Robustness and structure of complex networks

NASA Astrophysics Data System (ADS)

Shao, Shuai

This dissertation covers the two major parts of my PhD research on statistical physics and complex networks: i) modeling a new type of attack -- localized attack, and investigating robustness of complex networks under this type of attack; ii) discovering the clustering structure in complex networks and its influence on the robustness of coupled networks. Complex networks appear in every aspect of our daily life and are widely studied in Physics, Mathematics, Biology, and Computer Science. One important property of complex networks is their robustness under attacks, which depends crucially on the nature of attacks and the structure of the networks themselves. Previous studies have focused on two types of attack: random attack and targeted attack, which, however, are insufficient to describe many real-world damages. Here we propose a new type of attack -- localized attack, and study the robustness of complex networks under this type of attack, both analytically and via simulation. On the other hand, we also study the clustering structure in the network, and its influence on the robustness of a complex network system. In the first part, we propose a theoretical framework to study the robustness of complex networks under localized attack based on percolation theory and generating function method. We investigate the percolation properties, including the critical threshold of the phase transition pc and the size of the giant component Pinfinity. We compare localized attack with random attack and find that while random regular (RR) networks are more robust against localized attack, Erdoḧs-Renyi (ER) networks are equally robust under both types of attacks. As for scale-free (SF) networks, their robustness depends crucially on the degree exponent lambda. The simulation results show perfect agreement with theoretical predictions. We also test our model on two real-world networks: a peer-to-peer computer network and an airline network, and find that the real-world networks are much more vulnerable to localized attack compared with random attack. In the second part, we extend the tree-like generating function method to incorporating clustering structure in complex networks. We study the robustness of a complex network system, especially a network of networks (NON) with clustering structure in each network. We find that the system becomes less robust as we increase the clustering coefficient of each network. For a partially dependent network system, we also find that the influence of the clustering coefficient on network robustness decreases as we decrease the coupling strength, and the critical coupling strength qc, at which the first-order phase transition changes to second-order, increases as we increase the clustering coefficient.

Periodic trends in hexanuclear actinide clusters.

PubMed

Diwu, Juan; Wang, Shuao; Albrecht-Schmitt, Thomas E

2012-04-02

Four new Th(IV), U(IV), and Np(IV) hexanuclear clusters with 1,2-phenylenediphosphonate as the bridging ligand have been prepared by self-assembly at room temperature. The structures of Th(6)Tl(3)[C(6)H(4)(PO(3))(PO(3)H)](6)(NO(3))(7)(H(2)O)(6)·(NO(3))(2)·4H(2)O (Th6-3), (NH(4))(8.11)Np(12)Rb(3.89)[C(6)H(4)(PO(3))(PO(3)H)](12)(NO(3))(24)·15H(2)O (Np6-1), (NH(4))(4)U(12)Cs(8)[C(6)H(4)(PO(3))(PO(3)H)](12)(NO(3))(24)·18H(2)O (U6-1), and (NH(4))(4)U(12)Cs(2)[C(6)H(4)(PO(3))(PO(3)H)](12)(NO(3))(18)·40H(2)O (U6-2) are described and compared with other clusters of containing An(IV) or Ce(IV). All of the clusters share the common formula M(6)(H(2)O)(m)[C(6)H(3)(PO(3))(PO(3)H)](6)(NO(3))(n)((6-n)) (M = Ce, Th, U, Np, Pu). The metal centers are normally nine-coordinate, with five oxygen atoms from the ligand and an additional four either occupied by NO(3)(-) or H(2)O. It was found that the Ce, U, and Pu clusters favor both C(3i) and C(i) point groups, while Th only yields in C(i), and Np only C(3i). In the C(3i) clusters, there are two NO(3)(-) anions bonded to the metal centers. In the C(i) clusters, the number of NO(3)(-) anions varies from 0 to 2. The change in the ionic radius of the actinide ions tunes the cavity size of the clusters. The thorium clusters were found to accept larger ions including Cs(+) and Tl(+), whereas with uranium and later elements, only NH(4)(+) and/or Rb(+) reside in the center of the clusters.

Ionization-induced star formation - IV. Triggering in bound clusters

NASA Astrophysics Data System (ADS)

Dale, J. E.; Ercolano, B.; Bonnell, I. A.

2012-12-01

We present a detailed study of star formation occurring in bound star-forming clouds under the influence of internal ionizing feedback from massive stars across a spectrum of cloud properties. We infer which objects are triggered by comparing our feedback simulations with control simulations in which no feedback was present. We find that feedback always results in a lower star formation efficiency and usually but not always results in a larger number of stars or clusters. Cluster mass functions are not strongly affected by feedback, but stellar mass functions are biased towards lower masses. Ionization also affects the geometrical distribution of stars in ways that are robust against projection effects, but may make the stellar associations more or less subclustered depending on the background cloud environment. We observe a prominent pillar in one simulation which is the remains of an accretion flow feeding the central ionizing cluster of its host cloud and suggest that this may be a general formation mechanism for pillars such as those observed in M16. We find that the association of stars with structures in the gas such as shells or pillars is a good but by no means foolproof indication that those stars have been triggered and we conclude overall that it is very difficult to deduce which objects have been induced to form and which formed spontaneously simply from observing the system at a single time.

WISC-IV Profiles Are Associated with Differences in Symptomatology and Outcome in Children with ADHD

ERIC Educational Resources Information Center

Thaler, Nicholas S.; Bello, Danielle T.; Etcoff, Lewis M.

2013-01-01

Objective: The current study investigated the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) cluster profiles of children with ADHD to examine the association between IQ profiles and diagnostic frequency, symptomatology, and outcome in this population. Method: Hierarchical cluster analysis was conducted on 189 children with a…

Mismatch of Posttraumatic Stress Disorder (PTSD) Symptoms and DSM-IV Symptom Clusters in a Cancer Sample: Exploratory Factor Analysis of the PTSD Checklist-Civilian Version

PubMed Central

Shelby, Rebecca A.; Golden-Kreutz, Deanna M.; Andersen, Barbara L.

2007-01-01

The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV; American Psychiatric Association, 1994a) conceptualization of posttraumatic stress disorder (PTSD) includes three symptom clusters: reexperiencing, avoidance/numbing, and arousal. The PTSD Checklist-Civilian Version (PCL-C) corresponds to the DSM-IV PTSD symptoms. In the current study, we conducted exploratory factor analysis (EFA) of the PCL-C with two aims: (a) to examine whether the PCL-C evidenced the three-factor solution implied by the DSM-IV symptom clusters, and (b) to identify a factor solution for the PCL-C in a cancer sample. Women (N = 148) with Stage II or III breast cancer completed the PCL-C after completion of cancer treatment. We extracted two-, three-, four-, and five-factor solutions using EFA. Our data did not support the DSM-IV PTSD symptom clusters. Instead, EFA identified a four-factor solution including reexperiencing, avoidance, numbing, and arousal factors. Four symptom items, which may be confounded with illness and cancer treatment-related symptoms, exhibited poor factor loadings. Using these symptom items in cancer samples may lead to overdiagnosis of PTSD and inflated rates of PTSD symptoms. PMID:16281232

CCD photometry of Andromeda IV - Dwarf irregular galaxy or M31 open cluster?

NASA Technical Reports Server (NTRS)

Jones, Joseph H.

1993-01-01

CCD photometry of Andromeda IV was obtained during discretionary time in August of 1989 at the Canada-France-Hawaii Telescope on Mauna Kea and the data were reduced at CFHT during the summer of 1991. And IV has been catalogued both as a dwarf galaxy and as an open star cluster in M31. The color-magnitude diagrams presented indicate that this object has a young population of stars with a narrow age range, consistent with the characteristics of an open star cluster or stellar association. A radial velocity measurement taken from the literature and analyzed with respect to the rotation curve of M31 indicates this object resides in the disk of the Andromeda Galaxy, strengthening the conclusion that it is indeed a very large open star cluster or a densely populated stellar association rather than a dwarf irregular galaxy.

Developing appropriate methods for cost-effectiveness analysis of cluster randomized trials.

PubMed

Gomes, Manuel; Ng, Edmond S-W; Grieve, Richard; Nixon, Richard; Carpenter, James; Thompson, Simon G

2012-01-01

Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering--seemingly unrelated regression (SUR) without a robust standard error (SE)--and 4 methods that recognized clustering--SUR and generalized estimating equations (GEEs), both with robust SE, a "2-stage" nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92-0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters.

Bipolar disorder with comorbid cluster B personality disorder features: impact on suicidality.

PubMed

Garno, Jessica L; Goldberg, Joseph F; Ramirez, Paul Michael; Ritzler, Barry A

2005-03-01

Because of their overlapping phenomenology and mutually chronic, persistent nature, distinctions between bipolar disorder and cluster B personality disorders remain a source of unresolved clinical controversy. The extent to which comorbid personality disorders impact course and outcome for bipolar patients also has received little systematic study. One hundred DSM-IV bipolar I (N = 73) or II (N = 27) patients consecutively underwent diagnostic evaluations with structured clinical interviews for DSM-IV Axis I and cluster B Axis II disorders, along with assessments of histories of childhood trauma or abuse. Cluster B diagnostic comorbidity was examined relative to lifetime substance abuse, suicide attempt histories, and other clinical features. Thirty percent of subjects met DSM-IV criteria for a cluster B personality disorder (17% borderline, 6% antisocial, 5% histrionic, 8% narcissistic). Cluster B diagnoses were significantly linked with histories of childhood emotional abuse (p = .009), physical abuse (p = .014), and emotional neglect (p = .022), but not sexual abuse or physical neglect. Cluster B comorbidity was associated with significantly more lifetime suicide attempts and current depression. Lifetime suicide attempts were significantly associated with cluster B comorbidity (OR = 3.195, 95% CI = 1.124 to 9.088), controlling for current depression severity, lifetime substance abuse, and past sexual or emotional abuse. Cluster B personality disorders are prevalent comorbid conditions identifiable in a substantial number of individuals with bipolar disorder, making an independent contribution to increased lifetime suicide risk.

Magnetism in Mn-nanowires and -clusters as δ-doped layers in group IV semiconductors (Si, Ge)

NASA Astrophysics Data System (ADS)

Simov, K. R.; Glans, P.-A.; Jenkins, C. A.; Liberati, M.; Reinke, P.

2018-01-01

Mn doping of group-IV semiconductors (Si/Ge) is achieved by embedding nanostructured Mn-layers in group-IV matrix. The Mn-nanostructures are monoatomic Mn-wires or Mn-clusters and capped with an amorphous Si or Ge layer. The precise fabrication of δ-doped Mn-layers is combined with element-specific detection of the magnetic signature with x-ray magnetic circular dichroism. The largest moment (2.5 μB/Mn) is measured for Mn-wires with ionic bonding character and a-Ge overlayer cap; a-Si capping reduces the moment due to variations of bonding in agreement with theoretical predictions. The moments in δ-doped layers dominated by clusters is quenched with an antiferromagnetic component from Mn-Mn bonding.

Health-related fitness profiles in adolescents with complex congenital heart disease.

PubMed

Klausen, Susanne Hwiid; Wetterslev, Jørn; Søndergaard, Lars; Andersen, Lars L; Mikkelsen, Ulla Ramer; Dideriksen, Kasper; Zoffmann, Vibeke; Moons, Philip

2015-04-01

This study investigates whether subgroups of different health-related fitness (HrF) profiles exist among girls and boys with complex congenital heart disease (ConHD) and how these are associated with lifestyle behaviors. We measured the cardiorespiratory fitness, muscle strength, and body composition of 158 adolescents aged 13-16 years with previous surgery for a complex ConHD. Data on lifestyle behaviors were collected concomitantly between October 2010 and April 2013. A cluster analysis was conducted to identify profiles with similar HrF. For comparisons between clusters, multivariate analyses of covariance were used to test the differences in lifestyle behaviors. Three distinct profiles were formed: (1) Robust (43, 27%; 20 girls and 23 boys); (2) Moderately Robust (85, 54%; 37 girls and 48 boys); and (3) Less robust (30, 19%; 9 girls and 21 boys). The participants in the Robust clusters reported leading a physically active lifestyle and participants in the Less robust cluster reported leading a sedentary lifestyle. Diagnoses were evenly distributed between clusters. The cluster analysis attributed some of the variability in cardiorespiratory fitness among adolescents with complex ConHD to lifestyle behaviors and physical activity. Profiling of HrF offers a valuable new option in the management of person-centered health promotion. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

A cluster analytic study of the Wechsler Intelligence Test for Children-IV in children referred for psychoeducational assessment due to persistent academic difficulties.

PubMed

Hale, Corinne R; Casey, Joseph E; Ricciardi, Philip W R

2014-02-01

Wechsler Intelligence Test for Children-IV core subtest scores of 472 children were cluster analyzed to determine if reliable and valid subgroups would emerge. Three subgroups were identified. Clusters were reliable across different stages of the analysis as well as across algorithms and samples. With respect to external validity, the Globally Low cluster differed from the other two clusters on Wechsler Individual Achievement Test-II Word Reading, Numerical Operations, and Spelling subtests, whereas the latter two clusters did not differ from one another. The clusters derived have been identified in studies using previous WISC editions. Clusters characterized by poor performance on subtests historically associated with the VIQ (i.e., VCI + WMI) and PIQ (i.e., POI + PSI) did not emerge, nor did a cluster characterized by low scores on PRI subtests. Picture Concepts represented the highest subtest score in every cluster, failing to vary in a predictable manner with the other PRI subtests.

Neurodevelopmental disorders: cluster 2 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Andrews, G; Pine, D S; Hobbs, M J; Anderson, T M; Sunderland, M

2009-12-01

DSM-IV and ICD-10 are atheoretical and largely descriptive. Although this achieves good reliability, the validity of diagnoses can be increased by an understanding of risk factors and other clinical features. In an effort to group mental disorders on this basis, five clusters have been proposed. We now consider the second cluster, namely neurodevelopmental disorders. We reviewed the literature in relation to 11 validating criteria proposed by a DSM-V Task Force Study Group. This cluster reflects disorders of neurodevelopment rather than a 'childhood' disorders cluster. It comprises disorders subcategorized in DSM-IV and ICD-10 as Mental Retardation; Learning, Motor, and Communication Disorders; and Pervasive Developmental Disorders. Although these disorders seem to be heterogeneous, they share similarities on some risk and clinical factors. There is evidence of a neurodevelopmental genetic phenotype, the disorders have an early emerging and continuing course, and all have salient cognitive symptoms. Within-cluster co-morbidity also supports grouping these disorders together. Other childhood disorders currently listed in DSM-IV share similarities with the Externalizing and Emotional clusters. These include Conduct Disorder, Attention Deficit Hyperactivity Disorder and Separation Anxiety Disorder. The Tic, Eating/Feeding and Elimination disorders, and Selective Mutisms were allocated to the 'Not Yet Assigned' group. Neurodevelopmental disorders meet some of the salient criteria proposed by the American Psychiatric Association (APA) to suggest a classification cluster.

Developing Appropriate Methods for Cost-Effectiveness Analysis of Cluster Randomized Trials

PubMed Central

Gomes, Manuel; Ng, Edmond S.-W.; Nixon, Richard; Carpenter, James; Thompson, Simon G.

2012-01-01

Aim. Cost-effectiveness analyses (CEAs) may use data from cluster randomized trials (CRTs), where the unit of randomization is the cluster, not the individual. However, most studies use analytical methods that ignore clustering. This article compares alternative statistical methods for accommodating clustering in CEAs of CRTs. Methods. Our simulation study compared the performance of statistical methods for CEAs of CRTs with 2 treatment arms. The study considered a method that ignored clustering—seemingly unrelated regression (SUR) without a robust standard error (SE)—and 4 methods that recognized clustering—SUR and generalized estimating equations (GEEs), both with robust SE, a “2-stage” nonparametric bootstrap (TSB) with shrinkage correction, and a multilevel model (MLM). The base case assumed CRTs with moderate numbers of balanced clusters (20 per arm) and normally distributed costs. Other scenarios included CRTs with few clusters, imbalanced cluster sizes, and skewed costs. Performance was reported as bias, root mean squared error (rMSE), and confidence interval (CI) coverage for estimating incremental net benefits (INBs). We also compared the methods in a case study. Results. Each method reported low levels of bias. Without the robust SE, SUR gave poor CI coverage (base case: 0.89 v. nominal level: 0.95). The MLM and TSB performed well in each scenario (CI coverage, 0.92–0.95). With few clusters, the GEE and SUR (with robust SE) had coverage below 0.90. In the case study, the mean INBs were similar across all methods, but ignoring clustering underestimated statistical uncertainty and the value of further research. Conclusions. MLMs and the TSB are appropriate analytical methods for CEAs of CRTs with the characteristics described. SUR and GEE are not recommended for studies with few clusters. PMID:22016450

GENETIC AND ENVIRONMENTAL CONTRIBUTIONS TO THE CO-OCCURRENCE OF DEPRESSIVE PERSONALITY DISORDER AND DSM-IV PERSONALITY DISORDERS

PubMed Central

Ørstavik, Ragnhild E.; Kendler, Kenneth S.; Røysamb, Espen; Czajkowski, Nikolai; Tambs, Kristian; Reichborn-Kjennerud, Ted

2012-01-01

One of the main controversies with regard to depressive personality disorder (DPD) concerns the co-occurrence with the established DSM-IV personality disorders (PDs). The main aim of this study was to examine to what extent DPD and the DSM-IV PDs share genetic and environmental risk factors, using multivariate twin modeling. The DSM-IV Structured Interview for Personality was applied to 2,794 young adult twins. Paranoid PD from Cluster A, borderline PD from Cluster B, and all three PDs from Cluster C were independently and significantly associated with DPD in multiple regression analysis. The genetic correlations between DPD and the other PDs were strong (.53–.83), while the environmental correlations were moderate (.36–.40). Close to 50% of the total variance in DPD was disorder specific. However, only 5% was due to disorder-specific genetic factors, indicating that a substantial part of the genetic vulnerability to DPD also increases the vulnerability to other PDs. PMID:22686231

Genetic and environmental contributions to the co-occurrence of depressive personality disorder and DSM-IV personality disorders.

PubMed

Ørstavik, Ragnhild E; Kendler, Kenneth S; Røysamb, Espen; Czajkowski, Nikolai; Tambs, Kristian; Reichborn-Kjennerud, Ted

2012-06-01

One of the main controversies with regard to depressive personality disorder (DPD) concerns the co-occurrence with the established DSM-IV personality disorders (PDs). The main aim of this study was to examine to what extent DPD and the DSM-IV PDs share genetic and environmental risk factors, using multivariate twin modeling. The DSM-IV Structured Interview for Personality was applied to 2,794 young adult twins. Paranoid PD from Cluster A, borderline PD from Cluster B, and all three PDs from Cluster C were independently and significantly associated with DPD in multiple regression analysis. The genetic correlations between DPD and the other PDs were strong (.53-.83), while the environmental correlations were moderate (.36-.40). Close to 50% of the total variance in DPD was disorder specific. However, only 5% was due to disorder-specific genetic factors, indicating that a substantial part of the genetic vulnerability to DPD also increases the vulnerability to other PDs.

Stable dissipative optical vortex clusters by inhomogeneous effective diffusion.

PubMed

Li, Huishan; Lai, Shiquan; Qui, Yunli; Zhu, Xing; Xie, Jianing; Mihalache, Dumitru; He, Yingji

2017-10-30

We numerically show the generation of robust vortex clusters embedded in a two-dimensional beam propagating in a dissipative medium described by the generic cubic-quintic complex Ginzburg-Landau equation with an inhomogeneous effective diffusion term, which is asymmetrical in the two transverse directions and periodically modulated in the longitudinal direction. We show the generation of stable optical vortex clusters for different values of the winding number (topological charge) of the input optical beam. We have found that the number of individual vortex solitons that form the robust vortex cluster is equal to the winding number of the input beam. We have obtained the relationships between the amplitudes and oscillation periods of the inhomogeneous effective diffusion and the cubic gain and diffusion (viscosity) parameters, which depict the regions of existence and stability of vortex clusters. The obtained results offer a method to form robust vortex clusters embedded in two-dimensional optical beams, and we envisage potential applications in the area of structured light.

Influence of experimental history on nicotine self-administration in squirrel monkeys.

PubMed

Desai, Rajeev I; Sullivan, Katherine A; Kohut, Stephen J; Bergman, Jack

2016-06-01

Methods for establishing robust long-term self-administration of intravenous (i.v.) nicotine, the primary psychoactive agent in tobacco, are not well-established in laboratory animals. Here, we examine the use of a fading procedure to establish robust and consistent i.v. nicotine self-administration under second-order schedule conditions in squirrel monkeys. First, self-administration behavior was developed in two groups of male squirrel monkeys using a second-order fixed-interval 5-min schedule with fixed-ratio 5 units (FI 5-min (FR5: S)). Comparable performances were maintained by i.v. cocaine (0.032 mg/kg/injection (inj); group A, n = 3) and the combination of food delivery (20-30 % condensed milk) and 0.01 mg/kg/inj i.v. nicotine (group B, n = 3). Subsequently, the concentration of condensed milk was gradually reduced to zero in the second group and self-administration behavior was maintained by i.v. nicotine alone. Next, self-administration of a range of doses of i.v. nicotine (0.001-0.032 mg/kg/inj) and, in additional experiments, the minor tobacco alkaloid anatabine (0.01-0.18 mg/kg/inj) was studied in both groups. Results show that nicotine and anatabine had reinforcing effects in both groups. However, optimal doses of nicotine and anatabine maintained significantly higher rates of i.v. self-administration behavior in subjects trained with the fading procedure than in subjects provided with a history of cocaine-maintained responding. These results illustrate conditions under which robust i.v. nicotine self-administration can be established in squirrel monkeys and the influence of prior experimental history in the expression of reinforcing effects of nicotine and anatabine.

Dissociative Amnesia and DSM-IV-TR Cluster C Personality Traits.

PubMed

Leong, Stephanie; Waits, Wendi; Diebold, Carroll

2006-01-01

Dissociative amnesia is a disorder characterized by retrospectively reported memory gaps. These gaps involve an inability to recall personal information, usually of a traumatic or stressful nature. Dissociative amnesia most commonly occurs in the presence of other psychiatric conditions, particularly personality disorders. In the literature and in clinical practice, it is often associated with DSM-IV-TR Cluster B personality disorders. However, there is evidence to suggest that dissociative amnesia may be more likely to occur among individuals with Cluster C personality disorders. Presented here is a discussion of the types of memory loss, two cases of dissociative amnesia occurring in patients with Cluster C psychopathology, and a focused literature review.

Dissociative Amnesia and DSM-IV-TR Cluster C Personality Traits

PubMed Central

Waits, Wendi; Diebold, Carroll

2006-01-01

Dissociative amnesia is a disorder characterized by retrospectively reported memory gaps. These gaps involve an inability to recall personal information, usually of a traumatic or stressful nature. Dissociative amnesia most commonly occurs in the presence of other psychiatric conditions, particularly personality disorders. In the literature and in clinical practice, it is often associated with DSM-IV-TR Cluster B personality disorders. However, there is evidence to suggest that dissociative amnesia may be more likely to occur among individuals with Cluster C personality disorders. Presented here is a discussion of the types of memory loss, two cases of dissociative amnesia occurring in patients with Cluster C psychopathology, and a focused literature review. PMID:21103150

Robust MST-Based Clustering Algorithm.

PubMed

Liu, Qidong; Zhang, Ruisheng; Zhao, Zhili; Wang, Zhenghai; Jiao, Mengyao; Wang, Guangjing

2018-06-01

Minimax similarity stresses the connectedness of points via mediating elements rather than favoring high mutual similarity. The grouping principle yields superior clustering results when mining arbitrarily-shaped clusters in data. However, it is not robust against noises and outliers in the data. There are two main problems with the grouping principle: first, a single object that is far away from all other objects defines a separate cluster, and second, two connected clusters would be regarded as two parts of one cluster. In order to solve such problems, we propose robust minimum spanning tree (MST)-based clustering algorithm in this letter. First, we separate the connected objects by applying a density-based coarsening phase, resulting in a low-rank matrix in which the element denotes the supernode by combining a set of nodes. Then a greedy method is presented to partition those supernodes through working on the low-rank matrix. Instead of removing the longest edges from MST, our algorithm groups the data set based on the minimax similarity. Finally, the assignment of all data points can be achieved through their corresponding supernodes. Experimental results on many synthetic and real-world data sets show that our algorithm consistently outperforms compared clustering algorithms.

Structure-Function Analysis of Chloroplast Proteins via Random Mutagenesis Using Error-Prone PCR.

PubMed

Dumas, Louis; Zito, Francesca; Auroy, Pascaline; Johnson, Xenie; Peltier, Gilles; Alric, Jean

2018-06-01

Site-directed mutagenesis of chloroplast genes was developed three decades ago and has greatly advanced the field of photosynthesis research. Here, we describe a new approach for generating random chloroplast gene mutants that combines error-prone polymerase chain reaction of a gene of interest with chloroplast complementation of the knockout Chlamydomonas reinhardtii mutant. As a proof of concept, we targeted a 300-bp sequence of the petD gene that encodes subunit IV of the thylakoid membrane-bound cytochrome b 6 f complex. By sequencing chloroplast transformants, we revealed 149 mutations in the 300-bp target petD sequence that resulted in 92 amino acid substitutions in the 100-residue target subunit IV sequence. Our results show that this method is suited to the study of highly hydrophobic, multisubunit, and chloroplast-encoded proteins containing cofactors such as hemes, iron-sulfur clusters, and chlorophyll pigments. Moreover, we show that mutant screening and sequencing can be used to study photosynthetic mechanisms or to probe the mutational robustness of chloroplast-encoded proteins, and we propose that this method is a valuable tool for the directed evolution of enzymes in the chloroplast. © 2018 American Society of Plant Biologists. All rights reserved.

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

Campbell, W; Miften, M; Jones, B

Purpose: Pancreatic SBRT relies on extremely accurate delivery of ablative radiation doses to the target, and intra-fractional tracking of fiducial markers can facilitate improvements in dose delivery. However, this requires algorithms that are able to find fiducial markers with high speed and accuracy. The purpose of this study was to develop a novel marker tracking algorithm that is robust against many of the common errors seen with traditional template matching techniques. Methods: Using CBCT projection images, a method was developed to create detailed template images of fiducial marker clusters without prior knowledge of the number of markers, their positions, ormore » their orientations. Briefly, the method (i) enhances markers in projection images, (ii) stabilizes the cluster’s position, (iii) reconstructs the cluster in 3D, and (iv) precomputes a set of static template images dependent on gantry angle. Furthermore, breathing data were used to produce 4D reconstructions of clusters, yielding dynamic template images dependent on gantry angle and breathing amplitude. To test these two approaches, static and dynamic templates were used to track the motion of marker clusters in more than 66,000 projection images from 75 CBCT scans of 15 pancreatic SBRT patients. Results: For both static and dynamic templates, the new technique was able to locate marker clusters present in projection images 100% of the time. The algorithm was also able to correctly locate markers in several instances where only some of the markers were visible due to insufficient field-of-view. In cases where clusters exhibited deformation and/or rotation during breathing, dynamic templates resulted in cross-correlation scores up to 70% higher than static templates. Conclusion: Patient-specific templates provided complete tracking of fiducial marker clusters in CBCT scans, and dynamic templates helped to provide higher cross-correlation scores for deforming/rotating clusters. This novel algorithm provides an extremely accurate method to detect fiducial markers during treatment. Research funding provided by Varian Medical Systems to Miften and Jones.« less

Synthesis and Molecular Structure of a Novel Compound Containing a Carbonate-Bridged Hexacalcium Cluster Cation Assembled on a Trimeric Trititanium(IV)-Substituted Wells-Dawson Polyoxometalate.

PubMed

Hoshino, Takahiro; Isobe, Rina; Kaneko, Takuya; Matsuki, Yusuke; Nomiya, Kenji

2017-08-21

A novel compound containing a hexacalcium cluster cation, one carbonate anion, and one calcium cation assembled on a trimeric trititanium(IV)-substituted Wells-Dawson polyoxometalate (POM), [{Ca 6 (CO 3 )(μ 3 -OH)(OH 2 ) 18 }(P 2 W 15 Ti 3 O 61 ) 3 Ca(OH 2 ) 3 ] 19- (Ca 7 Ti 9 Trimer), was obtained as the Na 7 Ca 6 salt (NaCa-Ca 7 Ti 9 Trimer) by the reaction of calcium chloride with the monomeric trititanium(IV)-substituted Wells-Dawson POM species "[P 2 W 15 Ti 3 O 59 (OH) 3 ] 9- " (Ti 3 Monomer). Ti 3 Monomer was generated in situ under basic conditions from the separately prepared tetrameric species with bridging Ti(OH 2 ) 3 groups and an encapsulated Cl - ion, [{P 2 W 15 Ti 3 O 59 (OH) 3 } 4 {μ 3 -Ti(H 2 O) 3 } 4 Cl] 21- (Ti 16 Tetramer). The Na 7 Ca 6 salt of Ca 7 Ti 9 Trimer was characterized by complete elemental analysis, thermogravimetric (TG) and differential thermal analyses (DTA), FTIR, single-crystal X-ray structure analysis, and solution 183 W and 31 P NMR spectroscopy. X-ray crystallography revealed that the [Ca 6 (CO 3 )(μ 3 -OH)(OH 2 ) 18 ] 9+ cluster cation was composed of six calcium cations linked by one μ 6 -carbonato anion and one μ 3 -OH - anion. The cluster cation was assembled, together with one calcium ion, on a trimeric species composed of three tri-Ti(IV)-substituted Wells-Dawson subunits linked by Ti-O-Ti bonds. Ca 7 Ti 9 Trimer is an unprecedented POM species containing an alkaline-earth-metal cluster cation and is the first example of alkaline-earth-metal ions clustered around a titanium(IV)-substituted POM.

The structure of DSM-IV-TR personality disorder diagnoses in NESARC: a reanalysis.

PubMed

Trull, Timothy J; Vergés, Alvaro; Wood, Phillip K; Sher, Kenneth J

2013-12-01

Cox, Clara, Worobec, and Grant (2012) recently presented results from a series of analyses aimed at identifying the factor structure underlying the DSM-IV-TR (APA, 2000) personality diagnoses assessed in the large NESARC study. Cox et al. (2012) concluded that the best fitting model was one that modeled three lower-order factors (the three clusters of PDs as outlined by DSM-IV-TR), which in turn loaded on a single PD higher-order factor. Our reanalyses of the NESARC Wave 1 and Wave 2 data for personality disorder diagnoses revealed that the best fitting model was that of a general PD factor that spans each of the ten DSM-IV PD diagnoses, and our reanalyses do not support the three-cluster hierarchical structure outlined by Cox et al. (2012) and DSM-IV-TR. Finally, we note the importance of modeling the Wave 2 assessment method factor in analyses of NESARC PD data.

Ultraviolet gas absorption and dust extinction toward M8

NASA Technical Reports Server (NTRS)

Boggs, Don; Bohm-Vitense, Erika

1990-01-01

Interstellar absorption lines are analyzed using high-resolution IUE spectra of 11 stars in the young cluster NGC 6530 located in the M8 region. High-velocity clouds at -35 km/s and -60 km/s are seen toward all cluster stars. The components arise in gases that are part of large interstellar bubbles centered on the cluster and driven by stellar winds of the most luminous members. Absorption lines of species of different ionization states are separated in velocity. The velocity stratification is best explained as a 'champagne' flow of ionized gas away from the cluster. The C IV/Si IV ratios toward the hotter cluster members are consistent with simple photoionization models if the gas-phase C/Si ratio is increased by preferential accretion onto dust grains. High ion column densities in the central cluster decline with distance from W93, suggesting that radiation from a hot source near W93 has photoionized gas in the central cluster.

Cascading failure in scale-free networks with tunable clustering

NASA Astrophysics Data System (ADS)

Zhang, Xue-Jun; Gu, Bo; Guan, Xiang-Min; Zhu, Yan-Bo; Lv, Ren-Li

2016-02-01

Cascading failure is ubiquitous in many networked infrastructure systems, such as power grids, Internet and air transportation systems. In this paper, we extend the cascading failure model to a scale-free network with tunable clustering and focus on the effect of clustering coefficient on system robustness. It is found that the network robustness undergoes a nonmonotonic transition with the increment of clustering coefficient: both highly and lowly clustered networks are fragile under the intentional attack, and the network with moderate clustering coefficient can better resist the spread of cascading. We then provide an extensive explanation for this constructive phenomenon via the microscopic point of view and quantitative analysis. Our work can be useful to the design and optimization of infrastructure systems.

Clustering high dimensional data using RIA

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

Aziz, Nazrina

2015-05-15

Clustering may simply represent a convenient method for organizing a large data set so that it can easily be understood and information can efficiently be retrieved. However, identifying cluster in high dimensionality data sets is a difficult task because of the curse of dimensionality. Another challenge in clustering is some traditional functions cannot capture the pattern dissimilarity among objects. In this article, we used an alternative dissimilarity measurement called Robust Influence Angle (RIA) in the partitioning method. RIA is developed using eigenstructure of the covariance matrix and robust principal component score. We notice that, it can obtain cluster easily andmore » hence avoid the curse of dimensionality. It is also manage to cluster large data sets with mixed numeric and categorical value.« less

Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data

PubMed Central

Zeng, Beiyan; Chen, Yiping P.; Smith, Oscar H.

2003-01-01

Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r2 test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed. PMID:18629292

Malfunctioning of the iron-sulfur cluster assembly machinery in Saccharomyces cerevisiae produces oxidative stress via an iron-dependent mechanism, causing dysfunction in respiratory complexes.

PubMed

Gomez, Mauricio; Pérez-Gallardo, Rocío V; Sánchez, Luis A; Díaz-Pérez, Alma L; Cortés-Rojo, Christian; Meza Carmen, Victor; Saavedra-Molina, Alfredo; Lara-Romero, Javier; Jiménez-Sandoval, Sergio; Rodríguez, Francisco; Rodríguez-Zavala, José S; Campos-García, Jesús

2014-01-01

Biogenesis and recycling of iron-sulfur (Fe-S) clusters play important roles in the iron homeostasis mechanisms involved in mitochondrial function. In Saccharomyces cerevisiae, the Fe-S clusters are assembled into apoproteins by the iron-sulfur cluster machinery (ISC). The aim of the present study was to determine the effects of ISC gene deletion and consequent iron release under oxidative stress conditions on mitochondrial functionality in S. cerevisiae. Reactive oxygen species (ROS) generation, caused by H2O2, menadione, or ethanol, was associated with a loss of iron homeostasis and exacerbated by ISC system dysfunction. ISC mutants showed increased free Fe2+ content, exacerbated by ROS-inducers, causing an increase in ROS, which was decreased by the addition of an iron chelator. Our study suggests that the increment in free Fe2+ associated with ROS generation may have originated from mitochondria, probably Fe-S cluster proteins, under both normal and oxidative stress conditions, suggesting that Fe-S cluster anabolism is affected. Raman spectroscopy analysis and immunoblotting indicated that in mitochondria from SSQ1 and ISA1 mutants, the content of [Fe-S] centers was decreased, as was formation of Rieske protein-dependent supercomplex III2IV2, but this was not observed in the iron-deficient ATX1 and MRS4 mutants. In addition, the activity of complexes II and IV from the electron transport chain (ETC) was impaired or totally abolished in SSQ1 and ISA1 mutants. These results confirm that the ISC system plays important roles in iron homeostasis, ROS stress, and in assembly of supercomplexes III2IV2 and III2IV1, thus affecting the functionality of the respiratory chain.

Robust nonparametric quantification of clustering density of molecules in single-molecule localization microscopy

PubMed Central

Jiang, Shenghang; Park, Seongjin; Challapalli, Sai Divya; Fei, Jingyi; Wang, Yong

2017-01-01

We report a robust nonparametric descriptor, J′(r), for quantifying the density of clustering molecules in single-molecule localization microscopy. J′(r), based on nearest neighbor distribution functions, does not require any parameter as an input for analyzing point patterns. We show that J′(r) displays a valley shape in the presence of clusters of molecules, and the characteristics of the valley reliably report the clustering features in the data. Most importantly, the position of the J′(r) valley (rJm′) depends exclusively on the density of clustering molecules (ρc). Therefore, it is ideal for direct estimation of the clustering density of molecules in single-molecule localization microscopy. As an example, this descriptor was applied to estimate the clustering density of ptsG mRNA in E. coli bacteria. PMID:28636661

Genetically distinct genogroup IV norovirus strains identified in wastewater.

PubMed

Kitajima, Masaaki; Rachmadi, Andri T; Iker, Brandon C; Haramoto, Eiji; Gerba, Charles P

2016-12-01

We investigated the prevalence and genetic diversity of genogroup IV norovirus (GIV NoV) strains in wastewater in Arizona, United States, over a 13-month period. Among 50 wastewater samples tested, GIV NoVs were identified in 13 (26 %) of the samples. A total of 47 different GIV NoV strains were identified, which were classified into two genetically distinct clusters: the GIV.1 human cluster and a unique genetic cluster closely related to strains previously identified in Japanese wastewater. The results provide additional evidence of the considerable genetic diversity among GIV NoV strains through the analysis of wastewater containing virus strains shed from all populations.

Cosmology and astrophysics from relaxed galaxy clusters - IV: Robustly calibrating hydrostatic masses with weak lensing

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

Applegate, D. E; Mantz, A.; Allen, S. W.

This is the fourth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Here, we use measurements of weak gravitational lensing from the Weighing the Giants project to calibrate Chandra X-ray measurements of total mass that rely on the assumption of hydrostatic equilibrium. This comparison of X-ray and lensing masses measures the combined bias of X-ray hydrostatic masses from both astrophysical and instrumental sources. While we cannot disentangle the two sources of bias, only the combined bias is relevant for calibrating cosmological measurements using relaxed clusters. Assuming a fixed cosmology, and within amore » characteristic radius (r 2500) determined from the X-ray data, we measure a lensing to X-ray mass ratio of 0.96 ± 9% (stat) ± 9% (sys). We find no significant trends of this ratio with mass, redshift or the morphological indicators used to select the sample. Our results imply that any departures from hydrostatic equilibrium at these radii are offset by calibration errors of comparable magnitude, with large departures of tens-of-percent unlikely. In addition, we find a mean concentration of the sample measured from lensing data of c 200 = 3.0 +4.4 –1.8. In conclusion, anticipated short-term improvements in lensing systematics, and a modest expansion of the relaxed lensing sample, can easily increase the measurement precision by 30–50%, leading to similar improvements in cosmological constraints that employ X-ray hydrostatic mass estimates, such as on Ω m from the cluster gas mass fraction.« less

Cosmology and astrophysics from relaxed galaxy clusters - IV: Robustly calibrating hydrostatic masses with weak lensing

DOE PAGES

Applegate, D. E; Mantz, A.; Allen, S. W.; ...

2016-02-04

This is the fourth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Here, we use measurements of weak gravitational lensing from the Weighing the Giants project to calibrate Chandra X-ray measurements of total mass that rely on the assumption of hydrostatic equilibrium. This comparison of X-ray and lensing masses measures the combined bias of X-ray hydrostatic masses from both astrophysical and instrumental sources. While we cannot disentangle the two sources of bias, only the combined bias is relevant for calibrating cosmological measurements using relaxed clusters. Assuming a fixed cosmology, and within amore » characteristic radius (r 2500) determined from the X-ray data, we measure a lensing to X-ray mass ratio of 0.96 ± 9% (stat) ± 9% (sys). We find no significant trends of this ratio with mass, redshift or the morphological indicators used to select the sample. Our results imply that any departures from hydrostatic equilibrium at these radii are offset by calibration errors of comparable magnitude, with large departures of tens-of-percent unlikely. In addition, we find a mean concentration of the sample measured from lensing data of c 200 = 3.0 +4.4 –1.8. In conclusion, anticipated short-term improvements in lensing systematics, and a modest expansion of the relaxed lensing sample, can easily increase the measurement precision by 30–50%, leading to similar improvements in cosmological constraints that employ X-ray hydrostatic mass estimates, such as on Ω m from the cluster gas mass fraction.« less

Cosmology and astrophysics from relaxed galaxy clusters - IV. Robustly calibrating hydrostatic masses with weak lensing

NASA Astrophysics Data System (ADS)

Applegate, D. E.; Mantz, A.; Allen, S. W.; von der Linden, A.; Morris, R. Glenn; Hilbert, S.; Kelly, Patrick L.; Burke, D. L.; Ebeling, H.; Rapetti, D. A.; Schmidt, R. W.

2016-04-01

This is the fourth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Here, we use measurements of weak gravitational lensing from the Weighing the Giants project to calibrate Chandra X-ray measurements of total mass that rely on the assumption of hydrostatic equilibrium. This comparison of X-ray and lensing masses measures the combined bias of X-ray hydrostatic masses from both astrophysical and instrumental sources. While we cannot disentangle the two sources of bias, only the combined bias is relevant for calibrating cosmological measurements using relaxed clusters. Assuming a fixed cosmology, and within a characteristic radius (r2500) determined from the X-ray data, we measure a lensing to X-ray mass ratio of 0.96 ± 9 per cent (stat) ± 9 per cent (sys). We find no significant trends of this ratio with mass, redshift or the morphological indicators used to select the sample. Our results imply that any departures from hydrostatic equilibrium at these radii are offset by calibration errors of comparable magnitude, with large departures of tens-of-percent unlikely. In addition, we find a mean concentration of the sample measured from lensing data of c_{200} = 3.0_{-1.8}^{+4.4}. Anticipated short-term improvements in lensing systematics, and a modest expansion of the relaxed lensing sample, can easily increase the measurement precision by 30-50 per cent, leading to similar improvements in cosmological constraints that employ X-ray hydrostatic mass estimates, such as on Ωm from the cluster gas mass fraction.

Dimensional assessment of personality pathology in patients with eating disorders.

PubMed

Goldner, E M; Srikameswaran, S; Schroeder, M L; Livesley, W J; Birmingham, C L

1999-02-22

This study examined patients with eating disorders on personality pathology using a dimensional method. Female subjects who met DSM-IV diagnostic criteria for eating disorder (n = 136) were evaluated and compared to an age-controlled general population sample (n = 68). We assessed 18 features of personality disorder with the Dimensional Assessment of Personality Pathology - Basic Questionnaire (DAPP-BQ). Factor analysis and cluster analysis were used to derive three clusters of patients. A five-factor solution was obtained with limited intercorrelation between factors. Cluster analysis produced three clusters with the following characteristics: Cluster 1 members (constituting 49.3% of the sample and labelled 'rigid') had higher mean scores on factors denoting compulsivity and interpersonal difficulties; Cluster 2 (18.4% of the sample) showed highest scores in factors denoting psychopathy, neuroticism and impulsive features, and appeared to constitute a borderline psychopathology group; Cluster 3 (32.4% of the sample) was characterized by few differences in personality pathology in comparison to the normal population sample. Cluster membership was associated with DSM-IV diagnosis -- a large proportion of patients with anorexia nervosa were members of Cluster 1. An empirical classification of eating-disordered patients derived from dimensional assessment of personality pathology identified three groups with clinical relevance.

An empirical comparison of methods for analyzing correlated data from a discrete choice survey to elicit patient preference for colorectal cancer screening

PubMed Central

2012-01-01

Background A discrete choice experiment (DCE) is a preference survey which asks participants to make a choice among product portfolios comparing the key product characteristics by performing several choice tasks. Analyzing DCE data needs to account for within-participant correlation because choices from the same participant are likely to be similar. In this study, we empirically compared some commonly-used statistical methods for analyzing DCE data while accounting for within-participant correlation based on a survey of patient preference for colorectal cancer (CRC) screening tests conducted in Hamilton, Ontario, Canada in 2002. Methods A two-stage DCE design was used to investigate the impact of six attributes on participants' preferences for CRC screening test and willingness to undertake the test. We compared six models for clustered binary outcomes (logistic and probit regressions using cluster-robust standard error (SE), random-effects and generalized estimating equation approaches) and three models for clustered nominal outcomes (multinomial logistic and probit regressions with cluster-robust SE and random-effects multinomial logistic model). We also fitted a bivariate probit model with cluster-robust SE treating the choices from two stages as two correlated binary outcomes. The rank of relative importance between attributes and the estimates of β coefficient within attributes were used to assess the model robustness. Results In total 468 participants with each completing 10 choices were analyzed. Similar results were reported for the rank of relative importance and β coefficients across models for stage-one data on evaluating participants' preferences for the test. The six attributes ranked from high to low as follows: cost, specificity, process, sensitivity, preparation and pain. However, the results differed across models for stage-two data on evaluating participants' willingness to undertake the tests. Little within-patient correlation (ICC ≈ 0) was found in stage-one data, but substantial within-patient correlation existed (ICC = 0.659) in stage-two data. Conclusions When small clustering effect presented in DCE data, results remained robust across statistical models. However, results varied when larger clustering effect presented. Therefore, it is important to assess the robustness of the estimates via sensitivity analysis using different models for analyzing clustered data from DCE studies. PMID:22348526

A longitudinal analysis of posttraumatic stress disorder symptoms and their relationship with Fear and Anxious-Misery disorders: implications for DSM-V.

PubMed

Forbes, David; Parslow, Ruth; Creamer, Mark; O'Donnell, Meaghan; Bryant, Richard; McFarlane, Alexander; Silove, Derrick; Shalev, Arieh

2010-12-01

This paper examined the hypothesis that PTSD-unique symptom clusters of re-experiencing, active avoidance and hyperarousal were more related to the fear/phobic disorders, while shared PTSD symptoms of dysphoria were more closely related to Anxious-Misery disorders (MDD/GAD). Confirmatory factor and correlation analyses examining PTSD, anxiety and mood disorder data from 714 injury survivors interviewed 3, 12 and 24-months following their injury supported this hypothesis with these relationships remaining robust from 3-24 months posttrauma. Of the nine unique fear-oriented PTSD symptoms, only one is currently required for a DSM-IV diagnosis. Increasing emphasis on PTSD fear symptoms in DSM-V, such as proposed DSM-V changes to mandate active avoidance, is critical to improve specificity, ensure inclusion of dimensionally distinct features and facilitate tailoring of treatment. Copyright © 2010 Elsevier B.V. All rights reserved.

Sample size calculation in cost-effectiveness cluster randomized trials: optimal and maximin approaches.

PubMed

Manju, Md Abu; Candel, Math J J M; Berger, Martijn P F

2014-07-10

In this paper, the optimal sample sizes at the cluster and person levels for each of two treatment arms are obtained for cluster randomized trials where the cost-effectiveness of treatments on a continuous scale is studied. The optimal sample sizes maximize the efficiency or power for a given budget or minimize the budget for a given efficiency or power. Optimal sample sizes require information on the intra-cluster correlations (ICCs) for effects and costs, the correlations between costs and effects at individual and cluster levels, the ratio of the variance of effects translated into costs to the variance of the costs (the variance ratio), sampling and measuring costs, and the budget. When planning, a study information on the model parameters usually is not available. To overcome this local optimality problem, the current paper also presents maximin sample sizes. The maximin sample sizes turn out to be rather robust against misspecifying the correlation between costs and effects at the cluster and individual levels but may lose much efficiency when misspecifying the variance ratio. The robustness of the maximin sample sizes against misspecifying the ICCs depends on the variance ratio. The maximin sample sizes are robust under misspecification of the ICC for costs for realistic values of the variance ratio greater than one but not robust under misspecification of the ICC for effects. Finally, we show how to calculate optimal or maximin sample sizes that yield sufficient power for a test on the cost-effectiveness of an intervention.

Valine/isoleucine variants drive selective pressure in the VP1 sequence of EV-A71 enteroviruses.

PubMed

Duy, Nghia Ngu; Huong, Le Thi Thanh; Ravel, Patrice; Huong, Le Thi Song; Dwivedi, Ankit; Sessions, October Michael; Hou, Yan'An; Chua, Robert; Kister, Guilhem; Afelt, Aneta; Moulia, Catherine; Gubler, Duane J; Thiem, Vu Dinh; Thanh, Nguyen Thi Hien; Devaux, Christian; Duong, Tran Nhu; Hien, Nguyen Tran; Cornillot, Emmanuel; Gavotte, Laurent; Frutos, Roger

2017-05-08

In 2011-2012, Northern Vietnam experienced its first large scale hand foot and mouth disease (HFMD) epidemic. In 2011, a major HFMD epidemic was also reported in South Vietnam with fatal cases. This 2011-2012 outbreak was the first one to occur in North Vietnam providing grounds to study the etiology, origin and dynamic of the disease. We report here the analysis of the VP1 gene of strains isolated throughout North Vietnam during the 2011-2012 outbreak and before. The VP1 gene of 106 EV-A71 isolates from North Vietnam and 2 from Central Vietnam were sequenced. Sequence alignments were analyzed at the nucleic acid and protein level. Gene polymorphism was also analyzed. A Factorial Correspondence Analysis was performed to correlate amino acid mutations with clinical parameters. The sequences were distributed into four phylogenetic clusters. Three clusters corresponded to the subgenogroup C4 and the last one corresponded to the subgenogroup C5. Each cluster displayed different polymorphism characteristics. Proteins were highly conserved but three sites bearing only Isoleucine (I) or Valine (V) were characterized. The isoleucine/valine variability matched the clusters. Spatiotemporal analysis of the I/V variants showed that all variants which emerged in 2011 and then in 2012 were not the same but were all present in the region prior to the 2011-2012 outbreak. Some correlation was found between certain I/V variants and ethnicity and severity. The 2011-2012 outbreak was not caused by an exogenous strain coming from South Vietnam or elsewhere but by strains already present and circulating at low level in North Vietnam. However, what triggered the outbreak remains unclear. A selective pressure is applied on I/V variants which matches the genetic clusters. I/V variants were shown on other viruses to correlate with pathogenicity. This should be investigated in EV-A71. I/V variants are an easy and efficient way to survey and identify circulating EV-A71 strains.

Extension of the classical classification of β-turns

PubMed Central

de Brevern, Alexandre G.

2016-01-01

The functional properties of a protein primarily depend on its three-dimensional (3D) structure. These properties have classically been assigned, visualized and analysed on the basis of protein secondary structures. The β-turn is the third most important secondary structure after helices and β-strands. β-turns have been classified according to the values of the dihedral angles φ and ψ of the central residue. Conventionally, eight different types of β-turns have been defined, whereas those that cannot be defined are classified as type IV β-turns. This classification remains the most widely used. Nonetheless, the miscellaneous type IV β-turns represent 1/3rd of β-turn residues. An unsupervised specific clustering approach was designed to search for recurrent new turns in the type IV category. The classical rules of β-turn type assignment were central to the approach. The four most frequently occurring clusters defined the new β-turn types. Unexpectedly, these types, designated IV1, IV2, IV3 and IV4, represent half of the type IV β-turns and occur more frequently than many of the previously established types. These types show convincing particularities, in terms of both structures and sequences that allow for the classical β-turn classification to be extended for the first time in 25 years. PMID:27627963

Extension of the classical classification of β-turns.

PubMed

de Brevern, Alexandre G

2016-09-15

The functional properties of a protein primarily depend on its three-dimensional (3D) structure. These properties have classically been assigned, visualized and analysed on the basis of protein secondary structures. The β-turn is the third most important secondary structure after helices and β-strands. β-turns have been classified according to the values of the dihedral angles φ and ψ of the central residue. Conventionally, eight different types of β-turns have been defined, whereas those that cannot be defined are classified as type IV β-turns. This classification remains the most widely used. Nonetheless, the miscellaneous type IV β-turns represent 1/3(rd) of β-turn residues. An unsupervised specific clustering approach was designed to search for recurrent new turns in the type IV category. The classical rules of β-turn type assignment were central to the approach. The four most frequently occurring clusters defined the new β-turn types. Unexpectedly, these types, designated IV1, IV2, IV3 and IV4, represent half of the type IV β-turns and occur more frequently than many of the previously established types. These types show convincing particularities, in terms of both structures and sequences that allow for the classical β-turn classification to be extended for the first time in 25 years.

Unprecedented reduction of the uranyl ion [UO2]2+ into a polyoxo uranium(IV) cluster: synthesis and crystal structure of the first f-element oxide with a M6(micro3-O)8 core.

PubMed

Berthet, Jean-Claude; Thuéry, Pierre; Ephritikhine, Michel

2005-07-21

The smooth comproportionation reaction of the U(VI) and U(III) complexes UO2(OTf)2 and U(OTf)3, afforded the hexanuclear U(IV) oxide cluster [U6(micro3-O)8(micro2-OTf)8(py)8], a rare example of a metal oxide with a M6(micro3-O)8 core.

The effectiveness of a near-infrared vascular imaging device to support intravenous cannulation in children with dark skin color: a cluster randomized clinical trial.

PubMed

van der Woude, Olga C P; Cuper, Natascha J; Getrouw, Chavalleh; Kalkman, Cor J; de Graaff, Jurgen C

2013-06-01

Poor vein visibility can make IV cannulation challenging in children with dark skin color. In the operating room, we studied the effectiveness of a near-infrared vascular imaging device (VascuLuminator) to facilitate IV cannulation in children with dark skin color. In the operating room of a general hospital in Curacao, all consecutive children (0-15 years of age) requiring IV cannulation were included in a pragmatic cluster randomized clinical trial. The VascuLuminator was made available to anesthesiologists at the operating complex in randomized clusters of 1 week. Success at first attempt was 63% (27/43, 95% confidence interval [CI], 47%-77%) in the VascuLuminator group vs 51% (23 of 45 patients, 95% CI, 36%-66%) in the control group (P = 0.27). Median time to successful cannulation was 53 seconds (interquartile range: 34-154) in the VascuLuminator group and 68 seconds (interquartile range: 40-159) in the control group (P = 0.54), and hazard ratio was 1.12 (95% CI, 0.73-1.71). The VascuLuminator has limited value in improving success at first attempt of facilitating IV cannulation in children with dark skin color.

βIV Spectrinopathies Cause Profound Intellectual Disability, Congenital Hypotonia, and Motor Axonal Neuropathy.

PubMed

Wang, Chih-Chuan; Ortiz-González, Xilma R; Yum, Sabrina W; Gill, Sara M; White, Amy; Kelter, Erin; Seaver, Laurie H; Lee, Sansan; Wiley, Graham; Gaffney, Patrick M; Wierenga, Klaas J; Rasband, Matthew N

2018-06-07

βIV spectrin links ankyrinG (AnkG) and clustered ion channels at axon initial segments (AISs) and nodes of Ranvier to the axonal cytoskeleton. Here, we report bi-allelic pathogenic SPTBN4 variants (three homozygous and two compound heterozygous) that cause a severe neurological syndrome that includes congenital hypotonia, intellectual disability, and motor axonal and auditory neuropathy. We introduced these variants into βIV spectrin, expressed these in neurons, and found that 5/7 were loss-of-function variants disrupting AIS localization or abolishing phosphoinositide binding. Nerve biopsies from an individual with a loss-of-function variant had reduced nodal Na + channels and no nodal KCNQ2 K + channels. Modeling the disease in mice revealed that although ankyrinR (AnkR) and βI spectrin can cluster Na + channels and partially compensate for the loss of AnkG and βIV spectrin at nodes of Ranvier, AnkR and βI spectrin cannot cluster KCNQ2- and KCNQ3-subunit-containing K + channels. Our findings define a class of spectrinopathies and reveal the molecular pathologies causing nervous-system dysfunction. Copyright © 2018 American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Correlates of the molecular vaginal microbiota composition of African women.

PubMed

Gautam, Raju; Borgdorff, Hanneke; Jespers, Vicky; Francis, Suzanna C; Verhelst, Rita; Mwaura, Mary; Delany-Moretlwe, Sinead; Ndayisaba, Gilles; Kyongo, Jordan K; Hardy, Liselotte; Menten, Joris; Crucitti, Tania; Tsivtsivadze, Evgeni; Schuren, Frank; van de Wijgert, Janneke H H M

2015-02-21

Sociodemographic, behavioral and clinical correlates of the vaginal microbiome (VMB) as characterized by molecular methods have not been adequately studied. VMB dominated by bacteria other than lactobacilli may cause inflammation, which may facilitate HIV acquisition and other adverse reproductive health outcomes. We characterized the VMB of women in Kenya, Rwanda, South Africa and Tanzania (KRST) using a 16S rDNA phylogenetic microarray. Cytokines were quantified in cervicovaginal lavages. Potential sociodemographic, behavioral, and clinical correlates were also evaluated. Three hundred thirteen samples from 230 women were available for analysis. Five VMB clusters were identified: one cluster each dominated by Lactobacillus crispatus (KRST-I) and L. iners (KRST-II), and three clusters not dominated by a single species but containing multiple (facultative) anaerobes (KRST-III/IV/V). Women in clusters KRST-I and II had lower mean concentrations of interleukin (IL)-1α (p < 0.001) and Granulocyte Colony Stimulating Factor (G-CSF) (p = 0.01), but higher concentrations of interferon-γ-induced protein (IP-10) (p < 0.01) than women in clusters KRST-III/IV/V. A lower proportion of women in cluster KRST-I tested positive for bacterial sexually transmitted infections (STIs; ptrend = 0.07) and urinary tract infection (UTI; p = 0.06), and a higher proportion of women in clusters KRST-I and II had vaginal candidiasis (ptrend = 0.09), but these associations did not reach statistical significance. Women who reported unusual vaginal discharge were more likely to belong to clusters KRST-III/IV/V (p = 0.05). Vaginal dysbiosis in African women was significantly associated with vaginal inflammation; the associations with increased prevalence of STIs and UTI, and decreased prevalence of vaginal candidiasis, should be confirmed in larger studies.

Harnessing Sparse and Low-Dimensional Structures for Robust Clustering of Imagery Data

ERIC Educational Resources Information Center

Rao, Shankar Ramamohan

2009-01-01

We propose a robust framework for clustering data. In practice, data obtained from real measurement devices can be incomplete, corrupted by gross errors, or not correspond to any assumed model. We show that, by properly harnessing the intrinsic low-dimensional structure of the data, these kinds of practical problems can be dealt with in a uniform…

Robust watermarking scheme for binary images using a slice-based large-cluster algorithm with a Hamming Code

NASA Astrophysics Data System (ADS)

Chen, Wen-Yuan; Liu, Chen-Chung

2006-01-01

The problems with binary watermarking schemes are that they have only a small amount of embeddable space and are not robust enough. We develop a slice-based large-cluster algorithm (SBLCA) to construct a robust watermarking scheme for binary images. In SBLCA, a small-amount cluster selection (SACS) strategy is used to search for a feasible slice in a large-cluster flappable-pixel decision (LCFPD) method, which is used to search for the best location for concealing a secret bit from a selected slice. This method has four major advantages over the others: (a) SBLCA has a simple and effective decision function to select appropriate concealment locations, (b) SBLCA utilizes a blind watermarking scheme without the original image in the watermark extracting process, (c) SBLCA uses slice-based shuffling capability to transfer the regular image into a hash state without remembering the state before shuffling, and finally, (d) SBLCA has enough embeddable space that every 64 pixels could accommodate a secret bit of the binary image. Furthermore, empirical results on test images reveal that our approach is a robust watermarking scheme for binary images.

Self-report assessment of the DSM-IV personality disorders. Measurement of trait and distress characteristics: the ADP-IV.

PubMed

Schotte, C K; de Doncker, D; Vankerckhoven, C; Vertommen, H; Cosyns, P

1998-09-01

Self-report instruments assessing the DSM personality disorders are characterized by overdiagnosis due to their emphasis on the measurement of personality traits rather than the impairment and distress associated with the criteria. The ADP-IV, a Dutch questionnaire, introduces an alternative assessment method: each test item assesses 'Trait' as well as 'Distress/impairment' characteristics of a DSM-IV criterion. This item format allows dimensional as well as categorical diagnostic evaluations. The present study explores the validity of the ADP-IV in a sample of 659 subjects of the Flemish population. The dimensional personality disorder subscales, measuring Trait characteristics, are internally consistent and display a good concurrent validity with the Wisconsin Personality Disorders Inventory. Factor analysis at the item-level resulted in 11 orthogonal factors, describing personality dimensions such as psychopathy, social anxiety and avoidance, negative affect and self-image. Factor analysis at the subscale-level identified two basic dimensions, reflecting hostile (DSM-IV Cluster B) and anxious (DSM-IV Cluster C) interpersonal attitudes. Categorical ADP-IV diagnoses are obtained using scoring algorithms, which emphasize the Trait or the Distress concepts in the diagnostic evaluation. Prevalences of ADP-IV diagnoses of any personality disorder according to these algorithms vary between 2.28 and 20.64%. Although further research in clinical samples is required, the present results support the validity of the ADP-IV and the potential of the measurement of trait and distress characteristics as a method for assessing personality pathology.

Robust Bayesian clustering.

PubMed

Archambeau, Cédric; Verleysen, Michel

2007-01-01

A new variational Bayesian learning algorithm for Student-t mixture models is introduced. This algorithm leads to (i) robust density estimation, (ii) robust clustering and (iii) robust automatic model selection. Gaussian mixture models are learning machines which are based on a divide-and-conquer approach. They are commonly used for density estimation and clustering tasks, but are sensitive to outliers. The Student-t distribution has heavier tails than the Gaussian distribution and is therefore less sensitive to any departure of the empirical distribution from Gaussianity. As a consequence, the Student-t distribution is suitable for constructing robust mixture models. In this work, we formalize the Bayesian Student-t mixture model as a latent variable model in a different way from Svensén and Bishop [Svensén, M., & Bishop, C. M. (2005). Robust Bayesian mixture modelling. Neurocomputing, 64, 235-252]. The main difference resides in the fact that it is not necessary to assume a factorized approximation of the posterior distribution on the latent indicator variables and the latent scale variables in order to obtain a tractable solution. Not neglecting the correlations between these unobserved random variables leads to a Bayesian model having an increased robustness. Furthermore, it is expected that the lower bound on the log-evidence is tighter. Based on this bound, the model complexity, i.e. the number of components in the mixture, can be inferred with a higher confidence.

Predicting Future Suicide Attempts among Depressed Suicide Ideators: A 10-year Longitudinal Study

PubMed Central

May, Alexis M.; Klonsky, E. David; Klein, Daniel N.

2012-01-01

Suicidal ideation and attempts are a major public health problem. Research has identified many risk factors for suicidality; however, most fail to identify which suicide ideators are at greatest risk of progressing to a suicide attempt. Thus, the present study identified predictors of future suicide attempts in a sample of psychiatric patients reporting suicidal ideation. The sample comprised 49 individuals who met full DSM-IV criteria for major depressive disorder and/or dysthymic disorder and reported suicidal ideation at baseline. Participants were followed for 10 years. Demographic, psychological, personality, and psychosocial risk factors were assessed using validated questionnaires and structured interviews. Phi coefficients and point-biserial correlations were used to identify prospective predictors of attempts, and logistic regressions were used to identify which variables predicted future attempts over and above past suicide attempts. Six significant predictors of future suicide attempts were identified – cluster A personality disorder, cluster B personality disorder, lifetime substance abuse, baseline anxiety disorder, poor maternal relationship, and poor social adjustment. Finally, exploratory logistic regressions were used to examine the unique contribution of each significant predictor controlling for the others. Co-morbid cluster B personality disorder emerged as the only robust, unique predictor of future suicide attempts among depressed suicide ideators. Future research should continue to identify variables that predict transition from suicidal thoughts to suicide attempts, as such work will enhance clinical assessment of suicide risk as well as theoretical models of suicide. PMID:22575331

Competitive repetition suppression (CoRe) clustering: a biologically inspired learning model with application to robust clustering.

PubMed

Bacciu, Davide; Starita, Antonina

2008-11-01

Determining a compact neural coding for a set of input stimuli is an issue that encompasses several biological memory mechanisms as well as various artificial neural network models. In particular, establishing the optimal network structure is still an open problem when dealing with unsupervised learning models. In this paper, we introduce a novel learning algorithm, named competitive repetition-suppression (CoRe) learning, inspired by a cortical memory mechanism called repetition suppression (RS). We show how such a mechanism is used, at various levels of the cerebral cortex, to generate compact neural representations of the visual stimuli. From the general CoRe learning model, we derive a clustering algorithm, named CoRe clustering, that can automatically estimate the unknown cluster number from the data without using a priori information concerning the input distribution. We illustrate how CoRe clustering, besides its biological plausibility, posses strong theoretical properties in terms of robustness to noise and outliers, and we provide an error function describing CoRe learning dynamics. Such a description is used to analyze CoRe relationships with the state-of-the art clustering models and to highlight CoRe similitude with rival penalized competitive learning (RPCL), showing how CoRe extends such a model by strengthening the rival penalization estimation by means of loss functions from robust statistics.

Robust continuous clustering

PubMed Central

Shah, Sohil Atul

2017-01-01

Clustering is a fundamental procedure in the analysis of scientific data. It is used ubiquitously across the sciences. Despite decades of research, existing clustering algorithms have limited effectiveness in high dimensions and often require tuning parameters for different domains and datasets. We present a clustering algorithm that achieves high accuracy across multiple domains and scales efficiently to high dimensions and large datasets. The presented algorithm optimizes a smooth continuous objective, which is based on robust statistics and allows heavily mixed clusters to be untangled. The continuous nature of the objective also allows clustering to be integrated as a module in end-to-end feature learning pipelines. We demonstrate this by extending the algorithm to perform joint clustering and dimensionality reduction by efficiently optimizing a continuous global objective. The presented approach is evaluated on large datasets of faces, hand-written digits, objects, newswire articles, sensor readings from the Space Shuttle, and protein expression levels. Our method achieves high accuracy across all datasets, outperforming the best prior algorithm by a factor of 3 in average rank. PMID:28851838

[Research on K-means clustering segmentation method for MRI brain image based on selecting multi-peaks in gray histogram].

PubMed

Chen, Zhaoxue; Yu, Haizhong; Chen, Hao

2013-12-01

To solve the problem of traditional K-means clustering in which initial clustering centers are selected randomly, we proposed a new K-means segmentation algorithm based on robustly selecting 'peaks' standing for White Matter, Gray Matter and Cerebrospinal Fluid in multi-peaks gray histogram of MRI brain image. The new algorithm takes gray value of selected histogram 'peaks' as the initial K-means clustering center and can segment the MRI brain image into three parts of tissue more effectively, accurately, steadily and successfully. Massive experiments have proved that the proposed algorithm can overcome many shortcomings caused by traditional K-means clustering method such as low efficiency, veracity, robustness and time consuming. The histogram 'peak' selecting idea of the proposed segmentootion method is of more universal availability.

Robust spike sorting of retinal ganglion cells tuned to spot stimuli.

PubMed

Ghahari, Alireza; Badea, Tudor C

2016-08-01

We propose an automatic spike sorting approach for the data recorded from a microelectrode array during visual stimulation of wild type retinas with tiled spot stimuli. The approach first detects individual spikes per electrode by their signature local minima. With the mixture probability distribution of the local minima estimated afterwards, it applies a minimum-squared-error clustering algorithm to sort the spikes into different clusters. A template waveform for each cluster per electrode is defined, and a number of reliability tests are performed on it and its corresponding spikes. Finally, a divisive hierarchical clustering algorithm is used to deal with the correlated templates per cluster type across all the electrodes. According to the measures of performance of the spike sorting approach, it is robust even in the cases of recordings with low signal-to-noise ratio.

Tetravalent Ce in the Nitrate-Decorated Hexanuclear Cluster [Ce 6 (μ 3 -O) 4 (μ 3 -OH) 4 ] 12+ : A Structural End Point for Ceria Nanoparticles

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

Estes, Shanna L.; Antonio, Mark R.; Soderholm, L.

2016-03-17

We describe the synthesis and characterization of three glycine-stabilized hexanuclear Cely cluster compounds, each containing the [Ce-6(mu(3)-O)(4)(mu(3)-OH)(4)](12+) core structure. Crystallized from aqueous nitrate solutions with pH < 0, the core cluster structures exhibit variable decoration by nitrate, glycine, and water ligands depending on solution conditions, where increased nitrate and glycine decoration of the cluster core was observed for crystals synthesized at high Ce and nitrate concentrations. No other crystalline products were observed using this synthetic route. In addition to confirming the tetravalent oxidation state of cerium in one of the reported clusters, cyclic voltammetry also indicates that Ce-IV is reducedmore » at similar to+0.60 V vs Ag/AgCl (3 M NaCl), which is significantly less than the standard electrode potential. This large decrease in the Ce-IV/Ce-III reduction potential suggests that Ce-IV is significantly stabilized relative to Ce-III within the examined cluster. These compounds are discussed in terms of their importance as small, end member, ceric oxide nanoparticles. Single-crystal structural solutions, together with voltammetry and electrolysis data, permit the decoupling of Ce-III defects and substoichiometry. In addition, Ce-Ce distances can be used to determine an "effective" CeO2-x lattice constant, providing a simple method for comparing literature descriptions. The results are discussed in terms of their potential implications for the mechanisms by which nanoparticle ceria serve as catalysts and oxygen-storage materials.« less

Genetic ablation or pharmacological blockade of dipeptidyl peptidase IV does not impact T cell-dependent immune responses

PubMed Central

Vora, Kalpit A; Porter, Gene; Peng, Roche; Cui, Yan; Pryor, Kellyann; Eiermann, George; Zaller, Dennis M

2009-01-01

Background Current literature suggests that dipeptidyl peptidase IV (DPP-IV; CD26) plays an essential role in T-dependent immune responses, a role that could have important clinical consequences. To rigorously define the role of DPP-IV in the immune system, we evaluated genetic and pharmacological inhibition of the enzyme on T-dependent immune responses in vivo. Results The DPP-IV null animals mounted robust primary and secondary antibody responses to the T dependent antigens, 4-hydroxy-3-nitrophenylacetyl-ovalbumin (NP-Ova) and 4-hydroxy-3-nitrophenylacetyl-chicken gamma globulin (NP-CGG), which were comparable to wild type mice. Serum levels of antigen specific IgM, IgG1, IgG2a, IgG2b and IgG3 were similar between the two groups of animals. DPP-IV null animals mounted an efficient germinal center reaction by day 10 after antigen stimulation that was comparable to wild type mice. Moreover, the antibodies produced by DPP-IV null animals after repeated antigenic challenge were affinity matured. Similar observations were made using wild type animals treated with a highly selective DPP-IV inhibitor during the entire course of the experiments. T cell recall responses to ovalbumin and MOG peptide, evaluated by measuring proliferation and IL-2 release from cells isolated from draining lymph nodes, were equivalent in DPP-IV null and wild type animals. Furthermore, mice treated with DPP-IV inhibitor had intact T-cell recall responses to MOG peptide. In addition, female DPP-IV null and wild type mice treated with DPP-IV inhibitor exhibited normal and robust in vivo cytotoxic T cell responses after challenge with cells expressing the male H-Y minor histocompatibility antigen. Conclusion These data indicate Selective inhibition of DPP-IV does not impair T dependent immune responses to antigenic challenge. PMID:19358731

Clustering Methods; Part IV of Scientific Report No. ISR-18, Information Storage and Retrieval...

