Failures in Building Partnership for Success in the Competitive Market: The Case of Polish Ski Resorts

The topic of local stakeholders’ collaboration for success on the tourism market is a popular one, however research is usually devoted to well established Western economies. Created in this way, rules of cooperation are not fully suitable for new democracies in Central and Eastern European countries. Western standards of cooperation can not be achieved in Polish winter sports destinations, which is mirrored in the analyzed example of the Polish biggest ski resort – Szczyrk. Mutual mistrust and hostile attitude are typical for stakeholders in this example. The very low competitiveness level of the product is the most visible effect. Additionally, ski product development in Poland is highly criticized from the environmental point of view, which results in another difficult to manage, severe conflict sourced in different interpretations of the idea of sustainable tourism development.ski resort, partnership, Central and Eastern Europe, Polish ski industry

New tools and expanded data analysis capabilities at the protein structure prediction center

We outline the main tasks performed by the Protein Structure Prediction Center in support of the CASP7 experiment and provide a brief review of the major measures used in the automatic evaluation of predictions. We describe in more detail the software developed to facilitate analysis of modeling success over and beyond the available templates and the adopted Java-based tool enabling visualization of multiple structural superpositions between target and several models/templates. We also give an overview of the CASP infrastructure provided by the Center and discuss the organization of the results web pages available through http://predictioncenter.or

Optimization of tau identification in ATLAS experiment using multivariate tools

In elementary particle physics the efficient analysis of huge amount of collected data require the use of sophisticated selection and analysis algorithms. We have implemented a Support Vector Machine (SVM) integrated with the CERN TMVA/ROOT package. SVM approach to signal and background separation is based on building a separating hyperplane defined by the support vectors. The margin between them and the hyperplane is maximized. The extensions to a non-linear separation is performed by mapping the input vectors into a high dimensional space, in which data can be linearly separated. The use of kernel functions allows to perform computations in a high dimension feature space without explicitly knowing a mapping function. Our SVM implementation is based on Platt's Sequential Minimal Optimization (SMO) algorithm and includes various kernel functions like a linear function, polynomial and Gaussian. The identification of hadronic decays of tau leptons in the ATLAS experiment using a tau1P3P package is performed using, beside the baseline cut analysis, also multivariate analysis tools: neural network, PDE_RS and our implementation of the SVM algorithm. The use and the comparison of the three algorithms is presented

Concreteness and abstraction in everyday explanation

A number of philosophers argue for the value of abstraction in explanation. According to these prescriptive theories, an explanation becomes superior when it leaves out details that make no difference to the occurrence of the event one is trying to explain (the explanandum). Abstract explanations are not frugal placeholders for improved, detailed future explanations but are more valuable than their concrete counterparts because they highlight the factors that do the causal work, the factors in the absence of which the explanandum would not occur. We present several experiments that test whether people follow this prescription (i.e., whether people prefer explanations with abstract difference makers over explanations with concrete details and explanations that omit descriptively accurate but causally irrelevant information). Contrary to the prescription, we found a preference for concreteness and detail. Participants rated explanations with concrete details higher than their abstract counterparts and in many cases they did not penalize the presence of causally irrelevant details. Nevertheless, causality still constrained participants' preferences: They downgraded concrete explanations that did not communicate the critical causal properties

Structural Re-Alignment in an Immunogenic Surface Region of Ricin A Chain

We compared structure alignments generated by several protein structure comparison programs to determine whether existing methods would satisfactorily align residues at a highly conserved position within an immunogenic loop in ribosome inactivating proteins (RIPs). Using default settings, structure alignments generated by several programs (CE, DaliLite, FATCAT, LGA, MAMMOTH, MATRAS, SHEBA, SSM) failed to align the respective conserved residues, although LGA reported correct residue-residue (R-R) correspondences when the beta-carbon (Cb) position was used as the point of reference in the alignment calculations. Further tests using variable points of reference indicated that points distal from the beta carbon along a vector connecting the alpha and beta carbons yielded rigid structural alignments in which residues known to be highly conserved in RIPs were reported as corresponding residues in structural comparisons between ricin A chain, abrin-A, and other RIPs. Results suggest that approaches to structure alignment employing alternate point representations corresponding to side chain position may yield structure alignments that are more consistent with observed conservation of functional surface residues than do standard alignment programs, which apply uniform criteria for alignment (i.e. alpha carbon (Ca) as point of reference) along the entirety of the peptide chain. We present the results of tests that suggest the utility of allowing user-specified points of reference in generating alternate structural alignments, and we present a web server for automatically generating such alignments: http://as2ts.llnl.gov/AS2TS/LGA/lga_pdblist_plots.html

A study of quality measures for protein threading models

BACKGROUND: Prediction of protein structures is one of the fundamental challenges in biology today. To fully understand how well different prediction methods perform, it is necessary to use measures that evaluate their performance. Every two years, starting in 1994, the CASP (Critical Assessment of protein Structure Prediction) process has been organized to evaluate the ability of different predictors to blindly predict the structure of proteins. To capture different features of the models, several measures have been developed during the CASP processes. However, these measures have not been examined in detail before. In an attempt to develop fully automatic measures that can be used in CASP, as well as in other type of benchmarking experiments, we have compared twenty-one measures. These measures include the measures used in CASP3 and CASP2 as well as have measures introduced later. We have studied their ability to distinguish between the better and worse models submitted to CASP3 and the correlation between them. RESULTS: Using a small set of 1340 models for 23 different targets we show that most methods correlate with each other. Most pairs of measures show a correlation coefficient of about 0.5. The correlation is slightly higher for measures of similar types. We found that a significant problem when developing automatic measures is how to deal with proteins of different length. Also the comparisons between different measures is complicated as many measures are dependent on the size of the target. We show that the manual assessment can be reproduced to about 70% using automatic measures. Alignment independent measures, detects slightly more of the models with the correct fold, while alignment dependent measures agree better when selecting the best models for each target. Finally we show that using automatic measures would, to a large extent, reproduce the assessors ranking of the predictors at CASP3. CONCLUSIONS: We show that given a sufficient number of targets the manual and automatic measures would have given almost identical results at CASP3. If the intent is to reproduce the type of scoring done by the manual assessor in in CASP3, the best approach might be to use a combination of alignment independent and alignment dependent measures, as used in several recent studies

