Implementing TURF analysis through binary linear programming

This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

Quantifying quantitative literacy: Age heaping and the history of human capital

Age data frequently display excess frequencies at round or attractive ages, such as even numbers and multiples of five. This phenomenon of age heaping has been viewed as a problem in previous research, especially in demography and epidemiology. We see it as an opportunity and propose its use as a measure of human capital that can yield comparable estimates across a wide range of historical contexts. A simulation study yields methodological guidelines for measuring and interpreting differences in ageheaping, while analysis of contemporary and historical datasets demonstrates the existence of a robust correlation between age heaping and literacy at both the individual and aggregate level. To illustrate the method, we generate estimates of human capital in Europe over the very long run, which support the hypothesis of a major increase in human capital preceding the industrial revolution.

Experiments on substratum roughness, grainsize and volume influence on the motion and spreading of rock avalanches

The main objective of the research is to link granular physics with the modelling of rock avalanches. Laboratory experiments consist to find a convenient granular material, i.e. grainsize and physical behaviour, and testing it on simple slope geometry. When the appropriate sliding material is selected, we attempted to model the debris avalanche and the spreading on a slope with different substratum to understand the relationship between the volume and the reach angle, i.e. angle of the line joining the top of the scar and the end of the deposit. For a better understanding of the mass spreading, the deposits are scanned with a laser scanner. Datasets are compared to see how the grain size and volume influence a debris avalanche. The relationship between the roughness and grainsize of the substratum shows that the spreading of the sliding mass is increased when the roughness of the substratum starts to be equivalent or greater than the grainsize of the flowing mass. The runout distance displays a more complex relationship, because a long runout distance implies that grains are less spread. This means that if the substratum is too rough the distance diminishes, as well if it is too smooth because the effect on the apparent friction decreases. Up to now our findings do not permit to validate any previous model (Melosh, 1987; Bagnold 1956).

Can the trabecular bone score (TBS) be considered as a major clinical risk factor (CRF) of osteoporotic fractures? A meta-like analysis

Abstract: To have an added value over BMD, a CRF of osteoporotic fracture must be predictable of the fracture, independent of BMD, reversible and quantifiable. Many major recognized CRF exist.Out of these factorsmany of themare indirect factor of bone quality. TBS predicts fracture independently of BMD as demonstrated from previous studies. The aim of the study is to verify if TBS can be considered as a major CRF of osteoporotic fracture. Existing validated datasets of Caucasian women were analyzed. These datasets stem from different studies performed by the authors of this report or provided to our group. However, the level of evidence of these studies will vary. Thus, the different datasets were weighted differently according to their design. This meta-like analysis involves more than 32000 women (≥50 years) with 2000 osteoporotic fractures from two prospective studies (OFELY&MANITOBA) and 7 crosssectional studies. Weighted relative risk (RR) for TBS was expressed for each decrease of one standard deviation as well as per tertile difference (TBS=1.300 and 1.200) and compared with those obtained for the major CRF included in FRAX®. Overall TBS RR obtained (adjusted for age) was 1.79 [95%CI-1.37-2.37]. For all women combined, RR for fracture for the lowest comparedwith themiddle TBS tertilewas 1.55[1.46- 1.68] and for the lowest compared with the highest TBS tertile was 2.8[2.70-3.00]. TBS is comparable to most of the major CRF (Fig 1) and thus could be used as one of them. Further studies have to be conducted to confirm these first findings.

Performance Report for Fiscal Year, 2005

I am pleased to present the performance report for the Iowa Department for the Blind for fiscal year 2005. This report is provided in compliance with sections 8E.210 and 216B.7 of the Code of Iowa. It contains valuable information about the services the Department and its partners provided for Iowans during the past fiscal year in the areas of vocational rehabilitation, library services, and resource management. Major accomplishments of the year included new food service opportunities in the Randolph-Sheppard program, extensive remodeling of the Adult Orientation and Adjustment Center, and continued national prominence in vocational rehabilitation as measured by the U.S. Rehabilitation Services Administration, which on June 13, 2005 released data on federal standards and indicators for the year ended September 30, 2004. Earnings ratios and the percentage of employment for vocational rehabilitation clients of the Department remain among the best in the nation. This is corroborated by a report released in September, 2005 by the U.S. Government Accountability Office, which tested and summarized datasets compiled by the U.S. Department of Education for the nation’s 80 vocational rehabilitation agencies. Overall, we met or exceeded 26 of 32 results targets included in this report. Key strategic challenges, developments, and trends are also discussed in the "Department Overview" that follows. Sincerely, Allen C. Harris Director, Iowa Department for the Blind

Risk of prostate, breast and colorectal cancer after skin cancer diagnosis.

