A Gaussian-based rank approximation for subspace clustering

NASA Astrophysics Data System (ADS)

Xu, Fei; Peng, Chong; Hu, Yunhong; He, Guoping

2018-04-01

Low-rank representation (LRR) has been shown successful in seeking low-rank structures of data relationships in a union of subspaces. Generally, LRR and LRR-based variants need to solve the nuclear norm-based minimization problems. Beyond the success of such methods, it has been widely noted that the nuclear norm may not be a good rank approximation because it simply adds all singular values of a matrix together and thus large singular values may dominant the weight. This results in far from satisfactory rank approximation and may degrade the performance of lowrank models based on the nuclear norm. In this paper, we propose a novel nonconvex rank approximation based on the Gaussian distribution function, which has demanding properties to be a better rank approximation than the nuclear norm. Then a low-rank model is proposed based on the new rank approximation with application to motion segmentation. Experimental results have shown significant improvements and verified the effectiveness of our method.

Linear Subspace Ranking Hashing for Cross-Modal Retrieval.

PubMed

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.

Two-Dimensional Hermite Filters Simplify the Description of High-Order Statistics of Natural Images.

PubMed

Hu, Qin; Victor, Jonathan D

2016-09-01

Natural image statistics play a crucial role in shaping biological visual systems, understanding their function and design principles, and designing effective computer-vision algorithms. High-order statistics are critical for conveying local features, but they are challenging to study - largely because their number and variety is large. Here, via the use of two-dimensional Hermite (TDH) functions, we identify a covert symmetry in high-order statistics of natural images that simplifies this task. This emerges from the structure of TDH functions, which are an orthogonal set of functions that are organized into a hierarchy of ranks. Specifically, we find that the shape (skewness and kurtosis) of the distribution of filter coefficients depends only on the projection of the function onto a 1-dimensional subspace specific to each rank. The characterization of natural image statistics provided by TDH filter coefficients reflects both their phase and amplitude structure, and we suggest an intuitive interpretation for the special subspace within each rank.

Multiple graph regularized protein domain ranking.

PubMed

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.

Multiple graph regularized protein domain ranking

PubMed Central

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. PMID:23157331

Ranking of critical species to preserve the functionality of mutualistic networks using the k-core decomposition

PubMed Central

García-Algarra, Javier; Pastor, Juan Manuel; Iriondo, José María

2017-01-01

Background Network analysis has become a relevant approach to analyze cascading species extinctions resulting from perturbations on mutualistic interactions as a result of environmental change. In this context, it is essential to be able to point out key species, whose stability would prevent cascading extinctions, and the consequent loss of ecosystem function. In this study, we aim to explain how the k-core decomposition sheds light on the understanding the robustness of bipartite mutualistic networks. Methods We defined three k-magnitudes based on the k-core decomposition: k-radius, k-degree, and k-risk. The first one, k-radius, quantifies the distance from a node to the innermost shell of the partner guild, while k-degree provides a measure of centrality in the k-shell based decomposition. k-risk is a way to measure the vulnerability of a network to the loss of a particular species. Using these magnitudes we analyzed 89 mutualistic networks involving plant pollinators or seed dispersers. Two static extinction procedures were implemented in which k-degree and k-risk were compared against other commonly used ranking indexes, as for example MusRank, explained in detail in Material and Methods. Results When extinctions take place in both guilds, k-risk is the best ranking index if the goal is to identify the key species to preserve the giant component. When species are removed only in the primary class and cascading extinctions are measured in the secondary class, the most effective ranking index to identify the key species to preserve the giant component is k-degree. However, MusRank index was more effective when the goal is to identify the key species to preserve the greatest species richness in the second class. Discussion The k-core decomposition offers a new topological view of the structure of mutualistic networks. The new k-radius, k-degree and k-risk magnitudes take advantage of its properties and provide new insight into the structure of mutualistic networks. The k-risk and k-degree ranking indexes are especially effective approaches to identify key species to preserve when conservation practitioners focus on the preservation of ecosystem functionality over species richness. PMID:28533969

Ranking of critical species to preserve the functionality of mutualistic networks using the k-core decomposition.

PubMed

García-Algarra, Javier; Pastor, Juan Manuel; Iriondo, José María; Galeano, Javier

2017-01-01

Network analysis has become a relevant approach to analyze cascading species extinctions resulting from perturbations on mutualistic interactions as a result of environmental change. In this context, it is essential to be able to point out key species, whose stability would prevent cascading extinctions, and the consequent loss of ecosystem function. In this study, we aim to explain how the k -core decomposition sheds light on the understanding the robustness of bipartite mutualistic networks. We defined three k -magnitudes based on the k -core decomposition: k -radius, k -degree, and k -risk. The first one, k -radius, quantifies the distance from a node to the innermost shell of the partner guild, while k -degree provides a measure of centrality in the k -shell based decomposition. k -risk is a way to measure the vulnerability of a network to the loss of a particular species. Using these magnitudes we analyzed 89 mutualistic networks involving plant pollinators or seed dispersers. Two static extinction procedures were implemented in which k -degree and k -risk were compared against other commonly used ranking indexes, as for example MusRank, explained in detail in Material and Methods. When extinctions take place in both guilds, k -risk is the best ranking index if the goal is to identify the key species to preserve the giant component. When species are removed only in the primary class and cascading extinctions are measured in the secondary class, the most effective ranking index to identify the key species to preserve the giant component is k -degree. However, MusRank index was more effective when the goal is to identify the key species to preserve the greatest species richness in the second class. The k -core decomposition offers a new topological view of the structure of mutualistic networks. The new k -radius, k -degree and k -risk magnitudes take advantage of its properties and provide new insight into the structure of mutualistic networks. The k -risk and k -degree ranking indexes are especially effective approaches to identify key species to preserve when conservation practitioners focus on the preservation of ecosystem functionality over species richness.

Adsorption isotherms and kinetics of activated carbons produced from coals of different ranks.

PubMed

Purevsuren, B; Lin, Chin-Jung; Davaajav, Y; Ariunaa, A; Batbileg, S; Avid, B; Jargalmaa, S; Huang, Yu; Liou, Sofia Ya-Hsuan

2015-01-01

Activated carbons (ACs) from six coals, ranging from low-rank lignite brown coal to high-rank stone coal, were utilized as adsorbents to remove basic methylene blue (MB) from an aqueous solution. The surface properties of the obtained ACs were characterized via thermal analysis, N2 isothermal sorption, scanning electron microscopy, Fourier transform infrared spectroscopy, X-ray photoelectron spectroscopy and Boehm titration. As coal rank decreased, an increase in the heterogeneity of the pore structures and abundance of oxygen-containing functional groups increased MB coverage on its surface. The equilibrium data fitted well with the Langmuir model, and adsorption capacity of MB ranged from 51.8 to 344.8 mg g⁻¹. Good correlation coefficients were obtained using the intra-particle diffusion model, indicating that the adsorption of MB onto ACs is diffusion controlled. The values of the effective diffusion coefficient ranged from 0.61 × 10⁻¹⁰ to 7.1 × 10⁻¹⁰ m² s⁻¹, indicating that ACs from lower-rank coals have higher effective diffusivities. Among all the ACs obtained from selected coals, the AC from low-rank lignite brown coal was the most effective in removing MB from an aqueous solution.

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS.

PubMed

Yu, Hwanjo; Kim, Taehoon; Oh, Jinoh; Ko, Ilhwan; Kim, Sungchul; Han, Wook-Shin

2010-04-16

Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed. RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed. RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user's feedback and efficiently processes the function to return relevant articles in real time.

Enabling multi-level relevance feedback on PubMed by integrating rank learning into DBMS

PubMed Central

2010-01-01

Background Finding relevant articles from PubMed is challenging because it is hard to express the user's specific intention in the given query interface, and a keyword query typically retrieves a large number of results. Researchers have applied machine learning techniques to find relevant articles by ranking the articles according to the learned relevance function. However, the process of learning and ranking is usually done offline without integrated with the keyword queries, and the users have to provide a large amount of training documents to get a reasonable learning accuracy. This paper proposes a novel multi-level relevance feedback system for PubMed, called RefMed, which supports both ad-hoc keyword queries and a multi-level relevance feedback in real time on PubMed. Results RefMed supports a multi-level relevance feedback by using the RankSVM as the learning method, and thus it achieves higher accuracy with less feedback. RefMed "tightly" integrates the RankSVM into RDBMS to support both keyword queries and the multi-level relevance feedback in real time; the tight coupling of the RankSVM and DBMS substantially improves the processing time. An efficient parameter selection method for the RankSVM is also proposed, which tunes the RankSVM parameter without performing validation. Thereby, RefMed achieves a high learning accuracy in real time without performing a validation process. RefMed is accessible at http://dm.postech.ac.kr/refmed. Conclusions RefMed is the first multi-level relevance feedback system for PubMed, which achieves a high accuracy with less feedback. It effectively learns an accurate relevance function from the user’s feedback and efficiently processes the function to return relevant articles in real time. PMID:20406504

Perceptions About Competing Psychosocial Problems and Treatment Priorities Among Older Adults With Depression

PubMed Central

Proctor, Enola K.; Hasche, Leslie; Morrow-Howell, Nancy; Shumway, Martha; Snell, Grace

2009-01-01

Objective Depression often co-occurs with other conditions that may pose competing demands to depression care, particularly in later life. This study examined older adults’ perceptions of depression among cooccurring social, medical, and functional problems and compared the priority of depression with that of other problems. Methods The study’s purposeful sample comprised 49 adults age 60 or older with a history of depression and in publicly funded community long-term care. Fourpart, mixed-methods interviews sought to capture participants’ perceptions of life problems as well as the priority they placed on depression. Methods included standardized depression screening, semistructured qualitative interviews, listing of problems, and qualitative and quantitative analysis of problem rankings. Results Most participants identified health, functional, and psychosocial problems co-occurring with depressive symptoms. Depression was ranked low among the co-occurring conditions; 6% ranked depression as the most important of their problems, whereas 45% ranked it last. Relative rank scores for problems were remarkably similar, with the notable exception of depression, which was ranked lowest of all problems. Participants did not see depression as a high priority compared with co-occurring problems, particularly psychosocial ones. Conclusions Effective and durable improvements to mental health care must be shaped by an understanding of client perceptions and priorities. Motivational interviewing, health education, and assessment of treatment priorities may be necessary in helping older adults value and accept depression care. Nonspecialty settings of care may effectively link depression treatment to other services, thereby increasing receptivity to mental health services. PMID:18511588

Yager’s ranking method for solving the trapezoidal fuzzy number linear programming

NASA Astrophysics Data System (ADS)

Karyati; Wutsqa, D. U.; Insani, N.

2018-03-01

In the previous research, the authors have studied the fuzzy simplex method for trapezoidal fuzzy number linear programming based on the Maleki’s ranking function. We have found some theories related to the term conditions for the optimum solution of fuzzy simplex method, the fuzzy Big-M method, the fuzzy two-phase method, and the sensitivity analysis. In this research, we study about the fuzzy simplex method based on the other ranking function. It is called Yager's ranking function. In this case, we investigate the optimum term conditions. Based on the result of research, it is found that Yager’s ranking function is not like Maleki’s ranking function. Using the Yager’s function, the simplex method cannot work as well as when using the Maleki’s function. By using the Yager’s function, the value of the subtraction of two equal fuzzy numbers is not equal to zero. This condition makes the optimum table of the fuzzy simplex table is undetected. As a result, the simplified fuzzy simplex table becomes stopped and does not reach the optimum solution.

Multi-dimensional Rankings, Program Termination, and Complexity Bounds of Flowchart Programs

NASA Astrophysics Data System (ADS)

Alias, Christophe; Darte, Alain; Feautrier, Paul; Gonnord, Laure

Proving the termination of a flowchart program can be done by exhibiting a ranking function, i.e., a function from the program states to a well-founded set, which strictly decreases at each program step. A standard method to automatically generate such a function is to compute invariants for each program point and to search for a ranking in a restricted class of functions that can be handled with linear programming techniques. Previous algorithms based on affine rankings either are applicable only to simple loops (i.e., single-node flowcharts) and rely on enumeration, or are not complete in the sense that they are not guaranteed to find a ranking in the class of functions they consider, if one exists. Our first contribution is to propose an efficient algorithm to compute ranking functions: It can handle flowcharts of arbitrary structure, the class of candidate rankings it explores is larger, and our method, although greedy, is provably complete. Our second contribution is to show how to use the ranking functions we generate to get upper bounds for the computational complexity (number of transitions) of the source program. This estimate is a polynomial, which means that we can handle programs with more than linear complexity. We applied the method on a collection of test cases from the literature. We also show the links and differences with previous techniques based on the insertion of counters.

Thalamo-Sensorimotor Functional Connectivity Correlates with World Ranking of Olympic, Elite, and High Performance Athletes.

PubMed

Huang, Zirui; Davis, Henry Hap; Wolff, Annemarie; Northoff, Georg

2017-01-01

Brain plasticity studies have shown functional reorganization in participants with outstanding motor expertise. Little is known about neural plasticity associated with exceptionally long motor training or of its predictive value for motor performance excellence. The present study utilised resting-state functional magnetic resonance imaging (rs-fMRI) in a unique sample of world-class athletes: Olympic, elite, and internationally ranked swimmers ( n = 30). Their world ranking ranged from 1st to 250th: each had prepared for participation in the Olympic Games. Combining rs-fMRI graph-theoretical and seed-based functional connectivity analyses, it was discovered that the thalamus has its strongest connections with the sensorimotor network in elite swimmers with the highest world rankings (career best rank: 1-35). Strikingly, thalamo-sensorimotor functional connections were highly correlated with the swimmers' motor performance excellence, that is, accounting for 41% of the individual variance in best world ranking. Our findings shed light on neural correlates of long-term athletic performance involving thalamo-sensorimotor functional circuits.

Statistical Optimality in Multipartite Ranking and Ordinal Regression.

PubMed

Uematsu, Kazuki; Lee, Yoonkyung

2015-05-01

Statistical optimality in multipartite ranking is investigated as an extension of bipartite ranking. We consider the optimality of ranking algorithms through minimization of the theoretical risk which combines pairwise ranking errors of ordinal categories with differential ranking costs. The extension shows that for a certain class of convex loss functions including exponential loss, the optimal ranking function can be represented as a ratio of weighted conditional probability of upper categories to lower categories, where the weights are given by the misranking costs. This result also bridges traditional ranking methods such as proportional odds model in statistics with various ranking algorithms in machine learning. Further, the analysis of multipartite ranking with different costs provides a new perspective on non-smooth list-wise ranking measures such as the discounted cumulative gain and preference learning. We illustrate our findings with simulation study and real data analysis.

Sex-ratio biasing towards daughters among lower-ranking co-wives in Rwanda.

PubMed

Pollet, Thomas V; Fawcett, Tim W; Buunk, Abraham P; Nettle, Daniel

2009-12-23

There is considerable debate as to whether human females bias the sex ratio of their offspring as a function of their own condition. We apply the Trivers-Willard prediction-that mothers in poor condition will overproduce daughters-to a novel measure of condition, namely wife rank within a polygynous marriage. Using a large-scale sample of over 95 000 Rwandan mothers, we show that lower-ranking polygynous wives do indeed have significantly more daughters than higher-ranking polygynous wives and monogamously married women. This effect remains when controlling for potential confounds such as maternal age. We discuss these results in reference to previous work on sex-ratio adjustment in humans.

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

PubMed

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.

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

PubMed Central

Somasundaram, K.; Alli Rajendran, P.

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. PMID:25945362

SortNet: learning to rank by a neural preference function.

PubMed

Rigutini, Leonardo; Papini, Tiziano; Maggini, Marco; Scarselli, Franco

2011-09-01

Relevance ranking consists in sorting a set of objects with respect to a given criterion. However, in personalized retrieval systems, the relevance criteria may usually vary among different users and may not be predefined. In this case, ranking algorithms that adapt their behavior from users' feedbacks must be devised. Two main approaches are proposed in the literature for learning to rank: the use of a scoring function, learned by examples, that evaluates a feature-based representation of each object yielding an absolute relevance score, a pairwise approach, where a preference function is learned to determine the object that has to be ranked first in a given pair. In this paper, we present a preference learning method for learning to rank. A neural network, the comparative neural network (CmpNN), is trained from examples to approximate the comparison function for a pair of objects. The CmpNN adopts a particular architecture designed to implement the symmetries naturally present in a preference function. The learned preference function can be embedded as the comparator into a classical sorting algorithm to provide a global ranking of a set of objects. To improve the ranking performances, an active-learning procedure is devised, that aims at selecting the most informative patterns in the training set. The proposed algorithm is evaluated on the LETOR dataset showing promising performances in comparison with other state-of-the-art algorithms.

Local Functional Connectivity as a Pre-Surgical Tool for Seizure Focus Identification in Non-Lesion, Focal Epilepsy

PubMed Central

Weaver, K. E.; Chaovalitwongse, W. A.; Novotny, E. J.; Poliakov, A.; Grabowski, T. G.; Ojemann, J. G.

2013-01-01

Successful resection of cortical tissue engendering seizure activity is efficacious for the treatment of refractory, focal epilepsy. The pre-operative localization of the seizure focus is therefore critical to yielding positive, post-operative outcomes. In a small proportion of focal epilepsy patients presenting with normal MRI, identification of the seizure focus is significantly more challenging. We examined the capacity of resting state functional MRI (rsfMRI) to identify the seizure focus in a group of four non-lesion, focal (NLF) epilepsy individuals. We predicted that computing patterns of local functional connectivity in and around the epileptogenic zone combined with a specific reference to the corresponding region within the contralateral hemisphere would reliably predict the location of the seizure focus. We first averaged voxel-wise regional homogeneity (ReHo) across regions of interest (ROIs) from a standardized, probabilistic atlas for each NLF subject as well as 16 age- and gender-matched controls. To examine contralateral effects, we computed a ratio of the mean pair-wise correlations of all voxels within a ROI with the corresponding contralateral region (IntraRegional Connectivity – IRC). For each subject, ROIs were ranked (from lowest to highest) on ReHo, IRC, and the mean of the two values. At the group level, we observed a significant decrease in the rank for ROI harboring the seizure focus for the ReHo rankings as well as for the mean rank. At the individual level, the seizure focus ReHo rank was within bottom 10% lowest ranked ROIs for all four NLF epilepsy patients and three out of the four for the IRC rankings. However, when the two ranks were combined (averaging across ReHo and IRC ranks and scalars), the seizure focus ROI was either the lowest or second lowest ranked ROI for three out of the four epilepsy subjects. This suggests that rsfMRI may serve as an adjunct pre-surgical tool, facilitating the identification of the seizure focus in focal epilepsy. PMID:23641233

A collaborative filtering approach for protein-protein docking scoring functions.

PubMed

Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne

2011-04-22

A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.

A Collaborative Filtering Approach for Protein-Protein Docking Scoring Functions

PubMed Central

Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne

2011-01-01

A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures. PMID:21526112

Rank restriction for the variational calculation of two-electron reduced density matrices of many-electron atoms and molecules

DOE Office of Scientific and Technical Information (OSTI.GOV)

Naftchi-Ardebili, Kasra; Hau, Nathania W.; Mazziotti, David A.

2011-11-15

Variational minimization of the ground-state energy as a function of the two-electron reduced density matrix (2-RDM), constrained by necessary N-representability conditions, provides a polynomial-scaling approach to studying strongly correlated molecules without computing the many-electron wave function. Here we introduce a route to enhancing necessary conditions for N representability through rank restriction of the 2-RDM. Rather than adding computationally more expensive N-representability conditions, we directly enhance the accuracy of two-particle (2-positivity) conditions through rank restriction, which removes degrees of freedom in the 2-RDM that are not sufficiently constrained. We select the rank of the particle-hole 2-RDM by deriving the ranks associatedmore » with model wave functions, including both mean-field and antisymmetrized geminal power (AGP) wave functions. Because the 2-positivity conditions are exact for quantum systems with AGP ground states, the rank of the particle-hole 2-RDM from the AGP ansatz provides a minimum for its value in variational 2-RDM calculations of general quantum systems. To implement the rank-restricted conditions, we extend a first-order algorithm for large-scale semidefinite programming. The rank-restricted conditions significantly improve the accuracy of the energies; for example, the percentages of correlation energies recovered for HF, CO, and N{sub 2} improve from 115.2%, 121.7%, and 121.5% without rank restriction to 97.8%, 101.1%, and 100.0% with rank restriction. Similar results are found at both equilibrium and nonequilibrium geometries. While more accurate, the rank-restricted N-representability conditions are less expensive computationally than the full-rank conditions.« less

A multiplicative process for generating a beta-like survival function with application to the UK 2016 EU referendum results

NASA Astrophysics Data System (ADS)

Fenner, Trevor; Kaufmann, Eric; Levene, Mark; Loizou, George

Human dynamics and sociophysics suggest statistical models that may explain and provide us with better insight into social phenomena. Contextual and selection effects tend to produce extreme values in the tails of rank-ordered distributions of both census data and district-level election outcomes. Models that account for this nonlinearity generally outperform linear models. Fitting nonlinear functions based on rank-ordering census and election data therefore improves the fit of aggregate voting models. This may help improve ecological inference, as well as election forecasting in majoritarian systems. We propose a generative multiplicative decrease model that gives rise to a rank-order distribution and facilitates the analysis of the recent UK EU referendum results. We supply empirical evidence that the beta-like survival function, which can be generated directly from our model, is a close fit to the referendum results, and also may have predictive value when covariate data are available.

Optimization of global model composed of radial basis functions using the term-ranking approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cai, Peng; Tao, Chao, E-mail: taochao@nju.edu.cn; Liu, Xiao-Jun

2014-03-15

A term-ranking method is put forward to optimize the global model composed of radial basis functions to improve the predictability of the model. The effectiveness of the proposed method is examined by numerical simulation and experimental data. Numerical simulations indicate that this method can significantly lengthen the prediction time and decrease the Bayesian information criterion of the model. The application to real voice signal shows that the optimized global model can capture more predictable component in chaos-like voice data and simultaneously reduce the predictable component (periodic pitch) in the residual signal.

Learning Robust and Discriminative Subspace With Low-Rank Constraints.

PubMed

Li, Sheng; Fu, Yun

2016-11-01

In this paper, we aim at learning robust and discriminative subspaces from noisy data. Subspace learning is widely used in extracting discriminative features for classification. However, when data are contaminated with severe noise, the performance of most existing subspace learning methods would be limited. Recent advances in low-rank modeling provide effective solutions for removing noise or outliers contained in sample sets, which motivates us to take advantage of low-rank constraints in order to exploit robust and discriminative subspace for classification. In particular, we present a discriminative subspace learning method called the supervised regularization-based robust subspace (SRRS) approach, by incorporating the low-rank constraint. SRRS seeks low-rank representations from the noisy data, and learns a discriminative subspace from the recovered clean data jointly. A supervised regularization function is designed to make use of the class label information, and therefore to enhance the discriminability of subspace. Our approach is formulated as a constrained rank-minimization problem. We design an inexact augmented Lagrange multiplier optimization algorithm to solve it. Unlike the existing sparse representation and low-rank learning methods, our approach learns a low-dimensional subspace from recovered data, and explicitly incorporates the supervised information. Our approach and some baselines are evaluated on the COIL-100, ALOI, Extended YaleB, FERET, AR, and KinFace databases. The experimental results demonstrate the effectiveness of our approach, especially when the data contain considerable noise or variations.

Latent cardiac dysfunction as assessed by echocardiography in bed-bound patients following cerebrovascular accidents: comparison with nutritional status.

PubMed

Masugata, Hisashi; Senda, Shoichi; Goda, Fuminori; Yoshihara, Yumiko; Yoshikawa, Kay; Fujita, Norihiro; Himoto, Takashi; Okuyama, Hiroyuki; Taoka, Teruhisa; Imai, Masanobu; Kohno, Masakazu

2007-07-01

The aim of this study was to elucidate the cardiac function in bed-bound patients following cerebrovascular accidents. In accord with the criteria for activities of daily living (ADL) of the Japanese Ministry of Health, Labour and Welfare, 51 age-matched poststroke patients without heart disease were classified into 3 groups: rank A (house-bound) (n = 16, age, 85 +/- 6 years), rank B (chair-bound) (n = 16, age, 84 +/- 8 years), and rank C (bed-bound) (n = 19, age, 85 +/- 9 years). Using echocardiography, the left ventricular (LV) diastolic function was assessed by the ratio of early filling (E) and atrial contraction (A) transmitral flow velocities (E/A) of LV inflow. LV systolic function was assessed by LV ejection fraction (LVEF), and the Tei index was also measured to assess both LV systolic and diastolic function. No difference was observed in the E/A and LVEF among the 3 groups. The Tei index was higher in rank C (0.56 +/- 0.17) than in rank A (0.39 +/- 0.06) and rank B (0.48 +/- 0.17), and a statistically significant difference was observed between rank A and rank C (P < 0.05). Serum albumin and blood hemoglobin were significantly lower in rank C (3.1 +/- 0.4 and 10.6 +/- 1.8 g/dL) than in rank A (4.1 +/- 0.3 and 12.4 +/- 1.2 g/dL) (P < 0.001 and P < 0.05, respectively). These results indicate that latent cardiac dysfunction and poor nutritional status may exist in bed-bound patients (rank C) following cerebrovascular accidents. The Tei index may be a useful index of cardiac dysfunction in bed-bound patients because it is independent of the cardiac loading condition.

Jackknife Variance Estimator for Two Sample Linear Rank Statistics

DTIC Science & Technology

1988-11-01

Accesion For - - ,NTIS GPA&I "TIC TAB Unann c, nc .. [d Keywords: strong consistency; linear rank test’ influence function . i , at L By S- )Distribut...reverse if necessary and identify by block number) FIELD IGROUP SUB-GROUP Strong consistency; linear rank test; influence function . 19. ABSTRACT

A special case of reduced rank models for identification and modelling of time varying effects in survival analysis.

PubMed

Perperoglou, Aris

2016-12-10

Flexible survival models are in need when modelling data from long term follow-up studies. In many cases, the assumption of proportionality imposed by a Cox model will not be valid. Instead, a model that can identify time varying effects of fixed covariates can be used. Although there are several approaches that deal with this problem, it is not always straightforward how to choose which covariates should be modelled having time varying effects and which not. At the same time, it is up to the researcher to define appropriate time functions that describe the dynamic pattern of the effects. In this work, we suggest a model that can deal with both fixed and time varying effects and uses simple hypotheses tests to distinguish which covariates do have dynamic effects. The model is an extension of the parsimonious reduced rank model of rank 1. As such, the number of parameters is kept low, and thus, a flexible set of time functions, such as b-splines, can be used. The basic theory is illustrated along with an efficient fitting algorithm. The proposed method is applied to a dataset of breast cancer patients and compared with a multivariate fractional polynomials approach for modelling time-varying effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Compressed Continuous Computation v. 12/20/2016

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gorodetsky, Alex

2017-02-17

A library for performing numerical computation with low-rank functions. The (C3) library enables performing continuous linear and multilinear algebra with multidimensional functions. Common tasks include taking "matrix" decompositions of vector- or matrix-valued functions, approximating multidimensional functions in low-rank format, adding or multiplying functions together, integrating multidimensional functions.

Pulmonary function outcomes for assessing cystic fibrosis care.

PubMed

Wagener, Jeffrey S; Elkin, Eric P; Pasta, David J; Schechter, Michael S; Konstan, Michael W; Morgan, Wayne J

2015-05-01

Assessing cystic fibrosis (CF) patient quality of care requires the choice of an appropriate outcome measure. We looked systematically and in detail at pulmonary function outcomes that potentially reflect clinical practice patterns. Epidemiologic Study of Cystic Fibrosis data were used to evaluate six potential outcome variables (2002 best FVC, FEV(1), and FEF(25-75) and rate of decline for each from 2000 to 2002). We ranked CF care sites by outcome measure and then assessed any association with practice patterns and follow-up pulmonary function. Sites ranked in the top quartile had more frequent monitoring, treatment of exacerbations, and use of chronic therapies and oral corticosteroids. The follow-up rate of pulmonary function decline was not predicted by site ranking. Different pulmonary function outcomes associate slightly differently with practice patterns, although annual FEV(1) is at least as good as any other measure. Current site ranking only moderately predicts future ranking. Copyright © 2014 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Robust Visual Tracking via Online Discriminative and Low-Rank Dictionary Learning.

PubMed

Zhou, Tao; Liu, Fanghui; Bhaskar, Harish; Yang, Jie

2017-09-12

In this paper, we propose a novel and robust tracking framework based on online discriminative and low-rank dictionary learning. The primary aim of this paper is to obtain compact and low-rank dictionaries that can provide good discriminative representations of both target and background. We accomplish this by exploiting the recovery ability of low-rank matrices. That is if we assume that the data from the same class are linearly correlated, then the corresponding basis vectors learned from the training set of each class shall render the dictionary to become approximately low-rank. The proposed dictionary learning technique incorporates a reconstruction error that improves the reliability of classification. Also, a multiconstraint objective function is designed to enable active learning of a discriminative and robust dictionary. Further, an optimal solution is obtained by iteratively computing the dictionary, coefficients, and by simultaneously learning the classifier parameters. Finally, a simple yet effective likelihood function is implemented to estimate the optimal state of the target during tracking. Moreover, to make the dictionary adaptive to the variations of the target and background during tracking, an online update criterion is employed while learning the new dictionary. Experimental results on a publicly available benchmark dataset have demonstrated that the proposed tracking algorithm performs better than other state-of-the-art trackers.

Accuracy of cochlear implant recipients on pitch perception, melody recognition, and speech reception in noise.

PubMed

Gfeller, Kate; Turner, Christopher; Oleson, Jacob; Zhang, Xuyang; Gantz, Bruce; Froman, Rebecca; Olszewski, Carol

2007-06-01

The purposes of this study were to (a) examine the accuracy of cochlear implant recipients who use different types of devices and signal processing strategies on pitch ranking as a function of size of interval and frequency range and (b) to examine the relations between this pitch perception measure and demographic variables, melody recognition, and speech reception in background noise. One hundred fourteen cochlear implant users and 21 normal-hearing adults were tested on a pitch discrimination task (pitch ranking) that required them to determine direction of pitch change as a function of base frequency and interval size. Three groups were tested: (a) long electrode cochlear implant users (N = 101); (b) short electrode users that received acoustic plus electrical stimulation (A+E) (N = 13); and (c) a normal-hearing (NH) comparison group (N = 21). Pitch ranking was tested at standard frequencies of 131 to 1048 Hz, and the size of the pitch-change intervals ranged from 1 to 4 semitones. A generalized linear mixed model (GLMM) was fit to predict pitch ranking and to determine if group differences exist as a function of base frequency and interval size. Overall significance effects were measured with Chi-square tests and individual effects were measured with t-tests. Pitch ranking accuracy was correlated with demographic measures (age at time of testing, length of profound deafness, months of implant use), frequency difference limens, familiar melody recognition, and two measures of speech reception in noise. The long electrode recipients performed significantly poorer on pitch discrimination than the NH and A+E group. The A+E users performed similarly to the NH listeners as a function of interval size in the lower base frequency range, but their pitch discrimination scores deteriorated slightly in the higher frequency range. The long electrode recipients, although less accurate than participants in the NH and A+E groups, tended to perform with greater accuracy within the higher frequency range. There were statistically significant correlations between pitch ranking and familiar melody recognition as well as with pure-tone frequency difference limens at 200 and 400 Hz. Low-frequency acoustic hearing improves pitch discrimination as compared with traditional, electric-only cochlear implants. These findings have implications for musical tasks such as familiar melody recognition.

RANKL/RANK: from bone loss to the prevention of breast cancer.

PubMed

Sigl, Verena; Jones, Laundette P; Penninger, Josef M

2016-11-01

RANK and RANKL, a receptor ligand pair belonging to the tumour necrosis factor family, are the critical regulators of osteoclast development and bone metabolism. Besides their essential function in bone, RANK and RANKL have also been identified as the key factors for the formation of a lactating mammary gland in pregnancy. Mechanistically, RANK and RANKL link the sex hormone progesterone with stem cell expansion and proliferation of mammary epithelial cells. Based on their normal physiology, RANKL/RANK control the onset of hormone-induced breast cancer through the expansion of mammary progenitor cells. Recently, we and others were able to show that RANK and RANKL are also critical regulators of BRCA1-mutation-driven breast cancer. Currently, the preventive strategy for BRCA1-mutation carriers includes preventive mastectomy, associated with wide-ranging risks and psychosocial effects. The search for an alternative non-invasive prevention strategy is therefore of paramount importance. As our work strongly implicates RANK and RANKL as key molecules involved in the initiation of BRCA1-associated breast cancer, we propose that anti-RANKL therapy could be a feasible preventive strategy for women carrying BRCA1 mutations, and by extension to other women with high risk of breast cancer. © 2016 The Authors.

Low-rank structure learning via nonconvex heuristic recovery.

PubMed

Deng, Yue; Dai, Qionghai; Liu, Risheng; Zhang, Zengke; Hu, Sanqing

2013-03-01

In this paper, we propose a nonconvex framework to learn the essential low-rank structure from corrupted data. Different from traditional approaches, which directly utilizes convex norms to measure the sparseness, our method introduces more reasonable nonconvex measurements to enhance the sparsity in both the intrinsic low-rank structure and the sparse corruptions. We will, respectively, introduce how to combine the widely used ℓp norm (0 < p < 1) and log-sum term into the framework of low-rank structure learning. Although the proposed optimization is no longer convex, it still can be effectively solved by a majorization-minimization (MM)-type algorithm, with which the nonconvex objective function is iteratively replaced by its convex surrogate and the nonconvex problem finally falls into the general framework of reweighed approaches. We prove that the MM-type algorithm can converge to a stationary point after successive iterations. The proposed model is applied to solve two typical problems: robust principal component analysis and low-rank representation. Experimental results on low-rank structure learning demonstrate that our nonconvex heuristic methods, especially the log-sum heuristic recovery algorithm, generally perform much better than the convex-norm-based method (0 < p < 1) for both data with higher rank and with denser corruptions.

Consumer preference in ranking walking function utilizing the walking index for spinal cord injury II.

PubMed

Patrick, M; Ditunno, P; Ditunno, J F; Marino, R J; Scivoletto, G; Lam, T; Loffree, J; Tamburella, F; Leiby, B

2011-12-01

Blinded rank ordering. To determine consumer preference in walking function utilizing the walking Index for spinal cord injury II (WISCI II) in individuals with spinal cord injury (SCI)from the Canada, the Italy and the United States of America. In all, 42 consumers with incomplete SCI (25 cervical, 12 thoracic, 5 lumbar) from Canada (12/42), Italy (14/42) and the United States of America (16/42) ranked the 20 levels of the WISCI II scale by their individual preference for walking. Subjects were blinded to the original ranking of the WISCI II scale by clinical scientists. Photographs of each WISCI II level used in a previous pilot study were randomly shuffled and rank ordered. Percentile, conjoint/cluster and graphic analyses were performed. All three analyses illustrated consumer ranking followed a bimodal distribution. Ranking for two levels with physical assistance and two levels with a walker were bimodal with a difference of five to six ranks between consumer subgroups (quartile analysis). The larger cluster (N=20) showed preference for walking with assistance over the smaller cluster (N=12), whose preference was walking without assistance and more devices. In all, 64% (27/42) of consumers ranked WISCI II level with no devices or braces and 1 person assistance higher than multiple levels of the WISCI II requiring no assistance. These results were unexpected, as the hypothesis was that consumers would rank independent walking higher than walking with assistance. Consumer preference for walking function should be considered in addition to objective measures in designing SCI trials that use significant improvement in walking function as an outcome measure.

Maternal effects on offspring stress physiology in wild chimpanzees.

PubMed

Murray, Carson M; Stanton, Margaret A; Wellens, Kaitlin R; Santymire, Rachel M; Heintz, Matthew R; Lonsdorf, Elizabeth V

2018-01-01

Early life experiences are known to influence hypothalamic-pituitary-adrenal (HPA) axis development, which can impact health outcomes through the individual's ability to mount appropriate physiological reactions to stressors. In primates, these early experiences are most often mediated through the mother and can include the physiological environment experienced during gestation. Here, we investigate stress physiology of dependent offspring in wild chimpanzees for the first time and examine whether differences in maternal stress physiology are related to differences in offspring stress physiology. Specifically, we explore the relationship between maternal rank and maternal fecal glucocorticoid metabolite (FGM) concentration during pregnancy and early lactation (first 6 months post-partum) and examine whether differences based on maternal rank are associated with dependent offspring FGM concentrations. We found that low-ranking females exhibited significantly higher FGM concentrations during pregnancy than during the first 6 months of lactation. Furthermore, during pregnancy, low-ranking females experienced significantly higher FGM concentrations than high-ranking females. As for dependent offspring, we found that male offspring of low-ranking mothers experienced stronger decreases in FGM concentrations as they aged compared to males with high-ranking mothers or their dependent female counterparts. Together, these results suggest that maternal rank and FGM concentrations experienced during gestation are related to offspring stress physiology and that this relationship is particularly pronounced in males compared to females. Importantly, this study provides the first evidence for maternal effects on the development of offspring HPA function in wild chimpanzees, which likely relates to subsequent health and fitness outcomes. Am. J. Primatol. 80:e22525, 2018. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Predictive Power Estimation Algorithm (PPEA) - A New Algorithm to Reduce Overfitting for Genomic Biomarker Discovery

PubMed Central

Liu, Jiangang; Jolly, Robert A.; Smith, Aaron T.; Searfoss, George H.; Goldstein, Keith M.; Uversky, Vladimir N.; Dunker, Keith; Li, Shuyu; Thomas, Craig E.; Wei, Tao

2011-01-01

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses. PMID:21935387

Effect of mating activity and dominance rank on male masturbation among free-ranging male rhesus macaques

PubMed Central

Dubuc, Constance; Coyne, Sean P.; Maestripieri, Dario

2013-01-01

The adaptive function of male masturbation is still poorly understood, despite its high prevalence in humans and other animals. In non-human primates, male masturbation is most frequent among anthropoid monkeys and apes living in multimale-multifemale groups with a promiscuous mating system. In these species, male masturbation may be a non-functional by-product of high sexual arousal or be adaptive by providing advantages in terms of sperm competition or by decreasing the risk of sexually transmitted infections. We investigated the possible functional significance of male masturbation using behavioral data collected on 21 free-ranging male rhesus macaques (Macaca mulatta) at the peak of the mating season. We found some evidence that masturbation is linked to low mating opportunities: regardless of rank, males were most likely to be observed masturbating on days in which they were not observed mating, and lower-ranking males mated less and tended to masturbate more frequently than higher-ranking males. These results echo the findings obtained for two other species of macaques, but contrast those obtained in red colobus monkeys (Procolobus badius) and Cape ground squirrels (Xerus inauris). Interestingly, however, male masturbation events ended with ejaculation in only 15% of the observed masturbation time, suggesting that new hypotheses are needed to explain masturbation in this species. More studies are needed to establish whether male masturbation is adaptive and whether it serves similar or different functions in different sexually promiscuous species. PMID:24187414

Effect of mating activity and dominance rank on male masturbation among free-ranging male rhesus macaques.

PubMed

Dubuc, Constance; Coyne, Sean P; Maestripieri, Dario

2013-11-01

The adaptive function of male masturbation is still poorly understood, despite its high prevalence in humans and other animals. In non-human primates, male masturbation is most frequent among anthropoid monkeys and apes living in multimale-multifemale groups with a promiscuous mating system. In these species, male masturbation may be a non-functional by-product of high sexual arousal or be adaptive by providing advantages in terms of sperm competition or by decreasing the risk of sexually transmitted infections. We investigated the possible functional significance of male masturbation using behavioral data collected on 21 free-ranging male rhesus macaques ( Macaca mulatta ) at the peak of the mating season. We found some evidence that masturbation is linked to low mating opportunities: regardless of rank, males were most likely to be observed masturbating on days in which they were not observed mating, and lower-ranking males mated less and tended to masturbate more frequently than higher-ranking males. These results echo the findings obtained for two other species of macaques, but contrast those obtained in red colobus monkeys ( Procolobus badius ) and Cape ground squirrels ( Xerus inauris ). Interestingly, however, male masturbation events ended with ejaculation in only 15% of the observed masturbation time, suggesting that new hypotheses are needed to explain masturbation in this species. More studies are needed to establish whether male masturbation is adaptive and whether it serves similar or different functions in different sexually promiscuous species.

Systematic Differences in Signal Emitting and Receiving Revealed by PageRank Analysis of a Human Protein Interactome

PubMed Central

Li, Xiu-Qing

2012-01-01

Most protein PageRank studies do not use signal flow direction information in protein interactions because this information was not readily available in large protein databases until recently. Therefore, four questions have yet to be answered: A) What is the general difference between signal emitting and receiving in a protein interactome? B) Which proteins are among the top ranked in directional ranking? C) Are high ranked proteins more evolutionarily conserved than low ranked ones? D) Do proteins with similar ranking tend to have similar subcellular locations? In this study, we address these questions using the forward, reverse, and non-directional PageRank approaches to rank an information-directional network of human proteins and study their evolutionary conservation. The forward ranking gives credit to information receivers, reverse ranking to information emitters, and non-directional ranking mainly to the number of interactions. The protein lists generated by the forward and non-directional rankings are highly correlated, but those by the reverse and non-directional rankings are not. The results suggest that the signal emitting/receiving system is characterized by key-emittings and relatively even receivings in the human protein interactome. Signaling pathway proteins are frequent in top ranked ones. Eight proteins are both informational top emitters and top receivers. Top ranked proteins, except a few species-related novel-function ones, are evolutionarily well conserved. Protein-subunit ranking position reflects subunit function. These results demonstrate the usefulness of different PageRank approaches in characterizing protein networks and provide insights to protein interaction in the cell. PMID:23028653

Vps35 loss promotes hyperresorptive osteoclastogenesis and osteoporosis via sustained RANKL signaling

PubMed Central

Xia, Wen-Fang; Tang, Fu-Lei; Xiong, Lei; Xiong, Shan; Jung, Ji-Ung; Lee, Dae-Hoon; Li, Xing-Sheng; Feng, Xu; Mei, Lin

2013-01-01

Receptor activator of NF-κB (RANK) plays a critical role in osteoclastogenesis, an essential process for the initiation of bone remodeling to maintain healthy bone mass and structure. Although the signaling and function of RANK have been investigated extensively, much less is known about the negative regulatory mechanisms of its signaling. We demonstrate in this paper that RANK trafficking, signaling, and function are regulated by VPS35, a major component of the retromer essential for selective endosome to Golgi retrieval of membrane proteins. VPS35 loss of function altered RANK ligand (RANKL)–induced RANK distribution, enhanced RANKL sensitivity, sustained RANKL signaling, and increased hyperresorptive osteoclast (OC) formation. Hemizygous deletion of the Vps35 gene in mice promoted hyperresorptive osteoclastogenesis, decreased bone formation, and caused a subsequent osteoporotic deficit, including decreased trabecular bone volumes and reduced trabecular thickness and density in long bones. These results indicate that VPS35 critically deregulates RANK signaling, thus restraining increased formation of hyperresorptive OCs and preventing osteoporotic deficits. PMID:23509071

The structure of first-ranked cluster galaxies and the radius-magnitude relation

NASA Astrophysics Data System (ADS)

Lugger, P. M.

1984-11-01

To investigate theoretical predictions for the dynamical evolution of first-ranked galaxies, a quantitative study of their properties, as a function of cluster morphology, has been carried out using photographic plates obtained with the Palomar 48 inch (1.2 m) Schmidt telescope. Surface brightness profiles to radii of several hundred kpc for 35 first-ranked cluster galaxies have been analyzed. The dispersion in the metric magnitudes of first-ranked galaxies is quite small (about 0.4 mag), which is consistent with the results of Kristian, Sandage, and Westphal (1978) as well as those of Hoessel, Gunn, and Thuan (1980) and the recent work of Schneider, Gunn, and Hoessel (1983). For the cD (supergiant elliptical) galaxy sample, the mean metric magnitude is about 0.5 mag brighter than for the non-cD galaxies. The mean de Vaucouleurs effective radius for the cD galaxy sample is 80 percent larger than that of the non-cD sample. The relation between de Vaucouleurs effective radius and magnitude determined in the present study for first-ranked galaxies, log r(e) equal to about -0.26 M + constant is consistent with the relations found for fainter galaxies by Strom and Strom (1978) as well as Wirth (1982). The residuals in radius from the mean radius-magnitude relation for first-ranked galaxies do not correlate with the Bautz-Morgan (1970) type of the cluster.

Nonconvex Nonsmooth Low Rank Minimization via Iteratively Reweighted Nuclear Norm.

PubMed

Lu, Canyi; Tang, Jinhui; Yan, Shuicheng; Lin, Zhouchen

2016-02-01

The nuclear norm is widely used as a convex surrogate of the rank function in compressive sensing for low rank matrix recovery with its applications in image recovery and signal processing. However, solving the nuclear norm-based relaxed convex problem usually leads to a suboptimal solution of the original rank minimization problem. In this paper, we propose to use a family of nonconvex surrogates of L0-norm on the singular values of a matrix to approximate the rank function. This leads to a nonconvex nonsmooth minimization problem. Then, we propose to solve the problem by an iteratively re-weighted nuclear norm (IRNN) algorithm. IRNN iteratively solves a weighted singular value thresholding problem, which has a closed form solution due to the special properties of the nonconvex surrogate functions. We also extend IRNN to solve the nonconvex problem with two or more blocks of variables. In theory, we prove that the IRNN decreases the objective function value monotonically, and any limit point is a stationary point. Extensive experiments on both synthesized data and real images demonstrate that IRNN enhances the low rank matrix recovery compared with the state-of-the-art convex algorithms.

An Optimization-Based Method for Feature Ranking in Nonlinear Regression Problems.

PubMed

Bravi, Luca; Piccialli, Veronica; Sciandrone, Marco

2017-04-01

In this paper, we consider the feature ranking problem, where, given a set of training instances, the task is to associate a score with the features in order to assess their relevance. Feature ranking is a very important tool for decision support systems, and may be used as an auxiliary step of feature selection to reduce the high dimensionality of real-world data. We focus on regression problems by assuming that the process underlying the generated data can be approximated by a continuous function (for instance, a feedforward neural network). We formally state the notion of relevance of a feature by introducing a minimum zero-norm inversion problem of a neural network, which is a nonsmooth, constrained optimization problem. We employ a concave approximation of the zero-norm function, and we define a smooth, global optimization problem to be solved in order to assess the relevance of the features. We present the new feature ranking method based on the solution of instances of the global optimization problem depending on the available training data. Computational experiments on both artificial and real data sets are performed, and point out that the proposed feature ranking method is a valid alternative to existing methods in terms of effectiveness. The obtained results also show that the method is costly in terms of CPU time, and this may be a limitation in the solution of large-dimensional problems.

Learning to rank using user clicks and visual features for image retrieval.

PubMed

Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

2015-04-01

The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms.

Mining dynamic noteworthy functions in software execution sequences.

PubMed

Zhang, Bing; Huang, Guoyan; Wang, Yuqian; He, Haitao; Ren, Jiadong

2017-01-01

As the quality of crucial entities can directly affect that of software, their identification and protection become an important premise for effective software development, management, maintenance and testing, which thus contribute to improving the software quality and its attack-defending ability. Most analysis and evaluation on important entities like codes-based static structure analysis are on the destruction of the actual software running. In this paper, from the perspective of software execution process, we proposed an approach to mine dynamic noteworthy functions (DNFM)in software execution sequences. First, according to software decompiling and tracking stack changes, the execution traces composed of a series of function addresses were acquired. Then these traces were modeled as execution sequences and then simplified so as to get simplified sequences (SFS), followed by the extraction of patterns through pattern extraction (PE) algorithm from SFS. After that, evaluating indicators inner-importance and inter-importance were designed to measure the noteworthiness of functions in DNFM algorithm. Finally, these functions were sorted by their noteworthiness. Comparison and contrast were conducted on the experiment results from two traditional complex network-based node mining methods, namely PageRank and DegreeRank. The results show that the DNFM method can mine noteworthy functions in software effectively and precisely.

Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals

DOE PAGES

Rai, Prashant; Sargsyan, Khachik; Najm, Habib N.

2018-03-20

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. Here, the method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret the high dimensional integrand as a tensor in a suitable tensor product space and determine its entries by a compressed sensing based algorithm using only a few function evaluations. Secondly, we implement a rank reduction strategy to compress this tensor in a suitable low-rank tensor format using standard tensor compression tools. This allows representing a high dimensional integrand function asmore » a small sum of products of low dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate this low-rank representation, thus alleviating the curse of dimensionality. Finally, numerical tests on synthetic functions, as well as on energy correction integrals for water and formaldehyde molecules demonstrate the efficiency of this method using very few function evaluations as compared to other integration strategies.« less

Compressed sparse tensor based quadrature for vibrational quantum mechanics integrals

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rai, Prashant; Sargsyan, Khachik; Najm, Habib N.

A new method for fast evaluation of high dimensional integrals arising in quantum mechanics is proposed. Here, the method is based on sparse approximation of a high dimensional function followed by a low-rank compression. In the first step, we interpret the high dimensional integrand as a tensor in a suitable tensor product space and determine its entries by a compressed sensing based algorithm using only a few function evaluations. Secondly, we implement a rank reduction strategy to compress this tensor in a suitable low-rank tensor format using standard tensor compression tools. This allows representing a high dimensional integrand function asmore » a small sum of products of low dimensional functions. Finally, a low dimensional Gauss–Hermite quadrature rule is used to integrate this low-rank representation, thus alleviating the curse of dimensionality. Finally, numerical tests on synthetic functions, as well as on energy correction integrals for water and formaldehyde molecules demonstrate the efficiency of this method using very few function evaluations as compared to other integration strategies.« less

Communication during sex among female bonobos: effects of dominance, solicitation and audience

PubMed Central

Clay, Zanna; Zuberbühler, Klaus

2012-01-01

Bonobo females frequently form close bonds, which give them social power over other group members. One potential mechanism to facilitate female bonding is the performance of sexual interactions. Using naturalistic observations and experiments, we found various patterns that determined female-female sexual interactions. First, while low-ranked females interacted with all females, sexual interactions between high-ranked females were rare. Second, during genital contacts, females sometimes produced ‘copulation calls’, which were significantly affected by the rank of the caller and partner, as well as the solicitation direction. Third, there was a significant effect of the alpha female as a bystander, while variables relating to physical experience had no effects. Overall, results highlight the importance of sexual interactions for bonobo female social relations. Copulation calls are an important tool during this process, suggesting that they have become ritualised, beyond their reproductive function, to serve as broader social signals in flexible and potentially strategic ways. PMID:22389761

Methods for evaluating and ranking transportation energy conservation programs

NASA Astrophysics Data System (ADS)

Santone, L. C.

1981-04-01

The energy conservation programs are assessed in terms of petroleum savings, incremental costs to consumers probability of technical and market success, and external impacts due to environmental, economic, and social factors. Three ranking functions and a policy matrix are used to evaluate the programs. The net present value measure which computes the present worth of petroleum savings less the present worth of costs is modified by dividing by the present value of DOE funding to obtain a net present value per program dollar. The comprehensive ranking function takes external impacts into account. Procedures are described for making computations of the ranking functions and the attributes that require computation. Computations are made for the electric vehicle, Stirling engine, gas turbine, and MPG mileage guide program.

Efficiently Selecting the Best Web Services

NASA Astrophysics Data System (ADS)

Goncalves, Marlene; Vidal, Maria-Esther; Regalado, Alfredo; Yacoubi Ayadi, Nadia

Emerging technologies and linking data initiatives have motivated the publication of a large number of datasets, and provide the basis for publishing Web services and tools to manage the available data. This wealth of resources opens a world of possibilities to satisfy user requests. However, Web services may have similar functionality and assess different performance; therefore, it is required to identify among the Web services that satisfy a user request, the ones with the best quality. In this paper we propose a hybrid approach that combines reasoning tasks with ranking techniques to aim at the selection of the Web services that best implement a user request. Web service functionalities are described in terms of input and output attributes annotated with existing ontologies, non-functionality is represented as Quality of Services (QoS) parameters, and user requests correspond to conjunctive queries whose sub-goals impose restrictions on the functionality and quality of the services to be selected. The ontology annotations are used in different reasoning tasks to infer service implicit properties and to augment the size of the service search space. Furthermore, QoS parameters are considered by a ranking metric to classify the services according to how well they meet a user non-functional condition. We assume that all the QoS parameters of the non-functional condition are equally important, and apply the Top-k Skyline approach to select the k services that best meet this condition. Our proposal relies on a two-fold solution which fires a deductive-based engine that performs different reasoning tasks to discover the services that satisfy the requested functionality, and an efficient implementation of the Top-k Skyline approach to compute the top-k services that meet the majority of the QoS constraints. Our Top-k Skyline solution exploits the properties of the Skyline Frequency metric and identifies the top-k services by just analyzing a subset of the services that meet the non-functional condition. We report on the effects of the proposed reasoning tasks, the quality of the top-k services selected by the ranking metric, and the performance of the proposed ranking techniques. Our results suggest that the number of services can be augmented by up two orders of magnitude. In addition, our ranking techniques are able to identify services that have the best values in at least half of the QoS parameters, while the performance is improved.

Benchmarking Outpatient Rehabilitation Clinics Using Functional Status Outcomes.

PubMed

Gozalo, Pedro L; Resnik, Linda J; Silver, Benjamin

2016-04-01

To utilize functional status (FS) outcomes to benchmark outpatient therapy clinics. Outpatient therapy data from clinics using Focus on Therapeutic Outcomes (FOTO) assessments. Retrospective analysis of 538 clinics, involving 2,040 therapists and 90,392 patients admitted July 2006-June 2008. FS at discharge was modeled using hierarchical regression methods with patients nested within therapists within clinics. Separate models were estimated for all patients, for those with lumbar, and for those with shoulder impairments. All models risk-adjusted for intake FS, age, gender, onset, surgery count, functional comorbidity index, fear-avoidance level, and payer type. Inverse probability weighting adjusted for censoring. Functional status was captured using computer adaptive testing at intake and at discharge. Clinic and therapist effects explained 11.6 percent of variation in FS. Clinics ranked in the lowest quartile had significantly different outcomes than those in the highest quartile (p < .01). Clinics ranked similarly in lumbar and shoulder impairments (correlation = 0.54), but some clinics ranked in the highest quintile for one condition and in the lowest for the other. Benchmarking models based on validated FS measures clearly separated high-quality from low-quality clinics, and they could be used to inform value-based-payment policies. © Health Research and Educational Trust.

Cross-modal learning to rank via latent joint representation.

PubMed

Wu, Fei; Jiang, Xinyang; Li, Xi; Tang, Siliang; Lu, Weiming; Zhang, Zhongfei; Zhuang, Yueting

2015-05-01

Cross-modal ranking is a research topic that is imperative to many applications involving multimodal data. Discovering a joint representation for multimodal data and learning a ranking function are essential in order to boost the cross-media retrieval (i.e., image-query-text or text-query-image). In this paper, we propose an approach to discover the latent joint representation of pairs of multimodal data (e.g., pairs of an image query and a text document) via a conditional random field and structural learning in a listwise ranking manner. We call this approach cross-modal learning to rank via latent joint representation (CML²R). In CML²R, the correlations between multimodal data are captured in terms of their sharing hidden variables (e.g., topics), and a hidden-topic-driven discriminative ranking function is learned in a listwise ranking manner. The experiments show that the proposed approach achieves a good performance in cross-media retrieval and meanwhile has the capability to learn the discriminative representation of multimodal data.

Comparison of the efficacy and safety of thrombectomy devices in acute stroke : a network meta-analysis of randomized trials.

PubMed

Saber, Hamidreza; Rajah, Gary B; Kherallah, Riyad Y; Jadhav, Ashutosh P; Narayanan, Sandra

2017-12-15

Mechanical thrombectomy (MT) is increasingly used for large-vessel occlusions (LVO), but randomized clinical trial (RCT) level data with regard to differences in clinical outcomes of MT devices are limited. We conducted a network meta-analysis (NMA) that enables comparison of modern MT devices (Trevo, Solitaire, Aspiration) and strategies (stent retriever vs aspiration) across trials. Relevant RCTs were identified by a systematic review. The efficacy outcome was 90-day functional independence (modified Rankin Scale (mRS) score 0-2). Safety outcomes were 90-day catastrophic outcome (mRS 5-6) and symptomatic intracranial hemorrhage (sICH). Fixed-effect Bayesian NMA was performed to calculate risk estimates and the rank probabilities. In a NMA of six relevant RCTs (SWIFT, TREVO2, EXTEND-IA, SWIFT-PRIME, REVASCAT, THERAPY; total of 871 patients, 472 Solitaire vs medical-only, 108 Aspiration vs medical-only, 178 Trevo vs Merci, and 113 Solitaire vs Merci) with medical-only arm as the reference, Trevo had the greatest functional independence (OR 4.14, 95% credible interval (CrI) 1.41-11.80; top rank probability 92%) followed by Solitaire (OR 2.55, 95% CrI 1.75-3.74; top rank probability 72%). Solitaire and Aspiration devices had the greatest top rank probability with respect to low sICH and catastrophic outcomes (76% and 91%, respectively), but without significant differences between each other. In a separate network of seven RCTs (MR-CLEAN, ESCAPE, EXTEND-IA, SWIFT-PRIME, REVASCAT, THERAPY, ASTER; 1737 patients), first-line stent retriever was associated with a higher top rank probability of functional independence than aspiration (95% vs 54%), with comparable safety outcomes. These findings suggest that Trevo and Solitaire devices are associated with a greater likelihood of functional independence whereas Solitaire and Aspiration devices appear to be safer. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Trace Norm Regularized CANDECOMP/PARAFAC Decomposition With Missing Data.

PubMed

Liu, Yuanyuan; Shang, Fanhua; Jiao, Licheng; Cheng, James; Cheng, Hong

2015-11-01

In recent years, low-rank tensor completion (LRTC) problems have received a significant amount of attention in computer vision, data mining, and signal processing. The existing trace norm minimization algorithms for iteratively solving LRTC problems involve multiple singular value decompositions of very large matrices at each iteration. Therefore, they suffer from high computational cost. In this paper, we propose a novel trace norm regularized CANDECOMP/PARAFAC decomposition (TNCP) method for simultaneous tensor decomposition and completion. We first formulate a factor matrix rank minimization model by deducing the relation between the rank of each factor matrix and the mode- n rank of a tensor. Then, we introduce a tractable relaxation of our rank function, and then achieve a convex combination problem of much smaller-scale matrix trace norm minimization. Finally, we develop an efficient algorithm based on alternating direction method of multipliers to solve our problem. The promising experimental results on synthetic and real-world data validate the effectiveness of our TNCP method. Moreover, TNCP is significantly faster than the state-of-the-art methods and scales to larger problems.

The impact of winning and losing on family interactions: a biological approach to family therapy.

PubMed

Sloman, Leon; Sturman, Edward D

2012-10-01

To examine the connection between winning and losing and family functioning. We do this by hypothesizing a link between successful outcomes in individual competition and in functional family interaction. This enables us to show how therapeutic interventions can be directed toward the attachment system, by lowering anxiety and fostering mutual trust, and toward the social rank system, by promoting success and feelings of empowerment. A search of online databases was conducted with key search terms related to winning and losing, and their effects on attachment patterns and family interactions. Winning in agonistic encounters has been associated with lowered dysphoria, anxiety, and hostility. These affective states trigger positive patterns of family interaction through their effect on the social rank and attachment systems. Continued success promotes adaptive cycles of interaction, whereas inability to accept loss has the reverse effect. Early humans, who were more successful in competition, were better able to promote the survival and well-being of other family members, which would have accelerated our phylogenetic adaptation.

Evaluating Sermons: The Function of Grades in Teaching Preaching

ERIC Educational Resources Information Center

Helsel, Carolyn Browning

2017-01-01

What are grades doing in a homiletics classroom? This article traces the function of grades through the broader history of the educational system in the United States and then makes suggestions for how grades can be used more effectively in teaching preaching. Beginning in the nineteenth century, teachers used grades to rank and motivate students,…

Melodic interval perception by normal-hearing listeners and cochlear implant users

PubMed Central

Luo, Xin; Masterson, Megan E.; Wu, Ching-Chih

2014-01-01

The perception of melodic intervals (sequential pitch differences) is essential to music perception. This study tested melodic interval perception in normal-hearing (NH) listeners and cochlear implant (CI) users. Melodic interval ranking was tested using an adaptive procedure. CI users had slightly higher interval ranking thresholds than NH listeners. Both groups' interval ranking thresholds, although not affected by root note, significantly increased with standard interval size and were higher for descending intervals than for ascending intervals. The pitch direction effect may be due to a procedural artifact or a difference in central processing. In another test, familiar melodies were played with all the intervals scaled by a single factor. Subjects rated how in tune the melodies were and adjusted the scaling factor until the melodies sounded the most in tune. CI users had lower final interval ratings and less change in interval rating as a function of scaling factor than NH listeners. For CI users, the root-mean-square error of the final scaling factors and the width of the interval rating function were significantly correlated with the average ranking threshold for ascending rather than descending intervals, suggesting that CI users may have focused on ascending intervals when rating and adjusting the melodies. PMID:25324084

Establishment of a 12-gene expression signature to predict colon cancer prognosis

PubMed Central

Zhao, Guangxi; Dong, Pingping; Wu, Bingrui

2018-01-01

A robust and accurate gene expression signature is essential to assist oncologists to determine which subset of patients at similar Tumor-Lymph Node-Metastasis (TNM) stage has high recurrence risk and could benefit from adjuvant therapies. Here we applied a two-step supervised machine-learning method and established a 12-gene expression signature to precisely predict colon adenocarcinoma (COAD) prognosis by using COAD RNA-seq transcriptome data from The Cancer Genome Atlas (TCGA). The predictive performance of the 12-gene signature was validated with two independent gene expression microarray datasets: GSE39582 includes 566 COAD cases for the development of six molecular subtypes with distinct clinical, molecular and survival characteristics; GSE17538 is a dataset containing 232 colon cancer patients for the generation of a metastasis gene expression profile to predict recurrence and death in COAD patients. The signature could effectively separate the poor prognosis patients from good prognosis group (disease specific survival (DSS): Kaplan Meier (KM) Log Rank p = 0.0034; overall survival (OS): KM Log Rank p = 0.0336) in GSE17538. For patients with proficient mismatch repair system (pMMR) in GSE39582, the signature could also effectively distinguish high risk group from low risk group (OS: KM Log Rank p = 0.005; Relapse free survival (RFS): KM Log Rank p = 0.022). Interestingly, advanced stage patients were significantly enriched in high 12-gene score group (Fisher’s exact test p = 0.0003). After stage stratification, the signature could still distinguish poor prognosis patients in GSE17538 from good prognosis within stage II (Log Rank p = 0.01) and stage II & III (Log Rank p = 0.017) in the outcome of DFS. Within stage III or II/III pMMR patients treated with Adjuvant Chemotherapies (ACT) and patients with higher 12-gene score showed poorer prognosis (III, OS: KM Log Rank p = 0.046; III & II, OS: KM Log Rank p = 0.041). Among stage II/III pMMR patients with lower 12-gene scores in GSE39582, the subgroup receiving ACT showed significantly longer OS time compared with those who received no ACT (Log Rank p = 0.021), while there is no obvious difference between counterparts among patients with higher 12-gene scores (Log Rank p = 0.12). Besides COAD, our 12-gene signature is multifunctional in several other cancer types including kidney cancer, lung cancer, uveal and skin melanoma, brain cancer, and pancreatic cancer. Functional classification showed that seven of the twelve genes are involved in immune system function and regulation, so our 12-gene signature could potentially be used to guide decisions about adjuvant therapy for patients with stage II/III and pMMR COAD.

Expression profile of osteoprotegerin, RANK and RANKL genes in the femoral head of patients with avascular necrosis.

PubMed

Samara, Stavroula; Dailiana, Zoe; Chassanidis, Christos; Koromila, Theodora; Papatheodorou, Loukia; Malizos, Konstantinos N; Kollia, Panagoula

2014-02-01

Femoral head avascular necrosis (AVN) is a recalcitrant disease of the hip that leads to joint destruction. Osteoprotegerin (OPG), Receptor Activator of Nuclear Factor kappa-B (RANK) and RANK ligand (RANKL) regulate the balance between osteoclasts-osteoblasts. The expression of these genes affects the maturation and function of osteoblasts-osteoclasts and bone remodeling. In this study, we investigated the molecular pathways leading to AVN by studying the expression profile of OPG, RANK and RANKL genes. Quantitative Real Time-PCR was performed for evaluation of OPG, RANK and RANKL expression. Analysis was based on parallel evaluation of mRNA and protein levels in normal/necrotic sites of 42 osteonecrotic femoral heads (FHs). OPG and RANKL protein levels were estimated by western blotting. The OPG mRNA levels were higher (insignificantly) in the necrotic than the normal site (p > 0.05). Although the expression of RANK and RANKL was significantly lower than OPG in both sites, RANK and RANKL mRNA levels were higher in the necrotic part than the normal (p < 0.05). Protein levels of OPG and RANKL showed no remarkable divergence. Our results indicate that differential expression mechanisms for OPG, RANK and RANKL that could play an important role in the progress of bone remodeling in the necrotic area, disturbing bone homeostasis. This finding may have an effect on the resulting bone destruction and the subsequent collapse of the hip joint. Copyright © 2013. Published by Elsevier Inc.

A study on OPG/RANK/RANKL axis in osteoporotic bile duct-ligated rats and the involvement of nitrergic and opioidergic systems.