ERIC Educational Resources Information Center

Cornell Univ., Ithaca, NY. Dept. of Computer Science.

Two papers are included as Part Four of this report on Salton's Magical Automatic Retriever of Texts (SMART) project report. The first paper: "A Controlled Single Pass Classification Algorithm with Application to Multilevel Clustering" by D. B. Johnson and J. M. Laferente presents a single pass clustering method which compares favorably…

Generalized fuzzy C-means clustering algorithm with improved fuzzy partitions.

PubMed

Zhu, Lin; Chung, Fu-Lai; Wang, Shitong

2009-06-01

The fuzziness index m has important influence on the clustering result of fuzzy clustering algorithms, and it should not be forced to fix at the usual value m = 2. In view of its distinctive features in applications and its limitation in having m = 2 only, a recent advance of fuzzy clustering called fuzzy c-means clustering with improved fuzzy partitions (IFP-FCM) is extended in this paper, and a generalized algorithm called GIFP-FCM for more effective clustering is proposed. By introducing a novel membership constraint function, a new objective function is constructed, and furthermore, GIFP-FCM clustering is derived. Meanwhile, from the viewpoints of L(p) norm distance measure and competitive learning, the robustness and convergence of the proposed algorithm are analyzed. Furthermore, the classical fuzzy c-means algorithm (FCM) and IFP-FCM can be taken as two special cases of the proposed algorithm. Several experimental results including its application to noisy image texture segmentation are presented to demonstrate its average advantage over FCM and IFP-FCM in both clustering and robustness capabilities.

Oviposition and Sex Ratio of the Redbanded Stink Bug, Piezodorous guildinii, in Soybean.

PubMed

Temple, Joshua H; Davis, Jeffrey A; Hardke, Jarrod T; Price, Paul P; Leonard, B Rogers

2016-06-17

Redbanded stink bug, Piezodorus guildinii (Westwood), is a significant soybean pest across the mid-south region of the United States. The objectives of these studies were to characterize: (1) redbanded stink bug oviposition in relationship to soybean maturity group (MG), plant structure, crop phenology, and vertical distribution within the plant canopy; and (2) redbanded stink bug adult sex ratios in relationship to soybean phenology. A total of 5645 redbanded stink bug eggs in 421 egg masses (clusters) were field collected from naturally-occurring populations in MG IV and V soybean over a three year period (2009 to 2011). The mean number of eggs within a cluster was 16.6 ± 0.3. Plant structures by MG interactions were highly significant with more egg masses oviposited on leaves in MG IV (79.4%) and more on pods in MG V (72.7%). The ratio of females to males was similar in all soybean growth stages except R5, where the sex ratio increased to 1.4:1, coinciding with peak oviposition. Only 29.9% of egg clusters in MG IV and 18.3% of egg clusters in MG V were oviposited in the upper 35 cm of the soybean canopy. Based on these results, sampling strategies and insecticide application placement for stink bugs may require modification.

Oviposition and Sex Ratio of the Redbanded Stink Bug, Piezodorous guildinii, in Soybean

PubMed Central

Temple, Joshua H.; Davis, Jeffrey A.; Hardke, Jarrod T.; Price, Paul P.; Leonard, B. Rogers

2016-01-01

Redbanded stink bug, Piezodorus guildinii (Westwood), is a significant soybean pest across the mid-south region of the United States. The objectives of these studies were to characterize: (1) redbanded stink bug oviposition in relationship to soybean maturity group (MG), plant structure, crop phenology, and vertical distribution within the plant canopy; and (2) redbanded stink bug adult sex ratios in relationship to soybean phenology. A total of 5645 redbanded stink bug eggs in 421 egg masses (clusters) were field collected from naturally-occurring populations in MG IV and V soybean over a three year period (2009 to 2011). The mean number of eggs within a cluster was 16.6 ± 0.3. Plant structures by MG interactions were highly significant with more egg masses oviposited on leaves in MG IV (79.4%) and more on pods in MG V (72.7%). The ratio of females to males was similar in all soybean growth stages except R5, where the sex ratio increased to 1.4:1, coinciding with peak oviposition. Only 29.9% of egg clusters in MG IV and 18.3% of egg clusters in MG V were oviposited in the upper 35 cm of the soybean canopy. Based on these results, sampling strategies and insecticide application placement for stink bugs may require modification. PMID:27322333

Phylogenetic Evidence for Lateral Gene Transfer in the Intestine of Marine Iguanas

PubMed Central

Nelson, David M.; Cann, Isaac K. O.; Altermann, Eric; Mackie, Roderick I.

2010-01-01

Background Lateral gene transfer (LGT) appears to promote genotypic and phenotypic variation in microbial communities in a range of environments, including the mammalian intestine. However, the extent and mechanisms of LGT in intestinal microbial communities of non-mammalian hosts remains poorly understood. Methodology/Principal Findings We sequenced two fosmid inserts obtained from a genomic DNA library derived from an agar-degrading enrichment culture of marine iguana fecal material. The inserts harbored 16S rRNA genes that place the organism from which they originated within Clostridium cluster IV, a well documented group that habitats the mammalian intestinal tract. However, sequence analysis indicates that 52% of the protein-coding genes on the fosmids have top BLASTX hits to bacterial species that are not members of Clostridium cluster IV, and phylogenetic analysis suggests that at least 10 of 44 coding genes on the fosmids may have been transferred from Clostridium cluster XIVa to cluster IV. The fosmids encoded four transposase-encoding genes and an integrase-encoding gene, suggesting their involvement in LGT. In addition, several coding genes likely involved in sugar transport were probably acquired through LGT. Conclusion Our phylogenetic evidence suggests that LGT may be common among phylogenetically distinct members of the phylum Firmicutes inhabiting the intestinal tract of marine iguanas. PMID:20520734

Neurocognitive disorders: cluster 1 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Sachdev, P; Andrews, G; Hobbs, M J; Sunderland, M; Anderson, T M

2009-12-01

In an effort to group mental disorders on the basis of aetiology, five clusters have been proposed. In this paper, we consider the validity of the first cluster, neurocognitive disorders, within this proposal. These disorders are categorized as 'Dementia, Delirium, and Amnestic and Other Cognitive Disorders' in DSM-IV and 'Organic, including Symptomatic Mental Disorders' in ICD-10. We reviewed the literature in relation to 11 validating criteria proposed by a Study Group of the DSM-V Task Force as applied to the cluster of neurocognitive disorders. 'Neurocognitive' replaces the previous terms 'cognitive' and 'organic' used in DSM-IV and ICD-10 respectively as the descriptor for disorders in this cluster. Although cognitive/organic problems are present in other disorders, this cluster distinguishes itself by the demonstrable neural substrate abnormalities and the salience of cognitive symptoms and deficits. Shared biomarkers, co-morbidity and course offer less persuasive evidence for a valid cluster of neurocognitive disorders. The occurrence of these disorders subsequent to normal brain development sets this cluster apart from neurodevelopmental disorders. The aetiology of the disorders is varied, but the neurobiological underpinnings are better understood than for mental disorders in any other cluster. Neurocognitive disorders meet some of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster. Further developments in the aetiopathogenesis of these disorders will enhance the clinical utility of this cluster.

Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali.

PubMed

Minetti, Andrea; Riera-Montes, Margarita; Nackers, Fabienne; Roederer, Thomas; Koudika, Marie Hortense; Sekkenes, Johanne; Taconet, Aurore; Fermon, Florence; Touré, Albouhary; Grais, Rebecca F; Checchi, Francesco

2012-10-12

Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes.

Role of childhood traumatic experience in personality disorders in China.

PubMed

Zhang, TianHong; Chow, Annabelle; Wang, LanLan; Dai, YunFei; Xiao, ZePing

2012-08-01

There has been no large-scale examination of the association between types of childhood abuse and personality disorders (PDs) in China using standardized assessment tools and the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. Hence, this study aimed to explore the relationship between retrospective reports of various types of childhood maltreatments and current DSM-IV PDs in a clinical population in China, Shanghai. One thousand four hundred two subjects were randomly sampled from the Shanghai Psychological Counselling Centre. PDs were assessed using the Personality Diagnostic Questionnaire, Fourth Edition Plus. Participants were also interviewed using the Structured Clinical Interview for DSM-IV axis II. The Child Trauma Questionnaire (CTQ) was used to assess childhood maltreatment in 5 domains (emotional abuse, physical abuse, sexual abuse, emotional neglect, and physical neglect). According to Pearson correlations, childhood maltreatment had a strong association with most PDs. Subsequently, using partial correlations, significant relationships were also demonstrated between cluster B PDs and all the traumatic factors except physical neglect. A strongest positive correlation was found between cluster B PD and CTQ total scores (r = .312, P < .01). Using the Kruskal-Wallis rank sum test, significant differences in 4 groups of subjects (clusters A, B, and C PD and non-PD) in terms of emotional abuse (χ(2) = 34.864, P < .01), physical abuse (χ(2) = 14.996, P < .05), sex abuse (χ(2) = 9.211, P < .05), and emotional neglect (χ(2) = 17.987, P < .01) were found. Stepwise regression analysis indicated that emotional abuse and emotional neglect were predictive for clusters A and B PD, and sexual abuse was highly predictive for cluster B PD; only emotional neglect was predictive for cluster C PD. Early traumatic experiences are strongly related to the development of PDs. The effects of childhood maltreatment in the 3 clusters of PDs are different. Childhood trauma has the most significant impact on cluster B PD. Copyright © 2012 Elsevier Inc. All rights reserved.

Highly efficient and robust molecular ruthenium catalysts for water oxidation.

PubMed

Duan, Lele; Araujo, Carlos Moyses; Ahlquist, Mårten S G; Sun, Licheng

2012-09-25

Water oxidation catalysts are essential components of light-driven water splitting systems, which could convert water to H(2) driven by solar radiation (H(2)O + hν → 1/2O(2) + H(2)). The oxidation of water (H(2)O → 1/2O(2) + 2H(+) + 2e(-)) provides protons and electrons for the production of dihydrogen (2H(+) + 2e(-) → H(2)), a clean-burning and high-capacity energy carrier. One of the obstacles now is the lack of effective and robust water oxidation catalysts. Aiming at developing robust molecular Ru-bda (H(2)bda = 2,2'-bipyridine-6,6'-dicarboxylic acid) water oxidation catalysts, we carried out density functional theory studies, correlated the robustness of catalysts against hydration with the highest occupied molecular orbital levels of a set of ligands, and successfully directed the synthesis of robust Ru-bda water oxidation catalysts. A series of mononuclear ruthenium complexes [Ru(bda)L(2)] (L = pyridazine, pyrimidine, and phthalazine) were subsequently synthesized and shown to effectively catalyze Ce(IV)-driven [Ce(IV) = Ce(NH(4))(2)(NO(3))(6)] water oxidation with high oxygen production rates up to 286 s(-1) and high turnover numbers up to 55,400.

Cluster fusion-fission dynamics in the Singapore stock exchange

NASA Astrophysics Data System (ADS)

Teh, Boon Kin; Cheong, Siew Ann

2015-10-01

In this paper, we investigate how the cross-correlations between stocks in the Singapore stock exchange (SGX) evolve over 2008 and 2009 within overlapping one-month time windows. In particular, we examine how these cross-correlations change before, during, and after the Sep-Oct 2008 Lehman Brothers Crisis. To do this, we extend the complete-linkage hierarchical clustering algorithm, to obtain robust clusters of stocks with stronger intracluster correlations, and weaker intercluster correlations. After we identify the robust clusters in all time windows, we visualize how these change in the form of a fusion-fission diagram. Such a diagram depicts graphically how the cluster sizes evolve, the exchange of stocks between clusters, as well as how strongly the clusters mix. From the fusion-fission diagram, we see a giant cluster growing and disintegrating in the SGX, up till the Lehman Brothers Crisis in September 2008 and the market crashes of October 2008. After the Lehman Brothers Crisis, clusters in the SGX remain small for few months before giant clusters emerge once again. In the aftermath of the crisis, we also find strong mixing of component stocks between clusters. As a result, the correlation between initially strongly-correlated pairs of stocks decay exponentially with average life time of about a month. These observations impact strongly how portfolios and trading strategies should be formulated.

Genomic characterization and expression analysis of four apolipoprotein A-IV paralogs in Senegalese sole (Solea senegalensis Kaup).

PubMed

Roman-Padilla, J; Rodríguez-Rua, A; Claros, M G; Hachero-Cruzado, I; Manchado, M

2016-01-01

The apolipoprotein A-IV (ApoA-IV) plays a key role in lipid transport and feed intake regulation. In this work, four cDNA sequences encoding ApoA-IV paralogs were identified. Sequence analysis revealed conserved structural features including the common 33-codon block and nine repeated motifs. Gene structure analysis identified four exons and three introns except for apoA-IVAa1 (with only 3 exons). Synteny analysis showed that the four paralogs were structured into two clusters (cluster A containing apoA-IVAa1 and apoA-IVAa2 and cluster B with apoA-IVBa3 and apoA-IVBa4) linked to an apolipoprotein E. Phylogenetic analysis clearly separated the paralogs according to their cluster organization as well as revealed four subclades highly conserved in Acanthopterygii. Whole-mount analyses (WISH) in early larvae (0 and 1day post-hatch (dph)) showed that the four paralogs were mainly expressed in yolk syncytial layer surrounding the oil globules. Later, at 3 and 5dph, the four paralogs were mainly expressed in liver and intestine although with differences in their relative abundance and temporal expression patterns. Diet supply triggered the intensity of WISH signals in the intestine of the four paralogs. Quantification of mRNA abundance by qPCR using whole larvae only detected the induction by diet at 5dph. Moreover, transcript levels increased progressively with age except for apoA-IVAa2, which appeared as a low-expressed isoform. Expression analysis in juvenile tissues confirmed that the four paralogs were mainly expressed in liver and intestine and secondary in other tissues. The role of these ApoA-IV genes in lipid transport and the possible role of apoA-IVAa2 as a regulatory form are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

A Cyber-Attack Detection Model Based on Multivariate Analyses

NASA Astrophysics Data System (ADS)

Sakai, Yuto; Rinsaka, Koichiro; Dohi, Tadashi

In the present paper, we propose a novel cyber-attack detection model based on two multivariate-analysis methods to the audit data observed on a host machine. The statistical techniques used here are the well-known Hayashi's quantification method IV and cluster analysis method. We quantify the observed qualitative audit event sequence via the quantification method IV, and collect similar audit event sequence in the same groups based on the cluster analysis. It is shown in simulation experiments that our model can improve the cyber-attack detection accuracy in some realistic cases where both normal and attack activities are intermingled.

The degree-related clustering coefficient and its application to link prediction

NASA Astrophysics Data System (ADS)

Liu, Yangyang; Zhao, Chengli; Wang, Xiaojie; Huang, Qiangjuan; Zhang, Xue; Yi, Dongyun

2016-07-01

Link prediction plays a significant role in explaining the evolution of networks. However it is still a challenging problem that has been addressed only with topological information in recent years. Based on the belief that network nodes with a great number of common neighbors are more likely to be connected, many similarity indices have achieved considerable accuracy and efficiency. Motivated by the natural assumption that the effect of missing links on the estimation of a node's clustering ability could be related to node degree, in this paper, we propose a degree-related clustering coefficient index to quantify the clustering ability of nodes. Unlike the classical clustering coefficient, our new coefficient is highly robust when the observed bias of links is considered. Furthermore, we propose a degree-related clustering ability path (DCP) index, which applies the proposed coefficient to the link prediction problem. Experiments on 12 real-world networks show that our proposed method is highly accurate and robust compared with four common-neighbor-based similarity indices (Common Neighbors(CN), Adamic-Adar(AA), Resource Allocation(RA), and Preferential Attachment(PA)), and the recently introduced clustering ability (CA) index.

Determination of Arctic sea ice variability modes on interannual timescales via nonhierarchical clustering

NASA Astrophysics Data System (ADS)

Fučkar, Neven-Stjepan; Guemas, Virginie; Massonnet, François; Doblas-Reyes, Francisco

2015-04-01

Over the modern observational era, the northern hemisphere sea ice concentration, age and thickness have experienced a sharp long-term decline superimposed with strong internal variability. Hence, there is a crucial need to identify robust patterns of Arctic sea ice variability on interannual timescales and disentangle them from the long-term trend in noisy datasets. The principal component analysis (PCA) is a versatile and broadly used method for the study of climate variability. However, the PCA has several limiting aspects because it assumes that all modes of variability have symmetry between positive and negative phases, and suppresses nonlinearities by using a linear covariance matrix. Clustering methods offer an alternative set of dimension reduction tools that are more robust and capable of taking into account possible nonlinear characteristics of a climate field. Cluster analysis aggregates data into groups or clusters based on their distance, to simultaneously minimize the distance between data points in a given cluster and maximize the distance between the centers of the clusters. We extract modes of Arctic interannual sea-ice variability with nonhierarchical K-means cluster analysis and investigate the mechanisms leading to these modes. Our focus is on the sea ice thickness (SIT) as the base variable for clustering because SIT holds most of the climate memory for variability and predictability on interannual timescales. We primarily use global reconstructions of sea ice fields with a state-of-the-art ocean-sea-ice model, but we also verify the robustness of determined clusters in other Arctic sea ice datasets. Applied cluster analysis over the 1958-2013 period shows that the optimal number of detrended SIT clusters is K=3. Determined SIT cluster patterns and their time series of occurrence are rather similar between different seasons and months. Two opposite thermodynamic modes are characterized with prevailing negative or positive SIT anomalies over the Arctic basin. The intermediate mode, with negative anomalies centered on the East Siberian shelf and positive anomalies along the North American side of the basin, has predominately dynamic characteristics. The associated sea ice concentration (SIC) clusters vary more between different seasons and months, but the SIC patterns are physically framed by the SIT cluster patterns.

The Evolution of SINEs and LINEs in the genus Chironomus (Diptera).

PubMed

Papusheva, Ekaterina; Gruhl, Mary C; Berezikov, Eugene; Groudieva, Tatiana; Scherbik, Svetlana V; Martin, Jon; Blinov, Alexander; Bergtrom, Gerald

2004-03-01

Genomic DNA amplification from 51 species of the family Chironomidae shows that most contain relatives of NLRCth1 LINE and CTRT1 SINE retrotransposons first found in Chironomus thummi. More than 300 cloned PCR products were sequenced. The amplified region of the reverse transcriptase gene in the LINEs is intact and highly conserved, suggesting active elements. The SINEs are less conserved, consistent with minimal/no selection after transposition. A mitochondrial gene phylogeny resolves the Chironomus genus into six lineages (Guryev et al. 2001). LINE and SINE phylogenies resolve five of these lineages, indicating their monophyletic origin and vertical inheritance. However, both the LINE and the SINE tree topologies differ from the species phylogeny, resolving the elements into "clusters I-IV" and "cluster V" families. The data suggest a descent of all LINE and SINE subfamilies from two major families. Based on the species phylogeny, a few LINEs and a larger number of SINEs are cladisitically misplaced. Most misbranch with LINEs or SINEs from species with the same families of elements. From sequence comparisons, cladistically misplaced LINEs and several misplaced SINEs arose by convergent base substitutions. More diverged SINEs result from early transposition and some are derived from multiple source SINEs in the same species. SINEs from two species (C. dorsalis, C. pallidivittatus), expected to belong to the clusters I-IV family, branch instead with cluster V family SINEs; apparently both families predate separation of cluster V from clusters I-IV species. Correlation of the distribution of active SINEs and LINEs, as well as similar 3' sequence motifs in CTRT1 and NLRCth1, suggests coevolving retrotransposon pairs in which CTRT1 transposition depends on enzymes active during NLRCth1 LINE mobility.

A CHRNA5 Smoking Risk Variant Decreases the Aversive Effects of Nicotine in Humans.

PubMed

Jensen, Kevin P; DeVito, Elise E; Herman, Aryeh I; Valentine, Gerald W; Gelernter, Joel; Sofuoglu, Mehmet

2015-11-01

Genome-wide association studies have implicated the CHRNA5-CHRNA3-CHRNB4 gene cluster in risk for heavy smoking and several smoking-related disorders. The heavy smoking risk allele might reduce the aversive effects of nicotine, but this hypothesis has not been tested in humans. We evaluated the effects of a candidate causal variant in CHRNA5, rs16969968, on the acute response to nicotine in European American (EA) and African American (AA) smokers (n=192; 50% AA; 73% male). Following overnight abstinence from nicotine, participants completed a protocol that included an intravenous (IV) dose of saline and two escalating IV doses of nicotine. The outcomes evaluated were the aversive, pleasurable, and stimulatory ratings of nicotine's effects, cardiovascular reactivity to nicotine, withdrawal severity, and cognitive performance before and after the nicotine administration session. The heavy smoking risk allele (rs16969968*A; frequency=28% (EA) and 6% (AA)) was associated with lower ratings of aversive effects (P<5 × 10(-8)) with marked specificity. This effect was evident in EA and AA subjects analyzed as separate groups and was most robust at the highest nicotine dose. Rs16969968*A was also associated with greater improvement on a measure of cognitive control (Stroop Task) following nicotine administration. These findings support differential aversive response to nicotine as one likely mechanism for the association of CHRNA5-CHRNA3-CHRNB4 with heavy smoking.

Triosmium Clusters on a Support: Determination of Structure by X-Ray Absorption Spectroscopy and High-Resolution Microscopy

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

Shareghe, Mehraeen; Chi, Miaofang; Browning, Nigel D.

2011-01-01

The structures of small, robust metal clusters on a solid support were determined by a combination of spectroscopic and microscopic methods: extended X-ray absorption fine structure (EXAFS) spectroscopy, scanning transmission electron microscopy (STEM), and aberration-corrected STEM. The samples were synthesized from [Os{sub 3}(CO){sub 12}] on MgO powder to provide supported clusters intended to be triosmium. The results demonstrate that the supported clusters are robust in the absence of oxidants. Conventional high-angle annular dark-field (HAADF) STEM images demonstrate a high degree of uniformity of the clusters, with root-mean-square (rms) radii of 2.03 {+-} 0.06 {angstrom}. The EXAFS OsOs coordination number ofmore » 2.1 {+-} 0.4 confirms the presence of triosmium clusters on average and correspondingly determines an average rms cluster radius of 2.02 {+-} 0.04 {angstrom}. The high-resolution STEM images show the individual Os atoms in the clusters, confirming the triangular structures of their frames and determining OsOs distances of 2.80 {+-} 0.14 {angstrom}, matching the EXAFS value of 2.89 {+-} 0.06 {angstrom}. IR and EXAFS spectra demonstrate the presence of CO ligands on the clusters. This set of techniques is recommended as optimal for detailed and reliable structural characterization of supported clusters.« less

Fractalkine Signaling Attenuates Perivascular Clustering of Microglia and Fibrinogen Leakage during Systemic Inflammation in Mouse Models of Diabetic Retinopathy

PubMed Central

Mendiola, Andrew S.; Garza, Rolando; Cardona, Sandra M.; Mythen, Shannon A.; Lira, Sergio A.; Akassoglou, Katerina; Cardona, Astrid E.

2017-01-01

Fractalkine (FKN) is a chemokine expressed constitutively by healthy neurons and signals to microglia upon interaction with the FKN receptor, CX3CR1. Signaling between FKN and CX3CR1 transduces inhibitory signals that ameliorate microglial activation and proinflammatory cytokine release in neuroinflammatory conditions. The aim of this study is to determine the mechanisms associated with microglial activation and vascular leakage during diabetic retinopathy (DR) and under conditions of low-level endotoxemia, common in diabetic patients. Utilizing the Ins2Akita strain (Akita), a mouse model of type 1 diabetes, our results show that leakage of the blood-protein fibrin(ogen) into the retina occurs as a result of chronic (4 months) but not acute (1.5 months) hyperglycemia. Conversely, inducing endotoxin-mediated systemic inflammation during acute diabetes resulted in fibrinogen deposition in the retina, a phenotype that was exacerbated in mice lacking CX3CR1 signaling. Systemic inflammation in Cx3cr1−/− mice led to robust perivascular clustering of proliferating microglia in areas of fibrinogen extravasation, and induced IL-1β expression in microglia and astrocytes. Lastly, we determined a protective effect of modulating FKN/CX3CR1 signaling in the diabetic retina. We show that intravitreal (iv) administration of recombinant FKN into diabetic FKN-KO mice, reduced fibrinogen deposition and perivascular clustering of microglia in the retina during systemic inflammation. These data suggest that dysregulated microglial activation via loss of FKN/CX3CR1 signaling disrupts the vascular integrity in retina during systemic inflammation. PMID:28119571

Transportation: Grade 8. Cluster IV.

ERIC Educational Resources Information Center

Calhoun, Olivia H.

A curriculum guide for grade 8, the document is devoted to the occupational cluster "Transportation." It is divided into five units: surface transportation, interstate transportation, air transportation, water transportation, and subterranean transportation (the Metro). Each unit is introduced by a statement of the topic, the unit's…

Geographic structure evidenced in the toxic dinoflagellate Alexandrium pacificum Litaker (A. catenella - group IV (Whedon & Kofoid) Balech) along Japanese and Chinese coastal waters.

PubMed

Genovesi, Benjamin; Berrebi, Patrick; Nagai, Satoshi; Reynaud, Nathalie; Wang, Jinhui; Masseret, Estelle

2015-09-15

The intra-specific diversity and genetic structure within the Alexandrium pacificum Litaker (A. catenella - Group IV) populations along the Temperate Asian coasts, were studied among individuals isolated from Japan to China. The UPGMA dendrogram and FCA revealed the existence of 3 clusters. Assignment analysis suggested the occurrence of gene flows between the Japanese Pacific coast (cluster-1) and the Chinese Zhejiang coast (cluster-2). Human transportations are suspected to explain the lack of genetic difference between several pairs of distant Japanese samples, hardly explained by a natural dispersal mechanism. The genetic isolation of the population established in the Sea of Japan (cluster-3) suggested the existence of a strong ecological and geographical barrier. Along the Pacific coasts, the South-North current allows limited exchanges between Chinese and Japanese populations. The relationships between Temperate Asian and Mediterranean individuals suggested different scenario of large-scale dispersal mechanisms. Copyright © 2015. Published by Elsevier Ltd.

Performance of small cluster surveys and the clustered LQAS design to estimate local-level vaccination coverage in Mali

PubMed Central

2012-01-01

Background Estimation of vaccination coverage at the local level is essential to identify communities that may require additional support. Cluster surveys can be used in resource-poor settings, when population figures are inaccurate. To be feasible, cluster samples need to be small, without losing robustness of results. The clustered LQAS (CLQAS) approach has been proposed as an alternative, as smaller sample sizes are required. Methods We explored (i) the efficiency of cluster surveys of decreasing sample size through bootstrapping analysis and (ii) the performance of CLQAS under three alternative sampling plans to classify local VC, using data from a survey carried out in Mali after mass vaccination against meningococcal meningitis group A. Results VC estimates provided by a 10 × 15 cluster survey design were reasonably robust. We used them to classify health areas in three categories and guide mop-up activities: i) health areas not requiring supplemental activities; ii) health areas requiring additional vaccination; iii) health areas requiring further evaluation. As sample size decreased (from 10 × 15 to 10 × 3), standard error of VC and ICC estimates were increasingly unstable. Results of CLQAS simulations were not accurate for most health areas, with an overall risk of misclassification greater than 0.25 in one health area out of three. It was greater than 0.50 in one health area out of two under two of the three sampling plans. Conclusions Small sample cluster surveys (10 × 15) are acceptably robust for classification of VC at local level. We do not recommend the CLQAS method as currently formulated for evaluating vaccination programmes. PMID:23057445

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

A Spatiotemporal Clustering Approach to Maritime Domain Awareness

DTIC Science & Technology

2013-09-01

1997. [25] M. E. Celebi, “Effective initialization of k-means for color quantization,” 16th IEEE International Conference on Image Processing (ICIP...release; distribution is unlimited 12b. DISTRIBUTION CODE 13. ABSTRACT (maximum 200 words) Spatiotemporal clustering is the process of grouping...Department of Electrical and Computer Engineering iv THIS PAGE INTENTIONALLY LEFT BLANK v ABSTRACT Spatiotemporal clustering is the process of

Testing alternative factor models of PTSD and the robustness of the dysphoria factor.

PubMed

Elklit, Ask; Armour, Cherie; Shevlin, Mark

2010-01-01

This study first aimed to examine the structure of self-reported posttraumatic stress disorder (PTSD) symptoms using three different samples. The second aim of the paper was to test the robustness of the factor analytic model when depression scores were controlled for. Based on previous factor analytic findings and the DSM-IV formulation, six confirmatory factor models were specified and estimated that reflected different symptom clusters. The best fitting model was subsequently re-fitted to the data after including a depression variable. The analyses were based on responses from 973 participants across three samples. Sample 1 consisted of 633 parents who were members of 'The National Association of Infant Death' and who had lost a child. Sample 2 consisted of 227 victims of rape, who completed a questionnaire within 4 weeks of the rape. Each respondent had been in contact with the Centre for Rape Victims (CRV) at the Aarhus University Hospital, Denmark. Sample 3 consisted of 113 refugees resident in Denmark. All participants had been referred to a treatment centre which focused on rehabilitating refugees through treatment for psychosocial integration problems (RRCF: Rehabliterings og Revliderings Centre for Flygtninge). In total 500 participants received a diagnosis of PTSD/sub-clinical PTSD (Sample 1, N=214; 2, N=176; 3, N=110). A correlated four-factor model with re-experiencing, avoidance, dysphoria, and arousal factors provided the best fit to the sample data. The average attenuation in the factor loadings was highest for the dysphoria factor (M=-.26, SD=.11) compared to the re-experiencing (M=-.14, SD=.18), avoidance (M=-.10, SD=.21), and arousal (M=-.09, SD=.13) factors. With regards to the best fitting factor model these results concur with previous research findings using different trauma populations but do not reflect the current DSM-IV symptom groupings. The attenuation of dysphoria factor loadings suggests that dysphoria is a non-specific component of PTSD.

Factor structure and individual patterns of DSM-IV conduct disorder criteria in adolescent psychiatric inpatients.

PubMed

Janson, Harald; Kjelsberg, Ellen

2006-01-01

We investigated the factor structure of the DSM-IV conduct disorder (CD) diagnostic criteria and typical individual patterns of CD subscales in an adolescent inpatient population using detailed hospital records of a Norwegian nationwide sample of 1087 adolescent psychiatric inpatients scored for the 15 DSM-IV CD criteria. Varimax rotated principal components and full-information factor analyses of 12 CD criteria were carried out separately for boys and girls employing two methods. Standardized values on three subscales of CD criteria were subjected to Ward's method of hierarchical cluster analyses followed by k-means relocation employing a double cross-replication design. Similar factor structures emerged regardless of factoring method and gender. With the exception of Criteria 8 ("Fire setting") and 14 ("Run away from home") the factor loadings for both genders were in accordance with Loeber's tripartite model, with Aggression, Delinquency, and Rule Breaking factors largely corresponding to Loeber's overt, covert and authority conflict pathways. A five-cluster solution proved highly replicable and interpretable. One cluster gathered adolescents without CD, and the remaining four described groups with different conceptually meaningful constellations of CD criteria, which were not equally prevalent in each gender. Delinquency appeared in all symptomatic clusters. The cluster analytic results highlighted typical forms of expressions of conduct problems, and the fact that these forms may not be equally prevalent in girls and boys even while the underlying structure of conduct problems may be similar across genders. Future research should address the prediction of specific outcomes from CD criteria subscales or constellations.

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

PubMed

Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

2018-01-01

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

Predictors of comorbid personality disorders in patients with panic disorder with agoraphobia.

PubMed

Latas, M; Starcevic, V; Trajkovic, G; Bogojevic, G

2000-01-01

The aim of this study was to ascertain predictors of comorbid personality disorders in patients with panic disorder with agoraphobia (PDAG). Sixty consecutive outpatients with PDAG were administered the Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II) for the purpose of diagnosing personality disorders. Logistic regressions were used to identify predictors of any comorbid personality disorder, any DSM-IV cluster A, cluster B, and cluster C personality disorder. Independent variables in these regressions were gender, age, duration of panic disorder (PD), severity of PDAG, and scores on self-report instruments that assess the patient's perception of their parents, childhood separation anxiety, and traumatic experiences. High levels of parental protection on the Parental Bonding Instrument (PBI), indicating a perception of the parents as overprotective and controlling, emerged as the only statistically significant predictor of any comorbid personality disorder. This finding was attributed to the association between parental overprotection and cluster B personality disorders, particularly borderline personality disorder. The duration of PD was a significant predictor of any cluster B and any cluster C personality disorder, suggesting that some of the cluster B and cluster C personality disorders may be a consequence of the long-lasting PDAG. Any cluster B personality disorder was also associated with younger age. In conclusion, despite a generally nonspecific nature of the relationship between parental overprotection in childhood and adult psychopathology, the findings of this study suggest some specificity for the association between parental overprotection in childhood and personality disturbance in PDAG patients, particularly cluster B personality disorders.

Amplified Fragment Length Polymorphism Fingerprinting of Pseudomonas Strains from a Poultry Processing Plant

PubMed Central

Geornaras, Ifigenia; Kunene, Nokuthula F.; von Holy, Alexander; Hastings, John W.

1999-01-01

Molecular typing has been used previously to identify and trace dissemination of pathogenic and spoilage bacteria associated with food processing. Amplified fragment length polymorphism (AFLP) is a novel DNA fingerprinting technique which is considered highly reproducible and has high discriminatory power. This technique was used to fingerprint 88 Pseudomonas fluorescens and Pseudomonas putida strains that were previously isolated from plate counts of carcasses at six processing stages and various equipment surfaces and environmental sources of a poultry abattoir. Clustering of the AFLP patterns revealed a high level of diversity among the strains. Six clusters (clusters I through VI) were delineated at an arbitrary Dice coefficient level of 0.65; clusters III (31 strains) and IV (28 strains) were the largest clusters. More than one-half (52.3%) of the strains obtained from carcass samples, which may have represented the resident carcass population, grouped together in cluster III. By contrast, 43.2% of the strains from most of the equipment surfaces and environmental sources grouped together in cluster IV. In most cases, the clusters in which carcass strains from processing stages grouped corresponded to the clusters in which strains from the associated equipment surfaces and/or environmental sources were found. This provided evidence that there was cross-contamination between carcasses and the abattoir environment at the DNA level. The AFLP data also showed that strains were being disseminated from the beginning to the end of the poultry processing operation, since many strains associated with carcasses at the packaging stage were members of the same clusters as strains obtained from carcasses after the defeathering stage. PMID:10473382

Amplified fragment length polymorphism fingerprinting of Pseudomonas strains from a poultry processing plant.

PubMed

Geornaras, I; Kunene, N F; von Holy, A; Hastings, J W

1999-09-01

Molecular typing has been used previously to identify and trace dissemination of pathogenic and spoilage bacteria associated with food processing. Amplified fragment length polymorphism (AFLP) is a novel DNA fingerprinting technique which is considered highly reproducible and has high discriminatory power. This technique was used to fingerprint 88 Pseudomonas fluorescens and Pseudomonas putida strains that were previously isolated from plate counts of carcasses at six processing stages and various equipment surfaces and environmental sources of a poultry abattoir. Clustering of the AFLP patterns revealed a high level of diversity among the strains. Six clusters (clusters I through VI) were delineated at an arbitrary Dice coefficient level of 0.65; clusters III (31 strains) and IV (28 strains) were the largest clusters. More than one-half (52.3%) of the strains obtained from carcass samples, which may have represented the resident carcass population, grouped together in cluster III. By contrast, 43.2% of the strains from most of the equipment surfaces and environmental sources grouped together in cluster IV. In most cases, the clusters in which carcass strains from processing stages grouped corresponded to the clusters in which strains from the associated equipment surfaces and/or environmental sources were found. This provided evidence that there was cross-contamination between carcasses and the abattoir environment at the DNA level. The AFLP data also showed that strains were being disseminated from the beginning to the end of the poultry processing operation, since many strains associated with carcasses at the packaging stage were members of the same clusters as strains obtained from carcasses after the defeathering stage.

Unsupervised, Robust Estimation-based Clustering for Multispectral Images

NASA Technical Reports Server (NTRS)

Netanyahu, Nathan S.

1997-01-01

To prepare for the challenge of handling the archiving and querying of terabyte-sized scientific spatial databases, the NASA Goddard Space Flight Center's Applied Information Sciences Branch (AISB, Code 935) developed a number of characterization algorithms that rely on supervised clustering techniques. The research reported upon here has been aimed at continuing the evolution of some of these supervised techniques, namely the neural network and decision tree-based classifiers, plus extending the approach to incorporating unsupervised clustering algorithms, such as those based on robust estimation (RE) techniques. The algorithms developed under this task should be suited for use by the Intelligent Information Fusion System (IIFS) metadata extraction modules, and as such these algorithms must be fast, robust, and anytime in nature. Finally, so that the planner/schedule module of the IlFS can oversee the use and execution of these algorithms, all information required by the planner/scheduler must be provided to the IIFS development team to ensure the timely integration of these algorithms into the overall system.

Robust and Efficient Biomolecular Clustering of Tumor Based on ${p}$ -Norm Singular Value Decomposition.

PubMed

Kong, Xiang-Zhen; Liu, Jin-Xing; Zheng, Chun-Hou; Hou, Mi-Xiao; Wang, Juan

2017-07-01

High dimensionality has become a typical feature of biomolecular data. In this paper, a novel dimension reduction method named p-norm singular value decomposition (PSVD) is proposed to seek the low-rank approximation matrix to the biomolecular data. To enhance the robustness to outliers, the Lp-norm is taken as the error function and the Schatten p-norm is used as the regularization function in the optimization model. To evaluate the performance of PSVD, the Kmeans clustering method is then employed for tumor clustering based on the low-rank approximation matrix. Extensive experiments are carried out on five gene expression data sets including two benchmark data sets and three higher dimensional data sets from the cancer genome atlas. The experimental results demonstrate that the PSVD-based method outperforms many existing methods. Especially, it is experimentally proved that the proposed method is more efficient for processing higher dimensional data with good robustness, stability, and superior time performance.

Instrumental variables estimates of peer effects in social networks.

PubMed

An, Weihua

2015-03-01

Estimating peer effects with observational data is very difficult because of contextual confounding, peer selection, simultaneity bias, and measurement error, etc. In this paper, I show that instrumental variables (IVs) can help to address these problems in order to provide causal estimates of peer effects. Based on data collected from over 4000 students in six middle schools in China, I use the IV methods to estimate peer effects on smoking. My design-based IV approach differs from previous ones in that it helps to construct potentially strong IVs and to directly test possible violation of exogeneity of the IVs. I show that measurement error in smoking can lead to both under- and imprecise estimations of peer effects. Based on a refined measure of smoking, I find consistent evidence for peer effects on smoking. If a student's best friend smoked within the past 30 days, the student was about one fifth (as indicated by the OLS estimate) or 40 percentage points (as indicated by the IV estimate) more likely to smoke in the same time period. The findings are robust to a variety of robustness checks. I also show that sharing cigarettes may be a mechanism for peer effects on smoking. A 10% increase in the number of cigarettes smoked by a student's best friend is associated with about 4% increase in the number of cigarettes smoked by the student in the same time period. Copyright © 2014 Elsevier Inc. All rights reserved.

Exemplar-Based Clustering via Simulated Annealing

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich

2009-01-01

Several authors have touted the p-median model as a plausible alternative to within-cluster sums of squares (i.e., K-means) partitioning. Purported advantages of the p-median model include the provision of "exemplars" as cluster centers, robustness with respect to outliers, and the accommodation of a diverse range of similarity data. We developed…

Construction and Environment: Grade 7. Cluster IV.

ERIC Educational Resources Information Center

Calhoun, Olivia H.

A curriculum guide for grade 7, the document is devoted to the occupational cluster "Construction and Environment." It is divided into four units: urban renewal and development, urban and suburban construction and planning, megalopolis, and demography. Each unit is introduced by a statement of the topic, the unit's purpose, main ideas,…

PROPERTIES OF QSO METAL-LINE ABSORPTION SYSTEMS AT HIGH REDSHIFTS: NATURE AND EVOLUTION OF THE ABSORBERS AND NEW EVIDENCE ON ESCAPE OF IONIZING RADIATION FROM GALAXIES

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

Boksenberg, Alec; Sargent, Wallace L. W., E-mail: boksy@ast.cam.ac.uk

2015-05-15

Using Voigt-profile-fitting procedures on Keck High Resolution Spectrograph spectra of nine QSOs, we identify 1099 C IV absorber components clumped in 201 systems outside the Lyman forest over 1.6 ≲ z ≲ 4.4. With associated Si IV, C II, Si II  and N V where available, we investigate the bulk statistical and ionization properties of the components and systems and find no significant change in redshift for C IV and Si IV while C II, Si II  and N V change substantially. The C IV components exhibit strong clustering, but no clustering is detected for systems on scales from 150 kmmore » s{sup –1} out to 50,000 km s{sup –1}. We conclude that the clustering is due entirely to the peculiar velocities of gas present in the circumgalactic media of galaxies. Using specific combinations of ionic ratios, we compare our observations with model ionization predictions for absorbers exposed to the metagalactic ionizing radiation background augmented by proximity radiation from their associated galaxies and find that the generally accepted means of radiative escape by transparent channels from the internal star-forming sites is spectrally not viable for our stronger absorbers. We develop an active scenario based on runaway stars with resulting changes in the efflux of radiation that naturally enable the needed spectral convergence, and in turn provide empirical indicators of morphological evolution in the associated galaxies. Together with a coexisting population of relatively compact galaxies indicated by the weaker absorbers in our sample, the collective escape of radiation is sufficient to maintain the intergalactic medium ionized over the full range 1.9 < z ≲ 4.4.« less

Butyrate production in phylogenetically diverse Firmicutes isolated from the chicken caecum

PubMed Central

Eeckhaut, Venessa; Van Immerseel, Filip; Croubels, Siska; De Baere, Siegrid; Haesebrouck, Freddy; Ducatelle, Richard; Louis, Petra; Vandamme, Peter

2011-01-01

Summary Sixteen butyrate‐producing bacteria were isolated from the caecal content of chickens and analysed phylogenetically. They did not represent a coherent phylogenetic group, but were allied to four different lineages in the Firmicutes phylum. Fourteen strains appeared to represent novel species, based on a level of ≤ 98.5% 16S rRNA gene sequence similarity towards their nearest validly named neighbours. The highest butyrate concentrations were produced by the strains belonging to clostridial clusters IV and XIVa, clusters which are predominant in the chicken caecal microbiota. In only one of the 16 strains tested, the butyrate kinase operon could be amplified, while the butyryl‐CoA : acetate CoA‐transferase gene was detected in eight strains belonging to clostridial clusters IV, XIVa and XIVb. None of the clostridial cluster XVI isolates carried this gene based on degenerate PCR analyses. However, another CoA‐transferase gene more similar to propionate CoA‐transferase was detected in the majority of the clostridial cluster XVI isolates. Since this gene is located directly downstream of the remaining butyrate pathway genes in several human cluster XVI bacteria, it may be involved in butyrate formation in these bacteria. The present study indicates that butyrate producers related to cluster XVI may play a more important role in the chicken gut than in the human gut. PMID:21375722

Multi-Optimisation Consensus Clustering

NASA Astrophysics Data System (ADS)

Li, Jian; Swift, Stephen; Liu, Xiaohui

Ensemble Clustering has been developed to provide an alternative way of obtaining more stable and accurate clustering results. It aims to avoid the biases of individual clustering algorithms. However, it is still a challenge to develop an efficient and robust method for Ensemble Clustering. Based on an existing ensemble clustering method, Consensus Clustering (CC), this paper introduces an advanced Consensus Clustering algorithm called Multi-Optimisation Consensus Clustering (MOCC), which utilises an optimised Agreement Separation criterion and a Multi-Optimisation framework to improve the performance of CC. Fifteen different data sets are used for evaluating the performance of MOCC. The results reveal that MOCC can generate more accurate clustering results than the original CC algorithm.

Tissue Probability Map Constrained 4-D Clustering Algorithm for Increased Accuracy and Robustness in Serial MR Brain Image Segmentation

PubMed Central

Xue, Zhong; Shen, Dinggang; Li, Hai; Wong, Stephen

2010-01-01

The traditional fuzzy clustering algorithm and its extensions have been successfully applied in medical image segmentation. However, because of the variability of tissues and anatomical structures, the clustering results might be biased by the tissue population and intensity differences. For example, clustering-based algorithms tend to over-segment white matter tissues of MR brain images. To solve this problem, we introduce a tissue probability map constrained clustering algorithm and apply it to serial MR brain image segmentation, i.e., a series of 3-D MR brain images of the same subject at different time points. Using the new serial image segmentation algorithm in the framework of the CLASSIC framework, which iteratively segments the images and estimates the longitudinal deformations, we improved both accuracy and robustness for serial image computing, and at the mean time produced longitudinally consistent segmentation and stable measures. In the algorithm, the tissue probability maps consist of both the population-based and subject-specific segmentation priors. Experimental study using both simulated longitudinal MR brain data and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) data confirmed that using both priors more accurate and robust segmentation results can be obtained. The proposed algorithm can be applied in longitudinal follow up studies of MR brain imaging with subtle morphological changes for neurological disorders. PMID:26566399

Robust water fat separated dual-echo MRI by phase-sensitive reconstruction.

PubMed

Romu, Thobias; Dahlström, Nils; Leinhard, Olof Dahlqvist; Borga, Magnus

2017-09-01

The purpose of this work was to develop and evaluate a robust water-fat separation method for T1-weighted symmetric two-point Dixon data. A method for water-fat separation by phase unwrapping of the opposite-phase images by phase-sensitive reconstruction (PSR) is introduced. PSR consists of three steps; (1), identification of clusters of tissue voxels; (2), unwrapping of the phase in each cluster by solving Poisson's equation; and (3), finding the correct sign of each unwrapped opposite-phase cluster, so that the water-fat images are assigned the correct identities. Robustness was evaluated by counting the number of water-fat swap artifacts in a total of 733 image volumes. The method was also compared to commercial software. In the water-fat separated image volumes, the PSR method failed to unwrap the phase of one cluster and misclassified 10. One swap was observed in areas affected by motion and was constricted to the affected area. Twenty swaps were observed surrounding susceptibility artifacts, none of which spread outside the artifact affected regions. The PSR method had fewer swaps when compared to commercial software. The PSR method can robustly produce water-fat separated whole-body images based on symmetric two-echo spoiled gradient echo images, under both ideal conditions and in the presence of common artifacts. Magn Reson Med 78:1208-1216, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

A generalized Lyapunov theory for robust root clustering of linear state space models with real parameter uncertainty

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1992-01-01

The problem of analyzing and designing controllers for linear systems subject to real parameter uncertainty is considered. An elegant, unified theory for robust eigenvalue placement is presented for a class of D-regions defined by algebraic inequalities by extending the nominal matrix root clustering theory of Gutman and Jury (1981) to linear uncertain time systems. The author presents explicit conditions for matrix root clustering for different D-regions and establishes the relationship between the eigenvalue migration range and the parameter range. The bounds are all obtained by one-shot computation in the matrix domain and do not need any frequency sweeping or parameter gridding. The method uses the generalized Lyapunov theory for getting the bounds.

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

Petit, Chad M.; Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Rouge, LA 70803; Chouljenko, Vladimir N.

The SARS-coronavirus (SARS-CoV) is the etiological agent of the severe acute respiratory syndrome (SARS). The SARS-CoV spike (S) glycoprotein mediates membrane fusion events during virus entry and virus-induced cell-to-cell fusion. The cytoplasmic portion of the S glycoprotein contains four cysteine-rich amino acid clusters. Individual cysteine clusters were altered via cysteine-to-alanine amino acid replacement and the modified S glycoproteins were tested for their transport to cell-surfaces and ability to cause cell fusion in transient transfection assays. Mutagenesis of the cysteine cluster I, located immediately proximal to the predicted transmembrane, domain did not appreciably reduce cell-surface expression, although S-mediated cell fusion wasmore » reduced by more than 50% in comparison to the wild-type S. Similarly, mutagenesis of the cysteine cluster II located adjacent to cluster I reduced S-mediated cell fusion by more than 60% compared to the wild-type S, while cell-surface expression was reduced by less than 20%. Mutagenesis of cysteine clusters III and IV did not appreciably affect S cell-surface expression or S-mediated cell fusion. The wild-type S was palmitoylated as evidenced by the efficient incorporation of {sup 3}H-palmitic acid in wild-type S molecules. S glycoprotein palmitoylation was significantly reduced for mutant glycoproteins having cluster I and II cysteine changes, but was largely unaffected for cysteine cluster III and IV mutants. These results show that the S cytoplasmic domain is palmitoylated and that palmitoylation of the membrane proximal cysteine clusters I and II may be important for S-mediated cell fusion.« less

Instrumental variables and Mendelian randomization with invalid instruments

NASA Astrophysics Data System (ADS)

Kang, Hyunseung

Instrumental variables (IV) methods have been widely used to determine the causal effect of a treatment, exposure, policy, or an intervention on an outcome of interest. The IV method relies on having a valid instrument, a variable that is (A1) associated with the exposure, (A2) has no direct effect on the outcome, and (A3) is unrelated to the unmeasured confounders associated with the exposure and the outcome. However, in practice, finding a valid instrument, especially those that satisfy (A2) and (A3), can be challenging. For example, in Mendelian randomization studies where genetic markers are used as instruments, complete knowledge about instruments' validity is equivalent to complete knowledge about the involved genes' functions. The dissertation explores the theory, methods, and application of IV methods when invalid instruments are present. First, when we have multiple candidate instruments, we establish a theoretical bound whereby causal effects are only identified as long as less than 50% of instruments are invalid, without knowing which of the instruments are invalid. We also propose a fast penalized method, called sisVIVE, to estimate the causal effect. We find that sisVIVE outperforms traditional IV methods when invalid instruments are present both in simulation studies as well as in real data analysis. Second, we propose a robust confidence interval under the multiple invalid IV setting. This work is an extension of our work on sisVIVE. However, unlike sisVIVE which is robust to violations of (A2) and (A3), our confidence interval procedure provides honest coverage even if all three assumptions, (A1)-(A3), are violated. Third, we study the single IV setting where the one IV we have may actually be invalid. We propose a nonparametric IV estimation method based on full matching, a technique popular in causal inference for observational data, that leverages observed covariates to make the instrument more valid. We propose an estimator along with inferential results that are robust to mis-specifications of the covariate-outcome model. We also provide a sensitivity analysis should the instrument turn out to be invalid, specifically violate (A3). Fourth, in application work, we study the causal effect of malaria on stunting among children in Ghana. Previous studies on the effect of malaria and stunting were observational and contained various unobserved confounders, most notably nutritional deficiencies. To infer causality, we use the sickle cell genotype, a trait that confers some protection against malaria and was randomly assigned at birth, as an IV and apply our nonparametric IV method. We find that the risk of stunting increases by 0.22 (95% CI: 0.044,1) for every malaria episode and is sensitive to unmeasured confounders.

Insights into quasar UV spectra using unsupervised clustering analysis

NASA Astrophysics Data System (ADS)

Tammour, A.; Gallagher, S. C.; Daley, M.; Richards, G. T.

2016-06-01

Machine learning techniques can provide powerful tools to detect patterns in multidimensional parameter space. We use K-means - a simple yet powerful unsupervised clustering algorithm which picks out structure in unlabelled data - to study a sample of quasar UV spectra from the Quasar Catalog of the 10th Data Release of the Sloan Digital Sky Survey (SDSS-DR10) of Paris et al. Detecting patterns in large data sets helps us gain insights into the physical conditions and processes giving rise to the observed properties of quasars. We use K-means to find clusters in the parameter space of the equivalent width (EW), the blue- and red-half-width at half-maximum (HWHM) of the Mg II 2800 Å line, the C IV 1549 Å line, and the C III] 1908 Å blend in samples of broad absorption line (BAL) and non-BAL quasars at redshift 1.6-2.1. Using this method, we successfully recover correlations well-known in the UV regime such as the anti-correlation between the EW and blueshift of the C IV emission line and the shape of the ionizing spectra energy distribution (SED) probed by the strength of He II and the Si III]/C III] ratio. We find this to be particularly evident when the properties of C III] are used to find the clusters, while those of Mg II proved to be less strongly correlated with the properties of the other lines in the spectra such as the width of C IV or the Si III]/C III] ratio. We conclude that unsupervised clustering methods (such as K-means) are powerful methods for finding `natural' binning boundaries in multidimensional data sets and discuss caveats and future work.

Familial Clustering of Executive Functioning in Affected Sibling Pair Families with ADHD

ERIC Educational Resources Information Center

Slaats-Willemse, Dorine; Swaab-Barneveld, Hanna; De Sonneville, Leo; Buitelaar, Jan

2005-01-01

Objective: To investigate familial clustering of executive functioning (i.e., response inhibition, fine visuomotor functioning, and attentional control) in attention-deficit/hyperactivity disorder (ADHD)-affected sibling pairs. Method: Fifty-two affected sibling pairs aged 6 to 18 years and diagnosed with ADHD according to DSM-IV performed the…

The Effect of Draft DSM-5 Criteria on Posttraumatic Stress Disorder Prevalence

PubMed Central

Calhoun, Patrick S.; Hertzberg, Jeffrey S.; Kirby, Angela C.; Dennis, Michelle F.; Hair, Lauren P.; Dedert, Eric A.; Beckham, Jean C.

2012-01-01

Background This study was designed to examine the concordance of proposed DSM-5 posttraumatic stress disorder (PTSD) criteria with DSM-IV classification rules and examine the impact of the proposed DSM-5 PTSD criteria on prevalence. Method The sample (N=185) included participants who were recruited for studies focused on trauma and health conducted at an academic medical center and VA medical center in the southeastern United States. The prevalence and concordance between DSM-IV and the proposed DSM-5 classifications were calculated based on results from structured clinical interviews. Prevalence rates and diagnostic efficiency indices including sensitivity, specificity, area under the curve (AUC), and Kappa were calculated for each of the possible ways to define DSM-5 PTSD. Results Ninety-five percent of the sample reported an event that met both DSM-IV PTSD Criterion A1 and A2, but only 89% reported a trauma that met Criterion A on DSM-5. Results examining concordance between DSM-IV and DSM-5 algorithms indicated that several of the algorithms had AUCs above .90. The requirement of two symptoms from both Clusters D and E provided strong concordance to DSM-IV (AUC = .93; Kappa = .86) and a greater balance between sensitivity and specificity than requiring three symptoms in both Clusters D and E. Conclusions Despite several significant changes to the diagnostic criteria for PTSD for DSM-5, several possible classification rules provided good concordance with DSM-IV. The magnitude of the impact of DSM-5 decision rules on prevalence will be largely affected by the DSM-IV PTSD base rate in the population of interest. PMID:23109002

Aminoglycoside acetyltransferase 3-IV (aacC4) and hygromycin B 4-I phosphotransferase (hphB) in bacteria isolated from human and animal sources.

PubMed

Salauze, D; Otal, I; Gomez-Lus, R; Davies, J

1990-10-01

Members of the family Enterobacteriaceae harboring an enzyme of the aminoglycoside acetyltransferase 3 class (AAC-3-IV) (apramycin and gentamicin resistance) and hygromycin B phosphotransferase 4 (HPH-4-I) (hygromycin B resistance) have been isolated from human clinical sources in Europe. A cluster of genes containing IS140, aacC4, and hphB was found in these strains. We demonstrate by Southern hybridization that this cluster is identical to the operon found in animals that also contains insertion sequences belonging to the ISO family. This provides another example of presumptive transfer of antibiotic resistance genes between bacteria of animal and human origin.

The role of charge transfer in the oxidation state change of Ce atoms in the TM13-CeO2(111) systems (TM = Pd, Ag, Pt, Au): a DFT + U investigation.

PubMed

Tereshchuk, Polina; Freire, Rafael L H; Ungureanu, Crina G; Seminovski, Yohanna; Kiejna, Adam; Da Silva, Juarez L F

2015-05-28

Despite extensive studies of transition metal (TM) clusters supported on ceria (CeO2), fundamental issues such as the role of the TM atoms in the change in the oxidation state of Ce atoms are still not well understood. In this work, we report a theoretical investigation based on static and ab initio molecular dynamics density functional theory calculations of the interaction of 13-atom TM clusters (TM = Pd, Ag, Pt, Au) with the unreduced CeO2(111) surface represented by a large surface unit cell and employing Hubbard corrections for the strong on-site Coulomb correlation in the Ce f-electrons. We found that the TM13 clusters form pyramidal-like structures on CeO2(111) in the lowest energy configurations with the following stacking sequence, TM/TM4/TM8/CeO2(111), while TM13 adopts two-dimensional structures at high energy structures. TM13 induces a change in the oxidation state of few Ce atoms (3 of 16) located in the topmost Ce layer from Ce(IV) (itinerant Ce f-states) to Ce(III) (localized Ce f-states). There is a charge flow from the TM atoms to the CeO2(111) surface, which can be explained by the electronegativity difference between the TM (Pd, Ag, Pt, Au) and O atoms, however, the charge is not uniformly distributed on the topmost O layer due to the pressure induced by the TM13 clusters on the underlying O ions, which yields a decrease in the ionic charge of the O ions located below the cluster and an increase in the remaining O ions. Due to the charge flow mainly from the TM8-layer to the topmost O-layer, the charge cannot flow from the Ce(IV) atoms to the O atoms with the same magnitude as in the clean CeO2(111) surface. Consequently, the effective cationic charge decreases mainly for the Ce atoms that have a bond with the O atoms not located below the cluster, and hence, those Ce atoms change their oxidation state from IV to III. This increases the size of the Ce(III) compared with the Ce(IV) cations, which builds-in a strain within the topmost Ce layer, and hence, also affecting the location of the Ce(III) cations and the structure of the TM13 clusters.

Characterization and virulence clustering analysis of extraintestinal pathogenic Escherichia coli isolated from swine in China.

PubMed

Zhu, Yinchu; Dong, Wenyang; Ma, Jiale; Yuan, Lvfeng; Hejair, Hassan M A; Pan, Zihao; Liu, Guangjin; Yao, Huochun

2017-04-08

Swine extraintestinal pathogenic Escherichia coli (ExPEC) is an important pathogen that leads to economic and welfare costs in the swine industry worldwide, and is occurring with increasing frequency in China. By far, various virulence factors have been recognized in ExPEC. Here, we investigated the virulence genotypes and clonal structure of collected strains to improve the knowledge of phylogenetic traits of porcine ExPECs in China. We isolated 64 Chinese porcine ExPEC strains from 2013 to 14 in China. By multiplex PCR, the distribution of isolates belonging to phylogenetic groups B1, B2, A and D was 9.4%, 10.9%, 57.8% and 21.9%, respectively. Nineteen virulence-related genes were detected by PCR assay; ompA, fimH, vat, traT and iutA were highly prevalent. Virulence-related genes were remarkably more prevalent in group B2 than in groups A, B1 and D; notably, usp, cnf1, hlyD, papA and ibeA were only found in group B2 strains. Genotyping analysis was performed and four clusters of strains (named I to IV) were identified. Cluster IV contained all isolates from group B2 and Cluster IV isolates had the strongest pathogenicity in a mouse infection model. As phylogenetic group B2 and D ExPEC isolates are generally considered virulent, multilocus sequence typing (MLST) analysis was performed for these isolates to further investigate genetic relationships. Two novel sequence types, ST5170 and ST5171, were discovered. Among the nine clonal complexes identified among our group B2 and D isolates, CC12 and CC95 have been indicated to have high zoonotic pathogenicity. The distinction between group B2 and non-B2 isolates in virulence and genotype accorded with MLST analysis. This study reveals significant genetic diversity among ExPEC isolates and helps us to better understand their pathogenesis. Importantly, our data suggest group B2 (Cluster IV) strains have the highest risk of causing animal disease and illustrate the correlation between genotype and virulence.

SC3 - consensus clustering of single-cell RNA-Seq data

PubMed Central

Kiselev, Vladimir Yu.; Kirschner, Kristina; Schaub, Michael T.; Andrews, Tallulah; Yiu, Andrew; Chandra, Tamir; Natarajan, Kedar N; Reik, Wolf; Barahona, Mauricio; Green, Anthony R; Hemberg, Martin

2017-01-01

Single-cell RNA-seq (scRNA-seq) enables a quantitative cell-type characterisation based on global transcriptome profiles. We present Single-Cell Consensus Clustering (SC3), a user-friendly tool for unsupervised clustering which achieves high accuracy and robustness by combining multiple clustering solutions through a consensus approach. We demonstrate that SC3 is capable of identifying subclones based on the transcriptomes from neoplastic cells collected from patients. PMID:28346451

Medical Imaging Lesion Detection Based on Unified Gravitational Fuzzy Clustering

PubMed Central

Vianney Kinani, Jean Marie; Gallegos Funes, Francisco; Mújica Vargas, Dante; Ramos Díaz, Eduardo; Arellano, Alfonso

2017-01-01

We develop a swift, robust, and practical tool for detecting brain lesions with minimal user intervention to assist clinicians and researchers in the diagnosis process, radiosurgery planning, and assessment of the patient's response to the therapy. We propose a unified gravitational fuzzy clustering-based segmentation algorithm, which integrates the Newtonian concept of gravity into fuzzy clustering. We first perform fuzzy rule-based image enhancement on our database which is comprised of T1/T2 weighted magnetic resonance (MR) and fluid-attenuated inversion recovery (FLAIR) images to facilitate a smoother segmentation. The scalar output obtained is fed into a gravitational fuzzy clustering algorithm, which separates healthy structures from the unhealthy. Finally, the lesion contour is automatically outlined through the initialization-free level set evolution method. An advantage of this lesion detection algorithm is its precision and its simultaneous use of features computed from the intensity properties of the MR scan in a cascading pattern, which makes the computation fast, robust, and self-contained. Furthermore, we validate our algorithm with large-scale experiments using clinical and synthetic brain lesion datasets. As a result, an 84%–93% overlap performance is obtained, with an emphasis on robustness with respect to different and heterogeneous types of lesion and a swift computation time. PMID:29158887

A comparison of regional flood frequency analysis approaches in a simulation framework

NASA Astrophysics Data System (ADS)

Ganora, D.; Laio, F.

2016-07-01

Regional frequency analysis (RFA) is a well-established methodology to provide an estimate of the flood frequency curve at ungauged (or scarcely gauged) sites. Different RFA approaches exist, depending on the way the information is transferred to the site of interest, but it is not clear in the literature if a specific method systematically outperforms the others. The aim of this study is to provide a framework wherein carrying out the intercomparison by building up a virtual environment based on synthetically generated data. The considered regional approaches include: (i) a unique regional curve for the whole region; (ii) a multiple-region model where homogeneous subregions are determined through cluster analysis; (iii) a Region-of-Influence model which defines a homogeneous subregion for each site; (iv) a spatially smooth estimation procedure where the parameters of the regional model vary continuously along the space. Virtual environments are generated considering different patterns of heterogeneity, including step change and smooth variations. If the region is heterogeneous, with the parent distribution changing continuously within the region, the spatially smooth regional approach outperforms the others, with overall errors 10-50% lower than the other methods. In the case of a step-change, the spatially smooth and clustering procedures perform similarly if the heterogeneity is moderate, while clustering procedures work better when the step-change is severe. To extend our findings, an extensive sensitivity analysis has been performed to investigate the effect of sample length, number of virtual stations, return period of the predicted quantile, variability of the scale parameter of the parent distribution, number of predictor variables and different parent distribution. Overall, the spatially smooth approach appears as the most robust approach as its performances are more stable across different patterns of heterogeneity, especially when short records are considered.

Reconsideration of the seven discrete typing units within the species Trypanosoma cruzi, a new proposal of three reliable mitochondrial clades.

PubMed

Barnabé, Christian; Mobarec, Hugo Ignacio; Jurado, Marcelo Roman; Cortez, Jacqueline Andrea; Brenière, Simone Frédérique

2016-04-01

It is generally acknowledged that Trypanosoma cruzi, responsible for Chagas disease, is structured into six or seven distinct discrete typing units (DTUs), and termed TcI through TcVI and TcBat for the seventh, by a collective of researchers. However, such structuring can be validated only when the species is analyzed over its entire distribution area with the same genetic markers. Many works have dealt with several DTUs in limited areas, generally one country, others have dealt with only one DTU over the endemic area, but no work has reported data of all DTUs over the entire endemic area. Hence, the aim of this minireview was to analyze three gene sequences, already deposited in GenBank by others, over the entire geographical distribution of Chagas disease. Two mitochondrial (CytB and COII) and one nuclear gene (Gpi) were selected (i) among those most widely used in the field, (ii) of single copy for the nuclear one, and (iii) presenting common sequences of sufficient size for applying phylogenetic tools. They were analyzed using maximum likelihood trees and phylogenetic networks. Remarkably, only three significant clusters instead of seven were found with the mitochondrial genes. With the nuclear gene, surprisingly, all seven expected clusters did not have significant bootstrap values. Moreover, DTUs TcV and TcVI were indistinguishable as were TcIII and TcIV. Additionally, we have undertaken a minireview of seventy-five publications presenting phylogenetic trees with identifiable DTUs that allowed us, together with our own results, to seriously question the structuring of T. cruzi into six or seven separated DTUs. We propose that mitochondrial typing in three clusters currently named mtTcI, mtTcII, and mtTcIII is robust whereas nuclear typing may lead to a questionable clustering but it is valuable for detecting mitochondrial introgression, heterozygous states and allelic composition. Copyright © 2016 Elsevier B.V. All rights reserved.

IVS Pilot Project - Tropospheric Parameters

NASA Astrophysics Data System (ADS)

Boehm, J.; Schuh, H.; Engelhardt, G.; MacMillan, D.; Lanotte, R.; Tomasi, P.; Vereshchagina, I.; Haas, R.; Negusini, M.; Gubanov, V.

2003-04-01

In April 2002 the IVS (International VLBI Service for Geodesy and Astrometry) set up the IVS Pilot Project - Tropospheric Parameters and the Institute of Geodesy and Geophysics (IGG), Vienna, was asked to coordinate the project. After a call for participation six IVS Analysis Centers have joined the project and submitted their estimates of tropospheric parameters (wet and total zenith delays, horizontal gradients) for all IVS-R1 and IVS-R4 sessions since January 1st, 2002, on a regular basis. Using a two-step procedure the individual submissions are combined to stable and robust tropospheric parameters with 1h resolution and high accuracy. The zenith delays derived by VLBI are also compared with those provided by IGS (International GPS Service). At collocated sites (VLBI and GPS antennas at the same station) rather constant biases are found between the GPS and VLBI derived zenith delays, although both techniques are subject to the same tropospheric delays. Possible reasons for these biases are discussed.

Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays.

PubMed

Kanie, Kei; Kondo, Yuto; Owaki, Junki; Ikeda, Yurika; Narita, Yuji; Kato, Ryuji; Honda, Hiroyuki

2016-11-19

The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM) provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV), an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I), and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides.

Focused Screening of ECM-Selective Adhesion Peptides on Cellulose-Bound Peptide Microarrays

PubMed Central

Kanie, Kei; Kondo, Yuto; Owaki, Junki; Ikeda, Yurika; Narita, Yuji; Kato, Ryuji; Honda, Hiroyuki

2016-01-01

The coating of surfaces with bio-functional proteins is a promising strategy for the creation of highly biocompatible medical implants. Bio-functional proteins from the extracellular matrix (ECM) provide effective surface functions for controlling cellular behavior. We have previously screened bio-functional tripeptides for feasibility of mass production with the aim of identifying those that are medically useful, such as cell-selective peptides. In this work, we focused on the screening of tripeptides that selectively accumulate collagen type IV (Col IV), an ECM protein that accelerates the re-endothelialization of medical implants. A SPOT peptide microarray was selected for screening owing to its unique cellulose membrane platform, which can mimic fibrous scaffolds used in regenerative medicine. However, since the library size on the SPOT microarray was limited, physicochemical clustering was used to provide broader variation than that of random peptide selection. Using the custom focused microarray of 500 selected peptides, we assayed the relative binding rates of tripeptides to Col IV, collagen type I (Col I), and albumin. We discovered a cluster of Col IV-selective adhesion peptides that exhibit bio-safety with endothelial cells. The results from this study can be used to improve the screening of regeneration-enhancing peptides. PMID:28952593

Electronic structure of the Mn4OxCa cluster in the S0 and S2 states of the oxygen-evolving complex of photosystem II based on pulse 55Mn-ENDOR and EPR spectroscopy.

PubMed

Kulik, Leonid V; Epel, Boris; Lubitz, Wolfgang; Messinger, Johannes

2007-11-07

The heart of the oxygen-evolving complex (OEC) of photosystem II is a Mn4OxCa cluster that cycles through five different oxidation states (S0 to S4) during the light-driven water-splitting reaction cycle. In this study we interpret the recently obtained 55Mn hyperfine coupling constants of the S0 and S2 states of the OEC [Kulik et al. J. Am. Chem. Soc. 2005, 127, 2392-2393] on the basis of Y-shaped spin-coupling schemes with up to four nonzero exchange coupling constants, J. This analysis rules out the presence of one or more Mn(II) ions in S0 in methanol (3%) containing samples and thereby establishes that the oxidation states of the manganese ions in S0 and S2 are, at 4 K, Mn4(III, III, III, IV) and Mn4(III, IV, IV, IV), respectively. By applying a "structure filter" that is based on the recently reported single-crystal EXAFS data on the Mn4OxCa cluster [Yano et al. Science 2006, 314, 821-825] we (i) show that this new structural model is fully consistent with EPR and 55Mn-ENDOR data, (ii) assign the Mn oxidation states to the individual Mn ions, and (iii) propose that the known shortening of one 2.85 A Mn-Mn distance in S0 to 2.75 A in S1 [Robblee et al. J. Am. Chem. Soc. 2002, 124, 7459-7471] corresponds to a deprotonation of a mu-hydroxo bridge between MnA and MnB, i.e., between the outer Mn and its neighboring Mn of the mu3-oxo bridged moiety of the cluster. We summarize our results in a molecular model for the S0 --> S1 and S1 --> S2 transitions.

