Rank Dynamics

Science.gov (United States)

Gershenson, Carlos

Studies of rank distributions have been popular for decades, especially since the work of Zipf. For example, if we rank words of a given language by use frequency (most used word in English is 'the', rank 1; second most common word is 'of', rank 2), the distribution can be approximated roughly with a power law. The same applies for cities (most populated city in a country ranks first), earthquakes, metabolism, the Internet, and dozens of other phenomena. We recently proposed ``rank diversity'' to measure how ranks change in time, using the Google Books Ngram dataset. Studying six languages between 1800 and 2009, we found that the rank diversity curves of languages are universal, adjusted with a sigmoid on log-normal scale. We are studying several other datasets (sports, economies, social systems, urban systems, earthquakes, artificial life). Rank diversity seems to be universal, independently of the shape of the rank distribution. I will present our work in progress towards a general description of the features of rank change in time, along with simple models which reproduce it

Logging costs and production rates for the group selection cutting method

Science.gov (United States)

Philip M. McDonald

1965-01-01

Young-growth, mixed-conifer stands were logged by a group-selection method designed to create openings 30, 60, and 90 feet in diameter. Total costs for felling, limbing, bucking, and skidding on these openings ranged from $7.04 to $7.99 per thousand board feet. Cost differences between openings were not statistically significant. Logging costs for group selection...

Selective logging: does the imprint remain on tree structure and composition after 45 years?

Science.gov (United States)

Osazuwa-Peters, Oyomoare L.; Chapman, Colin A.; Zanne, Amy E.

2015-01-01

Selective logging of tropical forests is increasing in extent and intensity. The duration over which impacts of selective logging persist, however, remains an unresolved question, particularly for African forests. Here, we investigate the extent to which a past selective logging event continues to leave its imprint on different components of an East African forest 45 years later. We inventoried 2358 stems ≥10 cm in diameter in 26 plots (200 m × 10 m) within a 5.2 ha area in Kibale National Park, Uganda, in logged and unlogged forest. In these surveys, we characterized the forest light environment, taxonomic composition, functional trait composition using three traits (wood density, maximum height and maximum diameter) and forest structure based on three measures (stem density, total basal area and total above-ground biomass). In comparison to unlogged forests, selectively logged forest plots in Kibale National Park on average had higher light levels, different structure characterized by lower stem density, lower total basal area and lower above-ground biomass, and a distinct taxonomic composition driven primarily by changes in the relative abundance of species. Conversely, selectively logged forest plots were like unlogged plots in functional composition, having similar community-weighted mean values for wood density, maximum height and maximum diameter. This similarity in functional composition irrespective of logging history may be due to functional recovery of logged forest or background changes in functional attributes of unlogged forest. Despite the passage of 45 years, the legacy of selective logging on the tree community in Kibale National Park is still evident, as indicated by distinct taxonomic and structural composition and reduced carbon storage in logged forest compared with unlogged forest. The effects of selective logging are exerted via influences on tree demography rather than functional trait composition. PMID:27293697

Finding Maximal Quasiperiodicities in Strings

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Pedersen, Christian N. S.

2000-01-01

of length n in time O(n log n) and space O(n). Our algorithm uses the suffix tree as the fundamental data structure combined with efficient methods for merging and performing multiple searches in search trees. Besides finding all maximal quasiperiodic substrings, our algorithm also marks the nodes......Apostolico and Ehrenfeucht defined the notion of a maximal quasiperiodic substring and gave an algorithm that finds all maximal quasiperiodic substrings in a string of length n in time O(n log2 n). In this paper we give an algorithm that finds all maximal quasiperiodic substrings in a string...... in the suffix tree that have a superprimitive path-label....

Long-term Carbon Loss and Recovery Following Selective Logging in Amazon Forests

Energy Technology Data Exchange (ETDEWEB)

Huang, Maoyi; Asner, Gregory P.

2010-09-30

Amazon deforestation contributes significantly to global carbon (C) emissions. In comparison, the contribution from selective logging to atmospheric CO2 emissions, and its impact on regional C dynamics, is highly uncertain. Using a new geographically-based modeling approach in combination with high resolution remote sensing data from 1999-2002, we estimate that C emissions were 0.04 – 0.05 Pg C yr-1 due to selective logging from a ~2,664,960 km2 region of the Brazilian Amazon. Selective logging was responsible for 15-19% higher carbon emissions than reported from deforestation (clear-cutting) alone. Our simulations indicated that forest carbon lost via selective logging lasts two to three decades following harvest, and that the original live biomass takes up to a century to recover, if the forests are not subsequently cleared. The two- to three-decade loss of carbon results from the biomass damaged by logging activities, including leaves, wood, and roots, estimated to be 89.1 Tg C yr-1 from 1999-2002 over the study region, leaving 70.0 Tg C yr-1 and 7.9 Tg C yr-1 to accumulate as coarse woody debris and soil C, respectively. While avoided deforestation is central to crediting rainforest nations for reduced carbon emissions, the extent and intensity of selective logging are also critical to determining carbon emissions in the context of Reduced Emissions from Deforestation and Forest Degradation (REDD). We show that a combination of automated high-resolution satellite monitoring and detailed forest C modeling can yield spatially explicit estimates of harvest related C losses and subsequent recovery in support of REDD and other international carbon market mechanisms.

Two-stage recovery of amphibian assemblages following selective logging of tropical forests.

Science.gov (United States)

Adum, Gilbert Baase; Eichhorn, Markus Peter; Oduro, William; Ofori-Boateng, Caleb; Rödel, Mark-Oliver

2013-04-01

There is a lack of quantitative information on the effectiveness of selective-logging practices in ameliorating effects of logging on faunal communities. We conducted a large-scale replicated field study in 3 selectively logged moist semideciduous forests in West Africa at varying times after timber extraction to assess post logging effects on amphibian assemblages. Specifically, we assessed whether the diversity, abundance, and assemblage composition of amphibians changed over time for forest-dependent species and those tolerant of forest disturbance. In 2009, we sampled amphibians in 3 forests (total of 48 study plots, each 2 ha) in southwestern Ghana. In each forest, we established plots in undisturbed forest, recently logged forest, and forest logged 10 and 20 years previously. Logging intensity was constant across sites with 3 trees/ha removed. Recently logged forests supported substantially more species than unlogged forests. This was due to an influx of disturbance-tolerant species after logging. Simultaneously Simpson's index decreased, with increased in dominance of a few species. As time since logging increased richness of disturbance-tolerant species decreased until 10 years after logging when their composition was indistinguishable from unlogged forests. Simpson's index increased with time since logging and was indistinguishable from unlogged forest 20 years after logging. Forest specialists decreased after logging and recovered slowly. However, after 20 years amphibian assemblages had returned to a state indistinguishable from that of undisturbed forest in both abundance and composition. These results demonstrate that even with low-intensity logging (≤3 trees/ha) a minimum 20-year rotation of logging is required for effective conservation of amphibian assemblages in moist semideciduous forests. Furthermore, remnant patches of intact forests retained in the landscape and the presence of permanent brooks may aid in the effective recovery of amphibian

How to Rank Journals.

Science.gov (United States)

Bradshaw, Corey J A; Brook, Barry W

2016-01-01

There are now many methods available to assess the relative citation performance of peer-reviewed journals. Regardless of their individual faults and advantages, citation-based metrics are used by researchers to maximize the citation potential of their articles, and by employers to rank academic track records. The absolute value of any particular index is arguably meaningless unless compared to other journals, and different metrics result in divergent rankings. To provide a simple yet more objective way to rank journals within and among disciplines, we developed a κ-resampled composite journal rank incorporating five popular citation indices: Impact Factor, Immediacy Index, Source-Normalized Impact Per Paper, SCImago Journal Rank and Google 5-year h-index; this approach provides an index of relative rank uncertainty. We applied the approach to six sample sets of scientific journals from Ecology (n = 100 journals), Medicine (n = 100), Multidisciplinary (n = 50); Ecology + Multidisciplinary (n = 25), Obstetrics & Gynaecology (n = 25) and Marine Biology & Fisheries (n = 25). We then cross-compared the κ-resampled ranking for the Ecology + Multidisciplinary journal set to the results of a survey of 188 publishing ecologists who were asked to rank the same journals, and found a 0.68-0.84 Spearman's ρ correlation between the two rankings datasets. Our composite index approach therefore approximates relative journal reputation, at least for that discipline. Agglomerative and divisive clustering and multi-dimensional scaling techniques applied to the Ecology + Multidisciplinary journal set identified specific clusters of similarly ranked journals, with only Nature & Science separating out from the others. When comparing a selection of journals within or among disciplines, we recommend collecting multiple citation-based metrics for a sample of relevant and realistic journals to calculate the composite rankings and their relative uncertainty windows.

Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection

KAUST Repository

Chen, Lisha

2012-12-01

The reduced-rank regression is an effective method in predicting multiple response variables from the same set of predictor variables. It reduces the number of model parameters and takes advantage of interrelations between the response variables and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group and show that this penalty satisfies certain desirable invariance properties. We develop two numerical algorithms to solve the penalized regression problem and establish the asymptotic consistency of the proposed method. In particular, the manifold structure of the reduced-rank regression coefficient matrix is considered and studied in our theoretical analysis. In our simulation study and real data analysis, the new method is compared with several existing variable selection methods for multivariate regression and exhibits competitive performance in prediction and variable selection. © 2012 American Statistical Association.

A deductive approach to select or rank journals in multifaceted subject, Oceanography

Digital Repository Service at National Institute of Oceanography (India)

Sahu, S.R.; Panda, K.C.

journal) whereas Bradford’s differential approach (articles in the bibliographies of specific subject field) to account/rank the core journals. Both these methods make sense in the journal selection/ranking process to a specific subject field...

Selection of suitable e-learning approach using TOPSIS technique with best ranked criteria weights

Science.gov (United States)

Mohammed, Husam Jasim; Kasim, Maznah Mat; Shaharanee, Izwan Nizal Mohd

2017-11-01

This paper compares the performances of four rank-based weighting assessment techniques, Rank Sum (RS), Rank Reciprocal (RR), Rank Exponent (RE), and Rank Order Centroid (ROC) on five identified e-learning criteria to select the best weights method. A total of 35 experts in a public university in Malaysia were asked to rank the criteria and to evaluate five e-learning approaches which include blended learning, flipped classroom, ICT supported face to face learning, synchronous learning, and asynchronous learning. The best ranked criteria weights are defined as weights that have the least total absolute differences with the geometric mean of all weights, were then used to select the most suitable e-learning approach by using TOPSIS method. The results show that RR weights are the best, while flipped classroom approach implementation is the most suitable approach. This paper has developed a decision framework to aid decision makers (DMs) in choosing the most suitable weighting method for solving MCDM problems.

Problems of calibrating measuring instruments for selective gamma-gamma logging

International Nuclear Information System (INIS)

Daniel, J.; Smolarova, H.

1977-01-01

Quantitative determination of copper content in the Novoveska Huta chalcopyrite deposit is described using selective gamma-gamma logging. Factors influencing the calibration quality are discussed. (author)

Advances in ranking and selection, multiple comparisons, and reliability methodology and applications

CERN Document Server

Balakrishnan, N; Nagaraja, HN

2007-01-01

S. Panchapakesan has made significant contributions to ranking and selection and has published in many other areas of statistics, including order statistics, reliability theory, stochastic inequalities, and inference. Written in his honor, the twenty invited articles in this volume reflect recent advances in these areas and form a tribute to Panchapakesan's influence and impact on these areas. Thematically organized, the chapters cover a broad range of topics from: Inference; Ranking and Selection; Multiple Comparisons and Tests; Agreement Assessment; Reliability; and Biostatistics. Featuring

Automatic vowels selection and ranking in Russian enciphered texts

Directory of Open Access Journals (Sweden)

Yuri I. Petrenko

2018-01-01

, defined as the difference between the conditional probabilities of vowel-consonant and vowelvowel diagram’s types. For an alphabet consisted of N characters the program defines a combination of a given number k of “vowels” by exhaustive search. This combination of k symbols maximizes Markov criterion. The order relation of the new “vowels” for k = 1, 2, 3... characterizes the descending of their “strength” and can be used to separate vowels from consonants. In texts of sufficient volume there are possible approximate ranking of the vowel’s set. A more accurate ranking is possible when as a measure of “symbol power” Markov criterion’s increments are used. The algorithm speed can be greatly accelerated by using some tricks of steepest descent method. The test program discovered the independence of Markov criterion from the text’s author as well as its unimodality for long texts. Using this criterion, the algorithm can separate vowels from consonants for short (up to 100 characters texts as well as the ranking of vowels for texts as small as 250-500 letters. The similarity of Markov criterion’s statistics of letters “ь”, “ъ” and standard vowels is discovered. These two letters are inseparable by Markov criterion method from the standard vowels. The test results showed that Markov criterion method can be used for cryptanalysis of short Russian texts as well as texts of the other consonant languages. 

Classification of rank 2 cluster varieties

DEFF Research Database (Denmark)

Mandel, Travis

We classify rank 2 cluster varieties (those whose corresponding skew-form has rank 2) according to the deformation type of a generic fiber U of their X-spaces, as defined by Fock and Goncharov. Our approach is based on the work of Gross, Hacking, and Keel for cluster varieties and log Calabi...

Stand structure, composition and illegal logging in selectively logged production forests of Myanmar: Comparison of two compartments subject to different cutting frequency

Directory of Open Access Journals (Sweden)

Tual Cin Khai

2016-07-01

Full Text Available Appropriate cutting cycles and annual allowable cuts are crucial to ensure sustainability of tropical selective logging, but there have been limited field data to verify long-term effects of different cutting cycles. This study reveals some evidence of forest degradation in selectively logged production forests of Myanmar, which are subject to inappropriate cutting frequency. We compared stand structure, commercial species composition, and incidence of illegal logging between two compartments with low (LCF; 1 time and high (HCF; 5 times cutting frequency over a recent 18 years. Prior to the latest cutting, LCF had 176 trees ha−1 with an inverted-J shape distribution of diameter at breast height (DBH, including a substantial amount of teak (Tectona grandis and other commercially important species in each DBH class. HCF prior to the latest cut had only 41 trees ha−1 without many commercially important species. At HCF, nearly half the standing trees of various species and size were illegally cut following legal operations; this was for charcoal making in nearby kilns. At LCF, two species, teak and Xylia xylocarpa, were cut illegally and sawn for timber on the spot. More extensive and systematic surveys are needed to generalize the findings of forest degradation and illegal logging. However, our study calls for urgent reconsideration of logging practices with high cutting frequency, which can greatly degrade forests with accompanying illegal logging, and for rehabilitating strongly degraded, bamboo-dominated forests. To reduce illegal logging, it would be important to pay more attention on a MSS regulation stating that logging roads should be destroyed after logging operations.

A Ranking Method for Neutral Pion and Eta Selection in Hadronic Events

International Nuclear Information System (INIS)

Bingoel, A.

2004-01-01

The selection of neutral pions and etas with a high purity while maintaining also a high efficiency can be important in the formation of statistically significant mass spectra in the reconstruction of short-lived particles such as the omega meson (ω→π + + π - + π 0 ). In this study a Ranking method has been optimized for data from the ALEPH Experiment, CERN. The results show that the Ranking method, when applied to high multiplicity events, yields significant improvements in the purity of selected pion candidates and facilitates the relaxation of standard cuts thereby avoiding some systematic uncertainties

Contrasting taxonomic and functional responses of a tropical tree community to selective logging

OpenAIRE

Baraloto, C.; Hérault, B.; Paine, C. E. T.; Massot, H.; Blanc, L.; Bonal, D.; Molino, Jean-François; Nicolini, E. A.; Sabatier, Daniel

2012-01-01

1. Considerable debate surrounds the extent to which tropical forests can be managed for resource extraction while conserving biodiversity and ecosystem properties, which depend on functional composition. Here we evaluate the compatibility of these aims by examining the effects of logging on taxonomic and functional diversity and composition in a tropical forest. 2. Twenty years after selective logging, we inventoried 4140 stems regenerating in logging gaps and adjacent undisturbed areas, and...

Logging damage using an individual tree selection practice in Appalachian hardwood stands

Science.gov (United States)

Neil I. Lamson; H. Clay Smith; Gary W. Miller

1985-01-01

Four West Virginia hardwood stands, managed using individual-tree selection for the past 30 years, were examined after the third and, in one instance, the fourth periodic harvest to determine the severity of logging damage. On existing skid roads, trees were removed with a rubber-tired skidder or a crawler tractor with a rubber-tired arch. Logging damage reduced...

The Homogeneity of Social Selection in Accessing Higher Ranked Universities

DEFF Research Database (Denmark)

Munk, Martin David; Baklanov, Nikita

2018-01-01

This paper demonstrates the persistence of social selectivity throughout the educational ladder, with evident social reproduction at the top. By jointly modelling multiple choices of high school, university, field of study, and institutional rank of university using a multinomial transition model...

TENSOR DECOMPOSITIONS AND SPARSE LOG-LINEAR MODELS

Science.gov (United States)

Johndrow, James E.; Bhattacharya, Anirban; Dunson, David B.

2017-01-01

Contingency table analysis routinely relies on log-linear models, with latent structure analysis providing a common alternative. Latent structure models lead to a reduced rank tensor factorization of the probability mass function for multivariate categorical data, while log-linear models achieve dimensionality reduction through sparsity. Little is known about the relationship between these notions of dimensionality reduction in the two paradigms. We derive several results relating the support of a log-linear model to nonnegative ranks of the associated probability tensor. Motivated by these findings, we propose a new collapsed Tucker class of tensor decompositions, which bridge existing PARAFAC and Tucker decompositions, providing a more flexible framework for parsimoniously characterizing multivariate categorical data. Taking a Bayesian approach to inference, we illustrate empirical advantages of the new decompositions. PMID:29332971

ANALYSIS, SELECTION AND RANKING OF FOREIGN MARKETS. A COMPREHENSIVE APPROACH

Directory of Open Access Journals (Sweden)

LIVIU NEAMŢU

2013-12-01

Full Text Available Choosing the appropriate markets for growth and development is essential for a company that wishes expanding businesses through international economic exchanges. But in this business case foreign markets research is not sufficient even though is an important chapter in the decision technology and an indispensable condition for achieving firm’s objectives. If in marketing on the national market this market is defined requiring no more than its prospection and segmentation, in the case of the international market outside the research process there is a need of a selection of markets and their classification. Companies that have this intention know little or nothing about the conditions offered by a new market or another. Therefore, they must go, step by step, through a complex analysis process, multilevel- type, composed of selection and ranking of markets followed by the proper research through exploration and segmentation, which can lead to choosing the most profitable markets. In this regard, within this study, we propose a multi-criteria model for selection and ranking of international development markets, allowing companies access to those markets which are in compliance with the company's development strategy.

Selective logging and damage to unharvested trees in a hyrcanian forest of Iran

OpenAIRE

Farshad Keivan Behjou; Omid Ghafarzade Mollabashi

2012-01-01

Selective logging in mature hardwood stands of Caspian forests often causes physical damage to residual trees through felling and skidding operations, resulting in a decline in bole quality and subsequent loss of tree value. This study evaluated the logging damage to residual trees following logging operations. A total density of 5.1 trees/ha and 17.3 m3/ha of wood were harvested. On average, 9.8 trees were damaged for every tree extracted, including 8 trees destroyed or severely damaged. The...

Refined reservoir description to maximize oil recovery

International Nuclear Information System (INIS)

Flewitt, W.E.

1975-01-01

To assure maximized oil recovery from older pools, reservoir description has been advanced by fully integrating original open-hole logs and the recently introduced interpretive techniques made available through cased-hole wireline saturation logs. A refined reservoir description utilizing normalized original wireline porosity logs has been completed in the Judy Creek Beaverhill Lake ''A'' Pool, a reefal carbonate pool with current potential productivity of 100,000 BOPD and 188 active wells. Continuous porosity was documented within a reef rim and cap while discontinuous porous lenses characterized an interior lagoon. With the use of pulsed neutron logs and production data a separate water front and pressure response was recognized within discrete environmental units. The refined reservoir description aided in reservoir simulation model studies and quantifying pool performance. A pattern water flood has now replaced the original peripheral bottom water drive to maximize oil recovery

Spatial and temporal dynamics of forest canopy gaps following selective logging in the eastern Amazon.

Science.gov (United States)

GREGORY P. ASNER; MICHAEL KELLER; JOSEN M. SILVA

2004-01-01

Selective logging is a dominant form of land use in the Amazon basin and throughout the humid tropics, yet little is known about the spatial variability of forest canopy gap formation and closure following timber harvests. We established chronosequences of large-area (14–158 ha) selective logging sites spanning a 3.5-year period of forest regeneration and two distinct...

Forest canopy damage and recovery in reduced-impact and conventional selective logging in eastern Para, Brazil.

Science.gov (United States)

Rodrigo Pereira Jr.; Johan Zweedea; Gregory P. Asnerb; Keller; Michael

2002-01-01

We investigated ground and canopy damage and recovery following conventional logging and reduced-impact logging (RIL) of moist tropical forest in the eastern Amazon of Brazil. Paired conventional and RIL blocks were selectively logged with a harvest intensity of approximately 23 m3 ha

Automated method for measuring the extent of selective logging damage with airborne LiDAR data

Science.gov (United States)

Melendy, L.; Hagen, S. C.; Sullivan, F. B.; Pearson, T. R. H.; Walker, S. M.; Ellis, P.; Kustiyo; Sambodo, Ari Katmoko; Roswintiarti, O.; Hanson, M. A.; Klassen, A. W.; Palace, M. W.; Braswell, B. H.; Delgado, G. M.

2018-05-01

Selective logging has an impact on the global carbon cycle, as well as on the forest micro-climate, and longer-term changes in erosion, soil and nutrient cycling, and fire susceptibility. Our ability to quantify these impacts is dependent on methods and tools that accurately identify the extent and features of logging activity. LiDAR-based measurements of these features offers significant promise. Here, we present a set of algorithms for automated detection and mapping of critical features associated with logging - roads/decks, skid trails, and gaps - using commercial airborne LiDAR data as input. The automated algorithm was applied to commercial LiDAR data collected over two logging concessions in Kalimantan, Indonesia in 2014. The algorithm results were compared to measurements of the logging features collected in the field soon after logging was complete. The automated algorithm-mapped road/deck and skid trail features match closely with features measured in the field, with agreement levels ranging from 69% to 99% when adjusting for GPS location error. The algorithm performed most poorly with gaps, which, by their nature, are variable due to the unpredictable impact of tree fall versus the linear and regular features directly created by mechanical means. Overall, the automated algorithm performs well and offers significant promise as a generalizable tool useful to efficiently and accurately capture the effects of selective logging, including the potential to distinguish reduced impact logging from conventional logging.

Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection

KAUST Repository

Chen, Lisha; Huang, Jianhua Z.

2012-01-01

and hence improves predictive accuracy. We propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty. We apply a group-lasso type penalty that treats each row of the matrix of the regression coefficients as a group

Timber production in selectively logged tropical forests in South America.

Science.gov (United States)

Michael Keller; Gregory P. Asner; Geoffrey Blate; Frank McGlocklin; John Merry; Marielos Peña-Claros; Johan Zweede

2007-01-01

Selective logging is an extensive land-use practice in South America. Governments in the region have enacted policies to promote the establishment and maintenance of economically productive and sustainable forest industries.However, both biological and policy constraints threaten to limit the viability of the industry over the long term.Biological constraints, such as...

Ranking and selection of commercial off-the-shelf using fuzzy distance based approach

Directory of Open Access Journals (Sweden)

Rakesh Garg

2015-06-01

Full Text Available There is a tremendous growth of the use of the component based software engineering (CBSE approach for the development of software systems. The selection of the best suited COTS components which fulfils the necessary requirement for the development of software(s has become a major challenge for the software developers. The complexity of the optimal selection problem increases with an increase in alternative potential COTS components and the corresponding selection criteria. In this research paper, the problem of ranking and selection of Data Base Management Systems (DBMS components is modeled as a multi-criteria decision making problem. A ‘Fuzzy Distance Based Approach (FDBA’ method is proposed for the optimal ranking and selection of DBMS COTS components of an e-payment system based on 14 selection criteria grouped under three major categories i.e. ‘Vendor Capabilities’, ‘Business Issues’ and ‘Cost’. The results of this method are compared with other Analytical Hierarchy Process (AHP which is termed as a typical multi-criteria decision making approach. The proposed methodology is explained with an illustrated example.

Hardwood log grades and lumber grade yields for factory lumber logs

Science.gov (United States)

Leland F. Hanks; Glenn L. Gammon; Robert L. Brisbin; Everette D. Rast

1980-01-01

The USDA Forest Service Standard Grades for Hardwood Factory Lumber Logs are described, and lumber grade yields for 16 species and 2 species groups are presented by log grade and log diameter. The grades enable foresters, log buyers, and log sellers to select and grade those log suitable for conversion into standard factory grade lumber. By using the apropriate lumber...

Monitoring selective logging in western Amazonia with repeat lidar flights

Science.gov (United States)

H.E. Andersen; S.E. Reutebuch; R.J. McGaughey; M.V.N. d' Oliveira; M. Keller

2014-01-01

The objective of this study was to test the use of repeat flight, airborne laser scanning data (lidar) for estimating changes associated with low-impact selective logging (approx. 10-15 m3 ha−1 = 5-7% of total standing volume harvested) in natural tropical forests in the Western Brazilian Amazon. Specifically, we investigated change in area...

Forest Fragmentation and Selective Logging Have Inconsistent Effects on Multiple Animal-Mediated Ecosystem Processes in a Tropical Forest

Science.gov (United States)

Schleuning, Matthias; Farwig, Nina; Peters, Marcell K.; Bergsdorf, Thomas; Bleher, Bärbel; Brandl, Roland; Dalitz, Helmut; Fischer, Georg; Freund, Wolfram; Gikungu, Mary W.; Hagen, Melanie; Garcia, Francisco Hita; Kagezi, Godfrey H.; Kaib, Manfred; Kraemer, Manfred; Lung, Tobias; Schaab, Gertrud; Templin, Mathias; Uster, Dana; Wägele, J. Wolfgang; Böhning-Gaese, Katrin

2011-01-01

Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the

Log-Optimal Portfolio Selection Using the Blackwell Approachability Theorem

OpenAIRE

V'yugin, Vladimir

2014-01-01

We present a method for constructing the log-optimal portfolio using the well-calibrated forecasts of market values. Dawid's notion of calibration and the Blackwell approachability theorem are used for computing well-calibrated forecasts. We select a portfolio using this "artificial" probability distribution of market values. Our portfolio performs asymptotically at least as well as any stationary portfolio that redistributes the investment at each round using a continuous function of side in...

F...ffccts of selective logging and exploitation of non-timber forest ...

African Journals Online (AJOL)

medicines, craft materials and rood, whose value is significant to the communities neighbouring the forest. This study examined the effects of selective logging on the Budongo torcst reserve. Answers were sought to the following questions: what were the effects ofselcctivc Jogging on species abundance, wood volume.

On the rigidity of rank gradient in a group of intermediate growth

OpenAIRE

Grigorchuk, Rostislav; Kravchenko, Rostyslav

2018-01-01

We introduce and investigate the rigidity property of rank gradient in the case of the group $\\mathcal G$ of intermediate growth constructed by the first author. We show that $\\mathcal G$ is normally $(f,g)$-RG rigid where $f(n)=\\log(n)$ and $g(n) =\\log(\\log(n)).$

Adiabatic quantum algorithm for search engine ranking.

Science.gov (United States)

Garnerone, Silvano; Zanardi, Paolo; Lidar, Daniel A

2012-06-08

We propose an adiabatic quantum algorithm for generating a quantum pure state encoding of the PageRank vector, the most widely used tool in ranking the relative importance of internet pages. We present extensive numerical simulations which provide evidence that this algorithm can prepare the quantum PageRank state in a time which, on average, scales polylogarithmically in the number of web pages. We argue that the main topological feature of the underlying web graph allowing for such a scaling is the out-degree distribution. The top-ranked log(n) entries of the quantum PageRank state can then be estimated with a polynomial quantum speed-up. Moreover, the quantum PageRank state can be used in "q-sampling" protocols for testing properties of distributions, which require exponentially fewer measurements than all classical schemes designed for the same task. This can be used to decide whether to run a classical update of the PageRank.

Impact of selective logging on inbreeding and gene dispersal in an Amazonian tree population of Carapa guianensis Aubl.

Science.gov (United States)

Cloutier, D; Kanashiro, M; Ciampi, A Y; Schoen, D J

2007-02-01

Selective logging may impact patterns of genetic diversity within populations of harvested forest tree species by increasing distances separating conspecific trees, and modifying physical and biotic features of the forest habitat. We measured levels of gene diversity, inbreeding, pollen dispersal and spatial genetic structure (SGS) of an Amazonian insect-pollinated Carapa guianensis population before and after commercial selective logging. Similar levels of gene diversity and allelic richness were found before and after logging in both the adult and the seed generations. Pre- and post-harvest outcrossing rates were high, and not significantly different from one another. We found no significant levels of biparental inbreeding either before or after logging. Low levels of pollen pool differentiation were found, and the pre- vs. post-harvest difference was not significant. Pollen dispersal distance estimates averaged between 75 m and 265 m before logging, and between 76 m and 268 m after logging, depending on the value of tree density and the dispersal model used. There were weak and similar levels of differentiation of allele frequencies in the adults and in the pollen pool, before and after logging occurred, as well as weak and similar pre- and post-harvest levels of SGS among adult trees. The large neighbourhood sizes estimated suggest high historical levels of gene flow. Overall our results indicate that there is no clear short-term genetic impact of selective logging on this population of C. guianensis.

Bayesian Plackett-Luce Mixture Models for Partially Ranked Data.

Science.gov (United States)

Mollica, Cristina; Tardella, Luca

2017-06-01

The elicitation of an ordinal judgment on multiple alternatives is often required in many psychological and behavioral experiments to investigate preference/choice orientation of a specific population. The Plackett-Luce model is one of the most popular and frequently applied parametric distributions to analyze rankings of a finite set of items. The present work introduces a Bayesian finite mixture of Plackett-Luce models to account for unobserved sample heterogeneity of partially ranked data. We describe an efficient way to incorporate the latent group structure in the data augmentation approach and the derivation of existing maximum likelihood procedures as special instances of the proposed Bayesian method. Inference can be conducted with the combination of the Expectation-Maximization algorithm for maximum a posteriori estimation and the Gibbs sampling iterative procedure. We additionally investigate several Bayesian criteria for selecting the optimal mixture configuration and describe diagnostic tools for assessing the fitness of ranking distributions conditionally and unconditionally on the number of ranked items. The utility of the novel Bayesian parametric Plackett-Luce mixture for characterizing sample heterogeneity is illustrated with several applications to simulated and real preference ranked data. We compare our method with the frequentist approach and a Bayesian nonparametric mixture model both assuming the Plackett-Luce model as a mixture component. Our analysis on real datasets reveals the importance of an accurate diagnostic check for an appropriate in-depth understanding of the heterogenous nature of the partial ranking data.

Hyper-local, directions-based ranking of places

DEFF Research Database (Denmark)

Venetis, Petros; Gonzalez, Hector; Jensen, Christian S.

2011-01-01

they are numerous and contain precise locations. Specifically, the paper proposes a framework that takes a user location and a collection of near-by places as arguments, producing a ranking of the places. The framework enables a range of aspects of directions queries to be exploited for the ranking of places......, including the frequency with which places have been referred to in directions queries. Next, the paper proposes an algorithm and accompanying data structures capable of ranking places in response to hyper-local web queries. Finally, an empirical study with very large directions query logs offers insight...... into the potential of directions queries for the ranking of places and suggests that the proposed algorithm is suitable for use in real web search engines....

Atlas ranking and selection for automatic segmentation of the esophagus from CT scans

Science.gov (United States)

Yang, Jinzhong; Haas, Benjamin; Fang, Raymond; Beadle, Beth M.; Garden, Adam S.; Liao, Zhongxing; Zhang, Lifei; Balter, Peter; Court, Laurence

2017-12-01

In radiation treatment planning, the esophagus is an important organ-at-risk that should be spared in patients with head and neck cancer or thoracic cancer who undergo intensity-modulated radiation therapy. However, automatic segmentation of the esophagus from CT scans is extremely challenging because of the structure’s inconsistent intensity, low contrast against the surrounding tissues, complex and variable shape and location, and random air bubbles. The goal of this study is to develop an online atlas selection approach to choose a subset of optimal atlases for multi-atlas segmentation to the delineate esophagus automatically. We performed atlas selection in two phases. In the first phase, we used the correlation coefficient of the image content in a cubic region between each atlas and the new image to evaluate their similarity and to rank the atlases in an atlas pool. A subset of atlases based on this ranking was selected, and deformable image registration was performed to generate deformed contours and deformed images in the new image space. In the second phase of atlas selection, we used Kullback-Leibler divergence to measure the similarity of local-intensity histograms between the new image and each of the deformed images, and the measurements were used to rank the previously selected atlases. Deformed contours were overlapped sequentially, from the most to the least similar, and the overlap ratio was examined. We further identified a subset of optimal atlases by analyzing the variation of the overlap ratio versus the number of atlases. The deformed contours from these optimal atlases were fused together using a modified simultaneous truth and performance level estimation algorithm to produce the final segmentation. The approach was validated with promising results using both internal data sets (21 head and neck cancer patients and 15 thoracic cancer patients) and external data sets (30 thoracic patients).

AUC-Maximizing Ensembles through Metalearning.

Science.gov (United States)

LeDell, Erin; van der Laan, Mark J; Petersen, Maya

2016-05-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

Feature selection model based on clustering and ranking in pipeline for microarray data

Directory of Open Access Journals (Sweden)

Barnali Sahu

2017-01-01

Full Text Available Most of the available feature selection techniques in the literature are classifier bound. It means a group of features tied to the performance of a specific classifier as applied in wrapper and hybrid approach. Our objective in this study is to select a set of generic features not tied to any classifier based on the proposed framework. This framework uses attribute clustering and feature ranking techniques in pipeline in order to remove redundant features. On each uncovered cluster, signal-to-noise ratio, t-statistics and significance analysis of microarray are independently applied to select the top ranked features. Both filter and evolutionary wrapper approaches have been considered for feature selection and the data set with selected features are given to ensemble of predefined statistically different classifiers. The class labels of the test data are determined using majority voting technique. Moreover, with the aforesaid objectives, this paper focuses on obtaining a stable result out of various classification models. Further, a comparative analysis has been performed to study the classification accuracy and computational time of the current approach and evolutionary wrapper techniques. It gives a better insight into the features and further enhancing the classification accuracy with less computational time.

Log-Linear Model Based Behavior Selection Method for Artificial Fish Swarm Algorithm

Directory of Open Access Journals (Sweden)

Zhehuang Huang

2015-01-01

Full Text Available Artificial fish swarm algorithm (AFSA is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

Log-linear model based behavior selection method for artificial fish swarm algorithm.

Science.gov (United States)

Huang, Zhehuang; Chen, Yidong

2015-01-01

Artificial fish swarm algorithm (AFSA) is a population based optimization technique inspired by social behavior of fishes. In past several years, AFSA has been successfully applied in many research and application areas. The behavior of fishes has a crucial impact on the performance of AFSA, such as global exploration ability and convergence speed. How to construct and select behaviors of fishes are an important task. To solve these problems, an improved artificial fish swarm algorithm based on log-linear model is proposed and implemented in this paper. There are three main works. Firstly, we proposed a new behavior selection algorithm based on log-linear model which can enhance decision making ability of behavior selection. Secondly, adaptive movement behavior based on adaptive weight is presented, which can dynamically adjust according to the diversity of fishes. Finally, some new behaviors are defined and introduced into artificial fish swarm algorithm at the first time to improve global optimization capability. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and reasonable convergence speed compared with the standard artificial fish swarm algorithm.

Implementation of preference ranking organization method for enrichment evaluation (Promethee) on selection system of student’s achievement

Science.gov (United States)

Karlitasari, L.; Suhartini, D.; Nurrosikawati, L.

2018-03-01

Selection of Student Achievement is conducted every year, starting from the level of Study Program, Faculty, to University, which then rank one will be sent to Kopertis level. The criteria made for the selection are Academic and Rich Scientific, Organizational, Personality, and English. In order for the selection of Student Achievement is Objective, then in addition to the presence of the jury is expected to use methods that support the decision to be more optimal in determining the Student Achievement. One method used is the Promethee Method. Preference Ranking Organization Method for Enrichment Evaluation (Promethee) is a method of ranking in Multi Criteria Decision Making (MCDM). PROMETHEE has the advantage that there is a preference type against the criteria that can take into account alternatives with other alternatives on the same criteria. The conjecture of alternate dominance over a criterion used in PROMETHEE is the use of values in the relationships between alternative ranking values. Based on the calculation result, from 7 applicants between Manual and Promethee Matrices, rank 1, 2, and 3, did not change, only 4 to 7 positions were changed. However, after the sensitivity test, almost all criteria experience a high level of sensitivity. Although it does not affect the students who will be sent to the next level, but can bring psychological impact on prospective student’s achievement

Selective logging: do rates of forest turnover in stems, species composition and functional traits decrease with time since disturbance? - A 45 year perspective.

Science.gov (United States)

Osazuwa-Peters, Oyomoare L; Jiménez, Iván; Oberle, Brad; Chapman, Colin A; Zanne, Amy E

2015-12-01

Selective logging, the targeted harvesting of timber trees in a single cutting cycle, is globally rising in extent and intensity. Short-term impacts of selective logging on tropical forests have been widely investigated, but long-term effects on temporal dynamics of forest structure and composition are largely unknown. Understanding these long-term dynamics will help determine whether tropical forests are resilient to selective logging and inform choices between competing demands of anthropogenic use versus conservation of tropical forests. Forest dynamics can be studied within the framework of succession theory, which predicts that temporal turnover rates should decline with time since disturbance. Here, we investigated the temporal dynamics of a tropical forest in Kibale National Park, Uganda over 45 years following selective logging. We estimated turnover rates in stems, species composition, and functional traits (wood density and diameter at breast height), using observations from four censuses in 1989, 1999, 2006, and 2013, of stems ≥ 10 cm diameter within 17 unlogged and 9 logged 200 × 10 m vegetation plots. We used null models to account for interdependencies among turnover rates in stems, species composition, and functional traits. We tested predictions that turnover rates should be higher and decrease with increasing time since the selective logging event in logged forest, but should be less temporally variable in unlogged forest. Overall, we found higher turnover rates in logged forest for all three attributes, but turnover rates did not decline through time in logged forest and was not less temporally variable in unlogged forest. These results indicate that successional models that assume recovery to pre-disturbance conditions are inadequate for predicting the effects of selective logging on the dynamics of the tropical forest in Kibale. Selective logging resulted in persistently higher turnover rates, which may compromise the carbon storage capacity

Application of the maximal covering location problem to habitat reserve site selection: a review

Science.gov (United States)

Stephanie A. Snyder; Robert G. Haight

2016-01-01

The Maximal Covering Location Problem (MCLP) is a classic model from the location science literature which has found wide application. One important application is to a fundamental problem in conservation biology, the Maximum Covering Species Problem (MCSP), which identifies land parcels to protect to maximize the number of species represented in the selected sites. We...

Algebraic and computational aspects of real tensor ranks

CERN Document Server

Sakata, Toshio; Miyazaki, Mitsuhiro

2016-01-01

This book provides comprehensive summaries of theoretical (algebraic) and computational aspects of tensor ranks, maximal ranks, and typical ranks, over the real number field. Although tensor ranks have been often argued in the complex number field, it should be emphasized that this book treats real tensor ranks, which have direct applications in statistics. The book provides several interesting ideas, including determinant polynomials, determinantal ideals, absolutely nonsingular tensors, absolutely full column rank tensors, and their connection to bilinear maps and Hurwitz-Radon numbers. In addition to reviews of methods to determine real tensor ranks in details, global theories such as the Jacobian method are also reviewed in details. The book includes as well an accessible and comprehensive introduction of mathematical backgrounds, with basics of positive polynomials and calculations by using the Groebner basis. Furthermore, this book provides insights into numerical methods of finding tensor ranks through...

A Family Longevity Selection Score: Ranking Sibships by Their Longevity, Size, and Availability for Study

DEFF Research Database (Denmark)

Sebastiani, Paola; Hadley, Evan C; Province, Michael

2009-01-01

Family studies of exceptional longevity can potentially identify genetic and other factors contributing to long life and healthy aging. Although such studies seek families that are exceptionally long lived, they also need living members who can provide DNA and phenotype information. On the basis...... of these considerations, the authors developed a metric to rank families for selection into a family study of longevity. Their measure, the family longevity selection score (FLoSS), is the sum of 2 components: 1) an estimated family longevity score built from birth-, gender-, and nation-specific cohort survival...... probabilities and 2) a bonus for older living siblings. The authors examined properties of FLoSS-based family rankings by using data from 3 ongoing studies: the New England Centenarian Study, the Framingham Heart Study, and screenees for the Long Life Family Study. FLoSS-based selection yields families...

Maximal supergravities and the E10 model

International Nuclear Information System (INIS)

Kleinschmidt, Axel; Nicolai, Hermann

2006-01-01

The maximal rank hyperbolic Kac-Moody algebra e 10 has been conjectured to play a prominent role in the unification of duality symmetries in string and M theory. We review some recent developments supporting this conjecture

Does selective logging stress tropical forest invertebrates? Using fat stores to examine sublethal responses in dung beetles.

Science.gov (United States)

França, Filipe; Barlow, Jos; Araújo, Bárbara; Louzada, Julio

2016-12-01

The increased global demand for tropical timber has driven vast expanses of tropical forests to be selectively logged worldwide. While logging impacts on wildlife are predicted to change species distribution and abundance, the underlying physiological responses are poorly understood. Although there is a growing consensus that selective logging impacts on natural populations start with individual stress-induced sublethal responses, this literature is dominated by investigations conducted with vertebrates from temperate zones. Moreover, the sublethal effects of human-induced forest disturbance on tropical invertebrates have never been examined. To help address this knowledge gap, we examined the body fat content and relative abundance of three dung beetle species (Coleoptera: Scarabaeinae) with minimum abundance of 40 individuals within each examined treatment level. These were sampled across 34 plots in a before-after control-impact design (BACI) in a timber concession area of the Brazilian Amazon. For the first time, we present evidence of logging-induced physiological stress responses in tropical invertebrates. Selective logging increased the individual levels of fat storage and reduced the relative abundance of two dung beetle species. Given this qualitative similarity, we support the measurement of body fat content as reliable biomarker to assess stress-induced sublethal effects on dung beetles. Understanding how environmental modification impacts the wildlife has never been more important. Our novel approach provides new insights into the mechanisms through which forest disturbances impose population-level impacts on tropical invertebrates.

Effects of Selective Logging on Birds in the Sierra de Coalcoman, Sierra Madre del Sur, Michoacan, Western Mexico

Science.gov (United States)

Jose Fernando Villaseñor; Neyra Sosa; Laura Villaseñor

2005-01-01

In order to determine the effects of selective logging on pine-oak forest?s bird communities in central-western Mexico, we gathered information through 10-min point counts in plots without wood extraction and sites logged at different times in the past (1, 4, and 8 years). We did not find evidences to argue for effects of logging on bird communities; the study plots...

Genetic structure and genetic diversity of Swietenia macrophylla in areas subjected to selective logging in Quintana Roo, Mexico

OpenAIRE

Alcalá, Raúl Ernesto; Cruz, Silvia De la; Gutiérrez-Granados, Gabriel

2015-01-01

The hypothesis that selective logging has a negative effect by altering the genetic parameters of tropical tree species was evaluated. The genetic diversity and genetic structure between adult trees (N = 47) and saplings (N = 50) of Swietenia macrophylla were contrasted within an area subjected to selective logging in the Mayan zone. Although differences in the number of alleles and in their frequencies were detected between both groups, the observed and expected heterozygosity and the coeffi...

Entropy-based gene ranking without selection bias for the predictive classification of microarray data

Directory of Open Access Journals (Sweden)

Serafini Maria

2003-11-01

Full Text Available Abstract Background We describe the E-RFE method for gene ranking, which is useful for the identification of markers in the predictive classification of array data. The method supports a practical modeling scheme designed to avoid the construction of classification rules based on the selection of too small gene subsets (an effect known as the selection bias, in which the estimated predictive errors are too optimistic due to testing on samples already considered in the feature selection process. Results With E-RFE, we speed up the recursive feature elimination (RFE with SVM classifiers by eliminating chunks of uninteresting genes using an entropy measure of the SVM weights distribution. An optimal subset of genes is selected according to a two-strata model evaluation procedure: modeling is replicated by an external stratified-partition resampling scheme, and, within each run, an internal K-fold cross-validation is used for E-RFE ranking. Also, the optimal number of genes can be estimated according to the saturation of Zipf's law profiles. Conclusions Without a decrease of classification accuracy, E-RFE allows a speed-up factor of 100 with respect to standard RFE, while improving on alternative parametric RFE reduction strategies. Thus, a process for gene selection and error estimation is made practical, ensuring control of the selection bias, and providing additional diagnostic indicators of gene importance.

Selective logging: do rates of forest turnover in stems, species composition and functional traits decrease with time since disturbance? – A 45 year perspective

Science.gov (United States)

Osazuwa-Peters, Oyomoare L.; Jiménez, Iván; Oberle, Brad; Chapman, Colin A.; Zanne, Amy E.