PubMed

Doustimotlagh, Amir Hossein; Dehpour, Ahmad Reza; Etemad-Moghadam, Shahroo; Alaeddini, Mojgan; Ostadhadi, Sattar; Golestani, Abolfazl

2018-06-01

Chronic liver disease (CLD) affects millions of people and its impact on bone loss has become a subject of interest. Nitric oxide and endogenous opioids are suggested to increase during cholestasis/cirrhosis and may impact bone resorption by different mechanisms. The receptor activator of nuclear factor-κB (RANK)/RANK-ligand (RANKL)/osteoprotegerin (OPG) signaling pathway regulates bone resorption, but its role in metabolic bone disease subsequent to CLD is unknown. We aimed to investigate the involvement of nitrergic and opioidergic systems in bone loss relative to the RANK/RANKL/OPG pathway, in bile duct-ligated (BDL) rats. Eighty BDL/sham-operated (SO) rats received injections of 3 mg/kg/day Nω-Nitro-L-arginine methyl ester ± naltrexone (10 mg/kg/day) or saline for 28 days. Plasma bone turnover markers, OPG, RANK, and RANKL along with mRNA expression levels of the latter three were assessed. Plasma bone turnover markers and OPG level increased, but RANKL decreased in the BDL group compared with their SO controls (both: P ≤ 0.05). Administration of naltrexone reduced bone turnover markers and OPG level while increased RANKL content in comparison to BDL rats ( P ≤ 0.05). As compared to untreated BDL rats, nitric oxide inhibition showed no effect on bone turnover marker i.e. OPG, RANK, and RANKL levels. BDL significantly increased RANK mRNA, but had no significant effect on RANKL and OPG mRNA expression. The lack of association between plasma levels and quantitative gene expression of RANKL and OPG suggests an indirect function of these markers in BDL rats. Considering that opioid receptor blockage by naltrexone in BDL animals caused a significant decrease in OPG and an increase in RANKL plasma contents, it could be postulated that the opioidergic system may have a regulatory effect on these bone markers.

Scoring ligand similarity in structure-based virtual screening.

PubMed

Zavodszky, Maria I; Rohatgi, Anjali; Van Voorst, Jeffrey R; Yan, Honggao; Kuhn, Leslie A

2009-01-01

Scoring to identify high-affinity compounds remains a challenge in virtual screening. On one hand, protein-ligand scoring focuses on weighting favorable and unfavorable interactions between the two molecules. Ligand-based scoring, on the other hand, focuses on how well the shape and chemistry of each ligand candidate overlay on a three-dimensional reference ligand. Our hypothesis is that a hybrid approach, using ligand-based scoring to rank dockings selected by protein-ligand scoring, can ensure that high-ranking molecules mimic the shape and chemistry of a known ligand while also complementing the binding site. Results from applying this approach to screen nearly 70 000 National Cancer Institute (NCI) compounds for thrombin inhibitors tend to support the hypothesis. EON ligand-based ranking of docked molecules yielded the majority (4/5) of newly discovered, low to mid-micromolar inhibitors from a panel of 27 assayed compounds, whereas ranking docked compounds by protein-ligand scoring alone resulted in one new inhibitor. Since the results depend on the choice of scoring function, an analysis of properties was performed on the top-scoring docked compounds according to five different protein-ligand scoring functions, plus EON scoring using three different reference compounds. The results indicate that the choice of scoring function, even among scoring functions measuring the same types of interactions, can have an unexpectedly large effect on which compounds are chosen from screening. Furthermore, there was almost no overlap between the top-scoring compounds from protein-ligand versus ligand-based scoring, indicating the two approaches provide complementary information. Matchprint analysis, a new addition to the SLIDE (Screening Ligands by Induced-fit Docking, Efficiently) screening toolset, facilitated comparison of docked molecules' interactions with those of known inhibitors. The majority of interactions conserved among top-scoring compounds for a given scoring function, and from the different scoring functions, proved to be conserved interactions in known inhibitors. This was particularly true in the S1 pocket, which was occupied by all the docked compounds. (c) 2009 John Wiley & Sons, Ltd.

Mining dynamic noteworthy functions in software execution sequences

PubMed Central

Huang, Guoyan; Wang, Yuqian; He, Haitao; Ren, Jiadong

2017-01-01

As the quality of crucial entities can directly affect that of software, their identification and protection become an important premise for effective software development, management, maintenance and testing, which thus contribute to improving the software quality and its attack-defending ability. Most analysis and evaluation on important entities like codes-based static structure analysis are on the destruction of the actual software running. In this paper, from the perspective of software execution process, we proposed an approach to mine dynamic noteworthy functions (DNFM)in software execution sequences. First, according to software decompiling and tracking stack changes, the execution traces composed of a series of function addresses were acquired. Then these traces were modeled as execution sequences and then simplified so as to get simplified sequences (SFS), followed by the extraction of patterns through pattern extraction (PE) algorithm from SFS. After that, evaluating indicators inner-importance and inter-importance were designed to measure the noteworthiness of functions in DNFM algorithm. Finally, these functions were sorted by their noteworthiness. Comparison and contrast were conducted on the experiment results from two traditional complex network-based node mining methods, namely PageRank and DegreeRank. The results show that the DNFM method can mine noteworthy functions in software effectively and precisely. PMID:28278276

Network-based ranking methods for prediction of novel disease associated microRNAs.

PubMed

Le, Duc-Hau

2015-10-01

Many studies have shown roles of microRNAs on human disease and a number of computational methods have been proposed to predict such associations by ranking candidate microRNAs according to their relevance to a disease. Among them, machine learning-based methods usually have a limitation in specifying non-disease microRNAs as negative training samples. Meanwhile, network-based methods are becoming dominant since they well exploit a "disease module" principle in microRNA functional similarity networks. Of which, random walk with restart (RWR) algorithm-based method is currently state-of-the-art. The use of this algorithm was inspired from its success in predicting disease gene because the "disease module" principle also exists in protein interaction networks. Besides, many algorithms designed for webpage ranking have been successfully applied in ranking disease candidate genes because web networks share topological properties with protein interaction networks. However, these algorithms have not yet been utilized for disease microRNA prediction. We constructed microRNA functional similarity networks based on shared targets of microRNAs, and then we integrated them with a microRNA functional synergistic network, which was recently identified. After analyzing topological properties of these networks, in addition to RWR, we assessed the performance of (i) PRINCE (PRIoritizatioN and Complex Elucidation), which was proposed for disease gene prediction; (ii) PageRank with Priors (PRP) and K-Step Markov (KSM), which were used for studying web networks; and (iii) a neighborhood-based algorithm. Analyses on topological properties showed that all microRNA functional similarity networks are small-worldness and scale-free. The performance of each algorithm was assessed based on average AUC values on 35 disease phenotypes and average rankings of newly discovered disease microRNAs. As a result, the performance on the integrated network was better than that on individual ones. In addition, the performance of PRINCE, PRP and KSM was comparable with that of RWR, whereas it was worst for the neighborhood-based algorithm. Moreover, all the algorithms were stable with the change of parameters. Final, using the integrated network, we predicted six novel miRNAs (i.e., hsa-miR-101, hsa-miR-181d, hsa-miR-192, hsa-miR-423-3p, hsa-miR-484 and hsa-miR-98) associated with breast cancer. Network-based ranking algorithms, which were successfully applied for either disease gene prediction or for studying social/web networks, can be also used effectively for disease microRNA prediction. Copyright © 2015 Elsevier Ltd. All rights reserved.

Ranking Support Vector Machine with Kernel Approximation

PubMed Central

Dou, Yong

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. PMID:28293256

Ranking Support Vector Machine with Kernel Approximation.

PubMed

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.

Indexing and Retrieval for the Web.

ERIC Educational Resources Information Center

Rasmussen, Edie M.

2003-01-01

Explores current research on indexing and ranking as retrieval functions of search engines on the Web. Highlights include measuring search engine stability; evaluation of Web indexing and retrieval; Web crawlers; hyperlinks for indexing and ranking; ranking for metasearch; document structure; citation indexing; relevance; query evaluation;…

Partial Roc Reveals Superiority of Mutual Rank of Pearson's Correlation Coefficient as a Coexpression Measure to Elucidate Functional Association of Genes

NASA Astrophysics Data System (ADS)

Obayashi, Takeshi; Kinoshita, Kengo

2013-01-01

Gene coexpression analysis is a powerful approach to elucidate gene function. We have established and developed this approach using vast amount of publicly available gene expression data measured by microarray techniques. The coexpressed genes are used to estimate gene function of the guide gene or to construct gene coexpression networks. In the case to construct gene networks, researchers should introduce an arbitrary threshold of gene coexpression, because gene coexpression value is continuous value. In the viewpoint to introduce common threshold of gene coexpression, we previously reported rank of Pearson's correlation coefficient (PCC) is more useful than the original PCC value. In this manuscript, we re-assessed the measure of gene coexpression to construct gene coexpression network, and found that mutual rank (MR) of PCC showed better performance than rank of PCC and the original PCC in low false positive rate.

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

NASA Astrophysics Data System (ADS)

Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

DockRank: Ranking docked conformations using partner-specific sequence homology-based protein interface prediction

PubMed Central

Xue, Li C.; Jordan, Rafael A.; EL-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2015-01-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. Dock-Rank uses interface residues predicted by partner-specific sequence homology-based protein–protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. PMID:23873600

DockRank: ranking docked conformations using partner-specific sequence homology-based protein interface prediction.

PubMed

Xue, Li C; Jordan, Rafael A; El-Manzalawy, Yasser; Dobbs, Drena; Honavar, Vasant

2014-02-01

Selecting near-native conformations from the immense number of conformations generated by docking programs remains a major challenge in molecular docking. We introduce DockRank, a novel approach to scoring docked conformations based on the degree to which the interface residues of the docked conformation match a set of predicted interface residues. DockRank uses interface residues predicted by partner-specific sequence homology-based protein-protein interface predictor (PS-HomPPI), which predicts the interface residues of a query protein with a specific interaction partner. We compared the performance of DockRank with several state-of-the-art docking scoring functions using Success Rate (the percentage of cases that have at least one near-native conformation among the top m conformations) and Hit Rate (the percentage of near-native conformations that are included among the top m conformations). In cases where it is possible to obtain partner-specific (PS) interface predictions from PS-HomPPI, DockRank consistently outperforms both (i) ZRank and IRAD, two state-of-the-art energy-based scoring functions (improving Success Rate by up to 4-fold); and (ii) Variants of DockRank that use predicted interface residues obtained from several protein interface predictors that do not take into account the binding partner in making interface predictions (improving success rate by up to 39-fold). The latter result underscores the importance of using partner-specific interface residues in scoring docked conformations. We show that DockRank, when used to re-rank the conformations returned by ClusPro, improves upon the original ClusPro rankings in terms of both Success Rate and Hit Rate. DockRank is available as a server at http://einstein.cs.iastate.edu/DockRank/. Copyright © 2013 Wiley Periodicals, Inc.

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

PubMed

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.

The Functions and Dysfunctions of College Rankings: An Analysis of Institutional Expenditure

ERIC Educational Resources Information Center

Kim, Jeongeun

2018-01-01

College rankings have become a powerful influence in higher education. While the determinants of educational quality are not clearly defined, college rankings designate an institution's standing in a numerical order based on quantifiable measurements that focus primarily on institutional resources. Previous research has identified the…

Stability and change of personality across the life course: the impact of age and major life events on mean-level and rank-order stability of the Big Five.

PubMed

Specht, Jule; Egloff, Boris; Schmukle, Stefan C

2011-10-01

Does personality change across the entire life course, and are those changes due to intrinsic maturation or major life experiences? This longitudinal study investigated changes in the mean levels and rank order of the Big Five personality traits in a heterogeneous sample of 14,718 Germans across all of adulthood. Latent change and latent moderated regression models provided 4 main findings: First, age had a complex curvilinear influence on mean levels of personality. Second, the rank-order stability of Emotional Stability, Extraversion, Openness, and Agreeableness all followed an inverted U-shaped function, reaching a peak between the ages of 40 and 60 and decreasing afterward, whereas Conscientiousness showed a continuously increasing rank-order stability across adulthood. Third, personality predicted the occurrence of several objective major life events (selection effects) and changed in reaction to experiencing these events (socialization effects), suggesting that personality can change due to factors other than intrinsic maturation. Fourth, when events were clustered according to their valence, as is commonly done, effects of the environment on changes in personality were either overlooked or overgeneralized. In sum, our analyses show that personality changes throughout the life span, but with more pronounced changes in young and old ages, and that this change is partly attributable to social demands and experiences. 2011 APA, all rights reserved

Hazard-Ranking of Agricultural Pesticides for Chronic Health Effects in Yuma County, Arizona

PubMed Central

Sugeng, Anastasia J.; Beamer, Paloma I.; Lutz, Eric A.; Rosales, Cecilia B.

2013-01-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. PMID:23783270

Extracting a shape function for a signal with intra-wave frequency modulation.

PubMed

Hou, Thomas Y; Shi, Zuoqiang

2016-04-13

In this paper, we develop an effective and robust adaptive time-frequency analysis method for signals with intra-wave frequency modulation. To handle this kind of signals effectively, we generalize our data-driven time-frequency analysis by using a shape function to describe the intra-wave frequency modulation. The idea of using a shape function in time-frequency analysis was first proposed by Wu (Wu 2013 Appl. Comput. Harmon. Anal. 35, 181-199. (doi:10.1016/j.acha.2012.08.008)). A shape function could be any smooth 2π-periodic function. Based on this model, we propose to solve an optimization problem to extract the shape function. By exploring the fact that the shape function is a periodic function with respect to its phase function, we can identify certain low-rank structure of the signal. This low-rank structure enables us to extract the shape function from the signal. Once the shape function is obtained, the instantaneous frequency with intra-wave modulation can be recovered from the shape function. We demonstrate the robustness and efficiency of our method by applying it to several synthetic and real signals. One important observation is that this approach is very stable to noise perturbation. By using the shape function approach, we can capture the intra-wave frequency modulation very well even for noise-polluted signals. In comparison, existing methods such as empirical mode decomposition/ensemble empirical mode decomposition seem to have difficulty in capturing the intra-wave modulation when the signal is polluted by noise. © 2016 The Author(s).

Variable Importance in Multivariate Group Comparisons.

ERIC Educational Resources Information Center

Huberty, Carl J.; Wisenbaker, Joseph M.

1992-01-01

Interpretations of relative variable importance in multivariate analysis of variance are discussed, with attention to (1) latent construct definition; (2) linear discriminant function scores; and (3) grouping variable effects. Two numerical ranking methods are proposed and compared by the bootstrap approach using two real data sets. (SLD)

Ranked solutions to a class of combinatorial optimizations - with applications in mass spectrometry based peptide sequencing

NASA Astrophysics Data System (ADS)

Doerr, Timothy; Alves, Gelio; Yu, Yi-Kuo

2006-03-01

Typical combinatorial optimizations are NP-hard; however, for a particular class of cost functions the corresponding combinatorial optimizations can be solved in polynomial time. This suggests a way to efficiently find approximate solutions - - find a transformation that makes the cost function as similar as possible to that of the solvable class. After keeping many high-ranking solutions using the approximate cost function, one may then re-assess these solutions with the full cost function to find the best approximate solution. Under this approach, it is important to be able to assess the quality of the solutions obtained, e.g., by finding the true ranking of kth best approximate solution when all possible solutions are considered exhaustively. To tackle this statistical issue, we provide a systematic method starting with a scaling function generated from the fininte number of high- ranking solutions followed by a convergent iterative mapping. This method, useful in a variant of the directed paths in random media problem proposed here, can also provide a statistical significance assessment for one of the most important proteomic tasks - - peptide sequencing using tandem mass spectrometry data.

Does current reporting of lung function by the UK cystic fibrosis registry allow a fair comparison of adult centres?

PubMed

Nightingale, Julia Anne; Osmond, Clive

2017-09-01

Outcome data for UK cystic fibrosis centres are publicly available in an annual report, which ranks centres by median FEV 1 % predicted. We wished to assess whether there are differences in lung function outcomes between adult centres that might imply differing standards of care. UK Registry data from 4761 subjects at 34 anonymised adult centres were used to calculate mean FEV 1 % and rate of change of lung function for 2007-13. These measures were used to rank centres and compare outcomes. There are minor differences between centres for mean FEV 1 % for some years of the study and for rate of change of lung function over the study period. However, rankings are critically dependent on the outcome measure chosen and centre variation becomes negligible once patient population characteristics are taken into account. We have demonstrated that the ranking of centres is biased and any apparent difference in respiratory outcomes is unlikely to be related to differing standards of care between centres. Copyright © 2017 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Hazard-ranking of agricultural pesticides for chronic health effects in Yuma County, Arizona.

PubMed

Sugeng, Anastasia J; Beamer, Paloma I; Lutz, Eric A; Rosales, Cecilia B

2013-10-01

With thousands of pesticides registered by the United States Environmental Protection Agency, it not feasible to sample for all pesticides applied in agricultural communities. Hazard-ranking pesticides based on use, toxicity, and exposure potential can help prioritize community-specific pesticide hazards. This study applied hazard-ranking schemes for cancer, endocrine disruption, and reproductive/developmental toxicity in Yuma County, Arizona. An existing cancer hazard-ranking scheme was modified, and novel schemes for endocrine disruption and reproductive/developmental toxicity were developed to rank pesticide hazards. The hazard-ranking schemes accounted for pesticide use, toxicity, and exposure potential based on chemical properties of each pesticide. Pesticides were ranked as hazards with respect to each health effect, as well as overall chronic health effects. The highest hazard-ranked pesticides for overall chronic health effects were maneb, metam-sodium, trifluralin, pronamide, and bifenthrin. The relative pesticide rankings were unique for each health effect. The highest hazard-ranked pesticides differed from those most heavily applied, as well as from those previously detected in Yuma homes over a decade ago. The most hazardous pesticides for cancer in Yuma County, Arizona were also different from a previous hazard-ranking applied in California. Hazard-ranking schemes that take into account pesticide use, toxicity, and exposure potential can help prioritize pesticides of greatest health risk in agricultural communities. This study is the first to provide pesticide hazard-rankings for endocrine disruption and reproductive/developmental toxicity based on use, toxicity, and exposure potential. These hazard-ranking schemes can be applied to other agricultural communities for prioritizing community-specific pesticide hazards to target decreasing health risk. Copyright © 2013 Elsevier B.V. All rights reserved.

Effects of a progressive muscle relaxation intervention on dementia symptoms, activities of daily living, and immune function in group home residents with dementia in Japan

PubMed Central

Momose, Yumiko

2016-01-01

Aim To evaluate the effects of progressive muscle relaxation on the behavioral and psychological symptoms of dementia, activities of daily living, and immune function of elderly patients with dementia in group homes. Methods The participants were ranked by their group home unit. Odd ranks were assigned to the intervention group and even ranks to the control group. The intervention group participated in progressive muscle relaxation for 15 min each day for 90 days in the group environment; the control group members continued with their normal routine. All the participants’ secretory immunoglobulin A was measured and they were assessed with the Neuropsychiatric Inventory‐Nursing Home version, Nishimura Mental State Scale for the Elderly, and Nishimura Activities of Daily Living Scale. Results The intervention group comprised 18 participants from six units and the control group comprised 19 participants from five units. After the intervention, the Neuropsychiatric Inventory scores were significantly better in the intervention group, particularly for Agitation and Anxiety. The intervention group also showed significantly lower Apathy and Irritability scores and significant improvement in the Interest, Volition, and Social relationships scores on the Mental State Scale, with improvement in the activities of daily living total. However, there was no difference in the secretory immunoglobulin A level between the groups. Conclusion The results suggest that progressive muscle relaxation improves the behavioral and psychological symptoms of dementia and activities of daily living in group home residents with dementia, but does not affect their immune function. PMID:27696678

Phenotypic plasticity to light and nutrient availability alters functional trait ranking across eight perennial grassland species.

PubMed

Siebenkäs, Alrun; Schumacher, Jens; Roscher, Christiane

2015-03-27

Functional traits are often used as species-specific mean trait values in comparative plant ecology or trait-based predictions of ecosystem processes, assuming that interspecific differences are greater than intraspecific trait variation and that trait-based ranking of species is consistent across environments. Although this assumption is increasingly challenged, there is a lack of knowledge regarding to what degree the extent of intraspecific trait variation in response to varying environmental conditions depends on the considered traits and the characteristics of the studied species to evaluate the consequences for trait-based species ranking. We studied functional traits of eight perennial grassland species classified into different functional groups (forbs vs. grasses) and varying in their inherent growth stature (tall vs. small) in a common garden experiment with different environments crossing three levels of nutrient availability and three levels of light availability over 4 months of treatment applications. Grasses and forbs differed in almost all above- and belowground traits, while trait differences related to growth stature were generally small. The traits showing the strongest responses to resource availability were similarly for grasses and forbs those associated with allocation and resource uptake. The strength of trait variation in response to varying resource availability differed among functional groups (grasses > forbs) and species of varying growth stature (small-statured > tall-statured species) in many aboveground traits, but only to a lower extent in belowground traits. These differential responses altered trait-based species ranking in many aboveground traits, such as specific leaf area, tissue nitrogen and carbon concentrations and above-belowground allocation (leaf area ratio and root : shoot ratio) at varying resource supply, while trait-based species ranking was more consistent in belowground traits. Our study shows that species grouping according to functional traits is valid, but trait-based species ranking depends on environmental conditions, thus limiting the applicability of species-specific mean trait values in ecological studies. Published by Oxford University Press on behalf of the Annals of Botany Company.

A Study of the Dependence of the Properties of Galaxy Clusters on Cluster Morphology.

NASA Astrophysics Data System (ADS)

Lugger, Phyllis Minnie

1982-03-01

A quantitative study of the properties of clusters of galaxies as a function of cluster morphology has been carried out using photographic plates obtained with the Palomar 48 inch Schmidt telescope. Surface brightness profiles of 35 first ranked cluster galaxies and luminosity functions of nine clusters are presented and analyzed. The dispersion in the metric magnitudes of first ranked galaxies is quite small ((TURN) 0.4 mag) which is consistent with the results of Kristian, Sandage and Westphal as well as Hoessel, Gunn and Thuan. For the cD (supergiant elliptical) galaxy sample, the mean metric magnitude is (TURN) 0.5 mag brighter than for the non-cD galaxies. The dispersion in the metric magnitudes for the 10 cD galaxies studied is found to be much smaller ((sigma) (TURN) 0.1 mag) than the dispersion in the metric magnitudes of the non-cD first ranked galaxies ((sigma) (TURN) 0.4 mag). The de Vaucouleurs effective radius - magnitude relation determined in the present study for first ranked galaxies (log r(,e) = -0.2 M + const.) is consistent with the extrapolations to brighter magnitudes of the range of relations found by Strom and Strom. The average residuals from the mean radius-magnitude relation for the cD and non-cD galaxy samples were not found to differ at a significant level. Luminosity functions for the region within 0.5 Mpc of the cluster center for three of the clusters studied (A1656, A2147, and A2199) show a deficit of bright galaxies when compared to a concentric annular region with bounds of 0.5 and 1.0 Mpc. Characteristic magnitudes for the nine clusters (determined from square regions 4.6 Mpc on a side) show no significant correlation with cluster morphology, central density, or total magnitude of the first ranked galaxy. The mean values of the Schechter function parameters M('*) and (alpha) are in very good agreement with the previous determinations by Schechter and by Dressler. The differential luminosity functions for A569 and A1656 do not rise monotonically to fainter magnitudes but instead show dips. These data are used to test predictions of several recent theories of the dynamical evolution of clusters of galaxies.

A stochastic Markov chain approach for tennis: Monte Carlo simulation and modeling

NASA Astrophysics Data System (ADS)

Aslam, Kamran

This dissertation describes the computational formulation of probability density functions (pdfs) that facilitate head-to-head match simulations in tennis along with ranking systems developed from their use. A background on the statistical method used to develop the pdfs , the Monte Carlo method, and the resulting rankings are included along with a discussion on ranking methods currently being used both in professional sports and in other applications. Using an analytical theory developed by Newton and Keller in [34] that defines a tennis player's probability of winning a game, set, match and single elimination tournament, a computational simulation has been developed in Matlab that allows further modeling not previously possible with the analytical theory alone. Such experimentation consists of the exploration of non-iid effects, considers the concept the varying importance of points in a match and allows an unlimited number of matches to be simulated between unlikely opponents. The results of these studies have provided pdfs that accurately model an individual tennis player's ability along with a realistic, fair and mathematically sound platform for ranking them.

Extreme learning machine for ranking: generalization analysis and applications.

PubMed

Chen, Hong; Peng, Jiangtao; Zhou, Yicong; Li, Luoqing; Pan, Zhibin

2014-05-01

The extreme learning machine (ELM) has attracted increasing attention recently with its successful applications in classification and regression. In this paper, we investigate the generalization performance of ELM-based ranking. A new regularized ranking algorithm is proposed based on the combinations of activation functions in ELM. The generalization analysis is established for the ELM-based ranking (ELMRank) in terms of the covering numbers of hypothesis space. Empirical results on the benchmark datasets show the competitive performance of the ELMRank over the state-of-the-art ranking methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

7 CFR 633.5 - Application procedures.

Code of Federal Regulations, 2011 CFR

2011-01-01

... ranking criteria and limit the approval of requests for agreements in accordance with the ranking scheme... of matching funds, significance of wetland functions and values, and estimated success of protection...

Resolution of ranking hierarchies in directed networks.

PubMed

Letizia, Elisa; Barucca, Paolo; Lillo, Fabrizio

2018-01-01

Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit.

Resolution of ranking hierarchies in directed networks

PubMed Central

Barucca, Paolo; Lillo, Fabrizio

2018-01-01

Identifying hierarchies and rankings of nodes in directed graphs is fundamental in many applications such as social network analysis, biology, economics, and finance. A recently proposed method identifies the hierarchy by finding the ordered partition of nodes which minimises a score function, termed agony. This function penalises the links violating the hierarchy in a way depending on the strength of the violation. To investigate the resolution of ranking hierarchies we introduce an ensemble of random graphs, the Ranked Stochastic Block Model. We find that agony may fail to identify hierarchies when the structure is not strong enough and the size of the classes is small with respect to the whole network. We analytically characterise the resolution threshold and we show that an iterated version of agony can partly overcome this resolution limit. PMID:29394278

Functional form and risk adjustment of hospital costs: Bayesian analysis of a Box-Cox random coefficients model.

PubMed

Hollenbeak, Christopher S

2005-10-15

While risk-adjusted outcomes are often used to compare the performance of hospitals and physicians, the most appropriate functional form for the risk adjustment process is not always obvious for continuous outcomes such as costs. Semi-log models are used most often to correct skewness in cost data, but there has been limited research to determine whether the log transformation is sufficient or whether another transformation is more appropriate. This study explores the most appropriate functional form for risk-adjusting the cost of coronary artery bypass graft (CABG) surgery. Data included patients undergoing CABG surgery at four hospitals in the midwest and were fit to a Box-Cox model with random coefficients (BCRC) using Markov chain Monte Carlo methods. Marginal likelihoods and Bayes factors were computed to perform model comparison of alternative model specifications. Rankings of hospital performance were created from the simulation output and the rankings produced by Bayesian estimates were compared to rankings produced by standard models fit using classical methods. Results suggest that, for these data, the most appropriate functional form is not logarithmic, but corresponds to a Box-Cox transformation of -1. Furthermore, Bayes factors overwhelmingly rejected the natural log transformation. However, the hospital ranking induced by the BCRC model was not different from the ranking produced by maximum likelihood estimates of either the linear or semi-log model. Copyright (c) 2005 John Wiley & Sons, Ltd.

Non-Convex Sparse and Low-Rank Based Robust Subspace Segmentation for Data Mining.

PubMed

Cheng, Wenlong; Zhao, Mingbo; Xiong, Naixue; Chui, Kwok Tai

2017-07-15

Parsimony, including sparsity and low-rank, has shown great importance for data mining in social networks, particularly in tasks such as segmentation and recognition. Traditionally, such modeling approaches rely on an iterative algorithm that minimizes an objective function with convex l ₁-norm or nuclear norm constraints. However, the obtained results by convex optimization are usually suboptimal to solutions of original sparse or low-rank problems. In this paper, a novel robust subspace segmentation algorithm has been proposed by integrating l p -norm and Schatten p -norm constraints. Our so-obtained affinity graph can better capture local geometrical structure and the global information of the data. As a consequence, our algorithm is more generative, discriminative and robust. An efficient linearized alternating direction method is derived to realize our model. Extensive segmentation experiments are conducted on public datasets. The proposed algorithm is revealed to be more effective and robust compared to five existing algorithms.

Pitch ranking, electrode discrimination, and physiological spread of excitation using current steering in cochlear implants

PubMed Central

Goehring, Jenny L.; Neff, Donna L.; Baudhuin, Jacquelyn L.; Hughes, Michelle L.

2014-01-01

The first objective of this study was to determine whether adaptive pitch-ranking and electrode-discrimination tasks with cochlear-implant (CI) recipients produce similar results for perceiving intermediate “virtual-channel” pitch percepts using current steering. Previous studies have not examined both behavioral tasks in the same subjects with current steering. A second objective was to determine whether a physiological metric of spatial separation using the electrically evoked compound action potential spread-of-excitation (ECAP SOE) function could predict performance in the behavioral tasks. The metric was the separation index (Σ), defined as the difference in normalized amplitudes between two adjacent ECAP SOE functions, summed across all masker electrodes. Eleven CII or 90 K Advanced Bionics (Valencia, CA) recipients were tested using pairs of electrodes from the basal, middle, and apical portions of the electrode array. The behavioral results, expressed as d′, showed no significant differences across tasks. There was also no significant effect of electrode region for either task. ECAP Σ was not significantly correlated with pitch ranking or electrode discrimination for any of the electrode regions. Therefore, the ECAP separation index is not sensitive enough to predict perceptual resolution of virtual channels. PMID:25480063

Ranking Hearing Aid Input-Output Functions for Understanding Low-, Conversational-, and High-Level Speech in Multitalker Babble

ERIC Educational Resources Information Center

Chung, King; Killion, Mead C.; Christensen, Laurel A.

2007-01-01

Purpose: To determine the rankings of 6 input-output functions for understanding low-level, conversational, and high-level speech in multitalker babble without manipulating volume control for listeners with normal hearing, flat sensorineural hearing loss, and mildly sloping sensorineural hearing loss. Method: Peak clipping, compression limiting,…

Early play may predict later dominance relationships in yellow-bellied marmots (Marmota flaviventris).

PubMed

Blumstein, Daniel T; Chung, Lawrance K; Smith, Jennifer E

2013-05-22

Play has been defined as apparently functionless behaviour, yet since play is costly, models of adaptive evolution predict that it should have some beneficial function (or functions) that outweigh its costs. We provide strong evidence for a long-standing, but poorly supported hypothesis: that early social play is practice for later dominance relationships. We calculated the relative dominance rank by observing the directional outcome of playful interactions in juvenile and yearling yellow-bellied marmots (Marmota flaviventris) and found that these rank relationships were correlated with later dominance ranks calculated from agonistic interactions, however, the strength of this relationship attenuated over time. While play may have multiple functions, one of them may be to establish later dominance relationships in a minimally costly way.

Quantification of heterogeneity observed in medical images.

PubMed

Brooks, Frank J; Grigsby, Perry W

2013-03-02

There has been much recent interest in the quantification of visually evident heterogeneity within functional grayscale medical images, such as those obtained via magnetic resonance or positron emission tomography. In the case of images of cancerous tumors, variations in grayscale intensity imply variations in crucial tumor biology. Despite these considerable clinical implications, there is as yet no standardized method for measuring the heterogeneity observed via these imaging modalities. In this work, we motivate and derive a statistical measure of image heterogeneity. This statistic measures the distance-dependent average deviation from the smoothest intensity gradation feasible. We show how this statistic may be used to automatically rank images of in vivo human tumors in order of increasing heterogeneity. We test this method against the current practice of ranking images via expert visual inspection. We find that this statistic provides a means of heterogeneity quantification beyond that given by other statistics traditionally used for the same purpose. We demonstrate the effect of tumor shape upon our ranking method and find the method applicable to a wide variety of clinically relevant tumor images. We find that the automated heterogeneity rankings agree very closely with those performed visually by experts. These results indicate that our automated method may be used reliably to rank, in order of increasing heterogeneity, tumor images whether or not object shape is considered to contribute to that heterogeneity. Automated heterogeneity ranking yields objective results which are more consistent than visual rankings. Reducing variability in image interpretation will enable more researchers to better study potential clinical implications of observed tumor heterogeneity.

Functional complexity and ecosystem stability: an experimental approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Van Voris, P.; O'Neill, R.V.; Shugart, H.H.

1978-01-01

The complexity-stability hypothesis was experimentally tested using intact terrestrial microcosms. Functional complexity was defined as the number and significance of component interactions (i.e., population interactions, physical-chemical reactions, biological turnover rates) influenced by nonlinearities, feedbacks, and time delays. It was postulated that functional complexity could be nondestructively measured through analysis of a signal generated from the system. Power spectral analysis of hourly CO/sub 2/ efflux, from eleven old-field microcosms, was analyzed for the number of low frequency peaks and used to rank the functional complexity of each system. Ranking of ecosystem stability was based on the capacity of the system tomore » retain essential nutrients and was measured by net loss of Ca after the system was stressed. Rank correlation supported the hypothesis that increasing ecosystem functional complexity leads to increasing ecosystem stability. The results indicated that complex functional dynamics can serve to stabilize the system. The results also demonstrated that microcosms are useful tools for system-level investigations.« less

Implicating Receptor Activator of NF-κB (RANK)/RANK Ligand Signalling in Microglial Responses to Toll-Like Receptor Stimuli

PubMed Central

Kichev, Anton; Eede, Pascale; Gressens, Pierre; Thornton, Claire; Hagberg, Henrik

2017-01-01

Inflammation in the perinatal brain caused by maternal or intrauterine fetal infection is now well established as an important contributor to the development of perinatal brain injury. Exposure to inflammatory products can impair perinatal brain development and act as a risk factor for neurological dysfunction, cognitive disorders, cerebral palsy, or preterm birth. Pre-exposure to inflammation significantly exacerbates brain injury caused by hypoxic/ischaemic insult. Tumour necrosis factor (TNF) is a family of cytokines largely involved in inflammation signalling. In our previous study, we identified the importance of TNF-related apoptosis-inducing ligand (TRAIL) signalling in the development of perinatal brain injury. We observed a significant increase in the expression levels of a soluble decoy receptor for TRAIL, osteoprotegerin (OPG). Besides TRAIL, OPG is able to bind the receptor activator of the NF-κB (RANK) ligand (RANKL) and inhibit its signalling. The function of the RANK/RANKL/OPG system in the brain has not come under much scrutiny. The aim of this research study was to elucidate the role of RANK, RANKL, and OPG in microglial responses to the proinflammatory stimuli lipopolysaccharide (LPS) and polyinosinic-polycytidylic acid (Poly I:C). Here, we show that RANK signalling is important for regulating the activation of the BV2 microglial cell line. We found that LPS treatment causes a significant decrease in the expression of RANK in the BV2 cell line while significantly increasing the expression of OPG, Toll-like receptor (TLR)3, and the adaptor proteins MyD88 and TRIF. We found that pretreatment of BV2 cells with RANKL for 24 h before the LPS or Poly I:C exposure decreases the expression of inflammatory markers such as inducible nitric oxide synthase and cyclooxygenase. This is accompanied by a decreased expression of the TLR adaptor proteins MyD88 and TRIF, which we observed after RANKL treatment. Similar results were obtained in our experiments with primary mouse microglia. Using recently developed CRISPR/Cas9 technology, we generated a BV2 cell line lacking RANK (RANK-/- BV2). We showed that most effects of RANKL pretreatment were abolished, thereby proving the specificity of this effect. Taken together, these findings suggest that RANK signalling is important for modulating the inflammatory activation of microglial cells to a moderate level, and that RANK attenuates TLR3/TLR4 signalling. PMID:28402971

Implicating Receptor Activator of NF-κB (RANK)/RANK Ligand Signalling in Microglial Responses to Toll-Like Receptor Stimuli.

PubMed

Kichev, Anton; Eede, Pascale; Gressens, Pierre; Thornton, Claire; Hagberg, Henrik

2017-01-01

Inflammation in the perinatal brain caused by maternal or intrauterine fetal infection is now well established as an important contributor to the development of perinatal brain injury. Exposure to inflammatory products can impair perinatal brain development and act as a risk factor for neurological dysfunction, cognitive disorders, cerebral palsy, or preterm birth. Pre-exposure to inflammation significantly exacerbates brain injury caused by hypoxic/ischaemic insult. Tumour necrosis factor (TNF) is a family of cytokines largely involved in inflammation signalling. In our previous study, we identified the importance of TNF-related apoptosis-inducing ligand (TRAIL) signalling in the development of perinatal brain injury. We observed a significant increase in the expression levels of a soluble decoy receptor for TRAIL, osteoprotegerin (OPG). Besides TRAIL, OPG is able to bind the receptor activator of the NF-κB (RANK) ligand (RANKL) and inhibit its signalling. The function of the RANK/RANKL/OPG system in the brain has not come under much scrutiny. The aim of this research study was to elucidate the role of RANK, RANKL, and OPG in microglial responses to the proinflammatory stimuli lipopolysaccharide (LPS) and polyinosinic-polycytidylic acid (Poly I:C). Here, we show that RANK signalling is important for regulating the activation of the BV2 microglial cell line. We found that LPS treatment causes a significant decrease in the expression of RANK in the BV2 cell line while significantly increasing the expression of OPG, Toll-like receptor (TLR)3, and the adaptor proteins MyD88 and TRIF. We found that pretreatment of BV2 cells with RANKL for 24 h before the LPS or Poly I:C exposure decreases the expression of inflammatory markers such as inducible nitric oxide synthase and cyclooxygenase. This is accompanied by a decreased expression of the TLR adaptor proteins MyD88 and TRIF, which we observed after RANKL treatment. Similar results were obtained in our experiments with primary mouse microglia. Using recently developed CRISPR/Cas9 technology, we generated a BV2 cell line lacking RANK (RANK-/- BV2). We showed that most effects of RANKL pretreatment were abolished, thereby proving the specificity of this effect. Taken together, these findings suggest that RANK signalling is important for modulating the inflammatory activation of microglial cells to a moderate level, and that RANK attenuates TLR3/TLR4 signalling. © 2017 The Author(s) Published by S. Karger AG, Basel.

A Measurement of AFIT Contracting and Acquisition Management Program Usefulness as Perceived by Graduates and Their Supervisors.

DTIC Science & Technology

1982-09-01

21 functions. The legal category covers the business, commer- cial and contract law fields, including patents and royalties, technical data, claims...Course Rankings Question # Subject Area Median Rank 55,56,59 Contract Management Theory 7.0 1 53,54 Contract Law 6.5 2 So Contracting & Acquis. Mgt...respondents ranked Contract Management Theory as the most useful course among all courses in the AFIT CAM curriculum. Graduates ranked Contract Law as

A Universal Rank-Size Law

PubMed Central

2016-01-01

A mere hyperbolic law, like the Zipf’s law power function, is often inadequate to describe rank-size relationships. An alternative theoretical distribution is proposed based on theoretical physics arguments starting from the Yule-Simon distribution. A modeling is proposed leading to a universal form. A theoretical suggestion for the “best (or optimal) distribution”, is provided through an entropy argument. The ranking of areas through the number of cities in various countries and some sport competition ranking serves for the present illustrations. PMID:27812192

PageRank and rank-reversal dependence on the damping factor

NASA Astrophysics Data System (ADS)

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.

Co-expression Network Approach to Studying the Effects of Botulinum Neurotoxin-A.

PubMed

Mukund, Kavitha; Ward, Samuel R; Lieber, Richard L; Subramaniam, Shankar

2017-10-16

Botulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous workBotulinum Neurotoxin A (BoNT-A) is a potent neurotoxin with several clinical applications.The goal of this study was to utilize co-expression network theory to analyze temporal transcriptional data from skeletal muscle after BoNT-A treatment. Expression data for 2000 genes (extracted using a ranking heuristic) served as the basis for this analysis. Using weighted gene co-expression network analysis (WGCNA), we identified 19 co-expressed modules, further hierarchically clustered into 5 groups. Quantifying average expression and co-expression patterns across these groups revealed temporal aspects of muscle's response to BoNT-A. Functional analysis revealed enrichment of group 1 with metabolism; group 5 with contradictory functions of atrophy and cellular recovery; and groups 2 and 3 with extracellular matrix (ECM) and non-fast fiber isoforms. Topological positioning of two highly ranked, significantly expressed genes- Dclk1 and Ostalpha within group 5 suggested possible mechanistic roles in recovery from BoNT-A induced atrophy. Phenotypic correlations of groups with titin and myosin protein content further emphasized the effect of BoNT-A on the sarcomeric contraction machinery in early phase of chemodenervation. In summary, our approach revealed a hierarchical functional response to BoNT-A induced paralysis with early metabolic and later ECM responses and identified putative biomarkers associated with chemodenervation. Additionally, our results provide an unbiased validation of the response documented in our previous work.

Appearance is a function of the face.

PubMed

Borah, Gregory L; Rankin, Marlene K

2010-03-01

Increasingly, third-party insurers deny coverage to patients with posttraumatic and congenital facial deformities because these are not seen as "functional." Recent facial transplants have demonstrated that severely deformed patients are willing to undergo potentially life-threatening surgery in search of a normal physiognomy. Scant quantitative research exists that objectively documents appearance as a primary "function" of the face. This study was designed to establish a population-based definition of the functions of the human face, rank importance of the face among various anatomical areas, and determine the risk value the average person places on a normal appearance. Voluntary adult subjects (n = 210) in three states aged 18 to 75 years were recruited using a quota sampling technique. Subjects completed study questionnaires of demography and bias using the Gamble Chance of Death Questionnaire and the Rosenberg Self-Esteem Scale. The face ranked as the most important anatomical area for functional reconstruction. Appearance was the fifth most important function of the face, after breathing, sight, speech, and eating. Normal facial appearance was rated as very important for one to be a functioning member of American society (p = 0.01) by 49 percent. One in seven subjects (13 percent) would accept a 30 to 45 percent risk of death to obtain a "normal" face. Normal appearance is a primary function of the face, based on a large, culturally diverse population sample across the lifespan. Normal appearance ranks above smell and expression as a function. Restoration of facial appearance is ranked the most important anatomical area for repair. Normal facial appearance is very important for one to be a functional member of American society.

Multifaceted diversity-area relationships reveal global hotspots of mammalian species, trait and lineage diversity.

PubMed

Mazel, Florent; Guilhaumon, François; Mouquet, Nicolas; Devictor, Vincent; Gravel, Dominique; Renaud, Julien; Cianciaruso, Marcus Vinicius; Loyola, Rafael Dias; Diniz-Filho, José Alexandre Felizola; Mouillot, David; Thuiller, Wilfried

2014-08-01

To define biome-scale hotspots of phylogenetic and functional mammalian biodiversity (PD and FD, respectively) and compare them to 'classical' hotspots based on species richness (SR) only. Global. SR, PD & FD were computed for 782 terrestrial ecoregions using distribution ranges of 4616 mammalian species. We used a set of comprehensive diversity indices unified by a recent framework that incorporates the species relative coverage in each ecoregion. We build large-scale multifaceted diversity-area relationships to rank ecoregions according to their levels of biodiversity while accounting for the effect of area on each diversity facet. Finally we defined hotspots as the top-ranked ecoregions. While ignoring species relative coverage led to a relative good congruence between biome top ranked SR, PD and FD hotspots, ecoregions harboring a rich and abundantly represented evolutionary history and functional diversity did not match with top ranked ecoregions defined by species richness. More importantly PD and FD hotspots showed important spatial mismatches. We also found that FD and PD generally reached their maximum values faster than species richness as a function of area. The fact that PD/FD reach faster their maximal value than SR may suggest that the two former facets might be less vulnerable to habitat loss than the latter. While this point is expected, it is the first time that it is quantified at global scale and should have important consequences in conservation. Incorporating species relative coverage into the delineation of multifaceted hotspots of diversity lead to weak congruence between SR, PD and FD hotspots. This means that maximizing species number may fail at preserving those nodes (in the phylogenetic or functional tree) that are relatively abundant in the ecoregion. As a consequence it may be of prime importance to adopt a multifaceted biodiversity perspective to inform conservation strategies at global scale.

Multifaceted diversity-area relationships reveal global hotspots of mammalian species, trait and lineage diversity

PubMed Central

Mazel, Florent; Guilhaumon, François; Mouquet, Nicolas; Devictor, Vincent; Gravel, Dominique; Renaud, Julien; Cianciaruso, Marcus Vinicius; Loyola, Rafael Dias; Diniz-Filho, José Alexandre Felizola; Mouillot, David; Thuiller, Wilfried

2014-01-01

Aim To define biome-scale hotspots of phylogenetic and functional mammalian biodiversity (PD and FD, respectively) and compare them to ‘classical’ hotspots based on species richness (SR) only. Location Global Methods SR, PD & FD were computed for 782 terrestrial ecoregions using distribution ranges of 4616 mammalian species. We used a set of comprehensive diversity indices unified by a recent framework that incorporates the species relative coverage in each ecoregion. We build large-scale multifaceted diversity-area relationships to rank ecoregions according to their levels of biodiversity while accounting for the effect of area on each diversity facet. Finally we defined hotspots as the top-ranked ecoregions. Results While ignoring species relative coverage led to a relative good congruence between biome top ranked SR, PD and FD hotspots, ecoregions harboring a rich and abundantly represented evolutionary history and functional diversity did not match with top ranked ecoregions defined by species richness. More importantly PD and FD hotspots showed important spatial mismatches. We also found that FD and PD generally reached their maximum values faster than species richness as a function of area. Main conclusions The fact that PD/FD reach faster their maximal value than SR may suggest that the two former facets might be less vulnerable to habitat loss than the latter. While this point is expected, it is the first time that it is quantified at global scale and should have important consequences in conservation. Incorporating species relative coverage into the delineation of multifaceted hotspots of diversity lead to weak congruence between SR, PD and FD hotspots. This means that maximizing species number may fail at preserving those nodes (in the phylogenetic or functional tree) that are relatively abundant in the ecoregion. As a consequence it may be of prime importance to adopt a multifaceted biodiversity perspective to inform conservation strategies at global scale. PMID:25071413

Equity weights in the allocation of health care: the rank-dependent QALY model.

PubMed

Bleichrodt, Han; Diecidue, Enrico; Quiggin, John

2004-01-01

This paper introduces the rank-dependent quality-adjusted life-years (QALY) model, a new method to aggregate QALYs in economic evaluations of health care. The rank-dependent QALY model permits the formalization of influential concepts of equity in the allocation of health care, such as the fair innings approach, and it includes as special cases many of the social welfare functions that have been proposed in the literature. An important advantage of the rank-dependent QALY model is that it offers a straightforward procedure to estimate equity weights for QALYs. We characterize the rank-dependent QALY model and argue that its central condition has normative appeal.

LCK rank of locally conformally Kähler manifolds with potential

NASA Astrophysics Data System (ADS)

Ornea, Liviu; Verbitsky, Misha

2016-09-01

An LCK manifold with potential is a quotient of a Kähler manifold X equipped with a positive Kähler potential f, such that the monodromy group acts on X by holomorphic homotheties and multiplies f by a character. The LCK rank is the rank of the image of this character, considered as a function from the monodromy group to real numbers. We prove that an LCK manifold with potential can have any rank between 1 and b1(M) . Moreover, LCK manifolds with proper potential (ones with rank 1) are dense. Two errata to our previous work are given in the last section.

A sampling-based method for ranking protein structural models by integrating multiple scores and features.

PubMed

Shi, Xiaohu; Zhang, Jingfen; He, Zhiquan; Shang, Yi; Xu, Dong

2011-09-01

One of the major challenges in protein tertiary structure prediction is structure quality assessment. In many cases, protein structure prediction tools generate good structural models, but fail to select the best models from a huge number of candidates as the final output. In this study, we developed a sampling-based machine-learning method to rank protein structural models by integrating multiple scores and features. First, features such as predicted secondary structure, solvent accessibility and residue-residue contact information are integrated by two Radial Basis Function (RBF) models trained from different datasets. Then, the two RBF scores and five selected scoring functions developed by others, i.e., Opus-CA, Opus-PSP, DFIRE, RAPDF, and Cheng Score are synthesized by a sampling method. At last, another integrated RBF model ranks the structural models according to the features of sampling distribution. We tested the proposed method by using two different datasets, including the CASP server prediction models of all CASP8 targets and a set of models generated by our in-house software MUFOLD. The test result shows that our method outperforms any individual scoring function on both best model selection, and overall correlation between the predicted ranking and the actual ranking of structural quality.

Early play may predict later dominance relationships in yellow-bellied marmots (Marmota flaviventris)

PubMed Central

Blumstein, Daniel T.; Chung, Lawrance K.; Smith, Jennifer E.

2013-01-01

Play has been defined as apparently functionless behaviour, yet since play is costly, models of adaptive evolution predict that it should have some beneficial function (or functions) that outweigh its costs. We provide strong evidence for a long-standing, but poorly supported hypothesis: that early social play is practice for later dominance relationships. We calculated the relative dominance rank by observing the directional outcome of playful interactions in juvenile and yearling yellow-bellied marmots (Marmota flaviventris) and found that these rank relationships were correlated with later dominance ranks calculated from agonistic interactions, however, the strength of this relationship attenuated over time. While play may have multiple functions, one of them may be to establish later dominance relationships in a minimally costly way. PMID:23536602

Anchoring Effects in World University Rankings: Exploring Biases in Reputation Scores

ERIC Educational Resources Information Center

Bowman, Nicholas A.; Bastedo, Michael N.

2011-01-01

Despite ongoing debates about their uses and validity, university rankings are a popular means to compare institutions within a country and around the world. Anchoring theory suggests that these rankings may influence assessments of institutional reputation, and this effect may be particularly strong when a new rankings system is introduced. We…

Ranked solutions to a class of combinatorial optimizations—with applications in mass spectrometry based peptide sequencing and a variant of directed paths in random media

NASA Astrophysics Data System (ADS)

Doerr, Timothy P.; Alves, Gelio; Yu, Yi-Kuo

2005-08-01

Typical combinatorial optimizations are NP-hard; however, for a particular class of cost functions the corresponding combinatorial optimizations can be solved in polynomial time using the transfer matrix technique or, equivalently, the dynamic programming approach. This suggests a way to efficiently find approximate solutions-find a transformation that makes the cost function as similar as possible to that of the solvable class. After keeping many high-ranking solutions using the approximate cost function, one may then re-assess these solutions with the full cost function to find the best approximate solution. Under this approach, it is important to be able to assess the quality of the solutions obtained, e.g., by finding the true ranking of the kth best approximate solution when all possible solutions are considered exhaustively. To tackle this statistical issue, we provide a systematic method starting with a scaling function generated from the finite number of high-ranking solutions followed by a convergent iterative mapping. This method, useful in a variant of the directed paths in random media problem proposed here, can also provide a statistical significance assessment for one of the most important proteomic tasks-peptide sequencing using tandem mass spectrometry data. For directed paths in random media, the scaling function depends on the particular realization of randomness; in the mass spectrometry case, the scaling function is spectrum-specific.

Identifying Outcomes that Are Important to Living Kidney Donors: A Nominal Group Technique Study.

PubMed

Hanson, Camilla S; Chapman, Jeremy R; Gill, John S; Kanellis, John; Wong, Germaine; Craig, Jonathan C; Teixeira-Pinto, Armando; Chadban, Steve J; Garg, Amit X; Ralph, Angelique F; Pinter, Jule; Lewis, Joshua R; Tong, Allison

2018-06-07

Living kidney donor candidates accept a range of risks and benefits when they decide to proceed with nephrectomy. Informed consent around this decision assumes they receive reliable data about outcomes they regard as critical to their decision making. We identified the outcomes most important to living kidney donors and described the reasons for their choices. Previous donors were purposively sampled from three transplant units in Australia (Sydney and Melbourne) and Canada (Vancouver). In focus groups using the nominal group technique, participants identified outcomes of donation, ranked them in order of importance, and discussed the reasons for their preferences. An importance score was calculated for each outcome. Qualitative data were analyzed thematically. Across 14 groups, 123 donors aged 27-78 years identified 35 outcomes. Across all participants, the ten highest ranked outcomes were kidney function (importance=0.40, scale 0-1), time to recovery (0.27), surgical complications (0.24), effect on family (0.22), donor-recipient relationship (0.21), life satisfaction (0.18), lifestyle restrictions (0.18), kidney failure (0.14), mortality (0.13), and acute pain/discomfort (0.12). Kidney function and kidney failure were more important to Canadian participants, compared with Australian donors. The themes identified included worthwhile sacrifice, insignificance of risks and harms, confidence and empowerment, unfulfilled expectations, and heightened susceptibility. Living kidney donors prioritized a range of outcomes, with the most important being kidney health and the surgical, lifestyle, functional, and psychosocial effects of donation. Donors also valued improvements to their family life and donor-recipient relationship. There were clear regional differences in the rankings. Copyright © 2018 by the American Society of Nephrology.

28 CFR 0.137 - Designating officials to perform the functions and duties of certain offices in case of absence...

Code of Federal Regulations, 2010 CFR

2010-07-01

... paragraphs (a) or (b) of this section, the ranking deputy (or an equivalent official) in such unit who is... directs otherwise. Except as otherwise provided by law, if there is no ranking deputy available, the... designate the ranking deputy (or an equivalent official) in the unit who is available to act as head. If...

Bayesian Inference of Natural Rankings in Incomplete Competition Networks

PubMed Central

Park, Juyong; Yook, Soon-Hyung

2014-01-01

Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest – essential in determining reward and penalty – is frequently an ambiguous task due to the incomplete (partially filled) nature of competition networks. Here we introduce the “Natural Ranking,” an unambiguous ranking method applicable to a round robin tournament, and formulate an analytical model based on the Bayesian formula for inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in resolving important issues of ranking by applying it to real-world competition networks. PMID:25163528

Bayesian Inference of Natural Rankings in Incomplete Competition Networks

NASA Astrophysics Data System (ADS)

Park, Juyong; Yook, Soon-Hyung

2014-08-01

Competition between a complex system's constituents and a corresponding reward mechanism based on it have profound influence on the functioning, stability, and evolution of the system. But determining the dominance hierarchy or ranking among the constituent parts from the strongest to the weakest - essential in determining reward and penalty - is frequently an ambiguous task due to the incomplete (partially filled) nature of competition networks. Here we introduce the ``Natural Ranking,'' an unambiguous ranking method applicable to a round robin tournament, and formulate an analytical model based on the Bayesian formula for inferring the expected mean and error of the natural ranking of nodes from an incomplete network. We investigate its potential and uses in resolving important issues of ranking by applying it to real-world competition networks.

Task Satisfaction and Interpersonal Cohesiveness Among Laterally Divided Command Teams.

ERIC Educational Resources Information Center

Krieger, William G.

Ninety-six males participated in four-man teams involved in a complex decision making task. Subteams with differing functions but equal rank were established. Subteams either were or were not physically separated during the tasks. Group cohesiveness was not effected, but subteam task satisfaction differences were greatest when subteams remained…

The Organizational Communication Process in Schools

ERIC Educational Resources Information Center

Gunbayi, Ilhan

2007-01-01

This study examined the perceptions of teachers on the effectiveness of organizational communication in their schools and whether the perceptions differed between teachers in primary and junior high schools as a function of gender, age, marital status, seniority, and rank. Data were collected from a sample of 334 teachers in 63 schools, working in…

Maryland's high cancer mortality rate: a review of contributing demographic factors.

PubMed

Freedman, D M

1999-01-01

For many years, Maryland has ranked among the top states in cancer mortality. This study analyzed mortality data from the National Center for Health Statistics (CDC-Wonder) to help explain Maryland's cancer rate and rank. Age-adjusted rates are based on deaths per 100,000 population from 1991 through 1995. Rates and ranks overall, and stratified by age, are calculated for total cancer mortality, as well as for four major sites: lung, breast, prostate, and colorectal. Because states differ in their racial/gender mix, race/gender rates among states are also compared. Although Maryland ranks seventh in overall cancer mortality, its rates and rank by race and gender subpopulation are less high. For those under 75, white men ranked 26th, black men ranked 20th, and black and white women ranked 12th and 10th, respectively. Maryland's overall rank, as with any state, is a function of the rates of its racial and gender subpopulations and the relative size of these groups in the state. Many of the disparities between Maryland's overall high cancer rank and its lower rank by subpopulation also characterize the major cancer sites. Although a stratified presentation of cancer rates and ranks may be more favorable to Maryland, it should not be used to downplay the attention cancer mortality in Maryland deserves.

Relevance Rank Platform (RRP) for Functional Filtering of High Content Protein-Protein Interaction Data.

PubMed

Pokharel, Yuba Raj; Saarela, Jani; Szwajda, Agnieszka; Rupp, Christian; Rokka, Anne; Lal Kumar Karna, Shibendra; Teittinen, Kaisa; Corthals, Garry; Kallioniemi, Olli; Wennerberg, Krister; Aittokallio, Tero; Westermarck, Jukka

2015-12-01

High content protein interaction screens have revolutionized our understanding of protein complex assembly. However, one of the major challenges in translation of high content protein interaction data is identification of those interactions that are functionally relevant for a particular biological question. To address this challenge, we developed a relevance ranking platform (RRP), which consist of modular functional and bioinformatic filters to provide relevance rank among the interactome proteins. We demonstrate the versatility of RRP to enable a systematic prioritization of the most relevant interaction partners from high content data, highlighted by the analysis of cancer relevant protein interactions for oncoproteins Pin1 and PME-1. We validated the importance of selected interactions by demonstration of PTOV1 and CSKN2B as novel regulators of Pin1 target c-Jun phosphorylation and reveal previously unknown interacting proteins that may mediate PME-1 effects via PP2A-inhibition. The RRP framework is modular and can be modified to answer versatile research problems depending on the nature of the biological question under study. Based on comparison of RRP to other existing filtering tools, the presented data indicate that RRP offers added value especially for the analysis of interacting proteins for which there is no sufficient prior knowledge available. Finally, we encourage the use of RRP in combination with either SAINT or CRAPome computational tools for selecting the candidate interactors that fulfill the both important requirements, functional relevance, and high confidence interaction detection. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

Desirability-based methods of multiobjective optimization and ranking for global QSAR studies. Filtering safe and potent drug candidates from combinatorial libraries.

PubMed

Cruz-Monteagudo, Maykel; Borges, Fernanda; Cordeiro, M Natália D S; Cagide Fajin, J Luis; Morell, Carlos; Ruiz, Reinaldo Molina; Cañizares-Carmenate, Yudith; Dominguez, Elena Rosa

2008-01-01

Up to now, very few applications of multiobjective optimization (MOOP) techniques to quantitative structure-activity relationship (QSAR) studies have been reported in the literature. However, none of them report the optimization of objectives related directly to the final pharmaceutical profile of a drug. In this paper, a MOOP method based on Derringer's desirability function that allows conducting global QSAR studies, simultaneously considering the potency, bioavailability, and safety of a set of drug candidates, is introduced. The results of the desirability-based MOOP (the levels of the predictor variables concurrently producing the best possible compromise between the properties determining an optimal drug candidate) are used for the implementation of a ranking method that is also based on the application of desirability functions. This method allows ranking drug candidates with unknown pharmaceutical properties from combinatorial libraries according to the degree of similarity with the previously determined optimal candidate. Application of this method will make it possible to filter the most promising drug candidates of a library (the best-ranked candidates), which should have the best pharmaceutical profile (the best compromise between potency, safety and bioavailability). In addition, a validation method of the ranking process, as well as a quantitative measure of the quality of a ranking, the ranking quality index (Psi), is proposed. The usefulness of the desirability-based methods of MOOP and ranking is demonstrated by its application to a library of 95 fluoroquinolones, reporting their gram-negative antibacterial activity and mammalian cell cytotoxicity. Finally, the combined use of the desirability-based methods of MOOP and ranking proposed here seems to be a valuable tool for rational drug discovery and development.

Testing the encoding elaboration hypothesis: The effects of exemplar ranking on recognition and recall.

PubMed

Schnur, P

1977-11-01

Two experiments investigated the effects of exemplar ranking on retention. High-ranking exemplars are words judged to be prototypical of a given category; low-ranking exemplars are words judged to be atypical of a given category. In Experiment 1, an incidental learning paradigm was used to measure reaction time to answer an encoding question as well as subsequent recognition. It was found that low-ranking exemplars were classified more slowly but recognized better than high-ranking exemplars. Other comparisons of the effects of category encoding, rhyme encoding, and typescript encoding on response latency and recognition replicated the results of Craik and Tulving (1975). In Experiment 2, unanticipated free recall of live previously learned paired associate lists revealed that a list composed of low-ranking exemplars was better recalled than a comparable list composed of high-ranking exemplars. Moreover, this was true only when the lists were studied in the context of appropriate category cues. These findings are discussed in terms of the encoding elaboration hypothesis.

Maximising information recovery from rank-order codes

NASA Astrophysics Data System (ADS)

Sen, B.; Furber, S.

2007-04-01

The central nervous system encodes information in sequences of asynchronously generated voltage spikes, but the precise details of this encoding are not well understood. Thorpe proposed rank-order codes as an explanation of the observed speed of information processing in the human visual system. The work described in this paper is inspired by the performance of SpikeNET, a biologically inspired neural architecture using rank-order codes for information processing, and is based on the retinal model developed by VanRullen and Thorpe. This model mimics retinal information processing by passing an input image through a bank of Difference of Gaussian (DoG) filters and then encoding the resulting coefficients in rank-order. To test the effectiveness of this encoding in capturing the information content of an image, the rank-order representation is decoded to reconstruct an image that can be compared with the original. The reconstruction uses a look-up table to infer the filter coefficients from their rank in the encoded image. Since the DoG filters are approximately orthogonal functions, they are treated as their own inverses in the reconstruction process. We obtained a quantitative measure of the perceptually important information retained in the reconstructed image relative to the original using a slightly modified version of an objective metric proposed by Petrovic. It is observed that around 75% of the perceptually important information is retained in the reconstruction. In the present work we reconstruct the input using a pseudo-inverse of the DoG filter-bank with the aim of improving the reconstruction and thereby extracting more information from the rank-order encoded stimulus. We observe that there is an increase of 10 - 15% in the information retrieved from a reconstructed stimulus as a result of inverting the filter-bank.

Rank-preserving regression: a more robust rank regression model against outliers.

PubMed

Chen, Tian; Kowalski, Jeanne; Chen, Rui; Wu, Pan; Zhang, Hui; Feng, Changyong; Tu, Xin M

2016-08-30

Mean-based semi-parametric regression models such as the popular generalized estimating equations are widely used to improve robustness of inference over parametric models. Unfortunately, such models are quite sensitive to outlying observations. The Wilcoxon-score-based rank regression (RR) provides more robust estimates over generalized estimating equations against outliers. However, the RR and its extensions do not sufficiently address missing data arising in longitudinal studies. In this paper, we propose a new approach to address outliers under a different framework based on the functional response models. This functional-response-model-based alternative not only addresses limitations of the RR and its extensions for longitudinal data, but, with its rank-preserving property, even provides more robust estimates than these alternatives. The proposed approach is illustrated with both real and simulated data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

An Efficient Rank Based Approach for Closest String and Closest Substring

PubMed Central

2012-01-01

This paper aims to present a new genetic approach that uses rank distance for solving two known NP-hard problems, and to compare rank distance with other distance measures for strings. The two NP-hard problems we are trying to solve are closest string and closest substring. For each problem we build a genetic algorithm and we describe the genetic operations involved. Both genetic algorithms use a fitness function based on rank distance. We compare our algorithms with other genetic algorithms that use different distance measures, such as Hamming distance or Levenshtein distance, on real DNA sequences. Our experiments show that the genetic algorithms based on rank distance have the best results. PMID:22675483

Exponential Family Functional data analysis via a low-rank model.

PubMed

Li, Gen; Huang, Jianhua Z; Shen, Haipeng

2018-05-08

In many applications, non-Gaussian data such as binary or count are observed over a continuous domain and there exists a smooth underlying structure for describing such data. We develop a new functional data method to deal with this kind of data when the data are regularly spaced on the continuous domain. Our method, referred to as Exponential Family Functional Principal Component Analysis (EFPCA), assumes the data are generated from an exponential family distribution, and the matrix of the canonical parameters has a low-rank structure. The proposed method flexibly accommodates not only the standard one-way functional data, but also two-way (or bivariate) functional data. In addition, we introduce a new cross validation method for estimating the latent rank of a generalized data matrix. We demonstrate the efficacy of the proposed methods using a comprehensive simulation study. The proposed method is also applied to a real application of the UK mortality study, where data are binomially distributed and two-way functional across age groups and calendar years. The results offer novel insights into the underlying mortality pattern. © 2018, The International Biometric Society.

1-norm support vector novelty detection and its sparseness.

PubMed

Zhang, Li; Zhou, WeiDa

2013-12-01

This paper proposes a 1-norm support vector novelty detection (SVND) method and discusses its sparseness. 1-norm SVND is formulated as a linear programming problem and uses two techniques for inducing sparseness, or the 1-norm regularization and the hinge loss function. We also find two upper bounds on the sparseness of 1-norm SVND, or exact support vector (ESV) and kernel Gram matrix rank bounds. The ESV bound indicates that 1-norm SVND has a sparser representation model than SVND. The kernel Gram matrix rank bound can loosely estimate the sparseness of 1-norm SVND. Experimental results show that 1-norm SVND is feasible and effective. Copyright © 2013 Elsevier Ltd. All rights reserved.

Power and sample size evaluation for the Cochran-Mantel-Haenszel mean score (Wilcoxon rank sum) test and the Cochran-Armitage test for trend.