A multiple-feature and multiple-kernel scene segmentation algorithm for humanoid robot.

PubMed

Liu, Zhi; Xu, Shuqiong; Zhang, Yun; Chen, Chun Lung Philip

2014-11-01

This technical correspondence presents a multiple-feature and multiple-kernel support vector machine (MFMK-SVM) methodology to achieve a more reliable and robust segmentation performance for humanoid robot. The pixel wise intensity, gradient, and C1 SMF features are extracted via the local homogeneity model and Gabor filter, which would be used as inputs of MFMK-SVM model. It may provide multiple features of the samples for easier implementation and efficient computation of MFMK-SVM model. A new clustering method, which is called feature validity-interval type-2 fuzzy C-means (FV-IT2FCM) clustering algorithm, is proposed by integrating a type-2 fuzzy criterion in the clustering optimization process to improve the robustness and reliability of clustering results by the iterative optimization. Furthermore, the clustering validity is employed to select the training samples for the learning of the MFMK-SVM model. The MFMK-SVM scene segmentation method is able to fully take advantage of the multiple features of scene image and the ability of multiple kernels. Experiments on the BSDS dataset and real natural scene images demonstrate the superior performance of our proposed method.

Robust clustering of languages across Wikipedia growth

NASA Astrophysics Data System (ADS)

Ban, Kristina; Perc, Matjaž; Levnajić, Zoran

2017-10-01

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.

Robust clustering of languages across Wikipedia growth.

PubMed

Ban, Kristina; Perc, Matjaž; Levnajić, Zoran

2017-10-01

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy.

Robust clustering of languages across Wikipedia growth

PubMed Central

Ban, Kristina; Levnajić, Zoran

2017-01-01

Wikipedia is the largest existing knowledge repository that is growing on a genuine crowdsourcing support. While the English Wikipedia is the most extensive and the most researched one with over 5 million articles, comparatively little is known about the behaviour and growth of the remaining 283 smaller Wikipedias, the smallest of which, Afar, has only one article. Here, we use a subset of these data, consisting of 14 962 different articles, each of which exists in 26 different languages, from Arabic to Ukrainian. We study the growth of Wikipedias in these languages over a time span of 15 years. We show that, while an average article follows a random path from one language to another, there exist six well-defined clusters of Wikipedias that share common growth patterns. The make-up of these clusters is remarkably robust against the method used for their determination, as we verify via four different clustering methods. Interestingly, the identified Wikipedia clusters have little correlation with language families and groups. Rather, the growth of Wikipedia across different languages is governed by different factors, ranging from similarities in culture to information literacy. PMID:29134106

NOA: A Scalable Multi-Parent Clustering Hierarchy for WSNs

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

Cree, Johnathan V.; Delgado-Frias, Jose; Hughes, Michael A.

2012-08-10

NOA is a multi-parent, N-tiered, hierarchical clustering algorithm that provides a scalable, robust and reliable solution to autonomous configuration of large-scale wireless sensor networks. The novel clustering hierarchy's inherent benefits can be utilized by in-network data processing techniques to provide equally robust, reliable and scalable in-network data processing solutions capable of reducing the amount of data sent to sinks. Utilizing a multi-parent framework, NOA reduces the cost of network setup when compared to hierarchical beaconing solutions by removing the expense of r-hop broadcasting (r is the radius of the cluster) needed to build the network and instead passes network topologymore » information among shared children. NOA2, a two-parent clustering hierarchy solution, and NOA3, the three-parent variant, saw up to an 83% and 72% reduction in overhead, respectively, when compared to performing one round of a one-parent hierarchical beaconing, as well as 92% and 88% less overhead when compared to one round of two- and three-parent hierarchical beaconing hierarchy.« less

Career Clusters: Forecasting Demand for High School through College Jobs, 2008-2018

ERIC Educational Resources Information Center

Carnevale, Anthony P.; Smith, Nicole; Stone, James R., III; Kotamraju, Pradeep; Steuernagel, Bruce; Green, Kimberly A.

2011-01-01

This report presents data on job opportunities and skill requirements through 2018 arranged by the 16 career and technical education (CTE) career clusters in the Carl D. Perkins Act of 2006 (Perkins IV). These skill requirements reflect the length and extent of education and training required for the job. The authors detail changes in education…

Robust root clustering for linear uncertain systems using generalized Lyapunov theory

NASA Technical Reports Server (NTRS)

Yedavalli, R. K.

1993-01-01

Consideration is given to the problem of matrix root clustering in subregions of a complex plane for linear state space models with real parameter uncertainty. The nominal matrix root clustering theory of Gutman & Jury (1981) using the generalized Liapunov equation is extended to the perturbed matrix case, and bounds are derived on the perturbation to maintain root clustering inside a given region. The theory makes it possible to obtain an explicit relationship between the parameters of the root clustering region and the uncertainty range of the parameter space.

Robustness of serial clustering of extra-tropical cyclones to the choice of tracking method

NASA Astrophysics Data System (ADS)

Pinto, Joaquim G.; Ulbrich, Sven; Karremann, Melanie K.; Stephenson, David B.; Economou, Theodoros; Shaffrey, Len C.

2016-04-01

Cyclone families are a frequent synoptic weather feature in the Euro-Atlantic area in winter. Given appropriate large-scale conditions, the occurrence of such series (clusters) of storms may lead to large socio-economic impacts and cumulative losses. Recent studies analyzing Reanalysis data using single cyclone tracking methods have shown that serial clustering of cyclones occurs on both flanks and downstream regions of the North Atlantic storm track. This study explores the sensitivity of serial clustering to the choice of tracking method. With this aim, the IMILAST cyclone track database based on ERA-interim data is analysed. Clustering is estimated by the dispersion (ratio of variance to mean) of winter (DJF) cyclones passages near each grid point over the Euro-Atlantic area. Results indicate that while the general pattern of clustering is identified for all methods, there are considerable differences in detail. This can primarily be attributed to the differences in the variance of cyclone counts between the methods, which range up to one order of magnitude. Nevertheless, clustering over the Eastern North Atlantic and Western Europe can be identified for all methods and can thus be generally considered as a robust feature. The statistical links between large-scale patterns like the NAO and clustering are obtained for all methods, though with different magnitudes. We conclude that the occurrence of cyclone clustering over the Eastern North Atlantic and Western Europe is largely independent from the choice of tracking method and hence from the definition of a cyclone.

State estimation and prediction using clustered particle filters.

PubMed

Lee, Yoonsang; Majda, Andrew J

2016-12-20

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors.

Density-Aware Clustering Based on Aggregated Heat Kernel and Its Transformation

DOE PAGES

Huang, Hao; Yoo, Shinjae; Yu, Dantong; ...

2015-06-01

Current spectral clustering algorithms suffer from the sensitivity to existing noise, and parameter scaling, and may not be aware of different density distributions across clusters. If these problems are left untreated, the consequent clustering results cannot accurately represent true data patterns, in particular, for complex real world datasets with heterogeneous densities. This paper aims to solve these problems by proposing a diffusion-based Aggregated Heat Kernel (AHK) to improve the clustering stability, and a Local Density Affinity Transformation (LDAT) to correct the bias originating from different cluster densities. AHK statistically\\ models the heat diffusion traces along the entire time scale, somore » it ensures robustness during clustering process, while LDAT probabilistically reveals local density of each instance and suppresses the local density bias in the affinity matrix. Our proposed framework integrates these two techniques systematically. As a result, not only does it provide an advanced noise-resisting and density-aware spectral mapping to the original dataset, but also demonstrates the stability during the processing of tuning the scaling parameter (which usually controls the range of neighborhood). Furthermore, our framework works well with the majority of similarity kernels, which ensures its applicability to many types of data and problem domains. The systematic experiments on different applications show that our proposed algorithms outperform state-of-the-art clustering algorithms for the data with heterogeneous density distributions, and achieve robust clustering performance with respect to tuning the scaling parameter and handling various levels and types of noise.« less

State estimation and prediction using clustered particle filters

PubMed Central

Lee, Yoonsang; Majda, Andrew J.

2016-01-01

Particle filtering is an essential tool to improve uncertain model predictions by incorporating noisy observational data from complex systems including non-Gaussian features. A class of particle filters, clustered particle filters, is introduced for high-dimensional nonlinear systems, which uses relatively few particles compared with the standard particle filter. The clustered particle filter captures non-Gaussian features of the true signal, which are typical in complex nonlinear dynamical systems such as geophysical systems. The method is also robust in the difficult regime of high-quality sparse and infrequent observations. The key features of the clustered particle filtering are coarse-grained localization through the clustering of the state variables and particle adjustment to stabilize the method; each observation affects only neighbor state variables through clustering and particles are adjusted to prevent particle collapse due to high-quality observations. The clustered particle filter is tested for the 40-dimensional Lorenz 96 model with several dynamical regimes including strongly non-Gaussian statistics. The clustered particle filter shows robust skill in both achieving accurate filter results and capturing non-Gaussian statistics of the true signal. It is further extended to multiscale data assimilation, which provides the large-scale estimation by combining a cheap reduced-order forecast model and mixed observations of the large- and small-scale variables. This approach enables the use of a larger number of particles due to the computational savings in the forecast model. The multiscale clustered particle filter is tested for one-dimensional dispersive wave turbulence using a forecast model with model errors. PMID:27930332

The effect of draft DSM-V criteria on posttraumatic stress disorder prevalence.

PubMed

Calhoun, Patrick S; Hertzberg, Jeffrey S; Kirby, Angela C; Dennis, Michelle F; Hair, Lauren P; Dedert, Eric A; Beckham, Jean C

2012-12-01

This study was designed to examine the concordance of proposed DSM-V posttraumatic stress disorder (PTSD) criteria with DSM-IV classification rules and examine the impact of the proposed DSM-V PTSD criteria on prevalence. The sample (N = 185) included participants who were recruited for studies focused on trauma and health conducted at an academic medical center and VA medical center in the southeastern United States. The prevalence and concordance between DSM-IV and the proposed DSM-V classifications were calculated based on results from structured clinical interviews. Prevalence rates and diagnostic efficiency indices including sensitivity, specificity, area under the curve (AUC), and Kappa were calculated for each of the possible ways to define DSM-V PTSD. Ninety-five percent of the sample reported an event that met both DSM-IV PTSD Criterion A1 and A2, but only 89% reported a trauma that met Criterion A on DSM-V. Results examining concordance between DSM-IV and DSM-V algorithms indicated that several of the algorithms had AUCs above 0.90. The requirement of two symptoms from both Clusters D and E provided strong concordance to DSM-IV (AUC = 0.93; Kappa = 0.86) and a greater balance between sensitivity and specificity than requiring three symptoms in both Clusters D and E. Despite several significant changes to the diagnostic criteria for PTSD for DSM-V, several possible classification rules provided good concordance with DSM-IV. The magnitude of the impact of DSM-V decision rules on prevalence will be largely affected by the DSM-IV PTSD base rate in the population of interest. © 2012 Wiley Periodicals, Inc.

Advances in containment methods and plutonium recovery strategies that led to the structural characterization of plutonium(IV) tetrachloride tris-diphenylsulfoxide, PuCl 4(OSPh 2) 3

DOE PAGES

Schrell, Samantha K.; Boland, Kevin Sean; Cross, Justin Neil; ...

2017-01-18

In an attempt to further advance the understanding of plutonium coordination chemistry, we report a robust method for recycling and obtaining plutonium aqueous stock solutions that can be used as a convenient starting material in plutonium synthesis. This approach was used to prepare and characterize plutonium(IV) tetrachloride tris-diphenylsulfoxide, PuCl 4(OSPh 2) 3, by single crystal X-ray diffraction. The PuCl 4(OSPh 2) 3 compound represents a rare example of a 7-coordinate plutonium(IV) complex. Structural characterization of PuCl 4(OSPh 2) 3 by X-ray diffraction utilized a new containment method for radioactive crystals. The procedure makes use of epoxy, polyimide loops, and amore » polyester sheath to provide a robust method for safely containing and easily handling radioactive samples. Lastly, the described procedure is more user friendly than traditional containment methods that employ fragile quartz capillary tubes. Additionally, moving to polyester, instead of quartz, lowers the background scattering from the heavier silicon atoms.« less

Controlling transformations in the assembly of polyoxometalate clusters: {Mo11V7}, {Mo17V8} and {Mo72V30}.

PubMed

Miras, Haralampos N; Ochoa, M Nieves Corella; Long, De-Liang; Cronin, Leroy

2010-11-21

The reaction of molybdate with vanadium(V) in the presence of sulfite anions is explored showing how, via cation control, stepwise assembly through the {Mo(11)V(7)} cluster yields a {M(25)} cluster-based compound, [Mo(VI)(11)V(V)(5)V(IV)(2)O(52)(μ(9)-SO(3))(Mo(VI)(6)V(V)O(22))](10-) (1a), which was first discovered using cryospray mass spectrometry, whereas switching the cation away from ammonium allows the direct formation of the spherical 'Keplerate' {Mo(72)V(30)} cluster.

The Heritability of Cluster B Personality Disorders Assessed both by Personal Interview and Questionnaire

PubMed Central

Torgersen, Svenn; Myers, John; Reichborn-Kjennerud, Ted; Røysamb, Espen; Kubarych, Thomas S.; Kendler, Kenneth S.

2013-01-01

Whereas the heritability of common personality traits has been firmly established, the results of the few published studies on personality disorders (PDs) are highly divergent, with some studies finding high heredity and others very low. A problem with assessing personality disorders by means of interview is errors connected with interviewer bias. A way to overcome the problem is to use self-report questionnaires in addition to interviews. This study used both interview and questionnaire for assessing DSM-IV Cluster B personality disorders: antisocial personality disorder (APD), borderline (BPD), narcissistic (NPD), and histrionic (HPD). We assessed close to 2,800 twins from the Norwegian Institute of Public Health Twin Panel using a self-report questionnaire and, a few years later, the Structured Interview for DSM-IV Personality (SIDP-IV). Items from the self-report questionnaire that best predicted the PDs captured by the interview were then selected. Measurement models combining questionnaire and interview information were applied and were fitted using Mx. Whereas the heritability of Cluster B PDs assessed by interview was around .30, and around .40–.50 when assessed by self-report questionnaire, the heritability of the convergent latent factor, including information from both interview and self-report questionnaire was .69 for APD, .67 for BPD, .71 for NPD, and .63 for HPD. As is usually found for personality, the effect of shared-in families (familial) environment was zero. In conclusion, when both interview and self-report questionnaire are taken into account, the heritability of Cluster B PD appears to be in the upper range of previous findings for mental disorders. PMID:23281671

The heritability of Cluster B personality disorders assessed both by personal interview and questionnaire.

PubMed

Torgersen, Svenn; Myers, John; Reichborn-Kjennerud, Ted; Røysamb, Espen; Kubarych, Thomas S; Kendler, Kenneth S

2012-12-01

Whereas the heritability of common personality traits has been firmly established, the results of the few published studies on personality disorders (PDs) are highly divergent, with some studies finding high heredity and others very low. A problem with assessing personality disorders by means of interview is errors connected with interviewer bias. A way to overcome the problem is to use self-report questionnaires in addition to interviews. This study used both interview and questionnaire for assessing DSM-IV Cluster B personality disorders: antisocial personality disorder (APD), borderline (BPD), narcissistic (NPD), and histrionic (HPD). We assessed close to 2,800 twins from the Norwegian Institute of Public Health Twin Panel using a self-report questionnaire and, a few years later, the Structured Interview for DSM-IV Personality (SIDP-IV). Items from the self-report questionnaire that best predicted the PDs captured by the interview were then selected. Measurement models combining questionnaire and interview information were applied and were fitted using Mx. Whereas the heritability of Cluster B PDs assessed by interview was around .30, and around .40-.50 when assessed by self-report questionnaire, the heritability of the convergent latent factor, including information from both interview and self-report questionnaire was .69 for APD, .67 for BPD, .71 for NPD, and .63 for HPD. As is usually found for personality, the effect of shared-in families (familial) environment was zero. In conclusion, when both interview and self-report questionnaire are taken into account, the heritability of Cluster B PD appears to be in the upper range of previous findings for mental disorders.

THE PREPARATION OF CURRICULUM MATERIALS AND THE DEVELOPMENT OF TEACHERS FOR AN EXPERIMENTAL APPLICATION OF THE CLUSTER CONCEPT OF VOCATIONAL EDUCATION AT THE SECONDARY SCHOOL LEVEL. VOLUME IV, INSTRUCTIONAL PLANS FOR THE ELECTRO-MECHANICAL CLUSTER.

ERIC Educational Resources Information Center

MALEY, DONALD

DESIGNED FOR USE WITH 11TH AND 12TH GRADE STUDENTS, THIS CURRICULUM GUIDE FOR THE OCCUPATIONAL CLUSTER IN ELECTRO-MECHANICAL INSTALLATION AND REPAIR WAS DEVELOPED BY PARTICIPATING TEACHERS FROM RESULTS OF THE RESEARCH PROCEDURES DESCRIBED IN VOLUME I (VT 004 162). THE COURSE DESCRIPTIONS, NEED FOR THE COURSE, COURSE OBJECTIVES, PROCEDURES, AND…

The Robustness of Cluster Expansion: Assessing the Role of Relaxation

NASA Astrophysics Data System (ADS)

Nguyen, Andrew H.; Rosenbrock, Conrad W.; Hart, Gus L. W.

Cluster expansion (CE) has been used widely in combination with first-principles calculations to predict stable structures of metal alloys. CE treats alloys as a purely configuration problem, i.e., a problem in the distribution of the alloying elements on a fixed lattice. CE models are usually built from data taken from ``relaxed'' first-principles calculations where the individual atoms assume positions that minimize the total energy. A perennial question in the cluster expansion community is how the accuracy of the CE is affected by relaxations--technically, the formalism of CE breaks down when the underlying lattice is not preserved--but practitioners often argue that there is a one-to-one correspondence between relaxed and unrelaxed structures so that the formalism holds. We quantify the effect of relaxation on the robustness of cluster expansions by comparing CE fits for relaxed and unrelaxed data sets. Our results give a heuristic for when CE models can be trusted. Onr (MURI N00014-13-1-0635).

Improved fuzzy clustering algorithms in segmentation of DC-enhanced breast MRI.

PubMed

Kannan, S R; Ramathilagam, S; Devi, Pandiyarajan; Sathya, A

2012-02-01

Segmentation of medical images is a difficult and challenging problem due to poor image contrast and artifacts that result in missing or diffuse organ/tissue boundaries. Many researchers have applied various techniques however fuzzy c-means (FCM) based algorithms is more effective compared to other methods. The objective of this work is to develop some robust fuzzy clustering segmentation systems for effective segmentation of DCE - breast MRI. This paper obtains the robust fuzzy clustering algorithms by incorporating kernel methods, penalty terms, tolerance of the neighborhood attraction, additional entropy term and fuzzy parameters. The initial centers are obtained using initialization algorithm to reduce the computation complexity and running time of proposed algorithms. Experimental works on breast images show that the proposed algorithms are effective to improve the similarity measurement, to handle large amount of noise, to have better results in dealing the data corrupted by noise, and other artifacts. The clustering results of proposed methods are validated using Silhouette Method.

Seismic clusters analysis in Northeastern Italy by the nearest-neighbor approach

NASA Astrophysics Data System (ADS)

Peresan, Antonella; Gentili, Stefania

2018-01-01

The main features of earthquake clusters in Northeastern Italy are explored, with the aim to get new insights on local scale patterns of seismicity in the area. The study is based on a systematic analysis of robustly and uniformly detected seismic clusters, which are identified by a statistical method, based on nearest-neighbor distances of events in the space-time-energy domain. The method permits us to highlight and investigate the internal structure of earthquake sequences, and to differentiate the spatial properties of seismicity according to the different topological features of the clusters structure. To analyze seismicity of Northeastern Italy, we use information from local OGS bulletins, compiled at the National Institute of Oceanography and Experimental Geophysics since 1977. A preliminary reappraisal of the earthquake bulletins is carried out and the area of sufficient completeness is outlined. Various techniques are considered to estimate the scaling parameters that characterize earthquakes occurrence in the region, namely the b-value and the fractal dimension of epicenters distribution, required for the application of the nearest-neighbor technique. Specifically, average robust estimates of the parameters of the Unified Scaling Law for Earthquakes, USLE, are assessed for the whole outlined region and are used to compute the nearest-neighbor distances. Clusters identification by the nearest-neighbor method turn out quite reliable and robust with respect to the minimum magnitude cutoff of the input catalog; the identified clusters are well consistent with those obtained from manual aftershocks identification of selected sequences. We demonstrate that the earthquake clusters have distinct preferred geographic locations, and we identify two areas that differ substantially in the examined clustering properties. Specifically, burst-like sequences are associated with the north-western part and swarm-like sequences with the south-eastern part of the study region. The territorial heterogeneity of earthquakes clustering is in good agreement with spatial variability of scaling parameters identified by the USLE. In particular, the fractal dimension is higher to the west (about 1.2-1.4), suggesting a spatially more distributed seismicity, compared to the eastern parte of the investigated territory, where fractal dimension is very low (about 0.8-1.0).

An Efficient and Adaptive Mutual Authentication Framework for Heterogeneous Wireless Sensor Network-Based Applications

PubMed Central

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-01-01

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications. PMID:24521942

An efficient and adaptive mutual authentication framework for heterogeneous wireless sensor network-based applications.

PubMed

Kumar, Pardeep; Ylianttila, Mika; Gurtov, Andrei; Lee, Sang-Gon; Lee, Hoon-Jae

2014-02-11

Robust security is highly coveted in real wireless sensor network (WSN) applications since wireless sensors' sense critical data from the application environment. This article presents an efficient and adaptive mutual authentication framework that suits real heterogeneous WSN-based applications (such as smart homes, industrial environments, smart grids, and healthcare monitoring). The proposed framework offers: (i) key initialization; (ii) secure network (cluster) formation (i.e., mutual authentication and dynamic key establishment); (iii) key revocation; and (iv) new node addition into the network. The correctness of the proposed scheme is formally verified. An extensive analysis shows the proposed scheme coupled with message confidentiality, mutual authentication and dynamic session key establishment, node privacy, and message freshness. Moreover, the preliminary study also reveals the proposed framework is secure against popular types of attacks, such as impersonation attacks, man-in-the-middle attacks, replay attacks, and information-leakage attacks. As a result, we believe the proposed framework achieves efficiency at reasonable computation and communication costs and it can be a safeguard to real heterogeneous WSN applications.

The XMM Cluster Survey: X-ray analysis methodology

NASA Astrophysics Data System (ADS)

Lloyd-Davies, E. J.; Romer, A. Kathy; Mehrtens, Nicola; Hosmer, Mark; Davidson, Michael; Sabirli, Kivanc; Mann, Robert G.; Hilton, Matt; Liddle, Andrew R.; Viana, Pedro T. P.; Campbell, Heather C.; Collins, Chris A.; Dubois, E. Naomi; Freeman, Peter; Harrison, Craig D.; Hoyle, Ben; Kay, Scott T.; Kuwertz, Emma; Miller, Christopher J.; Nichol, Robert C.; Sahlén, Martin; Stanford, S. A.; Stott, John P.

2011-11-01

The XMM Cluster Survey (XCS) is a serendipitous search for galaxy clusters using all publicly available data in the XMM-Newton Science Archive. Its main aims are to measure cosmological parameters and trace the evolution of X-ray scaling relations. In this paper we describe the data processing methodology applied to the 5776 XMM observations used to construct the current XCS source catalogue. A total of 3675 > 4σ cluster candidates with >50 background-subtracted X-ray counts are extracted from a total non-overlapping area suitable for cluster searching of 410 deg2. Of these, 993 candidates are detected with >300 background-subtracted X-ray photon counts, and we demonstrate that robust temperature measurements can be obtained down to this count limit. We describe in detail the automated pipelines used to perform the spectral and surface brightness fitting for these candidates, as well as to estimate redshifts from the X-ray data alone. A total of 587 (122) X-ray temperatures to a typical accuracy of <40 (<10) per cent have been measured to date. We also present the methodology adopted for determining the selection function of the survey, and show that the extended source detection algorithm is robust to a range of cluster morphologies by inserting mock clusters derived from hydrodynamical simulations into real XMMimages. These tests show that the simple isothermal β-profiles is sufficient to capture the essential details of the cluster population detected in the archival XMM observations. The redshift follow-up of the XCS cluster sample is presented in a companion paper, together with a first data release of 503 optically confirmed clusters.

An empirical evaluation of the structure of DSM-IV personality disorders in a nationally representative sample: results of confirmatory factor analysis in the National Epidemiologic Survey on Alcohol and Related Conditions Waves 1 and 2.

PubMed

Cox, Brian J; Clara, Ian P; Worobec, Lydia M; Grant, Bridget F

2012-12-01

Individual personality disorders (PD) are grouped into three clusters in the DSM-IV (A, B, and C). There is very little empirical evidence available concerning the validity of this model in the general population. The current study included all 10 of the DSM-IV PD assessed in Wave 1 and Wave 2 of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Confirmatory factor analysis was used to evaluate three plausible models of the structure of Axis II personality disorders (the current hierarchical DSM-IV three-factor model in which individual PD are believed to load on their assigned clusters, which in turn load onto a single Axis II factor; a general single-factor model; and three independent factors). Each of these models was tested in both the total and also separately for gender. The higher order DSM-IV model demonstrated good fit to the data on a number of goodness-of-fit indices. The results for this model were very similar across genders. A model of PD based on the current DSM-IV hierarchical conceptualization of a higher order classification scheme received strong empirical support through confirmatory factor analysis using a number of goodness-of-fit indices in a nationally representative sample. Other models involving broad, higher order personality domains such as neuroticism in relation to personality disorders have yet to be tested in epidemiologic surveys and represent an important avenue for future research.

Initial Development of a Measure of Emotional Dysregulation for Individuals with Cluster B Personality Disorders

ERIC Educational Resources Information Center

Newhill, Christina E.; Mulvey, Edward P.; Pilkonis, Paul A.

2004-01-01

Individuals with DSM-IV Cluster B personality disorders are at particular risk of violence toward self or others. Emotional dysregulation is likely to be a factor in such incidents and is a central issue addressed in therapies with personality-disordered individuals. This article reports findings from a study that developed an original 18-item…

Robust X-ray angular correlations for the study of meso-structures

DOE PAGES

Lhermitte, Julien R.; Tian, Cheng; Stein, Aaron; ...

2017-05-08

As self-assembling nanomaterials become more sophisticated, it is becoming increasingly important to measure the structural order of finite-sized assemblies of nano-objects. These mesoscale clusters represent an acute challenge to conventional structural probes, owing to the range of implicated size scales (10 nm to several micrometres), the weak scattering signal and the dynamic nature of meso-clusters in native solution environments. The high X-ray flux and coherence of modern synchrotrons present an opportunity to extract structural information from these challenging systems, but conventional ensemble X-ray scattering averages out crucial information about local particle configurations. Conversely, a single meso-cluster scatters too weakly tomore » recover the full diffraction pattern. Using X-ray angular cross-correlation analysis, it is possible to combine multiple noisy measurements to obtain robust structural information. This paper explores the key theoretical limits and experimental challenges that constrain the application of these methods to probing structural order in real nanomaterials. A metric is presented to quantify the signal-to-noise ratio of angular correlations, and it is used to identify several experimental artifacts that arise. In particular, it is found that background scattering, data masking and inter-cluster interference profoundly affect the quality of correlation analyses. A robust workflow is demonstrated for mitigating these effects and extracting reliable angular correlations from realistic experimental data.« less

Decentralized formation flying control in a multiple-team hierarchy.

PubMed

Mueller, Joseph B; Thomas, Stephanie J

2005-12-01

In recent years, formation flying has been recognized as an enabling technology for a variety of mission concepts in both the scientific and defense arenas. Examples of developing missions at NASA include magnetospheric multiscale (MMS), solar imaging radio array (SIRA), and terrestrial planet finder (TPF). For each of these missions, a multiple satellite approach is required in order to accomplish the large-scale geometries imposed by the science objectives. In addition, the paradigm shift of using a multiple satellite cluster rather than a large, monolithic spacecraft has also been motivated by the expected benefits of increased robustness, greater flexibility, and reduced cost. However, the operational costs of monitoring and commanding a fleet of close-orbiting satellites is likely to be unreasonable unless the onboard software is sufficiently autonomous, robust, and scalable to large clusters. This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple team framework. The objective is to divide large clusters into teams of "manageable" size, so that the communication and computation demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using a messaging architecture for networking and threaded applications (MANTA). In this architecture, tasks may be remotely added, removed, or replaced post launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in Matlab, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.

Rational synthesis of high nuclearity Mo/Fe/S clusters: the reductive coupling approach in the convenient synthesis of (Cl(4)-cat)(2)Mo(2)Fe(6)S(8)(PR(3))(6) [R = Et, (n)Pr, (n)Bu] and the new [(Cl(4)-cat)(2)Mo(2)Fe(2)S(3)O(PEt(3))(3)Cl]-1/2(Fe(PEt(3))(2)(MeCN)(4)) and (Cl(4)-cat)(2)Mo(2)Fe(3)S(5)(PEt(3))(5) clusters.

PubMed

Han, J; Koutmos, M; Ahmad, S A; Coucouvanis, D

2001-11-05

A general method for the synthesis of high nuclearity Mo/Fe/S clusters is presented and involves the reductive coupling of the (Et(4)N)(2)[(Cl(4)-cat)MoOFeS(2)Cl(2)] (I) and (Et(4)N)(2)[Fe(2)S(2)Cl(4)] (II) clusters. The reaction of I and II with Fe(PR(3))(2)Cl(2) or sodium salts of noncoordinating anions such as NaPF(6) or NaBPh(4) in the presence of PR(3) (R = Et, (n)Pr, or (n)Bu) affords (Cl(4)-cat)(2)Mo(2)Fe(6)S(8)(PR(3))(6) [R = Et (IIIa), (n)Pr (IIIb), (n)Bu (IIIc)], Fe(6)S(6)(PEt(3))(4)Cl(2) (IV) and (PF(6))[Fe(6)S(8)(P(n)Pr(3))(6)] (V) as byproducts. The isolation of (Et(4)N)[Fe(PEt(3))Cl(3)] (VI), NaCl, and SPEt(3) supports a reductive coupling mechanism. Cluster IV and V also have been synthesized by the reductive self-coupling of compound II. The reductive coupling reaction between I and II by PEt(3) and NaPF(6) in a 1:1 ratio produces the (Et(4)N)(2)[(Cl(4)-cat)Mo(L)Fe(3)S(4)Cl(3)] clusters [L = MeCN (VIIa), THF (VIIb)]. The hitherto unknown [(Cl(4)-cat)(2)Mo(2)Fe(2)S(3)O(PEt(3))(3)Cl](+) cluster (VIII) has been isolated as the 2:1 salt of the (Fe(PEt(3))(2)(MeCN)(4))(2+) cation after the reductive self-coupling reaction of I in the presence of Fe(PEt(3))(2)Cl(2). Cluster VIII crystallizes in the monoclinic space group P2(1)/c with a = 11.098(3) A, b = 22.827(6) A, c = 25.855(6) A, beta = 91.680(4) degrees, and Z = 4. The formal oxidation states of metal atoms in VIII have been assigned as Mo(III), Mo(IV), Fe(II), and Fe(III) on the basis of zero-field Mössbauer spectra. The Fe(PEt(3))(2)(MeCN)(4) cation of VIII is also synthesized independently, isolated as the BPh(4)(-) salt (IX), and has been structurally characterized. The reductive coupling of compound I also affords in low yield the new (Cl(4)-cat)(2)Mo(2)Fe(3)S(5)(PEt(3))(5) cluster (X) as a byproduct. Cluster X crystallizes in the monoclinic space group P2(1)/n with a = 14.811(3) A, b = 22.188(4) A, c = 21.864(4) A, beta = 100.124(3) degrees, and Z = 4 and the structure shows very short Mo-Fe, Fe-Fe, Mo-S, Fe-S bonds. The oxidation states of the metal atoms in this neutral cluster (X) have been assigned as Mo(IV)Mo(III)Fe(II)Fe(II)Fe(III) based on zero-field Mössbauer and magnetic measurement. All Fe atoms are high spin and two of the three Fe-Fe distances are found at 2.4683(9) A and 2.4721(9) A.

Planck 2015 results. XXVII. The second Planck catalogue of Sunyaev-Zeldovich sources

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Banday, A. J.; Barreiro, R. B.; Barrena, R.; Bartlett, J. G.; Bartolo, N.; Battaner, E.; Battye, R.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bikmaev, I.; Böhringer, H.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Bucher, M.; Burenin, R.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Carvalho, P.; Catalano, A.; Challinor, A.; Chamballu, A.; Chary, R.-R.; Chiang, H. C.; Chon, G.; Christensen, P. R.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Comis, B.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Dahle, H.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Dickinson, C.; Diego, J. M.; Dolag, K.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Eisenhardt, P. R. M.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Falgarone, E.; Fergusson, J.; Feroz, F.; Ferragamo, A.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Génova-Santos, R. T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Grainge, K. J. B.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Hempel, A.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jin, T.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Khamitov, I.; Kisner, T. S.; Kneissl, R.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lagache, G.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mak, D. S. Y.; Mandolesi, N.; Mangilli, A.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; Mazzotta, P.; McGehee, P.; Mei, S.; Melchiorri, A.; Melin, J.-B.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nastasi, A.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Olamaie, M.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Pearson, T. J.; Perdereau, O.; Perotto, L.; Perrott, Y. C.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Reach, W. T.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rozo, E.; Rubiño-Martín, J. A.; Rumsey, C.; Rusholme, B.; Rykoff, E. S.; Sandri, M.; Santos, D.; Saunders, R. D. E.; Savelainen, M.; Savini, G.; Schammel, M. P.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Shimwell, T. W.; Spencer, L. D.; Stanford, S. A.; Stern, D.; Stolyarov, V.; Stompor, R.; Streblyanska, A.; Sudiwala, R.; Sunyaev, R.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tramonte, D.; Tristram, M.; Tucci, M.; Tuovinen, J.; Umana, G.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; White, S. D. M.; Wright, E. L.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

We present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest systematic all-sky surveyof galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data sets, and is the first SZ-selected cluster survey containing >103 confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that the estimates of the SZ strength parameter Y5R500are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical, and X-ray data sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under-luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples.

Planck 2015 results: XXVII. The second Planck catalogue of Sunyaev-Zeldovich sources

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

Here, we present the all-sky Planck catalogue of Sunyaev-Zeldovich (SZ) sources detected from the 29 month full-mission data. The catalogue (PSZ2) is the largest SZ-selected sample of galaxy clusters yet produced and the deepest systematic all-sky surveyof galaxy clusters. It contains 1653 detections, of which 1203 are confirmed clusters with identified counterparts in external data sets, and is the first SZ-selected cluster survey containing >103 confirmed clusters. We present a detailed analysis of the survey selection function in terms of its completeness and statistical reliability, placing a lower limit of 83% on the purity. Using simulations, we find that themore » estimates of the SZ strength parameter Y5R500are robust to pressure-profile variation and beam systematics, but accurate conversion to Y500 requires the use of prior information on the cluster extent. We describe the multi-wavelength search for counterparts in ancillary data, which makes use of radio, microwave, infra-red, optical, and X-ray data sets, and which places emphasis on the robustness of the counterpart match. We discuss the physical properties of the new sample and identify a population of low-redshift X-ray under-luminous clusters revealed by SZ selection. These objects appear in optical and SZ surveys with consistent properties for their mass, but are almost absent from ROSAT X-ray selected samples.« less

Evidence That the [beta] Subunit of Chlamydia trachomatis Ribonucleotide Reductase Is Active with the Manganese Ion of Its Manganese(IV)/Iron(III) Cofactor in Site 1

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

Dassama, Laura M.K.; Boal, Amie K.; Krebs, Carsten

2014-10-02

The reaction of a class I ribonucleotide reductase (RNR) begins when a cofactor in the {beta} subunit oxidizes a cysteine residue {approx}35 {angstrom} away in the {alpha} subunit, generating a thiyl radical. In the class Ic enzyme from Chlamydia trachomatis (Ct), the cysteine oxidant is the Mn{sup IV} ion of a Mn{sup IV}/Fe{sup III} cluster, which assembles in a reaction between O{sub 2} and the Mn{sup II}/Fe{sup II} complex of {beta}. The heterodinuclear nature of the cofactor raises the question of which site, 1 or 2, contains the Mn{sup IV} ion. Because site 1 is closer to the conserved locationmore » of the cysteine-oxidizing tyrosyl radical of class Ia and Ib RNRs, we suggested that the Mn{sup IV} ion most likely resides in this site (i.e., {sup 1}Mn{sup IV}/{sup 2}Fe{sup III}), but a subsequent computational study favored its occupation of site 2 ({sup 1}Fe{sup III}/{sup 2}Mn{sup IV}). In this work, we have sought to resolve the location of the Mn{sup IV} ion in Ct RNR-{beta} by correlating X-ray crystallographic anomalous scattering intensities with catalytic activity for samples of the protein reconstituted in vitro by two different procedures. In samples containing primarily Mn{sup IV}/Fe{sup III} clusters, Mn preferentially occupies site 1, but some anomalous scattering from site 2 is observed, implying that both {sup 1}Mn{sup II}/{sup 2}Fe{sup II} and {sup 1}Fe{sup II}/{sup 2}Mn{sup II} complexes are competent to react with O{sub 2} to produce the corresponding oxidized states. However, with diminished Mn{sup II} loading in the reconstitution, there is no evidence for Mn occupancy of site 2, and the greater activity of these 'low-Mn' samples on a per-Mn basis implies that the {sup 1}Mn{sup IV}/{sup 2}Fe{sup III}-{beta} is at least the more active of the two oxidized forms and may be the only active form.« less

Source selection for cluster weak lensing measurements in the Hyper Suprime-Cam survey

NASA Astrophysics Data System (ADS)

Medezinski, Elinor; Oguri, Masamune; Nishizawa, Atsushi J.; Speagle, Joshua S.; Miyatake, Hironao; Umetsu, Keiichi; Leauthaud, Alexie; Murata, Ryoma; Mandelbaum, Rachel; Sifón, Cristóbal; Strauss, Michael A.; Huang, Song; Simet, Melanie; Okabe, Nobuhiro; Tanaka, Masayuki; Komiyama, Yutaka

2018-03-01

We present optimized source galaxy selection schemes for measuring cluster weak lensing (WL) mass profiles unaffected by cluster member dilution from the Subaru Hyper Suprime-Cam Strategic Survey Program (HSC-SSP). The ongoing HSC-SSP survey will uncover thousands of galaxy clusters to z ≲ 1.5. In deriving cluster masses via WL, a critical source of systematics is contamination and dilution of the lensing signal by cluster members, and by foreground galaxies whose photometric redshifts are biased. Using the first-year CAMIRA catalog of ˜900 clusters with richness larger than 20 found in ˜140 deg2 of HSC-SSP data, we devise and compare several source selection methods, including selection in color-color space (CC-cut), and selection of robust photometric redshifts by applying constraints on their cumulative probability distribution function (P-cut). We examine the dependence of the contamination on the chosen limits adopted for each method. Using the proper limits, these methods give mass profiles with minimal dilution in agreement with one another. We find that not adopting either the CC-cut or P-cut methods results in an underestimation of the total cluster mass (13% ± 4%) and the concentration of the profile (24% ± 11%). The level of cluster contamination can reach as high as ˜10% at R ≈ 0.24 Mpc/h for low-z clusters without cuts, while employing either the P-cut or CC-cut results in cluster contamination consistent with zero to within the 0.5% uncertainties. Our robust methods yield a ˜60 σ detection of the stacked CAMIRA surface mass density profile, with a mean mass of M200c = [1.67 ± 0.05(stat)] × 1014 M⊙/h.

The Cluster Sensitivity Index: A Basic Measure of Classification Robustness

ERIC Educational Resources Information Center

Hom, Willard C.

2010-01-01

Analysts of institutional performance have occasionally used a peer grouping approach in which they compared institutions only to other institutions with similar characteristics. Because analysts historically have used cluster analysis to define peer groups (i.e., the group of comparable institutions), the author proposes and demonstrates with…

Cloning and heterologous expression of a novel subgroup of class IV polyhydroxyalkanoate synthase genes from the genus Bacillus.

PubMed

Mizuno, Kouhei; Kihara, Takahiro; Tsuge, Takeharu; Lundgren, Benjamin R; Sarwar, Zaara; Pinto, Atahualpa; Nomura, Christopher T

2017-01-01

Many microorganisms harbor genes necessary to synthesize biodegradable plastics known as polyhydroxyalkanoates (PHAs). We surveyed a genomic database and discovered a new cluster of class IV PHA synthase genes (phaRC). These genes are different in sequence and operon structure from any previously reported PHA synthase. The newly discovered PhaRC synthase was demonstrated to produce PHAs in recombinant Escherichia coli.

A Polyphasic and Taxogenomic Evaluation Uncovers Arcobacter cryaerophilus as a Species Complex That Embraces Four Genomovars

PubMed Central

Pérez-Cataluña, Alba; Collado, Luis; Salgado, Oscar; Lefiñanco, Violeta; Figueras, María J.

2018-01-01

The species Arcobacter cryaerophilus is found in many food products of animal origin and is the dominating species in wastewater. In addition, it is associated with cases of farm animal and human infectious diseases,. The species embraces two subgroups i.e., 1A (LMG 24291T = LMG 9904T) and 1B (LMG 10829) that can be differentiated by their 16S rRNA-RFLP pattern. However, some authors, on the basis of the shared intermediate levels of DNA-DNA hybridization, have suggested abandoning the subgroup classification. This contradiction indicates that the taxonomy of this species is not yet resolved. The objective of the present study was to perform a taxonomic evaluation of the diversity of A. cryaerophilus. Genomic information was used along with a Multilocus Phylogenetic Analysis (MLPA) and phenotypic characterization on a group of 52 temporally and geographically dispersed strains, coming from different types of samples and hosts from nine countries. The MLPA analysis showed that those strains formed four clusters (I–IV). Values of Average Nucleotide Identity (ANI) and in silico DNA-DNA Hybridization (isDDH) obtained between 13 genomes representing strains of the four clusters were below the proposed cut-offs of 96 and 70%, respectively, confirming that each of the clusters represented a different genomic species. However, none of the evaluated phenotypic tests enabled their unequivocal differentiation into species. Therefore, the genomic delimited clusters should be considered genomovars of the species A. cryaerophilus. These genomovars could have different clinical importance, since only the cluster I included strains isolated from human specimens. The discovery of at least one stable distinctive phenotypic character would be needed to define each cluster or genomovar as a different species. Until then, we propose naming them “A. cryaerophilus gv. pseudocryaerophilus” (Cluster I = LMG 10229T), “A. cryaerophilus gv. crypticus” (Cluster II = LMG 9065T), “A. cryaerophilus gv. cryaerophilus” (Cluster III = LMG 24291T) and “A. cryaerophilus gv. occultus” (Cluster IV = LMG 29976T).

OGLE Collection of Star Clusters. New Objects in the Outskirts of the Large Magellanic Cloud

NASA Astrophysics Data System (ADS)

Sitek, M.; Szymański, M. K.; Skowron, D. M.; Udalski, A.; Kostrzewa-Rutkowska, Z.; Skowron, J.; Karczmarek, P.; Cieślar, M.; Wyrzykowski, Ł.; Kozłowski, S.; Pietrukowicz, P.; Soszyński, I.; Mróz, P.; Pawlak, M.; Poleski, R.; Ulaczyk, K.

2016-09-01

The Magellanic System (MS), consisting of the Large Magellanic Cloud (LMC), the Small Magellanic Cloud (SMC) and the Magellanic Bridge (MBR), contains diverse sample of star clusters. Their spatial distribution, ages and chemical abundances may provide important information about the history of formation of the whole System. We use deep photometric maps derived from the images collected during the fourth phase of the Optical Gravitational Lensing Experiment (OGLE-IV) to construct the most complete catalog of star clusters in the Large Magellanic Cloud using the homogeneous photometric data. In this paper we present the collection of star clusters found in the area of about 225 square degrees in the outer regions of the LMC. Our sample contains 679 visually identified star cluster candidates, 226 of which were not listed in any of the previously published catalogs. The new clusters are mainly young small open clusters or clusters similar to associations.

Fine-Tuning the Activity of Metal–Organic Framework Supported Cobalt Catalysts for the Oxidative Dehydrogenation of Propane

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

Li, Zhanyong; Peters, Aaron W.; Platero-Prats, Ana E.

Few-atom cobalt-oxide clusters, when dispersed on a Zr-based metal–organic framework (MOF) NU-1000, have previously been shown to be active for the oxidative dehydrogenation (ODH) of propane at low temperatures (< 230 °C), affording a selective and stable propene production catalyst. In our current work, a series of promoter ions with varying Lewis acidity, including Ni(II), Zn(II), Al(III), Ti(IV) and Mo(VI), are anchored as metal-oxide,hydroxide clusters to NU-1000 via SIM (solvothermal deposition within MOFs–specifically the nodes) followed by incorporation of Co(II) ions via vapor-phase AIM (atomic layer deposition (ALD) in MOFs). This process yields a series of NU-1000-supported bimetallic-oxo,hydroxo,aqua clusters. Usingmore » difference envelope density (DED) analyses, the spatial locations of the promoter ions and catalytic cobalt ions are determined. For all samples the SIM-anchored promoter ions are sited between pairs of Zr 6 nodes along the MOF c-axis (channel-aligned axis) whereas the location of the AIM-anchored cobalt ions varies depending on the identity of promoter metal ion. With Ni(II)-, Al(III)-, or Ti(IV)-containing clusters as promoters, the oxy-cobalt species are sited atop the promoter sites; with Mo(VI) they grow exclusively on the MOF nodes sites (hexa-Zr(IV)- oxo,hydroxo,aqua units); with Zn(II) they grow on both the node and promoter. The NU-1000- supported bimetallic-oxide clusters are active for propane ODH after thermal activation under O 2 to open a cobalt coordination site and to oxidize Co(II) to Co(III), as evidenced by operando Xray absorption spectroscopy at the Co K-edge. The cobalt component is exclusively responsible for the observed catalysis. In accord with the decreasing Lewis acidity of the promoter ion, catalytic activity increases in the order: Mo(VI)« less

Fine-Tuning the Activity of Metal–Organic Framework Supported Cobalt Catalysts for the Oxidative Dehydrogenation of Propane

DOE PAGES

Li, Zhanyong; Peters, Aaron W.; Platero-Prats, Ana E.; ...

2017-10-04

Few-atom cobalt-oxide clusters, when dispersed on a Zr-based metal–organic framework (MOF) NU-1000, have previously been shown to be active for the oxidative dehydrogenation (ODH) of propane at low temperatures (< 230 °C), affording a selective and stable propene production catalyst. In our current work, a series of promoter ions with varying Lewis acidity, including Ni(II), Zn(II), Al(III), Ti(IV) and Mo(VI), are anchored as metal-oxide,hydroxide clusters to NU-1000 via SIM (solvothermal deposition within MOFs–specifically the nodes) followed by incorporation of Co(II) ions via vapor-phase AIM (atomic layer deposition (ALD) in MOFs). This process yields a series of NU-1000-supported bimetallic-oxo,hydroxo,aqua clusters. Usingmore » difference envelope density (DED) analyses, the spatial locations of the promoter ions and catalytic cobalt ions are determined. For all samples the SIM-anchored promoter ions are sited between pairs of Zr 6 nodes along the MOF c-axis (channel-aligned axis) whereas the location of the AIM-anchored cobalt ions varies depending on the identity of promoter metal ion. With Ni(II)-, Al(III)-, or Ti(IV)-containing clusters as promoters, the oxy-cobalt species are sited atop the promoter sites; with Mo(VI) they grow exclusively on the MOF nodes sites (hexa-Zr(IV)- oxo,hydroxo,aqua units); with Zn(II) they grow on both the node and promoter. The NU-1000- supported bimetallic-oxide clusters are active for propane ODH after thermal activation under O 2 to open a cobalt coordination site and to oxidize Co(II) to Co(III), as evidenced by operando Xray absorption spectroscopy at the Co K-edge. The cobalt component is exclusively responsible for the observed catalysis. In accord with the decreasing Lewis acidity of the promoter ion, catalytic activity increases in the order: Mo(VI)« less

Molecular epidemiology is becoming complex under the dynamic HIV prevalence: The perspective from Harbin, China.

PubMed

Shao, Bing; Song, Bo; Cao, Lijun; Du, Juan; Sun, Dongying; Lin, Yuanlong; Wang, Binyou; Wang, Fuxiang; Wang, Sunran

2016-05-01

Unlike most areas of China, HIV transmission via men who have sex with men (MSM) is increasing rapidly, and has become the main route of HIV transmission in Harbin city. The purpose of the current study was to elaborate the molecular epidemiologic characteristics of the new HIV epidemic. Eighty-one HIV-1 gag gene sequences (HXB2:806-1861) from local HIV infections were isolated; CRF01_AE predominated among HIV infections (71.6%), followed by subtype B (16.5%), CRF07_BC (6.2%), and unique recombinant strains (URFs; 6.2%). URFs were most often identified in the MSM population, which consisted of a recombination of CRF01_AE with subtype B or CRF07_BC. Six clusters were formed in this analysis; clusters I and II mainly circulated in southwest China. Clusters III and IV mainly circulated in southwest, southeast, and central China. Clusters V and VI mainly circulated in north and northeast China. Clusters III and IV may facilitate the transmission of the CRF01_AE strain from the southwest to the north and northeast regions of China. HIV subtypes are becoming diverse with the persistent epidemic in this geographic region. In brief, our results indicate that the molecular epidemiology of HIV is trending to be more complex. Thus, timely molecular epidemiologic supervision of HIV is necessary, especially for the MSM population. © 2015 Wiley Periodicals, Inc.

Adaptive Scaling of Cluster Boundaries for Large-Scale Social Media Data Clustering.

PubMed

Meng, Lei; Tan, Ah-Hwee; Wunsch, Donald C

2016-12-01

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the clustering mechanism of Fuzzy ART, and discover the vigilance region (VR) that essentially determines how a cluster in the Fuzzy ART system recognizes similar patterns in the feature space. The VR gives an intrinsic interpretation of the clustering mechanism and limitations of Fuzzy ART. Second, we introduce the idea of allowing different clusters in the Fuzzy ART system to have different vigilance levels in order to meet the diverse nature of the pattern distribution of social media data. To this end, we propose three vigilance adaptation methods, namely, the activation maximization (AM) rule, the confliction minimization (CM) rule, and the hybrid integration (HI) rule. With an initial vigilance value, the resulting clustering algorithms, namely, the AM-ART, CM-ART, and HI-ART, can automatically adapt the vigilance values of all clusters during the learning epochs in order to produce better cluster boundaries. Experiments on four social media data sets show that AM-ART, CM-ART, and HI-ART are more robust than Fuzzy ART to the initial vigilance value, and they usually achieve better or comparable performance and much faster speed than the state-of-the-art clustering algorithms that also do not require a predefined number of clusters.

Symptom Cluster Research With Biomarkers and Genetics Using Latent Class Analysis.

PubMed

Conley, Samantha

2017-12-01

The purpose of this article is to provide an overview of latent class analysis (LCA) and examples from symptom cluster research that includes biomarkers and genetics. A review of LCA with genetics and biomarkers was conducted using Medline, Embase, PubMed, and Google Scholar. LCA is a robust latent variable model used to cluster categorical data and allows for the determination of empirically determined symptom clusters. Researchers should consider using LCA to link empirically determined symptom clusters to biomarkers and genetics to better understand the underlying etiology of symptom clusters. The full potential of LCA in symptom cluster research has not yet been realized because it has been used in limited populations, and researchers have explored limited biologic pathways.

A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis

PubMed Central

Liu, Jingxian; Wu, Kefeng

2017-01-01

The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with traditional spectral clustering and fast affinity propagation clustering. Experimental results have illustrated its superior performance in terms of quantitative and qualitative evaluations. PMID:28777353

Robust fiber clustering of cerebral fiber bundles in white matter

NASA Astrophysics Data System (ADS)

Yao, Xufeng; Wang, Yongxiong; Zhuang, Songlin

2014-11-01

Diffusion tensor imaging fiber tracking (DTI-FT) has been widely accepted in the diagnosis and treatment of brain diseases. During the rendering pipeline of specific fiber tracts, the image noise and low resolution of DTI would lead to false propagations. In this paper, we propose a robust fiber clustering (FC) approach to diminish false fibers from one fiber tract. Our algorithm consists of three steps. Firstly, the optimized fiber assignment continuous tracking (FACT) is implemented to reconstruct one fiber tract; and then each curved fiber in the fiber tract is mapped to a point by kernel principal component analysis (KPCA); finally, the point clouds of fiber tract are clustered by hierarchical clustering which could distinguish false fibers from true fibers in one tract. In our experiment, the corticospinal tract (CST) in one case of human data in vivo was used to validate our method. Our method showed reliable capability in decreasing the false fibers in one tract. In conclusion, our method could effectively optimize the visualization of fiber bundles and would help a lot in the field of fiber evaluation.

Vertebra identification using template matching modelmp and K-means clustering.

PubMed

Larhmam, Mohamed Amine; Benjelloun, Mohammed; Mahmoudi, Saïd

2014-03-01

Accurate vertebra detection and segmentation are essential steps for automating the diagnosis of spinal disorders. This study is dedicated to vertebra alignment measurement, the first step in a computer-aided diagnosis tool for cervical spine trauma. Automated vertebral segment alignment determination is a challenging task due to low contrast imaging and noise. A software tool for segmenting vertebrae and detecting subluxations has clinical significance. A robust method was developed and tested for cervical vertebra identification and segmentation that extracts parameters used for vertebra alignment measurement. Our contribution involves a novel combination of a template matching method and an unsupervised clustering algorithm. In this method, we build a geometric vertebra mean model. To achieve vertebra detection, manual selection of the region of interest is performed initially on the input image. Subsequent preprocessing is done to enhance image contrast and detect edges. Candidate vertebra localization is then carried out by using a modified generalized Hough transform (GHT). Next, an adapted cost function is used to compute local voted centers and filter boundary data. Thereafter, a K-means clustering algorithm is applied to obtain clusters distribution corresponding to the targeted vertebrae. These clusters are combined with the vote parameters to detect vertebra centers. Rigid segmentation is then carried out by using GHT parameters. Finally, cervical spine curves are extracted to measure vertebra alignment. The proposed approach was successfully applied to a set of 66 high-resolution X-ray images. Robust detection was achieved in 97.5 % of the 330 tested cervical vertebrae. An automated vertebral identification method was developed and demonstrated to be robust to noise and occlusion. This work presents a first step toward an automated computer-aided diagnosis system for cervical spine trauma detection.

Recombination and positive selection contributed to the evolution of Listeria monocytogenes lineages III and IV, two distinct and well supported uncommon L. monocytogenes lineages.

PubMed

Tsai, Yeu-Harn Lucy; Maron, Steve B; McGann, Patrick; Nightingale, Kendra K; Wiedmann, Martin; Orsi, Renato H

2011-12-01

Listeriamonocytogenes lineages III and IV represent two uncommon lineages of the human and animal pathogen L. monocytogenes, characterized by occurrence of unusual phenotypic and genetic characteristics that differentiate them from the common lineages I and II. To gain further insights into the evolution of lineages III and IV, we amplified and sequenced housekeeping genes (i.e., gap, prs, purM, ribC, and sigB), internalin genes (i.e., inlA, inlB, inlC, inlG, inlC2, inlD, inlE, inlF, and inlH) and the virulence gene cluster containing prfA, plcA, hly, mpl, actA, and plcB for lineages III (n = 7) and IV (n = 4) isolates. Phylogenetic analyses of the sequences obtained along with previously reported sequence data for 40 isolates representing lineages I (n = 18), II (n = 21), and III (n = 1), showed that lineages III and IV represent divergent and monophyletic lineages. The virulence gene cluster as well as the inlAB operon were present in all isolates, with inlF absent from all lineages III and IV isolates. While all lineage IV isolates contained only inlC (in addition to inlAB), lineage III isolates showed considerable diversity with regard to internalin gene presence, including presence of (i) only inlC (n = 2), (ii) inlC and inlGC2DE (n = 3), (iii) only inlGC2DE (n = 2), and (iv) inlC and inlC2DE (n = 1). In addition to evidence for horizontal gene transfer events, among lineages III and IV isolates, in prs, actA, plcB, mpl, inlA, inlB, inlG, inlD, and inlE, we also found significant evidence for positive selection in the hly promoter region and, along the lineages III and IV branches, for actA (including in sites recognized for interactions with proteins involved in actin tail polymerization). In conclusion, lineages III and IV represent two distinct monophyletic groups with contributions of intragenic recombination to the evolution of their internalin genes as well as contributions of positive selection to evolution of the virulence genes island. Copyright © 2011 Elsevier B.V. All rights reserved.

Genomic analyses of bacterial porin-cytochrome gene clusters

DOE PAGES

Shi, Liang; Fredrickson, James K.; Zachara, John M.

2014-11-26

In this study, the porin-cytochrome (Pcc) protein complex is responsible for trans-outer membrane electron transfer during extracellular reduction of Fe(III) by the dissimilatory metal-reducing bacterium Geobacter sulfurreducens PCA. The identified and characterized Pcc complex of G. sulfurreducens PCA consists of a porin-like outer-membrane protein, a periplasmic 8-heme c type cytochrome (c-Cyt) and an outer-membrane 12-heme c-Cyt, and the genes encoding the Pcc proteins are clustered in the same regions of genome (i.e., the pcc gene clusters) of G. sulfurreducens PCA. A survey of additionally microbial genomes has identified the pcc gene clusters in all sequenced Geobacter spp. and other bacteriamore » from six different phyla, including Anaeromyxobacter dehalogenans 2CP-1, A. dehalogenans 2CP-C, Anaeromyxobacter sp. K, Candidatus Kuenenia stuttgartiensis, Denitrovibrio acetiphilus DSM 12809, Desulfurispirillum indicum S5, Desulfurivibrio alkaliphilus AHT2, Desulfurobacterium thermolithotrophum DSM 11699, Desulfuromonas acetoxidans DSM 684, Ignavibacterium album JCM 16511, and Thermovibrio ammonificans HB-1. The numbers of genes in the pcc gene clusters vary, ranging from two to nine. Similar to the metal-reducing (Mtr) gene clusters of other Fe(III)-reducing bacteria, such as Shewanella spp., additional genes that encode putative c-Cyts with predicted cellular localizations at the cytoplasmic membrane, periplasm and outer membrane often associate with the pcc gene clusters. This suggests that the Pcc-associated c-Cyts may be part of the pathways for extracellular electron transfer reactions. The presence of pcc gene clusters in the microorganisms that do not reduce solid-phase Fe(III) and Mn(IV) oxides, such as D. alkaliphilus AHT2 and I. album JCM 16511, also suggests that some of the pcc gene clusters may be involved in extracellular electron transfer reactions with the substrates other than Fe(III) and Mn(IV) oxides.« less

Variation in tibial functionality and fracture susceptibility among healthy, young adults arises from the acquisition of biologically distinct sets of traits.

PubMed

Jepsen, Karl J; Evans, Rachel; Negus, Charles H; Gagnier, Joel J; Centi, Amanda; Erlich, Tomer; Hadid, Amir; Yanovich, Ran; Moran, Daniel S

2013-06-01

Physiological systems like bone respond to many genetic and environmental factors by adjusting traits in a highly coordinated, compensatory manner to establish organ-level function. To be mechanically functional, a bone should be sufficiently stiff and strong to support physiological loads. Factors impairing this process are expected to compromise strength and increase fracture risk. We tested the hypotheses that individuals with reduced stiffness relative to body size will show an increased risk of fracturing and that reduced strength arises from the acquisition of biologically distinct sets of traits (ie, different combinations of morphological and tissue-level mechanical properties). We assessed tibial functionality retrospectively for 336 young adult women and men engaged in military training, and calculated robustness (total area/bone length), cortical area (Ct.Ar), and tissue-mineral density (TMD). These three traits explained 69% to 72% of the variation in tibial stiffness (p < 0.0001). Having reduced stiffness relative to body size (body weight × bone length) was associated with odds ratios of 1.5 (95% confidence interval [CI], 0.5-4.3) and 7.0 (95% CI, 2.0-25.1) for women and men, respectively, for developing a stress fracture based on radiography and scintigraphy. K-means cluster analysis was used to segregate men and women into subgroups based on robustness, Ct.Ar, and TMD adjusted for body size. Stiffness varied 37% to 42% among the clusters (p < 0.0001, ANOVA). For men, 78% of stress fracture cases segregated to three clusters (p < 0.03, chi-square). Clusters showing reduced function exhibited either slender tibias with the expected Ct.Ar and TMD relative to body size and robustness (ie, well-adapted bones) or robust tibias with reduced residuals for Ct.Ar or TMD relative to body size and robustness (ie, poorly adapted bones). Thus, we show there are multiple biomechanical and thus biological pathways leading to reduced function and increased fracture risk. Our results have important implications for developing personalized preventative diagnostics and treatments. Copyright © 2013 American Society for Bone and Mineral Research.

The energy and stability of helium-related cluster in nickel: A study of molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Gong, Hengfeng; Wang, Chengbin; Zhang, Wei; Xu, Jian; Huai, Ping; Deng, Huiqiu; Hu, Wangyu

2016-02-01

Using molecular dynamics simulation, we investigated the energy and stability of helium-related cluster in nickel. All the binding energies of the He-related clusters are demonstrated to be positive and increase with the cluster sizes. Due to the pre-existed self-interstitial nickel atom, the trapping capability of vacancy to defects becomes weak. Besides, the minimum energy configurations of He-related clusters exhibit the very high symmetry in the local atomistic environment. And for the HeN and HeNV1SIA1 clusters, the average length of He-He bonds shortens, but it elongates for the HeNV1 clusters with helium cluster sizes. The helium-to-vacancy ratio plays a decisive role on the binding energies of HeNVM cluster. These results can provide some excellent clues to insight the initial stage of helium bubbles nucleation and growth in the Ni-based alloys for the Generation-IV Molten Salt Reactor.

Short-range order in the Ca sub 1-x La sub x F sub 2+x solid solution: 1:0:3 or 1:0:4 clusters

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

Laval, J.P.; Abaouz, A.; Frit, B.

1989-08-01

The defect structure of the Ca{sub 1-x}La{sub x}F{sub 2+x} solid solution (0 {le} x {le} 0.38) has been examined at room temperature by powder neutron diffraction. Two kinds of (xxx) interstitial anions, whose respective numbers increase linearly with increasing dopant cation concentration, have been found: one labeled F{sup 0} (x {approx} 0.41) is a true interstitial; the other labeled F{sup {prime}{double prime}} (x {approx} 0.31) can be considered a relaxed normal anion. Two 1:0:n defect clusters are compatible, within the experimental errors, with these results: the 1:0:3 (1V{sub F}, OF{prime}, 3F{sup {double prime}}, 2 La{sup 3+}) and the 1:0:4 (1V{submore » F}, OF{prime}, 4F{sup {double prime}}, 3La{sup 3+}) clusters. Charge balance considerations and comparisons with the homologous Ca{sub 1-x}M{sub x}{sup IV}F{sub 2+2x} solid solutions (M{sup IV} = Th, U) allow us to think that the less dense 1:0:3 cluster is present for the whole domain of both kinds of solid solutions.« less

Respiratory chain supercomplexes associate with the cysteine desulfurase complex of the iron–sulfur cluster assembly machinery

PubMed Central

Böttinger, Lena; Mårtensson, Christoph U.; Song, Jiyao; Zufall, Nicole; Wiedemann, Nils; Becker, Thomas

2018-01-01

Mitochondria are the powerhouses of eukaryotic cells. The activity of the respiratory chain complexes generates a proton gradient across the inner membrane, which is used by the F1FO-ATP synthase to produce ATP for cellular metabolism. In baker’s yeast, Saccharomyces cerevisiae, the cytochrome bc1 complex (complex III) and cytochrome c oxidase (complex IV) associate in respiratory chain supercomplexes. Iron–sulfur clusters (ISC) form reactive centers of respiratory chain complexes. The assembly of ISC occurs in the mitochondrial matrix and is essential for cell viability. The cysteine desulfurase Nfs1 provides sulfur for ISC assembly and forms with partner proteins the ISC-biogenesis desulfurase complex (ISD complex). Here, we report an unexpected interaction of the active ISD complex with the cytochrome bc1 complex and cytochrome c oxidase. The individual deletion of complex III or complex IV blocks the association of the ISD complex with respiratory chain components. We conclude that the ISD complex binds selectively to respiratory chain supercomplexes. We propose that this molecular link contributes to coordination of iron–sulfur cluster formation with respiratory activity. PMID:29386296

Small Sample Performance of Bias-corrected Sandwich Estimators for Cluster-Randomized Trials with Binary Outcomes

PubMed Central

Li, Peng; Redden, David T.

2014-01-01

SUMMARY The sandwich estimator in generalized estimating equations (GEE) approach underestimates the true variance in small samples and consequently results in inflated type I error rates in hypothesis testing. This fact limits the application of the GEE in cluster-randomized trials (CRTs) with few clusters. Under various CRT scenarios with correlated binary outcomes, we evaluate the small sample properties of the GEE Wald tests using bias-corrected sandwich estimators. Our results suggest that the GEE Wald z test should be avoided in the analyses of CRTs with few clusters even when bias-corrected sandwich estimators are used. With t-distribution approximation, the Kauermann and Carroll (KC)-correction can keep the test size to nominal levels even when the number of clusters is as low as 10, and is robust to the moderate variation of the cluster sizes. However, in cases with large variations in cluster sizes, the Fay and Graubard (FG)-correction should be used instead. Furthermore, we derive a formula to calculate the power and minimum total number of clusters one needs using the t test and KC-correction for the CRTs with binary outcomes. The power levels as predicted by the proposed formula agree well with the empirical powers from the simulations. The proposed methods are illustrated using real CRT data. We conclude that with appropriate control of type I error rates under small sample sizes, we recommend the use of GEE approach in CRTs with binary outcomes due to fewer assumptions and robustness to the misspecification of the covariance structure. PMID:25345738

Identification of piecewise affine systems based on fuzzy PCA-guided robust clustering technique

NASA Astrophysics Data System (ADS)

Khanmirza, Esmaeel; Nazarahari, Milad; Mousavi, Alireza

2016-12-01

Hybrid systems are a class of dynamical systems whose behaviors are based on the interaction between discrete and continuous dynamical behaviors. Since a general method for the analysis of hybrid systems is not available, some researchers have focused on specific types of hybrid systems. Piecewise affine (PWA) systems are one of the subsets of hybrid systems. The identification of PWA systems includes the estimation of the parameters of affine subsystems and the coefficients of the hyperplanes defining the partition of the state-input domain. In this paper, we have proposed a PWA identification approach based on a modified clustering technique. By using a fuzzy PCA-guided robust k-means clustering algorithm along with neighborhood outlier detection, the two main drawbacks of the well-known clustering algorithms, i.e., the poor initialization and the presence of outliers, are eliminated. Furthermore, this modified clustering technique enables us to determine the number of subsystems without any prior knowledge about system. In addition, applying the structure of the state-input domain, that is, considering the time sequence of input-output pairs, provides a more efficient clustering algorithm, which is the other novelty of this work. Finally, the proposed algorithm has been evaluated by parameter identification of an IGV servo actuator. Simulation together with experiment analysis has proved the effectiveness of the proposed method.

Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments.

PubMed

Liu, Wen; Fu, Xiao; Deng, Zhongliang

2016-12-02

Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means.

Coordinate-Based Clustering Method for Indoor Fingerprinting Localization in Dense Cluttered Environments

PubMed Central

Liu, Wen; Fu, Xiao; Deng, Zhongliang

2016-01-01

Indoor positioning technologies has boomed recently because of the growing commercial interest in indoor location-based service (ILBS). Due to the absence of satellite signal in Global Navigation Satellite System (GNSS), various technologies have been proposed for indoor applications. Among them, Wi-Fi fingerprinting has been attracting much interest from researchers because of its pervasive deployment, flexibility and robustness to dense cluttered indoor environments. One challenge, however, is the deployment of Access Points (AP), which would bring a significant influence on the system positioning accuracy. This paper concentrates on WLAN based fingerprinting indoor location by analyzing the AP deployment influence, and studying the advantages of coordinate-based clustering compared to traditional RSS-based clustering. A coordinate-based clustering method for indoor fingerprinting location, named Smallest-Enclosing-Circle-based (SEC), is then proposed aiming at reducing the positioning error lying in the AP deployment and improving robustness to dense cluttered environments. All measurements are conducted in indoor public areas, such as the National Center For the Performing Arts (as Test-bed 1) and the XiDan Joy City (Floors 1 and 2, as Test-bed 2), and results show that SEC clustering algorithm can improve system positioning accuracy by about 32.7% for Test-bed 1, 71.7% for Test-bed 2 Floor 1 and 73.7% for Test-bed 2 Floor 2 compared with traditional RSS-based clustering algorithms such as K-means. PMID:27918454

Individualization as Driving Force of Clustering Phenomena in Humans

PubMed Central

Mäs, Michael; Flache, Andreas; Helbing, Dirk

2010-01-01

One of the most intriguing dynamics in biological systems is the emergence of clustering, in the sense that individuals self-organize into separate agglomerations in physical or behavioral space. Several theories have been developed to explain clustering in, for instance, multi-cellular organisms, ant colonies, bee hives, flocks of birds, schools of fish, and animal herds. A persistent puzzle, however, is the clustering of opinions in human populations, particularly when opinions vary continuously, such as the degree to which citizens are in favor of or against a vaccination program. Existing continuous opinion formation models predict “monoculture” in the long run, unless subsets of the population are perfectly separated from each other. Yet, social diversity is a robust empirical phenomenon, although perfect separation is hardly possible in an increasingly connected world. Considering randomness has not overcome the theoretical shortcomings so far. Small perturbations of individual opinions trigger social influence cascades that inevitably lead to monoculture, while larger noise disrupts opinion clusters and results in rampant individualism without any social structure. Our solution to the puzzle builds on recent empirical research, combining the integrative tendencies of social influence with the disintegrative effects of individualization. A key element of the new computational model is an adaptive kind of noise. We conduct computer simulation experiments demonstrating that with this kind of noise a third phase besides individualism and monoculture becomes possible, characterized by the formation of metastable clusters with diversity between and consensus within clusters. When clusters are small, individualization tendencies are too weak to prohibit a fusion of clusters. When clusters grow too large, however, individualization increases in strength, which promotes their splitting. In summary, the new model can explain cultural clustering in human societies. Strikingly, model predictions are not only robust to “noise”—randomness is actually the central mechanism that sustains pluralism and clustering. PMID:20975937

A Capability-Based Approach to Analyzing the Effectiveness and Robustness of an Offshore Patrol Vessel in the Search and Rescue Mission

DTIC Science & Technology

2012-12-01

13 D. NPSS MODEL DEVELOPMENT...COMPARISON: NPSS MODEL WITH ITALIAN MODEL ...................51 IV. CONCLUSIONS AND RECOMMENDATIONS...58 1. Italian Model Recommendations ......................................................58 2. NPSS Model

Fusion And Inference From Multiple And Massive Disparate Distributed Dynamic Data Sets

DTIC Science & Technology

2017-07-01

principled methodology for two-sample graph testing; designed a provably almost-surely perfect vertex clustering algorithm for block model graphs; proved...3.7 Semi-Supervised Clustering Methodology ...................................................................... 9 3.8 Robust Hypothesis Testing...dimensional Euclidean space – allows the full arsenal of statistical and machine learning methodology for multivariate Euclidean data to be deployed for

An examination of DSM-IV depressive symptoms and risk for suicide completion in major depressive disorder: a psychological autopsy study.

