Multiple purpose river development; studies in applied economic analysis

Mode of access: Internet.

Beauty illustrated by an analysis and classification of beauty in woman : with a critical view of the hypotheses of Hume, Hogarth, Burke, Knight, Alison, etc., and the hypotheses of beauty in sculpture and painting, by Leonardo da Vinci, Winckelmann, Mengs, Bossi, etc. /

The plates include one frontispiece, 22 plates numbered I-XXII and one addtional plate numbered XVIb.

Optimization and Machine Learning Frameworks for Complex Network Analysis

Thesis (Ph.D.)--University of Washington, 2016-06

Comparability of perceptual analysis of speech characteristics in Australian and Swedish speakers with multiple sclerosis

The aims of the present study were to compare the perceptual assessments of deviant speech signs (dysarthria) exhibited by Australian and Swedish speakers with multiple sclerosis (MS) and to explore whether judgements of dysarthria differed depending on whether the speakers and the judges spoke the same or different languages. Ten Australian and 10 Swedish individuals with MS (matched as closely as possible for age, gender, progression type and severity of dysarthria) were assessed by 2 Australian and 2 Swedish clinically experienced judges using a protocol including 33 speech parameters. Results show that the following perceptual dimensions were identified by both pairs of judges in both groups of speakers to a just noticeable or moderate degree: imprecise consonants, inappropriate pitch level, reduced general rate, and glottal fry. The reliability (Spearman rank-order correlation) of the consensus ratings from the Australian and the Swedish judges was high, with a mean rho of 85.7 for the Australian speakers and mean rho of 84.3 for the Swedish speakers. The most difficult perceptual parameters to assess (i.e. to agree on) included harshness, level of pitch and loudness, precision of consonants and general stress pattern. The study indicated that perceptual assessments of speech characteristics in individuals with MS are informative and can be achieved with high inter-judge reliability irrespective of the judge's knowledge of the speaker's language. Copyright (C) 2003 S. Karger AG, Basel.

Classification and analysis of integrating frameworks in multiscale modelling

Chemical engineers are turning to multiscale modelling to extend traditional modelling approaches into new application areas and to achieve higher levels of detail and accuracy. There is, however, little advice available on the best strategy to use in constructing a multiscale model. This paper presents a starting point for the systematic analysis of multiscale models by defining several integrating frameworks for linking models at different scales. It briefly explores how the nature of the information flow between the models at the different scales is influenced by the choice of framework, and presents some restrictions on model-framework compatibility. The concepts are illustrated with reference to the modelling of a catalytic packed bed reactor. (C) 2004 Elsevier Ltd. All rights reserved.

Columnar cell lesions of the breast: The missing link in breast cancer progression? A morphological and molecular analysis

Columnar cell lesions (CCLs) of the breast are a spectrum of lesions that have posed difficulties to pathologists for many years, prompting discussion concerning their biologic and clinical significance. We present a study of CCL in context with hyperplasia of usual type (HUT) and the more advanced lesions ductal carcinoma in situ (DCIS) and invasive ductal carcinoma. A total of 81 lesions from 18 patients were subjected to a comprehensive morphologic review based upon a modified version of Schnitt's classification system for CCL, immunophenotypic analysis (estrogen receptor [ER], progesterone receptor [PgR], Her2/neu, cytokeratin 5/6 [CK5/6], cytokeratin 14 [CK14], E-cadherin, p53) and for the first time, a whole genome molecular analysis by comparative genomic hybridization. Multiple CCLs from 3 patients were studied in particular detail, with topographic information and/or showing a morphologic spectrum of CCL within individual terminal duct lobular units. CCLs were ER an PgR positive, CK5/6 and CK14 negative, exhibit low numbers of genetic alterations and recurrent 16q loss, features that are similar to those of low grade in situ and invasive carcinoma. The molecular genetic profiles closely reflect the degree of proliferation and atypia in CCL, indicating some of these lesions represent both a morphologic and molecular continuum. In addition, overlapping chromosomal alterations between CCL and more advanced lesions within individual terminal duct lobular units suggest a commonality in molecular evolution. These data further support the hypothesis that CCLs are a nonobligate, intermediary step in the development of some forms of low grade in situ and invasive carcinoma. Copyright: © 2005 Lippincott Williams & Wilkins, Inc.

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

Low frequency of CHEK2 1100delC allele in Australian multiple-case breast cancer families: functional analysis in heterozygous individuals

A protein-truncating variant of CHEK2, 1100delC, is associated with a moderate increase in breast cancer risk. We have determined the prevalence of this allele in index cases from 300 Australian multiple-case breast cancer families, 95% of which had been found to be negative for mutations in BRCA1 and BRCA2. Only two (0.6%) index cases heterozygous for the CHEK2 mutation were identified. All available relatives in these two families were genotyped, but there was no evidence of co-segregation between the CHEK2 variant and breast cancer. Lymphoblastoid cell lines established from a heterozygous carrier contained approximately 20% of the CHEK2 1100delC mRNA relative to wild-type CHEK2 transcript. However, no truncated CHK2 protein was detectable. Analyses of expression and phosphorylation of wild-type CHK2 suggest that the variant is likely to act by haploinsufficiency. Analysis of CDC25A degradation, a downstream target of CHK2, suggests that some compensation occurs to allow normal degradation of CDC25A. Such compensation of the 1100delC defect in CHEK2 might explain the rather low breast cancer risk associated with the CHEK2 variant, compared to that associated with truncating mutations in BRCA1 or BRCA2.