PubMed

Lachin, John M

2011-11-10

The power of a chi-square test, and thus the required sample size, are a function of the noncentrality parameter that can be obtained as the limiting expectation of the test statistic under an alternative hypothesis specification. Herein, we apply this principle to derive simple expressions for two tests that are commonly applied to discrete ordinal data. The Wilcoxon rank sum test for the equality of distributions in two groups is algebraically equivalent to the Mann-Whitney test. The Kruskal-Wallis test applies to multiple groups. These tests are equivalent to a Cochran-Mantel-Haenszel mean score test using rank scores for a set of C-discrete categories. Although various authors have assessed the power function of the Wilcoxon and Mann-Whitney tests, herein it is shown that the power of these tests with discrete observations, that is, with tied ranks, is readily provided by the power function of the corresponding Cochran-Mantel-Haenszel mean scores test for two and R > 2 groups. These expressions yield results virtually identical to those derived previously for rank scores and also apply to other score functions. The Cochran-Armitage test for trend assesses whether there is an monotonically increasing or decreasing trend in the proportions with a positive outcome or response over the C-ordered categories of an ordinal independent variable, for example, dose. Herein, it is shown that the power of the test is a function of the slope of the response probabilities over the ordinal scores assigned to the groups that yields simple expressions for the power of the test. Copyright © 2011 John Wiley & Sons, Ltd.

Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

NASA Astrophysics Data System (ADS)

Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

2018-02-01

Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data.

PubMed

Taugourdeau, Simon; Villerd, Jean; Plantureux, Sylvain; Huguenin-Elie, Olivier; Amiaud, Bernard

2014-04-01

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete-case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete-case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices.

Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data

PubMed Central

Taugourdeau, Simon; Villerd, Jean; Plantureux, Sylvain; Huguenin-Elie, Olivier; Amiaud, Bernard

2014-01-01

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete-case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete-case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices. PMID:24772273

Job strain, rank, and mental health in the UK Armed Forces.

PubMed

Fear, Nicola Townsend; Rubin, G James; Hatch, Stephani; Hull, Lisa; Jones, Margaret; Hotopf, Matthew; Wessely, Simon; Rona, Roberto J

2009-01-01

We assessed whether job demand and job control have independent effects on psychological symptoms or whether job control modifies effect of job demand; we also assessed whether rank modified associations between job strain and psychological symptoms. We used the Post Traumatic Stress Disorder (PTSD) Checklist (PCL-C), General Health Questionnaire-12 (GHQ-12), Chalder Fatigue Scale, a checklist of 53 physical symptoms, and the WHO's Alcohol Use Disorders Identification Test (AUDIT). Job control, job demand, and rank were independently associated with PTSD, common mental disorders, multiple physical symptoms, and fatigue, but not with severe alcohol problems. Job control and demand had additive effects on psychological symptoms. Commissioned officers had lower risk of caseness for psychological symptoms than other ranks. Adjustment for rank had negligible effect on level of association between job strain and psychological symptoms. Reported job strain and rank contributed independently to psychological symptoms.

Low rank approximation in G 0W 0 calculations

DOE PAGES

Shao, MeiYue; Lin, Lin; Yang, Chao; ...

2016-06-04

The single particle energies obtained in a Kohn-Sham density functional theory (DFT) calculation are generally known to be poor approximations to electron excitation energies that are measured in tr ansport, tunneling and spectroscopic experiments such as photo-emission spectroscopy. The correction to these energies can be obtained from the poles of a single particle Green’s function derived from a many-body perturbation theory. From a computational perspective, the accuracy and efficiency of such an approach depends on how a self energy term that properly accounts for dynamic screening of electrons is approximated. The G 0W 0 approximation is a widely used techniquemore » in which the self energy is expressed as the convolution of a noninteracting Green’s function (G 0) and a screened Coulomb interaction (W 0) in the frequency domain. The computational cost associated with such a convolution is high due to the high complexity of evaluating W 0 at multiple frequencies. In this paper, we discuss how the cost of G 0W 0 calculation can be reduced by constructing a low rank approximation to the frequency dependent part of W 0 . In particular, we examine the effect of such a low rank approximation on the accuracy of the G 0W 0 approximation. We also discuss how the numerical convolution of G 0 and W 0 can be evaluated efficiently and accurately by using a contour deformation technique with an appropriate choice of the contour.« less

A Ranking Approach on Large-Scale Graph With Multidimensional Heterogeneous Information.

PubMed

Wei, Wei; Gao, Bin; Liu, Tie-Yan; Wang, Taifeng; Li, Guohui; Li, Hang

2016-04-01

Graph-based ranking has been extensively studied and frequently applied in many applications, such as webpage ranking. It aims at mining potentially valuable information from the raw graph-structured data. Recently, with the proliferation of rich heterogeneous information (e.g., node/edge features and prior knowledge) available in many real-world graphs, how to effectively and efficiently leverage all information to improve the ranking performance becomes a new challenging problem. Previous methods only utilize part of such information and attempt to rank graph nodes according to link-based methods, of which the ranking performances are severely affected by several well-known issues, e.g., over-fitting or high computational complexity, especially when the scale of graph is very large. In this paper, we address the large-scale graph-based ranking problem and focus on how to effectively exploit rich heterogeneous information of the graph to improve the ranking performance. Specifically, we propose an innovative and effective semi-supervised PageRank (SSP) approach to parameterize the derived information within a unified semi-supervised learning framework (SSLF-GR), then simultaneously optimize the parameters and the ranking scores of graph nodes. Experiments on the real-world large-scale graphs demonstrate that our method significantly outperforms the algorithms that consider such graph information only partially.

Objective criteria ranking framework for renewable energy policy decisions in Nigeria

NASA Astrophysics Data System (ADS)

K, Nwofor O.; N, Dike V.

2016-08-01

We present a framework that seeks to improve the objectivity of renewable energy policy decisions in Nigeria. It consists of expert ranking of resource abundance, resource efficiency and resource environmental comfort in the choice of renewable energy options for large scale power generation. The rankings are converted to a more objective function called Resource Appraisal Function (RAF) using dependence operators derived from logical relationships amongst the various criteria. The preferred option is that with the highest average RAF coupled with the least RAF variance. The method can be extended to more options, more criteria, and more opinions and can be adapted for similar decisions in education, environment and health sectors.

Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green's function theory

NASA Astrophysics Data System (ADS)

Rai, Prashant; Sargsyan, Khachik; Najm, Habib; Hermes, Matthew R.; Hirata, So

2017-09-01

A new method is proposed for a fast evaluation of high-dimensional integrals of potential energy surfaces (PES) that arise in many areas of quantum dynamics. It decomposes a PES into a canonical low-rank tensor format, reducing its integral into a relatively short sum of products of low-dimensional integrals. The decomposition is achieved by the alternating least squares (ALS) algorithm, requiring only a small number of single-point energy evaluations. Therefore, it eradicates a force-constant evaluation as the hotspot of many quantum dynamics simulations and also possibly lifts the curse of dimensionality. This general method is applied to the anharmonic vibrational zero-point and transition energy calculations of molecules using the second-order diagrammatic vibrational many-body Green's function (XVH2) theory with a harmonic-approximation reference. In this application, high dimensional PES and Green's functions are both subjected to a low-rank decomposition. Evaluating the molecular integrals over a low-rank PES and Green's functions as sums of low-dimensional integrals using the Gauss-Hermite quadrature, this canonical-tensor-decomposition-based XVH2 (CT-XVH2) achieves an accuracy of 0.1 cm-1 or higher and nearly an order of magnitude speedup as compared with the original algorithm using force constants for water and formaldehyde.

Influence of weather, rank, and home advantage on football outcomes in the Gulf region.

PubMed

Brocherie, Franck; Girard, Olivier; Farooq, Abdulaziz; Millet, Grégoire P

2015-02-01

The objective of this study was to investigate the effects of weather, rank, and home advantage on international football match results and scores in the Gulf Cooperation Council (GCC) region. Football matches (n = 2008) in six GCC countries were analyzed. To determine the weather influence on the likelihood of favorable outcome and goal difference, generalized linear model with a logit link function and multiple regression analysis were performed. In the GCC region, home teams tend to have greater likelihood of a favorable outcome (P < 0.001) and higher goal difference (P < 0.001). Temperature difference was identified as a significant explanatory variable when used independently (P < 0.001) or after adjustment for home advantage and team ranking (P < 0.001). The likelihood of favorable outcome for GCC teams increases by 3% for every 1-unit increase in temperature difference. After inclusion of interaction with opposition, this advantage remains significant only when playing against non-GCC opponents. While home advantage increased the odds of favorable outcome (P < 0.001) and goal difference (P < 0.001) after inclusion of interaction term, the likelihood of favorable outcome for a GCC team decreased (P < 0.001) when playing against a stronger opponent. Finally, the temperature and wet bulb globe temperature approximation were found as better indicators of the effect of environmental conditions than absolute and relative humidity or heat index on match outcomes. In GCC region, higher temperature increased the likelihood of a favorable outcome when playing against non-GCC teams. However, international ranking should be considered because an opponent with a higher rank reduced, but did not eliminate, the likelihood of a favorable outcome.

RANKL/RANK interaction promotes the growth of cervical cancer cells by strengthening the dialogue between cervical cancer cells and regulation of IL-8 secretion.

PubMed

Shang, Wen-Qing; Li, Hui; Liu, Li-Bing; Chang, Kai-Kai; Yu, Jia-Jun; Xie, Feng; Li, Ming-Qing; Yu, Jin-Jin

2015-12-01

Receptor activator for nuclear factor κB ligand (RANKL) is a member of the tumor necrosis factor (TNF) family. The interaction between RANKL and its receptor RANK plays an important role in the development and function of diverse tissues. However, the expression and role of RANKL in cervical cancer are still unknown. In the present study, we found that RANKL and RANK were highly co-expressed in cervical cancer. HeLa and SiHa cells secreted soluble RANKL (sRANKL), expressed member RANKL (mRANKL) and RANK. Recombinant human RANKL protein had no effect on the viability of HeLa and SiHa cells. Yet, blocking RANKL with an anti-human RANKL neutralizing antibody (α-RANKL) or recombinant human osteoprotegrin (OPG) protein resulted in the downregulation of Ki-67 and B-cell lymphoma 2 (Bcl-2) expression and an increase in Fas and Fas ligand (FasL) expression, as well as a high level of viability and a low level of apoptosis in the HeLa and SiHa cells. In addition, α-RANKL led to a decrease in IL-8 secretion. Recombinant human IL-8 protein reversed the effect of α-RANKL on the expression of proliferation- and apoptosis‑related molecules, and proliferation and apoptosis in the HeLa and SiHa cells. The present study suggests that a high level of mRANKL/RANK expression in cervical cancer lesions plays an important role in the rapid growth of cervical cancer cells possibly through strengthening the dialogue between cervical cancer cells and regulation of IL-8 secretion, which may be a possible target for cervical cancer therapy.

Identifying online user reputation of user-object bipartite networks

NASA Astrophysics Data System (ADS)

Liu, Xiao-Lu; Liu, Jian-Guo; Yang, Kai; Guo, Qiang; Han, Jing-Ti

2017-02-01

Identifying online user reputation based on the rating information of the user-object bipartite networks is important for understanding online user collective behaviors. Based on the Bayesian analysis, we present a parameter-free algorithm for ranking online user reputation, where the user reputation is calculated based on the probability that their ratings are consistent with the main part of all user opinions. The experimental results show that the AUC values of the presented algorithm could reach 0.8929 and 0.8483 for the MovieLens and Netflix data sets, respectively, which is better than the results generated by the CR and IARR methods. Furthermore, the experimental results for different user groups indicate that the presented algorithm outperforms the iterative ranking methods in both ranking accuracy and computation complexity. Moreover, the results for the synthetic networks show that the computation complexity of the presented algorithm is a linear function of the network size, which suggests that the presented algorithm is very effective and efficient for the large scale dynamic online systems.

Group sequential monitoring based on the weighted log-rank test statistic with the Fleming-Harrington class of weights in cancer vaccine studies.

PubMed

Hasegawa, Takahiro

2016-09-01

In recent years, immunological science has evolved, and cancer vaccines are now approved and available for treating existing cancers. Because cancer vaccines require time to elicit an immune response, a delayed treatment effect is expected and is actually observed in drug approval studies. Accordingly, we propose the evaluation of survival endpoints by weighted log-rank tests with the Fleming-Harrington class of weights. We consider group sequential monitoring, which allows early efficacy stopping, and determine a semiparametric information fraction for the Fleming-Harrington family of weights, which is necessary for the error spending function. Moreover, we give a flexible survival model in cancer vaccine studies that considers not only the delayed treatment effect but also the long-term survivors. In a Monte Carlo simulation study, we illustrate that when the primary analysis is a weighted log-rank test emphasizing the late differences, the proposed information fraction can be a useful alternative to the surrogate information fraction, which is proportional to the number of events. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Thermolysis of phenethyl phenyl ether: A model of ether linkages in low rank coal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Britt, P.F.; Buchanan, A.C. III; Malcolm, E.A.

Currently, an area of interest and frustration for coal chemists has been the direct liquefaction of low rank coal. Although low rank coals are more reactive than bituminous coals, they are more difficult to liquefy and offer lower liquefaction yields under conditions optimized for bituminous coals. Solomon, Serio, and co-workers have shown that: in the pyrolysis and liquefaction of low rank coals, a low temperature cross-linking reaction associated with oxygen functional groups occurs before tar evolution. A variety of pretreatments (demineralization, alkylation, and ion-exchange) have been shown to reduce these retrogressive reactions and increase tar yields, but the actual chemicalmore » reactions responsible for these processes have not been defined. In order to gain insight into the thermochemical reactions leading to cross-linking in low rank coal, we have undertaken a study of the pyrolysis of oxygen containing coal model compounds. Solid state NMR studies suggest that the alkyl aryl ether linkage may be present in modest amounts in low rank coal. Therefore, in this paper, we will investigate the thermolysis of phenethyl phenyl ether (PPE) as a model of 0-aryl ether linkages found in low rank coal, lignites, and lignin, an evolutionary precursor of coal. Our results have uncovered a new reaction channel that can account for 25% of the products formed. The impact of reaction conditions, including restricted mass transport, on this new reaction pathway and the role of oxygen functional groups in cross-linking reactions will be investigated.« less

Reconsidering the use of rankings in the valuation of health states: a model for estimating cardinal values from ordinal data

PubMed Central

Salomon, Joshua A

2003-01-01

Background In survey studies on health-state valuations, ordinal ranking exercises often are used as precursors to other elicitation methods such as the time trade-off (TTO) or standard gamble, but the ranking data have not been used in deriving cardinal valuations. This study reconsiders the role of ordinal ranks in valuing health and introduces a new approach to estimate interval-scaled valuations based on aggregate ranking data. Methods Analyses were undertaken on data from a previously published general population survey study in the United Kingdom that included rankings and TTO values for hypothetical states described using the EQ-5D classification system. The EQ-5D includes five domains (mobility, self-care, usual activities, pain/discomfort and anxiety/depression) with three possible levels on each. Rank data were analysed using a random utility model, operationalized through conditional logit regression. In the statistical model, probabilities of observed rankings were related to the latent utilities of different health states, modeled as a linear function of EQ-5D domain scores, as in previously reported EQ-5D valuation functions. Predicted valuations based on the conditional logit model were compared to observed TTO values for the 42 states in the study and to predictions based on a model estimated directly from the TTO values. Models were evaluated using the intraclass correlation coefficient (ICC) between predictions and mean observations, and the root mean squared error of predictions at the individual level. Results Agreement between predicted valuations from the rank model and observed TTO values was very high, with an ICC of 0.97, only marginally lower than for predictions based on the model estimated directly from TTO values (ICC = 0.99). Individual-level errors were also comparable in the two models, with root mean squared errors of 0.503 and 0.496 for the rank-based and TTO-based predictions, respectively. Conclusions Modeling health-state valuations based on ordinal ranks can provide results that are similar to those obtained from more widely analyzed valuation techniques such as the TTO. The information content in aggregate ranking data is not currently exploited to full advantage. The possibility of estimating cardinal valuations from ordinal ranks could also simplify future data collection dramatically and facilitate wider empirical study of health-state valuations in diverse settings and population groups. PMID:14687419

Global University Rankings--Impacts and Unintended Side Effects

ERIC Educational Resources Information Center

Kehm, Barbara M.

2014-01-01

In this article, global and other university rankings are critically assessed with regard to their unintended side effects and their impacts on the European and national landscape of universities, as well as on individual institutions. An emphasis is put on the effects of ranking logics rather than on criticising their methodology. Nevertheless,…

A General Class of Signed Rank Tests for Clustered Data when the Cluster Size is Potentially Informative

PubMed Central

Datta, Somnath; Nevalainen, Jaakko; Oja, Hannu

2012-01-01

SUMMARY Rank based tests are alternatives to likelihood based tests popularized by their relative robustness and underlying elegant mathematical theory. There has been a serge in research activities in this area in recent years since a number of researchers are working to develop and extend rank based procedures to clustered dependent data which include situations with known correlation structures (e.g., as in mixed effects models) as well as more general form of dependence. The purpose of this paper is to test the symmetry of a marginal distribution under clustered data. However, unlike most other papers in the area, we consider the possibility that the cluster size is a random variable whose distribution is dependent on the distribution of the variable of interest within a cluster. This situation typically arises when the clusters are defined in a natural way (e.g., not controlled by the experimenter or statistician) and in which the size of the cluster may carry information about the distribution of data values within a cluster. Under the scenario of an informative cluster size, attempts to use some form of variance adjusted sign or signed rank tests would fail since they would not maintain the correct size under the distribution of marginal symmetry. To overcome this difficulty Datta and Satten (2008; Biometrics, 64, 501–507) proposed a Wilcoxon type signed rank test based on the principle of within cluster resampling. In this paper we study this problem in more generality by introducing a class of valid tests employing a general score function. Asymptotic null distribution of these tests is obtained. A simulation study shows that a more general choice of the score function can sometimes result in greater power than the Datta and Satten test; furthermore, this development offers the user a wider choice. We illustrate our tests using a real data example on spinal cord injury patients. PMID:23074359

A General Class of Signed Rank Tests for Clustered Data when the Cluster Size is Potentially Informative.

PubMed

Datta, Somnath; Nevalainen, Jaakko; Oja, Hannu

2012-09-01

Rank based tests are alternatives to likelihood based tests popularized by their relative robustness and underlying elegant mathematical theory. There has been a serge in research activities in this area in recent years since a number of researchers are working to develop and extend rank based procedures to clustered dependent data which include situations with known correlation structures (e.g., as in mixed effects models) as well as more general form of dependence.The purpose of this paper is to test the symmetry of a marginal distribution under clustered data. However, unlike most other papers in the area, we consider the possibility that the cluster size is a random variable whose distribution is dependent on the distribution of the variable of interest within a cluster. This situation typically arises when the clusters are defined in a natural way (e.g., not controlled by the experimenter or statistician) and in which the size of the cluster may carry information about the distribution of data values within a cluster.Under the scenario of an informative cluster size, attempts to use some form of variance adjusted sign or signed rank tests would fail since they would not maintain the correct size under the distribution of marginal symmetry. To overcome this difficulty Datta and Satten (2008; Biometrics, 64, 501-507) proposed a Wilcoxon type signed rank test based on the principle of within cluster resampling. In this paper we study this problem in more generality by introducing a class of valid tests employing a general score function. Asymptotic null distribution of these tests is obtained. A simulation study shows that a more general choice of the score function can sometimes result in greater power than the Datta and Satten test; furthermore, this development offers the user a wider choice. We illustrate our tests using a real data example on spinal cord injury patients.

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

PubMed

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. Published by Elsevier Inc. All rights reserved.

Moving object detection via low-rank total variation regularization

NASA Astrophysics Data System (ADS)

Wang, Pengcheng; Chen, Qian; Shao, Na

2016-09-01

Moving object detection is a challenging task in video surveillance. Recently proposed Robust Principal Component Analysis (RPCA) can recover the outlier patterns from the low-rank data under some mild conditions. However, the l-penalty in RPCA doesn't work well in moving object detection because the irrepresentable condition is often not satisfied. In this paper, a method based on total variation (TV) regularization scheme is proposed. In our model, image sequences captured with a static camera are highly related, which can be described using a low-rank matrix. Meanwhile, the low-rank matrix can absorb background motion, e.g. periodic and random perturbation. The foreground objects in the sequence are usually sparsely distributed and drifting continuously, and can be treated as group outliers from the highly-related background scenes. Instead of l-penalty, we exploit the total variation of the foreground. By minimizing the total variation energy, the outliers tend to collapse and finally converge to be the exact moving objects. The TV-penalty is superior to the l-penalty especially when the outlier is in the majority for some pixels, and our method can estimate the outlier explicitly with less bias but higher variance. To solve the problem, a joint optimization function is formulated and can be effectively solved through the inexact Augmented Lagrange Multiplier (ALM) method. We evaluate our method along with several state-of-the-art approaches in MATLAB. Both qualitative and quantitative results demonstrate that our proposed method works effectively on a large range of complex scenarios.

Identification of symptom and functional domains that fibromyalgia patients would like to see improved: a cluster analysis.

PubMed

Bennett, Robert M; Russell, Jon; Cappelleri, Joseph C; Bushmakin, Andrew G; Zlateva, Gergana; Sadosky, Alesia

2010-06-28

The purpose of this study was to determine whether some of the clinical features of fibromyalgia (FM) that patients would like to see improved aggregate into definable clusters. Seven hundred and eighty-eight patients with clinically confirmed FM and baseline pain > or =40 mm on a 100 mm visual analogue scale ranked 5 FM clinical features that the subjects would most like to see improved after treatment (one for each priority quintile) from a list of 20 developed during focus groups. For each subject, clinical features were transformed into vectors with rankings assigned values 1-5 (lowest to highest ranking). Logistic analysis was used to create a distance matrix and hierarchical cluster analysis was applied to identify cluster structure. The frequency of cluster selection was determined, and cluster importance was ranked using cluster scores derived from rankings of the clinical features. Multidimensional scaling was used to visualize and conceptualize cluster relationships. Six clinical features clusters were identified and named based on their key characteristics. In order of selection frequency, the clusters were Pain (90%; 4 clinical features), Fatigue (89%; 4 clinical features), Domestic (42%; 4 clinical features), Impairment (29%; 3 functions), Affective (21%; 3 clinical features), and Social (9%; 2 functional). The "Pain Cluster" was ranked of greatest importance by 54% of subjects, followed by Fatigue, which was given the highest ranking by 28% of subjects. Multidimensional scaling mapped these clusters to two dimensions: Status (bounded by Physical and Emotional domains), and Setting (bounded by Individual and Group interactions). Common clinical features of FM could be grouped into 6 clusters (Pain, Fatigue, Domestic, Impairment, Affective, and Social) based on patient perception of relevance to treatment. Furthermore, these 6 clusters could be charted in the 2 dimensions of Status and Setting, thus providing a unique perspective for interpretation of FM symptomatology.

The effect of unfavourable and favourable social comparisons on paranoid ideation: An experimental study.

PubMed

Ascone, Leonie; Jaya, Edo S; Lincoln, Tania M

2017-09-01

Low social rank is associated with paranoia, but there is a lack of evidence for causality. We tested the effects of social comparisons on negative affect and paranoia with an online social rank paradigm, and whether striving to avoid inferiority or fears of social rejection moderated paranoid reactions. Female students (N = 172) were randomly exposed to one of two validated online profiles depicting a same-aged, high (unfavourable comparison) vs. low rank (favourable comparison) female student. Moderators were assessed at baseline. Social rank, anxiety, sadness and paranoia were assessed pre and post profile-exposure. There was a large effect of the experimental manipulation on social rank (p < 0.001, η 2 partial  = 0.191). The manipulations had no effects on anxiety and paranoia (p > 0.38). Sadness was significantly altered (p = 0.016, η 2 partial  = 0.033). There were significant moderation effects between the experimental conditions and insecure striving (trend-level) as well as fears of rejection. Our findings may be biased (overestimation of effects) as students are likely to be more competitive compared to the general population. Our rank manipulations did not alter paranoia. This suggests that changes in the cognitive representation of social rank alone - without triggering a strong emotional response - do not suffice to evoke paranoia. Although our results do not support the notion that threats to social rank cause paranoid symptoms, they suggest that threats to social rank are more likely to trigger paranoid states in those who are insecure in regard to their social position. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed Central

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

2017-01-01

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. PMID:28448451

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

PubMed

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.

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

PubMed

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

What Contributes More to the Ranking of Higher Education Institutions? A Comparison of Three World University Rankings

ERIC Educational Resources Information Center

Hou, Ya-Wen; Jacob, W. James

2017-01-01

Recently, many universities have drawn attention to world university rankings, which reflect the international competition of universities and represent their relative statuses. This study does not radically contradict types of global university rankings but calls for an examination of the effects of their indicators on the final ranking of…

Strengths of balloon films with flaws and repairs

NASA Technical Reports Server (NTRS)

Portanova, M. A.

1989-01-01

The effects of manufacture flaws and repairs in high altitude scientific balloons was examined. A right circular cylinder was used to induce a biaxial tension-tension stress field in the polyethlene film used to manufacture these balloons. A preliminary investigation of the effect that cylinder geometry has on stress rate as a function of inflation rate was conducted. The ultimate goal was to rank, by order of degrading effects, the flaws and repairs commonly found in current high altitude balloons.

IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking

PubMed Central

2014-01-01

Background Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones. In this paper, we propose a new re-ranking technique using a new energy-based scoring function, namely IFACEwat - a combined Interface Atomic Contact Energy (IFACE) and water effect. The IFACEwat aims to further improve the discrimination of the near-native structures of the initial rigid docking algorithm ZDOCK3.0.2. Unlike other re-ranking techniques, the IFACEwat explicitly implements interfacial water into the protein interfaces to account for the water-mediated contacts during the protein interactions. Results Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F2Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes. Conclusions With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near native structures found. As our implementation so far targeted to improve the results of ZDOCK3.0.2, and particularly for the Antigen/Antibody complexes, it is expected in the near future that more implementations will be conducted to be applicable for other initial rigid docking algorithms. PMID:25521441

A solution to Schroder's equation in several variables

DOE PAGES

Bridges, Robert A.

2016-03-04

For this paper, let φ be an analytic self-map of the n -ball, having 0 as the attracting fixed point and having full-rank near 0. We consider the generalized Schroder's equation, F °φ=φ'(0) kF with ka positive integer and prove there is always a solution F with linearly independent component functions, but that such an F cannot have full rank except possibly when k=1. Furthermore, when k=1 (Schroder's equation), necessary and sufficient conditions on φ are given to ensure F has full rank near 0 without the added assumption of diagonalizability as needed in the 2003 Cowen/MacCluer paper. In responsemore » to Enoch's 2007 paper, it is proven that any formal power series solution indeed represents an analytic function on the whole unit ball. Finally, how exactly resonance can lead to an obstruction of a full rank solution is discussed as well as some consequences of having solutions to Schroder's equation.« less

Robust subspace clustering via joint weighted Schatten-p norm and Lq norm minimization

NASA Astrophysics Data System (ADS)

Zhang, Tao; Tang, Zhenmin; Liu, Qing

2017-05-01

Low-rank representation (LRR) has been successfully applied to subspace clustering. However, the nuclear norm in the standard LRR is not optimal for approximating the rank function in many real-world applications. Meanwhile, the L21 norm in LRR also fails to characterize various noises properly. To address the above issues, we propose an improved LRR method, which achieves low rank property via the new formulation with weighted Schatten-p norm and Lq norm (WSPQ). Specifically, the nuclear norm is generalized to be the Schatten-p norm and different weights are assigned to the singular values, and thus it can approximate the rank function more accurately. In addition, Lq norm is further incorporated into WSPQ to model different noises and improve the robustness. An efficient algorithm based on the inexact augmented Lagrange multiplier method is designed for the formulated problem. Extensive experiments on face clustering and motion segmentation clearly demonstrate the superiority of the proposed WSPQ over several state-of-the-art methods.

Scaling properties of marathon races

NASA Astrophysics Data System (ADS)

Alvarez-Ramirez, Jose; Rodriguez, Eduardo

2006-06-01

Some regularities in popular marathon races are identified in this paper. It is found for high-performance participants (i.e., racing times in the range [2:15,3:15] h), the average velocity as a function of the marathoner's ranking behaves as a power-law, which may be suggesting the presence of critical phenomena. Elite marathoners with racing times below 2:15 h can be considered as outliers with respect to this behavior. For the main marathon pack (i.e., racing times in the range [3:00,6:00] h), the average velocity as a function of the marathoner's ranking behaves linearly. For this racing times, the interpersonal velocity, defined as the difference of velocities between consecutive runners, displays a continuum of scaling behavior ranging from uncorrelated noise for small scales to correlated 1/f-noise for large scales. It is a matter of fact that 1/f-noise is characterized by correlations extended over a wide range of scales, a clear indication of some sort of cooperative effect.

Fuzzy bi-objective linear programming for portfolio selection problem with magnitude ranking function

NASA Astrophysics Data System (ADS)

Kusumawati, Rosita; Subekti, Retno

2017-04-01

Fuzzy bi-objective linear programming (FBOLP) model is bi-objective linear programming model in fuzzy number set where the coefficients of the equations are fuzzy number. This model is proposed to solve portfolio selection problem which generate an asset portfolio with the lowest risk and the highest expected return. FBOLP model with normal fuzzy numbers for risk and expected return of stocks is transformed into linear programming (LP) model using magnitude ranking function.

Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green's function theory

DOE PAGES

Rai, Prashant; Sargsyan, Khachik; Najm, Habib; ...

2017-03-07

Here, a new method is proposed for a fast evaluation of high-dimensional integrals of potential energy surfaces (PES) that arise in many areas of quantum dynamics. It decomposes a PES into a canonical low-rank tensor format, reducing its integral into a relatively short sum of products of low-dimensional integrals. The decomposition is achieved by the alternating least squares (ALS) algorithm, requiring only a small number of single-point energy evaluations. Therefore, it eradicates a force-constant evaluation as the hotspot of many quantum dynamics simulations and also possibly lifts the curse of dimensionality. This general method is applied to the anharmonic vibrationalmore » zero-point and transition energy calculations of molecules using the second-order diagrammatic vibrational many-body Green's function (XVH2) theory with a harmonic-approximation reference. In this application, high dimensional PES and Green's functions are both subjected to a low-rank decomposition. Evaluating the molecular integrals over a low-rank PES and Green's functions as sums of low-dimensional integrals using the Gauss–Hermite quadrature, this canonical-tensor-decomposition-based XVH2 (CT-XVH2) achieves an accuracy of 0.1 cm -1 or higher and nearly an order of magnitude speedup as compared with the original algorithm using force constants for water and formaldehyde.« less

Low-rank canonical-tensor decomposition of potential energy surfaces: application to grid-based diagrammatic vibrational Green's function theory

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rai, Prashant; Sargsyan, Khachik; Najm, Habib

Here, a new method is proposed for a fast evaluation of high-dimensional integrals of potential energy surfaces (PES) that arise in many areas of quantum dynamics. It decomposes a PES into a canonical low-rank tensor format, reducing its integral into a relatively short sum of products of low-dimensional integrals. The decomposition is achieved by the alternating least squares (ALS) algorithm, requiring only a small number of single-point energy evaluations. Therefore, it eradicates a force-constant evaluation as the hotspot of many quantum dynamics simulations and also possibly lifts the curse of dimensionality. This general method is applied to the anharmonic vibrationalmore » zero-point and transition energy calculations of molecules using the second-order diagrammatic vibrational many-body Green's function (XVH2) theory with a harmonic-approximation reference. In this application, high dimensional PES and Green's functions are both subjected to a low-rank decomposition. Evaluating the molecular integrals over a low-rank PES and Green's functions as sums of low-dimensional integrals using the Gauss–Hermite quadrature, this canonical-tensor-decomposition-based XVH2 (CT-XVH2) achieves an accuracy of 0.1 cm -1 or higher and nearly an order of magnitude speedup as compared with the original algorithm using force constants for water and formaldehyde.« less

Clinical prognostic significance and pro-metastatic activity of RANK/RANKL via the AKT pathway in endometrial cancer.

PubMed

Wang, Jing; Liu, Yao; Wang, Lihua; Sun, Xiao; Wang, Yudong

2016-02-02

RANK/RANKL plays a key role in metastasis of certain malignant tumors, which makes it a promising target for developing novel therapeutic strategies for cancer. However, the prognostic value and pro-metastatic activity of RANK in endometrial cancer (EC) remain to be determined. Thus, the present study investigated the effect of RANK on the prognosis of EC patients, as well as the pro-metastatic activity of EC cells. The results indicated that those with high expression of RANK showed decreased overall survival and progression-free survival. Statistical analysis revealed the positive correlations between RANK/RANKL expression and metastasis-related factors. Additionally, RANK/RANKL significantly promoted cell migration/invasion via activating AKT/β-catenin/Snail pathway in vitro. However, RANK/RANKL-induced AKT activation could be suppressed after osteoprotegerin (OPG) treatment. Furthermore, the combination of medroxyprogesterone acetate (MPA) and RANKL could in turn attenuate the effect of RANKL alone. Similarly, MPA could partially inhibit the RANK-induced metastasis in an orthotopic mouse model via suppressing AKT/β-catenin/Snail pathway. Therefore, therapeutic inhibition of MPA in RANK/RANKL-induced metastasis was mediated by AKT/β-catenin/Snail pathway both in vitro and in vivo, suggesting a potential target of RANK for gene-based therapy for EC.

Modeling the leaf angle dynamics in rice plant.

PubMed

Zhang, Yonghui; Tang, Liang; Liu, Xiaojun; Liu, Leilei; Cao, Weixing; Zhu, Yan

2017-01-01

The leaf angle between stem and sheath (SSA) is an important rice morphological trait. The objective of this study was to develop and validate a dynamic SSA model under different nitrogen (N) rates for selected rice cultivars. The time-course data of SSA were collected in three years, and a dynamic SSA model was developed for different main stem leaf ranks under different N rates for two selected rice cultivars. SSA increased with tiller age. The SSA of the same leaf rank increased with increase in N rate. The maximum SSA increased with leaf rank from the first to the third leaf, then decreased from the third to the final leaf. The relationship between the maximum SSA and leaf rank on main stem could be described with a linear piecewise function. The change of SSA with thermal time (TT) was described by a logistic equation. A variety parameter (the maximum SSA of the 3rd leaf on main stem) and a nitrogen factor were introduced to quantify the effect of cultivar and N rate on SSA. The model was validated against data collected from both pot and field experiments. The relative root mean square error (RRMSE) was 11.56% and 14.05%, respectively. The resulting models could be used for virtual rice plant modeling and plant-type design.

Prescribed fire effects in a longleaf pine ecosystem--are winter fires working?

Treesearch

Rebecca J. Barlow; John S. Kush; John C. Gilbert; Sharon M. Hermann

2015-01-01

Longleaf pine (Pinus palustris Mill.) ecosystems once dominated 60 to 90 million acres and supported one of the most diverse floras in North America. It is well-known that longleaf pine ecosystems must burn frequently to maintain natural structure and function. This vegetation type ranks as one of the most fire-dependent in the country and must...

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

PubMed Central

2015-01-01

Retinal fundus images are widely used in diagnosing and providing treatment for several eye diseases. Prior works using retinal fundus images detected the presence of exudation with the aid of publicly available dataset using extensive segmentation process. Though it was proved to be computationally efficient, it failed to create a diabetic retinopathy feature selection system for transparently diagnosing the disease state. Also the diagnosis of diseases did not employ machine learning methods to categorize candidate fundus images into true positive and true negative ratio. Several candidate fundus images did not include more detailed feature selection technique for diabetic retinopathy. To apply machine learning methods and classify the candidate fundus images on the basis of sliding window a method called, Diabetic Fundus Image Recuperation (DFIR) is designed in this paper. The initial phase of DFIR method select the feature of optic cup in digital retinal fundus images based on Sliding Window Approach. With this, the disease state for diabetic retinopathy is assessed. The feature selection in DFIR method uses collection of sliding windows to obtain the features based on the histogram value. The histogram based feature selection with the aid of Group Sparsity Non-overlapping function provides more detailed information of features. Using Support Vector Model in the second phase, the DFIR method based on Spiral Basis Function effectively ranks the diabetic retinopathy diseases. The ranking of disease level for each candidate set provides a much promising result for developing practically automated diabetic retinopathy diagnosis system. Experimental work on digital fundus images using the DFIR method performs research on the factors such as sensitivity, specificity rate, ranking efficiency and feature selection time. PMID:25974230

Order-disorder transition in conflicting dynamics leading to rank-frequency generalized beta distributions

NASA Astrophysics Data System (ADS)

Alvarez-Martinez, R.; Martinez-Mekler, G.; Cocho, G.

2011-01-01

The behavior of rank-ordered distributions of phenomena present in a variety of fields such as biology, sociology, linguistics, finance and geophysics has been a matter of intense research. Often power laws have been encountered; however, their validity tends to hold mainly for an intermediate range of rank values. In a recent publication (Martínez-Mekler et al., 2009 [7]), a generalization of the functional form of the beta distribution has been shown to give excellent fits for many systems of very diverse nature, valid for the whole range of rank values, regardless of whether or not a power law behavior has been previously suggested. Here we give some insight on the significance of the two free parameters which appear as exponents in the functional form, by looking into discrete probabilistic branching processes with conflicting dynamics. We analyze a variety of realizations of these so-called expansion-modification models first introduced by Wentian Li (1989) [10]. We focus our attention on an order-disorder transition we encounter as we vary the modification probability p. We characterize this transition by means of the fitting parameters. Our numerical studies show that one of the fitting exponents is related to the presence of long-range correlations exhibited by power spectrum scale invariance, while the other registers the effect of disordering elements leading to a breakdown of these properties. In the absence of long-range correlations, this parameter is sensitive to the occurrence of unlikely events. We also introduce an approximate calculation scheme that relates this dynamics to multinomial multiplicative processes. A better understanding through these models of the meaning of the generalized beta-fitting exponents may contribute to their potential for identifying and characterizing universality classes.

An Electromagnetically-Controlled Precision Orbital Tracking Vehicle (POTV)

DTIC Science & Technology

1992-12-01

assume that C > B > A. Then 0 1(t) is purely sinusoidal. tk2 (t) is also sinusoidal because the forcing function z(t) is sinusoidal. 03 (t) is more...an unpredictable -manner. The problem arises from the rank deficiency of the G input matrix as shown below. Remember we have shown already that its...rank can never exceed five because rows two, four, and six are linearly dependent. The rank deficiency arises from the "translational part" of the input

The effect of morphological and functional variables on ranking position of professional junior Basque surfers.

PubMed

Fernández-López, Juan Ramón; Cámara, Jesús; Maldonado, Sara; Rosique-Gracia, Javier

2013-01-01

The aim of this study was to analyse the association of morphology as well as functional outcomes during a paddling test with ranking position (RP) of competitive junior surfers. Ten male surfers (age, mean 17.60, s=2.06 years) performed a maximum incremental test on a modified ergometer (Ergo Vasa Swim, USA) to determine, per unit of weight, the relative heart rate at lactate threshold (RHRLT) and at onset of blood lactate accumulation (RHROBLA) and the relative power output at LT (RWLT) and at OBLA (RWOBLA). Anthropometrics were weight, height and sum of six skinfolds (subscapular, triceps, supraspinal, abdominal, anterior thigh and calf) and Heath-Carter anthropometric somatotypes. A stepwise multiple regression was constructed to model and predict RP. Surfers shared a relative short stature and light weight, with a broader range of skinfold thickness (174.30, s=0.07 cm; 66.73, s=5.91 kg; 57.03, s=12.29 mm) and mean somatotype was ectomorphic-mesomorph: 2.20-4.36-3.09 (Category 2). Two model equations were possible: (A) RP = - 244.550 RWOBLA+262.787; (B) RP = - 217.028·RWOBLA+31.21·endomorphy + 169.16 with 63.1% and 83% of variance explained, respectively. A hierarchical cluster analysis on the Euclidean distances of the variables in model B also distinguished between upper and lower ranking groups. RWOBLA was more useful than endomorphy, anthropometric measures and also than the other functional outcomes to predict RPs. RWOBLA and endomorphy should be considered important variables that may influence the success of these young competitive surfers.

The Impacts of an Observationally-Based Cloud Fraction and Condensate Overlap Parameterization on a GCM's Cloud Radiative Effect

NASA Technical Reports Server (NTRS)

Oreopoulos, Lazaros; Lee, Dongmin; Norris, Peter; Yuan, Tianle

2011-01-01

It has been shown that the details of how cloud fraction overlap is treated in GCMs has substantial impact on shortwave and longwave fluxes. Because cloud condensate is also horizontally heterogeneous at GCM grid scales, another aspect of cloud overlap should in principle also be assessed, namely the vertical overlap of hydrometeor distributions. This type of overlap is usually examined in terms of rank correlations, i.e., linear correlations between hydrometeor amount ranks of the overlapping parts of cloud layers at specific separation distances. The cloud fraction overlap parameter and the rank correlation of hydrometeor amounts can be both expressed as inverse exponential functions of separation distance characterized by their respective decorrelation lengths (e-folding distances). Larger decorrelation lengths mean that hydrometeor fractions and probability distribution functions have high levels of vertical alignment. An analysis of CloudSat and CALIPSO data reveals that the two aspects of cloud overlap are related and their respective decorrelation lengths have a distinct dependence on latitude that can be parameterized and included in a GCM. In our presentation we will contrast the Cloud Radiative Effect (CRE) of the GEOS-5 atmospheric GCM (AGCM) when the observationally-based parameterization of decorrelation lengths is used to represent overlap versus the simpler cases of maximum-random overlap and globally constant decorrelation lengths. The effects of specific overlap representations will be examined for both diagnostic and interactive radiation runs in GEOS-5 and comparisons will be made with observed CREs from CERES and CloudSat (2B-FLXHR product). Since the radiative effects of overlap depend on the cloud property distributions of the AGCM, the availability of two different cloud schemes in GEOS-5 will give us the opportunity to assess a wide range of potential cloud overlap consequences on the model's climate.

Promoted combustion of nine structural metals in high-pressure gaseous oxygen - A comparison of ranking methods

NASA Technical Reports Server (NTRS)

Steinberg, Theodore A.; Rucker, Michelle A.; Beeson, Harold D.

1989-01-01

The 316, 321, 440C, and 17-4 PH stainless steels, as well as Inconel 600, Inconel 718, Waspaloy, Monel 400, and Al 2219, have been evaluated for relative nonflammability in a high-pressure oxygen environment with a view to the comparative advantages of four different flammability-ranking methods. The effects of changes in test pressure, sample diameter, promoter type, and sample configuration on ranking method results are evaluated; ranking methods employing velocity as the primary ranking criterion are limited by diameter effects, while those which use extinguishing pressure are nonselective for metals with similar flammabilities.

Spaceborne power systems preference analyses. Volume 1: Summary

NASA Technical Reports Server (NTRS)

Smith, J. H.; Feinberg, A.; Miles, R. F., Jr.

1985-01-01

Sixteen alternative spaceborne nuclear power system concepts were ranked using multiattribute decision analysis to identify promising concepts for further technology development. Four groups interviewed were: safety, systems definition and design, technology assessment, and mission analysis. The ranking results were consistent from group and for different utility function models for individuals.

"U.S. News & World Report" College Rankings: Modeling Institutional Effects on Organizational Reputation

ERIC Educational Resources Information Center

Bastedo, Michael N.; Bowman, Nicholas A.

2010-01-01

Processes of certification and evaluation are some of the most powerful institutional forces in organizational fields, and in the higher education field, rankings are a primary factor in assessing organizational performance. This article explores the institutional effects of the "U.S. News & World Report" undergraduate rankings on the reputational…

Obtaining Life-Cycle Cost-Effective Facilities in the Department of Defense

DTIC Science & Technology

2013-01-01

8 Step 3: Regional, Service- Level , and OSD Project Ranking...13 2.3. Actors and Barriers to Life-Cycle Cost-Effective Facilities in the Regional, Service- Level , and OSD Project Ranking...Congressional authorization and appropriation OMB evaluation Regional, service- level , and OSD project ranking Economic analysis and DD form 1391 completed

The effect of outpatient physical therapy intervention on pelvic floor muscles in women with urinary incontinence.

PubMed

Knorst, Mara R; Resende, Thais L; Santos, Thaís G; Goldim, José R

2013-01-01

To assess the effect of a weekly, short-term physical therapy intervention on the pelvic floor muscles and urinary incontinence (UI) among patients of the public health system. Quasi-experimental before-and-after study. Clinical history and function evaluation were performed using perineal bidigital maneuvers and perineometry. The intervention consisted of transvaginal electrical stimulation and pelvic floor kinesiotherapy. Data were analyzed using the paired t test or Wilcoxon signed-rank test, Pearson product-moment correlation coefficient or Spearman's rank correlation coefficient. A value of P<0.05 was considered significant. Eight-two women 55.1±10.9 years-old were evaluated. Mixed urinary incontinence (MUI), stress urinary incontinence (SUI) and urge urinary incontinence (UUI) were observed in 52.4%, 36.6% and 11%, respectively. The length of UI was 6.0 years (3.0-10). Approximately 13.64 physical therapy sessions were held on average. There was no difference in perineometry measurements following the intervention (40.6±24.1 versus 41.7±25.4, P=0.098). Muscle function significantly increased (P<0.01) in the bidigital maneuver. The patients reported being continent or satisfied with the treatment in 88.9% of cases. The results demonstrated an increase in muscle function and the attainment of urinary continence or treatment satisfaction in most cases.

The significance of the choice of radiobiological (NTCP) models in treatment plan objective functions.

PubMed

Miller, J; Fuller, M; Vinod, S; Suchowerska, N; Holloway, L

2009-06-01

A Clinician's discrimination between radiation therapy treatment plans is traditionally a subjective process, based on experience and existing protocols. A more objective and quantitative approach to distinguish between treatment plans is to use radiobiological or dosimetric objective functions, based on radiobiological or dosimetric models. The efficacy of models is not well understood, nor is the correlation of the rank of plans resulting from the use of models compared to the traditional subjective approach. One such radiobiological model is the Normal Tissue Complication Probability (NTCP). Dosimetric models or indicators are more accepted in clinical practice. In this study, three radiobiological models, Lyman NTCP, critical volume NTCP and relative seriality NTCP, and three dosimetric models, Mean Lung Dose (MLD) and the Lung volumes irradiated at 10Gy (V10) and 20Gy (V20), were used to rank a series of treatment plans using, harm to normal (Lung) tissue as the objective criterion. None of the models considered in this study showed consistent correlation with the Radiation Oncologists plan ranking. If radiobiological or dosimetric models are to be used in objective functions for lung treatments, based on this study it is recommended that the Lyman NTCP model be used because it will provide most consistency with traditional clinician ranking.

Robust Principal Component Analysis Regularized by Truncated Nuclear Norm for Identifying Differentially Expressed Genes.

PubMed

Wang, Ya-Xuan; Gao, Ying-Lian; Liu, Jin-Xing; Kong, Xiang-Zhen; Li, Hai-Jun

2017-09-01

Identifying differentially expressed genes from the thousands of genes is a challenging task. Robust principal component analysis (RPCA) is an efficient method in the identification of differentially expressed genes. RPCA method uses nuclear norm to approximate the rank function. However, theoretical studies showed that the nuclear norm minimizes all singular values, so it may not be the best solution to approximate the rank function. The truncated nuclear norm is defined as the sum of some smaller singular values, which may achieve a better approximation of the rank function than nuclear norm. In this paper, a novel method is proposed by replacing nuclear norm of RPCA with the truncated nuclear norm, which is named robust principal component analysis regularized by truncated nuclear norm (TRPCA). The method decomposes the observation matrix of genomic data into a low-rank matrix and a sparse matrix. Because the significant genes can be considered as sparse signals, the differentially expressed genes are viewed as the sparse perturbation signals. Thus, the differentially expressed genes can be identified according to the sparse matrix. The experimental results on The Cancer Genome Atlas data illustrate that the TRPCA method outperforms other state-of-the-art methods in the identification of differentially expressed genes.

Machine Learning Estimation of Atom Condensed Fukui Functions.

PubMed

Zhang, Qingyou; Zheng, Fangfang; Zhao, Tanfeng; Qu, Xiaohui; Aires-de-Sousa, João

2016-02-01

To enable the fast estimation of atom condensed Fukui functions, machine learning algorithms were trained with databases of DFT pre-calculated values for ca. 23,000 atoms in organic molecules. The problem was approached as the ranking of atom types with the Bradley-Terry (BT) model, and as the regression of the Fukui function. Random Forests (RF) were trained to predict the condensed Fukui function, to rank atoms in a molecule, and to classify atoms as high/low Fukui function. Atomic descriptors were based on counts of atom types in spheres around the kernel atom. The BT coefficients assigned to atom types enabled the identification (93-94 % accuracy) of the atom with the highest Fukui function in pairs of atoms in the same molecule with differences ≥0.1. In whole molecules, the atom with the top Fukui function could be recognized in ca. 50 % of the cases and, on the average, about 3 of the top 4 atoms could be recognized in a shortlist of 4. Regression RF yielded predictions for test sets with R(2) =0.68-0.69, improving the ability of BT coefficients to rank atoms in a molecule. Atom classification (as high/low Fukui function) was obtained with RF with sensitivity of 55-61 % and specificity of 94-95 %. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Minimizing the semantic gap in biomedical content-based image retrieval

NASA Astrophysics Data System (ADS)

Guan, Haiying; Antani, Sameer; Long, L. Rodney; Thoma, George R.

2010-03-01

A major challenge in biomedical Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings that minimize the semantic gap between the high-level biomedical semantic concepts and the low-level visual features in images. This paper presents a comprehensive learning-based scheme toward meeting this challenge and improving retrieval quality. The article presents two algorithms: a learning-based feature selection and fusion algorithm and the Ranking Support Vector Machine (Ranking SVM) algorithm. The feature selection algorithm aims to select 'good' features and fuse them using different similarity measurements to provide a better representation of the high-level concepts with the low-level image features. Ranking SVM is applied to learn the retrieval rank function and associate the selected low-level features with query concepts, given the ground-truth ranking of the training samples. The proposed scheme addresses four major issues in CBIR to improve the retrieval accuracy: image feature extraction, selection and fusion, similarity measurements, the association of the low-level features with high-level concepts, and the generation of the rank function to support high-level semantic image retrieval. It models the relationship between semantic concepts and image features, and enables retrieval at the semantic level. We apply it to the problem of vertebra shape retrieval from a digitized spine x-ray image set collected by the second National Health and Nutrition Examination Survey (NHANES II). The experimental results show an improvement of up to 41.92% in the mean average precision (MAP) over conventional image similarity computation methods.

iHelp: an intelligent online helpdesk system.

PubMed

Wang, Dingding; Li, Tao; Zhu, Shenghuo; Gong, Yihong

2011-02-01

Due to the importance of high-quality customer service, many companies use intelligent helpdesk systems (e.g., case-based systems) to improve customer service quality. However, these systems face two challenges: 1) Case retrieval measures: most case-based systems use traditional keyword-matching-based ranking schemes for case retrieval and have difficulty to capture the semantic meanings of cases and 2) result representation: most case-based systems return a list of past cases ranked by their relevance to a new request, and customers have to go through the list and examine the cases one by one to identify their desired cases. To address these challenges, we develop iHelp, an intelligent online helpdesk system, to automatically find problem-solution patterns from the past customer-representative interactions. When a new customer request arrives, iHelp searches and ranks the past cases based on their semantic relevance to the request, groups the relevant cases into different clusters using a mixture language model and symmetric matrix factorization, and summarizes each case cluster to generate recommended solutions. Case and user studies have been conducted to show the full functionality and the effectiveness of iHelp.

Machine learning in computational docking.

PubMed

Khamis, Mohamed A; Gomaa, Walid; Ahmed, Walaa F

2015-03-01

The objective of this paper is to highlight the state-of-the-art machine learning (ML) techniques in computational docking. The use of smart computational methods in the life cycle of drug design is relatively a recent development that has gained much popularity and interest over the last few years. Central to this methodology is the notion of computational docking which is the process of predicting the best pose (orientation + conformation) of a small molecule (drug candidate) when bound to a target larger receptor molecule (protein) in order to form a stable complex molecule. In computational docking, a large number of binding poses are evaluated and ranked using a scoring function. The scoring function is a mathematical predictive model that produces a score that represents the binding free energy, and hence the stability, of the resulting complex molecule. Generally, such a function should produce a set of plausible ligands ranked according to their binding stability along with their binding poses. In more practical terms, an effective scoring function should produce promising drug candidates which can then be synthesized and physically screened using high throughput screening process. Therefore, the key to computer-aided drug design is the design of an efficient highly accurate scoring function (using ML techniques). The methods presented in this paper are specifically based on ML techniques. Despite many traditional techniques have been proposed, the performance was generally poor. Only in the last few years started the application of the ML technology in the design of scoring functions; and the results have been very promising. The ML-based techniques are based on various molecular features extracted from the abundance of protein-ligand information in the public molecular databases, e.g., protein data bank bind (PDBbind). In this paper, we present this paradigm shift elaborating on the main constituent elements of the ML approach to molecular docking along with the state-of-the-art research in this area. For instance, the best random forest (RF)-based scoring function on PDBbind v2007 achieves a Pearson correlation coefficient between the predicted and experimentally determined binding affinities of 0.803 while the best conventional scoring function achieves 0.644. The best RF-based ranking power ranks the ligands correctly based on their experimentally determined binding affinities with accuracy 62.5% and identifies the top binding ligand with accuracy 78.1%. We conclude with open questions and potential future research directions that can be pursued in smart computational docking; using molecular features of different nature (geometrical, energy terms, pharmacophore), advanced ML techniques (e.g., deep learning), combining more than one ML models. Copyright © 2015 Elsevier B.V. All rights reserved.

Faculty Rank System, Research Motivation, and Faculty Research Productivity: Measure Refinement and Theory Testing.

ERIC Educational Resources Information Center

Tien, Flora F.; Blackburn, Robert T.

1996-01-01

A study explored the relationship between the traditional system of college faculty rank and faculty research productivity from the perspectives of behavioral reinforcement theory and selection function. Six hypotheses were generated and tested, using data from a 1989 national faculty survey. Results failed to support completely either the…

22 CFR 11.11 - Mid-level Foreign Service officer career candidate appointments.

Code of Federal Regulations, 2014 CFR

2014-04-01

... cannot reasonably be met from within the ranks of the career service, including by special training of... rank-order register for the class and functional specialty for which the candidate has been found... aptitude for learning them. A candidate may be appointed without first having passed an examination in a...

22 CFR 11.11 - Mid-level Foreign Service officer career candidate appointments.

Code of Federal Regulations, 2012 CFR

2012-04-01

... cannot reasonably be met from within the ranks of the career service, including by special training of... rank-order register for the class and functional specialty for which the candidate has been found... aptitude for learning them. A candidate may be appointed without first having passed an examination in a...

22 CFR 11.11 - Mid-level Foreign Service officer career candidate appointments.

Code of Federal Regulations, 2011 CFR

2011-04-01

... cannot reasonably be met from within the ranks of the career service, including by special training of... rank-order register for the class and functional specialty for which the candidate has been found... aptitude for learning them. A candidate may be appointed without first having passed an examination in a...

Tensor-based dynamic reconstruction method for electrical capacitance tomography

NASA Astrophysics Data System (ADS)

Lei, J.; Mu, H. P.; Liu, Q. B.; Li, Z. H.; Liu, S.; Wang, X. Y.

2017-03-01

Electrical capacitance tomography (ECT) is an attractive visualization measurement method, in which the acquisition of high-quality images is beneficial for the understanding of the underlying physical or chemical mechanisms of the dynamic behaviors of the measurement objects. In real-world measurement environments, imaging objects are often in a dynamic process, and the exploitation of the spatial-temporal correlations related to the dynamic nature will contribute to improving the imaging quality. Different from existing imaging methods that are often used in ECT measurements, in this paper a dynamic image sequence is stacked into a third-order tensor that consists of a low rank tensor and a sparse tensor within the framework of the multiple measurement vectors model and the multi-way data analysis method. The low rank tensor models the similar spatial distribution information among frames, which is slowly changing over time, and the sparse tensor captures the perturbations or differences introduced in each frame, which is rapidly changing over time. With the assistance of the Tikhonov regularization theory and the tensor-based multi-way data analysis method, a new cost function, with the considerations of the multi-frames measurement data, the dynamic evolution information of a time-varying imaging object and the characteristics of the low rank tensor and the sparse tensor, is proposed to convert the imaging task in the ECT measurement into a reconstruction problem of a third-order image tensor. An effective algorithm is developed to search for the optimal solution of the proposed cost function, and the images are reconstructed via a batching pattern. The feasibility and effectiveness of the developed reconstruction method are numerically validated.

Stability of the DSM-5 Section III pathological personality traits and their longitudinal associations with psychosocial functioning in personality disordered individuals.

PubMed

Wright, Aidan G C; Calabrese, William R; Rudick, Monica M; Yam, Wern How; Zelazny, Kerry; Williams, Trevor F; Rotterman, Jane H; Simms, Leonard J

2015-02-01

This study was conducted to establish (a) the stability of the DSM-5 Section III personality disorder (PD) traits, (b) whether these traits predict future psychosocial functioning, and (c) whether changes in traits track with changes in psychosocial functioning across time. Ninety-three outpatients (61% female) diagnosed with at least 1 PD completed patient-report measures at 2 time-points (M time between assessments = 1.44 years), including the Personality Inventory for the DSM-5 and several measures of psychosocial functioning. Effect sizes of rank-order and mean-level change were calculated. In addition, Time 1 traits were used to predict functioning measures at Time 2. Finally, latent change score models were estimated for DSM-5 Section III traits and functioning measures, and correlations among latent change scores were calculated to establish the relationship between change in traits and functional outcomes. Findings demonstrated that the DSM-5 Section III traits were highly stable in terms of normative (i.e., mean-level) change and rank-order stability over the course of the study. Furthermore, traits prospectively predicted psychosocial functioning. However, at the individual level traits and functioning were not entirely static over the study, and change in individuals' functioning tracked with changes in trait levels. These findings demonstrate that the DSM-5 Section III traits are highly stable consistent with the definition of PD, prospectively predictive of psychosocial functioning, and are dynamically associated with functioning over time. This study provides important evidence in support of the DSM-5 Section III PD model. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

[The effect of sensory stimuli of varying modality on the human body functioning and indices of tense muscular activity].

PubMed

Kaĭdalin, V S; Kamchatnikov, A G; Sentiabrev, N N; Katuntsev, V P

2007-01-01

The work had a purpose to study benefits of aromatic blends of tonic and relaxing essences and functional music on some of the psychophysiological properties of the human functional state and motor activeity. Participants were 30 sprinters (18-22 y.o. males) having the first-class and master ranks. The psychophysiological indices of the athletes' functional state were evaluated with the use of the "CAH" and Spilberger situational anxiety tests, calculated Cardeu vegetative index, time for simple motor reaction and reaction to a moving object. Motor activity was evaluated by top running speed determined with a photo-electronic time-keeper and by duration of pedaling on bicycle ergometer at maximal power. The running step parameters were recorded with electropodography. It was shown that the positive effect of the aromatic essence blends and functional music on motor activity developed fairly rapidly but did not last long. The article discusses features and possible ways the aromatic blends and music effect human organism.

An ensemble rank learning approach for gene prioritization.

PubMed

Lee, Po-Feng; Soo, Von-Wun

2013-01-01

Several different computational approaches have been developed to solve the gene prioritization problem. We intend to use the ensemble boosting learning techniques to combine variant computational approaches for gene prioritization in order to improve the overall performance. In particular we add a heuristic weighting function to the Rankboost algorithm according to: 1) the absolute ranks generated by the adopted methods for a certain gene, and 2) the ranking relationship between all gene-pairs from each prioritization result. We select 13 known prostate cancer genes in OMIM database as training set and protein coding gene data in HGNC database as test set. We adopt the leave-one-out strategy for the ensemble rank boosting learning. The experimental results show that our ensemble learning approach outperforms the four gene-prioritization methods in ToppGene suite in the ranking results of the 13 known genes in terms of mean average precision, ROC and AUC measures.

Global Rankings in the Nordic Region: Challenging the Identity of Research-Intensive Universities?

ERIC Educational Resources Information Center

Elken, Mari; Hovdhaugen, Elisabeth; Stensaker, Bjørn

2016-01-01

Global university rankings currently attract considerable attention, and it is often assumed that such rankings may cause universities to prioritize activities and outcomes that will have a positive effect in their ranking position. A possible consequence of this could be the spread of a particular model of an "ideal" university. This…

Close-Up Examination of Discourses Associated with Global University Rankings: Counter-Narratives in UK Policy Context

ERIC Educational Resources Information Center

Trowler, Paul; O' Connell, Catherine

2015-01-01

In little over a decade since their introduction, global rankings are perceived as having significant and problematic effects. The dominant "normative" research orientation applied to the research domain of rankings is identified as a contributory factor to the sustained interest in rankings. The paper argues for a "close-up"…

An Examination of Global University Rankings as a New Mechanism Influencing Mission Differentiation: The UK Context

ERIC Educational Resources Information Center

O'Connell, Catherine

2015-01-01

Since their emergence a decade ago, global university rankings have become a powerful force in higher education internationally. The majority of research studies on global rankings have examined the effects at institutional and national levels. This study offers a valuable perspective on the ways rankings (and other international benchmarks) are…

Using rank-order geostatistics for spatial interpolation of highly skewed data in a heavy-metal contaminated site.

PubMed

Juang, K W; Lee, D Y; Ellsworth, T R

2001-01-01

The spatial distribution of a pollutant in contaminated soils is usually highly skewed. As a result, the sample variogram often differs considerably from its regional counterpart and the geostatistical interpolation is hindered. In this study, rank-order geostatistics with standardized rank transformation was used for the spatial interpolation of pollutants with a highly skewed distribution in contaminated soils when commonly used nonlinear methods, such as logarithmic and normal-scored transformations, are not suitable. A real data set of soil Cd concentrations with great variation and high skewness in a contaminated site of Taiwan was used for illustration. The spatial dependence of ranks transformed from Cd concentrations was identified and kriging estimation was readily performed in the standardized-rank space. The estimated standardized rank was back-transformed into the concentration space using the middle point model within a standardized-rank interval of the empirical distribution function (EDF). The spatial distribution of Cd concentrations was then obtained. The probability of Cd concentration being higher than a given cutoff value also can be estimated by using the estimated distribution of standardized ranks. The contour maps of Cd concentrations and the probabilities of Cd concentrations being higher than the cutoff value can be simultaneously used for delineation of hazardous areas of contaminated soils.

The Alliance Hypothesis for Human Friendship

PubMed Central

DeScioli, Peter; Kurzban, Robert

2009-01-01

Background Exploration of the cognitive systems underlying human friendship will be advanced by identifying the evolved functions these systems perform. Here we propose that human friendship is caused, in part, by cognitive mechanisms designed to assemble support groups for potential conflicts. We use game theory to identify computations about friends that can increase performance in multi-agent conflicts. This analysis suggests that people would benefit from: 1) ranking friends, 2) hiding friend-ranking, and 3) ranking friends according to their own position in partners' rankings. These possible tactics motivate the hypotheses that people possess egocentric and allocentric representations of the social world, that people are motivated to conceal this information, and that egocentric friend-ranking is determined by allocentric representations of partners' friend-rankings (more than others' traits). Methodology/Principal Findings We report results from three studies that confirm predictions derived from the alliance hypothesis. Our main empirical finding, replicated in three studies, was that people's rankings of their ten closest friends were predicted by their own perceived rank among their partners' other friends. This relationship remained strong after controlling for a variety of factors such as perceived similarity, familiarity, and benefits. Conclusions/Significance Our results suggest that the alliance hypothesis merits further attention as a candidate explanation for human friendship. PMID:19492066

Cross-validation analysis for genetic evaluation models for ranking in endurance horses.

PubMed

García-Ballesteros, S; Varona, L; Valera, M; Gutiérrez, J P; Cervantes, I

2018-01-01

Ranking trait was used as a selection criterion for competition horses to estimate racing performance. In the literature the most common approaches to estimate breeding values are the linear or threshold statistical models. However, recent studies have shown that a Thurstonian approach was able to fix the race effect (competitive level of the horses that participate in the same race), thus suggesting a better prediction accuracy of breeding values for ranking trait. The aim of this study was to compare the predictability of linear, threshold and Thurstonian approaches for genetic evaluation of ranking in endurance horses. For this purpose, eight genetic models were used for each approach with different combinations of random effects: rider, rider-horse interaction and environmental permanent effect. All genetic models included gender, age and race as systematic effects. The database that was used contained 4065 ranking records from 966 horses and that for the pedigree contained 8733 animals (47% Arabian horses), with an estimated heritability around 0.10 for the ranking trait. The prediction ability of the models for racing performance was evaluated using a cross-validation approach. The average correlation between real and predicted performances across genetic models was around 0.25 for threshold, 0.58 for linear and 0.60 for Thurstonian approaches. Although no significant differences were found between models within approaches, the best genetic model included: the rider and rider-horse random effects for threshold, only rider and environmental permanent effects for linear approach and all random effects for Thurstonian approach. The absolute correlations of predicted breeding values among models were higher between threshold and Thurstonian: 0.90, 0.91 and 0.88 for all animals, top 20% and top 5% best animals. For rank correlations these figures were 0.85, 0.84 and 0.86. The lower values were those between linear and threshold approaches (0.65, 0.62 and 0.51). In conclusion, the Thurstonian approach is recommended for the routine genetic evaluations for ranking in endurance horses.

Dominance hierarchy and social relationships in a group of captive black-and-white snub-nosed monkeys (Rhinopithecus bieti).

