsening the OLETF strain’s obesity phenotype. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Cryogenic scanning tunneling spectroscopy studies of inhomogeneous superconductors

We applied scanning tunneling microscopy and spectroscopy, combined with magnetic susceptibility measurements and Mossbauer spectroscopy, in studies of three superconducting materials. Two belong to a new class of high T_c magnetic-superconductor systems, R_1.4Ce_0.6RuSr₂Cu₂O_10-δ (R=Eu and Gd), which are magnetically ordered at T_N≪T_c. The third is a granular normal-superconductor system, where the superconducting phase is YNi₂B₂C. In this paper we focus on the tunneling measurements, which exhibit large spatial variations of the local electronic properties for all three materials. Albeit, these local measurements also reveal pronounced differences between the third and the first two systems, which will be discussed in view of their macroscopic properties.     

The approximate swap and mismatch edit distance

There is no known algorithm that solves the general case of the approximate edit distance problem, where the edit operations are insertion, deletion, mismatch, and swap, in time o(nm), where n is the length of the text and m is the length of the pattern.In the effort to study this problem, the edit operations have been analyzed independently. Karloff [10] showed an algorithm that approximates the edit distance problem with only the mismatch operation in time . Amir et al. [4] showed that if the only edit operations allowed are swap and mismatch, then the exact edit distance problem can be solved in time .In this paper, we discuss the problem of approximate edit distance with swap and mismatch. We show a randomized time algorithm for the problem. The algorithm guarantees an approximation factor of (1+?) with probability of at least .     

Class Constrained Bin Covering

We study the following variant of the bin covering problem. We are given a set of unit sized items, where each item has a color associated with it. We are given an integer parameter k≥1 and an integer bin size B≥k. The goal is to assign the items (or a subset of the items) into a maximum number of subsets of at least B items each, such that in each such subset the total number of distinct colors of items is at least k. We study both the offline and the online variants of this problem. We first design an optimal polynomial time algorithm for the offline problem. For the online problem we give a lower bound of 1+H _k−1 (where H _k−1 denotes the (k−1)-th harmonic number), and an O(k)-competitive algorithm. Finally, we analyze the performance of the natural heuristic First fit.     

Visible light-induced charge retention and photocatalysis with hybrid CdSe-Au nanodumbbells

Visible light photocatalysis is a promising route for harnessing of solar energy to perform useful chemical reactions and to convert light to chemical energy. Nanoscale photocatalytic systems used to date were based mostly on oxide semiconductors aided by metal deposition and were operational only under UV illumination. Additionally, the degree of control over particle size and shape was limited. We report visible light photocatalysis using highly controlled hybrid gold-tipped CdSe nanorods (nanodumbbells). Under visible light irradiation, charge separation takes place between the semiconductor and metal parts of the hybrid particles. The charge-separated state was then utilized for direct photoreduction of a model acceptor molecule, methylene blue, or alternatively, retained for later use to perform the reduction reaction in the dark.     

An expert diagnosis system for classification of human parasite eggs based on multi-class SVM

In this paper, it is proposed a new methodology based on invariant moments and multi-class support vector machine (MCSVM) for classification of human parasite eggs in microscopic images. The MCSVM is one of the most used classifiers but it has not used for classification of human parasite eggs to date. This method composes four stages. These are pre-processing stage, feature extraction stage, classification stage, and testing stage. In pre-processing stage, the digital image processing methods, which are noise reduction, contrast enhancement, thresholding, and morphological and logical processes. In feature extraction stage, the invariant moments of pre-processed parasite images are calculated. Finally, in classification stage, the multi-class support vector machine (MCSVM) classifier is used for classification of features extracted feature extraction stage. We used MATLAB software for estimating the success classification rate of proposed approach in this study. For this aim, proposed approach was tested by using test data. At end of test, 97.70% overall success rates were obtained.