2015-01-01

Selective logging, the targeted harvesting of timber trees in a single cutting cycle, is globally rising in extent and intensity. Short-term impacts of selective logging on tropical forests have been widely investigated, but long-term effects on temporal dynamics of forest structure and composition are largely unknown. Understanding these long-term dynamics will help determine whether tropical forests are resilient to selective logging and inform choices between competing demands of anthropogenic use versus conservation of tropical forests. Forest dynamics can be studied within the framework of succession theory, which predicts that temporal turnover rates should decline with time since disturbance. Here, we investigated the temporal dynamics of a tropical forest in Kibale National Park, Uganda over 45 years following selective logging. We estimated turnover rates in stems, species composition, and functional traits (wood density and diameter at breast height), using observations from four censuses in 1989, 1999, 2006, and 2013, of stems ≥ 10 cm diameter within 17 unlogged and 9 logged 200 × 10 m vegetation plots. We used null models to account for interdependencies among turnover rates in stems, species composition, and functional traits. We tested predictions that turnover rates should be higher and decrease with increasing time since the selective logging event in logged forest, but should be less temporally variable in unlogged forest. Overall, we found higher turnover rates in logged forest for all three attributes, but turnover rates did not decline through time in logged forest and was not less temporally variable in unlogged forest. These results indicate that successional models that assume recovery to pre-disturbance conditions are inadequate for predicting the effects of selective logging on the dynamics of the tropical forest in Kibale. Selective logging resulted in persistently higher turnover rates, which may compromise the carbon storage capacity

Generation and relaxation of high rank coherences in AX3 systems in a selectively methionine labelled SH2 domain

International Nuclear Information System (INIS)

Kloiber, Karin; Fischer, Michael; Ledolter, Karin; Nagl, Michael; Schmid, Walther; Konrat, Robert

2007-01-01

The usefulness of selective isotope labelling patterns is demonstrated using the C-terminal SH2 domain of PLC-γ1 selectively 13 C labelled at methionine methyl groups. We demonstrate the generation and relaxation of coherences that are second rank in protons and first rank in carbons that derive from quadrupolar order in protons. The decay rates of second rank double quantum proton coherences are measured. These terms exhibit fewer channels for cross-correlated relaxation compared to single quantum coherences. Our results indicate the potential application of the measurement of high order proton coherences to the analysis of dynamics in methyl-bearing side chains

Convolutional Codes with Maximum Column Sum Rank for Network Streaming

OpenAIRE

Mahmood, Rafid; Badr, Ahmed; Khisti, Ashish

2015-01-01

The column Hamming distance of a convolutional code determines the error correction capability when streaming over a class of packet erasure channels. We introduce a metric known as the column sum rank, that parallels column Hamming distance when streaming over a network with link failures. We prove rank analogues of several known column Hamming distance properties and introduce a new family of convolutional codes that maximize the column sum rank up to the code memory. Our construction invol...

Effects of Force Field Selection on the Computational Ranking of MOFs for CO2 Separations.

Science.gov (United States)

Dokur, Derya; Keskin, Seda

2018-02-14

Metal-organic frameworks (MOFs) have been considered as highly promising materials for adsorption-based CO 2 separations. The number of synthesized MOFs has been increasing very rapidly. High-throughput molecular simulations are very useful to screen large numbers of MOFs in order to identify the most promising adsorbents prior to extensive experimental studies. Results of molecular simulations depend on the force field used to define the interactions between gas molecules and MOFs. Choosing the appropriate force field for MOFs is essential to make reliable predictions about the materials' performance. In this work, we performed two sets of molecular simulations using the two widely used generic force fields, Dreiding and UFF, and obtained adsorption data of CO 2 /H 2 , CO 2 /N 2 , and CO 2 /CH 4 mixtures in 100 different MOF structures. Using this adsorption data, several adsorbent evaluation metrics including selectivity, working capacity, sorbent selection parameter, and percent regenerability were computed for each MOF. MOFs were then ranked based on these evaluation metrics, and top performing materials were identified. We then examined the sensitivity of the MOF rankings to the force field type. Our results showed that although there are significant quantitative differences between some adsorbent evaluation metrics computed using different force fields, rankings of the top MOF adsorbents for CO 2 separations are generally similar: 8, 8, and 9 out of the top 10 most selective MOFs were found to be identical in the ranking for CO 2 /H 2 , CO 2 /N 2 , and CO 2 /CH 4 separations using Dreiding and UFF. We finally suggested a force field factor depending on the energy parameters of atoms present in the MOFs to quantify the robustness of the simulation results to the force field selection. This easily computable factor will be highly useful to determine whether the results are sensitive to the force field type or not prior to performing computationally demanding

A versatile curve-fit model for linear to deeply concave rank abundance curves

NARCIS (Netherlands)

Neuteboom, J.H.; Struik, P.C.

2005-01-01

A new, flexible curve-fit model for linear to concave rank abundance curves was conceptualized and validated using observational data. The model links the geometric-series model and log-series model and can also fit deeply concave rank abundance curves. The model is based ¿ in an unconventional way

Feature selection for splice site prediction: A new method using EDA-based feature ranking

Directory of Open Access Journals (Sweden)

Rouzé Pierre

2004-05-01

Full Text Available Abstract Background The identification of relevant biological features in large and complex datasets is an important step towards gaining insight in the processes underlying the data. Other advantages of feature selection include the ability of the classification system to attain good or even better solutions using a restricted subset of features, and a faster classification. Thus, robust methods for fast feature selection are of key importance in extracting knowledge from complex biological data. Results In this paper we present a novel method for feature subset selection applied to splice site prediction, based on estimation of distribution algorithms, a more general framework of genetic algorithms. From the estimated distribution of the algorithm, a feature ranking is derived. Afterwards this ranking is used to iteratively discard features. We apply this technique to the problem of splice site prediction, and show how it can be used to gain insight into the underlying biological process of splicing. Conclusion We show that this technique proves to be more robust than the traditional use of estimation of distribution algorithms for feature selection: instead of returning a single best subset of features (as they normally do this method provides a dynamical view of the feature selection process, like the traditional sequential wrapper methods. However, the method is faster than the traditional techniques, and scales better to datasets described by a large number of features.

A combined QSAR and partial order ranking approach to risk assessment.

Science.gov (United States)

Carlsen, L

2006-04-01

QSAR generated data appear as an attractive alternative to experimental data as foreseen in the proposed new chemicals legislation REACH. A preliminary risk assessment for the aquatic environment can be based on few factors, i.e. the octanol-water partition coefficient (Kow), the vapour pressure (VP) and the potential biodegradability of the compound in combination with the predicted no-effect concentration (PNEC) and the actual tonnage in which the substance is produced. Application of partial order ranking, allowing simultaneous inclusion of several parameters leads to a mutual prioritisation of the investigated substances, the prioritisation possibly being further analysed through the concept of linear extensions and average ranks. The ranking uses endpoint values (log Kow and log VP) derived from strictly linear 'noise-deficient' QSAR models as input parameters. Biodegradation estimates were adopted from the BioWin module of the EPI Suite. The population growth impairment of Tetrahymena pyriformis was used as a surrogate for fish lethality.

Carbon recovery dynamics following disturbance by selective logging in Amazonian forests

Science.gov (United States)

Piponiot, Camille; Sist, Plinio; Mazzei, Lucas; Peña-Claros, Marielos; Putz, Francis E; Rutishauser, Ervan; Shenkin, Alexander; Ascarrunz, Nataly; de Azevedo, Celso P; Baraloto, Christopher; França, Mabiane; Guedes, Marcelino; Honorio Coronado, Eurídice N; d'Oliveira, Marcus VN; Ruschel, Ademir R; da Silva, Kátia E; Doff Sotta, Eleneide; de Souza, Cintia R; Vidal, Edson; West, Thales AP; Hérault, Bruno

2016-01-01

When 2 Mha of Amazonian forests are disturbed by selective logging each year, more than 90 Tg of carbon (C) is emitted to the atmosphere. Emissions are then counterbalanced by forest regrowth. With an original modelling approach, calibrated on a network of 133 permanent forest plots (175 ha total) across Amazonia, we link regional differences in climate, soil and initial biomass with survivors’ and recruits’ C fluxes to provide Amazon-wide predictions of post-logging C recovery. We show that net aboveground C recovery over 10 years is higher in the Guiana Shield and in the west (21 ±3 Mg C ha-1) than in the south (12 ±3 Mg C ha-1) where environmental stress is high (low rainfall, high seasonality). We highlight the key role of survivors in the forest regrowth and elaborate a comprehensive map of post-disturbance C recovery potential in Amazonia. DOI: http://dx.doi.org/10.7554/eLife.21394.001 PMID:27993185

Long-term responses of populations and communities of trees to selective logging in tropical rain forests in Guyana

NARCIS (Netherlands)

Arets, E.J.M.M. (Eric Jacobus Monica Maria)

2005-01-01

Since only a small area of Guyana's forest can be effectively protected and because timber harvesting is an important source of income, logged forests will play an important role in the conservation of biodiversity in Guyana. Selective logging, in which only a few trees per hectare are harvested and

Empirical Bayes ranking and selection methods via semiparametric hierarchical mixture models in microarray studies.

Science.gov (United States)

Noma, Hisashi; Matsui, Shigeyuki

2013-05-20

The main purpose of microarray studies is screening of differentially expressed genes as candidates for further investigation. Because of limited resources in this stage, prioritizing genes are relevant statistical tasks in microarray studies. For effective gene selections, parametric empirical Bayes methods for ranking and selection of genes with largest effect sizes have been proposed (Noma et al., 2010; Biostatistics 11: 281-289). The hierarchical mixture model incorporates the differential and non-differential components and allows information borrowing across differential genes with separation from nuisance, non-differential genes. In this article, we develop empirical Bayes ranking methods via a semiparametric hierarchical mixture model. A nonparametric prior distribution, rather than parametric prior distributions, for effect sizes is specified and estimated using the "smoothing by roughening" approach of Laird and Louis (1991; Computational statistics and data analysis 12: 27-37). We present applications to childhood and infant leukemia clinical studies with microarrays for exploring genes related to prognosis or disease progression. Copyright © 2012 John Wiley & Sons, Ltd.

14 CFR 1214.1105 - Final ranking.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Final ranking. 1214.1105 Section 1214.1105... Recruitment and Selection Program § 1214.1105 Final ranking. Final rankings will be based on a combination of... preference will be included in this final ranking in accordance with applicable regulations. ...

Effects of selective logging on large mammal populations in a remote indigenous territory in the northern Peruvian Amazon

OpenAIRE

Pedro Mayor; Pedro Pérez-Peña; Mark Bowler; Pablo E. Puertas; Maire Kirkland; Richard Bodmer

2015-01-01

We examined the effects of selective timber logging carried out by local indigenous people in remote areas within indigenous territories on the mammal populations of the Yavari-Mirin River basin on the Peru-Brazil border. Recent findings show that habitat change in the study area is minimal, and any effect of logging activities on large mammal populations is highly likely to be the result of hunting associated with logging operations. We used hunting registers to estimate the monthly and year...

La competitividad logística en Latinoamérica: índice logístico vs. propuesta metodológica

Directory of Open Access Journals (Sweden)

Marco Alberto Valenzo Jiménez

2016-02-01

Full Text Available Este artículo muestra la situación actual de la competitividad logística en los países latinoamericanos, tomando como base el informe denominado “Connecting to Compite” (Trade Logistics in the Global Economy, 2007 del Banco Mundial. Este informe muestra el ranking de las posiciones que tienen los países latinoamericanos en materia de logística y en el cual se analizan las variables —aduanas, infraestructura, embarques internacionales, competencia logística, trazabilidad y seguimiento, costos logísticos domésticos y tiempo de entrega— que contiene la metodología utilizada por el Banco Mundial. La plataforma de estudio de este artículo parte del índice de competitividad logística, que, mediante la aplicación de la metodología “Valenzo – Martínez” permite analizar la base de datos de una manera más profunda, y da como resultado una escala de competitividad logística que nos muestra el nivel general de la competitividad logística en Latinoamérica, así como también el nivel de competitividad por variable, para, de esta manera, permitir una fácil interpretación de los resultados.

Optimizing Earth Data Search Ranking using Deep Learning and Real-time User Behaviour

Science.gov (United States)

Jiang, Y.; Yang, C. P.; Armstrong, E. M.; Huang, T.; Moroni, D. F.; McGibbney, L. J.; Greguska, F. R., III

2017-12-01

Finding Earth science data has been a challenging problem given both the quantity of data available and the heterogeneity of the data across a wide variety of domains. Current search engines in most geospatial data portals tend to induce end users to focus on one single data characteristic dimension (e.g., term frequency-inverse document frequency (TF-IDF) score, popularity, release date, etc.). This approach largely fails to take account of users' multidimensional preferences for geospatial data, and hence may likely result in a less than optimal user experience in discovering the most applicable dataset out of a vast range of available datasets. With users interacting with search engines, sufficient information is already hidden in the log files. Compared with explicit feedback data, information that can be derived/extracted from log files is virtually free and substantially more timely. In this dissertation, I propose an online deep learning framework that can quickly update the learning function based on real-time user clickstream data. The contributions of this framework include 1) a log processor that can ingest, process and create training data from web logs in a real-time manner; 2) a query understanding module to better interpret users' search intent using web log processing results and metadata; 3) a feature extractor that identifies ranking features representing users' multidimensional interests of geospatial data; and 4) a deep learning based ranking algorithm that can be trained incrementally using user behavior data. The search ranking results will be evaluated using precision at K and normalized discounted cumulative gain (NDCG).

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

International Nuclear Information System (INIS)

Eliazar, Iddo

2015-01-01

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars

Power-law and exponential rank distributions: A panoramic Gibbsian perspective

Energy Technology Data Exchange (ETDEWEB)

Eliazar, Iddo, E-mail: eliazar@post.tau.ac.il

2015-04-15

Rank distributions are collections of positive sizes ordered either increasingly or decreasingly. Many decreasing rank distributions, formed by the collective collaboration of human actions, follow an inverse power-law relation between ranks and sizes. This remarkable empirical fact is termed Zipf’s law, and one of its quintessential manifestations is the demography of human settlements — which exhibits a harmonic relation between ranks and sizes. In this paper we present a comprehensive statistical-physics analysis of rank distributions, establish that power-law and exponential rank distributions stand out as optimal in various entropy-based senses, and unveil the special role of the harmonic relation between ranks and sizes. Our results extend the contemporary entropy-maximization view of Zipf’s law to a broader, panoramic, Gibbsian perspective of increasing and decreasing power-law and exponential rank distributions — of which Zipf’s law is one out of four pillars.

Automated Detection of Selective Logging in Amazon Forests Using Airborne Lidar Data and Pattern Recognition Algorithms

Science.gov (United States)

Keller, M. M.; d'Oliveira, M. N.; Takemura, C. M.; Vitoria, D.; Araujo, L. S.; Morton, D. C.

2012-12-01

Selective logging, the removal of several valuable timber trees per hectare, is an important land use in the Brazilian Amazon and may degrade forests through long term changes in structure, loss of forest carbon and species diversity. Similar to deforestation, the annual area affected by selected logging has declined significantly in the past decade. Nonetheless, this land use affects several thousand km2 per year in Brazil. We studied a 1000 ha area of the Antimary State Forest (FEA) in the State of Acre, Brazil (9.304 ○S, 68.281 ○W) that has a basal area of 22.5 m2 ha-1 and an above-ground biomass of 231 Mg ha-1. Logging intensity was low, approximately 10 to 15 m3 ha-1. We collected small-footprint airborne lidar data using an Optech ALTM 3100EA over the study area once each in 2010 and 2011. The study area contained both recent and older logging that used both conventional and technologically advanced logging techniques. Lidar return density averaged over 20 m-2 for both collection periods with estimated horizontal and vertical precision of 0.30 and 0.15 m. A relative density model comparing returns from 0 to 1 m elevation to returns in 1-5 m elevation range revealed the pattern of roads and skid trails. These patterns were confirmed by ground-based GPS survey. A GIS model of the road and skid network was built using lidar and ground data. We tested and compared two pattern recognition approaches used to automate logging detection. Both segmentation using commercial eCognition segmentation and a Frangi filter algorithm identified the road and skid trail network compared to the GIS model. We report on the effectiveness of these two techniques.

Maximal Abelian sets of roots

CERN Document Server

Lawther, R

2018-01-01

In this work the author lets \\Phi be an irreducible root system, with Coxeter group W. He considers subsets of \\Phi which are abelian, meaning that no two roots in the set have sum in \\Phi \\cup \\{ 0 \\}. He classifies all maximal abelian sets (i.e., abelian sets properly contained in no other) up to the action of W: for each W-orbit of maximal abelian sets we provide an explicit representative X, identify the (setwise) stabilizer W_X of X in W, and decompose X into W_X-orbits. Abelian sets of roots are closely related to abelian unipotent subgroups of simple algebraic groups, and thus to abelian p-subgroups of finite groups of Lie type over fields of characteristic p. Parts of the work presented here have been used to confirm the p-rank of E_8(p^n), and (somewhat unexpectedly) to obtain for the first time the 2-ranks of the Monster and Baby Monster sporadic groups, together with the double cover of the latter. Root systems of classical type are dealt with quickly here; the vast majority of the present work con...

Time evolution of Wikipedia network ranking

Science.gov (United States)

Eom, Young-Ho; Frahm, Klaus M.; Benczúr, András; Shepelyansky, Dima L.

2013-12-01

We study the time evolution of ranking and spectral properties of the Google matrix of English Wikipedia hyperlink network during years 2003-2011. The statistical properties of ranking of Wikipedia articles via PageRank and CheiRank probabilities, as well as the matrix spectrum, are shown to be stabilized for 2007-2011. A special emphasis is done on ranking of Wikipedia personalities and universities. We show that PageRank selection is dominated by politicians while 2DRank, which combines PageRank and CheiRank, gives more accent on personalities of arts. The Wikipedia PageRank of universities recovers 80% of top universities of Shanghai ranking during the considered time period.

Well logging with natural gamma radiation

International Nuclear Information System (INIS)

Ellis, D.V.

1983-01-01

An invention is described for use in natural gamma radiation well logging in which measurements taken in a borehole are used in the search for valuable underground resources such as oil or gas. The invention comprises deriving a log of natural gamma radiation detected in selected energy windows for a selected borehole depth interval and converting it into a log of the selected subsurface materials, e.g. Th, U, K. This log is corrected for the effects of 1) either a gamma ray emitter in the borehole fluid, e.g. potassium salts and/or 2) a gamma ray attenuator in the borehole fluid, e.g. a strong attenuator such as barite and/or hematite. The Th, U, K log is particularly useful in the exploration of oil and gas resources since the Th, U, K concentrations are a good indication as to the presence, type and volume of shale and clay in the formations surrounding the borehole. (U.K.)

Long-term responses of rainforest erosional systems at different spatial scales to selective logging and climatic change

Science.gov (United States)

Walsh, R. P. D.; Bidin, K.; Blake, W. H.; Chappell, N. A.; Clarke, M. A.; Douglas, I.; Ghazali, R.; Sayer, A. M.; Suhaimi, J.; Tych, W.; Annammala, K. V.

2011-01-01

Long-term (21–30 years) erosional responses of rainforest terrain in the Upper Segama catchment, Sabah, to selective logging are assessed at slope, small and large catchment scales. In the 0.44 km2 Baru catchment, slope erosion measurements over 1990–2010 and sediment fingerprinting indicate that sediment sources 21 years after logging in 1989 are mainly road-linked, including fresh landslips and gullying of scars and toe deposits of 1994–1996 landslides. Analysis and modelling of 5–15 min stream-suspended sediment and discharge data demonstrate a reduction in storm-sediment response between 1996 and 2009, but not yet to pre-logging levels. An unmixing model using bed-sediment geochemical data indicates that 49 per cent of the 216 t km−2 a−1 2009 sediment yield comes from 10 per cent of its area affected by road-linked landslides. Fallout 210Pb and 137Cs values from a lateral bench core indicate that sedimentation rates in the 721 km2 Upper Segama catchment less than doubled with initially highly selective, low-slope logging in the 1980s, but rose 7–13 times when steep terrain was logged in 1992–1993 and 1999–2000. The need to keep steeplands under forest is emphasized if landsliding associated with current and predicted rises in extreme rainstorm magnitude-frequency is to be reduced in scale. PMID:22006973

Selecting Sums in Arrays

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Jørgensen, Allan Grønlund

2008-01-01

In an array of n numbers each of the \\binomn2+nUnknown control sequence '\\binom' contiguous subarrays define a sum. In this paper we focus on algorithms for selecting and reporting maximal sums from an array of numbers. First, we consider the problem of reporting k subarrays inducing the k largest...... sums among all subarrays of length at least l and at most u. For this problem we design an optimal O(n + k) time algorithm. Secondly, we consider the problem of selecting a subarray storing the k’th largest sum. For this problem we prove a time bound of Θ(n · max {1,log(k/n)}) by describing...... an algorithm with this running time and by proving a matching lower bound. Finally, we combine the ideas and obtain an O(n· max {1,log(k/n)}) time algorithm that selects a subarray storing the k’th largest sum among all subarrays of length at least l and at most u....

Selective logging in tropical forests decreases the robustness of liana-tree interaction networks to the loss of host tree species.

Science.gov (United States)

Magrach, Ainhoa; Senior, Rebecca A; Rogers, Andrew; Nurdin, Deddy; Benedick, Suzan; Laurance, William F; Santamaria, Luis; Edwards, David P

2016-03-16

Selective logging is one of the major drivers of tropical forest degradation, causing important shifts in species composition. Whether such changes modify interactions between species and the networks in which they are embedded remain fundamental questions to assess the 'health' and ecosystem functionality of logged forests. We focus on interactions between lianas and their tree hosts within primary and selectively logged forests in the biodiversity hotspot of Malaysian Borneo. We found that lianas were more abundant, had higher species richness, and different species compositions in logged than in primary forests. Logged forests showed heavier liana loads disparately affecting slow-growing tree species, which could exacerbate the loss of timber value and carbon storage already associated with logging. Moreover, simulation scenarios of host tree local species loss indicated that logging might decrease the robustness of liana-tree interaction networks if heavily infested trees (i.e. the most connected ones) were more likely to disappear. This effect is partially mitigated in the short term by the colonization of host trees by a greater diversity of liana species within logged forests, yet this might not compensate for the loss of preferred tree hosts in the long term. As a consequence, species interaction networks may show a lagged response to disturbance, which may trigger sudden collapses in species richness and ecosystem function in response to additional disturbances, representing a new type of 'extinction debt'. © 2016 The Author(s).

Selective logging in tropical forests decreases the robustness of liana–tree interaction networks to the loss of host tree species

Science.gov (United States)

Magrach, Ainhoa; Senior, Rebecca A.; Rogers, Andrew; Nurdin, Deddy; Benedick, Suzan; Laurance, William F.; Santamaria, Luis; Edwards, David P.

2016-01-01

Selective logging is one of the major drivers of tropical forest degradation, causing important shifts in species composition. Whether such changes modify interactions between species and the networks in which they are embedded remain fundamental questions to assess the ‘health’ and ecosystem functionality of logged forests. We focus on interactions between lianas and their tree hosts within primary and selectively logged forests in the biodiversity hotspot of Malaysian Borneo. We found that lianas were more abundant, had higher species richness, and different species compositions in logged than in primary forests. Logged forests showed heavier liana loads disparately affecting slow-growing tree species, which could exacerbate the loss of timber value and carbon storage already associated with logging. Moreover, simulation scenarios of host tree local species loss indicated that logging might decrease the robustness of liana–tree interaction networks if heavily infested trees (i.e. the most connected ones) were more likely to disappear. This effect is partially mitigated in the short term by the colonization of host trees by a greater diversity of liana species within logged forests, yet this might not compensate for the loss of preferred tree hosts in the long term. As a consequence, species interaction networks may show a lagged response to disturbance, which may trigger sudden collapses in species richness and ecosystem function in response to additional disturbances, representing a new type of ‘extinction debt’. PMID:26936241

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection.

Science.gov (United States)

Zhuang, Xiahai; Bai, Wenjia; Song, Jingjing; Zhan, Songhua; Qian, Xiaohua; Shi, Wenzhe; Lian, Yanyun; Rueckert, Daniel

2015-07-01

Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors' proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p ranking study, the proposed criterion based on conditional entropy yielded a performance curve with higher WHS Dice scores compared to the conventional schemes (p ranking algorithm and joint label fusion, the MAS scheme is able to generate accurate segmentation

A hybrid framework for reservoir characterization using fuzzy ranking and an artificial neural network

Science.gov (United States)

Wang, Baijie; Wang, Xin; Chen, Zhangxin

2013-08-01

Reservoir characterization refers to the process of quantitatively assigning reservoir properties using all available field data. Artificial neural networks (ANN) have recently been introduced to solve reservoir characterization problems dealing with the complex underlying relationships inherent in well log data. Despite the utility of ANNs, the current limitation is that most existing applications simply focus on directly implementing existing ANN models instead of improving/customizing them to fit the specific reservoir characterization tasks at hand. In this paper, we propose a novel intelligent framework that integrates fuzzy ranking (FR) and multilayer perceptron (MLP) neural networks for reservoir characterization. FR can automatically identify a minimum subset of well log data as neural inputs, and the MLP is trained to learn the complex correlations from the selected well log data to a target reservoir property. FR guarantees the selection of the optimal subset of representative data from the overall well log data set for the characterization of a specific reservoir property; and, this implicitly improves the modeling and predication accuracy of the MLP. In addition, a growing number of industrial agencies are implementing geographic information systems (GIS) in field data management; and, we have designed the GFAR solution (GIS-based FR ANN Reservoir characterization solution) system, which integrates the proposed framework into a GIS system that provides an efficient characterization solution. Three separate petroleum wells from southwestern Alberta, Canada, were used in the presented case study of reservoir porosity characterization. Our experiments demonstrate that our method can generate reliable results.

On the ranking of chemicals based on their PBT characteristics: comparison of different ranking methodologies using selected POPs as an illustrative example.

Science.gov (United States)

Sailaukhanuly, Yerbolat; Zhakupbekova, Arai; Amutova, Farida; Carlsen, Lars

2013-01-01

Knowledge of the environmental behavior of chemicals is a fundamental part of the risk assessment process. The present paper discusses various methods of ranking of a series of persistent organic pollutants (POPs) according to the persistence, bioaccumulation and toxicity (PBT) characteristics. Traditionally ranking has been done as an absolute (total) ranking applying various multicriteria data analysis methods like simple additive ranking (SAR) or various utility functions (UFs) based rankings. An attractive alternative to these ranking methodologies appears to be partial order ranking (POR). The present paper compares different ranking methods like SAR, UF and POR. Significant discrepancies between the rankings are noted and it is concluded that partial order ranking, as a method without any pre-assumptions concerning possible relation between the single parameters, appears as the most attractive ranking methodology. In addition to the initial ranking partial order methodology offers a wide variety of analytical tools to elucidate the interplay between the objects to be ranked and the ranking parameters. In the present study is included an analysis of the relative importance of the single P, B and T parameters. Copyright © 2012 Elsevier Ltd. All rights reserved.

Finding Maximal Pairs with Bounded Gap

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Lyngsø, Rune B.; Pedersen, Christian N. S.

1999-01-01

. In this paper we present methods for finding all maximal pairs under various constraints on the gap. In a string of length n we can find all maximal pairs with gap in an upper and lower bounded interval in time O(n log n+z) where z is the number of reported pairs. If the upper bound is removed the time reduces...... to O(n+z). Since a tandem repeat is a pair where the gap is zero, our methods can be seen as a generalization of finding tandem repeats. The running time of our methods equals the running time of well known methods for finding tandem repeats....

Bias and Stability of Single Variable Classifiers for Feature Ranking and Selection.

Science.gov (United States)

Fakhraei, Shobeir; Soltanian-Zadeh, Hamid; Fotouhi, Farshad

2014-11-01

Feature rankings are often used for supervised dimension reduction especially when discriminating power of each feature is of interest, dimensionality of dataset is extremely high, or computational power is limited to perform more complicated methods. In practice, it is recommended to start dimension reduction via simple methods such as feature rankings before applying more complex approaches. Single Variable Classifier (SVC) ranking is a feature ranking based on the predictive performance of a classifier built using only a single feature. While benefiting from capabilities of classifiers, this ranking method is not as computationally intensive as wrappers. In this paper, we report the results of an extensive study on the bias and stability of such feature ranking method. We study whether the classifiers influence the SVC rankings or the discriminative power of features themselves has a dominant impact on the final rankings. We show the common intuition of using the same classifier for feature ranking and final classification does not always result in the best prediction performance. We then study if heterogeneous classifiers ensemble approaches provide more unbiased rankings and if they improve final classification performance. Furthermore, we calculate an empirical prediction performance loss for using the same classifier in SVC feature ranking and final classification from the optimal choices.

Selection and ranking of patient video cases in paediatric neurology in relation to learner levels.

Science.gov (United States)

Balslev, Thomas; Muijtjens, Arno M M; Maarbjerg, Sabine Frølich; de Grave, Willem

2018-05-01

Teaching and learning with patient video cases may add authenticity, enhance diagnostic accuracy and improve chances of early diagnosis. The aim of this study is firstly to identify selection criteria for key Patient video cases (PVCs), secondly to identify trends in relevance of PVCs for learner levels and thirdly, to rank PVCs for learner levels. Based on a literature review, we identified criteria for key PVCs for use in paediatric neurology. We then performed a multi-round Delphi analysis to obtain agreement between 28 expert clinician teachers concerning key PVCs for four learner levels. We identified two major criteria: key PVCs should demonstrate key movements, and these movements should be subtle and/or difficult to note. The expert clinician teachers subsequently assessed a list of 14 topics for key PVCs. We found a clear, increasing trend in relevance scores, from medical students to young residents to experienced residents and specialists. For medical students and residents, epileptic spasms, Down syndrome, developmental delay, cerebral palsy and absence epilepsy were highly ranked. For specialists, conditions like chorea, focal seizures or eye movement disorders topped the ranking list, although ranking was less clear for this group of advanced learners. Key PVCs should demonstrate movements that are difficult to note for learners. Ranked lists of key PVCs for teaching and learning at different learner levels are now available and may help institutions build validated local libraries of PVCs. Copyright © 2017 European Paediatric Neurology Society. Published by Elsevier Ltd. All rights reserved.

A selective logging mechanism for hardware transactional memory systems

OpenAIRE

Lupon Navazo, Marc; Magklis, Grigorios; González Colás, Antonio María

2011-01-01

Log-based Hardware Transactional Memory (HTM) systems offer an elegant solution to handle speculative data that overflow transactional L1 caches. By keeping the pre-transactional values on a software-resident log, speculative values can be safely moved across the memory hierarchy, without requiring expensive searches on L1 misses or commits.

Influence of Lumber Volume Maximization on Value in Sawing Hardwood Sawlogs

Science.gov (United States)

Philip H. Steele; Francis G. Wagner; Lalit Kumar; Philip A. Araman

1992-01-01

Research based on applying volume-maximizing sawing solutions to idealized hardwood log forms has shown that average lumber yield can be increased by 6 percent. It is possible, however, that a lumber volume-maximizing solution may result in a decrease in lumber grade and a net reduction in total value of sawn lumber. The objective of this study was to determine the...

Analysis of RIA standard curve by log-logistic and cubic log-logit models

International Nuclear Information System (INIS)

Yamada, Hideo; Kuroda, Akira; Yatabe, Tami; Inaba, Taeko; Chiba, Kazuo

1981-01-01

In order to improve goodness-of-fit in RIA standard analysis, programs for computing log-logistic and cubic log-logit were written in BASIC using personal computer P-6060 (Olivetti). Iterative least square method of Taylor series was applied for non-linear estimation of logistic and log-logistic. Hear ''log-logistic'' represents Y = (a - d)/(1 + (log(X)/c)sup(b)) + d As weights either 1, 1/var(Y) or 1/σ 2 were used in logistic or log-logistic and either Y 2 (1 - Y) 2 , Y 2 (1 - Y) 2 /var(Y), or Y 2 (1 - Y) 2 /σ 2 were used in quadratic or cubic log-logit. The term var(Y) represents squares of pure error and σ 2 represents estimated variance calculated using a following equation log(σ 2 + 1) = log(A) + J log(y). As indicators for goodness-of-fit, MSL/S sub(e)sup(2), CMD% and WRV (see text) were used. Better regression was obtained in case of alpha-fetoprotein by log-logistic than by logistic. Cortisol standard curve was much better fitted with cubic log-logit than quadratic log-logit. Predicted precision of AFP standard curve was below 5% in log-logistic in stead of 8% in logistic analysis. Predicted precision obtained using cubic log-logit was about five times lower than that with quadratic log-logit. Importance of selecting good models in RIA data processing was stressed in conjunction with intrinsic precision of radioimmunoassay system indicated by predicted precision. (author)

A family longevity selection score: ranking sibships by their longevity, size, and availability for study.

Science.gov (United States)

Sebastiani, Paola; Hadley, Evan C; Province, Michael; Christensen, Kaare; Rossi, Winifred; Perls, Thomas T; Ash, Arlene S

2009-12-15

Family studies of exceptional longevity can potentially identify genetic and other factors contributing to long life and healthy aging. Although such studies seek families that are exceptionally long lived, they also need living members who can provide DNA and phenotype information. On the basis of these considerations, the authors developed a metric to rank families for selection into a family study of longevity. Their measure, the family longevity selection score (FLoSS), is the sum of 2 components: 1) an estimated family longevity score built from birth-, gender-, and nation-specific cohort survival probabilities and 2) a bonus for older living siblings. The authors examined properties of FLoSS-based family rankings by using data from 3 ongoing studies: the New England Centenarian Study, the Framingham Heart Study, and screenees for the Long Life Family Study. FLoSS-based selection yields families with exceptional longevity, satisfactory sibship sizes and numbers of living siblings, and high ages. Parameters in the FLoSS formula can be tailored for studies of specific populations or age ranges or with different conditions. The first component of the FLoSS also provides a conceptually sound survival measure to characterize exceptional longevity in individuals or families in various types of studies and correlates well with later-observed longevity.

Impacts of selective logging on inbreeding and gene flow in two Amazonian timber species with contrasting ecological and reproductive characteristics.

Science.gov (United States)

Vinson, C C; Kanashiro, M; Harris, S A; Boshier, D H

2015-01-01

Selective logging in Brazil allows for the removal of up to 90% of trees above 50 cm diameter of a given timber species, independent of a species' life history characteristics or how quickly it will recover. The genetic and demographic effects of selective logging on two Amazonian timber species (Dipteryx odorata Leguminosae, Jacaranda copaia Bignoniaceae) with contrasting ecological and reproductive characteristics were assessed in the same forest. Genetic diversity and gene flow were characterized by genotyping adults and seed sampled before and after logging, using hypervariable microsatellite markers. Overall, there were no short-term genetic impacts on the J. copaia population, with commercial application of current Brazilian forest management regulations. In contrast, for D. Odorata, selective logging showed a range of genetic impacts, with a 10% loss of alleles, and reductions in siring by pollen from trees within the 546-ha study area (23-11%) and in the number of pollen donors per progeny array (2.8-1.6), illustrating the importance of the surrounding landscape. Asynchrony in flowering between D. odorata trees led to trees with no breeding partners, which could limit the species reproduction and regeneration under current regulations. The results are summarized with other published studies from the same site and the implications for forest management discussed. The different types and levels of impacts associated with each species support the idea that ecological and genetic information by species, ecological guild or reproductive group is essential in helping to derive sustainable logging guidelines for tropical forests. © 2014 John Wiley & Sons Ltd.

To Make Good Decision: A Group DSS for Multiple Criteria Alternative Rank and Selection

Directory of Open Access Journals (Sweden)

Chen-Shu Wang

2015-01-01

Full Text Available Decision making is a recursive process and usually involves multiple decision criteria. However, such multiple criteria decision making may have a problem in which partial decision criteria may conflict with each other. An information technology, such as the decision support system (DSS and group DSS (GDSS, emerges to assist decision maker for decision-making process. Both the DSS and GDSS should integrate with a symmetrical approach to assist decision maker to take all decision criteria into consideration simultaneously. This study proposes a GDSS architecture named hybrid decision-making support model (HDMSM and integrated four decision approaches (Delphi, DEMATEL, ANP, and MDS to help decision maker to rank and select appropriate alternatives. The HDMSM consists of five steps, namely, criteria identification, criteria correlation calculation, criteria evaluation, critical criteria selection, and alternative rank and comparison. Finally, to validate the proposed feasibility of the proposed model, this study also conducts a case study to find out the important indexes of corporate social responsibility (CSR from multiple perspectives. As the case study demonstrates the proposed HDMSM enables a group of decision makers to implement the MCDM effectively and help them to analyze the relation and degree of mutual influence among different evaluation factors.

Sharp bounds on the ranks of negativity of certain sums

Indian Academy of Sciences (India)

with a finite rank of negativity k (i.e., k is the maximal dimension of any linear subspace ..... By linear algebra, we can choose a linear subspace E of L which is mapped ...... matics and its applications (Cambridge University Press) (1994) vol. 49.

Effects of selective logging on large mammal populations in a remote indigenous territory in the northern Peruvian Amazon

Directory of Open Access Journals (Sweden)

Pedro Mayor

2015-12-01

Full Text Available We examined the effects of selective timber logging carried out by local indigenous people in remote areas within indigenous territories on the mammal populations of the Yavari-Mirin River basin on the Peru-Brazil border. Recent findings show that habitat change in the study area is minimal, and any effect of logging activities on large mammal populations is highly likely to be the result of hunting associated with logging operations. We used hunting registers to estimate the monthly and yearly biomass extracted during timber operations and to calculate the catch per unit effort (CPUE in subsistence hunting in the community of Esperanza 2 to 5 years before logging activities started and 4 to 7 years after logging began. We also used line transects and the distance method to estimate animal densities before and after logging. We found that 1389 hunted animals and 27,459 kg of mammal biomass were extracted per year from logging concessions. CPUE for ungulates declined; however, it increased for other mammal orders, such as rodents and primates, indicating a shift to alternative prey items. Although collared peccaries (Pecari tajacu and tapirs (Tapirus terrestris may also have declined in numbers, this shift may have been caused by a possibly natural population crash in white-lipped peccaries (Tayassu pecari that coincided with the logging periods. We found no evidence that populations of primates were reduced by the logging activities. Because primates are sensitive to hunting, and their populations were of principal concern as logging commenced, this indicates that these forests remain of high conservation value. The unusual socioeconomic situation of these remote territories may mean that they are compatible with wildlife conservation in the Yavari-Mirin basin.

Log Analysis Using Splunk Hadoop Connect

Science.gov (United States)

2017-06-01

23 A. INPUT SELECTION ...Conversion Resource Consumption .............................................. 28 Figure 8. Distribution of Events in Years...running a logging service puts a performance tax on the system and may cause the degradation of performance. More thorough 8 logging will cause a

Discriminative Multi-View Interactive Image Re-Ranking.

Science.gov (United States)

Li, Jun; Xu, Chang; Yang, Wankou; Sun, Changyin; Tao, Dacheng

2017-07-01

Given an unreliable visual patterns and insufficient query information, content-based image retrieval is often suboptimal and requires image re-ranking using auxiliary information. In this paper, we propose a discriminative multi-view interactive image re-ranking (DMINTIR), which integrates user relevance feedback capturing users' intentions and multiple features that sufficiently describe the images. In DMINTIR, heterogeneous property features are incorporated in the multi-view learning scheme to exploit their complementarities. In addition, a discriminatively learned weight vector is obtained to reassign updated scores and target images for re-ranking. Compared with other multi-view learning techniques, our scheme not only generates a compact representation in the latent space from the redundant multi-view features but also maximally preserves the discriminative information in feature encoding by the large-margin principle. Furthermore, the generalization error bound of the proposed algorithm is theoretically analyzed and shown to be improved by the interactions between the latent space and discriminant function learning. Experimental results on two benchmark data sets demonstrate that our approach boosts baseline retrieval quality and is competitive with the other state-of-the-art re-ranking strategies.

Multiple graph regularized protein domain ranking.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-11-19

Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Feature Subset Selection and Instance Filtering for Cross-project Defect Prediction - Classification and Ranking

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Faimison Porto

2016-12-01

Full Text Available The defect prediction models can be a good tool on organizing the project's test resources. The models can be constructed with two main goals: 1 to classify the software parts - defective or not; or 2 to rank the most defective parts in a decreasing order. However, not all companies maintain an appropriate set of historical defect data. In this case, a company can build an appropriate dataset from known external projects - called Cross-project Defect Prediction (CPDP. The CPDP models, however, present low prediction performances due to the heterogeneity of data. Recently, Instance Filtering methods were proposed in order to reduce this heterogeneity by selecting the most similar instances from the training dataset. Originally, the similarity is calculated based on all the available dataset features (or independent variables. We propose that using only the most relevant features on the similarity calculation can result in more accurate filtered datasets and better prediction performances. In this study we extend our previous work. We analyse both prediction goals - Classification and Ranking. We present an empirical evaluation of 41 different methods by associating Instance Filtering methods with Feature Selection methods. We used 36 versions of 11 open source projects on experiments. The results show similar evidences for both prediction goals. First, the defect prediction performance of CPDP models can be improved by associating Feature Selection and Instance Filtering. Second, no evaluated method presented general better performances. Indeed, the most appropriate method can vary according to the characteristics of the project being predicted.

Logging utilization in Idaho: Current and past trends

Science.gov (United States)

Eric A. Simmons; Todd A. Morgan; Erik C. Berg; Stanley J. Zarnoch; Steven W. Hayes; Mike T. Thompson

2014-01-01

A study of commercial timber-harvesting activities in Idaho was conducted during 2008 and 2011 to characterize current tree utilization, logging operations, and changes from previous Idaho logging utilization studies. A two-stage simple random sampling design was used to select sites and felled trees for measurement within active logging sites. Thirty-three logging...

Sign rank versus Vapnik-Chervonenkis dimension

Science.gov (United States)

Alon, N.; Moran, Sh; Yehudayoff, A.

2017-12-01

This work studies the maximum possible sign rank of sign (N × N)-matrices with a given Vapnik-Chervonenkis dimension d. For d=1, this maximum is three. For d=2, this maximum is \\widetilde{\\Theta}(N1/2). For d >2, similar but slightly less accurate statements hold. The lower bounds improve on previous ones by Ben-David et al., and the upper bounds are novel. The lower bounds are obtained by probabilistic constructions, using a theorem of Warren in real algebraic topology. The upper bounds are obtained using a result of Welzl about spanning trees with low stabbing number, and using the moment curve. The upper bound technique is also used to: (i) provide estimates on the number of classes of a given Vapnik-Chervonenkis dimension, and the number of maximum classes of a given Vapnik-Chervonenkis dimension--answering a question of Frankl from 1989, and (ii) design an efficient algorithm that provides an O(N/log(N)) multiplicative approximation for the sign rank. We also observe a general connection between sign rank and spectral gaps which is based on Forster's argument. Consider the adjacency (N × N)-matrix of a Δ-regular graph with a second eigenvalue of absolute value λ and Δ ≤ N/2. We show that the sign rank of the signed version of this matrix is at least Δ/λ. We use this connection to prove the existence of a maximum class C\\subseteq\\{+/- 1\\}^N with Vapnik-Chervonenkis dimension 2 and sign rank \\widetilde{\\Theta}(N1/2). This answers a question of Ben-David et al. regarding the sign rank of large Vapnik-Chervonenkis classes. We also describe limitations of this approach, in the spirit of the Alon-Boppana theorem. We further describe connections to communication complexity, geometry, learning theory, and combinatorics. Bibliography: 69 titles.

Long-term impacts of selective logging on two Amazonian tree species with contrasting ecological and reproductive characteristics: inferences from Eco-gene model simulations.

Science.gov (United States)

Vinson, C C; Kanashiro, M; Sebbenn, A M; Williams, T C R; Harris, S A; Boshier, D H

2015-08-01

The impact of logging and subsequent recovery after logging is predicted to vary depending on specific life history traits of the logged species. The Eco-gene simulation model was used to evaluate the long-term impacts of selective logging over 300 years on two contrasting Brazilian Amazon tree species, Dipteryx odorata and Jacaranda copaia. D. odorata (Leguminosae), a slow growing climax tree, occurs at very low densities, whereas J. copaia (Bignoniaceae) is a fast growing pioneer tree that occurs at high densities. Microsatellite multilocus genotypes of the pre-logging populations were used as data inputs for the Eco-gene model and post-logging genetic data was used to verify the output from the simulations. Overall, under current Brazilian forest management regulations, there were neither short nor long-term impacts on J. copaia. By contrast, D. odorata cannot be sustainably logged under current regulations, a sustainable scenario was achieved by increasing the minimum cutting diameter at breast height from 50 to 100 cm over 30-year logging cycles. Genetic parameters were only slightly affected by selective logging, with reductions in the numbers of alleles and single genotypes. In the short term, the loss of alleles seen in J. copaia simulations was the same as in real data, whereas fewer alleles were lost in D. odorata simulations than in the field. The different impacts and periods of recovery for each species support the idea that ecological and genetic information are essential at species, ecological guild or reproductive group levels to help derive sustainable management scenarios for tropical forests.

Modelling tropical forests response to logging

Science.gov (United States)

Cazzolla Gatti, Roberto; Di Paola, Arianna; Valentini, Riccardo; Paparella, Francesco

2013-04-01

Tropical rainforests are among the most threatened ecosystems by large-scale fragmentation due to human activity such as heavy logging and agricultural clearance. Although, they provide crucial ecosystem goods and services, such as sequestering carbon from the atmosphere, protecting watersheds and conserving biodiversity. In several countries forest resource extraction has experienced a shift from clearcutting to selective logging to maintain a significant forest cover and understock of living biomass. However the knowledge on the short and long-term effects of removing selected species in tropical rainforest are scarce and need to be further investigated. One of the main effects of selective logging on forest dynamics seems to be the local disturbance which involve the invasion of open space by weed, vines and climbers at the expense of the late-successional state cenosis. We present a simple deterministic model that describes the dynamics of tropical rainforest subject to selective logging to understand how and why weeds displace native species. We argue that the selective removal of tallest tropical trees carries out gaps of light that allow weeds, vines and climbers to prevail on native species, inhibiting the possibility of recovery of the original vegetation. Our results show that different regime shifts may occur depending on the type of forest management adopted. This hypothesis is supported by a dataset of trees height and weed/vines cover that we collected from 9 plots located in Central and West Africa both in untouched and managed areas.

Results of mine logging in Sn-W prospectina in Cinovec deposit

International Nuclear Information System (INIS)

Kudrna, R.; Masek, K.; Pavlik, I.; Rejl, L.

1984-01-01

The method is suggested of indicating cassiterite ore mineralization in the Cinovec deposit by combining the methods of selective gamma-gamma logging and magnetic susceptibility logging. The estimate of the tin content was based on selective gamma-gamma logging. (B.S.)

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan

2012-11-19

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

KAUST Repository

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2012-01-01

Background: Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods.Results: To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods.Conclusion: The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications. 2012 Wang et al; licensee BioMed Central Ltd.

Multiple graph regularized protein domain ranking

Directory of Open Access Journals (Sweden)

Wang Jim

2012-11-01

Full Text Available Abstract Background Protein domain ranking is a fundamental task in structural biology. Most protein domain ranking methods rely on the pairwise comparison of protein domains while neglecting the global manifold structure of the protein domain database. Recently, graph regularized ranking that exploits the global structure of the graph defined by the pairwise similarities has been proposed. However, the existing graph regularized ranking methods are very sensitive to the choice of the graph model and parameters, and this remains a difficult problem for most of the protein domain ranking methods. Results To tackle this problem, we have developed the Multiple Graph regularized Ranking algorithm, MultiG-Rank. Instead of using a single graph to regularize the ranking scores, MultiG-Rank approximates the intrinsic manifold of protein domain distribution by combining multiple initial graphs for the regularization. Graph weights are learned with ranking scores jointly and automatically, by alternately minimizing an objective function in an iterative algorithm. Experimental results on a subset of the ASTRAL SCOP protein domain database demonstrate that MultiG-Rank achieves a better ranking performance than single graph regularized ranking methods and pairwise similarity based ranking methods. Conclusion The problem of graph model and parameter selection in graph regularized protein domain ranking can be solved effectively by combining multiple graphs. This aspect of generalization introduces a new frontier in applying multiple graphs to solving protein domain ranking applications.

