Diversity has been the subject of study in various disciplines from biology to social science and computing. Respecting and utilising the diversity of the population is increasingly important to broadening knowledge. This paper describes a pipeline for diversity profiling of a pool of text in order to understand its coverage of an underpinning domain. The application is illustrated by using a domain ontology on presentation skills in a case study with 38 postgraduates who made comments while learning pitch presentations with the Active Video Watching system (AVW-Space). The outcome shows different patterns of coverage on the domain by the comments in each of the eight videos.

Abstract— The optimized methods for a forecasting demand have been discussed among researchers to overview the most sufficient need in a rapid expansion city. The methods developed test and compare between all interrelated issues. Many variables are involved in the calculation of energy future demand, the prediction makes aggressive result to achieved requirements. After discussing proposed research methods a suitable and accurate approach is elected to be applied for any city to satisfy the public demand. The objectives of this research are to overview all the methods of forecasting of the electrical demand using different approaches , and come out with the most optimum suitable procedure in the field of electrical network for long and short terms. The result indicates a brilliant analysis with high contribution in the electrical industry, will find its application in a global rapid expansion city. The methods show a tradeoff between cost, reliability and complexity of operations regardless of energy generated.

Structural changes affecting cardiomyocyte function may contribute to the pathophysiological

remodeling underlying cardiac function impairment. Recent reports have shown that

endogenous nitric oxide (NO) plays an important role in this process. In order to examine the role

of NO in cardiomyocyte remodeling, male rats were acclimated to room temperature (22± 1
C) or

cold (4 ± 1
C) and treated with 2.25% L-arginine
HCl or 0.01% L-NAME (Nx-nitro-L-arginine

methyl ester)
HCl for 45 days. Untreated groups served as controls. Right heart ventricles were routinely

prepared for light microscopic examination. Stereological estimations of volume densities of

cardiomyocytes, surrounding blood vessels and connective tissue, as well as the morphometric measurements

of cardiomyocyte diameters were performed. Tissue sections were also analyzed for

structural alterations. We observed that both L-arginine and L-NAME supplementation induced

cardiomyocyte hypertrophy, regardless of ambient temperature. However, cardiomyocyte hypertrophy

was associated with fibrosis and extra collagen deposition only in the L-NAME treated group.

Taken together, our results suggest that NO has a modulatory role in right heart ventricle remodeling

by coordinating hypertrophy of cardiomyocytes and fibrous tissue preventing cardiac fibrosis.

The segmentation of various retinal layers is vital for diagnosing and tracking progress of medication of various ocular diseases. Due to the complexity of retinal structures, the tediousness of manual segmentation and variation from different specialists, many methods have been proposed to aid with this analysis. However image artifacts, in addition to inhomogeneity in pathological structures, remain a challenge, with negative influence on the performance of segmentation algorithms. Previous attempts normally pre-process the images or model the segmentation to handle the obstruction but it still remains an area of active research, especially in relation to the graph based algorithms. In this paper we present an automatic retinal layer segmentation method, which is comprised of fuzzy histogram hyperbolization and graph cut methods to segment 8 boundaries and 7 layers of the retina on 150 OCT B-Sans images, 50 each from the temporal, nasal and centre of foveal region. Our method shows positive results, with additional tolerance and adaptability to contour variance and pathological inconsistency of the retinal structures in all regions.

In the medical field, the identification of skin cancer (Malignant Melanoma) in dermoscopy images is still a challenging task for radiologists and researchers. Due to its rapid increase, the need for decision support systems to assist the radiologists to detect it in early stages becomes essential and necessary. Computer Aided Diagnosis (CAD) systems have significant potential to increase the accuracy of its early detection. Typically, CAD systems use various types of features to characterize skin lesions. The features are often concatenated into one vector (early fusion) to represent the image. In this paper, we present a novel method for melanoma detection from images. First the lesions are segmented by combining Particle Swarm Optimization and Markov Random Field methods. Then the K-means is applied on the segmented lesions to separate them into homogeneous clusters, from which important features are extracted. Finally, an Artificial Neural Network with Radial Basis Function is applied for the detection of melanoma. The method was tested on 200 dermoscopy images. The experimental results show that the proposed method achieved higher accuracy in terms of melanoma detection, compared to alternative methods.

Abstract—Early detection of malignant melanoma skin cancer is crucial for treating the disease and saving lives. Many computerized techniques have been reported in the literature to diagnose and classify the disease with satisfactory skin cancer detection performance. However, reducing the false detection rate is still challenging and preoccupying because false positives trigger the alarm and require intervention by an expert pathologist for further examination and screening. In this paper, an automatic skin cancer diagno- sis system that combines different textural and color features is proposed. New textural and color features are used in a bag-of-features approach for efficient and accurate detection. We particularly claim that the Histogram of Gradients (HG) and the Histogram of Lines (HL) are more suitable for the analysis and clas- sification of dermoscopic and standard skin images than the conventional Histogram of Oriented Gradient (HOG) and the Histogram of Oriented Lines (HOL), respectively. The HG and HL are bagged separately us- ing a codebook for each and then combined with other bagged color vector angles and Zernike moments to exploit the color information. The overall system has been assessed through intensive experiments using different classifiers on a dermoscopic image dataset and another standard dataset. Experimental results have shown the superiority of the proposed system over state-of-the-art techniques.

Leishmania pyrimidine salvage is replete with opportunities for therapeutic intervention with enzyme inhibitors or antimetabolites. Their uptake into cells depends upon specific transporters; therefore it is essential to establish whether various Leishmania species possess similar pyrimidine transporters capable of drug uptake. Here, we report a comprehensive characterization of pyrimidine transport in L. major and L. mexicana. In both species, two transporters for uridine/adenosine were detected, one of which also transported uracil and the antimetabolites 5-fluoruracil (5-FU) and 5F,2'deoxyuridine (5F,2'dUrd), and was designated uridine-uracil transporter 1 (UUT1); the other transporter mediated uptake of adenosine, uridine, 5F,2'dUrd and thymidine and was designated Nucleoside Transporter 1 (NT1). To verify the reported L. donovani model of two NT1-like genes encoding uridine/adenosine transporters, and an NT2 gene encoding an inosine transporter, we cloned the corresponding L. major and L. mexicana genes, expressing each in T. brucei. Consistent with the L. donovani reports, the NT1-like genes of either species mediated the adenosine-sensitive uptake of [3H]-uridine but not of [3H]-inosine. Conversely, the NT2-like genes mediated uptake of [3H]-inosine but not [3H]-uridine. Among pyrimidine antimetabolites tested, 5-FU and 5F,2'dUrd were the most effective antileishmanials; resistance to both analogs was induced in L. major and L. mexicana. In each case it was found that the resistant cells had lost the transport capacity for the inducing drug. Metabolomics analysis found that the mechanism of action of 5-FU and 5F-2'dUrd was similar in both Leishmania species, with major changes in deoxynucleotide metabolism. We conclude that the pyrimidine salvage system is highly conserved in Leishmania species - essential information for the development of pyrimidine-based chemotherapy.