PubMed

McGirr, Alexander; Renaud, Johanne; Seguin, Monique; Alda, Martin; Benkelfat, Chawki; Lesage, Alain; Turecki, Gustavo

2007-01-01

It is unclear whether certain DSM-IV depressive symptoms are more prevalent among individuals who die in the context of a major depressive episode and those who do not, whether this is associated with proximal or distal suicide risk, and whether depressive symptoms cluster to indicate suicide risk. A psychological autopsy method with best informants was used to investigate DSM-IV depressive symptoms among 156 suicides who died in the context of a major depressive episode and 81 major depressive controls. Suicides' depressive symptoms were more likely to include weight or appetite loss, insomnia, feelings of worthlessness or inappropriate guilt as well as recurrent thoughts of death or suicidal ideation. Fatigue and difficulties concentrating or indecisiveness were less prevalent among depressed suicides. These associations were independent of concomitant axis I and II psychopathology. The concomitant presence of (a) fatigue as well as impaired concentration or indecisiveness and (b) weight or appetite gain and hypersomnia was associated with decreased suicide risk. Inter-episode symptom concordance suggests that insomnia is an immediate indicator of suicide risk, while weight or appetite loss and feelings of worthlessness or guilt are not. This study employed proxy-based interviews. We found that discrete DSM-IV depressive symptoms and clusters of depressive symptoms help differentiate depressed individuals who die by suicide and those who do not. Moreover, some DSM-IV depressive symptoms are associated with an immediate risk for suicide, while others may result from an etiology of depression common to suicide without directly increasing suicide risk.

Properties of QSO Metal-line Absorption Systems at High Redshifts: Nature and Evolution of the Absorbers and New Evidence on Escape of Ionizing Radiation from Galaxies

NASA Astrophysics Data System (ADS)

Boksenberg, Alec; Sargent, Wallace L. W.

2015-05-01

Using Voigt-profile-fitting procedures on Keck High Resolution Spectrograph spectra of nine QSOs, we identify 1099 C IV absorber components clumped in 201 systems outside the Lyman forest over 1.6 <~ z <~ 4.4. With associated Si IV, C II, Si II and N V where available, we investigate the bulk statistical and ionization properties of the components and systems and find no significant change in redshift for C IV and Si IV while C II, Si II and N V change substantially. The C IV components exhibit strong clustering, but no clustering is detected for systems on scales from 150 km s-1 out to 50,000 km s-1. We conclude that the clustering is due entirely to the peculiar velocities of gas present in the circumgalactic media of galaxies. Using specific combinations of ionic ratios, we compare our observations with model ionization predictions for absorbers exposed to the metagalactic ionizing radiation background augmented by proximity radiation from their associated galaxies and find that the generally accepted means of radiative escape by transparent channels from the internal star-forming sites is spectrally not viable for our stronger absorbers. We develop an active scenario based on runaway stars with resulting changes in the efflux of radiation that naturally enable the needed spectral convergence, and in turn provide empirical indicators of morphological evolution in the associated galaxies. Together with a coexisting population of relatively compact galaxies indicated by the weaker absorbers in our sample, the collective escape of radiation is sufficient to maintain the intergalactic medium ionized over the full range 1.9 < z <~ 4.4. The data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The Observatory was made possible by the generous financial support of the W. M. Keck Foundation.

Non-Linear Metamodeling Extensions to the Robust Parameter Design of Computer Simulations

DTIC Science & Technology

2016-09-15

design By principal component analysis," Total Quality Management, vol. 8, no. 6, pp. 409-416, 1997. [25] A. Salmasnia, R. B . Kazemzadeh and S. T . A...and D. T . Sturrock, Simulation with Arena (3rd ed.), New York, NY: McGraw-Hill, 2004. [85] A. M. Mathai and S. B . Provost, Quadratic Forms in Random...PhD Member ADEDEJI B . BADIRU, PhD Dean, Graduate School of Engineering and Management iv AFIT-ENS-DS-16-S-026 Abstract Robust

STAR CLUSTERS IN A NUCLEAR STAR FORMING RING: THE DISAPPEARING STRING OF PEARLS

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

Väisänen, Petri; Barway, Sudhanshu; Randriamanakoto, Zara, E-mail: petri@saao.ac.za

2014-12-20

An analysis of the star cluster population in a low-luminosity early-type galaxy, NGC 2328, is presented. The clusters are found in a tight star forming nuclear spiral/ring pattern and we also identify a bar from structural two-dimensional decomposition. These massive clusters are forming very efficiently in the circumnuclear environment and they are young, possibly all less than 30 Myr of age. The clusters indicate an azimuthal age gradient, consistent with a ''pearls-on-a-string'' formation scenario, suggesting bar-driven gas inflow. The cluster mass function has a robust down turn at low masses at all age bins. Assuming clusters are born with a power-lawmore » distribution, this indicates extremely rapid disruption at timescales of just several million years. If found to be typical, it means that clusters born in dense circumnuclear rings do not survive to become old globular clusters in non-interacting systems.« less

NAS Requirements Checklist for Job Queuing/Scheduling Software

NASA Technical Reports Server (NTRS)

Jones, James Patton

1996-01-01

The increasing reliability of parallel systems and clusters of computers has resulted in these systems becoming more attractive for true production workloads. Today, the primary obstacle to production use of clusters of computers is the lack of a functional and robust Job Management System for parallel applications. This document provides a checklist of NAS requirements for job queuing and scheduling in order to make most efficient use of parallel systems and clusters for parallel applications. Future requirements are also identified to assist software vendors with design planning.

Neuropsychological Profiles on the WAIS-IV of Adults With ADHD.

PubMed

Theiling, Johanna; Petermann, Franz

2016-11-01

The aim of the study was to investigate the pattern of neuropsychological profiles on the Wechsler Adult Intelligence Scale-IV (WAIS-IV) for adults With ADHD relative to randomly matched controls and to assess overall intellectual ability discrepancies of the Full Scale Intelligence Quotient (FSIQ) and the General Ability Index (GAI). In all, 116 adults With ADHD and 116 controls between 16 and 71 years were assessed. Relative to controls, adults With ADHD show significant decrements in subtests with working memory and processing speed demands with moderate to large effect sizes and a higher GAI in comparison with the FSIQ. This suggests first that deficits identified with previous WAIS versions are robust in adults With ADHD and remain deficient when assessed with the WAIS-IV; second that the WAIS-IV reliably differentiates between patients and controls; and third that a reduction of the FSIQ is most likely due to a decrement in working memory and processing speed abilities. The findings have essential implications for the diagnostic process. © The Author(s) 2014.

Resolving Recent Plant Radiations: Power and Robustness of Genotyping-by-Sequencing.

PubMed

Fernández-Mazuecos, Mario; Mellers, Greg; Vigalondo, Beatriz; Sáez, Llorenç; Vargas, Pablo; Glover, Beverley J

2018-03-01

Disentangling species boundaries and phylogenetic relationships within recent evolutionary radiations is a challenge due to the poor morphological differentiation and low genetic divergence between species, frequently accompanied by phenotypic convergence, interspecific gene flow and incomplete lineage sorting. Here we employed a genotyping-by-sequencing (GBS) approach, in combination with morphometric analyses, to investigate a small western Mediterranean clade in the flowering plant genus Linaria that radiated in the Quaternary. After confirming the morphological and genetic distinctness of eight species, we evaluated the relative performances of concatenation and coalescent methods to resolve phylogenetic relationships. Specifically, we focused on assessing the robustness of both approaches to variations in the parameter used to estimate sequence homology (clustering threshold). Concatenation analyses suffered from strong systematic bias, as revealed by the high statistical support for multiple alternative topologies depending on clustering threshold values. By contrast, topologies produced by two coalescent-based methods (NJ$_{\\mathrm{st}}$, SVDquartets) were robust to variations in the clustering threshold. Reticulate evolution may partly explain incongruences between NJ$_{\\mathrm{st}}$, SVDquartets and concatenated trees. Integration of morphometric and coalescent-based phylogenetic results revealed (i) extensive morphological divergence associated with recent splits between geographically close or sympatric sister species and (ii) morphological convergence in geographically disjunct species. These patterns are particularly true for floral traits related to pollinator specialization, including nectar spur length, tube width and corolla color, suggesting pollinator-driven diversification. Given its relatively simple and inexpensive implementation, GBS is a promising technique for the phylogenetic and systematic study of recent radiations, but care must be taken to evaluate the robustness of results to variation of data assembly parameters.

Using cluster ensemble and validation to identify subtypes of pervasive developmental disorders.

PubMed

Shen, Jess J; Lee, Phil-Hyoun; Holden, Jeanette J A; Shatkay, Hagit

2007-10-11

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior. Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.

Using Cluster Ensemble and Validation to Identify Subtypes of Pervasive Developmental Disorders

PubMed Central

Shen, Jess J.; Lee, Phil Hyoun; Holden, Jeanette J.A.; Shatkay, Hagit

2007-01-01

Pervasive Developmental Disorders (PDD) are neurodevelopmental disorders characterized by impairments in social interaction, communication and behavior.1 Given the diversity and varying severity of PDD, diagnostic tools attempt to identify homogeneous subtypes within PDD. Identifying subtypes can lead to targeted etiology studies and to effective type-specific intervention. Cluster analysis can suggest coherent subsets in data; however, different methods and assumptions lead to different results. Several previous studies applied clustering to PDD data, varying in number and characteristics of the produced subtypes19. Most studies used a relatively small dataset (fewer than 150 subjects), and all applied only a single clustering method. Here we study a relatively large dataset (358 PDD patients), using an ensemble of three clustering methods. The results are evaluated using several validation methods, and consolidated through an integration step. Four clusters are identified, analyzed and compared to subtypes previously defined by the widely used diagnostic tool DSM-IV.2 PMID:18693920

Robust and fast-converging level set method for side-scan sonar image segmentation

NASA Astrophysics Data System (ADS)

Liu, Yan; Li, Qingwu; Huo, Guanying

2017-11-01

A robust and fast-converging level set method is proposed for side-scan sonar (SSS) image segmentation. First, the noise in each sonar image is removed using the adaptive nonlinear complex diffusion filter. Second, k-means clustering is used to obtain the initial presegmentation image from the denoised image, and then the distance maps of the initial contours are reinitialized to guarantee the accuracy of the numerical calculation used in the level set evolution. Finally, the satisfactory segmentation is achieved using a robust variational level set model, where the evolution control parameters are generated by the presegmentation. The proposed method is successfully applied to both synthetic image with speckle noise and real SSS images. Experimental results show that the proposed method needs much less iteration and therefore is much faster than the fuzzy local information c-means clustering method, the level set method using a gamma observation model, and the enhanced region-scalable fitting method. Moreover, the proposed method can usually obtain more accurate segmentation results compared with other methods.

Atomically Precise Metal Nanoclusters for Catalytic Application

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

Jin, Rongchao

2016-11-18

The central goal of this project is to explore the catalytic application of atomically precise gold nanoclusters. By solving the total structures of ligand-protected nanoclusters, we aim to correlate the catalytic properties of metal nanoclusters with their atomic/electronic structures. Such correlation unravel some fundamental aspects of nanocatalysis, such as the nature of particle size effect, origin of catalytic selectivity, particle-support interactions, the identification of catalytically active centers, etc. The well-defined nanocluster catalysts mediate the knowledge gap between single crystal model catalysts and real-world conventional nanocatalysts. These nanoclusters also hold great promise in catalyzing certain types of reactions with extraordinarily highmore » selectivity. These aims are in line with the overall goals of the catalytic science and technology of DOE and advance the BES mission “to support fundamental research to understand, predict, and ultimately control matter and energy at the level of electrons, atoms, and molecules”. Our group has successfully prepared different sized, robust gold nanoclusters protected by thiolates, such as Au 25(SR) 18, Au 28(SR) 20, Au 38(SR) 24, Au 99(SR) 42, Au 144(SR) 60, etc. Some of these nanoclusters have been crystallographically characterized through X-ray crystallography. These ultrasmall nanoclusters (< 2 nm diameter) exhibit discrete electronic structures due to quantum size effect, as opposed to quasicontinuous band structure of conventional metal nanoparticles or bulk metals. The available atomic structures (metal core plus surface ligands) of nanoclusters serve as the basis for structure-property correlations. We have investigated the unique catalytic properties of nanoclusters (i.e. not observed in conventional nanogold catalysts) and revealed the structure-selectivity relationships. Highlights of our works include: i) Effects of ligand, cluster charge state, and size on the catalytic reactivity in CO oxidation, semihydrogenation of alkynes; ii) Size-controlled synthesis of Au-n clusters and structural elucidation; iii) Catalytic mechanisms and correlation with structures of cluster catalyst; iv) Catalytic properties of Au nanorods in chemoselective hydrogenation of nitrobenzaldehyde and visible light driven photocatalytic reactions.« less

Grouping by proximity and the visual impression of approximate number in random dot arrays.

PubMed

Im, Hee Yeon; Zhong, Sheng-Hua; Halberda, Justin

2016-09-01

We address the challenges of how to model human perceptual grouping in random dot arrays and how perceptual grouping affects human number estimation in these arrays. We introduce a modeling approach relying on a modified k-means clustering algorithm to formally describe human observers' grouping behavior. We found that a default grouping window size of approximately 4° of visual angle describes human grouping judgments across a range of random dot arrays (i.e., items within 4° are grouped together). This window size was highly consistent across observers and images, and was also stable across stimulus durations, suggesting that the k-means model captured a robust signature of perceptual grouping. Further, the k-means model outperformed other models (e.g., CODE) at describing human grouping behavior. Next, we found that the more the dots in a display are clustered together, the more human observers tend to underestimate the numerosity of the dots. We demonstrate that this effect is independent of density, and the modified k-means model can predict human observers' numerosity judgments and underestimation. Finally, we explored the robustness of the relationship between clustering and dot number underestimation and found that the effects of clustering remain, but are greatly reduced, when participants receive feedback on every trial. Together, this work suggests some promising avenues for formal models of human grouping behavior, and it highlights the importance of a 4° window of perceptual grouping. Lastly, it reveals a robust, somewhat plastic, relationship between perceptual grouping and number estimation. Copyright © 2015 Elsevier Ltd. All rights reserved.

Biosensor approach to psychopathology classification.

PubMed

Koshelev, Misha; Lohrenz, Terry; Vannucci, Marina; Montague, P Read

2010-10-21

We used a multi-round, two-party exchange game in which a healthy subject played a subject diagnosed with a DSM-IV (Diagnostic and Statistics Manual-IV) disorder, and applied a Bayesian clustering approach to the behavior exhibited by the healthy subject. The goal was to characterize quantitatively the style of play elicited in the healthy subject (the proposer) by their DSM-diagnosed partner (the responder). The approach exploits the dynamics of the behavior elicited in the healthy proposer as a biosensor for cognitive features that characterize the psychopathology group at the other side of the interaction. Using a large cohort of subjects (n = 574), we found statistically significant clustering of proposers' behavior overlapping with a range of DSM-IV disorders including autism spectrum disorder, borderline personality disorder, attention deficit hyperactivity disorder, and major depressive disorder. To further validate these results, we developed a computer agent to replace the human subject in the proposer role (the biosensor) and show that it can also detect these same four DSM-defined disorders. These results suggest that the highly developed social sensitivities that humans bring to a two-party social exchange can be exploited and automated to detect important psychopathologies, using an interpersonal behavioral probe not directly related to the defining diagnostic criteria.

Incorporation of μ3-CO3 into an MnIII/MnIV Mn12 cluster: {[(cyclam)MnIV(μ-O)2MnIII(H2O)(μ-OH)]6(μ3-CO3)2}Cl8·24H2O

PubMed Central

Levaton, Ben B.; Olmstead, Marilyn M.

2010-01-01

The centrosymmetric title cluster, hexa­aquadi-μ3-carbonato-hexa­cyclamhexa-μ2-hydroxido-dodeca-μ2-oxido-hexa­mang­an­ese(IV)hexa­manganese(III) octa­chloride tetra­cosa­hydrate, [Mn12(CO3)2O12(OH)6(C10H24N4)6(H2O)6]Cl8·24H2O, has two μ3-CO3 groups that not only bridge octahedrally coordinated MnIII ions but also act as acceptors to two different kinds of hydrogen bonds. The carbonate anion is planar within experimental error and has an average C—O distance of 1.294 (4) Å. The crystal packing is stabilized by O—H⋯Cl, O—H⋯O, N—H⋯Cl and N—H⋯O hydrogen bonds. Two of the four independent chloride ions are disordered over five positions, and eight of the 12 independent water mol­ecules are disordered over 21 positions. PMID:21587382

Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects

PubMed Central

2012-01-01

Background Time-course gene expression data such as yeast cell cycle data may be periodically expressed. To cluster such data, currently used Fourier series approximations of periodic gene expressions have been found not to be sufficiently adequate to model the complexity of the time-course data, partly due to their ignoring the dependence between the expression measurements over time and the correlation among gene expression profiles. We further investigate the advantages and limitations of available models in the literature and propose a new mixture model with autoregressive random effects of the first order for the clustering of time-course gene-expression profiles. Some simulations and real examples are given to demonstrate the usefulness of the proposed models. Results We illustrate the applicability of our new model using synthetic and real time-course datasets. We show that our model outperforms existing models to provide more reliable and robust clustering of time-course data. Our model provides superior results when genetic profiles are correlated. It also gives comparable results when the correlation between the gene profiles is weak. In the applications to real time-course data, relevant clusters of coregulated genes are obtained, which are supported by gene-function annotation databases. Conclusions Our new model under our extension of the EMMIX-WIRE procedure is more reliable and robust for clustering time-course data because it adopts a random effects model that allows for the correlation among observations at different time points. It postulates gene-specific random effects with an autocorrelation variance structure that models coregulation within the clusters. The developed R package is flexible in its specification of the random effects through user-input parameters that enables improved modelling and consequent clustering of time-course data. PMID:23151154

The panchromatic Hubble Andromeda Treasury. V. Ages and masses of the year 1 stellar clusters

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

Fouesneau, Morgan; Johnson, L. Clifton; Weisz, Daniel R.

We present ages and masses for 601 star clusters in M31 from the analysis of the six filter integrated light measurements from near-ultraviolet to near-infrared wavelengths, made as part of the Panchromatic Hubble Andromeda Treasury (PHAT). We derive the ages and masses using a probabilistic technique, which accounts for the effects of stochastic sampling of the stellar initial mass function. Tests on synthetic data show that this method, in conjunction with the exquisite sensitivity of the PHAT observations and their broad wavelength baseline, provides robust age and mass recovery for clusters ranging from ∼10{sup 2} to 2 × 10{sup 6}more » M {sub ☉}. We find that the cluster age distribution is consistent with being uniform over the past 100 Myr, which suggests a weak effect of cluster disruption within M31. The age distribution of older (>100 Myr) clusters falls toward old ages, consistent with a power-law decline of index –1, likely from a combination of fading and disruption of the clusters. We find that the mass distribution of the whole sample can be well described by a single power law with a spectral index of –1.9 ± 0.1 over the range of 10{sup 3}-3 × 10{sup 5} M {sub ☉}. However, if we subdivide the sample by galactocentric radius, we find that the age distributions remain unchanged. However, the mass spectral index varies significantly, showing best-fit values between –2.2 and –1.8, with the shallower slope in the highest star formation intensity regions. We explore the robustness of our study to potential systematics and conclude that the cluster mass function may vary with respect to environment.« 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.

Epidemiological characteristics of reported sporadic and outbreak cases of E. coli O157 in people from Alberta, Canada (2000-2002): methodological challenges of comparing clustered to unclustered data.

PubMed

Pearl, D L; Louie, M; Chui, L; Doré, K; Grimsrud, K M; Martin, S W; Michel, P; Svenson, L W; McEwen, S A

2008-04-01

Using multivariable models, we compared whether there were significant differences between reported outbreak and sporadic cases in terms of their sex, age, and mode and site of disease transmission. We also determined the potential role of administrative, temporal, and spatial factors within these models. We compared a variety of approaches to account for clustering of cases in outbreaks including weighted logistic regression, random effects models, general estimating equations, robust variance estimates, and the random selection of one case from each outbreak. Age and mode of transmission were the only epidemiologically and statistically significant covariates in our final models using the above approaches. Weighing observations in a logistic regression model by the inverse of their outbreak size appeared to be a relatively robust and valid means for modelling these data. Some analytical techniques, designed to account for clustering, had difficulty converging or producing realistic measures of association.

Rat epileptic seizures evoked by BmK {alpha}IV and its possible mechanisms involved in sodium channels

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

Chai Zhifang; Bai Zhantao; Zhang Xuying

2007-05-01

This study showed that rat unilateral intracerebroventricular injection of BmK {alpha}IV, a sodium channel modulator derived from scorpion Buthus martensi Karsch, induced clusters of spikes, epileptic discharges and convulsion-related behavioral changes. BmK {alpha}IV potently promoted the release of endogenous glutamate from rat cerebrocortical synaptosomes. In vitro examination of the effect of BmK {alpha}IV on intrasynaptosomal free calcium concentration [Ca{sup 2+}]{sub i} and sodium concentration [Na{sup +}]{sub i} revealed that BmK {alpha}IV-evoked glutamate release from synaptosomes was associated with an increase in Ca{sup 2+} and Na{sup +} influx. Moreover, BmK {alpha}IV-mediated glutamate release and ion influx was completely blocked by tetrodotoxin,more » a blocker of sodium channel. Together, these results suggest that the induction of BmK {alpha}IV-evoked epileptic seizures may be involved in the modulation of BmK {alpha}IV on tetrodotoxin-sensitive sodium channels located on the nerve terminal, which subsequently enhances the Ca{sup 2+} influx to cause an increase of glutamate release. These findings may provide some insight regarding the mechanism of neuronal action of BmK {alpha}IV in the central nervous system for understanding epileptogenesis involved in sodium channels.« less

Spray Drying as a Reliable Route to Produce Metastable Carbamazepine Form IV.

PubMed

Halliwell, Rebecca A; Bhardwaj, Rajni M; Brown, Cameron J; Briggs, Naomi E B; Dunn, Jaclyn; Robertson, John; Nordon, Alison; Florence, Alastair J

2017-07-01

Carbamazepine (CBZ) is an active pharmaceutical ingredient used in the treatment of epilepsy that can form at least 5 polymorphic forms. Metastable form IV was originally discovered from crystallization with polymer additives; however, it has not been observed from subsequent solvent-only crystallization efforts. This work reports the reproducible formation of phase pure crystalline form IV by spray drying of methanolic CBZ solution. Characterization of the material was carried out using diffraction, scanning electron microscopy, and differential scanning calorimetry. In situ Raman spectroscopy was used to monitor the spray-dried product during the spray drying process. This work demonstrates that spray drying provides a robust method for the production of form IV CBZ, and the combination of high supersaturation and rapid solid isolation from solution overcomes the apparent limitation of more traditional solution crystallization approaches to produce metastable crystalline forms. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

iNJclust: Iterative Neighbor-Joining Tree Clustering Framework for Inferring Population Structure.

PubMed

Limpiti, Tulaya; Amornbunchornvej, Chainarong; Intarapanich, Apichart; Assawamakin, Anunchai; Tongsima, Sissades

2014-01-01

Understanding genetic differences among populations is one of the most important issues in population genetics. Genetic variations, e.g., single nucleotide polymorphisms, are used to characterize commonality and difference of individuals from various populations. This paper presents an efficient graph-based clustering framework which operates iteratively on the Neighbor-Joining (NJ) tree called the iNJclust algorithm. The framework uses well-known genetic measurements, namely the allele-sharing distance, the neighbor-joining tree, and the fixation index. The behavior of the fixation index is utilized in the algorithm's stopping criterion. The algorithm provides an estimated number of populations, individual assignments, and relationships between populations as outputs. The clustering result is reported in the form of a binary tree, whose terminal nodes represent the final inferred populations and the tree structure preserves the genetic relationships among them. The clustering performance and the robustness of the proposed algorithm are tested extensively using simulated and real data sets from bovine, sheep, and human populations. The result indicates that the number of populations within each data set is reasonably estimated, the individual assignment is robust, and the structure of the inferred population tree corresponds to the intrinsic relationships among populations within the data.

Identify High-Quality Protein Structural Models by Enhanced K-Means.

PubMed

Wu, Hongjie; Li, Haiou; Jiang, Min; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K -means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K -means clustering ( SK -means), whereas the other employs squared distance to optimize the initial centroids ( K -means++). Our results showed that SK -means and K -means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K -means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK -means and K -means++ demonstrated substantial improvements relative to results from SPICKER and classical K -means.

Identify High-Quality Protein Structural Models by Enhanced K-Means

PubMed Central

Li, Haiou; Chen, Cheng; Lv, Qiang; Wu, Chuang

2017-01-01

Background. One critical issue in protein three-dimensional structure prediction using either ab initio or comparative modeling involves identification of high-quality protein structural models from generated decoys. Currently, clustering algorithms are widely used to identify near-native models; however, their performance is dependent upon different conformational decoys, and, for some algorithms, the accuracy declines when the decoy population increases. Results. Here, we proposed two enhanced K-means clustering algorithms capable of robustly identifying high-quality protein structural models. The first one employs the clustering algorithm SPICKER to determine the initial centroids for basic K-means clustering (SK-means), whereas the other employs squared distance to optimize the initial centroids (K-means++). Our results showed that SK-means and K-means++ were more robust as compared with SPICKER alone, detecting 33 (59%) and 42 (75%) of 56 targets, respectively, with template modeling scores better than or equal to those of SPICKER. Conclusions. We observed that the classic K-means algorithm showed a similar performance to that of SPICKER, which is a widely used algorithm for protein-structure identification. Both SK-means and K-means++ demonstrated substantial improvements relative to results from SPICKER and classical K-means. PMID:28421198

The genetic epidemiology of personality disorders

PubMed Central

Reichborn-Kjennerud, Ted

2010-01-01

Genetic epidemiologic studies indicate that all ten personality disorders (PDs) classified on the DSM-IV axis II are modestly to moderately heritable. Shared environmental and nonadditive genetic factors are of minor or no importance. No sex differences have been identified. Multivariate studies suggest that the extensive comorbidity between the PDs can be explained by three common genetic and environmental risk factors. The genetic factors do not reflect the DSM-IV cluster structure, but rather: i) broad vulnerability to PD pathology or negative emotionality; ii) high impulsivity/low agreeableness; and iii) introversion. Common genetic and environmental liability factors contribute to comorbidity between pairs or clusters of axis I and axis II disorders. Molecular genetic studies of PDs, mostly candidate gene association studies, indicate that genes linked to neurotransmitter pathways, especially in the serotonergic and dopaminergic systems, are involved. Future studies, using newer methods like genome-wide association, might take advantage of the use of endophenotypes. PMID:20373672

A Comparison of the Familiality of Chronic Depression in Recurrent Early-onset Depression Pedigrees Using Different Definitions of Chronicity

PubMed Central

Mondimore, Francis M.; Zandi, Peter P.; MacKinnon, Dean F.; McInnis, Melvin G.; Miller, Erin B.; Schweizer, Barbara; Crowe, Raymond P.; Scheftner, William A.; Weissman, Myrna M.; Levinson, Douglas F.; DePaulo, J. Raymond; Potash, James B.

2007-01-01

Background The study of chronicity in the course of major depression has been complicated by varying definitions of this illness feature. Because familial clustering is one component of diagnostic validity we compared family clustering of chronicity as defined in the DSM-IV to that of chronicity determined by an assessment of lifetime course of depressive illness. Methods In 1750 affected subjects from 652 families recruited for a genetic study of recurrent, early-onset depression, we applied several definitions of chronicity. Odds ratios were determined for the likelihood of chronicity in a proband predicting chronicity in an affected relative. Results There was greater family clustering of chronicity as determined by assessment of lifetime course (OR=2.54) than by DSM–IV defined chronic major depressive episode (MDE) (OR=1.93) or dysthymic disorder (OR = 1.76). In families with probands who had preadolescent onset of MDD, familiality was increased by all definitions, with a much larger increase observed for chronicity by lifetime course (ORs were 6.14 for lifetime chronicity, 2.43 for chronic MDE, and 3.42 for comorbid dysthymic disorder), Agreement between these definitions of chronicity was only fair. Limitations The data used to determine chronicity were collected retrospectively and not blindly to relatives’ status, and assessment of lifetime course was based on global clinical impressions gathered during a semi-structured diagnostic interview. Also, it can be difficult to determine whether individuals with recurrent major depressive episodes who frequently experience long periods of low grade depressive symptoms meet the strict timing requirements of DSM–IV dysthymic disorder. Conclusions An assessment of lifetime symptom course identifies a more familial, and thus possibly a more valid, type of chronic depression than the current DSM-IV categories which are defined in terms of particular cross-sectional features of illness. PMID:17126912

Clustering self-organizing maps (SOM) method for human papillomavirus (HPV) DNA as the main cause of cervical cancer disease

NASA Astrophysics Data System (ADS)

Bustamam, A.; Aldila, D.; Fatimah, Arimbi, M. D.

2017-07-01

One of the most widely used clustering method, since it has advantage on its robustness, is Self-Organizing Maps (SOM) method. This paper discusses the application of SOM method on Human Papillomavirus (HPV) DNA which is the main cause of cervical cancer disease, the most dangerous cancer in developing countries. We use 18 types of HPV DNA-based on the newest complete genome. By using open-source-based program R, clustering process can separate 18 types of HPV into two different clusters. There are two types of HPV in the first cluster while 16 others in the second cluster. The analyzing result of 18 types HPV based on the malignancy of the virus (the difficultness to cure). Two of HPV types the first cluster can be classified as tame HPV, while 16 others in the second cluster are classified as vicious HPV.

Constructing the L2-Graph for Robust Subspace Learning and Subspace Clustering.

PubMed

Peng, Xi; Yu, Zhiding; Yi, Zhang; Tang, Huajin

2017-04-01

Under the framework of graph-based learning, the key to robust subspace clustering and subspace learning is to obtain a good similarity graph that eliminates the effects of errors and retains only connections between the data points from the same subspace (i.e., intrasubspace data points). Recent works achieve good performance by modeling errors into their objective functions to remove the errors from the inputs. However, these approaches face the limitations that the structure of errors should be known prior and a complex convex problem must be solved. In this paper, we present a novel method to eliminate the effects of the errors from the projection space (representation) rather than from the input space. We first prove that l 1 -, l 2 -, l ∞ -, and nuclear-norm-based linear projection spaces share the property of intrasubspace projection dominance, i.e., the coefficients over intrasubspace data points are larger than those over intersubspace data points. Based on this property, we introduce a method to construct a sparse similarity graph, called L2-graph. The subspace clustering and subspace learning algorithms are developed upon L2-graph. We conduct comprehensive experiment on subspace learning, image clustering, and motion segmentation and consider several quantitative benchmarks classification/clustering accuracy, normalized mutual information, and running time. Results show that L2-graph outperforms many state-of-the-art methods in our experiments, including L1-graph, low rank representation (LRR), and latent LRR, least square regression, sparse subspace clustering, and locally linear representation.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A formal concept analysis approach to consensus clustering of multi-experiment expression data

PubMed Central

2014-01-01

Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological signals. Conclusions The proposed FCA-enhanced consensus clustering technique is a general approach to the combination of clustering algorithms with FCA for deriving clustering solutions from multiple gene expression matrices. The experimental results presented herein demonstrate that it is a robust data integration technique able to produce good quality clustering solution that is representative for the whole set of expression matrices. PMID:24885407

Differentiation of Trichophyton rubrum clinical isolates from Japanese and Chinese patients by randomly amplified polymorphic DNA and DNA sequence analysis of the non-transcribed spacer region of the rRNA gene.

PubMed

Yang, Xiumin; Sugita, Takashi; Takashima, Masako; Hiruma, Masataro; Li, Ruoyu; Sudo, Hajime; Ogawa, Hideoki; Ikeda, Shigaku

2009-04-01

Trichophyton rubrum is the most common pathogen causing dermatophytosis worldwide. Recent genetic investigations showed that the microorganism originated in Africa and then spread to Europe and North America via Asia. We investigated the intraspecific diversity of T. rubrum isolated from two closely located Asian countries, Japan and China. A total of 150 clinical isolates of T. rubrum obtained from Japanese and Chinese patients were analyzed by randomly amplified polymorphic DNA (RAPD) and DNA sequence analysis of the non-transcribed spacer (NTS) region in the rRNA gene. RAPD analysis divided the 150 strains into two major clusters, A and B. Of the Japanese isolates, 30% belonged to cluster A and 70% belonged to cluster B, whereas 91% of the Chinese isolates were in cluster A. The NTS region of the rRNA gene was divided into four major groups (I-IV) based on DNA sequencing. The majority of Japanese isolates were type IV (51%), and the majority of Chinese isolates were type III (75%). These results suggest that although Japan and China are neighboring countries, the origins of T. rubrum isolates from these countries may not be identical. These findings provide information useful for tracing the global transmission routes of T. rubrum.

X-ray and optical substructures of the DAFT/FADA survey clusters

NASA Astrophysics Data System (ADS)

Guennou, L.; Durret, F.; Adami, C.; Lima Neto, G. B.

2013-04-01

We have undertaken the DAFT/FADA survey with the double aim of setting constraints on dark energy based on weak lensing tomography and of obtaining homogeneous and high quality data for a sample of 91 massive clusters in the redshift range 0.4-0.9 for which there were HST archive data. We have analysed the XMM-Newton data available for 42 of these clusters to derive their X-ray temperatures and luminosities and search for substructures. Out of these, a spatial analysis was possible for 30 clusters, but only 23 had deep enough X-ray data for a really robust analysis. This study was coupled with a dynamical analysis for the 26 clusters having at least 30 spectroscopic galaxy redshifts in the cluster range. Altogether, the X-ray sample of 23 clusters and the optical sample of 26 clusters have 14 clusters in common. We present preliminary results on the coupled X-ray and dynamical analyses of these 14 clusters.

Intravenous levetiracetam vs phenytoin for status epilepticus and cluster seizures: A prospective, randomized study.

PubMed

Gujjar, Arunodaya R; Nandhagopal, Ramachandiran; Jacob, Poovathoor C; Al-Hashim, Abdulhakeem; Al-Amrani, Khalfan; Ganguly, Shyam S; Al-Asmi, Abdullah

2017-07-01

Status Epilepticus (SE) is a common medical emergency carrying a high morbidity and mortality. Levetiracetam (LEV) is a novel anticonvulsant effective against varied seizures. Few prospective studies have addressed its use in SE. We aimed to examine the efficacy of intravenous LEV in controlling SE and cluster attacks of seizures (CS), in comparison with IV phenytoin (DPH), using a prospective, randomized study design. Adult patients with SE or CS, following an initial dose of IV benzodiazepine to control ongoing seizure, were randomized to receive either medication. Rates of seizure control over 24h, adverse effects and outcomes were compared. A logistic regression model was used to identify outcome predictors. 52 patients with SE and 63 with CS received either LEV or DPH. In the SE group, LEV was effective in18/22(82%) and DPH in 22/30(73.3%) patients in controlling seizures. Among patients with CS, LEV was effective in 31/38(81.6%) and DPH in 20/25(80%). With the use of LEV, DPH or both, SE and CS were controlled among 92% and 96% of patients respectively. Adverse events included hypotension (in 2 on DPH) and transient agitation (2 on LEV). IV Levetiracetam controls status epilepticus or cluster seizures with an efficacy comparable to that of phenytoin. Use of these two agents consecutively may control >90% of all such conditions without resort to anaesthetic agents. Further studies should explore its efficacy in larger cohorts of epileptic emergencies. Copyright © 2017 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Synthesis, Magnetism, and X-ray Molecular Structure of the Mixed-Valence Vanadium(IV/V)-Oxygen Cluster [VO(4) subset(V(18)O(45))](9-).

PubMed

Suber, Lorenza; Bonamico, Mario; Fares, Vincenzo

1997-05-07

Within the transition metal oxide systems, vanadium presents a unique chemistry due to its capacity to form a great number of mixed-valence oxo clusters which often have the peculiarity to incorporate species that function, for size, shape, and charge, as templates. Prismatic, lustrous dark brown crystals of [(n-C(4)H(9))NH(3)](9)[V(19)O(49)].7H(2)O are obtained by reacting (n-C(4)H(9)NH(3))VO(3), VOSO(4), and (n-C(4)H(9))NH(2) in H(2)O. The X-ray crystal structure shows an ellipsoidal metal-oxo cluster formed by 15 VO(5) and 3 VO(4) polyhedra surrounding an almost regular VO(4) tetrahedron located on the 3-fold axis of a trigonal cell of dimensions a = 19.113(5) Å and c = 13.743(5) Å with space group P&thremacr; and Z = 2. Exponentially weighted bond valence sum calculations, manganometric titration of the V(IV) centers, and magnetic measurements are consistent with the presence of three localized and three delocalized electrons. Variable-temperature solid-state susceptibility studies indicate antiferromagnetic coupling between V(IV) centers. Cyclic voltammetry in acetonitrile shows a irreversible reduction at -1.24 V and a reversible oxidation at +0.17 V (vs Ag/AgCl). The title compound converts quantitatively to the metal oxide K(2)V(3)O(8) with an extended layered structure as soon as a potassium salt is added to a neutral aqueous solution of the polyoxoanion.

Block clustering based on difference of convex functions (DC) programming and DC algorithms.

PubMed

Le, Hoai Minh; Le Thi, Hoai An; Dinh, Tao Pham; Huynh, Van Ngai

2013-10-01

We investigate difference of convex functions (DC) programming and the DC algorithm (DCA) to solve the block clustering problem in the continuous framework, which traditionally requires solving a hard combinatorial optimization problem. DC reformulation techniques and exact penalty in DC programming are developed to build an appropriate equivalent DC program of the block clustering problem. They lead to an elegant and explicit DCA scheme for the resulting DC program. Computational experiments show the robustness and efficiency of the proposed algorithm and its superiority over standard algorithms such as two-mode K-means, two-mode fuzzy clustering, and block classification EM.

Zodiacal Exoplanets in Time (ZEIT). VI. A Three-planet System in the Hyades Cluster Including an Earth-sized Planet

NASA Astrophysics Data System (ADS)

Mann, Andrew W.; Vanderburg, Andrew; Rizzuto, Aaron C.; Kraus, Adam L.; Berlind, Perry; Bieryla, Allyson; Calkins, Michael L.; Esquerdo, Gilbert A.; Latham, David W.; Mace, Gregory N.; Morris, Nathan R.; Quinn, Samuel N.; Sokal, Kimberly R.; Stefanik, Robert P.

2018-01-01

Planets in young clusters are powerful probes of the evolution of planetary systems. Here we report the discovery of three planets transiting EPIC 247589423, a late-K dwarf in the Hyades (≃800 Myr) cluster, and robust detection limits for additional planets in the system. The planets were identified from their K2 light curves as part of our survey of young clusters and star-forming regions. The smallest planet has a radius comparable to Earth ({0.99}-0.04+0.06{R}\\oplus ), making it one of the few Earth-sized planets with a known, young age. The two larger planets are likely a mini-Neptune and a super-Earth, with radii of {2.91}-0.10+0.11{R}\\oplus and {1.45}-0.08+0.11{R}\\oplus , respectively. The predicted radial velocity signals from these planets are between 0.4 and 2 m s-1, achievable with modern precision RV spectrographs. Because the target star is bright (V = 11.2) and has relatively low-amplitude stellar variability for a young star (2-6 mmag), EPIC 247589423 hosts the best known planets in a young open cluster for precise radial velocity follow-up, enabling a robust test of earlier claims that young planets are less dense than their older counterparts.

Atomically manufactured nickel–silicon quantum dots displaying robust resonant tunneling and negative differential resistance

DOE PAGES

Cheng, Jian -Yih; Fisher, Brandon L.; Guisinger, Nathan P.; ...

2017-05-22

Providing a spin-free host material in the development of quantum information technology has made silicon a very interesting and desirable material for qubit design. Much of the work and experimental progress has focused on isolated phosphorous atoms. In this article, we report on the exploration of Ni–Si clusters that are atomically manufactured via self-assembly from the bottom-up and behave as isolated quantum dots. These small quantum dot structures are probed at the atomic-scale with scanning tunneling microscopy and spectroscopy, revealing robust resonance through discrete quantized energy levels within the Ni–Si clusters. The resonance energy is reproducible and the peak spacingmore » of the quantum dot structures increases as the number of atoms in the cluster decrease. Probing these quantum dot structures on degenerately doped silicon results in the observation of negative differential resistance in both I–V and dI/dV spectra. At higher surface coverage of nickel, a well-known √19 surface modification is observed and is essentially a tightly packed array of the clusters. Spatial conductance maps reveal variations in the local density of states that suggest the clusters are influencing the electronic properties of their neighbors. Furthermore, all of these results are extremely encouraging towards the utilization of metal modified silicon surfaces to advance or complement existing quantum information technology.« less

Atomically manufactured nickel–silicon quantum dots displaying robust resonant tunneling and negative differential resistance

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

Cheng, Jian -Yih; Fisher, Brandon L.; Guisinger, Nathan P.

Providing a spin-free host material in the development of quantum information technology has made silicon a very interesting and desirable material for qubit design. Much of the work and experimental progress has focused on isolated phosphorous atoms. In this article, we report on the exploration of Ni–Si clusters that are atomically manufactured via self-assembly from the bottom-up and behave as isolated quantum dots. These small quantum dot structures are probed at the atomic-scale with scanning tunneling microscopy and spectroscopy, revealing robust resonance through discrete quantized energy levels within the Ni–Si clusters. The resonance energy is reproducible and the peak spacingmore » of the quantum dot structures increases as the number of atoms in the cluster decrease. Probing these quantum dot structures on degenerately doped silicon results in the observation of negative differential resistance in both I–V and dI/dV spectra. At higher surface coverage of nickel, a well-known √19 surface modification is observed and is essentially a tightly packed array of the clusters. Spatial conductance maps reveal variations in the local density of states that suggest the clusters are influencing the electronic properties of their neighbors. Furthermore, all of these results are extremely encouraging towards the utilization of metal modified silicon surfaces to advance or complement existing quantum information technology.« less

New Genotypes of Enterocytozoon bieneusi Isolated from Sika Deer and Red Deer in China.

PubMed

Huang, Jianying; Zhang, Zhenjie; Yang, Yong; Wang, Rongjun; Zhao, Jinfeng; Jian, Fuchun; Ning, Changshen; Zhang, Longxian

2017-01-01

To examine the occurrence and genotype distribution of Enterocytozoon bieneusi in cervids, 615 fecal samples were collected from red deer ( Cervus elaphus ) and sika deer ( Cervus nippon ) on 10 different farms in Henan and Jilin Province. Enterocytozoon bieneusi was identified and genotyped with a nested PCR analysis of the internal transcribed spacer (ITS) region of the rRNA genes, showing an average infection rate of 35.9% (221/615). In this study, 25 ITS genotypes were identified including seven known genotypes (BEB6, EbpC, EbpA, D, HLJDI, HLJD-IV, and COS-I) and 18 novel genotypes (designated JLD-I to JLD-XIV, HND-I to HND-IV). Among these, BEB6 (131/221, 59.3%) was the predominant genotype ( P < 0.01), followed by HLJDI (18/221, 8.1%) and JLD-VIII (16/221, 7.2%). BEB6 has recently been detected in humans and nonhuman primates in China. The phylogenetic analysis showed that BEB6, HLJDI, HLJD-IV, COS-I, and 10 novel genotypes (JLD-VII to JLD-XIV, HND-III to HND-IV) clustered in group 2. Genotype D, EbpC, and EbpA, known to cause human microsporidiosis worldwide, clustered in group 1, the members of which have zoonotic potential, together with eight novel genotypes (JLD-I to JLD-VI, HND-I to HND-II). Therefore, deer may play a role in the transmission of E. bieneusi to humans.

Gene Expression Analysis Reveals New Possible Mechanisms of Vancomycin-Induced Nephrotoxicity and Identifies Gene Markers Candidates

PubMed Central

Dieterich, Christine; Puey, Angela; Lyn, Sylvia; Swezey, Robert; Furimsky, Anna; Fairchild, David; Mirsalis, Jon C.; Ng, Hanna H.

2009-01-01

Vancomycin, one of few effective treatments against methicillin-resistant Staphylococcus aureus, is nephrotoxic. The goals of this study were to (1) gain insights into molecular mechanisms of nephrotoxicity at the genomic level, (2) evaluate gene markers of vancomycin-induced kidney injury, and (3) compare gene expression responses after iv and ip administration. Groups of six female BALB/c mice were treated with seven daily iv or ip doses of vancomycin (50, 200, and 400 mg/kg) or saline, and sacrificed on day 8. Clinical chemistry and histopathology demonstrated kidney injury at 400 mg/kg only. Hierarchical clustering analysis revealed that kidney gene expression profiles of all mice treated at 400 mg/kg clustered with those of mice administered 200 mg/kg iv. Transcriptional profiling might thus be more sensitive than current clinical markers for detecting kidney damage, though the profiles can differ with the route of administration. Analysis of transcripts whose expression was changed by at least twofold compared with vehicle saline after high iv and ip doses of vancomycin suggested the possibility of oxidative stress and mitochondrial damage in vancomycin-induced toxicity. In addition, our data showed changes in expression of several transcripts from the complement and inflammatory pathways. Such expression changes were confirmed by relative real-time reverse transcription–polymerase chain reaction. Finally, our results further substantiate the use of gene markers of kidney toxicity such as KIM-1/Havcr1, as indicators of renal injury. PMID:18930951

Gene expression analysis reveals new possible mechanisms of vancomycin-induced nephrotoxicity and identifies gene markers candidates.

PubMed

Dieterich, Christine; Puey, Angela; Lin, Sylvia; Lyn, Sylvia; Swezey, Robert; Furimsky, Anna; Fairchild, David; Mirsalis, Jon C; Ng, Hanna H

2009-01-01

Vancomycin, one of few effective treatments against methicillin-resistant Staphylococcus aureus, is nephrotoxic. The goals of this study were to (1) gain insights into molecular mechanisms of nephrotoxicity at the genomic level, (2) evaluate gene markers of vancomycin-induced kidney injury, and (3) compare gene expression responses after iv and ip administration. Groups of six female BALB/c mice were treated with seven daily iv or ip doses of vancomycin (50, 200, and 400 mg/kg) or saline, and sacrificed on day 8. Clinical chemistry and histopathology demonstrated kidney injury at 400 mg/kg only. Hierarchical clustering analysis revealed that kidney gene expression profiles of all mice treated at 400 mg/kg clustered with those of mice administered 200 mg/kg iv. Transcriptional profiling might thus be more sensitive than current clinical markers for detecting kidney damage, though the profiles can differ with the route of administration. Analysis of transcripts whose expression was changed by at least twofold compared with vehicle saline after high iv and ip doses of vancomycin suggested the possibility of oxidative stress and mitochondrial damage in vancomycin-induced toxicity. In addition, our data showed changes in expression of several transcripts from the complement and inflammatory pathways. Such expression changes were confirmed by relative real-time reverse transcription-polymerase chain reaction. Finally, our results further substantiate the use of gene markers of kidney toxicity such as KIM-1/Havcr1, as indicators of renal injury.

The threshold for stellar winds in hot main-sequence stars

NASA Technical Reports Server (NTRS)

Grigsby, James A.; Morrison, Nancy D.

1995-01-01

The profiles of ultraviolet resonance lines of C IV were surveyed in a sample of 29 cluster and association members in the spectral type range O9-B2 III-V, together with a few field stars of interest. The temperatures and gravities of the stars were taken from the model atmosphere analysis by Grigsby, Morrison, & Anderson (1992), and the luminosities were estimated on the basis of cluster and association distances from the recent literature. A parameter P(sub w) was defined in order to describe the degree and assymetry of the C IV profile. This parameter, together with total C IV equivalent width, was found to be well correlated with stellar luminosity and temperature. A few anomalous stars were noted: tau Sco, HD 66665, HD 13621, and the ON stars HD12323 and HD 201345. The results suggest a sudden onset of observable mass loss at T(effective) = 27,500 +/- 500 K, log (L/solar luminosity) = 4.4 +/- 0.12, in agreement with the previous study by Prinja (1989). At T(effective) = 28,000 K and log g = 4, our non-LTE model atmospheres show an enhancement in the ground-state population of C(+3) in their topmost layer, which could be responsible for initiation of the winds via radiation pressure on the C(+3) ions, or for the onset of visibility of C(+3) ions in the wind because of an increase in the optical depth in the C IV lines in the outermost layers.

Requiring both avoidance and emotional numbing in DSM-V PTSD: will it help?

PubMed

Forbes, David; Fletcher, Susan; Lockwood, Emma; O'Donnell, Meaghan; Creamer, Mark; Bryant, Richard A; McFarlane, Alexander; Silove, Derrick

2011-05-01

The proposed DSM-V criteria for posttraumatic stress disorder (PTSD) specifically require both active avoidance and emotional numbing symptoms for a diagnosis. In DSM-IV, since both are included in the same cluster, active avoidance is not essential. Numbing symptoms overlap with depression, which may result in spurious comorbidity or overdiagnosis of PTSD. This paper investigated the impact of requiring both active avoidance and emotional numbing on the rates of PTSD diagnosis and comorbidity with depression. We investigated PTSD and depression in 835 traumatic injury survivors at 3 and 12 months post-injury. We used the DSM-IV criteria but explored the potential impact of DSM-IV and DSM-V approaches to avoidance and numbing using comparison of proportion analyses. The DSM-V requirement of both active avoidance and emotional numbing resulted in significant reductions in PTSD caseness compared with DSM-IV of 22% and 26% respectively at 3 and 12 months posttrauma. By 12 months, the rates of comorbid PTSD in those with depression were significantly lower (44% vs. 34%) using the new criteria, primarily due to the lack of avoidance symptoms. These preliminary data suggest that requiring both active avoidance and numbing as separate clusters offers a useful refinement of the PTSD diagnosis. Requiring active avoidance may help to define the unique aspects of PTSD and reduce spurious diagnoses of PTSD in those with depression. Copyright © 2010. Published by Elsevier B.V.

Digital image modification detection using color information and its histograms.

PubMed

Zhou, Haoyu; Shen, Yue; Zhu, Xinghui; Liu, Bo; Fu, Zigang; Fan, Na

2016-09-01

The rapid development of many open source and commercial image editing software makes the authenticity of the digital images questionable. Copy-move forgery is one of the most widely used tampering techniques to create desirable objects or conceal undesirable objects in a scene. Existing techniques reported in the literature to detect such tampering aim to improve the robustness of these methods against the use of JPEG compression, blurring, noise, or other types of post processing operations. These post processing operations are frequently used with the intention to conceal tampering and reduce tampering clues. A robust method based on the color moments and other five image descriptors is proposed in this paper. The method divides the image into fixed size overlapping blocks. Clustering operation divides entire search space into smaller pieces with similar color distribution. Blocks from the tampered regions will reside within the same cluster since both copied and moved regions have similar color distributions. Five image descriptors are used to extract block features, which makes the method more robust to post processing operations. An ensemble of deep compositional pattern-producing neural networks are trained with these extracted features. Similarity among feature vectors in clusters indicates possible forged regions. Experimental results show that the proposed method can detect copy-move forgery even if an image was distorted by gamma correction, addictive white Gaussian noise, JPEG compression, or blurring. Copyright © 2016. Published by Elsevier Ireland Ltd.

MOCCA-SURVEY Database I: Is NGC 6535 a dark star cluster harbouring an IMBH?

NASA Astrophysics Data System (ADS)

Askar, Abbas; Bianchini, Paolo; de Vita, Ruggero; Giersz, Mirek; Hypki, Arkadiusz; Kamann, Sebastian

2017-01-01

We describe the dynamical evolution of a unique type of dark star cluster model in which the majority of the cluster mass at Hubble time is dominated by an intermediate-mass black hole (IMBH). We analysed results from about 2000 star cluster models (Survey Database I) simulated using the Monte Carlo code MOnte Carlo Cluster simulAtor and identified these dark star cluster models. Taking one of these models, we apply the method of simulating realistic `mock observations' by utilizing the Cluster simulatiOn Comparison with ObservAtions (COCOA) and Simulating Stellar Cluster Observation (SISCO) codes to obtain the photometric and kinematic observational properties of the dark star cluster model at 12 Gyr. We find that the perplexing Galactic globular cluster NGC 6535 closely matches the observational photometric and kinematic properties of the dark star cluster model presented in this paper. Based on our analysis and currently observed properties of NGC 6535, we suggest that this globular cluster could potentially harbour an IMBH. If it exists, the presence of this IMBH can be detected robustly with proposed kinematic observations of NGC 6535.

Phylogeography of Australia's king brown snake (Pseudechis australis) reveals Pliocene divergence and Pleistocene dispersal of a top predator.

PubMed

Kuch, Ulrich; Keogh, J Scott; Weigel, John; Smith, Laurie A; Mebs, Dietrich

2005-03-01

King brown snakes or mulga snakes (Pseudechis australis) are the largest and among the most dangerous and wide-ranging venomous snakes in Australia and New Guinea. They occur in diverse habitats, are important predators, and exhibit considerable morphological variation. We infer the relationships and historical biogeography of P. australis based on phylogenetic analysis of 1,249 base pairs from the mitochondrial cytochrome b, NADH dehydrogenase subunit 4 and three adjacent tRNA genes using Bayesian, maximum-likelihood, and maximum-parsimony methods. All methods reveal deep phylogenetic structure with four strongly supported clades comprising snakes from New Guinea (I), localities all over Australia (II), the Kimberleys of Western Australia (III), and north-central Australia (IV), suggesting a much more ancient radiation than previously believed. This conclusion is robust to different molecular clock estimations indicating divergence in Pliocene or Late Miocene, after landbridge dispersal to New Guinea had occurred. While members of clades I, III and IV are medium-sized, slender snakes, those of clade II attain large sizes and a robust build, rendering them top predators in their ecosystems. Genetic differentiation within clade II is low and haplotype distribution largely incongruent with geography or colour morphs, suggesting Pleistocene dispersal and recent ecomorph evolution. Significant haplotype diversity exists in clades III and IV, implying that clade IV comprises two species. Members of clade II are broadly sympatric with members of both northern Australian clades. Thus, our data support the recognition of at least five species from within P. australis (auct.) under various criteria. We discuss biogeographical, ecological and medical implications of our findings.

Phylogeography of Australia's king brown snake (Pseudechis australis) reveals Pliocene divergence and Pleistocene dispersal of a top predator

NASA Astrophysics Data System (ADS)

Kuch, Ulrich; Keogh, J. Scott; Weigel, John; Smith, Laurie A.; Mebs, Dietrich

2005-03-01

King brown snakes or mulga snakes (Pseudechis australis) are the largest and among the most dangerous and wide-ranging venomous snakes in Australia and New Guinea. They occur in diverse habitats, are important predators, and exhibit considerable morphological variation. We infer the relationships and historical biogeography of P. australis based on phylogenetic analysis of 1,249 base pairs from the mitochondrial cytochrome b, NADH dehydrogenase subunit 4 and three adjacent tRNA genes using Bayesian, maximum-likelihood, and maximum-parsimony methods. All methods reveal deep phylogenetic structure with four strongly supported clades comprising snakes from New Guinea (I), localities all over Australia (II), the Kimberleys of Western Australia (III), and north-central Australia (IV), suggesting a much more ancient radiation than previously believed. This conclusion is robust to different molecular clock estimations indicating divergence in Pliocene or Late Miocene, after landbridge dispersal to New Guinea had occurred. While members of clades I, III and IV are medium-sized, slender snakes, those of clade II attain large sizes and a robust build, rendering them top predators in their ecosystems. Genetic differentiation within clade II is low and haplotype distribution largely incongruent with geography or colour morphs, suggesting Pleistocene dispersal and recent ecomorph evolution. Significant haplotype diversity exists in clades III and IV, implying that clade IV comprises two species. Members of clade II are broadly sympatric with members of both northern Australian clades. Thus, our data support the recognition of at least five species from within P. australis (auct.) under various criteria. We discuss biogeographical, ecological and medical implications of our findings.

Modeling of correlated data with informative cluster sizes: An evaluation of joint modeling and within-cluster resampling approaches.

PubMed

Zhang, Bo; Liu, Wei; Zhang, Zhiwei; Qu, Yanping; Chen, Zhen; Albert, Paul S

2017-08-01

Joint modeling and within-cluster resampling are two approaches that are used for analyzing correlated data with informative cluster sizes. Motivated by a developmental toxicity study, we examined the performances and validity of these two approaches in testing covariate effects in generalized linear mixed-effects models. We show that the joint modeling approach is robust to the misspecification of cluster size models in terms of Type I and Type II errors when the corresponding covariates are not included in the random effects structure; otherwise, statistical tests may be affected. We also evaluate the performance of the within-cluster resampling procedure and thoroughly investigate the validity of it in modeling correlated data with informative cluster sizes. We show that within-cluster resampling is a valid alternative to joint modeling for cluster-specific covariates, but it is invalid for time-dependent covariates. The two methods are applied to a developmental toxicity study that investigated the effect of exposure to diethylene glycol dimethyl ether.

Proteus mirabilis fimbriae- and urease-dependent clusters assemble in an extracellular niche to initiate bladder stone formation.

PubMed

Schaffer, Jessica N; Norsworthy, Allison N; Sun, Tung-Tien; Pearson, Melanie M

2016-04-19

The catheter-associated uropathogenProteus mirabilisfrequently causes urinary stones, but little has been known about the initial stages of bladder colonization and stone formation. We found thatP. mirabilisrapidly invades the bladder urothelium, but generally fails to establish an intracellular niche. Instead, it forms extracellular clusters in the bladder lumen, which form foci of mineral deposition consistent with development of urinary stones. These clusters elicit a robust neutrophil response, and we present evidence of neutrophil extracellular trap generation during experimental urinary tract infection. We identified two virulence factors required for cluster development: urease, which is required for urolithiasis, and mannose-resistantProteus-like fimbriae. The extracellular cluster formation byP. mirabilisstands in direct contrast to uropathogenicEscherichia coli, which readily formed intracellular bacterial communities but not luminal clusters or urinary stones. We propose that extracellular clusters are a key mechanism ofP. mirabilissurvival and virulence in the bladder.

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

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

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

A robust multilevel simultaneous eigenvalue solver

NASA Technical Reports Server (NTRS)

Costiner, Sorin; Taasan, Shlomo

1993-01-01

Multilevel (ML) algorithms for eigenvalue problems are often faced with several types of difficulties such as: the mixing of approximated eigenvectors by the solution process, the approximation of incomplete clusters of eigenvectors, the poor representation of solution on coarse levels, and the existence of close or equal eigenvalues. Algorithms that do not treat appropriately these difficulties usually fail, or their performance degrades when facing them. These issues motivated the development of a robust adaptive ML algorithm which treats these difficulties, for the calculation of a few eigenvectors and their corresponding eigenvalues. The main techniques used in the new algorithm include: the adaptive completion and separation of the relevant clusters on different levels, the simultaneous treatment of solutions within each cluster, and the robustness tests which monitor the algorithm's efficiency and convergence. The eigenvectors' separation efficiency is based on a new ML projection technique generalizing the Rayleigh Ritz projection, combined with a technique, the backrotations. These separation techniques, when combined with an FMG formulation, in many cases lead to algorithms of O(qN) complexity, for q eigenvectors of size N on the finest level. Previously developed ML algorithms are less focused on the mentioned difficulties. Moreover, algorithms which employ fine level separation techniques are of O(q(sub 2)N) complexity and usually do not overcome all these difficulties. Computational examples are presented where Schrodinger type eigenvalue problems in 2-D and 3-D, having equal and closely clustered eigenvalues, are solved with the efficiency of the Poisson multigrid solver. A second order approximation is obtained in O(qN) work, where the total computational work is equivalent to only a few fine level relaxations per eigenvector.

Temporal Order in Periodically Driven Spins in Star-Shaped Clusters

NASA Astrophysics Data System (ADS)

Pal, Soham; Nishad, Naveen; Mahesh, T. S.; Sreejith, G. J.

2018-05-01

We experimentally study the response of star-shaped clusters of initially unentangled N =4 , 10, and 37 nuclear spin-1 /2 moments to an inexact π -pulse sequence and show that an Ising coupling between the center and the satellite spins results in robust period-2 magnetization oscillations. The period is stable against bath effects, but the amplitude decays with a timescale that depends on the inexactness of the pulse. Simulations reveal a semiclassical picture in which the rigidity of the period is due to a randomizing effect of the Larmor precession under the magnetization of surrounding spins. The timescales with stable periodicity increase with net initial magnetization, even in the presence of perturbations, indicating a robust temporal ordered phase for large systems with finite magnetization per spin.

IVS Tropospheric Parameters: Comparison with DORIS and GPS for CONT02

NASA Technical Reports Server (NTRS)

Schuh, Harald; Snajdrova, Kristyna; Boehm, Johannes; Willis, Pascal; Engelhardt, Gerald; Lanotte, Roberto; Tomasi, Paolo; Negusini, Monia; MacMillan, Daniel; Vereshchagina, Iraida

2004-01-01

In April 2002 the IVS (International VLBI Service for Geodesy and Astrometry) set up the Pilot Project - Tropospheric Parameters, and the Institute of Geodesy and Geophysics (IGG), Vienna, was put in charge of coordinating the project. Seven IVS Analysis Centers have joined the project and regularly submitted their estimates of tropospheric parameters (wet and total zenith delays, horizontal gradients) for all IVS-R1 mid IVS-R4 sessions since January 1st, 2002. The individual submissions are combined by a two-step procedure to obtain stable, robust and highly accurate tropospheric parameter time series with one hour resolution (internal accuracy: 2-4 ram). Starting with July 2003, the combined tropospheric estimates became operational IVS products. In the second half of October 2002 the VLBI campaign CONT02 was observed with 8 stations participating around the globe. At four of them (Gilmore Creek, U.S.A.; Hartebeesthoek, South Africa; Kokee Park, U.S.A.; Ny-Alesund, Norway) also total zenith delays from DORIS (Doppler Orbitography and Radiopositioning Integrated by Satellite) are available and these estimates are compared with those from the IGS (International GPS Service) and the IVS. The distance from the DORIS beacons to the co-located GPS and VLBI stations is around 2 km or less for the four sites mentioned above.

The Open Cluster Chemical Abundances and Mapping (OCCAM) Survey: Current Status

NASA Astrophysics Data System (ADS)

Frinchaboy, Peter; O'Connell, Julia; Donor, John; Cunha, Katia; Thompson, Benjamin; Melendez, Matthew; Shetrone, Matthew; Zasowski, Gail; Majewski, Steven R.; APOGEE TEAM

2018-01-01

The Open Cluster Chemical Analysis and Mapping (OCCAM) survey aims to produce a comprehensive, uniform, infrared-based data set forhundreds of open clusters, and constrain key Galactic dynamical and chemical parameters using the SDSS/APOGEE survey and follow-up from the McDonald Observatory Otto Struve 2.1-m telescope and Sandiford Cass Echelle Spectrograph (R ~ 60,000). We report on multi-element radial abundance gradients obtained from a sample of over 30 disk open clusters. The APOGEE chemical abundances were derived automatically by the ASPCAP pipeline and these are part of the SDSS IV Data Release 14, optical follow-up were analyzed using equivalent width analysis and spectral synthesis. We present the current open cluster sample that spans a significant range in age allowing exploration of the evolution of the Galactic abundance gradients. This work is supported by an NSF AAG grants AST-1311835 & AST-1715662.

On the enhancement of magnetic anisotropy in cobalt clusters via non-magnetic doping.

PubMed

Islam, M Fhokrul; Khanna, Shiv N

2014-03-26

We show that the magnetic anisotropy energy (MAE) in cobalt clusters can be significantly enhanced by doping them with group IV elements. Our first-principles electronic structure calculations show that Co4C2 and Co12C4 clusters have MAEs of 25 K and 61 K, respectively. The large MAE is due to controlled mixing between Co d- and C p-states and can be further tuned by replacing C by Si. Larger assemblies of such primitive units are shown to be stable with MAEs exceeding 100 K in units as small as 1.2 nm, in agreement with the recent observation of large coercivity. These results may pave the way for the use of nano-clusters in high density magnetic memory devices for spintronics applications.

An outbreak of post-partum breast abscesses in Mumbai, India caused by ST22-MRSA-IV: genetic characteristics and epidemiological implications

PubMed Central

MANOHARAN, A.; ZHANG, L.; POOJARY, A.; BHANDARKAR, L.; KOPPIKAR, G.; ROBINSON, D. A.

2012-01-01

SUMMARY A cluster of methicillin-resistant Staphylococcus aureus (MRSA) breast abscesses in women who had given birth at a hospital in Mumbai, India was investigated retrospectively. Nineteen of twenty cases were caused by a single clone: pvl-positive, spa type 648 (Ridom t852), ccrB:dru subtype 3:0, ST22-MRSA-IV. Despite the presence of pvl and SCCmec type IV, which are common genetic markers among community-associated MRSA, this outbreak was caused by a healthcare-associated, community-onset MRSA that was common in the hospital environment. Thus, infection control practices may have an important role in limiting the spread of this virulent clone. PMID:22475374

Inter-rater agreement of comorbid DSM-IV personality disorders in substance abusers.

PubMed

Hesse, Morten; Thylstrup, Birgitte

2008-05-17

Little is known about the inter-rater agreement of personality disorders in clinical settings. Clinicians rated 75 patients with substance use disorders on the DSM-IV criteria of personality disorders in random order, and on rating scales representing the severity of each. Convergent validity agreement was moderate (range for r = 0.55, 0.67) for cluster B disorders rated with DSM-IV criteria, and discriminant validity was moderate for eight of the ten personality disorders. Convergent validity of the rating scales was only moderate for antisocial and narcissistic personality disorder. Dimensional ratings may be used in research studies and clinical practice with some caution, and may be collected as one of several sources of information to describe the personality of a patient.

Untangling Magmatic Processes and Hydrothermal Alteration of in situ Superfast Spreading Ocean Crust at ODP/IODP Site 1256 with Fuzzy c-means Cluster Analysis of Rock Magnetic Properties

NASA Astrophysics Data System (ADS)

Dekkers, M. J.; Heslop, D.; Herrero-Bervera, E.; Acton, G.; Krasa, D.

2014-12-01

Ocean Drilling Program (ODP)/Integrated ODP (IODP) Hole 1256D (6.44.1' N, 91.56.1' W) on the Cocos Plate occurs in 15.2 Ma oceanic crust generated by superfast seafloor spreading. Presently, it is the only drill hole that has sampled all three oceanic crust layers in a tectonically undisturbed setting. Here we interpret down-hole trends in several rock-magnetic parameters with fuzzy c-means cluster analysis, a multivariate statistical technique. The parameters include the magnetization ratio, the coercivity ratio, the coercive force, the low-field susceptibility, and the Curie temperature. By their combined, multivariate, analysis the effects of magmatic and hydrothermal processes can be evaluated. The optimal number of clusters - a key point in the analysis because there is no a priori information on this - was determined through a combination of approaches: by calculation of several cluster validity indices, by testing for coherent cluster distributions on non-linear-map plots, and importantly by testing for stability of the cluster solution from all possible starting points. Here, we consider a solution robust if the cluster allocation is independent of the starting configuration. The five-cluster solution appeared to be robust. Three clusters are distinguished in the extrusive segment of the Hole that express increasing hydrothermal alteration of the lavas. The sheeted dike and gabbro portions are characterized by two clusters, both with higher coercivities than in lava samples. Extensive alteration, however, can obliterate magnetic property differences between lavas, dikes, and gabbros. The imprint of thermochemical alteration on the iron-titanium oxides is only partially related to the porosity of the rocks. All clusters display rock magnetic characteristics in line with a stable NRM. This implies that the entire sampled sequence of ocean crust can contribute to marine magnetic anomalies. Determination of the absolute paleointensity with thermal techniques is not straightforward because of the propensity of oxyexsolution during laboratory heating and/or the presence of intergrowths. The upper part of the extrusive sequence, the granoblastic portion of the dikes, and moderately altered gabbros may contain a comparatively uncontaminated thermoremanent magnetization.

Genetic diversity of red-grained rice landraces in Hani's terraced fields based on phenotypic characteristics

NASA Astrophysics Data System (ADS)

Zhou, Xiaomei; Zheng, Yun; Zhang, Tingting; Zhang, Xiaoqian; Ma, Mengli; Meng, Hengling; Wang, Tiantao; Lu, Bingyue

2018-06-01

In order to provide useful information for protection and utilization of red-grained rice landraces from Hani's terraced fields, the phenotypic diversity of 61 red-grained rice landraces were assessed based 20 quantitative traits. The results indicated that the phenotypic diversity was abundant in red-grained rice landraces. Coefficients of variation (CV) ranged from 4.878% to 72.878%, and the largest of CV was the panicle neck length, while grain width was smallest. Shannon-Weaver diversity index (H') of 20 traits ranged from 1.464 to 2.165, the largest and the smallest H' values were observed in filled grain number and chalkiness, respectively. Cluster analysis based on unweighted pair group method showed 61 red-grain rice landraces grouped into eight clusters at a cut-off value of 6.2631. The first cluster included 11 landraces, the main cluster II involved 42 landraces, and the cluster IV included 3 landraces. Laopinzhonghongmi, Chena2, Laojingnuo, Bianhao6 and Baimi were separated from the main clusters.