Ultraviolet radiation is the major cause of skin cancer, but promotes vitamin D synthesis, and vitamin D has been inversely related to the risk of several common cancers including prostate, breast and colorectum. We therefore computed the incidence of prostate, breast and colorectal cancer following skin cancer using the datasets of the Swiss cancer Registries of Vaud and Neuchâtel. Between 1974 and 2005, 6,985 histologically confirmed squamous cell skin cancers, 21,046 basal cell carcinomas and 3,346 cutaneous malignant melanomas were registered, and followed up to the end of 2005 for the occurrence of second primary cancer of the prostate, breast and colorectum. Overall, 680 prostate cancers were observed versus 568.3 expected (standardized incidence ratio (SIR) = 1.20; 95% confidence interval (CI): 1.11-1.29), 440 breast cancers were observed versus 371.5 expected (SIR = 1.18; 95% CI: 1.08-1.30) and 535 colorectal cancers were observed versus 464.6 expected (SIR = 1.15; 95% CI: 1.06-1.25). When basal cell, squamous cell and skin melanoma were considered separately, all the SIRs for prostate, breast and colorectal cancers were around or slightly above unity. Likewise, the results were consistent across strata of age at skin cancer diagnosis and location (head and neck versus others), and for male and female colorectal cancers. These findings, based on a population with a long tradition of systematic histologic examination of all surgically treated skin lesions, do not support the hypothesis that prostate, breast and colorectal cancer risk is decreased following skin cancer.

Sequencing primate genomes: what have we learned?

We summarize the progress in whole-genome sequencing and analyses of primate genomes. These emerging genome datasets have broadened our understanding of primate genome evolution revealing unexpected and complex patterns of evolutionary change. This includes the characterization of genome structural variation, episodic changes in the repeat landscape, differences in gene expression, new models regarding speciation, and the ephemeral nature of the recombination landscape. The functional characterization of genomic differences important in primate speciation and adaptation remains a significant challenge. Limited access to biological materials, the lack of detailed phenotypic data and the endangered status of many critical primate species have significantly attenuated research into the genetic basis of primate evolution. Next-generation sequencing technologies promise to greatly expand the number of available primate genome sequences; however, such draft genome sequences will likely miss critical genetic differences within complex genomic regions unless dedicated efforts are put forward to understand the full spectrum of genetic variation.

AWSum-Combining Classification with Knowledge Aquisition

Many classifiers achieve high levels of accuracy but have limited applicability in real world situations because they do not lead to a greater understanding or insight into the^way features influence the classification. In areas such as health informatics a classifier that clearly identifies the influences on classification can be used to direct research and formulate interventions. This research investigates the practical applications of Automated Weighted Sum, (AWSum), a classifier that provides accuracy comparable to other techniques whilst providing insight into the data. This is achieved by calculating a weight for each feature value that represents its influence on the class value. The merits of this approach in classification and insight are evaluated on a Cystic Fibrosis and Diabetes datasets with positive results.

Is bank debt special for the transmission of monetary policy? Evidence from the stock market

We combine existing balance sheet and stock market data with two new datasets to studywhether, how much, and why bank lending to firms matters for the transmission of monetarypolicy. The first new dataset enables us to quantify the bank dependence of firms precisely,as the ratio of bank debt to total assets. We show that a two standard deviation increase inthe bank dependence of a firm makes its stock price about 25% more responsive to monetarypolicy shocks. We explore the channels through which this effect occurs, and find that thestock prices of bank-dependent firms that borrow from financially weaker banks display astronger sensitivity to monetary policy shocks. This finding is consistent with the banklending channel, a theory according to which the strength of bank balance sheets mattersfor monetary policy transmission. We construct a new database of hedging activities andshow that the stock prices of bank-dependent firms that hedge against interest rate riskdisplay a lower sensitivity to monetary policy shocks. This finding is consistent with aninterest rate pass-through channel that operates via the direct transmission of policy ratesto lending rates associated with the widespread use of floating-rates in bank loans and creditline agreements.

Validation of the Mini Nutritional Assessment short-form (MNA-SF): a practical tool for identification of nutritional status.

OBJECTIVE: To validate a revision of the Mini Nutritional Assessment short-form (MNA(R)-SF) against the full MNA, a standard tool for nutritional evaluation. METHODS: A literature search identified studies that used the MNA for nutritional screening in geriatric patients. The contacted authors submitted original datasets that were merged into a single database. Various combinations of the questions on the current MNA-SF were tested using this database through combination analysis and ROC based derivation of classification thresholds. RESULTS: Twenty-seven datasets (n=6257 participants) were initially processed from which twelve were used in the current analysis on a sample of 2032 study participants (mean age 82.3y) with complete information on all MNA items. The original MNA-SF was a combination of six questions from the full MNA. A revised MNA-SF included calf circumference (CC) substituted for BMI performed equally well. A revised three-category scoring classification for this revised MNA-SF, using BMI and/or CC, had good sensitivity compared to the full MNA. CONCLUSION: The newly revised MNA-SF is a valid nutritional screening tool applicable to geriatric health care professionals with the option of using CC when BMI cannot be calculated. This revised MNA-SF increases the applicability of this rapid screening tool in clinical practice through the inclusion of a "malnourished" category.