Validating rankings in soccer championships

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Annibal Parracho Sant'Anna

2012-08-01

Full Text Available The final ranking of a championship is determined by quality attributes combined with other factors which should be filtered out of any decision on relegation or draft for upper level tournaments. Factors like referees' mistakes and difficulty of certain matches due to its accidental importance to the opponents should have their influence reduced. This work tests approaches to combine classification rules considering the imprecision of the number of points as a measure of quality and of the variables that provide reliable explanation for it. Two home-advantage variables are tested and shown to be apt to enter as explanatory variables. Independence between the criteria is checked against the hypothesis of maximal correlation. The importance of factors and of composition rules is evaluated on the basis of correlation between rank vectors, number of classes and number of clubs in tail classes. Data from five years of the Brazilian Soccer Championship are analyzed.

Identifying APT Malware Domain Based on Mobile DNS Logging

Directory of Open Access Journals (Sweden)

Weina Niu

2017-01-01

Full Text Available Advanced Persistent Threat (APT is a serious threat against sensitive information. Current detection approaches are time-consuming since they detect APT attack by in-depth analysis of massive amounts of data after data breaches. Specifically, APT attackers make use of DNS to locate their command and control (C&C servers and victims’ machines. In this paper, we propose an efficient approach to detect APT malware C&C domain with high accuracy by analyzing DNS logs. We first extract 15 features from DNS logs of mobile devices. According to Alexa ranking and the VirusTotal’s judgement result, we give each domain a score. Then, we select the most normal domains by the score metric. Finally, we utilize our anomaly detection algorithm, called Global Abnormal Forest (GAF, to identify malware C&C domains. We conduct a performance analysis to demonstrate that our approach is more efficient than other existing works in terms of calculation efficiency and recognition accuracy. Compared with Local Outlier Factor (LOF, k-Nearest Neighbor (KNN, and Isolation Forest (iForest, our approach obtains more than 99% F-M and R for the detection of C&C domains. Our approach not only can reduce data volume that needs to be recorded and analyzed but also can be applicable to unsupervised learning.

The Results of Complex Selective Logging in Beech-Hornbeam Tree Stands of the Greater Caucasus in Azerbaijan

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A. B. Yakhyaev

2014-06-01

Full Text Available The results of complex selective logging conducted in beech-hornbeam tree stands on the northeastern slope of the Greater Caucasus are analyzed in the paper. Experiments were carried out in two forestry districts, involving beech stands, comprising 2–3 units, with 30° slopes, in beech forests with woodruff, fescue and forb forest types. It has been revealed that for recovering the main tree species, as well as for increasing productivity and sustainability of the beech-hornbeam tree stands, which was spread out in the northern exposures, 2–3 repetitions of complex selective logging are recommended. It is recommended that in order to increase the amount of beech in the tree stand composition to 6–8 units in young stands and to 4–6 units at the slopes of south exposures, to complete 3–4 thinning operations, with the increasing beech share to 4–5 units in the upper story and in the undergrowth.

Evaluation of the osteoclastogenic process associated with RANK / RANK-L / OPG in odontogenic myxomas

Science.gov (United States)

González-Galván, María del Carmen; Mosqueda-Taylor, Adalberto; Bologna-Molina, Ronell; Setien-Olarra, Amaia; Marichalar-Mendia, Xabier; Aguirre-Urizar, José-Manuel

2018-01-01

Background Odontogenic myxoma (OM) is a benign intraosseous neoplasm that exhibits local aggressiveness and high recurrence rates. Osteoclastogenesis is an important phenomenon in the tumor growth of maxillary neoplasms. RANK (Receptor Activator of Nuclear Factor κappa B) is the signaling receptor of RANK-L (Receptor activator of nuclear factor kappa-Β ligand) that activates the osteoclasts. OPG (osteoprotegerin) is a decoy receptor for RANK-L that inhibits pro-osteoclastogenesis. The RANK / RANKL / OPG system participates in the regulation of osteolytic activity under normal conditions, and its alteration has been associated with greater bone destruction, and also with tumor growth. Objectives To analyze the immunohistochemical expression of OPG, RANK and RANK-L proteins in odontogenic myxomas (OMs) and their relationship with the tumor size. Material and Methods Eighteen OMs, 4 small ( 3cm) and 18 dental follicles (DF) that were included as control were studied by means of standard immunohistochemical procedure with RANK, RANKL and OPG antibodies. For the evaluation, 5 fields (40x) of representative areas of OM and DF were selected where the expression of each antibody was determined. Descriptive and comparative statistical analyses were performed with the obtained data. Results There are significant differences in the expression of RANK in OM samples as compared to DF (p = 0.022) and among the OMSs and OMLs (p = 0.032). Also a strong association is recognized in the expression of RANK-L and OPG in OM samples. Conclusions Activation of the RANK / RANK-L / OPG triad seems to be involved in the mechanisms of bone balance and destruction, as well as associated with tumor growth in odontogenic myxomas. Key words:Odontogenic myxoma, dental follicle, RANK, RANK-L, OPG, osteoclastogenesis. PMID:29680857

Selection of sugarcane mutants with resistance to red-rot disease, water-logging and delayed/non-flowering

Energy Technology Data Exchange (ETDEWEB)

Shaikh, M A.Q.; Shamsuzzaman, K M; Majid, M A; Howlider, M A.R.; Islam, M M [Institute of Nuclear Agriculture, Mymensingh (Bangladesh)

1997-07-01

Three batches of sugarcane cuttings were irradiated with gamma-rays in three different years for isolating mutants for delayed flowering, resistance to red-rot disease and water-logged conditions. In the first batch cuttings of cvs. `Isd-2/54`, `Latarijaba` and `Nagarbari` were irradiated with 20-40 Gy gamma-rays. In M{sub 1} V{sub 4} generation, 2,114 canes selected from inoculated M{sub 1}V{sub 3} generation, were re-inoculated with red-hot pathogen. Of these, four canes were resistant and 64 canes were moderately resistant to the disease. The M{sub 1}V{sub 5} generation of the selected clones was grown at two locations for selection. In the second batch, cuttings of cvs. `Isd-16`, `Isd-2/54`, `Nagarbari` and `Latarijaba` were irradiated with 20-60 Gy gamma-rays. The irradiated material was divided into three lots and each lot was put under different selection pressure. For isolating mutants with resistance to red-rot disease, 15,104 canes were artificially inoculated in the M{sub 1}V{sub 3}. Among these, one clone was resistant and 16 were moderately resistant. Of the 10,000 M{sub 1}V{sub 3} canes, grown under water-logged condition and selected for greenness of leaf at harvest, 38 canes were reasonably tolerant. For selecting late flowering mutants, about 8,500 canes were left in a field for a month after normal harvest; of these five showed late flowering. These mutants were grown for further selection in the M{sub 1}V{sub 4}. To screen out non-flowering canes, cvs. `I-291/87`, an early flowering types, and `I525/85`, a late flowering type were irradiated with 20-40 Gy gamma rays. M{sub 1}V{sub 3} generation has been grown in the field. (author). 13 refs, 6 tabs.

Centralizers of maximal regular subgroups in simple Lie groups and relative congruence classes of representations

Energy Technology Data Exchange (ETDEWEB)

Larouche, M [Departement de Mathematiques et Statistique, Universite de Montreal, 2920 chemin de la Tour, Montreal, Quebec H3T 1J4 (Canada); Lemire, F W [Department of Mathematics, University of Windsor, Windsor, Ontario (Canada); Patera, J, E-mail: larouche@dms.umontreal.ca, E-mail: lemire@uwindsor.ca, E-mail: patera@crm.umontreal.ca [Centre de Recherches Mathematiques, Universite de Montreal, CP 6128-Centre ville, Montreal, Quebec H3C 3J7 (Canada)

2011-10-14

In this paper, we present a new, uniform and comprehensive description of centralizers of the maximal regular subgroups in compact simple Lie groups of all types and ranks. The centralizer is either a direct product of finite cyclic groups, a continuous group of rank 1, or a product, not necessarily direct, of a continuous group of rank 1 with a finite cyclic group. Explicit formulas for the action of such centralizers on irreducible representations of the simple Lie algebras are given. (paper)

Multiatlas whole heart segmentation of CT data using conditional entropy for atlas ranking and selection

Energy Technology Data Exchange (ETDEWEB)

Zhuang, Xiahai, E-mail: zhuangxiahai@sjtu.edu.cn; Qian, Xiaohua [SJTU-CU International Cooperative Research Center, Department of Engineering Mechanics, School of Naval Architecture Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China); Bai, Wenjia; Shi, Wenzhe; Rueckert, Daniel [Biomedical Image Analysis Group, Department of Computing, Imperial College London, 180 Queens Gate, London SW7 2AZ (United Kingdom); Song, Jingjing; Zhan, Songhua [Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai 201203 (China); Lian, Yanyun [Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai 201210 (China)

2015-07-15

Purpose: Cardiac computed tomography (CT) is widely used in clinical diagnosis of cardiovascular diseases. Whole heart segmentation (WHS) plays a vital role in developing new clinical applications of cardiac CT. However, the shape and appearance of the heart can vary greatly across different scans, making the automatic segmentation particularly challenging. The objective of this work is to develop and evaluate a multiatlas segmentation (MAS) scheme using a new atlas ranking and selection algorithm for automatic WHS of CT data. Research on different MAS strategies and their influence on WHS performance are limited. This work provides a detailed comparison study evaluating the impacts of label fusion, atlas ranking, and sizes of the atlas database on the segmentation performance. Methods: Atlases in a database were registered to the target image using a hierarchical registration scheme specifically designed for cardiac images. A subset of the atlases were selected for label fusion, according to the authors’ proposed atlas ranking criterion which evaluated the performance of each atlas by computing the conditional entropy of the target image given the propagated atlas labeling. Joint label fusion was used to combine multiple label estimates to obtain the final segmentation. The authors used 30 clinical cardiac CT angiography (CTA) images to evaluate the proposed MAS scheme and to investigate different segmentation strategies. Results: The mean WHS Dice score of the proposed MAS method was 0.918 ± 0.021, and the mean runtime for one case was 13.2 min on a workstation. This MAS scheme using joint label fusion generated significantly better Dice scores than the other label fusion strategies, including majority voting (0.901 ± 0.276, p < 0.01), locally weighted voting (0.905 ± 0.0247, p < 0.01), and probabilistic patch-based fusion (0.909 ± 0.0249, p < 0.01). In the atlas ranking study, the proposed criterion based on conditional entropy yielded a performance curve

An intrinsic robust rank-one-approximation approach for currencyportfolio optimization

Directory of Open Access Journals (Sweden)

Hongxuan Huang

2018-03-01

Full Text Available A currency portfolio is a special kind of wealth whose value fluctuates with foreignexchange rates over time, which possesses 3Vs (volume, variety and velocity properties of big datain the currency market. In this paper, an intrinsic robust rank one approximation (ROA approachis proposed to maximize the value of currency portfolios over time. The main results of the paperinclude four parts: Firstly, under the assumptions about the currency market, the currency portfoliooptimization problem is formulated as the basic model, in which there are two types of variablesdescribing currency amounts in portfolios and the amount of each currency exchanged into another,respectively. Secondly, the rank one approximation problem and its variants are also formulated toapproximate a foreign exchange rate matrix, whose performance is measured by the Frobenius normor the 2-norm of a residual matrix. The intrinsic robustness of the rank one approximation is provedtogether with summarizing properties of the basic ROA problem and designing a modified powermethod to search for the virtual exchange rates hidden in a foreign exchange rate matrix. Thirdly,a technique for decision variables reduction is presented to attack the currency portfolio optimization.The reduced formulation is referred to as the ROA model, which keeps only variables describingcurrency amounts in portfolios. The optimal solution to the ROA model also induces a feasible solutionto the basic model of the currency portfolio problem by integrating forex operations from the ROAmodel with practical forex rates. Finally, numerical examples are presented to verify the feasibility ande ciency of the intrinsic robust rank one approximation approach. They also indicate that there existsan objective measure for evaluating and optimizing currency portfolios over time, which is related tothe virtual standard currency and independent of any real currency selected specially for measurement.

A multi-criteria decision-making approach to rank supplier selection criteria for hospital waste management: A case from Pakistan.

Science.gov (United States)

Ishtiaq, Palvisha; Khan, Sharfuddin Ahmed; Haq, Moiz-Ul

2018-04-01

To address environmental issues and cost effectiveness, waste management is necessary for healthcare facilities. Most importantly, segregation of hazardous and non-hazardous waste must be done as in many developing countries; disposal of both types of healthcare waste is done together, which is an unsafe practice. Waste generated in hospitals needs proper management to minimise hazards for patient and healthcare workers. At the same time, it is quite difficult for hospitals to find a systematic way to select appropriate suppliers for hospital waste management. Therefore, the purpose of this article is to identify, validate, and rank criteria that are essential for hospital waste management suppliers' selection. The analytical hierarchal process approach has been used and a survey from Pakistan's largest city (Karachi) has been considered to rank the most appropriate criteria that is necessary to select the supplier, especially in a developing country like Pakistan. Results show that waste management cost (45.5%) and suppliers' details (31.5%) are the top two main criteria for supplier selection; and storage cost (15.7%), waste handling cost (14.7%), and qualification of the suppliers (10.9%) are the top three most important overall sub-criteria for supplier selection for hospital waste management.

Relative importance of various regeneration mechanisms in different restoration stages of Quercus variabilis forest after selective logging

Directory of Open Access Journals (Sweden)

Yaoqin Xue

2014-08-01

Full Text Available Aim of study: Quercus variabilis (Chinese cork oak reproduces asexually and sexually. This study aimed to determine the status and growth of asexual and sexual recruits of Q. variabilis in different forest recovery stages.Area of study: Three selective logged stands and one unlogged stand in Q. variabilis forest, Shaanxi Province, China.Material and Methods: Origin, number, basal diameter, height and size structure of Q. variabilis shoots (height ≤200 cm were investigated in the plots of 5, 10, and 20-years post-logging stands and unlogged stand. Effects of recovery stage on the density and growth of the three original recruits (stump sprouts, stem base sprouts and true seedlings were analysis by One-way ANOVA.Main results: Sprouts dominated logged stands, whereas true seedlings dominated unlogged stand, stem base sprouts only existed in 20-years post-logging and unlogged stands. Stump sprout density and sprout number per stump both declined with extended post-logging time. True seedlings density increased from 7 to 20 shoots/100 m2 as the postlogging time extended, and peaked in unlogged stand (94 shoots/100 m2. An ongoing size structure was observed in true seedlings in all stands. Stump sprouts were taller and greater than true seedlings.Research highlights: Stump sprouts contributed more to Q. variabilis forest recovery in the early stage after disturbance. The contribution of true seedlings was limited in the same stage, but they were beneficial for population long-term development. Stem base sprouts were most likely to be a survival strategy rather than a reproductive strategy.Key words: asexual reproduction; true seedling; post-logging time; Chinese cork oak.

Selection and ranking of occupational safety indicators based on fuzzy AHP: A case study in road construction companies

Directory of Open Access Journals (Sweden)

Janackovic, Goran Lj.

2013-11-01

Full Text Available This paper presents the factors, performance, and indicators of occupational safety, as well as a method to select and rank occupational safety indicators based on the expert evaluation method and the fuzzy analytic hierarchy process (fuzzy AHP. A case study is done on road construction companies in Serbia. The key safety performance indicators for the road construction industry are identified and ranked according to the results of a survey that included experts who assessed occupational safety risks in these companies. The case study confirmed that organisational factors have a dominant effect on the quality of the occupational health and safety management system in Serbian road construction companies.

Control of Shareholders’ Wealth Maximization in Nigeria

OpenAIRE

A. O. Oladipupo; C. O. Okafor

2014-01-01

This research focuses on who controls shareholder’s wealth maximization and how does this affect firm’s performance in publicly quoted non-financial companies in Nigeria. The shareholder fund was the dependent while explanatory variables were firm size (proxied by log of turnover), retained earning (representing management control) and dividend payment (representing measure of shareholders control). The data used for this study were obtained from the Nigerian Stock Exchange [NSE] fact book an...

Geophysical log analysis of selected test and residential wells at the Shenandoah Road National Superfund Site, East Fishkill, Dutchess County, New York

Science.gov (United States)

Reynolds, Richard J.; Anderson, J. Alton; Williams, John H.

2015-01-01

The U.S. Geological Survey collected and analyzed geophysical logs from 20 test wells and 23 residential wells at the Shenandoah Road National Superfund Site in East Fishkill, New York, from 2006 through 2010 as part of an Interagency Agreement to provide hydrogeologic technical support to the U.S. Environmental Protection Agency, Region 2. The geophysical logs collected include caliper, gamma, acoustic and optical televiewer, deviation, electromagnetic-induction, magnetic-susceptibility, fluid-property, and flow under ambient and pumped conditions. The geophysical logs were analyzed along with single-well aquifer test data and drilling logs to characterize the lithology, fabric, fractures, and flow zones penetrated by the wells. The results of the geophysical log analysis were used as part of the hydrogeologic characterization of the site and in the design of discrete-zone monitoring installations in the test wells and selected residential wells.

Feature ranking and rank aggregation for automatic sleep stage classification: a comparative study.

Science.gov (United States)

Najdi, Shirin; Gharbali, Ali Abdollahi; Fonseca, José Manuel

2017-08-18

Nowadays, sleep quality is one of the most important measures of healthy life, especially considering the huge number of sleep-related disorders. Identifying sleep stages using polysomnographic (PSG) signals is the traditional way of assessing sleep quality. However, the manual process of sleep stage classification is time-consuming, subjective and costly. Therefore, in order to improve the accuracy and efficiency of the sleep stage classification, researchers have been trying to develop automatic classification algorithms. Automatic sleep stage classification mainly consists of three steps: pre-processing, feature extraction and classification. Since classification accuracy is deeply affected by the extracted features, a poor feature vector will adversely affect the classifier and eventually lead to low classification accuracy. Therefore, special attention should be given to the feature extraction and selection process. In this paper the performance of seven feature selection methods, as well as two feature rank aggregation methods, were compared. Pz-Oz EEG, horizontal EOG and submental chin EMG recordings of 22 healthy males and females were used. A comprehensive feature set including 49 features was extracted from these recordings. The extracted features are among the most common and effective features used in sleep stage classification from temporal, spectral, entropy-based and nonlinear categories. The feature selection methods were evaluated and compared using three criteria: classification accuracy, stability, and similarity. Simulation results show that MRMR-MID achieves the highest classification performance while Fisher method provides the most stable ranking. In our simulations, the performance of the aggregation methods was in the average level, although they are known to generate more stable results and better accuracy. The Borda and RRA rank aggregation methods could not outperform significantly the conventional feature ranking methods. Among

Timber tree regeneration along abandoned logging roads in a tropical Bolivian forest

DEFF Research Database (Denmark)

Nabe-Nielsen, J.; Severiche, W.; Fredericksen, T.

2007-01-01

Sustainable management of selectively logged tropical forests requires that felled trees are replaced through increased recruitment and growth. This study compares road track and roadside regeneration with regeneration in unlogged and selectively logged humid tropical forest in north-eastern Boli......Sustainable management of selectively logged tropical forests requires that felled trees are replaced through increased recruitment and growth. This study compares road track and roadside regeneration with regeneration in unlogged and selectively logged humid tropical forest in north......-eastern Bolivia. Some species benefited from increased light intensities on abandoned logging roads. Others benefited from low densities of competing vegetation on roads with compacted soils. This was the case for the small-seeded species Ficus boliviana C.C. Berg and Terminalia oblonga (Ruiz & Pav.) Steud. Some...

Reliability-based decision making for selection of ready-mix concrete supply using stochastic superiority and inferiority ranking method

International Nuclear Information System (INIS)

Chou, Jui-Sheng; Ongkowijoyo, Citra Satria

2015-01-01

Corporate competitiveness is heavily influenced by the information acquired, processed, utilized and transferred by professional staff involved in the supply chain. This paper develops a decision aid for selecting on-site ready-mix concrete (RMC) unloading type in decision making situations involving multiple stakeholders and evaluation criteria. The uncertainty of criteria weights set by expert judgment can be transformed in random ways based on the probabilistic virtual-scale method within a prioritization matrix. The ranking is performed by grey relational grade systems considering stochastic criteria weight based on individual preference. Application of the decision aiding model in actual RMC case confirms that the method provides a robust and effective tool for facilitating decision making under uncertainty. - Highlights: • This study models decision aiding method to assess ready-mix concrete unloading type. • Applying Monte Carlo simulation to virtual-scale method achieves a reliable process. • Individual preference ranking method enhances the quality of global decision making. • Robust stochastic superiority and inferiority ranking obtains reasonable results

Effect of selective logging on genetic diversity and gene flow in Cariniana legalis sampled from a cacao agroforestry system.

Science.gov (United States)

Leal, J B; Santos, R P; Gaiotto, F A

2014-01-28

The fragments of the Atlantic Forest of southern Bahia have a long history of intense logging and selective cutting. Some tree species, such as jequitibá rosa (Cariniana legalis), have experienced a reduction in their populations with respect to both area and density. To evaluate the possible effects of selective logging on genetic diversity, gene flow, and spatial genetic structure, 51 C. legalis individuals were sampled, representing the total remaining population from the cacao agroforestry system. A total of 120 alleles were observed from the 11 microsatellite loci analyzed. The average observed heterozygosity (0.486) was less than the expected heterozygosity (0.721), indicating a loss of genetic diversity in this population. A high fixation index (FIS = 0.325) was found, which is possibly due to a reduction in population size, resulting in increased mating among relatives. The maximum (1055 m) and minimum (0.095 m) distances traveled by pollen or seeds were inferred based on paternity tests. We found 36.84% of unique parents among all sampled seedlings. The progenitors of the remaining seedlings (63.16%) were most likely out of the sampled area. Positive and significant spatial genetic structure was identified in this population among classes 10 to 30 m away with an average coancestry coefficient between pairs of individuals of 0.12. These results suggest that the agroforestry system of cacao cultivation is contributing to maintaining levels of diversity and gene flow in the studied population, thus minimizing the effects of selective logging.

Treatment plan ranking using physical and biological indices

International Nuclear Information System (INIS)

Ebert, M. A.; University of Western Asutralia, WA

2001-01-01

Full text: The ranking of dose distributions is of importance in several areas such as i) comparing rival treatment plans, ii) comparing iterations in an optimisation routine, and iii) dose-assessment of clinical trial data. This study aimed to investigate the influence of choice of objective function in ranking tumour dose distributions. A series of physical (mean, maximum, minimum, standard deviation of dose) dose-volume histogram (DVH) reduction indices and biologically-based (tumour-control probability - TCP; equivalent uniform dose -EUD) indices were used to rank a series of hypothetical DVHs, as well as DVHs obtained from a series of 18 prostate patients. The distribution in ranking and change in distribution with change in indice parameters were investigated. It is found that not only is the ranking of DVHs dependent on the actual model used to perform the DVH reduction, it is also found to depend on the inherent characteristics of each model (i.e., selected parameters). The adjacent figure shows an example where the 18 prostate patients are ranked (grey-scale from black to white) by EUD when an α value of 0.8 Gy -1 is used in the model. The change of ranking as α varies is evident. Conclusion: This study has shown that the characteristics of the model selected in plan optimisation or DVH ranking will have an impact on the ranking obtained. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

Ranking oil viscosity in heavy-oil reservoirs

Energy Technology Data Exchange (ETDEWEB)

Bonnie, R.J.M. [Halliburton Energy Services, Calgary, AB (Canada); Seccombe, J. [BP Alaska, AK (United States)

2005-11-01

This paper discussed attempts to identify lower viscosity zones within the Ugnu formation at Milne Point field in Alaska through the use of Nuclear Magnetic Resonance (NMR) measurements. To date, only 1 well has been completed in the Ugnu, and BP Alaska is now engaged in studies to find ways to commercialize the formation. While geochemical analysis of oil samples extracted from sidewall cores has successfully identified sweet spots, the costs are prohibitive and they are too slow for real-time decision-making. NMR data acquisition offers a more economical, continuous and almost instantaneous alternative. Two wells were logged and analyzed using both logging while drilling (LWD) NMR and wire log (WL)-NMR tools. With the WL-NMR tool, data were collected in continuous passes and in a series of 45 minute stationary points, acquiring both routine T{sub 2} and diffusion editing data to predict oil viscosity. The LWD-NMR tool was set up to acquire T{sub 1} data when drilling. Forward modelling was used to generate NMR T{sub 2} spectra for reservoir parameters. The NMR logs indicate that the technology is a viable non-radioactive porosity measurement alternative. Data quality had high-vertical resolution and spectral resolution and showed good agreement with density-derived porosity. Zones with viscous oil were located and findings were validated by geochemical analyses. Bandwidth limitation was the only obstacle that prevented real time application of the NMR ranking process. 6 refs., 11 figs.

A multi-criteria analysis approach for ranking and selection of microorganisms for the production of oils for biodiesel production.

Science.gov (United States)

Ahmad, Farah B; Zhang, Zhanying; Doherty, William O S; O'Hara, Ian M

2015-08-01

Oleaginous microorganisms have potential to be used to produce oils as alternative feedstock for biodiesel production. Microalgae (Chlorella protothecoides and Chlorella zofingiensis), yeasts (Cryptococcus albidus and Rhodotorula mucilaginosa), and fungi (Aspergillus oryzae and Mucor plumbeus) were investigated for their ability to produce oil from glucose, xylose and glycerol. Multi-criteria analysis (MCA) using analytic hierarchy process (AHP) and preference ranking organization method for the enrichment of evaluations (PROMETHEE) with graphical analysis for interactive aid (GAIA), was used to rank and select the preferred microorganisms for oil production for biodiesel application. This was based on a number of criteria viz., oil concentration, content, production rate and yield, substrate consumption rate, fatty acids composition, biomass harvesting and nutrient costs. PROMETHEE selected A. oryzae, M. plumbeus and R. mucilaginosa as the most prospective species for oil production. However, further analysis by GAIA Webs identified A. oryzae and M. plumbeus as the best performing microorganisms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Efficient File Sharing by Multicast - P2P Protocol Using Network Coding and Rank Based Peer Selection

Science.gov (United States)

Stoenescu, Tudor M.; Woo, Simon S.

2009-01-01

In this work, we consider information dissemination and sharing in a distributed peer-to-peer (P2P highly dynamic communication network. In particular, we explore a network coding technique for transmission and a rank based peer selection method for network formation. The combined approach has been shown to improve information sharing and delivery to all users when considering the challenges imposed by the space network environments.

PADDLING PERFORMANCE AND RANKING POSITION IN JUNIOR SURFERS COMPETING AT THE ASSOCIATION OF SURFING PROFESSIONALS: A PILOT STUDY

Directory of Open Access Journals (Sweden)

Jesús Cámara

2011-11-01

Full Text Available Abstract  The aims of this pilot study are on one hand, to evaluate the upper body aerobic characteristics of junior surfers competing at the European branch of the Association of Surfing Professionals (ASP and on the other, to assess the relationship between the junior surfers' upper body aerobic characteristics and their ranking position. Ten surfers competing at the European junior branch of the ASP took part in the study. The maximal oxygen uptake (VO2MAX, the maximum power output (WMAX, the maximum lactate concentration [La]MAX, the maximum heart rate (HRMAX and the power output at the intensity where the lactate threshold and the onset of blood lactate accumulation are produced (WLT and WOBLA were determined during an incremental maximal test in a swim bench ergometer. It was observed a lack of a significant relationship between the ranking position and the parameters at maximal intensity (VO2PEAK, WMAX, HRMAX y [La]MAX. The WLT (W · kg-1 and the WOBLA (W · kg-1 were significantly related to ranking position (r= -0.69, p= 0.02; r= -0.72, p= 0.01, respectively.

A New Direction of Cancer Classification: Positive Effect of Low-Ranking MicroRNAs.

Science.gov (United States)

Li, Feifei; Piao, Minghao; Piao, Yongjun; Li, Meijing; Ryu, Keun Ho

2014-10-01

Many studies based on microRNA (miRNA) expression profiles showed a new aspect of cancer classification. Because one characteristic of miRNA expression data is the high dimensionality, feature selection methods have been used to facilitate dimensionality reduction. The feature selection methods have one shortcoming thus far: they just consider the problem of where feature to class is 1:1 or n:1. However, because one miRNA may influence more than one type of cancer, human miRNA is considered to be ranked low in traditional feature selection methods and are removed most of the time. In view of the limitation of the miRNA number, low-ranking miRNAs are also important to cancer classification. We considered both high- and low-ranking features to cover all problems (1:1, n:1, 1:n, and m:n) in cancer classification. First, we used the correlation-based feature selection method to select the high-ranking miRNAs, and chose the support vector machine, Bayes network, decision tree, k-nearest-neighbor, and logistic classifier to construct cancer classification. Then, we chose Chi-square test, information gain, gain ratio, and Pearson's correlation feature selection methods to build the m:n feature subset, and used the selected miRNAs to determine cancer classification. The low-ranking miRNA expression profiles achieved higher classification accuracy compared with just using high-ranking miRNAs in traditional feature selection methods. Our results demonstrate that the m:n feature subset made a positive impression of low-ranking miRNAs in cancer classification.

Selection Methods for Undergraduate Admissions in Australia. Does the Australian Predominate Entry Scheme the Australian Tertiary Admissions Rank (ATAR) Have a Future?

Science.gov (United States)

Blyth, Kathryn

2014-01-01

This article considers the Australian entry score system, the Australian Tertiary Admissions Rank (ATAR), and its usage as a selection mechanism for undergraduate places in Australian higher education institutions and asks whether its role as the main selection criterion will continue with the introduction of demand driven funding in 2012.…

An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in northern Mato Grosso, Brazilian Amazon

Science.gov (United States)

Grecchi, Rosana Cristina; Beuchle, René; Shimabukuro, Yosio Edemir; Aragão, Luiz E. O. C.; Arai, Egidio; Simonetti, Dario; Achard, Frédéric

2017-09-01

Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase of the

An integrated remote sensing and GIS approach for monitoring areas affected by selective logging: A case study in northern Mato Grosso, Brazilian Amazon.

Science.gov (United States)

Grecchi, Rosana Cristina; Beuchle, René; Shimabukuro, Yosio Edemir; Aragão, Luiz E O C; Arai, Egidio; Simonetti, Dario; Achard, Frédéric

2017-09-01

Forest cover disturbances due to processes such as logging and forest fires are a widespread issue especially in the tropics, and have heavily affected forest biomass and functioning in the Brazilian Amazon in the past decades. Satellite remote sensing has played a key role for assessing logging activities in this region; however, there are still remaining challenges regarding the quantification and monitoring of these processes affecting forested lands. In this study, we propose a new method for monitoring areas affected by selective logging in one of the hotspots of Mato Grosso state in the Brazilian Amazon, based on a combination of object-based and pixel-based classification approaches applied on remote sensing data. Logging intensity and changes over time are assessed within grid cells of 300 m × 300 m spatial resolution. Our method encompassed three main steps: (1) mapping forest/non-forest areas through an object-based classification approach applied to a temporal series of Landsat images during the period 2000-2015, (2) mapping yearly logging activities from soil fraction images on the same Landsat data series, and (3) integrating information from previous steps within a regular grid-cell of 300 m × 300 m in order to monitor disturbance intensities over this 15-years period. The overall accuracy of the baseline forest/non-forest mask (year 2000) and of the undisturbed vs disturbed forest (for selected years) were 93% and 84% respectively. Our results indicate that annual forest disturbance rates, mainly due to logging activities, were higher than annual deforestation rates during the whole period of study. The deforested areas correspond to circa 25% of the areas affected by forest disturbances. Deforestation rates were highest from 2001 to 2005 and then decreased considerably after 2006. In contrast, the annual forest disturbance rates show high temporal variability with a slow decrease over the 15-year period, resulting in a significant increase

Experience in well logging study of Eocene deposits at the territory of Central and West Azerbaijan

International Nuclear Information System (INIS)

Shilov, G.Ya.; Makhmudova, V.M.; Agabekova, L.A.

1989-01-01

Experience of investigation of Eocene deposits in Azerbaijan by well-logging methods (WLM), including gamma-logging (GL), neutron gamma-logging (NGL), gamma-gamma logging (GGL), is generalized. Clay rocks are characterized by the maximal NGL and GL values, tuff sandstones - by the average NGL values. NGL and GGL data are used to determine porosity of strata. Complex interpretation of WLM data enables to obtain reliable evaluations of lithology, porosity and oil saturation of Eocene rocks. Algorithm of quantitative interpretation of WLM materials is suggested. Efficiency of WLM interpretation was equal to 95 %. Since the suggested algorithm is formalized completely, it can be realized in systems of complex WLM interpretation by computer

Influence of deforestation, logging, and fire on malaria in the Brazilian Amazon.

Science.gov (United States)

Hahn, Micah B; Gangnon, Ronald E; Barcellos, Christovam; Asner, Gregory P; Patz, Jonathan A

2014-01-01

Malaria is a significant public health threat in the Brazilian Amazon. Previous research has shown that deforestation creates breeding sites for the main malaria vector in Brazil, Anopheles darlingi, but the influence of selective logging, forest fires, and road construction on malaria risk has not been assessed. To understand these impacts, we constructed a negative binomial model of malaria counts at the municipality level controlling for human population and social and environmental risk factors. Both paved and unpaved roadways and fire zones in a municipality increased malaria risk. Within the timber production states where 90% of deforestation has occurred, compared with areas without selective logging, municipalities where 0-7% of the remaining forests were selectively logged had the highest malaria risk (1.72, 95% CI 1.18-2.51), and areas with higher rates of selective logging had the lowest risk (0.39, 95% CI 0.23-0.67). We show that roads, forest fires, and selective logging are previously unrecognized risk factors for malaria in the Brazilian Amazon and highlight the need for regulation and monitoring of sub-canopy forest disturbance.

Development of regional stump-to-mill logging cost estimators

Science.gov (United States)

Chris B. LeDoux; John E. Baumgras

1989-01-01

Planning logging operations requires estimating the logging costs for the sale or tract being harvested. Decisions need to be made on equipment selection and its application to terrain. In this paper a methodology is described that has been developed and implemented to solve the problem of accurately estimating logging costs by region. The methodology blends field time...

Ranking and Mapping the Contributions by Overseas Chinese Strategy Scholars

DEFF Research Database (Denmark)

Li, Weiwen; Li, Peter Ping; Shu, Cheng

2015-01-01

The authors comment on an article by H. Jiao and colleagues regarding development of a ranking of overseas Chines strategy scholars in terms of their contributions to the strategy research. Topics include selection of 24 business journals ranked by the University of Texas at Dallas for their rese......The authors comment on an article by H. Jiao and colleagues regarding development of a ranking of overseas Chines strategy scholars in terms of their contributions to the strategy research. Topics include selection of 24 business journals ranked by the University of Texas at Dallas...... for their research; identifying authors who had published articles in periodicals such as "Management and Organization Review;" and development of a coding protocol and discussing coding procedure.....

Inclusive Fitness Maximization:An Axiomatic Approach

OpenAIRE

Okasha, Samir; Weymark, John; Bossert, Walter

2014-01-01

Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of qu...

Reconstructing Sessions from Data Discovery and Access Logs to Build a Semantic Knowledge Base for Improving Data Discovery

Directory of Open Access Journals (Sweden)

Yongyao Jiang

2016-04-01

Full Text Available Big geospatial data are archived and made available through online web discovery and access. However, finding the right data for scientific research and application development is still a challenge. This paper aims to improve the data discovery by mining the user knowledge from log files. Specifically, user web session reconstruction is focused upon in this paper as a critical step for extracting usage patterns. However, reconstructing user sessions from raw web logs has always been difficult, as a session identifier tends to be missing in most data portals. To address this problem, we propose two session identification methods, including time-clustering-based and time-referrer-based methods. We also present the workflow of session reconstruction and discuss the approach of selecting appropriate thresholds for relevant steps in the workflow. The proposed session identification methods and workflow are proven to be able to extract data access patterns for further pattern analyses of user behavior and improvement of data discovery for more relevancy data ranking, suggestion, and navigation.

Logging a roadside stand to protect scenic values

Science.gov (United States)

Philip M. McDonald; Raymond V. Whiteley

1972-01-01

A case study on the Challenge Experimental Forest, California, demonstrated that logging along roadsides need not despoil roadside stands. Nearly every tree was "viewed" before marking. Because of the "special-care" procedures followed, combined logging and slash-disposal cost was about twice that of a single-tree selection cut.

Inhibition of osteoclastogenesis by RNA interference targeting RANK

Directory of Open Access Journals (Sweden)

Ma Ruofan

2012-08-01

Full Text Available Abstract Background Osteoclasts and osteoblasts regulate bone resorption and formation to allow bone remodeling and homeostasis. The balance between bone resorption and formation is disturbed by abnormal recruitment of osteoclasts. Osteoclast differentiation is dependent on the receptor activator of nuclear factor NF-kappa B (RANK ligand (RANKL as well as the macrophage colony-stimulating factor (M-CSF. The RANKL/RANK system and RANK signaling induce osteoclast formation mediated by various cytokines. The RANK/RANKL pathway has been primarily implicated in metabolic, degenerative and neoplastic bone disorders or osteolysis. The central role of RANK/RANKL interaction in osteoclastogenesis makes RANK an attractive target for potential therapies in treatment of osteolysis. The purpose of this study was to assess the effect of inhibition of RANK expression in mouse bone marrow macrophages on osteoclast differentiation and bone resorption. Methods Three pairs of short hairpin RNAs (shRNA targeting RANK were designed and synthesized. The optimal shRNA was selected among three pairs of shRNAs by RANK expression analyzed by Western blot and Real-time PCR. We investigated suppression of osteoclastogenesis of mouse bone marrow macrophages (BMMs using the optimal shRNA by targeting RANK. Results Among the three shRANKs examined, shRANK-3 significantly suppressed [88.3%] the RANK expression (p Conclusions These findings suggest that retrovirus-mediated shRNA targeting RANK inhibits osteoclast differentiation and osteolysis. It may appear an attractive target for preventing osteolysis in humans with a potential clinical application.

Influence of deforestation, logging, and fire on malaria in the Brazilian Amazon.

Directory of Open Access Journals (Sweden)

Micah B Hahn

Full Text Available Malaria is a significant public health threat in the Brazilian Amazon. Previous research has shown that deforestation creates breeding sites for the main malaria vector in Brazil, Anopheles darlingi, but the influence of selective logging, forest fires, and road construction on malaria risk has not been assessed. To understand these impacts, we constructed a negative binomial model of malaria counts at the municipality level controlling for human population and social and environmental risk factors. Both paved and unpaved roadways and fire zones in a municipality increased malaria risk. Within the timber production states where 90% of deforestation has occurred, compared with areas without selective logging, municipalities where 0-7% of the remaining forests were selectively logged had the highest malaria risk (1.72, 95% CI 1.18-2.51, and areas with higher rates of selective logging had the lowest risk (0.39, 95% CI 0.23-0.67. We show that roads, forest fires, and selective logging are previously unrecognized risk factors for malaria in the Brazilian Amazon and highlight the need for regulation and monitoring of sub-canopy forest disturbance.

PageRank tracker: from ranking to tracking.

Science.gov (United States)

Gong, Chen; Fu, Keren; Loza, Artur; Wu, Qiang; Liu, Jia; Yang, Jie

2014-06-01

Video object tracking is widely used in many real-world applications, and it has been extensively studied for over two decades. However, tracking robustness is still an issue in most existing methods, due to the difficulties with adaptation to environmental or target changes. In order to improve adaptability, this paper formulates the tracking process as a ranking problem, and the PageRank algorithm, which is a well-known webpage ranking algorithm used by Google, is applied. Labeled and unlabeled samples in tracking application are analogous to query webpages and the webpages to be ranked, respectively. Therefore, determining the target is equivalent to finding the unlabeled sample that is the most associated with existing labeled set. We modify the conventional PageRank algorithm in three aspects for tracking application, including graph construction, PageRank vector acquisition and target filtering. Our simulations with the use of various challenging public-domain video sequences reveal that the proposed PageRank tracker outperforms mean-shift tracker, co-tracker, semiboosting and beyond semiboosting trackers in terms of accuracy, robustness and stability.

Remote sensing of selective logging in Amazonia Assessing limitations based on detailed field observations, Landsat ETM+, and textural analysis.

Science.gov (United States)

Gregory P. Asner; Michael Keller; Rodrigo Pereira; Johan C. Zweede

2002-01-01

We combined a detailed field study of forest canopy damage with calibrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) reflectance data and texture analysis to assess the sensitivity of basic broadband optical remote sensing to selective logging in Amazonia. Our field study encompassed measurements of ground damage and canopy gap fractions along a chronosequence of...

Analyzing Decision Logs to Understand Decision Making in Serious Crime Investigations.

Science.gov (United States)

Dando, Coral J; Ormerod, Thomas C

2017-12-01

Objective To study decision making by detectives when investigating serious crime through the examination of decision logs to explore hypothesis generation and evidence selection. Background Decision logs are used to record and justify decisions made during serious crime investigations. The complexity of investigative decision making is well documented, as are the errors associated with miscarriages of justice and inquests. The use of decision logs has not been the subject of an empirical investigation, yet they offer an important window into the nature of investigative decision making in dynamic, time-critical environments. Method A sample of decision logs from British police forces was analyzed qualitatively and quantitatively to explore hypothesis generation and evidence selection by police detectives. Results Analyses revealed diversity in documentation of decisions that did not correlate with case type and identified significant limitations of the decision log approach to supporting investigative decision making. Differences emerged between experienced and less experienced officers' decision log records in exploration of alternative hypotheses, generation of hypotheses, and sources of evidential inquiry opened over phase of investigation. Conclusion The practical use of decision logs is highly constrained by their format and context of use. Despite this, decision log records suggest that experienced detectives display strategic decision making to avoid confirmation and satisficing, which affect less experienced detectives. Application Potential applications of this research include both training in case documentation and the development of new decision log media that encourage detectives, irrespective of experience, to generate multiple hypotheses and optimize the timely selection of evidence to test them.

Recovery after 25 years of the tree and palms species diversity on a selectively logged forest in a Venezuelan lowland ecosystem

Energy Technology Data Exchange (ETDEWEB)

Lozada, J.R.; Arends, E.; Sánchez, D.; Villarreal, A.; Guevara, J.; Soriano, P.; Costa, M.

2016-07-01

Aim of the study: We evaluate palm and tree species diversity in a floodplain forest and the changes affecting the plots subjected to different intensities of selective logging. Area of study: The western alluvial plains of Venezuela. Materials and Methods: A randomized complete blocks design was established 25 years ago with three felling treatments (trees with diameter greater than 20 cm, 40 cm and 60 cm). Each treatment had three replications, using 1 ha permanent plots. We have measured all trees and palms bigger than over 10 cm in diameter. The data set was used to calculate the Importance Value Index of each species, the Shannon-Wiener index, the Hill Numbers and the Chao-Sørensen index. Main results: Disturbance increases the importance value index of pioneer species like Cecropia peltata, Ochroma pyramidale and Triplaris americana. All treatments produce changes on the floristic diversity but most of them are not significant. Only the high impact treatment causes a decrease in the species richness, but after 5 year of recovery this parameter is close to its previous levels (N0= 43.5). In logged forests, species loss (9.2%) is lower than in the control plots (11.7%) and is also lower than the rate of occurrence of species input (14.6%). Research highlights: In these logged forests restoration of diversity is acceptable because is higher than 91% (Chao-Sørensen index). Selective logging, with low and medium intensity, is a disturbance that works in a similar way to natural disturbances. All the diversity indexes recovered the pre-harvest level values. (Author)

Fates of trees damaged by logging in Amazonian Bolivia

NARCIS (Netherlands)

Shenkin, A.; Bolker, B.; Peña Claros, M.; Licona, J.C.; Putz, F.E.

2015-01-01

Estimation of carbon losses from trees felled and incidentally-killed during selective logging of tropical forests is relatively straightforward and well-documented, but less is known about the fates of collaterally-damaged trees that initially survive. Tree response to logging damage is an

CMLOG: A common message logging system

International Nuclear Information System (INIS)

Chen, J.; Akers, W.; Bickley, M.; Wu, D.; Watson, W. III

1997-01-01

The Common Message Logging (CMLOG) system is an object-oriented and distributed system that not only allows applications and systems to log data (messages) of any type into a centralized database but also lets applications view incoming messages in real-time or retrieve stored data from the database according to selection rules. It consists of a concurrent Unix server that handles incoming logging or searching messages, a Motif browser that can view incoming messages in real-time or display stored data in the database, a client daemon that buffers and sends logging messages to the server, and libraries that can be used by applications to send data to or retrieve data from the database via the server. This paper presents the design and implementation of the CMLOG system meanwhile it will also address the issue of integration of CMLOG into existing control systems. CMLOG into existing control systems

Ranking of bank branches with undesirable and fuzzy data: A DEA-based approach

Directory of Open Access Journals (Sweden)

Sohrab Kordrostami

2016-07-01

Full Text Available Banks are one of the most important financial sectors in order to the economic development of each country. Certainly, efficiency scores and ranks of banks are significant and effective aspects towards future planning. Sometimes the performance of banks must be measured in the presence of undesirable and vague factors. For these reasons in the current paper a procedure based on data envelopment analysis (DEA is introduced for evaluating the efficiency and complete ranking of decision making units (DMUs where undesirable and fuzzy measures exist. To illustrate, in the presence of undesirable and fuzzy measures, DMUs are evaluated by using a fuzzy expected value approach and DMUs with similar efficiency scores are ranked by using constraints and the Maximal Balance Index based on the optimal shadow prices. Afterwards, the efficiency scores of 25 branches of an Iranian commercial bank are evaluated using the proposed method. Also, a complete ranking of bank branches is presented to discriminate branches.

Laboratory- and Field-Based Assessment of Maximal Aerobic Power of Elite Stand-Up Paddle-Board Athletes.

