Segmentation and classification of biological cell images by a multifractal approach

Recently, the clinical role of image processing has been developed considerably. The resources of this new technology were exploited for the needs of doctors in their practice. In this study, we propose a computer vision for tracking the uterine collar cancer. Here, we present three stages: preprocessing, segmentation, and classification. The segmentation stage uses a multifractal algorithm based on the computation of the singularity exponents; its role is separating each cell on its core and its cytoplasm, which permits the analysis of each one in the recognition stage for deducing a response about the malignity of the cell. However, the classification is performed by an algorithm of area growth. Knowing that there are four layers in the epithelium, the classification allows for learning the type of each cell in an image for organizing the research in the recognition stage. Thus, we contribute to the creation of a database for the recognition stage. This base contains the core and cytoplasm images with information about the type of each cell. Promising results were obtained with a short execution time that permits the start of the recognition stage. © 2003 Wiley Periodicals, Inc.     

Prolegomena to a Cognitive Investigation of Euclidean Diagrammatic Reasoning

Euclidean diagrammatic reasoning refers to the diagrammatic inferential practice that originated in the geometrical proofs of Euclid’s Elements. A seminal philosophical analysis of this practice by Manders (‘The Euclidean diagram’, 2008) has revealed that a systematic method of reasoning underlies the use of diagrams in Euclid’s proofs, leading in turn to a logical analysis aiming to capture this method formally via proof systems. The central premise of this paper is that our understanding of Euclidean diagrammatic reasoning can be fruitfully advanced by confronting these logical and philosophical analyses with the field of cognitive science. Surprisingly, central aspects of the philosophical and logical analyses resonate in very natural ways with research topics in mathematical cognition, spatial cognition and the psychology of reasoning. The paper develops these connections, concentrating on four issues: (1) the cognitive origins of Euclidean diagrammatic reasoning, (2) the cognitive representations of spatial relations in Euclidean diagrams, (3) the nature of the cognitive processes and cognitive representations involved in Euclidean diagrammatic reasoning seen as a form of visuospatial relational reasoning and (4) the complexity of Euclidean diagrammatic reasoning for the human cognitive system. For each of these issues, our analysis generates concrete experiment proposals, opening thereby the way for further empirical investigations. The paper is thus a prolegomenon to a research program on Euclidean diagrammatic reasoning at the crossroads of logic, philosophy and cognitive science.     

A survey of neural network based automated systems for human chromosome classification

Chromosome classification and karyotype establishment are important procedures for genetic diseases diagnosis. Various computer-aided systems have been developed to automate this tedious and time consuming task, which is performed manually in most cytogenetic laboratories. This paper provides a comprehensive review of past and recent research in the area of automatic chromosome classification systems. We start by reviewing methods for feature extraction, followed by a neural network based chromosome classifiers survey. We sum-up various techniques and methods in this area of research and discuss important issues and outcomes within each study for both chromosome feature extraction and classification. Although the ANN based chromosome classifiers are the main topic of this survey, a number of classifiers based on other algorithms are exposed to give an overall idea about additional techniques employed in chromosome classification.     

Self-referencing enhances memory specificity with age.

Self-referencing has been identified as an advantageous mnemonic strategy for young and older adults. However, little research has investigated the ways in which self-referencing may influence older adults' memory for details, which is typically impaired with age, beyond memory for the item itself. Experiment 1 assessed the effects of self- and other-referencing on memory for visually detailed pictures of objects in thirty-two young and thirty-two older adults. Results indicate that self- and close other-referencing similarly enhance general (item) and specific (detail) recognition for both young and older adults relative to the distant other condition. Experiment 2 extended these findings to source memory, with young and older adults encoding verbal information in self-referent, semantic, and structural conditions. Findings suggest that self-referencing provides an age-equivalent boost in general memory and specific memory for specific source details. We conclude that the mnemonic benefits of referencing the self extend to specific memory for visual and verbal information across the lifespan. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Biosynthesis of copper oxide nanoparticles using biomass,peel, and extract polysaccharides of Solanum Tuberosum for ultrasound‐assisted adsorption of azo direct red 80 contaminants

Bio-fabrication of nanomaterials using plant polysaccharides has recently attracted much scientific attention due to its low cost and simple operation. The green synthesis of copper oxide nanoparticles as adsorbent is performed for the removal of azo direct red 80 contaminants from aqueous solution with adsorption and ultrasonic-assisted adsorption processes. The biomass, peel, and extract polysaccharides of Solanum Tuberosum were applied as eco-friendly stabilizing agents to synthesize nanoparticles. The CuO nanoparticles were characterized using FESEM, XRD, BET, and antibacterial activity tests. The CuO nanoparticles biosynthesized from peel extract have better structural properties as compared to the nanoparticles prepared from biomass and extract of Solanum Tuberosum. The result showed that the average crystallite size of the CuO nanoparticles was about 25 nm with a specific surface area of 16.35 m²/g. The adsorption capacities of 13.09 and 14.07 mg/g were obtained for dye removal with the adsorption and ultrasonic-assisted adsorption processes. Adsorption process followed the pseudo-second-order kinetic model and the contribution of intra-particle diffusion was also observed. The adsorption potential of the nanoparticles in adsorption and ultrasonic-assisted adsorption processes was assessed for binary dye solution with synergetic effect. The CuO nanoparticle has shown its high regeneration ability even after 4 consecutive cycles of regeneration-reuse.     

Influence of mix proportions on microstructure and gas permeability of cement pastes and mortars

This paper presents a study on the influence of mix proportions of cementitious materials on their transfer properties, namely porosity and gas permeability. These latter are known as durability indicators. The work is performed on a wide range of cement pastes and mortars (24 compositions). These compositions are defined by mix proportion parameters (water/cement ratio, limestone filler/cement ratio, and amount of superplasticizer and volume fraction of paste). To characterize these materials, an experimental campaign was carried out, including different types of test (water porosimetry, mercury intrusion porosimetry, desorption isotherms and gas permeability). The influence of the composition parameters on the studied durability indicators is highlighted and correlation between gas permeability and microstructural properties (total porosity and critical pore diameter) is established. Finally, a method to predict materials permeability from that of the cement paste is proposed.     

Heavy metals in drilling‐waste leachates from East Java,Indonesia

This study examined the leaching toxicity characteristics of heavy metals in drilling‐waste mud by the toxicity characteristic leaching procedure (TCLP). Ten heavy metal elements As, Ba, Cd, Cr, Cu, Pb, Se, Ag, Zn and Hg were investigated. Test drilling‐waste mud samples were collected from eight active exploration wells. The TCLP results showed that the concentrations of the metals were below the Indonesian Regulatory Standards Nos. 18 and 85 (1999) regarding hazardous waste management. Barium was detected in all the leachates, and ranged from 0.40 to 6.59 mg/l. Mercury was below detectable levels at only two stations. Values of the other metals varied significantly from one station to another.