PubMed

Cui, Liang-Wei; Sun, Qing-Lei; Li, Bao-Guo

2014-05-01

Different types of dominance hierarchies reflect different social relationships in primates. In this study, we clarified the hierarchy and social relationships in a one-male unit of captive Rhinopithecus bieti observed between August 1998 and March 1999. Mean frequency of agonistic behaviour among adult females was 0.13 interactions per hour. Adult females exhibited a linear hierarchy with a reversal of 10.9%, indicating an unstable relationship; therefore, R. bieti appears to be a relaxed/tolerant species. The lack of a relationship between the agonistic ratio of the adult male towards adult females and their ranks indicated that males did not show increased aggression towards low-ranking females. Differentiated female affiliative relationships were loosely formed in terms of the male, and to some extent influenced by female estrus, implying that relationships between the male and females is influenced by estrus and not rank alone. A positive correlation between the agonistic ratio of adult females and their ranks showed that the degree to which one female negatively impacted others decreased with reduction in rank. Similarly, a positive correlation between the agonistic ratio of females and differences in rank suggests that a female had fewer negative effects on closely ranked individuals than distantly ranked ones. These data indicate that rank may influence relationships between females. A steeper slope of regression between the agonistic ratio and inter-female rank differences indicated that the extent of the power difference in high-ranking females exerting negative effects on low-ranking ones was larger during the mating season than the birth season, suggesting that rank may influence the mating success of females.

Analysis of Duplicated Multiple-Samples Rank Data Using the Mack-Skillings Test.

PubMed

Carabante, Kennet Mariano; Alonso-Marenco, Jose Ramon; Chokumnoyporn, Napapan; Sriwattana, Sujinda; Prinyawiwatkul, Witoon

2016-07-01

Appropriate analysis for duplicated multiple-samples rank data is needed. This study compared analysis of duplicated rank preference data using the Friedman versus Mack-Skillings tests. Panelists (n = 125) ranked twice 2 orange juice sets: different-samples set (100%, 70%, vs. 40% juice) and similar-samples set (100%, 95%, vs. 90%). These 2 sample sets were designed to get contrasting differences in preference. For each sample set, rank sum data were obtained from (1) averaged rank data of each panelist from the 2 replications (n = 125), (2) rank data of all panelists from each of the 2 separate replications (n = 125 each), (3) jointed rank data of all panelists from the 2 replications (n = 125), and (4) rank data of all panelists pooled from the 2 replications (n = 250); rank data (1), (2), and (4) were separately analyzed by the Friedman test, although those from (3) by the Mack-Skillings test. The effect of sample sizes (n = 10 to 125) was evaluated. For the similar-samples set, higher variations in rank data from the 2 replications were observed; therefore, results of the main effects were more inconsistent among methods and sample sizes. Regardless of analysis methods, the larger the sample size, the higher the χ(2) value, the lower the P-value (testing H0 : all samples are not different). Analyzing rank data (2) separately by replication yielded inconsistent conclusions across sample sizes, hence this method is not recommended. The Mack-Skillings test was more sensitive than the Friedman test. Furthermore, it takes into account within-panelist variations and is more appropriate for analyzing duplicated rank data. © 2016 Institute of Food Technologists®

Dominance hierarchy and social relationships in a group of Captive black-and-white snub-nosed monkeys (Rhinopithecus bieti)

PubMed Central

CUI, Liang-Wei; SUN, Qing-Lei; LI, Bao-Guo

2014-01-01

Different types of dominance hierarchies reflect different social relationships in primates. In this study, we clarified the hierarchy and social relationships in a one-male unit of captive Rhinopithecus bieti observed between August 1998 and March 1999. Mean frequency of agonistic behaviour among adult females was 0.13 interactions per hour. Adult females exhibited a linear hierarchy with a reversal of 10.9%, indicating an unstable relationship; therefore, R. bieti appears to be a relaxed/tolerant species. The lack of a relationship between the agonistic ratio of the adult male towards adult females and their ranks indicated that males did not show increased aggression towards low-ranking females. Differentiated female affiliative relationships were loosely formed in terms of the male, and to some extent influenced by female estrus, implying that relationships between the male and females is influenced by estrus and not rank alone. A positive correlation between the agonistic ratio of adult females and their ranks showed that the degree to which one female negatively impacted others decreased with reduction in rank. Similarly, a positive correlation between the agonistic ratio of females and differences in rank suggests that a female had fewer negative effects on closely ranked individuals than distantly ranked ones. These data indicate that rank may influence relationships between females. A steeper slope of regression between the agonistic ratio and inter-female rank differences indicated that the extent of the power difference in high-ranking females exerting negative effects on low-ranking ones was larger during the mating season than the birth season, suggesting that rank may influence the mating success of females. PMID:24866491

Controlling for Response Order Effects in Ranking Items Using Latent Choice Factor Modeling

ERIC Educational Resources Information Center

Vriens, Ingrid; Moors, Guy; Gelissen, John; Vermunt, Jeroen K.

2017-01-01

Measuring values in sociological research sometimes involves the use of ranking data. A disadvantage of a ranking assignment is that the order in which the items are presented might influence the choice preferences of respondents regardless of the content being measured. The standard procedure to rule out such effects is to randomize the order of…

Visualizing Rank Time Series of Wikipedia Top-Viewed Pages.

PubMed

Xia, Jing; Hou, Yumeng; Chen, Yingjie Victor; Qian, Zhenyu Cheryl; Ebert, David S; Chen, Wei

2017-01-01

Visual clutter is a common challenge when visualizing large rank time series data. WikiTopReader, a reader of Wikipedia page rank, lets users explore connections among top-viewed pages by connecting page-rank behaviors with page-link relations. Such a combination enhances the unweighted Wikipedia page-link network and focuses attention on the page of interest. A set of user evaluations shows that the system effectively represents evolving ranking patterns and page-wise correlation.

Money and happiness: rank of income, not income, affects life satisfaction.

PubMed

Boyce, Christopher J; Brown, Gordon D A; Moore, Simon C

2010-04-01

Does money buy happiness, or does happiness come indirectly from the higher rank in society that money brings? We tested a rank-income hypothesis, according to which people gain utility from the ranked position of their income within a comparison group. The rank hypothesis contrasts with traditional reference-income hypotheses, which suggest that utility from income depends on comparison to a social reference-group norm. We found that the ranked position of an individual's income predicts general life satisfaction, whereas absolute income and reference income have no effect. Furthermore, individuals weight upward comparisons more heavily than downward comparisons. According to the rank hypothesis, income and utility are not directly linked: Increasing an individual's income will increase his or her utility only if ranked position also increases and will necessarily reduce the utility of others who will lose rank.

Social ranking effects on tooth-brushing behaviour.

PubMed

Maltby, John; Paterson, Kevin; Day, Liz; Jones, Ceri; Kinnear, Hayley; Buchanan, Heather

2016-05-01

A tooth-brushing social rank hypothesis is tested suggesting tooth-brushing duration is influenced when individuals position their behaviour in a rank when comparing their behaviour with other individuals. Study 1 used a correlation design, Study 2 used a semi-experimental design, and Study 3 used a randomized intervention design to examine the tooth-brushing social rank hypothesis in terms of self-reported attitudes, cognitions, and behaviour towards tooth-brushing duration. Study 1 surveyed participants to examine whether the perceived health benefits of tooth-brushing duration could be predicted from the ranking of each person's tooth-brushing duration. Study 2 tested whether manipulating the rank position of the tooth-brushing duration influenced participant-perceived health benefits of tooth-brushing duration. Study 3 used a longitudinal intervention method to examine whether messages relating to the rank positions of tooth-brushing durations causally influenced the self-report tooth-brushing duration. Study 1 demonstrates that perceptions of the health benefits from tooth-brushing duration are predicted by the perceptions of how that behaviour ranks in comparison to other people's behaviour. Study 2 demonstrates that the perceptions of the health benefits of tooth-brushing duration can be manipulated experimentally by changing the ranked position of a person's tooth-brushing duration. Study 3 experimentally demonstrates the possibility of increasing the length of time for which individuals clean their teeth by focusing on how they rank among their peers in terms of tooth-brushing duration. The effectiveness of interventions using social-ranking methods relative to those that emphasize comparisons made against group averages or normative guidelines are discussed. What is already known on this subject? Individual make judgements based on social rank information. Social rank information has been shown to influence positive health behaviours such as exercise. What does this study add? The health benefits of tooth-brushing are predicted by how tooth-brushing duration ranks within a distribution. Focussing on how teeth-cleaning duration ranks among others produces longer teeth-cleaning durations. © 2015 The British Psychological Society.

Intrinsic classes in the Union of European Football Associations soccer team ranking

NASA Astrophysics Data System (ADS)

Ausloos, Marcel

2014-11-01

A strong structural regularity of classes is found in soccer teams ranked by the Union of European Football Associations (UEFA) for the time interval 2009-2014. It concerns 424 to 453 teams according to the 5 competition seasons. The analysis is based on the rank-size theory considerations, the size being the UEFA coefficient at the end of a season. Three classes emerge: (i) the few "top" teams, (ii) 300 teams, (iii) the rest of the involved teams (about 150) in the tail of the distribution. There are marked empirical laws describing each class. A 3-parameter Lavalette function is used to describe the concave curving as the rank increases, and to distinguish the the tail from the central behavior.

General MoM Solutions for Large Arrays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fasenfest, B; Capolino, F; Wilton, D R

2003-07-22

This paper focuses on a numerical procedure that addresses the difficulties of dealing with large, finite arrays while preserving the generality and robustness of full-wave methods. We present a fast method based on approximating interactions between sufficiently separated array elements via a relatively coarse interpolation of the Green's function on a uniform grid commensurate with the array's periodicity. The interaction between the basis and testing functions is reduced to a three-stage process. The first stage is a projection of standard (e.g., RWG) subdomain bases onto a set of interpolation functions that interpolate the Green's function on the array face. Thismore » projection, which is used in a matrix/vector product for each array cell in an iterative solution process, need only be carried out once for a single cell and results in a low-rank matrix. An intermediate stage matrix/vector product computation involving the uniformly sampled Green's function is of convolutional form in the lateral (transverse) directions so that a 2D FFT may be used. The final stage is a third matrix/vector product computation involving a matrix resulting from projecting testing functions onto the Green's function interpolation functions; the low-rank matrix is either identical to (using Galerkin's method) or similar to that for the bases projection. An effective MoM solution scheme is developed for large arrays using a modification of the AIM (Adaptive Integral Method) method. The method permits the analysis of arrays with arbitrary contours and nonplanar elements. Both fill and solve times within the MoM method are improved with respect to more standard MoM solvers.« less

The prediction of airborne and structure-borne noise potential for a tire

NASA Astrophysics Data System (ADS)

Sakamoto, Nicholas Y.

Tire/pavement interaction noise is a major component of both exterior pass-by noise and vehicle interior noise. The current testing methods for ranking tires from loud to quiet require expensive equipment, multiple tires, and/or long experimental set-up and run times. If a laboratory based off-vehicle test could be used to identify the airborne and structure-borne potential of a tire from its dynamic characteristics, a relative ranking of a large group of tires could be performed at relatively modest expense. This would provide a smaller sample set of tires for follow-up testing and thus save expense for automobile OEMs. The focus of this research was identifying key noise features from a tire/pavement experiment. These results were compared against a stationary tire test in which the natural response of the tire to a forced input was measured. Since speed was identified as having some effect on the noise, an input function was also developed to allow the tires to be ranked at an appropriate speed. A relative noise model was used on a second sample set of tires to verify if the ranking could be used against interior vehicle measurements. While overall level analysis of the specified spectrum had mixed success, important noise generating features were identified, and the methods used could be improved to develop a standard off-vehicle test to predict a tire's noise potential.

Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks

PubMed Central

Chen, Jianhui; Liu, Ji; Ye, Jieping

2013-01-01

We consider the problem of learning incoherent sparse and low-rank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the sparse and low-rank patterns are induced by a cardinality regularization term and a low-rank constraint, respectively. This formulation is non-convex; we convert it into its convex surrogate, which can be routinely solved via semidefinite programming for small-size problems. We propose to employ the general projected gradient scheme to efficiently solve such a convex surrogate; however, in the optimization formulation, the objective function is non-differentiable and the feasible domain is non-trivial. We present the procedures for computing the projected gradient and ensuring the global convergence of the projected gradient scheme. The computation of projected gradient involves a constrained optimization problem; we show that the optimal solution to such a problem can be obtained via solving an unconstrained optimization subproblem and an Euclidean projection subproblem. We also present two projected gradient algorithms and analyze their rates of convergence in details. In addition, we illustrate the use of the presented projected gradient algorithms for the proposed multi-task learning formulation using the least squares loss. Experimental results on a collection of real-world data sets demonstrate the effectiveness of the proposed multi-task learning formulation and the efficiency of the proposed projected gradient algorithms. PMID:24077658

Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks.

PubMed

Chen, Jianhui; Liu, Ji; Ye, Jieping

2012-02-01

We consider the problem of learning incoherent sparse and low-rank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the sparse and low-rank patterns are induced by a cardinality regularization term and a low-rank constraint, respectively. This formulation is non-convex; we convert it into its convex surrogate, which can be routinely solved via semidefinite programming for small-size problems. We propose to employ the general projected gradient scheme to efficiently solve such a convex surrogate; however, in the optimization formulation, the objective function is non-differentiable and the feasible domain is non-trivial. We present the procedures for computing the projected gradient and ensuring the global convergence of the projected gradient scheme. The computation of projected gradient involves a constrained optimization problem; we show that the optimal solution to such a problem can be obtained via solving an unconstrained optimization subproblem and an Euclidean projection subproblem. We also present two projected gradient algorithms and analyze their rates of convergence in details. In addition, we illustrate the use of the presented projected gradient algorithms for the proposed multi-task learning formulation using the least squares loss. Experimental results on a collection of real-world data sets demonstrate the effectiveness of the proposed multi-task learning formulation and the efficiency of the proposed projected gradient algorithms.

Diverse effects of degree of urbanisation and forest size on species richness and functional diversity of plants, and ground surface-active ants and spiders

PubMed Central

Melliger, Ramona Laila; Rusterholz, Hans-Peter; Baur, Bruno

2018-01-01

Urbanisation is increasing worldwide and is regarded a major driver of environmental change altering local species assemblages in urban green areas. Forests are one of the most frequent habitat types in urban landscapes harbouring many native species and providing important ecosystem services. By using a multi-taxa approach covering a range of trophic ranks, we examined the influence of degree of urbanisation and forest size on the species richness and functional diversity of plants, and ground surface-active ants and spiders. We conducted field surveys in twenty-six forests in the urban region of Basel, Switzerland. We found that a species’ response to urbanisation varied depending on trophic rank, habitat specificity and the diversity indices used. In plants, species richness decreased with degree of urbanisation, whereas that of both arthropod groups was not affected. However, ants and spiders at higher trophic rank showed greater shifts in species composition with increasing degree of urbanisation, and the percentage of forest specialists in both arthropod groups increased with forest size. Local abiotic site characteristics were also crucial for plant species diversity and species composition, while the structural diversity of both leaf litter and vegetation was important for the diversity of ants and spiders. Our results highlight that even small urban forests can harbour a considerable biodiversity including habitat specialists. Nonetheless, urbanisation directly and indirectly caused major shifts in species composition. Therefore, special consideration needs to be given to vulnerable species, including those with special habitat requirements. Locally adapted management practices could be a step forward to enhance habitat quality in a way to maximize diversity of forest species and thus ensure forest ecosystem functioning; albeit large-scale factors also remain important. PMID:29920553

Diverse effects of degree of urbanisation and forest size on species richness and functional diversity of plants, and ground surface-active ants and spiders.

PubMed

Melliger, Ramona Laila; Braschler, Brigitte; Rusterholz, Hans-Peter; Baur, Bruno

2018-01-01

Urbanisation is increasing worldwide and is regarded a major driver of environmental change altering local species assemblages in urban green areas. Forests are one of the most frequent habitat types in urban landscapes harbouring many native species and providing important ecosystem services. By using a multi-taxa approach covering a range of trophic ranks, we examined the influence of degree of urbanisation and forest size on the species richness and functional diversity of plants, and ground surface-active ants and spiders. We conducted field surveys in twenty-six forests in the urban region of Basel, Switzerland. We found that a species' response to urbanisation varied depending on trophic rank, habitat specificity and the diversity indices used. In plants, species richness decreased with degree of urbanisation, whereas that of both arthropod groups was not affected. However, ants and spiders at higher trophic rank showed greater shifts in species composition with increasing degree of urbanisation, and the percentage of forest specialists in both arthropod groups increased with forest size. Local abiotic site characteristics were also crucial for plant species diversity and species composition, while the structural diversity of both leaf litter and vegetation was important for the diversity of ants and spiders. Our results highlight that even small urban forests can harbour a considerable biodiversity including habitat specialists. Nonetheless, urbanisation directly and indirectly caused major shifts in species composition. Therefore, special consideration needs to be given to vulnerable species, including those with special habitat requirements. Locally adapted management practices could be a step forward to enhance habitat quality in a way to maximize diversity of forest species and thus ensure forest ecosystem functioning; albeit large-scale factors also remain important.

Inhibition of differentiation and function of osteoclasts by dimethyl sulfoxide (DMSO).

PubMed

Yang, Chunxi; Madhu, Vedavathi; Thomas, Candace; Yang, Xinlin; Du, Xeujun; Dighe, Abhijit S; Cui, Quanjun

2015-12-01

Dimethyl sulfoxide (DMSO) is an FDA-approved organosulfur solvent that is reported to have therapeutic value in osteoarthritis and osteopenia. DMSO is used as a cryoprotectant for the cryopreservation of bone grafts and mesenchymal stem cells which are later used for bone repair. It is also used as a solvent in the preparation of various scaffolds used for bone tissue engineering purposes. DMSO has been reported to inhibit osteoclast formation in vitro but the mechanism involved has remained elusive. We investigated the effect of DMSO on osteoclast differentiation and function using a conventional model system of RAW 264.7 cells. The differentiation of RAW 264.7 cells was induced by adding 50 ng/ml RANKL and the effect of DMSO (0.01 and 1% v/v) on RANKL-induced osteoclastogenesis was investigated. Addition of 1% DMSO significantly inhibited RANKL-induced formation of TRAP+, multinucleated, mature osteoclasts and osteoclast late-stage precursors (c-Kit(-) c-Fms(+) Mac-1(+) RANK(+)). While DMSO did not inhibit proliferation per se, it did inhibit the effect of RANKL on proliferation of RAW 264.7 cells. Key genes related to osteoclast function (TRAP, Integrin αVβ3, Cathepsin K and MMP9) were significantly down-regulated by DMSO. RANKL-induced expression of RANK gene was significantly reduced in the presence of DMSO. Our data, and reports from other investigators, that DMSO enhances osteoblastic differentiation of mesenchymal stem cells and also prevents bone loss in ovarietcomized rats, suggest that DMSO has tremendous potential in the treatment of osteoporosis and bone diseases arising from uncontrolled activities of the osteoclasts.

Resting-state functional magnetic resonance imaging of the subthalamic microlesion and stimulation effects in Parkinson's disease: Indications of a principal role of the brainstem.

PubMed

Holiga, Štefan; Mueller, Karsten; Möller, Harald E; Urgošík, Dušan; Růžička, Evžen; Schroeter, Matthias L; Jech, Robert

2015-01-01

During implantation of deep-brain stimulation (DBS) electrodes in the target structure, neurosurgeons and neurologists commonly observe a "microlesion effect" (MLE), which occurs well before initiating subthalamic DBS. This phenomenon typically leads to a transitory improvement of motor symptoms of patients suffering from Parkinson's disease (PD). Mechanisms behind MLE remain poorly understood. In this work, we exploited the notion of ranking to assess spontaneous brain activity in PD patients examined by resting-state functional magnetic resonance imaging in response to penetration of DBS electrodes in the subthalamic nucleus. In particular, we employed a hypothesis-free method, eigenvector centrality (EC), to reveal motor-communication-hubs of the highest rank and their reorganization following the surgery; providing a unique opportunity to evaluate the direct impact of disrupting the PD motor circuitry in vivo without prior assumptions. Penetration of electrodes was associated with increased EC of functional connectivity in the brainstem. Changes in connectivity were quantitatively related to motor improvement, which further emphasizes the clinical importance of the functional integrity of the brainstem. Surprisingly, MLE and DBS were associated with anatomically different EC maps despite their similar clinical benefit on motor functions. The DBS solely caused an increase in connectivity of the left premotor region suggesting separate pathophysiological mechanisms of both interventions. While the DBS acts at the cortical level suggesting compensatory activation of less affected motor regions, the MLE affects more fundamental circuitry as the dysfunctional brainstem predominates in the beginning of PD. These findings invigorate the overlooked brainstem perspective in the understanding of PD and support the current trend towards its early diagnosis.

Validation of the CNS Penetration-Effectiveness Rank for Quantifying Antiretroviral Penetration Into the Central Nervous System

PubMed Central

Letendre, Scott; Marquie-Beck, Jennifer; Capparelli, Edmund; Best, Brookie; Clifford, David; Collier, Ann C.; Gelman, Benjamin B.; McArthur, Justin C.; McCutchan, J. Allen; Morgello, Susan; Simpson, David; Grant, Igor; Ellis, Ronald J.

2009-01-01

Objective To evaluate whether penetration of a combination regimen into the central nervous system (CNS), as estimated by the CNS Penetration-Effectiveness (CPE) rank, is associated with lower cerebrospinal fluid (CSF) viral load. Design Data were analyzed from 467 participants who were human immunodeficiency virus (HIV) seropositive and who reported antiretroviral (ARV) drug use. Individual ARV drugs were assigned a penetration rank of 0 (low), 0.5 (intermediate), or 1 (high) based on their chemical properties, concentrations in CSF, and/or effectiveness in the CNS in clinical studies. The CPE rank was calculated by summing the individual penetration ranks for each ARV in the regimen. Results The median CPE rank was 1.5 (interquartile range, 1–2). Lower CPE ranks correlated with higher CSF viral loads. Ranks less than 2 were associated with an 88% increase in the odds of detectable CSF viral load. In multivariate regression, lower CPE ranks were associated with detectable CSF viral loads even after adjusting for total number of ARV drugs, ARV drug adherence, plasma viral load, duration and type of the current regimen, and CD4 count. Conclusions Poorer penetration of ARV drugs into the CNS appears to allow continued HIV replication in the CNS as indicated by higher CSF HIV viral loads. Because inhibition of HIV replication in the CNS is probably critical in treating patients who have HIV-associated neurocognitive disorders, ARV treatment strategies that account for CNS penetration should be considered in consensus treatment guidelines and validated in clinical studies. PMID:18195140

[Comprehensive evaluation and selection of urban eco-engineering virescent trees in Shenyang City].

PubMed

Lu, Min; Jiang, Fengqi; Li, Yingjie

2004-07-01

Urban virescence eco-engineering is the core of urban eco-environmental construction, which can promote urban sustainable development. In urban virescence eco-engineering, the comprehensive evaluation of ecological adapt-ability and ecological effect of urban plants is the scientific basis of rational application and selection of urban garden plants. The ecological effect and integrative functions of urban virescence eco-engineering depend upon the selection and layout of garden plants. Using the methods of garden expert consultation and evaluation, this paper established systematically integrative evaluation and application indices of virescence plants in Shenyang City, from the aspects of ecological adaptability, ecological effect, beautification effect, resistance to plant diseases and insect pests, anti-pollution and economic results. According to garden experts evaluation and location of Shenyang, 200 sorts of virescence trees were evaluated and classified on the basis of the comprehensive evaluation system of virescence trees, and using cold resistance, drought resistance, barren resistance, plant diseases and insect pests resistance, anti-pollution, ornamental quality and ecological effects as the indexes. The results showed that the number of first rank trees was 58, the second was 93, methods of third was 38, and the fourth was 11, ranked by integrative performance.

Criteria for choosing clinically effective glaucoma treatment: A discussion panel consensus

PubMed Central

Thygesen, John; Burk, Reinhard; Carassa, Roberto; Crichton, Andrew; Goñi, Francisco Javier; Menage, Mitch; Miglior, Stefano; Montgomery, Donald; Nordmann, John-Philippe; Roberts, Tim; Singh, Kuldev

2007-01-01

Abstract Background: In the clinical management of patients at risk for or diagnosed with primary open-angle glaucoma (POAG), the aim of medical treatment is to reduce intraocular pressure (IOP) and then maintain it over time at a level that preserves both the structure and function of the optic nerve. Objective: The objective of this report was to establish a consensus on the criteria that should be used to determine the characteristics of IOP-lowering medication. Methods: Discussion was held among a panel of 12 physicians considered to be experts in glaucoma to develop a consensus on the criteria used by them to determine the characteristics of the IOP-lowering medication chosen for initial monotherapy and adjunctive treatment of ocular hypertension (OHT) or POAG. Consensus development combined available evidence and the impressions of these physicians regarding the clinical effectiveness of IOP-lowering medication for OHT and POAG. Once the panel identified the criteria, the order of priority and the relative importance of these criteria were then established in the setting of 3 risk categories (low, medium, and high) for a patient to experience significant visual disability from glaucoma over their expected life span. Results: The panel identified 5 criteria to determine the characteristics of IOP-lowering medication for OHT and POAG: IOP-lowering effect, systemic adverse events (AEs), ocular tolerability, compliance/administration, and cost of treatment. IOP-lowering effect was consistently ranked as the highest priority and cost as the lowest. The priority of compliance/administration did not vary by clinical situation. Systemic AEs and ocular tolerability were ranked as higher priorities in initial monotherapy than in adjunctive treatment and ranked lower as the risk for visual disability increased. The priority given to the criteria used to determine clinical effectiveness varied both with the risk for functional vision loss from glaucoma and whether initial monotherapy or adjunctive treatment was being considered. Conclusion: Glaucoma treatment should be assessed with regard to the need not only to lower IOP but also to minimize systemic and ocular AEs, promote patient compliance, and minimize cost. The order of priority and relative importance given to these treatment criteria will vary as part of individualizing patient care. PMID:24683204

A machine learning approach for ranking clusters of docked protein‐protein complexes by pairwise cluster comparison

PubMed Central

Pfeiffenberger, Erik; Chaleil, Raphael A.G.; Moal, Iain H.

2017-01-01

ABSTRACT Reliable identification of near‐native poses of docked protein–protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein–protein interactions is challenging for traditional biophysical or knowledge based potentials and the identification of many false positive binding sites is not unusual. Often, ranking protocols are based on initial clustering of docked poses followed by the application of an energy function to rank each cluster according to its lowest energy member. Here, we present an approach of cluster ranking based not only on one molecular descriptor (e.g., an energy function) but also employing a large number of descriptors that are integrated in a machine learning model, whereby, an extremely randomized tree classifier based on 109 molecular descriptors is trained. The protocol is based on first locally enriching clusters with additional poses, the clusters are then characterized using features describing the distribution of molecular descriptors within the cluster, which are combined into a pairwise cluster comparison model to discriminate near‐native from incorrect clusters. The results show that our approach is able to identify clusters containing near‐native protein–protein complexes. In addition, we present an analysis of the descriptors with respect to their power to discriminate near native from incorrect clusters and how data transformations and recursive feature elimination can improve the ranking performance. Proteins 2017; 85:528–543. © 2016 Wiley Periodicals, Inc. PMID:27935158

A Quantitative Method to Identify Lithology Beneath Cover

NASA Astrophysics Data System (ADS)

Gettings, M. E.

2008-12-01

Geophysical terranes (map areas of similar potential field data response) can be used in the estimation of geological map units beneath cover (bedrock, alluvium, or tectonic block). Potential field data over nearby bedrock terranes defines "candidate terranes". Geophysical anomaly dimensions, shapes, amplitudes, trends/structural grain, and fractal measures yield a vector of measures characterizing the terrane. To compare candidate terranes fields with those for covered areas, the effect of depth of cover must be taken into account. Gravity anomaly data yields depth estimates by which the aeromagnetic data of candidate terranes are then upward continued. Comparison of characteristics of the upward continued fields from the candidate terranes to those of covered areas rank the candidates. Because of signal loss in upward continuation and overlap of physical properties, the vectors of measures for the candidate terranes are usually not unique. Possibility theory offers a relatively objective and robust method that can be used to rank terrane types that includes uncertainty. The strategy is to prepare membership functions for each measure of each candidate terrane and the covered area, based on observed values and degree of knowledge, and then form the fuzzy-logical combination of these to estimate the possibility and its uncertainty for each candidate terrane. Membership functions include uncertainty by the degree of membership for various possibility values. With no other information, uncertainty is based on information content from survey specifications and geologic features dimensions. Geologic data can also be included, such as structural trends, proximity, and tectonic history. Little knowledge implies wide membership functions; perfect knowledge, a delta function. This and the combination rules in fuzzy logic yield a robust estimation method. An uncertain membership function of a characteristic contributes much less to the possibility than a precise one. The final result for each covered area is a ranked possibility function for each candidate terrane as the underlying bedrock of the covered area that honors the aeromagnetic field and the geologic constraints that have been included. An example of the application of this method is presented for an area in south central Arizona.

A rank-based Prediction Algorithm of Learning User's Intention

NASA Astrophysics Data System (ADS)

Shen, Jie; Gao, Ying; Chen, Cang; Gong, HaiPing

Internet search has become an important part in people's daily life. People can find many types of information to meet different needs through search engines on the Internet. There are two issues for the current search engines: first, the users should predetermine the types of information they want and then change to the appropriate types of search engine interfaces. Second, most search engines can support multiple kinds of search functions, each function has its own separate search interface. While users need different types of information, they must switch between different interfaces. In practice, most queries are corresponding to various types of information results. These queries can search the relevant results in various search engines, such as query "Palace" contains the websites about the introduction of the National Palace Museum, blog, Wikipedia, some pictures and video information. This paper presents a new aggregative algorithm for all kinds of search results. It can filter and sort the search results by learning three aspects about the query words, search results and search history logs to achieve the purpose of detecting user's intention. Experiments demonstrate that this rank-based method for multi-types of search results is effective. It can meet the user's search needs well, enhance user's satisfaction, provide an effective and rational model for optimizing search engines and improve user's search experience.

Improving the Rank Precision of Population Health Measures for Small Areas with Longitudinal and Joint Outcome Models

PubMed Central

Athens, Jessica K.; Remington, Patrick L.; Gangnon, Ronald E.

2015-01-01

Objectives The University of Wisconsin Population Health Institute has published the County Health Rankings since 2010. These rankings use population-based data to highlight health outcomes and the multiple determinants of these outcomes and to encourage in-depth health assessment for all United States counties. A significant methodological limitation, however, is the uncertainty of rank estimates, particularly for small counties. To address this challenge, we explore the use of longitudinal and pooled outcome data in hierarchical Bayesian models to generate county ranks with greater precision. Methods In our models we used pooled outcome data for three measure groups: (1) Poor physical and poor mental health days; (2) percent of births with low birth weight and fair or poor health prevalence; and (3) age-specific mortality rates for nine age groups. We used the fixed and random effects components of these models to generate posterior samples of rates for each measure. We also used time-series data in longitudinal random effects models for age-specific mortality. Based on the posterior samples from these models, we estimate ranks and rank quartiles for each measure, as well as the probability of a county ranking in its assigned quartile. Rank quartile probabilities for univariate, joint outcome, and/or longitudinal models were compared to assess improvements in rank precision. Results The joint outcome model for poor physical and poor mental health days resulted in improved rank precision, as did the longitudinal model for age-specific mortality rates. Rank precision for low birth weight births and fair/poor health prevalence based on the univariate and joint outcome models were equivalent. Conclusion Incorporating longitudinal or pooled outcome data may improve rank certainty, depending on characteristics of the measures selected. For measures with different determinants, joint modeling neither improved nor degraded rank precision. This approach suggests a simple way to use existing information to improve the precision of small-area measures of population health. PMID:26098858

Molecular docking.

PubMed

Morris, Garrett M; Lim-Wilby, Marguerita

2008-01-01

Molecular docking is a key tool in structural molecular biology and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode(s) of a ligand with a protein of known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compounds, rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discusses the background and theory of molecular docking software, and covers the usage of some of the most-cited docking software.

Identifying a set of influential spreaders in complex networks

NASA Astrophysics Data System (ADS)

Zhang, Jian-Xiong; Chen, Duan-Bing; Dong, Qiang; Zhao, Zhi-Dan

2016-06-01

Identifying a set of influential spreaders in complex networks plays a crucial role in effective information spreading. A simple strategy is to choose top-r ranked nodes as spreaders according to influence ranking method such as PageRank, ClusterRank and k-shell decomposition. Besides, some heuristic methods such as hill-climbing, SPIN, degree discount and independent set based are also proposed. However, these approaches suffer from a possibility that some spreaders are so close together that they overlap sphere of influence or time consuming. In this report, we present a simply yet effectively iterative method named VoteRank to identify a set of decentralized spreaders with the best spreading ability. In this approach, all nodes vote in a spreader in each turn, and the voting ability of neighbors of elected spreader will be decreased in subsequent turn. Experimental results on four real networks show that under Susceptible-Infected-Recovered (SIR) and Susceptible-Infected (SI) models, VoteRank outperforms the traditional benchmark methods on both spreading rate and final affected scale. What’s more, VoteRank has superior computational efficiency.

Systematically Ranking the Tightness of Membrane Association for Peripheral Membrane Proteins (PMPs)*

PubMed Central

Gao, Liyan; Ge, Haitao; Huang, Xiahe; Liu, Kehui; Zhang, Yuanya; Xu, Wu; Wang, Yingchun

2015-01-01

Large-scale quantitative evaluation of the tightness of membrane association for nontransmembrane proteins is important for identifying true peripheral membrane proteins with functional significance. Herein, we simultaneously ranked more than 1000 proteins of the photosynthetic model organism Synechocystis sp. PCC 6803 for their relative tightness of membrane association using a proteomic approach. Using multiple precisely ranked and experimentally verified peripheral subunits of photosynthetic protein complexes as the landmarks, we found that proteins involved in two-component signal transduction systems and transporters are overall tightly associated with the membranes, whereas the associations of ribosomal proteins are much weaker. Moreover, we found that hypothetical proteins containing the same domains generally have similar tightness. This work provided a global view of the structural organization of the membrane proteome with respect to divergent functions, and built the foundation for future investigation of the dynamic membrane proteome reorganization in response to different environmental or internal stimuli. PMID:25505158

Low-ranking female Japanese macaques make efforts for social grooming

PubMed Central

Kurihara, Yosuke

2016-01-01

Abstract Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates. PMID:29491896

Low-ranking female Japanese macaques make efforts for social grooming.

PubMed

Kurihara, Yosuke

2016-04-01

Grooming is essential to build social relationships in primates. Its importance is universal among animals from different ranks; however, rank-related differences in feeding patterns can lead to conflicts between feeding and grooming in low-ranking animals. Unifying the effects of dominance rank on feeding and grooming behaviors contributes to revealing the importance of grooming. Here, I tested whether the grooming behavior of low-ranking females were similar to that of high-ranking females despite differences in their feeding patterns. I followed 9 Japanese macaques Macaca fuscata fuscata adult females from the Arashiyama group, and analyzed the feeding patterns and grooming behaviors of low- and high-ranking females. Low-ranking females fed on natural foods away from the provisioning site, whereas high-ranking females obtained more provisioned food at the site. Due to these differences in feeding patterns, low-ranking females spent less time grooming than high-ranking females. However, both low- and high-ranking females performed grooming around the provisioning site, which was linked to the number of neighboring individuals for low-ranking females and feeding on provisioned foods at the site for high-ranking females. The similarity in grooming area led to a range and diversity of grooming partners that did not differ with rank. Thus, low-ranking females can obtain small amounts of provisioned foods and perform grooming with as many partners around the provisioning site as high-ranking females. These results highlight the efforts made by low-ranking females to perform grooming and suggest the importance of grooming behavior in group-living primates.

Functional Group, Biomass, and Climate Change Effects on Ecological Drought in Semiarid Grasslands

NASA Astrophysics Data System (ADS)

Wilson, S. D.; Schlaepfer, D. R.; Bradford, J. B.; Lauenroth, W. K.; Duniway, M. C.; Hall, S. A.; Jamiyansharav, K.; Jia, G.; Lkhagva, A.; Munson, S. M.; Pyke, D. A.; Tietjen, B.

2018-03-01

Water relations in plant communities are influenced both by contrasting functional groups (grasses and shrubs) and by climate change via complex effects on interception, uptake, and transpiration. We modeled the effects of functional group replacement and biomass increase, both of which can be outcomes of invasion and vegetation management, and climate change on ecological drought (soil water potential below which photosynthesis stops) in 340 semiarid grassland sites over 30 year periods. Relative to control vegetation (climate and site-determined mixes of functional groups), the frequency and duration of drought were increased by shrubs and decreased by annual grasses. The rankings of shrubs, control vegetation, and annual grasses in terms of drought effects were generally consistent in current and future climates, suggesting that current differences among functional groups on drought effects predict future differences. Climate change accompanied by experimentally increased biomass (i.e., the effects of invasions that increase community biomass or management that increases productivity through fertilization or respite from grazing) increased drought frequency and duration and advanced drought onset. Our results suggest that the replacement of perennial temperate semiarid grasslands by shrubs, or increased biomass, can increase ecological drought in both current and future climates.

Functional group, biomass, and climate change effects on ecological drought in semiarid grasslands

USGS Publications Warehouse

Wilson, Scott D.; Schlaepfer, Daniel R.; Bradford, John B.; Lauenroth, William K.; Duniway, Michael C.; Hall, Sonia A.; Jamiyansharav, Khishigbayar; Jia, Gensuo; Lkhagva, Ariuntsetseg; Munson, Seth M.; Pyke, David A.; Tietjen, Britta

2018-01-01

Water relations in plant communities are influenced both by contrasting functional groups (grasses, shrubs) and by climate change via complex effects on interception, uptake and transpiration. We modelled the effects of functional group replacement and biomass increase, both of which can be outcomes of invasion and vegetation management, and climate change on ecological drought (soil water potential below which photosynthesis stops) in 340 semiarid grassland sites over 30‐year periods. Relative to control vegetation (climate and site‐determined mixes of functional groups), the frequency and duration of drought were increased by shrubs and decreased by annual grasses. The rankings of shrubs, control vegetation, and annual grasses in terms of drought effects were generally consistent in current and future climates, suggesting that current differences among functional groups on drought effects predict future differences. Climate change accompanied by experimentally‐increased biomass (i.e. the effects of invasions that increase community biomass, or management that increases productivity through fertilization or respite from grazing) increased drought frequency and duration, and advanced drought onset. Our results suggest that the replacement of perennial temperate semiarid grasslands by shrubs, or increased biomass, can increase ecological drought both in current and future climates.

EXAMINING SOCIOECONOMIC HEALTH DISPARITIES USING A RANK-DEPENDENT RÉNYI INDEX.

PubMed

Talih, Makram

2015-06-01

The Rényi index (RI) is a one-parameter class of indices that summarize health disparities among population groups by measuring divergence between the distributions of disease burden and population shares of these groups. The rank-dependent RI introduced in this paper is a two-parameter class of health disparity indices that also accounts for the association between socioeconomic rank and health; it may be derived from a rank-dependent social welfare function. Two competing classes are discussed and the rank-dependent RI is shown to be more robust to changes in the distribution of either socioeconomic rank or health. The standard error and sampling distribution of the rank-dependent RI are evaluated using linearization and re-sampling techniques, and the methodology is illustrated using health survey data from the U.S. National Health and Nutrition Examination Survey and registry data from the U.S. Surveillance, Epidemiology and End Results Program. Such data underlie many population-based objectives within the U.S. Healthy People 2020 initiative. The rank-dependent RI provides a unified mathematical framework for eliciting various societal positions with regards to the policies that are tied to such wide-reaching public health initiatives. For example, if population groups with lower socioeconomic position were ascertained to be more likely to utilize costly public programs, then the parameters of the RI could be selected to reflect prioritizing those population groups for intervention or treatment.

EXAMINING SOCIOECONOMIC HEALTH DISPARITIES USING A RANK-DEPENDENT RÉNYI INDEX

PubMed Central

Talih, Makram

2015-01-01

The Rényi index (RI) is a one-parameter class of indices that summarize health disparities among population groups by measuring divergence between the distributions of disease burden and population shares of these groups. The rank-dependent RI introduced in this paper is a two-parameter class of health disparity indices that also accounts for the association between socioeconomic rank and health; it may be derived from a rank-dependent social welfare function. Two competing classes are discussed and the rank-dependent RI is shown to be more robust to changes in the distribution of either socioeconomic rank or health. The standard error and sampling distribution of the rank-dependent RI are evaluated using linearization and re-sampling techniques, and the methodology is illustrated using health survey data from the U.S. National Health and Nutrition Examination Survey and registry data from the U.S. Surveillance, Epidemiology and End Results Program. Such data underlie many population-based objectives within the U.S. Healthy People 2020 initiative. The rank-dependent RI provides a unified mathematical framework for eliciting various societal positions with regards to the policies that are tied to such wide-reaching public health initiatives. For example, if population groups with lower socioeconomic position were ascertained to be more likely to utilize costly public programs, then the parameters of the RI could be selected to reflect prioritizing those population groups for intervention or treatment. PMID:26566419

Relationships between genotype x environment interactions and rank orders for a set of genotypes tested in different environments.

PubMed

Hühn, M; Lotito, S; Piepho, H P

1993-09-01

Multilocation trials in plant breeding lead to cross-classified data sets with rows=genotypes and columns=environments, where the breeder is particularly interested in the rank orders of the genotypes in the different environments. Non-identical rank orders are the result of genotype x environment interactions. Not every interaction, however, causes rank changes among the genotypes (rank-interaction). From a breeder's point of view, interaction is tolerable only as long as it does not affect the rank orders. Therefore, the question arises of under which circumstances does interaction become rank-interaction. This paper contributes to our understanding of this topic. In our study we emphasized the detection of relationships between the similarity of the rank orders (measured by Kendall's coefficient of concordance W) and the functions of the diverse variance components (genotypes, environments, interaction, error). On the basis of extensive data sets on different agricultural crops (faba bean, fodder beet, sugar beet, oats, winter rape) obtained from registration trials (1985-1989) carried out in the Federal Republic of Germany, we obtained the following as main result: W ≅ σ 2 (g) /(σ 2 (g) + σ 2 (v) ) where σ 2 (g) =genotypic variance and σ 2 (v) = σ 2 (ge) + σ 2 (o) /L with σ 2 (ge) =interaction variance, σ 2 (o) =error variance and L=number of replications.

Oral symptoms and functional outcome related to oral and oropharyngeal cancer.

PubMed

Kamstra, Jolanda I; Jager-Wittenaar, Harriet; Dijkstra, Pieter U; Huisman, Paulien M; van Oort, Rob P; van der Laan, Bernard F A M; Roodenburg, Jan L N

2011-09-01

This study aimed to assess: (1) oral symptoms of patients treated for oral or oropharyngeal cancer; (2) how patients rank the burden of oral symptoms; (3) the impact of the tumor, the treatment, and oral symptoms on functional outcome. Eighty-nine patients treated for oral or oropharyngeal cancer were asked about their oral symptoms related to mouth opening, dental status, oral sensory function, tongue mobility, salivary function, and pain. They were asked to rank these oral symptoms according to the degree of burden experienced. The Mandibular Function Impairment Questionnaire (MFIQ) was used to assess functional outcome. In a multivariate linear regression analyses, variables related to MFIQ scores (p≤0.10) were entered as predictors with MFIQ score as the outcome. Lack of saliva (52%), restricted mouth opening (48%), and restricted tongue mobility (46%) were the most frequently reported oral symptoms. Lack of saliva was most frequently (32%) ranked as the most burdensome oral symptom. For radiated patients, an inability to wear a dental prosthesis, a T3 or T4 stage, and a higher age were predictive of MFIQ scores. For non-radiated patients, a restricted mouth opening, an inability to wear a dental prosthesis, restricted tongue mobility, and surgery of the mandible were predictive of MFIQ scores. Lack of saliva was not only the most frequently reported oral symptom after treatment for oral or oropharyngeal cancer, but also the most burdensome. Functional outcome is strongly influenced by an inability to wear a dental prosthesis in both radiated and non-radiated patients.

Combined aspirin and cilostazol treatment is associated with reduced platelet aggregation and prevention of exercise-induced platelet activation.

PubMed

Cleanthis, M; Bhattacharya, V; Smout, J; Ashour, H; Stansby, G

2009-05-01

Cilostazol has proven efficacy in increasing walking distance in claudicants, but it has not been demonstrated to be more effective than placebo in secondary cardiovascular prevention. The direct effect of exercise on platelet function remains less well defined. We have investigated the effect of combination treatment with aspirin and cilostazol on platelet activity in claudicants subjected to repeated treadmill exercise. Nineteen claudicants completed a double-blind, randomised, controlled, cross-over trial. Each subject received a 2-week course of aspirin (75mg) and placebo and aspirin and cilostazol (100mg twice daily). Following each 2-week treatment period, patients participated in a standardised treadmill test (3.2kmh(-1), 10 degrees incline) walking to maximal claudication distance. The exercise was repeated thrice in total, and blood was sampled before and after exercise. Platelet activation was measured using free platelet counting aggregation, flow cytometry for surface markers of platelet activation and soluble P-selectin assay. Compared to aspirin and placebo, combination treatment with aspirin and cilostazol was associated with reduced arachidonic-acid-induced platelet aggregation (p<0.01, Wilcoxon signed-rank test). Aspirin and placebo treatment were associated with elevated P-selectin expression, platelet-monocyte aggregation and reduced CD42b expression (p<0.05, Wilcoxon signed-rank test) post-exercise. No difference was seen in spontaneous platelet aggregation whilst soluble P-selectin was reduced post-exercise with combination treatment with aspirin and cilostazol (p<0.05, Wilcoxon signed-rank test). Combination treatment with aspirin and cilostazol results in suppression of platelet activation and reduces the effect of exercise on platelets. The benefit seen may be a result of cilostazol enhancing the inhibitory effect of aspirin on the cyclo-oxygenase pathway.

Religious Penalty in the U.S. News & World Report College Rankings

ERIC Educational Resources Information Center

Baumann, Robert W.; Chu, David K. W.; Anderton, Charles H.

2009-01-01

Since its debut in 1983, the "U.S. News & World Report College Guide" has become the premier "consumer report" of higher education. We find that peer assessment, which is the largest component of the "U.S. News & World Report" ranking function, contains a penalty for religiously affiliated schools that is independent of the other "U.S. News &…

Social status drives social relationships in groups of unrelated female rhesus macaques

PubMed Central

Snyder-Mackler, Noah; Kohn, Jordan N.; Barreiro, Luis B.; Johnson, Zachary P.; Wilson, Mark E.; Tung, Jenny

2015-01-01

Strong social relationships confer health and fitness benefits in a number of species, motivating the need to understand the processes through which they arise. In female cercopithecine primates, both kinship and dominance rank are thought to influence rates of affiliative behaviour and social partner preference. Teasing apart the relative importance of these factors has been challenging, however, as female kin often occupy similar positions in the dominance hierarchy. Here, we isolated the specific effects of rank on social relationships in female rhesus macaques by analysing grooming patterns in 18 social groups that did not contain close relatives, and in which dominance ranks were experimentally randomized. We found that grooming was asymmetrically directed towards higher-ranking females and that grooming bouts temporarily decreased the likelihood of aggression between grooming partners, supporting the idea that grooming is associated with social tolerance. Even in the absence of kin, females formed the strongest grooming relationships with females adjacent to them in rank, a pattern that was strongest for the highest-ranking females. Using simulations, we show that three rules for allocating grooming based on dominance rank recapitulated most of the relationships we observed. Finally, we evaluated whether a female's tendency to engage in grooming behaviour was stable across time and social setting. We found that one measure, the rate of grooming females provided to others (but not the rate of grooming females received), exhibited modest stability after accounting for the primary effect of dominance rank. Together, our findings indicate that dominance rank has strong effects on social relationships in the absence of kin, suggesting the importance of considering social status and social connectedness jointly when investigating their health and fitness consequences. PMID:26769983

Social status drives social relationships in groups of unrelated female rhesus macaques.

PubMed

Snyder-Mackler, Noah; Kohn, Jordan N; Barreiro, Luis B; Johnson, Zachary P; Wilson, Mark E; Tung, Jenny

2016-01-01

Strong social relationships confer health and fitness benefits in a number of species, motivating the need to understand the processes through which they arise. In female cercopithecine primates, both kinship and dominance rank are thought to influence rates of affiliative behaviour and social partner preference. Teasing apart the relative importance of these factors has been challenging, however, as female kin often occupy similar positions in the dominance hierarchy. Here, we isolated the specific effects of rank on social relationships in female rhesus macaques by analysing grooming patterns in 18 social groups that did not contain close relatives, and in which dominance ranks were experimentally randomized. We found that grooming was asymmetrically directed towards higher-ranking females and that grooming bouts temporarily decreased the likelihood of aggression between grooming partners, supporting the idea that grooming is associated with social tolerance. Even in the absence of kin, females formed the strongest grooming relationships with females adjacent to them in rank, a pattern that was strongest for the highest-ranking females. Using simulations, we show that three rules for allocating grooming based on dominance rank recapitulated most of the relationships we observed. Finally, we evaluated whether a female's tendency to engage in grooming behaviour was stable across time and social setting. We found that one measure, the rate of grooming females provided to others (but not the rate of grooming females received), exhibited modest stability after accounting for the primary effect of dominance rank. Together, our findings indicate that dominance rank has strong effects on social relationships in the absence of kin, suggesting the importance of considering social status and social connectedness jointly when investigating their health and fitness consequences.

Targeting receptor-activator of nuclear kappaB ligand in aneurysmal bone cysts: verification of target and therapeutic response.

PubMed

Pelle, Dominic W; Ringler, Jonathan W; Peacock, Jacqueline D; Kampfschulte, Kevin; Scholten, Donald J; Davis, Mary M; Mitchell, Deanna S; Steensma, Matthew R

2014-08-01

Aneurysmal bone cyst (ABC) is a benign tumor of bone presenting as a cystic, expansile lesion in both the axial and appendicular skeleton. Axial lesions demand special consideration, because treatment-related morbidity can be devastating. In similar lesions, such as giant cell tumor of bone (GCTB), the receptor-activator of nuclear kappaB ligand (RANKL)-receptor-activator of nuclear kappaB (RANK) signaling axis is essential to tumor progression. Although ABC and GCTB are distinct entities, they both contain abundant multinucleated giant cells and are osteolytic characteristically. We hypothesize that ABCs express both RANKL and RANK similarly in a cell-type specific manner, and that targeted RANKL therapy will mitigate ABC tumor progression. Cellular expression of RANKL and RANK was determined in freshly harvested ABC samples using laser confocal microscopy. A consistent cell-type-specific pattern was observed: fibroblastlike stromal cells expressed RANKL strongly whereas monocyte/macrophage precursor and multinucleated giant cells expressed RANK. Relative RANKL expression was determined by quantitative real-time polymerase chain reaction in ABC and GCTB tissue samples; no difference in relative expression was observed (P > 0.05). In addition, we review the case of a 5-year-old boy with a large, aggressive sacral ABC. After 3 months of targeted RANKL inhibition with denosumab, magnetic resonance imaging demonstrated tumor shrinkage, bone reconstitution, and healing of a pathologic fracture. Ambulation, and bowel and bladder function were restored at 6 months. Denosumab treatment was well tolerated. Post hoc analysis demonstrated strong RANKL expression in the pretreatment tumor sample. These findings demonstrate that RANKL-RANK signal activation is essential to ABC tumor progression. RANKL-targeted therapy may be an effective alternative to surgery in select ABC presentations. Copyright © 2014 Mosby, Inc. All rights reserved.

Association of PAX4 genetic variants with oral antidiabetic drugs efficacy in Chinese type 2 diabetes patients.

PubMed

Chen, M; Hu, C; Zhang, R; Jiang, F; Wang, J; Peng, D; Tang, S; Sun, X; Yan, J; Luo, Y; Bao, Y; Jia, W

2014-10-01

The aim of this study was to investigate the association of PAX4 variants with therapeutic effect of oral antidiabetic drugs in Chinese type 2 diabtes mellitus (T2DM) patients. A total of 209 newly diagnosed T2DM patients were randomly assigned to treatment with repaglinide or rosiglitazone for 48 weeks, and the therapeutic effects were compared. In the rosiglitazone cohort, rs6467136 GA+AA carriers showed greater decrease in 2-h glucose levels (P=0.0063) and higher cumulative attainment rates of target 2-h glucose levels (Plog rank=0.0093) than GG homozygotes. In the subgroup with defective β-cell function, rs6467136 GA+AA carriers exhibited greater decrements of 2-h glucose level and improvement of homeostasis model assessment of insulin resistance (P=0.0143). Moreover, GA+AA carriers were more likely to attain the target fasting and 2-h glucose level (Plog rank=0.0091 and 0.007, respectively). However, these single-nucleotide polymorphisms showed no effect on repaglinide efficacy. In conclusion, PAX4 variant rs6467136 was associated with the therapeutic effect of rosiglitazone in Chinese T2DM patients.

Daily Interpersonal Experience Partially Explains the Association Between Social Rank and Physical Health.

PubMed

Cundiff, Jenny M; Kamarck, Thomas W; Manuck, Stephen B

2016-12-01

Socioeconomic position is a well-established risk factor for poor physical health. This study examines whether the effects of lower social rank on physical health may be accounted for by differences in daily social experience. In a large community sample (N = 475), we examined whether subjective social rank is associated with self-rated health, in part, through positive and negative perceptions of daily interpersonal interactions, assessed using ecological momentary assessment. Higher social rank was associated with higher average perceived positivity of social interactions in daily life (e.g., B = .18, p < .001), but not with perceived negativity of social interactions. Further, the association between social rank and self-rated physical health was partially accounted for by differences in perceived positivity of social interactions. This effect was independent of well-characterized objective markers of SES and personality traits. Differences in the quality of day-to-day social interactions is a viable pathway linking lower social rank to poorer physical health.

Kinetic model of turbulence in an incompressible fluid

NASA Technical Reports Server (NTRS)

Tchen, C. M.

1978-01-01

A statistical description of turbulence in an incompressible fluid obeying the Navier-Stokes equations is proposed, where pressure is regarded as a potential for the interaction between fluid elements. A scaling procedure divides a fluctuation into three ranks representing the three transport processes of macroscopic evolution, transport property, and relaxation. Closure is obtained by relaxation, and a kinetic equation is obtained for the fluctuation of the macroscopic rank of the distribution function. The solution gives the transfer function and eddy viscosity. When applied to the inertia subrange of the energy spectrum the analysis recovers the Kolmogorov law and its numerical coefficient.

[The reproductive correlates of social hierarchy in laboratory male mice].

PubMed

Osadchuk, L B; Salomacheva, I N; Bragin, A V; Osadchuk, A V

2007-01-01

In laboratory male mice the effects of social hierarchy on hormonal and spermatogenic testicular function, accessory organs and testicular weights, sexual behaviour have been investigated using an experimental model of social hierarchy, which is characterised by a minimal size (two male mice) and 5 days period of social interactions. The social rank of the partners was detected by asymmetry in aggressive behaviour. Using the experimental condition, when the both partners have no preferences for exclusive use of area we demonstrated that there were no rank differences in the number of mounts and testicular testosterone content. Nevertheless a rank asymmetry in the male sniffing behaviour towards a receptive female, weights of the testes, seminal vesicles, epididymes and the number of epididymal sperm was kept up in a stable social group. Social dominance was found to affect negatively on testicular testosterone increase in response to introduction of a receptive female and sexual attractiveness of male to a receptive female in both dominant and subordinate males. The results obtained demonstrate the impact of social hierarchy on reproduction in laboratory male mice, particular in respect of spermatogenesis and the testicular testosterone in response to a receptive female.

A Bayesian hierarchical model for discrete choice data in health care.

PubMed

Antonio, Anna Liza M; Weiss, Robert E; Saigal, Christopher S; Dahan, Ely; Crespi, Catherine M

2017-01-01

In discrete choice experiments, patients are presented with sets of health states described by various attributes and asked to make choices from among them. Discrete choice experiments allow health care researchers to study the preferences of individual patients by eliciting trade-offs between different aspects of health-related quality of life. However, many discrete choice experiments yield data with incomplete ranking information and sparsity due to the limited number of choice sets presented to each patient, making it challenging to estimate patient preferences. Moreover, methods to identify outliers in discrete choice data are lacking. We develop a Bayesian hierarchical random effects rank-ordered multinomial logit model for discrete choice data. Missing ranks are accounted for by marginalizing over all possible permutations of unranked alternatives to estimate individual patient preferences, which are modeled as a function of patient covariates. We provide a Bayesian version of relative attribute importance, and adapt the use of the conditional predictive ordinate to identify outlying choice sets and outlying individuals with unusual preferences compared to the population. The model is applied to data from a study using a discrete choice experiment to estimate individual patient preferences for health states related to prostate cancer treatment.

A Fuzzy analytical hierarchy process approach in irrigation networks maintenance

NASA Astrophysics Data System (ADS)

Riza Permana, Angga; Rintis Hadiani, Rr.; Syafi'i

2017-11-01

Ponorogo Regency has 440 Irrigation Area with a total area of 17,950 Ha. Due to the limited budget and lack of maintenance cause decreased function on the irrigation. The aim of this study is to make an appropriate system to determine the indices weighted of the rank prioritization criteria for irrigation network maintenance using a fuzzy-based methodology. The criteria that are used such as the physical condition of irrigation networks, area of service, estimated maintenance cost, and efficiency of irrigation water distribution. 26 experts in the field of water resources in the Dinas Pekerjaan Umum were asked to fill out the questionnaire, and the result will be used as a benchmark to determine the rank of irrigation network maintenance priority. The results demonstrate that the physical condition of irrigation networks criterion (W1) = 0,279 has the greatest impact on the assessment process. The area of service (W2) = 0,270, efficiency of irrigation water distribution (W4) = 0,249, and estimated maintenance cost (W3) = 0,202 criteria rank next in effectiveness, respectively. The proposed methodology deals with uncertainty and vague data using triangular fuzzy numbers, and, moreover, it provides a comprehensive decision-making technique to assess maintenance priority on irrigation network.

Characteristics of Single-Event Upsets in a Fabric Switch (ADS151)

NASA Technical Reports Server (NTRS)

Buchner, Stephen; Carts, Martin A.; McMorrow, Dale; Kim, Hak; Marshall, Paul W.; LaBel, Kenneth A.

2003-01-01

Abstract-Two types of single event effects - bit errors and single event functional interrupts - were observed during heavy-ion testing of the AD8151 crosspoint switch. Bit errors occurred in bursts with the average number of bits in a burst being dependent on both the ion LET and on the data rate. A pulsed laser was used to identify the locations on the chip where the bit errors and single event functional interrupts occurred. Bit errors originated in the switches, drivers, and output buffers. Single event functional interrupts occurred when the laser was focused on the second rank latch containing the data specifying the state of each switch in the 33x17 matrix.

RANK-c attenuates aggressive properties of ER-negative breast cancer by inhibiting NF-κB activation and EGFR signaling.

PubMed

Sirinian, Chaido; Papanastasiou, Anastasios D; Schizas, Michail; Spella, Magda; Stathopoulos, Georgios T; Repanti, Maria; Zarkadis, Ioannis K; King, Tari A; Kalofonos, Haralabos P

2018-05-29

The RANK/RANKL axis emerges as a key regulator of breast cancer initiation, progression, and metastasis. RANK-c is a RANK receptor isoform produced through alternative splicing of the TNFRSF11A (RANK) gene and a dominant-negative regulator of RANK-induced nuclear factor-κB (NF-κB) activation. Here we report that RANK-c transcript is expressed in 3.2% of cases in The Cancer Genome Atlas breast cancer cohort evenly between ER-positive and ER-negative cases. Nevertheless, the ratio of RANK to RANK-c (RANK/RANK-c) is increased in ER-negative breast cancer cell lines compared to ER-positive breast cancer cell lines. In addition, forced expression of RANK-c in ER-negative breast cancer cell lines inhibited stimuli-induced NF-κB activation and attenuated migration, invasion, colony formation, and adhesion of cancer cells. Further, RANK-c expression in MDA-MB-231 cells inhibited lung metastasis and colonization in vivo. The RANK-c-mediated inhibition of cancer cell aggressiveness and nuclear factor-κB (NF-κB) activation in breast cancer cells seems to rely on a RANK-c/TNF receptor-associated factor-2 (TRAF2) protein interaction. This was further confirmed by a mutated RANK-c that is unable to interact with TRAF2 and abolishes the ability to attenuate NF-κB activation, migration, and invasion. Additional protein interaction characterization revealed epidermal growth factor receptor (EGFR) as a novel interacting partner for RANK-c in breast cancer cells with a negative effect on EGFR phosphorylation and EGF-dependent downstream signaling pathway activation. Our findings further elucidate the complex molecular biology of the RANKL/RANK system in breast cancer and provide preliminary data for RANK-c as a possible marker for disease progression and aggressiveness.

Harassment of adults by immatures in bonobos (Pan paniscus): testing the Exploratory Aggression and Rank Improvement hypotheses.

PubMed

Boose, Klaree; White, Frances

2017-10-01

The immatures of many primate species frequently pester adult group members with aggressive behaviors referred to as a type of harassment. Although these behaviors are characteristic of immatures as they develop from infancy through adolescence, there have been few studies that specifically address the adaptive significance of harassment. Two functional hypotheses have been generated from observations of the behavior in chimpanzees. The Exploratory Aggression hypothesis describes harassment as a mechanism used by immatures to learn about the parameters of aggression and dominance behavior and to acquire information about novel, complex, or unpredictable relationships. The Rank Improvement hypothesis describes harassment as a mechanism of dominance acquisition used by immatures to outrank adults. This study investigated harassment of adults by immatures in a group of bonobos housed at the Columbus Zoo and compared the results to the predictions outlined by the Exploratory Aggression and Rank Improvement hypotheses. Although all immature bonobos in this group harassed adults, adolescents performed the behavior more frequently than did infants or juveniles and low-ranking adults were targeted more frequently than high-ranking. Targets responded more with agonistic behaviors than with neutral behaviors and the amount of harassment an individual received was significantly correlated with the amount of agonistic responses given. Furthermore, bouts of harassment were found to continue significantly more frequently when responses were agonistic than when they were neutral. Adolescents elicited mostly agonistic responses from targets whereas infants and juveniles received mostly neutral responses. These results support predictions from each hypothesis where harassment functions both as a mechanism of social exploration and as a tool to establish dominance rank.

Penalized nonparametric scalar-on-function regression via principal coordinates

PubMed Central

Reiss, Philip T.; Miller, David L.; Wu, Pei-Shien; Hua, Wen-Yu

2016-01-01

A number of classical approaches to nonparametric regression have recently been extended to the case of functional predictors. This paper introduces a new method of this type, which extends intermediate-rank penalized smoothing to scalar-on-function regression. In the proposed method, which we call principal coordinate ridge regression, one regresses the response on leading principal coordinates defined by a relevant distance among the functional predictors, while applying a ridge penalty. Our publicly available implementation, based on generalized additive modeling software, allows for fast optimal tuning parameter selection and for extensions to multiple functional predictors, exponential family-valued responses, and mixed-effects models. In an application to signature verification data, principal coordinate ridge regression, with dynamic time warping distance used to define the principal coordinates, is shown to outperform a functional generalized linear model. PMID:29217963

Generalization Performance of Regularized Ranking With Multiscale Kernels.

PubMed

Zhou, Yicong; Chen, Hong; Lan, Rushi; Pan, Zhibin

2016-05-01

The regularized kernel method for the ranking problem has attracted increasing attentions in machine learning. The previous regularized ranking algorithms are usually based on reproducing kernel Hilbert spaces with a single kernel. In this paper, we go beyond this framework by investigating the generalization performance of the regularized ranking with multiscale kernels. A novel ranking algorithm with multiscale kernels is proposed and its representer theorem is proved. We establish the upper bound of the generalization error in terms of the complexity of hypothesis spaces. It shows that the multiscale ranking algorithm can achieve satisfactory learning rates under mild conditions. Experiments demonstrate the effectiveness of the proposed method for drug discovery and recommendation tasks.

Patient Preferences and Urologist Judgments on Prostate Cancer Therapy in Japan.

PubMed

Nakayama, Masahiko; Kobayashi, Hisanori; Okazaki, Masateru; Imanaka, Keiichiro; Yoshizawa, Kazutake; Mahlich, Jörg

2018-05-01

The purpose of the present study is to investigate the concordance of treatment preferences between patients and physicians in prostate cancer (PCa) in Japan. An internet-based discrete choice experiment was conducted. Patients and physicians were asked to select their preferred treatment from a pair of hypothetical treatments consisting of four attributes: quality of life (QOL), treatment effectiveness, side effects, and accessibility of treatment. The data were analyzed using a conditional logistic regression model to calculate coefficients and the relative importance (RI) of each attribute. A total of 103 PCa patients and 127 physicians responded. The study looked at 37 patients considered as advanced PCa and 66 who were non-advanced PCa. All of the physicians were urologists. Advanced PCa patients ranked the attributes as follows: treatment effectiveness (RI: 32%), accessibility of treatment (RI: 26%), QOL (RI: 23%), and side effects (RI: 19%). For physicians, the RI ranking was the same as for advanced PCa patients; treatment effectiveness (RI: 29%), accessibility of treatment (RI: 27%), QOL (RI: 26%), and side effects (RI: 18%). For non-advanced PCa patients, accessibility of treatment ranked the highest RI (27%) and treatment effectiveness ranked as the lowest RI (14%). Our study suggests that the ranking of the attributes was consistent between advanced PCa patients and physicians. The most influential attribute was treatment effectiveness. Treatment preferences also vary by disease stage.