Science.gov (United States)

Schram, Ben; Hing, Wayne; Climstein, Mike

2016-01-01

Stand-up paddle boarding (SUP) is a rapidly growing sport and recreational activity for which only anecdotal evidence exists on its proposed health, fitness, and injury-rehabilitation benefits. 10 internationally and nationally ranked elite SUP athletes. Participants were assessed for their maximal aerobic power on an ergometer in a laboratory and compared with other water-based athletes. Field-based assessments were subsequently performed using a portable gas-analysis system, and a correlation between the 2 measures was performed. Maximal aerobic power (relative) was significantly higher (P = .037) when measured in the field with a portable gas-analysis system (45.48 ± 6.96 mL · kg(-1) · min(-1)) than with laboratory-based metabolic-cart measurements (43.20 ± 6.67 mL · kg(-1) · min(-1)). There was a strong, positive correlation (r = .907) between laboratory and field maximal aerobic power results. Significantly higher (P = .000) measures of SUP paddling speed were found in the field than with the laboratory ergometer (+42.39%). There were no significant differences in maximal heart rate between the laboratory and field settings (P = .576). The results demonstrate the maximal aerobic power representative of internationally and nationally ranked SUP athletes and show that SUP athletes can be assessed for maximal aerobic power in the laboratory with high correlation to field-based measures. The field-based portable gas-analysis unit has a tendency to consistently measure higher oxygen consumption. Elite SUP athletes display aerobic power outputs similar to those of other upper-limb-dominant elite water-based athletes (surfing, dragon-boat racing, and canoeing).

Selection of suitable hand gestures for reliable myoelectric human computer interface.

Science.gov (United States)

Castro, Maria Claudia F; Arjunan, Sridhar P; Kumar, Dinesh K

2015-04-09

Myoelectric controlled prosthetic hand requires machine based identification of hand gestures using surface electromyogram (sEMG) recorded from the forearm muscles. This study has observed that a sub-set of the hand gestures have to be selected for an accurate automated hand gesture recognition, and reports a method to select these gestures to maximize the sensitivity and specificity. Experiments were conducted where sEMG was recorded from the muscles of the forearm while subjects performed hand gestures and then was classified off-line. The performances of ten gestures were ranked using the proposed Positive-Negative Performance Measurement Index (PNM), generated by a series of confusion matrices. When using all the ten gestures, the sensitivity and specificity was 80.0% and 97.8%. After ranking the gestures using the PNM, six gestures were selected and these gave sensitivity and specificity greater than 95% (96.5% and 99.3%); Hand open, Hand close, Little finger flexion, Ring finger flexion, Middle finger flexion and Thumb flexion. This work has shown that reliable myoelectric based human computer interface systems require careful selection of the gestures that have to be recognized and without such selection, the reliability is poor.

Journal Rankings by Health Management Faculty Members: Are There Differences by Rank, Leadership Status, or Area of Expertise?

Science.gov (United States)

Menachemi, Nir; Hogan, Tory H; DelliFraine, Jami L

2015-01-01

Health administration (HA) faculty members publish in a variety of journals, including journals focused on management, economics, policy, and information technology. HA faculty members are evaluated on the basis of the quality and quantity of their journal publications. However, it is unclear how perceptions of these journals vary by subdiscipline, department leadership role, or faculty rank. It is also not clear how perceptions of journals may have changed over the past decade since the last evaluation of journal rankings in the field was published. The purpose of the current study is to examine how respondents rank journals in the field of HA, as well as the variation in perception by academic rank, department leadership status, and area of expertise. Data were drawn from a survey of HA faculty members at U.S. universities, which was completed in 2012. Different journal ranking patterns were noted for faculty members of different subdisciplines. The health management-oriented journals (Health Care Management Review and Journal of Healthcare Management) were ranked higher than in previous research, suggesting that journal ranking perceptions may have changed over the intervening decade. Few differences in perceptions were noted by academic rank, but we found that department chairs were more likely than others to select Health Affairs in their top three most prestigious journals (β = 0.768; p journal prestige varied between a department chair and untenured faculty in different disciplines, and this perceived difference could have implications for promotion and tenure decisions.

Improved analysis of bacterial CGH data beyond the log-ratio paradigm

Directory of Open Access Journals (Sweden)

Aakra Ågot

2009-03-01

Full Text Available Abstract Background Existing methods for analyzing bacterial CGH data from two-color arrays are based on log-ratios only, a paradigm inherited from expression studies. We propose an alternative approach, where microarray signals are used in a different way and sequence identity is predicted using a supervised learning approach. Results A data set containing 32 hybridizations of sequenced versus sequenced genomes have been used to test and compare methods. A ROC-analysis has been performed to illustrate the ability to rank probes with respect to Present/Absent calls. Classification into Present and Absent is compared with that of a gaussian mixture model. Conclusion The results indicate our proposed method is an improvement of existing methods with respect to ranking and classification of probes, especially for multi-genome arrays.

A strong response to selection on mass-independent maximal metabolic rate without a correlated response in basal metabolic rate

DEFF Research Database (Denmark)

Wone, B W M; Madsen, Per; Donovan, E R

2015-01-01

Metabolic rates are correlated with many aspects of ecology, but how selection on different aspects of metabolic rates affects their mutual evolution is poorly understood. Using laboratory mice, we artificially selected for high maximal mass-independent metabolic rate (MMR) without direct selection...... on mass-independent basal metabolic rate (BMR). Then we tested for responses to selection in MMR and correlated responses to selection in BMR. In other lines, we antagonistically selected for mice with a combination of high mass-independent MMR and low mass-independent BMR. All selection protocols...... and data analyses included body mass as a covariate, so effects of selection on the metabolic rates are mass adjusted (that is, independent of effects of body mass). The selection lasted eight generations. Compared with controls, MMR was significantly higher (11.2%) in lines selected for increased MMR...

An intrinsic robust rank-one-approximation approach for currencyportfolio optimization

OpenAIRE

Hongxuan Huang; Zhengjun Zhang

2018-01-01

A currency portfolio is a special kind of wealth whose value fluctuates with foreignexchange rates over time, which possesses 3Vs (volume, variety and velocity) properties of big datain the currency market. In this paper, an intrinsic robust rank one approximation (ROA) approachis proposed to maximize the value of currency portfolios over time. The main results of the paperinclude four parts: Firstly, under the assumptions about the currency market, the currency portfoliooptimization problem ...

Pulsed radiation decay logging

International Nuclear Information System (INIS)

Mills, W.R. Jr.

1983-01-01

There are provided new and improved well logging processes and systems wherein the detection of secondary radiation is accomplished during a plurality of time windows in a manner to accurately characterize the decay rate of the secondary radiation. The system comprises a well logging tool having a primary pulsed radiation source which emits repetitive time-spaced bursts of primary radiation and detector means for detecting secondary radiation resulting from the primary radiation and producing output signals in response to the detected radiation. A plurality of measuring channels are provided, each of which produces a count rate function representative of signals received from the detector means during successive time windows occurring between the primary radiation bursts. The logging system further comprises means responsive to the measuring channels for producing a plurality of functions representative of the ratios of the radiation count rates measured during adjacent pairs of the time windows. Comparator means function to compare the ratio functions and select at least one of the ratio functions to generate a signal representative of the decay rate of the secondary radiation

Who's #1? The Science of Rating and Ranking

CERN Document Server

Langville, Amy N

2012-01-01

A website's ranking on Google can spell the difference between success and failure for a new business. NCAA football ratings determine which schools get to play for the big money in postseason bowl games. Product ratings influence everything from the clothes we wear to the movies we select on Netflix. Ratings and rankings are everywhere, but how exactly do they work? Who's #1? offers an engaging and accessible account of how scientific rating and ranking methods are created and applied to a variety of uses. Amy Langville and Carl Meyer provide the first comprehensive overview of the mathemat

Augmenting the Deliberative Method for Ranking Risks.

Science.gov (United States)

Susel, Irving; Lasley, Trace; Montezemolo, Mark; Piper, Joel

2016-01-01

The Department of Homeland Security (DHS) characterized and prioritized the physical cross-border threats and hazards to the nation stemming from terrorism, market-driven illicit flows of people and goods (illegal immigration, narcotics, funds, counterfeits, and weaponry), and other nonmarket concerns (movement of diseases, pests, and invasive species). These threats and hazards pose a wide diversity of consequences with very different combinations of magnitudes and likelihoods, making it very challenging to prioritize them. This article presents the approach that was used at DHS to arrive at a consensus regarding the threats and hazards that stand out from the rest based on the overall risk they pose. Due to time constraints for the decision analysis, it was not feasible to apply multiattribute methodologies like multiattribute utility theory or the analytic hierarchy process. Using a holistic approach was considered, such as the deliberative method for ranking risks first published in this journal. However, an ordinal ranking alone does not indicate relative or absolute magnitude differences among the risks. Therefore, the use of the deliberative method for ranking risks is not sufficient for deciding whether there is a material difference between the top-ranked and bottom-ranked risks, let alone deciding what the stand-out risks are. To address this limitation of ordinal rankings, the deliberative method for ranking risks was augmented by adding an additional step to transform the ordinal ranking into a ratio scale ranking. This additional step enabled the selection of stand-out risks to help prioritize further analysis. © 2015 Society for Risk Analysis.

On the dimension of subspaces with bounded Schmidt rank

International Nuclear Information System (INIS)

Cubitt, Toby; Montanaro, Ashley; Winter, Andreas

2008-01-01

We consider the question of how large a subspace of a given bipartite quantum system can be when the subspace contains only highly entangled states. This is motivated in part by results of Hayden et al. [e-print arXiv:quant-ph/0407049; Commun. Math. Phys., 265, 95 (2006)], which show that in large dxd-dimensional systems there exist random subspaces of dimension almost d 2 , all of whose states have entropy of entanglement at least log d-O(1). It is also a generalization of results on the dimension of completely entangled subspaces, which have connections with the construction of unextendible product bases. Here we take as entanglement measure the Schmidt rank, and determine, for every pair of local dimensions d A and d B , and every r, the largest dimension of a subspace consisting only of entangled states of Schmidt rank r or larger. This exact answer is a significant improvement on the best bounds that can be obtained using the random subspace techniques in Hayden et al. We also determine the converse: the largest dimension of a subspace with an upper bound on the Schmidt rank. Finally, we discuss the question of subspaces containing only states with Schmidt equal to r

ADN* Density log estimation Using Rockcell*

International Nuclear Information System (INIS)

Okuku, C.; Iloghalu, Emeka. M.; Omotayo, O.

2003-01-01

This work is intended to inform on the possibilities of estimating good density data in zones associated with sliding in a reservoir with ADN* tool with or without ADOS in string in cases where repeat sections were not done, possibly due to hole stability or directional concerns. This procedure has been equally used to obtain a better density data in corkscrew holes. Density data (ROBB) was recomputed using neural network in RockCell* to estimate the density over zones of interest. RockCell* is a Schlumberger software that has neural network functionally which can be used to estimate missing logs using the combination of the responses of other log curves and intervals that are not affected by sliding. In this work, an interval was selected and within this interval twelve litho zones were defined using the unsupervised neural network. From this a training set was selected based on intervals of very good log responses outside the sliding zones. This training set was used to train and run the neural network for a specific lithostratigraphic interval. The results matched the known good density curve. Then after this, an estimation of the density curve was done using the supervised neural network. The output from this estimation matched very closely in the good portions of the log, thus providing some density measurements in the sliding zone. This methodology provides a scientific solution to missing data during the process of Formation evaluation

Positioning Open Access Journals in a LIS Journal Ranking

Science.gov (United States)

Xia, Jingfeng

2012-01-01

This research uses the h-index to rank the quality of library and information science journals between 2004 and 2008. Selected open access (OA) journals are included in the ranking to assess current OA development in support of scholarly communication. It is found that OA journals have gained momentum supporting high-quality research and…

Inclusive fitness maximization: An axiomatic approach.

Science.gov (United States)

Okasha, Samir; Weymark, John A; Bossert, Walter

2014-06-07

Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of quasi-inclusive fitness maximization can be derived from axioms on an individual׳s 'as if preferences' (binary choices) for the case in which phenotypic effects are additive. Our results help integrate evolutionary theory and rational choice theory, help draw out the behavioural implications of inclusive fitness maximization, and point to a possible way in which evolution could lead organisms to implement it. Copyright © 2014 Elsevier Ltd. All rights reserved.

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

Science.gov (United States)

Gibbs, David L; Shmulevich, Ilya

2017-06-01

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle

Science.gov (United States)

Shmulevich, Ilya

2017-01-01

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf. PMID:28628618

Solving the influence maximization problem reveals regulatory organization of the yeast cell cycle.

Directory of Open Access Journals (Sweden)

David L Gibbs

2017-06-01

Full Text Available The Influence Maximization Problem (IMP aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. By picking a set of source nodes, a diffusion process covers a portion of the network. The size of the network cover relates to the influence of the source nodes. The set of nodes that maximizes influence is the solution to the IMP. By solving the IMP over different numbers of source nodes, an influence ranking on genes was produced. The influence ranking was compared to other metrics of network centrality. Although the top genes from each centrality ranking contained well-known cell cycle regulators, there was little agreement and no clear winner. However, it was found that influential genes tend to directly regulate or sit upstream of genes ranked by other centrality measures. The influential nodes act as critical sources of information flow, potentially having a large impact on the state of the network. Biological events that affect influential nodes and thereby affect information flow could have a strong effect on network dynamics, potentially leading to disease. Code and data can be found at: https://github.com/gibbsdavidl/miergolf.

PageRank and rank-reversal dependence on the damping factor

Science.gov (United States)

Son, S.-W.; Christensen, C.; Grassberger, P.; Paczuski, M.

2012-12-01

PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d0=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d0.

PageRank and rank-reversal dependence on the damping factor.

Science.gov (United States)

Son, S-W; Christensen, C; Grassberger, P; Paczuski, M

2012-12-01

PageRank (PR) is an algorithm originally developed by Google to evaluate the importance of web pages. Considering how deeply rooted Google's PR algorithm is to gathering relevant information or to the success of modern businesses, the question of rank stability and choice of the damping factor (a parameter in the algorithm) is clearly important. We investigate PR as a function of the damping factor d on a network obtained from a domain of the World Wide Web, finding that rank reversal happens frequently over a broad range of PR (and of d). We use three different correlation measures, Pearson, Spearman, and Kendall, to study rank reversal as d changes, and we show that the correlation of PR vectors drops rapidly as d changes from its frequently cited value, d_{0}=0.85. Rank reversal is also observed by measuring the Spearman and Kendall rank correlation, which evaluate relative ranks rather than absolute PR. Rank reversal happens not only in directed networks containing rank sinks but also in a single strongly connected component, which by definition does not contain any sinks. We relate rank reversals to rank pockets and bottlenecks in the directed network structure. For the network studied, the relative rank is more stable by our measures around d=0.65 than at d=d_{0}.

Probability distribution of atmospheric pollutants: comparison among four methods for the determination of the log-normal distribution parameters; La distribuzione di probabilita` degli inquinanti atmosferici: confronto tra quattro metodi per la determinazione dei parametri della distribuzione log-normale

Energy Technology Data Exchange (ETDEWEB)

Bellasio, R [Enviroware s.r.l., Agrate Brianza, Milan (Italy). Centro Direzionale Colleoni; Lanzani, G; Ripamonti, M; Valore, M [Amministrazione Provinciale, Como (Italy)

1998-04-01

This work illustrates the possibility to interpolate the measured concentrations of CO, NO, NO{sub 2}, O{sub 3}, SO{sub 2} during one year (1995) at the 13 stations of the air quality monitoring station network of the Provinces of Como and Lecco (Italy) by means of a log-normal distribution. Particular attention was given in choosing the method for the determination of the log-normal distribution parameters among four possible methods: I natural, II percentiles, III moments, IV maximum likelihood. In order to evaluate the goodness of fit a ranking procedure was carried out over the values of four indices: absolute deviation, weighted absolute deviation, Kolmogorov-Smirnov index and Cramer-von Mises-Smirnov index. The capability of the log-normal distribution to fit the measured data is then discussed as a function of the pollutant and of the monitoring station. Finally an example of application is given: the effect of an emission reduction strategy in Lombardy Region (the so called `bollino blu`) is evaluated using a log-normal distribution. [Italiano] In questo lavoro si discute la possibilita` di interpolare le concentrazioni misurate di CO, NO, NO{sub 2}, O{sub 3}, SO{sub 2} durante un anno solare (il 1995) nelle 13 stazioni della Rete di Rilevamento della qualita` dell`aria delle Provincie di Como e di Lecco mediante una funzione log-normale. In particolare si discute quale metodo e` meglio usare per l`individuazione dei 2 parametri caratteristici della log-normale, tra 4 teoreticamente possibili: I naturale, II dei percentili, III dei momenti, IV della massima verosimiglianza. Per valutare i risultati ottenuti si usano: la deviazione assoluta, la deviazione pesata, il parametro di Kolmogorov-Smirnov e quello di Cramer-von Mises-Smirnov effettuando un ranking tra i metodi in funzione degli inquinanti e della stazione di misura. Ancora in funzione degli inquinanti e delle diverse stazioni di misura si discute poi la capacita` della funzione log-normale di

Can Future Academic Surgeons be Identified in the Residency Ranking Process?

Science.gov (United States)

Beninato, Toni; Kleiman, David A; Zarnegar, Rasa; Fahey, Thomas J

2016-01-01

The goal of surgical residency training programs is to train competent surgeons. Academic surgical training programs also have as a mission training future academicians-surgical scientists, teachers, and leaders. However, selection of surgical residents is dependent on a relatively unscientific process. Here we sought to determine how well the residency selection process is able to identify future academicians in surgery. Rank lists from an academic surgical residency program from 1992 to 1997 were examined. All ranked candidates׳ career paths after residency were reviewed to determine whether they stayed in academics, were university affiliated, or in private practice. The study was performed at New York Presbyterian Hospital-Weill Cornell Medical College, New York, NY. A total of 663 applicants for general surgery residency participated in this study. In total 6 rank lists were evaluated, which included 663 candidates. Overall 76% remained in a general surgery subspecialty. Of those who remained in general surgery, 49% were in private practice, 20% were university affiliated, and 31% had academic careers. Approximately 47% of candidates that were ranked in the top 20 had ≥20 publications, with decreasing percentages as rank number increased. There was a strong correlation between the candidates׳ rank position and pursuing an academic career (p career. The residency selection process can identify candidates likely to be future academicians. Copyright © 2016 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

Clean utilization of low-rank coals for low-cost power generation

International Nuclear Information System (INIS)

Sondreal, E.A.

1992-01-01

Despite the unique utilization problems of low-rank coals, the ten US steam electric plants having the lowest operating cost in 1990 were all fueled on either lignite or subbituminous coal. Ash deposition problems, which have been a major barrier to sustaining high load on US boilers burning high-sodium low-rank coals, have been substantially reduced by improvements in coal selection, boiler design, on-line cleaning, operating conditions, and additives. Advantages of low-rank coals in advanced systems are their noncaking behavior when heated, their high reactivity allowing more complete reaction at lower temperatures, and the low sulfur content of selected deposits. The principal barrier issues are the high-temperature behavior of ash and volatile alkali derived from the coal-bound sodium found in some low-rank coals. Successful upgrading of low-rank coals requires that the product be both stable and suitable for end use in conventional and advanced systems. Coal-water fuel produced by hydrothermal processing of high-moisture low-rank coal meets these criteria, whereas most dry products from drying or carbonizing in hot gas tend to create dust and spontaneous ignition problems unless coated, agglomerated, briquetted, or afforded special handling

Drug binding affinities and potencies are best described by a log-normal distribution and use of geometric means

International Nuclear Information System (INIS)

Stanisic, D.; Hancock, A.A.; Kyncl, J.J.; Lin, C.T.; Bush, E.N.

1986-01-01

(-)-Norepinephrine (NE) is used as an internal standard in their in vitro adrenergic assays, and the concentration of NE which produces a half-maximal inhibition of specific radioligand binding (affinity; K/sub I/), or half-maximal contractile response (potency; ED 50 ) has been measured numerous times. The goodness-of-fit test for normality was performed on both normal (Gaussian) or log 10 -normal frequency histograms of these data using the SAS Univariate procedure. Specific binding of 3 H-prazosin to rat liver (α 1 -), 3 H rauwolscine to rat cortex (α 2 -) and 3 H-dihydroalprenolol to rat ventricle (β 1 -) or rat lung (β 2 -receptors) was inhibited by NE; the distributions of NE K/sub I/'s at all these sites were skewed to the right, with highly significant (p 50 's of NE in isolated rabbit aorta (α 1 ), phenoxybenzamine-treated dog saphenous vein (α 2 ) and guinea pig atrium (β 1 ). The vasorelaxant potency of atrial natriuretic hormone in histamine-contracted rabbit aorta also was better described by a log-normal distribution, indicating that log-normalcy is probably a general phenomenon of drug-receptor interactions. Because data of this type appear to be log-normally distributed, geometric means should be used in parametric statistical analyses

LogScope

Science.gov (United States)

Havelund, Klaus; Smith, Margaret H.; Barringer, Howard; Groce, Alex

2012-01-01

LogScope is a software package for analyzing log files. The intended use is for offline post-processing of such logs, after the execution of the system under test. LogScope can, however, in principle, also be used to monitor systems online during their execution. Logs are checked against requirements formulated as monitors expressed in a rule-based specification language. This language has similarities to a state machine language, but is more expressive, for example, in its handling of data parameters. The specification language is user friendly, simple, and yet expressive enough for many practical scenarios. The LogScope software was initially developed to specifically assist in testing JPL s Mars Science Laboratory (MSL) flight software, but it is very generic in nature and can be applied to any application that produces some form of logging information (which almost any software does).

A performance analysis in AF full duplex relay selection network

Science.gov (United States)

Ngoc, Long Nguyen; Hong, Nhu Nguyen; Loan, Nguyen Thi Phuong; Kieu, Tam Nguyen; Voznak, Miroslav; Zdralek, Jaroslav

2018-04-01

This paper studies on the relaying selective matter in amplify-and-forward (AF) cooperation communication with full-duplex (FD) activity. Various relay choice models supposing the present of different instant information are investigated. We examine a maximal relaying choice that optimizes the instant FD channel capacity and asks for global channel state information (CSI) as well as partial CSI learning. To make comparison easy, accurate outage probability clauses and asymptote form of these strategies that give a diversity rank are extracted. From that, we can see clearly that the number of relays, noise factor, the transmittance coefficient as well as the information transfer power had impacted on their performance. Besides, the optimal relay selection (ORS) model can promote than that of the partial relay selection (PRS) model.

Compressed Sensing with Rank Deficient Dictionaries

DEFF Research Database (Denmark)

Hansen, Thomas Lundgaard; Johansen, Daniel Højrup; Jørgensen, Peter Bjørn

2012-01-01

In compressed sensing it is generally assumed that the dictionary matrix constitutes a (possibly overcomplete) basis of the signal space. In this paper we consider dictionaries that do not span the signal space, i.e. rank deficient dictionaries. We show that in this case the signal-to-noise ratio...... (SNR) in the compressed samples can be increased by selecting the rows of the measurement matrix from the column space of the dictionary. As an example application of compressed sensing with a rank deficient dictionary, we present a case study of compressed sensing applied to the Coarse Acquisition (C...

Ranking structures and rank-rank correlations of countries: The FIFA and UEFA cases

Science.gov (United States)

Ausloos, Marcel; Cloots, Rudi; Gadomski, Adam; Vitanov, Nikolay K.

2014-04-01

Ranking of agents competing with each other in complex systems may lead to paradoxes according to the pre-chosen different measures. A discussion is presented on such rank-rank, similar or not, correlations based on the case of European countries ranked by UEFA and FIFA from different soccer competitions. The first question to be answered is whether an empirical and simple law is obtained for such (self-) organizations of complex sociological systems with such different measuring schemes. It is found that the power law form is not the best description contrary to many modern expectations. The stretched exponential is much more adequate. Moreover, it is found that the measuring rules lead to some inner structures in both cases.

Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

Science.gov (United States)

Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

2016-03-10

Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

Science.gov (United States)

Li, Kai; Qi, Guo-Jun; Ye, Jun; Hua, Kien A

2017-09-01

Hashing has attracted a great deal of research in recent years due to its effectiveness for the retrieval and indexing of large-scale high-dimensional multimedia data. In this paper, we propose a novel ranking-based hashing framework that maps data from different modalities into a common Hamming space where the cross-modal similarity can be measured using Hamming distance. Unlike existing cross-modal hashing algorithms where the learned hash functions are binary space partitioning functions, such as the sign and threshold function, the proposed hashing scheme takes advantage of a new class of hash functions closely related to rank correlation measures which are known to be scale-invariant, numerically stable, and highly nonlinear. Specifically, we jointly learn two groups of linear subspaces, one for each modality, so that features' ranking orders in different linear subspaces maximally preserve the cross-modal similarities. We show that the ranking-based hash function has a natural probabilistic approximation which transforms the original highly discontinuous optimization problem into one that can be efficiently solved using simple gradient descent algorithms. The proposed hashing framework is also flexible in the sense that the optimization procedures are not tied up to any specific form of loss function, which is typical for existing cross-modal hashing methods, but rather we can flexibly accommodate different loss functions with minimal changes to the learning steps. We demonstrate through extensive experiments on four widely-used real-world multimodal datasets that the proposed cross-modal hashing method can achieve competitive performance against several state-of-the-arts with only moderate training and testing time.

Correlation of Cognitive Abilities Level, Age and Ranks in Judo

Directory of Open Access Journals (Sweden)

Kraček Stanislav

2016-11-01

Full Text Available The aim of this paper is to ascertain the correlation between selected cognitive abilities, age and performance of judokas according to ranking. The study group consisted of judokas in the age group 18 ± 2.4 years. The Stroop Color-Word Test - Victoria Version (VST was the instrument used to determine the level of cognitive abilities. The data obtained were measured by the Pearson Correlation (r correlation test. The results of the study show an associative relationship of indirect correlation (p < 0.01 between age and all of the three categories of the Stroop test. This is an indirect correlation, so the higher the age, the lower the time (better performance of the probands in the Stroop test. There was no statistically significant correlation between performance in the categories of the Stroop test and rankings. The outcomes show that the level of selected cognitive abilities depends on age, but the level of the selected cognitive abilities does not affect the ranking of the judokas.

Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

Directory of Open Access Journals (Sweden)

Carlos Alberto Silva

2017-10-01

Full Text Available Airborne lidar is a technology well-suited for mapping many forest attributes, including aboveground biomass (AGB stocks and changes in selective logging in tropical forests. However, trade-offs still exist between lidar pulse density and accuracy of AGB estimates. We assessed the impacts of lidar pulse density on the estimation of AGB stocks and changes using airborne lidar and field plot data in a selectively logged tropical forest located near Paragominas, Pará, Brazil. Field-derived AGB was computed at 85 square 50 × 50 m plots in 2014. Lidar data were acquired in 2012 and 2014, and for each dataset the pulse density was subsampled from its original density of 13.8 and 37.5 pulses·m−2 to lower densities of 12, 10, 8, 6, 4, 2, 0.8, 0.6, 0.4 and 0.2 pulses·m−2. For each pulse density dataset, a power-law model was developed to estimate AGB stocks from lidar-derived mean height and corresponding changes between the years 2012 and 2014. We found that AGB change estimates at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg·ha−1 when pulse density decreased from 12 to 0.2 pulses·m−2. The effects of pulse density were more pronounced in areas of steep slope, especially when the digital terrain models (DTMs used in the lidar derived forest height were created from reduced pulse density data. In particular, when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and the estimated AGB stock and changes did not exceed 20 Mg·ha−1. The results suggest that AGB change can be monitored in selective logging in tropical forests with reasonable accuracy and low cost with low pulse density lidar surveys if a baseline high-quality DTM is available from at least one lidar survey. We recommend the results of this study to be considered in developing projects and national

Log files for testing usability

NARCIS (Netherlands)

Klein Teeselink, G.; Siepe, A.H.M.; Pijper, de J.R.

1999-01-01

The aim of this study is to gain insight in the usefulness of log file analysis as a method to evaluate the usability of individual interface components and their influence on the usability of the overall user interface. We selected a music player as application, with four different interfaces and

Revenue-Maximizing Radio Access Technology Selection with Net Neutrality Compliance in Heterogeneous Wireless Networks

Directory of Open Access Journals (Sweden)

Elissar Khloussy

2018-01-01

Full Text Available The net neutrality principle states that users should have equal access to all Internet content and that Internet Service Providers (ISPs should not practice differentiated treatment on any of the Internet traffic. While net neutrality aims to restrain any kind of discrimination, it also grants exemption to a certain category of traffic known as specialized services (SS, by allowing the ISP to dedicate part of the resources for the latter. In this work, we consider a heterogeneous LTE/WiFi wireless network and we investigate revenue-maximizing Radio Access Technology (RAT selection strategies that are net neutrality-compliant, with exemption granted to SS traffic. Our objective is to find out how the bandwidth reservation for SS traffic would be made in a way that allows maximizing the revenue while being in compliance with net neutrality and how the choice of the ratio of reserved bandwidth would affect the revenue. The results show that reserving bandwidth for SS traffic in one RAT (LTE can achieve higher revenue. On the other hand, when the capacity is reserved across both LTE and WiFi, higher social benefit in terms of number of admitted users can be realized, as well as lower blocking probability for the Internet access traffic.

Effects of logging on roadless space in intact forest landscapes of the Congo Basin.

Science.gov (United States)

Kleinschroth, Fritz; Healey, John R; Gourlet-Fleury, Sylvie; Mortier, Frédéric; Stoica, Radu S

2017-04-01

Forest degradation in the tropics is often associated with roads built for selective logging. The protection of intact forest landscapes (IFL) that are not accessible by roads is high on the biodiversity conservation agenda and a challenge for logging concessions certified by the Forest Stewardship Council (FSC). A frequently advocated conservation objective is to maximize the retention of roadless space, a concept that is based on distance to the nearest road from any point. We developed a novel use of the empty-space function - a general statistical tool based on stochastic geometry and random sets theory - to calculate roadless space in a part of the Congo Basin where road networks have been expanding rapidly. We compared the temporal development of roadless space in certified and uncertified logging concessions inside and outside areas declared IFL in 2000. Inside IFLs, road-network expansion led to a decrease in roadless space by more than half from 1999 to 2007. After 2007, loss leveled out in most areas to close to 0 due to an equilibrium between newly built roads and abandoned roads that became revegetated. However, concessions in IFL certified by FSC since around 2007 continuously lost roadless space and reached a level comparable to all other concessions. Only national parks remained mostly roadless. We recommend that forest-management policies make the preservation of large connected forest areas a top priority by effectively monitoring - and limiting - the occupation of space by roads that are permanently accessible. © 2016 The Authors. Conservation Biology published by Wiley Periodicals, Inc. on behalf of Society for Conservation Biology.

Dynamic Planar Convex Hull with Optimal Query Time and O(log n · log log n ) Update Time

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Jakob, Riko

2000-01-01

The dynamic maintenance of the convex hull of a set of points in the plane is one of the most important problems in computational geometry. We present a data structure supporting point insertions in amortized O(log n · log log log n) time, point deletions in amortized O(log n · log log n) time......, and various queries about the convex hull in optimal O(log n) worst-case time. The data structure requires O(n) space. Applications of the new dynamic convex hull data structure are improved deterministic algorithms for the k-level problem and the red-blue segment intersection problem where all red and all...

Veneer-log production and receipts, North Central Region, 1976.

Science.gov (United States)

James E. Blyth; Jerold T. Hahn

1978-01-01

Shows 1976 veneer-log production and receipts by species in the Lake States (Michigan, Minnesota, and Wisconsin) and in the Central States (Illinois, Indiana, Iowa, and Missouri). Comparisons are made with similar data for 1974. Includes tables showing veneer-log production and receipts (for selected years) since 1946 in the Lake States and since 1956 in the Central...

Veneer-log production and receipts, North Central Region, 1974.

Science.gov (United States)

James E. Blyth; Jerold T. Hahn

1976-01-01

Shows 1974 veneer-log production and receipts by species in the Lake States (Michigan, Minnesota, and Wisconsin) and in the Central States (Illinois, Indiana, Iowa, and Missouri). Comparisons are made with similar data for 1972. Includes tables showing veneer-log production and receipts (for selected years) since 1946 in the Lake States and since 1956 in the Central...

Scheduling for Multiuser MIMO Downlink Channels with Ranking-Based Feedback

Science.gov (United States)

Kountouris, Marios; Sälzer, Thomas; Gesbert, David

2008-12-01

We consider a multi-antenna broadcast channel with more single-antenna receivers than transmit antennas and partial channel state information at the transmitter (CSIT). We propose a novel type of CSIT representation for the purpose of user selection, coined as ranking-based feedback. Each user calculates and feeds back the rank, an integer between 1 and W + 1, of its instantaneous channel quality information (CQI) among a set of W past CQI measurements. Apart from reducing significantly the required feedback load, ranking-based feedback enables the transmitter to select users that are on the highest peak (quantile) with respect to their own channel distribution, independently of the distribution of other users. It can also be shown that this feedback metric can restore temporal fairness in heterogeneous networks, in which users' channels are not identically distributed and mobile terminals experience different average signal-to-noise ratio (SNR). The performance of a system that performs user selection using ranking-based CSIT in the context of random opportunistic beamforming is analyzed, and we provide design guidelines on the number of required past CSIT samples and the impact of finite W on average throughput. Simulation results show that feedback reduction of order of 40-50% can be achieved with negligible decrease in system throughput.

Ranking the adaptive capacity of nations to climate change when socio-political goals are explicit

International Nuclear Information System (INIS)

Haddad, B.M.

2005-01-01

The typical categories for measuring national adaptive capacity to climate change include a nation's wealth, technology, education, information, skills, infrastructure, access to resources, and management capabilities. Resulting rankings predictably mirror more general rankings of economic development, such as the Human Development Index. This approach is incomplete since it does not consider the normative or motivational context of adaptation. For what purpose or toward what goal does a nation aspire, and in that context, what is its adaptive capacity? This paper posits 11 possible national socio-political goals that fall into the three categories of teleological legitimacy, procedural legitimacy, and norm-based decision rules. A model that sorts nations in terms of adaptive capacity based on national socio-political aspirations is presented. While the aspiration of maximizing summed utility matches typical existing rankings, alternative aspirations, including contractarian liberalism, technocratic management, and dictatorial/religious rule alter the rankings. An example describes how this research can potentially inform how priorities are set for international assistance for climate change adaptation. (author)

Tri-maximal vs. bi-maximal neutrino mixing

International Nuclear Information System (INIS)

Scott, W.G

2000-01-01

It is argued that data from atmospheric and solar neutrino experiments point strongly to tri-maximal or bi-maximal lepton mixing. While ('optimised') bi-maximal mixing gives an excellent a posteriori fit to the data, tri-maximal mixing is an a priori hypothesis, which is not excluded, taking account of terrestrial matter effects

SibRank: Signed bipartite network analysis for neighbor-based collaborative ranking

Science.gov (United States)

Shams, Bita; Haratizadeh, Saman

2016-09-01

Collaborative ranking is an emerging field of recommender systems that utilizes users' preference data rather than rating values. Unfortunately, neighbor-based collaborative ranking has gained little attention despite its more flexibility and justifiability. This paper proposes a novel framework, called SibRank that seeks to improve the state of the art neighbor-based collaborative ranking methods. SibRank represents users' preferences as a signed bipartite network, and finds similar users, through a novel personalized ranking algorithm in signed networks.

Deriving consensus rankings via multicriteria decision making methodology

OpenAIRE

Amy Poh Ai Ling; Mohamad Nasir Saludin; Masao Mukaidono

2012-01-01

Purpose - This paper seeks to take a cautionary stance to the impact of the marketing mix on customer satisfaction, via a case study deriving consensus rankings for benchmarking on selected retail stores in Malaysia. Design/methodology/approach - The ELECTRE I model is used in deriving consensus rankings via multicriteria decision making method for benchmarking base on the marketing mix model 4P's. Descriptive analysis is used to analyze best practice among the four marketing tactics. Finding...

Grid-based lattice summation of electrostatic potentials by assembled rank-structured tensor approximation

Science.gov (United States)

Khoromskaia, Venera; Khoromskij, Boris N.

2014-12-01

Our recent method for low-rank tensor representation of sums of the arbitrarily positioned electrostatic potentials discretized on a 3D Cartesian grid reduces the 3D tensor summation to operations involving only 1D vectors however retaining the linear complexity scaling in the number of potentials. Here, we introduce and study a novel tensor approach for fast and accurate assembled summation of a large number of lattice-allocated potentials represented on 3D N × N × N grid with the computational requirements only weakly dependent on the number of summed potentials. It is based on the assembled low-rank canonical tensor representations of the collected potentials using pointwise sums of shifted canonical vectors representing the single generating function, say the Newton kernel. For a sum of electrostatic potentials over L × L × L lattice embedded in a box the required storage scales linearly in the 1D grid-size, O(N) , while the numerical cost is estimated by O(NL) . For periodic boundary conditions, the storage demand remains proportional to the 1D grid-size of a unit cell, n = N / L, while the numerical cost reduces to O(N) , that outperforms the FFT-based Ewald-type summation algorithms of complexity O(N3 log N) . The complexity in the grid parameter N can be reduced even to the logarithmic scale O(log N) by using data-sparse representation of canonical N-vectors via the quantics tensor approximation. For justification, we prove an upper bound on the quantics ranks for the canonical vectors in the overall lattice sum. The presented approach is beneficial in applications which require further functional calculus with the lattice potential, say, scalar product with a function, integration or differentiation, which can be performed easily in tensor arithmetics on large 3D grids with 1D cost. Numerical tests illustrate the performance of the tensor summation method and confirm the estimated bounds on the tensor ranks.

Building uncertainty into cost-effectiveness rankings: portfolio risk-return tradeoffs and implications for decision rules.

Science.gov (United States)

O'Brien, B J; Sculpher, M J

2000-05-01

Current principles of cost-effectiveness analysis emphasize the rank ordering of programs by expected economic return (eg, quality-adjusted life-years gained per dollar expended). This criterion ignores the variance associated with the cost-effectiveness of a program, yet variance is a common measure of risk when financial investment options are appraised. Variation in health care program return is likely to be a criterion of program selection for health care managers with fixed budgets and outcome performance targets. Characterizing health care resource allocation as a risky investment problem, we show how concepts of portfolio analysis from financial economics can be adopted as a conceptual framework for presenting cost-effectiveness data from multiple programs as mean-variance data. Two specific propositions emerge: (1) the current convention of ranking programs by expected return is a special case of the portfolio selection problem in which the decision maker is assumed to be indifferent to risk, and (2) for risk-averse decision makers, the degree of joint risk or covariation in cost-effectiveness between programs will create incentives to diversify an investment portfolio. The conventional normative assumption of risk neutrality for social-level public investment decisions does not apply to a large number of health care resource allocation decisions in which health care managers seek to maximize returns subject to budget constraints and performance targets. Portfolio theory offers a useful framework for studying mean-variance tradeoffs in cost-effectiveness and offers some positive predictions (and explanations) of actual decision making in the health care sector.

Ranking nodes in growing networks: When PageRank fails.

Science.gov (United States)

Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

2015-11-10

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm's efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank's performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Geophysical borehole logging in the unsaturated zone, Yucca Mountain, Nevada

International Nuclear Information System (INIS)

Schimschal, U.; Nelson, P.H.

1991-01-01

Borehole geophysical logging for site characterization in the volcanic rocks at the proposed nuclear waste repository at Yucca Mountain, Nevada, requires data collection under rather unusual conditions. Logging tools must operate in rugose, dry holes above the water table in the unsaturated zone. Not all logging tools will operate in this environment, therefore; careful consideration must be given to selection and calibration. A sample suite of logs is presented that demonstrates correlation of geological formations from borehole to borehole, the definition of zones of altered mineralogy, and the quantitative estimates of rock properties. The authors show the results of an exploratory calculation of porosity and water saturation based upon density and epithermal neutron logs. Comparison of the results with a few core samples is encouraging, particularly because the logs can provide continuous data in boreholes where core samples are not available

14 CFR 1214.1104 - Evaluation and ranking of highly qualified candidates.

Science.gov (United States)

2010-01-01

... 14 Aeronautics and Space 5 2010-01-01 2010-01-01 false Evaluation and ranking of highly qualified candidates. 1214.1104 Section 1214.1104 Aeronautics and Space NATIONAL AERONAUTICS AND SPACE ADMINISTRATION... ranking of highly qualified candidates. (a) A selection board consisting of discipline experts, and such...

Identification of contemporary selection signatures using composite log likelihood and their associations with marbling score in Korean cattle.

Science.gov (United States)

Ryu, Jihye; Lee, Chaeyoung

2014-12-01

Positive selection not only increases beneficial allele frequency but also causes augmentation of allele frequencies of sequence variants in close proximity. Signals for positive selection were detected by the statistical differences in subsequent allele frequencies. To identify selection signatures in Korean cattle, we applied a composite log-likelihood (CLL)-based method, which calculates a composite likelihood of the allelic frequencies observed across sliding windows of five adjacent loci and compares the value with the critical statistic estimated by 50,000 permutations. Data for a total of 11,799 nucleotide polymorphisms were used with 71 Korean cattle and 209 foreign beef cattle. As a result, 147 signals were identified for Korean cattle based on CLL estimates (P selected. Further genetic association analysis with 41 intragenic variants in the selection signatures with the greatest CLL for each chromosome revealed that marbling score was associated with five variants. Intensive association studies with all the selection signatures identified in this study are required to exclude signals associated with other phenotypes or signals falsely detected and thus to identify genetic markers for meat quality. © 2014 Stichting International Foundation for Animal Genetics.

Reduced Rank Regression

DEFF Research Database (Denmark)

Johansen, Søren

2008-01-01

The reduced rank regression model is a multivariate regression model with a coefficient matrix with reduced rank. The reduced rank regression algorithm is an estimation procedure, which estimates the reduced rank regression model. It is related to canonical correlations and involves calculating...

An ecosystem model for tropical forest disturbance and selective logging

Science.gov (United States)

Maoyi Huang; Gregory P. Asner; Michael Keller; Joseph A. Berry

2008-01-01

[1] A new three-dimensional version of the Carnegie-Ames-Stanford Approach (CASA) ecosystem model (CASA-3D) was developed to simulate regional carbon cycling in tropical forest ecosystems after disturbances such as logging. CASA-3D has the following new features: (1) an alternative approach for calculating absorbed photosynthetically active radiation (APAR) using new...

Logging Concessions Enable Illegal Logging Crisis in the Peruvian Amazon

OpenAIRE

Finer, Matt; Jenkins, Clinton N.; Sky, Melissa A. Blue; Pine, Justin

2014-01-01

The Peruvian Amazon is an important arena in global efforts to promote sustainable logging in the tropics. Despite recent efforts to achieve sustainability, such as provisions in the US?Peru Trade Promotion Agreement, illegal logging continues to plague the region. We present evidence that Peru's legal logging concession system is enabling the widespread illegal logging via the regulatory documents designed to ensure sustainable logging. Analyzing official government data, we found that 68.3%...

RankProdIt: A web-interactive Rank Products analysis tool

Directory of Open Access Journals (Sweden)

Laing Emma

2010-08-01

Full Text Available Abstract Background The first objective of a DNA microarray experiment is typically to generate a list of genes or probes that are found to be differentially expressed or represented (in the case of comparative genomic hybridizations and/or copy number variation between two conditions or strains. Rank Products analysis comprises a robust algorithm for deriving such lists from microarray experiments that comprise small numbers of replicates, for example, less than the number required for the commonly used t-test. Currently, users wishing to apply Rank Products analysis to their own microarray data sets have been restricted to the use of command line-based software which can limit its usage within the biological community. Findings Here we have developed a web interface to existing Rank Products analysis tools allowing users to quickly process their data in an intuitive and step-wise manner to obtain the respective Rank Product or Rank Sum, probability of false prediction and p-values in a downloadable file. Conclusions The online interactive Rank Products analysis tool RankProdIt, for analysis of any data set containing measurements for multiple replicated conditions, is available at: http://strep-microarray.sbs.surrey.ac.uk/RankProducts

Dynamic PET reconstruction using temporal patch-based low rank penalty for ROI-based brain kinetic analysis

International Nuclear Information System (INIS)

Kim, Kyungsang; Ye, Jong Chul; Son, Young Don; Cho, Zang Hee; Bresler, Yoram; Ra, Jong Beom

2015-01-01

Dynamic positron emission tomography (PET) is widely used to measure changes in the bio-distribution of radiopharmaceuticals within particular organs of interest over time. However, to retain sufficient temporal resolution, the number of photon counts in each time frame must be limited. Therefore, conventional reconstruction algorithms such as the ordered subset expectation maximization (OSEM) produce noisy reconstruction images, thus degrading the quality of the extracted time activity curves (TACs). To address this issue, many advanced reconstruction algorithms have been developed using various spatio-temporal regularizations. In this paper, we extend earlier results and develop a novel temporal regularization, which exploits the self-similarity of patches that are collected in dynamic images. The main contribution of this paper is to demonstrate that the correlation of patches can be exploited using a low-rank constraint that is insensitive to global intensity variations. The resulting optimization framework is, however, non-Lipschitz and non-convex due to the Poisson log-likelihood and low-rank penalty terms. Direct application of the conventional Poisson image deconvolution by an augmented Lagrangian (PIDAL) algorithm is, however, problematic due to its large memory requirements, which prevents its parallelization. Thus, we propose a novel optimization framework using the concave-convex procedure (CCCP) by exploiting the Legendre–Fenchel transform, which is computationally efficient and parallelizable. In computer simulation and a real in vivo experiment using a high-resolution research tomograph (HRRT) scanner, we confirm that the proposed algorithm can improve image quality while also extracting more accurate region of interests (ROI) based kinetic parameters. Furthermore, we show that the total reconstruction time for HRRT PET is significantly accelerated using our GPU implementation, which makes the algorithm very practical in clinical environments

RankExplorer: Visualization of Ranking Changes in Large Time Series Data.

Science.gov (United States)

Shi, Conglei; Cui, Weiwei; Liu, Shixia; Xu, Panpan; Chen, Wei; Qu, Huamin

2012-12-01

For many applications involving time series data, people are often interested in the changes of item values over time as well as their ranking changes. For example, people search many words via search engines like Google and Bing every day. Analysts are interested in both the absolute searching number for each word as well as their relative rankings. Both sets of statistics may change over time. For very large time series data with thousands of items, how to visually present ranking changes is an interesting challenge. In this paper, we propose RankExplorer, a novel visualization method based on ThemeRiver to reveal the ranking changes. Our method consists of four major components: 1) a segmentation method which partitions a large set of time series curves into a manageable number of ranking categories; 2) an extended ThemeRiver view with embedded color bars and changing glyphs to show the evolution of aggregation values related to each ranking category over time as well as the content changes in each ranking category; 3) a trend curve to show the degree of ranking changes over time; 4) rich user interactions to support interactive exploration of ranking changes. We have applied our method to some real time series data and the case studies demonstrate that our method can reveal the underlying patterns related to ranking changes which might otherwise be obscured in traditional visualizations.