Band Structure of the IV-VI Black Phosphorus Analog and Thermoelectric SnSe

NASA Astrophysics Data System (ADS)

Pletikosić, I.; von Rohr, F.; Pervan, P.; Das, P. K.; Vobornik, I.; Cava, R. J.; Valla, T.

2018-04-01

The success of black phosphorus in fast electronic and photonic devices is hindered by its rapid degradation in the presence of oxygen. Orthorhombic tin selenide is a representative of group IV-VI binary compounds that are robust and isoelectronic and share the same structure with black phosphorus. We measure the band structure of SnSe and find highly anisotropic valence bands that form several valleys having fast dispersion within the layers and negligible dispersion across. This is exactly the band structure desired for efficient thermoelectric generation where SnSe has shown great promise.

Band Structure of the IV-VI Black Phosphorus Analog and Thermoelectric SnSe

DOE PAGES

Pletikosic, Ivo; von Rohr, F.; Pervan, P.; ...

2018-04-10

Here, the success of black phosphorus in fast electronic and photonic devices is hindered by its rapid degradation in the presence of oxygen. Orthorhombic tin selenide is a representative of group IV-VI binary compounds that are robust and isoelectronic and share the same structure with black phosphorus. We measure the band structure of SnSe and find highly anisotropic valence bands that form several valleys having fast dispersion within the layers and negligible dispersion across. This is exactly the band structure desired for efficient thermoelectric generation where SnSe has shown great promise.

Band Structure of the IV-VI Black Phosphorus Analog and Thermoelectric SnSe

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

Pletikosic, Ivo; von Rohr, F.; Pervan, P.

Here, the success of black phosphorus in fast electronic and photonic devices is hindered by its rapid degradation in the presence of oxygen. Orthorhombic tin selenide is a representative of group IV-VI binary compounds that are robust and isoelectronic and share the same structure with black phosphorus. We measure the band structure of SnSe and find highly anisotropic valence bands that form several valleys having fast dispersion within the layers and negligible dispersion across. This is exactly the band structure desired for efficient thermoelectric generation where SnSe has shown great promise.

Does Expert Advice Improve Educational Choice?

PubMed Central

2015-01-01

This paper reports evidence that an individual meeting with a study counselor at high school significantly improves the quality of choice of tertiary educational field, as self-assessed 18 months after graduation from college. To address endogeneity, we explore the variation in study counseling practices between schools as an instrumental variable (IV). Following careful scrutiny of the validity of the IV, our results indicate a significant and positive influence of study counseling on the quality of educational choice, foremost among males and those with low educated parents. The overall result is stable across a number of robustness checks. PMID:26692388

Clustering of financial time series with application to index and enhanced index tracking portfolio

NASA Astrophysics Data System (ADS)

Dose, Christian; Cincotti, Silvano

2005-09-01

A stochastic-optimization technique based on time series cluster analysis is described for index tracking and enhanced index tracking problems. Our methodology solves the problem in two steps, i.e., by first selecting a subset of stocks and then setting the weight of each stock as a result of an optimization process (asset allocation). Present formulation takes into account constraints on the number of stocks and on the fraction of capital invested in each of them, whilst not including transaction costs. Computational results based on clustering selection are compared to those of random techniques and show the importance of clustering in noise reduction and robust forecasting applications, in particular for enhanced index tracking.

VANET Clustering Based Routing Protocol Suitable for Deserts.

PubMed

Nasr, Mohammed Mohsen Mohammed; Abdelgader, Abdeldime Mohamed Salih; Wang, Zhi-Gong; Shen, Lian-Feng

2016-04-06

In recent years, there has emerged applications of vehicular ad hoc networks (VANETs) towards security, safety, rescue, exploration, military and communication redundancy systems in non-populated areas, besides its ordinary use in urban environments as an essential part of intelligent transportation systems (ITS). This paper proposes a novel algorithm for the process of organizing a cluster structure and cluster head election (CHE) suitable for VANETs. Moreover, it presents a robust clustering-based routing protocol, which is appropriate for deserts and can achieve high communication efficiency, ensuring reliable information delivery and optimal exploitation of the equipment on each vehicle. A comprehensive simulation is conducted to evaluate the performance of the proposed CHE and routing algorithms.

VANET Clustering Based Routing Protocol Suitable for Deserts

PubMed Central

Mohammed Nasr, Mohammed Mohsen; Abdelgader, Abdeldime Mohamed Salih; Wang, Zhi-Gong; Shen, Lian-Feng

2016-01-01

In recent years, there has emerged applications of vehicular ad hoc networks (VANETs) towards security, safety, rescue, exploration, military and communication redundancy systems in non-populated areas, besides its ordinary use in urban environments as an essential part of intelligent transportation systems (ITS). This paper proposes a novel algorithm for the process of organizing a cluster structure and cluster head election (CHE) suitable for VANETs. Moreover, it presents a robust clustering-based routing protocol, which is appropriate for deserts and can achieve high communication efficiency, ensuring reliable information delivery and optimal exploitation of the equipment on each vehicle. A comprehensive simulation is conducted to evaluate the performance of the proposed CHE and routing algorithms. PMID:27058539

Evolution of the nuclear receptor superfamily: early diversification from an ancestral orphan receptor.

PubMed

Laudet, V

1997-12-01

From a database containing the published nuclear hormone receptor (NR) sequences I constructed an alignment of the C, D and E domains of these molecules. Using this alignment, I have performed tree reconstruction using both distance matrix and parsimony analysis. The robustness of each branch was estimated using bootstrap resampling methods. The trees constructed by these two methods gave congruent topologies. From these analyses I defined six NR subfamilies: (i) a large one clustering thyroid hormone receptors (TRs), retinoic acid receptors (RARs), peroxisome proliferator-activated receptors (PPARs), vitamin D receptors (VDRs) and ecdysone receptors (EcRs) as well as numerous orphan receptors such as RORs or Rev-erbs; (ii) one containing retinoid X receptors (RXRs) together with COUP, HNF4, tailless, TR2 and TR4 orphan receptors; (iii) one containing steroid receptors; (iv) one containing the NGFIB orphan receptors; (v) one containing FTZ-F1 orphan receptors; and finally (vi) one containing to date only one gene, the GCNF1 orphan receptor. The relationships between the six subfamilies are not known except for subfamilies I and IV which appear to be related. Interestingly, most of the liganded receptors appear to be derived when compared with orphan receptors. This suggests that the ligand-binding ability of NRs has been gained by orphan receptors during the course of evolution to give rise to the presently known receptors. The distribution into six subfamilies correlates with the known abilities of the various NRs to bind to DNA as homo- or heterodimers. For example, receptors heterodimerizing efficiently with RXR belong to the first or the fourth subfamilies. I suggest that the ability to heterodimerize evolved once, just before the separation of subfamilies I and IV and that the first NR was able to bind to DNA as a homodimer. From the study of NR sequences existing in vertebrates, arthropods and nematodes, I define two major steps of NR diversification: one that took place very early, probably during the multicellularization event leading to all the metazoan phyla, and a second occurring later on, corresponding to the advent of vertebrates. Finally, I show that in vertebrate species the various groups of NRs accumulated mutations at very different rates.

Improved Robustness and Efficiency for Automatic Visual Site Monitoring

DTIC Science & Technology

2009-09-01

the space of expected poses. To avoid having to compare each test window with the whole training corpus, he builds a template hierarchy by...directions of motion. In a second layer of clustering, it also learns how the low-level clusters co-occur with each other. An infinite mix- ture model is used...implementation. We demonstrate the utility of this detector by modeling scene-level activities with a Hierarchical

A system for learning statistical motion patterns.

PubMed

Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve

2006-09-01

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.

Main-Sequence O Stars in NGC 6231: Enhanced Winds

NASA Astrophysics Data System (ADS)

Morrison, Nancy D.

Three late O-type main-sequence stars in the open cluster NGC 6231 will be observed with IUE at high dispersion, and their C IV and N V resonance-line profiles will be studied. From low-dispersion IUE observations, 10 members of the cluster have been found to have anomalously strong C IV resonance lines for their spectral types. Massa, Savage, and Cassinelli (1984) observed two of these "UV peculiar" stars (spectral types B0.5 V and B1 V) at high dispersion. They found that the C IV lines have a strong, broad, shortward-shifted absorption component, which suggests a greatly enhanced wind relative to the average for the spectral type. They proposed that the enhancement is due to an overabundance of C. Recently, however, Grigsby, Gordon, Morrison, and Zimba (1992) showed from optical spectra that these stars have normal C abundances. Thus, there is not yet a convincing explanation for these strikingly anomalous stellar winds. By extending the temperature range over which the phenomenon has been studied at high dispersion, however, we expect to gain new physical information. From wind modeling of the line profiles, we will derive mass-loss rates and terminal velocities, and we will test whether these winds are described by radiation-driven wind theory.

Multi scales based sparse matrix spectral clustering image segmentation

NASA Astrophysics Data System (ADS)

Liu, Zhongmin; Chen, Zhicai; Li, Zhanming; Hu, Wenjin

2018-04-01

In image segmentation, spectral clustering algorithms have to adopt the appropriate scaling parameter to calculate the similarity matrix between the pixels, which may have a great impact on the clustering result. Moreover, when the number of data instance is large, computational complexity and memory use of the algorithm will greatly increase. To solve these two problems, we proposed a new spectral clustering image segmentation algorithm based on multi scales and sparse matrix. We devised a new feature extraction method at first, then extracted the features of image on different scales, at last, using the feature information to construct sparse similarity matrix which can improve the operation efficiency. Compared with traditional spectral clustering algorithm, image segmentation experimental results show our algorithm have better degree of accuracy and robustness.

The dysregulated cluster in personality profiling research: Longitudinal stability and associations with bulimic behaviors and correlates

PubMed Central

Slane, Jennifer D.; Klump, Kelly L.; Donnellan, M. Brent; McGue, Matthew; Iacono, William G.

2013-01-01

Among cluster analytic studies of the personality profiles associated with bulimia nervosa, a group of individuals characterized by emotional lability and behavioral dysregulation (i.e., a dysregulated cluster) has emerged most consistently. However, previous studies have all been cross-sectional and mostly used clinical samples. This study aimed to replicate associations between the dysregulated personality cluster and bulimic symptoms and related characteristics using a longitudinal, population-based sample. Participants were females assessed at ages 17 and 25 from the Minnesota Twin Family Study, clustered based on their personality traits. The Dysregulated cluster was successfully identified at both time points and was more stable across time than either the Resilient or Sensation Seeking clusters. Rates of bulimic symptoms and related behaviors (e.g., alcohol use problems) were also highest in the dysregulated group. Findings suggest that the dysregulated cluster is a relatively stable and robust profile that is associated with bulimic symptoms. PMID:23398096

STUDIES IN RESEARCH METHODOLOGY. IV. A SAMPLING STUDY OF THE CENTRAL LIMIT THEOREM AND THE ROBUSTNESS OF ONE-SAMPLE PARAMETRIC TESTS,

DTIC Science & Technology

iconoclastic . Even at N=1024 these departures were quite appreciable at the testing tails, being greatest for chi-square and least for Z, and becoming worse in all cases at increasingly extreme tail areas. (Author)

Emotional disorders: cluster 4 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Goldberg, D P; Krueger, R F; Andrews, G; Hobbs, M J

2009-12-01

The extant major psychiatric classifications DSM-IV, and ICD-10, are atheoretical and largely descriptive. Although this achieves good reliability, the validity of a medical diagnosis would be greatly enhanced by an understanding of risk factors and clinical manifestations. In an effort to group mental disorders on the basis of aetiology, five clusters have been proposed. This paper considers the validity of the fourth cluster, emotional disorders, within that proposal. We reviewed the literature in relation to 11 validating criteria proposed by a Study Group of the DSM-V Task Force, as applied to the cluster of emotional disorders. An emotional cluster of disorders identified using the 11 validators is feasible. Negative affectivity is the defining feature of the emotional cluster. Although there are differences between disorders in the remaining validating criteria, there are similarities that support the feasibility of an emotional cluster. Strong intra-cluster co-morbidity may reflect the action of common risk factors and also shared higher-order symptom dimensions in these emotional disorders. Emotional disorders meet many of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster.

Efficient Agent-Based Cluster Ensembles

NASA Technical Reports Server (NTRS)

Agogino, Adrian; Tumer, Kagan

2006-01-01

Numerous domains ranging from distributed data acquisition to knowledge reuse need to solve the cluster ensemble problem of combining multiple clusterings into a single unified clustering. Unfortunately current non-agent-based cluster combining methods do not work in a distributed environment, are not robust to corrupted clusterings and require centralized access to all original clusterings. Overcoming these issues will allow cluster ensembles to be used in fundamentally distributed and failure-prone domains such as data acquisition from satellite constellations, in addition to domains demanding confidentiality such as combining clusterings of user profiles. This paper proposes an efficient, distributed, agent-based clustering ensemble method that addresses these issues. In this approach each agent is assigned a small subset of the data and votes on which final cluster its data points should belong to. The final clustering is then evaluated by a global utility, computed in a distributed way. This clustering is also evaluated using an agent-specific utility that is shown to be easier for the agents to maximize. Results show that agents using the agent-specific utility can achieve better performance than traditional non-agent based methods and are effective even when up to 50% of the agents fail.

Requirements for efficient cell-type proportioning: regulatory timescales, stochasticity and lateral inhibition

NASA Astrophysics Data System (ADS)

Pfeuty, B.; Kaneko, K.

2016-04-01

The proper functioning of multicellular organisms requires the robust establishment of precise proportions between distinct cell types. This developmental differentiation process typically involves intracellular regulatory and stochastic mechanisms to generate cell-fate diversity as well as intercellular signaling mechanisms to coordinate cell-fate decisions at tissue level. We thus surmise that key insights about the developmental regulation of cell-type proportion can be captured by the modeling study of clustering dynamics in population of inhibitory-coupled noisy bistable systems. This general class of dynamical system is shown to exhibit a very stable two-cluster state, but also metastability, collective oscillations or noise-induced state hopping, which can prevent from timely and reliably reaching a robust and well-proportioned clustered state. To circumvent these obstacles or to avoid fine-tuning, we highlight a general strategy based on dual-time positive feedback loops, such as mediated through transcriptional versus epigenetic mechanisms, which improves proportion regulation by coordinating early and flexible lineage priming with late and firm commitment. This result sheds new light on the respective and cooperative roles of multiple regulatory feedback, stochasticity and lateral inhibition in developmental dynamics.

Large Magellanic Cloud Near-infrared Synoptic Survey. IV. Leavitt Laws for Type II Cepheid Variables

NASA Astrophysics Data System (ADS)

Bhardwaj, Anupam; Macri, Lucas M.; Rejkuba, Marina; Kanbur, Shashi M.; Ngeow, Chow-Choong; Singh, Harinder P.

2017-04-01

We present time-series observations of Population II Cepheids in the Large Magellanic Cloud at near-infrared (JHK s ) wavelengths. Our sample consists of 81 variables with accurate periods and optical (VI) magnitudes from the OGLE survey, covering various subtypes of pulsators (BL Herculis, W Virginis, and RV Tauri). We generate light-curve templates using high-quality I-band data in the LMC from OGLE and K s -band data in the Galactic bulge from VISTA Variables in Via Láctea survey and use them to obtain robust mean magnitudes. We derive period-luminosity (P-L) relations in the near-infrared and Period-Wesenheit (P-W) relations by combining optical and near-infrared data. Our P-L and P-W relations are consistent with published work when excluding long-period RV Tauris. We find that Pop II Cepheids and RR Lyraes follow the same P-L relations in the LMC. Therefore, we use trigonometric parallax from the Gaia DR1 for VY Pyx and the Hubble Space Telescope parallaxes for k Pav and 5 RR Lyrae variables to obtain an absolute calibration of the Galactic K s -band P-L relation, resulting in a distance modulus to the LMC of {μ }{LMC}=18.54+/- 0.08 mag. We update the mean magnitudes of Pop II Cepheids in Galactic globular clusters using our light-curve templates and obtain distance estimates to those systems, anchored to a precise late-type eclipsing binary distance to the LMC. We find that the distances to these globular clusters based on Pop II Cepheids are consistent (within 2σ ) with estimates based on the {M}V-[{Fe}/{{H}}] relation for horizontal branch stars.

AXIS - A High Angular Resoltuion X-ray Probe Concept Study

NASA Astrophysics Data System (ADS)

Mushotzky, Richard; AXIS Study Team

2018-01-01

AXIS is a probe-class concept under study to the 2020 Decadal survey. AXIS will extend and enhance the science of high angular resolution x-ray imaging and spectroscopy in the next decade with ~0.3" angular resolution over a 7' radius field of view and an order of magnitude more collecting area than Chandra in the 0.3-12 keV band with a cost consistent with a probe.These capabilities enable major advances in a wide range of science such as: (1) measuring the event horizon scale structure in AGN accretion disks and the spins of supermassive black holes through observations of gravitationally-microlensed quasars; (ii) determining AGN and starburst feedback in galaxies and galaxy clusters through direct imaging of winds and interaction of jets and via spatially resolved imaging of galaxies at high-z; (iii) fueling of AGN by probing the Bondi radius of over 20 nearby galaxies; (iv) hierarchical structure formation and the SMBH merger rate through measurement of the occurrence rate of dual AGN and occupation fraction of SMBHs; (v) advancing SNR physics and galaxy ecology through large detailed samples of SNR in nearby galaxies; (vi) measuring the Cosmic Web through its connection to cluster outskirts. With a nominal 2028 launch, AXIS benefits from natural synergies with the ELTs, LSST, ALMA, WFIRST and ATHENA. AXIS utilizes breakthroughs in the construction of lightweight X-ray optics from mono-crystalline silicon blocks, and developments in the fabrication of large format, small pixel, high readout rate detectors allowing a robust and cost effective design. The AXIS team welcomes input and feedback from the community in preparation for the 2020 Decadal review.

Bootstrap-based methods for estimating standard errors in Cox's regression analyses of clustered event times.

PubMed

Xiao, Yongling; Abrahamowicz, Michal

2010-03-30

We propose two bootstrap-based methods to correct the standard errors (SEs) from Cox's model for within-cluster correlation of right-censored event times. The cluster-bootstrap method resamples, with replacement, only the clusters, whereas the two-step bootstrap method resamples (i) the clusters, and (ii) individuals within each selected cluster, with replacement. In simulations, we evaluate both methods and compare them with the existing robust variance estimator and the shared gamma frailty model, which are available in statistical software packages. We simulate clustered event time data, with latent cluster-level random effects, which are ignored in the conventional Cox's model. For cluster-level covariates, both proposed bootstrap methods yield accurate SEs, and type I error rates, and acceptable coverage rates, regardless of the true random effects distribution, and avoid serious variance under-estimation by conventional Cox-based standard errors. However, the two-step bootstrap method over-estimates the variance for individual-level covariates. We also apply the proposed bootstrap methods to obtain confidence bands around flexible estimates of time-dependent effects in a real-life analysis of cluster event times.

Semisupervised Clustering by Iterative Partition and Regression with Neuroscience Applications

PubMed Central

Qian, Guoqi; Wu, Yuehua; Ferrari, Davide; Qiao, Puxue; Hollande, Frédéric

2016-01-01

Regression clustering is a mixture of unsupervised and supervised statistical learning and data mining method which is found in a wide range of applications including artificial intelligence and neuroscience. It performs unsupervised learning when it clusters the data according to their respective unobserved regression hyperplanes. The method also performs supervised learning when it fits regression hyperplanes to the corresponding data clusters. Applying regression clustering in practice requires means of determining the underlying number of clusters in the data, finding the cluster label of each data point, and estimating the regression coefficients of the model. In this paper, we review the estimation and selection issues in regression clustering with regard to the least squares and robust statistical methods. We also provide a model selection based technique to determine the number of regression clusters underlying the data. We further develop a computing procedure for regression clustering estimation and selection. Finally, simulation studies are presented for assessing the procedure, together with analyzing a real data set on RGB cell marking in neuroscience to illustrate and interpret the method. PMID:27212939

Rotation Periods of Open Cluster Stars. IV.

NASA Astrophysics Data System (ADS)

Prosser, Charles F.; Grankin, Konstantin N.

We present the results from a photometric monitoring program of primarily solar-type open cluster stars obtained during 1994 and 1995. Several members of the α Persei cluster have been monitored and the corresponding relation between coronal x-ray activity and rotation period derived. The relation among mid-G/K type members illustrates both the previously noticed downturn in L_X/L_bol at high rotation rates and the sharp decrease in coronal activity at long rotation periods as seen among Pleiades stars. Intensive observation of one slowly rotating G-type member of IC 4665 has enabled a period determination of 8-10 days to be made and illustrates the need for (and limitations of) high quality observations.

The microbial ecology of anaerobic cellulose degradation in municipal waste landfill sites: evidence of a role for fibrobacters.

PubMed

McDonald, James E; Houghton, James N I; Rooks, David J; Allison, Heather E; McCarthy, Alan J

2012-04-01

Cellulose is reputedly the most abundant organic polymer in the biosphere, yet despite the fundamental role of cellulolytic microorganisms in global carbon cycling and as potential sources of novel enzymes for biotechnology, their identity and ecology is not well established. Cellulose is a major component of landfill waste and its degradation is therefore a key feature of the anaerobic microbial decomposition process. Here, we targeted a number of taxa containing known cellulolytic anaerobes (members of the bacterial genus Fibrobacter, lineages of Clostridium clusters I, III, IV and XIV, and anaerobic fungi of the Neocallimastigales) in landfill leachate and colonized cellulose 'baits' via PCR and quantitative PCR (qPCR). Fibrobacter spp. and Clostridium clusters III, IV and XIV were detected in almost all leachate samples and cluster III and XIV clostridia were the most abundant (1-6% and 1-17% of total bacterial 16S rRNA gene copies respectively). Two landfill leachate microcosms were constructed to specifically assess those microbial communities that colonize and degrade cellulose substrates in situ. Scanning electron microscopy (SEM) of colonized cotton revealed extensive cellulose degradation in one microcosm, and Fibrobacter spp. and Clostridium cluster III represented 29% and 17%, respectively, of total bacterial 16S rRNA gene copies in the biofilm. Visible cellulose degradation was not observed in the second microcosm, and this correlated with negligible relative abundances of Clostridium cluster III and Fibrobacter spp. (≤ 0.1%), providing the first evidence that the novel fibrobacters recently detected in landfill sites and other non-gut environments colonize and degrade cellulose substrates in situ. © 2012 Society for Applied Microbiology and Blackwell Publishing Ltd.

Toward an empirical definition of pediatric PTSD: the phenomenology of PTSD symptoms in youth.

PubMed

Carrion, Victor G; Weems, Carl F; Ray, Rebecca; Reiss, Allan L

2002-02-01

To examine the frequency and intensity of posttraumatic stress disorder (PTSD) symptoms and their relation to clinical impairment, to examine the requirement of meeting all DSM-IV symptom cluster criteria (i.e., criteria B, C, D), and to examine the aggregation of PTSD symptom clusters across developmental stages. Fifty-nine children between the ages of 7 and 14 years with a history of trauma and PTSD symptoms were assessed with the Clinician-Administered PTSD Scale for Children and Adolescents. Data support the utility of distinguishing between the frequency and the intensity of symptoms in the investigation of the phenomenology of pediatric PTSD. Children fulfilling requirements for two symptom clusters did not differ significantly from children meeting all three cluster criteria with regard to impairment and distress. Reexperience (cluster B) showed increased aggregation with avoidance and numbing (cluster C) and hyperarousal (cluster D) in the later stages of puberty. Frequency and intensity of symptoms may both contribute to the phenomenology of pediatric PTSD. Children with subthreshold criteria for PTSD demonstrate substantial functional impairment and distress.

OGLE Collection of Star Clusters. New Objects in the Magellanic Bridge and the Outskirts of the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Sitek, M.; Szymański, M. K.; Udalski, A.; Skowron, D. M.; Kostrzewa-Rutkowska, Z.; Skowron, J.; Karczmarek, P.; Cieślar, M.; Wyrzykowski, Ł.; Kozłowski, S.; Pietrukowicz, P.; Soszyński, I.; Mróz, P.; Pawlak, M.; Poleski, R.; Ulaczyk, K.

2017-12-01

The Magellanic System (MS) encompasses the nearest neighbors of the Milky Way, the Large (LMC) and Small (SMC) Magellanic Clouds, and the Magellanic Bridge (MBR). This system contains a diverse sample of star clusters. Their parameters, such as the spatial distribution, chemical composition and age distribution yield important information about the formation scenario of the whole Magellanic System. Using deep photometric maps compiled in the fourth phase of the Optical Gravitational Lensing Experiment (OGLE-IV) we present the most complete catalog of star clusters in the Magellanic System ever constructed from homogeneous, long time-scale photometric data. In this second paper of the series, we show the collection of star clusters found in the area of about 360 square degrees in the MBR and in the outer regions of the SMC. Our sample contains 198 visually identified star cluster candidates, 75 of which were not listed in any of the previously published catalogs. The new discoveries are mainly young small open clusters or clusters similar to associations.

SaRAD: a Simple and Robust Abbreviation Dictionary.

PubMed

Adar, Eytan

2004-03-01

Due to recent interest in the use of textual material to augment traditional experiments it has become necessary to automatically cluster, classify and filter natural language information. The Simple and Robust Abbreviation Dictionary (SaRAD) provides an easy to implement, high performance tool for the construction of a biomedical symbol dictionary. The algorithms, applied to the MEDLINE document set, result in a high quality dictionary and toolset to disambiguate abbreviation symbols automatically.

Delay-induced cluster patterns in coupled Cayley tree networks

NASA Astrophysics Data System (ADS)

Singh, A.; Jalan, S.

2013-07-01

We study effects of delay in diffusively coupled logistic maps on the Cayley tree networks. We find that smaller coupling values exhibit sensitiveness to value of delay, and lead to different cluster patterns of self-organized and driven types. Whereas larger coupling strengths exhibit robustness against change in delay values, and lead to stable driven clusters comprising nodes from last generation of the Cayley tree. Furthermore, introduction of delay exhibits suppression as well as enhancement of synchronization depending upon coupling strength values. To the end we discuss the importance of results to understand conflicts and cooperations observed in family business.

Kinematic fingerprint of core-collapsed globular clusters

NASA Astrophysics Data System (ADS)

Bianchini, P.; Webb, J. J.; Sills, A.; Vesperini, E.

2018-03-01

Dynamical evolution drives globular clusters towards core collapse, which strongly shapes their internal properties. Diagnostics of core collapse have so far been based on photometry only, namely on the study of the concentration of the density profiles. Here, we present a new method to robustly identify core-collapsed clusters based on the study of their stellar kinematics. We introduce the kinematic concentration parameter, ck, the ratio between the global and local degree of energy equipartition reached by a cluster, and show through extensive direct N-body simulations that clusters approaching core collapse and in the post-core collapse phase are strictly characterized by ck > 1. The kinematic concentration provides a suitable diagnostic to identify core-collapsed clusters, independent from any other previous methods based on photometry. We also explore the effects of incomplete radial and stellar mass coverage on the calculation of ck and find that our method can be applied to state-of-art kinematic data sets.

Swarm Intelligence in Text Document Clustering

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

Cui, Xiaohui; Potok, Thomas E

2008-01-01

Social animals or insects in nature often exhibit a form of emergent collective behavior. The research field that attempts to design algorithms or distributed problem-solving devices inspired by the collective behavior of social insect colonies is called Swarm Intelligence. Compared to the traditional algorithms, the swarm algorithms are usually flexible, robust, decentralized and self-organized. These characters make the swarm algorithms suitable for solving complex problems, such as document collection clustering. The major challenge of today's information society is being overwhelmed with information on any topic they are searching for. Fast and high-quality document clustering algorithms play an important role inmore » helping users to effectively navigate, summarize, and organize the overwhelmed information. In this chapter, we introduce three nature inspired swarm intelligence clustering approaches for document clustering analysis. These clustering algorithms use stochastic and heuristic principles discovered from observing bird flocks, fish schools and ant food forage.« less

Dynamic multifactor clustering of financial networks

NASA Astrophysics Data System (ADS)

Ross, Gordon J.

2014-02-01

We investigate the tendency for financial instruments to form clusters when there are multiple factors influencing the correlation structure. Specifically, we consider a stock portfolio which contains companies from different industrial sectors, located in several different countries. Both sector membership and geography combine to create a complex clustering structure where companies seem to first be divided based on sector, with geographical subclusters emerging within each industrial sector. We argue that standard techniques for detecting overlapping clusters and communities are not able to capture this type of structure and show how robust regression techniques can instead be used to remove the influence of both sector and geography from the correlation matrix separately. Our analysis reveals that prior to the 2008 financial crisis, companies did not tend to form clusters based on geography. This changed immediately following the crisis, with geography becoming a more important determinant of clustering structure.

Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition

PubMed Central

Cui, Zhiming; Zhao, Pengpeng

2014-01-01

A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045

Minimal spanning trees at the percolation threshold: A numerical calculation

NASA Astrophysics Data System (ADS)

Sweeney, Sean M.; Middleton, A. Alan

2013-09-01

The fractal dimension of minimal spanning trees on percolation clusters is estimated for dimensions d up to d=5. A robust analysis technique is developed for correlated data, as seen in such trees. This should be a robust method suitable for analyzing a wide array of randomly generated fractal structures. The trees analyzed using these techniques are built using a combination of Prim's and Kruskal's algorithms for finding minimal spanning trees. This combination reduces memory usage and allows for simulation of larger systems than would otherwise be possible. The path length fractal dimension ds of MSTs on critical percolation clusters is found to be compatible with the predictions of the perturbation expansion developed by T. S. Jackson and N. Read [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.81.021131 81, 021131 (2010)].

Assessment of personality functioning: validity of the operationalized psychodynamic diagnosis axis IV (structure).

PubMed

Doering, Stephan; Burgmer, Markus; Heuft, Gereon; Menke, Dina; Bäumer, Brigitta; Lübking, Margit; Feldmann, Marcus; Schneider, Gudrun

2014-01-01

The assessment of personality functioning has recently become a focus of psychiatric diagnostics. The interview-based Operationalized Psychodynamic Diagnosis (OPD-2) provides a 'structure axis' for the assessment of personality functioning. One hundred twenty-four psychiatric patients were diagnosed by means of the Structured Clinical Interviews for DSM-IV (SCID-I and SCID-II), underwent OPD-2 interviews, and completed 9 questionnaires. The OPD-2 structure axis shows good interrater reliability (intraclass correlation = 0.793). Correlations between the OPD-2 structure axis domains and a priori selected questionnaire scales were of medium size and significant. Patients with a personality disorder (PD) showed significantly worse personality functioning than those without. In cluster B PD, personality functioning was more severely impaired than in cluster C PD. The OPD-2 structure axis shows good reliability as well as concurrent and discriminant validity and can be recommended for clinical use and research purposes. © 2013 S. Karger AG, Basel.

Identification of a cluster IV pleiotropic drug resistance transporter gene expressed in the style of Nicotiana plumbaginifolia.

PubMed

Trombik, Tomasz; Jasinski, Michal; Crouzet, Jérome; Boutry, Marc

2008-01-01

ATP-binding cassette transporters of the pleiotropic drug resistance (PDR) subfamily are composed of five clusters. We have cloned a gene, NpPDR2, belonging to the still uncharacterized cluster IV from Nicotiana plumbaginifolia. NpPDR2 transcripts were found in the roots and mature flowers. In the latter, NpPDR2 expression was restricted to the style and only after pollination. A 1.5-kb genomic sequence containing the putative NpPDR2 transcription promoter was fused to the beta-glucuronidase reporter gene. The GUS expression pattern confirmed the RT-PCR results that NpPDR2 was expressed in roots and the flower style and showed that it was localized around the conductive tissues. Unlike other PDR genes, NpPDR2 expression was not induced in leaf tissues by none of the hormones typically involved in biotic and abiotic stress response. Moreover, unlike NpPDR1 known to be involved in biotic stress response, NpPDR2 expression was not induced in the style upon Botrytis cinerea infection. In N. plumbaginifolia plants in which NpPDR2 expression was prevented by RNA interference, no unusual phenotype was observed, including at the flowering stage, which suggests that NpPDR2 is not essential in the reproductive process under the tested conditions.

VizieR Online Data Catalog: GLASS. IV. Lensing cluster Abell 2744 (Wang+, 2015)

NASA Astrophysics Data System (ADS)

Wang, X.; Hoag, A.; Huang, K.-H.; Treu, T.; Bradac, M.; Schmidt, K. B.; Brammer, G. B.; Vulcani, B.; Jones, T. A.; Ryan, R. E. Jr; Amorin, R.; Castellano, M.; Fontana, A.; Merlin, E.; Trenti, M.

2016-02-01

The two position angles (P.A.s) of Grism Lens-Amplified Survey from Space (GLASS) data analyzed in this study were taken on 2014 August 22 and 23 (P.A.=135) and 2014 October 24 and 25 (P.A.=233), respectively. The Hubble Frontier Fields initiative (HFF, P.I. Lotz) is a Director's Discretionary Time legacy program with HST devoting 840 orbits of HST time to acquire optical ACS and NIR WFC3 imaging of six of the strongest lensing galaxy clusters on the sky. All six HFF clusters are included in the GLASS sample. The Spitzer Frontier Fields program (P.I. Soifer) is a Director's Discretionary Time program that images all six strong lensing galaxy clusters targeted by the HFF in both warm IRAC channels (3.6 and 4.5um). (2 data files).

Bi cluster-assembled interconnects produced using SU8 templates

NASA Astrophysics Data System (ADS)

Partridge, J. G.; Matthewson, T.; Brown, S. A.

2007-04-01

Bi clusters with an average diameter of 25 nm have been deposited from an inert gas aggregation source and assembled into thin-film interconnects which are formed between planar electrical contacts and supported on Si substrates passivated with Si3N4 or thermally grown oxide. A layer of SU8 (a negative photoresist based on EPON SU-8 epoxy resin) is patterned using optical or electron-beam lithography, and it defines the position and dimensions of the cluster film. The conduction between the contacts is monitored throughout the deposition/assembly process, and subsequent I(V) characterization is performed in situ. Bi cluster-assembled interconnects have been fabricated with nanoscale widths and with up to 1:1 thickness:width aspect ratios. The conductivity of these interconnects has been increased, post-deposition, using a simple thermal annealing process.

Electronic structural changes of Mn in the oxygen-evolving complex of photosystem II during the catalytic cycle.

PubMed

Glatzel, Pieter; Schroeder, Henning; Pushkar, Yulia; Boron, Thaddeus; Mukherjee, Shreya; Christou, George; Pecoraro, Vincent L; Messinger, Johannes; Yachandra, Vittal K; Bergmann, Uwe; Yano, Junko

2013-05-20

The oxygen-evolving complex (OEC) in photosystem II (PS II) was studied in the S0 through S3 states using 1s2p resonant inelastic X-ray scattering spectroscopy. The spectral changes of the OEC during the S-state transitions are subtle, indicating that the electrons are strongly delocalized throughout the cluster. The result suggests that, in addition to the Mn ions, ligands are also playing an important role in the redox reactions. A series of Mn(IV) coordination complexes were compared, particularly with the PS II S3 state spectrum to understand its oxidation state. We find strong variations of the electronic structure within the series of Mn(IV) model systems. The spectrum of the S3 state best resembles those of the Mn(IV) complexes Mn3(IV)Ca2 and saplnMn2(IV)(OH)2. The current result emphasizes that the assignment of formal oxidation states alone is not sufficient for understanding the detailed electronic structural changes that govern the catalytic reaction in the OEC.

Lack of an Efficient Endoplasmic Reticulum-localized Recycling System Protects Peroxiredoxin IV from Hyperoxidation*

PubMed Central

Cao, Zhenbo; Subramaniam, Suraj; Bulleid, Neil J.

2014-01-01

Typical 2-Cys peroxiredoxins are required to remove hydrogen peroxide from several different cellular compartments. Their activity can be regulated by hyperoxidation and consequent inactivation of the active-site peroxidatic cysteine. Here we developed a simple assay to quantify the hyperoxidation of peroxiredoxins. Hyperoxidation of peroxiredoxins can only occur efficiently in the presence of a recycling system, usually involving thioredoxin and thioredoxin reductase. We demonstrate that there is a marked difference in the sensitivity of the endoplasmic reticulum-localized peroxiredoxin to hyperoxidation compared with either the cytosolic or mitochondrial enzymes. Each enzyme is equally sensitive to hyperoxidation in the presence of a robust recycling system. Our results demonstrate that peroxiredoxin IV recycling in the endoplasmic reticulum is much less efficient than in the cytosol or mitochondria, leading to the protection of peroxiredoxin IV from hyperoxidation. PMID:24403061

A genetic graph-based approach for partitional clustering.

PubMed

Menéndez, Héctor D; Barrero, David F; Camacho, David

2014-05-01

Clustering is one of the most versatile tools for data analysis. In the recent years, clustering that seeks the continuity of data (in opposition to classical centroid-based approaches) has attracted an increasing research interest. It is a challenging problem with a remarkable practical interest. The most popular continuity clustering method is the spectral clustering (SC) algorithm, which is based on graph cut: It initially generates a similarity graph using a distance measure and then studies its graph spectrum to find the best cut. This approach is sensitive to the parameters of the metric, and a correct parameter choice is critical to the quality of the cluster. This work proposes a new algorithm, inspired by SC, that reduces the parameter dependency while maintaining the quality of the solution. The new algorithm, named genetic graph-based clustering (GGC), takes an evolutionary approach introducing a genetic algorithm (GA) to cluster the similarity graph. The experimental validation shows that GGC increases robustness of SC and has competitive performance in comparison with classical clustering methods, at least, in the synthetic and real dataset used in the experiments.

Progeny Clustering: A Method to Identify Biological Phenotypes

PubMed Central

Hu, Chenyue W.; Kornblau, Steven M.; Slater, John H.; Qutub, Amina A.

2015-01-01

Estimating the optimal number of clusters is a major challenge in applying cluster analysis to any type of dataset, especially to biomedical datasets, which are high-dimensional and complex. Here, we introduce an improved method, Progeny Clustering, which is stability-based and exceptionally efficient in computing, to find the ideal number of clusters. The algorithm employs a novel Progeny Sampling method to reconstruct cluster identity, a co-occurrence probability matrix to assess the clustering stability, and a set of reference datasets to overcome inherent biases in the algorithm and data space. Our method was shown successful and robust when applied to two synthetic datasets (datasets of two-dimensions and ten-dimensions containing eight dimensions of pure noise), two standard biological datasets (the Iris dataset and Rat CNS dataset) and two biological datasets (a cell phenotype dataset and an acute myeloid leukemia (AML) reverse phase protein array (RPPA) dataset). Progeny Clustering outperformed some popular clustering evaluation methods in the ten-dimensional synthetic dataset as well as in the cell phenotype dataset, and it was the only method that successfully discovered clinically meaningful patient groupings in the AML RPPA dataset. PMID:26267476

Salen- Zr(IV) complex grafted into amine-tagged MIL-101(Cr) as a robust multifunctional catalyst for biodiesel production and organic transformation reactions

NASA Astrophysics Data System (ADS)

Hassan, Hassan M. A.; Betiha, Mohamed A.; Mohamed, Shaimaa K.; El-Sharkawy, E. A.; Ahmed, Emad A.

2017-08-01

The synthesis of metal-organic frameworks (MOFs), porous coordination polymers with functional groups has received immense interest due to the functional groups can offer desirable properties and allow post-synthetic modification. Herein, for the first time, Zr(IV)-Sal Schiff base complex incorporated into amino-functionalized MIL-101(Cr) framework by salicylaldehyde condensing to amino group, and coordinating Zr(IV) ion have been successfully synthesized. The worthiness of the synthesized material as a catalyst has been examined for the esterification of oleic acid (free fatty acid) with methanol producing biodiesel (methyl oleate), Knoveonagel condensation reaction of aldehydes and Friedel-Crafts acylation of anisole. Our findings demonstrated that Salen-Zr(IV) grafted to framework of NH2-MIL-101(Cr) as a solid acid catalyst exhibited distinct catalytic performance for the production of biodiesel by esterification of oleic acid with methanol, Knoveonagel condensation and Friedel-Crafts acylation. These could be attributed to high surface area which allow high distribution of Zr(IV) species lead to a sufficient contact with the reactants species. Furthermore, the catalyst showed excellent recycling efficiency due to the strong interaction between the Zr(IV) ions and chelating groups in the NH2-MIL-101(Cr)-Sal.

Sulfate Assimilation Mediates Tellurite Reduction and Toxicity in Saccharomyces cerevisiae▿†

PubMed Central

Ottosson, Lars-Göran; Logg, Katarina; Ibstedt, Sebastian; Sunnerhagen, Per; Käll, Mikael; Blomberg, Anders; Warringer, Jonas

2010-01-01

Despite a century of research and increasing environmental and human health concerns, the mechanistic basis of the toxicity of derivatives of the metalloid tellurium, Te, in particular the oxyanion tellurite, Te(IV), remains unsolved. Here, we provide an unbiased view of the mechanisms of tellurium metabolism in the yeast Saccharomyces cerevisiae by measuring deviations in Te-related traits of a complete collection of gene knockout mutants. Reduction of Te(IV) and intracellular accumulation as metallic tellurium strongly correlated with loss of cellular fitness, suggesting that Te(IV) reduction and toxicity are causally linked. The sulfate assimilation pathway upstream of Met17, in particular, the sulfite reductase and its cofactor siroheme, was shown to be central to tellurite toxicity and its reduction to elemental tellurium. Gene knockout mutants with altered Te(IV) tolerance also showed a similar deviation in tolerance to both selenite and, interestingly, selenomethionine, suggesting that the toxicity of these agents stems from a common mechanism. We also show that Te(IV) reduction and toxicity in yeast is partially mediated via a mitochondrial respiratory mechanism that does not encompass the generation of substantial oxidative stress. The results reported here represent a robust base from which to attack the mechanistic details of Te(IV) toxicity and reduction in a eukaryotic organism. PMID:20675578

Tropospheric Parameters Determined by VLBI Within the IVS

NASA Astrophysics Data System (ADS)

Schuh, H.; Boehm, J.

2003-12-01

In April 2002 the IVS (International VLBI Service for Geodesy and Astrometry) set up the Pilot Project - Tropospheric Parameters, and the Institute of Geodesy and Geophysics (IGG), Vienna, was put in charge of coordinating the project. Seven IVS Analysis Centers have joined the project and regularly submitted their estimates of tropospheric parameters (wet and total zenith delays, horizontal gradients) for all IVS-R1 and IVS-R4 sessions since January 1st, 2002. The individual submissions are combined by a two-step procedure to obtain stable, robust and highly accurate tropospheric parameter time series with one hour resolution. The internal accuracy of the combined wet zenith delays is between 2 and 4 mm. The zenith delays derived by VLBI are compared with those provided by the International GPS Service (IGS). At sites with co-located VLBI and GPS antennas the short-term variabilities of the GPS and VLBI derived zenith delays generally show a good agreement but biases are found between the results of the two techniques. Possible reasons for these biases are discussed. Since July 1st, 2003, within the IVS the tropospheric parameters are determined as operational products. The presentation also includes the VLBI CONT02 campaign of 15 days of continuous observing in the second half of October 2002.

Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

PubMed Central

Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

2011-01-01

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733

Statistical Issues in Galaxy Cluster Cosmology

NASA Technical Reports Server (NTRS)

Mantz, Adam

2013-01-01

The number and growth of massive galaxy clusters are sensitive probes of cosmological structure formation. Surveys at various wavelengths can detect clusters to high redshift, but the fact that cluster mass is not directly observable complicates matters, requiring us to simultaneously constrain scaling relations of observable signals with mass. The problem can be cast as one of regression, in which the data set is truncated, the (cosmology-dependent) underlying population must be modeled, and strong, complex correlations between measurements often exist. Simulations of cosmological structure formation provide a robust prediction for the number of clusters in the Universe as a function of mass and redshift (the mass function), but they cannot reliably predict the observables used to detect clusters in sky surveys (e.g. X-ray luminosity). Consequently, observers must constrain observable-mass scaling relations using additional data, and use the scaling relation model in conjunction with the mass function to predict the number of clusters as a function of redshift and luminosity.

Proteus mirabilis fimbriae- and urease-dependent clusters assemble in an extracellular niche to initiate bladder stone formation

PubMed Central

Schaffer, Jessica N.; Norsworthy, Allison N.; Sun, Tung-Tien

2016-01-01

The catheter-associated uropathogen Proteus mirabilis frequently causes urinary stones, but little has been known about the initial stages of bladder colonization and stone formation. We found that P. mirabilis rapidly invades the bladder urothelium, but generally fails to establish an intracellular niche. Instead, it forms extracellular clusters in the bladder lumen, which form foci of mineral deposition consistent with development of urinary stones. These clusters elicit a robust neutrophil response, and we present evidence of neutrophil extracellular trap generation during experimental urinary tract infection. We identified two virulence factors required for cluster development: urease, which is required for urolithiasis, and mannose-resistant Proteus-like fimbriae. The extracellular cluster formation by P. mirabilis stands in direct contrast to uropathogenic Escherichia coli, which readily formed intracellular bacterial communities but not luminal clusters or urinary stones. We propose that extracellular clusters are a key mechanism of P. mirabilis survival and virulence in the bladder. PMID:27044107

Cúmulos jóvenes inmersos en campos de edad intermedia en la barra de la Nube Mayor de Magallanes

NASA Astrophysics Data System (ADS)

Piatti, A. E.; Geisler, D.; Bica, E.; Clariá, J. J.

We present Washington system photometry for 11 star clusters immersed in the northwest part of the Large Magellanic Cloud (LMC) bar. The fields are heavily populated by the intermediate-age component of the LMC bar. We succeeded in disentangling cluster colour-magnitude diagrams from those of the fields and in deriving reddening and ages for five clusters - SL 218, BRHT4b, NGC 1839, NGC 1838 and NGC 1863 - with the aid of recent Washington System theoretical isochrones. The resulting cluster ages range between 50 and 125 Myr. Despite their proximity, NGC 1836 and BRHT4b have very different ages. Thus the possibility for these two objects being a binary cluster is very unlikely, although a capture cannot be ruled out a priori. Our results suggest that for each intermediate-age cluster remaining in the LMC bar region, a number of robust young blue star clusters occurs in the same region (Piatti et al. 2003, MNRAS, 343, 851).

Decentralized Formation Flying Control in a Multiple-Team Hierarchy

NASA Technical Reports Server (NTRS)

Mueller, Joseph .; Thomas, Stephanie J.

2005-01-01

This paper presents the prototype of a system that addresses these objectives-a decentralized guidance and control system that is distributed across spacecraft using a multiple-team framework. The objective is to divide large clusters into teams of manageable size, so that the communication and computational demands driven by N decentralized units are related to the number of satellites in a team rather than the entire cluster. The system is designed to provide a high-level of autonomy, to support clusters with large numbers of satellites, to enable the number of spacecraft in the cluster to change post-launch, and to provide for on-orbit software modification. The distributed guidance and control system will be implemented in an object-oriented style using MANTA (Messaging Architecture for Networking and Threaded Applications). In this architecture, tasks may be remotely added, removed or replaced post-launch to increase mission flexibility and robustness. This built-in adaptability will allow software modifications to be made on-orbit in a robust manner. The prototype system, which is implemented in MATLAB, emulates the object-oriented and message-passing features of the MANTA software. In this paper, the multiple-team organization of the cluster is described, and the modular software architecture is presented. The relative dynamics in eccentric reference orbits is reviewed, and families of periodic, relative trajectories are identified, expressed as sets of static geometric parameters. The guidance law design is presented, and an example reconfiguration scenario is used to illustrate the distributed process of assigning geometric goals to the cluster. Next, a decentralized maneuver planning approach is presented that utilizes linear-programming methods to enact reconfiguration and coarse formation keeping maneuvers. Finally, a method for performing online collision avoidance is discussed, and an example is provided to gauge its performance.

An optimal autonomous microgrid cluster based on distributed generation droop parameter optimization and renewable energy sources using an improved grey wolf optimizer

NASA Astrophysics Data System (ADS)

Moazami Goodarzi, Hamed; Kazemi, Mohammad Hosein

2018-05-01

Microgrid (MG) clustering is regarded as an important driver in improving the robustness of MGs. However, little research has been conducted on providing appropriate MG clustering. This article addresses this shortfall. It proposes a novel multi-objective optimization approach for finding optimal clustering of autonomous MGs by focusing on variables such as distributed generation (DG) droop parameters, the location and capacity of DG units, renewable energy sources, capacitors and powerline transmission. Power losses are minimized and voltage stability is improved while virtual cut-set lines with minimum power transmission for clustering MGs are obtained. A novel chaotic grey wolf optimizer (CGWO) algorithm is applied to solve the proposed multi-objective problem. The performance of the approach is evaluated by utilizing a 69-bus MG in several scenarios.

Basic firefly algorithm for document clustering

NASA Astrophysics Data System (ADS)

Mohammed, Athraa Jasim; Yusof, Yuhanis; Husni, Husniza

2015-12-01

The Document clustering plays significant role in Information Retrieval (IR) where it organizes documents prior to the retrieval process. To date, various clustering algorithms have been proposed and this includes the K-means and Particle Swarm Optimization. Even though these algorithms have been widely applied in many disciplines due to its simplicity, such an approach tends to be trapped in a local minimum during its search for an optimal solution. To address the shortcoming, this paper proposes a Basic Firefly (Basic FA) algorithm to cluster text documents. The algorithm employs the Average Distance to Document Centroid (ADDC) as the objective function of the search. Experiments utilizing the proposed algorithm were conducted on the 20Newsgroups benchmark dataset. Results demonstrate that the Basic FA generates a more robust and compact clusters than the ones produced by K-means and Particle Swarm Optimization (PSO).

AtlA functions as a peptidoglycan lytic transglycosylase in the Neisseria gonorrhoeae type IV secretion system.

PubMed

Kohler, Petra L; Hamilton, Holly L; Cloud-Hansen, Karen; Dillard, Joseph P

2007-08-01

Type IV secretion systems require peptidoglycan lytic transglycosylases for efficient secretion, but the function of these enzymes is not clear. The type IV secretion system gene cluster of Neisseria gonorrhoeae encodes two peptidoglycan transglycosylase homologues. One, LtgX, is similar to peptidoglycan transglycosylases from other type IV secretion systems. The other, AtlA, is similar to endolysins from bacteriophages and is not similar to any described type IV secretion component. We characterized the enzymatic function of AtlA in order to examine its role in the type IV secretion system. Purified AtlA was found to degrade macromolecular peptidoglycan and to produce 1,6-anhydro peptidoglycan monomers, characteristic of lytic transglycosylase activity. We found that AtlA can functionally replace the lambda endolysin to lyse Escherichia coli. In contrast, a sensitive measure of lysis demonstrated that AtlA does not lyse gonococci expressing it or gonococci cocultured with an AtlA-expressing strain. The gonococcal type IV secretion system secretes DNA during growth. A deletion of ltgX or a substitution in the putative active site of AtlA severely decreased DNA secretion. These results indicate that AtlA and LtgX are actively involved in type IV secretion and that AtlA is not involved in lysis of gonococci to release DNA. This is the first demonstration that a type IV secretion peptidoglycanase has lytic transglycosylase activity. These data show that AtlA plays a role in type IV secretion of DNA that requires peptidoglycan breakdown without cell lysis.

Image segmentation-based robust feature extraction for color image watermarking

NASA Astrophysics Data System (ADS)

Li, Mianjie; Deng, Zeyu; Yuan, Xiaochen

2018-04-01

This paper proposes a local digital image watermarking method based on Robust Feature Extraction. The segmentation is achieved by Simple Linear Iterative Clustering (SLIC) based on which an Image Segmentation-based Robust Feature Extraction (ISRFE) method is proposed for feature extraction. Our method can adaptively extract feature regions from the blocks segmented by SLIC. This novel method can extract the most robust feature region in every segmented image. Each feature region is decomposed into low-frequency domain and high-frequency domain by Discrete Cosine Transform (DCT). Watermark images are then embedded into the coefficients in the low-frequency domain. The Distortion-Compensated Dither Modulation (DC-DM) algorithm is chosen as the quantization method for embedding. The experimental results indicate that the method has good performance under various attacks. Furthermore, the proposed method can obtain a trade-off between high robustness and good image quality.

Robust fluoroscopic respiratory gating for lung cancer radiotherapy without implanted fiducial markers

NASA Astrophysics Data System (ADS)

Cui, Ying; Dy, Jennifer G.; Sharp, Greg C.; Alexander, Brian; Jiang, Steve B.

2007-02-01

For gated lung cancer radiotherapy, it is difficult to generate accurate gating signals due to the large uncertainties when using external surrogates and the risk of pneumothorax when using implanted fiducial markers. We have previously investigated and demonstrated the feasibility of generating gating signals using the correlation scores between the reference template image and the fluoroscopic images acquired during the treatment. In this paper, we present an in-depth study, aiming at the improvement of robustness of the algorithm and its validation using multiple sets of patient data. Three different template generating and matching methods have been developed and evaluated: (1) single template method, (2) multiple template method, and (3) template clustering method. Using the fluoroscopic data acquired during patient setup before each fraction of treatment, reference templates are built that represent the tumour position and shape in the gating window, which is assumed to be at the end-of-exhale phase. For the single template method, all the setup images within the gating window are averaged to generate a composite template. For the multiple template method, each setup image in the gating window is considered as a reference template and used to generate an ensemble of correlation scores. All the scores are then combined to generate the gating signal. For the template clustering method, clustering (grouping of similar objects together) is performed to reduce the large number of reference templates into a few representative ones. Each of these methods has been evaluated against the reference gating signal as manually determined by a radiation oncologist. Five patient datasets were used for evaluation. In each case, gated treatments were simulated at both 35% and 50% duty cycles. False positive, negative and total error rates were computed. Experiments show that the single template method is sensitive to noise; the multiple template and clustering methods are more robust to noise due to the smoothing effect of aggregation of correlation scores; and the clustering method results in the best performance in terms of computational efficiency and accuracy.

Tabu Search enhances network robustness under targeted attacks

NASA Astrophysics Data System (ADS)

Sun, Shi-wen; Ma, Yi-lin; Li, Rui-qi; Wang, Li; Xia, Cheng-yi

2016-03-01

We focus on the optimization of network robustness with respect to intentional attacks on high-degree nodes. Given an existing network, this problem can be considered as a typical single-objective combinatorial optimization problem. Based on the heuristic Tabu Search optimization algorithm, a link-rewiring method is applied to reconstruct the network while keeping the degree of every node unchanged. Through numerical simulations, BA scale-free network and two real-world networks are investigated to verify the effectiveness of the proposed optimization method. Meanwhile, we analyze how the optimization affects other topological properties of the networks, including natural connectivity, clustering coefficient and degree-degree correlation. The current results can help to improve the robustness of existing complex real-world systems, as well as to provide some insights into the design of robust networks.

Interstellar matter near the Pleiades. IV - The wake of the Pleiades through the interstellar medium in Taurus

NASA Technical Reports Server (NTRS)

White, Richard E.; Bally, John

1993-01-01

A large emission 'cavity' whose bright rims extend about 5 deg eastward from the Pleiades, and is pressurized by the soft-UV radiation of the cluster, has been revealed by a mosaic of IRAS images; the emission cavity delineates the wake of the Pleiades as it moves supersonically through the ISM. Photoelectric heating is identified as the most likely agent of the cluster-cloud interaction generating a shock wave, and prompts the hypothesis that transverse expansion of heated gas near the cluster plays a crucial role in driving the shock. The cloud trajectory can be traced back to an origin in Gould's Belt some 15 Myr ago, in a blowout of gas into the Galactic halo.

Scalable Robust Principal Component Analysis Using Grassmann Averages.

PubMed

Hauberg, Sren; Feragen, Aasa; Enficiaud, Raffi; Black, Michael J

2016-11-01

In large datasets, manual data verification is impossible, and we must expect the number of outliers to increase with data size. While principal component analysis (PCA) can reduce data size, and scalable solutions exist, it is well-known that outliers can arbitrarily corrupt the results. Unfortunately, state-of-the-art approaches for robust PCA are not scalable. We note that in a zero-mean dataset, each observation spans a one-dimensional subspace, giving a point on the Grassmann manifold. We show that the average subspace corresponds to the leading principal component for Gaussian data. We provide a simple algorithm for computing this Grassmann Average ( GA), and show that the subspace estimate is less sensitive to outliers than PCA for general distributions. Because averages can be efficiently computed, we immediately gain scalability. We exploit robust averaging to formulate the Robust Grassmann Average (RGA) as a form of robust PCA. The resulting Trimmed Grassmann Average ( TGA) is appropriate for computer vision because it is robust to pixel outliers. The algorithm has linear computational complexity and minimal memory requirements. We demonstrate TGA for background modeling, video restoration, and shadow removal. We show scalability by performing robust PCA on the entire Star Wars IV movie; a task beyond any current method. Source code is available online.

Two transitional type Ia supernovae located in the Fornax cluster member NGC 1404: SN 2007on and SN 2011iv

NASA Astrophysics Data System (ADS)

Gall, C.; Stritzinger, M. D.; Ashall, C.; Baron, E.; Burns, C. R.; Hoeflich, P.; Hsiao, E. Y.; Mazzali, P. A.; Phillips, M. M.; Filippenko, A. V.; Anderson, J. P.; Benetti, S.; Brown, P. J.; Campillay, A.; Challis, P.; Contreras, C.; Elias de la Rosa, N.; Folatelli, G.; Foley, R. J.; Fraser, M.; Holmbo, S.; Marion, G. H.; Morrell, N.; Pan, Y.-C.; Pignata, G.; Suntzeff, N. B.; Taddia, F.; Robledo, S. Torres; Valenti, S.

2018-03-01

We present an analysis of ultraviolet (UV) to near-infrared observations of the fast-declining Type Ia supernovae (SNe Ia) 2007on and 2011iv, hosted by the Fornax cluster member NGC 1404. The B-band light curves of SN 2007on and SN 2011iv are characterised by Δm15 (B) decline-rate values of 1.96 mag and 1.77 mag, respectively. Although they have similar decline rates, their peak B- and H-band magnitudes differ by 0.60 mag and 0.35 mag, respectively. After correcting for the luminosity vs. decline rate and the luminosity vs. colour relations, the peak B-band and H-band light curves provide distances that differ by 14% and 9%, respectively. These findings serve as a cautionary tale for the use of transitional SNe Ia located in early-type hosts in the quest to measure cosmological parameters. Interestingly, even though SN 2011iv is brighter and bluer at early times, by three weeks past maximum and extending over several months, its B - V colour is 0.12 mag redder than that of SN 2007on. To reconcile this unusual behaviour, we turn to guidance from a suite of spherical one-dimensional Chandrasekhar-mass delayed-detonation explosion models. In this context, 56Ni production depends on both the so-called transition density and the central density of the progenitor white dwarf. To first order, the transition density drives the luminosity-width relation, while the central density is an important second-order parameter. Within this context, the differences in the B - V colour evolution along the Lira regime suggest that the progenitor of SN 2011iv had a higher central density than SN 2007on. The photometry tables are only available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/611/A58

Major impact of N-methylation on cytotoxicity and hydrolysis of salan Ti(IV) complexes: sterics and electronics are intertwined.

PubMed

Meker, Sigalit; Manna, Cesar M; Peri, Dani; Tshuva, Edit Y

2011-10-14

A series of Ti(IV) complexes containing diamino bis(phenolato) "salan" type ligands with NH coordination were prepared, and their hydrolysis and cytotoxicity were analyzed and compared to the N-methylated analogues. Substituting methyl groups on the coordinative nitrogen donor of highly active and stable Ti(IV) salan complexes with H atoms has two main consequences: the hydrolysis rate increases and the cytotoxic activity diminishes. In addition, the small modification of a single replacement of Me with H leads to a different major hydrolysis product, where a dinuclear Ti(IV) complex with two bridging oxo ligands is obtained, as characterized by X-ray crystallography, rather than a trinuclear cluster. A partial hydrolysis product containing a single oxo bridge was also crystallographically analyzed. Investigation of a series of complexes with NH donors of different steric and electronic effects revealed that cytotoxicity may be restored by fine tuning these parameters even for complexes of low stability.

Lane detection based on color probability model and fuzzy clustering

NASA Astrophysics Data System (ADS)

Yu, Yang; Jo, Kang-Hyun

2018-04-01

In the vehicle driver assistance systems, the accuracy and speed of lane line detection are the most important. This paper is based on color probability model and Fuzzy Local Information C-Means (FLICM) clustering algorithm. The Hough transform and the constraints of structural road are used to detect the lane line accurately. The global map of the lane line is drawn by the lane curve fitting equation. The experimental results show that the algorithm has good robustness.

Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

PubMed

Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

2018-05-01

Cystic fibrosis pulmonary exacerbations accelerate pulmonary decline and increase mortality. Previously, we identified a 10-gene leukocyte panel measured directly from whole blood, which indicates response to exacerbation treatment. We hypothesized that molecular characteristics of exacerbations could also predict future disease severity. We tested whether a 10-gene panel measured from whole blood could identify patient cohorts at increased risk for severe morbidity and mortality, beyond standard clinical measures. Transcript abundance for the 10-gene panel was measured from whole blood at the beginning of exacerbation treatment (n = 57). A hierarchical cluster analysis of subjects based on their gene expression was performed, yielding four molecular clusters. An analysis of cluster membership and outcomes incorporating an independent cohort (n = 21) was completed to evaluate robustness of cluster partitioning of genes to predict severe morbidity and mortality. The four molecular clusters were analyzed for differences in forced expiratory volume in 1 second, C-reactive protein, return to baseline forced expiratory volume in 1 second after treatment, time to next exacerbation, and time to morbidity or mortality events (defined as lung transplant referral, lung transplant, intensive care unit admission for respiratory insufficiency, or death). Clustering based on gene expression discriminated between patient groups with significant differences in forced expiratory volume in 1 second, admission frequency, and overall morbidity and mortality. At 5 years, all subjects in cluster 1 (very low risk) were alive and well, whereas 90% of subjects in cluster 4 (high risk) had suffered a major event (P = 0.0001). In multivariable analysis, the ability of gene expression to predict clinical outcomes remained significant, despite adjustment for forced expiratory volume in 1 second, sex, and admission frequency. The robustness of gene clustering to categorize patients appropriately in terms of clinical characteristics, and short- and long-term clinical outcomes, remained consistent, even when adding in a secondary population with significantly different clinical outcomes. Whole blood gene expression profiling allows molecular classification of acute pulmonary exacerbations, beyond standard clinical measures, providing a predictive tool for identifying subjects at increased risk for mortality and disease progression.

Construction of ground-state preserving sparse lattice models for predictive materials simulations

NASA Astrophysics Data System (ADS)

Huang, Wenxuan; Urban, Alexander; Rong, Ziqin; Ding, Zhiwei; Luo, Chuan; Ceder, Gerbrand

2017-08-01

First-principles based cluster expansion models are the dominant approach in ab initio thermodynamics of crystalline mixtures enabling the prediction of phase diagrams and novel ground states. However, despite recent advances, the construction of accurate models still requires a careful and time-consuming manual parameter tuning process for ground-state preservation, since this property is not guaranteed by default. In this paper, we present a systematic and mathematically sound method to obtain cluster expansion models that are guaranteed to preserve the ground states of their reference data. The method builds on the recently introduced compressive sensing paradigm for cluster expansion and employs quadratic programming to impose constraints on the model parameters. The robustness of our methodology is illustrated for two lithium transition metal oxides with relevance for Li-ion battery cathodes, i.e., Li2xFe2(1-x)O2 and Li2xTi2(1-x)O2, for which the construction of cluster expansion models with compressive sensing alone has proven to be challenging. We demonstrate that our method not only guarantees ground-state preservation on the set of reference structures used for the model construction, but also show that out-of-sample ground-state preservation up to relatively large supercell size is achievable through a rapidly converging iterative refinement. This method provides a general tool for building robust, compressed and constrained physical models with predictive power.

Administration of intravenous morphine for acute pain in the emergency department inflicts an economic burden in Europe

PubMed Central

Casamayor, Montserrat; Hennebert, Marc; Brazzi, Luca; Prosen, Gregor

2018-01-01

Background Acute pain is among the leading causes of referral to the emergency department (ED) in industrialized countries. Its management mainly depends on intensity. Moderate-to-severe pain is treated with intravenous (IV) administered opioids, of which morphine is the most commonly used in the ED. We have estimated the burden of IV administration of morphine in the five key European countries (EU5) using a micro-costing approach. Scope A structured literature review was conducted to identify clinical guidelines for acute pain management in EU5 and clinical studies conducted in the ED setting. The data identified in this literature review constituted the source for all model input parameters, which were clustered as analgesic (morphine), material used for IV morphine administration, nurse workforce time and management of morphine-related adverse events and IV-related complications. Findings The cost per patient of IV morphine administration in the ED ranges between €18.31 in Spain and €28.38 in Germany. If costs associated with the management of morphine-related adverse events and IV-related complications are also considered, the total costs amount to €121.13–€132.43. The main driver of those total costs is the management of IV-related complications (phlebitis, extravasation and IV prescription errors; 73% of all costs) followed by workforce time (14%). Conclusions IV morphine provides effective pain relief in the ED, but the costs associated with the IV administration inflict an economic burden on the respective national health services in EU5. An equally rapid-onset and efficacious analgesic that does not require IV administration could reduce this burden. PMID:29675049

75 FR 16739 - EDA Participation in the Energy Efficient Building Systems Regional Innovation Cluster Initiative

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-02

... innovation and drivers of regional economic growth. The E-RIC should leverage the region's unique competitive... investment boards, institutions of higher education including community colleges, and other public and... activities, or a consortium of political subdivisions; (iv) institution of higher education or a consortium...

Active galactic nuclei. IV - Supplying black hole clusters by tidal disruption and by tidal capture of stars

NASA Technical Reports Server (NTRS)

Stoeger, W. R.; Pacholczyk, A. G.; Stepinski, T. F.

1992-01-01

The extent to which individual holes in a cluster of black holes with a mass spectrum can liberate and accrete the resulting material by tidally disrupting stars they encounter, or by capturing stars as binary companions is studied. It is found that the smaller black holes in 'the halo' of such clusters can adequately supply themselves to the level M-dot sub h or greater than 0.0001(M-dot sub h) sub crit, and up to 0.05(M-dot sub h)sub crit for the smallest holes, by tidal disruption, as long as the cluster is embedded in a distribution of stars of relatively high density (not less than 0.1M sub cl/cu pc), and as long as the entire cluster of stars is not too compact (not less than 0.5 pc). Consideration is given to modifications this 'internal' mode of supply introduces in the spectrum emitted by such black hole clusters, and to the current status of their viability as models for AGN and QSOs in light of dynamical studies by Quinlan and Shapiro (1987, 1989).

Externalizing disorders: cluster 5 of the proposed meta-structure for DSM-V and ICD-11.

PubMed

Krueger, R F; South, S C

2009-12-01

The extant major psychiatric classifications DSM-IV and ICD-10 are purportedly atheoretical and largely descriptive. Although this achieves good reliability, the validity of a medical diagnosis is greatly enhanced by an understanding of the etiology. In an attempt to group mental disorders on the basis of etiology, five clusters have been proposed. We consider the validity of the fifth cluster, externalizing disorders, within this proposal. We reviewed the literature in relation to 11 validating criteria proposed by the Study Group of the DSM-V Task Force, in terms of the extent to which these criteria support the idea of a coherent externalizing spectrum of disorders. This cluster distinguishes itself by the central role of disinhibitory personality in mental disorders spread throughout sections of the current classifications, including substance dependence, antisocial personality disorder and conduct disorder. Shared biomarkers, co-morbidity and course offer additional evidence for a valid cluster of externalizing disorders. Externalizing disorders meet many of the salient criteria proposed by the Study Group of the DSM-V Task Force to suggest a classification cluster.

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.

Improving Electronic Sensor Reliability by Robust Outlier Screening

PubMed Central

Moreno-Lizaranzu, Manuel J.; Cuesta, Federico

2013-01-01

Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs. PMID:24113682

Improving electronic sensor reliability by robust outlier screening.

PubMed

Moreno-Lizaranzu, Manuel J; Cuesta, Federico

2013-10-09

Electronic sensors are widely used in different application areas, and in some of them, such as automotive or medical equipment, they must perform with an extremely low defect rate. Increasing reliability is paramount. Outlier detection algorithms are a key component in screening latent defects and decreasing the number of customer quality incidents (CQIs). This paper focuses on new spatial algorithms (Good Die in a Bad Cluster with Statistical Bins (GDBC SB) and Bad Bin in a Bad Cluster (BBBC)) and an advanced outlier screening method, called Robust Dynamic Part Averaging Testing (RDPAT), as well as two practical improvements, which significantly enhance existing algorithms. Those methods have been used in production in Freescale® Semiconductor probe factories around the world for several years. Moreover, a study was conducted with production data of 289,080 dice with 26 CQIs to determine and compare the efficiency and effectiveness of all these algorithms in identifying CQIs.

A robust fuzzy local Information c-means clustering algorithm with noise detection

NASA Astrophysics Data System (ADS)

Shang, Jiayu; Li, Shiren; Huang, Junwei

2018-04-01

Fuzzy c-means clustering (FCM), especially with spatial constraints (FCM_S), is an effective algorithm suitable for image segmentation. Its reliability contributes not only to the presentation of fuzziness for belongingness of every pixel but also to exploitation of spatial contextual information. But these algorithms still remain some problems when processing the image with noise, they are sensitive to the parameters which have to be tuned according to prior knowledge of the noise. In this paper, we propose a new FCM algorithm, combining the gray constraints and spatial constraints, called spatial and gray-level denoised fuzzy c-means (SGDFCM) algorithm. This new algorithm conquers the parameter disadvantages mentioned above by considering the possibility of noise of each pixel, which aims to improve the robustness and obtain more detail information. Furthermore, the possibility of noise can be calculated in advance, which means the algorithm is effective and efficient.