Low-dose cerebral perfusion computed tomography image restoration via low-rank and total variation regularizations

PubMed Central

Niu, Shanzhou; Zhang, Shanli; Huang, Jing; Bian, Zhaoying; Chen, Wufan; Yu, Gaohang; Liang, Zhengrong; Ma, Jianhua

2016-01-01

Cerebral perfusion x-ray computed tomography (PCT) is an important functional imaging modality for evaluating cerebrovascular diseases and has been widely used in clinics over the past decades. However, due to the protocol of PCT imaging with repeated dynamic sequential scans, the associative radiation dose unavoidably increases as compared with that used in conventional CT examinations. Minimizing the radiation exposure in PCT examination is a major task in the CT field. In this paper, considering the rich similarity redundancy information among enhanced sequential PCT images, we propose a low-dose PCT image restoration model by incorporating the low-rank and sparse matrix characteristic of sequential PCT images. Specifically, the sequential PCT images were first stacked into a matrix (i.e., low-rank matrix), and then a non-convex spectral norm/regularization and a spatio-temporal total variation norm/regularization were then built on the low-rank matrix to describe the low rank and sparsity of the sequential PCT images, respectively. Subsequently, an improved split Bregman method was adopted to minimize the associative objective function with a reasonable convergence rate. Both qualitative and quantitative studies were conducted using a digital phantom and clinical cerebral PCT datasets to evaluate the present method. Experimental results show that the presented method can achieve images with several noticeable advantages over the existing methods in terms of noise reduction and universal quality index. More importantly, the present method can produce more accurate kinetic enhanced details and diagnostic hemodynamic parameter maps. PMID:27440948

Conformal and Nearly Conformal Theories at Large N

NASA Astrophysics Data System (ADS)

Tarnoplskiy, Grigory M.

In this thesis we present new results in conformal and nearly conformal field theories in various dimensions. In chapter two, we study different properties of the conformal Quantum Electrodynamics (QED) in continuous dimension d. At first we study conformal QED using large Nf methods, where Nf is the number of massless fermions. We compute its sphere free energy as a function of d, ignoring the terms of order 1/Nf and higher. For finite Nf we use the epsilon-expansion. Next we use a large Nf diagrammatic approach to calculate the leading corrections to CT, the coefficient of the two-point function of the stress-energy tensor, and CJ, the coefficient of the two-point function of the global symmetry current. We present explicit formulae as a function of d and check them versus the expectations in 2 and 4 - epsilon dimensions. In chapter three, we discuss vacuum stability in 1 + 1 dimensional conformal field theories with external background fields. We show that the vacuum decay rate is given by a non-local two-form. This two-form is a boundary term that must be added to the effective in/out Lagrangian. The two-form is expressed in terms of a Riemann-Hilbert decomposition for background gauge fields, and is given by its novel "functional'' version in the gravitational case. In chapter four, we explore Tensor models. Such models possess the large N limit dominated by the melon diagrams. The quantum mechanics of a real anti-commuting rank-3 tensor has a large N limit similar to the Sachdev-Ye-Kitaev (SYK) model. We also discuss the quantum mechanics of a complex 3-index anti-commuting tensor and argue that it is equivalent in the large N limit to a version of SYK model with complex fermions. Finally, we discuss models of a commuting tensor in dimension d. We study the spectrum of the large N quantum field theory of bosonic rank-3 tensors using the Schwinger-Dyson equations. We compare some of these results with the 4 - epsilon expansion, finding perfect agreement. We also study the spectra of bosonic theories of rank q - 1 tensors with φq interactions.

Identification of Functionally Related Enzymes by Learning-to-Rank Methods.

PubMed

Stock, Michiel; Fober, Thomas; Hüllermeier, Eyke; Glinca, Serghei; Klebe, Gerhard; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem

2014-01-01

Enzyme sequences and structures are routinely used in the biological sciences as queries to search for functionally related enzymes in online databases. To this end, one usually departs from some notion of similarity, comparing two enzymes by looking for correspondences in their sequences, structures or surfaces. For a given query, the search operation results in a ranking of the enzymes in the database, from very similar to dissimilar enzymes, while information about the biological function of annotated database enzymes is ignored. In this work, we show that rankings of that kind can be substantially improved by applying kernel-based learning algorithms. This approach enables the detection of statistical dependencies between similarities of the active cleft and the biological function of annotated enzymes. This is in contrast to search-based approaches, which do not take annotated training data into account. Similarity measures based on the active cleft are known to outperform sequence-based or structure-based measures under certain conditions. We consider the Enzyme Commission (EC) classification hierarchy for obtaining annotated enzymes during the training phase. The results of a set of sizeable experiments indicate a consistent and significant improvement for a set of similarity measures that exploit information about small cavities in the surface of enzymes.

Effects of sociodemographic, treatment variables, and medical characteristics on quality of life of patients with maxillectomy restored with obturator prostheses.

PubMed

Artopoulou, Ioli Ioanna; Karademas, Evangelos C; Papadogeorgakis, Nikolaos; Papathanasiou, Ioannis; Polyzois, Gregory

2017-12-01

Restoration of maxillary defects resulting from tumor ablative surgery presents a difficult challenge, with both functional and esthetic issues. Whether rehabilitation with an obturator prosthesis could significantly contribute to improved quality of life in patients with maxillary resection has been scarcely studied, with relatively small study samples. The purpose of this survey study was to assess the overall functioning of the obturator prosthesis and the effect of specific sociodemographic, medical, and treatment variables on obturator functioning and quality of life in patients with maxillectomy. Global quality of life (QOL) and satisfaction with the obturator prosthesis of 57 patients who underwent maxillectomy and prosthetic rehabilitation at the National and Kapodistrian University of Athens were assessed using 3 questionnaires: European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire C30 (QLQ-C30), the EORTC QLQ-HN35, and the obturator functioning scale. The data were analyzed using the Kruskal-Wallis 1-way ANOVA on ranks, hierarchical multiple regression analysis, and the Spearman rank order correlation (α=.05). Satisfactory functioning of the obturator prosthesis was the most significant predictor of improved QOL (P<.05). QOL was significantly related to additional treatments (P<.05), the size of the primary tumor (P<.05), and the size of the maxillectomy defect (P<.05). The most significant predictors of good obturator functioning were additional treatments (P<.01), age at the time of surgery (P<.05), presence of mandibular teeth (P<.05), and previous maxillary removable prosthetic experience (P<.05). Obturator functioning scale appearance and insertion subscales (r=0.47, P<.01), followed by speech (r=0.42, P<.01), were significantly related to better QOL. A well-functioning obturator prosthesis was the most significant determinant for improved QOL in patients with maxillary resection. Age at the time of surgery, adjuvant treatments, presence of mandibular teeth, and previous maxillary removable prosthetic experience were the most significant predictors for better obturator functioning, whereas the size of the maxillectomy defect had a significant effect on QOL but did not influence the functional outcome. Copyright © 2017 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

Russian Practices in Rating the Effectiveness of University Programs

ERIC Educational Resources Information Center

Balatskii, E.

2014-01-01

Russian universities do not do well in international rankings. Recent attempts in Russia to create different forms of ranking are aimed at reflecting what strengths universities there may have, but it is up to the universities themselves to find ways to better characterize themselves in existing systems of ranking.

H-index of Collective Health professors in Brazil.

PubMed

Pereira, Julio Cesar Rodrigues; Bronhara, Bruna

2011-06-01

To estimate reference values and the hierarchy function of professors engaged in Collective Health in Brazil by analyzing the distribution of the h-index. From the Portal da Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Portal of Coordination for the Improvement of Higher Education Personnel ), 934 authors were identified in 2008, of whom 819 were analyzed. The h-index of each professor was obtained through the Web of Science using search algorithms controlling for namesakes and alternative spellings of their names. For each Brazilian region and for the country as a whole, we adjusted an exponential probability density function to provide the population parameters and rate of decline by region. Ranking measures were identified using the complement of the cumulative probability function and the hierarchy function among authors according to the h-index by region. Among the professors analyzed, 29.8% had no citation record in Web of Science (h=0). The mean h for the country was 3.1, and the region with greatest mean was the southern region (h=4.7). The median h for the country was 3.1, and the greatest median was for the southern region (3.2). Standardizing populations to one hundred, the first rank in the country was h=16, but stratification by region shows that, within the northeastern, southeastern and southern regions, a greater value is necessary for achieving the first rank. In the southern region, the index needed to achieve the first rank was h=24. Most of the Brazilian Collective Health authors, if assessed on the basis of the Web of Science h-index, did not exceed h=5. Regional differences exist, with the southeastern and northeastern regions being similar and the southern region being outstanding.

CT Image Sequence Restoration Based on Sparse and Low-Rank Decomposition

PubMed Central

Gou, Shuiping; Wang, Yueyue; Wang, Zhilong; Peng, Yong; Zhang, Xiaopeng; Jiao, Licheng; Wu, Jianshe

2013-01-01

Blurry organ boundaries and soft tissue structures present a major challenge in biomedical image restoration. In this paper, we propose a low-rank decomposition-based method for computed tomography (CT) image sequence restoration, where the CT image sequence is decomposed into a sparse component and a low-rank component. A new point spread function of Weiner filter is employed to efficiently remove blur in the sparse component; a wiener filtering with the Gaussian PSF is used to recover the average image of the low-rank component. And then we get the recovered CT image sequence by combining the recovery low-rank image with all recovery sparse image sequence. Our method achieves restoration results with higher contrast, sharper organ boundaries and richer soft tissue structure information, compared with existing CT image restoration methods. The robustness of our method was assessed with numerical experiments using three different low-rank models: Robust Principle Component Analysis (RPCA), Linearized Alternating Direction Method with Adaptive Penalty (LADMAP) and Go Decomposition (GoDec). Experimental results demonstrated that the RPCA model was the most suitable for the small noise CT images whereas the GoDec model was the best for the large noisy CT images. PMID:24023764

Constrained Low-Rank Learning Using Least Squares-Based Regularization.

PubMed

Li, Ping; Yu, Jun; Wang, Meng; Zhang, Luming; Cai, Deng; Li, Xuelong

2017-12-01

Low-rank learning has attracted much attention recently due to its efficacy in a rich variety of real-world tasks, e.g., subspace segmentation and image categorization. Most low-rank methods are incapable of capturing low-dimensional subspace for supervised learning tasks, e.g., classification and regression. This paper aims to learn both the discriminant low-rank representation (LRR) and the robust projecting subspace in a supervised manner. To achieve this goal, we cast the problem into a constrained rank minimization framework by adopting the least squares regularization. Naturally, the data label structure tends to resemble that of the corresponding low-dimensional representation, which is derived from the robust subspace projection of clean data by low-rank learning. Moreover, the low-dimensional representation of original data can be paired with some informative structure by imposing an appropriate constraint, e.g., Laplacian regularizer. Therefore, we propose a novel constrained LRR method. The objective function is formulated as a constrained nuclear norm minimization problem, which can be solved by the inexact augmented Lagrange multiplier algorithm. Extensive experiments on image classification, human pose estimation, and robust face recovery have confirmed the superiority of our method.

Capital death in the world market

NASA Astrophysics Data System (ADS)

Avakian, Adam; Podobnik, Boris; Piskor, Manuela; Stanley, H. Eugene

2014-03-01

We study the gross domestic product (GDP) per capita together with the market capitalization (MCAP) per capita as two indicators of the effect of globalization. We find that g, the GDP per capita, as a function of m, the MCAP per capita, follows a power law with average exponent close to 1/3. In addition, the Zipf ranking approach confirms that the m for countries with initially lower values of m tends to grow more rapidly than for countries with initially larger values of m. If the trends over the past 20 years continue to hold in the future, then the Zipf ranking approach leads to the prediction that in about 50 years, all countries participating in globalization will have comparable values of their MCAP per capita. We call this economic state "capital death," in analogy to the physics state of "heat death" predicted by thermodynamic arguments.

Efficacy of antidepressive medication for depression in Parkinson disease: a network meta-analysis

PubMed Central

Zhuo, Chuanjun; Xue, Rong; Luo, Lanlan; Ji, Feng; Tian, Hongjun; Qu, Hongru; Lin, Xiaodong; Jiang, Ronghuan; Tao, Ran

2017-01-01

Abstract Background: Parkinson disease (PD) was considered as the 2nd most prevalent neurodegenerative disorder after Alzheimer disease, while depression is a prevailing nonmotor symptom of PD. Typically used antidepression medication includes tricyclic antidepressants (TCA), selective serotonin reuptake inhibitors (SSRI), serotonin and norepinephrine reuptake inhibitors (SNRI), monoamine-oxidase inhibitors (MAOI), and dopamine agonists (DA). Our study aimed at evaluating the efficacy of antidepressive medications for depression of PD. Methods: Web of Science, PubMed, Embase, and the Cochrane library were searched for related articles. Traditional meta-analysis and network meta-analysis (NMA) were performed with outcomes including depression score, UPDRS-II, UPDRS-III, and adverse effects. Surface under the cumulative ranking curve (SUCRA) was also performed to illustrate the rank probabilities of different medications on various outcomes. The consistency of direct and indirect evidence was also assessed by node-splitting method. Results: Results of traditional pairwise meta-analysis were performed. Concerning depression score, significant improvement was observed in AD, MAOI, SSRI, and SNRI compared with placebo. NMA was performed and more information could be obtained. DA was illustrated to be effective over placebo concerning UPDRS-III, MAOI, and SNRI. DA demonstrated a better prognosis in UPDRS-II scores compared with placebo and MAOI. However, DA and SSRI demonstrated a significant increase in adverse effects compared with placebo. The SUCRA value was calculated to evaluate the ranking probabilities of all medications on investigated outcomes, and the consistency between direct and indirect evidences was assessed by node-splitting method. Conclusion: SSRI had a satisfying efficacy for the depression of PD patients and could improve activities of daily living and motor function of patient but the adverse effects are unneglectable. SNRI are the safest medication with high efficacy for depression as well while other outcomes are relatively poor. PMID:28562526

Max-margin multiattribute learning with low-rank constraint.

PubMed

Zhang, Qiang; Chen, Lin; Li, Baoxin

2014-07-01

Attribute learning has attracted a lot of interests in recent years for its advantage of being able to model high-level concepts with a compact set of midlevel attributes. Real-world objects often demand multiple attributes for effective modeling. Most existing methods learn attributes independently without explicitly considering their intrinsic relatedness. In this paper, we propose max margin multiattribute learning with low-rank constraint, which learns a set of attributes simultaneously, using only relative ranking of the attributes for the data. By learning all the attributes simultaneously through low-rank constraint, the proposed method is able to capture their intrinsic correlation for improved learning; by requiring only relative ranking, the method avoids restrictive binary labels of attributes that are often assumed by many existing techniques. The proposed method is evaluated on both synthetic data and real visual data including a challenging video data set. Experimental results demonstrate the effectiveness of the proposed method.

Effects of normalization on quantitative traits in association test

PubMed Central

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Alternatives to the use of antimicrobial agents in pig production: A multi-country expert-ranking of perceived effectiveness, feasibility and return on investment.

PubMed

Postma, Merel; Stärk, Katharina D C; Sjölund, Marie; Backhans, Annette; Beilage, Elisabeth Grosse; Lösken, Svenja; Belloc, Catherine; Collineau, Lucie; Iten, Denise; Visschers, Vivianne; Nielsen, Elisabeth O; Dewulf, Jeroen

2015-03-01

Nineteen alternatives to antimicrobial agents were ranked on perceived effectiveness, feasibility and return on investment (ROI) from 0 (not effective, not feasible, no ROI) to 10 (fully effective, completely feasible, maximum ROI) by 111 pig health experts from Belgium, Denmark, France, Germany, Sweden and Switzerland. The top 5 measures in terms of perceived effectiveness were (1) improved internal biosecurity, (2) improved external biosecurity, (3) improved climate/environmental conditions, (4) high health/Specific Pathogen Free/disease eradication and (5) increased vaccination. The top 5 measures in terms of perceived feasibility were (1) increased vaccination, (2) increased use of anti-inflammatory products, (3) improved water quality, (4) feed quality/optimization and (5) use of zinc/metals. The top 5 measures in terms of perceived ROI were (1) improved internal biosecurity, (2) zinc/metals, (3) diagnostics/action plan, (4) feed quality/optimization and (5) climate/environmental improvements. Univariate linear regression showed that veterinary practitioners rank internal biosecurity, vaccination, use of zinc/metals, feed quality optimization and climate/environmental on average highest, while researchers and professors focused more on increased use of diagnostics and action plans. Financial incentives/penalties ranked low in all countries. Belgian respondents ranked feed quality significantly lower compared to the German respondents while reduction of stocking density was ranked higher in Belgium compared to Denmark. Categorical Principal Component Analysis applied to the average ranking supported the finding that veterinary practitioners had a preference for more practical, common and already known alternatives. The results showed that improvements in biosecurity, increased use of vaccination, use of zinc/metals, feed quality improvement and regular diagnostic testing combined with a clear action plan were perceived to be the most promising alternatives to antimicrobials in industrial pig production based on combined effectiveness, feasibility and ROI. Copyright © 2015 Elsevier B.V. All rights reserved.

Similarity preserving low-rank representation for enhanced data representation and effective subspace learning.

PubMed

Zhang, Zhao; Yan, Shuicheng; Zhao, Mingbo

2014-05-01

Latent Low-Rank Representation (LatLRR) delivers robust and promising results for subspace recovery and feature extraction through mining the so-called hidden effects, but the locality of both similar principal and salient features cannot be preserved in the optimizations. To solve this issue for achieving enhanced performance, a boosted version of LatLRR, referred to as Regularized Low-Rank Representation (rLRR), is proposed through explicitly including an appropriate Laplacian regularization that can maximally preserve the similarity among local features. Resembling LatLRR, rLRR decomposes given data matrix from two directions by seeking a pair of low-rank matrices. But the similarities of principal and salient features can be effectively preserved by rLRR. As a result, the correlated features are well grouped and the robustness of representations is also enhanced. Based on the outputted bi-directional low-rank codes by rLRR, an unsupervised subspace learning framework termed Low-rank Similarity Preserving Projections (LSPP) is also derived for feature learning. The supervised extension of LSPP is also discussed for discriminant subspace learning. The validity of rLRR is examined by robust representation and decomposition of real images. Results demonstrated the superiority of our rLRR and LSPP in comparison to other related state-of-the-art algorithms. Copyright © 2014 Elsevier Ltd. All rights reserved.

Global-change drivers of ecosystem functioning modulated by natural variability and saturating responses.

PubMed

Flombaum, Pedro; Yahdjian, Laura; Sala, Osvaldo E

2017-02-01

Humans are altering global environment at an unprecedented rate through changes in biodiversity, climate, nitrogen cycle, and land use. To address their effects on ecosystem functioning, experiments most frequently explore one driver at a time and control as many confounding factors as possible. Yet, which driver exerts the largest influence on ecosystem functioning and whether their relative importance changes among systems remain unclear. We analyzed experiments in the Patagonian steppe that evaluated the aboveground net primary production (ANPP) response to manipulated gradients of species richness, precipitation, temperature, nitrogen fertilization (N), and grazing intensity. We compared the effect on ANPP relative to ambient conditions considering intensity and direction of manipulations for each driver. The ranking of responses to drivers with comparable manipulation intensity was as follows: biodiversity>grazing>precipitation>N. For a similar intensity of manipulation, the effect of biodiversity loss was 4.0, 3.6, and 1.5, times larger than N deposition, decreased precipitation, and increased grazing intensity. We interpreted our results considering two hypotheses. First, the response of ANPP to changes in precipitation and biodiversity is saturating, so we expected larger effects when the driver was reduced, relative to ambient conditions, than when it was increased. Experimental manipulations that reduced ambient levels had larger effects than those that increased them. Second, the sensitivity of ANPP to each driver is inversely related to the natural variability of the driver. In Patagonia, the ranking of natural variability of drivers is as follows: precipitation>grazing>temperature>biodiversity>N. So, in general, the ecosystem was most sensitive to drivers that varied the least. Comparable results from Cedar Creek (MN) support both hypotheses and suggest that sensitivity to drivers varies among ecosystem types. Given the importance of understanding ecosystem sensitivity to predict global-change impacts, it is necessary to design new experiments located in regions with contrasting natural variability and that include the full range of drivers. © 2016 John Wiley & Sons Ltd.

The Marketing of Canadian University Rankings: A Misadventure Now 24 Years Old

ERIC Educational Resources Information Center

Cramer, Kenneth M.; Page, Stewart; Burrows, Vanessa; Lamoureux, Chastine; Mackay, Sarah; Pedri, Victoria; Pschibul, Rebecca

2016-01-01

Based on analyses of Maclean's ranking data pertaining to Canadian universities published over the last 24 years, we present a summary of statistical findings of annual ranking exercises, as well as discussion about their current status and the effects upon student welfare. Some illustrative tables are also presented. Using correlational and…

Rank Advancement in Academic Careers: Sex Differences and the Effects of Productivity.

ERIC Educational Resources Information Center

Long, J. Scott; And Others

1993-01-01

Presents evidence on sex differences in rank advancement in academic careers, and considers the relative importance of quality and quantity of publications. Results for 556 male and 450 female biochemists show the importance of time in rank and number of publications and that rates of promotion are lower for women. (SLD)

The Hierarchical Face: Higher Rankings Lead to Less Cooperative Looks

ERIC Educational Resources Information Center

Chen, Patricia; Myers, Christopher G.; Kopelman, Shirli; Garcia, Stephen M.

2012-01-01

In 3 studies, we tested the hypothesis that the higher ranked an individual's group is, the less cooperative the facial expression of that person is judged to be. Study 1 established this effect among business school deans, with observers rating individuals from higher ranked schools as appearing less cooperative, despite lacking prior knowledge…

Evaluating Combinations of Ranked Lists and Visualizations of Inter-Document Similarity.

ERIC Educational Resources Information Center

Allan, James; Leuski, Anton; Swan, Russell; Byrd, Donald

2001-01-01

Considers how ideas from document clustering can be used to improve retrieval accuracy of ranked lists in interactive systems and how to evaluate system effectiveness. Describes a TREC (Text Retrieval Conference) study that constructed and evaluated systems that present the user with ranked lists and a visualization of inter-document similarities.…

Compressive Sensing via Nonlocal Smoothed Rank Function

PubMed Central

Fan, Ya-Ru; Liu, Jun; Zhao, Xi-Le

2016-01-01

Compressive sensing (CS) theory asserts that we can reconstruct signals and images with only a small number of samples or measurements. Recent works exploiting the nonlocal similarity have led to better results in various CS studies. To better exploit the nonlocal similarity, in this paper, we propose a non-convex smoothed rank function based model for CS image reconstruction. We also propose an efficient alternating minimization method to solve the proposed model, which reduces a difficult and coupled problem to two tractable subproblems. Experimental results have shown that the proposed method performs better than several existing state-of-the-art CS methods for image reconstruction. PMID:27583683

Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment.

PubMed

Siart, Benjamin; Pflüger, Lena S; Wallner, Bernard

2016-01-01

Status within social hierarchies has great effects on the lives of socially organized mammals. Its effects on human behavior and related physiology, however, is relatively little studied. The present study investigated the impact of military rank on fairness and behavior in relation to salivary cortisol (C) and testosterone (T) levels in male soldiers. For this purpose 180 members of the Austrian Armed Forces belonging to two distinct rank groups participated in two variations of a computer-based guard duty allocation experiment. The rank groups were (1) warrant officers (high rank, HR) and (2) enlisted men (low rank, LR). One soldier from each rank group participated in every experiment. At the beginning of the experiment, one participant was assigned to start standing guard and the other participant at rest. The participant who started at rest could choose if and when to relieve his fellow soldier and therefore had control over the experiment. In order to trigger perception of unfair behavior, an additional experiment was conducted which was manipulated by the experimenter. In the manipulated version both soldiers started in the standing guard position and were never relieved, believing that their opponent was at rest , not relieving them. Our aim was to test whether unfair behavior causes a physiological reaction. Saliva samples for hormone analysis were collected at regular intervals throughout the experiment. We found that in the un-manipulated setup high-ranking soldiers spent less time standing guard than lower ranking individuals. Rank was a significant predictor for C but not for T levels during the experiment. C levels in the HR group were higher than in the LR group. C levels were also elevated in the manipulated experiment compared to the un-manipulated experiment, especially in LR. We assume that the elevated C levels in HR were caused by HR feeling their status challenged by the situation of having to negotiate with an individual of lower military rank. This would be in line with the observation that unequally shared duty favored HR in most cases. We conclude that social status, in the form of military rank affects fairness behavior in social interaction and endocrine levels.

Pulling Rank: Military Rank Affects Hormone Levels and Fairness in an Allocation Experiment

PubMed Central

Siart, Benjamin; Pflüger, Lena S.; Wallner, Bernard

2016-01-01

Status within social hierarchies has great effects on the lives of socially organized mammals. Its effects on human behavior and related physiology, however, is relatively little studied. The present study investigated the impact of military rank on fairness and behavior in relation to salivary cortisol (C) and testosterone (T) levels in male soldiers. For this purpose 180 members of the Austrian Armed Forces belonging to two distinct rank groups participated in two variations of a computer-based guard duty allocation experiment. The rank groups were (1) warrant officers (high rank, HR) and (2) enlisted men (low rank, LR). One soldier from each rank group participated in every experiment. At the beginning of the experiment, one participant was assigned to start standing guard and the other participant at rest. The participant who started at rest could choose if and when to relieve his fellow soldier and therefore had control over the experiment. In order to trigger perception of unfair behavior, an additional experiment was conducted which was manipulated by the experimenter. In the manipulated version both soldiers started in the standing guard position and were never relieved, believing that their opponent was at rest, not relieving them. Our aim was to test whether unfair behavior causes a physiological reaction. Saliva samples for hormone analysis were collected at regular intervals throughout the experiment. We found that in the un-manipulated setup high-ranking soldiers spent less time standing guard than lower ranking individuals. Rank was a significant predictor for C but not for T levels during the experiment. C levels in the HR group were higher than in the LR group. C levels were also elevated in the manipulated experiment compared to the un-manipulated experiment, especially in LR. We assume that the elevated C levels in HR were caused by HR feeling their status challenged by the situation of having to negotiate with an individual of lower military rank. This would be in line with the observation that unequally shared duty favored HR in most cases. We conclude that social status, in the form of military rank affects fairness behavior in social interaction and endocrine levels. PMID:27891109

A framework for list representation, enabling list stabilization through incorporation of gene exchangeabilities.

PubMed

Soneson, Charlotte; Fontes, Magnus

2012-01-01

Analysis of multivariate data sets from, for example, microarray studies frequently results in lists of genes which are associated with some response of interest. The biological interpretation is often complicated by the statistical instability of the obtained gene lists, which may partly be due to the functional redundancy among genes, implying that multiple genes can play exchangeable roles in the cell. In this paper, we use the concept of exchangeability of random variables to model this functional redundancy and thereby account for the instability. We present a flexible framework to incorporate the exchangeability into the representation of lists. The proposed framework supports straightforward comparison between any 2 lists. It can also be used to generate new more stable gene rankings incorporating more information from the experimental data. Using 2 microarray data sets, we show that the proposed method provides more robust gene rankings than existing methods with respect to sampling variations, without compromising the biological significance of the rankings.

Quantum probability ranking principle for ligand-based virtual screening.

PubMed

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Quantum probability ranking principle for ligand-based virtual screening

NASA Astrophysics Data System (ADS)

Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal

2017-04-01

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.

Best Friends: Alliances, Friend Ranking, and the MySpace Social Network.

PubMed

DeScioli, Peter; Kurzban, Robert; Koch, Elizabeth N; Liben-Nowell, David

2011-01-01

Like many topics of psychological research, the explanation for friendship is at once intuitive and difficult to address empirically. These difficulties worsen when one seeks, as we do, to go beyond "obvious" explanations ("humans are social creatures") to ask deeper questions, such as "What is the evolved function of human friendship?" In recent years, however, a new window into human behavior has opened as a growing fraction of people's social activity has moved online, leaving a wealth of digital traces behind. One example is a feature of the MySpace social network that allows millions of users to rank their "Top Friends." In this study, we collected over 10 million people's friendship decisions from MySpace to test predictions made by hypotheses about human friendship. We found particular support for the alliance hypothesis, which holds that human friendship is caused by cognitive systems that function to create alliances for potential disputes. Because an ally's support can be undermined by a stronger outside relationship, the alliance model predicts that people will prefer partners who rank them above other friends. Consistent with the alliance model, we found that an individual's choice of best friend in MySpace is strongly predicted by how partners rank that individual. © The Author(s) 2011.

Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.

PubMed

Eom, Young-Ho; Shepelyansky, Dima L

2013-01-01

How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013.

Highlighting Entanglement of Cultures via Ranking of Multilingual Wikipedia Articles

PubMed Central

Eom, Young-Ho; Shepelyansky, Dima L.

2013-01-01

How different cultures evaluate a person? Is an important person in one culture is also important in the other culture? We address these questions via ranking of multilingual Wikipedia articles. With three ranking algorithms based on network structure of Wikipedia, we assign ranking to all articles in 9 multilingual editions of Wikipedia and investigate general ranking structure of PageRank, CheiRank and 2DRank. In particular, we focus on articles related to persons, identify top 30 persons for each rank among different editions and analyze distinctions of their distributions over activity fields such as politics, art, science, religion, sport for each edition. We find that local heroes are dominant but also global heroes exist and create an effective network representing entanglement of cultures. The Google matrix analysis of network of cultures shows signs of the Zipf law distribution. This approach allows to examine diversity and shared characteristics of knowledge organization between cultures. The developed computational, data driven approach highlights cultural interconnections in a new perspective. Dated: June 26, 2013 PMID:24098338

Do Standard Instrumental Acoustic, Perceptual, and Subjective Voice Outcomes Indicate Therapy Success in Patients With Functional Dysphonia?

PubMed

Reetz, Stephanie; Bohlender, Joerg E; Brockmann-Bauser, Meike

2018-01-29

The validity and sensitivity to change of instrumental acoustic measurements in patients with functional dysphonia have been controversially discussed. This work examines combined voice therapy effects on standard acoustic measurements, and if these agree with perceptual and subjective voice outcomes. Retrospective study. Thirty-nine patients (26 women, 13 men) aged 20-70 years (mean: 46.3, standard deviation 12.8) with functional dysphonia were investigated before and after combined voice therapy. Instrumental parameters included mean and range of speaking fundamental frequency (f o ) and intensity (SPL (dBA)); maximum SPL and mean f o of calling voice; minimum, maximum, range of singing voice f o and SPL, jitter (%), and the Dysphonia Severity Index. Voice Handicap Index-9 international was used for subjective and Grading-Roughness-Breathiness-Asthenia-Strain scale for perceptual assessment. Differences were investigated by Wilcoxon signed ranks test and coherences by Spearman rank correlation coefficient. After treatment, the speaking voice f o range (7-8.13 semitones) and SPL range (12.9-14.85 dB(A)) were significantly larger (P < 0.05). Both parameters were highly correlated (P < 0.001). Subjective symptoms were significantly reduced from a mean Voice Handicap Index-9 international of 15.6-8.6, and all perceptual Grading-Roughness-Breathiness-Asthenia-Strain scale parameters were significantly improved (G: 1.05-0.51) after therapy (P < 0.05). These findings were not associated with any acoustic parameter (P > 0.05). Significantly improved subjective and perceptual findings verify positive combined voice therapy effects in patients with functional dysphonia. The larger f o and SPL speaking voice range after treatment indicate an altered voice technique. These instrumental measures may be clinical indicators of therapy success and transfer effects. Copyright © 2017 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Contextual effects on the perceived health benefits of exercise: the exercise rank hypothesis.

PubMed

Maltby, John; Wood, Alex M; Vlaev, Ivo; Taylor, Michael J; Brown, Gordon D A

2012-12-01

Many accounts of social influences on exercise participation describe how people compare their behaviors to those of others. We develop and test a novel hypothesis, the exercise rank hypothesis, of how this comparison can occur. The exercise rank hypothesis, derived from evolutionary theory and the decision by sampling model of judgment, suggests that individuals' perceptions of the health benefits of exercise are influenced by how individuals believe the amount of exercise ranks in comparison with other people's amounts of exercise. Study 1 demonstrated that individuals' perceptions of the health benefits of their own current exercise amounts were as predicted by the exercise rank hypothesis. Study 2 demonstrated that the perceptions of the health benefits of an amount of exercise can be manipulated by experimentally changing the ranked position of the amount within a comparison context. The discussion focuses on how social norm-based interventions could benefit from using rank information.

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

NASA Astrophysics Data System (ADS)

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.

Knowledge about the research and ethics committee at Makerere University, Kampala.

PubMed

Ibingira, B R; Ochieng, J

2013-12-01

All research involving human participants should be reviewed by a competent and independent institutional research and ethics committee. Research conducted at Makerere University College of Health Sciences should be subjected to a rigorous review process by the ethics committee in order to protect human participants' interests, rights and welfare. To evaluate researchers' knowledge about the functions and ethical review process of the College of Health Sciences research and ethics committee. A cross sectional study. 135 researchers consented to participate in the study, but 70 questionnaires were answered giving a 52% response. Age ranged between 30 to 61 years, majority of participants 30-39 years. Most of the respondents do agree that the REC functions include Protocol review 86%, protection of research participants 84.3%, and monitoring of ongoing research. During ethical review, the RECpays special attention to scientific design [79.7%] and ethical issues [75.3%], but less to the budget and literature review. More than 97% of the respondents believe that the REC is either average or very good, while 2.8% rank it below average. Respondents knew the major functions of the committee including protection of the rights and welfare of research participants, protocol review and monitoring of on going research, and the elements of protocol review that are given more attention include ;scientific design and ethical issues. Overall performance of the REC was ranked as average by respondents. The committee should limit delays in approval and effectively handle all functions of the committee.

Experimental analysis of multi-attribute decision-making based on Atanassov intuitionistic fuzzy sets: a discussion of anchor dependency and accuracy functions

NASA Astrophysics Data System (ADS)

Chen, Ting-Yu

2012-06-01

This article presents a useful method for relating anchor dependency and accuracy functions to multiple attribute decision-making (MADM) problems in the context of Atanassov intuitionistic fuzzy sets (A-IFSs). Considering anchored judgement with displaced ideals and solution precision with minimal hesitation, several auxiliary optimisation models have proposed to obtain the optimal weights of the attributes and to acquire the corresponding TOPSIS (the technique for order preference by similarity to the ideal solution) index for alternative rankings. Aside from the TOPSIS index, as a decision-maker's personal characteristics and own perception of self may also influence the direction in the axiom of choice, the evaluation of alternatives is conducted based on distances of each alternative from the positive and negative ideal alternatives, respectively. This article originates from Li's [Li, D.-F. (2005), 'Multiattribute Decision Making Models and Methods Using Intuitionistic Fuzzy Sets', Journal of Computer and System Sciences, 70, 73-85] work, which is a seminal study of intuitionistic fuzzy decision analysis using deduced auxiliary programming models, and deems it a benchmark method for comparative studies on anchor dependency and accuracy functions. The feasibility and effectiveness of the proposed methods are illustrated by a numerical example. Finally, a comparative analysis is illustrated with computational experiments on averaging accuracy functions, TOPSIS indices, separation measures from positive and negative ideal alternatives, consistency rates of ranking orders, contradiction rates of the top alternative and average Spearman correlation coefficients.

Gene selection with multiple ordering criteria.

PubMed

Chen, James J; Tsai, Chen-An; Tzeng, Shengli; Chen, Chun-Houh

2007-03-05

A microarray study may select different differentially expressed gene sets because of different selection criteria. For example, the fold-change and p-value are two commonly known criteria to select differentially expressed genes under two experimental conditions. These two selection criteria often result in incompatible selected gene sets. Also, in a two-factor, say, treatment by time experiment, the investigator may be interested in one gene list that responds to both treatment and time effects. We propose three layer ranking algorithms, point-admissible, line-admissible (convex), and Pareto, to provide a preference gene list from multiple gene lists generated by different ranking criteria. Using the public colon data as an example, the layer ranking algorithms are applied to the three univariate ranking criteria, fold-change, p-value, and frequency of selections by the SVM-RFE classifier. A simulation experiment shows that for experiments with small or moderate sample sizes (less than 20 per group) and detecting a 4-fold change or less, the two-dimensional (p-value and fold-change) convex layer ranking selects differentially expressed genes with generally lower FDR and higher power than the standard p-value ranking. Three applications are presented. The first application illustrates a use of the layer rankings to potentially improve predictive accuracy. The second application illustrates an application to a two-factor experiment involving two dose levels and two time points. The layer rankings are applied to selecting differentially expressed genes relating to the dose and time effects. In the third application, the layer rankings are applied to a benchmark data set consisting of three dilution concentrations to provide a ranking system from a long list of differentially expressed genes generated from the three dilution concentrations. The layer ranking algorithms are useful to help investigators in selecting the most promising genes from multiple gene lists generated by different filter, normalization, or analysis methods for various objectives.

Health information on internet: quality, importance, and popularity of persian health websites.

PubMed

Samadbeik, Mahnaz; Ahmadi, Maryam; Mohammadi, Ali; Mohseni Saravi, Beniamin

2014-04-01

The Internet has provided great opportunities for disseminating both accurate and inaccurate health information. Therefore, the quality of information is considered as a widespread concern affecting the human life. Despite the increasingly substantial growth in the number of users, Persian health websites and the proportion of internet-using patients, little is known about the quality of Persian medical and health websites. The current study aimed to first assess the quality, popularity and importance of websites providing Persian health-related information, and second to evaluate the correlation of the popularity and importance ranking with quality score on the Internet. The sample websites were identified by entering the health-related keywords into four most popular search engines of Iranian users based on the Alexa ranking at the time of study. Each selected website was assessed using three qualified tools including the Bomba and Land Index, Google PageRank and the Alexa ranking. The evaluated sites characteristics (ownership structure, database, scope and objective) really did not have an effect on the Alexa traffic global rank, Alexa traffic rank in Iran, Google PageRank and Bomba total score. Most websites (78.9 percent, n = 56) were in the moderate category (8 ≤ x ≤ 11.99) based on their quality levels. There was no statistically significant association between Google PageRank with Bomba index variables and Alexa traffic global rank (P > 0.05). The Persian health websites had better Bomba quality scores in availability and usability guidelines as compared to other guidelines. The Google PageRank did not properly reflect the real quality of evaluated websites and Internet users seeking online health information should not merely rely on it for any kind of prejudgment regarding Persian health websites. However, they can use Iran Alexa rank as a primary filtering tool of these websites. Therefore, designing search engines dedicated to explore accredited Persian health-related Web sites can be an effective method to access high-quality Persian health websites.

Discriminative Multi-View Interactive Image Re-Ranking.

PubMed

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.

Smoothed low rank and sparse matrix recovery by iteratively reweighted least squares minimization.

PubMed

Lu, Canyi; Lin, Zhouchen; Yan, Shuicheng

2015-02-01

This paper presents a general framework for solving the low-rank and/or sparse matrix minimization problems, which may involve multiple nonsmooth terms. The iteratively reweighted least squares (IRLSs) method is a fast solver, which smooths the objective function and minimizes it by alternately updating the variables and their weights. However, the traditional IRLS can only solve a sparse only or low rank only minimization problem with squared loss or an affine constraint. This paper generalizes IRLS to solve joint/mixed low-rank and sparse minimization problems, which are essential formulations for many tasks. As a concrete example, we solve the Schatten-p norm and l2,q-norm regularized low-rank representation problem by IRLS, and theoretically prove that the derived solution is a stationary point (globally optimal if p,q ≥ 1). Our convergence proof of IRLS is more general than previous one that depends on the special properties of the Schatten-p norm and l2,q-norm. Extensive experiments on both synthetic and real data sets demonstrate that our IRLS is much more efficient.

RANK/RANKL/OPG Signalization Implication in Periodontitis: New Evidence from a RANK Transgenic Mouse Model

PubMed Central

Sojod, Bouchra; Chateau, Danielle; Mueller, Christopher G.; Babajko, Sylvie; Berdal, Ariane; Lézot, Frédéric; Castaneda, Beatriz

2017-01-01

Periodontitis is based on a complex inflammatory over-response combined with possible genetic predisposition factors. The RANKL/RANK/OPG signaling pathway is implicated in bone resorption through its key function in osteoclast differentiation and activation, as well as in the inflammatory response. This central element of osteo-immunology has been suggested to be perturbed in several diseases, including periodontitis, as it is a predisposing factor for this disease. The aim of the present study was to validate this hypothesis using a transgenic mouse line, which over-expresses RANK (RTg) and develops a periodontitis-like phenotype at 5 months of age. RTg mice exhibited severe alveolar bone loss, an increased number of TRAP positive cells, and disorganization of periodontal ligaments. This phenotype was more pronounced in females. We also observed dental root resorption lacunas. Hyperplasia of the gingival epithelium, including Malassez epithelial rests, was visible as early as 25 days, preceding any other symptoms. These results demonstrate that perturbations of the RANKL/RANK/OPG system constitute a core element of periodontitis, and more globally, osteo-immune diseases. PMID:28596739

Social effects on foraging behavior and success depend on local environmental conditions

PubMed Central

Marshall, Harry H; Carter, Alecia J; Ashford, Alexandra; Rowcliffe, J Marcus; Cowlishaw, Guy

2015-01-01

In social groups, individuals' dominance rank, social bonds, and kinship with other group members have been shown to influence their foraging behavior. However, there is growing evidence that the particular effects of these social traits may also depend on local environmental conditions. We investigated this by comparing the foraging behavior of wild chacma baboons, Papio ursinus, under natural conditions and in a field experiment where food was spatially clumped. Data were collected from 55 animals across two troops over a 5-month period, including over 900 agonistic foraging interactions and over 600 food patch visits in each condition. In both conditions, low-ranked individuals received more agonism, but this only translated into reduced foraging performances for low-ranked individuals in the high-competition experimental conditions. Our results suggest one possible reason for this pattern may be low-ranked individuals strategically investing social effort to negotiate foraging tolerance, but the rank-offsetting effect of this investment being overwhelmed in the higher-competition experimental environment. Our results also suggest that individuals may use imbalances in their social bonds to negotiate tolerance from others under a wider range of environmental conditions, but utilize the overall strength of their social bonds in more extreme environments where feeding competition is more intense. These findings highlight that behavioral tactics such as the strategic investment of social effort may allow foragers to mitigate the costs of low rank, but that the effectiveness of these tactics is likely to be limited in certain environments. PMID:25691973

Poisson statistics of PageRank probabilities of Twitter and Wikipedia networks

NASA Astrophysics Data System (ADS)

Frahm, Klaus M.; Shepelyansky, Dima L.

2014-04-01

We use the methods of quantum chaos and Random Matrix Theory for analysis of statistical fluctuations of PageRank probabilities in directed networks. In this approach the effective energy levels are given by a logarithm of PageRank probability at a given node. After the standard energy level unfolding procedure we establish that the nearest spacing distribution of PageRank probabilities is described by the Poisson law typical for integrable quantum systems. Our studies are done for the Twitter network and three networks of Wikipedia editions in English, French and German. We argue that due to absence of level repulsion the PageRank order of nearby nodes can be easily interchanged. The obtained Poisson law implies that the nearby PageRank probabilities fluctuate as random independent variables.

Arthroscopic Shoulder Surgery in Female Professional Tennis Players: Ability and Timing to Return to Play.

PubMed

Young, Simon W; Dakic, Jodie; Stroia, Kathleen; Nguyen, Michael L; Safran, Marc R

2017-07-01

To assess the outcome and time to return to previous level of competitive play after shoulder surgery in professional tennis players. Retrospective case series. Tertiary academic centre. The records of all female tennis players on the Women's Tennis Association (WTA) professional circuit between January 2008 and June 2010 were reviewed to identify players who underwent shoulder surgery on their dominant (serving) shoulder. Primary outcomes were the ability and time to return to professional play and if they were able to return to their previous level of function as determined by singles ranking. Preoperative and postoperative singles rankings were used to determine rate and completeness of return to preoperative function. During the study period, 8 professional women tennis players from the WTA tour underwent shoulder surgery on their dominant arm. Indications included rotator cuff debridement or repair, labral reconstruction for instability or superior labral anterior posterior lesion, and neurolysis of the suprascapular nerve. Seven players (88%) returned to professional play. The mean time to return to play was 7 months after surgery. However, only 25% (2 of 8) players achieved their preinjury singles rank or better by 18 months postoperatively. In total, 4 players returned to their preinjury singles ranking, with their peak singles ranking being attained at a mean of 2.4 years postoperatively. In professional female tennis players, a high return to play rate after arthroscopic shoulder surgery is associated with a prolonged and often incomplete return to previous level of performance. Thus, counseling the patient to this fact is important to manage expectations. Level IV-Case Series.

How Variances in Business School Rankings Affect Enrollment Trends and Practices

ERIC Educational Resources Information Center

De Veyga, Guillermo A.

2016-01-01

This study examined the effect that variances in the"U.S. News & World Report" rankings have on enrollment trends and practices in both top and non-top 25 business schools. The purpose of this study was to determine whether mobility in the rankings was met with a statistically significant response to the research questions presented.…

Carving out the end of the world or (superconformal bootstrap in six dimensions)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chang, Chi-Ming; Lin, Ying-Hsuan

We bootstrap N=(1,0) superconformal field theories in six dimensions, by analyzing the four-point function of flavor current multiplets. By assuming E 8 flavor group, we present universal bounds on the central charge C T and the flavor central charge C J. Based on the numerical data, we conjecture that the rank-one E-string theory saturates the universal lower bound on C J , and numerically determine the spectrum of long multiplets in the rank-one E-string theory. We comment on the possibility of solving the higher-rank E-string theories by bootstrap and thereby probing M-theory on AdS 7×S 4/Z 2 .

Carving out the end of the world or (superconformal bootstrap in six dimensions)

DOE PAGES

Chang, Chi-Ming; Lin, Ying-Hsuan

2017-08-29

We bootstrap N=(1,0) superconformal field theories in six dimensions, by analyzing the four-point function of flavor current multiplets. By assuming E 8 flavor group, we present universal bounds on the central charge C T and the flavor central charge C J. Based on the numerical data, we conjecture that the rank-one E-string theory saturates the universal lower bound on C J , and numerically determine the spectrum of long multiplets in the rank-one E-string theory. We comment on the possibility of solving the higher-rank E-string theories by bootstrap and thereby probing M-theory on AdS 7×S 4/Z 2 .

Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

PubMed

Mathur, Sunil; Sadana, Ajit

2015-12-01

We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

Are university rankings useful to improve research? A systematic review.

PubMed

Vernon, Marlo M; Balas, E Andrew; Momani, Shaher

2018-01-01

Concerns about reproducibility and impact of research urge improvement initiatives. Current university ranking systems evaluate and compare universities on measures of academic and research performance. Although often useful for marketing purposes, the value of ranking systems when examining quality and outcomes is unclear. The purpose of this study was to evaluate usefulness of ranking systems and identify opportunities to support research quality and performance improvement. A systematic review of university ranking systems was conducted to investigate research performance and academic quality measures. Eligibility requirements included: inclusion of at least 100 doctoral granting institutions, be currently produced on an ongoing basis and include both global and US universities, publish rank calculation methodology in English and independently calculate ranks. Ranking systems must also include some measures of research outcomes. Indicators were abstracted and contrasted with basic quality improvement requirements. Exploration of aggregation methods, validity of research and academic quality indicators, and suitability for quality improvement within ranking systems were also conducted. A total of 24 ranking systems were identified and 13 eligible ranking systems were evaluated. Six of the 13 rankings are 100% focused on research performance. For those reporting weighting, 76% of the total ranks are attributed to research indicators, with 24% attributed to academic or teaching quality. Seven systems rely on reputation surveys and/or faculty and alumni awards. Rankings influence academic choice yet research performance measures are the most weighted indicators. There are no generally accepted academic quality indicators in ranking systems. No single ranking system provides a comprehensive evaluation of research and academic quality. Utilizing a combined approach of the Leiden, Thomson Reuters Most Innovative Universities, and the SCImago ranking systems may provide institutions with a more effective feedback for research improvement. Rankings which extensively rely on subjective reputation and "luxury" indicators, such as award winning faculty or alumni who are high ranking executives, are not well suited for academic or research performance improvement initiatives. Future efforts should better explore measurement of the university research performance through comprehensive and standardized indicators. This paper could serve as a general literature citation when one or more of university ranking systems are used in efforts to improve academic prominence and research performance.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shao, MeiYue; Lin, Lin; Yang, Chao

The single particle energies obtained in a Kohn-Sham density functional theory (DFT) calculation are generally known to be poor approximations to electron excitation energies that are measured in tr ansport, tunneling and spectroscopic experiments such as photo-emission spectroscopy. The correction to these energies can be obtained from the poles of a single particle Green’s function derived from a many-body perturbation theory. From a computational perspective, the accuracy and efficiency of such an approach depends on how a self energy term that properly accounts for dynamic screening of electrons is approximated. The G 0W 0 approximation is a widely used techniquemore » in which the self energy is expressed as the convolution of a noninteracting Green’s function (G 0) and a screened Coulomb interaction (W 0) in the frequency domain. The computational cost associated with such a convolution is high due to the high complexity of evaluating W 0 at multiple frequencies. In this paper, we discuss how the cost of G 0W 0 calculation can be reduced by constructing a low rank approximation to the frequency dependent part of W 0 . In particular, we examine the effect of such a low rank approximation on the accuracy of the G 0W 0 approximation. We also discuss how the numerical convolution of G 0 and W 0 can be evaluated efficiently and accurately by using a contour deformation technique with an appropriate choice of the contour.« less

Enhanced collective influence: A paradigm to optimize network disruption

NASA Astrophysics Data System (ADS)

Wu, Tao; Chen, Leiting; Zhong, Linfeng; Xian, Xingping

2017-04-01

The function of complex networks typically relies on the integrity of underlying structure. Sometimes, practical applications need to attack networks' function, namely inactivate and fragment networks' underlying structure. To effectively dismantle complex networks and regulate the function of them, a centrality measure, named CI (Morone and Makse, 2015), was proposed for node ranking. We observe that the performance of CI centrality in network disruption problem may deteriorate when it is used in networks with different topology properties. Specifically, the structural features of local network topology are overlooked in CI centrality, even though the local network topology of the nodes with a fixed CI value may have very different organization. To improve the ranking accuracy of CI, this paper proposes a variant ECI to CI by considering loop density and degree diversity of local network topology. And the proposed ECI centrality would degenerate into CI centrality with the reduction of the loop density and the degree diversity level. By comparing ECI with CI and classical centrality measures in both synthetic and real networks, the experimental results suggest that ECI can largely improve the performance of CI for network disruption. Based on the results, we analyze the correlation between the improvement and the properties of the networks. We find that the performance of ECI is positively correlated with assortative coefficient and community modularity and negatively correlated with degree inequality of networks, which can be used as guidance for practical applications.

Comparing Effects of Biologic Agents in Treating Patients with Rheumatoid Arthritis: A Multiple Treatment Comparison Regression Analysis.

PubMed

Tvete, Ingunn Fride; Natvig, Bent; Gåsemyr, Jørund; Meland, Nils; Røine, Marianne; Klemp, Marianne

2015-01-01

Rheumatoid arthritis patients have been treated with disease modifying anti-rheumatic drugs (DMARDs) and the newer biologic drugs. We sought to compare and rank the biologics with respect to efficacy. We performed a literature search identifying 54 publications encompassing 9 biologics. We conducted a multiple treatment comparison regression analysis letting the number experiencing a 50% improvement on the ACR score be dependent upon dose level and disease duration for assessing the comparable relative effect between biologics and placebo or DMARD. The analysis embraced all treatment and comparator arms over all publications. Hence, all measured effects of any biologic agent contributed to the comparison of all biologic agents relative to each other either given alone or combined with DMARD. We found the drug effect to be dependent on dose level, but not on disease duration, and the impact of a high versus low dose level was the same for all drugs (higher doses indicated a higher frequency of ACR50 scores). The ranking of the drugs when given without DMARD was certolizumab (ranked highest), etanercept, tocilizumab/ abatacept and adalimumab. The ranking of the drugs when given with DMARD was certolizumab (ranked highest), tocilizumab, anakinra/rituximab, golimumab/ infliximab/ abatacept, adalimumab/ etanercept [corrected]. Still, all drugs were effective. All biologic agents were effective compared to placebo, with certolizumab the most effective and adalimumab (without DMARD treatment) and adalimumab/ etanercept (combined with DMARD treatment) the least effective. The drugs were in general more effective, except for etanercept, when given together with DMARDs.

Comparing Effects of Biologic Agents in Treating Patients with Rheumatoid Arthritis: A Multiple Treatment Comparison Regression Analysis

PubMed Central

Tvete, Ingunn Fride; Natvig, Bent; Gåsemyr, Jørund; Meland, Nils; Røine, Marianne; Klemp, Marianne

2015-01-01

Rheumatoid arthritis patients have been treated with disease modifying anti-rheumatic drugs (DMARDs) and the newer biologic drugs. We sought to compare and rank the biologics with respect to efficacy. We performed a literature search identifying 54 publications encompassing 9 biologics. We conducted a multiple treatment comparison regression analysis letting the number experiencing a 50% improvement on the ACR score be dependent upon dose level and disease duration for assessing the comparable relative effect between biologics and placebo or DMARD. The analysis embraced all treatment and comparator arms over all publications. Hence, all measured effects of any biologic agent contributed to the comparison of all biologic agents relative to each other either given alone or combined with DMARD. We found the drug effect to be dependent on dose level, but not on disease duration, and the impact of a high versus low dose level was the same for all drugs (higher doses indicated a higher frequency of ACR50 scores). The ranking of the drugs when given without DMARD was certolizumab (ranked highest), etanercept, tocilizumab/ abatacept and adalimumab. The ranking of the drugs when given with DMARD was certolizumab (ranked highest), tocilizumab, anakinra, rituximab, golimumab/ infliximab/ abatacept, adalimumab/ etanercept. Still, all drugs were effective. All biologic agents were effective compared to placebo, with certolizumab the most effective and adalimumab (without DMARD treatment) and adalimumab/ etanercept (combined with DMARD treatment) the least effective. The drugs were in general more effective, except for etanercept, when given together with DMARDs. PMID:26356639

The Smoothed Dirichlet Distribution: Understanding Cross-Entropy Ranking in Information Retrieval

DTIC Science & Technology

2006-07-01

reflect those of the spon- sor. viii ABSTRACT Unigram Language modeling is a successful probabilistic framework for Information Retrieval (IR) that uses...the Relevance model (RM), a state-of-the-art model for IR in the language modeling framework that uses the same cross-entropy as its ranking function...In addition, the SD based classifier provides more flexibility than RM in modeling documents owing to a consistent generative framework . We

Ranking and clustering of nodes in networks with smart teleportation

NASA Astrophysics Data System (ADS)

Lambiotte, R.; Rosvall, M.

2012-05-01

Random teleportation is a necessary evil for ranking and clustering directed networks based on random walks. Teleportation enables ergodic solutions, but the solutions must necessarily depend on the exact implementation and parametrization of the teleportation. For example, in the commonly used PageRank algorithm, the teleportation rate must trade off a heavily biased solution with a uniform solution. Here we show that teleportation to links rather than nodes enables a much smoother trade-off and effectively more robust results. We also show that, by not recording the teleportation steps of the random walker, we can further reduce the effect of teleportation with dramatic effects on clustering.

Learning Short Binary Codes for Large-scale Image Retrieval.

PubMed

Liu, Li; Yu, Mengyang; Shao, Ling

2017-03-01

Large-scale visual information retrieval has become an active research area in this big data era. Recently, hashing/binary coding algorithms prove to be effective for scalable retrieval applications. Most existing hashing methods require relatively long binary codes (i.e., over hundreds of bits, sometimes even thousands of bits) to achieve reasonable retrieval accuracies. However, for some realistic and unique applications, such as on wearable or mobile devices, only short binary codes can be used for efficient image retrieval due to the limitation of computational resources or bandwidth on these devices. In this paper, we propose a novel unsupervised hashing approach called min-cost ranking (MCR) specifically for learning powerful short binary codes (i.e., usually the code length shorter than 100 b) for scalable image retrieval tasks. By exploring the discriminative ability of each dimension of data, MCR can generate one bit binary code for each dimension and simultaneously rank the discriminative separability of each bit according to the proposed cost function. Only top-ranked bits with minimum cost-values are then selected and grouped together to compose the final salient binary codes. Extensive experimental results on large-scale retrieval demonstrate that MCR can achieve comparative performance as the state-of-the-art hashing algorithms but with significantly shorter codes, leading to much faster large-scale retrieval.

Niche partitioning and biogeography of high light adapted Prochlorococcus across taxonomic ranks in the North Pacific

PubMed Central

Larkin, Alyse A; Blinebry, Sara K; Howes, Caroline; Lin, Yajuan; Loftus, Sarah E; Schmaus, Carrie A; Zinser, Erik R; Johnson, Zackary I

2016-01-01

The distribution of major clades of Prochlorococcus tracks light, temperature and other environmental variables; yet, the drivers of genomic diversity within these ecotypes and the net effect on biodiversity of the larger community are poorly understood. We examined high light (HL) adapted Prochlorococcus communities across spatial and temporal environmental gradients in the Pacific Ocean to determine the ecological drivers of population structure and diversity across taxonomic ranks. We show that the Prochlorococcus community has the highest diversity at low latitudes, but seasonality driven by temperature, day length and nutrients adds complexity. At finer taxonomic resolution, some ‘sub-ecotype' clades have unique, cohesive responses to environmental variables and distinct biogeographies, suggesting that presently defined ecotypes can be further partitioned into ecologically meaningful units. Intriguingly, biogeographies of the HL-I sub-ecotypes are driven by unique combinations of environmental traits, rather than through trait hierarchy, while the HL-II sub-ecotypes appear ecologically similar, thus demonstrating differences among these dominant HL ecotypes. Examining biodiversity across taxonomic ranks reveals high-resolution dynamics of Prochlorococcus evolution and ecology that are masked at phylogenetically coarse resolution. Spatial and seasonal trends of Prochlorococcus communities suggest that the future ocean may be comprised of different populations, with implications for ecosystem structure and function. PMID:26800235

Ranking targets in structure-based virtual screening of three-dimensional protein libraries: methods and problems.

PubMed

Kellenberger, Esther; Foata, Nicolas; Rognan, Didier

2008-05-01

Structure-based virtual screening is a promising tool to identify putative targets for a specific ligand. Instead of docking multiple ligands into a single protein cavity, a single ligand is docked in a collection of binding sites. In inverse screening, hits are in fact targets which have been prioritized within the pool of best ranked proteins. The target rate depends on specificity and promiscuity in protein-ligand interactions and, to a considerable extent, on the effectiveness of the scoring function, which still is the Achilles' heel of molecular docking. In the present retrospective study, virtual screening of the sc-PDB target library by GOLD docking was carried out for four compounds (biotin, 4-hydroxy-tamoxifen, 6-hydroxy-1,6-dihydropurine ribonucleoside, and methotrexate) of known sc-PDB targets and, several ranking protocols based on GOLD fitness score and topological molecular interaction fingerprint (IFP) comparison were evaluated. For the four investigated ligands, the fusion of GOLD fitness and two IFP scores allowed the recovery of most targets, including the rare proteins which are not readily suitable for statistical analysis, while significantly filtering out most false positive entries. The current survey suggests that selecting a small number of targets (<20) for experimental evaluation is achievable with a pure structure-based approach.

Training: The No. 1 Manpower Management Function

ERIC Educational Resources Information Center

Lippert, Frederick G.

1977-01-01

Reports results of a University of Connecticut study in which business administration graduate students in a manpower management course ranked six major functions of a competent personnel department according to perceived importance. A description of the course is included. (TA)

Global network centrality of university rankings

NASA Astrophysics Data System (ADS)

Guo, Weisi; Del Vecchio, Marco; Pogrebna, Ganna

2017-10-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport's aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity.

Global network centrality of university rankings

PubMed Central

Del Vecchio, Marco; Pogrebna, Ganna

2017-01-01

Universities and higher education institutions form an integral part of the national infrastructure and prestige. As academic research benefits increasingly from international exchange and cooperation, many universities have increased investment in improving and enabling their global connectivity. Yet, the relationship of university performance and its global physical connectedness has not been explored in detail. We conduct, to our knowledge, the first large-scale data-driven analysis into whether there is a correlation between university relative ranking performance and its global connectivity via the air transport network. The results show that local access to global hubs (as measured by air transport network betweenness) strongly and positively correlates with the ranking growth (statistical significance in different models ranges between 5% and 1% level). We also found that the local airport’s aggregate flight paths (degree) and capacity (weighted degree) has no effect on university ranking, further showing that global connectivity distance is more important than the capacity of flight connections. We also examined the effect of local city economic development as a confounding variable and no effect was observed suggesting that access to global transportation hubs outweighs economic performance as a determinant of university ranking. The impact of this research is that we have determined the importance of the centrality of global connectivity and, hence, established initial evidence for further exploring potential connections between university ranking and regional investment policies on improving global connectivity. PMID:29134105

Performance Analysis of Scientific and Engineering Applications Using MPInside and TAU

NASA Technical Reports Server (NTRS)

Saini, Subhash; Mehrotra, Piyush; Taylor, Kenichi Jun Haeng; Shende, Sameer Suresh; Biswas, Rupak

2010-01-01

In this paper, we present performance analysis of two NASA applications using performance tools like Tuning and Analysis Utilities (TAU) and SGI MPInside. MITgcmUV and OVERFLOW are two production-quality applications used extensively by scientists and engineers at NASA. MITgcmUV is a global ocean simulation model, developed by the Estimating the Circulation and Climate of the Ocean (ECCO) Consortium, for solving the fluid equations of motion using the hydrostatic approximation. OVERFLOW is a general-purpose Navier-Stokes solver for computational fluid dynamics (CFD) problems. Using these tools, we analyze the MPI functions (MPI_Sendrecv, MPI_Bcast, MPI_Reduce, MPI_Allreduce, MPI_Barrier, etc.) with respect to message size of each rank, time consumed by each function, and how ranks communicate. MPI communication is further analyzed by studying the performance of MPI functions used in these two applications as a function of message size and number of cores. Finally, we present the compute time, communication time, and I/O time as a function of the number of cores.

Beyond Low Rank + Sparse: Multi-scale Low Rank Matrix Decomposition

PubMed Central

Ong, Frank; Lustig, Michael

2016-01-01

We present a natural generalization of the recent low rank + sparse matrix decomposition and consider the decomposition of matrices into components of multiple scales. Such decomposition is well motivated in practice as data matrices often exhibit local correlations in multiple scales. Concretely, we propose a multi-scale low rank modeling that represents a data matrix as a sum of block-wise low rank matrices with increasing scales of block sizes. We then consider the inverse problem of decomposing the data matrix into its multi-scale low rank components and approach the problem via a convex formulation. Theoretically, we show that under various incoherence conditions, the convex program recovers the multi-scale low rank components either exactly or approximately. Practically, we provide guidance on selecting the regularization parameters and incorporate cycle spinning to reduce blocking artifacts. Experimentally, we show that the multi-scale low rank decomposition provides a more intuitive decomposition than conventional low rank methods and demonstrate its effectiveness in four applications, including illumination normalization for face images, motion separation for surveillance videos, multi-scale modeling of the dynamic contrast enhanced magnetic resonance imaging and collaborative filtering exploiting age information. PMID:28450978

Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation

PubMed Central

Bryndová, Michala; Kasari, Liis; Norberg, Anna; Weiss, Matthias; Bishop, Tom R.; Luke, Sarah H.; Sam, Katerina; Le Bagousse-Pinguet, Yoann; Lepš, Jan; Götzenberger, Lars; de Bello, Francesco

2016-01-01

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package “traitor” to facilitate assessments of missing trait data. PMID:26881747

Evaluating Functional Diversity: Missing Trait Data and the Importance of Species Abundance Structure and Data Transformation.

PubMed

Májeková, Maria; Paal, Taavi; Plowman, Nichola S; Bryndová, Michala; Kasari, Liis; Norberg, Anna; Weiss, Matthias; Bishop, Tom R; Luke, Sarah H; Sam, Katerina; Le Bagousse-Pinguet, Yoann; Lepš, Jan; Götzenberger, Lars; de Bello, Francesco

2016-01-01

Functional diversity (FD) is an important component of biodiversity that quantifies the difference in functional traits between organisms. However, FD studies are often limited by the availability of trait data and FD indices are sensitive to data gaps. The distribution of species abundance and trait data, and its transformation, may further affect the accuracy of indices when data is incomplete. Using an existing approach, we simulated the effects of missing trait data by gradually removing data from a plant, an ant and a bird community dataset (12, 59, and 8 plots containing 62, 297 and 238 species respectively). We ranked plots by FD values calculated from full datasets and then from our increasingly incomplete datasets and compared the ranking between the original and virtually reduced datasets to assess the accuracy of FD indices when used on datasets with increasingly missing data. Finally, we tested the accuracy of FD indices with and without data transformation, and the effect of missing trait data per plot or per the whole pool of species. FD indices became less accurate as the amount of missing data increased, with the loss of accuracy depending on the index. But, where transformation improved the normality of the trait data, FD values from incomplete datasets were more accurate than before transformation. The distribution of data and its transformation are therefore as important as data completeness and can even mitigate the effect of missing data. Since the effect of missing trait values pool-wise or plot-wise depends on the data distribution, the method should be decided case by case. Data distribution and data transformation should be given more careful consideration when designing, analysing and interpreting FD studies, especially where trait data are missing. To this end, we provide the R package "traitor" to facilitate assessments of missing trait data.

Female reproductive success in a species with an age-inversed hierarchy.