A Multiobjective Programming Method for Ranking All Units Based on Compensatory DEA Model

Directory of Open Access Journals (Sweden)

Haifang Cheng

2014-01-01

Full Text Available In order to rank all decision making units (DMUs on the same basis, this paper proposes a multiobjective programming (MOP model based on a compensatory data envelopment analysis (DEA model to derive a common set of weights that can be used for the full ranking of all DMUs. We first revisit a compensatory DEA model for ranking all units, point out the existing problem for solving the model, and present an improved algorithm for which an approximate global optimal solution of the model can be obtained by solving a sequence of linear programming. Then, we applied the key idea of the compensatory DEA model to develop the MOP model in which the objectives are to simultaneously maximize all common weights under constraints that the sum of efficiency values of all DMUs is equal to unity and the sum of all common weights is also equal to unity. In order to solve the MOP model, we transform it into a single objective programming (SOP model using a fuzzy programming method and solve the SOP model using the proposed approximation algorithm. To illustrate the ranking method using the proposed method, two numerical examples are solved.

http Log Analysis

DEFF Research Database (Denmark)

Bøving, Kristian Billeskov; Simonsen, Jesper

2004-01-01

This article documents how log analysis can inform qualitative studies concerning the usage of web-based information systems (WIS). No prior research has used http log files as data to study collaboration between multiple users in organisational settings. We investigate how to perform http log...... analysis; what http log analysis says about the nature of collaborative WIS use; and how results from http log analysis may support other data collection methods such as surveys, interviews, and observation. The analysis of log files initially lends itself to research designs, which serve to test...... hypotheses using a quantitative methodology. We show that http log analysis can also be valuable in qualitative research such as case studies. The results from http log analysis can be triangulated with other data sources and for example serve as a means of supporting the interpretation of interview data...

PageRank as a method to rank biomedical literature by importance.

Science.gov (United States)

Yates, Elliot J; Dixon, Louise C

2015-01-01

Optimal ranking of literature importance is vital in overcoming article overload. Existing ranking methods are typically based on raw citation counts, giving a sum of 'inbound' links with no consideration of citation importance. PageRank, an algorithm originally developed for ranking webpages at the search engine, Google, could potentially be adapted to bibliometrics to quantify the relative importance weightings of a citation network. This article seeks to validate such an approach on the freely available, PubMed Central open access subset (PMC-OAS) of biomedical literature. On-demand cloud computing infrastructure was used to extract a citation network from over 600,000 full-text PMC-OAS articles. PageRanks and citation counts were calculated for each node in this network. PageRank is highly correlated with citation count (R = 0.905, P PageRank can be trivially computed on commodity cluster hardware and is linearly correlated with citation count. Given its putative benefits in quantifying relative importance, we suggest it may enrich the citation network, thereby overcoming the existing inadequacy of citation counts alone. We thus suggest PageRank as a feasible supplement to, or replacement of, existing bibliometric ranking methods.

Log quality enhancement: A systematic assessment of logging company wellsite performance and log quality

International Nuclear Information System (INIS)

Farnan, R.A.; Mc Hattie, C.M.

1984-01-01

To improve the monitoring of logging company performance, computer programs were developed to assess information en masse from log quality check lists completed on wellsite by the service company engineer and Phillips representative. A study of all logging jobs performed by different service companies for Phillips in Oklahoma (panhandle excepted) during 1982 enabled several pertinent and beneficial interpretations to be made. Company A provided the best tool and crew service. Company B incurred an excessive amount of lost time related to tool failure, in particular the neutron-density tool combination. Company C, although used only three times, incurred no lost time. With a reasonable data base valid conclusions were made pertaining, for example, to repeated tool malfunctions. The actual logs were then assessed for quality

Maintaining ecosystem resilience: functional responses of tree cavity nesters to logging in temperate forests of the Americas.

Science.gov (United States)

Ibarra, José Tomás; Martin, Michaela; Cockle, Kristina L; Martin, Kathy

2017-06-30

Logging often reduces taxonomic diversity in forest communities, but little is known about how this biodiversity loss affects the resilience of ecosystem functions. We examined how partial logging and clearcutting of temperate forests influenced functional diversity of birds that nest in tree cavities. We used point-counts in a before-after-control-impact design to examine the effects of logging on the value, range, and density of functional traits in bird communities in Canada (21 species) and Chile (16 species). Clearcutting, but not partial logging, reduced diversity in both systems. The effect was much more pronounced in Chile, where logging operations removed critical nesting resources (large decaying trees), than in Canada, where decaying aspen Populus tremuloides were retained on site. In Chile, logging was accompanied by declines in species richness, functional richness (amount of functional niche occupied by species), community-weighted body mass (average mass, weighted by species densities), and functional divergence (degree of maximization of divergence in occupied functional niche). In Canada, clearcutting did not affect species richness but nevertheless reduced functional richness and community-weighted body mass. Although some cavity-nesting birds can persist under intensive logging operations, their ecosystem functions may be severely compromised unless future nest trees can be retained on logged sites.

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Science.gov (United States)

Huang, Zhengnan; Zhang, Hongjiu; Boss, Jonathan; Goutman, Stephen A; Mukherjee, Bhramar; Dinov, Ivo D; Guan, Yuanfang

2017-12-01

Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS) Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

Temporal Decay in Timber Species Composition and Value in Amazonian Logging Concessions.

Science.gov (United States)

Richardson, Vanessa A; Peres, Carlos A

2016-01-01

Throughout human history, slow-renewal biological resource populations have been predictably overexploited, often to the point of economic extinction. We assess whether and how this has occurred with timber resources in the Brazilian Amazon. The asynchronous advance of industrial-scale logging frontiers has left regional-scale forest landscapes with varying histories of logging. Initial harvests in unlogged forests can be highly selective, targeting slow-growing, high-grade, shade-tolerant hardwood species, while later harvests tend to focus on fast-growing, light-wooded, long-lived pioneer trees. Brazil accounts for 85% of all native neotropical forest roundlog production, and the State of Pará for almost half of all timber production in Brazilian Amazonia, the largest old-growth tropical timber reserve controlled by any country. Yet the degree to which timber harvests beyond the first-cut can be financially profitable or demographically sustainable remains poorly understood. Here, we use data on legally planned logging of ~17.3 million cubic meters of timber across 314 species extracted from 824 authorized harvest areas in private and community-owned forests, 446 of which reported volumetric composition data by timber species. We document patterns of timber extraction by volume, species composition, and monetary value along aging eastern Amazonian logging frontiers, which are then explained on the basis of historical and environmental variables. Generalized linear models indicate that relatively recent logging operations farthest from heavy-traffic roads are the most selective, concentrating gross revenues on few high-value species. We find no evidence that the post-logging timber species composition and total value of forest stands recovers beyond the first-cut, suggesting that the commercially most valuable timber species become predictably rare or economically extinct in old logging frontiers. In avoiding even more destructive land-use patterns, managing

Ranking the adaptive capacity of nations to climate change when socio-political goals are explicit

Energy Technology Data Exchange (ETDEWEB)

Haddad, B.M. [University of California, Santa Cruz, CA (United States)

2005-07-01

The typical categories for measuring national adaptive capacity to climate change include a nation's wealth, technology, education, information, skills, infrastructure, access to resources, and management capabilities. Resulting rankings predictably mirror more general rankings of economic development, such as the Human Development Index. This approach is incomplete since it does not consider the normative or motivational context of adaptation. For what purpose or toward what goal does a nation aspire, and in that context, what is its adaptive capacity? This paper posits 11 possible national socio-political goals that fall into the three categories of teleological legitimacy, procedural legitimacy, and norm-based decision rules. A model that sorts nations in terms of adaptive capacity based on national socio-political aspirations is presented. While the aspiration of maximizing summed utility matches typical existing rankings, alternative aspirations, including contractarian liberalism, technocratic management, and dictatorial/religious rule alter the rankings. An example describes how this research can potentially inform how priorities are set for international assistance for climate change adaptation. (author)

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

Energy Technology Data Exchange (ETDEWEB)

Ghasemi, Jahan B.; Zolfonoun, Ehsan [Toosi University of Technology, Tehran (Korea, Republic of)

2012-05-15

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

A New Variable Selection Method Based on Mutual Information Maximization by Replacing Collinear Variables for Nonlinear Quantitative Structure-Property Relationship Models

International Nuclear Information System (INIS)

Ghasemi, Jahan B.; Zolfonoun, Ehsan

2012-01-01

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms

Log N-log S in inconclusive

Science.gov (United States)

Klebesadel, R. W.; Fenimore, E. E.; Laros, J.

1983-01-01

The log N-log S data acquired by the Pioneer Venus Orbiter Gamma Burst Detector (PVO) are presented and compared to similar data from the Soviet KONUS experiment. Although the PVO data are consistent with and suggestive of a -3/2 power law distribution, the results are not adequate at this state of observations to differentiate between a -3/2 and a -1 power law slope.

RANK and RANK ligand expression in primary human osteosarcoma

Directory of Open Access Journals (Sweden)

Daniel Branstetter

2015-09-01

Our results demonstrate RANKL expression was observed in the tumor element in 68% of human OS using IHC. However, the staining intensity was relatively low and only 37% (29/79 of samples exhibited≥10% RANKL positive tumor cells. RANK expression was not observed in OS tumor cells. In contrast, RANK expression was clearly observed in other cells within OS samples, including the myeloid osteoclast precursor compartment, osteoclasts and in giant osteoclast cells. The intensity and frequency of RANKL and RANK staining in OS samples were substantially less than that observed in GCTB samples. The observation that RANKL is expressed in OS cells themselves suggests that these tumors may mediate an osteoclastic response, and anti-RANKL therapy may potentially be protective against bone pathologies in OS. However, the absence of RANK expression in primary human OS cells suggests that any autocrine RANKL/RANK signaling in human OS tumor cells is not operative, and anti-RANKL therapy would not directly affect the tumor.

Ranking nodes in growing networks: When PageRank fails

Science.gov (United States)

Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng

2015-11-01

PageRank is arguably the most popular ranking algorithm which is being applied in real systems ranging from information to biological and infrastructure networks. Despite its outstanding popularity and broad use in different areas of science, the relation between the algorithm’s efficacy and properties of the network on which it acts has not yet been fully understood. We study here PageRank’s performance on a network model supported by real data, and show that realistic temporal effects make PageRank fail in individuating the most valuable nodes for a broad range of model parameters. Results on real data are in qualitative agreement with our model-based findings. This failure of PageRank reveals that the static approach to information filtering is inappropriate for a broad class of growing systems, and suggest that time-dependent algorithms that are based on the temporal linking patterns of these systems are needed to better rank the nodes.

Log-fueled boilers; Les chaudieres a buches

Energy Technology Data Exchange (ETDEWEB)

NONE

2002-07-01

This document describes the different technologies of wood boilers fueled with logs (ascending combustion and natural draught, horizontal combustion and natural draught, reverse combustion and natural draught, reverse combustion and forced draught), their advantages and drawbacks, selection criteria and installation rules. (J.S.)

Encyclopedia of well logging

International Nuclear Information System (INIS)

Desbrandes, R.

1985-01-01

The 16 chapters of this book aim to provide students, trainees and engineers with a manual covering all well-logging measurements ranging from drilling to productions, from oil to minerals going by way of geothermal energy. Each chapter is a summary but a bibliography is given at the end of each chapter. Well-logging during drilling, wireline logging equipment and techniques, petroleum logging, data processing of borehole data, interpretation of well-logging, sampling tools, completion and production logging, logging in relief wells to kill off uncontrolled blowouts, techniques for high temperature geothermal energy, small-scale mining and hydrology, logging with oil-base mud and finally recommended logging programs are all topics covered. There is one chapter on nuclear well-logging which is indexed separately. (UK)

Interpretation of horizontal well production logs: influence of logging tool

Energy Technology Data Exchange (ETDEWEB)

Ozkan, E. [Colorado School of Mines, Boulder, CO (United States); Sarica, C. [Pennsylvania State Univ., College Park, PA (United States); Haci, M. [Drilling Measurements, Inc (United States)

1998-12-31

The influence of a production-logging tool on wellbore flow rate and pressure measurements was investigated, focusing on the disturbence caused by the production-logging tool and the coiled tubing on the original flow conditions in the wellbore. The investigation was carried out using an analytical model and single-phase liquid flow was assumed. Results showed that the production-logging tool influenced the measurements as shown by the deviation of the original flow-rate, pressure profiles and low-conductivity wellbores. High production rates increase the effect of the production-logging tool. Recovering or inferring the original flow conditions in the wellbore from the production-logging data is a very complex process which cannot be solved easily. For this reason, the conditions under which the information obtained by production-logging is meaningful is of considerable practical interest. 7 refs., 2 tabs., 15 figs.

Comparison of Anthropometry and Lower Limb Power Qualities According to Different Levels and Ranking Position of Competitive Surfers.

Science.gov (United States)

Fernandez-Gamboa, Iosu; Yanci, Javier; Granados, Cristina; Camara, Jesus

2017-08-01

Fernandez-Gamboa, I, Yanci, J, Granados, C, and Camara, J. Comparison of anthropometry and lower limb power qualities according to different levels and ranking position of competitive surfers. J Strength Cond Res 31(8): 2231-2237, 2017-The aim of this study was to compare competitive surfers' lower limb power output depending on their competitive level, and to evaluate the association between competition rankings. Twenty competitive surfers were divided according to the competitive level as follows: international (INT) or national (NAT), and competitive ranking (RANK1-50 or RANK51-100). Vertical jump and maximal peak power of the lower limbs were measured. No differences were found between INT and NAT surfers in the anthropometric variables, in the vertical jump, or in lower extremity power; although the NAT group had higher levels on the elasticity index, squat jumps (SJs), and counter movement jumps (CMJs) compared with the INT group. The RANK1-50 group had a lower biceps skinfold (p RANK1-50 group. Moderate to large significant correlations were obtained between the surfers' ranking position and some skinfolds, the sum of skinfolds, and vertical jump. Results demonstrate that surfers' physical performance seems to be an accurate indicator of ranking positioning, also revealing that vertical jump capacity and anthropometric variables play an important role in their competitive performance, which may be important when considering their power training.

Complete hazard ranking to analyze right-censored data: An ALS survival study.

Directory of Open Access Journals (Sweden)

Zhengnan Huang

2017-12-01

Full Text Available Survival analysis represents an important outcome measure in clinical research and clinical trials; further, survival ranking may offer additional advantages in clinical trials. In this study, we developed GuanRank, a non-parametric ranking-based technique to transform patients' survival data into a linear space of hazard ranks. The transformation enables the utilization of machine learning base-learners including Gaussian process regression, Lasso, and random forest on survival data. The method was submitted to the DREAM Amyotrophic Lateral Sclerosis (ALS Stratification Challenge. Ranked first place, the model gave more accurate ranking predictions on the PRO-ACT ALS dataset in comparison to Cox proportional hazard model. By utilizing right-censored data in its training process, the method demonstrated its state-of-the-art predictive power in ALS survival ranking. Its feature selection identified multiple important factors, some of which conflicts with previous studies.

Rank-k Maximal Statistics for Divergence and Probability of Misclassification

Science.gov (United States)

Decell, H. P., Jr.

1972-01-01

A technique is developed for selecting from n-channel multispectral data some k combinations of the n-channels upon which to base a given classification technique so that some measure of the loss of the ability to distinguish between classes, using the compressed k-dimensional data, is minimized. Information loss in compressing the n-channel data to k channels is taken to be the difference in the average interclass divergences (or probability of misclassification) in n-space and in k-space.

RANK/RANK-Ligand/OPG: Ein neuer Therapieansatz in der Osteoporosebehandlung

Directory of Open Access Journals (Sweden)

Preisinger E

2007-01-01

Full Text Available Die Erforschung der Kopplungsmechanismen zur Osteoklastogenese, Knochenresorption und Remodellierung eröffnete neue mögliche Therapieansätze in der Behandlung der Osteoporose. Eine Schlüsselrolle beim Knochenabbau spielt der RANK- ("receptor activator of nuclear factor (NF- κB"- Ligand (RANKL. Durch die Bindung von RANKL an den Rezeptor RANK wird die Knochenresorption eingeleitet. OPG (Osteoprotegerin sowie der für den klinischen Gebrauch entwickelte humane monoklonale Antikörper (IgG2 Denosumab blockieren die Bindung von RANK-Ligand an RANK und verhindern den Knochenabbau.

Colleges Question Data Used by "Yahoo!" To Rank the "Most Wired" Campus.

Science.gov (United States)

Young, Jeffrey R.

1997-01-01

College administrators are complaining that "Yahoo! Internet Life" magazine used a flawed surveying process and inaccurate data to select the institutions it named in a recent ranking of "American's 100 Most Wired Colleges." Even some institutions faring well in the ranking have concerns about the survey, citing problems with…

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha

2014-12-08

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

Sparse reduced-rank regression with covariance estimation

KAUST Repository

Chen, Lisha; Huang, Jianhua Z.

2014-01-01

Improving the predicting performance of the multiple response regression compared with separate linear regressions is a challenging question. On the one hand, it is desirable to seek model parsimony when facing a large number of parameters. On the other hand, for certain applications it is necessary to take into account the general covariance structure for the errors of the regression model. We assume a reduced-rank regression model and work with the likelihood function with general error covariance to achieve both objectives. In addition we propose to select relevant variables for reduced-rank regression by using a sparsity-inducing penalty, and to estimate the error covariance matrix simultaneously by using a similar penalty on the precision matrix. We develop a numerical algorithm to solve the penalized regression problem. In a simulation study and real data analysis, the new method is compared with two recent methods for multivariate regression and exhibits competitive performance in prediction and variable selection.

Multi-task feature selection in microarray data by binary integer programming.

Science.gov (United States)

Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Comparative effects of oil palm and selective logging on erosion, river channels and water chemistry in Malaysian steeplands

Science.gov (United States)

Walsh, Rory; Nainar, Anand; Nurhidayu, Siti; Higton, Sam; Annammala, Kogilavani; Wall, Katy; Bidin, Kawi; Blake, William; Darling, Isabella

2017-04-01

Oil palm land-use has expanded greatly in recent decades in SE Asia and other parts of the wet tropics, including to steepland areas, where bench-terraced landscaping is involved. Retaining (and sometimes restoring) riparian forest strips and rainforest fragments on the steepest slopes have been adopted as elements of strategies designed to reduce adverse effects on runoff generation, erosion, downstream sedimentation, flooding and pollutional problems - as well as biodiversity and emissions. Results of catchment monitoring, soil erosion and sediment fingerprinting research in oil palm and selectively logged steeplands of eastern Sabah and Peninsular Malaysia are presented. The evidence indicates the greater scale and temporal persistence of effects that oil palm land-use (compared with selective logging) has had on suspended sediment dynamics, soil erosion, downstream sedimentation, channel geometry and dynamics and river pollution. The importance of (1) high densities of roads and tracks and (2) relatively impermeable bench-terraced terrain in enhancing runoff, sediment and nutrient outputs in storm events is stressed. Influences of oil palm management practices including riparian forest strips in increasing or reducing these effects are critically reviewed and ways of increasing the effectiveness of riparian forest strips are proposed. The design and rationale of current projects exploring and testing consequences of existing and proposed improved land management practices are briefly described. The key importance of involvement of people from the oil palm industry (including multinational companies, smallholders and their organizations) and Government bodies that are responsible for land-use policies and land management practices is stressed.

Extrapolating Weak Selection in Evolutionary Games

Science.gov (United States)

Wu, Bin; García, Julián; Hauert, Christoph; Traulsen, Arne

2013-01-01

In evolutionary games, reproductive success is determined by payoffs. Weak selection means that even large differences in game outcomes translate into small fitness differences. Many results have been derived using weak selection approximations, in which perturbation analysis facilitates the derivation of analytical results. Here, we ask whether results derived under weak selection are also qualitatively valid for intermediate and strong selection. By “qualitatively valid” we mean that the ranking of strategies induced by an evolutionary process does not change when the intensity of selection increases. For two-strategy games, we show that the ranking obtained under weak selection cannot be carried over to higher selection intensity if the number of players exceeds two. For games with three (or more) strategies, previous examples for multiplayer games have shown that the ranking of strategies can change with the intensity of selection. In particular, rank changes imply that the most abundant strategy at one intensity of selection can become the least abundant for another. We show that this applies already to pairwise interactions for a broad class of evolutionary processes. Even when both weak and strong selection limits lead to consistent predictions, rank changes can occur for intermediate intensities of selection. To analyze how common such games are, we show numerically that for randomly drawn two-player games with three or more strategies, rank changes frequently occur and their likelihood increases rapidly with the number of strategies . In particular, rank changes are almost certain for , which jeopardizes the predictive power of results derived for weak selection. PMID:24339769

Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies.

Science.gov (United States)

Wang, Haohan; Aragam, Bryon; Xing, Eric P

2018-04-26

A fundamental and important challenge in modern datasets of ever increasing dimensionality is variable selection, which has taken on renewed interest recently due to the growth of biological and medical datasets with complex, non-i.i.d. structures. Naïvely applying classical variable selection methods such as the Lasso to such datasets may lead to a large number of false discoveries. Motivated by genome-wide association studies in genetics, we study the problem of variable selection for datasets arising from multiple subpopulations, when this underlying population structure is unknown to the researcher. We propose a unified framework for sparse variable selection that adaptively corrects for population structure via a low-rank linear mixed model. Most importantly, the proposed method does not require prior knowledge of sample structure in the data and adaptively selects a covariance structure of the correct complexity. Through extensive experiments, we illustrate the effectiveness of this framework over existing methods. Further, we test our method on three different genomic datasets from plants, mice, and human, and discuss the knowledge we discover with our method. Copyright © 2018. Published by Elsevier Inc.

Maximizing Crossbred Performance through Purebred Genomic Selection

DEFF Research Database (Denmark)

Esfandyari, Hadi; Sørensen, Anders Christian; Bijma, Pieter

Genomic selection (GS) can be used to select purebreds for crossbred performance (CP). As dominance is the likely genetic basis of heterosis, explicitly including dominance in the GS model may be beneficial for selection of purebreds for CP, when estimating allelic effects from pure line data. Th...

Competency-based residency training and the web log: modeling practice-based learning and enhancing medical knowledge

Directory of Open Access Journals (Sweden)

Matthew F. Hollon

2015-12-01

Full Text Available Background: By using web-based tools in medical education, there are opportunities to innovatively teach important principles from the general competencies of graduate medical education. Objectives: Postulating that faculty transparency in learning from uncertainties in clinical work could help residents to incorporate the principles of practice-based learning and improvement (PBLI in their professional development, faculty in this community-based residency program modeled the steps of PBLI on a weekly basis through the use of a web log. Method: The program confidentially surveyed residents before and after this project about actions consistent with PBLI and knowledge acquired through reading the web log. Results: The frequency that residents encountered clinical situations where they felt uncertain declined over the course of the 24 weeks of the project from a mean frequency of uncertainty of 36% to 28% (Wilcoxon signed rank test, p=0.008; however, the frequency with which residents sought answers when faced with uncertainty did not change (Wilcoxon signed rank test, p=0.39, remaining high at approximately 80%. Residents answered a mean of 52% of knowledge questions correct when tested prior to faculty posts to the blog, rising to a mean of 65% of questions correct when tested at the end of the project (paired t-test, p=0.001. Conclusions: Faculty role modeling of PBLI behaviors and posting clinical questions and answers to a web log led to modest improvements in medical knowledge but did not alter behavior that was already taking place frequently among residents.

Nuclear well logging in hydrology

International Nuclear Information System (INIS)

1971-01-01

they are described in detail elsewhere. The tracer techniques which have been included involve the use of well-logging methods to locate isotopic tracers inserted either in an adjacent borehole or in the same borehole as that in which the logs are made. Throughout the report, sufficient references have been selected to ensure that proven methods are adequately represented, but a comprehensive bibliography is not included. The International Atomic Energy Agency, at the request of the Coordinating Council of the International Hydrological Decade, is providing the Secretariat for the Working Group on Nuclear Techniques in Hydrology of the International Hydrological Decade (IHD). The Working Group and Secretariat have contributed to and coordinated the preparation of this report as well as an earlier more general report, Guidebook on Nuclear Techniques in Hydrology, IAEA Technical Reports Series No.91. Nuclear logging, along with other borehole geophysical methods, was adopted and developed primarily by the petroleum industry for use in exploration and developmental work. The information in this report shows that nuclear logging may also be useful in hydrology. Qualitative and under proper conditions quantitative interpretations about the physical, chemical, petrographic and hydraulic properties of formations and their contained fluids can be made from nuclear logs. The IHD Working Group on Nuclear Techniques in Hydrology, during its fourth meeting (in 1969), considered in detail the present status of nuclear logging with respect to hydrological investigations. Particularly it considered: (1) whether suitable equipment is at present available; (2) whether it could fulfil the need of hydrologists today; and (3) whether it was yet economic for use in hydrological investigations. The Working Group noted that the two main deficiencies in nuclear logging for hydrological purposes are: (1) the general lack of information in a coordinated form, and (2) the scarcity of

Returns to Tenure: Time or Rank?

DEFF Research Database (Denmark)

Buhai, Ioan Sebastian

-specific investment, efficiency-wages or adverse-selection models. However, rent extracting arguments as suggested by the theory of internal labor markets, indicate that the relative position of the worker in the seniority hierarchy of the firm, her 'seniority rank', may also explain part of the observed returns...... relative to their peer workers), as predicted by theories on unionized and insider-outsider markets....

Determining factors behind the pagerank log-log plot

NARCIS (Netherlands)

Volkovich, Y.; Litvak, Nelli; Donato, Debora; Bonato, Anthony; Chung, Fan R.K.

2007-01-01

We study the relation between PageRank and other parameters of information networks such as in-degree, out-degree, and the fraction of dangling nodes. We model this relation through a stochastic equation inspired by the original definition of PageRank. Further, we use the theory of regular variation

Research of Subgraph Estimation Page Rank Algorithm for Web Page Rank

Directory of Open Access Journals (Sweden)

LI Lan-yin

2017-04-01

Full Text Available The traditional PageRank algorithm can not efficiently perform large data Webpage scheduling problem. This paper proposes an accelerated algorithm named topK-Rank，which is based on PageRank on the MapReduce platform. It can find top k nodes efficiently for a given graph without sacrificing accuracy. In order to identify top k nodes，topK-Rank algorithm prunes unnecessary nodes and edges in each iteration to dynamically construct subgraphs，and iteratively estimates lower/upper bounds of PageRank scores through subgraphs. Theoretical analysis shows that this method guarantees result exactness. Experiments show that topK-Rank algorithm can find k nodes much faster than the existing approaches.

Methods for processing of pulsed neutron logging data

International Nuclear Information System (INIS)

Iskenderov, V.G.

1975-01-01

Conditions were examined for calculating the lifetime of thermal neutrons in neutron-neutron logging by selecting optimum values for the time lag. The dispersion and mean square error of the calculated lifetime values for thermal neutrons are evaluated

Learning to rank figures within a biomedical article.

Directory of Open Access Journals (Sweden)

Feifan Liu

Full Text Available Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1 First Author, (2 Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3 Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or

Learning to rank figures within a biomedical article.

Science.gov (United States)

Liu, Feifan; Yu, Hong

2014-01-01

Hundreds of millions of figures are available in biomedical literature, representing important biomedical experimental evidence. This ever-increasing sheer volume has made it difficult for scientists to effectively and accurately access figures of their interest, the process of which is crucial for validating research facts and for formulating or testing novel research hypotheses. Current figure search applications can't fully meet this challenge as the "bag of figures" assumption doesn't take into account the relationship among figures. In our previous study, hundreds of biomedical researchers have annotated articles in which they serve as corresponding authors. They ranked each figure in their paper based on a figure's importance at their discretion, referred to as "figure ranking". Using this collection of annotated data, we investigated computational approaches to automatically rank figures. We exploited and extended the state-of-the-art listwise learning-to-rank algorithms and developed a new supervised-learning model BioFigRank. The cross-validation results show that BioFigRank yielded the best performance compared with other state-of-the-art computational models, and the greedy feature selection can further boost the ranking performance significantly. Furthermore, we carry out the evaluation by comparing BioFigRank with three-level competitive domain-specific human experts: (1) First Author, (2) Non-Author-In-Domain-Expert who is not the author nor co-author of an article but who works in the same field of the corresponding author of the article, and (3) Non-Author-Out-Domain-Expert who is not the author nor co-author of an article and who may or may not work in the same field of the corresponding author of an article. Our results show that BioFigRank outperforms Non-Author-Out-Domain-Expert and performs as well as Non-Author-In-Domain-Expert. Although BioFigRank underperforms First Author, since most biomedical researchers are either in- or out

Diagnosing and ranking retinopathy disease level using diabetic fundus image recuperation approach.

Science.gov (United States)

Somasundaram, K; Rajendran, P Alli

2015-01-01

Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED) and Optimally Adjusted Morphological Operator (OAMO) effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR) method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

Which family physician should I choose? The analytic hierarchy process approach for ranking of criteria in the selection of a family physician.

Science.gov (United States)

Kuruoglu, Emel; Guldal, Dilek; Mevsim, Vildan; Gunvar, Tolga

2015-08-05

Choosing the most appropriate family physician (FP) for the individual, plays a fundamental role in primary care. The aim of this study is to determine the selection criteria for the patients in choosing their family doctors and priority ranking of these criteria by using the multi-criteria decision-making method of the Analytic Hierarchy Process (AHP) model. The study was planned and conducted in two phases. In the first phase, factors affecting the patients' decisions were revealed with a qualitative research. In the next phase, the priorities of FP selection criteria were determined by using AHP model. Criteria were compared in pairs. 96 patient were asked to fill the information forms which contains comparison scores in the Family Health Centres. According to the analysis of focus group discussions FP selection criteria were congregated in to five groups: Individual Characteristics, Patient-Doctor relationship, Professional characteristics, the Setting, and Ethical Characteristics. For each of the 96 participants, comparison matrixes were formed based on the scores of their information forms. Of these, models of only 5 (5.2 %) of the participants were consistent, in other words, they have been able to score consistent ranking. The consistency ratios (CR) were found to be smaller than 0.10. Therefore the comparison matrix of this new model, which was formed based on the medians of scores only given by these 5 participants, was consistent (CR = 0.06 < 0.10). According to comparison results; with a 0.467 value-weight, the most important criterion for choosing a family physician is his/her 'Professional characteristics'. Selection criteria for choosing a FP were put in a priority order by using AHP model. These criteria can be used as measures for selecting alternative FPs in further researches.

Phenomenology of maximal and near-maximal lepton mixing

International Nuclear Information System (INIS)

Gonzalez-Garcia, M. C.; Pena-Garay, Carlos; Nir, Yosef; Smirnov, Alexei Yu.

2001-01-01

The possible existence of maximal or near-maximal lepton mixing constitutes an intriguing challenge for fundamental theories of flavor. We study the phenomenological consequences of maximal and near-maximal mixing of the electron neutrino with other (x=tau and/or muon) neutrinos. We describe the deviations from maximal mixing in terms of a parameter ε(equivalent to)1-2sin 2 θ ex and quantify the present experimental status for |ε| e mixing comes from solar neutrino experiments. We find that the global analysis of solar neutrino data allows maximal mixing with confidence level better than 99% for 10 -8 eV 2 ∼ 2 ∼ -7 eV 2 . In the mass ranges Δm 2 ∼>1.5x10 -5 eV 2 and 4x10 -10 eV 2 ∼ 2 ∼ -7 eV 2 the full interval |ε| e mixing in atmospheric neutrinos, supernova neutrinos, and neutrinoless double beta decay

A new mutually reinforcing network node and link ranking algorithm.

Science.gov (United States)

Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E

2015-10-23

This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

A new mutually reinforcing network node and link ranking algorithm

Science.gov (United States)

Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

2015-10-01

This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity.

A new mutually reinforcing network node and link ranking algorithm

Science.gov (United States)

Wang, Zhenghua; Dueñas-Osorio, Leonardo; Padgett, Jamie E.

2015-01-01

This study proposes a novel Normalized Wide network Ranking algorithm (NWRank) that has the advantage of ranking nodes and links of a network simultaneously. This algorithm combines the mutual reinforcement feature of Hypertext Induced Topic Selection (HITS) and the weight normalization feature of PageRank. Relative weights are assigned to links based on the degree of the adjacent neighbors and the Betweenness Centrality instead of assigning the same weight to every link as assumed in PageRank. Numerical experiment results show that NWRank performs consistently better than HITS, PageRank, eigenvector centrality, and edge betweenness from the perspective of network connectivity and approximate network flow, which is also supported by comparisons with the expensive N-1 benchmark removal criteria based on network efficiency. Furthermore, it can avoid some problems, such as the Tightly Knit Community effect, which exists in HITS. NWRank provides a new inexpensive way to rank nodes and links of a network, which has practical applications, particularly to prioritize resource allocation for upgrade of hierarchical and distributed networks, as well as to support decision making in the design of networks, where node and link importance depend on a balance of local and global integrity. PMID:26492958

Materials Selection for Aerospace Systems

Science.gov (United States)

Arnold, Steven M.; Cebon, David; Ashby, Mike

2012-01-01

A systematic design-oriented, five-step approach to material selection is described: 1) establishing design requirements, 2) material screening, 3) ranking, 4) researching specific candidates and 5) applying specific cultural constraints to the selection process. At the core of this approach is the definition performance indices (i.e., particular combinations of material properties that embody the performance of a given component) in conjunction with material property charts. These material selection charts, which plot one property against another, are introduced and shown to provide a powerful graphical environment wherein one can apply and analyze quantitative selection criteria, such as those captured in performance indices, and make trade-offs between conflicting objectives. Finding a material with a high value of these indices maximizes the performance of the component. Two specific examples pertaining to aerospace (engine blades and pressure vessels) are examined, both at room temperature and elevated temperature (where time-dependent effects are important) to demonstrate the methodology. The discussion then turns to engineered/hybrid materials and how these can be effectively tailored to fill in holes in the material property space, so as to enable innovation and increases in performance as compared to monolithic materials. Finally, a brief discussion is presented on managing the data needed for materials selection, including collection, analysis, deployment, and maintenance issues.

VaRank: a simple and powerful tool for ranking genetic variants

Directory of Open Access Journals (Sweden)

Véronique Geoffroy

2015-03-01

Full Text Available Background. Most genetic disorders are caused by single nucleotide variations (SNVs or small insertion/deletions (indels. High throughput sequencing has broadened the catalogue of human variation, including common polymorphisms, rare variations or disease causing mutations. However, identifying one variation among hundreds or thousands of others is still a complex task for biologists, geneticists and clinicians.Results. We have developed VaRank, a command-line tool for the ranking of genetic variants detected by high-throughput sequencing. VaRank scores and prioritizes variants annotated either by Alamut Batch or SnpEff. A barcode allows users to quickly view the presence/absence of variants (with homozygote/heterozygote status in analyzed samples. VaRank supports the commonly used VCF input format for variants analysis thus allowing it to be easily integrated into NGS bioinformatics analysis pipelines. VaRank has been successfully applied to disease-gene identification as well as to molecular diagnostics setup for several hundred patients.Conclusions. VaRank is implemented in Tcl/Tk, a scripting language which is platform-independent but has been tested only on Unix environment. The source code is available under the GNU GPL, and together with sample data and detailed documentation can be downloaded from http://www.lbgi.fr/VaRank/.

Time-Aware Service Ranking Prediction in the Internet of Things Environment.

Science.gov (United States)

Huang, Yuze; Huang, Jiwei; Cheng, Bo; He, Shuqing; Chen, Junliang

2017-04-27

With the rapid development of the Internet of things (IoT), building IoT systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

Time-Aware Service Ranking Prediction in the Internet of Things Environment

Directory of Open Access Journals (Sweden)

Yuze Huang

2017-04-01

Full Text Available With the rapid development of the Internet of things (IoT, building IoT systems with high quality of service (QoS has become an urgent requirement in both academia and industry. During the procedures of building IoT systems, QoS-aware service selection is an important concern, which requires the ranking of a set of functionally similar services according to their QoS values. In reality, however, it is quite expensive and even impractical to evaluate all geographically-dispersed IoT services at a single client to obtain such a ranking. Nevertheless, distributed measurement and ranking aggregation have to deal with the high dynamics of QoS values and the inconsistency of partial rankings. To address these challenges, we propose a time-aware service ranking prediction approach named TSRPred for obtaining the global ranking from the collection of partial rankings. Specifically, a pairwise comparison model is constructed to describe the relationships between different services, where the partial rankings are obtained by time series forecasting on QoS values. The comparisons of IoT services are formulated by random walks, and thus, the global ranking can be obtained by sorting the steady-state probabilities of the underlying Markov chain. Finally, the efficacy of TSRPred is validated by simulation experiments based on large-scale real-world datasets.

Generalized localization for the double trigonometric Fourier series and the Walsh-Fourier series of functions in L log +L log + log +L

International Nuclear Information System (INIS)

Bloshanskaya, S K; Bloshanskii, I L; Roslova, T Y

1998-01-01

For an arbitrary open set Ω subset of I 2 =[0,1) 2 and an arbitrary function f element of L log + L log + log + L(I 2 ) such that f=0 on Ω the double Fourier series of f with respect to the trigonometric system Ψ=E and the Walsh-Paley system Ψ=W is shown to converge to zero (over rectangles) almost everywhere on Ω. Thus, it is proved that generalized localization almost everywhere holds on arbitrary open subsets of the square I 2 for the double trigonometric Fourier series and the Walsh-Fourier series of functions in the class L log + L log + log + L (in the case of summation over rectangles). It is also established that such localization breaks down on arbitrary sets that are not dense in I 2 , in the classes Φ Ψ (L)(I 2 ) for the orthonormal system Ψ=E and an arbitrary function such that Φ E (u)=o(u log + log + u) as u→∞ or for Φ W (u)=u( log + log + u) 1-ε , 0<ε<1

Ranking agility factors affecting hospitals in Iran

Directory of Open Access Journals (Sweden)

M. Abdi Talarposht

2017-04-01

Full Text Available Background: Agility is an effective response to the changing and unpredictable environment and using these changes as opportunities for organizational improvement. Objective: The aim of the present study was to rank the factors affecting agile supply chain of hospitals of Iran. Methods: This applied study was conducted by cross sectional-descriptive method at some point of 2015 for one year. The research population included managers, administrators, faculty members and experts were selected hospitals. A total of 260 people were selected as sample from the health centers. The construct validity of the questionnaire was approved by confirmatory factor analysis test and its reliability was approved by Cronbach's alpha (α=0.97. All data were analyzed by Kolmogorov-Smirnov, Chi-square and Friedman tests. Findings: The development of staff skills, the use of information technology, the integration of processes, appropriate planning, and customer satisfaction and product quality had a significant impact on the agility of public hospitals of Iran (P<0.001. New product introductions had earned the highest ranking and the development of staff skills earned the lowest ranking. Conclusion: The new product introduction, market responsiveness and sensitivity, reduce costs, and the integration of organizational processes, ratings better to have acquired agility hospitals in Iran. Therefore, planners and officials of hospitals have to, through the promotion quality and variety of services customer-oriented, providing a basis for investing in the hospital and etc to apply for agility supply chain public hospitals of Iran.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan

2014-04-17

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse structure, we assume that each multimedia object could be represented as a sparse linear combination of all other objects, and combination coefficients are regarded as a similarity measure between objects and used to regularize their ranking scores. Moreover, we propose to learn the sparse combination coefficients and the ranking scores simultaneously. A unified objective function is constructed with regard to both the combination coefficients and the ranking scores, and is optimized by an iterative algorithm. Experiments on two multimedia database retrieval data sets demonstrate the significant improvements of the propose algorithm over state-of-the-art ranking score learning algorithms.

The impact of selective-logging and forest clearance for oil palm on fungal communities in Borneo.

Science.gov (United States)

Kerfahi, Dorsaf; Tripathi, Binu M; Lee, Junghoon; Edwards, David P; Adams, Jonathan M

2014-01-01

Tropical forests are being rapidly altered by logging, and cleared for agriculture. Understanding the effects of these land use changes on soil fungi, which play vital roles in the soil ecosystem functioning and services, is a major conservation frontier. Using 454-pyrosequencing of the ITS1 region of extracted soil DNA, we compared communities of soil fungi between unlogged, once-logged, and twice-logged rainforest, and areas cleared for oil palm, in Sabah, Malaysia. Overall fungal community composition differed significantly between forest and oil palm plantation. The OTU richness and Chao 1 were higher in forest, compared to oil palm plantation. As a proportion of total reads, Basidiomycota were more abundant in forest soil, compared to oil palm plantation soil. The turnover of fungal OTUs across space, true β-diversity, was also higher in forest than oil palm plantation. Ectomycorrhizal (EcM) fungal abundance was significantly different between land uses, with highest relative abundance (out of total fungal reads) observed in unlogged forest soil, lower abundance in logged forest, and lowest in oil palm. In their entirety, these results indicate a pervasive effect of conversion to oil palm on fungal community structure. Such wholesale changes in fungal communities might impact the long-term sustainability of oil palm agriculture. Logging also has more subtle long term effects, on relative abundance of EcM fungi, which might affect tree recruitment and nutrient cycling. However, in general the logged forest retains most of the diversity and community composition of unlogged forest.

Climbers and logging in the Forêt Classée du Haut Sassandra, Côte d'Ivoire.

NARCIS (Netherlands)

Kouamé, F.N.; Bongers, F.J.J.M.; Poorter, L.; Traoré, D.

2004-01-01

In this study we compare climber abundance and size in centres of post-logging skid tracks and log loading areas to their adjacent relatively undisturbed border zones, in a selectively logged forest in the west-centre of Me d'Ivoire. We also evaluate the effect of time after logging (age) on these

Low-rank coal research

Energy Technology Data Exchange (ETDEWEB)

Weber, G. F.; Laudal, D. L.

1989-01-01

This work is a compilation of reports on ongoing research at the University of North Dakota. Topics include: Control Technology and Coal Preparation Research (SO{sub x}/NO{sub x} control, waste management), Advanced Research and Technology Development (turbine combustion phenomena, combustion inorganic transformation, coal/char reactivity, liquefaction reactivity of low-rank coals, gasification ash and slag characterization, fine particulate emissions), Combustion Research (fluidized bed combustion, beneficiation of low-rank coals, combustion characterization of low-rank coal fuels, diesel utilization of low-rank coals), Liquefaction Research (low-rank coal direct liquefaction), and Gasification Research (hydrogen production from low-rank coals, advanced wastewater treatment, mild gasification, color and residual COD removal from Synfuel wastewaters, Great Plains Gasification Plant, gasifier optimization).

Perils of parsimony: properties of reduced-rank estimates of genetic covariance matrices.

Science.gov (United States)

Meyer, Karin; Kirkpatrick, Mark

2008-10-01

Eigenvalues and eigenvectors of covariance matrices are important statistics for multivariate problems in many applications, including quantitative genetics. Estimates of these quantities are subject to different types of bias. This article reviews and extends the existing theory on these biases, considering a balanced one-way classification and restricted maximum-likelihood estimation. Biases are due to the spread of sample roots and arise from ignoring selected principal components when imposing constraints on the parameter space, to ensure positive semidefinite estimates or to estimate covariance matrices of chosen, reduced rank. In addition, it is shown that reduced-rank estimators that consider only the leading eigenvalues and -vectors of the "between-group" covariance matrix may be biased due to selecting the wrong subset of principal components. In a genetic context, with groups representing families, this bias is inverse proportional to the degree of genetic relationship among family members, but is independent of sample size. Theoretical results are supplemented by a simulation study, demonstrating close agreement between predicted and observed bias for large samples. It is emphasized that the rank of the genetic covariance matrix should be chosen sufficiently large to accommodate all important genetic principal components, even though, paradoxically, this may require including a number of components with negligible eigenvalues. A strategy for rank selection in practical analyses is outlined.

Development and first application of an operating events ranking tool

International Nuclear Information System (INIS)

Šimić, Zdenko; Zerger, Benoit; Banov, Reni

2015-01-01

Highlights: • A method using analitycal hierarchy process for ranking operating events is developed and tested. • The method is applied for 5 years of U.S. NRC Licensee Event Reports (1453 events). • Uncertainty and sensitivity of the ranking results are evaluated. • Real events assessment shows potential of the method for operating experience feedback. - Abstract: The operating experience feedback is important for maintaining and improving safety and availability in nuclear power plants. Detailed investigation of all events is challenging since it requires excessive resources, especially in case of large event databases. This paper presents an event groups ranking method to complement the analysis of individual operating events. The basis for the method is the use of an internationally accepted events characterization scheme that allows different ways of events grouping and ranking. The ranking method itself consists of implementing the analytical hierarchy process (AHP) by means of a custom developed tool which allows events ranking based on ranking indexes pre-determined by expert judgment. Following the development phase, the tool was applied to analyze a complete set of 5 years of real nuclear power plants operating events (1453 events). The paper presents the potential of this ranking method to identify possible patterns throughout the event database and therefore to give additional insights into the events as well as to give quantitative input for the prioritization of further more detailed investigation of selected event groups

Borehole logging

International Nuclear Information System (INIS)

Olsen, H.

1995-01-01

Numerous ground water investigations have been accomplished by means of borehole logging. Borehole logging can be applied to establish new water recovery wells, to control the existing water producing wells and source areas and to estimate ground water quality. (EG)

Rapid estimation of aquifer salinity structure from oil and gas geophysical logs

Science.gov (United States)

Shimabukuro, D.; Stephens, M.; Ducart, A.; Skinner, S. M.

2016-12-01

We describe a workflow for creating aquifer salinity maps using Archie's equation for areas that have geophysical data from oil and gas wells. We apply this method in California, where geophysical logs are available in raster format from the Division of Oil, Gas, and Geothermal Resource (DOGGR) online archive. This method should be applicable to any region where geophysical logs are readily available. Much of the work is controlled by computer code, allowing salinity estimates for new areas to be rapidly generated. For a region of interest, the DOGGR online database is scraped for wells that were logged with multi-tool suites, such as the Platform Express or Triple Combination Logging Tools. Then, well construction metadata, such as measured depth, spud date, and well orientation, is attached. The resultant local database allows a weighted criteria selection of wells that are most likely to have the shallow resistivity, deep resistivity, and density porosity measurements necessary to calculate salinity over the longest depth interval. The algorithm can be adjusted for geophysical log availability for older well fields and density of sampling. Once priority wells are identified, a student researcher team uses Neuralog software to digitize the raster geophysical logs. Total dissolved solid (TDS) concentration is then calculated in clean, wet sand intervals using the resistivity-porosity method, a modified form of Archie's equation. These sand intervals are automatically selected using a combination of spontaneous potential and the difference in shallow resistivity and deep resistivity measurements. Gamma ray logs are not used because arkosic sands common in California make it difficult to distinguish sand and shale. Computer calculation allows easy adjustment of Archie's parameters. The result is a semi-continuous TDS profile for the wells of interest. These profiles are combined and contoured using standard 3-d visualization software to yield preliminary salinity

Selection Strategies for Social Influence in the Threshold Model

Science.gov (United States)

Karampourniotis, Panagiotis; Szymanski, Boleslaw; Korniss, Gyorgy

The ubiquity of online social networks makes the study of social influence extremely significant for its applications to marketing, politics and security. Maximizing the spread of influence by strategically selecting nodes as initiators of a new opinion or trend is a challenging problem. We study the performance of various strategies for selection of large fractions of initiators on a classical social influence model, the Threshold model (TM). Under the TM, a node adopts a new opinion only when the fraction of its first neighbors possessing that opinion exceeds a pre-assigned threshold. The strategies we study are of two kinds: strategies based solely on the initial network structure (Degree-rank, Dominating Sets, PageRank etc.) and strategies that take into account the change of the states of the nodes during the evolution of the cascade, e.g. the greedy algorithm. We find that the performance of these strategies depends largely on both the network structure properties, e.g. the assortativity, and the distribution of the thresholds assigned to the nodes. We conclude that the optimal strategy needs to combine the network specifics and the model specific parameters to identify the most influential spreaders. Supported in part by ARL NS-CTA, ARO, and ONR.