Identifying subtypes among offenders with antisocial personality disorder: a cluster-analytic study.

PubMed

Poythress, Norman G; Edens, John F; Skeem, Jennifer L; Lilienfeld, Scott O; Douglas, Kevin S; Frick, Paul J; Patrick, Christopher J; Epstein, Monica; Wang, Tao

2010-05-01

The question of whether antisocial personality disorder (ASPD) and psychopathy are largely similar or fundamentally different constructs remains unresolved. In the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994), many of the personality features of psychopathy are cast as associated features of ASPD, although the DSM-IV offers no guidance as to how, or the extent to which, these features relate to ASPD. In a sample of 691 offenders who met DSM-IV criteria for ASPD, we used model-based clustering to identify subgroups of individuals with relatively homogeneous profiles on measures of associated features (psychopathic personality traits) and other constructs with potential etiological significance for subtypes of ASPD. Two emergent groups displayed profiles that conformed broadly to theoretical descriptions of primary psychopathy and Karpman's (1941) variant of secondary psychopathy. As expected, a third group (nonpsychopathic ASPD) lacked substantial associated features. A fourth group exhibited elevated psychopathic features as well as a highly fearful temperament, a profile not clearly predicted by extant models. Planned comparisons revealed theoretically informative differences between primary and secondary groups in multiple domains, including self-report measures, passive avoidance learning, clinical ratings, and official records. Our results inform ongoing debates about the overlap between psychopathy and ASPD and raise questions about the wisdom of placing most individuals who habitually violate social norms and laws into a single diagnostic category.

Pili-taxis: Clustering of Neisseria gonorrhoeae bacteria

NASA Astrophysics Data System (ADS)

Taktikos, Johannes; Zaburdaev, Vasily; Biais, Nicolas; Stark, Holger; Weitz, David A.

2012-02-01

The first step of colonization of Neisseria gonorrhoeae bacteria, the etiological agent of gonorrhea, is the attachment to human epithelial cells. The attachment of N. gonorrhoeae bacteria to surfaces or other cells is primarily mediated by filamentous appendages, called type IV pili (Tfp). Cycles of elongation and retraction of Tfp are responsible for a common bacterial motility called twitching motility which allows the bacteria to crawl over surfaces. Experimentally, N. gonorrhoeae cells initially dispersed over a surface agglomerate into round microcolonies within hours. It is so far not known whether this clustering is driven entirely by the Tfp dynamics or if chemotactic interactions are needed. Thus, we investigate whether the agglomeration may stem solely from the pili-mediated attraction between cells. By developing a statistical model for pili-taxis, we try to explain the experimental measurements of the time evolution of the mean cluster size, number of clusters, and area fraction covered by the cells.

Regularities in the sequences of the number of nucleons in the revolving clusters for the ground-state energy bands of the even-even nuclei with neutron number equal to or greater than 126.

PubMed

Pauling, L

1990-06-01

Values of m, the number of nucleons in the revolving cluster, and of R, the radius of revolution of the cluster about the center of mass of the spherical part of the nucleus, are calculated from the observed values of the energy for the ground-state bands of all nuclei with neutron number N >/= 126 on the basis of the assumptions (i) that both m and R change in a reasonable way with increase in the angular momentum quantum number J and with change in the proton number Z and the neutron number N, (ii) that m is usually an even integer, (iii) that certain clusters are especially stable, and (iv) that there is a special stability of the doubly magic sphere p82n126.

Regularities in the sequences of the number of nucleons in the revolving clusters for the ground-state energy bands of the even-even nuclei with neutron number equal to or greater than 126.

PubMed Central

Pauling, L

1990-01-01

Values of m, the number of nucleons in the revolving cluster, and of R, the radius of revolution of the cluster about the center of mass of the spherical part of the nucleus, are calculated from the observed values of the energy for the ground-state bands of all nuclei with neutron number N >/= 126 on the basis of the assumptions (i) that both m and R change in a reasonable way with increase in the angular momentum quantum number J and with change in the proton number Z and the neutron number N, (ii) that m is usually an even integer, (iii) that certain clusters are especially stable, and (iv) that there is a special stability of the doubly magic sphere p82n126. PMID:11607085

Enhancers and super-enhancers have an equivalent regulatory role in embryonic stem cells through regulation of single or multiple genes

PubMed Central

Moorthy, Sakthi D.; Davidson, Scott; Shchuka, Virlana M.; Singh, Gurdeep; Malek-Gilani, Nakisa; Langroudi, Lida; Martchenko, Alexandre; So, Vincent; Macpherson, Neil N.; Mitchell, Jennifer A.

2017-01-01

Transcriptional enhancers are critical for maintaining cell-type–specific gene expression and driving cell fate changes during development. Highly transcribed genes are often associated with a cluster of individual enhancers such as those found in locus control regions. Recently, these have been termed stretch enhancers or super-enhancers, which have been predicted to regulate critical cell identity genes. We employed a CRISPR/Cas9-mediated deletion approach to study the function of several enhancer clusters (ECs) and isolated enhancers in mouse embryonic stem (ES) cells. Our results reveal that the effect of deleting ECs, also classified as ES cell super-enhancers, is highly variable, resulting in target gene expression reductions ranging from 12% to as much as 92%. Partial deletions of these ECs which removed only one enhancer or a subcluster of enhancers revealed partially redundant control of the regulated gene by multiple enhancers within the larger cluster. Many highly transcribed genes in ES cells are not associated with a super-enhancer; furthermore, super-enhancer predictions ignore 81% of the potentially active regulatory elements predicted by cobinding of five or more pluripotency-associated transcription factors. Deletion of these additional enhancer regions revealed their robust regulatory role in gene transcription. In addition, select super-enhancers and enhancers were identified that regulated clusters of paralogous genes. We conclude that, whereas robust transcriptional output can be achieved by an isolated enhancer, clusters of enhancers acting on a common target gene act in a partially redundant manner to fine tune transcriptional output of their target genes. PMID:27895109

Enhancing robustness and immunization in geographical networks

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

Huang Liang; Department of Physics, Lanzhou University, Lanzhou 730000; Yang Kongqing

2007-03-15

We find that different geographical structures of networks lead to varied percolation thresholds, although these networks may have similar abstract topological structures. Thus, strategies for enhancing robustness and immunization of a geographical network are proposed. Using the generating function formalism, we obtain an explicit form of the percolation threshold q{sub c} for networks containing arbitrary order cycles. For three-cycles, the dependence of q{sub c} on the clustering coefficients is ascertained. The analysis substantiates the validity of the strategies with analytical evidence.

Robust synchronization of spin-torque oscillators with an LCR load.

PubMed

Pikovsky, Arkady

2013-09-01

We study dynamics of a serial array of spin-torque oscillators with a parallel inductor-capacitor-resistor (LCR) load. In a large range of parameters the fully synchronous regime, where all the oscillators have the same state and the output field is maximal, is shown to be stable. However, not always such a robust complete synchronization develops from a random initial state; in many cases nontrivial clustering is observed, with a partial synchronization resulting in a quasiperiodic or chaotic mean-field dynamics.

MICCA: a complete and accurate software for taxonomic profiling of metagenomic data.

PubMed

Albanese, Davide; Fontana, Paolo; De Filippo, Carlotta; Cavalieri, Duccio; Donati, Claudio

2015-05-19

The introduction of high throughput sequencing technologies has triggered an increase of the number of studies in which the microbiota of environmental and human samples is characterized through the sequencing of selected marker genes. While experimental protocols have undergone a process of standardization that makes them accessible to a large community of scientist, standard and robust data analysis pipelines are still lacking. Here we introduce MICCA, a software pipeline for the processing of amplicon metagenomic datasets that efficiently combines quality filtering, clustering of Operational Taxonomic Units (OTUs), taxonomy assignment and phylogenetic tree inference. MICCA provides accurate results reaching a good compromise among modularity and usability. Moreover, we introduce a de-novo clustering algorithm specifically designed for the inference of Operational Taxonomic Units (OTUs). Tests on real and synthetic datasets shows that thanks to the optimized reads filtering process and to the new clustering algorithm, MICCA provides estimates of the number of OTUs and of other common ecological indices that are more accurate and robust than currently available pipelines. Analysis of public metagenomic datasets shows that the higher consistency of results improves our understanding of the structure of environmental and human associated microbial communities. MICCA is an open source project.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks.

PubMed

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-03-20

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks

PubMed Central

Fu, Pengcheng; Cheng, Yongbo; Tang, Hongying; Li, Baoqing; Pei, Jun; Yuan, Xiaobing

2017-01-01

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods. PMID:28335537

Designing a robust activity recognition framework for health and exergaming using wearable sensors.

PubMed

Alshurafa, Nabil; Xu, Wenyao; Liu, Jason J; Huang, Ming-Chun; Mortazavi, Bobak; Roberts, Christian K; Sarrafzadeh, Majid

2014-09-01

Detecting human activity independent of intensity is essential in many applications, primarily in calculating metabolic equivalent rates and extracting human context awareness. Many classifiers that train on an activity at a subset of intensity levels fail to recognize the same activity at other intensity levels. This demonstrates weakness in the underlying classification method. Training a classifier for an activity at every intensity level is also not practical. In this paper, we tackle a novel intensity-independent activity recognition problem where the class labels exhibit large variability, the data are of high dimensionality, and clustering algorithms are necessary. We propose a new robust stochastic approximation framework for enhanced classification of such data. Experiments are reported using two clustering techniques, K-Means and Gaussian Mixture Models. The stochastic approximation algorithm consistently outperforms other well-known classification schemes which validate the use of our proposed clustered data representation. We verify the motivation of our framework in two applications that benefit from intensity-independent activity recognition. The first application shows how our framework can be used to enhance energy expenditure calculations. The second application is a novel exergaming environment aimed at using games to reward physical activity performed throughout the day, to encourage a healthy lifestyle.

MICCA: a complete and accurate software for taxonomic profiling of metagenomic data

PubMed Central

Albanese, Davide; Fontana, Paolo; De Filippo, Carlotta; Cavalieri, Duccio; Donati, Claudio

2015-01-01

The introduction of high throughput sequencing technologies has triggered an increase of the number of studies in which the microbiota of environmental and human samples is characterized through the sequencing of selected marker genes. While experimental protocols have undergone a process of standardization that makes them accessible to a large community of scientist, standard and robust data analysis pipelines are still lacking. Here we introduce MICCA, a software pipeline for the processing of amplicon metagenomic datasets that efficiently combines quality filtering, clustering of Operational Taxonomic Units (OTUs), taxonomy assignment and phylogenetic tree inference. MICCA provides accurate results reaching a good compromise among modularity and usability. Moreover, we introduce a de-novo clustering algorithm specifically designed for the inference of Operational Taxonomic Units (OTUs). Tests on real and synthetic datasets shows that thanks to the optimized reads filtering process and to the new clustering algorithm, MICCA provides estimates of the number of OTUs and of other common ecological indices that are more accurate and robust than currently available pipelines. Analysis of public metagenomic datasets shows that the higher consistency of results improves our understanding of the structure of environmental and human associated microbial communities. MICCA is an open source project. PMID:25988396

Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

USGS Publications Warehouse

Safner, T.; Miller, M.P.; McRae, B.H.; Fortin, M.-J.; Manel, S.

2011-01-01

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

Sickle cell disease in the Kurdish population of northern Iraq.

PubMed

Al-Allawi, Nasir A S; Jalal, Sana D; Nerwey, Farida F; Al-Sayan, Galawezh O O; Al-Zebari, Sahima S M; Alshingaly, Awny A; Markous, Raji D; Jubrael, Jaladet M S; Hamamy, Hanan

2012-01-01

Epidemiological studies have revealed that sickle cell disease patients are clustered in two geographical areas in Iraq, one among the Arabs in the extreme south, another among the Kurdish population in the extreme north, where they constitute major health problems. However, no studies have focused on the genotypes responsible for sickle cell disease or the β-globin gene haplotypes associated with it. For the latter purpose, a total of 103 unrelated Kurdish sickle cell disease patients were evaluated by restriction fragment length polymorphism (RFLP) for the sickle cell mutation, followed by multiplex polymerase chain reaction (PCR) and reverse hybridization for β- and α-thalassemia (β- and α-thal) mutations, whenever indicated. Results showed that the most common genotype was sickle cell anemia (68.0%) followed by Hb S/β(0)-thal and Hb S/β(+)-thal at frequencies of 24.2 and 7.8%, respectively. Eight β-thal mutations were associated with the latter two genotypes including: IVS-II-1 (G>A), IVS-I-110 (G>A), codon 8 (-AA), codon 44 (-C), codon 22 (-7 bp), IVS-I-1 (G>A), codon 30 (G>C) and IVS-I-6 (T>C). In Hb SS patients, the -α(3.7) deletion was documented in 10.0% and was the only α-thal mutation detected. Furthermore, 5' β-globin gene cluster haplotyping of 128 β(S) chromosomes revealed that the most common haplotype seen in 69.5% was the Benin haplotype, followed by the Arab-Indian haplotype in 12.5%. These latter findings closely resemble reports from neighboring Turkey, Syria, Jordan, Lebanon and Mediterranean countries, suggesting a possible common origin, but are in contrast to findings from the Eastern Arabian Peninsula and Iran.

Relevance and Diversity of Nitrospira Populations in Biofilters of Brackish RAS

PubMed Central

Kruse, Myriam; Keuter, Sabine; Bakker, Evert; Spieck, Eva; Eggers, Till; Lipski, André

2013-01-01

Lithoautotrophic nitrite-oxidizing bacterial populations from moving-bed biofilters of brackish recirculation aquaculture systems (RAS; shrimp and barramundi) were tested for their metabolic activity and phylogenetic diversity. Samples from the biofilters were labeled with 13C-bicarbonate and supplemented with nitrite at concentrations of 0.3, 3 and 10 mM, and incubated at 17 and 28°C, respectively. The biofilm material was analyzed by fatty acid methyl ester - stable isotope probing (FAME-SIP). High portions of up to 45% of Nitrospira-related labeled lipid markers were found confirming that Nitrospira is the major autotrophic nitrite oxidizer in these brackish systems with high nitrogen loads. Other nitrite-oxidizing bacteria such as Nitrobacter or Nitrotoga were functionally not relevant in the investigated biofilters. Nitrospira-related 16S rRNA gene sequences were obtained from the samples with 10 mM nitrite and analyzed by a cloning approach. Sequence studies revealed four different phylogenetic clusters within the marine sublineage IV of Nitrospira, though most sequences clustered with the type strain of Nitrospira marina and with a strain isolated from a marine RAS. Three lipids dominated the whole fatty acid profiles of nitrite-oxidizing marine and brackish enrichments of Nitrospira sublineage IV organisms. The membranes included two marker lipids (16∶1 cis7 and 16∶1 cis11) combined with the non-specific acid 16∶0 as major compounds and confirmed these marker lipids as characteristic for sublineage IV species. The predominant labeling of these characteristic fatty acids and the phylogenetic sequence analyses of the marine Nitrospira sublineage IV identified organisms of this sublineage as main autotrophic nitrite-oxidizers in the investigated brackish biofilter systems. PMID:23705006

Cluster analysis of Southeastern U.S. climate stations

NASA Astrophysics Data System (ADS)

Stooksbury, D. E.; Michaels, P. J.

1991-09-01

A two-step cluster analysis of 449 Southeastern climate stations is used to objectively determine general climate clusters (groups of climate stations) for eight southeastern states. The purpose is objectively to define regions of climatic homogeneity that should perform more robustly in subsequent climatic impact models. This type of analysis has been successfully used in many related climate research problems including the determination of corn/climate districts in Iowa (Ortiz-Valdez, 1985) and the classification of synoptic climate types (Davis, 1988). These general climate clusters may be more appropriate for climate research than the standard climate divisions (CD) groupings of climate stations, which are modifications of the agro-economic United States Department of Agriculture crop reporting districts. Unlike the CD's, these objectively determined climate clusters are not restricted by state borders and thus have reduced multicollinearity which makes them more appropriate for the study of the impact of climate and climatic change.

Using cluster analysis to organize and explore regional GPS velocities

USGS Publications Warehouse

Simpson, Robert W.; Thatcher, Wayne; Savage, James C.

2012-01-01

Cluster analysis offers a simple visual exploratory tool for the initial investigation of regional Global Positioning System (GPS) velocity observations, which are providing increasingly precise mappings of actively deforming continental lithosphere. The deformation fields from dense regional GPS networks can often be concisely described in terms of relatively coherent blocks bounded by active faults, although the choice of blocks, their number and size, can be subjective and is often guided by the distribution of known faults. To illustrate our method, we apply cluster analysis to GPS velocities from the San Francisco Bay Region, California, to search for spatially coherent patterns of deformation, including evidence of block-like behavior. The clustering process identifies four robust groupings of velocities that we identify with four crustal blocks. Although the analysis uses no prior geologic information other than the GPS velocities, the cluster/block boundaries track three major faults, both locked and creeping.

Automating the expert consensus paradigm for robust lung tissue classification

NASA Astrophysics Data System (ADS)

Rajagopalan, Srinivasan; Karwoski, Ronald A.; Raghunath, Sushravya; Bartholmai, Brian J.; Robb, Richard A.

2012-03-01

Clinicians confirm the efficacy of dynamic multidisciplinary interactions in diagnosing Lung disease/wellness from CT scans. However, routine clinical practice cannot readily accomodate such interactions. Current schemes for automating lung tissue classification are based on a single elusive disease differentiating metric; this undermines their reliability in routine diagnosis. We propose a computational workflow that uses a collection (#: 15) of probability density functions (pdf)-based similarity metrics to automatically cluster pattern-specific (#patterns: 5) volumes of interest (#VOI: 976) extracted from the lung CT scans of 14 patients. The resultant clusters are refined for intra-partition compactness and subsequently aggregated into a super cluster using a cluster ensemble technique. The super clusters were validated against the consensus agreement of four clinical experts. The aggregations correlated strongly with expert consensus. By effectively mimicking the expertise of physicians, the proposed workflow could make automation of lung tissue classification a clinical reality.

Bimetallic Ag-Pt Sub-nanometer Supported Clusters as Highly Efficient and Robust Oxidation Catalysts

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

Negreiros, Fabio R.; Halder, Avik; Yin, Chunrong

A combined experimental and theoretical investigation of Ag-Pt sub-nanometer clusters as heterogeneous catalysts in the CO -> CO2 reaction (COox) is presented. Ag9Pt2 and Ag9Pt3 clusters are size-selected in the gas phase, deposited on an ultrathin amorphous alumina support, and tested as catalysts experimentally under realistic conditions and by first-principles simulations at realistic coverage. Insitu GISAXS/TPRx demonstrates that the clusters do not sinter or deactivate even after prolonged exposure to reactants at high temperature, and present comparable, extremely high COox catalytic efficiency. Such high activity and stability are ascribed to a synergic role of Ag and Pt in ultranano-aggregates, inmore » which Pt anchors the clusters to the support and binds and activates two CO molecules, while Ag binds and activates O-2, and Ag/Pt surface proximity disfavors poisoning by CO or oxidized species.« less

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma.

PubMed

Klett, Hagen; Fuellgraf, Hannah; Levit-Zerdoun, Ella; Hussung, Saskia; Kowar, Silke; Küsters, Simon; Bronsert, Peter; Werner, Martin; Wittel, Uwe; Fritsch, Ralph; Busch, Hauke; Boerries, Melanie

2018-01-01

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic.

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma

PubMed Central

Klett, Hagen; Fuellgraf, Hannah; Levit-Zerdoun, Ella; Hussung, Saskia; Kowar, Silke; Küsters, Simon; Bronsert, Peter; Werner, Martin; Wittel, Uwe; Fritsch, Ralph; Busch, Hauke; Boerries, Melanie

2018-01-01

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic. PMID:29675033

Locally Weighted Ensemble Clustering.

PubMed

Huang, Dong; Wang, Chang-Dong; Lai, Jian-Huang

2018-05-01

Due to its ability to combine multiple base clusterings into a probably better and more robust clustering, the ensemble clustering technique has been attracting increasing attention in recent years. Despite the significant success, one limitation to most of the existing ensemble clustering methods is that they generally treat all base clusterings equally regardless of their reliability, which makes them vulnerable to low-quality base clusterings. Although some efforts have been made to (globally) evaluate and weight the base clusterings, yet these methods tend to view each base clustering as an individual and neglect the local diversity of clusters inside the same base clustering. It remains an open problem how to evaluate the reliability of clusters and exploit the local diversity in the ensemble to enhance the consensus performance, especially, in the case when there is no access to data features or specific assumptions on data distribution. To address this, in this paper, we propose a novel ensemble clustering approach based on ensemble-driven cluster uncertainty estimation and local weighting strategy. In particular, the uncertainty of each cluster is estimated by considering the cluster labels in the entire ensemble via an entropic criterion. A novel ensemble-driven cluster validity measure is introduced, and a locally weighted co-association matrix is presented to serve as a summary for the ensemble of diverse clusters. With the local diversity in ensembles exploited, two novel consensus functions are further proposed. Extensive experiments on a variety of real-world datasets demonstrate the superiority of the proposed approach over the state-of-the-art.

Major cluster mergers and the location of the brightest cluster galaxy

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

Martel, Hugo; Robichaud, Fidèle; Barai, Paramita, E-mail: Hugo.Martel@phy.ulaval.ca

Using a large N-body cosmological simulation combined with a subgrid treatment of galaxy formation, merging, and tidal destruction, we study the formation and evolution of the galaxy and cluster population in a comoving volume (100 Mpc){sup 3} in a ΛCDM universe. At z = 0, our computational volume contains 1788 clusters with mass M {sub cl} > 1.1 × 10{sup 12} M {sub ☉}, including 18 massive clusters with M {sub cl} > 10{sup 14} M {sub ☉}. It also contains 1, 088, 797 galaxies with mass M {sub gal} ≥ 2 × 10{sup 9} M {sub ☉} and luminositymore » L > 9.5 × 10{sup 5} L {sub ☉}. For each cluster, we identified the brightest cluster galaxy (BCG). We then computed two separate statistics: the fraction f {sub BNC} of clusters in which the BCG is not the closest galaxy to the center of the cluster in projection, and the ratio Δv/σ, where Δv is the difference in radial velocity between the BCG and the whole cluster and σ is the radial velocity dispersion of the cluster. We found that f {sub BNC} increases from 0.05 for low-mass clusters (M {sub cl} ∼ 10{sup 12} M {sub ☉}) to 0.5 for high-mass clusters (M {sub cl} > 10{sup 14} M {sub ☉}) with very little dependence on cluster redshift. Most of this result turns out to be a projection effect and when we consider three-dimensional distances instead of projected distances, f {sub BNC} increases only to 0.2 at high-cluster mass. The values of Δv/σ vary from 0 to 1.8, with median values in the range 0.03-0.15 when considering all clusters, and 0.12-0.31 when considering only massive clusters. These results are consistent with previous observational studies and indicate that the central galaxy paradigm, which states that the BCG should be at rest at the center of the cluster, is usually valid, but exceptions are too common to be ignored. We built merger trees for the 18 most massive clusters in the simulation. Analysis of these trees reveal that 16 of these clusters have experienced 1 or several major or semi-major mergers in the past. These mergers leave each cluster in a non-equilibrium state, but eventually the cluster settles into an equilibrium configuration, unless it is disturbed by another major or semi-major merger. We found evidence that these mergers are responsible for the off-center positions and peculiar velocities of some BCGs. Our results thus support the merging-group scenario, in which some clusters form by the merging of smaller groups in which the galaxies have already formed, including the galaxy destined to become the BCG. Finally, we argue that f {sub BNC} is not a very robust statistics, as it is very sensitive to projection and selection effects, but that Δv/σ is more robust. Still, both statistics exhibit a signature of major mergers between clusters of galaxies.« less

MULTI-K: accurate classification of microarray subtypes using ensemble k-means clustering

PubMed Central

Kim, Eun-Youn; Kim, Seon-Young; Ashlock, Daniel; Nam, Dougu

2009-01-01

Background Uncovering subtypes of disease from microarray samples has important clinical implications such as survival time and sensitivity of individual patients to specific therapies. Unsupervised clustering methods have been used to classify this type of data. However, most existing methods focus on clusters with compact shapes and do not reflect the geometric complexity of the high dimensional microarray clusters, which limits their performance. Results We present a cluster-number-based ensemble clustering algorithm, called MULTI-K, for microarray sample classification, which demonstrates remarkable accuracy. The method amalgamates multiple k-means runs by varying the number of clusters and identifies clusters that manifest the most robust co-memberships of elements. In addition to the original algorithm, we newly devised the entropy-plot to control the separation of singletons or small clusters. MULTI-K, unlike the simple k-means or other widely used methods, was able to capture clusters with complex and high-dimensional structures accurately. MULTI-K outperformed other methods including a recently developed ensemble clustering algorithm in tests with five simulated and eight real gene-expression data sets. Conclusion The geometric complexity of clusters should be taken into account for accurate classification of microarray data, and ensemble clustering applied to the number of clusters tackles the problem very well. The C++ code and the data sets tested are available from the authors. PMID:19698124

Comparison of Clustering Techniques for Residential Energy Behavior using Smart Meter Data

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

Jin, Ling; Lee, Doris; Sim, Alex

Current practice in whole time series clustering of residential meter data focuses on aggregated or subsampled load data at the customer level, which ignores day-to-day differences within customers. This information is critical to determine each customer’s suitability to various demand side management strategies that support intelligent power grids and smart energy management. Clustering daily load shapes provides fine-grained information on customer attributes and sources of variation for subsequent models and customer segmentation. In this paper, we apply 11 clustering methods to daily residential meter data. We evaluate their parameter settings and suitability based on 6 generic performance metrics and post-checkingmore » of resulting clusters. Finally, we recommend suitable techniques and parameters based on the goal of discovering diverse daily load patterns among residential customers. To the authors’ knowledge, this paper is the first robust comparative review of clustering techniques applied to daily residential load shape time series in the power systems’ literature.« less

Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.

PubMed

Paraskevopoulou, Sivylla E; Wu, Di; Eftekhar, Amir; Constandinou, Timothy G

2014-09-30

This work presents a novel unsupervised algorithm for real-time adaptive clustering of neural spike data (spike sorting). The proposed Hierarchical Adaptive Means (HAM) clustering method combines centroid-based clustering with hierarchical cluster connectivity to classify incoming spikes using groups of clusters. It is described how the proposed method can adaptively track the incoming spike data without requiring any past history, iteration or training and autonomously determines the number of spike classes. Its performance (classification accuracy) has been tested using multiple datasets (both simulated and recorded) achieving a near-identical accuracy compared to k-means (using 10-iterations and provided with the number of spike classes). Also, its robustness in applying to different feature extraction methods has been demonstrated by achieving classification accuracies above 80% across multiple datasets. Last but crucially, its low complexity, that has been quantified through both memory and computation requirements makes this method hugely attractive for future hardware implementation. Copyright © 2014 Elsevier B.V. All rights reserved.

Detecting synchronization clusters in multivariate time series via coarse-graining of Markov chains.

PubMed

Allefeld, Carsten; Bialonski, Stephan

2007-12-01

Synchronization cluster analysis is an approach to the detection of underlying structures in data sets of multivariate time series, starting from a matrix R of bivariate synchronization indices. A previous method utilized the eigenvectors of R for cluster identification, analogous to several recent attempts at group identification using eigenvectors of the correlation matrix. All of these approaches assumed a one-to-one correspondence of dominant eigenvectors and clusters, which has however been shown to be wrong in important cases. We clarify the usefulness of eigenvalue decomposition for synchronization cluster analysis by translating the problem into the language of stochastic processes, and derive an enhanced clustering method harnessing recent insights from the coarse-graining of finite-state Markov processes. We illustrate the operation of our method using a simulated system of coupled Lorenz oscillators, and we demonstrate its superior performance over the previous approach. Finally we investigate the question of robustness of the algorithm against small sample size, which is important with regard to field applications.

A uniform metallicity in the outskirts of massive, nearby galaxy clusters

DOE PAGES

Urban, O.; Werner, N.; Allen, S. W.; ...

2017-06-20

Suzaku measurements of a homogeneous metal distribution of Z ~ 0:3 Solar in the outskirts of the nearby Perseus cluster suggest that chemical elements were deposited and mixed into the intergalactic medium before clusters formed, likely over 10 billion years ago. A key prediction of this early enrichment scenario is that the intracluster medium in all massive clusters should be uniformly enriched to a similar level. Here, we confirm this prediction by determining the iron abundances in the outskirts (r > 0:25r200) of a sample of ten other nearby galaxy clusters observed with Suzaku for which robust measurements based onmore » the Fe-K lines can be made. Across our sample the iron abundances are consistent with a constant value, ZFe = 0:316 ± 0:012 Solar (Χ 2 = 28:85 for 25 degrees of freedom). This is remarkably similar to the measurements for the Perseus cluster of ZFe = 0:314±0:012 Solar, using the Solar abundance scale of Asplund et al. (2009).« less

Evidence that 50% of BALQSO Outflows Are Situated at Least 100 pc from the Central Source

NASA Astrophysics Data System (ADS)

Arav, Nahum; Liu, Guilin; Xu, Xinfeng; Stidham, James; Benn, Chris; Chamberlain, Carter

2018-04-01

The most robust way for determining the distance of quasar absorption outflows is the use of troughs from ionic excited states. The column density ratio between the excited and resonance states yields the outflow number density. Combined with a knowledge of the outflow’s ionization parameter, a distance from the central source (R) can be determined. Here we report results from two surveys targeting outflows that show troughs from S IV. One survey includes 1091 SDSS and BOSS quasar spectra, and the other includes higher-quality spectra of 13 quasars observed with the Very Large Telescope. Our S IV samples include 38 broad absorption line (BAL) outflows and four mini-BAL outflows. The S IV is formed in the same physical region of the outflow as the canonical outflow-identifying species C IV. Our results show that S IV absorption is only detected in 25% of C IV BAL outflows. The smaller detection fraction is due to the higher total column density (N H) needed to detect S IV absorption. Since R empirically anticorrelates with N H, the results of these surveys can be extrapolated to C IV quasar outflows with lower N H as well. We find that at least 50% of quasar outflows are at distances larger than 100 pc from the central source, and at least 12% are at distances larger than 1000 pc. These results have profound implications for the study of the origin and acceleration mechanism of quasar outflows and their effects on the host galaxy.

Cross-cultural reliability and validity of ADHD assessed by the ADHD Rating Scale in a pan-European study.

PubMed

Döpfner, Manfred; Steinhausen, Hans-Christoph; Coghill, David; Dalsgaard, Søren; Poole, Lynne; Ralston, Stephen J; Rothenberger, Aribert

2006-12-01

To provide psychometric information on the Attention-Deficit/Hyperactivity Disorder (ADHD) Rating Scale-IV (ADHD-RS-IV) in a large population of children with ADHD. Patients aged 6-18 years (n=1,478 in baseline analysis) were rated by 244 physicians on the ADHD-RS-IV based on a semi-structured interview with the patient's parent. Physicians additionally rated functional impairment (CGAS) and health status (CGI-S), and parents rated their child's behavioural and emotional problems (SDQ) and quality of life (CHIP-CE). Inattention and hyperactivity-impulsivity as dimensions of ADHD were replicated. 3-factor solutions reflecting the ICD-10 definition, with hyperactivity, impulsivity and inattention as separate dimensions were extracted in some national sub-samples and in separate analyses for boys and younger children.Good internal consistencies, strong country effects and small effects of age were found. Based on ADHD-RS-IV, 88.5% of patients met the criteria for any ADHD diagnosis. Correlations between ADHD-RS-IV and measures of functional impairment were low but statistically significant. The correlations with SDQ and CHIP-CE scales confirm the convergent and divergent validity of ADHD-RS-IV. Impressive evidence for the cross-cultural factorial validity, internal consistency as well as convergent and divergent validity of ADHD-RS-IV was found. ADHD can be assessed reliably and validly in routine care across Europe. The ICD-10 3-factor model seems to be less robust than the DSM-IV 2-factor model, but may be a good description for special populations (boys, younger children).

RRW: repeated random walks on genome-scale protein networks for local cluster discovery

PubMed Central

Macropol, Kathy; Can, Tolga; Singh, Ambuj K

2009-01-01

Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW) for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL), and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters. PMID:19740439

Extraction behaviour and mechanism of Pt(iv) and Pd(ii) by liquid-liquid extraction with an ionic liquid [HBBIm]Br.

PubMed

Liu, Wenhui; Wang, Qi; Zheng, Yan; Wang, Shubin; Yan, Yan; Yang, Yanzhao

2017-06-06

In this study, a method of one-step separation and recycling of high purity Pd(ii) and Pt(iv) using an ionic liquid, 1-butyl-3-benzimidazolium bromate ([HBBIm]Br), was investigated. The effects of [HBBIm]Br concentration, initial metal concentration, and loading capacity of [HBBIm]Br were examined in detail. It was observed that [HBBIm]Br was a very effective extractant for selectively extracting Pd(ii) and precipitating Pt(iv). Through selectively extracting Pd(ii) and precipitating Pt(iv), each metal with high purity was separately obtained from mixed Pd(ii) and Pt(iv) multi-metal solution. The method of one-step separation of Pd(ii) and Pt(iv) is simple and convenient. The anion exchange mechanism between [HBBIm]Br and Pt(iv) was proven through Job's method and FTIR and 1 H NMR spectroscopies. The coordination mechanism between [HBBIm]Br and Pd(ii) was demonstrated via single X-ray diffraction and was found to be robust and distinct, as supported by the ab initio quantum-chemical studies. The crystals of the [PdBr 2 ·2BBIm] complex were formed first. Moreover, the influence of the concentrations of hydrochloric acid, sodium chloride, and sodium nitrate on the precipitation of Pt(iv) and extraction of Pd(ii) was studied herein. It was found that only the concentration of H + could inhibit the separation of Pt(iv) because H + could attract the anion PtCl 6 2- ; thus, the exchange (anion exchange mechanism) between the anions PtCl 6 2- and Br - was prevented. However, both the concentration of H + and Cl - can obviously inhibit the extraction of Pd(ii) because H + and Cl - are the reaction products and increasing their concentration can inhibit the progress of the reaction (coordination mechanism).

A Self-Adaptive Fuzzy c-Means Algorithm for Determining the Optimal Number of Clusters

PubMed Central

Wang, Zhihao; Yi, Jing

2016-01-01

For the shortcoming of fuzzy c-means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The algorithm, according to the characteristics of the dataset, automatically determined the possible maximum number of clusters instead of using the empirical rule n and obtained the optimal initial cluster centroids, improving the limitation of FCM that randomly selected cluster centroids lead the convergence result to the local minimum. Secondly, this paper, by introducing a penalty function, proposed a new fuzzy clustering validity index based on fuzzy compactness and separation, which ensured that when the number of clusters verged on that of objects in the dataset, the value of clustering validity index did not monotonically decrease and was close to zero, so that the optimal number of clusters lost robustness and decision function. Then, based on these studies, a self-adaptive FCM algorithm was put forward to estimate the optimal number of clusters by the iterative trial-and-error process. At last, experiments were done on the UCI, KDD Cup 1999, and synthetic datasets, which showed that the method not only effectively determined the optimal number of clusters, but also reduced the iteration of FCM with the stable clustering result. PMID:28042291

Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise

NASA Astrophysics Data System (ADS)

Brekhna, Brekhna; Mahmood, Arif; Zhou, Yuanfeng; Zhang, Caiming

2017-11-01

Superpixels have gradually become popular in computer vision and image processing applications. However, no comprehensive study has been performed to evaluate the robustness of superpixel algorithms in regard to common forms of noise in natural images. We evaluated the robustness of 11 recently proposed algorithms to different types of noise. The images were corrupted with various degrees of Gaussian blur, additive white Gaussian noise, and impulse noise that either made the object boundaries weak or added extra information to it. We performed a robustness analysis of simple linear iterative clustering (SLIC), Voronoi Cells (VCells), flooding-based superpixel generation (FCCS), bilateral geodesic distance (Bilateral-G), superpixel via geodesic distance (SSS-G), manifold SLIC (M-SLIC), Turbopixels, superpixels extracted via energy-driven sampling (SEEDS), lazy random walk (LRW), real-time superpixel segmentation by DBSCAN clustering, and video supervoxels using partially absorbing random walks (PARW) algorithms. The evaluation process was carried out both qualitatively and quantitatively. For quantitative performance comparison, we used achievable segmentation accuracy (ASA), compactness, under-segmentation error (USE), and boundary recall (BR) on the Berkeley image database. The results demonstrated that all algorithms suffered performance degradation due to noise. For Gaussian blur, Bilateral-G exhibited optimal results for ASA and USE measures, SLIC yielded optimal compactness, whereas FCCS and DBSCAN remained optimal for BR. For the case of additive Gaussian and impulse noises, FCCS exhibited optimal results for ASA, USE, and BR, whereas Bilateral-G remained a close competitor in ASA and USE for Gaussian noise only. Additionally, Turbopixel demonstrated optimal performance for compactness for both types of noise. Thus, no single algorithm was able to yield optimal results for all three types of noise across all performance measures. Conclusively, to solve real-world problems effectively, more robust superpixel algorithms must be developed.

Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks.

PubMed

Wang, Zhaowei; Zeng, Peng; Zhou, Mingtuo; Li, Dong; Wang, Jintao

2017-01-13

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs' demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays.

Cluster-Based Maximum Consensus Time Synchronization for Industrial Wireless Sensor Networks †

PubMed Central

Wang, Zhaowei; Zeng, Peng; Zhou, Mingtuo; Li, Dong; Wang, Jintao

2017-01-01

Time synchronization is one of the key technologies in Industrial Wireless Sensor Networks (IWSNs), and clustering is widely used in WSNs for data fusion and information collection to reduce redundant data and communication overhead. Considering IWSNs’ demand for low energy consumption, fast convergence, and robustness, this paper presents a novel Cluster-based Maximum consensus Time Synchronization (CMTS) method. It consists of two parts: intra-cluster time synchronization and inter-cluster time synchronization. Based on the theory of distributed consensus, the proposed method utilizes the maximum consensus approach to realize the intra-cluster time synchronization, and adjacent clusters exchange the time messages via overlapping nodes to synchronize with each other. A Revised-CMTS is further proposed to counteract the impact of bounded communication delays between two connected nodes, because the traditional stochastic models of the communication delays would distort in a dynamic environment. The simulation results show that our method reduces the communication overhead and improves the convergence rate in comparison to existing works, as well as adapting to the uncertain bounded communication delays. PMID:28098750

Detection of the power lines in UAV remote sensed images using spectral-spatial methods.

PubMed

Bhola, Rishav; Krishna, Nandigam Hari; Ramesh, K N; Senthilnath, J; Anand, Gautham

2018-01-15

In this paper, detection of the power lines on images acquired by Unmanned Aerial Vehicle (UAV) based remote sensing is carried out using spectral-spatial methods. Spectral clustering was performed using Kmeans and Expectation Maximization (EM) algorithm to classify the pixels into the power lines and non-power lines. The spectral clustering methods used in this study are parametric in nature, to automate the number of clusters Davies-Bouldin index (DBI) is used. The UAV remote sensed image is clustered into the number of clusters determined by DBI. The k clustered image is merged into 2 clusters (power lines and non-power lines). Further, spatial segmentation was performed using morphological and geometric operations, to eliminate the non-power line regions. In this study, UAV images acquired at different altitudes and angles were analyzed to validate the robustness of the proposed method. It was observed that the EM with spatial segmentation (EM-Seg) performed better than the Kmeans with spatial segmentation (Kmeans-Seg) on most of the UAV images. Copyright © 2017 Elsevier Ltd. All rights reserved.

A modified procedure for mixture-model clustering of regional geochemical data

USGS Publications Warehouse

Ellefsen, Karl J.; Smith, David B.; Horton, John D.

2014-01-01

A modified procedure is proposed for mixture-model clustering of regional-scale geochemical data. The key modification is the robust principal component transformation of the isometric log-ratio transforms of the element concentrations. This principal component transformation and the associated dimension reduction are applied before the data are clustered. The principal advantage of this modification is that it significantly improves the stability of the clustering. The principal disadvantage is that it requires subjective selection of the number of clusters and the number of principal components. To evaluate the efficacy of this modified procedure, it is applied to soil geochemical data that comprise 959 samples from the state of Colorado (USA) for which the concentrations of 44 elements are measured. The distributions of element concentrations that are derived from the mixture model and from the field samples are similar, indicating that the mixture model is a suitable representation of the transformed geochemical data. Each cluster and the associated distributions of the element concentrations are related to specific geologic and anthropogenic features. In this way, mixture model clustering facilitates interpretation of the regional geochemical data.

A Systematic Evaluation of ADHD and Comorbid Psychopathology in a Population-Based Twin Sample

ERIC Educational Resources Information Center

Volk, Heather E.; Neuman, Rosalind J.; Todd, Richard D.

2005-01-01

Objective: Clinical and population samples demonstrate that attention-deficit/hyperactivity disorder (ADHD) occurs with other disorders. Comorbid disorder clustering within ADHD subtypes is not well studied. Method: Latent class analysis (LCA) examined the co-occurrence of DSM-IV ADHD, oppositional defiant disorder (ODD), conduct disorder (CD),…

Navigation of a Satellite Cluster with Realistic Dynamics

DTIC Science & Technology

1991-12-01

20 2.2.1 Dynamics ( Clohessy - Wiltshire Equations) ............ 21 2.2.2 Iterated, Extended Kalman Filter.................26 iv I1l...8 Figure 4. Point mass and Clohessy - Wiltshire orbits (10 orbits) .......... 16 Figure 5. Real dynamics and Clohessy - Wiltshire orbits (10...filter ..... 31 Figure 8. Comparison of the Clohessy - Wiltshire and truth model solutions

The properties of clusters in the gas phase. IV - Complexes of H2O and HNOx clustering on NOx/-/

NASA Technical Reports Server (NTRS)

Lee, N.; Castleman, A. W., Jr.; Keesee, R. G.

1980-01-01

Thermodynamic quantities for the gas-phase clustering equilibria of NO2(-) and NO3(-) were determined with high-pressure mass spectrometry. A comparison of values of the free energy of hydration derived from the data shows good agreement with formerly reported values at 296 K. New data for larger NO2(-) and NO3(-) hydrates as well as NO2(-)(HNO2)n were obtained in this study. To aid in understanding the bonding and stability of the hydrates of nitrite and nitrate ions, CNDO/2 calculations were performed, and the results are discussed. A correlation between the aqueous-phase total hydration enthalpy of a single ion and its gas-phase hydration enthalpy was obtained. Atmospheric implications of the data are also briefly discussed.

Seven-Color Photometry and Classification of Stars in the Direction of Open Cluster M29 (NGC 6913) in Cygnus

DTIC Science & Technology

2013-01-01

Spitzer, 2MASS , VVISE and IPHAS databases is acknowledged. The project is partly supported by the Research Council of Lithuania, grant No. MIP-061/2013...1304. YSO [WISE, IPHAS]; 1305. HD 19򒵺 (A), B5V [5], B8III [6]; 1306. G5III [5[; 1307. WDS 20243+3811 (sep ~ 1.9"); 1313. YSO [ 2MASS , Spitze... 2MASS , IPHAS); 1387. Fl III [!6[; 1391. HD 229261 (B9), BS [5,8], B6II [16], B5IV-V [17[; 1407. F2 [5[; 1408. B3 V [16[; 1419. A2IV [16[; 1427

Robust spike classification based on frequency domain neural waveform features.

PubMed

Yang, Chenhui; Yuan, Yuan; Si, Jennie

2013-12-01

We introduce a new spike classification algorithm based on frequency domain features of the spike snippets. The goal for the algorithm is to provide high classification accuracy, low false misclassification, ease of implementation, robustness to signal degradation, and objectivity in classification outcomes. In this paper, we propose a spike classification algorithm based on frequency domain features (CFDF). It makes use of frequency domain contents of the recorded neural waveforms for spike classification. The self-organizing map (SOM) is used as a tool to determine the cluster number intuitively and directly by viewing the SOM output map. After that, spike classification can be easily performed using clustering algorithms such as the k-Means. In conjunction with our previously developed multiscale correlation of wavelet coefficient (MCWC) spike detection algorithm, we show that the MCWC and CFDF detection and classification system is robust when tested on several sets of artificial and real neural waveforms. The CFDF is comparable to or outperforms some popular automatic spike classification algorithms with artificial and real neural data. The detection and classification of neural action potentials or neural spikes is an important step in single-unit-based neuroscientific studies and applications. After the detection of neural snippets potentially containing neural spikes, a robust classification algorithm is applied for the analysis of the snippets to (1) extract similar waveforms into one class for them to be considered coming from one unit, and to (2) remove noise snippets if they do not contain any features of an action potential. Usually, a snippet is a small 2 or 3 ms segment of the recorded waveform, and differences in neural action potentials can be subtle from one unit to another. Therefore, a robust, high performance classification system like the CFDF is necessary. In addition, the proposed algorithm does not require any assumptions on statistical properties of the noise and proves to be robust under noise contamination.

Screening for PTSD among detained adolescents: Implications of the changes in the DSM-5.

PubMed

Modrowski, Crosby A; Bennett, Diana C; Chaplo, Shannon D; Kerig, Patricia K

2017-01-01

Screening for posttraumatic stress disorder (PTSD) is highly relevant for youth involved in the juvenile justice system given their high rates of trauma exposure and posttraumatic stress symptoms. However, to date, no studies have investigated the implications of the recent revisions to the Diagnostic and Statistical Manual for Mental Disorders (5th ed., DSM-5; American Psychiatric Association [APA], 2013) diagnostic criteria for PTSD for screening in this population. To this end, the present study compared PTSD screening rates using the Diagnostic and Statistical Manual of Mental Disorders (4th ed., text rev., DSM-IV-TR; APA, 2013) versus DSM-5 criteria in a group of detained adolescents. Participants included 209 youth (60 girls) aged 13-19 (M = 15.97, SD = 1.24). Youth completed measures of lifetime trauma exposure and past-month posttraumatic stress symptoms. Over 95% of youth in the sample reported exposure to at least 1 type of traumatic event. Approximately 19.60% of the sample screened positive for PTSD according to the DSM-5 compared to 17.70% according to the DSM-IV-TR. Girls were more likely than boys to screen positive for PTSD according to the DSM-IV-TR compared to the DSM-5. The main factors accounting for the differences in screening rates across the versions of PTSD criteria involved the removal of Criterion A2 from the DSM-5, the separation of avoidance symptoms (Criterion C) into their own cluster, the addition of a cluster involving negative alterations in cognitions and mood (Criterion D), and revisions to the cluster of arousal symptoms (Criterion E). Future research should continue to investigate gender differences in PTSD symptoms in youth and consider the implications of these diagnostic changes for the accurate diagnosis and referral to treatment of adolescents who demonstrate posttraumatic stress reactions. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Spatio-Temporal Clustering of Monitoring Network

NASA Astrophysics Data System (ADS)

Hussain, I.; Pilz, J.

2009-04-01

Pakistan has much diversity in seasonal variation of different locations. Some areas are in desserts and remain very hot and waterless, for example coastal areas are situated along the Arabian Sea and have very warm season and a little rainfall. Some areas are covered with mountains, have very low temperature and heavy rainfall; for instance Karakoram ranges. The most important variables that have an impact on the climate are temperature, precipitation, humidity, wind speed and elevation. Furthermore, it is hard to find homogeneous regions in Pakistan with respect to climate variation. Identification of homogeneous regions in Pakistan can be useful in many aspects. It can be helpful for prediction of the climate in the sub-regions and for optimizing the number of monitoring sites. In the earlier literature no one tried to identify homogeneous regions of Pakistan with respect to climate variation. There are only a few papers about spatio-temporal clustering of monitoring network. Steinhaus (1956) presented the well-known K-means clustering method. It can identify a predefined number of clusters by iteratively assigning centriods to clusters based. Castro et al. (1997) developed a genetic heuristic algorithm to solve medoids based clustering. Their method is based on genetic recombination upon random assorting recombination. The suggested method is appropriate for clustering the attributes which have genetic characteristics. Sap and Awan (2005) presented a robust weighted kernel K-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. Soltani and Modarres (2006) used hierarchical and divisive cluster analysis to categorize patterns of rainfall in Iran. They only considered rainfall at twenty-eight monitoring sites and concluded that eight clusters existed. Soltani and Modarres (2006) classified the sites by using only average rainfall of sites, they did not consider time replications and spatial coordinates. Kerby et.al (2007) purposed spatial clustering method based on likelihood. They took account of the geographic locations through the variance covariance matrix. Their purposed method works like hierarchical clustering methods. Moreovere, it is inappropiriate for time replication data and could not perform well for large number of sites. Tuia.et.al (2008) used scan statistics for identifying spatio-temporal clusters for fire sequences in the Tuscany region in Italy. The scan statistics clustering method was developed by Kulldorff et al. (1997) to detect spatio-temporal clusters in epidemiology and assessing their significance. The purposed scan statistics method is used only for univariate discrete stochastic random variables. In this paper we make use of a very simple approach for spatio-temporal clustering which can create separable and homogeneous clusters. Most of the clustering methods are based on Euclidean distances. It is well known that geographic coordinates are spherical coordinates and estimating Euclidean distances from spherical coordinates is inappropriate. As a transformation from geographic coordinates to rectangular (D-plane) coordinates we use the Lambert projection method. The partition around medoids clustering method is incorporated on the data including D-plane coordinates. Ordinary kriging is taken as validity measure for the precipitation data. The kriging results for clusters are more accurate and have less variation compared to complete monitoring network precipitation data. References Casto.V.E and Murray.A.T (1997). Spatial Clustering with Data Mining with Genetic Algorithms. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.8573 Kaufman.L and Rousseeuw.P.J (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley series of Probability and Mathematical Statistics, New York. Kulldorf.M (1997). A spatial scan statistic. Commun. Stat.-Theor. Math. 26(6), 1481-1496 Kerby. A , Marx. D, Samal. A and Adamchuck. V. (2007). Spatial Clustering Using the Likelihood Function. Seventh IEEE International Conference on Data Mining - Workshops Steinhaus.H (1956). Sur la division des corp materiels en parties. Bull. Acad. Polon. Sci., C1. III vol IV:801- 804 Snyder, J. P. (1987). Map Projection: A Working Manual. U. S. Geological Survey Professional Paper 1395. Washington, DC: U. S. Government Printing Office, pp. 104-110 Sap.M.N and Awan. A.M (2005). Finding Spatio-Temporal Patterns in Climate Data Using Clustering. Proceedings of the International Conference on Cyberworlds (CW'05) Soltani.S and Modarres.R (2006). Classification of Spatio -Temporal Pattern of Rainfall in Iran: Using Hierarchical and Divisive Cluster Analysis. Journal of Spatial Hydrology Vol.6, No.2 Tuia.D, Ratle.F, Lasaponara.R, Telesca.L and Kanevski.M (2008). Scan Statistics Analysis for Forest Fire Clusters. Commun. in Nonlinear science and numerical simulation 13,1689-1694.

Lensing is low: cosmology, galaxy formation or new physics?

NASA Astrophysics Data System (ADS)

Leauthaud, Alexie; Saito, Shun; Hilbert, Stefan; Barreira, Alexandre; More, Surhud; White, Martin; Alam, Shadab; Behroozi, Peter; Bundy, Kevin; Coupon, Jean; Erben, Thomas; Heymans, Catherine; Hildebrandt, Hendrik; Mandelbaum, Rachel; Miller, Lance; Moraes, Bruno; Pereira, Maria E. S.; Rodríguez-Torres, Sergio A.; Schmidt, Fabian; Shan, Huan-Yuan; Viel, Matteo; Villaescusa-Navarro, Francisco

2017-05-01

We present high signal-to-noise galaxy-galaxy lensing measurements of the Baryon Oscillation Spectroscopic Survey constant mass (CMASS) sample using 250 deg2 of weak-lensing data from Canada-France-Hawaii Telescope Lensing Survey and Canada-France-Hawaii Telescope Stripe 82 Survey. We compare this signal with predictions from mock catalogues trained to match observables including the stellar mass function and the projected and two-dimensional clustering of CMASS. We show that the clustering of CMASS, together with standard models of the galaxy-halo connection, robustly predicts a lensing signal that is 20-40 per cent larger than observed. Detailed tests show that our results are robust to a variety of systematic effects. Lowering the value of S_8=σ _8 \\sqrt{Ω _m/0.3} compared to Planck Collaboration XIII reconciles the lensing with clustering. However, given the scale of our measurement (r < 10 h-1 Mpc), other effects may also be at play and need to be taken into consideration. We explore the impact of baryon physics, assembly bias, massive neutrinos and modifications to general relativity on ΔΣ and show that several of these effects may be non-negligible given the precision of our measurement. Disentangling cosmological effects from the details of the galaxy-halo connection, the effect of baryons, and massive neutrinos, is the next challenge facing joint lensing and clustering analyses. This is especially true in the context of large galaxy samples from Baryon Acoustic Oscillation surveys with precise measurements but complex selection functions.

Essential core of the Hawking–Ellis types

NASA Astrophysics Data System (ADS)

Martín-Moruno, Prado; Visser, Matt

2018-06-01

The Hawking–Ellis (Segre–Plebański) classification of possible stress–energy tensors is an essential tool in analyzing the implications of the Einstein field equations in a more-or-less model-independent manner. In the current article the basic idea is to simplify the Hawking–Ellis type I, II, III, and IV classification by isolating the ‘essential core’ of the type II, type III, and type IV stress–energy tensors; this being done by subtracting (special cases of) type I to simplify the (Lorentz invariant) eigenvalue structure as much as possible without disturbing the eigenvector structure. We will denote these ‘simplified cores’ type II0, type III0, and type IV0. These ‘simplified cores’ have very nice and simple algebraic properties. Furthermore, types I and II0 have very simple classical interpretations, while type IV0 is known to arise semi-classically (in renormalized expectation values of standard stress–energy tensors). In contrast type III0 stands out in that it has neither a simple classical interpretation, nor even a simple semi-classical interpretation. We will also consider the robustness of this classification considering the stability of the different Hawking–Ellis types under perturbations. We argue that types II and III are definitively unstable, whereas types I and IV are stable.

GENES AS INSTRUMENTS FOR STUDYING RISK BEHAVIOR EFFECTS: AN APPLICATION TO MATERNAL SMOKING AND OROFACIAL CLEFTS

PubMed Central

Jugessur, Astanand; Murray, Jeffrey C.; Moreno, Lina; Wilcox, Allen; Lie, Rolv T.

2011-01-01

This study uses instrumental variable (IV) models with genetic instruments to assess the effects of maternal smoking on the child’s risk of orofacial clefts (OFC), a common birth defect. The study uses genotypic variants in neurotransmitter and detoxification genes relateded to smoking as instruments for cigarette smoking before and during pregnancy. Conditional maximum likelihood and two-stage IV probit models are used to estimate the IV model. The data are from a population-level sample of affected and unaffected children in Norway. The selected genetic instruments generally fit the IV assumptions but may be considered “weak” in predicting cigarette smoking. We find that smoking before and during pregnancy increases OFC risk substantially under the IV model (by about 4–5 times at the sample average smoking rate). This effect is greater than that found with classical analytic models. This may be because the usual models are not able to consider self-selection into smoking based on unobserved confounders, or it may to some degree reflect limitations of the instruments. Inference based on weak-instrument robust confidence bounds is consistent with standard inference. Genetic instruments may provide a valuable approach to estimate the “causal” effects of risk behaviors with genetic-predisposing factors (such as smoking) on health and socioeconomic outcomes. PMID:22102793

ON THE CLUSTERING OF SUBMILLIMETER GALAXIES

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

Williams, Christina C.; Giavalisco, Mauro; Yun, Min S.

2011-06-01

We measure the angular two-point correlation function of submillimeter galaxies (SMGs) from 1.1 mm imaging of the COSMOS field with the AzTEC camera and ASTE 10 m telescope. These data yield one of the largest contiguous samples of SMGs to date, covering an area of 0.72 deg{sup 2} down to a 1.26 mJy beam{sup -1} (1{sigma}) limit, including 189 (328) sources with S/N {>=}3.5 (3). We can only set upper limits to the correlation length r{sub 0}, modeling the correlation function as a power law with pre-assigned slope. Assuming existing redshift distributions, we derive 68.3% confidence level upper limits ofmore » r{sub 0} {approx}< 6-8h{sup -1} Mpc at 3.7 mJy and r{sub 0} {approx}< 11-12 h{sup -1} Mpc at 4.2 mJy. Although consistent with most previous estimates, these upper limits imply that the real r{sub 0} is likely smaller. This casts doubts on the robustness of claims that SMGs are characterized by significantly stronger spatial clustering (and thus larger mass) than differently selected galaxies at high redshift. Using Monte Carlo simulations we show that even strongly clustered distributions of galaxies can appear unclustered when sampled with limited sensitivity and coarse angular resolution common to current submillimeter surveys. The simulations, however, also show that unclustered distributions can appear strongly clustered under these circumstances. From the simulations, we predict that at our survey depth, a mapped area of 2 deg{sup 2} is needed to reconstruct the correlation function, assuming smaller beam sizes of future surveys (e.g., the Large Millimeter Telescope's 6'' beam size). At present, robust measures of the clustering strength of bright SMGs appear to be below the reach of most observations.« less

LoCuSS: pre-processing in galaxy groups falling into massive galaxy clusters at z = 0.2

NASA Astrophysics Data System (ADS)

Bianconi, M.; Smith, G. P.; Haines, C. P.; McGee, S. L.; Finoguenov, A.; Egami, E.

2018-01-01

We report direct evidence of pre-processing of the galaxies residing in galaxy groups falling into galaxy clusters drawn from the Local Cluster Substructure Survey (LoCuSS). 34 groups have been identified via their X-ray emission in the infall regions of 23 massive ( = 1015 M⊙) clusters at 0.15 < z < 0.3. Highly complete spectroscopic coverage combined with 24 μm imaging from Spitzer allows us to make a consistent and robust selection of cluster and group members including star-forming galaxies down to a stellar mass limit of M⋆ = 2 × 1010 M⊙. The fraction fSF of star-forming galaxies in infalling groups is lower and with a flatter trend with respect to clustercentric radius when compared to the rest of the cluster galaxy population. At R ≈ 1.3 r200, the fraction of star-forming galaxies in infalling groups is half that in the cluster galaxy population. This is direct evidence that star-formation quenching is effective in galaxies already prior to them settling in the cluster potential, and that groups are favourable locations for this process.

Membrane Resonance Enables Stable and Robust Gamma Oscillations

PubMed Central

Moca, Vasile V.; Nikolić, Danko; Singer, Wolf; Mureşan, Raul C.

2014-01-01

Neuronal mechanisms underlying beta/gamma oscillations (20–80 Hz) are not completely understood. Here, we show that in vivo beta/gamma oscillations in the cat visual cortex sometimes exhibit remarkably stable frequency even when inputs fluctuate dramatically. Enhanced frequency stability is associated with stronger oscillations measured in individual units and larger power in the local field potential. Simulations of neuronal circuitry demonstrate that membrane properties of inhibitory interneurons strongly determine the characteristics of emergent oscillations. Exploration of networks containing either integrator or resonator inhibitory interneurons revealed that: (i) Resonance, as opposed to integration, promotes robust oscillations with large power and stable frequency via a mechanism called RING (Resonance INduced Gamma); resonance favors synchronization by reducing phase delays between interneurons and imposes bounds on oscillation cycle duration; (ii) Stability of frequency and robustness of the oscillation also depend on the relative timing of excitatory and inhibitory volleys within the oscillation cycle; (iii) RING can reproduce characteristics of both Pyramidal INterneuron Gamma (PING) and INterneuron Gamma (ING), transcending such classifications; (iv) In RING, robust gamma oscillations are promoted by slow but are impaired by fast inputs. Results suggest that interneuronal membrane resonance can be an important ingredient for generation of robust gamma oscillations having stable frequency. PMID:23042733

Optimizing the robustness of electrical power systems against cascading failures.

PubMed

Zhang, Yingrui; Yağan, Osman

2016-06-21

Electrical power systems are one of the most important infrastructures that support our society. However, their vulnerabilities have raised great concern recently due to several large-scale blackouts around the world. In this paper, we investigate the robustness of power systems against cascading failures initiated by a random attack. This is done under a simple yet useful model based on global and equal redistribution of load upon failures. We provide a comprehensive understanding of system robustness under this model by (i) deriving an expression for the final system size as a function of the size of initial attacks; (ii) deriving the critical attack size after which system breaks down completely; (iii) showing that complete system breakdown takes place through a first-order (i.e., discontinuous) transition in terms of the attack size; and (iv) establishing the optimal load-capacity distribution that maximizes robustness. In particular, we show that robustness is maximized when the difference between the capacity and initial load is the same for all lines; i.e., when all lines have the same redundant space regardless of their initial load. This is in contrast with the intuitive and commonly used setting where capacity of a line is a fixed factor of its initial load.

The HO-1/CO system regulates mitochondrial-capillary density relationships in human skeletal muscle.

PubMed

Pecorella, Shelly R H; Potter, Jennifer V F; Cherry, Anne D; Peacher, Dionne F; Welty-Wolf, Karen E; Moon, Richard E; Piantadosi, Claude A; Suliman, Hagir B

2015-10-15

The heme oxygenase-1 (HO-1)/carbon monoxide (CO) system induces mitochondrial biogenesis, but its biological impact in human skeletal muscle is uncertain. The enzyme system generates CO, which stimulates mitochondrial proliferation in normal muscle. Here we examined whether CO breathing can be used to produce a coordinated metabolic and vascular response in human skeletal muscle. In 19 healthy subjects, we performed vastus lateralis muscle biopsies and tested one-legged maximal O2 uptake (V̇o2max) before and after breathing air or CO (200 ppm) for 1 h daily for 5 days. In response to CO, there was robust HO-1 induction along with increased mRNA levels for nuclear-encoded mitochondrial transcription factor A (Tfam), cytochrome c, cytochrome oxidase subunit IV (COX IV), and mitochondrial-encoded COX I and NADH dehydrogenase subunit 1 (NDI). CO breathing did not increase V̇o2max (1.96 ± 0.51 pre-CO, 1.87 ± 0.50 post-CO l/min; P = not significant) but did increase muscle citrate synthase, mitochondrial density (139.0 ± 34.9 pre-CO, 219.0 ± 36.2 post-CO; no. of mitochondrial profiles/field), myoglobin content and glucose transporter (GLUT4) protein level and led to GLUT4 localization to the myocyte membrane, all consistent with expansion of the tissue O2 transport system. These responses were attended by increased cluster of differentiation 31 (CD31)-positive muscle capillaries (1.78 ± 0.16 pre-CO, 2.37 ± 0.59 post-CO; capillaries/muscle fiber), implying the enrichment of microvascular O2 reserve. The findings support that induction of the HO-1/CO system by CO not only improves muscle mitochondrial density, but regulates myoglobin content, GLUT4 localization, and capillarity in accordance with current concepts of skeletal muscle plasticity. Copyright © 2015 the American Physiological Society.

Visual tracking using objectness-bounding box regression and correlation filters

NASA Astrophysics Data System (ADS)

Mbelwa, Jimmy T.; Zhao, Qingjie; Lu, Yao; Wang, Fasheng; Mbise, Mercy

2018-03-01

Visual tracking is a fundamental problem in computer vision with extensive application domains in surveillance and intelligent systems. Recently, correlation filter-based tracking methods have shown a great achievement in terms of robustness, accuracy, and speed. However, such methods have a problem of dealing with fast motion (FM), motion blur (MB), illumination variation (IV), and drifting caused by occlusion (OCC). To solve this problem, a tracking method that integrates objectness-bounding box regression (O-BBR) model and a scheme based on kernelized correlation filter (KCF) is proposed. The scheme based on KCF is used to improve the tracking performance of FM and MB. For handling drift problem caused by OCC and IV, we propose objectness proposals trained in bounding box regression as prior knowledge to provide candidates and background suppression. Finally, scheme KCF as a base tracker and O-BBR are fused to obtain a state of a target object. Extensive experimental comparisons of the developed tracking method with other state-of-the-art trackers are performed on some of the challenging video sequences. Experimental comparison results show that our proposed tracking method outperforms other state-of-the-art tracking methods in terms of effectiveness, accuracy, and robustness.

Intravenous lacosamide in seizure emergencies: Observations from a hospitalized in-patient adult population.

PubMed

d'Orsi, Giuseppe; Pascarella, Maria Grazia; Martino, Tommaso; Carapelle, Elena; Pacillo, Francesca; Di Claudio, Maria Teresa; Mancini, Daniela; Trivisano, Marina; Avolio, Carlo; Specchio, Luigi M

2016-11-01

to evaluate the efficacy and safety of intravenous (IV) lacosamide (LCM) in the treatment of seizure clusters (SC) and status epilepticus (SE) in hospitalized adult patients. we prospectively analyzed treatment response, seizure outcome, and adverse effects of IV LCM in 38 patients with seizure emergencies (15 with SC, 23 with SE) during a hospital stay. The loading dose of IV LCM was 200-400mg and the maintenance dose was 200-400mg daily. Response to IV LCM was evaluated within 20min, 4h and 24h of LCM infusion. an acute anti-seizure effect after IV LCM was especially evident when it was first used - (SC) or second line (established SE) treatment. In particular, 87% of SC patients (13/15) and 80% of established SE (8/10) demonstrated response to LCM treatment, while no patients with super-refractory SE (0/8) responded to IV LCM according to our criteria. The loading of IV LCM was well tolerated, with mild adverse effects (2/38 temporary dizziness). In most patients, during and after administration of the loading dose of IV LCM a temporary (30min-1h) sedation was observed. No ECG and laboratory values-changes were documented in any of the patients. LCM is an effective and well-tolerated treatment when used to treat SC in hospitalized adult patients. As add-on therapy, it may be useful to stop seizure activity in patients with focal SE not responding to first/second-line intravenous AEDs. Copyright © 2016 British Epilepsy Association. Published by Elsevier Ltd. All rights reserved.

Associations Between Personality Disorder Characteristics, Psychological Symptoms, and Sexual Functioning in Young Women.

PubMed

Grauvogl, Andrea; Pelzer, Britt; Radder, Veerle; van Lankveld, Jacques

2018-02-01

Recently, the etiology of sexual dysfunctions in women has been approached from different angles. In clinical practice and in previous studies, it has been observed that women with sexual problems experience anxiety problems and express more rigid and perfectionistic personality traits than women without these problems. To investigate whether personality disorder characteristics according to the Diagnostic and Statistical Manual of Mental Disorders, 4th Edition, Text Revision (DSM-IV-TR) and psychological symptoms are associated with sexual problems in women. 188 women 18 to 25 years old participated in this cross-sectional study. Questionnaires measuring sexual functioning (Female Sexual Function Index), personality disorder characteristics (Assessment of DSM-IV-TR Personality Disorders Questionnaire), and psychological symptoms (Brief Symptom Inventory and Center for Epidemiological Studies Depression Scale) were used. The main outcome measure used was sexual functioning assessed by self-report. Results, using analysis of variance, indicated that women with sexual problems report significantly more cluster A (specifically schizoid) and C (specifically avoidant and obsessive-compulsive) personality disorder characteristics than women without sexual problems. Furthermore, using multiple regression analyses, higher cluster A (specifically schizoid) and lower cluster B (specifically borderline and antisocial) personality disorder characteristics indicated lower levels of sexual functioning. Psychological symptoms partly mediated the effect of cluster A personality disorder characteristics on sexual functioning. The results of this study indicate that clinical practice should extend its scope by focusing more on improving adaptive personality characteristics, such as extraversion and individualism seen in cluster B personality characteristics, and decreasing the perfectionistic, introvert, and self-doubting characteristics seen in cluster C personality characteristics. Because of the correlational design and use of self-report measures, causal relations cannot be established between personality disorder characteristics and sexual functioning. Overall, the results indicate that personality disorder characteristics can play an important associative role in the development and maintenance of sexual functioning problems in women. Grauvogl A, Pelzer B, Radder V, van Lankveld J. Associations Between Personality Disorder Characteristics, Psychological Symptoms, and Sexual Functioning in Young Women. J Sex Med 2018;15:192-200. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Hundred Thousand Degree Gas in the Virgo Cluster of Galaxies

NASA Astrophysics Data System (ADS)

Sparks, W. B.; Pringle, J. E.; Carswell, R. F.; Donahue, M.; Martin, R.; Voit, M.; Cracraft, M.; Manset, N.; Hough, J. H.

2012-05-01

The physical relationship between low-excitation gas filaments at ~104 K, seen in optical line emission, and diffuse X-ray emitting coronal gas at ~107 K in the centers of many galaxy clusters is not understood. It is unclear whether the ~104 K filaments have cooled and condensed from the ambient hot (~107 K) medium or have some other origin such as the infall of cold gas in a merger, or the disturbance of an internal cool reservoir of gas by nuclear activity. Observations of gas at intermediate temperatures (~105-106 K) can potentially reveal whether the central massive galaxies are gaining cool gas through condensation or losing it through conductive evaporation and hence identify plausible scenarios for transport processes in galaxy cluster gas. Here we present spectroscopic detection of ~105 K gas spatially associated with the Hα filaments in a central cluster galaxy, M87, in the Virgo Cluster. The measured emission-line fluxes from triply ionized carbon (C IV 1549 Å) and singly ionized helium (He II 1640 Å) are consistent with a model in which thermal conduction determines the interaction between hot and cold phases.

Subsyndromal symptomatic depression: a new concept.

PubMed

Sadek, N; Bona, J

2000-01-01

Although DSM-IV acknowledged the clinical significance of some subthreshold forms of unipolar depression, such as minor depression (MinD) and recurrent brief depression (RBD), clinicians continued to struggle with the concept of "subthreshold" depression. A substantial number of patients continued to present with depressive symptoms that still did not satisfy any DSM-IV diagnosis. Generally, these patients failed to complain of anhedonia and depressed mood, a criterion that DSM-IV mandates for any diagnosis of depression. Therefore, researchers reexamined the question of whether this cluster of depressive symptoms, in the absence of anhedonia and depressed mood, was clinically significant. Some researchers labeled this cluster of symptoms, "subsyndromal symptomatic depression" (SSD). Specifically, SSD is defined as a depressive state having two or more symptoms of depression of the same quality as in major depression (MD), excluding depressed mood and anhedonia. The symptoms must be present for more than 2 weeks and be associated with social dysfunction. Using Medline Search, the authors reviewed the literature on the epidemiology, demographics, clinical characteristics, and psychosocial impairment of SSD. SSD is found to be comparable in demographics and clinical characteristics to MD, MinD, and dysthymia. SSD is also associated with significant psychosocial dysfunction as compared with healthy subjects. Further; it has significant risk for suicide and future MD. Few studies have been conducted on the treatment of SSD. The high prevalence of SSD, the significant psychosocial impairment associated with it, and the chronicity of its course make subsyndromal symptomatic depression a matter for serious consideration by clinicians and researchers.