PubMed

DE Vries, Dorien; Koenig, Andreas; Borries, Carola

2016-11-01

In most group-living mammals, reproductive success declines with increasing age and increases with increasing rank. Such effects have mainly been studied in matrilineal and in "age positive" hierarchies, which are stable and in which high ranking females often outperform low ranking ones. These relationships are less well-understood in age-inversed dominance hierarchies, in which a female's rank changes over time. We analyzed demographic data of 2 wild, unprovisioned groups of gray langurs (Semnopithecus schistaceus) near Ramnagar, Nepal covering periods of 5 years each. Female rank was unstable and age-inversed. We measured reproductive success via birth rates (57 births), infant survival (proportion of infants surviving to 2 years) and number of offspring surviving to 2 years of age (successful births) for 3 age and 3 rank classes. We found that old females performed significantly worse than expected (birth rate P = 0.04; successful births P = 0.03). The same was true for low ranking females (P = 0.04, and P < 0.01, respectively). Infant survival was highest for young and middle-aged as well as for high and middle ranking females. Overall, the results for these unstable hierarchies were rather similar to those for stable hierarchies of other mammals, particularly several nonhuman primates. Compared to a provisioned population of a closely related species, the wild and unprovisioned population examined (i) showed stronger age effects, while (ii) female reproductive success was equally affected by rank. Future comparative studies are needed to examine whether captive or provisioned populations deviate predictably from wild populations. © 2016 International Society of Zoological Sciences, Institute of Zoology/Chinese Academy of Sciences and John Wiley & Sons Australia, Ltd.

A Mixed-Method Exploration of Functioning in Safe Schools/Healthy Students Partnerships

ERIC Educational Resources Information Center

Merrill, Marina L.; Taylor, Nicole L.; Martin, Alison J.; Maxim, Lauren A.; D'Ambrosio, Ryan; Gabriel, Roy M.; Wendt, Staci J.; Mannix, Danyelle; Wells, Michael E.

2012-01-01

This paper presents a mixed-method approach to measuring the functioning of Safe Schools/Healthy Students (SS/HS) Initiative partnerships. The SS/HS national evaluation team developed a survey to collect partners' perceptions of functioning within SS/HS partnerships. Average partnership functioning scores were used to rank each site from lowest to…

Ranking State Fiscal Structures Using Theory and Evidence

ERIC Educational Resources Information Center

Bania, Neil; Stone, Joe A.

2008-01-01

This paper offers unique rankings of the extent to which fiscal structures of U.S. states contribute to economic growth. The rankings are novel in two key respects: They are well grounded in established growth theory, in which the effect of taxes depends both on the level of taxes and on the composition of expenditures; and they are derived from…

Collaborative hierarchy maintains cooperation in asymmetric games.

PubMed

Antonioni, Alberto; Pereda, María; Cronin, Katherine A; Tomassini, Marco; Sánchez, Angel

2018-03-29

The interplay of social structure and cooperative behavior is under much scrutiny lately as behavior in social contexts becomes increasingly relevant for everyday life. Earlier experimental work showed that the existence of a social hierarchy, earned through competition, was detrimental for the evolution of cooperative behaviors. Here, we study the case in which individuals are ranked in a hierarchical structure based on their performance in a collective effort by having them play a Public Goods Game. In the first treatment, participants are ranked according to group earnings while, in the second treatment, their rankings are based on individual earnings. Subsequently, participants play asymmetric Prisoner's Dilemma games where higher-ranked players gain more than lower ones. Our experiments show that there are no detrimental effects of the hierarchy formed based on group performance, yet when ranking is assigned individually we observe a decrease in cooperation. Our results show that different levels of cooperation arise from the fact that subjects are interpreting rankings as a reputation which carries information about which subjects were cooperators in the previous phase. Our results demonstrate that noting the manner in which a hierarchy is established is essential for understanding its effects on cooperation.

The rank-heat plot is a novel way to present the results from a network meta-analysis including multiple outcomes.

PubMed

Veroniki, Areti Angeliki; Straus, Sharon E; Fyraridis, Alexandros; Tricco, Andrea C

2016-08-01

To present a novel and simple graphical approach to improve the presentation of the treatment ranking in a network meta-analysis (NMA) including multiple outcomes. NMA simultaneously compares many relevant interventions for a clinical condition from a network of trials, and allows ranking of the effectiveness and/or safety of each intervention. There are numerous ways to present the NMA results, which can challenge their interpretation by research users. The rank-heat plot is a novel graph that can be used to quickly recognize which interventions are most likely the best or worst interventions with respect to their effectiveness and/or safety for a single or multiple outcome(s) and may increase interpretability. Using empirical NMAs, we show that the need for a concise and informative presentation of results is imperative, particularly as the number of competing treatments and outcomes in an NMA increases. The rank-heat plot is an efficient way to present the results of ranking statistics, particularly when a large amount of data is available, and it is targeted to users from various backgrounds. Copyright © 2016 Elsevier Inc. All rights reserved.

Low rank approach to computing first and higher order derivatives using automatic differentiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reed, J. A.; Abdel-Khalik, H. S.; Utke, J.

2012-07-01

This manuscript outlines a new approach for increasing the efficiency of applying automatic differentiation (AD) to large scale computational models. By using the principles of the Efficient Subspace Method (ESM), low rank approximations of the derivatives for first and higher orders can be calculated using minimized computational resources. The output obtained from nuclear reactor calculations typically has a much smaller numerical rank compared to the number of inputs and outputs. This rank deficiency can be exploited to reduce the number of derivatives that need to be calculated using AD. The effective rank can be determined according to ESM by computingmore » derivatives with AD at random inputs. Reduced or pseudo variables are then defined and new derivatives are calculated with respect to the pseudo variables. Two different AD packages are used: OpenAD and Rapsodia. OpenAD is used to determine the effective rank and the subspace that contains the derivatives. Rapsodia is then used to calculate derivatives with respect to the pseudo variables for the desired order. The overall approach is applied to two simple problems and to MATWS, a safety code for sodium cooled reactors. (authors)« less

Role of RANK and Akt1 activation in human osteosarcoma progression: A clinicopathological study.

PubMed

Zhu, Jianxi; Liu, Yuwei; Zhu, Yong; Zeng, Min; Xie, Jie; Lei, Pengfei; Li, Kanghua; Hu, Yihe

2017-06-01

The receptor activator of nuclear factor κB (RANK) axis is the fundamental signaling pathway in bone formation as well as bone tumor pathophysiology. The aim of the present study was to evaluate the impact of the expression of RANK and its downstream signaling molecule Akt1 on tumor progression in patients with osteosarcoma. Expression of RANK and Akt1 was examined in 78 human osteosarcoma samples by immunohistochemistry using formalin-fixed samples. Following this, each graded immunohistochemistry result was correlated with clinicopathological parameters and patient survival. In total, 60 osteosarcomas (76.9%) expressed RANK and 58 cases (74.4%) showed expression of Akt1. In addition, expression of RANK was negatively correlated with disease-free survival by Kaplan-Meier analysis. A resistance was observed to chemotherapy in RANK-expressing cases, which was statistically significant (P<0.05). In addition, chemotherapy and staging of the tumor were found to independent factors that have an effect on patient survival (P<0.05). Thus, RANK was identified as a negative prognostic factor of osteosarcoma survival.

Construction of normal-regular decisions of Bessel typed special system

NASA Astrophysics Data System (ADS)

Tasmambetov, Zhaksylyk N.; Talipova, Meiramgul Zh.

2017-09-01

Studying a special system of differential equations in the separate production of the second order is solved by the degenerate hypergeometric function reducing to the Bessel functions of two variables. To construct a solution of this system near regular and irregular singularities, we use the method of Frobenius-Latysheva applying the concepts of rank and antirank. There is proved the basic theorem that establishes the existence of four linearly independent solutions of studying system type of Bessel. To prove the existence of normal-regular solutions we establish necessary conditions for the existence of such solutions. The existence and convergence of a normally regular solution are shown using the notion of rank and antirank.

Estimating sales and sales market share from sales rank data for consumer appliances

NASA Astrophysics Data System (ADS)

Touzani, Samir; Van Buskirk, Robert

2016-06-01

Our motivation in this work is to find an adequate probability distribution to fit sales volumes of different appliances. This distribution allows for the translation of sales rank into sales volume. This paper shows that the log-normal distribution and specifically the truncated version are well suited for this purpose. We demonstrate that using sales proxies derived from a calibrated truncated log-normal distribution function can be used to produce realistic estimates of market average product prices, and product attributes. We show that the market averages calculated with the sales proxies derived from the calibrated, truncated log-normal distribution provide better market average estimates than sales proxies estimated with simpler distribution functions.

Multisensory training can promote or impede visual perceptual learning of speech stimuli: visual-tactile vs. visual-auditory training.

PubMed

Eberhardt, Silvio P; Auer, Edward T; Bernstein, Lynne E

2014-01-01

In a series of studies we have been investigating how multisensory training affects unisensory perceptual learning with speech stimuli. Previously, we reported that audiovisual (AV) training with speech stimuli can promote auditory-only (AO) perceptual learning in normal-hearing adults but can impede learning in congenitally deaf adults with late-acquired cochlear implants. Here, impeder and promoter effects were sought in normal-hearing adults who participated in lipreading training. In Experiment 1, visual-only (VO) training on paired associations between CVCVC nonsense word videos and nonsense pictures demonstrated that VO words could be learned to a high level of accuracy even by poor lipreaders. In Experiment 2, visual-auditory (VA) training in the same paradigm but with the addition of synchronous vocoded acoustic speech impeded VO learning of the stimuli in the paired-associates paradigm. In Experiment 3, the vocoded AO stimuli were shown to be less informative than the VO speech. Experiment 4 combined vibrotactile speech stimuli with the visual stimuli during training. Vibrotactile stimuli were shown to promote visual perceptual learning. In Experiment 5, no-training controls were used to show that training with visual speech carried over to consonant identification of untrained CVCVC stimuli but not to lipreading words in sentences. Across this and previous studies, multisensory training effects depended on the functional relationship between pathways engaged during training. Two principles are proposed to account for stimulus effects: (1) Stimuli presented to the trainee's primary perceptual pathway will impede learning by a lower-rank pathway. (2) Stimuli presented to the trainee's lower rank perceptual pathway will promote learning by a higher-rank pathway. The mechanisms supporting these principles are discussed in light of multisensory reverse hierarchy theory (RHT).

Extension of Kaplan-Meier methods in observational studies with time-varying treatment.

PubMed

Xu, Stanley; Shetterly, Susan; Powers, David; Raebel, Marsha A; Tsai, Thomas T; Ho, P Michael; Magid, David

2012-01-01

Inverse probability of treatment weighted Kaplan-Meier estimates have been developed to compare two treatments in the presence of confounders in observational studies. Recently, stabilized weights were developed to reduce the influence of extreme inverse probability of treatment-weighted weights in estimating treatment effects. The objective of this research was to use adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests to examine the effect of a treatment that varies over time in an observational study. We proposed stabilized weight adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests when the treatment was time-varying over the follow-up period. We applied these new methods in examining the effect of an anti-platelet agent, clopidogrel, on subsequent events, including bleeding, myocardial infarction, and death after a drug-eluting stent was implanted into a coronary artery. In this population, clopidogrel use may change over time based on a patient's behavior (e.g., nonadherence) and physicians' recommendations (e.g., end of duration of therapy). Consequently, clopidogrel use was treated as a time-varying variable. We demonstrate that 1) the sample sizes at three chosen time points are almost identical in the original and weighted datasets; and 2) the covariates between patients on and off clopidogrel were well balanced after stabilized weights were applied to the original samples. The stabilized weight-adjusted Kaplan-Meier estimates and modified log-rank and Wilcoxon tests are useful in presenting and comparing survival functions for time-varying treatments in observational studies while adjusting for known confounders. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Multisensory training can promote or impede visual perceptual learning of speech stimuli: visual-tactile vs. visual-auditory training

PubMed Central

Eberhardt, Silvio P.; Auer Jr., Edward T.; Bernstein, Lynne E.

2014-01-01

In a series of studies we have been investigating how multisensory training affects unisensory perceptual learning with speech stimuli. Previously, we reported that audiovisual (AV) training with speech stimuli can promote auditory-only (AO) perceptual learning in normal-hearing adults but can impede learning in congenitally deaf adults with late-acquired cochlear implants. Here, impeder and promoter effects were sought in normal-hearing adults who participated in lipreading training. In Experiment 1, visual-only (VO) training on paired associations between CVCVC nonsense word videos and nonsense pictures demonstrated that VO words could be learned to a high level of accuracy even by poor lipreaders. In Experiment 2, visual-auditory (VA) training in the same paradigm but with the addition of synchronous vocoded acoustic speech impeded VO learning of the stimuli in the paired-associates paradigm. In Experiment 3, the vocoded AO stimuli were shown to be less informative than the VO speech. Experiment 4 combined vibrotactile speech stimuli with the visual stimuli during training. Vibrotactile stimuli were shown to promote visual perceptual learning. In Experiment 5, no-training controls were used to show that training with visual speech carried over to consonant identification of untrained CVCVC stimuli but not to lipreading words in sentences. Across this and previous studies, multisensory training effects depended on the functional relationship between pathways engaged during training. Two principles are proposed to account for stimulus effects: (1) Stimuli presented to the trainee’s primary perceptual pathway will impede learning by a lower-rank pathway. (2) Stimuli presented to the trainee’s lower rank perceptual pathway will promote learning by a higher-rank pathway. The mechanisms supporting these principles are discussed in light of multisensory reverse hierarchy theory (RHT). PMID:25400566

Are your covariates under control? How normalization can re-introduce covariate effects.

PubMed

Pain, Oliver; Dudbridge, Frank; Ronald, Angelica

2018-04-30

Many statistical tests rely on the assumption that the residuals of a model are normally distributed. Rank-based inverse normal transformation (INT) of the dependent variable is one of the most popular approaches to satisfy the normality assumption. When covariates are included in the analysis, a common approach is to first adjust for the covariates and then normalize the residuals. This study investigated the effect of regressing covariates against the dependent variable and then applying rank-based INT to the residuals. The correlation between the dependent variable and covariates at each stage of processing was assessed. An alternative approach was tested in which rank-based INT was applied to the dependent variable before regressing covariates. Analyses based on both simulated and real data examples demonstrated that applying rank-based INT to the dependent variable residuals after regressing out covariates re-introduces a linear correlation between the dependent variable and covariates, increasing type-I errors and reducing power. On the other hand, when rank-based INT was applied prior to controlling for covariate effects, residuals were normally distributed and linearly uncorrelated with covariates. This latter approach is therefore recommended in situations were normality of the dependent variable is required.

Kriging for Simulation Metamodeling: Experimental Design, Reduced Rank Kriging, and Omni-Rank Kriging

NASA Astrophysics Data System (ADS)

Hosking, Michael Robert

This dissertation improves an analyst's use of simulation by offering improvements in the utilization of kriging metamodels. There are three main contributions. First an analysis is performed of what comprises good experimental designs for practical (non-toy) problems when using a kriging metamodel. Second is an explanation and demonstration of how reduced rank decompositions can improve the performance of kriging, now referred to as reduced rank kriging. Third is the development of an extension of reduced rank kriging which solves an open question regarding the usage of reduced rank kriging in practice. This extension is called omni-rank kriging. Finally these results are demonstrated on two case studies. The first contribution focuses on experimental design. Sequential designs are generally known to be more efficient than "one shot" designs. However, sequential designs require some sort of pilot design from which the sequential stage can be based. We seek to find good initial designs for these pilot studies, as well as designs which will be effective if there is no following sequential stage. We test a wide variety of designs over a small set of test-bed problems. Our findings indicate that analysts should take advantage of any prior information they have about their problem's shape and/or their goals in metamodeling. In the event of a total lack of information we find that Latin hypercube designs are robust default choices. Our work is most distinguished by its attention to the higher levels of dimensionality. The second contribution introduces and explains an alternative method for kriging when there is noise in the data, which we call reduced rank kriging. Reduced rank kriging is based on using a reduced rank decomposition which artificially smoothes the kriging weights similar to a nugget effect. Our primary focus will be showing how the reduced rank decomposition propagates through kriging empirically. In addition, we show further evidence for our explanation through tests of reduced rank kriging's performance over different situations. In total, reduced rank kriging is a useful tool for simulation metamodeling. For the third contribution we will answer the question of how to find the best rank for reduced rank kriging. We do this by creating an alternative method which does not need to search for a particular rank. Instead it uses all potential ranks; we call this approach omnirank kriging. This modification realizes the potential gains from reduced rank kriging and provides a workable methodology for simulation metamodeling. Finally, we will demonstrate the use and value of these developments on two case studies, a clinic operation problem and a location problem. These cases will validate the value of this research. Simulation metamodeling always attempts to extract maximum information from limited data. Each one of these contributions will allow analysts to make better use of their constrained computational budgets.

Ranking 93 health interventions for low- and middle-income countries by cost-effectiveness

PubMed Central

Gelband, Hellen; Jamison, Dean; Levin, Carol; Nugent, Rachel; Watkins, David

2017-01-01

Background Cost-effectiveness rankings of health interventions are useful inputs for national healthcare planning and budgeting. Previous comprehensive rankings for low- and middle- income countries were undertaken in 2005 and 2006, accompanying the development of strategies for the Millennium Development Goals. We update the rankings using studies published since 2000, as strategies are being considered for the Sustainable Development Goals. Methods Expert systematic searches of the literature were undertaken for a broad range of health interventions. Cost-effectiveness results using Disability Adjusted Life-Years (DALYs) as the health outcome were standardized to 2012 US dollars. Results 149 individual studies of 93 interventions qualified for inclusion. Interventions for Reproductive, Maternal, Newborn and Child Health accounted for 37% of interventions, and major infectious diseases (AIDS, TB, malaria and neglected tropical diseases) for 24%, consistent with the priorities of the Millennium Development Goals. More than half of the interventions considered cost less than $200 per DALY and hence can be considered for inclusion in Universal Health Care packages even in low-income countries. Discussion Important changes have occurred in rankings since 2006. Priorities have changed as a result of new technologies, new methods for changing behavior, and significant price changes for some vaccines and drugs. Achieving the Sustainable Development Goals will require LMICs to study a broader range of health interventions, particularly in adult health. Some interventions are no longer studied, in some cases because they have become usual care, in other cases because they are no longer relevant. Updating cost-effectiveness rankings on a regular basis is potentially a valuable exercise. PMID:28797115

FSMRank: feature selection algorithm for learning to rank.

PubMed

Lai, Han-Jiang; Pan, Yan; Tang, Yong; Yu, Rong

2013-06-01

In recent years, there has been growing interest in learning to rank. The introduction of feature selection into different learning problems has been proven effective. These facts motivate us to investigate the problem of feature selection for learning to rank. We propose a joint convex optimization formulation which minimizes ranking errors while simultaneously conducting feature selection. This optimization formulation provides a flexible framework in which we can easily incorporate various importance measures and similarity measures of the features. To solve this optimization problem, we use the Nesterov's approach to derive an accelerated gradient algorithm with a fast convergence rate O(1/T(2)). We further develop a generalization bound for the proposed optimization problem using the Rademacher complexities. Extensive experimental evaluations are conducted on the public LETOR benchmark datasets. The results demonstrate that the proposed method shows: 1) significant ranking performance gain compared to several feature selection baselines for ranking, and 2) very competitive performance compared to several state-of-the-art learning-to-rank algorithms.

The Role of Tonsillectomy in Adults with Tonsillar Hypertrophy and Obstructive Sleep Apnea.

PubMed

Smith, Matthew M; Peterson, Ed; Yaremchuk, Kathleen L

2017-08-01

Objective To determine if tonsillectomy alone is an effective treatment in improving obstructive sleep apnea in adult subjects with tonsillar hypertrophy and to evaluate the effect of tonsillectomy on patient-reported quality-of-life indices. Study Design Case series with planned data collection. Setting Academic hospital. Subjects and Methods Thirty-four subjects completed enrollment and intervention from January 2011 to January 2016. Subjects completed pre- and postoperative quality-of-life questionnaires, including the Insomnia Severity Index, Epworth Sleepiness Scale, and the Functional Outcomes of Sleep Questionnaire-10. Surgical response to treatment was defined by a >50% decrease in the Apnea-Hypopnea Index and a decrease in the overall Apnea-Hypopnea Index to <20. Wilcoxon matched-pairs signed-rank tests were used to test each variable to assess for a change from pre- to postintervention. Subjects were then split into 3 BMI subgroups, with results also evaluated by Wilcoxon matched-pairs signed-rank tests. Results There was a significant difference discovered between the mean preoperative Apnea-Hypopnea Index of 31.57 and the mean postoperative value of 8.12 ( P < .001). All patient-reported outcomes improved significantly following tonsillectomy. After stratifying all outcome variables (Apnea-Hypopnea Index, Epworth Sleepiness Scale, Insomnia Severity Index, and Functional Outcomes of Sleep Questionnaire-10) by sex, race, and tonsil size, no statistically significant difference was noted among any of these subgroups. There was a 78% surgical response to treatment. Conclusion Tonsillectomy appears to be an effective treatment for obstructive sleep apnea in a select population of adults with tonsillar hypertrophy.

Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention

PubMed Central

Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

2015-01-01

Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases. PMID:26295344

Adaptation and Evaluation of a Multi-Criteria Decision Analysis Model for Lyme Disease Prevention.

PubMed

Aenishaenslin, Cécile; Gern, Lise; Michel, Pascal; Ravel, André; Hongoh, Valérie; Waaub, Jean-Philippe; Milord, François; Bélanger, Denise

2015-01-01

Designing preventive programs relevant to vector-borne diseases such as Lyme disease (LD) can be complex given the need to include multiple issues and perspectives into prioritizing public health actions. A multi-criteria decision aid (MCDA) model was previously used to rank interventions for LD prevention in Quebec, Canada, where the disease is emerging. The aim of the current study was to adapt and evaluate the decision model constructed in Quebec under a different epidemiological context, in Switzerland, where LD has been endemic for the last thirty years. The model adaptation was undertaken with a group of Swiss stakeholders using a participatory approach. The PROMETHEE method was used for multi-criteria analysis. Key elements and results of the MCDA model are described and contrasted with the Quebec model. All criteria and most interventions of the MCDA model developed for LD prevention in Quebec were directly transferable to the Swiss context. Four new decision criteria were added, and the list of proposed interventions was modified. Based on the overall group ranking, interventions targeting human populations were prioritized in the Swiss model, with the top ranked action being the implementation of a large communication campaign. The addition of criteria did not significantly alter the intervention rankings, but increased the capacity of the model to discriminate between highest and lowest ranked interventions. The current study suggests that beyond the specificity of the MCDA models developed for Quebec and Switzerland, their general structure captures the fundamental and common issues that characterize the complexity of vector-borne disease prevention. These results should encourage public health organizations to adapt, use and share MCDA models as an effective and functional approach to enable the integration of multiple perspectives and considerations in the prevention and control of complex public health issues such as Lyme disease or other vector-borne and zoonotic diseases.

A User’s Guide to BISAM (BIvariate SAMple): The Bivariate Data Modeling Program.

DTIC Science & Technology

1983-08-01

method for the null case specified and is then used to form the bivariate density-quantile function as described in section 4. If D(U) in stage...employed assigns average ranks for tied observations. Other methods for assigning ranks to tied observations are often employed but are not attempted...34 €.. . . . .. . .. . . . ,.. . ,•. . . ... *.., .. , - . . . . - - . . .. - -. .. observations will weaken the results obtained since underlying continuous distributions are assumed. One should avoid such situations if possible. Two methods

Use of Information Technology Tools in Source Selection Decision Making: A Study on USAF’s KC-X Tanker Replacement Program

DTIC Science & Technology

2008-06-01

The most common outranking methods are the preference ranking organization method for enrichment evaluation ( PROMETHEE ) and the elimination and...Brans and Ph. Vincke, “A Preference Ranking Organization Method: (The PROMETHEE Method for Multiple Criteria Decision-Making),” Management Science 31... PROMETHEE ). This method needs a preference function for each criterion to compute the degree of preference.72 “The credibility of the outranking

Face the hierarchy: ERP and oscillatory brain responses in social rank processing.

PubMed

Breton, Audrey; Jerbi, Karim; Henaff, Marie-Anne; Cheylus, Anne; Baudouin, Jean-Yves; Schmitz, Christina; Krolak-Salmon, Pierre; Van der Henst, Jean-Baptiste

2014-01-01

Recognition of social hierarchy is a key feature that helps us navigate through our complex social environment. Neuroimaging studies have identified brain structures involved in the processing of hierarchical stimuli but the precise temporal dynamics of brain activity associated with such processing remains largely unknown. Here, we used electroencephalography to examine the effect of social hierarchy on neural responses elicited by faces. In contrast to previous studies, the key manipulation was that a hierarchical context was constructed, not by varying facial expressions, but by presenting neutral-expression faces in a game setting. Once the performance-based hierarchy was established, participants were presented with high-rank, middle-rank and low-rank player faces and had to evaluate the rank of each face with respect to their own position. Both event-related potentials and task-related oscillatory activity were investigated. Three main findings emerge from the study. First, the experimental manipulation had no effect on the early N170 component, which may suggest that hierarchy did not modulate the structural encoding of neutral-expression faces. Second, hierarchy significantly modulated the amplitude of the late positive potential (LPP) within a 400-700 ms time-window, with more a prominent LPP occurring when the participants processed the face of the highest-rank player. Third, high-rank faces were associated with the highest reduction of alpha power. Taken together these findings provide novel electrophysiological evidence for enhanced allocation of attentional resource in the presence of high-rank faces. At a broader level, this study brings new insights into the neural processing underlying social categorization.

Respiratory symptoms, lung function, and sensitisation to flour in a British bakery.

PubMed Central

Musk, A W; Venables, K M; Crook, B; Nunn, A J; Hawkins, R; Crook, G D; Graneek, B J; Tee, R D; Farrer, N; Johnson, D A

1989-01-01

A survey of dust exposure, respiratory symptoms, lung function, and response to skin prick tests was conducted in a modern British bakery. Of the 318 bakery employees, 279 (88%) took part. Jobs were ranked from 0 to 10 by perceived dustiness and this ranking correlated well with total dust concentration measured in 79 personal dust samples. Nine samples had concentrations greater than 10 mg/m3, the exposure limit for nuisance dust. All participants completed a self administered questionnaire on symptoms and their relation to work. FEV1 and FVC were measured by a dry wedge spirometer and bronchial reactivity to methacholine was estimated. Skin prick tests were performed with three common allergens and with 11 allergens likely to be found in bakery dust, including mites and moulds. Of the participants in the main exposure group, 35% reported chest symptoms which in 13% were work related. The corresponding figures for nasal symptoms were 38% and 19%. Symptoms, lung function, bronchial reactivity, and response to skin prick tests were related to current or past exposure to dust using logistic or linear regression analysis as appropriate. Exposure rank was significantly associated with most of the response variables studied. The study shows that respiratory symptoms and sensitisation are common, even in a modern bakery. PMID:2789967

Are university rankings useful to improve research? A systematic review

PubMed Central

Momani, Shaher

2018-01-01

Introduction Concerns about reproducibility and impact of research urge improvement initiatives. Current university ranking systems evaluate and compare universities on measures of academic and research performance. Although often useful for marketing purposes, the value of ranking systems when examining quality and outcomes is unclear. The purpose of this study was to evaluate usefulness of ranking systems and identify opportunities to support research quality and performance improvement. Methods A systematic review of university ranking systems was conducted to investigate research performance and academic quality measures. Eligibility requirements included: inclusion of at least 100 doctoral granting institutions, be currently produced on an ongoing basis and include both global and US universities, publish rank calculation methodology in English and independently calculate ranks. Ranking systems must also include some measures of research outcomes. Indicators were abstracted and contrasted with basic quality improvement requirements. Exploration of aggregation methods, validity of research and academic quality indicators, and suitability for quality improvement within ranking systems were also conducted. Results A total of 24 ranking systems were identified and 13 eligible ranking systems were evaluated. Six of the 13 rankings are 100% focused on research performance. For those reporting weighting, 76% of the total ranks are attributed to research indicators, with 24% attributed to academic or teaching quality. Seven systems rely on reputation surveys and/or faculty and alumni awards. Rankings influence academic choice yet research performance measures are the most weighted indicators. There are no generally accepted academic quality indicators in ranking systems. Discussion No single ranking system provides a comprehensive evaluation of research and academic quality. Utilizing a combined approach of the Leiden, Thomson Reuters Most Innovative Universities, and the SCImago ranking systems may provide institutions with a more effective feedback for research improvement. Rankings which extensively rely on subjective reputation and “luxury” indicators, such as award winning faculty or alumni who are high ranking executives, are not well suited for academic or research performance improvement initiatives. Future efforts should better explore measurement of the university research performance through comprehensive and standardized indicators. This paper could serve as a general literature citation when one or more of university ranking systems are used in efforts to improve academic prominence and research performance. PMID:29513762

Cross ranking of cities and regions: population versus income

NASA Astrophysics Data System (ADS)

Cerqueti, Roy; Ausloos, Marcel

2015-07-01

This paper explores the relationship between the inner economical structure of communities and their population distribution through a rank-rank analysis of official data, along statistical physics ideas within two techniques. The data is taken on Italian cities. The analysis is performed both at a global (national) and at a more local (regional) level in order to distinguish ‘macro’ and ‘micro’ aspects. First, the rank-size rule is found not to be a standard power law, as in many other studies, but a doubly decreasing power law. Next, the Kendall τ and the Spearman ρ rank correlation coefficients which measure pair concordance and the correlation between fluctuations in two rankings, respectively,—as a correlation function does in thermodynamics, are calculated for finding rank correlation (if any) between demography and wealth. Results show non only global disparities for the whole (country) set, but also (regional) disparities, when comparing the number of cities in regions, the number of inhabitants in cities and that in regions, as well as when comparing the aggregated tax income of the cities and that of regions. Different outliers are pointed out and justified. Interestingly, two classes of cities in the country and two classes of regions in the country are found. ‘Common sense’ social, political, and economic considerations sustain the findings. More importantly, the methods show that they allow to distinguish communities, very clearly, when specific criteria are numerically sound. A specific modeling for the findings is presented, i.e. for the doubly decreasing power law and the two phase system, based on statistics theory, e.g. urn filling. The model ideas can be expected to hold when similar rank relationship features are observed in fields. It is emphasized that the analysis makes more sense than one through a Pearson Π value-value correlation analysis

A Comparative Study of the Roles and Functions of School Principals and Bilingual Program Administrators.

ERIC Educational Resources Information Center

Sanchez,Gilbert; Cali, Alfred J.

This study was designed to compare time allocations to major functions actually performed and idealized by bilingual administrators and principals; to rank specific procedures used in accomplishing these functions; to determine staffing patterns, and program and organizational characteristics; and to isolate personal/professional demographics of…

Assessment of the relationship between the output of the educational systems and the assumed effective factors in Medical Education written in Data Banks and Ranking of Iran Medical Faculties book

PubMed Central

Mishmast Nehy, GhA

2015-01-01

Developing and expanding the universities and increasing the admission of medical students did resolve the physician shortage, but it brought down the educational quality in return. To face this problem, the administrates needed to promote the quality of education which in turn needed accurate up to date information about conditions in different universities. Information about these issues was collected by the Medical Education Council Secretariat and finally published as the Data Bank and Ranking of the Medical Faculties. Method: Although nowadays ranking is more qualitative rather than quantitative, the above ranking was done by a statistical method. In this research, the intended statistic population consisted of the data included in the database and the ranking of all 38 medical faculties. To perform this research, the ranking of faculties in the comprehensive entrance exam which indicated the input of educational system was considered the index at first, and later, the ranking of the faculties in the effective factors in education, was arranged according to the regulation of the input system; then outputs of the educational system were adjusted according to the input system and finally a comprehensive table of all the educational information was provided. Then, the relationship of various factors in education with outputs of educational system were discussed. Result: The correlations of each and all factors, which have an effective part on education were considered separately, collectively, and together, based on the information of the above book. No connection was detected within the factors, which affected the education and the output in different universities. The only relation notable was the admission degree and the outcomes of the national basic science exams. Since no meaningful connection was found within the present parameters, it seemed to be wrong to follow the path that the other sections of the world have taken in choosing the ranking factors. PMID:28316660

Assessment of the relationship between the output of the educational systems and the assumed effective factors in Medical Education written in Data Banks and Ranking of Iran Medical Faculties book.

PubMed

Mishmast Nehy, GhA

2015-01-01

Developing and expanding the universities and increasing the admission of medical students did resolve the physician shortage, but it brought down the educational quality in return. To face this problem, the administrates needed to promote the quality of education which in turn needed accurate up to date information about conditions in different universities. Information about these issues was collected by the Medical Education Council Secretariat and finally published as the Data Bank and Ranking of the Medical Faculties. Method: Although nowadays ranking is more qualitative rather than quantitative, the above ranking was done by a statistical method. In this research, the intended statistic population consisted of the data included in the database and the ranking of all 38 medical faculties. To perform this research, the ranking of faculties in the comprehensive entrance exam which indicated the input of educational system was considered the index at first, and later, the ranking of the faculties in the effective factors in education, was arranged according to the regulation of the input system; then outputs of the educational system were adjusted according to the input system and finally a comprehensive table of all the educational information was provided. Then, the relationship of various factors in education with outputs of educational system were discussed. Result: The correlations of each and all factors, which have an effective part on education were considered separately, collectively, and together, based on the information of the above book. No connection was detected within the factors, which affected the education and the output in different universities. The only relation notable was the admission degree and the outcomes of the national basic science exams. Since no meaningful connection was found within the present parameters, it seemed to be wrong to follow the path that the other sections of the world have taken in choosing the ranking factors.

Health Information on Internet: Quality, Importance, and Popularity of Persian Health Websites

PubMed Central

Samadbeik, Mahnaz; Ahmadi, Maryam; Mohammadi, Ali; Mohseni Saravi, Beniamin

2014-01-01

Background: The Internet has provided great opportunities for disseminating both accurate and inaccurate health information. Therefore, the quality of information is considered as a widespread concern affecting the human life. Despite the increasingly substantial growth in the number of users, Persian health websites and the proportion of internet-using patients, little is known about the quality of Persian medical and health websites. Objectives: The current study aimed to first assess the quality, popularity and importance of websites providing Persian health-related information, and second to evaluate the correlation of the popularity and importance ranking with quality score on the Internet. Materials and Methods: The sample websites were identified by entering the health-related keywords into four most popular search engines of Iranian users based on the Alexa ranking at the time of study. Each selected website was assessed using three qualified tools including the Bomba and Land Index, Google PageRank and the Alexa ranking. Results: The evaluated sites characteristics (ownership structure, database, scope and objective) really did not have an effect on the Alexa traffic global rank, Alexa traffic rank in Iran, Google PageRank and Bomba total score. Most websites (78.9 percent, n = 56) were in the moderate category (8 ≤ x ≤ 11.99) based on their quality levels. There was no statistically significant association between Google PageRank with Bomba index variables and Alexa traffic global rank (P > 0.05). Conclusions: The Persian health websites had better Bomba quality scores in availability and usability guidelines as compared to other guidelines. The Google PageRank did not properly reflect the real quality of evaluated websites and Internet users seeking online health information should not merely rely on it for any kind of prejudgment regarding Persian health websites. However, they can use Iran Alexa rank as a primary filtering tool of these websites. Therefore, designing search engines dedicated to explore accredited Persian health-related Web sites can be an effective method to access high-quality Persian health websites. PMID:24910795

Econophysics of a ranked demand and supply resource allocation problem

NASA Astrophysics Data System (ADS)

Priel, Avner; Tamir, Boaz

2018-01-01

We present a two sided resource allocation problem, between demands and supplies, where both parties are ranked. For example, in Big Data problems where a set of different computational tasks is divided between a set of computers each with its own resources, or between employees and employers where both parties are ranked, the employees by their fitness and the employers by their package benefits. The allocation process can be viewed as a repeated game where in each iteration the strategy is decided by a meta-rule, based on the ranks of both parties and the results of the previous games. We show the existence of a phase transition between an absorbing state, where all demands are satisfied, and an active one where part of the demands are always left unsatisfied. The phase transition is governed by the ratio between supplies and demand. In a job allocation problem we find positive correlation between the rank of the workers and the rank of the factories; higher rank workers are usually allocated to higher ranked factories. These all suggest global emergent properties stemming from local variables. To demonstrate the global versus local relations, we introduce a local inertial force that increases the rank of employees in proportion to their persistence time in the same factory. We show that such a local force induces non trivial global effects, mostly to benefit the lower ranked employees.

Using binary classification to prioritize and curate articles for the Comparative Toxicogenomics Database.

PubMed

Vishnyakova, Dina; Pasche, Emilie; Ruch, Patrick

2012-01-01

We report on the original integration of an automatic text categorization pipeline, so-called ToxiCat (Toxicogenomic Categorizer), that we developed to perform biomedical documents classification and prioritization in order to speed up the curation of the Comparative Toxicogenomics Database (CTD). The task can be basically described as a binary classification task, where a scoring function is used to rank a selected set of articles. Then components of a question-answering system are used to extract CTD-specific annotations from the ranked list of articles. The ranking function is generated using a Support Vector Machine, which combines three main modules: an information retrieval engine for MEDLINE (EAGLi), a gene normalization service (NormaGene) developed for a previous BioCreative campaign and finally, a set of answering components and entity recognizer for diseases and chemicals. The main components of the pipeline are publicly available both as web application and web services. The specific integration performed for the BioCreative competition is available via a web user interface at http://pingu.unige.ch:8080/Toxicat.

Role of RANKL (TNFSF11)-dependent osteopetrosis in the dental phenotype of Msx2 null mutant mice.

PubMed

Castaneda, Beatriz; Simon, Yohann; Ferbus, Didier; Robert, Benoit; Chesneau, Julie; Mueller, Christopher; Berdal, Ariane; Lézot, Frédéric

2013-01-01

The MSX2 homeoprotein is implicated in all aspects of craniofacial skeletal development. During postnatal growth, MSX2 is expressed in all cells involved in mineralized tissue formation and plays a role in their differentiation and function. Msx2 null (Msx2 (-/-)) mice display complex craniofacial skeleton abnormalities with bone and tooth defects. A moderate form osteopetrotic phenotype is observed, along with decreased expression of RANKL (TNFSF11), the main osteoclast-differentiating factor. In order to elucidate the role of such an osteopetrosis in the Msx2 (-/-) mouse dental phenotype, a bone resorption rescue was performed by mating Msx2 (-/-) mice with a transgenic mouse line overexpressing Rank (Tnfrsf11a). Msx2 (-/-) Rank(Tg) mice had significant improvement in the molar phenotype, while incisor epithelium defects were exacerbated in the enamel area, with formation of massive osteolytic tumors. Although compensation for RANKL loss of function could have potential as a therapy for osteopetrosis, but in Msx2 (-/-) mice, this approach via RANK overexpression in monocyte-derived lineages, amplified latent epithelial tumor development in the peculiar continuously growing incisor.

Sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants.

PubMed

Gerner, Nadine V; Cailleaud, Kevin; Bassères, Anne; Liess, Matthias; Beketov, Mikhail A

2017-11-01

Hydrocarbons have an utmost economical importance but may also cause substantial ecological impacts due to accidents or inadequate transportation and use. Currently, freshwater biomonitoring methods lack an indicator that can unequivocally reflect the impacts caused by hydrocarbons while being independent from effects of other stressors. The aim of the present study was to develop a sensitivity ranking for freshwater invertebrates towards hydrocarbon contaminants, which can be used in hydrocarbon-specific bioindicators. We employed the Relative Sensitivity method and developed the sensitivity ranking S hydrocarbons based on literature ecotoxicological data supplemented with rapid and mesocosm test results. A first validation of the sensitivity ranking based on an earlier field study has been conducted and revealed the S hydrocarbons ranking to be promising for application in sensitivity based indicators. Thus, the first results indicate that the ranking can serve as the core component of future hydrocarbon-specific and sensitivity trait based bioindicators.

Specific Features of Executive Dysfunction in Alzheimer-Type Mild Dementia Based on Computerized Cambridge Neuropsychological Test Automated Battery (CANTAB) Test Results.

PubMed

Kuzmickienė, Jurgita; Kaubrys, Gintaras

2016-10-08

BACKGROUND The primary manifestation of Alzheimer's disease (AD) is decline in memory. Dysexecutive symptoms have tremendous impact on functional activities and quality of life. Data regarding frontal-executive dysfunction in mild AD are controversial. The aim of this study was to assess the presence and specific features of executive dysfunction in mild AD based on Cambridge Neuropsychological Test Automated Battery (CANTAB) results. MATERIAL AND METHODS Fifty newly diagnosed, treatment-naïve, mild, late-onset AD patients (MMSE ≥20, AD group) and 25 control subjects (CG group) were recruited in this prospective, cross-sectional study. The CANTAB tests CRT, SOC, PAL, SWM were used for in-depth cognitive assessment. Comparisons were performed using the t test or Mann-Whitney U test, as appropriate. Correlations were evaluated by Pearson r or Spearman R. Statistical significance was set at p<0.05. RESULTS AD and CG groups did not differ according to age, education, gender, or depression. Few differences were found between groups in the SOC test for performance measures: Mean moves (minimum 3 moves): AD (Rank Sum=2227), CG (Rank Sum=623), p<0.001. However, all SOC test time measures differed significantly between groups: SOC Mean subsequent thinking time (4 moves): AD (Rank Sum=2406), CG (Rank Sum=444), p<0.001. Correlations were weak between executive function (SOC) and episodic/working memory (PAL, SWM) (R=0.01-0.38) or attention/psychomotor speed (CRT) (R=0.02-0.37). CONCLUSIONS Frontal-executive functions are impaired in mild AD patients. Executive dysfunction is highly prominent in time measures, but minimal in performance measures. Executive disorders do not correlate with a decline in episodic and working memory or psychomotor speed in mild AD.

High-resolution dynamic 31 P-MRSI using a low-rank tensor model.

PubMed

Ma, Chao; Clifford, Bryan; Liu, Yuchi; Gu, Yuning; Lam, Fan; Yu, Xin; Liang, Zhi-Pei

2017-08-01

To develop a rapid 31 P-MRSI method with high spatiospectral resolution using low-rank tensor-based data acquisition and image reconstruction. The multidimensional image function of 31 P-MRSI is represented by a low-rank tensor to capture the spatial-spectral-temporal correlations of data. A hybrid data acquisition scheme is used for sparse sampling, which consists of a set of "training" data with limited k-space coverage to capture the subspace structure of the image function, and a set of sparsely sampled "imaging" data for high-resolution image reconstruction. An explicit subspace pursuit approach is used for image reconstruction, which estimates the bases of the subspace from the "training" data and then reconstructs a high-resolution image function from the "imaging" data. We have validated the feasibility of the proposed method using phantom and in vivo studies on a 3T whole-body scanner and a 9.4T preclinical scanner. The proposed method produced high-resolution static 31 P-MRSI images (i.e., 6.9 × 6.9 × 10 mm 3 nominal resolution in a 15-min acquisition at 3T) and high-resolution, high-frame-rate dynamic 31 P-MRSI images (i.e., 1.5 × 1.5 × 1.6 mm 3 nominal resolution, 30 s/frame at 9.4T). Dynamic spatiospectral variations of 31 P-MRSI signals can be efficiently represented by a low-rank tensor. Exploiting this mathematical structure for data acquisition and image reconstruction can lead to fast 31 P-MRSI with high resolution, frame-rate, and SNR. Magn Reson Med 78:419-428, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

A multimedia retrieval framework based on semi-supervised ranking and relevance feedback.

PubMed

Yang, Yi; Nie, Feiping; Xu, Dong; Luo, Jiebo; Zhuang, Yueting; Pan, Yunhe

2012-04-01

We present a new framework for multimedia content analysis and retrieval which consists of two independent algorithms. First, we propose a new semi-supervised algorithm called ranking with Local Regression and Global Alignment (LRGA) to learn a robust Laplacian matrix for data ranking. In LRGA, for each data point, a local linear regression model is used to predict the ranking scores of its neighboring points. A unified objective function is then proposed to globally align the local models from all the data points so that an optimal ranking score can be assigned to each data point. Second, we propose a semi-supervised long-term Relevance Feedback (RF) algorithm to refine the multimedia data representation. The proposed long-term RF algorithm utilizes both the multimedia data distribution in multimedia feature space and the history RF information provided by users. A trace ratio optimization problem is then formulated and solved by an efficient algorithm. The algorithms have been applied to several content-based multimedia retrieval applications, including cross-media retrieval, image retrieval, and 3D motion/pose data retrieval. Comprehensive experiments on four data sets have demonstrated its advantages in precision, robustness, scalability, and computational efficiency.

Gamma knife radiosurgery for vestibular schwannomas: tumor control and functional preservation in 70 patients.

PubMed

Arthurs, Benjamin J; Lamoreaux, Wayne T; Mackay, Alexander R; Demakas, John J; Giddings, Neil A; Fairbanks, Robert K; Cooke, Barton S; Elaimy, Ameer L; Peressini, Ben; Lee, Christopher M

2011-06-01

We present the previously unreported outcomes of 70 patients treated with Gamma knife radiosurgery for vestibular schwannoma (VS), including comprehensive analysis of clinical outcomes and the effects of lower marginal doses. We performed a retrospective study of patients treated for VS at Gamma knife of Spokane between 2003 and 2008. Endpoints measured include tumor control, hearing preservation, and facial nerve preservation, including the effect of tumor size and marginal dose. Statistical analysis was performed with Wilcoxon signed-rank test, paired Student t test, Mann-Whitney U test, Kendall's rank correlation, Fisher exact test, and Liddell's exact χ(2) test for matched pairs. With a mean follow-up of 26 months, 93.8% of tumors either shrank or remained static after receiving a mean marginal dose of 12.7 Gy. Tumor control was independent of marginal dose or tumor size. Hearing preservation was achieved in 64% of patients with serviceable function before the treatment. Hearing changes were independent of dose or tumor size. Preservation of good facial nerve function was achieved in 95% of patients. Post-treatment hydrocephalus occurred in 4.4% of patients, but no other significant morbidities were elucidated. In the treatment of VS, contemporary radiosurgical techniques and the use of marginal doses below 13 Gy offer excellent tumor control, at high rates relative to surgical intervention. These findings are independent of marginal dose and tumor size. Patients should be informed about the benefits and risks of radiosurgery and microsurgery before choosing an intervention. Further analysis of post-treatment outcomes should be encouraged as follow-up times increase and the treatment protocols continue to evolve.

Paracrine-mediated osteoclastogenesis by the osteosarcoma MG63 cell line: is RANKL/RANK signalling really important?

PubMed

Costa-Rodrigues, J; Teixeira, C A; Fernandes, M H

2011-08-01

Although in the past little attention has been paid to the influence of osteosarcoma cells in osteoclast function, recent studies suggest a close relationship between osteosarcoma aggressiveness and osteoclastic activity. The present study addresses the paracrine effects of MG63 cells, a human osteosarcoma-derived cell line, on the differentiation of peripheral blood osteoclast precursor cells (PBMC). PBMC were cultured for 21 days in the presence of conditioned media from MG63 cell cultures (CM) collected at 48 h (CM_MG1), 7 days (CM_MG2) and 14 days (CM_MG3). MG63 cell cultures displayed the expression of ALP and BMP-2 and, also, the osteoclastogenic genes M-CSF and RANKL, although with a low expression of RANKL. PBMC cultures supplemented with CM presented an evident osteoclastogenic behavior, which was dependent on the culture period of the MG63 cells. The inductive effect appeared to be more relevant for the differentiation and activation genes, c-myc and c-src, and lower for genes associated with osteoclast function. In addition, PBMC cultures displayed increased functional parameters, including calcium phosphate resorbing activity. Assessment of the PBMC cultures in the presence of U0126, PDTC, and indomethacin suggested that in addition to MEK and NFkB pathways, other signaling mechanisms, probably not involving RANKL/RANK interaction, might be activated in the presence of conditioned medium from MG63. In conclusion, MG63 cell line appears to induce a significant paracrine-mediated osteoclastogenic response. Understanding the mechanisms underlying the interaction of osteosarcoma cells and osteoclasts may contribute to the development of new potential approaches in the treatment of such bone metabolic diseases.

Quantization of the Szekeres system

NASA Astrophysics Data System (ADS)

Paliathanasis, A.; Zampeli, Adamantia; Christodoulakis, T.; Mustafa, M. T.

2018-06-01

We study the quantum corrections on the Szekeres system in the context of canonical quantization in the presence of symmetries. We start from an effective point-like Lagrangian with two integrals of motion, one corresponding to the Hamiltonian and the other to a second rank killing tensor. Imposing their quantum version on the wave function results to a solution which is then interpreted in the context of Bohmian mechanics. In this semiclassical approach, it is shown that there is no quantum corrections, thus the classical trajectories of the Szekeres system are not affected at this level. Finally, we define a probability function which shows that a stationary surface of the probability corresponds to a classical exact solution.

Local Knowledge When Ranking Journals: Reproductive Effects and Resistant Possibilities

ERIC Educational Resources Information Center

Canagarajah, Suresh

2014-01-01

This article is based on the engagement of a US-based scholar and faculty members in a non-Western university in a mentoring exercise on publishing. It demonstrates how the "list" constructed in a particular academic department in the university for ranking relevant journals for publication has reproductive effects on knowledge…

Effects of OCR Errors on Ranking and Feedback Using the Vector Space Model.

ERIC Educational Resources Information Center

Taghva, Kazem; And Others

1996-01-01

Reports on the performance of the vector space model in the presence of OCR (optical character recognition) errors in information retrieval. Highlights include precision and recall, a full-text test collection, smart vector representation, impact of weighting parameters, ranking variability, and the effect of relevance feedback. (Author/LRW)

Functional Assessment of Genetic Variants with Outcomes Adapted to Clinical Decision-Making

PubMed Central

Thouvenot, Pierre; Ben Yamin, Barbara; Fourrière, Lou; Lescure, Aurianne; Boudier, Thomas; Del Nery, Elaine; Chauchereau, Anne; Goldgar, David E.; Stoppa-Lyonnet, Dominique; Nicolas, Alain; Millot, Gaël A.

2016-01-01

Understanding the medical effect of an ever-growing number of human variants detected is a long term challenge in genetic counseling. Functional assays, based on in vitro or in vivo evaluations of the variant effects, provide essential information, but they require robust statistical validation, as well as adapted outputs, to be implemented in the clinical decision-making process. Here, we assessed 25 pathogenic and 15 neutral missense variants of the BRCA1 breast/ovarian cancer susceptibility gene in four BRCA1 functional assays. Next, we developed a novel approach that refines the variant ranking in these functional assays. Lastly, we developed a computational system that provides a probabilistic classification of variants, adapted to clinical interpretation. Using this system, the best functional assay exhibits a variant classification accuracy estimated at 93%. Additional theoretical simulations highlight the benefit of this ready-to-use system in the classification of variants after functional assessment, which should facilitate the consideration of functional evidences in the decision-making process after genetic testing. Finally, we demonstrate the versatility of the system with the classification of siRNAs tested for human cell growth inhibition in high throughput screening. PMID:27272900

Chimpanzee females queue but males compete for social status

PubMed Central

Foerster, Steffen; Franz, Mathias; Murray, Carson M.; Gilby, Ian C.; Feldblum, Joseph T.; Walker, Kara K.; Pusey, Anne E.

2016-01-01

Dominance hierarchies are widespread in animal social groups and often have measureable effects on individual health and reproductive success. Dominance ranks are not static individual attributes, however, but instead are influenced by two independent processes: 1) changes in hierarchy membership and 2) successful challenges of higher-ranking individuals. Understanding which of these processes dominates the dynamics of rank trajectories can provide insights into fitness benefits of within-sex competition. This question has yet to be examined systematically in a wide range of taxa due to the scarcity of long-term data and a lack of appropriate methodologies for distinguishing between alternative causes of rank changes over time. Here, we expand on recent work and develop a new likelihood-based Elo rating method that facilitates the systematic assessment of rank dynamics in animal social groups, even when interaction data are sparse. We apply this method to characterize long-term rank trajectories in wild eastern chimpanzees (Pan troglodytes schweinfurthii) and find remarkable sex differences in rank dynamics, indicating that females queue for social status while males actively challenge each other to rise in rank. Further, our results suggest that natal females obtain a head start in the rank queue if they avoid dispersal, with potential fitness benefits. PMID:27739527

Low-rank coal oil agglomeration product and process

DOEpatents

Knudson, Curtis L.; Timpe, Ronald C.; Potas, Todd A.; DeWall, Raymond A.; Musich, Mark A.

1992-01-01

A selectively-sized, raw, low-rank coal is processed to produce a low ash and relative water-free agglomerate with an enhanced heating value and a hardness sufficient to produce a non-decrepitating, shippable fuel. The low-rank coal is treated, under high shear conditions, in the first stage to cause ash reduction and subsequent surface modification which is necessary to facilitate agglomerate formation. In the second stage the treated low-rank coal is contacted with bridging and binding oils under low shear conditions to produce agglomerates of selected size. The bridging and binding oils may be coal or petroleum derived. The process incorporates a thermal deoiling step whereby the bridging oil may be completely or partially recovered from the agglomerate; whereas, partial recovery of the bridging oil functions to leave as an agglomerate binder, the heavy constituents of the bridging oil. The recovered oil is suitable for recycling to the agglomeration step or can serve as a value-added product.

Low-rank coal oil agglomeration product and process

DOEpatents

Knudson, C.L.; Timpe, R.C.; Potas, T.A.; DeWall, R.A.; Musich, M.A.

1992-11-10

A selectively-sized, raw, low-rank coal is processed to produce a low ash and relative water-free agglomerate with an enhanced heating value and a hardness sufficient to produce a non-degradable, shippable fuel. The low-rank coal is treated, under high shear conditions, in the first stage to cause ash reduction and subsequent surface modification which is necessary to facilitate agglomerate formation. In the second stage the treated low-rank coal is contacted with bridging and binding oils under low shear conditions to produce agglomerates of selected size. The bridging and binding oils may be coal or petroleum derived. The process incorporates a thermal deoiling step whereby the bridging oil may be completely or partially recovered from the agglomerate; whereas, partial recovery of the bridging oil functions to leave as an agglomerate binder, the heavy constituents of the bridging oil. The recovered oil is suitable for recycling to the agglomeration step or can serve as a value-added product.

Ranking and averaging independent component analysis by reproducibility (RAICAR).

PubMed

Yang, Zhi; LaConte, Stephen; Weng, Xuchu; Hu, Xiaoping

2008-06-01

Independent component analysis (ICA) is a data-driven approach that has exhibited great utility for functional magnetic resonance imaging (fMRI). Standard ICA implementations, however, do not provide the number and relative importance of the resulting components. In addition, ICA algorithms utilizing gradient-based optimization give decompositions that are dependent on initialization values, which can lead to dramatically different results. In this work, a new method, RAICAR (Ranking and Averaging Independent Component Analysis by Reproducibility), is introduced to address these issues for spatial ICA applied to fMRI. RAICAR utilizes repeated ICA realizations and relies on the reproducibility between them to rank and select components. Different realizations are aligned based on correlations, leading to aligned components. Each component is ranked and thresholded based on between-realization correlations. Furthermore, different realizations of each aligned component are selectively averaged to generate the final estimate of the given component. Reliability and accuracy of this method are demonstrated with both simulated and experimental fMRI data. Copyright 2007 Wiley-Liss, Inc.

A parallel computer implementation of fast low-rank QR approximation of the Biot-Savart law

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, D A; Fasenfest, B J; Stowell, M L

2005-11-07

In this paper we present a low-rank QR method for evaluating the discrete Biot-Savart law on parallel computers. It is assumed that the known current density and the unknown magnetic field are both expressed in a finite element expansion, and we wish to compute the degrees-of-freedom (DOF) in the basis function expansion of the magnetic field. The matrix that maps the current DOF to the field DOF is full, but if the spatial domain is properly partitioned the matrix can be written as a block matrix, with blocks representing distant interactions being low rank and having a compressed QR representation.more » The matrix partitioning is determined by the number of processors, the rank of each block (i.e. the compression) is determined by the specific geometry and is computed dynamically. In this paper we provide the algorithmic details and present computational results for large-scale computations.« less

Structural Analysis of PTM Hotspots (SAPH-ire) – A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families*

PubMed Central

Dewhurst, Henry M.; Choudhury, Shilpa; Torres, Matthew P.

2015-01-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)—a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits—conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit–N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. PMID:26070665

Robustness of weighted networks

NASA Astrophysics Data System (ADS)

Bellingeri, Michele; Cassi, Davide

2018-01-01

Complex network response to node loss is a central question in different fields of network science because node failure can cause the fragmentation of the network, thus compromising the system functioning. Previous studies considered binary networks where the intensity (weight) of the links is not accounted for, i.e. a link is either present or absent. However, in real-world networks the weights of connections, and thus their importance for network functioning, can be widely different. Here, we analyzed the response of real-world and model networks to node loss accounting for link intensity and the weighted structure of the network. We used both classic binary node properties and network functioning measure, introduced a weighted rank for node importance (node strength), and used a measure for network functioning that accounts for the weight of the links (weighted efficiency). We find that: (i) the efficiency of the attack strategies changed using binary or weighted network functioning measures, both for real-world or model networks; (ii) in some cases, removing nodes according to weighted rank produced the highest damage when functioning was measured by the weighted efficiency; (iii) adopting weighted measure for the network damage changed the efficacy of the attack strategy with respect the binary analyses. Our results show that if the weighted structure of complex networks is not taken into account, this may produce misleading models to forecast the system response to node failure, i.e. consider binary links may not unveil the real damage induced in the system. Last, once weighted measures are introduced, in order to discover the best attack strategy, it is important to analyze the network response to node loss using nodes rank accounting the intensity of the links to the node.

Fish cell lines as a tool for the ecotoxicity assessment and ranking of engineered nanomaterials.

PubMed

Bermejo-Nogales, A; Fernández-Cruz, M L; Navas, J M

2017-11-01

Risk assessment of engineered nanomaterials (ENMs) is being hindered by the sheer production volume of these materials. In this regard, the grouping and ranking of ENMs appears as a promising strategy. Here we sought to evaluate the usefulness of in vitro systems based on fish cell lines for ranking a set of ENMs on the basis of their cytotoxicity. We used the topminnow (Poeciliopsis lucida) liver cell line (PLHC-1) and the rainbow trout (Oncorhynchus mykiss) fibroblast-like gonadal cell line (RTG-2). ENMs were obtained from the EU Joint Research Centre repository. The size frequency distribution of ENM suspensions in cell culture media was characterized. Cytotoxicity was evaluated after 24 h of exposure. PLHC-1 cells exhibited higher sensitivity to the ENMs than RTG-2 cells. ZnO-NM was found to exert toxicity mainly by altering lysosome function and metabolic activity, while multi-walled carbon nanotubes (MWCNTs) caused plasma membrane disruption at high concentrations. The hazard ranking for toxicity (ZnO-NM > MWCNT ≥ CeO 2 -NM = SiO 2 -NM) was inversely related to the ranking in size detected in culture medium. Our findings reveal the suitability of fish cell lines for establishing hazard rankings of ENMs in the framework of integrated approaches to testing and assessment. Copyright © 2017 Elsevier Inc. All rights reserved.

Reduced-Rank Array Modes of the California Current Observing System

NASA Astrophysics Data System (ADS)

Moore, Andrew M.; Arango, Hernan G.; Edwards, Christopher A.

2018-01-01

The information content of the ocean observing array spanning the U.S. west coast is explored using the reduced-rank array modes (RAMs) derived from a four-dimensional variational (4D-Var) data assimilation system covering a period of three decades. RAMs are an extension of the original formulation of array modes introduced by Bennett (1985) but in the reduced model state-space explored by the 4D-Var system, and reveal the extent to which this space is activated by the observations. The projection of the RAMs onto the empirical orthogonal functions (EOFs) of the 4D-Var background error correlation matrix provides a quantitative measure of the effectiveness of the measurements in observing the circulation. It is found that much of the space spanned by the background error covariance is unconstrained by the present ocean observing system. The RAM spectrum is also used to introduce a new criterion to prevent 4D-Var from overfitting the model to the observations.

Protein model discrimination using mutational sensitivity derived from deep sequencing.

PubMed

Adkar, Bharat V; Tripathi, Arti; Sahoo, Anusmita; Bajaj, Kanika; Goswami, Devrishi; Chakrabarti, Purbani; Swarnkar, Mohit K; Gokhale, Rajesh S; Varadarajan, Raghavan

2012-02-08

A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of ∼1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (RankScore), which correlated with the residue depth, and identify active-site residues. Using these correlations, ∼98% of correct models of CcdB (RMSD ≤ 4Å) were identified from a large set of decoys. The model-discrimination methodology was further validated on eleven different monomeric proteins using simulated RankScore values. The methodology is also a rapid, accurate way to obtain relative activities of each mutant in a large pool and derive sequence-structure-function relationships without protein isolation or characterization. It can be applied to any system in which mutational effects can be monitored by a phenotypic readout. Copyright © 2012 Elsevier Ltd. All rights reserved.

Resting-state functional magnetic resonance imaging of the subthalamic microlesion and stimulation effects in Parkinson's disease: Indications of a principal role of the brainstem

PubMed Central

Holiga, Štefan; Mueller, Karsten; Möller, Harald E.; Urgošík, Dušan; Růžička, Evžen; Schroeter, Matthias L.; Jech, Robert

2015-01-01

During implantation of deep-brain stimulation (DBS) electrodes in the target structure, neurosurgeons and neurologists commonly observe a “microlesion effect” (MLE), which occurs well before initiating subthalamic DBS. This phenomenon typically leads to a transitory improvement of motor symptoms of patients suffering from Parkinson's disease (PD). Mechanisms behind MLE remain poorly understood. In this work, we exploited the notion of ranking to assess spontaneous brain activity in PD patients examined by resting-state functional magnetic resonance imaging in response to penetration of DBS electrodes in the subthalamic nucleus. In particular, we employed a hypothesis-free method, eigenvector centrality (EC), to reveal motor-communication-hubs of the highest rank and their reorganization following the surgery; providing a unique opportunity to evaluate the direct impact of disrupting the PD motor circuitry in vivo without prior assumptions. Penetration of electrodes was associated with increased EC of functional connectivity in the brainstem. Changes in connectivity were quantitatively related to motor improvement, which further emphasizes the clinical importance of the functional integrity of the brainstem. Surprisingly, MLE and DBS were associated with anatomically different EC maps despite their similar clinical benefit on motor functions. The DBS solely caused an increase in connectivity of the left premotor region suggesting separate pathophysiological mechanisms of both interventions. While the DBS acts at the cortical level suggesting compensatory activation of less affected motor regions, the MLE affects more fundamental circuitry as the dysfunctional brainstem predominates in the beginning of PD. These findings invigorate the overlooked brainstem perspective in the understanding of PD and support the current trend towards its early diagnosis. PMID:26509113

Multimodal biometric system using rank-level fusion approach.

PubMed

Monwar, Md Maruf; Gavrilova, Marina L

2009-08-01

In many real-world applications, unimodal biometric systems often face significant limitations due to sensitivity to noise, intraclass variability, data quality, nonuniversality, and other factors. Attempting to improve the performance of individual matchers in such situations may not prove to be highly effective. Multibiometric systems seek to alleviate some of these problems by providing multiple pieces of evidence of the same identity. These systems help achieve an increase in performance that may not be possible using a single-biometric indicator. This paper presents an effective fusion scheme that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing principal component analysis and Fisher's linear discriminant methods for individual matchers (face, ear, and signature) identity authentication and utilizing the novel rank-level fusion method in order to consolidate the results obtained from different biometric matchers. The ranks of individual matchers are combined using the highest rank, Borda count, and logistic regression approaches. The results indicate that fusion of individual modalities can improve the overall performance of the biometric system, even in the presence of low quality data. Insights on multibiometric design using rank-level fusion and its performance on a variety of biometric databases are discussed in the concluding section.

Temporal Restricted Visual Tracking Via Reverse-Low-Rank Sparse Learning.

PubMed

Yang, Yehui; Hu, Wenrui; Xie, Yuan; Zhang, Wensheng; Zhang, Tianzhu

2017-02-01

An effective representation model, which aims to mine the most meaningful information in the data, plays an important role in visual tracking. Some recent particle-filter-based trackers achieve promising results by introducing the low-rank assumption into the representation model. However, their assumed low-rank structure of candidates limits the robustness when facing severe challenges such as abrupt motion. To avoid the above limitation, we propose a temporal restricted reverse-low-rank learning algorithm for visual tracking with the following advantages: 1) the reverse-low-rank model jointly represents target and background templates via candidates, which exploits the low-rank structure among consecutive target observations and enforces the temporal consistency of target in a global level; 2) the appearance consistency may be broken when target suffers from sudden changes. To overcome this issue, we propose a local constraint via l 1,2 mixed-norm, which can not only ensures the local consistency of target appearance, but also tolerates the sudden changes between two adjacent frames; and 3) to alleviate the inference of unreasonable representation values due to outlier candidates, an adaptive weighted scheme is designed to improve the robustness of the tracker. By evaluating on 26 challenge video sequences, the experiments show the effectiveness and favorable performance of the proposed algorithm against 12 state-of-the-art visual trackers.

Anaerobic bioprocessing of low-rank coals. [Veillonella alcalescens and Propionibacterium acidipropionici

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, M.K.; Narayan, R.; Han, O.

1992-01-30

The overall goal of this project is to find biological methods to remove carboxylic functionalities from low-rank coals under ambient conditions and to assess the properties of these modified coals towards coal liquefaction. The main objectives of this quarter were: (1) continuation of microbial consortia development, (2) evaluation of the isolated organisms for decarboxylation, (3) selection of best performing culture (known cultures vs. new isolates), and (4) coal decarboxylation using activated carbon as blanks. The project began on September 12, 1990.

Survey of Quantification and Distance Functions Used for Internet-based Weak-link Sociological Phenomena

DTIC Science & Technology

2016-03-01

well as the Yahoo search engine and a classic SearchKing HIST algorithm. The co-PI immersed herself in the sociology literature for the relevant...Google matrix, PageRank as well as the Yahoo search engine and a classic SearchKing HIST algorithm. The co-PI immersed herself in the sociology...The PI studied all mathematical literature he can find related to the Google search engine, Google matrix, PageRank as well as the Yahoo search

Effects of Wenyangbushen formula on the expression of VEGF, OPG, RANK and RANKL in rabbits with steroid-induced femoral head avascular necrosis.