Research on B Cell Algorithm for Learning to Rank Method Based on Parallel Strategy.

Science.gov (United States)

Tian, Yuling; Zhang, Hongxian

2016-01-01

For the purposes of information retrieval, users must find highly relevant documents from within a system (and often a quite large one comprised of many individual documents) based on input query. Ranking the documents according to their relevance within the system to meet user needs is a challenging endeavor, and a hot research topic-there already exist several rank-learning methods based on machine learning techniques which can generate ranking functions automatically. This paper proposes a parallel B cell algorithm, RankBCA, for rank learning which utilizes a clonal selection mechanism based on biological immunity. The novel algorithm is compared with traditional rank-learning algorithms through experimentation and shown to outperform the others in respect to accuracy, learning time, and convergence rate; taken together, the experimental results show that the proposed algorithm indeed effectively and rapidly identifies optimal ranking functions.

Logging Concessions Enable Illegal Logging Crisis in the Peruvian Amazon

Science.gov (United States)

Finer, Matt; Jenkins, Clinton N.; Sky, Melissa A. Blue; Pine, Justin

2014-04-01

The Peruvian Amazon is an important arena in global efforts to promote sustainable logging in the tropics. Despite recent efforts to achieve sustainability, such as provisions in the US-Peru Trade Promotion Agreement, illegal logging continues to plague the region. We present evidence that Peru's legal logging concession system is enabling the widespread illegal logging via the regulatory documents designed to ensure sustainable logging. Analyzing official government data, we found that 68.3% of all concessions supervised by authorities were suspected of major violations. Of the 609 total concessions, nearly 30% have been cancelled for violations and we expect this percentage to increase as investigations continue. Moreover, the nature of the violations indicate that the permits associated with legal concessions are used to harvest trees in unauthorized areas, thus threatening all forested areas. Many of the violations pertain to the illegal extraction of CITES-listed timber species outside authorized areas. These findings highlight the need for additional reforms.

Logging concessions enable illegal logging crisis in the Peruvian Amazon.

Science.gov (United States)

Finer, Matt; Jenkins, Clinton N; Sky, Melissa A Blue; Pine, Justin

2014-04-17

The Peruvian Amazon is an important arena in global efforts to promote sustainable logging in the tropics. Despite recent efforts to achieve sustainability, such as provisions in the US-Peru Trade Promotion Agreement, illegal logging continues to plague the region. We present evidence that Peru's legal logging concession system is enabling the widespread illegal logging via the regulatory documents designed to ensure sustainable logging. Analyzing official government data, we found that 68.3% of all concessions supervised by authorities were suspected of major violations. Of the 609 total concessions, nearly 30% have been cancelled for violations and we expect this percentage to increase as investigations continue. Moreover, the nature of the violations indicate that the permits associated with legal concessions are used to harvest trees in unauthorized areas, thus threatening all forested areas. Many of the violations pertain to the illegal extraction of CITES-listed timber species outside authorized areas. These findings highlight the need for additional reforms.

Maximizing crossbred performance through purebred genomic selection

DEFF Research Database (Denmark)

Esfandyari, Hadi; Sørensen, Anders Christian; Bijma, Piter

2015-01-01

Background In livestock production, many animals are crossbred, with two distinct advantages: heterosis and breed complementarity. Genomic selection (GS) can be used to select purebred parental lines for crossbred performance (CP). Dominance being the likely genetic basis of heterosis, explicitly...

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Science.gov (United States)

Fushing, Hsieh; McAssey, Michael P; Beisner, Brianne; McCowan, Brenda

2011-03-15

We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Ranking network of a captive rhesus macaque society: a sophisticated corporative kingdom.

Directory of Open Access Journals (Sweden)

Hsieh Fushing

2011-03-01

Full Text Available We develop a three-step computing approach to explore a hierarchical ranking network for a society of captive rhesus macaques. The computed network is sufficiently informative to address the question: Is the ranking network for a rhesus macaque society more like a kingdom or a corporation? Our computations are based on a three-step approach. These steps are devised to deal with the tremendous challenges stemming from the transitivity of dominance as a necessary constraint on the ranking relations among all individual macaques, and the very high sampling heterogeneity in the behavioral conflict data. The first step simultaneously infers the ranking potentials among all network members, which requires accommodation of heterogeneous measurement error inherent in behavioral data. Our second step estimates the social rank for all individuals by minimizing the network-wide errors in the ranking potentials. The third step provides a way to compute confidence bounds for selected empirical features in the social ranking. We apply this approach to two sets of conflict data pertaining to two captive societies of adult rhesus macaques. The resultant ranking network for each society is found to be a sophisticated mixture of both a kingdom and a corporation. Also, for validation purposes, we reanalyze conflict data from twenty longhorn sheep and demonstrate that our three-step approach is capable of correctly computing a ranking network by eliminating all ranking error.

Selecting ground-motion models developed for induced seismicity in geothermal areas

Science.gov (United States)

Edwards, Benjamin; Douglas, John

2013-11-01

We present a case study of the ranking and weighting of ground-motion prediction equations (GMPEs) for seismic hazard assessment of enhanced geothermal systems (EGSs). The study region is Cooper Basin (Australia), where a hot-fractured-rock project was established in 2002. We test the applicability of 36 GMPEs based on stochastic simulations previously proposed for use at EGSs. Each GMPE has a set of corresponding model parameters describing stress drop, regional and local (near-surface) attenuation. To select suitable GMPEs for Cooper Basin from the full set, we applied two methods. In the first, seismograms recorded on the local monitoring network were spectrally analysed to determine characteristic stress and attenuation parameters. In a second approach, residual analysis using the log-likelihood (LLH) method was used to directly compare recorded and predicted short-period response spectral accelerations. The resulting ranking was consistent with the models selected based on spectral analysis, with the advantage that a transparent weighting approach was available using the LLH method. Region-specific estimates of variability were computed, with significantly lower values observed compared to previous studies of small earthquakes. This was consistent with the limited range of stress drops and attenuation observed from the spectral analysis.

Diagnosing and Ranking Retinopathy Disease Level Using Diabetic Fundus Image Recuperation Approach

Directory of Open Access Journals (Sweden)

K. Somasundaram

2015-01-01

Full Text Available Retinal fundus images are widely used in diagnosing different types of eye diseases. The existing methods such as Feature Based Macular Edema Detection (FMED and Optimally Adjusted Morphological Operator (OAMO effectively detected the presence of exudation in fundus images and identified the true positive ratio of exudates detection, respectively. These mechanically detected exudates did not include more detailed feature selection technique to the system for detection of diabetic retinopathy. To categorize the exudates, Diabetic Fundus Image Recuperation (DFIR method based on sliding window approach is developed in this work to select the features of optic cup in digital retinal fundus images. The DFIR feature selection uses collection of sliding windows with varying range to obtain the features based on the histogram value using Group Sparsity Nonoverlapping Function. Using support vector model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy disease level. The ranking of disease level on each candidate set provides a much promising result for developing practically automated and assisted diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, ranking efficiency, and feature selection time.

Single-trial log transformation is optimal in frequency analysis of resting EEG alpha.

Science.gov (United States)

Smulders, Fren T Y; Ten Oever, Sanne; Donkers, Franc C L; Quaedflieg, Conny W E M; van de Ven, Vincent

2018-02-01

The appropriate definition and scaling of the magnitude of electroencephalogram (EEG) oscillations is an underdeveloped area. The aim of this study was to optimize the analysis of resting EEG alpha magnitude, focusing on alpha peak frequency and nonlinear transformation of alpha power. A family of nonlinear transforms, Box-Cox transforms, were applied to find the transform that (a) maximized a non-disputed effect: the increase in alpha magnitude when the eyes are closed (Berger effect), and (b) made the distribution of alpha magnitude closest to normal across epochs within each participant, or across participants. The transformations were performed either at the single epoch level or at the epoch-average level. Alpha peak frequency showed large individual differences, yet good correspondence between various ways to estimate it in 2 min of eyes-closed and 2 min of eyes-open resting EEG data. Both alpha magnitude and the Berger effect were larger for individual alpha than for a generic (8-12 Hz) alpha band. The log-transform on single epochs (a) maximized the t-value of the contrast between the eyes-open and eyes-closed conditions when tested within each participant, and (b) rendered near-normally distributed alpha power across epochs and participants, thereby making further transformation of epoch averages superfluous. The results suggest that the log-normal distribution is a fundamental property of variations in alpha power across time in the order of seconds. Moreover, effects on alpha power appear to be multiplicative rather than additive. These findings support the use of the log-transform on single epochs to achieve appropriate scaling of alpha magnitude. © 2018 The Authors. European Journal of Neuroscience published by Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

A Multi-temporal Analysis of Logging Impacts on Tropical Forest Structure Using Airborne Lidar Data

Science.gov (United States)

Keller, M. M.; Pinagé, E. R.; Duffy, P.; Longo, M.; dos-Santos, M. N.; Leitold, V.; Morton, D. C.

2017-12-01

The long-term impacts of selective logging on carbon cycling and ecosystem function in tropical-forests are still uncertain. Despite improvements in selective logging detection using satellite data, quantifying changes in forest structure from logging and recovery following logging is difficult using orbital data. We analyzed the dynamics of forest structure comparing logged and unlogged forests in the Eastern Brazilian Amazon (Paragominas Municipality, Pará State) using small footprint discrete return airborne lidar data acquired in 2012 and 2014. Logging operations were conducted at the 1200 ha study site from 2006 through 2013 using reduced impact logging techniques—management practices that minimize canopy and ground damage compared to more common conventional logging. Nevertheless, logging still reduced aboveground biomass by 10% to 20% in logged areas compared to intact forests. We aggregated lidar point-cloud data at spatial scales ranging from 50 m to 250 m and developed a binomial classification model based on the height distribution of lidar returns in 2012 and validated the model against the 2014 lidar acquisition. We accurately classified intact and logged forest classes compared with field data. Classification performance improved as spatial resolution increased (AUC = 0.974 at 250 m). We analyzed the differences in canopy gaps, understory damage (based on a relative density model), and biomass (estimated from total canopy height) of intact and logged classes. As expected, logging greatly increased both canopy gap formation and understory damage. However, while the area identified as canopy gap persisted for at least 8 years (from the oldest logging treatments in 2006 to the most recent lidar acquisition in 2014), the effects of ground damage were mostly erased by vigorous understory regrowth after about 5 years. The rate of new gap formation was 6 to 7 times greater in recently logged forests compared to undisturbed forests. New gaps opened at a

Rationality alters the rank between peer punishment and social exclusion

Science.gov (United States)

Sui, Xiukai; Wu, Bin; Wang, Long

2018-02-01

Peer punishment and social exclusion are two ways to punish free-riders. Previous work usually focuses on how their presence, either peer punishment or social exclusion, shapes the evolution of cooperation. Little attention has been given to which of these two strategies is favored by natural selection when they are both present. Here we investigate how rationality alters the ranking of these two strategies. Under weak rationality, for compulsory public goods games, peer punishment has an evolutionary advantage over social exclusion if the efficiency of punishment or the cost of exclusion is high. Furthermore, this rank is preserved for voluntary public goods games where loners are involved. Under strong rationality, however, peer punishment cannot prevail over social exclusion for both compulsory and voluntary public goods games. This indicates that rationality greatly alters the rank between peer punishment and social exclusion. Moreover, we find that this ranking is sensitive to the rationality. Our work thus gives an insight into how different types of punishment evolve.

Sparse structure regularized ranking

KAUST Repository

Wang, Jim Jing-Yan; Sun, Yijun; Gao, Xin

2014-01-01

Learning ranking scores is critical for the multimedia database retrieval problem. In this paper, we propose a novel ranking score learning algorithm by exploring the sparse structure and using it to regularize ranking scores. To explore the sparse

Minimizing bias in biomass allometry: Model selection and log transformation of data

Science.gov (United States)

Joseph Mascaro; undefined undefined; Flint Hughes; Amanda Uowolo; Stefan A. Schnitzer

2011-01-01

Nonlinear regression is increasingly used to develop allometric equations for forest biomass estimation (i.e., as opposed to the raditional approach of log-transformation followed by linear regression). Most statistical software packages, however, assume additive errors by default, violating a key assumption of allometric theory and possibly producing spurious models....

A legacy of low-impact logging does not elevate prevalence of potentially pathogenic protozoa in free-ranging gorillas and chimpanzees in the Republic of Congo: logging and parasitism in African apes.

Science.gov (United States)

Gillespie, Thomas R; Morgan, David; Deutsch, J Charlie; Kuhlenschmidt, Mark S; Salzer, Johanna S; Cameron, Kenneth; Reed, Trish; Sanz, Crickette

2009-12-01

Many studies have examined the long-term effects of selective logging on the abundance and diversity of free-ranging primates. Logging is known to reduce the abundance of some primate species through associated hunting and the loss of food trees for frugivores; however, the potential role of pathogens in such primate population declines is largely unexplored. Selective logging results in a suite of alterations in host ecology and forest structure that may alter pathogen dynamics in resident wildlife populations. In addition, environmental pollution with human fecal material may present a risk for wildlife infections with zoonotic protozoa, such as Cryptosporidium and Giardia. To better understand this interplay, we compared patterns of infection with these potentially pathogenic protozoa in sympatric western lowland gorillas (Gorilla gorilla gorilla) and chimpanzees (Pan troglodytes troglodytes) in the undisturbed Goualougo Triangle of Nouabalé-Ndoki National Park and the adjacent previously logged Kabo Concession in northern Republic of Congo. No Cryptosporidium infections were detected in any of the apes examined and prevalence of infection with Giardia was low (3.73% overall) and did not differ between logged and undisturbed forest for chimpanzees or gorillas. These results provide a baseline for prevalence of these protozoa in forest-dwelling African apes and suggest that low-intensity logging may not result in long-term elevated prevalence of potentially pathogenic protozoa.

Strategic alternatives ranking methodology: Multiple RCRA incinerator evaluation test case

International Nuclear Information System (INIS)

Baker, G.; Thomson, R.D.; Reece, J.; Springer, L.; Main, D.

1988-01-01

This paper presents an important process approach to permit quantification and ranking of multiple alternatives being considered in remedial actions or hazardous waste strategies. This process is a methodology for evaluating programmatic options in support of site selection or environmental analyses. Political or other less tangible motivations for alternatives may be quantified by means of establishing the range of significant variables, weighting their importance, and by establishing specific criteria for scoring individual alternatives. An application of the process to a recent AFLC program permitted ranking incineration alternatives from a list of over 130 options. The process forced participation by the organizations to be effected, allowed a consensus of opinion to be achieved, allowed complete flexibility to evaluate factor sensitivity, and resulted in strong, quantifiable support for any subsequent site-selection action NEPA documents

Maximal Bell's inequality violation for non-maximal entanglement

International Nuclear Information System (INIS)

Kobayashi, M.; Khanna, F.; Mann, A.; Revzen, M.; Santana, A.

2004-01-01

Bell's inequality violation (BIQV) for correlations of polarization is studied for a product state of two two-mode squeezed vacuum (TMSV) states. The violation allowed is shown to attain its maximal limit for all values of the squeezing parameter, ζ. We show via an explicit example that a state whose entanglement is not maximal allow maximal BIQV. The Wigner function of the state is non-negative and the average value of either polarization is nil

Predictive-property-ranked variable reduction in partial least squares modelling with final complexity adapted models: comparison of properties for ranking.

Science.gov (United States)

Andries, Jan P M; Vander Heyden, Yvan; Buydens, Lutgarde M C

2013-01-14

The calibration performance of partial least squares regression for one response (PLS1) can be improved by eliminating uninformative variables. Many variable-reduction methods are based on so-called predictor-variable properties or predictive properties, which are functions of various PLS-model parameters, and which may change during the steps of the variable-reduction process. Recently, a new predictive-property-ranked variable reduction method with final complexity adapted models, denoted as PPRVR-FCAM or simply FCAM, was introduced. It is a backward variable elimination method applied on the predictive-property-ranked variables. The variable number is first reduced, with constant PLS1 model complexity A, until A variables remain, followed by a further decrease in PLS complexity, allowing the final selection of small numbers of variables. In this study for three data sets the utility and effectiveness of six individual and nine combined predictor-variable properties are investigated, when used in the FCAM method. The individual properties include the absolute value of the PLS1 regression coefficient (REG), the significance of the PLS1 regression coefficient (SIG), the norm of the loading weight (NLW) vector, the variable importance in the projection (VIP), the selectivity ratio (SR), and the squared correlation coefficient of a predictor variable with the response y (COR). The selective and predictive performances of the models resulting from the use of these properties are statistically compared using the one-tailed Wilcoxon signed rank test. The results indicate that the models, resulting from variable reduction with the FCAM method, using individual or combined properties, have similar or better predictive abilities than the full spectrum models. After mean-centring of the data, REG and SIG, provide low numbers of informative variables, with a meaning relevant to the response, and lower than the other individual properties, while the predictive abilities are

Geophysical borehole logging in selected areas in the Greater Accra plains and the Densu river basin

International Nuclear Information System (INIS)

Amartey, E. A.

2009-06-01

Geophysical borehole logging was complemented by Vertical Electrical Sounding (VES) method to study fractured bedrock aquifer systems on the compounds of Ghana Atomic Energy Commission (GAEC), Water Research Institute (WRI) in the Accra Plains and the Hydrometric Station of the Department of Geology, University of Ghana at Buokrom in the Densu River Basin. Single-point resistance, resistivity and natural gamma logging in a total of nine boreholes were conducted to identify and characterize the various aquifers in the study areas. Results obtained from the single-point resistance and resistivity logs showed clearly the characteristics of water-bearing fracture zones in the various rock formations. The gamma logs obtained for each area were correlated to form hydrostratigraphic units to establish potential zones of high water-bearing fractures. VES modeled curves shows hydrogeological units of the geological formation which compares well with features obtained on the logs. The investigation identified fractured zone thicknesses of <1 m to 2 m at GAEC area, <1 m to 9 m at WRI area and <1 m to 10 m thicknesses at the Buokrom area. The fractured bedrock aquifers identified have been characterized based on their thicknesses as follows. Five minor (thickness < 5 m), two medium (thickness 5 m to 14 m) and three major (thickness ⩾15 m) fractures were identified at the GAEC area. At the WRI area three minor and five medium fractures were identified. Also four minor and five medium fractures were identified for the Buokrom area boreholes. (au)

SIP-FS: a novel feature selection for data representation

Directory of Open Access Journals (Sweden)

Yiyou Guo

2018-02-01

Full Text Available Abstract Multiple features are widely used to characterize real-world datasets. It is desirable to select leading features with stability and interpretability from a set of distinct features for a comprehensive data description. However, most of existing feature selection methods focus on the predictability (e.g., prediction accuracy of selected results yet neglect stability. To obtain compact data representation, a novel feature selection method is proposed to improve stability, and interpretability without sacrificing predictability (SIP-FS. Instead of mutual information, generalized correlation is adopted in minimal redundancy maximal relevance to measure the relation between different feature types. Several feature types (each contains a certain number of features can then be selected and evaluated quantitatively to determine what types contribute to a specific class, thereby enhancing the so-called interpretability of features. Moreover, stability is introduced in the criterion of SIP-FS to obtain consistent results of ranking. We conduct experiments on three publicly available datasets using one-versus-all strategy to select class-specific features. The experiments illustrate that SIP-FS achieves significant performance improvements in terms of stability and interpretability with desirable prediction accuracy and indicates advantages over several state-of-the-art approaches.

Many-Objective Optimization Using Adaptive Differential Evolution with a New Ranking Method

Directory of Open Access Journals (Sweden)

Xiaoguang He

2014-01-01

Full Text Available Pareto dominance is an important concept and is usually used in multiobjective evolutionary algorithms (MOEAs to determine the nondominated solutions. However, for many-objective problems, using Pareto dominance to rank the solutions even in the early generation, most obtained solutions are often the nondominated solutions, which results in a little selection pressure of MOEAs toward the optimal solutions. In this paper, a new ranking method is proposed for many-objective optimization problems to verify a relatively smaller number of representative nondominated solutions with a uniform and wide distribution and improve the selection pressure of MOEAs. After that, a many-objective differential evolution with the new ranking method (MODER for handling many-objective optimization problems is designed. At last, the experiments are conducted and the proposed algorithm is compared with several well-known algorithms. The experimental results show that the proposed algorithm can guide the search to converge to the true PF and maintain the diversity of solutions for many-objective problems.

Use of search engine optimization factors for Google page rank prediction

OpenAIRE

Tvrdi, Barbara

2012-01-01

Over the years, search engines have become an important tool for finding information. It is known that users select the link on the first page of search results in 62% of the cases. Search engine optimization techniques enable website improvement and therefore a better ranking in search engines. The exact specification of the factors that affect website ranking is not disclosed by search engine owners. In this thesis we tried to choose some most frequently mentioned search engine optimizatio...

Target recognition of log-polar ladar range images using moment invariants

Science.gov (United States)

Xia, Wenze; Han, Shaokun; Cao, Jie; Yu, Haoyong

2017-01-01

The ladar range image has received considerable attentions in the automatic target recognition field. However, previous research does not cover target recognition using log-polar ladar range images. Therefore, we construct a target recognition system based on log-polar ladar range images in this paper. In this system combined moment invariants and backpropagation neural network are selected as shape descriptor and shape classifier, respectively. In order to fully analyze the effect of log-polar sampling pattern on recognition result, several comparative experiments based on simulated and real range images are carried out. Eventually, several important conclusions are drawn: (i) if combined moments are computed directly by log-polar range images, translation, rotation and scaling invariant properties of combined moments will be invalid (ii) when object is located in the center of field of view, recognition rate of log-polar range images is less sensitive to the changing of field of view (iii) as object position changes from center to edge of field of view, recognition performance of log-polar range images will decline dramatically (iv) log-polar range images has a better noise robustness than Cartesian range images. Finally, we give a suggestion that it is better to divide field of view into recognition area and searching area in the real application.

On the number of vertices of each rank in phylogenetic trees and their generalizations

OpenAIRE

Bóna, Miklós

2015-01-01

We find surprisingly simple formulas for the limiting probability that the rank of a randomly selected vertex in a randomly selected phylogenetic tree or generalized phylogenetic tree is a given integer.

rpsftm: An R Package for Rank Preserving Structural Failure Time Models.

Science.gov (United States)

Allison, Annabel; White, Ian R; Bond, Simon

2017-12-04

Treatment switching in a randomised controlled trial occurs when participants change from their randomised treatment to the other trial treatment during the study. Failure to account for treatment switching in the analysis (i.e. by performing a standard intention-to-treat analysis) can lead to biased estimates of treatment efficacy. The rank preserving structural failure time model (RPSFTM) is a method used to adjust for treatment switching in trials with survival outcomes. The RPSFTM is due to Robins and Tsiatis (1991) and has been developed by White et al. (1997, 1999). The method is randomisation based and uses only the randomised treatment group, observed event times, and treatment history in order to estimate a causal treatment effect. The treatment effect, ψ , is estimated by balancing counter-factual event times (that would be observed if no treatment were received) between treatment groups. G-estimation is used to find the value of ψ such that a test statistic Z ( ψ ) = 0. This is usually the test statistic used in the intention-to-treat analysis, for example, the log rank test statistic. We present an R package that implements the method of rpsftm.

Maximizing and customer loyalty: Are maximizers less loyal?

Directory of Open Access Journals (Sweden)

Linda Lai

2011-06-01

Full Text Available Despite their efforts to choose the best of all available solutions, maximizers seem to be more inclined than satisficers to regret their choices and to experience post-decisional dissonance. Maximizers may therefore be expected to change their decisions more frequently and hence exhibit lower customer loyalty to providers of products and services compared to satisficers. Findings from the study reported here (N = 1978 support this prediction. Maximizers reported significantly higher intentions to switch to another service provider (television provider than satisficers. Maximizers' intentions to switch appear to be intensified and mediated by higher proneness to regret, increased desire to discuss relevant choices with others, higher levels of perceived knowledge of alternatives, and higher ego involvement in the end product, compared to satisficers. Opportunities for future research are suggested.

A strong response to selection on mass-independent maximal metabolic rate without a correlated response in basal metabolic rate.

Science.gov (United States)

Wone, B W M; Madsen, P; Donovan, E R; Labocha, M K; Sears, M W; Downs, C J; Sorensen, D A; Hayes, J P

2015-04-01

Metabolic rates are correlated with many aspects of ecology, but how selection on different aspects of metabolic rates affects their mutual evolution is poorly understood. Using laboratory mice, we artificially selected for high maximal mass-independent metabolic rate (MMR) without direct selection on mass-independent basal metabolic rate (BMR). Then we tested for responses to selection in MMR and correlated responses to selection in BMR. In other lines, we antagonistically selected for mice with a combination of high mass-independent MMR and low mass-independent BMR. All selection protocols and data analyses included body mass as a covariate, so effects of selection on the metabolic rates are mass adjusted (that is, independent of effects of body mass). The selection lasted eight generations. Compared with controls, MMR was significantly higher (11.2%) in lines selected for increased MMR, and BMR was slightly, but not significantly, higher (2.5%). Compared with controls, MMR was significantly higher (5.3%) in antagonistically selected lines, and BMR was slightly, but not significantly, lower (4.2%). Analysis of breeding values revealed no positive genetic trend for elevated BMR in high-MMR lines. A weak positive genetic correlation was detected between MMR and BMR. That weak positive genetic correlation supports the aerobic capacity model for the evolution of endothermy in the sense that it fails to falsify a key model assumption. Overall, the results suggest that at least in these mice there is significant capacity for independent evolution of metabolic traits. Whether that is true in the ancestral animals that evolved endothermy remains an important but unanswered question.

Multiplex PageRank.

Directory of Open Access Journals (Sweden)

Arda Halu

Full Text Available Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Multiplex PageRank.

Science.gov (United States)

Halu, Arda; Mondragón, Raúl J; Panzarasa, Pietro; Bianconi, Ginestra

2013-01-01

Many complex systems can be described as multiplex networks in which the same nodes can interact with one another in different layers, thus forming a set of interacting and co-evolving networks. Examples of such multiplex systems are social networks where people are involved in different types of relationships and interact through various forms of communication media. The ranking of nodes in multiplex networks is one of the most pressing and challenging tasks that research on complex networks is currently facing. When pairs of nodes can be connected through multiple links and in multiple layers, the ranking of nodes should necessarily reflect the importance of nodes in one layer as well as their importance in other interdependent layers. In this paper, we draw on the idea of biased random walks to define the Multiplex PageRank centrality measure in which the effects of the interplay between networks on the centrality of nodes are directly taken into account. In particular, depending on the intensity of the interaction between layers, we define the Additive, Multiplicative, Combined, and Neutral versions of Multiplex PageRank, and show how each version reflects the extent to which the importance of a node in one layer affects the importance the node can gain in another layer. We discuss these measures and apply them to an online multiplex social network. Findings indicate that taking the multiplex nature of the network into account helps uncover the emergence of rankings of nodes that differ from the rankings obtained from one single layer. Results provide support in favor of the salience of multiplex centrality measures, like Multiplex PageRank, for assessing the prominence of nodes embedded in multiple interacting networks, and for shedding a new light on structural properties that would otherwise remain undetected if each of the interacting networks were analyzed in isolation.

Study of the reservoirs of Jurassic and Cretaceous periods in the south-cast slope of Central Kara-Kum vault using combination of acoustic logging, neutron-gamma logging, gamma logging, and electrical logging

International Nuclear Information System (INIS)

Meredov, T.M.; Baranov, M.I.

1978-01-01

Considered is the possibility of application of the combination of neutron-gamma logging, gamma logging al partitioncoustic logging and electrical logging to lithologica of sections, discovery reservoir layers in carbonate and terrigeneous sections as well as quantitative estimation of the porosity coefficients values at prospecting areas in the south-east slope of Central Kara-Kum vault. Neutron-gamma logging mostly makes it possible to partition carbonate rocks into limestones, dolomites and their interstitial variaties and to indicate sand stone layers with different degree of carbonate content

Ensemble Manifold Rank Preserving for Acceleration-Based Human Activity Recognition.

Science.gov (United States)

Tao, Dapeng; Jin, Lianwen; Yuan, Yuan; Xue, Yang

2016-06-01

With the rapid development of mobile devices and pervasive computing technologies, acceleration-based human activity recognition, a difficult yet essential problem in mobile apps, has received intensive attention recently. Different acceleration signals for representing different activities or even a same activity have different attributes, which causes troubles in normalizing the signals. We thus cannot directly compare these signals with each other, because they are embedded in a nonmetric space. Therefore, we present a nonmetric scheme that retains discriminative and robust frequency domain information by developing a novel ensemble manifold rank preserving (EMRP) algorithm. EMRP simultaneously considers three aspects: 1) it encodes the local geometry using the ranking order information of intraclass samples distributed on local patches; 2) it keeps the discriminative information by maximizing the margin between samples of different classes; and 3) it finds the optimal linear combination of the alignment matrices to approximate the intrinsic manifold lied in the data. Experiments are conducted on the South China University of Technology naturalistic 3-D acceleration-based activity dataset and the naturalistic mobile-devices based human activity dataset to demonstrate the robustness and effectiveness of the new nonmetric scheme for acceleration-based human activity recognition.

Improving Ranking Using Quantum Probability

OpenAIRE

Melucci, Massimo

2011-01-01

The paper shows that ranking information units by quantum probability differs from ranking them by classical probability provided the same data used for parameter estimation. As probability of detection (also known as recall or power) and probability of false alarm (also known as fallout or size) measure the quality of ranking, we point out and show that ranking by quantum probability yields higher probability of detection than ranking by classical probability provided a given probability of ...

Socially selected ornaments and fitness: Signals of fighting ability in paper wasps are positively associated with survival, reproductive success, and rank.

Science.gov (United States)

Tibbetts, Elizabeth A; Forrest, Taylor; Vernier, Cassondra; Jinn, Judy; Madagame, Andrew

2015-11-01

Many animals have ornaments that mediate choice and competition in social and sexual contexts. Individuals with elaborate sexual ornaments typically have higher fitness than those with less elaborate ornaments, but less is known about whether socially selected ornaments are associated with fitness. Here, we test the relationship between fitness and facial patterns that are a socially selected signal of fighting ability in Polistes dominula wasps. We found wasps that signal higher fighting ability have larger nests, are more likely to survive harsh winters, and obtain higher dominance rank than wasps that signal lower fighting ability. In comparison, body weight was not associated with fitness. Larger wasps were dominant over smaller wasps, but showed no difference in nest size or survival. Overall, the positive relationship between wasp facial patterns and fitness indicates that receivers can obtain diverse information about a signaler's phenotypic quality by paying attention to socially selected ornaments. Therefore, there are surprisingly strong parallels between the information conveyed by socially and sexually selected signals. Similar fitness relationships in social and sexually selected signals may be one reason it can be difficult to distinguish the role of social versus sexual selection in ornament evolution. © 2015 The Author(s). Evolution © 2015 The Society for the Study of Evolution.

The Meaning of Logs

NARCIS (Netherlands)

Etalle, Sandro; Massacci, Fabio; Yautsiukhin, Artsiom

2007-01-01

While logging events is becoming increasingly common in computing, in communication and in collaborative work, log systems need to satisfy increasingly challenging (if not conflicting) requirements.Despite the growing pervasiveness of log systems, to date there is no high-level framework which

The Meaning of Logs

NARCIS (Netherlands)

Etalle, Sandro; Massacci, Fabio; Yautsiukhin, Artsiom; Lambrinoudakis, Costas; Pernul, Günther; Tjoa, A Min

While logging events is becoming increasingly common in computing, in communication and in collaborative environments, log systems need to satisfy increasingly challenging (if not conflicting) requirements. In this paper we propose a high-level framework for modeling log systems, and reasoning about

Comparing rankings of selected TRI organic chemicals for two environments using a level III fugacity model and toxicity

International Nuclear Information System (INIS)

Edwards, F.G.; Egemen, E.; Nirmalakhandan, N.

1998-01-01

The Toxics Release Inventory, TRI (USEPA, 1995) is a comprehensive listing of chemicals, mass released, source of releases, and other related information for chemicals which are released into the environment in the US. These chemicals are then ranked according to the mass released as a indication of their environmental impact. Industries have been encouraged to adopt production methods to decrease the release of chemicals which are ranked highly in the TRI. Clearly, this ranking of the chemicals based upon the mass released fails to take into account very important environmental aspects. The first and most obvious aspect is the wide range of toxicity's of the chemicals released. Numerous researchers have proposed systems to rank chemicals according to their toxicity. The second aspect, which a mass released based ranking does not take into account, is the fate and transport of each chemical within the environment. Cohen and Ryan (1985) and Mackay and Paterson (1991) have proposed models to evaluate the fate and transport of chemicals released into the environment. Some authors have incorporated the mass released and toxicity with some fate and transport aspects to rank the impact of released chemicals. But, due to the complexities of modeling the environment, the lack of published data on properties of chemicals, and the lack of information on the speciation of chemicals in complex systems, modeling the fate and transport of toxic chemicals in the environment remains difficult. To provide an indication of the need to rank chemicals according to their environmental impact instead of the mass released, the authors have utilized a subset of 45 organic chemicals from the TRI, modeled the fate and transport of the chemicals using a Level III fugacity model, and compared those equilibrium concentrations with toxicity data to yield a hazard value for each chemical

How Many Alternatives Can Be Ranked? A Comparison of the Paired Comparison and Ranking Methods.

Science.gov (United States)

Ock, Minsu; Yi, Nari; Ahn, Jeonghoon; Jo, Min-Woo

2016-01-01

To determine the feasibility of converting ranking data into paired comparison (PC) data and suggest the number of alternatives that can be ranked by comparing a PC and a ranking method. Using a total of 222 health states, a household survey was conducted in a sample of 300 individuals from the general population. Each respondent performed a PC 15 times and a ranking method 6 times (two attempts of ranking three, four, and five health states, respectively). The health states of the PC and the ranking method were constructed to overlap each other. We converted the ranked data into PC data and examined the consistency of the response rate. Applying probit regression, we obtained the predicted probability of each method. Pearson correlation coefficients were determined between the predicted probabilities of those methods. The mean absolute error was also assessed between the observed and the predicted values. The overall consistency of the response rate was 82.8%. The Pearson correlation coefficients were 0.789, 0.852, and 0.893 for ranking three, four, and five health states, respectively. The lowest mean absolute error was 0.082 (95% confidence interval [CI] 0.074-0.090) in ranking five health states, followed by 0.123 (95% CI 0.111-0.135) in ranking four health states and 0.126 (95% CI 0.113-0.138) in ranking three health states. After empirically examining the consistency of the response rate between a PC and a ranking method, we suggest that using five alternatives in the ranking method may be superior to using three or four alternatives. Copyright © 2016 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Review of magnetic susceptibility logging and its application to uranium exploration

International Nuclear Information System (INIS)

George, D.C.; Scott, J.H.

1982-01-01

Borehole measurement of magnetic susceptibility can show anomalies associated with mineralization or alteration. The detection of small anomalies is necessary, so efforts have been made in recent years to improve the sensitivity and the stability of magnetic susceptibility logging tools. Typical tools contain a single coil constructed as a solenoid wound on ferrite rods about 30cm long. The coil is heated to a constant temperature to reduce drift, and careful design is necessary to optimize temperature control and to maximize sensitivity. Measurements of coil resistance and inductance, which indicate conductivity and susceptibility, are made using a Maxwell bridge circuit. Circuit analysis shows that conductivity measurements are difficult and that stringent requirements are placed on phase stability of measurement circuitry. Corrections to the observed log are necessary to account for borehole size. The response of the tool to a thin zones of anomalous susceptibility is double peaked and a set of curves has been developed for interpretation. Calibrations of the tools are made by measuring the tool's response in models of known susceptibility

Neophilia Ranking of Scientific Journals.

Science.gov (United States)

Packalen, Mikko; Bhattacharya, Jay

2017-01-01

The ranking of scientific journals is important because of the signal it sends to scientists about what is considered most vital for scientific progress. Existing ranking systems focus on measuring the influence of a scientific paper (citations)-these rankings do not reward journals for publishing innovative work that builds on new ideas. We propose an alternative ranking based on the proclivity of journals to publish papers that build on new ideas, and we implement this ranking via a text-based analysis of all published biomedical papers dating back to 1946. In addition, we compare our neophilia ranking to citation-based (impact factor) rankings; this comparison shows that the two ranking approaches are distinct. Prior theoretical work suggests an active role for our neophilia index in science policy. Absent an explicit incentive to pursue novel science, scientists underinvest in innovative work because of a coordination problem: for work on a new idea to flourish, many scientists must decide to adopt it in their work. Rankings that are based purely on influence thus do not provide sufficient incentives for publishing innovative work. By contrast, adoption of the neophilia index as part of journal-ranking procedures by funding agencies and university administrators would provide an explicit incentive for journals to publish innovative work and thus help solve the coordination problem by increasing scientists' incentives to pursue innovative work.

Hierarchical partial order ranking

International Nuclear Information System (INIS)

Carlsen, Lars

2008-01-01

Assessing the potential impact on environmental and human health from the production and use of chemicals or from polluted sites involves a multi-criteria evaluation scheme. A priori several parameters are to address, e.g., production tonnage, specific release scenarios, geographical and site-specific factors in addition to various substance dependent parameters. Further socio-economic factors may be taken into consideration. The number of parameters to be included may well appear to be prohibitive for developing a sensible model. The study introduces hierarchical partial order ranking (HPOR) that remedies this problem. By HPOR the original parameters are initially grouped based on their mutual connection and a set of meta-descriptors is derived representing the ranking corresponding to the single groups of descriptors, respectively. A second partial order ranking is carried out based on the meta-descriptors, the final ranking being disclosed though average ranks. An illustrative example on the prioritisation of polluted sites is given. - Hierarchical partial order ranking of polluted sites has been developed for prioritization based on a large number of parameters

Top News Events of 1973 Ranked for Educators.

Science.gov (United States)

Burdin, Joel L.

This document presents a listing of those news events for 1973 that are thought by the author to have the most immediate or potential significance for educators. It is noted that the selections were made primarily from the "Washington Post,""Washington Star-News,""New York Times," and weekly news magazines. The events, ranked in order of present…

Portfolio selection using ELECTRE III: Evidence from Tehran Stock Exchange

Directory of Open Access Journals (Sweden)

Aazam Shabani Vezmelai

2015-04-01

Full Text Available Ranking the companies can be a useful guide for investors to select an optimum portfolio. Tehran stock exchange (TSE uses liquidity criterion to rank the companies; however, this study shows that preferences of investors, the criteria they use to evaluate companies’ performances, and the extent to which ranking of companies based on investors’ criteria are in line with the ranking announced by the stock exchange. Since the criteria used for ranking the companies are various and often conflicting and because each multiple criteria technique has its own specific characteristics, various rankings are offered. Therefore, it is required to utilize multiple criteria decision making models to avoid confusion of investors. For this purpose, some companies were selected from 50 top companies listed in 2011 in TSE, which maintained the reliability of their ranks and finally, 20 companies were selected and were ranked based on investors’ criteria using EECTRE III Technique. The obtained ranking was then compared with the ranking offered by stock exchange. Research results indicate that ELECTRE III technique was a useful and efficient method to select a portfolio. Moreover, value-based criteria as well as accounting criteria are suitable and useful bases for investors to select a portfolio.

Effects of post-fire logging on California spotted owl occupancy

Directory of Open Access Journals (Sweden)

Chad T. Hanson

2018-01-01

Full Text Available In fire-adapted forest ecosystems around the world, there has been growing concern about adverse impacts of post-fire logging on native biodiversity and ecological processes. This is also true in conifer forests of California, U.S.A. which are home to a rare and declining owl subspecies, the California spotted owl (Strix occidentalis occidentalis. While there has been recent concern about the California spotted owl occupancy in large fire areas where some territories have substantial high-severity fire effects, the influence of post-fire logging on the California spotted owl occupancy has been investigated very little, leading to some uncertainty about interpretation of conflicting results in different large fires. Research has found these owls preferentially select high-severity fire areas, characterised by high levels of snags and native shrubs, for foraging in forests that were not logged after fire, suggesting that removal of this foraging habitat might impact occupancy. The authors assessed the effect of post-fire logging and high-severity fire, on occupancy of this subspecies in eight large fire areas, within spotted owl sites with two different levels of high-severity fire effects. They found a significant adverse effect of such logging and no effect of high-severity fire alone. These results indicate it is post-fire logging, not large fires themselves, that poses a conservation threat to this imperilled species.

A Survey on PageRank Computing

OpenAIRE

Berkhin, Pavel

2005-01-01

This survey reviews the research related to PageRank computing. Components of a PageRank vector serve as authority weights for web pages independent of their textual content, solely based on the hyperlink structure of the web. PageRank is typically used as a web search ranking component. This defines the importance of the model and the data structures that underly PageRank processing. Computing even a single PageRank is a difficult computational task. Computing many PageRanks is a much mor...

THE USE OF RANKING SAMPLING METHOD WITHIN MARKETING RESEARCH

Directory of Open Access Journals (Sweden)

CODRUŢA DURA

2011-01-01

Full Text Available Marketing and statistical literature available to practitioners provides a wide range of sampling methods that can be implemented in the context of marketing research. Ranking sampling method is based on taking apart the general population into several strata, namely into several subdivisions which are relatively homogenous regarding a certain characteristic. In fact, the sample will be composed by selecting, from each stratum, a certain number of components (which can be proportional or non-proportional to the size of the stratum until the pre-established volume of the sample is reached. Using ranking sampling within marketing research requires the determination of some relevant statistical indicators - average, dispersion, sampling error etc. To that end, the paper contains a case study which illustrates the actual approach used in order to apply the ranking sample method within a marketing research made by a company which provides Internet connection services, on a particular category of customers – small and medium enterprises.

A Selective Role for Dopamine in Learning to Maximize Reward But Not to Minimize Effort: Evidence from Patients with Parkinson's Disease.

Science.gov (United States)

Skvortsova, Vasilisa; Degos, Bertrand; Welter, Marie-Laure; Vidailhet, Marie; Pessiglione, Mathias

2017-06-21

Instrumental learning is a fundamental process through which agents optimize their choices, taking into account various dimensions of available options such as the possible reward or punishment outcomes and the costs associated with potential actions. Although the implication of dopamine in learning from choice outcomes is well established, less is known about its role in learning the action costs such as effort. Here, we tested the ability of patients with Parkinson's disease (PD) to maximize monetary rewards and minimize physical efforts in a probabilistic instrumental learning task. The implication of dopamine was assessed by comparing performance ON and OFF prodopaminergic medication. In a first sample of PD patients ( n = 15), we observed that reward learning, but not effort learning, was selectively impaired in the absence of treatment, with a significant interaction between learning condition (reward vs effort) and medication status (OFF vs ON). These results were replicated in a second, independent sample of PD patients ( n = 20) using a simplified version of the task. According to Bayesian model selection, the best account for medication effects in both studies was a specific amplification of reward magnitude in a Q-learning algorithm. These results suggest that learning to avoid physical effort is independent from dopaminergic circuits and strengthen the general idea that dopaminergic signaling amplifies the effects of reward expectation or obtainment on instrumental behavior. SIGNIFICANCE STATEMENT Theoretically, maximizing reward and minimizing effort could involve the same computations and therefore rely on the same brain circuits. Here, we tested whether dopamine, a key component of reward-related circuitry, is also implicated in effort learning. We found that patients suffering from dopamine depletion due to Parkinson's disease were selectively impaired in reward learning, but not effort learning. Moreover, anti-parkinsonian medication restored the

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

International Nuclear Information System (INIS)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A.

2009-01-01

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle

Development of a multi-criteria assessment model for ranking of renewable and non-renewable transportation fuel vehicles

Energy Technology Data Exchange (ETDEWEB)

Safaei Mohamadabadi, H.; Tichkowsky, G.; Kumar, A. [Department of Mechanical Engineering, University of Alberta, Edmonton, Alberta (Canada)

2009-01-15

Several factors, including economical, environmental, and social factors, are involved in selection of the best fuel-based vehicles for road transportation. This leads to a multi-criteria selection problem for multi-alternatives. In this study, a multi-criteria assessment model was developed to rank different road transportation fuel-based vehicles (both renewable and non-renewable) using a method called Preference Ranking Organization Method for Enrichment and Evaluations (PROMETHEE). This method combines qualitative and quantitative criteria to rank various alternatives. In this study, vehicles based on gasoline, gasoline-electric (hybrid), E85 ethanol, diesel, B100 biodiesel, and compressed natural gas (CNG) were considered as alternatives. These alternatives were ranked based on five criteria: vehicle cost, fuel cost, distance between refueling stations, number of vehicle options available to the consumer, and greenhouse gas (GHG) emissions per unit distance traveled. In addition, sensitivity analyses were performed to study the impact of changes in various parameters on final ranking. Two base cases and several alternative scenarios were evaluated. In the base case scenario with higher weight on economical parameters, gasoline-based vehicle was ranked higher than other vehicles. In the base case scenario with higher weight on environmental parameters, hybrid vehicle was ranked first followed by biodiesel-based vehicle. (author)

Improving feature ranking for biomarker discovery in proteomics mass spectrometry data using genetic programming

Science.gov (United States)

Ahmed, Soha; Zhang, Mengjie; Peng, Lifeng

2014-07-01

Feature selection on mass spectrometry (MS) data is essential for improving classification performance and biomarker discovery. The number of MS samples is typically very small compared with the high dimensionality of the samples, which makes the problem of biomarker discovery very hard. In this paper, we propose the use of genetic programming for biomarker detection and classification of MS data. The proposed approach is composed of two phases: in the first phase, feature selection and ranking are performed. In the second phase, classification is performed. The results show that the proposed method can achieve better classification performance and biomarker detection rate than the information gain- (IG) based and the RELIEF feature selection methods. Meanwhile, four classifiers, Naive Bayes, J48 decision tree, random forest and support vector machines, are also used to further test the performance of the top ranked features. The results show that the four classifiers using the top ranked features from the proposed method achieve better performance than the IG and the RELIEF methods. Furthermore, GP also outperforms a genetic algorithm approach on most of the used data sets.