A Robust and Fast Method for Sidescan Sonar Image Segmentation Using Nonlocal Despeckling and Active Contour Model.

PubMed

Huo, Guanying; Yang, Simon X; Li, Qingwu; Zhou, Yan

2017-04-01

Sidescan sonar image segmentation is a very important issue in underwater object detection and recognition. In this paper, a robust and fast method for sidescan sonar image segmentation is proposed, which deals with both speckle noise and intensity inhomogeneity that may cause considerable difficulties in image segmentation. The proposed method integrates the nonlocal means-based speckle filtering (NLMSF), coarse segmentation using k -means clustering, and fine segmentation using an improved region-scalable fitting (RSF) model. The NLMSF is used before the segmentation to effectively remove speckle noise while preserving meaningful details such as edges and fine features, which can make the segmentation easier and more accurate. After despeckling, a coarse segmentation is obtained by using k -means clustering, which can reduce the number of iterations. In the fine segmentation, to better deal with possible intensity inhomogeneity, an edge-driven constraint is combined with the RSF model, which can not only accelerate the convergence speed but also avoid trapping into local minima. The proposed method has been successfully applied to both noisy and inhomogeneous sonar images. Experimental and comparative results on real and synthetic sonar images demonstrate that the proposed method is robust against noise and intensity inhomogeneity, and is also fast and accurate.

A highly efficient measure of mass segregation in star clusters

NASA Astrophysics Data System (ADS)

Olczak, C.; Spurzem, R.; Henning, Th.

2011-08-01

Context. Investigations of mass segregation are of vital interest for the understanding of the formation and dynamical evolution of stellar systems on a wide range of spatial scales. A consistent analysis requires a robust measure among different objects and well-defined comparison with theoretical expectations. Various methods have been used for this purpose but usually with limited significance, quantifiability, and application to both simulations and observations. Aims: We aim at developing a measure of mass segregation with as few parameters as possible, robustness against peculiar configurations, independence of mass determination, simple implementation, stable algorithm, and that is equally well adoptable for data from either simulations or observations. Methods: Our method is based on the minimum spanning tree (MST) that serves as a geometry-independent measure of concentration. Compared to previous such approaches we obtain a significant refinement by using the geometrical mean as an intermediate-pass. Results: The geometrical mean boosts the sensitivity compared to previous applications of the MST. It thus allows the detection of mass segregation with much higher confidence and for much lower degrees of mass segregation than other approaches. The method shows in particular very clear signatures even when applied to small subsets of the entire population. We confirm with high significance strong mass segregation of the five most massive stars in the Orion nebula cluster (ONC). Conclusions: Our method is the most sensitive general measure of mass segregation so far and provides robust results for both data from simulations and observations. As such it is ideally suited for tracking mass segregation in young star clusters and to investigate the long standing paradigm of primordial mass segregation by comparison of simulations and observations.

An Approach to Cluster EU Member States into Groups According to Pathways of Salmonella in the Farm-to-Consumption Chain for Pork Products.

PubMed

Vigre, Håkan; Domingues, Ana Rita Coutinho Calado; Pedersen, Ulrik Bo; Hald, Tine

2016-03-01

The aim of the project as the cluster analysis was to in part to develop a generic structured quantitative microbiological risk assessment (QMRA) model of human salmonellosis due to pork consumption in EU member states (MSs), and the objective of the cluster analysis was to group the EU MSs according to the relative contribution of different pathways of Salmonella in the farm-to-consumption chain of pork products. In the development of the model, by selecting a case study MS from each cluster the model was developed to represent different aspects of pig production, pork production, and consumption of pork products across EU states. The objective of the cluster analysis was to aggregate MSs into groups of countries with similar importance of different pathways of Salmonella in the farm-to-consumption chain using available, and where possible, universal register data related to the pork production and consumption in each country. Based on MS-specific information about distribution of (i) small and large farms, (ii) small and large slaughterhouses, (iii) amount of pork meat consumed, and (iv) amount of sausages consumed we used nonhierarchical and hierarchical cluster analysis to group the MSs. The cluster solutions were validated internally using statistic measures and externally by comparing the clustered MSs with an estimated human incidence of salmonellosis due to pork products in the MSs. Finally, each cluster was characterized qualitatively using the centroids of the clusters. © 2016 Society for Risk Analysis.

The Robustness Analysis of Wireless Sensor Networks under Uncertain Interference

PubMed Central

Deng, Changjian

2013-01-01

Based on the complex network theory, robustness analysis of condition monitoring wireless sensor network under uncertain interference is present. In the evolution of the topology of sensor networks, the density weighted algebraic connectivity is taken into account, and the phenomenon of removing and repairing the link and node in the network is discussed. Numerical simulation is conducted to explore algebraic connectivity characteristics and network robustness performance. It is found that nodes density has the effect on algebraic connectivity distribution in the random graph model; high density nodes carry more connections, use more throughputs, and may be more unreliable. Moreover, the results show that, when network should be more error tolerant or robust by repairing nodes or adding new nodes, the network should be better clustered in median and high scale wireless sensor networks and be meshing topology in small scale networks. PMID:24363613

Galaxy masses in large surveys: Connecting luminous and dark matter with weak lensing and kinematics

NASA Astrophysics Data System (ADS)

Reyes, Reinabelle

2011-01-01

Galaxy masses are difficult to determine because light traces stars and gas in a non-trivial way, and does not trace dark matter, which extends well beyond the luminous regions of galaxies. In this thesis, I use the most direct probes of dark matter available---weak gravitational lensing and galaxy kinematics---to trace the total mass in galaxies (and galaxy clusters) in large surveys. In particular, I use the large, homogeneous dataset from the Sloan Digital Sky Survey (SDSS), which provides spectroscopic redshifts for a large sample of galaxies at z ≲ 0.2 and imaging data to a depth of r < 22. By combining complementary probes, I am able to obtain robust observational constraints that cannot be obtained from any single technique alone. First, I use weak lensing of galaxy clusters to derive an optimal optical tracer of cluster mass, which was found to be a combination of cluster richness and the luminosity of the brightest cluster galaxy. Next, I combine weak lensing of luminous red galaxies with redshift distortions and clustering measurements to derive a robust probe of gravity on cosmological scales. Finally, I combine weak lensing with the kinematics of disk galaxies to constrain the total mass profile over several orders of magnitude. I derive a minimal-scatter relation between disk velocity and stellar mass (also known as the Tully-Fisher relation) that can be used, by construction, on a similarly-selected lens sample. Then, I combine this relation with halo mass measurements from weak lensing to place constraints on the ratio of the optical to virial velocities, as well as the ratio of halo to stellar masses, both as a function of stellar mass. These results will serve as inputs to and constraints on disk galaxy formation models, which will be explored in future work.

Appearance of the octupole ordered phase IV in CexLa1 -x B6

NASA Astrophysics Data System (ADS)

Sera, M.; Kunimori, K.; Matsumura, T.; Kondo, A.; Tanida, H.; Tou, H.; Iga, F.

2018-05-01

We investigated the physical properties of CexLa1 -xB6 at x ˜0.8 , below which the Tβ-type antiferro-octupole (AFO) ordered phase IV appears as a result of the larger suppression rate of TQ than TN by La doping. The most important result is that while the peak of the specific heat at TQ is rapidly suppressed and broadened by La doping, that at TIV is sharp and large. This indicates that although the Tβ-AFO order in the phase IV is robust against the local lattice distortion induced by La doping, the Ox y-type antiferroquadrupole (AFQ) ordered phase II is very weak. The Tx y z-AFO interaction is robust against La doping from the observation of the pronounced enhancement of TQ even in a small x region. Based on these La-doping effect of the multipole interactions, we carried out the mean-field calculation for the four-sublattice model to reproduce the magnetic phase diagrams of CexLa1 -xB6 . Based on the calculated results, we propose that the small splitting of the quartet is induced by La doping in phase I to explain the magnetic phase diagram for x <0.65 . We could obtain the calculated results roughly consistent with the experimental results, although there appear new problems. We classified the mechanisms of the four different types of the competition among the four interactions with roughly the same magnitude, which induce the interesting and complicated properties in CexLa1 -xB6 .

Scientific and Engineering Studies. Compiled 1983. Signal Processing Studies

DTIC Science & Technology

1983-01-01

figure 12D in the neighborhood of this frequency can serve as an indicator of the number of poles and zeros clustered there. When Pmax was increased...use >(.) to estimate (iv)If coherence CXy(f0) ■ I, why use the completely statistically dependent y(t) data to estimate GMX (f0)1 This philosophy of

Galactic cannibalism. IV. The evidence-correlations between dynamical time scales and Bautz-Morgan type

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

McGlynn, T.A.; Ostriker, J.P.

1980-11-01

If the luminosity of supergiant cD galaxies in particular, and the Bautz-Morgan sequence of galaxy types in general, is produced by dynamical evolutionary processes, then one expects to find a correlation between dynamical times and ..delta..M/sub 12/, the magnitude difference between first and second brightest cluster members.

Laser Applications in Microelectronic and Optoelectronic Manufacturing IV

DTIC Science & Technology

1999-07-15

laser irradiation of the clusters with 6000 laser pulses of X...insulating ma- terials during and after irradiation by tunable, ultrashort pulses from a mid-infrared laser . The three salient examples we con- sider...with ultrashort pulses re- sembles the rear-side ablation seen in irradiation of calcite by Nd:YAG lasers (1064 nm), while the off-resonance FEL

Model-based clustering for RNA-seq data.

PubMed

Si, Yaqing; Liu, Peng; Li, Pinghua; Brutnell, Thomas P

2014-01-15

RNA-seq technology has been widely adopted as an attractive alternative to microarray-based methods to study global gene expression. However, robust statistical tools to analyze these complex datasets are still lacking. By grouping genes with similar expression profiles across treatments, cluster analysis provides insight into gene functions and networks, and hence is an important technique for RNA-seq data analysis. In this manuscript, we derive clustering algorithms based on appropriate probability models for RNA-seq data. An expectation-maximization algorithm and another two stochastic versions of expectation-maximization algorithms are described. In addition, a strategy for initialization based on likelihood is proposed to improve the clustering algorithms. Moreover, we present a model-based hybrid-hierarchical clustering method to generate a tree structure that allows visualization of relationships among clusters as well as flexibility of choosing the number of clusters. Results from both simulation studies and analysis of a maize RNA-seq dataset show that our proposed methods provide better clustering results than alternative methods such as the K-means algorithm and hierarchical clustering methods that are not based on probability models. An R package, MBCluster.Seq, has been developed to implement our proposed algorithms. This R package provides fast computation and is publicly available at http://www.r-project.org

Comparison of cluster-based and source-attribution methods for estimating transmission risk using large HIV sequence databases.

PubMed

Le Vu, Stéphane; Ratmann, Oliver; Delpech, Valerie; Brown, Alison E; Gill, O Noel; Tostevin, Anna; Fraser, Christophe; Volz, Erik M

2018-06-01

Phylogenetic clustering of HIV sequences from a random sample of patients can reveal epidemiological transmission patterns, but interpretation is hampered by limited theoretical support and statistical properties of clustering analysis remain poorly understood. Alternatively, source attribution methods allow fitting of HIV transmission models and thereby quantify aspects of disease transmission. A simulation study was conducted to assess error rates of clustering methods for detecting transmission risk factors. We modeled HIV epidemics among men having sex with men and generated phylogenies comparable to those that can be obtained from HIV surveillance data in the UK. Clustering and source attribution approaches were applied to evaluate their ability to identify patient attributes as transmission risk factors. We find that commonly used methods show a misleading association between cluster size or odds of clustering and covariates that are correlated with time since infection, regardless of their influence on transmission. Clustering methods usually have higher error rates and lower sensitivity than source attribution method for identifying transmission risk factors. But neither methods provide robust estimates of transmission risk ratios. Source attribution method can alleviate drawbacks from phylogenetic clustering but formal population genetic modeling may be required to estimate quantitative transmission risk factors. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Rapid identification and classification of bacteria by 16S rDNA restriction fragment melting curve analyses (RFMCA).

PubMed

Rudi, Knut; Kleiberg, Gro H; Heiberg, Ragnhild; Rosnes, Jan T

2007-08-01

The aim of this work was to evaluate restriction fragment melting curve analyses (RFMCA) as a novel approach for rapid classification of bacteria during food production. RFMCA was evaluated for bacteria isolated from sous vide food products, and raw materials used for sous vide production. We identified four major bacterial groups in the material analysed (cluster I-Streptococcus, cluster II-Carnobacterium/Bacillus, cluster III-Staphylococcus and cluster IV-Actinomycetales). The accuracy of RFMCA was evaluated by comparison with 16S rDNA sequencing. The strains satisfying the RFMCA quality filtering criteria (73%, n=57), with both 16S rDNA sequence information and RFMCA data (n=45) gave identical group assignments with the two methods. RFMCA enabled rapid and accurate classification of bacteria that is database compatible. Potential application of RFMCA in the food or pharmaceutical industry will include development of classification models for the bacteria expected in a given product, and then to build an RFMCA database as a part of the product quality control.

Transient Maternal Hypothyroidism Alters Neural Progenitor Expression Resulting in Abnormal Brain Development

EPA Science Inventory

Heterotopias are a birth defect of the brain, and have varying etiologies in humans. They are characterized as clusters of mislocalized neurons, and are associated with disorders such as autism, epilepsy, and learning disabilities. We have previously characterized the robust pene...

Transient Maternal Hypothyroidism Alters Neural Progenitors Resulting in Abnormal Brain Development

EPA Science Inventory

Heterotopias are a birth defect of the brain and have varying etiologies in humans. They are characterized as clusters of mislocalized neurons and are associated with disorders such as autism, epilepsy, and learning disabilities. We have previously characterized the robust penetr...

Interpretable dimensionality reduction of single cell transcriptome data with deep generative models.

PubMed

Ding, Jiarui; Condon, Anne; Shah, Sohrab P

2018-05-21

Single-cell RNA-sequencing has great potential to discover cell types, identify cell states, trace development lineages, and reconstruct the spatial organization of cells. However, dimension reduction to interpret structure in single-cell sequencing data remains a challenge. Existing algorithms are either not able to uncover the clustering structures in the data or lose global information such as groups of clusters that are close to each other. We present a robust statistical model, scvis, to capture and visualize the low-dimensional structures in single-cell gene expression data. Simulation results demonstrate that low-dimensional representations learned by scvis preserve both the local and global neighbor structures in the data. In addition, scvis is robust to the number of data points and learns a probabilistic parametric mapping function to add new data points to an existing embedding. We then use scvis to analyze four single-cell RNA-sequencing datasets, exemplifying interpretable two-dimensional representations of the high-dimensional single-cell RNA-sequencing data.

Spatiotemporal coding of inputs for a system of globally coupled phase oscillators

NASA Astrophysics Data System (ADS)

Wordsworth, John; Ashwin, Peter

2008-12-01

We investigate the spatiotemporal coding of low amplitude inputs to a simple system of globally coupled phase oscillators with coupling function g(ϕ)=-sin(ϕ+α)+rsin(2ϕ+β) that has robust heteroclinic cycles (slow switching between cluster states). The inputs correspond to detuning of the oscillators. It was recently noted that globally coupled phase oscillators can encode their frequencies in the form of spatiotemporal codes of a sequence of cluster states [P. Ashwin, G. Orosz, J. Wordsworth, and S. Townley, SIAM J. Appl. Dyn. Syst. 6, 728 (2007)]. Concentrating on the case of N=5 oscillators we show in detail how the spatiotemporal coding can be used to resolve all of the information that relates the individual inputs to each other, providing that a long enough time series is considered. We investigate robustness to the addition of noise and find a remarkable stability, especially of the temporal coding, to the addition of noise even for noise of a comparable magnitude to the inputs.

Anomaly Detection of Electromyographic Signals.

PubMed

Ijaz, Ahsan; Choi, Jongeun

2018-04-01

In this paper, we provide a robust framework to detect anomalous electromyographic (EMG) signals and identify contamination types. As a first step for feature selection, optimally selected Lawton wavelets transform is applied. Robust principal component analysis (rPCA) is then performed on these wavelet coefficients to obtain features in a lower dimension. The rPCA based features are used for constructing a self-organizing map (SOM). Finally, hierarchical clustering is applied on the SOM that separates anomalous signals residing in the smaller clusters and breaks them into logical units for contamination identification. The proposed methodology is tested using synthetic and real world EMG signals. The synthetic EMG signals are generated using a heteroscedastic process mimicking desired experimental setups. A sub-part of these synthetic signals is introduced with anomalies. These results are followed with real EMG signals introduced with synthetic anomalies. Finally, a heterogeneous real world data set is used with known quality issues under an unsupervised setting. The framework provides recall of 90% (± 3.3) and precision of 99%(±0.4).

Genomic diversity and phylogenetic relationships among lipid-requiring diphtheroids from humans and characterization of Corynebacterium macginleyi sp. nov.

PubMed

Riegel, P; Ruimy, R; de Briel, D; Prévost, G; Jehl, F; Christen, R; Monteil, H

1995-01-01

DNA relatedness experiments were performed with 38 clinical isolates and 13 reference strains of coryneform taxa exhibiting a lipid requirement for optimal growth. Forty-five of these strains split into five genomic groups at the species level, whereas six other strains remained unclustered. Genomospecies II fits Corynebacterium accolens, but the other genomospecies were not genetically related to any of the defined Corynebacterium species. Phylogenetic analyses of genes coding for small-subunit rRNA sequences revealed that two genomospecies (I and III) and C. accolens form a tight cluster within the robust branch that groups all Corynebacterium species presently sequenced. Reference strains of biotypes C-1, C-2, and C-3 of "Corynebacterium pseudogenitalium" were found to fall into genomospecies I, as well as "Corynebacterium tuberculostearicum," Centers for Disease Control and Prevention (CDC) coryneform group G-1, and CDC coryneform group G-2 reference strains. Biochemical tests allowed differentiation between genomospecies except between genomospecies IV and V and between six unclustered strains and genomospecies I. We propose a new classification for these lipid-requiring diphtheroids within the genus Corynebacterium with the delineation of some CDC coryneform group G-1 strains (genomospecies III) as a new species for which the name Corynebacterium macginleyi is proposed. The type strain is strain JCL-2 (CIP 104099), isolated from a human corneal ulcer.

Manifold Learning in MR spectroscopy using nonlinear dimensionality reduction and unsupervised clustering.

PubMed

Yang, Guang; Raschke, Felix; Barrick, Thomas R; Howe, Franklyn A

2015-09-01

To investigate whether nonlinear dimensionality reduction improves unsupervised classification of (1) H MRS brain tumor data compared with a linear method. In vivo single-voxel (1) H magnetic resonance spectroscopy (55 patients) and (1) H magnetic resonance spectroscopy imaging (MRSI) (29 patients) data were acquired from histopathologically diagnosed gliomas. Data reduction using Laplacian eigenmaps (LE) or independent component analysis (ICA) was followed by k-means clustering or agglomerative hierarchical clustering (AHC) for unsupervised learning to assess tumor grade and for tissue type segmentation of MRSI data. An accuracy of 93% in classification of glioma grade II and grade IV, with 100% accuracy in distinguishing tumor and normal spectra, was obtained by LE with unsupervised clustering, but not with the combination of k-means and ICA. With (1) H MRSI data, LE provided a more linear distribution of data for cluster analysis and better cluster stability than ICA. LE combined with k-means or AHC provided 91% accuracy for classifying tumor grade and 100% accuracy for identifying normal tissue voxels. Color-coded visualization of normal brain, tumor core, and infiltration regions was achieved with LE combined with AHC. The LE method is promising for unsupervised clustering to separate brain and tumor tissue with automated color-coding for visualization of (1) H MRSI data after cluster analysis. © 2014 Wiley Periodicals, Inc.

Association of an α-globin gene cluster duplication and heterozygous β-thalassemia in a patient with a severe thalassemia syndrome.

PubMed

Jiang, Hua; Liu, Sha; Zhang, Yong-Ling; Wan, Jun-Hui; Li, Ru; Li, Dong-Zhi

2015-01-01

We describe a new case of a β-thalassemia (β-thal) heterozygote with the mutation IVS-II-654 (C>T) presenting with a transfusion-dependent phenotype. Multiplex ligation-dependent probe amplification (MLPA) and array comparative genomic hybridization (CGH) analyses of the α-globin gene cluster revealed a full duplication of the α-globin genes including the upstream regulatory element. The duplicated allele and the normal allele in trans resulted in a total of six active α-globin genes. The severe clinical phenotype seemed to be related to the considerable excess of the α- and β-globin deficit caused by the presence of the β-thal. α-Globin cluster duplication should be considered in patients heterozygous for β-thal who show a more severe phenotype than β-thal trait.

An empirical potential for simulating vacancy clusters in tungsten.

PubMed

Mason, D R; Nguyen-Manh, D; Becquart, C S

2017-12-20

We present an empirical interatomic potential for tungsten, particularly well suited for simulations of vacancy-type defects. We compare energies and structures of vacancy clusters generated with the empirical potential with an extensive new database of values computed using density functional theory, and show that the new potential predicts low-energy defect structures and formation energies with high accuracy. A significant difference to other popular embedded-atom empirical potentials for tungsten is the correct prediction of surface energies. Interstitial properties and short-range pairwise behaviour remain similar to the Ackford-Thetford potential on which it is based, making this potential well-suited to simulations of microstructural evolution following irradiation damage cascades. Using atomistic kinetic Monte Carlo simulations, we predict vacancy cluster dissociation in the range 1100-1300 K, the temperature range generally associated with stage IV recovery.

Local resonances in STM manipulation of chlorobenzene on Si(111)-7×7: performance of different cluster models and density functionals

NASA Astrophysics Data System (ADS)

Utecht, Manuel; Klamroth, Tillmann

2018-07-01

Hot localised charge carriers on the Si(111)-7×7 surface are modelled by small charged clusters. Such resonances induce non-local desorption, i.e. more than 10 nm away from the injection site, of chlorobenzene in scanning tunnelling microscope experiments. We used such a cluster model to characterise resonance localisation and vibrational activation for positive and negative resonances recently. In this work, we investigate to which extent the model depends on details of the used cluster or quantum chemistry methods and try to identify the smallest possible cluster suitable for a description of the neutral surface and the ion resonances. Furthermore, a detailed analysis for different chemisorption orientations is performed. While some properties, as estimates of the resonance energy or absolute values for atomic changes, show such a dependency, the main findings are very robust with respect to changes in the model and/or the chemisorption geometry.

Determining Distance, Age, and Activity in a New Benchmark Cluster: Ruprecht 147

NASA Astrophysics Data System (ADS)

Wright, Jason T.

2009-08-01

This proposal seeks 0.7 night of time on Hectochelle to observe the F, G, and K dwarfs of Ruprecht 147, recently identified as the closest old stellar cluster. At only ~ 200 pc and at an age of ~ 1-2 Gyr, this will be an important benchmark in stellar astrophysics, providing the only sample of spectroscopically accessible old, late-type stars of determinable age. Hectochelle is the ideal instrument to study this cluster, with a FOV, fiber count, and telescope aperture well matched to the cluster's diameter (~ 1°), richness (~ 100 identified members), and distance modulus (6.5-7 mag., putting the G and K dwarfs at B=11-15). Hectochelle will measure the Ca II line strengths of members to establish, for the first time, the chromospheric activity levels of a statistically significant sample of single, G and K dwarfs of this modest age. Hectochelle will also vet background stars for suitability as astrometric reference stars for a forthcoming HST FGS proposal to robustly measure the cluster's distance.

Shortest-path constraints for 3D multiobject semiautomatic segmentation via clustering and Graph Cut.

PubMed

Kéchichian, Razmig; Valette, Sébastien; Desvignes, Michel; Prost, Rémy

2013-11-01

We derive shortest-path constraints from graph models of structure adjacency relations and introduce them in a joint centroidal Voronoi image clustering and Graph Cut multiobject semiautomatic segmentation framework. The vicinity prior model thus defined is a piecewise-constant model incurring multiple levels of penalization capturing the spatial configuration of structures in multiobject segmentation. Qualitative and quantitative analyses and comparison with a Potts prior-based approach and our previous contribution on synthetic, simulated, and real medical images show that the vicinity prior allows for the correct segmentation of distinct structures having identical intensity profiles and improves the precision of segmentation boundary placement while being fairly robust to clustering resolution. The clustering approach we take to simplify images prior to segmentation strikes a good balance between boundary adaptivity and cluster compactness criteria furthermore allowing to control the trade-off. Compared with a direct application of segmentation on voxels, the clustering step improves the overall runtime and memory footprint of the segmentation process up to an order of magnitude without compromising the quality of the result.

Effect of data truncation in an implementation of pixel clustering on a custom computing machine

NASA Astrophysics Data System (ADS)

Leeser, Miriam E.; Theiler, James P.; Estlick, Michael; Kitaryeva, Natalya V.; Szymanski, John J.

2000-10-01

We investigate the effect of truncating the precision of hyperspectral image data for the purpose of more efficiently segmenting the image using a variant of k-means clustering. We describe the implementation of the algorithm on field-programmable gate array (FPGA) hardware. Truncating the data to only a few bits per pixel in each spectral channel permits a more compact hardware design, enabling greater parallelism, and ultimately a more rapid execution. It also enables the storage of larger images in the onboard memory. In exchange for faster clustering, however, one trades off the quality of the produced segmentation. We find, however, that the clustering algorithm can tolerate considerable data truncation with little degradation in cluster quality. This robustness to truncated data can be extended by computing the cluster centers to a few more bits of precision than the data. Since there are so many more pixels than centers, the more aggressive data truncation leads to significant gains in the number of pixels that can be stored in memory and processed in hardware concurrently.

Use of the TAT in the assessment of DSM-IV cluster B personality disorders.

PubMed

Ackerman, S J; Clemence, A J; Weatherill, R; Hilsenroth, M J

1999-12-01

The Social Cognition and Object Relations Scale (SCORS), developed by Western, Lohr, Silk, Kerber, and Goodrich (1985), is a diagnostic instrument used to assess an array of psychological functioning by using clinical narratives such as the Thematic Apperception Test (TAT; Murray, 1943) stories. This study investigated the utility of the SCORS to differentiate between Diagnostic and Statistical Manual of Mental Disorders (4th ed. [DSM-IV]; American Psychiatric Association, 1994) antisocial personality disorder (ANPD), borderline personality disorder (BPD), narcissistic personality disorder (NPD), and Cluster C personality disorder (CPD). A sample of 58 patients was separated into four groups: ANPD (n = 9), BPD (n = 21; 18 with a primary BPD diagnosis and 3 with prominent borderline traits who met 4 of the 5 DSM-IV criteria necessary for a BPD diagnosis), NPD (n = 16; 8 with a primary NPD diagnosis and 8 with prominent narcissistic traits who met 4 of the 5 DSM-IV criteria necessary for a NPD diagnosis), and CPD (n = 12). These groups were then compared on the 8 SCORS variables by using 5 TAT cards (1, 2, 3BM, 4, and 13MF). Spearman-Brown correction for 2-way mixed effects model of reliability for the 8 SCORS variables ranged from .70 to .95. The results of categorical and dimensional analyses indicate that (a) SCORS variables can be used to differentiate ANPD, BPD, and NPD; (b) the BPD group scored significantly lower (greater maladjustment) than did the CPD group on certain variables; (c) the BPD group scored significantly lower (greater maladjustment) than did the NPD group on all 8 SCORS variables; (d) the ANPD group scored significantly lower than did the NPD group on certain variables; (e) certain variables were found to be empirically related to the total number of DSM-IV ANPD, BPD, and NPD criteria; and (f) certain variables were found to be empirically related to Minnesota Multiphasic Personality Inventory-2 (MMPI-2; Butcher, Dahlstrom, Graham, Tellegen, & Kaemmer, 1989) Personality disorder scales. The results of this study are discussed in terms of clinical utility, conceptual, and theoretical implications.

New insights into Trypanosoma cruzi evolution, genotyping and molecular diagnostics from satellite DNA sequence analysis.

PubMed

Ramírez, Juan C; Torres, Carolina; Curto, María de Los A; Schijman, Alejandro G

2017-12-01

Trypanosoma cruzi has been subdivided into seven Discrete Typing Units (DTUs), TcI-TcVI and Tcbat. Two major evolutionary models have been proposed to explain the origin of hybrid lineages, but while it is widely accepted that TcV and TcVI are the result of genetic exchange between TcII and TcIII strains, the origin of TcIII and TcIV is still a matter of debate. T. cruzi satellite DNA (SatDNA), comprised of 195 bp units organized in tandem repeats, from both TcV and TcVI stocks were found to have SatDNA copies type TcI and TcII; whereas contradictory results were observed for TcIII stocks and no TcIV sequence has been analyzed yet. Herein, we have gone deeper into this matter analyzing 335 distinct SatDNA sequences from 19 T. cruzi stocks representative of DTUs TcI-TcVI for phylogenetic inference. Bayesian phylogenetic tree showed that all sequences were grouped in three major clusters, which corresponded to sequences from DTUs TcI/III, TcII and TcIV; whereas TcV and TcVI stocks had two sets of sequences distributed into TcI/III and TcII clusters. As expected, the lowest genetic distances were found between TcI and TcIII, and between TcV and TcVI sequences; whereas the highest ones were observed between TcII and TcI/III, and among TcIV sequences and those from the remaining DTUs. In addition, signature patterns associated to specific T. cruzi lineages were identified and new primers that improved SatDNA-based qPCR sensitivity were designed. Our findings support the theory that TcIII is not the result of a hybridization event between TcI and TcII, and that TcIV had an independent origin from the other DTUs, contributing to clarifying the evolutionary history of T. cruzi lineages. Moreover, this work opens the possibility of typing samples from Chagas disease patients with low parasitic loads and improving molecular diagnostic methods of T. cruzi infection based on SatDNA sequence amplification.

A molecular phylogeny of anseriformes based on mitochondrial DNA analysis.

PubMed

Donne-Goussé, Carole; Laudet, Vincent; Hänni, Catherine

2002-06-01

To study the phylogenetic relationships among Anseriformes, sequences for the complete mitochondrial control region (CR) were determined from 45 waterfowl representing 24 genera, i.e., half of the existing genera. To confirm the results based on CR analysis we also analyzed representative species based on two mitochondrial protein-coding genes, cytochrome b (cytb) and NADH dehydrogenase subunit 2 (ND2). These data allowed us to construct a robust phylogeny of the Anseriformes and to compare it with existing phylogenies based on morphological or molecular data. Chauna and Dendrocygna were identified as early offshoots of the Anseriformes. All the remaining taxa fell into two clades that correspond to the two subfamilies Anatinae and Anserinae. Within Anserinae Branta and Anser cluster together, whereas Coscoroba, Cygnus, and Cereopsis form a relatively weak clade with Cygnus diverging first. Five clades are clearly recognizable among Anatinae: (i) the Anatini with Anas and Lophonetta; (ii) the Aythyini with Aythya and Netta; (iii) the Cairinini with Cairina and Aix; (iv) the Mergini with Mergus, Bucephala, Melanitta, Callonetta, Somateria, and Clangula, and (v) the Tadornini with Tadorna, Chloephaga, and Alopochen. The Tadornini diverged early on from the Anatinae; then the Mergini and a large group that comprises the Anatini, Aythyini, Cairinini, and two isolated genera, Chenonetta and Marmaronetta, diverged. The phylogeny obtained with the control region appears more robust than the one obtained with mitochondrial protein-coding genes such as ND2 and cytb. This suggests that the CR is a powerful tool for bird phylogeny, not only at a small scale (i.e., relationships between species) but also at the family level. Whereas morphological analysis effectively resolved the split between Anatinae and Anserinae and the existence of some of the clades, the precise composition of the clades are different when morphological and molecular data are compared. (c) 2002 Elsevier Science (USA).

Wave failure at strong coupling in intracellular C a2 + signaling system with clustered channels

NASA Astrophysics Data System (ADS)

Li, Xiang; Wu, Yuning; Gao, Xuejuan; Cai, Meichun; Shuai, Jianwei

2018-01-01

As an important intracellular signal, C a2 + ions control diverse cellular functions. In this paper, we discuss the C a2 + signaling with a two-dimensional model in which the inositol 1,4,5-trisphosphate (I P3 ) receptor channels are distributed in clusters on the endoplasmic reticulum membrane. The wave failure at large C a2 + diffusion coupling is discussed in detail in the model. We show that with varying model parameters the wave failure is a robust behavior with either deterministic or stochastic channel dynamics. We suggest that the wave failure should be a general behavior in inhomogeneous diffusing systems with clustered excitable regions and may occur in biological C a2 + signaling systems.

Origin of Pareto-like spatial distributions in ecosystems.

PubMed

Manor, Alon; Shnerb, Nadav M

2008-12-31

Recent studies of cluster distribution in various ecosystems revealed Pareto statistics for the size of spatial colonies. These results were supported by cellular automata simulations that yield robust criticality for endogenous pattern formation based on positive feedback. We show that this patch statistics is a manifestation of the law of proportionate effect. Mapping the stochastic model to a Markov birth-death process, the transition rates are shown to scale linearly with cluster size. This mapping provides a connection between patch statistics and the dynamics of the ecosystem; the "first passage time" for different colonies emerges as a powerful tool that discriminates between endogenous and exogenous clustering mechanisms. Imminent catastrophic shifts (such as desertification) manifest themselves in a drastic change of the stability properties of spatial colonies.

Genotyping in the cloud with Crossbow.

PubMed

Gurtowski, James; Schatz, Michael C; Langmead, Ben

2012-09-01

Crossbow is a scalable, portable, and automatic cloud computing tool for identifying SNPs from high-coverage, short-read resequencing data. It is built on Apache Hadoop, an implementation of the MapReduce software framework. Hadoop allows Crossbow to distribute read alignment and SNP calling subtasks over a cluster of commodity computers. Two robust tools, Bowtie and SOAPsnp, implement the fundamental alignment and variant calling operations respectively, and have demonstrated capabilities within Crossbow of analyzing approximately one billion short reads per hour on a commodity Hadoop cluster with 320 cores. Through protocol examples, this unit will demonstrate the use of Crossbow for identifying variations in three different operating modes: on a Hadoop cluster, on a single computer, and on the Amazon Elastic MapReduce cloud computing service.

Layer-by-Layer Molecular Assemblies for Dye-Sensitized Photoelectrosynthesis Cells Prepared by Atomic Layer Deposition

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

Wang, Degao; Sheridan, Matthew V.; Shan, Bing

2017-08-30

In a Dye Sensitized Photoelectrosynthesis Cell (DSPEC) the relative orientation of catalyst and chromophore play important roles. Here we introduce a new, robust, Atomic Layer Deposition (ALD) procedure for the preparation of assemblies on wide bandgap semiconductors. In the procedure, phosphonated metal complex precursors react with metal ion bridging to an external chromophore or catalyst to give assemblies bridged by Al(III), Sn(IV), Ti(IV), or Zr(IV) metal oxide units as bridges. The procedure has been extended to chromophore-catalyst assemblies for water oxidation catalysis. A SnO2 bridged assembly on SnO2/TiO2 core/shell electrodes undergoes water splitting with an incident photon conversion efficiency (IPCE)more » of 17.1% at 440 nm. Reduction of water at a Ni(II)-based catalyst on NiO films has been shown to give H2. Compared to conventional solution-based procedures, the ALD approach offers significant advantages in scope and flexibility for the preparation of stable surface structures.« less

Experiments in Coherent Change Detection for Synthetic Aperture Sonar

DTIC Science & Technology

2010-06-01

data from synthetic aperture sonars mounted on autonomous undersea ve- hicles and actively navigated tow bodies. A noncoherent example carried out...III of this paper describe approaches for au- tomatic change detection and introduces CCD. Section IV pro- vides an example of noncoherent change...registration insufficiently robust to support correlation-based change detection (whether cohe- rent or noncoherent ). Fig. 6. Baseline (a) and

A curvature-based weighted fuzzy c-means algorithm for point clouds de-noising

NASA Astrophysics Data System (ADS)

Cui, Xin; Li, Shipeng; Yan, Xiutian; He, Xinhua

2018-04-01

In order to remove the noise of three-dimensional scattered point cloud and smooth the data without damnify the sharp geometric feature simultaneity, a novel algorithm is proposed in this paper. The feature-preserving weight is added to fuzzy c-means algorithm which invented a curvature weighted fuzzy c-means clustering algorithm. Firstly, the large-scale outliers are removed by the statistics of r radius neighboring points. Then, the algorithm estimates the curvature of the point cloud data by using conicoid parabolic fitting method and calculates the curvature feature value. Finally, the proposed clustering algorithm is adapted to calculate the weighted cluster centers. The cluster centers are regarded as the new points. The experimental results show that this approach is efficient to different scale and intensities of noise in point cloud with a high precision, and perform a feature-preserving nature at the same time. Also it is robust enough to different noise model.

Understanding the enormous diversity of bacteriophages: the tailed phages that infect the bacterial family Enterobacteriaceae.

PubMed

Grose, Julianne H; Casjens, Sherwood R

2014-11-01

Bacteriophages are the predominant biological entity on the planet. The recent explosion of sequence information has made estimates of their diversity possible. We describe the genomic comparison of 337 fully sequenced tailed phages isolated on 18 genera and 31 species of bacteria in the Enterobacteriaceae. These phages were largely unambiguously grouped into 56 diverse clusters (32 lytic and 24 temperate) that have syntenic similarity over >50% of the genomes within each cluster, but substantially less sequence similarity between clusters. Most clusters naturally break into sets of more closely related subclusters, 78% of which are correlated with their host genera. The largest groups of related phages are superclusters united by genome synteny to lambda (81 phages) and T7 (51 phages). This study forms a robust framework for understanding diversity and evolutionary relationships of existing tailed phages, for relating newly discovered phages and for determining host/phage relationships.

Understanding the enormous diversity of bacteriophages: the tailed phages that infect the bacterial family Enterobacteriaceae

PubMed Central

Grose, Julianne H.; Casjens, Sherwood R.

2014-01-01

Bacteriophages are the predominant biological entity on the planet. The recent explosion of sequence information has made estimates of their diversity possible. We describe the genomic comparison of 337 fully sequenced tailed phages isolated on 18 genera and 31 species of bacteria in the Enterobacteriaceae. These phages were largely unambiguously grouped into 56 diverse clusters (32 lytic and 24 temperate) that have syntenic similarity over >50% of the genomes within each cluster, but substantially less sequence similarity between clusters. Most clusters naturally break into sets of more closely related subclusters, 78% of which are correlated with their host genera. The largest groups of related phages are superclusters united by genome synteny to lambda (81 phages) and T7 (51 phages). This study forms a robust framework for understanding diversity and evolutionary relationships of existing tailed phages, for relating newly discovered phages and for determining host/phage relationships. PMID:25240328

ODE, RDE and SDE models of cell cycle dynamics and clustering in yeast.

PubMed

Boczko, Erik M; Gedeon, Tomas; Stowers, Chris C; Young, Todd R

2010-07-01

Biologists have long observed periodic-like oxygen consumption oscillations in yeast populations under certain conditions, and several unsatisfactory explanations for this phenomenon have been proposed. These ‘autonomous oscillations’ have often appeared with periods that are nearly integer divisors of the calculated doubling time of the culture. We hypothesize that these oscillations could be caused by a form of cell cycle synchronization that we call clustering. We develop some novel ordinary differential equation models of the cell cycle. For these models, and for random and stochastic perturbations, we give both rigorous proofs and simulations showing that both positive and negative growth rate feedback within the cell cycle are possible agents that can cause clustering of populations within the cell cycle. It occurs for a variety of models and for a broad selection of parameter values. These results suggest that the clustering phenomenon is robust and is likely to be observed in nature. Since there are necessarily an integer number of clusters, clustering would lead to periodic-like behaviour with periods that are nearly integer divisors of the period of the cell cycle. Related experiments have shown conclusively that cell cycle clustering occurs in some oscillating yeast cultures.

Performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data.

PubMed

Yelland, Lisa N; Salter, Amy B; Ryan, Philip

2011-10-15

Modified Poisson regression, which combines a log Poisson regression model with robust variance estimation, is a useful alternative to log binomial regression for estimating relative risks. Previous studies have shown both analytically and by simulation that modified Poisson regression is appropriate for independent prospective data. This method is often applied to clustered prospective data, despite a lack of evidence to support its use in this setting. The purpose of this article is to evaluate the performance of the modified Poisson regression approach for estimating relative risks from clustered prospective data, by using generalized estimating equations to account for clustering. A simulation study is conducted to compare log binomial regression and modified Poisson regression for analyzing clustered data from intervention and observational studies. Both methods generally perform well in terms of bias, type I error, and coverage. Unlike log binomial regression, modified Poisson regression is not prone to convergence problems. The methods are contrasted by using example data sets from 2 large studies. The results presented in this article support the use of modified Poisson regression as an alternative to log binomial regression for analyzing clustered prospective data when clustering is taken into account by using generalized estimating equations.

Hybrid clustering based fuzzy structure for vibration control - Part 1: A novel algorithm for building neuro-fuzzy system

NASA Astrophysics Data System (ADS)

Nguyen, Sy Dzung; Nguyen, Quoc Hung; Choi, Seung-Bok

2015-01-01

This paper presents a new algorithm for building an adaptive neuro-fuzzy inference system (ANFIS) from a training data set called B-ANFIS. In order to increase accuracy of the model, the following issues are executed. Firstly, a data merging rule is proposed to build and perform a data-clustering strategy. Subsequently, a combination of clustering processes in the input data space and in the joint input-output data space is presented. Crucial reason of this task is to overcome problems related to initialization and contradictory fuzzy rules, which usually happen when building ANFIS. The clustering process in the input data space is accomplished based on a proposed merging-possibilistic clustering (MPC) algorithm. The effectiveness of this process is evaluated to resume a clustering process in the joint input-output data space. The optimal parameters obtained after completion of the clustering process are used to build ANFIS. Simulations based on a numerical data, 'Daily Data of Stock A', and measured data sets of a smart damper are performed to analyze and estimate accuracy. In addition, convergence and robustness of the proposed algorithm are investigated based on both theoretical and testing approaches.

Evaluation of Primers Targeting the Diazotroph Functional Gene and Development of NifMAP – A Bioinformatics Pipeline for Analyzing nifH Amplicon Data

PubMed Central

Angel, Roey; Nepel, Maximilian; Panhölzl, Christopher; Schmidt, Hannes; Herbold, Craig W.; Eichorst, Stephanie A.; Woebken, Dagmar

2018-01-01

Diazotrophic microorganisms introduce biologically available nitrogen (N) to the global N cycle through the activity of the nitrogenase enzyme. The genetically conserved dinitrogenase reductase (nifH) gene is phylogenetically distributed across four clusters (I–IV) and is widely used as a marker gene for N2 fixation, permitting investigators to study the genetic diversity of diazotrophs in nature and target potential participants in N2 fixation. To date there have been limited, standardized pipelines for analyzing the nifH functional gene, which is in stark contrast to the 16S rRNA gene. Here we present a bioinformatics pipeline for processing nifH amplicon datasets – NifMAP (“NifH MiSeq Illumina Amplicon Analysis Pipeline”), which as a novel aspect uses Hidden-Markov Models to filter out homologous genes to nifH. By using this pipeline, we evaluated the broadly inclusive primer pairs (Ueda19F–R6, IGK3–DVV, and F2–R6) that target the nifH gene. To evaluate any systematic biases, the nifH gene was amplified with the aforementioned primer pairs in a diverse collection of environmental samples (soils, rhizosphere and roots samples, biological soil crusts and estuarine samples), in addition to a nifH mock community consisting of six phylogenetically diverse members. We noted that all primer pairs co-amplified nifH homologs to varying degrees; up to 90% of the amplicons were nifH homologs with IGK3–DVV in some samples (rhizosphere and roots from tall oat-grass). In regards to specificity, we observed some degree of bias across the primer pairs. For example, primer pair F2–R6 discriminated against cyanobacteria (amongst others), yet captured many sequences from subclusters IIIE and IIIL-N. These aforementioned subclusters were largely missing by the primer pair IGK3–DVV, which also tended to discriminate against Alphaproteobacteria, but amplified sequences within clusters IIIC (affiliated with Clostridia) and clusters IVB and IVC. Primer pair Ueda19F–R6 exhibited the least bias and successfully captured diazotrophs in cluster I and subclusters IIIE, IIIL, IIIM, and IIIN, but tended to discriminate against Firmicutes and subcluster IIIC. Taken together, our newly established bioinformatics pipeline, NifMAP, along with our systematic evaluations of nifH primer pairs permit more robust, high-throughput investigations of diazotrophs in diverse environments. PMID:29760683

Evolution of phenotypic clusters through competition and local adaptation along an environmental gradient.

PubMed

Leimar, Olof; Doebeli, Michael; Dieckmann, Ulf

2008-04-01

We have analyzed the evolution of a quantitative trait in populations that are spatially extended along an environmental gradient, with gene flow between nearby locations. In the absence of competition, there is stabilizing selection toward a locally best-adapted trait that changes gradually along the gradient. According to traditional ideas, gradual spatial variation in environmental conditions is expected to lead to gradual variation in the evolved trait. A contrasting possibility is that the trait distribution instead breaks up into discrete clusters. Doebeli and Dieckmann (2003) argued that competition acting locally in trait space and geographical space can promote such clustering. We have investigated this possibility using deterministic population dynamics for asexual populations, analyzing our model numerically and through an analytical approximation. We examined how the evolution of clusters is affected by the shape of competition kernels, by the presence of Allee effects, and by the strength of gene flow along the gradient. For certain parameter ranges clustering was a robust outcome, and for other ranges there was no clustering. Our analysis shows that the shape of competition kernels is important for clustering: the sign structure of the Fourier transform of a competition kernel determines whether the kernel promotes clustering. Also, we found that Allee effects promote clustering, whereas gene flow can have a counteracting influence. In line with earlier findings, we could demonstrate that phenotypic clustering was favored by gradients of intermediate slope.

Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters.

PubMed

Lukashin, A V; Fuchs, R

2001-05-01

Cluster analysis of genome-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and samples. In the present paper, we focus on several important issues related to clustering algorithms that have not yet been fully studied. We describe a simple and robust algorithm for the clustering of temporal gene expression profiles that is based on the simulated annealing procedure. In general, this algorithm guarantees to eventually find the globally optimal distribution of genes over clusters. We introduce an iterative scheme that serves to evaluate quantitatively the optimal number of clusters for each specific data set. The scheme is based on standard approaches used in regular statistical tests. The basic idea is to organize the search of the optimal number of clusters simultaneously with the optimization of the distribution of genes over clusters. The efficiency of the proposed algorithm has been evaluated by means of a reverse engineering experiment, that is, a situation in which the correct distribution of genes over clusters is known a priori. The employment of this statistically rigorous test has shown that our algorithm places greater than 90% genes into correct clusters. Finally, the algorithm has been tested on real gene expression data (expression changes during yeast cell cycle) for which the fundamental patterns of gene expression and the assignment of genes to clusters are well understood from numerous previous studies.

Transient Maternal Hypothyroidism Alters Neural Progenitor Cells Resulting in Abnormal Brain Development

EPA Science Inventory

Heterotopias are a birth defect of the brain and have varying etiologies in humans. They are characterized as clusters of mislocalized neurons and are associated with disorders such as autism and epilepsy. We have previously characterized the robust penetrance of a cortical heter...

The intact dupA cluster is a more reliable Helicobacter pylori virulence marker than dupA alone.

PubMed

Jung, Sung Woo; Sugimoto, Mitsushige; Shiota, Seiji; Graham, David Y; Yamaoka, Yoshio

2012-01-01

The duodenal ulcer promoting (dupA) gene, located in the plasticity region of Helicobacter pylori, is associated with duodenal ulcer development. dupA was predicted to form a type IV secretory system (T4SS) with vir genes around dupA (dupA cluster). We investigated the prevalence of dupA and dupA clusters and clarified associations between the dupA cluster status and clinical outcomes in the U.S. population. In all, 245 H. pylori strains were examined using PCR to evaluate the status of dupA and the adjacent vir genes predicted to form T4SS, in addition to the status of cag pathogenicity island (PAI). The associations between dupA cluster status and interleukin-8 (IL-8) and IL-12 production were also examined. The presence of dupA and all adjacent vir genes were defined as a complete dupA cluster. Many variations related to the status of dupA and dupA cluster genes were identified. Concurrent H. pylori infection and the presence of a complete dupA cluster increases duodenal ulcer risk compared to H. pylori infection with incomplete dupA cluster or without the dupA gene independent on the cag PAI status (adjusted odds ratio, 2.13; 95% confidence interval, 1.13 to 4.03). Gastric mucosal IL-8 levels were also significantly higher in the complete dupA cluster group than in other groups (P=0.01). In conclusion, although the causal relationship between the dupA cluster and duodenal ulcer development is not proved, the presence of a complete dupA cluster but not dupA alone, is associated with duodenal ulcer development.

The Intact dupA Cluster Is a More Reliable Helicobacter pylori Virulence Marker than dupA Alone

PubMed Central

Jung, Sung Woo; Sugimoto, Mitsushige; Shiota, Seiji; Graham, David Y.

2012-01-01

The duodenal ulcer promoting (dupA) gene, located in the plasticity region of Helicobacter pylori, is associated with duodenal ulcer development. dupA was predicted to form a type IV secretory system (T4SS) with vir genes around dupA (dupA cluster). We investigated the prevalence of dupA and dupA clusters and clarified associations between the dupA cluster status and clinical outcomes in the U.S. population. In all, 245 H. pylori strains were examined using PCR to evaluate the status of dupA and the adjacent vir genes predicted to form T4SS, in addition to the status of cag pathogenicity island (PAI). The associations between dupA cluster status and interleukin-8 (IL-8) and IL-12 production were also examined. The presence of dupA and all adjacent vir genes were defined as a complete dupA cluster. Many variations related to the status of dupA and dupA cluster genes were identified. Concurrent H. pylori infection and the presence of a complete dupA cluster increases duodenal ulcer risk compared to H. pylori infection with incomplete dupA cluster or without the dupA gene independent on the cag PAI status (adjusted odds ratio, 2.13; 95% confidence interval, 1.13 to 4.03). Gastric mucosal IL-8 levels were also significantly higher in the complete dupA cluster group than in other groups (P = 0.01). In conclusion, although the causal relationship between the dupA cluster and duodenal ulcer development is not proved, the presence of a complete dupA cluster but not dupA alone, is associated with duodenal ulcer development. PMID:22038914

Diffuse reticuloendothelial system involvement in type IV glycogen storage disease with a novel GBE1 mutation: a case report and review.

PubMed

Magoulas, Pilar L; El-Hattab, Ayman W; Roy, Angshumoy; Bali, Deeksha S; Finegold, Milton J; Craigen, William J

2012-06-01

Glycogen storage disease type IV is a rare autosomal recessive disorder of glycogen metabolism caused by mutations in the GBE1 gene that encodes the 1,4-alpha-glucan-branching enzyme 1. Its clinical presentation is variable, with the most common form presenting in early childhood with primary hepatic involvement. Histologic manifestations in glycogen storage disease type IV typically consist of intracytoplasmic non-membrane-bound inclusions containing abnormally branched glycogen (polyglucosan bodies) within hepatocytes and myocytes. We report a female infant with classic hepatic form of glycogen storage disease type IV who demonstrated diffuse reticuloendothelial system involvement with the spleen, bone marrow, and lymph nodes infiltrated by foamy histiocytes with intracytoplasmic polyglucosan deposits. Sequence analysis of the GBE1 gene revealed compound heterozygosity for a previously described frameshift mutation (c.1239delT) and a novel missense mutation (c.1279G>A) that is predicted to alter a conserved glycine residue. GBE enzyme analysis revealed no detectable activity. A review of the literature for glycogen storage disease type IV patients with characterized molecular defects and deficient enzyme activity reveals most GBE1 mutations to be missense mutations clustering in the catalytic enzyme domain. Individuals with the classic hepatic form of glycogen storage disease type IV tend to be compound heterozygotes for null and missense mutations. Although the extensive reticuloendothelial system involvement that was observed in our patient is not typical of glycogen storage disease type IV, it may be associated with severe enzymatic deficiency and a poor outcome. Copyright © 2012 Elsevier Inc. All rights reserved.

The shape of galaxy dark matter halos in massive galaxy clusters: Insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-04-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and VLT/MUSE spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z=0.397, M(R < 200 kpc)=1.6×1014M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar halos are allowed, the model improves by 35%. This technique may provide a new way to investigate the processes and timescales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

Mechanism for Collective Cell Alignment in Myxococcus xanthus Bacteria

PubMed Central

Balagam, Rajesh; Igoshin, Oleg A.

2015-01-01

Myxococcus xanthus cells self-organize into aligned groups, clusters, at various stages of their lifecycle. Formation of these clusters is crucial for the complex dynamic multi-cellular behavior of these bacteria. However, the mechanism underlying the cell alignment and clustering is not fully understood. Motivated by studies of clustering in self-propelled rods, we hypothesized that M. xanthus cells can align and form clusters through pure mechanical interactions among cells and between cells and substrate. We test this hypothesis using an agent-based simulation framework in which each agent is based on the biophysical model of an individual M. xanthus cell. We show that model agents, under realistic cell flexibility values, can align and form cell clusters but only when periodic reversals of cell directions are suppressed. However, by extending our model to introduce the observed ability of cells to deposit and follow slime trails, we show that effective trail-following leads to clusters in reversing cells. Furthermore, we conclude that mechanical cell alignment combined with slime-trail-following is sufficient to explain the distinct clustering behaviors observed for wild-type and non-reversing M. xanthus mutants in recent experiments. Our results are robust to variation in model parameters, match the experimentally observed trends and can be applied to understand surface motility patterns of other bacterial species. PMID:26308508

The shape of galaxy dark matter haloes in massive galaxy clusters: insights from strong gravitational lensing

NASA Astrophysics Data System (ADS)

Jauzac, Mathilde; Harvey, David; Massey, Richard

2018-07-01

We assess how much unused strong lensing information is available in the deep Hubble Space Telescope imaging and Very Large Telescope/Multi Unit Spectroscopic Explorer spectroscopy of the Frontier Field clusters. As a pilot study, we analyse galaxy cluster MACS J0416.1-2403 (z = 0.397, M(R < 200 kpc) = 1.6 × 1014 M⊙), which has 141 multiple images with spectroscopic redshifts. We find that many additional parameters in a cluster mass model can be constrained, and that adding even small amounts of extra freedom to a model can dramatically improve its figures of merit. We use this information to constrain the distribution of dark matter around cluster member galaxies, simultaneously with the cluster's large-scale mass distribution. We find tentative evidence that some galaxies' dark matter has surprisingly similar ellipticity to their stars (unlike in the field, where it is more spherical), but that its orientation is often misaligned. When non-coincident dark matter and stellar haloes are allowed, the model improves by 35 per cent. This technique may provide a new way to investigate the processes and time-scales on which dark matter is stripped from galaxies as they fall into a massive cluster. Our preliminary conclusions will be made more robust by analysing the remaining five Frontier Field clusters.

Mapping Informative Clusters in a Hierarchial Framework of fMRI Multivariate Analysis

PubMed Central

Xu, Rui; Zhen, Zonglei; Liu, Jia

2010-01-01

Pattern recognition methods have become increasingly popular in fMRI data analysis, which are powerful in discriminating between multi-voxel patterns of brain activities associated with different mental states. However, when they are used in functional brain mapping, the location of discriminative voxels varies significantly, raising difficulties in interpreting the locus of the effect. Here we proposed a hierarchical framework of multivariate approach that maps informative clusters rather than voxels to achieve reliable functional brain mapping without compromising the discriminative power. In particular, we first searched for local homogeneous clusters that consisted of voxels with similar response profiles. Then, a multi-voxel classifier was built for each cluster to extract discriminative information from the multi-voxel patterns. Finally, through multivariate ranking, outputs from the classifiers were served as a multi-cluster pattern to identify informative clusters by examining interactions among clusters. Results from both simulated and real fMRI data demonstrated that this hierarchical approach showed better performance in the robustness of functional brain mapping than traditional voxel-based multivariate methods. In addition, the mapped clusters were highly overlapped for two perceptually equivalent object categories, further confirming the validity of our approach. In short, the hierarchical framework of multivariate approach is suitable for both pattern classification and brain mapping in fMRI studies. PMID:21152081

The Mass Function in h+(chi) Persei

NASA Astrophysics Data System (ADS)

Bragg, Ann; Kenyon, Scott

2000-08-01

Knowledge of the stellar initial mass function (IMF) is critical to understanding star formation and galaxy evolution. Past studies of the IMF in open clusters have primarily used luminosity functions to determine mass functions, frequently in relatively sparse clusters. Our goal with this project is to derive a reliable, well- sampled IMF for a pair of very dense young clusters (h+(chi) Persei) with ages, 1-2 × 10^7 yr (e.g., Vogt A& A 11:359), where stellar evolution theory is robust. We will construct the HR diagram using both photometry and spectral types to derive more accurate stellar masses and ages than are possible using photometry alone. Results from the two clusters will be compared to examine the universality of the IMF. We currently have a spectroscopic sample covering an area within 9 arc-minutes of the center of each cluster taken with the FAST Spectrograph. The sample is complete to V=15.4 and contains ~ 1000 stars. We request 2 nights at WIYN/HYDRA to extend this sample to deeper magnitudes, allowing us to determine the IMF of the clusters to a lower limiting mass and to search for a pre-main sequence, theoretically predicted to be present for clusters of this age. Note that both clusters are contained within a single HYDRA field.

Quasar outflows and AGN feedback in the extreme UV: HST/COS observations of HE 0238-1904

NASA Astrophysics Data System (ADS)

Arav, Nahum; Borguet, Benoit; Chamberlain, Carter; Edmonds, Doug; Danforth, Charles

2013-12-01

Spectroscopic observations of quasar outflows at rest-frame 500-1000 Å have immense diagnostic power. We present analyses of such data, where absorption troughs from O IV and O IV* allow us to obtain the distance of the outflows from the AGN and troughs from Ne VIII and Mg X reveal the warm absorber phase of the outflow. Their inferred column densities, combined with those of O VI, N IV and H I, yield two important results. (1) The outflow shows two ionization phases, where the high-ionization phase carries the bulk of the material. This is similar to the situation seen in X-ray warm absorber studies. Furthermore, the low-ionization phase is inferred to have a volume filling factor of 10-5-10-6. (2) We determine a distance of 3000 pc from the outflow to the central source using the O IV*/O IV column density ratio and the knowledge of the ionization parameter. Since this is a typical high-ionization outflow, we can determine robust values for the outflow's mass flux and kinetic luminosity of 40 M⊙ yr-1 and 1045 erg s-1, respectively, where the latter is roughly equal to 1 per cent of the bolometric luminosity. Such a large kinetic luminosity and mass flow rate measured in a typical high-ionization wind suggest that quasar outflows are a major contributor to AGN feedback mechanisms.

Evaluation of Title I ESEA Projects, 1971-1972. Volume IV, Auxiliary Services to Schools and Pupils.

ERIC Educational Resources Information Center

Chern, Hermine J.; And Others

This final volume of reports on the evaluation of ESEA Title I projects in Philadelphia 1971-1972 is concerned with the cluster "Auxiliary Services to Schools and Pupils." In this report are examined the theoretical bases for the creation and integration of projects directed toward the broad-based career development goals of the School…

Personality Disorder in Adult Attention-Deficit/Hyperactivity Disorder: Attrition and Change During Long-term Treatment.

PubMed

Gift, Thomas E; Reimherr, Frederick W; Marchant, Barrie K; Steans, Tammy A; Wender, Paul H

2016-05-01

Personality disorders (PDs) are commonly found in adults with attention-deficit/hyperactivity disorder (ADHD) and are associated with increased ADHD symptoms and psychosocial impairment. To assess the impact of PDs or personality traits on retention rates in ADHD trials and whether treating ADHD affects the expression of PD, data were analyzed from 2 methylphenidate trials. Assessment of PDs and personality traits included using the Wisconsin Personality Disorders Inventory IV and the Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition Personality Disorders. Attention-deficit/hyperactivity disorder symptoms were evaluated using the Wender-Reimherr Adult Attention Deficit Disorder Scale. Major findings were that subjects with cluster A, cluster B, passive-aggressive, or more than 1 PD showed more attrition. Subjects dropping out also had more schizoid and narcissistic traits. Attention-deficit/hyperactivity disorder symptoms (p < 0.001) and all personality traits (range, p = 0.03 to p = 0.001) improved, but there was almost no correlation between changes on these 2 measures. Conversely, of 11 Wisconsin Personality Disorders Inventory IV items that improved most, 8 resembled ADHD or oppositional defiant disorder symptoms.

K2: A NEW METHOD FOR THE DETECTION OF GALAXY CLUSTERS BASED ON CANADA-FRANCE-HAWAII TELESCOPE LEGACY SURVEY MULTICOLOR IMAGES

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

Thanjavur, Karun; Willis, Jon; Crampton, David, E-mail: karun@uvic.c

2009-11-20

We have developed a new method, K2, optimized for the detection of galaxy clusters in multicolor images. Based on the Red Sequence approach, K2 detects clusters using simultaneous enhancements in both colors and position. The detection significance is robustly determined through extensive Monte Carlo simulations and through comparison with available cluster catalogs based on two different optical methods, and also on X-ray data. K2 also provides quantitative estimates of the candidate clusters' richness and photometric redshifts. Initially, K2 was applied to the two color (gri) 161 deg{sup 2} images of the Canada-France-Hawaii Telescope Legacy Survey Wide (CFHTLS-W) data. Our simulationsmore » show that the false detection rate for these data, at our selected threshold, is only approx1%, and that the cluster catalogs are approx80% complete up to a redshift of z = 0.6 for Fornax-like and richer clusters and to z approx 0.3 for poorer clusters. Based on the g-, r-, and i-band photometric catalogs of the Terapix T05 release, 35 clusters/deg{sup 2} are detected, with 1-2 Fornax-like or richer clusters every 2 deg{sup 2}. Catalogs containing data for 6144 galaxy clusters have been prepared, of which 239 are rich clusters. These clusters, especially the latter, are being searched for gravitational lenses-one of our chief motivations for cluster detection in CFHTLS. The K2 method can be easily extended to use additional color information and thus improve overall cluster detection to higher redshifts. The complete set of K2 cluster catalogs, along with the supplementary catalogs for the member galaxies, are available on request from the authors.« less

Effects of bfp Mutations on Biogenesis of Functional Enteropathogenic Escherichia coli Type IV Pili

PubMed Central

Anantha, Ravi P.; Stone, Kelly D.; Donnenberg, Michael S.

2000-01-01

Enteropathogenic Escherichia coli expresses a type IV fimbria known as the bundle-forming pilus (BFP) that is required for autoaggregation and localized adherence (LA) to host cells. A cluster of 14 genes is sufficient to reconstitute BFP biogenesis in a laboratory strain of E. coli. We have undertaken a systematic mutagenesis of the individual genes to determine the effect of each mutation on BFP biogenesis and LA. Here we report the construction and analysis of nonpolar mutations in six genes of the bfp cluster, bfpG, bfpB, bfpC, bfpD, bfpP, and bfpH, as well as the further analysis of a previously described bfpA mutant strain that is unable to express bundlin, the pilin protein. We found that mutations in bfpB, which encodes an outer membrane protein; bfpD, which encodes a putative nucleotide-binding protein; and bfpG and bfpC, which do not have sequence homologues in other type IV pilus systems, do not affect prebundlin expression or processing but block both BFP biogenesis and LA. The mutation in bfpP, the prepilin peptidase gene, does not affect prebundlin expression but blocks signal sequence cleavage of prebundlin, BFP biogenesis, and LA. The mutation in bfpH, which is predicted to encode a lytic transglycosylase, has no effect on prebundlin expression, prebundlin processing, BFP biogenesis, or LA. For each mutant for which altered phenotypes were detected, complementation with a plasmid containing the corresponding wild-type allele restored the wild-type phenotypes. We also found that association of prebundlin or bundlin with sucrose density flotation gradient fractions containing both inner and outer membrane proteins does not require any accessory proteins. These studies indicate that many bfp gene products are required for biogenesis of functional type IV pili but that mutations in the individual genes do not lead to the identification of new phases of pilus assembly. PMID:10762251

Bipolar obsessive-compulsive disorder and personality disorders.

PubMed

Maina, Giuseppe; Albert, Umberto; Pessina, Enrico; Bogetto, Filippo

2007-11-01

Relatively few systematic data exist on the clinical impact of bipolar comorbidity in obsessive-compulsive disorder (OCD) and no studies have investigated the influence of such a comorbidity on the prevalence and pattern of Axis II comorbidity. The aim of the present study was to explore the comorbidity of personality disorders in a group of patients with OCD and comorbid bipolar disorder (BD). The sample consisted of 204 subjects with a principal diagnosis of OCD (DSM-IV) and a Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) score>or=16 recruited from all patients consecutively referred to the Anxiety and Mood Disorders Unit, Department of Neuroscience, University of Turin over a period of 5 years (January 1998-December 2002). Diagnostic evaluation and Axis I comorbidities were collected by means of the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I). Personality status was assessed by using the Structured Clinical Interview for DSM-IV Axis II Disorders (SCID-II). Socio-demographic and clinical features (including Axis II comorbidities) were compared between OCD patients with and without a lifetime comorbidity of BD. A total of 21 patients with OCD (10.3%) met DSM-IV criteria for a lifetime BD diagnosis: 4 (2.0%) with BD type I and 17 (8.3%) with BD type II. Those without a BD diagnosis showed significantly higher rates of male gender, sexual and hoarding obsessions, repeating compulsions and lifetime comorbid substance use disorders, when compared with patients with BD/OCD. With regard to personality disorders, those with BD/OCD showed higher prevalence rates of Cluster A (42.9% versus 21.3%; p=0.027) and Cluster B (57.1% versus 29.0%; p=0.009) personality disorders. Narcissistic and antisocial personality disorders were more frequent in BD/OCD. Our results point towards clinically relevant effects of comorbid BD on the personality profiles of OCD patients, with higher rates of narcissistic and antisocial personality disorders in BD/OCD patients.

Winds in hot main-sequence stars near the static limit

NASA Technical Reports Server (NTRS)

Morrison, Nancy D.

1995-01-01

This project began with the acquisition of short-wavelength, high-dispersion IUE spectra of selected late O- and early B-type stars that are near the main sequence in open clusters and associations. The profiles of the resonance lines of N(V), Si(IV), and C(IV) were studied, and we found that the C(IV) lines are the most sensitive indicators of mass loss (stellar winds) in stars of this type. The mass loss manifests itself as an extension of the short-wavelength absorption wing of the doublet, while there is no P Cygni-type emission on the long-wavelength side of the line profile. We investigated whether the short-wavelength extension could be caused by blended lines of other ionic species formed in the photosphere. Although blending is present and introduces uncertainty into the estimation of the precise location on the main sequence of the onset of the mass-loss signature, it is a crucial issue only in a few marginal cases. Mass loss certainly overwhelms blending in its influence on the spectrum between spectral types B0 and B1 (effective temperatures in the range 25,000-27,000 K). We defined a parameter called P(sub w), to describe the degree of asymmetry of the C(IV) resonance-line profile, and we studied the dependence of this parameter on the fundamental stellar parameters. For this purpose, we derived new estimates of the stellar T(eff) and log g from a non-LTE, line-blanketed model-atmosphere analysis of these stars (Grigsby, Morrison, and Anderson 1992). In order to estimate the stellar luminosities, we performed an exhaustive search of the literature for the most reliable available estimates of the distances of the clusters and associations to which the program stars belong. The dependence of P(sub w) on stellar temperature and luminosity is also studied.

A TRAJECTORY-CLUSTERING CORRELATION METHODOLOGY FOR EXAMINING THE LONG-RANGE TRANSPORT OF AIR POLLUTANTS. (R825260)

EPA Science Inventory

We present a robust methodology for examining the relationship between synoptic-scale atmospheric transport patterns and pollutant concentration levels observed at a site. Our approach entails calculating a large number of back-trajectories from the observational site over a long...

Ultra-diffuse cluster galaxies as key to the MOND cluster conundrum

NASA Astrophysics Data System (ADS)

Milgrom, Mordehai

2015-12-01

Modified Newtonian Dynamics (MOND) reduces greatly the mass discrepancy in clusters of galaxies,but does leave a global discrepancy of about a factor of 2 (epitomized by the structure of the Bullet Cluster). It has been proposed, within the minimalist and purist MOND, that clusters harbour some indigenous, yet undetected, cluster baryonic (dark) matter (CBDM), whose total amount is comparable with that of the observed hot gas. Koda et al. have recently identified more than a thousand ultra-diffuse, galaxy-like objects (UDGs) in the Coma cluster. These, they argue, require, within Newtonian dynamics, that they are much more massive than their observed stellar component. Here, I propound that some of the CBDM is internal to UDGs, which endows them with robustness. The rest of the CBDM objects formed in now-disrupted kin of the UDGs, and is dispersed in the intracluster medium. The discovery of cluster UDGs is not in itself a resolution of the MOND cluster conundrum, but it lends greater plausibility to CBDM as its resolution. Alternatively, if the UDGs are only now falling into Coma, their large size and very low surface brightness could result from the inflation due to the MOND, variable external-field effect (EFE). I also consider briefly solutions to the conundrum that invoke more elaborate extensions of purist MOND, e.g. that in clusters, the MOND constant takes up larger than canonical values of the MOND constant. Whatever solves the cluster conundrum within MOND might also naturally account for UDGs.

On Wiener polarity index of bicyclic networks.

PubMed

Ma, Jing; Shi, Yongtang; Wang, Zhen; Yue, Jun

2016-01-11

Complex networks are ubiquitous in biological, physical and social sciences. Network robustness research aims at finding a measure to quantify network robustness. A number of Wiener type indices have recently been incorporated as distance-based descriptors of complex networks. Wiener type indices are known to depend both on the network's number of nodes and topology. The Wiener polarity index is also related to the cluster coefficient of networks. In this paper, based on some graph transformations, we determine the sharp upper bound of the Wiener polarity index among all bicyclic networks. These bounds help to understand the underlying quantitative graph measures in depth.