PubMed

Song, Hong-Mei; Wei, Ying-Chen; Li, Nan; Wu, Bin; Xie, Na; Zhang, Kun-Mu; Wang, Shi-Zhong; Wang, He-Ming

2015-12-01

The present study aimed to investigate the effects of Wenyangbushen formula on the mRNA and protein expression levels of vascular endothelial growth factor (VEGF), osteoprotegerin (OPG), receptor activator of nuclear factor (NF)‑κβ ligand (RANK), and RANK ligand (RANKL) in a rabbit model of steroid‑induced avascular necrosis of the femoral head (SANFH). The present study also aimed to examine the potential mechanism underlying the effect of this formula on the treatment of SANFH. A total of 136 New Zealand rabbits were randomly divided into five groups: Normal group, model group, and three groups treated with the traditional Chinese medicine (TCM), Wenyangbushen decoction, at a low, moderate and high dose, respectively. The normal group and positive control group were intragastrically administered with saline. The TCM groups were treated with Wenyangbushen decoction at the indicated dosage. Following treatment for 8 weeks, the mRNA and protein expression levels of VEGF, OPG, RANK and RANKL in the femoral head tissues were determined using reverse transcription‑quantitative polymerase chain reaction and western blot analyses, respectively. The data revealed that Wenyangbushen decoction effectively promoted the growth of bone cells, osteoblasts and chondrocytes, and prevented cell apoptosis in the SANFH. The mRNA and protein expression levels of OPG and VEGF were increased, while the levels of RANK and RANKL were reduced in the necrotic tissue of the model group, compared with those in the normal rabbits. Wenyangbushen treatment prevented these changes, manifested by an upregulation in the expression levels of VEGF and OPG, and downregulation in the expression levels of RANK and RANKL in a dose‑dependent manner. It was concluded that treatment with Wenyangbushen formula alleviated necrosis of the femoral head induced by steroids. It was observed to promote bone cell, osteoblast and chondrocyte growth, as well as prevent cell apoptosis. In addition, it upregulated the expression levels of OPG and VEGF, and inhibited the expression levels of RANK and RANKL. These results suggest the potential use of Wenyangbushen formula as a possible approach for the effective treatment of SANFH.

A Social Rank Explanation of How Money Influences Health

PubMed Central

2014-01-01

Objective: Financial resources are a potent determinant of health, yet it remains unclear why this is the case. We aimed to identify whether the frequently observed association between absolute levels of monetary resources and health may occur because money acts an indirect proxy for a person’s social rank. Method: To address this question we examined over 230,000 observations on 40,400 adults drawn from two representative national panel studies; the British Household Panel Survey and the English Longitudinal Study of Ageing. We identified each person’s absolute income/wealth and their objective ranked position of income/wealth within a social reference-group. Absolute and rank income/wealth variables were then used to predict a series of self-reported and objectively recorded health outcomes in cross-sectional and longitudinal analyses. Results: As anticipated, those with higher levels of absolute income/wealth were found to have better health than others, after adjustment for age, gender, education, marital status, and labor force status. When evaluated simultaneously the ranked position of income/wealth but not absolute income/wealth predicted all health outcomes examined including: objective measures of allostatic load and obesity, the presence of long-standing illness, and ratings of health, physical functioning, role limitations, and pain. The health benefits of high rank were consistent in cross-sectional and longitudinal analyses and did not depend on the reference-group used to rank participants. Conclusions: This is the first study to demonstrate that social position rather than material conditions may explain the impact of money on human health. PMID:25133843

Low rank approximation method for efficient Green's function calculation of dissipative quantum transport

NASA Astrophysics Data System (ADS)

Zeng, Lang; He, Yu; Povolotskyi, Michael; Liu, XiaoYan; Klimeck, Gerhard; Kubis, Tillmann

2013-06-01

In this work, the low rank approximation concept is extended to the non-equilibrium Green's function (NEGF) method to achieve a very efficient approximated algorithm for coherent and incoherent electron transport. This new method is applied to inelastic transport in various semiconductor nanodevices. Detailed benchmarks with exact NEGF solutions show (1) a very good agreement between approximated and exact NEGF results, (2) a significant reduction of the required memory, and (3) a large reduction of the computational time (a factor of speed up as high as 150 times is observed). A non-recursive solution of the inelastic NEGF transport equations of a 1000 nm long resistor on standard hardware illustrates nicely the capability of this new method.

Derivatives of random matrix characteristic polynomials with applications to elliptic curves

NASA Astrophysics Data System (ADS)

Snaith, N. C.

2005-12-01

The value distribution of derivatives of characteristic polynomials of matrices from SO(N) is calculated at the point 1, the symmetry point on the unit circle of the eigenvalues of these matrices. We consider subsets of matrices from SO(N) that are constrained to have at least n eigenvalues equal to 1 and investigate the first non-zero derivative of the characteristic polynomial at that point. The connection between the values of random matrix characteristic polynomials and values of L-functions in families has been well established. The motivation for this work is the expectation that through this connection with L-functions derived from families of elliptic curves, and using the Birch and Swinnerton-Dyer conjecture to relate values of the L-functions to the rank of elliptic curves, random matrix theory will be useful in probing important questions concerning these ranks.

The tensor hypercontracted parametric reduced density matrix algorithm: coupled-cluster accuracy with O(r(4)) scaling.

PubMed

Shenvi, Neil; van Aggelen, Helen; Yang, Yang; Yang, Weitao; Schwerdtfeger, Christine; Mazziotti, David

2013-08-07

Tensor hypercontraction is a method that allows the representation of a high-rank tensor as a product of lower-rank tensors. In this paper, we show how tensor hypercontraction can be applied to both the electron repulsion integral tensor and the two-particle excitation amplitudes used in the parametric 2-electron reduced density matrix (p2RDM) algorithm. Because only O(r) auxiliary functions are needed in both of these approximations, our overall algorithm can be shown to scale as O(r(4)), where r is the number of single-particle basis functions. We apply our algorithm to several small molecules, hydrogen chains, and alkanes to demonstrate its low formal scaling and practical utility. Provided we use enough auxiliary functions, we obtain accuracy similar to that of the standard p2RDM algorithm, somewhere between that of CCSD and CCSD(T).

Nerve Transfers for Improved Hand Function Following Cervical Spinal Cord Injury

DTIC Science & Technology

the cervical spine resulting in diminished or complete loss of arm and/or hand function. Cervical SCI patients consistently rank hand function as the...most desired function above bowel and bladder function, sexual function, standing, and pain control. The overall goal of the proposed study is to...evaluate the efficacy of nerve transfers to treat patients with cervical SCIs. Over the last decade, nerve transfers have been used with increasing

Social rank and social cooperation: Impact of social comparison processes on cooperative decision-making

PubMed Central

Sanfey, Alan G.

2017-01-01

Successful navigation of our complex social world requires the capability to recognize and judge the relative status of others. Hence, social comparison processes are of great importance in our interactions, informing us of our relative standing and in turn potentially motivating our behavior. However, so far few studies have examined in detail how social comparison can influence interpersonal decision-making. One aspect of social decision-making that is of particular importance is cooperative behavior, and identifying means of maintaining and promoting cooperation in the provision of public goods is of vital interest to society. Here, we manipulated social comparison by grading performance rankings on a reaction time task, and then measured cooperative decisions via a modified Public Goods Game (PGG). Findings revealed that individuals ranked highest tended to be more cooperative as compared to those who placed in the bottom rank. Interestingly, this effect was regardless of whether the comparison group members were the subsequent players in the PGG or not, and this effect was stronger in those with higher social orientation. In summary, the present research shows how different social comparison processes (assessed via social rankings) can operate in our daily interaction with others, demonstrating an important effect on cooperative behavior. PMID:28388684

Complex sources of variance in female dominance rank in a nepotistic society

PubMed Central

Lea, Amanda J.; Learn, Niki H.; Theus, Marcus J.; Altmann, Jeanne; Alberts, Susan C.

2016-01-01

Many mammalian societies are structured by dominance hierarchies, and an individual’s position within this hierarchy can influence reproduction, behaviour, physiology and health. In nepotistic hierarchies, which are common in cercopithecine primates and also seen in spotted hyaenas, Crocuta crocuta, adult daughters are expected to rank immediately below their mother, and in reverse age order (a phenomenon known as ‘youngest ascendancy’). This pattern is well described, but few studies have systematically examined the frequency or causes of departures from the expected pattern. Using a longitudinal data set from a natural population of yellow baboons, Papio cynocephalus, we measured the influence of maternal kin, paternal kin and group size on female rank positions at two life history milestones, menarche and first live birth. At menarche, most females (73%) ranked adjacent to their family members (i.e. the female held an ordinal rank in consecutive order with other members of her maternal family); however, only 33% of females showed youngest ascendancy within their matriline at menarche. By the time they experienced their first live birth, many females had improved their dominance rank: 78% ranked adjacent to their family members and 49% showed youngest ascendancy within their matriline. The presence of mothers and maternal sisters exerted a powerful influence on rank outcomes. However, the presence of fathers, brothers and paternal siblings did not produce a clear effect on female dominance rank in our analyses, perhaps because females in our data set co-resided with variable numbers and types of paternal and male relatives. Our results also raise the possibility that female body size or competitive ability may influence dominance rank, even in this classically nepotistic species. In total, our analyses reveal that the predictors of dominance rank in nepotistic rank systems are much more complex than previously thought. PMID:26997663

Deep Multimodal Distance Metric Learning Using Click Constraints for Image Ranking.

PubMed

Yu, Jun; Yang, Xiaokang; Gao, Fei; Tao, Dacheng

2017-12-01

How do we retrieve images accurately? Also, how do we rank a group of images precisely and efficiently for specific queries? These problems are critical for researchers and engineers to generate a novel image searching engine. First, it is important to obtain an appropriate description that effectively represent the images. In this paper, multimodal features are considered for describing images. The images unique properties are reflected by visual features, which are correlated to each other. However, semantic gaps always exist between images visual features and semantics. Therefore, we utilize click feature to reduce the semantic gap. The second key issue is learning an appropriate distance metric to combine these multimodal features. This paper develops a novel deep multimodal distance metric learning (Deep-MDML) method. A structured ranking model is adopted to utilize both visual and click features in distance metric learning (DML). Specifically, images and their related ranking results are first collected to form the training set. Multimodal features, including click and visual features, are collected with these images. Next, a group of autoencoders is applied to obtain initially a distance metric in different visual spaces, and an MDML method is used to assign optimal weights for different modalities. Next, we conduct alternating optimization to train the ranking model, which is used for the ranking of new queries with click features. Compared with existing image ranking methods, the proposed method adopts a new ranking model to use multimodal features, including click features and visual features in DML. We operated experiments to analyze the proposed Deep-MDML in two benchmark data sets, and the results validate the effects of the method.

Unified method of knowledge representation in the evolutionary artificial intelligence systems

NASA Astrophysics Data System (ADS)

Bykov, Nickolay M.; Bykova, Katherina N.

2003-03-01

The evolution of artificial intelligence systems called by complicating of their operation topics and science perfecting has resulted in a diversification of the methods both the algorithms of knowledge representation and usage in these systems. Often by this reason it is very difficult to design the effective methods of knowledge discovering and operation for such systems. In the given activity the authors offer a method of unitized representation of the systems knowledge about objects of an external world by rank transformation of their descriptions, made in the different features spaces: deterministic, probabilistic, fuzzy and other. The proof of a sufficiency of the information about the rank configuration of the object states in the features space for decision making is presented. It is shown that the geometrical and combinatorial model of the rank configurations set introduce their by group of some system of incidence, that allows to store the information on them in a convolute kind. The method of the rank configuration description by the DRP - code (distance rank preserving code) is offered. The problems of its completeness, information capacity, noise immunity and privacy are reviewed. It is shown, that the capacity of a transmission channel for such submission of the information is more than unit, as the code words contain the information both about the object states, and about the distance ranks between them. The effective algorithm of the data clustering for the object states identification, founded on the given code usage, is described. The knowledge representation with the help of the rank configurations allows to unitize and to simplify algorithms of the decision making by fulfillment of logic operations above the DRP - code words. Examples of the proposed clustering techniques operation on the given samples set, the rank configuration of resulted clusters and its DRP-codes are presented.

Factors affecting match performance in professional Australian football.

PubMed

Sullivan, Courtney; Bilsborough, Johann C; Cianciosi, Michael; Hocking, Joel; Cordy, Justin T; Coutts, Aaron J

2014-05-01

To determine the physical activity measures and skill-performance characteristics that contribute to coaches' perception of performance and player performance rank in professional Australian Football (AF). Prospective, longitudinal. Physical activity profiles were assessed via microtechnology (GPS and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill-performance measure and player-rank scores (Champion Data Rank) were provided by a commercial statistical provider. The physical-performance variables, skill involvements, and individual player performance scores were expressed relative to playing time for each quarter. A stepwise multiple regression was used to examine the contribution of physical activity and skill involvements to coaches' perception of performance and player rank in AF. Stepwise multiple-regression analysis revealed that 42.2% of the variance in coaches' perception of a player's performance could be explained by the skill-performance characteristics (player rank/min, effective kicks/min, pressure points/min, handballs/min, and running bounces/ min), with a small contribution from physical activity measures (accelerations/min) (adjusted R2 = .422, F6,282 = 36.054, P < .001). Multiple regression also revealed that 66.4% of the adjusted variance in player rank could be explained by total disposals/min, effective kicks/min, pressure points/min, kick clangers/min, marks/min, speed (m/min), and peak speed (adjusted R2 = .664, F7,281 = 82.289, P < .001). Increased physical activity throughout a match (speed [m/min] β - 0.097 and peak speed β - 0.116) negatively affects player rank in AF. Skill performance rather than increased physical activity is more important to coaches' perception of performance and player rank in professional AF.

'Theory of Mind', psychotic-like experiences and psychometric schizotypy in adolescents from the general population.

PubMed

Barragan, Marcela; Laurens, Kristin R; Navarro, José Blas; Obiols, Jordi E

2011-04-30

This study examined 'Theory of Mind' (ToM) functioning, its association with psychometric schizotypy and with self-reported psychotic-like experiences (PLEs) and depressive symptoms, in a community sample of adolescents. Seventy-two adolescents (mean age 14.51years) from Barcelona, Spain, completed questionnaires assessing PLEs, depressive symptoms, and schizotypy. A verbal ToM task and a vocabulary test were administered. The effect of symptomatology, vocabulary ability, age, and gender on task performance was explored. Neither total score on schizotypy nor PLEs were associated with ToM performance. A significant effect of vocabulary on adolescent's performance of both ToM and control stories was found. ToM showed significant negative associations with positive schizotypy, and with one cluster of positive PLEs: first-rank experiences. Positive significant associations between ToM and persecutory delusions and the impulsive aspects of schizotypy were found. Depressive symptoms did not affect ToM performance. Positive schizotypal traits and first-rank symptoms are associated with ToM deficits in adolescents. Results support the trait-(versus state-) dependent notion of ToM impairments in schizophrenia. ToM may be a developmental impairment associated with positive schizotypy and PLEs. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Fast dimension reduction and integrative clustering of multi-omics data using low-rank approximation: application to cancer molecular classification.

PubMed

Wu, Dingming; Wang, Dongfang; Zhang, Michael Q; Gu, Jin

2015-12-01

One major goal of large-scale cancer omics study is to identify molecular subtypes for more accurate cancer diagnoses and treatments. To deal with high-dimensional cancer multi-omics data, a promising strategy is to find an effective low-dimensional subspace of the original data and then cluster cancer samples in the reduced subspace. However, due to data-type diversity and big data volume, few methods can integrative and efficiently find the principal low-dimensional manifold of the high-dimensional cancer multi-omics data. In this study, we proposed a novel low-rank approximation based integrative probabilistic model to fast find the shared principal subspace across multiple data types: the convexity of the low-rank regularized likelihood function of the probabilistic model ensures efficient and stable model fitting. Candidate molecular subtypes can be identified by unsupervised clustering hundreds of cancer samples in the reduced low-dimensional subspace. On testing datasets, our method LRAcluster (low-rank approximation based multi-omics data clustering) runs much faster with better clustering performances than the existing method. Then, we applied LRAcluster on large-scale cancer multi-omics data from TCGA. The pan-cancer analysis results show that the cancers of different tissue origins are generally grouped as independent clusters, except squamous-like carcinomas. While the single cancer type analysis suggests that the omics data have different subtyping abilities for different cancer types. LRAcluster is a very useful method for fast dimension reduction and unsupervised clustering of large-scale multi-omics data. LRAcluster is implemented in R and freely available via http://bioinfo.au.tsinghua.edu.cn/software/lracluster/ .

Strategy Precedes Operational Effectiveness: Aligning High Graduation Rankings with Competitive Graduation Grade Point Averages

ERIC Educational Resources Information Center

Apprey, Maurice; Bassett, Kimberley C.; Preston-Grimes, Patrice; Lewis, Dion W.; Wood, Beverly

2014-01-01

Two pivotal and interconnected claims are addressed in this article. First, strategy precedes program effectiveness. Second, graduation rates and rankings are insufficient in any account of academic progress for African American students. In this article, graduation is regarded as the floor and not the ceiling, as it were. The ideal situation in…

Research priorities of the Canadian chiropractic profession: a consensus study using a modified Delphi technique.

PubMed

French, Simon D; Beliveau, Peter J H; Bruno, Paul; Passmore, Steven R; Hayden, Jill A; Srbely, John; Kawchuk, Greg N

2017-01-01

Research funds are limited and a healthcare profession that supports research activity should establish research priority areas. The study objective was to identify research priority areas for the Canadian chiropractic profession, and for stakeholders in the chiropractic profession to rank these in order of importance. We conducted a modified Delphi consensus study between August 2015 and May 2017 to determine the views of Canadian chiropractic organisations (e.g. Canadian Chiropractic Association; provincial associations) and stakeholder groups (e.g. chiropractic educational institutions; researchers). Participants completed three online Delphi survey rounds. In Round 1, participants suggested research areas within four broad research themes: 1) Basic science; 2) Clinical; 3) Health services; and 4) Population health. In Round 2, researchers created sub-themes by categorising the areas suggested in Round 1, and participants judged the importance of the research sub-themes. We defined consensus as at least 70% of participants agreeing that a research area was "essential" or "very important". In Round 3, results from Round 2 were presented to the participants to re-evaluate the importance of sub-themes. Finally, participants completed an online pairwise ranking activity to determine the rank order of the list of important research sub-themes. Fifty-seven participants, of 85 people invited, completed Round 1 (response rate 67%). Fifty-six participants completed Round 2, 55 completed Round 3, and 53 completed the ranking activity. After three Delphi rounds and the pairwise ranking activity was completed, the ranked list of research sub-themes considered important were: 1) Integration of chiropractic care into multidisciplinary settings; 2) Costs and cost-effectiveness of chiropractic care; 3) Effect of chiropractic care on reducing medical services; 4) Effects of chiropractic care; 5) Safety/side effects of chiropractic care; 6) Chiropractic care for older adults; 7) Neurophysiological mechanisms and effects of spinal manipulative therapy; 8) General mechanisms and effects of spinal manipulative therapy. This project identified research priority areas for the Canadian chiropractic profession. The top three priority areas were all in the area of health services research: 1) Integration of chiropractic care into multidisciplinary settings; 2) Costs and cost-effectiveness of chiropractic care; 3) Effect of chiropractic care on reducing medical services.

Hydrophobic potential of mean force as a solvation function for protein structure prediction.

PubMed

Lin, Matthew S; Fawzi, Nicolas Lux; Head-Gordon, Teresa

2007-06-01

We have developed a solvation function that combines a Generalized Born model for polarization of protein charge by the high dielectric solvent, with a hydrophobic potential of mean force (HPMF) as a model for hydrophobic interaction, to aid in the discrimination of native structures from other misfolded states in protein structure prediction. We find that our energy function outperforms other reported scoring functions in terms of correct native ranking for 91% of proteins and low Z scores for a variety of decoy sets, including the challenging Rosetta decoys. This work shows that the stabilizing effect of hydrophobic exposure to aqueous solvent that defines the HPMF hydration physics is an apparent improvement over solvent-accessible surface area models that penalize hydrophobic exposure. Decoys generated by thermal sampling around the native-state basin reveal a potentially important role for side-chain entropy in the future development of even more accurate free energy surfaces.

Solving a class of generalized fractional programming problems using the feasibility of linear programs.

PubMed

Shen, Peiping; Zhang, Tongli; Wang, Chunfeng

2017-01-01

This article presents a new approximation algorithm for globally solving a class of generalized fractional programming problems (P) whose objective functions are defined as an appropriate composition of ratios of affine functions. To solve this problem, the algorithm solves an equivalent optimization problem (Q) via an exploration of a suitably defined nonuniform grid. The main work of the algorithm involves checking the feasibility of linear programs associated with the interesting grid points. It is proved that the proposed algorithm is a fully polynomial time approximation scheme as the ratio terms are fixed in the objective function to problem (P), based on the computational complexity result. In contrast to existing results in literature, the algorithm does not require the assumptions on quasi-concavity or low-rank of the objective function to problem (P). Numerical results are given to illustrate the feasibility and effectiveness of the proposed algorithm.

Objective evaluation of insert material for diabetic and athletic footwear.

PubMed

Brodsky, J W; Kourosh, S; Stills, M; Mooney, V

1988-12-01

Five of the most commonly used materials for shoe inserts (soft Plastazote, medium Pelite, PPT, Spenco, and Sorbothane) were objectively evaluated in the laboratory to characterize their behavior in the following three specific functions that correspond to clinical use: (1) the effect on the materials of repeated compression. (2) the effect of a combination of repetitive shear and compression. (3) the force-distribution (force-attenuation) properties of these materials, both when new and after repeated compression. The last function represents a model for relief of pressure beneath plantar bony prominences, a topic of special concern for the insensitive foot. All materials were effective in reducing transmitted force over the simulated bony prominence with a rank order of effectiveness. Other factors considered were: amount and rate of permanent deformation offset by considerations of enhanced moldability when comparing the neoprene and urethane materials with the polyethylene foams. The ideal insert represents a combination of material to achieve both durability and moldability.

Low-rank coal oil agglomeration

DOEpatents

Knudson, Curtis L.; Timpe, Ronald C.

1991-01-01

A low-rank coal oil agglomeration process. High mineral content, a high ash content subbituminous coals are effectively agglomerated with a bridging oil which is partially water soluble and capable of entering the pore structure, and usually coal derived.

Characterization of neurophysiologic and neurocognitive biomarkers for use in genomic and clinical outcome studies of schizophrenia.

PubMed

Light, Gregory A; Swerdlow, Neal R; Rissling, Anthony J; Radant, Allen; Sugar, Catherine A; Sprock, Joyce; Pela, Marlena; Geyer, Mark A; Braff, David L

2012-01-01

Endophenotypes are quantitative, laboratory-based measures representing intermediate links in the pathways between genetic variation and the clinical expression of a disorder. Ideal endophenotypes exhibit deficits in patients, are stable over time and across shifts in psychopathology, and are suitable for repeat testing. Unfortunately, many leading candidate endophenotypes in schizophrenia have not been fully characterized simultaneously in large cohorts of patients and controls across these properties. The objectives of this study were to characterize the extent to which widely-used neurophysiological and neurocognitive endophenotypes are: 1) associated with schizophrenia, 2) stable over time, independent of state-related changes, and 3) free of potential practice/maturation or differential attrition effects in schizophrenia patients (SZ) and nonpsychiatric comparison subjects (NCS). Stability of clinical and functional measures was also assessed. Participants (SZ n = 341; NCS n = 205) completed a battery of neurophysiological (MMN, P3a, P50 and N100 indices, PPI, startle habituation, antisaccade), neurocognitive (WRAT-3 Reading, LNS-forward, LNS-reorder, WCST-64, CVLT-II). In addition, patients were rated on clinical symptom severity as well as functional capacity and status measures (GAF, UPSA, SOF). 223 subjects (SZ n = 163; NCS n = 58) returned for retesting after 1 year. Most neurophysiological and neurocognitive measures exhibited medium-to-large deficits in schizophrenia, moderate-to-substantial stability across the retest interval, and were independent of fluctuations in clinical status. Clinical symptoms and functional measures also exhibited substantial stability. A Longitudinal Endophenotype Ranking System (LERS) was created to rank neurophysiological and neurocognitive biomarkers according to their effect sizes across endophenotype criteria. The majority of neurophysiological and neurocognitive measures exhibited deficits in patients, stability over a 1-year interval and did not demonstrate practice or time effects supporting their use as endophenotypes in neural substrate and genomic studies. These measures hold promise for informing the "gene-to-phene gap" in schizophrenia research.

Characterization of Neurophysiologic and Neurocognitive Biomarkers for Use in Genomic and Clinical Outcome Studies of Schizophrenia

PubMed Central

Light, Gregory A.; Swerdlow, Neal R.; Rissling, Anthony J.; Radant, Allen; Sugar, Catherine A.; Sprock, Joyce; Pela, Marlena; Geyer, Mark A.; Braff, David L.

2012-01-01

Background Endophenotypes are quantitative, laboratory-based measures representing intermediate links in the pathways between genetic variation and the clinical expression of a disorder. Ideal endophenotypes exhibit deficits in patients, are stable over time and across shifts in psychopathology, and are suitable for repeat testing. Unfortunately, many leading candidate endophenotypes in schizophrenia have not been fully characterized simultaneously in large cohorts of patients and controls across these properties. The objectives of this study were to characterize the extent to which widely-used neurophysiological and neurocognitive endophenotypes are: 1) associated with schizophrenia, 2) stable over time, independent of state-related changes, and 3) free of potential practice/maturation or differential attrition effects in schizophrenia patients (SZ) and nonpsychiatric comparison subjects (NCS). Stability of clinical and functional measures was also assessed. Methods Participants (SZ n = 341; NCS n = 205) completed a battery of neurophysiological (MMN, P3a, P50 and N100 indices, PPI, startle habituation, antisaccade), neurocognitive (WRAT-3 Reading, LNS-forward, LNS-reorder, WCST-64, CVLT-II). In addition, patients were rated on clinical symptom severity as well as functional capacity and status measures (GAF, UPSA, SOF). 223 subjects (SZ n = 163; NCS n = 58) returned for retesting after 1 year. Results Most neurophysiological and neurocognitive measures exhibited medium-to-large deficits in schizophrenia, moderate-to-substantial stability across the retest interval, and were independent of fluctuations in clinical status. Clinical symptoms and functional measures also exhibited substantial stability. A Longitudinal Endophenotype Ranking System (LERS) was created to rank neurophysiological and neurocognitive biomarkers according to their effect sizes across endophenotype criteria. Conclusions The majority of neurophysiological and neurocognitive measures exhibited deficits in patients, stability over a 1-year interval and did not demonstrate practice or time effects supporting their use as endophenotypes in neural substrate and genomic studies. These measures hold promise for informing the “gene-to-phene gap” in schizophrenia research. PMID:22802938

Evaluating nodes importance in complex network based on PageRank algorithm

NASA Astrophysics Data System (ADS)

Li, Kai; He, Yongfeng

2018-04-01

To evaluate the important nodes in the complex network, and aim at the problems existing in the traditional PageRank algorithm, we propose a modified PageRank algorithm. The algorithm has convergence for the evaluation of the importance of the suspended nodes and the nodes with a directed loop network. The simulation example shows the effectiveness of the modified algorithm for the evaluation of the complexity of the complex network nodes.

Regulation of coal polymer degradation by fungi. Eighth quarterly report, [April--June 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

Irvine, R.L.; Bumpus, J.A.

1996-07-28

This project addresses the solubilization of low-rank coal (leonardite) by lignin degrading fungi. During this reporting period efforts were focused on determining the effect of pH on coal solubilization by oxalate ion and other biologically important compounds that might function as metal chelators, on the role of laccase in coal solubilization and metabolism, on decolorization of soluble coal macromolecule by Phanerochaete chrysosporium and T. versicolor in solid agar media, and on solubilization of coal in slurry cultures and solid phase reactors.

Rational GARCH model: An empirical test for stock returns

NASA Astrophysics Data System (ADS)

Takaishi, Tetsuya

2017-05-01

We propose a new ARCH-type model that uses a rational function to capture the asymmetric response of volatility to returns, known as the "leverage effect". Using 10 individual stocks on the Tokyo Stock Exchange and two stock indices, we compare the new model with several other asymmetric ARCH-type models. We find that according to the deviance information criterion, the new model ranks first for several stocks. Results show that the proposed new model can be used as an alternative asymmetric ARCH-type model in empirical applications.

Behavioral and neurobiological characteristics influencing social hierarchy formation in female cynomolgus monkeys.

PubMed

Riddick, N V; Czoty, P W; Gage, H D; Kaplan, J R; Nader, S H; Icenhower, M; Pierre, P J; Bennett, A; Garg, P K; Garg, S; Nader, M A

2009-02-18

Socially housed monkeys have been used as a model to study human diseases. The present study examined behavioral, physiological and neurochemical measures as predictors of social rank in 16 experimentally naïve, individually housed female cynomolgus monkeys (Macaca fascicularis). The two behavioral measures examined were novel object reactivity (NOR), as determined by latency to touch an opaque acrylic box placed in the home cage, and locomotor activity assessed in a novel open-field apparatus. Serum cortisol concentrations were evaluated three times per week for four consecutive weeks, and stress reactivity was assessed on one occasion by evaluating the cortisol response to adrenocorticotropic hormone (ACTH) following dexamethasone suppression. Measures of serotonin (5-HT) function included whole blood 5-HT (WBS) concentrations, cerebrospinal fluid (CSF) concentrations of the 5-HT metabolite 5-hydroxyindoleacetic acid (5-HIAA) and brain 5-HT transporter (SERT) availability obtained using positron emission tomography (PET). After baseline measures were obtained, monkeys were assigned to four social groups of four monkeys per group. The two measures that correlated with eventual social rank were CSF 5-HIAA concentrations, which were significantly higher in the animals who eventually became subordinate, and latency to touch the novel object, which was significantly lower in eventual subordinate monkeys. Measures of 5-HT function did not change as a consequence of social rank. These data suggest that levels of central 5-HIAA and measures of novel object reactivity may be trait markers that influence eventual social rank in female macaques.

Strategic 3-hydroxy-2-butanone release in the dominant male lobster cockroach, Nauphoeta cinerea

NASA Astrophysics Data System (ADS)

Chen, Shu-Chun; Yang, Rou-Ling; Ho, Hsiao-Yung; Chou, Szu-Ying; Kou, Rong

2007-11-01

In the lobster cockroach Nauphoete cinerea, the dominant subordinate hierarchy formed via the agonistic interactions is unstable, and changes in rank order are common. Our previous results showed that in the first encounter fight during initial rank formation, microgram levels of 3H-2B are released by the aggressive posture (AP)-adopting dominant male. In the present study, the pattern of daily pheromone (3H-2B) release during the domination period and on the day of rank switch, rank duration, and rank switch frequency were investigated in three-male groups and six-male groups to examine the effect of higher frequency of agonistic encounters. The results showed that, in the three-male groups (50-day observation period), daily 3H-2B release rate was not constant, but fluctuated, the average duration of dominant rank was 16.6 ± 2.0 days, rank switch occurred in 58.8% of groups, and the frequency of rank switching (average number of rank switches/group/50 days) was 1.4 ± 0.2. For the six-male groups (30-day observation period), the daily 3H-2B release rate also fluctuated, but the duration of dominant rank was significantly shorter at 4.2 ± 0.6 days, rank switch occurred in 100% of groups, and the frequency of rank switching (average number of rank switches/group/30 days) was significantly higher at 6.9 ± 0.6. The results for both sets of male groups showed that as a new rank formed (either on the first encounter day or on the day of rank switching), the dominant status was significantly associated with a higher 3H-2B release rate. In the animal kingdom, fighting usually involves communication or the exchange of signals, and the results of this study indicated that the fluctuating daily 3H-2B release rate adopted by the dominants is a kind of strategic release and the 3H-2B release rate is a signal used to determine dominance.

Low-rank coal oil agglomeration

DOEpatents

Knudson, C.L.; Timpe, R.C.

1991-07-16

A low-rank coal oil agglomeration process is described. High mineral content, a high ash content subbituminous coals are effectively agglomerated with a bridging oil which is partially water soluble and capable of entering the pore structure, and is usually coal-derived.

Exploring Empirical Rank-Frequency Distributions Longitudinally through a Simple Stochastic Process

PubMed Central

Finley, Benjamin J.; Kilkki, Kalevi

2014-01-01

The frequent appearance of empirical rank-frequency laws, such as Zipf’s law, in a wide range of domains reinforces the importance of understanding and modeling these laws and rank-frequency distributions in general. In this spirit, we utilize a simple stochastic cascade process to simulate several empirical rank-frequency distributions longitudinally. We focus especially on limiting the process’s complexity to increase accessibility for non-experts in mathematics. The process provides a good fit for many empirical distributions because the stochastic multiplicative nature of the process leads to an often observed concave rank-frequency distribution (on a log-log scale) and the finiteness of the cascade replicates real-world finite size effects. Furthermore, we show that repeated trials of the process can roughly simulate the longitudinal variation of empirical ranks. However, we find that the empirical variation is often less that the average simulated process variation, likely due to longitudinal dependencies in the empirical datasets. Finally, we discuss the process limitations and practical applications. PMID:24755621

The effect of uncertainties in distance-based ranking methods for multi-criteria decision making

NASA Astrophysics Data System (ADS)

Jaini, Nor I.; Utyuzhnikov, Sergei V.

2017-08-01

Data in the multi-criteria decision making are often imprecise and changeable. Therefore, it is important to carry out sensitivity analysis test for the multi-criteria decision making problem. The paper aims to present a sensitivity analysis for some ranking techniques based on the distance measures in multi-criteria decision making. Two types of uncertainties are considered for the sensitivity analysis test. The first uncertainty is related to the input data, while the second uncertainty is towards the Decision Maker preferences (weights). The ranking techniques considered in this study are TOPSIS, the relative distance and trade-off ranking methods. TOPSIS and the relative distance method measure a distance from an alternative to the ideal and antiideal solutions. In turn, the trade-off ranking calculates a distance of an alternative to the extreme solutions and other alternatives. Several test cases are considered to study the performance of each ranking technique in both types of uncertainties.

The origins of deference: when do people prefer lower status?

PubMed

Anderson, Cameron; Willer, Robb; Kilduff, Gavin J; Brown, Courtney E

2012-05-01

Although the desire for high status is considered universal, prior research suggests individuals often opt for lower status positions. Why would anyone favor a position of apparent disadvantage? In 5 studies, we found that the broad construct of status striving can be broken up into two conceptions: one based on rank, the other on respect. While individuals might universally desire high levels of respect, we find that they vary widely in the extent to which they strive for high-status rank, with many individuals opting for middle- or low-status rank. The status rank that individuals preferred depended on their self-perceived value to the group: when they believed they provided less value, they preferred lower status rank. Mediation and moderation analyses suggest that beliefs about others' expectations were the primary driver of these effects. Individuals who believed they provided little value to their group inferred that others expected them to occupy a lower status position. Individuals in turn conformed to these perceived expectations, accepting lower status rank in such settings.

Exploring empirical rank-frequency distributions longitudinally through a simple stochastic process.

PubMed

Finley, Benjamin J; Kilkki, Kalevi

2014-01-01

The frequent appearance of empirical rank-frequency laws, such as Zipf's law, in a wide range of domains reinforces the importance of understanding and modeling these laws and rank-frequency distributions in general. In this spirit, we utilize a simple stochastic cascade process to simulate several empirical rank-frequency distributions longitudinally. We focus especially on limiting the process's complexity to increase accessibility for non-experts in mathematics. The process provides a good fit for many empirical distributions because the stochastic multiplicative nature of the process leads to an often observed concave rank-frequency distribution (on a log-log scale) and the finiteness of the cascade replicates real-world finite size effects. Furthermore, we show that repeated trials of the process can roughly simulate the longitudinal variation of empirical ranks. However, we find that the empirical variation is often less that the average simulated process variation, likely due to longitudinal dependencies in the empirical datasets. Finally, we discuss the process limitations and practical applications.

Singular perturbations with boundary conditions and the Casimir effect in the half space

NASA Astrophysics Data System (ADS)

Albeverio, S.; Cognola, G.; Spreafico, M.; Zerbini, S.

2010-06-01

We study the self-adjoint extensions of a class of nonmaximal multiplication operators with boundary conditions. We show that these extensions correspond to singular rank 1 perturbations (in the sense of Albeverio and Kurasov [Singular Perturbations of Differential Operaters (Cambridge University Press, Cambridge, 2000)]) of the Laplace operator, namely, the formal Laplacian with a singular delta potential, on the half space. This construction is the appropriate setting to describe the Casimir effect related to a massless scalar field in the flat space-time with an infinite conducting plate and in the presence of a pointlike "impurity." We use the relative zeta determinant (as defined in the works of Müller ["Relative zeta functions, relative determinants and scattering theory," Commun. Math. Phys. 192, 309 (1998)] and Spreafico and Zerbini ["Finite temperature quantum field theory on noncompact domains and application to delta interactions," Rep. Math. Phys. 63, 163 (2009)]) in order to regularize the partition function of this model. We study the analytic extension of the associated relative zeta function, and we present explicit results for the partition function and for the Casimir force.

Understanding perceived availability and importance of tobacco control interventions to inform European adoption of a UK economic model: a cross-sectional study.

PubMed

Kulchaitanaroaj, Puttarin; Kaló, Zoltán; West, Robert; Cheung, Kei Long; Evers, Silvia; Vokó, Zoltán; Hiligsmann, Mickael; de Vries, Hein; Owen, Lesley; Trapero-Bertran, Marta; Leidl, Reiner; Pokhrel, Subhash

2018-02-14

The evidence on the extent to which stakeholders in different European countries agree with availability and importance of tobacco-control interventions is limited. This study assessed and compared stakeholders' views from five European countries and compared the perceived ranking of interventions with evidence-based ranking using cost-effectiveness data. An interview survey (face-to-face, by phone or Skype) was conducted between April and July 2014 with five categories of stakeholders - decision makers, service purchasers, service providers, evidence generators and health promotion advocates - from Germany, Hungary, the Netherlands, Spain, and the United Kingdom. A list of potential stakeholders drawn from the research team's contacts and snowballing served as the sampling frame. An email invitation was sent to all stakeholders in this list and recruitment was based on positive replies. Respondents were asked to rate availability and importance of 30 tobacco control interventions. Kappa coefficients assessed agreement of stakeholders' views. A mean importance score for each intervention was used to rank the interventions. This ranking was compared with the ranking based on cost-effectiveness data from a published review. Ninety-three stakeholders (55.7% response rate) completed the survey: 18.3% were from Germany, 17.2% from Hungary, 30.1% from the Netherlands, 19.4% from Spain, and 15.1% from the UK. Of those, 31.2% were decision makers, 26.9% evidence generators, 19.4% service providers, 15.1% health-promotion advocates, and 7.5% purchasers of services/pharmaceutical products. Smoking restrictions in public areas were rated as the most important intervention (mean score = 1.89). The agreement on availability of interventions between the stakeholders was very low (kappa = 0.098; 95% CI = [0.085, 0.111] but the agreement on the importance of the interventions was fair (kappa = 0.239; 95% CI = [0.208, 0.253]). A correlation was found between availability and importance rankings for stage-based interventions. The importance ranking was not statistically concordant with the ranking based on published cost-effectiveness data (Kendall rank correlation coefficient = 0.40; p-value = 0.11; 95% CI = [- 0.09, 0.89]). The intrinsic differences in stakeholder views must be addressed while transferring economic evidence Europe-wide. Strong engagement with stakeholders, focussing on better communication, has a potential to mitigate this challenge.

Task-specific ankle robotics gait training after stroke: a randomized pilot study.

PubMed

Forrester, Larry W; Roy, Anindo; Hafer-Macko, Charlene; Krebs, Hermano I; Macko, Richard F

2016-06-02

An unsettled question in the use of robotics for post-stroke gait rehabilitation is whether task-specific locomotor training is more effective than targeting individual joint impairments to improve walking function. The paretic ankle is implicated in gait instability and fall risk, but is difficult to therapeutically isolate and refractory to recovery. We hypothesize that in chronic stroke, treadmill-integrated ankle robotics training is more effective to improve gait function than robotics focused on paretic ankle impairments. Participants with chronic hemiparetic gait were randomized to either six weeks of treadmill-integrated ankle robotics (n = 14) or dose-matched seated ankle robotics (n = 12) videogame training. Selected gait measures were collected at baseline, post-training, and six-week retention. Friedman, and Wilcoxon Sign Rank and Fisher's exact tests evaluated within and between group differences across time, respectively. Six weeks post-training, treadmill robotics proved more effective than seated robotics to increase walking velocity, paretic single support, paretic push-off impulse, and active dorsiflexion range of motion. Treadmill robotics durably improved gait dorsiflexion swing angle leading 6/7 initially requiring ankle braces to self-discarded them, while their unassisted paretic heel-first contacts increased from 44 % to 99.6 %, versus no change in assistive device usage (0/9) following seated robotics. Treadmill-integrated, but not seated ankle robotics training, durably improves gait biomechanics, reversing foot drop, restoring walking propulsion, and establishing safer foot landing in chronic stroke that may reduce reliance on assistive devices. These findings support a task-specific approach integrating adaptive ankle robotics with locomotor training to optimize mobility recovery. NCT01337960. https://clinicaltrials.gov/ct2/show/NCT01337960?term=NCT01337960&rank=1.

Any sleep is a dream far away: a nominal group study assessing how gout affects sleep.

PubMed

Singh, Jasvinder A

2018-02-23

There are no qualitative studies of sleep in gout; the aim of this study was to examine the impact of gout on sleep. Nine nominal groups were conducted, oversampling for African-Americans and women with gout. Patients discussed and rank-ordered their concerns. Nine nominal groups with 46 gout patients were conducted with mean age, 61 years (s.d. 10.6) and gout duration, 14.9 years (s.d. 12); 63% were men, 46% African-American, 52% married, 46% retired and 63% were allopurinol users. The most frequently cited highly ranked concerns could be divided into three categories. The first category, character of sleep interruption, included the concerns: severe and complete sleep interruption by gout flare pain (nine groups); and inability to get rapid eye movement sleep (one group). The second category, causes of sleep interruption, included: inability to get into a comfortable position during sleep (six groups); anxiety and depression associated with severe gout pain (seven groups); sleep interruption by moderate chronic joint pain (three groups); frequent trips to the bathroom interfering with sleep (two groups); gout medication side effects (four groups); frequent trips to the emergency room (one group); joint swelling with physical/functional deficit interfering with sleep (two groups); and flare pain interfering with sleep apnoea management (two groups). The final category, consequences of sleep interruption, included: effect on daily functioning (two groups); worsens other health conditions, which then affect sleep (four groups); and cumulative effect on sleep (one group). Gout has significant impact on sleep quantity, quality and architecture. Sleep disruption due to gout has several pathways and significant consequences.

Undergraduate Mathematics Students' Understanding of the Concept of Function

ERIC Educational Resources Information Center

Bardini, Caroline; Pierce, Robyn; Vincent, Jill; King, Deborah

2014-01-01

Concern has been expressed that many commencing undergraduate mathematics students have mastered skills without conceptual understanding. A pilot study carried out at a leading Australian university indicates that a significant number of students, with high tertiary entrance ranks, have very limited understanding of the concept of function,…

Revising a priority list based on cost-effectiveness: the role of the prominence effect and distorted utility judgments.

PubMed

Baron, J; Ubel, P A

2001-01-01

People sometimes object to the results of cost-effectiveness analysis when the analysis produces a ranking of options based on both cost and benefit. We suggest 2 new reasons for these objections: the prominence effect, in which people attend mostly to a more prominent attrbute (benefit as opposed to cost), and distortion of utility judgments. We simulated the production of a cost-effectiveness ranking list in 3 experiments using questionnaires on the World Wide Web. Subjects rated the utility of 16 health benefits using either rating scale or person trade-off elicitation methods. In some experiments, subjects were asked to rate the utility of the health benefits with attention also to the cost of achieving the benefits. In all experiments, at the end, subjects were shown a priority list based on their own utility judgments and were asked whether they wanted to move any of the health benefits up or down the list. In all experiments, subjects wanted to give higher priority to treatments with higher benefit, even when they also had higher cost. They thus wanted to give less weight to high cost (which would, by itself, lead to lower ranking) and more weight to benefit than the weight implied by their own prior judgments. The desire for revision was reduced when subjects made their utility judgments after indicating whether the utility was above or below the midpoint of the scale (a manipulation previously found to reduce distortion). The desire to change cost-effectiveness rankings is in part a preference reversal phenomenon that occurs because people attend mainly to the benefit of health interventions as opposed to cost, when they examine the ranking. People should be wary of tinkering with priority lists by examining the lists themselves.

Associations of relative deprivation and income rank with depressive symptoms among older adults in Japan.

PubMed

Gero, Krisztina; Kondo, Katsunori; Kondo, Naoki; Shirai, Kokoro; Kawachi, Ichiro

2017-09-01

Income is hypothesized to affect health not just through material pathways (i.e., the ability to purchase health-enhancing goods) but also through psychosocial pathways (e.g., social comparisons with others). Two concepts relevant to the psychosocial effects of income are: relative deprivation (for example expressed by the Yitzhaki Index, measuring the magnitude of difference in income among individuals) and Income Rank. This study examined whether higher relative deprivation and lower income rank are associated with depressive symptoms in an older population independently of absolute income. Using cross-sectional data of 83,100 participants (40,038 men and 43,062 women) in the Japan Gerontological Evaluation Study (JAGES), this study applied multiple logistic regression models to calculate the odds ratios (OR) of depression associated with relative deprivation/Income Rank. The Japanese Geriatric Depression Scale (GDS-15) was used to assess depressive symptoms, and subjects with a score of ≥5 were categorized as depressed. Reference groups for calculating the Yitzhaki Index and income rank were constructed based on same gender, age-group, and municipality of residence. The findings indicated that after controlling for demographic factors, each 100,000 yen increase in relative deprivation and 0.1 unit decrease in relative rank was associated with a 1.07 (95% CI = 1.07, 1.08) and a 1.15 (95% CI = 1.14, 1.16) times higher odds of depression, respectively, in men. The corresponding ORs in women were 1.05 (95% CI = 1.05, 1.06) and 1.12 (95% CI = 1.11, 1.13), respectively. After adjustment for other covariates and stratification by income quartiles, the results remained statistically significant. Women in the highest income quartile appeared to be more susceptible to the adverse mental health effects of low income rank, while among men the associations were reversed. Low income rank appeared to be more toxic for the poor. Concepts of relative income appear to be relevant for mental health over and above the effects of absolute income. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ranking Highlights in Personal Videos by Analyzing Edited Videos.

PubMed

Sun, Min; Farhadi, Ali; Chen, Tseng-Hung; Seitz, Steve

2016-11-01

We present a fully automatic system for ranking domain-specific highlights in unconstrained personal videos by analyzing online edited videos. A novel latent linear ranking model is proposed to handle noisy training data harvested online. Specifically, given a targeted domain such as "surfing," our system mines the YouTube database to find pairs of raw and their corresponding edited videos. Leveraging the assumption that an edited video is more likely to contain highlights than the trimmed parts of the raw video, we obtain pair-wise ranking constraints to train our model. The learning task is challenging due to the amount of noise and variation in the mined data. Hence, a latent loss function is incorporated to mitigate the issues caused by the noise. We efficiently learn the latent model on a large number of videos (about 870 min in total) using a novel EM-like procedure. Our latent ranking model outperforms its classification counterpart and is fairly competitive compared with a fully supervised ranking system that requires labels from Amazon Mechanical Turk. We further show that a state-of-the-art audio feature mel-frequency cepstral coefficients is inferior to a state-of-the-art visual feature. By combining both audio-visual features, we obtain the best performance in dog activity, surfing, skating, and viral video domains. Finally, we show that impressive highlights can be detected without additional human supervision for seven domains (i.e., skating, surfing, skiing, gymnastics, parkour, dog activity, and viral video) in unconstrained personal videos.

Navy Nurse Corps manpower management model.

PubMed

Kinstler, Daniel P; Johnson, Raymond W; Richter, Anke; Kocher, Kathryn

2008-01-01

The Navy Nurse Corps is part of a team of professionals that provides high quality, economical health care to approximately 700,000 active duty Navy and Marine Corps members, as well as 2.6 million retired and family members. Navy Nurse Corps manpower management efficiency is critical to providing this care. This paper aims to focus on manpower planning in the Navy Nurse Corps. The Nurse Corps manages personnel primarily through the recruitment process, drawing on multiple hiring sources. Promotion rates at the lowest two ranks are mandated, but not at the higher ranks. Retention rates vary across pay grades. Using these promotion and attrition rates, a Markov model was constructed to model the personnel flow of junior nurse corps officers. Hiring sources were shown to have a statistically significant effect on promotion and retention rates. However, these effects were not found to be practically significant in the Markov model. Only small improvements in rank imbalances are possible given current recruiting guidelines. Allowing greater flexibility in recruiting practices, fewer recruits would generate a 25 percent reduction in rank imbalances, but result in understaffing. Recruiting different ranks at entry would generate a 65 percent reduction in rank imbalances without understaffing issues. Policies adjusting promotion and retention rates are more powerful in controlling personnel flows than adjusting hiring sources. These policies are the only means for addressing the fundamental sources of rank imbalances in the Navy Nurse Corps arising from current manpower guidelines. The paper shows that modeling to improve manpower management may enable the Navy Nurse Corps to more efficiently fulfill its mandate for high-quality healthcare.

The necessity of sociodemographic status adjustment in hospital value rankings for perforated appendicitis in children.

PubMed

Tian, Yao; Sweeney, John F; Wulkan, Mark L; Heiss, Kurt F; Raval, Mehul V

2016-06-01

Hospitals are increasingly focused on demonstration of high-value care for common surgical procedures. Although sociodemographic status (SDS) factors have been tied to various surgical outcomes, the impact of SDS factors on hospital value rankings has not been well explored. Our objective was to examine effects of SDS factors on high-value surgical care at the patient level, and to illustrate the importance of SDS adjustment when evaluating hospital-level performance. Perforated appendicitis hospitalizations were identified from the 2012 Kids' Inpatient Database. The primary outcome of interest was high-value care as defined by evaluation of duration of stay and cost. SDS factors included race, health insurance type, median household income, and patient location. The impact of SDS on high-value care was estimated using regression models after accounting for hospital-level variation. Risk-adjusted value rankings were compared before and after adjustment for SDS. From 9,986 hospitalizations, 998 high-value encounters were identified. African Americans were less likely to experience high-value care compared with white patients after adjusting for all SDS variables. Although private insurance and living in nonmetro counties were associated independently with high-value care, the effects were attenuated in the fully adjusted models. For the 136 hospitals ranked according to risk-adjusted value status, 59 hospitals' rankings improved after adjustment and 53 hospitals' rankings declined. After adjustment for patient and hospital factors, SDS has a small but significant impact on risk-adjusted hospital performance ranking for pediatric appendicitis. Adjustment for SDS should be considered in future comparative performance assessment. Copyright © 2016 Elsevier Inc. All rights reserved.

Escape the Black Hole of Lecturing: Put Collaborative Ranking Tasks on Your Event Horizon

NASA Astrophysics Data System (ADS)

Hudgins, D. W.; Prather, E. E.; Grayson, D. J.

2005-05-01

At the University of Arizona, we have been developing and testing a new type of introductory astronomy curriculum material called Ranking Tasks. Ranking Tasks are a form of conceptual exercise that presents students with four to six physical situations, usually by pictures or diagrams, and asks students to rank order the situations based on some resulting effect. Our study developed design guidelines for Ranking Tasks based on learning theory and classroom pilot studies. Our research questions were: Do in-class collaborative Ranking Task exercises result in student conceptual gains when used in conjunction with traditional lecture-based instruction? And are these gains sufficient to justify implementing them into the astronomy classroom? We conducted a single-group repeated measures experiment across eight core introductory astronomy topics with 250 students at the University of Arizona in the Fall of 2004. The study found that traditional lecture-based instruction alone produced statistically significant gains - raising test scores to 61% post-lecture from 32% on the pretest. While significant, we find these gains to be unsatisfactory from a teaching and learning perspective. The study data shows that adding a collaborative learning component to the class structured around Ranking Task exercises helped students achieve statistically significant gains - with post-Ranking Task scores over the eight astronomy topic rising to 77%. Interestingly, we found that the normalized gain from the Ranking Tasks was equal to the entire previous gain from traditional instruction. Further analysis of the data revealed that Ranking Tasks equally benefited both genders; they also equally benefited both high and low-scoring median groups based on their pretest scores. Based on these results, we conclude that adding collaborative Ranking Task exercises to traditional lecture-based instruction can significantly improve student conceptual understanding of core topics in astronomy.

Query-Adaptive Hash Code Ranking for Large-Scale Multi-View Visual Search.

PubMed

Liu, Xianglong; Huang, Lei; Deng, Cheng; Lang, Bo; Tao, Dacheng

2016-10-01

Hash-based nearest neighbor search has become attractive in many applications. However, the quantization in hashing usually degenerates the discriminative power when using Hamming distance ranking. Besides, for large-scale visual search, existing hashing methods cannot directly support the efficient search over the data with multiple sources, and while the literature has shown that adaptively incorporating complementary information from diverse sources or views can significantly boost the search performance. To address the problems, this paper proposes a novel and generic approach to building multiple hash tables with multiple views and generating fine-grained ranking results at bitwise and tablewise levels. For each hash table, a query-adaptive bitwise weighting is introduced to alleviate the quantization loss by simultaneously exploiting the quality of hash functions and their complement for nearest neighbor search. From the tablewise aspect, multiple hash tables are built for different data views as a joint index, over which a query-specific rank fusion is proposed to rerank all results from the bitwise ranking by diffusing in a graph. Comprehensive experiments on image search over three well-known benchmarks show that the proposed method achieves up to 17.11% and 20.28% performance gains on single and multiple table search over the state-of-the-art methods.

The Visual Analogue Scale for Rating, Ranking and Paired-Comparison (VAS-RRP): A new technique for psychological measurement.

PubMed

Sung, Yao-Ting; Wu, Jeng-Shin

2018-04-17

Traditionally, the visual analogue scale (VAS) has been proposed to overcome the limitations of ordinal measures from Likert-type scales. However, the function of VASs to overcome the limitations of response styles to Likert-type scales has not yet been addressed. Previous research using ranking and paired comparisons to compensate for the response styles of Likert-type scales has suffered from limitations, such as that the total score of ipsative measures is a constant that cannot be analyzed by means of many common statistical techniques. In this study we propose a new scale, called the Visual Analogue Scale for Rating, Ranking, and Paired-Comparison (VAS-RRP), which can be used to collect rating, ranking, and paired-comparison data simultaneously, while avoiding the limitations of each of these data collection methods. The characteristics, use, and analytic method of VAS-RRPs, as well as how they overcome the disadvantages of Likert-type scales, ranking, and VASs, are discussed. On the basis of analyses of simulated and empirical data, this study showed that VAS-RRPs improved reliability, response style bias, and parameter recovery. Finally, we have also designed a VAS-RRP Generator for researchers' construction and administration of their own VAS-RRPs.

Langerhans cell precursors acquire RANK/CD265 in prenatal human skin

PubMed Central

Schöppl, Alice; Botta, Albert; Prior, Marion; Akgün, Johnnie; Schuster, Christopher; Elbe-Bürger, Adelheid

2015-01-01

The skin is the first barrier against foreign pathogens and the prenatal formation of a strong network of various innate and adaptive cells is required to protect the newborn from perinatal infections. While many studies about the immune system in healthy and diseased adult human skin exist, our knowledge about the cutaneous prenatal/developing immune system and especially about the phenotype and function of antigen-presenting cells such as epidermal Langerhans cells (LCs) in human skin is still scarce. It has been shown previously that LCs in healthy adult human skin express receptor activator of NF-κB (RANK), an important molecule prolonging their survival. In this study, we investigated at which developmental stage LCs acquire this important molecule. Immunofluorescence double-labeling of cryostat sections revealed that LC precursors in prenatal human skin either do not yet [10–11 weeks of estimated gestational age (EGA)] or only faintly (13–15 weeks EGA) express RANK. LCs express RANK at levels comparable to adult LCs by the end of the second trimester. Comparable with adult skin, dermal antigen-presenting cells at no gestational age express this marker. These findings indicate that epidermal leukocytes gradually acquire RANK during gestation – a phenomenon previously observed also for other markers on LCs in prenatal human skin. PMID:25722033

Automatically identifying health outcome information in MEDLINE records.

PubMed

Demner-Fushman, Dina; Few, Barbara; Hauser, Susan E; Thoma, George

2006-01-01

Understanding the effect of a given intervention on the patient's health outcome is one of the key elements in providing optimal patient care. This study presents a methodology for automatic identification of outcomes-related information in medical text and evaluates its potential in satisfying clinical information needs related to health care outcomes. An annotation scheme based on an evidence-based medicine model for critical appraisal of evidence was developed and used to annotate 633 MEDLINE citations. Textual, structural, and meta-information features essential to outcome identification were learned from the created collection and used to develop an automatic system. Accuracy of automatic outcome identification was assessed in an intrinsic evaluation and in an extrinsic evaluation, in which ranking of MEDLINE search results obtained using PubMed Clinical Queries relied on identified outcome statements. The accuracy and positive predictive value of outcome identification were calculated. Effectiveness of the outcome-based ranking was measured using mean average precision and precision at rank 10. Automatic outcome identification achieved 88% to 93% accuracy. The positive predictive value of individual sentences identified as outcomes ranged from 30% to 37%. Outcome-based ranking improved retrieval accuracy, tripling mean average precision and achieving 389% improvement in precision at rank 10. Preliminary results in outcome-based document ranking show potential validity of the evidence-based medicine-model approach in timely delivery of information critical to clinical decision support at the point of service.

Variance-Stable R-Estimators.

DTIC Science & Technology

1984-05-01

By means of the concept of change-of variance function we investigate the stability properties of the asymptotic variance of R-estimators. This allows us to construct the optimal V-robust R-estimator that minimizes the asymptotic variance at the model, under the side condition of a bounded change-of variance function. Finally, we discuss the connection between this function and an influence function for two-sample rank tests introduced by Eplett (1980). (Author)

Computing many-body wave functions with guaranteed precision: the first-order Møller-Plesset wave function for the ground state of helium atom.

PubMed

Bischoff, Florian A; Harrison, Robert J; Valeev, Edward F

2012-09-14

We present an approach to compute accurate correlation energies for atoms and molecules using an adaptive discontinuous spectral-element multiresolution representation for the two-electron wave function. Because of the exponential storage complexity of the spectral-element representation with the number of dimensions, a brute-force computation of two-electron (six-dimensional) wave functions with high precision was not practical. To overcome the key storage bottlenecks we utilized (1) a low-rank tensor approximation (specifically, the singular value decomposition) to compress the wave function, and (2) explicitly correlated R12-type terms in the wave function to regularize the Coulomb electron-electron singularities of the Hamiltonian. All operations necessary to solve the Schrödinger equation were expressed so that the reconstruction of the full-rank form of the wave function is never necessary. Numerical performance of the method was highlighted by computing the first-order Møller-Plesset wave function of a helium atom. The computed second-order Møller-Plesset energy is precise to ~2 microhartrees, which is at the precision limit of the existing general atomic-orbital-based approaches. Our approach does not assume special geometric symmetries, hence application to molecules is straightforward.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

PubMed

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both local and global learning strategies, able to exploit the overall topology of the network. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Regularization iteration imaging algorithm for electrical capacitance tomography

NASA Astrophysics Data System (ADS)

Tong, Guowei; Liu, Shi; Chen, Hongyan; Wang, Xueyao

2018-03-01

The image reconstruction method plays a crucial role in real-world applications of the electrical capacitance tomography technique. In this study, a new cost function that simultaneously considers the sparsity and low-rank properties of the imaging targets is proposed to improve the quality of the reconstruction images, in which the image reconstruction task is converted into an optimization problem. Within the framework of the split Bregman algorithm, an iterative scheme that splits a complicated optimization problem into several simpler sub-tasks is developed to solve the proposed cost function efficiently, in which the fast-iterative shrinkage thresholding algorithm is introduced to accelerate the convergence. Numerical experiment results verify the effectiveness of the proposed algorithm in improving the reconstruction precision and robustness.

Role of RANKL (TNFSF11)-Dependent Osteopetrosis in the Dental Phenotype of Msx2 Null Mutant Mice

PubMed Central

Castaneda, Beatriz; Simon, Yohann; Ferbus, Didier; Robert, Benoit; Chesneau, Julie; Mueller, Christopher

2013-01-01

The MSX2 homeoprotein is implicated in all aspects of craniofacial skeletal development. During postnatal growth, MSX2 is expressed in all cells involved in mineralized tissue formation and plays a role in their differentiation and function. Msx2 null (Msx2 −/−) mice display complex craniofacial skeleton abnormalities with bone and tooth defects. A moderate form osteopetrotic phenotype is observed, along with decreased expression of RANKL (TNFSF11), the main osteoclast-differentiating factor. In order to elucidate the role of such an osteopetrosis in the Msx2 −/− mouse dental phenotype, a bone resorption rescue was performed by mating Msx2 −/− mice with a transgenic mouse line overexpressing Rank (Tnfrsf11a). Msx2 −/− RankTg mice had significant improvement in the molar phenotype, while incisor epithelium defects were exacerbated in the enamel area, with formation of massive osteolytic tumors. Although compensation for RANKL loss of function could have potential as a therapy for osteopetrosis, but in Msx2 −/− mice, this approach via RANK overexpression in monocyte-derived lineages, amplified latent epithelial tumor development in the peculiar continuously growing incisor. PMID:24278237

Social rank affects the haematologic profile in red deer hinds.

PubMed

Ceacero, Francisco; Gaspar-López, Enrique; Landete-Castillejos, Tomás; Gallego, Laureano; García, Andrés J

2018-04-14

We studied the effects of social rank on the haematologic profile in a herd of 24 female Iberian red deer hinds. Social rank hierarchy was determined and blood samples were taken and analysed. After adjusting for age and body mass, dominance ranking showed a significant negative effect (ie, lower values in dominant hinds) on white blood cell (WBC) count, haemoglobin and haematocrit. Our results are similar to those reported for stressed individuals due to physical immobilisation, but do not support the predicted enhanced erythropoiesis due to higher levels of androgens. The results for WBC numbers may also reflect that subordinate hinds must allocate a higher amount of resources to immunity as a result of injuries incurred from dominant hinds, while simultaneously facing restricted access to food sources. For red blood cell (RBC) counts, the results may be due to subordinate hinds likely needing increased haematocrit and haemoglobin levels for fast flight responses. Our data show that social rank influences haematologic profile, and thus it should be considered when correctly interpreting blood analyses in social cervid species. © British Veterinary Association (unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Improve Biomedical Information Retrieval using Modified Learning to Rank Methods.

PubMed

Xu, Bo; Lin, Hongfei; Lin, Yuan; Ma, Yunlong; Yang, Liang; Wang, Jian; Yang, Zhihao

2016-06-14

In these years, the number of biomedical articles has increased exponentially, which becomes a problem for biologists to capture all the needed information manually. Information retrieval technologies, as the core of search engines, can deal with the problem automatically, providing users with the needed information. However, it is a great challenge to apply these technologies directly for biomedical retrieval, because of the abundance of domain specific terminologies. To enhance biomedical retrieval, we propose a novel framework based on learning to rank. Learning to rank is a series of state-of-the-art information retrieval techniques, and has been proved effective in many information retrieval tasks. In the proposed framework, we attempt to tackle the problem of the abundance of terminologies by constructing ranking models, which focus on not only retrieving the most relevant documents, but also diversifying the searching results to increase the completeness of the resulting list for a given query. In the model training, we propose two novel document labeling strategies, and combine several traditional retrieval models as learning features. Besides, we also investigate the usefulness of different learning to rank approaches in our framework. Experimental results on TREC Genomics datasets demonstrate the effectiveness of our framework for biomedical information retrieval.

Comparing the loss of functional independence of older adults in the U.S. and China.

PubMed

Fong, Joelle H; Feng, Jun

2018-01-01

Functional loss among older adults is known to follow a hierarchical sequence, but little is known about whether such sequences differ across socio-cultural contexts. The aim of this study is to construct activities of daily livings (ADL) scales for oldest-old adults in the United States and China so as to compare their functional loss sequences. We use data from the Asset and Health Dynamics of the Oldest Old (n=1607) and Chinese Longitudinal Healthy Longevity Survey (n=5570) for years 1998-2008. ADL items are calibrated within a scale using the Rasch measurement model. Rasch scores are averaged across survey waves to identify the ADL loss sequence for each study population. We also assess scale stability over measurement periods. Factor analyses confirm that the ADL items in each study population can be combined meaningfully to form a hierarchical sequence. Internal consistency assessed by Cronbach's alpha is high (0.81 to 0.95). We find that bathing is the first activity that both older Americans and Chinese have difficulty with, while eating is the last activity. There are, however, differences in the rank order for toileting (ranked more challenging in the Chinese sample) and dressing (ranked more challenging in the U.S. sample). Item orderings are stable over time. The results highlight the relative importance of bathing in the functional loss sequence for older adults, regardless of socio-cultural context. Health interventions are needed to address deficits in the bathroom environment, especially in developing countries like China. Copyright © 2017 Elsevier B.V. All rights reserved.

[Rank distributions in community ecology from the statistical viewpoint].

PubMed

Maksimov, V N

2004-01-01

Traditional statistical methods for definition of empirical functions of abundance distribution (population, biomass, production, etc.) of species in a community are applicable for processing of multivariate data contained in the above quantitative indices of the communities. In particular, evaluation of moments of distribution suffices for convolution of the data contained in a list of species and their abundance. At the same time, the species should be ranked in the list in ascending rather than descending population and the distribution models should be analyzed on the basis of the data on abundant species only.