On conditional independence and log-convexity

Czech Academy of Sciences Publication Activity Database

Matúš, František

2012-01-01

Roč. 48, č. 4 (2012), s. 1137-1147 ISSN 0246-0203 R&D Projects: GA AV ČR IAA100750603; GA ČR GA201/08/0539 Institutional support: RVO:67985556 Keywords : Conditional independence * Markov properties * factorizable distributions * graphical Markov models * log-convexity * Gibbs- Markov equivalence * Markov fields * Gaussian distributions * positive definite matrices * covariance selection model Subject RIV: BA - General Mathematics Impact factor: 0.933, year: 2012 http://library.utia.cas.cz/separaty/2013/MTR/matus-0386229.pdf

The behavioral economics of consumer brand choice: patterns of reinforcement and utility maximization.

Science.gov (United States)

Foxall, Gordon R; Oliveira-Castro, Jorge M; Schrezenmaier, Teresa C

2004-06-30

Purchasers of fast-moving consumer goods generally exhibit multi-brand choice, selecting apparently randomly among a small subset or "repertoire" of tried and trusted brands. Their behavior shows both matching and maximization, though it is not clear just what the majority of buyers are maximizing. Each brand attracts, however, a small percentage of consumers who are 100%-loyal to it during the period of observation. Some of these are exclusively buyers of premium-priced brands who are presumably maximizing informational reinforcement because their demand for the brand is relatively price-insensitive or inelastic. Others buy exclusively the cheapest brands available and can be assumed to maximize utilitarian reinforcement since their behavior is particularly price-sensitive or elastic. Between them are the majority of consumers whose multi-brand buying takes the form of selecting a mixture of economy -- and premium-priced brands. Based on the analysis of buying patterns of 80 consumers for 9 product categories, the paper examines the continuum of consumers so defined and seeks to relate their buying behavior to the question of how and what consumers maximize.

SDSS Log Viewer: visual exploratory analysis of large-volume SQL log data

Science.gov (United States)

Zhang, Jian; Chen, Chaomei; Vogeley, Michael S.; Pan, Danny; Thakar, Ani; Raddick, Jordan

2012-01-01

User-generated Structured Query Language (SQL) queries are a rich source of information for database analysts, information scientists, and the end users of databases. In this study a group of scientists in astronomy and computer and information scientists work together to analyze a large volume of SQL log data generated by users of the Sloan Digital Sky Survey (SDSS) data archive in order to better understand users' data seeking behavior. While statistical analysis of such logs is useful at aggregated levels, efficiently exploring specific patterns of queries is often a challenging task due to the typically large volume of the data, multivariate features, and data requirements specified in SQL queries. To enable and facilitate effective and efficient exploration of the SDSS log data, we designed an interactive visualization tool, called the SDSS Log Viewer, which integrates time series visualization, text visualization, and dynamic query techniques. We describe two analysis scenarios of visual exploration of SDSS log data, including understanding unusually high daily query traffic and modeling the types of data seeking behaviors of massive query generators. The two scenarios demonstrate that the SDSS Log Viewer provides a novel and potentially valuable approach to support these targeted tasks.

Wikipedia ranking of world universities

Science.gov (United States)

Lages, José; Patt, Antoine; Shepelyansky, Dima L.

2016-03-01

We use the directed networks between articles of 24 Wikipedia language editions for producing the wikipedia ranking of world Universities (WRWU) using PageRank, 2DRank and CheiRank algorithms. This approach allows to incorporate various cultural views on world universities using the mathematical statistical analysis independent of cultural preferences. The Wikipedia ranking of top 100 universities provides about 60% overlap with the Shanghai university ranking demonstrating the reliable features of this approach. At the same time WRWU incorporates all knowledge accumulated at 24 Wikipedia editions giving stronger highlights for historically important universities leading to a different estimation of efficiency of world countries in university education. The historical development of university ranking is analyzed during ten centuries of their history.

Static dictionaries on AC⁰ RAMs: query time (√log n/log log n) is necessary and sufficient

DEFF Research Database (Denmark)

Andersson, Arne; Miltersen, Peter Bro; Riis, Søren

1996-01-01

) on the time for answering membership queries in a set of size n when reasonable space is used for the data structure storing the set; the upper bound can be obtained using O(n) space, and the lower bound holds even if we allow space 2polylog n. Several variations of this result are also obtained. Among others......, we show a tradeoff between time and circuit depth under the unit-cost assumption: any RAM instruction set which permits a linear space, constant query time solution to the static dictionary problem must have an instruction of depth Ω(log w/log log to), where w is the word size of the machine (and log...

Best practices in ranking communicable disease threats: a literature review, 2015.

Science.gov (United States)

O'Brien, Eleanor Charlotte; Taft, Rachel; Geary, Katie; Ciotti, Massimo; Suk, Jonathan E

2016-04-28

The threat of serious, cross-border communicable disease outbreaks in Europe poses a significant challenge to public health and emergency preparedness because the relative likelihood of these threats and the pathogens involved are constantly shifting in response to a range of changing disease drivers. To inform strategic planning by enabling effective resource allocation to manage the consequences of communicable disease outbreaks, it is useful to be able to rank and prioritise pathogens. This paper reports on a literature review which identifies and evaluates the range of methods used for risk ranking. Searches were performed across biomedical and grey literature databases, supplemented by reference harvesting and citation tracking. Studies were selected using transparent inclusion criteria and underwent quality appraisal using a bespoke checklist based on the AGREE II criteria. Seventeen studies were included in the review, covering five methodologies. A narrative analysis of the selected studies suggests that no single methodology was superior. However, many of the methods shared common components, around which a 'best-practice' framework was formulated. This approach is intended to help inform decision makers' choice of an appropriate risk-ranking study design.

WISER ranking of the African national libraries' websites | Gupta ...

African Journals Online (AJOL)

... as number of webpages, in-links, rich content files, publications in Google Scholar. It was also found that the website of National Library of South Africa also holds the first rank in WISER among the selected websites of African national libraries. Keywords: National, Libraries, Webometrics, WIF, WISER, Website, evaluation, ...

OCT despeckling via weighted nuclear norm constrained non-local low-rank representation

Science.gov (United States)

Tang, Chang; Zheng, Xiao; Cao, Lijuan

2017-10-01

As a non-invasive imaging modality, optical coherence tomography (OCT) plays an important role in medical sciences. However, OCT images are always corrupted by speckle noise, which can mask image features and pose significant challenges for medical analysis. In this work, we propose an OCT despeckling method by using non-local, low-rank representation with weighted nuclear norm constraint. Unlike previous non-local low-rank representation based OCT despeckling methods, we first generate a guidance image to improve the non-local group patches selection quality, then a low-rank optimization model with a weighted nuclear norm constraint is formulated to process the selected group patches. The corrupted probability of each pixel is also integrated into the model as a weight to regularize the representation error term. Note that each single patch might belong to several groups, hence different estimates of each patch are aggregated to obtain its final despeckled result. Both qualitative and quantitative experimental results on real OCT images show the superior performance of the proposed method compared with other state-of-the-art speckle removal techniques.

Processing well logging data, for example for verification and calibration of well logs

International Nuclear Information System (INIS)

Suau, J.; Boutemy, Y.

1981-01-01

A method is described of machine processing well logging data derived from borehole exploring devices which investigate earth formations traversed by boreholes. The method can be used for verifying and recalibrating logs, reconstructing missing logs and combining the data to form a statistical model of the traversed earth formations. (U.K.)

Health systems around the world - a comparison of existing health system rankings.

Science.gov (United States)

Schütte, Stefanie; Acevedo, Paula N Marin; Flahault, Antoine

2018-06-01

Existing health systems all over the world are different due to the different combinations of components that can be considered for their establishment. The ranking of health systems has been a focal points for many years especially the issue of performance. In 2000 the World Health Organization (WHO) performed a ranking to compare the Performance of the health system of the member countries. Since then other health system rankings have been performed and it became an issue of public discussion. A point of contention regarding these rankings is the methodology employed by each of them, since no gold standard exists. Therefore, this review focuses on evaluating the methodologies of each existing health system performance ranking to assess their reproducibility and transparency. A search was conducted to identify existing health system rankings, and a questionnaire was developed for the comparison of the methodologies based on the following indicators: (1) General information, (2) Statistical methods, (3) Data (4) Indicators. Overall nine rankings were identified whereas six of them focused rather on the measurement of population health without any financial component and were therefore excluded. Finally, three health system rankings were selected for this review: "Health Systems: Improving Performance" by the WHO, "Mirror, Mirror on the wall: How the Performance of the US Health Care System Compares Internationally" by the Commonwealth Fund and "the Most efficient Health Care" by Bloomberg. After the completion of the comparison of the rankings by giving them scores according to the indicators, the ranking performed the WHO was considered the most complete regarding the ability of reproducibility and transparency of the methodology. This review and comparison could help in establishing consensus in the field of health system research. This may also help giving recommendations for future health rankings and evaluating the current gap in the literature.

Teachers' Educational Qualification, Rank Level, Working Duration, Age, Work Motivation and Work Effectiveness

OpenAIRE

Wiyono, Bambang Budi

2009-01-01

Teachers’ Educational Qualification, Rank Level, Working Duration, Age, Working Mo­tivation, and Working Effectiveness The study investigated the effects of educational qualification, rank level, working duration and age on the elementary school teachers’ working motivation and working ef­fectiveness. The sample of the study consisted of 438 elementary school teachers in Malang which were selected through cluster sampling technique. The study was conducted using explanatory design in the form...

A decision theoretic framework for profit maximization in direct marketing

NARCIS (Netherlands)

Muus, L.; van der Scheer, H.; Wansbeek, T.J.; Montgomery, A.; Franses, P.H.B.F.

2002-01-01

One of the most important issues facing a firm involved in direct marketing is the selection of addresses from a mailing list. When the parameters of the model describing consumers' reaction to a mailing are known, addresses for a future mailing can be selected in a profit-maximizing way. Usually,

Principles of maximally classical and maximally realistic quantum ...

Indian Academy of Sciences (India)

Principles of maximally classical and maximally realistic quantum mechanics. S M ROY. Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India. Abstract. Recently Auberson, Mahoux, Roy and Singh have proved a long standing conjecture of Roy and Singh: In 2N-dimensional phase space, ...

La logística integral como ventaja competitiva y sistema logístico

Directory of Open Access Journals (Sweden)

Mario Anselmo Martínez gallardo

2013-07-01

Full Text Available Esta investigación analiza la logística integral como una ventaja competitiva y el sistema logístico. Es opinión de los autores que la logística integral es esencial para el intercambio de mercancías, toda vez que reduce costos y hace más ágil la actividad comercial. La utilización de esta logística representa una ventaja competitiva con respecto de otras empresas por la optimización del capital y ahorro de tiempo.

Selective laser trabeculoplasty in patients with pseudoexfoliative glaucoma vs primary open angle glaucoma: a one-year comparative study

Directory of Open Access Journals (Sweden)

Arezoo Miraftabi

2016-03-01

Full Text Available AIM: To compare the efficacy of single-session 360-degree selective laser trabeculoplasty (SLT for reduction of intraocular pressure (IOP in patients with pseudoexfoliative glaucoma (PXFG and primary open angle glaucoma (POAG. METHODS: This is a single-center, prospective, nonrandomized comparative study. Patients older than 18 years of age with uncontrolled PXFG or POAG eyes requiring additional therapy while on maximally tolerated IOP-lowering medications were included. The primary outcome measure changed in IOP from baseline. Success was defined as IOP reduction ≥20% from baseline without any additional IOP-lowering medication. All patients were examined at 1d, 1wk, 1, 3, 6, 9, 12mo after SLT. RESULTS: Nineteen patients (20 eyes with PXFG and 27 patients (28 eyes with POAG were included in the study. In the visual fields mean deviation was -2.88 (±1.67 in the POAG and -3.1 (±1.69 in the PXFG groups (P=0.3. The mean (±SD IOP was 22.9 (±3.7 mm Hg in the POAG group and 25.7 (±4.4 mm Hg in the PXFG group at baseline and decreased to 18.4 (±3.2 and 18.0 (±3.9 mm Hg in the POAG group (P<0.001 and P=0.02, and to 17.9 (±4.0 and 21.0 (±6.6 mm Hg in the PXFG group (P<0.001 and P=0.47 at 6 and 12mo, respectively. The number of medications was 2.6 (±0.8 in the POAG group and 2.5 (±0.8 in the PXFG group at baseline, and did not change at all follow-up visits in both groups (P=0.16 in POAG and 0.57 in PXFG. Based on Kaplan-Meier survival analysis, the success rate was 75% in the POAG group compared to 94.1% in the PXFG group (P=0.08; log rank test at 6mo, and 29.1% and 25.0% at 12mo, respectively (P=0.9; log rank. CONCLUSION: The 360-degree SLT is an effective and well-tolerated therapeutic modality in patients with POAG and PXFG by reducing IOP without any change in number of medications. The response was more pronounced early in the postoperative period in patients with PXFG whereas there was no statistically significant difference at 12

Optimized Design of Spacing in Pulsed Neutron Gamma Density Logging While Drilling

Directory of Open Access Journals (Sweden)

ZHANG Feng;HAN Zhong-yue;WU He;HAN Fei

2016-10-01

Full Text Available Radioactive source, used in traditional density logging, has great impact on the environment, while the pulsed neutron source applied in the logging tool is more safety and greener. In our country, the pulsed neutron-gamma density logging technology is still in the stage of development. Optimizing the parameters of neutron-gamma density instrument is essential to improve the measuring accuracy. This paper mainly studied the effects of spacing to typical neutron-gamma density logging tool which included one D-T neutron generator and two gamma scintillation detectors. The optimization of spacing were based on measuring sensitivity and counting statistic. The short spacing from 25 to 35 cm and long spacing from 60 to 65 cm were selected as the optimal position for near and far detector respectively. The result can provide theoretical support for design and manufacture of the instrument.

Reduced-impact logging and biodiversity conservation: a case study from Borneo.

Science.gov (United States)

Edwards, David P; Woodcock, Paul; Edwards, Felicity A; Larsen, Trond H; Hsu, Wayne W; Benedick, Suzan; Wilcove, David S

2012-03-01

A key driver of rain forest degradation is rampant commercial logging. Reduced-impact logging (RIL) techniques dramatically reduce residual damage to vegetation and soils, and they enhance the long-term economic viability of timber operations when compared to conventionally managed logging enterprises. Consequently, the application of RIL is increasing across the tropics, yet our knowledge of the potential for RIL also to reduce the negative impacts of logging on biodiversity is minimal. We compare the impacts of RIL on birds, leaf-litter ants, and dung beetles during a second logging rotation in Sabah, Borneo, with the impacts of conventional logging (CL) as well as with primary (unlogged) forest. Our study took place 1-8 years after the cessation of logging. The species richness and composition of RIL vs. CL forests were very similar for each taxonomic group. Both RIL and CL differed significantly from unlogged forests in terms of bird and ant species composition (although both retained a large number of the species found in unlogged forests), whereas the composition of dung beetle communities did not differ significantly among forest types. Our results show little difference in biodiversity between RIL and CL over the short-term. However, biodiversity benefits from RIL may accrue over longer time periods after the cessation of logging. We highlight a severe lack of studies investigating this possibility. Moreover, if RIL increases the economic value of selectively logged forests (e.g., via REDD+, a United Nations program: Reducing Emissions from Deforestation and Forest Degradation in Developing Countries), it could help prevent them from being converted to agricultural plantations, which results in a tremendous loss of biodiversity.

Ranking of microRNA target prediction scores by Pareto front analysis.

Science.gov (United States)

Sahoo, Sudhakar; Albrecht, Andreas A

2010-12-01

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts. Copyright © 2010 Elsevier Ltd. All rights reserved.

Development of the Operational Events Groups Ranking Tool

International Nuclear Information System (INIS)

Simic, Zdenko; Banov, Reni

2014-01-01

Both because of complexity and ageing, facilities like nuclear power plants require feedback from the operating experience in order to further improve safety and operation performance. That is the reason why significant effort is dedicated to operating experience feedback. This paper contains description of the specification and development of the application for the operating events ranking software tool. Robust and consistent way of selecting most important events for detail investigation is important because it is not feasible or even useful to investigate all of them. Development of the tool is based on the comprehensive events characterisation and methodical prioritization. This includes rich set of events parameters which allow their top level preliminary analysis, different ways of groupings and even to evaluate uncertainty propagation to the ranking results. One distinct feature of the implemented method is that user (i.e., expert) could determine how important is particular ranking parameter based on their pairwise comparison. For tools demonstration and usability it is crucial that sample database is also created. For useful analysis the whole set of events for 5 years is selected and characterised. Based on the preliminary results this tool seems valuable for new preliminary prospective on data as whole, and especially for the identification of events groups which should have priority in the more detailed assessment. The results are consisting of different informative views on the events groups importance and related sensitivity and uncertainty results. This presents valuable tool for improving overall picture about specific operating experience and also for helping identify the most important events groups for further assessment. It is clear that completeness and consistency of the input data characterisation is very important to get full and valuable importance ranking. Method and tool development described in this paper is part of continuous effort of

University Rankings and Social Science

OpenAIRE

Marginson, S.

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real outputs are of no common value. It is necessary that rankings be soundly based in scientific terms if a virtuous relationship between performance and...

24 CFR 599.401 - Ranking of applications.

Science.gov (United States)

2010-04-01

... 24 Housing and Urban Development 3 2010-04-01 2010-04-01 false Ranking of applications. 599.401... Communities § 599.401 Ranking of applications. (a) Ranking order. Rural and urban applications will be ranked... applications ranked first. (b) Separate ranking categories. After initial ranking, both rural and urban...

Profit maximization mitigates competition

DEFF Research Database (Denmark)

Dierker, Egbert; Grodal, Birgit

1996-01-01

We consider oligopolistic markets in which the notion of shareholders' utility is well-defined and compare the Bertrand-Nash equilibria in case of utility maximization with those under the usual profit maximization hypothesis. Our main result states that profit maximization leads to less price...... competition than utility maximization. Since profit maximization tends to raise prices, it may be regarded as beneficial for the owners as a whole. Moreover, if profit maximization is a good proxy for utility maximization, then there is no need for a general equilibrium analysis that takes the distribution...... of profits among consumers fully into account and partial equilibrium analysis suffices...

Implications of maximal Jarlskog invariant and maximal CP violation

International Nuclear Information System (INIS)

Rodriguez-Jauregui, E.; Universidad Nacional Autonoma de Mexico

2001-04-01

We argue here why CP violating phase Φ in the quark mixing matrix is maximal, that is, Φ=90 . In the Standard Model CP violation is related to the Jarlskog invariant J, which can be obtained from non commuting Hermitian mass matrices. In this article we derive the conditions to have Hermitian mass matrices which give maximal Jarlskog invariant J and maximal CP violating phase Φ. We find that all squared moduli of the quark mixing elements have a singular point when the CP violation phase Φ takes the value Φ=90 . This special feature of the Jarlskog invariant J and the quark mixing matrix is a clear and precise indication that CP violating Phase Φ is maximal in order to let nature treat democratically all of the quark mixing matrix moduli. (orig.)

The log S -log N distribution of gamma ray brust

International Nuclear Information System (INIS)

Yamagami, Takamasa; Nishimura, Jun; Fujii, Masami

1982-01-01

The relation between the size S and the frequency N of gamma ray burst has been studied. This relation may be determined from the celestial distribution of gamma ray burst sources. The present analysis gives that the log S - log N relation for any direction is determined by the celestial distribution of gamma ray burst sources. The observed bursts were analyzed. The celestial distribution of gamma ray burst sources was observed by the satellites of USSR. The results showed that the distribution seemed to be isotropic. However, the calculated log S - log N relation based on the isotropic distribution wasF in disagreement with the observed ones. As the result of analysis, it was found that the observed bursts missed low energy part because of the threshold of detectors. The levels of discrimination of detection were not clear. When a proper threshold level is set for each type of burst, and the size of bursts is determined, the above mentioned discrepancy will be deleted regardless of luminosity and the spatial distribution of bursts. (Kato, T.)

Digital mineral logging system

International Nuclear Information System (INIS)

West, J.B.

1980-01-01

A digital mineral logging system acquires data from a mineral logging tool passing through a borehole and transmits the data uphole to an electronic digital signal processor. A predetermined combination of sensors, including a deviometer, is located in a logging tool for the acquisition of the desired data as the logging tool is raised from the borehole. Sensor data in analog format is converted in the logging tool to a digital format and periodically batch transmitted to the surface at a predetermined sampling rate. An identification code is provided for each mineral logging tool, and the code is transmitted to the surface along with the sensor data. The self-identifying tool code is transmitted to the digital signal processor to identify the code against a stored list of the range of numbers assigned to that type of tool. The data is transmitted up the d-c power lines of the tool by a frequency shift key transmission technique. At the surface, a frequency shift key demodulation unit transmits the decoupled data to an asynchronous receiver interfaced to the electronic digital signal processor. During a recording phase, the signals from the logging tool are read by the electronic digital signal processor and stored for later processing. During a calculating phase, the stored data is processed by the digital signal processor and the results are outputted to a printer or plotter, or both

On Page Rank

NARCIS (Netherlands)

Hoede, C.

In this paper the concept of page rank for the world wide web is discussed. The possibility of describing the distribution of page rank by an exponential law is considered. It is shown that the concept is essentially equal to that of status score, a centrality measure discussed already in 1953 by

Citation graph based ranking in Invenio

CERN Document Server

Marian, Ludmila; Rajman, Martin; Vesely, Martin

2010-01-01

Invenio is the web-based integrated digital library system developed at CERN. Within this framework, we present four types of ranking models based on the citation graph that complement the simple approach based on citation counts: time-dependent citation counts, a relevancy ranking which extends the PageRank model, a time-dependent ranking which combines the freshness of citations with PageRank and a ranking that takes into consideration the external citations. We present our analysis and results obtained on two main data sets: Inspire and CERN Document Server. Our main contributions are: (i) a study of the currently available ranking methods based on the citation graph; (ii) the development of new ranking methods that correct some of the identified limitations of the current methods such as treating all citations of equal importance, not taking time into account or considering the citation graph complete; (iii) a detailed study of the key parameters for these ranking methods. (The original publication is ava...

Ranking DMUs by Comparing DEA Cross-Efficiency Intervals Using Entropy Measures

Directory of Open Access Journals (Sweden)

Tim Lu

2016-12-01

Full Text Available Cross-efficiency evaluation, an extension of data envelopment analysis (DEA, can eliminate unrealistic weighing schemes and provide a ranking for decision making units (DMUs. In the literature, the determination of input and output weights uniquely receives more attentions. However, the problem of choosing the aggressive (minimal or benevolent (maximal formulation for decision-making might still remain. In this paper, we develop a procedure to perform cross-efficiency evaluation without the need to make any specific choice of DEA weights. The proposed procedure takes into account the aggressive and benevolent formulations at the same time, and the choice of DEA weights can then be avoided. Consequently, a number of cross-efficiency intervals is obtained for each DMU. The entropy, which is based on information theory, is an effective tool to measure the uncertainty. We then utilize the entropy to construct a numerical index for DMUs with cross-efficiency intervals. A mathematical program is proposed to find the optimal entropy values of DMUs for comparison. With the derived entropy value, we can rank DMUs accordingly. Two examples are illustrated to show the effectiveness of the idea proposed in this paper.

Tackling Information Asymmetry in Networks: A New Entropy-Based Ranking Index

Science.gov (United States)

Barucca, Paolo; Caldarelli, Guido; Squartini, Tiziano

2018-06-01

Information is a valuable asset in socio-economic systems, a significant part of which is entailed into the network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure; since this entails a different ability of quantifying relevant, systemic properties (e.g. the risk of contagion in a network of liabilities), agents capable of providing a better estimation of (otherwise) inaccessible network properties, ultimately have a competitive advantage. In this paper, we address the issue of quantifying the information asymmetry of nodes: to this aim, we define a novel index—InfoRank—intended to rank nodes according to their information content. In order to do so, each node ego-network is enforced as a constraint of an entropy-maximization problem and the subsequent uncertainty reduction is used to quantify the node-specific accessible information. We, then, test the performance of our ranking procedure in terms of reconstruction accuracy and show that it outperforms other centrality measures in identifying the "most informative" nodes. Finally, we discuss the socio-economic implications of network information asymmetry.

Rank-dependent grooming patterns and cortisol alleviation in Barbary macaques.

Science.gov (United States)

Sonnweber, Ruth S; Ravignani, Andrea; Stobbe, Nina; Schiestl, Gisela; Wallner, Bernard; Fitch, W Tecumseh

2015-06-01

Flexibly adapting social behavior to social and environmental challenges helps to alleviate glucocorticoid (GC) levels, which may have positive fitness implications for an individual. For primates, the predominant social behavior is grooming. Giving grooming to others is particularly efficient in terms of GC mitigation. However, grooming is confined by certain limitations such as time constraints or restricted access to other group members. For instance, dominance hierarchies may impact grooming partner availability in primate societies. Consequently specific grooming patterns emerge. In despotic species focusing grooming activity on preferred social partners significantly ameliorates GC levels in females of all ranks. In this study we investigated grooming patterns and GC management in Barbary macaques, a comparably relaxed species. We monitored changes in grooming behavior and cortisol (C) for females of different ranks. Our results show that the C-amelioration associated with different grooming patterns had a gradual connection with dominance hierarchy: while higher-ranking individuals showed lowest urinary C measures when they focused their grooming on selected partners within their social network, lower-ranking individuals expressed lowest C levels when dispersing their grooming activity evenly across their social partners. We argue that the relatively relaxed social style of Barbary macaque societies allows individuals to flexibly adapt grooming patterns, which is associated with rank-specific GC management. © 2015 Wiley Periodicals, Inc.

Automated recognition of stratigraphic marker shales from geophysical logs in iron ore deposits

Science.gov (United States)

Silversides, Katherine; Melkumyan, Arman; Wyman, Derek; Hatherly, Peter

2015-04-01

The mining of stratiform ore deposits requires a means of determining the location of stratigraphic boundaries. A variety of geophysical logs may provide the required data but, in the case of banded iron formation hosted iron ore deposits in the Hamersley Ranges of Western Australia, only one geophysical log type (natural gamma) is collected for this purpose. The information from these logs is currently processed by slow manual interpretation. In this paper we present an alternative method of automatically identifying recurring stratigraphic markers in natural gamma logs from multiple drill holes. Our approach is demonstrated using natural gamma geophysical logs that contain features corresponding to the presence of stratigraphically important marker shales. The host stratigraphic sequence is highly consistent throughout the Hamersley and the marker shales can therefore be used to identify the stratigraphic location of the banded iron formation (BIF) or BIF hosted ore. The marker shales are identified using Gaussian Processes (GP) trained by either manual or active learning methods and the results are compared to the existing geological interpretation. The manual method involves the user selecting the signatures for improving the library, whereas the active learning method uses the measure of uncertainty provided by the GP to select specific examples for the user to consider for addition. The results demonstrate that both GP methods can identify a feature, but the active learning approach has several benefits over the manual method. These benefits include greater accuracy in the identified signatures, faster library building, and an objective approach for selecting signatures that includes the full range of signatures across a deposit in the library. When using the active learning method, it was found that the current manual interpretation could be replaced in 78.4% of the holes with an accuracy of 95.7%.

Equilibrium initial data for moving puncture simulations: the stationary 1 + log slicing

International Nuclear Information System (INIS)

Baumgarte, T W; Matera, K; Etienne, Z B; Liu, Y T; Shapiro, S L; Taniguchi, K; Murchadha, N O

2009-01-01

We discuss a 'stationary 1 + log' slicing condition for the construction of solutions to Einstein's constraint equations. For stationary spacetimes, these initial data give a stationary foliation when evolved with 'moving puncture' gauge conditions that are often used in black hole evolutions. The resulting slicing is time independent and agrees with the slicing generated by being dragged along a timelike Killing vector of the spacetime. When these initial data are evolved with moving puncture gauge conditions, numerical errors arising from coordinate evolution should be minimized. While these properties appear very promising, suggesting that this slicing condition should be an attractive alternative to, for example, maximal slicing, we demonstrate in this paper that solutions can be constructed only for a small class of problems. For binary black hole initial data, in particular, it is often assumed that there exists an approximate helical Killing vector that generates the binary's orbit. We show that 1 + log slices that are stationary with respect to such a helical Killing vector cannot be asymptotically flat, unless the spacetime possesses an additional axial Killing vector.

Model selection and inference a practical information-theoretic approach

CERN Document Server

Burnham, Kenneth P

1998-01-01

This book is unique in that it covers the philosophy of model-based data analysis and an omnibus strategy for the analysis of empirical data The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data Kullback-Leibler information represents a fundamental quantity in science and is Hirotugu Akaike's basis for model selection The maximized log-likelihood function can be bias-corrected to provide an estimate of expected, relative Kullback-Leibler information This leads to Akaike's Information Criterion (AIC) and various extensions and these are relatively simple and easy to use in practice, but little taught in statistics classes and far less understood in the applied sciences than should be the case The information theoretic approaches provide a unified and rigorous theory, an extension of likelihood theory, an important application of information theory, and are ...

When sparse coding meets ranking: a joint framework for learning sparse codes and ranking scores

KAUST Repository

Wang, Jim Jing-Yan

2017-06-28

Sparse coding, which represents a data point as a sparse reconstruction code with regard to a dictionary, has been a popular data representation method. Meanwhile, in database retrieval problems, learning the ranking scores from data points plays an important role. Up to now, these two problems have always been considered separately, assuming that data coding and ranking are two independent and irrelevant problems. However, is there any internal relationship between sparse coding and ranking score learning? If yes, how to explore and make use of this internal relationship? In this paper, we try to answer these questions by developing the first joint sparse coding and ranking score learning algorithm. To explore the local distribution in the sparse code space, and also to bridge coding and ranking problems, we assume that in the neighborhood of each data point, the ranking scores can be approximated from the corresponding sparse codes by a local linear function. By considering the local approximation error of ranking scores, the reconstruction error and sparsity of sparse coding, and the query information provided by the user, we construct a unified objective function for learning of sparse codes, the dictionary and ranking scores. We further develop an iterative algorithm to solve this optimization problem.

University Rankings: The Web Ranking

Science.gov (United States)

Aguillo, Isidro F.

2012-01-01

The publication in 2003 of the Ranking of Universities by Jiao Tong University of Shanghai has revolutionized not only academic studies on Higher Education, but has also had an important impact on the national policies and the individual strategies of the sector. The work gathers the main characteristics of this and other global university…

Adaptive linear rank tests for eQTL studies.

Science.gov (United States)

Szymczak, Silke; Scheinhardt, Markus O; Zeller, Tanja; Wild, Philipp S; Blankenberg, Stefan; Ziegler, Andreas

2013-02-10

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal-Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. Copyright © 2012 John Wiley & Sons, Ltd.

Recovery of a lowland dipterocarp forest twenty two years after selective logging at Sekundur, Gunung Leuser National Park, North Sumatra, Indonesia

Directory of Open Access Journals (Sweden)

Dolly - Priatna

2006-12-01

Full Text Available PRIATNA, D.; KARTAWINATA, K.; ABDULHADI, R. 2004. Recovery of a lowland dipterocarp forest twenty two years after selective logging at Sekundur, Gunung Leuser National Park, North Sumatra, Indonesia. Reinwardtia 12 (3: 237–255. — A permanent 2-ha plot of lowland forest selectively logged in 1978 at Sekundur, Gunung Leuser National Park, which is also a Biosphere Reserve and a World Heritage Site, North Sumatra, was established and investigated in 1982. It was re-examined in 2000, where remeasurement and reidentification of all trees with DBH 10 cm were made. The areas of gap, building and mature phases of the canopy were also measured and mapped. Within this plot, 133 species, 87 genera and 39 families were recorded, with the total number of trees of 1145 or density of 572.5/ha. Euphorbiaceae was the richest family with 18 species (13.5 % of the total and total number of trees of 248 (21.7 % of the total or density of 124 trees/ha. The most important families were Dipterocarpaceae with IV (Importance Value = 52.0, followed by Euphorbiaceae with IV = 51.8. The most prevalent species was Shorea kunstleri (Dipterocarpaceae with IV =24.4, followed by Macaranga diepenhorstii (Euphorbiaceae with IV = 12.4. They were the species with highest density, 34 trees/ha and 23.5 trees/ha, respectively. During the period of 18 years there has been no shift in the richest families, most important families and most important species. Euphorbiaceae was the richest family and Dipterocarpaceae was the most important family, with Shorea kunstleri as the most important species with highest importance value throughout the period. The number of species increased from 127 to 133 with increase in density by 36.8% , from 418.5 trees/ha to 572.5 trees/ha. The mortality was 25.57 % or 1.4 % per year. The diameter class distribution indicated that the forest recovery has not been complete. Trees were small, comprising 67.6 % with diameters of 10-20 cm and only two trees

Ranking Specific Sets of Objects.

Science.gov (United States)

Maly, Jan; Woltran, Stefan

2017-01-01

Ranking sets of objects based on an order between the single elements has been thoroughly studied in the literature. In particular, it has been shown that it is in general impossible to find a total ranking - jointly satisfying properties as dominance and independence - on the whole power set of objects. However, in many applications certain elements from the entire power set might not be required and can be neglected in the ranking process. For instance, certain sets might be ruled out due to hard constraints or are not satisfying some background theory. In this paper, we treat the computational problem whether an order on a given subset of the power set of elements satisfying different variants of dominance and independence can be found, given a ranking on the elements. We show that this problem is tractable for partial rankings and NP-complete for total rankings.

PageRank of integers

International Nuclear Information System (INIS)

Frahm, K M; Shepelyansky, D L; Chepelianskii, A D

2012-01-01

We up a directed network tracing links from a given integer to its divisors and analyze the properties of the Google matrix of this network. The PageRank vector of this matrix is computed numerically and it is shown that its probability is approximately inversely proportional to the PageRank index thus being similar to the Zipf law and the dependence established for the World Wide Web. The spectrum of the Google matrix of integers is characterized by a large gap and a relatively small number of nonzero eigenvalues. A simple semi-analytical expression for the PageRank of integers is derived that allows us to find this vector for matrices of billion size. This network provides a new PageRank order of integers. (paper)

Does resident ranking during recruitment accurately predict subsequent performance as a surgical resident?

Science.gov (United States)

Fryer, Jonathan P; Corcoran, Noreen; George, Brian; Wang, Ed; Darosa, Debra

2012-01-01

While the primary goal of ranking applicants for surgical residency training positions is to identify the candidates who will subsequently perform best as surgical residents, the effectiveness of the ranking process has not been adequately studied. We evaluated our general surgery resident recruitment process between 2001 and 2011 inclusive, to determine if our recruitment ranking parameters effectively predicted subsequent resident performance. We identified 3 candidate ranking parameters (United States Medical Licensing Examination [USMLE] Step 1 score, unadjusted ranking score [URS], and final adjusted ranking [FAR]), and 4 resident performance parameters (American Board of Surgery In-Training Examination [ABSITE] score, PGY1 resident evaluation grade [REG], overall REG, and independent faculty rating ranking [IFRR]), and assessed whether the former were predictive of the latter. Analyses utilized Spearman correlation coefficient. We found that the URS, which is based on objective and criterion based parameters, was a better predictor of subsequent performance than the FAR, which is a modification of the URS based on subsequent determinations of the resident selection committee. USMLE score was a reliable predictor of ABSITE scores only. However, when we compared our worst residence performances with the performances of the other residents in this evaluation, the data did not produce convincing evidence that poor resident performances could be reliably predicted by any of the recruitment ranking parameters. Finally, stratifying candidates based on their rank range did not effectively define a ranking cut-off beyond which resident performance would drop off. Based on these findings, we recommend surgery programs may be better served by utilizing a more structured resident ranking process and that subsequent adjustments to the rank list generated by this process should be undertaken with caution. Copyright © 2012 Association of Program Directors in Surgery

Ranking Support Vector Machine with Kernel Approximation.

Science.gov (United States)

Chen, Kai; Li, Rongchun; Dou, Yong; Liang, Zhengfa; Lv, Qi

2017-01-01

Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM) is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels) can give higher accuracy than linear RankSVM (RankSVM with a linear kernel) for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss) objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

Ranking Support Vector Machine with Kernel Approximation

Directory of Open Access Journals (Sweden)

Kai Chen

2017-01-01

Full Text Available Learning to rank algorithm has become important in recent years due to its successful application in information retrieval, recommender system, and computational biology, and so forth. Ranking support vector machine (RankSVM is one of the state-of-art ranking models and has been favorably used. Nonlinear RankSVM (RankSVM with nonlinear kernels can give higher accuracy than linear RankSVM (RankSVM with a linear kernel for complex nonlinear ranking problem. However, the learning methods for nonlinear RankSVM are still time-consuming because of the calculation of kernel matrix. In this paper, we propose a fast ranking algorithm based on kernel approximation to avoid computing the kernel matrix. We explore two types of kernel approximation methods, namely, the Nyström method and random Fourier features. Primal truncated Newton method is used to optimize the pairwise L2-loss (squared Hinge-loss objective function of the ranking model after the nonlinear kernel approximation. Experimental results demonstrate that our proposed method gets a much faster training speed than kernel RankSVM and achieves comparable or better performance over state-of-the-art ranking algorithms.

University Rankings and Social Science

Science.gov (United States)

Marginson, Simon

2014-01-01

University rankings widely affect the behaviours of prospective students and their families, university executive leaders, academic faculty, governments and investors in higher education. Yet the social science foundations of global rankings receive little scrutiny. Rankings that simply recycle reputation without any necessary connection to real…

Maximizers versus satisficers

Directory of Open Access Journals (Sweden)

Andrew M. Parker

2007-12-01

Full Text Available Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007. Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002, we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions, more avoidance of decision making, and greater tendency to experience regret. Contrary to predictions, self-reported maximizers were more likely to report spontaneous decision making. However, the relationship between self-reported maximizing and worse life outcomes is largely unaffected by controls for measures of other decision-making styles, decision-making competence, and demographic variables.

Determination of the rock clayiness from statistically standardized gamma-logging diagrams

International Nuclear Information System (INIS)

Kholodilov, V.V.

1975-01-01

Statistical standardization (using mathematical expectancy and dispersion) was done on gamma-logging diagrams made from 43 boreholes in producing strata of mid Jurassic and lower Cretaceous deposits in the Dagestan Plain. The material of the deposits is chiefly sands and aleurites containing 5 to 45% clay. The dependence of the standard deviation of the gamma-log curves on the clayiness of the rocks was determined at intervals of 400 and 300 meters. The intervals were selected by considering the borehole depth. The coefficients of correlation were 0.87 and 0.86, respectively

Selected emissions and efficiencies of energy systems based on logging and sawmill residues

International Nuclear Information System (INIS)

Maelkki, Helena; Virtanen, Yrjoe

2003-01-01

Bioenergy has an important role in the implementation of the Kyoto agreement in Finland. The main sources of wood residues for energy production are logging areas and sawmills. The use of forest chips can be of great significance in reducing carbon dioxide emissions by replacing fossil fuels. Increasing the use of forest chips has environmental benefits, but it also includes possible environmental disadvantages. Therefore, system research is needed to assess the forest chip utilisation prospects for their environmental quality to secure sustainable forest management. Life-cycle methodology was developed and applied to assess environmental burdens and impacts of the logging and sawmill residues throughout the whole fuel chain from the forest to energy production. According to the study, the energy efficiencies of the forest chip systems are quite high. Net CO 2 emissions of the systems are low owing to the low input of external primary energy required to operate the systems. Although wood energy is renewable, it has many similarities with fossil fuels, e.g. as the emissions of the conversion phase are significant

Two-dimensional ranking of Wikipedia articles

Science.gov (United States)

Zhirov, A. O.; Zhirov, O. V.; Shepelyansky, D. L.

2010-10-01

The Library of Babel, described by Jorge Luis Borges, stores an enormous amount of information. The Library exists ab aeterno. Wikipedia, a free online encyclopaedia, becomes a modern analogue of such a Library. Information retrieval and ranking of Wikipedia articles become the challenge of modern society. While PageRank highlights very well known nodes with many ingoing links, CheiRank highlights very communicative nodes with many outgoing links. In this way the ranking becomes two-dimensional. Using CheiRank and PageRank we analyze the properties of two-dimensional ranking of all Wikipedia English articles and show that it gives their reliable classification with rich and nontrivial features. Detailed studies are done for countries, universities, personalities, physicists, chess players, Dow-Jones companies and other categories.

Estimation of the non records logs from existing logs using artificial neural networks

Directory of Open Access Journals (Sweden)

Mehdi Mohammad Salehi

2017-12-01

Full Text Available Finding the information of the hydrocarbon reservoirs from well logs is one of the main objectives of the engineers. But, missing the log records (due to many reasons such as broken instruments, unsuitable borehole and etc. is a major challenge to achieve it. Prediction of the density and resistivity logs (Rt, DT and LLS from the conventional wire-line logs in one of the Iranian southwest oil fields is the main purpose of this study. Multilayer neural network was applied to develop an intelligent predictive model for prediction of the logs. A total of 3000 data sets from 3 wells (A, B and C of the studied field were used. Among them, the data of A, B and C wells were used to constructing and testing the model, respectively. To evaluate the performance of the model, the mean square error (MSE and correlation coefficient (R2 in the test data were calculated. A comparison between the MSE of the proposed model and recently intelligent models shows that the proposed model is more accurate than others. Acceptable accuracy and using conventional well logging data are the highlight advantages of the proposed intelligent model.

Examples of detection of water flow by oxygen activation on pulsed neutron logs

International Nuclear Information System (INIS)

de Rosset, W.H.M.

1986-01-01

Upward flow of water in cased wellbores may be detected with pulsed neutron capture (PNC) and gamma ray (GR) tools. Water entering tubing, casing and flowing behind pipe may similarly be evaluated qualitatively. Gamma ray background anomalies in PNC data and elevation of GR tool response occur when water is flowing above threshold velocities and volumes. The technique requires logging the well under static and flow conditions or logging at different tools speeds in a flowing well. Oxygen activation results in increased gamma ray count rates at each detector. PNC far detector and GR well log curves from each log run (flowing well, static well) are overlain. The increases for each curve are offset from the point of water entry by a distance similar to tool source-detector spacing. These offsets in gamma increase are 15-20 ft. higher for the GR than for the PNC far detector and distinguish oxygen activation due to flowing water from common hot spots. The amount of gamma ray increase is controlled by the velocity of upward flow of water past the tool, the amount of water flowing, and the distance of the flow from the tool. Prior planning is important to gain usable information in flowing wells. The upward relative velocity imposes maximal and minimal tool speeds to produce significant gamma increases, and tool speed must be adjusted to optimize gamma changes. Use of the technique to answer actual production problems is illustrated with examples. Insight was gained which led to the correction of the problem in each case

Analysis of borehole-radar reflection logs from selected HC boreholes at the Project Shoal area, Churchill County, Nevada

Science.gov (United States)

Lane, J.W.; Joesten, P.K.; Pohll, G.M.; Mihevic, Todd

2001-01-01

Single-hole borehole-radar reflection logs were collected and interpreted in support of a study to characterize ground-water flow and transport at the Project Shoal Area (PSA) in Churchill County, Nevada. Radar logging was conducted in six boreholes using 60-MHz omni-directional electric-dipole antennas and a 60-MHz magnetic-dipole directional receiving antenna.Radar data from five boreholes were interpreted to identify the location, orientation, estimated length, and spatial continuity of planar reflectors present in the logs. The overall quality of the radar data is marginal and ranges from very poor to good. Twenty-seven reflectors were interpreted from the directional radar reflection logs. Although the range of orientation interpreted for the reflectors is large, a significant number of reflectors strike northeast-southwest and east-west to slightly northwest-southeast. Reflectors are moderate to steeply dipping and reflector length ranged from less than 7 m to more than 133 m.Qualitative scores were assigned to each reflector to provide a sense of the spatial continuity of the reflector and the characteristics of the field data relative to an ideal planar reflector (orientation score). The overall orientation scores are low, which reflects the general data quality, but also indicates that the properties of most reflectors depart from the ideal planar case. The low scores are consistent with reflections from fracture zones that contain numerous, closely spaced, sub-parallel fractures.Interpretation of borehole-radar direct-wave velocity and amplitude logs identified several characteristics of the logged boreholes: (1) low-velocity zones correlate with decreased direct-wave amplitude, indicating the presence of fracture zones; (2) direct-wave amplitude increases with depth in three of the boreholes, suggesting an increase in electrical resistivity with depth resulting from changes in mineral assemblage or from a decrease in the specific conductance of ground

Robust Visual Tracking Via Consistent Low-Rank Sparse Learning

KAUST Repository

Zhang, Tianzhu

2014-06-19

Object tracking is the process of determining the states of a target in consecutive video frames based on properties of motion and appearance consistency. In this paper, we propose a consistent low-rank sparse tracker (CLRST) that builds upon the particle filter framework for tracking. By exploiting temporal consistency, the proposed CLRST algorithm adaptively prunes and selects candidate particles. By using linear sparse combinations of dictionary templates, the proposed method learns the sparse representations of image regions corresponding to candidate particles jointly by exploiting the underlying low-rank constraints. In addition, the proposed CLRST algorithm is computationally attractive since temporal consistency property helps prune particles and the low-rank minimization problem for learning joint sparse representations can be efficiently solved by a sequence of closed form update operations. We evaluate the proposed CLRST algorithm against 14 state-of-the-art tracking methods on a set of 25 challenging image sequences. Experimental results show that the CLRST algorithm performs favorably against state-of-the-art tracking methods in terms of accuracy and execution time.

Quantitative approaches for profit maximization in direct marketing

NARCIS (Netherlands)

van der Scheer, H.R.

1998-01-01

An effective direct marketing campaign aims at selecting those targets, offer and communication elements - at the right time - that maximize the net profits. The list of individuals to be mailed, i.e. the targets, is considered to be the most important component. Therefore, a large amount of direct

Geophysical borehole logging. Final disposal of spent fuel

International Nuclear Information System (INIS)

Rouhiainen, P.