Mutations in UDP-Glucose:Sterol Glucosyltransferase in Arabidopsis Cause Transparent Testa Phenotype and Suberization Defect in Seeds

In higher plants, the most abundant sterol derivatives are steryl glycosides (SGs) and acyl SGs. Arabidopsis (Arabidopsis thaliana) contains two genes, UGT80A2 and UGT80B1, that encode UDP-Glc:sterol glycosyltransferases, enzymes that catalyze the synthesis of SGs. Lines having mutations in UGT80A2, UGT80B1, or both UGT80A2 and UGT8B1 were identified and characterized. The ugt80A2 lines were viable and exhibited relatively minor effects on plant growth. Conversely, ugt80B1 mutants displayed an array of phenotypes that were pronounced in the embryo and seed. Most notable was the finding that ugt80B1 was allelic to transparent testa15 and displayed a transparent testa phenotype and a reduction in seed size. In addition to the role of UGT80B1 in the deposition of flavanoids, a loss of suberization of the seed was apparent in ugt80B1 by the lack of autofluorescence at the hilum region. Moreover, in ugt80B1, scanning and transmission electron microscopy reveals that the outer integument of the seed coat lost the electron-dense cuticle layer at its surface and displayed altered cell morphology. Gas chromatography coupled with mass spectrometry of lipid polyester monomers confirmed a drastic decrease in aliphatic suberin and cutin-like polymers that was associated with an inability to limit tetrazolium salt uptake. The findings suggest a membrane function for SGs and acyl SGs in trafficking of lipid polyester precursors. An ancillary observation was that cellulose biosynthesis was unaffected in the double mutant, inconsistent with a predicted role for SGs in priming cellulose synthesis

A Computational Model of Jetliner Taxiing

The Next Generation Air Transportation System (NextGen) is transforming the way planes move on the ground as well as in the sky. Some of the proposed changes, such as automated scheduling algorithms to generate taxi clearances and speed-based taxi clearances, require thorough testing to ensure safety and reliability. Cognitive modeling is able to uniquely address these issues in a compromise between costly human-in-the-loop simulations and deterministic computer simulations. In this thesis, I present an ACT-R cognitive model to emulate pilot taxiing behavior in a dynamic environment, in order to predict human behavior in novel situations imposed by NextGen constraints. The model is validated by comparing taxi routes generated by the model to routes driven by real pilots while on the job

Protein Classification Based on Analysis of Local Sequence-Structure Correspondence

The goal of this project was to develop an algorithm to detect and calculate common structural motifs in compared structures, and define a set of numerical criteria to be used for fully automated motif based protein structure classification. The Protein Data Bank (PDB) contains more than 33,000 experimentally solved protein structures, and the Structural Classification of Proteins (SCOP) database, a manual classification of these structures, cannot keep pace with the rapid growth of the PDB. In our approach called STRALCP (STRucture Alignment based Clustering of Proteins), we generate detailed information about global and local similarities between given set of structures, identify similar fragments that are conserved within analyzed proteins, and use these conserved regions (detected structural motifs) to classify proteins

Computational analysis of pathogen-borne metallo β-lactamases reveals discriminating structural features between B1 types

<p>Abstract</p> <p>Background</p> <p>Genes conferring antibiotic resistance to groups of bacterial pathogens are cause for considerable concern, as many once-reliable antibiotics continue to see a reduction in efficacy. The recent discovery of the metallo β-lactamase <it>blaNDM-1 </it>gene, which appears to grant antibiotic resistance to a variety of Enterobacteriaceae <it>via </it>a mobile plasmid, is one example of this distressing trend. The following work describes a computational analysis of pathogen-borne MBLs that focuses on the structural aspects of characterized proteins.</p> <p>Results</p> <p>Using both sequence and structural analyses, we examine residues and structural features specific to various pathogen-borne MBL types. This analysis identifies a linker region within MBL-like folds that may act as a discriminating structural feature between these proteins, and specifically resistance-associated acquirable MBLs. Recently released crystal structures of the newly emerged NDM-1 protein were aligned against related MBL structures using a variety of global and local structural alignment methods, and the overall fold conformation is examined for structural conservation. Conservation appears to be present in most areas of the protein, yet is strikingly absent within a linker region, making NDM-1 unique with respect to a linker-based classification scheme. Variability analysis of the NDM-1 crystal structure highlights unique residues in key regions as well as identifying several characteristics shared with other transferable MBLs.</p> <p>Conclusions</p> <p>A discriminating linker region identified in MBL proteins is highlighted and examined in the context of NDM-1 and primarily three other MBL types: IMP-1, VIM-2 and ccrA. The presence of an unusual linker region variant and uncommon amino acid composition at specific structurally important sites may help to explain the unusually broad kinetic profile of NDM-1 and may aid in directing research attention to areas of this protein, and possibly other MBLs, that may be targeted for inactivation or attenuation of enzymatic activity.</p