A multiple account framework for cost-benefit analysis

The paper presents a spreadsheet-based multiple account framework for cost-benefit analysis which incorporates all the usual concerns of cost-benefit analysts such as shadow-pricing to account for market failure. distribution of net benefits. sensitivity and risk analysis, cost of public funds, and environmental effects. The approach is generalizable to a wide range of projects and situations and offers a number of advantages to both analysts and decision-makers, including transparency, a check on internal consistency, and a detailed summary of project net benefits disaggregated by stakeholder group. Of particular importance is the ease with which this framework allows for a project to be evaluated from alternative decision-making perspectives and under alternative policy scenarios where the trade-offs among the project's stakeholders can readily be identified and quantified. (C) 2004 Elsevier Ltd. All rights reserved.

Topological side-chain classification of beta-turns: Ideal motifs for peptidomimetic development

beta-turns are important topological motifs for biological recognition of proteins and peptides. Organic molecules that sample the side chain positions of beta-turns have shown broad binding capacity to multiple different receptors, for example benzodiazepines. beta-turns have traditionally been classified into various types based on the backbone dihedral angles (phi 2, psi 2, phi 3 and psi 3). Indeed, 57-68% of beta-turns are currently classified into 8 different backbone families (Type I, Type II, Type I', Type II', Type VIII, Type VIa1, Type VIa2 and Type VIb and Type IV which represents unclassified beta-turns). Although this classification of beta-turns has been useful, the resulting beta-turn types are not ideal for the design of beta-turn mimetics as they do not reflect topological features of the recognition elements, the side chains. To overcome this, we have extracted beta-turns from a data set of non-homologous and high-resolution protein crystal structures. The side chain positions, as defined by C-alpha-C-beta vectors, of these turns have been clustered using the kth nearest neighbor clustering and filtered nearest centroid sorting algorithms. Nine clusters were obtained that cluster 90% of the data, and the average intra-cluster RMSD of the four C-alpha-C-beta vectors is 0.36. The nine clusters therefore represent the topology of the side chain scaffold architecture of the vast majority of beta-turns. The mean structures of the nine clusters are useful for the development of beta-turn mimetics and as biological descriptors for focusing combinatorial chemistry towards biologically relevant topological space.

Determination of Cole parameters in multiple frequency bioelectrical impedance analysis using only the measurement of impedances

Conventional bioimpedance spectrometers measure resistance and reactance over a range of frequencies and, by application of a mathematical model for an equivalent circuit (the Cole model), estimate resistance at zero and infinite frequencies. Fitting of the experimental data to the model is accomplished by iterative, nonlinear curve fitting. An alternative fitting method is described that uses only the magnitude of the measured impedances at four selected frequencies. The two methods showed excellent agreement when compared using data obtained both from measurements of equivalent circuits and of humans. These results suggest that operational equivalence to a technically complex, frequency-scanning, phase-sensitive BIS analyser could be achieved from a simple four-frequency, impedance-only analyser.

Multisensorial obstacles detection and classification for ADAS and autonomous driving

A reliable perception of the real world is a key-feature for an autonomous vehicle and the Advanced Driver Assistance Systems (ADAS). Obstacles detection (OD) is one of the main components for the correct reconstruction of the dynamic world. Historical approaches based on stereo vision and other 3D perception technologies (e.g. LIDAR) have been adapted to the ADAS first and autonomous ground vehicles, after, providing excellent results. The obstacles detection is a very broad field and this domain counts a lot of works in the last years. In academic research, it has been clearly established the essential role of these systems to realize active safety systems for accident prevention, reflecting also the innovative systems introduced by industry. These systems need to accurately assess situational criticalities and simultaneously assess awareness of these criticalities by the driver; it requires that the obstacles detection algorithms must be reliable and accurate, providing: a real-time output, a stable and robust representation of the environment and an estimation independent from lighting and weather conditions. Initial systems relied on only one exteroceptive sensor (e.g. radar or laser for ACC and camera for LDW) in addition to proprioceptive sensors such as wheel speed and yaw rate sensors. But, current systems, such as ACC operating at the entire speed range or autonomous braking for collision avoidance, require the use of multiple sensors since individually they can not meet these requirements. It has led the community to move towards the use of a combination of them in order to exploit the benefits of each one. Pedestrians and vehicles detection are ones of the major thrusts in situational criticalities assessment, still remaining an active area of research. ADASs are the most prominent use case of pedestrians and vehicles detection. Vehicles should be equipped with sensing capabilities able to detect and act on objects in dangerous situations, where the driver would not be able to avoid a collision. A full ADAS or autonomous vehicle, with regard to pedestrians and vehicles, would not only include detection but also tracking, orientation, intent analysis, and collision prediction. The system detects obstacles using a probabilistic occupancy grid built from a multi-resolution disparity map. Obstacles classification is based on an AdaBoost SoftCascade trained on Aggregate Channel Features. A final stage of tracking and fusion guarantees stability and robustness to the result.