1984-01-01

Teollisuuden Voima Oy (Industrial Power Company Ltd.) will take precautions for final disposal of spent fuel in the Finnish bedrock. The first stage of the site selection studies includes drilling of a deep borehole down to approximately 1000 meters in the year 1984. The report deals with geophysical borehole logging methods, which could be used for the studies. The aim of geophysical borehole logging methods is to descripe specially hydrogeological and structural features. Only the most essential methods are dealt with in this report. Attention is paid to the information produced with the methods, derscription of the methods, interpretation and limitations. The feasibility and possibilities for the aims are evaluated. The evaluations are based mainly on the results from Sweden, England, Canada and USA as well as experiencies gained in Finland

Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

Science.gov (United States)

Lorenz, Aaron J

2013-03-01

Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS). It is well known that because alleles are replicated across individuals in quantitative trait loci mapping and MAS, more resources should be allocated to increasing population size compared with phenotypic selection. Genomic selection is a form of MAS using all marker information simultaneously to predict individual genetic values for complex traits and has widely been found superior to MAS. No studies have explicitly investigated how resource allocation decisions affect success of genomic selection. My objective was to study the effect of resource allocation on response to MAS and genomic selection in a single biparental population of doubled haploid lines by using computer simulation. Simulation results were compared with previously derived formulas for the calculation of prediction accuracy under different levels of heritability and population size. Response of prediction accuracy to resource allocation strategies differed between genomic selection models (ridge regression best linear unbiased prediction [RR-BLUP], BayesCπ) and multiple linear regression using ordinary least-squares estimation (OLS), leading to different optimal resource allocation choices between OLS and RR-BLUP. For OLS, it was always advantageous to maximize population size at the expense of replication, but a high degree of flexibility was observed for RR-BLUP. Prediction accuracy of doubled haploid lines included in the training set was much greater than of those excluded from the training set, so there was little benefit to phenotyping only a subset of the lines genotyped. Finally, observed prediction accuracies in the simulation compared well to calculated prediction accuracies, indicating these theoretical formulas are useful for making resource allocation

The contribution of large trees to total transpiration rates in a pre-montane tropical forest and its implications for selective logging practices

Science.gov (United States)

Orozco, G.; Moore, G. W.; Miller, G. R.

2012-12-01

In the humid tropics, conservationists generally prefer selective logging practices over clearcutting. Large valuable timber is removed while the remaining forest is left relatively undisturbed. However, little is known about the impact of selective logging on site water balance. Because large trees have very deep sapwood and exposed canopies, they tend to have high transpiration. The first objective was to evaluate the methods used for scaling sap flow measurements to the watershed with particular emphasis on large trees. The second objective of this study was to determine the relative contribution of large trees to site water balance. Our study was conducted in a pre-montane transitional forest at the Texas A&M University Soltis Center in north-central Costa Rica. During the period between January and July 2012, sap flux was monitored in a 30-m diameter plot within a 10-ha watershed. Two pairs of heat dissipation sensors were installed in the outer 0-20 mm of each of 15 trees selected to represent the full range of tree sizes. In six of the largest trees, depth profiles were recorded at 10-mm intervals to a depth of 60 mm using compensation heat pulse sensors. To estimate sapwood basal area of the entire watershed, a stand survey was conducted in three 30-m-diameter plots. In each plot, we measured basal area of all trees and estimated sapwood basal area from sapwood depth measured in nearly half of the trees. An estimated 36.5% of the total sapwood area in this watershed comes from the outer 20 mm of sapwood, with the remaining 63.5% of sapwood from depths deeper than 20 mm. Nearly 13% of sapwood is from depths beyond 60 mm. Sap velocity profiles indicate the highest flow rates occurred in the 0-2 cm depths, with declines of 17% and 25% in the 20-40 mm and 40-60 mm ranges, respectively. Our results demonstrate the need to measure sap velocity profiles in large tropical trees. If total transpiration had been estimated solely from the 0-20 mm heat dissipation

Efficient Multi-Label Feature Selection Using Entropy-Based Label Selection

Directory of Open Access Journals (Sweden)

Jaesung Lee

2016-11-01

Full Text Available Multi-label feature selection is designed to select a subset of features according to their importance to multiple labels. This task can be achieved by ranking the dependencies of features and selecting the features with the highest rankings. In a multi-label feature selection problem, the algorithm may be faced with a dataset containing a large number of labels. Because the computational cost of multi-label feature selection increases according to the number of labels, the algorithm may suffer from a degradation in performance when processing very large datasets. In this study, we propose an efficient multi-label feature selection method based on an information-theoretic label selection strategy. By identifying a subset of labels that significantly influence the importance of features, the proposed method efficiently outputs a feature subset. Experimental results demonstrate that the proposed method can identify a feature subset much faster than conventional multi-label feature selection methods for large multi-label datasets.

RANKING ENTERPRISES IN TERMS OF COMPETENCES INSIDE REGIONAL PRODUCTION NETWORK

Directory of Open Access Journals (Sweden)

Marko Mladineo

2013-02-01

Full Text Available Today's economic crisis has led to bankruptcy of many successful, but usually large-sized enterprises. This brought into question the future of large-sized enterprises. However, the only alternative to largesized enterprises (LEs is networking of small and medium-sized enterprises (SMEs into Regional Production Networks (RPNet. RPNet is non-hierarchical organizational form in which every SME is autonomous. Hence, every SME of production network is capable and wiling to be part of special cooperation inside network called Virtual Enterprise (VE. For each new product a new virtual enterprise is formed from different SMEs. The question is: which SMEs will be part of new virtual enterprise? If it is possible to evaluate SME's competences, it is also possible to rank SMEs. Ranking of SMEs according to technical, organizational and human competences is multi-criteria decision analysis (MCDA problem. So, in this paper PROMETHEE method is selected to perform a ranking of SMEs.

Effect of ranking criteria on development goals in capital and manpower-limited oil and gas organizations

International Nuclear Information System (INIS)

Starzer, M.R.

1991-01-01

This paper summarizes a study to determine the effect of financial ranking criteria on development goals of oil and gas organizations. Economic analysis and ranking was applied to one hundred projects representing oil and gas investment opportunities available to an organization. Each project's after tax cash flows were subjected to four financial analysis methods for ranking. The four analysis methods used were net present value to investment ratio (NPVI), internal rate of return (IRR), payback period and profit to investment ratio (P/I). After ranking, the projects were totaled according to a particular organizational objective. Totaling of projects by ranking would continue until a limiting resource to the organization was exhausted. This study demonstrates the insensitivity of financial analysis methods for ranking whether the organization is limited by capital or manpower. It concludes that the only requirement for a ranking criterion to properly allocate resources is that the criterion quantifies the organizational goal to some degree. Decision makers charged with selecting the most attractive growth portfolio of investment opportunities will do well with any profit measuring criterion for ranking

Developing maximal neuromuscular power: Part 1--biological basis of maximal power production.

Science.gov (United States)

Cormie, Prue; McGuigan, Michael R; Newton, Robert U

2011-01-01

This series of reviews focuses on the most important neuromuscular function in many sport performances, the ability to generate maximal muscular power. Part 1 focuses on the factors that affect maximal power production, while part 2, which will follow in a forthcoming edition of Sports Medicine, explores the practical application of these findings by reviewing the scientific literature relevant to the development of training programmes that most effectively enhance maximal power production. The ability of the neuromuscular system to generate maximal power is affected by a range of interrelated factors. Maximal muscular power is defined and limited by the force-velocity relationship and affected by the length-tension relationship. The ability to generate maximal power is influenced by the type of muscle action involved and, in particular, the time available to develop force, storage and utilization of elastic energy, interactions of contractile and elastic elements, potentiation of contractile and elastic filaments as well as stretch reflexes. Furthermore, maximal power production is influenced by morphological factors including fibre type contribution to whole muscle area, muscle architectural features and tendon properties as well as neural factors including motor unit recruitment, firing frequency, synchronization and inter-muscular coordination. In addition, acute changes in the muscle environment (i.e. alterations resulting from fatigue, changes in hormone milieu and muscle temperature) impact the ability to generate maximal power. Resistance training has been shown to impact each of these neuromuscular factors in quite specific ways. Therefore, an understanding of the biological basis of maximal power production is essential for developing training programmes that effectively enhance maximal power production in the human.

Geophysical well logging operations and log analysis in Geothermal Well Desert Peak No. B-23-1

Energy Technology Data Exchange (ETDEWEB)

Sethi, D.K.; Fertl, W.H.

1980-03-01

Geothermal Well Desert Peak No. B-23-1 was logged by Dresser Atlas during April/May 1979 to a total depth of 2939 m (9642 ft). A temperature of 209/sup 0/C (408/sup 0/F) was observed on the maximum thermometer run with one of the logging tools. Borehole tools rated to a maximum temperature of 204.4/sup 0/C (400/sup 0/F) were utilized for logging except for the Densilog tool, which was from the other set of borehole instruments, rated to a still higher temperature, i.e., 260/sup 0/C (500/sup 0/F). The quality of the logs recorded and the environmental effects on the log response have been considered. The log response in the unusual lithologies of igneous and metamorphic formations encountered in this well could be correlated with the drill cutting data. An empirical, statistical log interpretation approach has made it possible to obtain meaningful information on the rocks penetrated. Various crossplots/histograms of the corrected log data have been generated on the computer. These are found to provide good resolution between the lithological units in the rock sequence. The crossplotting techniques and the statistical approach were combined with the drill cutting descriptions in order to arrive at the lithological characteristics. The results of log analysis and recommendations for logging of future wells have been included.

Theoretical and Numerical Study of Seismoelectric Logs for Logging While Drilling (LWD

Directory of Open Access Journals (Sweden)

Sun Xiang-Yang

2017-01-01

Full Text Available When the acoustic field propagates in the porous medium, the electromagnetic wave can be induced by the seismoelectric effects which can be used in the logging. This paper studies the seismoelectric wave field and deduces the formulations of the acoustic and electromagnetic field of the liquid in the well, and gives the acoustic and electromagnetic boundary conditions between the driller collar and the log liquid, when the driller collar is added. We also do the numerical simulation of the seismoelectric wave field excited by monopole source, study the velocity dispersion characteristics of the acoustic and electromagnetic field, and investigate the detective depth of the seismoelectric logs. Through the simulation we know the seismoelectric logs can avoid the interference of drill collar wave. This paper also provides theoretical guidance for the design of receiving antenna.

Rank-based Tests of the Cointegrating Rank in Semiparametric Error Correction Models

NARCIS (Netherlands)

Hallin, M.; van den Akker, R.; Werker, B.J.M.

2012-01-01

Abstract: This paper introduces rank-based tests for the cointegrating rank in an Error Correction Model with i.i.d. elliptical innovations. The tests are asymptotically distribution-free, and their validity does not depend on the actual distribution of the innovations. This result holds despite the

Universal scaling in sports ranking

International Nuclear Information System (INIS)

Deng Weibing; Li Wei; Cai Xu; Bulou, Alain; Wang Qiuping A

2012-01-01

Ranking is a ubiquitous phenomenon in human society. On the web pages of Forbes, one may find all kinds of rankings, such as the world's most powerful people, the world's richest people, the highest-earning tennis players, and so on and so forth. Herewith, we study a specific kind—sports ranking systems in which players' scores and/or prize money are accrued based on their performances in different matches. By investigating 40 data samples which span 12 different sports, we find that the distributions of scores and/or prize money follow universal power laws, with exponents nearly identical for most sports. In order to understand the origin of this universal scaling we focus on the tennis ranking systems. By checking the data we find that, for any pair of players, the probability that the higher-ranked player tops the lower-ranked opponent is proportional to the rank difference between the pair. Such a dependence can be well fitted to a sigmoidal function. By using this feature, we propose a simple toy model which can simulate the competition of players in different matches. The simulations yield results consistent with the empirical findings. Extensive simulation studies indicate that the model is quite robust with respect to the modifications of some parameters. (paper)

Face logging in Copenhagen Limestone, Denmark

DEFF Research Database (Denmark)

Jakobsen, Lisa; Foged, Niels Nielsen; Erichsen, Lars

2015-01-01

tunnel in Copenhagen more than 2.5 km face logs were made in 467 locations at underground stations, shafts, caverns and along bored tunnels. Over 160 geotechnical boreholes, many with geophysical logging were executed prior to construction works. The bedrock consists of Paleogene "Copenhagen limestone......The requirement for excavation support can be assessed from face logging. Face logs can also improve our knowledge of lithological and structural conditions within bedrock and supplement information from boreholes and geophysical logs. During the construction of 8 km metro tunnel and 4 km heating....... The induration degrees recorded in face logs and boreholes are compared and correlated. Distinct geophysical log markers are used to divide the limestone into three units. These marker horizons are correlated between face logs and geotechnical boreholes. A 3D model of the strength variations recorded within...

Logging costs and cutting methods in young-growth ponderosa pine in California

Science.gov (United States)

Philip M. McDonald; William A. Atkinson; Dale O. Hall

1969-01-01

Mixed-conifer stands at the Challenge Experimental Forest, Calif., were cut to four specifications: seed-tree, group selection, single tree selection, and clearcut. Logging costs and production rates were compared and evaluated. Cutting method had little effect on felling or skidding production; felling ranged from 1,802 to 2,019 bd ft per hour, and skidding from 3,138...

Minkowski metrics in creating universal ranking algorithms

Directory of Open Access Journals (Sweden)

Andrzej Ameljańczyk

2014-06-01

Full Text Available The paper presents a general procedure for creating the rankings of a set of objects, while the relation of preference based on any ranking function. The analysis was possible to use the ranking functions began by showing the fundamental drawbacks of commonly used functions in the form of a weighted sum. As a special case of the ranking procedure in the space of a relation, the procedure based on the notion of an ideal element and generalized Minkowski distance from the element was proposed. This procedure, presented as universal ranking algorithm, eliminates most of the disadvantages of ranking functions in the form of a weighted sum.[b]Keywords[/b]: ranking functions, preference relation, ranking clusters, categories, ideal point, universal ranking algorithm

Recurrent fuzzy ranking methods

Science.gov (United States)

Hajjari, Tayebeh

2012-11-01

With the increasing development of fuzzy set theory in various scientific fields and the need to compare fuzzy numbers in different areas. Therefore, Ranking of fuzzy numbers plays a very important role in linguistic decision-making, engineering, business and some other fuzzy application systems. Several strategies have been proposed for ranking of fuzzy numbers. Each of these techniques has been shown to produce non-intuitive results in certain case. In this paper, we reviewed some recent ranking methods, which will be useful for the researchers who are interested in this area.

Carbon emissions from tropical forest degradation caused by logging

International Nuclear Information System (INIS)

Pearson, Timothy R H; Brown, Sandra; Casarim, Felipe M

2014-01-01

The focus of land-use related efforts in developing countries to reduce carbon emissions has been on slowing deforestation, yet international agreements are to reduce emissions from both deforestation and forest degradation (REDD). The second ‘D’ is poorly understood and accounted for a number of technical and policy reasons. Here we introduce a complete accounting method for estimating emission factors from selective timber harvesting, a substantial form of forest degradation in many tropical developing countries. The method accounts separately for emissions from the extracted log, from incidental damage to the surrounding forest, and from logging infrastructure, and emissions are expressed as units of carbon per cubic meter of timber extracted to allow for simple application to timber harvesting statistics. We applied the method in six tropical countries (Belize, Bolivia, Brazil, Guyana, Indonesia, and Republic of Congo), resulting in total emission factors of 0.99−2.33 Mg C m −3 . In all cases, emissions were dominated by damage to surrounding vegetation and the infrastructure rather than the logs themselves, and total emissions represented about 3–15% of the biomass carbon stocks of the associated unlogged forests. We then combined the emission factors with country level logging statistics for nine key timber producing countries represented by our study areas to gain an understanding of the order of magnitude of emissions from degradation compared to those recently reported for deforestation in the same countries. For the nine countries included, emissions from logging were on average equivalent to about 12% of those from deforestation. For those nine countries with relatively low emissions from deforestation, emissions from logging were equivalent to half or more of those from deforestation, whereas for those countries with the highest emissions from deforestation, emissions from logging were equivalent to <10% of those from deforestation

Ranking Operations Management conferences

NARCIS (Netherlands)

Steenhuis, H.J.; de Bruijn, E.J.; Gupta, Sushil; Laptaned, U

2007-01-01

Several publications have appeared in the field of Operations Management which rank Operations Management related journals. Several ranking systems exist for journals based on , for example, perceived relevance and quality, citation, and author affiliation. Many academics also publish at conferences

Rolling Bearing Fault Diagnosis Using Modified Neighborhood Preserving Embedding and Maximal Overlap Discrete Wavelet Packet Transform with Sensitive Features Selection

Directory of Open Access Journals (Sweden)

Fei Dong

2018-01-01

Full Text Available In order to enhance the performance of bearing fault diagnosis and classification, features extraction and features dimensionality reduction have become more important. The original statistical feature set was calculated from single branch reconstruction vibration signals obtained by using maximal overlap discrete wavelet packet transform (MODWPT. In order to reduce redundancy information of original statistical feature set, features selection by adjusted rand index and sum of within-class mean deviations (FSASD was proposed to select fault sensitive features. Furthermore, a modified features dimensionality reduction method, supervised neighborhood preserving embedding with label information (SNPEL, was proposed to realize low-dimensional representations for high-dimensional feature space. Finally, vibration signals collected from two experimental test rigs were employed to evaluate the performance of the proposed procedure. The results show that the effectiveness, adaptability, and superiority of the proposed procedure can serve as an intelligent bearing fault diagnosis system.

Log4J

CERN Document Server

Perry, Steven

2009-01-01

Log4j has been around for a while now, and it seems like so many applications use it. I've used it in my applications for years now, and I'll bet you have too. But every time I need to do something with log4j I've never done before I find myself searching for examples of how to do whatever that is, and I don't usually have much luck. I believe the reason for this is that there is a not a great deal of useful information about log4j, either in print or on the Internet. The information is too simple to be of real-world use, too complicated to be distilled quickly (which is what most developers

Supplier evaluation in manufacturing environment using compromise ranking method with grey interval numbers

Directory of Open Access Journals (Sweden)

Prasenjit Chatterjee

2012-04-01

Full Text Available Evaluation of proper supplier for manufacturing organizations is one of the most challenging problems in real time manufacturing environment due to a wide variety of customer demands. It has become more and more complicated to meet the challenges of international competitiveness and as the decision makers need to assess a wide range of alternative suppliers based on a set of conflicting criteria. Thus, the main objective of supplier selection is to select highly potential supplier through which all the set goals regarding the purchasing and manufacturing activity can be achieved. Because of these reasons, supplier selection has got considerable attention by the academicians and researchers. This paper presents a combined multi-criteria decision making methodology for supplier evaluation for given industrial applications. The proposed methodology is based on a compromise ranking method combined with Grey Interval Numbers considering different cardinal and ordinal criteria and their relative importance. A ‘supplier selection index’ is also proposed to help evaluation and ranking the alternative suppliers. Two examples are illustrated to demonstrate the potentiality and applicability of the proposed method.

Country-specific determinants of world university rankings

OpenAIRE

Pietrucha, Jacek

2017-01-01

This paper examines country-specific factors that affect the three most influential world university rankings (the Academic Ranking of World Universities, the QS World University Ranking, and the Times Higher Education World University Ranking). We run a cross sectional regression that covers 42–71 countries (depending on the ranking and data availability). We show that the position of universities from a country in the ranking is determined by the following country-specific variables: econom...

Unsupervised signature extraction from forensic logs

NARCIS (Netherlands)

Thaler, S.M.; Menkovski, V.; Petkovic, M.; Altun, Y.; Das, K.; Mielikäinen, T.; Malerba, D.; Stefanowski, J.; Read, J.; Žitnik, M.; Ceci, M.

2017-01-01

Signature extraction is a key part of forensic log analysis. It involves recognizing patterns in log lines such that log lines that originated from the same line of code are grouped together. A log signature consists of immutable parts and mutable parts. The immutable parts define the signature, and

Robust Tracking with Discriminative Ranking Middle-Level Patches

Directory of Open Access Journals (Sweden)

Hong Liu

2014-04-01

Full Text Available The appearance model has been shown to be essential for robust visual tracking since it is the basic criterion to locating targets in video sequences. Though existing tracking-by-detection algorithms have shown to be greatly promising, they still suffer from the drift problem, which is caused by updating appearance models. In this paper, we propose a new appearance model composed of ranking middle-level patches to capture more object distinctiveness than traditional tracking-by-detection models. Targets and backgrounds are represented by both low-level bottom-up features and high-level top-down patches, which can compensate each other. Bottom-up features are defined at the pixel level, and each feature gets its discrimination score through selective feature attention mechanism. In top-down feature extraction, rectangular patches are ranked according to their bottom-up discrimination scores, by which all of them are clustered into irregular patches, named ranking middle-level patches. In addition, at the stage of classifier training, the online random forests algorithm is specially refined to reduce drifting problems. Experiments on challenging public datasets and our test videos demonstrate that our approach can effectively prevent the tracker drifting problem and obtain competitive performance in visual tracking.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

Science.gov (United States)

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Log-balanced combinatorial sequences

Directory of Open Access Journals (Sweden)

Tomislav Došlic

2005-01-01

Full Text Available We consider log-convex sequences that satisfy an additional constraint imposed on their rate of growth. We call such sequences log-balanced. It is shown that all such sequences satisfy a pair of double inequalities. Sufficient conditions for log-balancedness are given for the case when the sequence satisfies a two- (or more- term linear recurrence. It is shown that many combinatorially interesting sequences belong to this class, and, as a consequence, that the above-mentioned double inequalities are valid for all of them.

LOG2MARKUP: State module to transform a Stata text log into a markup document

DEFF Research Database (Denmark)

2016-01-01

log2markup extract parts of the text version from the Stata log command and transform the logfile into a markup based document with the same name, but with extension markup (or otherwise specified in option extension) instead of log. The author usually uses markdown for writing documents. However...

Universal emergence of PageRank

Energy Technology Data Exchange (ETDEWEB)

Frahm, K M; Georgeot, B; Shepelyansky, D L, E-mail: frahm@irsamc.ups-tlse.fr, E-mail: georgeot@irsamc.ups-tlse.fr, E-mail: dima@irsamc.ups-tlse.fr [Laboratoire de Physique Theorique du CNRS, IRSAMC, Universite de Toulouse, UPS, 31062 Toulouse (France)

2011-11-18

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter {alpha} Element-Of ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when {alpha} {yields} 1. The whole network can be divided into a core part and a group of invariant subspaces. For {alpha} {yields} 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at {alpha} {yields} 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

Universal emergence of PageRank

International Nuclear Information System (INIS)

Frahm, K M; Georgeot, B; Shepelyansky, D L

2011-01-01

The PageRank algorithm enables us to rank the nodes of a network through a specific eigenvector of the Google matrix, using a damping parameter α ∈ ]0, 1[. Using extensive numerical simulations of large web networks, with a special accent on British University networks, we determine numerically and analytically the universal features of the PageRank vector at its emergence when α → 1. The whole network can be divided into a core part and a group of invariant subspaces. For α → 1, PageRank converges to a universal power-law distribution on the invariant subspaces whose size distribution also follows a universal power law. The convergence of PageRank at α → 1 is controlled by eigenvalues of the core part of the Google matrix, which are extremely close to unity, leading to large relaxation times as, for example, in spin glasses. (paper)

QSPR Models for Predicting Log Pliver Values for Volatile Organic Compounds Combining Statistical Methods and Domain Knowledge

Directory of Open Access Journals (Sweden)

Mónica F. Díaz

2012-12-01

Full Text Available Volatile organic compounds (VOCs are contained in a variety of chemicals that can be found in household products and may have undesirable effects on health. Thereby, it is important to model blood-to-liver partition coefficients (log Pliver for VOCs in a fast and inexpensive way. In this paper, we present two new quantitative structure-property relationship (QSPR models for the prediction of log Pliver, where we also propose a hybrid approach for the selection of the descriptors. This hybrid methodology combines a machine learning method with a manual selection based on expert knowledge. This allows obtaining a set of descriptors that is interpretable in physicochemical terms. Our regression models were trained using decision trees and neural networks and validated using an external test set. Results show high prediction accuracy compared to previous log Pliver models, and the descriptor selection approach provides a means to get a small set of descriptors that is in agreement with theoretical understanding of the target property.

Maximizers versus satisficers

OpenAIRE

Andrew M. Parker; Wandi Bruine de Bruin; Baruch Fischhoff

2007-01-01

Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007). Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002), we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions...

Life cycle performances of log wood applied for soil bioengineering constructions

Science.gov (United States)

Kalny, Gerda; Strauss-Sieberth, Alexandra; Strauss, Alfred; Rauch, Hans Peter

2016-04-01

Nowadays there is a high demand on engineering solutions considering not only technical aspects but also ecological and aesthetic values. Soil bioengineering is a construction technique that uses biological components for hydraulic and civil engineering solutions. Soil bioengineering solutions are based on the application of living plants and other auxiliary materials including among others log wood. This kind of construction material supports the soil bioengineering system as long as the plants as living construction material overtake the stability function. Therefore it is important to know about the durability and the degradation process of the wooden logs to retain the integral performance of a soil bio engineering system. These aspects will be considered within the framework of the interdisciplinary research project „ELWIRA Plants, wood, steel and concrete - life cycle performances as construction materials". Therefore field investigations on soil bioengineering construction material, specifically European Larch wood logs, of different soil bioengineering structures at the river Wien have been conducted. The drilling resistance as a parameter for particular material characteristics of selected logs was measured and analysed. The drilling resistance was measured with a Rinntech Resistograph instrument at different positions of the wooden logs, all surrounded with three different backfills: Fully surrounded with air, with earth contact on one side and near the water surface in wet-dry conditions. The age of the used logs ranges from one year old up to 20 year old. Results show progress of the drilling resistance throughout the whole cross section as an indicator to assess soil bioengineering construction material. Logs surrounded by air showed a higher drilling resistance than logs with earth contact and the ones exposed to wet-dry conditions. Hence the functional capability of wooden logs were analysed and discussed in terms of different levels of degradation

Radiometric well logging instruments

International Nuclear Information System (INIS)

Davydov, A.V.

1975-01-01

The technical properties of well instruments for radioactive logging used in the radiometric logging complexes PKS-1000-1 (''Sond-1'') and PRKS-2 (''Vitok-2'') are described. The main features of the electric circuit of the measuring channels are given

Development of phenomena identification and ranking table for APR1400 main steam line break

International Nuclear Information System (INIS)

Song, J. H.; Chung, B. D.; Jeong, J. J.

2003-01-01

A Phenomena Identification and Ranking Table (PIRT) was developed for the Main Steam Line Break (MSLB) event of an APR-1400 (Advanced Power Reactor-1400). A team of experts from research institutes, industries, and regulatory bodies participated in the development. The selected event was a double-ended steam line break at full power with the reactor coolant pump running. The panel selected the fuel performance as the primary safety criterion for ranking. The plant design data, the results of APR-1400 safety analysis, and the results of additional best estimate analysis by MARS2.1 were utilized. Three phases of pre-trip, rapid cool-down, and safety injection phase were identified. Then, the ranking of a system, components, phenomenon/process based on the relative importance to the primary evaluation criterion were followed for each time phase. Finally, the knowledge-level for each important process in the component was ranked in terms of the existing knowledge. The highly ranked phenomena identified for APR-1400 MSLB are tube wall heat transfer at the steam generator shell, void distribution at the steam generator shell, liquid entrainment in the separators, mixture level in the separators, boron mixing in the upper down comer, boron transport and thermal mixing in the lower plenum, stored energy release in the upper head, and flow to and/from the upper head. The PIRT will be used as a guide in planning cost effective experimental programs and code development efforts, especially for the quantification of the process and/or phenomena, which have a high importance but low knowledge level

Hardwood log supply: a broader perspective

Science.gov (United States)

Iris Montague; Adri Andersch; Jan Wiedenbeck; Urs. Buehlmann

2015-01-01

At regional and state meetings we talk with others in our business about the problems we face: log exports, log quality, log markets, logger shortages, cash flow problems, the weather. These are familiar talking points and real and persistent problems. But what is the relative importance of these problems for log procurement in different regions of...

Maximal frustration as an immunological principle.

Science.gov (United States)

de Abreu, F Vistulo; Mostardinha, P

2009-03-06

A fundamental problem in immunology is that of understanding how the immune system selects promptly which cells to kill without harming the body. This problem poses an apparent paradox. Strong reactivity against pathogens seems incompatible with perfect tolerance towards self. We propose a different view on cellular reactivity to overcome this paradox: effector functions should be seen as the outcome of cellular decisions which can be in conflict with other cells' decisions. We argue that if cellular systems are frustrated, then extensive cross-reactivity among the elements in the system can decrease the reactivity of the system as a whole and induce perfect tolerance. Using numerical and mathematical analyses, we discuss two simple models that perform optimal pathogenic detection with no autoimmunity if cells are maximally frustrated. This study strongly suggests that a principle of maximal frustration could be used to build artificial immune systems. It would be interesting to test this principle in the real adaptive immune system.

Dynamic Matrix Rank

DEFF Research Database (Denmark)

Frandsen, Gudmund Skovbjerg; Frandsen, Peter Frands

2009-01-01

We consider maintaining information about the rank of a matrix under changes of the entries. For n×n matrices, we show an upper bound of O(n1.575) arithmetic operations and a lower bound of Ω(n) arithmetic operations per element change. The upper bound is valid when changing up to O(n0.575) entries...... in a single column of the matrix. We also give an algorithm that maintains the rank using O(n2) arithmetic operations per rank one update. These bounds appear to be the first nontrivial bounds for the problem. The upper bounds are valid for arbitrary fields, whereas the lower bound is valid for algebraically...... closed fields. The upper bound for element updates uses fast rectangular matrix multiplication, and the lower bound involves further development of an earlier technique for proving lower bounds for dynamic computation of rational functions....

Analysis of borehole-radar reflection logs from selected HC boreholes at the Project Shoal area, Churchill County, Nevada; TOPICAL

International Nuclear Information System (INIS)

Lane, J.W. Jr.; Joesten, P.K.; Pohll, Greg; Mihevic, Todd

2001-01-01

Single-hole borehole-radar reflection logs were collected and interpreted in support of a study to characterize ground-water flow and transport at the Project Shoal Area (PSA) in Churchill County, Nevada. Radar logging was conducted in six boreholes using 60-MHz omni-directional electric-dipole antennas and a 60-MHz magnetic-dipole directional receiving antenna. Radar data from five boreholes were interpreted to identify the location, orientation, estimated length, and spatial continuity of planar reflectors present in the logs. The overall quality of the radar data is marginal and ranges from very poor to good. Twenty-seven reflectors were interpreted from the directional radar reflection logs. Although the range of orientation interpreted for the reflectors is large, a significant number of reflectors strike northeast-southwest and east-west to slightly northwest-southeast. Reflectors are moderate to steeply dipping and reflector length ranged from less than 7 m to more than 133 m. Qualitative scores were assigned to each reflector to provide a sense of the spatial continuity of the reflector and the characteristics of the field data relative to an ideal planar reflector (orientation score). The overall orientation scores are low, which reflects the general data quality, but also indicates that the properties of most reflectors depart from the ideal planar case. The low scores are consistent with reflections from fracture zones that contain numerous, closely spaced, sub-parallel fractures. Interpretation of borehole-radar direct-wave velocity and amplitude logs identified several characteristics of the logged boreholes: (1) low-velocity zones correlate with decreased direct-wave amplitude, indicating the presence of fracture zones; (2) direct-wave amplitude increases with depth in three of the boreholes, suggesting an increase in electrical resistivity with depth resulting from changes in mineral assemblage or from a decrease in the specific conductance of ground

Conservation threats and the phylogenetic utility of IUCN Red List rankings in Incilius toads.

Science.gov (United States)

Schachat, Sandra R; Mulcahy, Daniel G; Mendelson, Joseph R

2016-02-01

Phylogenetic analysis of extinction threat is an emerging tool in the field of conservation. However, there are problems with the methods and data as commonly used. Phylogenetic sampling usually extends to the level of family or genus, but International Union for Conservation of Nature (IUCN) rankings are available only for individual species, and, although different species within a taxonomic group may have the same IUCN rank, the species may have been ranked as such for different reasons. Therefore, IUCN rank may not reflect evolutionary history and thus may not be appropriate for use in a phylogenetic context. To be used appropriately, threat-risk data should reflect the cause of extinction threat rather than the IUCN threat ranking. In a case study of the toad genus Incilius, with phylogenetic sampling at the species level (so that the resolution of the phylogeny matches character data from the IUCN Red List), we analyzed causes of decline and IUCN threat rankings by calculating metrics of phylogenetic signal (such as Fritz and Purvis' D). We also analyzed the extent to which cause of decline and threat ranking overlap by calculating phylogenetic correlation between these 2 types of character data. Incilius species varied greatly in both threat ranking and cause of decline; this variability would be lost at a coarser taxonomic resolution. We found far more phylogenetic signal, likely correlated with evolutionary history, for causes of decline than for IUCN threat ranking. Individual causes of decline and IUCN threat rankings were largely uncorrelated on the phylogeny. Our results demonstrate the importance of character selection and taxonomic resolution when extinction threat is analyzed in a phylogenetic context. © 2015 Society for Conservation Biology.

Semi-automatic logarithmic converter of logs

International Nuclear Information System (INIS)

Gol'dman, Z.A.; Bondar's, V.V.

1974-01-01

Semi-automatic logarithmic converter of logging charts. An original semi-automatic converter was developed for use in converting BK resistance logging charts and the time interval, ΔT, of acoustic logs from a linear to a logarithmic scale with a specific ratio for subsequent combining of them with neutron-gamma logging charts in operative interpretation of logging materials by a normalization method. The converter can be used to increase productivity by giving curves different from those obtained in manual, pointwise processing. The equipment operates reliably and is simple in use. (author)

Statistical methods for ranking data

CERN Document Server

Alvo, Mayer

2014-01-01

This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.

Power to the logs!

CERN Multimedia

CERN. Geneva; MACMAHON, Joseph

2015-01-01

Are you tired of using grep, vi and emacs to read your logs? Do you feel like you’re missing the big picture? Does the word "statistics" put a smile on your face? Then it’s time to give power to the logs!

Hitting the Rankings Jackpot

Science.gov (United States)

Chapman, David W.

2008-01-01

Recently, Samford University was ranked 27th in the nation in a report released by "Forbes" magazine. In this article, the author relates how the people working at Samford University were surprised at its ranking. Although Samford is the largest privately institution in Alabama, its distinguished academic achievements aren't even…

A method of estimating log weights.

Science.gov (United States)

Charles N. Mann; Hilton H. Lysons

1972-01-01

This paper presents a practical method of estimating the weights of logs before they are yarded. Knowledge of log weights is required to achieve optimum loading of modern yarding equipment. Truckloads of logs are weighed and measured to obtain a local density index (pounds per cubic foot) for a species of logs. The density index is then used to estimate the weights of...

California-Nevada uranium logging. Final report

International Nuclear Information System (INIS)

1981-04-01

The purpose of this project was to obtain geophysical logs of industry drill holes to assess the uranium resource potential of geologic formations of interest. The work was part of the US Department of Energy's National Uranium Resource Evaluation (NURE) Program. The principal objective of the logging program was to determine radioelement grade of formations through natural gamma ray detectors. Supplementary information was obtained from resistivity (R), self-potential (SP), point resistance (RE), and neutron density (NN) logs for formation interpretation. Additional data for log interpretation was obtained from caliper logs, casing schedules, and downhole temperature. This data was obtained from well operators when available, with new logs obtained where not formerly available. This report contains a summary of the project and data obtained to date

Cardiorespiratory Coordination in Repeated Maximal Exercise

Directory of Open Access Journals (Sweden)

Sergi Garcia-Retortillo

2017-06-01

Full Text Available Increases in cardiorespiratory coordination (CRC after training with no differences in performance and physiological variables have recently been reported using a principal component analysis approach. However, no research has yet evaluated the short-term effects of exercise on CRC. The aim of this study was to delineate the behavior of CRC under different physiological initial conditions produced by repeated maximal exercises. Fifteen participants performed 2 consecutive graded and maximal cycling tests. Test 1 was performed without any previous exercise, and Test 2 6 min after Test 1. Both tests started at 0 W and the workload was increased by 25 W/min in males and 20 W/min in females, until they were not able to maintain the prescribed cycling frequency of 70 rpm for more than 5 consecutive seconds. A principal component (PC analysis of selected cardiovascular and cardiorespiratory variables (expired fraction of O2, expired fraction of CO2, ventilation, systolic blood pressure, diastolic blood pressure, and heart rate was performed to evaluate the CRC defined by the number of PCs in both tests. In order to quantify the degree of coordination, the information entropy was calculated and the eigenvalues of the first PC (PC1 were compared between tests. Although no significant differences were found between the tests with respect to the performed maximal workload (Wmax, maximal oxygen consumption (VO2 max, or ventilatory threshold (VT, an increase in the number of PCs and/or a decrease of eigenvalues of PC1 (t = 2.95; p = 0.01; d = 1.08 was found in Test 2 compared to Test 1. Moreover, entropy was significantly higher (Z = 2.33; p = 0.02; d = 1.43 in the last test. In conclusion, despite the fact that no significant differences were observed in the conventionally explored maximal performance and physiological variables (Wmax, VO2 max, and VT between tests, a reduction of CRC was observed in Test 2. These results emphasize the interest of CRC

Combination thermal and radiation shield for well logging apparatus

International Nuclear Information System (INIS)

Wilson, B.F.

1984-01-01

A device for providing both thermal protection and radiation shielding for components such as radiation detectors within a well logging instrument comprises a thermally insulative flask containing a weldment filled with a mass of eutectic material which undergoes a change of state e.g. melting at a temperature which will provide an acceptable thermal environment for such components for extended time periods. The eutectic material which is preferably a bismuth (58%)/tin (42%) alloy has a specific gravity (> 8.5) facilitating its use as a radiation shield and is distributed around the radiation detectors so as to selectively impede the impinging of the detectors by radiation. The device is incorporated in a skid of a well logging instrument for measuring γ backscatter. A γ source is located either above or within the protective shielding. (author)

A novel approach proposed for fractured zone detection using petrophysical logs

International Nuclear Information System (INIS)

Tokhmechi, B; Memarian, H; Noubari, H A; Moshiri, B

2009-01-01

Fracture detection is a key step in wellbore stability and fractured reservoir fluid flow simulation. While different methods have been proposed for fractured zones detection, each of them is associated with certain shortcomings that prevent their full use in different related engineering applications. In this paper, a novel combined method is proposed for fractured zone detection, using processing of petrophysical logs with wavelet, classification and data fusion techniques. Image and petrophysical logs from Asmari reservoir in eight wells of an oilfield in southwestern Iran were used to investigate the accuracy and applicability of the proposed method. Initially, an energy matching strategy was utilized to select the optimum mother wavelets for de-noising and decomposition of petrophysical logs. Parzen and Bayesian classifiers were applied to raw, de-noised and various frequency bands of logs after decomposition in order to detect fractured zones. Results show that the low-frequency bands (approximation 2, a 2 ) of de-noised logs are the best data for fractured zones detection. These classifiers considered one well as test well and the other seven wells as train wells. Majority voting, optimistic OWA (ordered weighted averaging) and pessimistic OWA methods were used to fuse the results obtained from seven train wells. Results confirmed that Parzen and optimistic OWA are the best combined methods to detect fractured zones. The generalization of method is confirmed with an average accuracy of about 72%

A tilting approach to ranking influence

KAUST Repository

Genton, Marc G.

2014-12-01

We suggest a new approach, which is applicable for general statistics computed from random samples of univariate or vector-valued or functional data, to assessing the influence that individual data have on the value of a statistic, and to ranking the data in terms of that influence. Our method is based on, first, perturbing the value of the statistic by ‘tilting’, or reweighting, each data value, where the total amount of tilt is constrained to be the least possible, subject to achieving a given small perturbation of the statistic, and, then, taking the ranking of the influence of data values to be that which corresponds to ranking the changes in data weights. It is shown, both theoretically and numerically, that this ranking does not depend on the size of the perturbation, provided that the perturbation is sufficiently small. That simple result leads directly to an elegant geometric interpretation of the ranks; they are the ranks of the lengths of projections of the weights onto a ‘line’ determined by the first empirical principal component function in a generalized measure of covariance. To illustrate the generality of the method we introduce and explore it in the case of functional data, where (for example) it leads to generalized boxplots. The method has the advantage of providing an interpretable ranking that depends on the statistic under consideration. For example, the ranking of data, in terms of their influence on the value of a statistic, is different for a measure of location and for a measure of scale. This is as it should be; a ranking of data in terms of their influence should depend on the manner in which the data are used. Additionally, the ranking recognizes, rather than ignores, sign, and in particular can identify left- and right-hand ‘tails’ of the distribution of a random function or vector.

TEACHERS’ EDUCATIONAL QUALIFICATION, RANK LEVEL, WORKING DURATION, AGE, WORK MOTIVATION AND WORK EFFECTIVENESS

Directory of Open Access Journals (Sweden)

Bambang Budi Wiyono

2016-02-01

Full Text Available Teachers’ Educational Qualification, Rank Level, Working Duration, Age, Working Mo­tivation, and Working Effectiveness The study investigated the effects of educational qualification, rank level, working duration and age on the elementary school teachers’ working motivation and working ef­fectiveness. The sample of the study consisted of 438 elementary school teachers in Malang which were selected through cluster sampling technique. The study was conducted using explanatory design in the form of causal model. The data were collected using questionnaire and documentation, and were analyzed descrip­tively employing structural equation technique. The study revealed that that the effect of the educational qualification, rank level, working duration and age on teachers’ working motivation and working effec­tiveness, both directly and indirectly, was not significant.

EFFECT OF THINNING AND FERTILIZATION ON Eucalyptus grandis Hill ex-Maiden PITH DISPLACEMENT AND LOG END SPLITTlNG

Directory of Open Access Journals (Sweden)

Israel Luiz de Lima

2007-06-01

Full Text Available The aim of this study was to analyse the influence of thinning and fertilization on some log properties which influence sawn wood yield in a 21 year-old grown Eucalyptus grandis stand. Three selective thinning intensities (37, 50 and 75%, presence or absence of fertilizers on the beginning of the thinning, two diameter classes and two logs taken from two different vertical positions were taken as the study factors. The influence of the factors and their combination on tree growth stresses were indirectly evaluate through log end splitting and pith displacement in relation to its normal central position. Thinning, fertilization, diameter class and log position on the tree height did not have significant effect on pith displacement. The logs from fertilized plots presented higher log end splitting index than others.

Ranking adverse drug reactions with crowdsourcing.

Science.gov (United States)

Gottlieb, Assaf; Hoehndorf, Robert; Dumontier, Michel; Altman, Russ B

2015-03-23

There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. The intent of the study was to rank ADRs according to severity. We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

Ranking Adverse Drug Reactions With Crowdsourcing

KAUST Repository

Gottlieb, Assaf

2015-03-23

Background: There is no publicly available resource that provides the relative severity of adverse drug reactions (ADRs). Such a resource would be useful for several applications, including assessment of the risks and benefits of drugs and improvement of patient-centered care. It could also be used to triage predictions of drug adverse events. Objective: The intent of the study was to rank ADRs according to severity. Methods: We used Internet-based crowdsourcing to rank ADRs according to severity. We assigned 126,512 pairwise comparisons of ADRs to 2589 Amazon Mechanical Turk workers and used these comparisons to rank order 2929 ADRs. Results: There is good correlation (rho=.53) between the mortality rates associated with ADRs and their rank. Our ranking highlights severe drug-ADR predictions, such as cardiovascular ADRs for raloxifene and celecoxib. It also triages genes associated with severe ADRs such as epidermal growth-factor receptor (EGFR), associated with glioblastoma multiforme, and SCN1A, associated with epilepsy. Conclusions: ADR ranking lays a first stepping stone in personalized drug risk assessment. Ranking of ADRs using crowdsourcing may have useful clinical and financial implications, and should be further investigated in the context of health care decision making.

32 CFR 700.846 - Status of logs.

Science.gov (United States)

2010-07-01

... Officers Afloat § 700.846 Status of logs. The deck log, the engineering log, the compass record, the bearing hooks, the engineer's bell book, and any records generated by automated data logging equipment...

Trade-offs between carbon stocks and timber recovery in tropical forests are mediated by logging intensity.

Science.gov (United States)

Roopsind, Anand; Caughlin, T Trevor; van der Hout, Peter; Arets, Eric; Putz, Francis E

2018-03-30

Forest degradation accounts for ~ 70% of total carbon losses from tropical forests. Substantial emissions are from selective logging, a land-use activity that decreases forest carbon density. To maintain carbon values in selectively logged forests, climate change mitigation policies and government agencies promote the adoption of reduced-impact logging (RIL) practices. However, whether RIL will maintain both carbon and timber values in managed tropical forests over time remains uncertain. In this study, we quantify the recovery of timber stocks and aboveground carbon at an experimental site where forests were subjected to different intensities of RIL (4 trees ha -1 , 8 trees ha -1 , and 16 trees ha -1 ). Our census data spans 20 years post-logging and 17 years after the liberation of future crop trees from competition in a tropical forest on the Guiana Shield, a globally important forest carbon reservoir. We model recovery of timber and carbon with a breakpoint regression that allowed us to capture elevated tree mortality immediately after logging. Recovery rates of timber and carbon were governed by the presence of residual trees (i.e., trees that persisted through the first harvest). The liberation treatment stimulated faster recovery of timber albeit at a carbon cost. Model results suggest a threshold logging intensity beyond which forests managed for timber and carbon derive few benefits from RIL, with recruitment and residual growth not sufficient to offset losses. Inclusion of the breakpoint at which carbon and timber gains outpaced post-logging mortality led to high predictive accuracy, including out-of-sample R 2 values >90%, and enabled inference on demographic changes post-logging. Our modeling framework is broadly applicable to studies that aim to quantify impacts of logging on forest recovery. Overall, we demonstrate that initial mortality drives variation in recovery rates, that the second harvest depends on old growth wood, and that timber

Ranking scientific publications: the effect of nonlinearity

Science.gov (United States)

Yao, Liyang; Wei, Tian; Zeng, An; Fan, Ying; di, Zengru

2014-10-01

Ranking the significance of scientific publications is a long-standing challenge. The network-based analysis is a natural and common approach for evaluating the scientific credit of papers. Although the number of citations has been widely used as a metric to rank papers, recently some iterative processes such as the well-known PageRank algorithm have been applied to the citation networks to address this problem. In this paper, we introduce nonlinearity to the PageRank algorithm when aggregating resources from different nodes to further enhance the effect of important papers. The validation of our method is performed on the data of American Physical Society (APS) journals. The results indicate that the nonlinearity improves the performance of the PageRank algorithm in terms of ranking effectiveness, as well as robustness against malicious manipulations. Although the nonlinearity analysis is based on the PageRank algorithm, it can be easily extended to other iterative ranking algorithms and similar improvements are expected.