Analysis of the Hessian for Inverse Scattering Problems. Part 3. Inverse Medium Scattering of Electromagnetic Waves in Three Dimensions

DTIC Science & Technology

2012-08-01

small data noise and model error, the discrete Hessian can be approximated by a low-rank matrix. This in turn enables fast solution of an appropriately...implication of the compactness of the Hessian is that for small data noise and model error, the discrete Hessian can be approximated by a low-rank matrix. This...probability distribution is given by the inverse of the Hessian of the negative log likelihood function. For Gaussian data noise and model error, this

A new mutually reinforcing network node and link ranking algorithm

PubMed Central

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

Predicting intensity ranks of peptide fragment ions.

PubMed

Frank, Ari M

2009-05-01

Accurate modeling of peptide fragmentation is necessary for the development of robust scoring functions for peptide-spectrum matches, which are the cornerstone of MS/MS-based identification algorithms. Unfortunately, peptide fragmentation is a complex process that can involve several competing chemical pathways, which makes it difficult to develop generative probabilistic models that describe it accurately. However, the vast amounts of MS/MS data being generated now make it possible to use data-driven machine learning methods to develop discriminative ranking-based models that predict the intensity ranks of a peptide's fragment ions. We use simple sequence-based features that get combined by a boosting algorithm into models that make peak rank predictions with high accuracy. In an accompanying manuscript, we demonstrate how these prediction models are used to significantly improve the performance of peptide identification algorithms. The models can also be useful in the design of optimal multiple reaction monitoring (MRM) transitions, in cases where there is insufficient experimental data to guide the peak selection process. The prediction algorithm can also be run independently through PepNovo+, which is available for download from http://bix.ucsd.edu/Software/PepNovo.html.

Predicting Intensity Ranks of Peptide Fragment Ions

PubMed Central

Frank, Ari M.

2009-01-01

Accurate modeling of peptide fragmentation is necessary for the development of robust scoring functions for peptide-spectrum matches, which are the cornerstone of MS/MS-based identification algorithms. Unfortunately, peptide fragmentation is a complex process that can involve several competing chemical pathways, which makes it difficult to develop generative probabilistic models that describe it accurately. However, the vast amounts of MS/MS data being generated now make it possible to use data-driven machine learning methods to develop discriminative ranking-based models that predict the intensity ranks of a peptide's fragment ions. We use simple sequence-based features that get combined by a boosting algorithm in to models that make peak rank predictions with high accuracy. In an accompanying manuscript, we demonstrate how these prediction models are used to significantly improve the performance of peptide identification algorithms. The models can also be useful in the design of optimal MRM transitions, in cases where there is insufficient experimental data to guide the peak selection process. The prediction algorithm can also be run independently through PepNovo+, which is available for download from http://bix.ucsd.edu/Software/PepNovo.html. PMID:19256476

Performance of low-rank QR approximation of the finite element Biot-Savart law

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, D; Fasenfest, B

2006-10-16

In this paper we present a low-rank QR method for evaluating the discrete Biot-Savart law. Our goal is to develop an algorithm that is easily implemented on parallel computers. It is assumed that the known current density and the unknown magnetic field are both expressed in a finite element expansion, and we wish to compute the degrees-of-freedom (DOF) in the basis function expansion of the magnetic field. The matrix that maps the current DOF to the field DOF is full, but if the spatial domain is properly partitioned the matrix can be written as a block matrix, with blocks representingmore » distant interactions being low rank and having a compressed QR representation. While an octree partitioning of the matrix may be ideal, for ease of parallel implementation we employ a partitioning based on number of processors. The rank of each block (i.e. the compression) is determined by the specific geometry and is computed dynamically. In this paper we provide the algorithmic details and present computational results for large-scale computations.« less

Prediction of plant lncRNA by ensemble machine learning classifiers.

PubMed

Simopoulos, Caitlin M A; Weretilnyk, Elizabeth A; Golding, G Brian

2018-05-02

In plants, long non-protein coding RNAs are believed to have essential roles in development and stress responses. However, relative to advances on discerning biological roles for long non-protein coding RNAs in animal systems, this RNA class in plants is largely understudied. With comparatively few validated plant long non-coding RNAs, research on this potentially critical class of RNA is hindered by a lack of appropriate prediction tools and databases. Supervised learning models trained on data sets of mostly non-validated, non-coding transcripts have been previously used to identify this enigmatic RNA class with applications largely focused on animal systems. Our approach uses a training set comprised only of empirically validated long non-protein coding RNAs from plant, animal, and viral sources to predict and rank candidate long non-protein coding gene products for future functional validation. Individual stochastic gradient boosting and random forest classifiers trained on only empirically validated long non-protein coding RNAs were constructed. In order to use the strengths of multiple classifiers, we combined multiple models into a single stacking meta-learner. This ensemble approach benefits from the diversity of several learners to effectively identify putative plant long non-coding RNAs from transcript sequence features. When the predicted genes identified by the ensemble classifier were compared to those listed in GreeNC, an established plant long non-coding RNA database, overlap for predicted genes from Arabidopsis thaliana, Oryza sativa and Eutrema salsugineum ranged from 51 to 83% with the highest agreement in Eutrema salsugineum. Most of the highest ranking predictions from Arabidopsis thaliana were annotated as potential natural antisense genes, pseudogenes, transposable elements, or simply computationally predicted hypothetical protein. Due to the nature of this tool, the model can be updated as new long non-protein coding transcripts are identified and functionally verified. This ensemble classifier is an accurate tool that can be used to rank long non-protein coding RNA predictions for use in conjunction with gene expression studies. Selection of plant transcripts with a high potential for regulatory roles as long non-protein coding RNAs will advance research in the elucidation of long non-protein coding RNA function.

Relationship between Small Animal Intern Rank and Performance at a University Teaching Hospital.

PubMed

Hofmeister, Erik H; Saba, Corey; Kent, Marc; Creevy, Kate E

2015-01-01

The purpose of this study was to determine if there is a relationship between selection committee rankings of internship applicants and the performance of small animal interns. The hypothesis was that there would be a relationship between selection committee rank order and intern performance; the more highly an application was ranked, the better the intern's performance scores would be. In 2007, the Department of Small Animal Medicine and Surgery instituted a standardized approach to its intern selection process both to streamline the process and to track its effectiveness. At the end of intern years 2010-2014, every faculty member in the department was provided an intern assessment form for that year's class. There was no relationship between an individual intern's final rank by the selection committee and his/her performance either as a percentile score or a Likert-type score (p=.25, R2=0.04; p=0.31, R2=0.03, respectively). Likewise, when interns were divided into the top and bottom quartile based on their final rank by the selection committee, there was no relationship between their rank and their performance as a percentile score (median rank 15 vs. 20; p=.14) or Likert-type score (median rank 14 vs. 19; p=.27). Institutions that use a similar intern selection method may need to reconsider the time and effort being expended for an outcome that does not predict performance. Alternatively, specific criteria more predictive of performance outcomes should be identified and employed in the internship selection process.

Unfolded equations for current interactions of 4d massless fields as a free system in mixed dimensions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gelfond, O. A., E-mail: gel@lpi.ru; Vasiliev, M. A., E-mail: vasiliev@lpi.ru

2015-03-15

Interactions of massless fields of all spins in four dimensions with currents of any spin are shown to result from a solution of the linear problem that describes a gluing between a rank-one (massless) system and a rank-two (current) system in the unfolded dynamics approach. Since the rank-two system is dual to a free rank-one higher-dimensional system that effectively describes conformal fields in six space-time dimensions, the constructed system can be interpreted as describing a mixture between linear conformal fields in four and six dimensions. An interpretation of the obtained results in the spirit of the AdS/CFT correspondence is discussed.

Relationships between Work and Life away from Work among University Faculty: Gender and Rank Effects.

ERIC Educational Resources Information Center

Sorcinelli, Mary Deane; Near, Janet P.

Spillover between work and life away from work was studied with 100 college faculty, who lived in a small college town, where work and life outside of work appear closely bound. The effects of gender and academic rank on the incidence of spillover between work and nonwork were assessed. Faculty from humanities and natural sciences departments and…

Methodology to identify risk-significant components for inservice inspection and testing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anderson, M.T.; Hartley, R.S.; Jones, J.L. Jr.

1992-08-01

Periodic inspection and testing of vital system components should be performed to ensure the safe and reliable operation of Department of Energy (DOE) nuclear processing facilities. Probabilistic techniques may be used to help identify and rank components by their relative risk. A risk-based ranking would allow varied DOE sites to implement inspection and testing programs in an effective and cost-efficient manner. This report describes a methodology that can be used to rank components, while addressing multiple risk issues.

Cost-Effective Air Transportation of Australian Defence Force Personnel within Australia

DTIC Science & Technology

1988-09-01

the RAAF scheduled air service system. Cost-Effectiveness William A. Niskanen describes cost-effectiveness as part of the general theory of maximising...positioned somewhere in the middle of the analytic spectrum between the classical theory of the firm at one end and the operations analysis at the...were used in the simulation to assign a rank to each entity . 44 Table VIII Rank Category P Distributions CATEGORY (per cent) LOCATION 1 2 3 4 5

Visual Search with Image Modification in Age-Related Macular Degeneration

PubMed Central

Wiecek, Emily; Jackson, Mary Lou; Dakin, Steven C.; Bex, Peter

2012-01-01

Purpose. AMD results in loss of central vision and a dependence on low-resolution peripheral vision. While many image enhancement techniques have been proposed, there is a lack of quantitative comparison of the effectiveness of enhancement. We developed a natural visual search task that uses patients' eye movements as a quantitative and functional measure of the efficacy of image modification. Methods. Eye movements of 17 patients (mean age = 77 years) with AMD were recorded while they searched for target objects in natural images. Eight different image modification methods were implemented and included manipulations of local image or edge contrast, color, and crowding. In a subsequent task, patients ranked their preference of the image modifications. Results. Within individual participants, there was no significant difference in search duration or accuracy across eight different image manipulations. When data were collapsed across all image modifications, a multivariate model identified six significant predictors for normalized search duration including scotoma size and acuity, as well as interactions among scotoma size, age, acuity, and contrast (P < 0.05). Additionally, an analysis of image statistics showed no correlation with search performance across all image modifications. Rank ordering of enhancement methods based on participants' preference revealed a trend that participants preferred the least modified images (P < 0.05). Conclusions. There was no quantitative effect of image modification on search performance. A better understanding of low- and high-level components of visual search in natural scenes is necessary to improve future attempts at image enhancement for low vision patients. Different search tasks may require alternative image modifications to improve patient functioning and performance. PMID:22930725

Weighted Discriminative Dictionary Learning based on Low-rank Representation

NASA Astrophysics Data System (ADS)

Chang, Heyou; Zheng, Hao

2017-01-01

Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.

Transformational leadership in the local police in Spain: a leader-follower distance approach.

PubMed

Álvarez, Octavio; Lila, Marisol; Tomás, Inés; Castillo, Isabel

2014-01-01

Based on the transformational leadership theory (Bass, 1985), the aim of the present study was to analyze the differences in leadership styles according to the various leading ranks and the organizational follower-leader distance reported by a representative sample of 975 local police members (828 male and 147 female) from Valencian Community (Spain). Results showed differences by rank (p < .01), and by rank distance (p < .05). The general intendents showed the most optimal profile of leadership in all the variables examined (transformational-leadership behaviors, transactional-leadership behaviors, laissez-faire behaviors, satisfaction with the leader, extra effort by follower, and perceived leadership effectiveness). By contrast, the least optimal profiles were presented by intendents. Finally, the maximum distance (five ranks) generally yielded the most optimal profiles, whereas the 3-rank distance generally produced the least optimal profiles for all variables examined. Outcomes and practical implications for the workforce dimensioning are also discussed.

Prioritizing industries for occupational injury and illness prevention and research, Washington State Workers' compensation claims, 1999-2003.

PubMed

Bonauto, David; Silverstein, Barbara; Adams, Darrin; Foley, Michael

2006-08-01

The objective of this study was to identify high-risk industry groups for effective allocation of occupational safety and health prevention and research resources. We used all compensable Washington state workers' compensation claims to rank North American Industry Classification System (NAICS) industry groups by a "prevention index" (PI). The PI is the average of the rank orders of each industry group's claim count and claim incidence rate. Of the 274 industry groups ranked by PI for all compensable workers' compensation claims, the following industry groups ranked the highest: NAICS 2381 Foundation, Structure, and Building Exterior Contractors, NAICS 4841 General Freight Trucking, and NAICS 2361 Residential Building Construction. Industry group PI rankings are reported for the seven most common costly occupational injury types. Use of a PI can focus prevention and research resources where they can be of most benefit.

Effect of Knee Orthoses on Hamstring Contracture in Children With Cerebral Palsy: Multiple Single-Subject Study.

PubMed

Laessker-Alkema, Kristina; Eek, Meta Nyström

2016-01-01

To examine the effect of knee orthoses on extensibility of the hamstrings in children with spastic cerebral palsy (CP). The short-term effects of knee orthoses on passive range of motion (ROM), spasticity, and gross motor function of the hamstrings. Ten children with spastic CP, aged 5 to 14 years, at Gross Motor Function Classification System levels I to V, were followed. The orthoses were worn for a minimum of 30 minutes day, 5 days per week, during the intervention period of 8 weeks. Visual analysis using the Two Standard Deviation Band Method supported improvements in passive ROM for all 20 hamstring muscles and in 12 of 14 knee extension measurements. Analyses with the Wilcoxon signed rank test confirm the individual results and support a significant increase in hamstring muscles (P = .005) and knee extension (right: P =.028; left: P =.018) compared with baseline. In children with spastic CP, 8 weeks of treatment with knee orthoses can improve extensibility of the hamstrings.

The impact of gout on patient's lives: a study of African-American and Caucasian men and women with gout.

PubMed

Singh, Jasvinder A

2014-06-24

The aim of this study was to examine the impact of gout on quality of life (QOL) and study differences by gender and race. Ten race- and sex-stratified nominal groups were conducted, oversampling for African-Americans and women with gout. Patients presented, discussed, combined and rank-ordered their concerns. A total of 62 patients with mean age 65.1 years, 60% men, 64% African-American, participated in 10 nominal groups: African-American men (n = 23; 3 groups); African-American women (n = 18; 3 groups); Caucasian men (n = 15; 3 groups); and Caucasian women (n = 6; 1 group). The most frequently cited high-ranked concerns among the ten nominal groups were: (1) effect of gout flare on daily activities (n = 10 groups); (2) work disability (n = 8 groups); (3) severe pain (n = 8 groups); (4) joint swelling and tenderness (n = 6 groups); (5) food restrictions (n = 6 groups); (6) medication related issues (n = 6 groups); (7) dependency on family and others (n = 5 groups); (8) emotional Impact (n = 5 groups); (9) interference with sexual function (n = 4 groups); (10) difficulty with shoes (n = 4 groups); and (11) sleep disruption (n = 4 groups). Compared with men, women ranked the following concerns high more often: problems with shoes (n = 4 versus n = 0 groups); dependency (n = 3 versus n = 2 groups); and joint/limb deformity (n = 2 versus n = 0 group). Compared with Caucasians, African-Americans ranked the following concerns high more often: dietary restrictions (n = 6 versus n = 0 groups); severe pain (n = 6 versus n = 2 groups); gout bringing the day to a "halt" (n = 2 versus n = 0 group); effect on emotional health (n = 4 versus n = 1 groups); and the need for canes/crutches during flares (n = 2 versus n = 0 group). Gout has a significant impact on a patient's QOL. Important differences in the impact of gout by gender and race were noted.

Adjuvant ovarian function suppression and cognitive function in women with breast cancer

PubMed Central

Phillips, Kelly-Anne; Regan, Meredith M; Ribi, Karin; Francis, Prudence A; Puglisi, Fabio; Bellet, Meritxell; Spazzapan, Simon; Karlsson, Per; Budman, Daniel R; Zaman, Khalil; Abdi, Ehtesham A; Domchek, Susan M; Feng, Yang; Price, Karen N; Coates, Alan S; Gelber, Richard D; Maruff, Paul; Boyle, Frances; Forbes, John F; Ahles, Tim; Fleming, Gini F; Bernhard, Jürg

2016-01-01

Background: To examine the effect on cognitive function of adjuvant ovarian function suppression (OFS) for breast cancer. Methods: The Suppression of Ovarian Function (SOFT) trial randomised premenopausal women with hormone receptor-positive breast cancer to 5 years adjuvant endocrine therapy with tamoxifen+OFS, exemestane+OFS or tamoxifen alone. The Co-SOFT substudy assessed objective cognitive function and patient reported outcomes at randomisation (T0), and 1 year later (T1); the primary endpoint was change in global cognitive function, measured by the composite objective cognitive function score. Data were compared for the pooled tamoxifen+OFS and exemestane+OFS groups vs the tamoxifen alone group using the Wilcoxon rank-sum test. Results: Of 86 participants, 74 underwent both T0 and T1 cognitive testing; 54 randomised to OFS+ either tamoxifen (28) or exemestane (26) and 20 randomised to tamoxifen alone. There was no significant difference in the changes in the composite cognitive function scores between the OFS+ tamoxifen or exemestane groups and the tamoxifen group (mean±s.d., −0.21±0.92 vs −0.04±0.49, respectively, P=0.71, effect size=−0.20), regardless of prior chemotherapy status, and adjusting for baseline characteristics. Conclusions: The Co-SOFT study, although limited by small samples size, provides no evidence that adding OFS to adjuvant oral endocrine therapy substantially affects global cognitive function. PMID:27092785

A Layered Searchable Encryption Scheme with Functional Components Independent of Encryption Methods

PubMed Central

Luo, Guangchun; Qin, Ke

2014-01-01

Searchable encryption technique enables the users to securely store and search their documents over the remote semitrusted server, which is especially suitable for protecting sensitive data in the cloud. However, various settings (based on symmetric or asymmetric encryption) and functionalities (ranked keyword query, range query, phrase query, etc.) are often realized by different methods with different searchable structures that are generally not compatible with each other, which limits the scope of application and hinders the functional extensions. We prove that asymmetric searchable structure could be converted to symmetric structure, and functions could be modeled separately apart from the core searchable structure. Based on this observation, we propose a layered searchable encryption (LSE) scheme, which provides compatibility, flexibility, and security for various settings and functionalities. In this scheme, the outputs of the core searchable component based on either symmetric or asymmetric setting are converted to some uniform mappings, which are then transmitted to loosely coupled functional components to further filter the results. In such a way, all functional components could directly support both symmetric and asymmetric settings. Based on LSE, we propose two representative and novel constructions for ranked keyword query (previously only available in symmetric scheme) and range query (previously only available in asymmetric scheme). PMID:24719565

A general method for decomposing the causes of socioeconomic inequality in health.

PubMed

Heckley, Gawain; Gerdtham, Ulf-G; Kjellsson, Gustav

2016-07-01

We introduce a general decomposition method applicable to all forms of bivariate rank dependent indices of socioeconomic inequality in health, including the concentration index. The technique is based on recentered influence function regression and requires only the application of OLS to a transformed variable with similar interpretation. Our method requires few identifying assumptions to yield valid estimates in most common empirical applications, unlike current methods favoured in the literature. Using the Swedish Twin Registry and a within twin pair fixed effects identification strategy, our new method finds no evidence of a causal effect of education on income-related health inequality. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Regenerative Stem Cell Therapy for Breast Cancer Bone Metastasis

DTIC Science & Technology

2015-11-01

nitrocellulose membranes (Millipore) followed by blocking with 2% non- fat milk and incubation with primary antibodies, overnight at 4C. The b-actin...TNF-like proteins : Osteoprotegerin (OPG), RANK and RANKL, which together regulate osteoclast function (1). The dysregulation of the functional...among proteins in the same family are an indication they may have functional importance, so these residues may be important in mediating the

Atp1a3-deficient heterozygous mice show lower rank in the hierarchy and altered social behavior.

PubMed

Sugimoto, H; Ikeda, K; Kawakami, K

2018-06-01

Atp1a3 is the Na-pump alpha3 subunit gene expressed mainly in neurons of the brain. Atp1a3-deficient heterozygous mice (Atp1a3 +/- ) show altered neurotransmission and deficits of motor function after stress loading. To understand the function of Atp1a3 in a social hierarchy, we evaluated social behaviors (social interaction, aggression, social approach and social dominance) of Atp1a3 +/- and compared the rank and hierarchy structure between Atp1a3 +/- and wild-type mice within a housing cage using the round-robin tube test and barbering observations. Formation of a hierarchy decreases social conflict and promote social stability within the group. The hierarchical rank is a reflection of social dominance within a cage, which is heritable and can be regulated by specific genes in mice. Here we report: (1) The degree of social interaction but not aggression was lower in Atp1a3 +/- than wild-type mice, and Atp1a3 +/- approached Atp1a3 +/- mice more frequently than wild type. (2) The frequency of barbering was lower in the Atp1a3 +/- group than in the wild-type group, while no difference was observed in the mixed-genotype housing condition. (3) Hierarchy formation was not different between Atp1a3 +/- and wild type. (4) Atp1a3 +/- showed a lower rank in the mixed-genotype housing condition than that in the wild type, indicating that Atp1a3 regulates social dominance. In sum, Atp1a3 +/- showed unique social behavior characteristics of lower social interaction and preference to approach the same genotype mice and a lower ranking in the hierarchy. © 2017 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Zipf 's law and the effect of ranking on probability distributions

NASA Astrophysics Data System (ADS)

Günther, R.; Levitin, L.; Schapiro, B.; Wagner, P.

1996-02-01

Ranking procedures are widely used in the description of many different types of complex systems. Zipf's law is one of the most remarkable frequency-rank relationships and has been observed independently in physics, linguistics, biology, demography, etc. We show that ranking plays a crucial role in making it possible to detect empirical relationships in systems that exist in one realization only, even when the statistical ensemble to which the systems belong has a very broad probability distribution. Analytical results and numerical simulations are presented which clarify the relations between the probability distributions and the behavior of expected values for unranked and ranked random variables. This analysis is performed, in particular, for the evolutionary model presented in our previous papers which leads to Zipf's law and reveals the underlying mechanism of this phenomenon in terms of a system with interdependent and interacting components as opposed to the “ideal gas” models suggested by previous researchers. The ranking procedure applied to this model leads to a new, unexpected phenomenon: a characteristic “staircase” behavior of the mean values of the ranked variables (ranked occupation numbers). This result is due to the broadness of the probability distributions for the occupation numbers and does not follow from the “ideal gas” model. Thus, it provides an opportunity, by comparison with empirical data, to obtain evidence as to which model relates to reality.

Regulatory Reform: Compliance Guide Requirement Has Had Little Effect on Agency Practices

DTIC Science & Technology

2001-12-01

United States General Accounting Office GAO Report to the Ranking Minority Member Committee on Small Business and Entrepreneurship , U.S. Senate...20548 December 28, 2001 The Honorable Christopher S. Bond Ranking Minority Member Committee on Small Business and Entrepreneurship United States

On the effect of response transformations in sequential parameter optimization.

PubMed

Wagner, Tobias; Wessing, Simon

2012-01-01

Parameter tuning of evolutionary algorithms (EAs) is attracting more and more interest. In particular, the sequential parameter optimization (SPO) framework for the model-assisted tuning of stochastic optimizers has resulted in established parameter tuning algorithms. In this paper, we enhance the SPO framework by introducing transformation steps before the response aggregation and before the actual modeling. Based on design-of-experiments techniques, we empirically analyze the effect of integrating different transformations. We show that in particular, a rank transformation of the responses provides significant improvements. A deeper analysis of the resulting models and additional experiments with adaptive procedures indicates that the rank and the Box-Cox transformation are able to improve the properties of the resultant distributions with respect to symmetry and normality of the residuals. Moreover, model-based effect plots document a higher discriminatory power obtained by the rank transformation.

The preferred traits of mates in a cross-national study of heterosexual and homosexual men and women: an examination of biological and cultural influences.

PubMed

Lippa, Richard A

2007-04-01

BBC Internet survey participants (119,733 men and 98,462 women) chose from a list of 23 traits those they considered first, second, and third most important in a relationship partner. Across all participants, the traits ranked most important were: intelligence, humor, honesty, kindness, overall good looks, face attractiveness, values, communication skills, and dependability. On average, men ranked good looks and facial attractiveness more important than women did (d = 0.55 and 0.36, respectively), whereas women ranked honesty, humor, kindness, and dependability more important than men did (ds = 0.23, 0.22, 0.18, and 0.15). Sexual orientation differences were smaller than sex differences in trait rankings, but some were meaningful; for example, heterosexual more than homosexual participants assigned importance to religion, fondness for children, and parenting abilities. Multidimensional scaling analyses showed that trait preference profiles clustered by participant sex, not by sexual orientation, and by sex more than by nationality. Sex-by-nation ANOVAs of individuals' trait rankings showed that sex differences in rankings of attractiveness, but not of character traits, were extremely consistent across 53 nations and that nation main effects and sex-by-nation interactions were stronger for character traits than for physical attractiveness. United Nations indices of gender equality correlated, across nations, with men's and women's rankings of character traits but not with their rankings of physical attractiveness. These results suggest that cultural factors had a relatively greater impact on men's and women's rankings of character traits, whereas biological factors had a relatively greater impact on men's and women's rankings of physical attractiveness.

Web Image Search Re-ranking with Click-based Similarity and Typicality.

PubMed

Yang, Xiaopeng; Mei, Tao; Zhang, Yong Dong; Liu, Jie; Satoh, Shin'ichi

2016-07-20

In image search re-ranking, besides the well known semantic gap, intent gap, which is the gap between the representation of users' query/demand and the real intent of the users, is becoming a major problem restricting the development of image retrieval. To reduce human effects, in this paper, we use image click-through data, which can be viewed as the "implicit feedback" from users, to help overcome the intention gap, and further improve the image search performance. Generally, the hypothesis visually similar images should be close in a ranking list and the strategy images with higher relevance should be ranked higher than others are widely accepted. To obtain satisfying search results, thus, image similarity and the level of relevance typicality are determinate factors correspondingly. However, when measuring image similarity and typicality, conventional re-ranking approaches only consider visual information and initial ranks of images, while overlooking the influence of click-through data. This paper presents a novel re-ranking approach, named spectral clustering re-ranking with click-based similarity and typicality (SCCST). First, to learn an appropriate similarity measurement, we propose click-based multi-feature similarity learning algorithm (CMSL), which conducts metric learning based on clickbased triplets selection, and integrates multiple features into a unified similarity space via multiple kernel learning. Then based on the learnt click-based image similarity measure, we conduct spectral clustering to group visually and semantically similar images into same clusters, and get the final re-rank list by calculating click-based clusters typicality and withinclusters click-based image typicality in descending order. Our experiments conducted on two real-world query-image datasets with diverse representative queries show that our proposed reranking approach can significantly improve initial search results, and outperform several existing re-ranking approaches.

Effects of parceling on model selection: Parcel-allocation variability in model ranking.

PubMed

Sterba, Sonya K; Rights, Jason D

2017-03-01

Research interest often lies in comparing structural model specifications implying different relationships among latent factors. In this context parceling is commonly accepted, assuming the item-level measurement structure is well known and, conservatively, assuming items are unidimensional in the population. Under these assumptions, researchers compare competing structural models, each specified using the same parcel-level measurement model. However, little is known about consequences of parceling for model selection in this context-including whether and when model ranking could vary across alternative item-to-parcel allocations within-sample. This article first provides a theoretical framework that predicts the occurrence of parcel-allocation variability (PAV) in model selection index values and its consequences for PAV in ranking of competing structural models. These predictions are then investigated via simulation. We show that conditions known to manifest PAV in absolute fit of a single model may or may not manifest PAV in model ranking. Thus, one cannot assume that low PAV in absolute fit implies a lack of PAV in ranking, and vice versa. PAV in ranking is shown to occur under a variety of conditions, including large samples. To provide an empirically supported strategy for selecting a model when PAV in ranking exists, we draw on relationships between structural model rankings in parcel- versus item-solutions. This strategy employs the across-allocation modal ranking. We developed software tools for implementing this strategy in practice, and illustrate them with an example. Even if a researcher has substantive reason to prefer one particular allocation, investigating PAV in ranking within-sample still provides an informative sensitivity analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Mining User Dwell Time for Personalized Web Search Re-Ranking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Songhua; Jiang, Hao; Lau, Francis

We propose a personalized re-ranking algorithm through mining user dwell times derived from a user's previously online reading or browsing activities. We acquire document level user dwell times via a customized web browser, from which we then infer conceptword level user dwell times in order to understand a user's personal interest. According to the estimated concept word level user dwell times, our algorithm can estimate a user's potential dwell time over a new document, based on which personalized webpage re-ranking can be carried out. We compare the rankings produced by our algorithm with rankings generated by popular commercial search enginesmore » and a recently proposed personalized ranking algorithm. The results clearly show the superiority of our method. In this paper, we propose a new personalized webpage ranking algorithmthrough mining dwell times of a user. We introduce a quantitative model to derive concept word level user dwell times from the observed document level user dwell times. Once we have inferred a user's interest over the set of concept words the user has encountered in previous readings, we can then predict the user's potential dwell time over a new document. Such predicted user dwell time allows us to carry out personalized webpage re-ranking. To explore the effectiveness of our algorithm, we measured the performance of our algorithm under two conditions - one with a relatively limited amount of user dwell time data and the other with a doubled amount. Both evaluation cases put our algorithm for generating personalized webpage rankings to satisfy a user's personal preference ahead of those by Google, Yahoo!, and Bing, as well as a recent personalized webpage ranking algorithm.« less

A Study of Consistency in Design Selection and the Rank Ordering of Alternatives Using a Value Driven Design Approach

NASA Astrophysics Data System (ADS)

Subramanian, Tenkasi R.

In the current day, with the rapid advancement in technology, engineering design is growing in complexity. Nowadays, engineers have to deal with design problems that are large, complex and involving multi-level decision analyses. With the increase in complexity and size of systems, the production and development cost tend to overshoot the allocated budget and resources. This often results in project delays and project cancellation. This is particularly true for aerospace systems. Value Driven Design proves to be means to strengthen the design process and help counter such trends. Value Driven is a novel framework for optimization which puts stakeholder preferences at the forefront of the design process to capture their true preferences to present system alternatives that are consistent the stakeholder's expectations. Traditional systems engineering techniques promote communication of stakeholder preferences in the form of requirements which confines the design space by imposing additional constraints on it. This results in a design that does not capture the true preferences of the stakeholder. Value Driven Design provides an alternate approach to design wherein a value function is created that corresponds to the true preferences of the stakeholder. The applicability of VDD broad, but it is imperative to first explore its feasibility to ensure the development of an efficient, robust and elegant system design. The key to understanding the usability of VDD is to investigate the formation, propagation and use of a value function. This research investigates the use of rank correlation metrics to ensure consistent rank ordering of design alternatives, while investigating the fidelity of the value function. The impact of design uncertainties on rank ordering. A satellite design system consisting of a satellite, ground station and launch vehicle is used to demonstrate the use of the metrics to aid in decision support during the design process.

A risk assessment framework for assessing metallic nanomaterials of environmental concern: aquatic exposure and behavior.

PubMed

O'Brien, Niall Joseph; Cummins, Enda J

2011-05-01

Nanomaterials are finding application in many different environmentally relevant products and processes due to enhanced catalytic, antimicrobial, and oxidative properties of materials at this scale. As the market share of nano-functionalized products increases, so too does the potential for environmental exposure and contamination. This study presents some exposure ranking methods that consider potential metallic nanomaterial surface water exposure and fate, due to nano-functionalized products, through a number of exposure pathways. These methods take into account the limited and disparate data currently available for metallic nanomaterials and apply variability and uncertainty principles, together with qualitative risk assessment principles, to develop a scientific ranking. Three exposure scenarios with three different nanomaterials were considered to demonstrate these assessment methods: photo-catalytic exterior paint (nano-scale TiO₂), antimicrobial food packaging (nano-scale Ag), and particulate-reducing diesel fuel additives (nano-scale CeO₂). Data and hypotheses from literature relating to metallic nanomaterial aquatic behavior (including the behavior of materials that may relate to nanomaterials in aquatic environments, e.g., metals, pesticides, surfactants) were used together with commercial nanomaterial characteristics and Irish natural aquatic environment characteristics to rank the potential concentrations, transport, and persistence behaviors within subjective categories. These methods, and the applied scenarios, reveal where data critical to estimating exposure and risk are lacking. As research into the behavior of metallic nanomaterials in different environments emerges, the influence of material and environmental characteristics on nanomaterial behavior within these exposure- and risk-ranking methods may be redefined on a quantitative basis. © 2010 Society for Risk Analysis.

The personal interview: assessing the potential for personality similarity to bias the selection of orthopaedic residents.

PubMed

Quintero, Andres J; Segal, Lee S; King, Tonya S; Black, Kevin P

2009-10-01

The selection of medical students for training in orthopaedic surgery consists of an objective screening of cognitive skills to secure interviews for the brightest candidates, followed by subjective measures of candidates to confirm whether applicants are worthy of further consideration. The personal interview and its potential biased impact on the orthopaedic workforce were evaluated. During 2004-2006 at the Penn State College of Medicine, the authors performed a prospective cohort study in which 30 consenting interviewers and 135 interviewees completed the Myers-Briggs Type Indicator before the interviews. Completed surveys were evaluated after submitting the resident selection list to the National Residency Matching Program, and candidate rankings based solely on the personal interview were analyzed. Clinicians ranked candidates more favorably when they shared certain personality preferences (P = .044) and when they shared the preference groupings of the quadrant extrovert-sensing and either the function pair sensing-thinking (P = .007) or the temperament sensing-judging (P = .003), or the function pair sensing-feeling and the temperament sensing-judging (P = .029). No associations existed between personality preferences and interviewee rankings performed by basic scientists and resident interviewers. The results support the hypothesis that, within the department studied, there was a significant association between similarities in personality type and the rankings that individual faculty interviewers assigned to applicants at the completion of each interview session. The authors believe that it is important for the faculty member to recognize that this tendency exists. Finally, promoting diversity within the admission committee may foster a diverse resident body and orthopaedic workforce.

Why do some women prefer submissive men? Hierarchically disparate couples reach higher reproductive success in European urban humans.

PubMed

Jozifkova, Eva; Konvicka, Martin; Flegr, Jaroslav

2014-01-01

Equality between partners is considering a feature of the functional partnerships in westernized societies. However, the evolutionary consequences of how in-pair hierarchy influences reproduction are less known. Attraction of some high-ranking women towards low-ranking men represents a puzzle. Young urban adults (120 men, 171 women) filled out a questionnaire focused on their sexual preference for higher or lower ranking partners, their future in-pair hierarchy, and hierarchy between their parents. Human pairs with a hierarchic disparity between partners conceive more offspring than pairs of equally-ranking individuals, who, in turn, conceive more offspring than pairs of two dominating partners. Importantly, the higher reproductive success of hierarchically disparate pairs holds, regardless of which sex, male or female, is the dominant one. In addition, the subjects preferring hierarchy disparity in partnerships were with greater probability sexually aroused by such disparity, suggesting that both the partnership preference and the triggers of sexual arousal may reflect a mating strategy. These results challenge the frequently held belief in within-pair equality as a trademark of functional partnerships. It rather appears that existence of some disparity improves within-pair cohesion, facilitating both cooperation between partners and improving the pairs' ability to face societal challenges. The parallel existence of submissivity-dominance hierarchies within human sexes allows for the parallel existence of alternative reproductive strategies, and may form a background for the diversity of mating systems observed in human societies. Arousal of overemphasized dominance/submissiveness may explain sadomasochistic sex, still little understood from the evolutionary psychology point of view.

Geographically Modified PageRank Algorithms: Identifying the Spatial Concentration of Human Movement in a Geospatial Network.

PubMed

Chin, Wei-Chien-Benny; Wen, Tzai-Hung

2015-01-01

A network approach, which simplifies geographic settings as a form of nodes and links, emphasizes the connectivity and relationships of spatial features. Topological networks of spatial features are used to explore geographical connectivity and structures. The PageRank algorithm, a network metric, is often used to help identify important locations where people or automobiles concentrate in the geographical literature. However, geographic considerations, including proximity and location attractiveness, are ignored in most network metrics. The objective of the present study is to propose two geographically modified PageRank algorithms-Distance-Decay PageRank (DDPR) and Geographical PageRank (GPR)-that incorporate geographic considerations into PageRank algorithms to identify the spatial concentration of human movement in a geospatial network. Our findings indicate that in both intercity and within-city settings the proposed algorithms more effectively capture the spatial locations where people reside than traditional commonly-used network metrics. In comparing location attractiveness and distance decay, we conclude that the concentration of human movement is largely determined by the distance decay. This implies that geographic proximity remains a key factor in human mobility.

Image Re-Ranking Based on Topic Diversity.

PubMed

Qian, Xueming; Lu, Dan; Wang, Yaxiong; Zhu, Li; Tang, Yuan Yan; Wang, Meng

2017-08-01

Social media sharing Websites allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval. Tag-based image search is an important method to find images shared by users in social networks. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a topic diverse ranking approach for tag-based image retrieval with the consideration of promoting the topic coverage performance. First, we construct a tag graph based on the similarity between each tag. Then, the community detection method is conducted to mine the topic community of each tag. After that, inter-community and intra-community ranking are introduced to obtain the final retrieved results. In the inter-community ranking process, an adaptive random walk model is employed to rank the community based on the multi-information of each topic community. Besides, we build an inverted index structure for images to accelerate the searching process. Experimental results on Flickr data set and NUS-Wide data sets show the effectiveness of the proposed approach.

Sparse subspace clustering for data with missing entries and high-rank matrix completion.

PubMed

Fan, Jicong; Chow, Tommy W S

2017-09-01

Many methods have recently been proposed for subspace clustering, but they are often unable to handle incomplete data because of missing entries. Using matrix completion methods to recover missing entries is a common way to solve the problem. Conventional matrix completion methods require that the matrix should be of low-rank intrinsically, but most matrices are of high-rank or even full-rank in practice, especially when the number of subspaces is large. In this paper, a new method called Sparse Representation with Missing Entries and Matrix Completion is proposed to solve the problems of incomplete-data subspace clustering and high-rank matrix completion. The proposed algorithm alternately computes the matrix of sparse representation coefficients and recovers the missing entries of a data matrix. The proposed algorithm recovers missing entries through minimizing the representation coefficients, representation errors, and matrix rank. Thorough experimental study and comparative analysis based on synthetic data and natural images were conducted. The presented results demonstrate that the proposed algorithm is more effective in subspace clustering and matrix completion compared with other existing methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Substantial injuries influence ranking position in young elite athletes of athletics, cross-country skiing and orienteering.

PubMed

von Rosen, P; Heijne, A

2018-04-01

The relationship between injury and performance in young athletes is scarcely studied. The aim of this study was therefore to explore the association between injury prevalence and ranking position among adolescent elite athletes. One hundred and sixty-two male and female adolescent elite athletes (age range 15-19), competing in athletics (n = 59), cross-country skiing (n = 66), and orienteering (n = 37), were monitored weekly over 22-47 weeks using a web-based injury questionnaire. Ranking lists were collected. A significant (P = .003) difference was found in the seasonal substantial injury prevalence across the ranked athletes over the season, where the top-ranked (median 3.6%, 25-75th percentiles 0%-14.3%) and middle-ranked athletes (median 2.3%, 25-75th percentiles 0%-10.0%) had a lower substantial injury prevalence compared to the low-ranked athletes (median 11.3%, 25-75th percentiles 2.5%-27.1%), during both preseason (P = .002) and competitive season (P = .031). Athletes who improved their ranking position (51%, n = 51) reported a lower substantial injury prevalence (median 0%, 25-75th percentiles 0%-10.0%) compared to those who decreased (49%, n = 49) their ranking position (md 6.7%, 25-75th percentiles 0%-22.5%). In the top-ranked group, no athlete reported substantial injury more than 40% of all data collection time points compared to 9.6% (n = 5) in the middle-ranked, and 17.3% (n = 9) in the low-ranked group. Our results provide supporting evidence that substantial injuries, such as acute and overuse injuries leading to moderate or severe reductions in training or sports performance, influence ranking position in adolescent elite athletes. The findings are crucial to stakeholders involved in adolescent elite sports and support the value of designing effective preventive interventions for substantial injuries. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Aesculin modulates bone metabolism by suppressing receptor activator of NF-κB ligand (RANKL)-induced osteoclastogenesis and transduction signals.

PubMed

Zhao, Xiao-Li; Chen, Lin-Feng; Wang, Zhen

2017-06-17

Aesculin (AES), a coumarin compound derived from Aesculus hippocasanum L, is reported to exert protective role against inflammatory diseases, gastric disease and cancer. However, direct effect of AES in bone metabolism is deficient. In this study, we examined the effects of AES on osteoclast (OC) differentiation in receptor activator of NF-κB ligand (RANKL)-induced RAW264.7 cells. AES inhibits the OC differentiation in both dose- and time-dependent manner within non-toxic concentrations, as analyzed by Tartrate Resistant Acid Phosphatase (TRAP) staining. The actin ring formation manifesting OC function is also decreased by AES. Moreover, expressions of osteoclastogenesis related genes Trap, Atp6v0d2, Cathepsin K and Mmp-9 are decreased upon AES treatment. Mechanistically, AES attenuates the activation of MAPKs and NF-κB activity upon RANKL induction, thus leading to the reduction of Nfatc1 mRNA expression. Moreover, AES inhibits Rank expression, and RANK overexpression markedly decreases AES's effect on OC differentiation and NF-κB activity. Consistently, AES protects against bone mass loss in the ovariectomized and dexamethasone treated rat osteoporosis model. Taken together, our data demonstrate that AES can modulate bone metabolism by suppressing osteoclastogenesis and related transduction signals. AES therefore could be a promising agent for the treatment of osteoporosis. Copyright © 2017 Elsevier Inc. All rights reserved.

Effects of Imide-Orthoborate Dual-Salt Mixtures in Organic Carbonate Electrolytes on the Stability of Lithium Metal Batteries.

PubMed

Li, Xing; Zheng, Jianming; Engelhard, Mark H; Mei, Donghai; Li, Qiuyan; Jiao, Shuhong; Liu, Ning; Zhao, Wengao; Zhang, Ji-Guang; Xu, Wu

2018-01-24

The effects of lithium imide and lithium orthoborate dual-salt electrolytes of different salt chemistries in carbonate solvents on the cycling stability of lithium (Li) metal batteries are systematically and comparatively investigated. Two imide salts (LiTFSI and LiFSI) and two orthoborate salts (LiBOB and LiDFOB) are chosen for this study and compared with the conventional LiPF 6 salt. Density functional theory calculations indicate that the chemical and electrochemical stabilities rank in the following order: LiTFSI-LiBOB > LiTFSI-LiDFOB > LiFSI-LiDFOB > LiFSI-LiBOB. The experimental cycling stability of the Li metal batteries with the electrolytes ranks in the following order: LiTFSI-LiBOB > LiTFSI-LiDFOB > LiFSI-LiDFOB > LiPF 6 > LiFSI-LiBOB, which is in well accordance with the calculation results. The LiTFSI-LiBOB can effectively protect the Al substrate and form a more robust surface film on Li metal anode, while the LiFSI-LiBOB results in serious corrosion to the stainless steel cell case and a thicker and looser surface film on Li anode. The key findings of this work emphasize that the salt chemistry is critically important for enhancing the interfacial stability of Li metal anode and should be carefully manipulated in the development of high-performance Li metal batteries.

The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections

PubMed Central

Epstein, Robert; Robertson, Ronald E.

2015-01-01

Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. Here we report the results of five relevant double-blind, randomized controlled experiments, using a total of 4,556 undecided voters representing diverse demographic characteristics of the voting populations of the United States and India. The fifth experiment is especially notable in that it was conducted with eligible voters throughout India in the midst of India’s 2014 Lok Sabha elections just before the final votes were cast. The results of these experiments demonstrate that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) search ranking bias can be masked so that people show no awareness of the manipulation. We call this type of influence, which might be applicable to a variety of attitudes and beliefs, the search engine manipulation effect. Given that many elections are won by small margins, our results suggest that a search engine company has the power to influence the results of a substantial number of elections with impunity. The impact of such manipulations would be especially large in countries dominated by a single search engine company. PMID:26243876

The search engine manipulation effect (SEME) and its possible impact on the outcomes of elections.

PubMed

Epstein, Robert; Robertson, Ronald E

2015-08-18

Internet search rankings have a significant impact on consumer choices, mainly because users trust and choose higher-ranked results more than lower-ranked results. Given the apparent power of search rankings, we asked whether they could be manipulated to alter the preferences of undecided voters in democratic elections. Here we report the results of five relevant double-blind, randomized controlled experiments, using a total of 4,556 undecided voters representing diverse demographic characteristics of the voting populations of the United States and India. The fifth experiment is especially notable in that it was conducted with eligible voters throughout India in the midst of India's 2014 Lok Sabha elections just before the final votes were cast. The results of these experiments demonstrate that (i) biased search rankings can shift the voting preferences of undecided voters by 20% or more, (ii) the shift can be much higher in some demographic groups, and (iii) search ranking bias can be masked so that people show no awareness of the manipulation. We call this type of influence, which might be applicable to a variety of attitudes and beliefs, the search engine manipulation effect. Given that many elections are won by small margins, our results suggest that a search engine company has the power to influence the results of a substantial number of elections with impunity. The impact of such manipulations would be especially large in countries dominated by a single search engine company.

Structural Analysis of PTM Hotspots (SAPH-ire)--A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families.

PubMed

Dewhurst, Henry M; Choudhury, Shilpa; Torres, Matthew P

2015-08-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)--a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits--conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit-N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

The impact of tiered physician networks on patient choices.

PubMed

Sinaiko, Anna D; Rosenthal, Meredith B

2014-08-01

To assess whether patient choice of physician or health plan was affected by physician tier-rankings. Administrative claims and enrollment data on 171,581 nonelderly beneficiaries enrolled in Massachusetts Group Insurance Commission health plans that include a tiered physician network and who had an office visit with a tiered physician. We estimate the impact of tier-rankings on physician market share within a plan of new patients and on the percent of a physician's patients who switch to other physicians with fixed effects regression models. The effect of tiering on consumer plan choice is estimated using logistic regression and a pre-post study design. Physicians in the bottom (least-preferred) tier, particularly certain specialist physicians, had lower market share of new patient visits than physicians with higher tier-rankings. Patients whose physician was in the bottom tier were more likely to switch health plans. There was no effect of tier-ranking on patients switching away from physicians whom they have seen previously. The effect of tiering appears to be among patients who choose new physicians and at the lower end of the distribution of tiered physicians, rather than moving patients to the "best" performers. These findings suggest strong loyalty of patients to physicians more likely to be considered their personal doctor. © Health Research and Educational Trust.

Knockouts of high-ranking males have limited impact on baboon social networks.

PubMed

Franz, Mathias; Altmann, Jeanne; Alberts, Susan C

Social network structures can crucially impact complex social processes such as collective behaviour or the transmission of information and diseases. However, currently it is poorly understood how social networks change over time. Previous studies on primates suggest that `knockouts' (due to death or dispersal) of high-ranking individuals might be important drivers for structural changes in animal social networks. Here we test this hypothesis using long-term data on a natural population of baboons, examining the effects of 29 natural knockouts of alpha or beta males on adult female social networks. We investigated whether and how knockouts affected (1) changes in grooming and association rates among adult females, and (2) changes in mean degree and global clustering coefficient in these networks. The only significant effect that we found was a decrease in mean degree in grooming networks in the first month after knockouts, but this decrease was rather small, and grooming networks rebounded to baseline levels by the second month after knockouts. Taken together our results indicate that the removal of high-ranking males has only limited or no lasting effects on social networks of adult female baboons. This finding calls into question the hypothesis that the removal of high-ranking individuals has a destabilizing effect on social network structures in social animals.

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

NASA Astrophysics Data System (ADS)

da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2018-01-01

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Sense and simplicity in HADDOCK scoring: Lessons from CASP‐CAPRI round 1

PubMed Central

Vangone, A.; Rodrigues, J. P. G. L. M.; Xue, L. C.; van Zundert, G. C. P.; Geng, C.; Kurkcuoglu, Z.; Nellen, M.; Narasimhan, S.; Karaca, E.; van Dijk, M.; Melquiond, A. S. J.; Visscher, K. M.; Trellet, M.; Kastritis, P. L.

2016-01-01

ABSTRACT Our information‐driven docking approach HADDOCK is a consistent top predictor and scorer since the start of its participation in the CAPRI community‐wide experiment. This sustained performance is due, in part, to its ability to integrate experimental data and/or bioinformatics information into the modelling process, and also to the overall robustness of the scoring function used to assess and rank the predictions. In the CASP‐CAPRI Round 1 scoring experiment we successfully selected acceptable/medium quality models for 18/14 of the 25 targets – a top‐ranking performance among all scorers. Considering that for only 20 targets acceptable models were generated by the community, our effective success rate reaches as high as 90% (18/20). This was achieved using the standard HADDOCK scoring function, which, thirteen years after its original publication, still consists of a simple linear combination of intermolecular van der Waals and Coulomb electrostatics energies and an empirically derived desolvation energy term. Despite its simplicity, this scoring function makes sense from a physico‐chemical perspective, encoding key aspects of biomolecular recognition. In addition to its success in the scoring experiment, the HADDOCK server takes the first place in the server prediction category, with 16 successful predictions. Much like our scoring protocol, because of the limited time per target, the predictions relied mainly on either an ab initio center‐of‐mass and symmetry restrained protocol, or on a template‐based approach whenever applicable. These results underline the success of our simple but sensible prediction and scoring scheme. Proteins 2017; 85:417–423. © 2016 Wiley Periodicals, Inc. PMID:27802573

75 FR 43500 - Privacy Act of 1974; System of Records

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-26

... effective on August 25, 2010, unless comments are received that would result in a contrary determination... name, rank, Social Security Number (SSN), designator, address and signature. The system manager may... Integrity Drive, Millington, TN 38055-0000. Requests should contain full name, rank, Social Security Number...

Design for the sacubitril/valsartan (LCZ696) compared with enalapril study of pediatric patients with heart failure due to systemic left ventricle systolic dysfunction (PANORAMA-HF study).

PubMed

Shaddy, Robert; Canter, Charles; Halnon, Nancy; Kochilas, Lazaros; Rossano, Joseph; Bonnet, Damien; Bush, Christopher; Zhao, Ziqiang; Kantor, Paul; Burch, Michael; Chen, Fabian

2017-11-01

Sacubitril/valsartan (LCZ696) is an angiotensin receptor neprilysin inhibitor approved for the treatment of adult heart failure (HF); however, the benefit of sacubitril/valsartan in pediatric HF patients is unknown. This global multi-center study will use an adaptive, seamless two-part design. Part 1 will assess the pharmacokinetics/pharmacodynamics of single ascending doses of sacubitril/valsartan in pediatric (1 month to <18 years) HF patients with systemic left ventricle and reduced left ventricular systolic function stratified into 3 age groups (Group 1: 6 to <18 years; Group 2: 1 to <6 years; Group 3: 1 month to <1 year). Part 2 is a 52-week, efficacy and safety study where 360 eligible patients will be randomized to sacubitril/valsartan or enalapril. A novel global rank primary endpoint derived by ranking patients (worst-to-best outcome) based on clinical events such as death, initiation of mechanical life support, listing for urgent heart transplant, worsening HF, measures of functional capacity (NYHA/Ross scores), and patient-reported HF symptoms will be used to assess efficacy. The PANORAMA-HF study, which will be the largest prospective pediatric HF trial conducted to date and the first to use a global rank primary endpoint, will determine whether sacubitril/valsartan is superior to enalapril for treatment of pediatric HF patients with reduced systemic left ventricular systolic function. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Urinary testosterone-metabolite levels and dominance rank in male and female bonobos (Pan paniscus).

PubMed

Sannen, Adinda; Van Elsacker, Linda; Heistermann, Michael; Eens, Marcel

2004-04-01

The correlation between testosterone (T) and dominance rank may vary among species, and is expected to become stronger as the importance of aggressive competition for rank increases. However, it may also vary among social situations within a species, showing a stronger correlation during socially unstable periods. Knowledge on this topic in great apes, especially in females, is scant. This study presents the first data on the relationship between T and dominance rank in both sexes of the bonobo ( Pan paniscus). For each period (four socially unstable and two stable ones), linear rank orders were determined and subsequently correlated with the accompanying mean urinary T-metabolite concentrations (measured as immunoreactive 5alpha-androstan-17alpha-ol-3-one). No correlation between these two variables was found for either sex among individuals during socially unstable or stable periods. Also, within an individual over the six periods, no relationship of T with rank could be demonstrated. These results suggest that either the outcomes of aggressions have no influence on T levels, or such clear outcomes appear insufficiently frequent to affect T levels over longer periods. Even during the unstable periods, the rate of aggressions was not higher than during stable periods, suggesting that frequencies of aggression have little effect on rank. Further analyses indeed demonstrated no correlation between frequencies of overall aggressions or any type of aggressive behavior separately, or rank. Perhaps factors other than the frequency of displayed aggressions alone have a marked influence on a bonobo's rank, for example, coalition partners. Overall, in bonobos, T apparently does not form a physiological reflection of social status.

Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization.

PubMed

Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R; Luo, Zhigang

2015-01-01

RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher's discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes' weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher's criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data.

Integrating evolutionary game theory into an agent-based model of ductal carcinoma in situ: Role of gap junctions in cancer progression.

PubMed

Malekian, Negin; Habibi, Jafar; Zangooei, Mohammad Hossein; Aghakhani, Hojjat

2016-11-01

There are many cells with various phenotypic behaviors in cancer interacting with each other. For example, an apoptotic cell may induce apoptosis in adjacent cells. A living cell can also protect cells from undergoing apoptosis and necrosis. These survival and death signals are propagated through interaction pathways between adjacent cells called gap junctions. The function of these signals depends on the cellular context of the cell receiving them. For instance, a receiver cell experiencing a low level of oxygen may interpret a received survival signal as an apoptosis signal. In this study, we examine the effect of these signals on tumor growth. We make an evolutionary game theory component in order to model the signal propagation through gap junctions. The game payoffs are defined as a function of cellular context. Then, the game theory component is integrated into an agent-based model of tumor growth. After that, the integrated model is applied to ductal carcinoma in situ, a type of early stage breast cancer. Different scenarios are explored to observe the impact of the gap junction communication and parameters of the game theory component on cancer progression. We compare these scenarios by using the Wilcoxon signed-rank test. The Wilcoxon signed-rank test succeeds in proving a significant difference between the tumor growth of the model before and after considering the gap junction communication. The Wilcoxon signed-rank test also proves that the tumor growth significantly depends on the oxygen threshold of turning survival signals into apoptosis. In this study, the gap junction communication is modeled by using evolutionary game theory to illustrate its role at early stage cancers such as ductal carcinoma in situ. This work indicates that the gap junction communication and the oxygen threshold of turning survival signals into apoptosis can notably affect cancer progression. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Protein-protein docking using region-based 3D Zernike descriptors

PubMed Central

2009-01-01

Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods. PMID:20003235

Protein-protein docking using region-based 3D Zernike descriptors.

PubMed

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD < or = 2.5 A) within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

Multi-modal highlight generation for sports videos using an information-theoretic excitability measure

NASA Astrophysics Data System (ADS)

Hasan, Taufiq; Bořil, Hynek; Sangwan, Abhijeet; L Hansen, John H.

2013-12-01

The ability to detect and organize `hot spots' representing areas of excitement within video streams is a challenging research problem when techniques rely exclusively on video content. A generic method for sports video highlight selection is presented in this study which leverages both video/image structure as well as audio/speech properties. Processing begins where the video is partitioned into small segments and several multi-modal features are extracted from each segment. Excitability is computed based on the likelihood of the segmental features residing in certain regions of their joint probability density function space which are considered both exciting and rare. The proposed measure is used to rank order the partitioned segments to compress the overall video sequence and produce a contiguous set of highlights. Experiments are performed on baseball videos based on signal processing advancements for excitement assessment in the commentators' speech, audio energy, slow motion replay, scene cut density, and motion activity as features. Detailed analysis on correlation between user excitability and various speech production parameters is conducted and an effective scheme is designed to estimate the excitement level of commentator's speech from the sports videos. Subjective evaluation of excitability and ranking of video segments demonstrate a higher correlation with the proposed measure compared to well-established techniques indicating the effectiveness of the overall approach.

Exploratory analysis of normative performance on the UCSD Performance-Based Skills Assessment-Brief.

PubMed

Vella, Lea; Patterson, Thomas L; Harvey, Philip D; McClure, Margaret McNamara; Mausbach, Brent T; Taylor, Michael J; Twamley, Elizabeth W

2017-10-01

The UCSD Performance-Based Skills Assessment (UPSA) is a performance-based measure of functional capacity. The brief, two-domain (finance and communication ability) version of the assessment (UPSA-B) is now widely used in both clinical research and treatment trials. To date, research has not examined possible demographic-UPSA-B relationships within a non-psychiatric population. We aimed to produce and describe preliminary normative scores for the UPSA-B over a full range of ages and educational attainment. The finance and communication subscales of the UPSA were administered to 190 healthy participants in the context of three separate studies. These data were combined to examine the effects of age, sex, and educational attainment on the UPSA-B domain and total scores. Fractional polynomial regression was used to compute demographically-corrected T-scores for the UPSA-B total score, and percentile rank conversion was used for the two subscales. Age and education both had significant non-linear effects on the UPSA-B total score. The finance subscale was significantly related to both gender and years of education, whereas the communication subscale was not significantly related to any of the demographic characteristics. Demographically corrected T-scores and percentile ranks for UPSA-B scores are now available for use in clinical research. Published by Elsevier B.V.

Prophylactic Bracing Has No Effect on Lower Extremity Alignment or Functional Performance.

PubMed

Hueber, Garrett A; Hall, Emily A; Sage, Brad W; Docherty, Carrie L

2017-07-01

Prophylactic ankle bracing is commonly used during physical activity. Understanding how bracing affects body mechanics is critically important when discussing both injury prevention and sport performance. The purpose is to determine if ankle bracing affects lower extremity mechanics during the Landing Error Scoring System test (LESS) and Sage Sway Index (SSI). Thirty physically active participants volunteered for this study. Participants completed the LESS and SSI in both a braced and unsupported conditions. Total errors were recorded for the LESS. Total errors and time (seconds) were recorded for the SSI. The Wilcoxon signed-rank test was utilized to evaluate any differences between the brace conditions for each dependent variable. A priori alpha level was set at p<0.05. The Wilcoxon signed-rank test yielded no significant difference between the braced and unsupported conditions for the LESS (Z=-0.35, p=0.72), SSI time (Z=-0.36, p=0.72), or SSI Errors (Z=-0.37, p=0.71). Ankle braces had no effect on subjective clinical assessments of lower extremity alignment or postural stability. Utilization of a prophylactic support at the ankle did not substantially alter the proximal components of the lower kinetic chain. © Georg Thieme Verlag KG Stuttgart · New York.

On comparison of net survival curves.

PubMed

Pavlič, Klemen; Perme, Maja Pohar

2017-05-02

Relative survival analysis is a subfield of survival analysis where competing risks data are observed, but the causes of death are unknown. A first step in the analysis of such data is usually the estimation of a net survival curve, possibly followed by regression modelling. Recently, a log-rank type test for comparison of net survival curves has been introduced and the goal of this paper is to explore its properties and put this methodological advance into the context of the field. We build on the association between the log-rank test and the univariate or stratified Cox model and show the analogy in the relative survival setting. We study the properties of the methods using both the theoretical arguments as well as simulations. We provide an R function to enable practical usage of the log-rank type test. Both the log-rank type test and its model alternatives perform satisfactory under the null, even if the correlation between their p-values is rather low, implying that both approaches cannot be used simultaneously. The stratified version has a higher power in case of non-homogeneous hazards, but also carries a different interpretation. The log-rank type test and its stratified version can be interpreted in the same way as the results of an analogous semi-parametric additive regression model despite the fact that no direct theoretical link can be established between the test statistics.

Langerhans cell precursors acquire RANK/CD265 in prenatal human skin.

PubMed

Schöppl, Alice; Botta, Albert; Prior, Marion; Akgün, Johnnie; Schuster, Christopher; Elbe-Bürger, Adelheid

2015-01-01

The skin is the first barrier against foreign pathogens and the prenatal formation of a strong network of various innate and adaptive cells is required to protect the newborn from perinatal infections. While many studies about the immune system in healthy and diseased adult human skin exist, our knowledge about the cutaneous prenatal/developing immune system and especially about the phenotype and function of antigen-presenting cells such as epidermal Langerhans cells (LCs) in human skin is still scarce. It has been shown previously that LCs in healthy adult human skin express receptor activator of NF-κB (RANK), an important molecule prolonging their survival. In this study, we investigated at which developmental stage LCs acquire this important molecule. Immunofluorescence double-labeling of cryostat sections revealed that LC precursors in prenatal human skin either do not yet [10-11 weeks of estimated gestational age (EGA)] or only faintly (13-15 weeks EGA) express RANK. LCs express RANK at levels comparable to adult LCs by the end of the second trimester. Comparable with adult skin, dermal antigen-presenting cells at no gestational age express this marker. These findings indicate that epidermal leukocytes gradually acquire RANK during gestation - a phenomenon previously observed also for other markers on LCs in prenatal human skin. Copyright © 2015 The Authors. Published by Elsevier GmbH.. All rights reserved.

Ranking of predictor variables based on effect size criterion provides an accurate means of automatically classifying opinion column articles

NASA Astrophysics Data System (ADS)

Legara, Erika Fille; Monterola, Christopher; Abundo, Cheryl

2011-01-01

We demonstrate an accurate procedure based on linear discriminant analysis that allows automatic authorship classification of opinion column articles. First, we extract the following stylometric features of 157 column articles from four authors: statistics on high frequency words, number of words per sentence, and number of sentences per paragraph. Then, by systematically ranking these features based on an effect size criterion, we show that we can achieve an average classification accuracy of 93% for the test set. In comparison, frequency size based ranking has an average accuracy of 80%. The highest possible average classification accuracy of our data merely relying on chance is ∼31%. By carrying out sensitivity analysis, we show that the effect size criterion is superior than frequency ranking because there exist low frequency words that significantly contribute to successful author discrimination. Consistent results are seen when the procedure is applied in classifying the undisputed Federalist papers of Alexander Hamilton and James Madison. To the best of our knowledge, the work is the first attempt in classifying opinion column articles, that by virtue of being shorter in length (as compared to novels or short stories), are more prone to over-fitting issues. The near perfect classification for the longer papers supports this claim. Our results provide an important insight on authorship attribution that has been overlooked in previous studies: that ranking discriminant variables based on word frequency counts is not necessarily an optimal procedure.

Ranking in evolving complex networks

NASA Astrophysics Data System (ADS)

Liao, Hao; Mariani, Manuel Sebastian; Medo, Matúš; Zhang, Yi-Cheng; Zhou, Ming-Yang

2017-05-01

Complex networks have emerged as a simple yet powerful framework to represent and analyze a wide range of complex systems. The problem of ranking the nodes and the edges in complex networks is critical for a broad range of real-world problems because it affects how we access online information and products, how success and talent are evaluated in human activities, and how scarce resources are allocated by companies and policymakers, among others. This calls for a deep understanding of how existing ranking algorithms perform, and which are their possible biases that may impair their effectiveness. Many popular ranking algorithms (such as Google's PageRank) are static in nature and, as a consequence, they exhibit important shortcomings when applied to real networks that rapidly evolve in time. At the same time, recent advances in the understanding and modeling of evolving networks have enabled the development of a wide and diverse range of ranking algorithms that take the temporal dimension into account. The aim of this review is to survey the existing ranking algorithms, both static and time-aware, and their applications to evolving networks. We emphasize both the impact of network evolution on well-established static algorithms and the benefits from including the temporal dimension for tasks such as prediction of network traffic, prediction of future links, and identification of significant nodes.

Learning to rank image tags with limited training examples.

PubMed

Songhe Feng; Zheyun Feng; Rong Jin

2015-04-01

With an increasing number of images that are available in social media, image annotation has emerged as an important research topic due to its application in image matching and retrieval. Most studies cast image annotation into a multilabel classification problem. The main shortcoming of this approach is that it requires a large number of training images with clean and complete annotations in order to learn a reliable model for tag prediction. We address this limitation by developing a novel approach that combines the strength of tag ranking with the power of matrix recovery. Instead of having to make a binary decision for each tag, our approach ranks tags in the descending order of their relevance to the given image, significantly simplifying the problem. In addition, the proposed method aggregates the prediction models for different tags into a matrix, and casts tag ranking into a matrix recovery problem. It introduces the matrix trace norm to explicitly control the model complexity, so that a reliable prediction model can be learned for tag ranking even when the tag space is large and the number of training images is limited. Experiments on multiple well-known image data sets demonstrate the effectiveness of the proposed framework for tag ranking compared with the state-of-the-art approaches for image annotation and tag ranking.

Influence of the microwave irradiation dewatering on the combustion characteristics of Chinese brown coals

NASA Astrophysics Data System (ADS)

Ge, Lichao; Feng, Hongcui; Xu, Chang; Zhang, Yanwei; Wang, Zhihua

2018-02-01

This study investigates the influence of microwave irradiation on coal composition, pore structure, coal rank, and combustion characteristics of typical brown coals in China. Results show that the upgrading process significantly decreased the inherent moisture, and increased calorific value and fixed carbon content. After upgrading, pore distribution extended to micropore region, oxygen functional groups were reduced and destroyed, and the apparent aromaticity increased suggesting an improvement in the coal rank. Based on thermogravimetric analysis, the combustion processes of upgraded coals were delayed toward the high temperature region, and the temperatures of ignition, peak and burnout increased. Based on the average combustion rate and comprehensive combustion parameter, the upgraded coals performed better compared with raw brown coals and a high rank coal. In ignition and burnout segments, the activation energy increased but exhibited a decrease in the combustion stage.