Spatial analysis of corresponding fingerprint features from match and close non-match populations

The development of statistical models for forensic fingerprint identification purposes has been the subject of increasing research attention in recent years. This can be partly seen as a response to a number of commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. In addition, key forensic identification bodies such as ENFSI [1] and IAI [2] have recently endorsed and acknowledged the potential benefits of using statistical models as an important tool in support of the fingerprint identification process within the ACE-V framework. In this paper, we introduce a new Likelihood Ratio (LR) model based on Support Vector Machines (SVMs) trained with features discovered via morphometric and spatial analyses of corresponding minutiae configurations for both match and close non-match populations often found in AFIS candidate lists. Computed LR values are derived from a probabilistic framework based on SVMs that discover the intrinsic spatial differences of match and close non-match populations. Lastly, experimentation performed on a set of over 120,000 publicly available fingerprint images (mostly sourced from the National Institute of Standards and Technology (NIST) datasets) and a distortion set of approximately 40,000 images, is presented, illustrating that the proposed LR model is reliably guiding towards the right proposition in the identification assessment of match and close non-match populations. Results further indicate that the proposed model is a promising tool for fingerprint practitioners to use for analysing the spatial consistency of corresponding minutiae configurations.

Profiling of counterfeit medicines by vibrational spectroscopy

Counterfeit pharmaceutical products have become a widespread problem in the last decade. Various analytical techniques have been applied to discriminate between genuine and counterfeit products. Among these, Near-infrared (NIR) and Raman spectroscopy provided promising results.The present study offers a methodology allowing to provide more valuable information fororganisations engaged in the fight against counterfeiting of medicines.A database was established by analyzing counterfeits of a particular pharmaceutical product using Near-infrared (NIR) and Raman spectroscopy. Unsupervised chemometric techniques (i.e. principal component analysis - PCA and hierarchical cluster analysis - HCA) were implemented to identify the classes within the datasets. Gas Chromatography coupled to Mass Spectrometry (GC-MS) and Fourier Transform Infrared Spectroscopy (FT-IR) were used to determine the number of different chemical profiles within the counterfeits. A comparison with the classes established by NIR and Raman spectroscopy allowed to evaluate the discriminating power provided by these techniques. Supervised classifiers (i.e. k-Nearest Neighbors, Partial Least Squares Discriminant Analysis, Probabilistic Neural Networks and Counterpropagation Artificial Neural Networks) were applied on the acquired NIR and Raman spectra and the results were compared to the ones provided by the unsupervised classifiers.The retained strategy for routine applications, founded on the classes identified by NIR and Raman spectroscopy, uses a classification algorithm based on distance measures and Receiver Operating Characteristics (ROC) curves. The model is able to compare the spectrum of a new counterfeit with that of previously analyzed products and to determine if a new specimen belongs to one of the existing classes, consequently allowing to establish a link with other counterfeits of the database.

Quantitative analysis of crystal/grain sizes and their distributions in 2D and 3D

We review methods to estimate the average crystal (grain) size and the crystal (grain) size distribution in solid rocks. Average grain sizes often provide the base for stress estimates or rheological calculations requiring the quantification of grain sizes in a rock's microstructure. The primary data for grain size data are either 1D (i.e. line intercept methods), 2D (area analysis) or 3D (e.g., computed tomography, serial sectioning). These data have been used for different data treatments over the years, whereas several studies assume a certain probability function (e.g., logarithm, square root) to calculate statistical parameters as the mean, median, mode or the skewness of a crystal size distribution. The finally calculated average grain sizes have to be compatible between the different grain size estimation approaches in order to be properly applied, for example, in paleo-piezometers or grain size sensitive flow laws. Such compatibility is tested for different data treatments using one- and two-dimensional measurements. We propose an empirical conversion matrix for different datasets. These conversion factors provide the option to make different datasets compatible with each other, although the primary calculations were obtained in different ways. In order to present an average grain size, we propose to use the area-weighted and volume-weighted mean in the case of unimodal grain size distributions, respectively, for 2D and 3D measurements. The shape of the crystal size distribution is important for studies of nucleation and growth of minerals. The shape of the crystal size distribution of garnet populations is compared between different 2D and 3D measurements, which are serial sectioning and computed tomography. The comparison of different direct measured 3D data; stereological data and direct presented 20 data show the problems of the quality of the smallest grain sizes and the overestimation of small grain sizes in stereological tools, depending on the type of CSD. (C) 2011 Published by Elsevier Ltd.

AssociationViewer: a scalable and integrated software tool for visualization of large-scale variation data in genomic context.

SUMMARY: We present a tool designed for visualization of large-scale genetic and genomic data exemplified by results from genome-wide association studies. This software provides an integrated framework to facilitate the interpretation of SNP association studies in genomic context. Gene annotations can be retrieved from Ensembl, linkage disequilibrium data downloaded from HapMap and custom data imported in BED or WIG format. AssociationViewer integrates functionalities that enable the aggregation or intersection of data tracks. It implements an efficient cache system and allows the display of several, very large-scale genomic datasets. AVAILABILITY: The Java code for AssociationViewer is distributed under the GNU General Public Licence and has been tested on Microsoft Windows XP, MacOSX and GNU/Linux operating systems. It is available from the SourceForge repository. This also includes Java webstart, documentation and example datafiles.