The Distribution and Ages of Star Clusters in the Small Magellanic Cloud: Constraints on the Interaction History of the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Bitsakis, Theodoros; González-Lópezlira, R. A.; Bonfini, P.; Bruzual, G.; Maravelias, G.; Zaritsky, D.; Charlot, S.; Ramírez-Siordia, V. H.

2018-02-01

We present a new study of the spatial distribution and ages of the star clusters in the Small Magellanic Cloud (SMC). To detect and estimate the ages of the star clusters we rely on the new fully automated method developed by Bitsakis et al. Our code detects 1319 star clusters in the central 18 deg2 of the SMC we surveyed (1108 of which have never been reported before). The age distribution of those clusters suggests enhanced cluster formation around 240 Myr ago. It also implies significant differences in the cluster distribution of the bar with respect to the rest of the galaxy, with the younger clusters being predominantly located in the bar. Having used the same setup, and data from the same surveys as for our previous study of the LMC, we are able to robustly compare the cluster properties between the two galaxies. Our results suggest that the bulk of the clusters in both galaxies were formed approximately 300 Myr ago, probably during a direct collision between the two galaxies. On the other hand, the locations of the young (≤50 Myr) clusters in both Magellanic Clouds, found where their bars join the H I arms, suggest that cluster formation in those regions is a result of internal dynamical processes. Finally, we discuss the potential causes of the apparent outside-in quenching of cluster formation that we observe in the SMC. Our findings are consistent with an evolutionary scheme where the interactions between the Magellanic Clouds constitute the major mechanism driving their overall evolution.

Gender differences in psychiatric disorders and clusters of self-esteem among detained adolescents.

PubMed

Van Damme, Lore; Colins, Olivier F; Vanderplasschen, Wouter

2014-12-30

Detained minors display substantial mental health needs. This study focused on two features (psychopathology and self-esteem) that have received considerable attention in the literature and clinical work, but have rarely been studied simultaneously in detained youths. The aims of this study were to examine gender differences in psychiatric disorders and clusters of self-esteem, and to test the hypothesis that the cluster of adolescents with lower (versus higher) levels of self-esteem have higher rates of psychiatric disorders. The prevalence of psychiatric disorders was assessed in 440 Belgian, detained adolescents using the Diagnostic Interview Schedule for Children-IV. Self-esteem was assessed using the Self-perception Profile for Adolescents. Model-based cluster analyses were performed to identify youths with lower and/or higher levels of self-esteem across several domains. Girls have higher rates for most psychiatric disorders and lower levels of self-esteem than boys. A higher number of clusters was identified in boys (four) than girls (three). Generally, the cluster of adolescents with lower (versus higher) levels of self-esteem had a higher prevalence of psychiatric disorders. These results suggest that the detection of low levels of self-esteem in adolescents, especially girls, might help clinicians to identify a subgroup of detained adolescents with the highest prevalence of psychopathology.

Relating DSM-5 section III personality traits to section II personality disorder diagnoses.

PubMed

Morey, L C; Benson, K T; Skodol, A E

2016-02-01

The DSM-5 Personality and Personality Disorders Work Group formulated a hybrid dimensional/categorical model that represented personality disorders as combinations of core impairments in personality functioning with specific configurations of problematic personality traits. Specific clusters of traits were selected to serve as indicators for six DSM categorical diagnoses to be retained in this system - antisocial, avoidant, borderline, narcissistic, obsessive-compulsive and schizotypal personality disorders. The goal of the current study was to describe the empirical relationships between the DSM-5 section III pathological traits and DSM-IV/DSM-5 section II personality disorder diagnoses. Data were obtained from a sample of 337 clinicians, each of whom rated one of his or her patients on all aspects of the DSM-IV and DSM-5 proposed alternative model. Regression models were constructed to examine trait-disorder relationships, and the incremental validity of core personality dysfunctions (i.e. criterion A features for each disorder) was examined in combination with the specified trait clusters. Findings suggested that the trait assignments specified by the Work Group tended to be substantially associated with corresponding DSM-IV concepts, and the criterion A features provided additional diagnostic information in all but one instance. Although the DSM-5 section III alternative model provided a substantially different taxonomic structure for personality disorders, the associations between this new approach and the traditional personality disorder concepts in DSM-5 section II make it possible to render traditional personality disorder concepts using alternative model traits in combination with core impairments in personality functioning.

THE CURIOUS CASE OF THE ALPHA PERSEI CORONA: A DWARF IN SUPERGIANT'S CLOTHING?

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

Ayres, Thomas R., E-mail: Thomas.Ayres@Colorado.edu

2011-09-10

Alpha Persei (HD 20902: F5 Iab) is a luminous, nonvariable supergiant located at the blue edge of the Cepheid instability strip. It is one of the brightest coronal X-ray sources in the young open cluster bearing its name, yet warm supergiants as a class generally avoid conspicuous high-energy activity. The Cosmic Origins Spectrograph on the Hubble Space Telescope has recently uncovered additional oddities. The 1290-1430 A far-ultraviolet (FUV) spectrum of {alpha} Per is dominated by photospheric continuum emission, with numerous superposed absorption features, mainly stellar. However, the normal proxies of coronal activity, such as the Si IV 1400 A doubletmore » (T {approx} 8 x 10{sup 4} K), are very weak, as are the chromospheric C II 1335 A multiplet (T {approx} 3 x 10{sup 4} K) and O I 1305 A triplet. In fact, the Si IV features of {alpha} Per are not only narrower than those of later, G-type supergiants of similar L{sub X}/L{sub bol}, but are also fainter (in L{sub SiIV}/L{sub bol}) by two orders of magnitude. Further, a reanalysis of the ROSAT pointing on {alpha} Per finds the X-ray centroid offset from the stellar position by 9'', at a moderate level of significance. The FUV and X-ray discrepancies raise the possibility that the coronal source might be unrelated to the supergiant, perhaps an accidentally close dwarf cluster member; heretofore unrecognized in the optical, lost in the glare of the bright star.« less

A comparative theoretical study on the structural, electronic and nonlinear optical features of B12N12 and Al12N12 nanoclusters with the groups III, IV and V dopants

NASA Astrophysics Data System (ADS)

Shakerzadeh, Ehsan; Barazesh, Neda; Talebi, Sima Zargar

2014-12-01

The structural, electronic and nonlinear optical properties of the two important fullerene-like cages of B12N12 and Al12N12 nanostructures with the groups III, IV and V dopants are investigated through density functional theory (DFT) calculations. It has been found that doping process induces local deformation at bond lengths near the doping site. Natural bond orbital (NBO) analyses are also performed for scrutinizing the structural properties of the considered nanoclusters. The results indicate that the groups III, IV and V dopants remarkably narrow the energy gap of the B12N12 nanocluster. On the other hand, although the energy gap of Al12N12 nanocluster is insensitive to groups III and V dopants; the carbon, silicon and germanium dopants extremely reduce the energy gap of this cluster. It seems that the electronic character of the B12N12 and Al12N12 nanocluster is sensitive to the dopants and it could be adjusted by particular impurity. Moreover the considered dopants induce hyperpolarizability in both of the considered nanoclusters. Interestingly, the replacing aluminum atom by carbon one in Al12N12 nanocluster (CAl11N12) leads to an extremely large hyperpolarizability value of 4358.77 a.u., which is the largest one among the considered doped clusters. It shows that the doping process plays an important role in enhancing the first hyperpolarizability of the B12N12 and Al12N12 nanoclusters.

Identifying a Robust and Practical Quasar Accretion-Rate Indicator Using the Chandra Archive

NASA Astrophysics Data System (ADS)

Shemmer, Ohad

2017-09-01

Understanding the rapid growth of supermassive black holes and the assembly of their host galaxies is severely limited by the lack of reliable estimates of black-hole mass and accretion rate in distant quasars. We propose to utilize the Chandra archive to identify the most reliable and practical Eddington-ratio indicator by investigating diagnostics of quasar accretion power in the hard-X-ray, C IV, and Hbeta spectral bands of a carefully-selected sample of optically-selected sources. We will perform a ``stress test'' to each of these diagnostics, relying critically on the hard-X-ray observable properties, and deliver a prescription for the most robust Eddington-ratio estimate that can be utilized economically at the highest accessible redshifts.

Relationship between Oral Malodor and the Global Composition of Indigenous Bacterial Populations in Saliva ▿

PubMed Central

Takeshita, Toru; Suzuki, Nao; Nakano, Yoshio; Shimazaki, Yoshihiro; Yoneda, Masahiro; Hirofuji, Takao; Yamashita, Yoshihisa

2010-01-01

Oral malodor develops mostly from the metabolic activities of indigenous bacterial populations within the oral cavity, but whether healthy or oral malodor-related patterns of the global bacterial composition exist remains unclear. In this study, the bacterial compositions in the saliva of 240 subjects complaining of oral malodor were divided into groups based on terminal-restriction fragment length polymorphism (T-RFLP) profiles using hierarchical cluster analysis, and the patterns of the microbial community composition of those exhibiting higher and lower malodor were explored. Four types of bacterial community compositions were detected (clusters I, II, III, and IV). Two parameters for measuring oral malodor intensity (the concentration of volatile sulfur compounds in mouth air and the organoleptic score) were noticeably lower in cluster I than in the other clusters. Using multivariate analysis, the differences in the levels of oral malodor were significant after adjustment for potential confounding factors such as total bacterial count, mean periodontal pocket depth, and tongue coating score (P < 0.001). Among the four clusters with different proportions of indigenous members, the T-RFLP profiles of cluster I were implicated as the bacterial populations with higher proportions of Streptococcus, Granulicatella, Rothia, and Treponema species than those of the other clusters. These results clearly correlate the global composition of indigenous bacterial populations with the severity of oral malodor. PMID:20228112

VRprofile: gene-cluster-detection-based profiling of virulence and antibiotic resistance traits encoded within genome sequences of pathogenic bacteria.

PubMed

Li, Jun; Tai, Cui; Deng, Zixin; Zhong, Weihong; He, Yongqun; Ou, Hong-Yu

2017-01-10

VRprofile is a Web server that facilitates rapid investigation of virulence and antibiotic resistance genes, as well as extends these trait transfer-related genetic contexts, in newly sequenced pathogenic bacterial genomes. The used backend database MobilomeDB was firstly built on sets of known gene cluster loci of bacterial type III/IV/VI/VII secretion systems and mobile genetic elements, including integrative and conjugative elements, prophages, class I integrons, IS elements and pathogenicity/antibiotic resistance islands. VRprofile is thus able to co-localize the homologs of these conserved gene clusters using HMMer or BLASTp searches. With the integration of the homologous gene cluster search module with a sequence composition module, VRprofile has exhibited better performance for island-like region predictions than the other widely used methods. In addition, VRprofile also provides an integrated Web interface for aligning and visualizing identified gene clusters with MobilomeDB-archived gene clusters, or a variety set of bacterial genomes. VRprofile might contribute to meet the increasing demands of re-annotations of bacterial variable regions, and aid in the real-time definitions of disease-relevant gene clusters in pathogenic bacteria of interest. VRprofile is freely available at http://bioinfo-mml.sjtu.edu.cn/VRprofile. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Unveiling the Dynamical State of Massive Clusters through the ICL Fraction

NASA Astrophysics Data System (ADS)

Jiménez-Teja, Yolanda; Dupke, Renato; Benítez, Narciso; Koekemoer, Anton M.; Zitrin, Adi; Umetsu, Keiichi; Ziegler, Bodo L.; Frye, Brenda L.; Ford, Holland; Bouwens, Rychard J.; Bradley, Larry D.; Broadhurst, Thomas; Coe, Dan; Donahue, Megan; Graves, Genevieve J.; Grillo, Claudio; Infante, Leopoldo; Jouvel, Stephanie; Kelson, Daniel D.; Lahav, Ofer; Lazkoz, Ruth; Lemze, Dorom; Maoz, Dan; Medezinski, Elinor; Melchior, Peter; Meneghetti, Massimo; Mercurio, Amata; Merten, Julian; Molino, Alberto; Moustakas, Leonidas A.; Nonino, Mario; Ogaz, Sara; Riess, Adam G.; Rosati, Piero; Sayers, Jack; Seitz, Stella; Zheng, Wei

2018-04-01

We have selected a sample of 11 massive clusters of galaxies observed by the Hubble Space Telescope in order to study the impact of the dynamical state on the intracluster light (ICL) fraction, the ratio of total integrated ICL to the total galaxy member light. With the exception of the Bullet cluster, the sample is drawn from the Cluster Lensing and Supernova Survey and the Frontier Fields program, containing five relaxed and six merging clusters. The ICL fraction is calculated in three optical filters using the CHEFs ICL estimator, a robust and accurate algorithm free of a priori assumptions. We find that the ICL fraction in the three bands is, on average, higher for the merging clusters, ranging between ∼7% and 23%, compared with the ∼2%–11% found for the relaxed systems. We observe a nearly constant value (within the error bars) in the ICL fraction of the regular clusters at the three wavelengths considered, which would indicate that the colors of the ICL and the cluster galaxies are, on average, coincident and, thus, so are their stellar populations. However, we find a higher ICL fraction in the F606W filter for the merging clusters, consistent with an excess of lower-metallicity/younger stars in the ICL, which could have migrated violently from the outskirts of the infalling galaxies during the merger event.

The Atacama Cosmology Telescope: High-Resolution Sunyaev-Zel'dovich Array Observations of ACT SZE-Selected Clusters from the Equatorial Strip

NASA Technical Reports Server (NTRS)

Reese, Erik D.; Mroczkowski, Tony; Menanteau, Felipe; Hilton, Matt; Sievers, Jonathan; Aguirre, Paula; Appel, John William; Baker, Andrew J.; Bond, J. Richard; Das, Sudeep;

The Atacama Cosmology Telescope: High-Resolution Sunyaev-Zeldovich Array Observations of ACT SZE-Selected Clusters from the Equatorial Strip

NASA Technical Reports Server (NTRS)

Reese, Erik; Mroczkowski, Tony; Menateau, Felipe; Hilton, Matt; Sievers, Jonathan; Aguirre, Paula; Appel, John William; Baker, Andrew J.; Bond, J. Richard; Das, Sudeep;

Clustering Analysis of Antibiograms and Antibiogram Types of Streptococcus agalactiae Strains from Tilapia in China.

PubMed

Liu, Chan; Feng, Juan; Zhang, Defeng; Xie, Yundan; Li, Anxing; Wang, Jiangyong; Su, Youlu

2018-05-11

In view of the changing antibiotic-resistance profiles of Streptococcus agalactiae from tilapia in China, antimicrobial susceptibilities of 75 S. agalactiae strains were determined by the disc diffusion method, and cluster analyses of the antibiograms and antibiogram types were performed. All strains displayed multidrug resistance (MDR). The antimicrobial-resistance rates were highest (>90%) to aminoglycosides, sulfonamides, pipemidic acid, and norfloxacin, followed by penicillin, ampicillin, and ciprofloxacin (26.7-38.7%); those to furadantin, lincomycin, erythromycin, ofloxacin, tetracycline, and florfenicol were low (<10%), and no resistance to vancomycin, cefalexin, cefoxitin, amoxicillin, medemycin, doxitard, oxytetracycline, rifampin, chloramphenicol, or thiamphenicol was detected. Statistical analysis showed that the resistance rate to ciprofloxacin increased significantly in 2016 (p = 0.009), whereas that to trimethoprim/sulfamethoxazole decreased (p = 0.017). Cluster analyses identified that the strains had 23 antibiogram types (A-W) and clustered in five groups (Groups I-V). The strains with higher antimicrobial resistance mainly clustered in Groups I and II. Our results show that the antibiograms varied with time and by location and that antibiogram types are constantly updating and expanding. Effective measures must be taken to reduce the antimicrobial resistance and spread of MDR strains.

Implementation and Testing of the JANUS Standard with SSC Pacific’s Software-Defined Acoustic Modem

DTIC Science & Technology

2017-10-01

Communications Outpost (FDECO) Innovative Naval Prototype (INP) Program by the Advanced Photonic Technologies Branch (Code 55360), Space and Naval Warfare...underwater acoustic communication operations with NATO and non-NATO military and civilian maritime assets. iv ACRONYMS SPAWAR Space and Naval Warfare...the center frequency [1]. The ease of implementation and proven robustness in harsh underwater acoustic communication channels paved the way for

An Examination of a Proposed DSM-IV Pathological Gambling Hierarchy in a Treatment Seeking Population: Similarities with Substance Dependence and Evidence for Three Classification Systems.

PubMed

Christensen, Darren R; Jackson, Alun C; Dowling, Nicki A; Volberg, Rachel A; Thomas, Shane A

2015-09-01

Toce-Gerstein et al. (Addiction 98:1661-1672, 2003) investigated the distribution of Diagnostic and Statistical Manual for Mental Disorders, 4th edition (DSM-IV) pathological gambling criteria endorsement in a U.S. community sample for those people endorsing a least one of the DSM-IV criteria (n = 399). They proposed a hierarchy of gambling disorders where endorsement of 1-2 criteria were deemed 'At-Risk', 3-4 'Problem gamblers', 5-7 'Low Pathological', and 8-10 'High Pathological' gamblers. This article examines these claims in a larger Australian treatment seeking population. Data from 4,349 clients attending specialist problem gambling services were assessed for meeting the ten DSM-IV pathological gambling criteria. Results found higher overall criteria endorsement frequencies, three components, a direct relationship between criteria endorsement and gambling severity, clustering of criteria similar to the Toce-Gerstein et al. taxonomy, high accuracy scores for numerical and criteria specific taxonomies, and also high accuracy scores for dichotomous pathological gambling diagnoses. These results suggest significant complexities in the frequencies of criteria reports and relationships between criteria.

VizieR Online Data Catalog: HST Frontier Fields Herschel sources (Rawle+, 2016)

NASA Astrophysics Data System (ADS)

Rawle, T. D.; Altieri, B.; Egami, E.; Perez-Gonzalez, P. G.; Boone, F.; Clement, B.; Ivison, R. J.; Richard, J.; Rujopakarn, W.; Valtchanov, I.; Walth, G.; Weiner, B. J.; Blain, A. W.; Dessauges-Zavadsky, M.; Kneib, J.-P.; Lutz, D.; Rodighiero, G.; Schaerer, D.; Smail, I.

2017-07-01

We present a complete census of the 263 Herschel-detected sources within the HST Frontier Fields, including 163 lensed sources located behind the clusters. Our primary aim is to provide a robust legacy catalogue of the Herschel fluxes, which we combine with archival data from Spitzer and WISE to produce IR SEDs. We optimally combine the IR photometry with data from HST, VLA and ground-based observatories in order to identify optical counterparts and gain source redshifts. Each cluster is observed in two distinct regions, referred to as the central and parallel footprints. (2 data files).

Assessment of interaction-strength interpolation formulas for gold and silver clusters

NASA Astrophysics Data System (ADS)

Giarrusso, Sara; Gori-Giorgi, Paola; Della Sala, Fabio; Fabiano, Eduardo

2018-04-01

The performance of functionals based on the idea of interpolating between the weak- and the strong-interaction limits the global adiabatic-connection integrand is carefully studied for the challenging case of noble-metal clusters. Different interpolation formulas are considered and various features of this approach are analyzed. It is found that these functionals, when used as a correlation correction to Hartree-Fock, are quite robust for the description of atomization energies, while performing less well for ionization potentials. Future directions that can be envisaged from this study and a previous one on main group chemistry are discussed.

Effective return, risk aversion and drawdowns

NASA Astrophysics Data System (ADS)

Dacorogna, Michel M.; Gençay, Ramazan; Müller, Ulrich A.; Pictet, Olivier V.

2001-01-01

We derive two risk-adjusted performance measures for investors with risk averse preferences. Maximizing these measures is equivalent to maximizing the expected utility of an investor. The first measure, Xeff, is derived assuming a constant risk aversion while the second measure, Reff, is based on a stronger risk aversion to clustering of losses than of gains. The clustering of returns is captured through a multi-horizon framework. The empirical properties of Xeff, Reff are studied within the context of real-time trading models for foreign exchange rates and their properties are compared to those of more traditional measures like the annualized return, the Sharpe Ratio and the maximum drawdown. Our measures are shown to be more robust against clustering of losses and have the ability to fully characterize the dynamic behaviour of investment strategies.

SLURM: Simple Linux Utility for Resource Management

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

Jette, M; Dunlap, C; Garlick, J

2002-04-24

Simple Linux Utility for Resource Management (SLURM) is an open source, fault-tolerant, and highly scalable cluster management and job scheduling system for Linux clusters of thousands of nodes. Components include machine status, partition management, job management, and scheduling modules. The design also includes a scalable, general-purpose communication infrastructure. Development will take place in four phases: Phase I results in a solid infrastructure; Phase II produces a functional but limited interactive job initiation capability without use of the interconnect/switch; Phase III provides switch support and documentation; Phase IV provides job status, fault-tolerance, and job queuing and control through Livermore's Distributed Productionmore » Control System (DPCS), a meta-batch and resource management system.« less

The Small World of Psychopathology

PubMed Central

Borsboom, Denny; Cramer, Angélique O. J.; Schmittmann, Verena D.; Epskamp, Sacha; Waldorp, Lourens J.

2011-01-01

Background Mental disorders are highly comorbid: people having one disorder are likely to have another as well. We explain empirical comorbidity patterns based on a network model of psychiatric symptoms, derived from an analysis of symptom overlap in the Diagnostic and Statistical Manual of Mental Disorders-IV (DSM-IV). Principal Findings We show that a) half of the symptoms in the DSM-IV network are connected, b) the architecture of these connections conforms to a small world structure, featuring a high degree of clustering but a short average path length, and c) distances between disorders in this structure predict empirical comorbidity rates. Network simulations of Major Depressive Episode and Generalized Anxiety Disorder show that the model faithfully reproduces empirical population statistics for these disorders. Conclusions In the network model, mental disorders are inherently complex. This explains the limited successes of genetic, neuroscientific, and etiological approaches to unravel their causes. We outline a psychosystems approach to investigate the structure and dynamics of mental disorders. PMID:22114671

Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution

PubMed Central

Lo, Kenneth

2011-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components. PMID:22125375

Flexible mixture modeling via the multivariate t distribution with the Box-Cox transformation: an alternative to the skew-t distribution.

PubMed

Lo, Kenneth; Gottardo, Raphael

2012-01-01

Cluster analysis is the automated search for groups of homogeneous observations in a data set. A popular modeling approach for clustering is based on finite normal mixture models, which assume that each cluster is modeled as a multivariate normal distribution. However, the normality assumption that each component is symmetric is often unrealistic. Furthermore, normal mixture models are not robust against outliers; they often require extra components for modeling outliers and/or give a poor representation of the data. To address these issues, we propose a new class of distributions, multivariate t distributions with the Box-Cox transformation, for mixture modeling. This class of distributions generalizes the normal distribution with the more heavy-tailed t distribution, and introduces skewness via the Box-Cox transformation. As a result, this provides a unified framework to simultaneously handle outlier identification and data transformation, two interrelated issues. We describe an Expectation-Maximization algorithm for parameter estimation along with transformation selection. We demonstrate the proposed methodology with three real data sets and simulation studies. Compared with a wealth of approaches including the skew-t mixture model, the proposed t mixture model with the Box-Cox transformation performs favorably in terms of accuracy in the assignment of observations, robustness against model misspecification, and selection of the number of components.

Definition and characterization of an extended social-affective default network.

PubMed

Amft, Maren; Bzdok, Danilo; Laird, Angela R; Fox, Peter T; Schilbach, Leonhard; Eickhoff, Simon B

2015-03-01

Recent evidence suggests considerable overlap between the default mode network (DMN) and regions involved in social, affective and introspective processes. We considered these overlapping regions as the social-affective part of the DMN. In this study, we established a robust mapping of the underlying brain network formed by these regions and those strongly connected to them (the extended social-affective default network). We first seeded meta-analytic connectivity modeling and resting-state analyses in the meta-analytically defined DMN regions that showed statistical overlap with regions associated with social and affective processing. Consensus connectivity of each seed was subsequently delineated by a conjunction across both connectivity analyses. We then functionally characterized the ensuing regions and performed several cluster analyses. Among the identified regions, the amygdala/hippocampus formed a cluster associated with emotional processes and memory functions. The ventral striatum, anterior cingulum, subgenual cingulum and ventromedial prefrontal cortex formed a heterogeneous subgroup associated with motivation, reward and cognitive modulation of affect. Posterior cingulum/precuneus and dorsomedial prefrontal cortex were associated with mentalizing, self-reference and autobiographic information. The cluster formed by the temporo-parietal junction and anterior middle temporal sulcus/gyrus was associated with language and social cognition. Taken together, the current work highlights a robustly interconnected network that may be central to introspective, socio-affective, that is, self- and other-related mental processes.

Functional cliques in the amygdala and related brain networks driven by fear assessment acquired during movie viewing.

PubMed

Kinreich, Sivan; Intrator, Nathan; Hendler, Talma

2011-01-01

One of the greatest challenges involved in studying the brain mechanisms of fear is capturing the individual's unique instantaneous experience. Brain imaging studies to date commonly sacrifice valuable information regarding the individual real-time conscious experience, especially when focusing on elucidating the amygdala's activity. Here, we assumed that by using a minimally intrusive cue along with applying a robust clustering approach to probe the amygdala, it would be possible to rate fear in real time and to derive the related network of activation. During functional magnetic resonance imaging scanning, healthy volunteers viewed two excerpts from horror movies and were periodically auditory cued to rate their instantaneous experience of "I'm scared." Using graph theory and community mathematical concepts, data-driven clustering of the fear-related functional cliques in the amygdala was performed guided by the individually marked periods of heightened fear. Individually tailored functions derived from these amygdala activation cliques were subsequently applied as general linear model predictors to a whole-brain analysis to reveal the correlated networks. Our results suggest that by using a localized robust clustering approach, it is possible to probe activation in the right dorsal amygdala that is directly related to individual real-time emotional experience. Moreover, this fear-evoked amygdala revealed two opposing networks of co-activation and co-deactivation, which correspond to vigilance and rest-related circuits, respectively.

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

Soffientini, Chiara Dolores, E-mail: chiaradolores.soffientini@polimi.it; Baselli, Giuseppe; De Bernardi, Elisabetta

Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previousmore » analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81. Conclusions: The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.« less

Clustering of longitudinal data by using an extended baseline: A new method for treatment efficacy clustering in longitudinal data.

PubMed

Schramm, Catherine; Vial, Céline; Bachoud-Lévi, Anne-Catherine; Katsahian, Sandrine

2018-01-01

Heterogeneity in treatment efficacy is a major concern in clinical trials. Clustering may help to identify the treatment responders and the non-responders. In the context of longitudinal cluster analyses, sample size and variability of the times of measurements are the main issues with the current methods. Here, we propose a new two-step method for the Clustering of Longitudinal data by using an Extended Baseline. The first step relies on a piecewise linear mixed model for repeated measurements with a treatment-time interaction. The second step clusters the random predictions and considers several parametric (model-based) and non-parametric (partitioning, ascendant hierarchical clustering) algorithms. A simulation study compares all options of the clustering of longitudinal data by using an extended baseline method with the latent-class mixed model. The clustering of longitudinal data by using an extended baseline method with the two model-based algorithms was the more robust model. The clustering of longitudinal data by using an extended baseline method with all the non-parametric algorithms failed when there were unequal variances of treatment effect between clusters or when the subgroups had unbalanced sample sizes. The latent-class mixed model failed when the between-patients slope variability is high. Two real data sets on neurodegenerative disease and on obesity illustrate the clustering of longitudinal data by using an extended baseline method and show how clustering may help to identify the marker(s) of the treatment response. The application of the clustering of longitudinal data by using an extended baseline method in exploratory analysis as the first stage before setting up stratified designs can provide a better estimation of treatment effect in future clinical trials.

Collective Signal Processing in Cluster Chemotaxis: Roles of Adaptation, Amplification, and Co-attraction in Collective Guidance

PubMed Central

Camley, Brian A.; Zimmermann, Juliane; Levine, Herbert; Rappel, Wouter-Jan

2016-01-01

Single eukaryotic cells commonly sense and follow chemical gradients, performing chemotaxis. Recent experiments and theories, however, show that even when single cells do not chemotax, clusters of cells may, if their interactions are regulated by the chemoattractant. We study this general mechanism of “collective guidance” computationally with models that integrate stochastic dynamics for individual cells with biochemical reactions within the cells, and diffusion of chemical signals between the cells. We show that if clusters of cells use the well-known local excitation, global inhibition (LEGI) mechanism to sense chemoattractant gradients, the speed of the cell cluster becomes non-monotonic in the cluster’s size—clusters either larger or smaller than an optimal size will have lower speed. We argue that the cell cluster speed is a crucial readout of how the cluster processes chemotactic signals; both amplification and adaptation will alter the behavior of cluster speed as a function of size. We also show that, contrary to the assumptions of earlier theories, collective guidance does not require persistent cell-cell contacts and strong short range adhesion. If cell-cell adhesion is absent, and the cluster cohesion is instead provided by a co-attraction mechanism, e.g. chemotaxis toward a secreted molecule, collective guidance may still function. However, new behaviors, such as cluster rotation, may also appear in this case. Co-attraction and adaptation allow for collective guidance that is robust to varying chemoattractant concentrations while not requiring strong cell-cell adhesion. PMID:27367541

A user credit assessment model based on clustering ensemble for broadband network new media service supervision

NASA Astrophysics Data System (ADS)

Liu, Fang; Cao, San-xing; Lu, Rui

2012-04-01

This paper proposes a user credit assessment model based on clustering ensemble aiming to solve the problem that users illegally spread pirated and pornographic media contents within the user self-service oriented broadband network new media platforms. Its idea is to do the new media user credit assessment by establishing indices system based on user credit behaviors, and the illegal users could be found according to the credit assessment results, thus to curb the bad videos and audios transmitted on the network. The user credit assessment model based on clustering ensemble proposed by this paper which integrates the advantages that swarm intelligence clustering is suitable for user credit behavior analysis and K-means clustering could eliminate the scattered users existed in the result of swarm intelligence clustering, thus to realize all the users' credit classification automatically. The model's effective verification experiments are accomplished which are based on standard credit application dataset in UCI machine learning repository, and the statistical results of a comparative experiment with a single model of swarm intelligence clustering indicates this clustering ensemble model has a stronger creditworthiness distinguishing ability, especially in the aspect of predicting to find user clusters with the best credit and worst credit, which will facilitate the operators to take incentive measures or punitive measures accurately. Besides, compared with the experimental results of Logistic regression based model under the same conditions, this clustering ensemble model is robustness and has better prediction accuracy.

Impact of SZ cluster residuals in CMB maps and CMB-LSS cross-correlations

NASA Astrophysics Data System (ADS)

Chen, T.; Remazeilles, M.; Dickinson, C.

2018-06-01

Residual foreground contamination in cosmic microwave background (CMB) maps, such as the residual contamination from thermal Sunyaev-Zeldovich (SZ) effect in the direction of galaxy clusters, can bias the cross-correlation measurements between CMB and large-scale structure optical surveys. It is thus essential to quantify those residuals and, if possible, to null out SZ cluster residuals in CMB maps. We quantify for the first time the amount of SZ cluster contamination in the released Planck 2015 CMB maps through (i) the stacking of CMB maps in the direction of the clusters, and (ii) the computation of cross-correlation power spectra between CMB maps and the SDSS-IV large-scale structure data. Our cross-power spectrum analysis yields a 30σ detection at the cluster scale (ℓ = 1500-2500) and a 39σ detection on larger scales (ℓ = 500-1500) due to clustering of SZ clusters, giving an overall 54σ detection of SZ cluster residuals in the Planck CMB maps. The Planck 2015 NILC CMB map is shown to have 44 ± 4% of thermal SZ foreground emission left in it. Using the 'Constrained ILC' component separation technique, we construct an alternative Planck CMB map, the 2D-ILC map, which is shown to have negligible SZ contamination, at the cost of being slightly more contaminated by Galactic foregrounds and noise. We also discuss the impact of the SZ residuals in CMB maps on the measurement of the ISW effect, which is shown to be negligible based on our analysis.

A distinct and divergent lineage of genomic island-associated Type IV Secretion Systems in Legionella.

PubMed

Wee, Bryan A; Woolfit, Megan; Beatson, Scott A; Petty, Nicola K

2013-01-01

Legionella encodes multiple classes of Type IV Secretion Systems (T4SSs), including the Dot/Icm protein secretion system that is essential for intracellular multiplication in amoebal and human hosts. Other T4SSs not essential for virulence are thought to facilitate the acquisition of niche-specific adaptation genes including the numerous effector genes that are a hallmark of this genus. Previously, we identified two novel gene clusters in the draft genome of Legionella pneumophila strain 130b that encode homologues of a subtype of T4SS, the genomic island-associated T4SS (GI-T4SS), usually associated with integrative and conjugative elements (ICE). In this study, we performed genomic analyses of 14 homologous GI-T4SS clusters found in eight publicly available Legionella genomes and show that this cluster is unusually well conserved in a region of high plasticity. Phylogenetic analyses show that Legionella GI-T4SSs are substantially divergent from other members of this subtype of T4SS and represent a novel clade of GI-T4SSs only found in this genus. The GI-T4SS was found to be under purifying selection, suggesting it is functional and may play an important role in the evolution and adaptation of Legionella. Like other GI-T4SSs, the Legionella clusters are also associated with ICEs, but lack the typical integration and replication modules of related ICEs. The absence of complete replication and DNA pre-processing modules, together with the presence of Legionella-specific regulatory elements, suggest the Legionella GI-T4SS-associated ICE is unique and may employ novel mechanisms of regulation, maintenance and excision. The Legionella GI-T4SS cluster was found to be associated with several cargo genes, including numerous antibiotic resistance and virulence factors, which may confer a fitness benefit to the organism. The in-silico characterisation of this new T4SS furthers our understanding of the diversity of secretion systems involved in the frequent horizontal gene transfers that allow Legionella to adapt to and exploit diverse environmental niches.

A Distinct and Divergent Lineage of Genomic Island-Associated Type IV Secretion Systems in Legionella

PubMed Central

Wee, Bryan A.; Woolfit, Megan; Beatson, Scott A.; Petty, Nicola K.

2013-01-01

Legionella encodes multiple classes of Type IV Secretion Systems (T4SSs), including the Dot/Icm protein secretion system that is essential for intracellular multiplication in amoebal and human hosts. Other T4SSs not essential for virulence are thought to facilitate the acquisition of niche-specific adaptation genes including the numerous effector genes that are a hallmark of this genus. Previously, we identified two novel gene clusters in the draft genome of Legionella pneumophila strain 130b that encode homologues of a subtype of T4SS, the genomic island-associated T4SS (GI-T4SS), usually associated with integrative and conjugative elements (ICE). In this study, we performed genomic analyses of 14 homologous GI-T4SS clusters found in eight publicly available Legionella genomes and show that this cluster is unusually well conserved in a region of high plasticity. Phylogenetic analyses show that Legionella GI-T4SSs are substantially divergent from other members of this subtype of T4SS and represent a novel clade of GI-T4SSs only found in this genus. The GI-T4SS was found to be under purifying selection, suggesting it is functional and may play an important role in the evolution and adaptation of Legionella. Like other GI-T4SSs, the Legionella clusters are also associated with ICEs, but lack the typical integration and replication modules of related ICEs. The absence of complete replication and DNA pre-processing modules, together with the presence of Legionella-specific regulatory elements, suggest the Legionella GI-T4SS-associated ICE is unique and may employ novel mechanisms of regulation, maintenance and excision. The Legionella GI-T4SS cluster was found to be associated with several cargo genes, including numerous antibiotic resistance and virulence factors, which may confer a fitness benefit to the organism. The in-silico characterisation of this new T4SS furthers our understanding of the diversity of secretion systems involved in the frequent horizontal gene transfers that allow Legionella to adapt to and exploit diverse environmental niches. PMID:24358157

Determination of Cluster Distances from Chandra Imaging Spectroscopy and Sunyaev-Zeldovich Effect Measurements. I; Analysis Methods and Initial Results

NASA Technical Reports Server (NTRS)

Bonamente, Massimiliano; Joy, Marshall K.; Carlstrom, John E.; LaRoque, Samuel J.

2004-01-01

X-ray and Sunyaev-Zeldovich Effect data ca,n be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from the Chandra Observatory, which provides both spatial and spectral information, and interferometric radio measurements of the Sunyam-Zeldovich Effect are available from the BIMA and 0VR.O arrays. We introduce a Monte Carlo Markov chain procedure for the joint analysis of X-ray and Sunyaev-Zeldovich Effect data. The advantages of this method are the high computational efficiency and the ability to measure the full probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and the cluster distance. We apply this technique to the Chandra X-ray data and the OVRO radio data for the galaxy cluster Abell 611. Comparisons with traditional likelihood-ratio methods reveal the robustness of the method. This method will be used in a follow-up paper to determine the distance of a large sample of galaxy clusters for which high-resolution Chandra X-ray and BIMA/OVRO radio data are available.

Fast clustering using adaptive density peak detection.

PubMed

Wang, Xiao-Feng; Xu, Yifan

2017-12-01

Common limitations of clustering methods include the slow algorithm convergence, the instability of the pre-specification on a number of intrinsic parameters, and the lack of robustness to outliers. A recent clustering approach proposed a fast search algorithm of cluster centers based on their local densities. However, the selection of the key intrinsic parameters in the algorithm was not systematically investigated. It is relatively difficult to estimate the "optimal" parameters since the original definition of the local density in the algorithm is based on a truncated counting measure. In this paper, we propose a clustering procedure with adaptive density peak detection, where the local density is estimated through the nonparametric multivariate kernel estimation. The model parameter is then able to be calculated from the equations with statistical theoretical justification. We also develop an automatic cluster centroid selection method through maximizing an average silhouette index. The advantage and flexibility of the proposed method are demonstrated through simulation studies and the analysis of a few benchmark gene expression data sets. The method only needs to perform in one single step without any iteration and thus is fast and has a great potential to apply on big data analysis. A user-friendly R package ADPclust is developed for public use.

Continuous Variable Cluster State Generation over the Optical Spatial Mode Comb

DOE PAGES

Pooser, Raphael C.; Jing, Jietai

2014-10-20

One way quantum computing uses single qubit projective measurements performed on a cluster state (a highly entangled state of multiple qubits) in order to enact quantum gates. The model is promising due to its potential scalability; the cluster state may be produced at the beginning of the computation and operated on over time. Continuous variables (CV) offer another potential benefit in the form of deterministic entanglement generation. This determinism can lead to robust cluster states and scalable quantum computation. Recent demonstrations of CV cluster states have made great strides on the path to scalability utilizing either time or frequency multiplexingmore » in optical parametric oscillators (OPO) both above and below threshold. The techniques relied on a combination of entangling operators and beam splitter transformations. Here we show that an analogous transformation exists for amplifiers with Gaussian inputs states operating on multiple spatial modes. By judicious selection of local oscillators (LOs), the spatial mode distribution is analogous to the optical frequency comb consisting of axial modes in an OPO cavity. We outline an experimental system that generates cluster states across the spatial frequency comb which can also scale the amount of quantum noise reduction to potentially larger than in other systems.« less

Combining self-organizing mapping and supervised affinity propagation clustering approach to investigate functional brain networks involved in motor imagery and execution with fMRI measurements.

PubMed

Zhang, Jiang; Liu, Qi; Chen, Huafu; Yuan, Zhen; Huang, Jin; Deng, Lihua; Lu, Fengmei; Zhang, Junpeng; Wang, Yuqing; Wang, Mingwen; Chen, Liangyin

2015-01-01

Clustering analysis methods have been widely applied to identifying the functional brain networks of a multitask paradigm. However, the previously used clustering analysis techniques are computationally expensive and thus impractical for clinical applications. In this study a novel method, called SOM-SAPC that combines self-organizing mapping (SOM) and supervised affinity propagation clustering (SAPC), is proposed and implemented to identify the motor execution (ME) and motor imagery (MI) networks. In SOM-SAPC, SOM was first performed to process fMRI data and SAPC is further utilized for clustering the patterns of functional networks. As a result, SOM-SAPC is able to significantly reduce the computational cost for brain network analysis. Simulation and clinical tests involving ME and MI were conducted based on SOM-SAPC, and the analysis results indicated that functional brain networks were clearly identified with different response patterns and reduced computational cost. In particular, three activation clusters were clearly revealed, which include parts of the visual, ME and MI functional networks. These findings validated that SOM-SAPC is an effective and robust method to analyze the fMRI data with multitasks.

Trends and molecular mechanisms of antimicrobial resistance in clinical staphylococci isolated from companion animals over a 16 year period.

PubMed

Couto, Natacha; Monchique, Cláudia; Belas, Adriana; Marques, Cátia; Gama, Luís T; Pomba, Constança

2016-06-01

The objective of this study was to investigate the evolution of resistance to antimicrobials, corresponding mechanisms and molecular characteristics of Staphylococcus spp., between 1999 and 2014. Susceptibility to 38 antimicrobials was determined for 632 clinical staphylococcal isolates obtained from companion animals (dogs, cats, horses and other animals). Twenty antimicrobial resistance genes, including mecA and mecC, were screened by PCR. Methicillin-resistant staphylococci were characterized by spa (Staphylococcus aureus), SCCmec, MLST and PFGE typing. Statistical analyses were performed using SAS v9.3 and differences were considered relevant if P ≤ 0.05. The mecA gene was identified in 74 staphylococcal isolates (11.6%): 11 MRSA (40.7%), 40 methicillin-resistant Staphylococcus pseudintermedius (MRSP; 8.7%) and 23 methicillin-resistant CoNS (26.7%). Resistance to the majority of antimicrobials and the number of mecA-positive isolates increased significantly over time. Eighteen spa types were identified, including two new ones. MRSA isolates were divided into three PFGE clusters that included ST22-IV, ST105-II, ST398-V and ST5-VI. Most methicillin-resistant Staphylococcus epidermidis isolates were of clonal complex (CC) 5, including a new ST, and clustered in eight PFGE clusters. MRSP were grouped into five PFGE clusters and included ST45-NT, ST71-II-III, ST195-III, ST196-V, ST339-NT, ST342-IV and the new ST400-III. Methicillin-resistant Staphylococcus haemolyticus clustered in two PFGE clusters. The significant increase in antimicrobial-resistant and mecA-positive isolates in recent years is worrying. Furthermore, several isolates are MDR, which complicates antimicrobial treatment and increases the risk of transfer to humans or human isolates. Several clonal lineages of MRSA and methicillin-resistant S. epidermidis circulating in human hospitals and the community were found, suggesting that companion animals can become infected with and contribute to the dissemination of highly successful human clones. Urgent measures, such as determination of clinical breakpoints and guidelines for antimicrobial use, are needed. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Antimicrobial Chemotherapy. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Mono- and Digalactosyldiacylglycerol Composition of Dinoflagellates. IV. Temperature-Induced Modulation of Fatty Acid Regiochemistry as Observed by Electrospray Ionization/Mass Spectrometry

USDA-ARS?s Scientific Manuscript database

A recent survey of the intact mono- and digalactosyldiacylglycerol (MGDG and DGDG, respectively) composition of 35 peridinin-containing dinoflagellates found a division into two clusters, one that possessed C18/C18 (sn-1/sn-2) forms and one that possessed C20/C18 (sn-1/sn-2) forms of MGDG and DGDG. ...

Optimization Techniques for Clustering,Connectivity, and Flow Problems in Complex Networks

DTIC Science & Technology

2012-10-01

discrete optimization and for analysis of performance of algorithm portfolios; introducing a metaheuristic framework of variable objective search that...The results of empirical evaluation of the proposed algorithm are also included. 1.3 Theoretical analysis of heuristics and designing new metaheuristic ...analysis of heuristics for inapproximable problems and designing new metaheuristic approaches for the problems of interest; (IV) Developing new models

Molecular basis of beta-thalassemia in the Maldives.

PubMed

Furuumi, H; Firdous, N; Inoue, T; Ohta, H; Winichagoon, P; Fucharoen, S; Fukumaki, Y

1998-03-01

We have systematically analyzed beta-thalassemia genes using polymerase chain reaction-related techniques, dot-blot hybridization with oligonucleotide probes, allele specific-polymerase chain reaction, and sequencing of amplified DNA fragments from 41 unrelated patients, including 37 beta-thalassemia homozygotes, three with beta-thalassemia/Hb E, and one with beta-thalassemia/Hb S. Four different beta-thalassemia mutations were detected in 78 alleles. These are the IVS-I-5 (G-->C), codon 30 (AGG-->ACG) [also indicated as IVS-I (-1)], IVS-I-1 (G-->A), and codons 41/42 (-TTCT) mutations. The distribution of the beta-thalassemia mutations in the Maldives is 58 alleles (74.3%) with the IVS-I-5 (G-->C) mutation, 12 (15.4%) with the codon 30 (AGG-->ACG) mutation, seven (9%) with the IVS-I-1 (G-->A) mutation, and one with the codons 41/42 (-TTCT) mutation. The first three mutations account for 98.7% of the total number of beta-thalassemia chromosomes studied. These mutations are clustered in the region spanning 6 bp around the junction of exon 1 and the first intervening sequence of the beta-globin gene. These observations have significant implications for setting up a thalassemia prevention and control program in the Maldives. Analysis of haplotypes and frameworks of chromosomes bearing each beta-thalassemia mutation suggested that the origin and spread of these mutations were reflected by the historical record.

Association between personality traits and DSM-IV diagnosis of insomnia in perimenopausal women

PubMed Central

Sassoon, Stephanie A.; de Zambotti, Massimiliano; Colrain, Ian M.; Baker, Fiona C.

2013-01-01

Objective The aim of this study was to determine the role of personality factors in the development of DSM-IV insomnia coincident with perimenopause. Method Perimenopausal women (35 with DSM-IV insomnia and 28 with self-reported normal sleep) underwent clinical assessments and completed menopause-related questionnaires, the NEO-FFI, and the Structured Interview for DSM-IV Personality (SID-P). Logistic regressions determined whether personality factors and hot flash-related interference were associated with an insomnia diagnosis concurrent with the menopause transition. Results Women with insomnia reported higher neuroticism, lower agreeableness, and lower conscientiousness than controls on the NEO-FFI. Moreover, women with insomnia were more likely to meet DSM-IV criteria for Cluster C personality disorders, particularly obsessive compulsive personality disorder, on the SID-P. Women with insomnia were more likely to have had a past depressive episode and history of severe premenstrual symptoms. Findings from regressions revealed that higher neuroticism and greater interference from hot flashes were associated with insomnia classification even after controlling for history of depression, suggesting that sensitivity to hot flashes and a greater degree of neuroticism are independent contributors toward establishing which women are most likely to have sleep problems during perimenopause. Conclusions Findings show the relevance of personality factors, particularly neuroticism and obsessive-compulsive personality, in influencing a woman’s experience of insomnia as she goes through the menopause transition. PMID:24448105

The Joint Structure of DSM–IV Axis I and Axis II Disorders

PubMed Central

Røysamb, Espen; Tambs, Kristian; Ørstavik, Ragnhild E.; Torgersen, Svenn; Kendler, Kenneth S.; Neale, Michael C.; Aggen, Steven H.; Reichborn-Kjennerud, Ted

2011-01-01

The Diagnostic and Statistical Manual (4th ed. [DSM–IV]; American Psychiatric Association, 1994) distinction between clinical disorders on Axis I and personality disorders on Axis II has become increasingly controversial. Although substantial comorbidity between axes has been demonstrated, the structure of the liability factors underlying these two groups of disorders is poorly understood. The aim of this study was to determine the latent factor structure of a broad set of common Axis I disorders and all Axis II personality disorders and thereby to identify clusters of disorders and account for comorbidity within and between axes. Data were collected in Norway, through a population-based interview study (N = 2,794 young adult twins). Axis I and Axis II disorders were assessed with the Composite International Diagnostic Interview (CIDI) and the Structured Interview for DSM–IV Personality (SIDP–IV), respectively. Exploratory and confirmatory factor analyses were used to investigate the underlying structure of 25 disorders. A four-factor model fit the data well, suggesting a distinction between clinical and personality disorders as well as a distinction between broad groups of internalizing and externalizing disorders. The location of some disorders was not consistent with the DSM–IV classification; antisocial personality disorder belonged primarily to the Axis I externalizing spectrum, dysthymia appeared as a personality disorder, and borderline personality disorder appeared in an interspectral position. The findings have implications for a meta-structure for the DSM. PMID:21319931

Locating sources within a dense sensor array using graph clustering

NASA Astrophysics Data System (ADS)

Gerstoft, P.; Riahi, N.

2017-12-01

We develop a model-free technique to identify weak sources within dense sensor arrays using graph clustering. No knowledge about the propagation medium is needed except that signal strengths decay to insignificant levels within a scale that is shorter than the aperture. We then reinterpret the spatial coherence matrix of a wave field as a matrix whose support is a connectivity matrix of a graph with sensors as vertices. In a dense network, well-separated sources induce clusters in this graph. The geographic spread of these clusters can serve to localize the sources. The support of the covariance matrix is estimated from limited-time data using a hypothesis test with a robust phase-only coherence test statistic combined with a physical distance criterion. The latter criterion ensures graph sparsity and thus prevents clusters from forming by chance. We verify the approach and quantify its reliability on a simulated dataset. The method is then applied to data from a dense 5200 element geophone array that blanketed of the city of Long Beach (CA). The analysis exposes a helicopter traversing the array and oil production facilities.

An adaptive clustering algorithm for image matching based on corner feature

NASA Astrophysics Data System (ADS)

Wang, Zhe; Dong, Min; Mu, Xiaomin; Wang, Song

2018-04-01

The traditional image matching algorithm always can not balance the real-time and accuracy better, to solve the problem, an adaptive clustering algorithm for image matching based on corner feature is proposed in this paper. The method is based on the similarity of the matching pairs of vector pairs, and the adaptive clustering is performed on the matching point pairs. Harris corner detection is carried out first, the feature points of the reference image and the perceived image are extracted, and the feature points of the two images are first matched by Normalized Cross Correlation (NCC) function. Then, using the improved algorithm proposed in this paper, the matching results are clustered to reduce the ineffective operation and improve the matching speed and robustness. Finally, the Random Sample Consensus (RANSAC) algorithm is used to match the matching points after clustering. The experimental results show that the proposed algorithm can effectively eliminate the most wrong matching points while the correct matching points are retained, and improve the accuracy of RANSAC matching, reduce the computation load of whole matching process at the same time.

Self-Assembly of Octopus Nanoparticles into Pre-Programmed Finite Clusters

NASA Astrophysics Data System (ADS)

Halverson, Jonathan; Tkachenko, Alexei

2012-02-01

The precise control of the spatial arrangement of nanoparticles (NP) is often required to take full advantage of their novel optical and electronic properties. NPs have been shown to self-assemble into crystalline structures using either patchy surface regions or complementary DNA strands to direct the assembly. Due to a lack of specificity of the interactions these methods lead to only a limited number of structures. An emerging approach is to bind ssDNA at specific sites on the particle surface making so-called octopus NPs. Using octopus NPs we investigate the inverse problem of the self-assembly of finite clusters. That is, for a given target cluster (e.g., arranging the NPs on the vertices of a dodecahedron) what are the minimum number of complementary DNA strands needed for the robust self-assembly of the cluster from an initially homogeneous NP solution? Based on the results of Brownian dynamics simulations we have compiled a set of design rules for various target clusters including cubes, pyramids, dodecahedrons and truncated icosahedrons. Our approach leads to control over the kinetic pathway and has demonstrated nearly perfect yield of the target.

Globular and Open Clusters Observed by SDSS/SEGUE: the Giant Stars

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

Morrison, Heather L.; Ma, Zhibo; Clem, James L.

We present griz observations for the clusters M92, M13 and NGC 6791 and gr photometry for M71, Be 29 and NGC 7789. In addition we present new membership identifications for all these clusters, which have been observed spectroscopically as calibrators for the SDSS/SEGUE survey; this paper focuses in particular on the red giant branch stars in the clusters. In a number of cases, these giants were too bright to be observed in the normal SDSS survey operations, and we describe the procedure used to obtain spectra for these stars. For M71, also present a new variable reddening map and amore » new fiducial for the gr giant branch. For NGC 7789, we derived a transformation from Teff to g-r for giants of near solar abundance, using IRFM Teff measures of stars with good ugriz and 2MASS photometry and SEGUE spectra. The result of our analysis is a robust list of known cluster members with correctly dereddened and (if needed) transformed gr photometry for crucial calibration efforts for SDSS and SEGUE.« less

Globular and Open Clusters Observed by SDSS/SEGUE: The Giant Stars

NASA Astrophysics Data System (ADS)

Morrison, Heather L.; Ma, Zhibo; Clem, James L.; An, Deokkeun; Connor, Thomas; Schechtman-Rook, Andrew; Casagrande, Luca; Rockosi, Constance; Yanny, Brian; Harding, Paul; Beers, Timothy C.; Johnson, Jennifer A.; Schneider, Donald P.

2016-01-01

We present griz observations for the clusters M92, M13 and NGC 6791 and gr photometry for M71, Be 29 and NGC 7789. In addition we present new membership identifications for all these clusters, which have been observed spectroscopically as calibrators for the Sloan Digital Sky Survey (SDSS)/SEGUE survey; this paper focuses in particular on the red giant branch stars in the clusters. In a number of cases, these giants were too bright to be observed in the normal SDSS survey operations, and we describe the procedure used to obtain spectra for these stars. For M71, we also present a new variable reddening map and a new fiducial for the gr giant branch. For NGC 7789, we derived a transformation from Teff to g-r for giants of near solar abundance, using IRFM Teff measures of stars with good ugriz and 2MASS photometry and SEGUE spectra. The result of our analysis is a robust list of known cluster members with correctly dereddened and (if needed) transformed gr photometry for crucial calibration efforts for SDSS and SEGUE.

Markov Chain Monte Carlo Joint Analysis of Chandra X-Ray Imaging Spectroscopy and Sunyaev-Zel'dovich Effect Data

NASA Technical Reports Server (NTRS)

Bonamente, Massimillano; Joy, Marshall K.; Carlstrom, John E.; Reese, Erik D.; LaRoque, Samuel J.

2004-01-01

X-ray and Sunyaev-Zel'dovich effect data can be combined to determine the distance to galaxy clusters. High-resolution X-ray data are now available from Chandra, which provides both spatial and spectral information, and Sunyaev-Zel'dovich effect data were obtained from the BIMA and Owens Valley Radio Observatory (OVRO) arrays. We introduce a Markov Chain Monte Carlo procedure for the joint analysis of X-ray and Sunyaev- Zel'dovich effect data. The advantages of this method are the high computational efficiency and the ability to measure simultaneously the probability distribution of all parameters of interest, such as the spatial and spectral properties of the cluster gas and also for derivative quantities such as the distance to the cluster. We demonstrate this technique by applying it to the Chandra X-ray data and the OVRO radio data for the galaxy cluster A611. Comparisons with traditional likelihood ratio methods reveal the robustness of the method. This method will be used in follow-up paper to determine the distances to a large sample of galaxy cluster.

Globular and Open Clusters Observed by SDSS/SEGUE: the Giant Stars

DOE PAGES

Morrison, Heather L.; Ma, Zhibo; Clem, James L.; ...

2015-12-18

We present griz observations for the clusters M92, M13 and NGC 6791 and gr photometry for M71, Be 29 and NGC 7789. In addition we present new membership identifications for all these clusters, which have been observed spectroscopically as calibrators for the SDSS/SEGUE survey; this paper focuses in particular on the red giant branch stars in the clusters. In a number of cases, these giants were too bright to be observed in the normal SDSS survey operations, and we describe the procedure used to obtain spectra for these stars. For M71, also present a new variable reddening map and amore » new fiducial for the gr giant branch. For NGC 7789, we derived a transformation from Teff to g-r for giants of near solar abundance, using IRFM Teff measures of stars with good ugriz and 2MASS photometry and SEGUE spectra. The result of our analysis is a robust list of known cluster members with correctly dereddened and (if needed) transformed gr photometry for crucial calibration efforts for SDSS and SEGUE.« less

Pan-Genomic Approaches in Lactobacillus reuteri as a Porcine Probiotic: Investigation of Host Adaptation and Antipathogenic Activity.

PubMed

Lee, Jun-Yeong; Han, Geon Goo; Choi, Jaeyun; Jin, Gwi-Deuk; Kang, Sang-Kee; Chae, Byung Jo; Kim, Eun Bae; Choi, Yun-Jaie

2017-10-01

After the introduction of a ban on the use of antibiotic growth promoters (AGPs) for livestock, reuterin-producing Lactobacillus reuteri is getting attention as an alternative to AGPs. In this study, we investigated genetic features of L. reuteri associated with host specificity and antipathogenic effect. We isolated 104 L. reuteri strains from porcine feces, and 16 strains, composed of eight strains exhibiting the higher antipathogenic effect (group HS) and eight strains exhibiting the lower effect (group LS), were selected for genomic comparison. We generated draft genomes of the 16 isolates and investigated their pan-genome together with the 26 National Center for Biotechnology Information-registered genomes. L. reuteri genomes organized six clades with multi-locus sequence analysis, and the clade IV includes the 16 isolates. First, we identified six L. reuteri clade IV-specific genes including three hypothetical protein-coding genes. The three annotated genes encode transposases and cell surface proteins, indicating that these genes are the result of adaptation to the host gastrointestinal epithelia and that these host-specific traits were acquired by horizontal gene transfer. We also identified differences between groups HS and LS in the pdu-cbi-cob-hem gene cluster, which is essential for reuterin and cobalamin synthesis, and six genes specific to group HS are revealed. While the strains of group HS possessed all genes of this cluster, LS strains have lost many genes of the cluster. This study provides a deeper understanding of the relationship between probiotic properties and genomic features of L. reuteri.

Caproiciproducens galactitolivorans gen. nov., sp. nov., a bacterium capable of producing caproic acid from galactitol, isolated from a wastewater treatment plant.

PubMed

Kim, Byung-Chun; Seung Jeon, Byoung; Kim, Seil; Kim, Hyunook; Um, Youngsoon; Sang, Byoung-In

2015-12-01

A strictly anaerobic, Gram-stain-positive, non-spore-forming, rod-shaped bacterial strain, designated BS-1T, was isolated from an anaerobic digestion reactor during a study of bacteria utilizing galactitol as the carbon source. Its cells were 0.3-0.5 μm × 2-4 μm, and they grew at 35-45 °C and at pH 6.0-8.0. Strain BS-1T produced H2, CO2, ethanol, acetic acid, butyric acid and caproic acid as metabolic end products of anaerobic fermentation. Phylogenetic analysis, based on the 16S rRNA gene sequence, showed that strain BS-1T represented a novel bacterial genus within the family Ruminococcaceae, Clostridium Cluster IV. The type strains that were most closely related to strain BS-1T were Clostridium sporosphaeroides KCTC 5598T (94.5 %), Clostridium leptum KCTC 5155T (94.3 %), Ruminococcus bromii ATCC 27255T (92.1 %) and Ethanoligenens harbinense YUAN-3T (91.9 %). Strain BS-1T had 17.6 % and 20.9 % DNA-DNA relatedness values with C. sporosphaeroides DSM 1294T and C. leptum DSM 753T, respectively. The major components of the cellular fatty acids were C16 : 0 dimethyl aldehyde (DMA) (22.1 %), C16 : 0 aldehyde (14.1 %) and summed feature 11 (iso-C17 : 0 3-OH and/or C18 : 2 DMA; 10.0 %). The genomic DNA G+C content was 50.0 mol%. Phenotypic and phylogenetic characteristics allowed strain BS-1T to be clearly distinguished from other taxa of the genus Clostridium Cluster IV. On the basis of these data, the isolate is considered to represent a novel genus and novel species within Clostridium Cluster IV, for which the name Caproiciproducens galactitolivorans gen. nov., sp. nov. is proposed. The type species is BS-1T ( = JCM 30532T and KCCM 43048T).

Attention Deficit Hyperactivity Disorder Subtypes and Symptom Response in Adults Treated with Lisdexamfetamine Dimesylate

PubMed Central

Mattingly, Greg; Weisler, Richard; Dirks, Bryan; Babcock, Thomas; Adeyi, Ben; Scheckner, Brian; Lasser, Robert

2012-01-01

Objective: To evaluate the efficacy of lisdexamfetamine dimesylate in adults with attention deficit hyperactivity disorder symptom subtypes who exhibit predominantly inattention, hyperactivity/ impulsivity, or combined symptom clusters. Design/Setting/Participants: This is a post-hoc analysis from a multicenter, one-year, open-label lisdexamfetamine dimesylate study in adults with attention deficit hyperactivity disorder previously completing two weeks or more in a four-week, randomized, placebo-controlled lisdexamfetamine dimesylate study, using Attention Deficit Hyperactivity Disorder Rating Scale IV symptom ratings as an attention deficit hyperactivity disorder subtype proxy (N=349). Measurements: Attention Deficit Hyperactivity Disorder Rating Scale IV was measured at baseline of prior study and throughout the open-label study. Proxy subtypes were based on item scores of 2 (moderate) or 3 (severe), representing endorsement of at least six of nine symptoms on respective subscales; predominantly combined type endorsed at least six of nine symptoms on each subscale. Overall safety evaluations included treatment-emergent adverse events. Results: At baseline, 93 of 345 participants exhibited predominantly inattention, 13 predominantly hyperactivity/ impulsivity, 236 combined symptom clusters, and three were unassigned. For the three subgroups, respectively, mean (standard deviation) Attention Deficit Hyperactivity Disorder Rating Scale IV total scores at baseline were 34.5 (4.02), 33.8 (3.27), and 43.6 (5.24); change from baseline to endpoint scores were -19.3 (9.48), -24.0 (7.22), and -27.3 (11.78). Mean (standard deviation) end-of-study lisdexamfetamine dimesylate dose was 57.7 (14.75), 53.1 (16.01), and 56.9 (14.94)mg/day, respectively. Treatment-emergent adverse events (>5%) were upper respiratory tract infection (21.8%), insomnia (19.5%), headache (17.2%), dry mouth (16.6%), decreased appetite (14.3%), irritability (11.2%), anxiety (8.3%), nasopharyngitis (7.4%), sinusitis (6.6%), decreased weight (6.0%), back pain (5.4%), and muscle spasms (5.2%). Conclusions: Lisdexamfetamine dimesylate was effective in participants with predominantly inattention, hyperactivity/ impulsivity, and combined attention deficit hyperactivity disorder symptom clusters. Groups exhibiting specific predominant subtype symptoms did not differ in clinical response to lisdexamfetamine dimesylate. PMID:22808446

A Spatial Division Clustering Method and Low Dimensional Feature Extraction Technique Based Indoor Positioning System

PubMed Central

Mo, Yun; Zhang, Zhongzhao; Meng, Weixiao; Ma, Lin; Wang, Yao

2014-01-01

Indoor positioning systems based on the fingerprint method are widely used due to the large number of existing devices with a wide range of coverage. However, extensive positioning regions with a massive fingerprint database may cause high computational complexity and error margins, therefore clustering methods are widely applied as a solution. However, traditional clustering methods in positioning systems can only measure the similarity of the Received Signal Strength without being concerned with the continuity of physical coordinates. Besides, outage of access points could result in asymmetric matching problems which severely affect the fine positioning procedure. To solve these issues, in this paper we propose a positioning system based on the Spatial Division Clustering (SDC) method for clustering the fingerprint dataset subject to physical distance constraints. With the Genetic Algorithm and Support Vector Machine techniques, SDC can achieve higher coarse positioning accuracy than traditional clustering algorithms. In terms of fine localization, based on the Kernel Principal Component Analysis method, the proposed positioning system outperforms its counterparts based on other feature extraction methods in low dimensionality. Apart from balancing online matching computational burden, the new positioning system exhibits advantageous performance on radio map clustering, and also shows better robustness and adaptability in the asymmetric matching problem aspect. PMID:24451470

Reversible electric-field manipulation of the adsorption morphology and magnetic anisotropy of small Fe and Co clusters on graphene

NASA Astrophysics Data System (ADS)

Tanveer, M.; Dorantes-Dávila, J.; Pastor, G. M.

2017-12-01

First-principles electronic calculations show how the adsorption morphology, orbital magnetism, and magnetic anisotropy energy (MAE) of small CoN and FeN clusters (N ≤3 ) on graphene (G) can be reversibly controlled under the action of an external electric field (EF). A variety of cluster-specific and EF-induced effects are revealed, including (i) perpendicular or canted adsorption configurations of the dimers and trimers, (ii) significant morphology-dependent permanent dipole moments and electric susceptibilities, (iii) EF-induced reversible transitions among the different metastable adsorption morphologies of Fe3 and Co3 on graphene, (iv) qualitative changes in the MAE landscape driven by structural changes, (v) colossal values of the magnetic anisotropy Δ E ≃45 meV per atom in Co2/G , (vi) EF-induced spin-reorientation transitions in Co3/G , and (vii) reversibly tunable coercive field and blocking temperatures, which in some cases allow a barrierless magnetization reversal of the cluster. These remarkable electric and magnetic fingerprints open new possibilities of characterizing and exploiting the size- and structural-dependent properties of magnetic nanostructures at surfaces.

Intermediate P* from soluble methane monooxygenase contains a diferrous cluster.

PubMed

Banerjee, Rahul; Meier, Katlyn K; Münck, Eckard; Lipscomb, John D

2013-06-25

During a single turnover of the hydroxylase component (MMOH) of soluble methane monooxygenase from Methylosinus trichosporium OB3b, several discrete intermediates are formed. The diiron cluster of MMOH is first reduced to the Fe(II)Fe(II) state (H(red)). O₂ binds rapidly at a site away from the cluster to form the Fe(II)Fe(II) intermediate O, which converts to an Fe(III)Fe(III)-peroxo intermediate P and finally to the Fe(IV)Fe(IV) intermediate Q. Q binds and reacts with methane to yield methanol and water. The rate constants for these steps are increased by a regulatory protein, MMOB. Previously reported transient kinetic studies have suggested that an intermediate P* forms between O and P in which the g = 16 EPR signal characteristic of the reduced diiron cluster of H(red) and O is lost. This was interpreted as signaling oxidation of the cluster, but a low level of accumulation of P* prevented further characterization. In this study, three methods for directly detecting and trapping P* are applied together to allow its spectroscopic and kinetic characterization. First, the MMOB mutant His33Ala is used to specifically slow the decay of P* without affecting its formation rate, leading to its nearly quantitative accumulation. Second, spectra-kinetic data collection is used to provide a sensitive measure of the formation and decay rate constants of intermediates as well as their optical spectra. Finally, the substrate furan is included to react with Q and quench its strong chromophore. The optical spectrum of P* closely mimics those of H(red) and O, but it is distinctly different from that of P. The reaction cycle rate constants allowed prediction of the times for maximal accumulation of the intermediates. Mössbauer spectra of rapid freeze-quench samples at these times show that the intermediates are formed at almost exactly the predicted levels. The Mössbauer spectra show that the diiron cluster of P*, quite unexpectedly, is in the Fe(II)Fe(II) state. Thus, the loss of the g = 16 EPR signal results from a change in the electronic structure of the Fe(II)Fe(II) center rather than oxidation. The similarity of the optical and Mössbauer spectra of H(red), O, and P* suggests that only subtle changes occur in the electronic and physical structure of the diiron cluster as P* forms. Nevertheless, the changes that do occur are necessary for O₂ to be activated for hydrocarbon oxidation.

Robust Requirements Tracing via Internet Search Technology: Improving an IV and V Technique. Phase 2

NASA Technical Reports Server (NTRS)

Hayes, Jane; Dekhtyar, Alex

2004-01-01

There are three major objectives to this phase of the work. (1) Improvement of Information Retrieval (IR) methods for Independent Verification and Validation (IV&V) requirements tracing. Information Retrieval methods are typically developed for very large (order of millions - tens of millions and more documents) document collections and therefore, most successfully used methods somewhat sacrifice precision and recall in order to achieve efficiency. At the same time typical IR systems treat all user queries as independent of each other and assume that relevance of documents to queries is subjective for each user. The IV&V requirements tracing problem has a much smaller data set to operate on, even for large software development projects; the set of queries is predetermined by the high-level specification document and individual requirements considered as query input to IR methods are not necessarily independent from each other. Namely, knowledge about the links for one requirement may be helpful in determining the links of another requirement. Finally, while the final decision on the exact form of the traceability matrix still belongs to the IV&V analyst, his/her decisions are much less arbitrary than those of an Internet search engine user. All this suggests that the information available to us in the framework of the IV&V tracing problem can be successfully leveraged to enhance standard IR techniques, which in turn would lead to increased recall and precision. We developed several new methods during Phase II; (2) IV&V requirements tracing IR toolkit. Based on the methods developed in Phase I and their improvements developed in Phase II, we built a toolkit of IR methods for IV&V requirements tracing. The toolkit has been integrated, at the data level, with SAIC's SuperTracePlus (STP) tool; (3) Toolkit testing. We tested the methods included in the IV&V requirements tracing IR toolkit on a number of projects.

Heterometallic appended {MMn(III)4} cubanes encapsulated by lacunary polytungstate ligands.

PubMed

Wu, Hai-Hong; Yao, Shuang; Zhang, Zhi-Ming; Li, Yang-Guang; Song, You; Liu, Zhu-Jun; Han, Xin-Bao; Wang, En-Bo

2013-01-14

The heterometallic appended {MMn(III)(4)} (M = Dy(3+) and K(+)) cubanes were firstly trapped by two diamagnetic POM shells, which were robust enough to construct inorganic crystalline tubular materials. Magnetic study reveals the presence of a SMM-like slow magnetic relaxation feature in the heterometallic cluster-containing POM.

Financial fluctuations anchored to economic fundamentals: A mesoscopic network approach.

PubMed

Sharma, Kiran; Gopalakrishnan, Balagopal; Chakrabarti, Anindya S; Chakraborti, Anirban

2017-08-14

We demonstrate the existence of an empirical linkage between nominal financial networks and the underlying economic fundamentals, across countries. We construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and infer the relative importance of the sectors in the nominal network through measures of centrality and clustering algorithms. Eigenvector centrality robustly identifies the backbone of the minimum spanning tree defined on the return networks as well as the primary cluster in the multidimensional scaling map. We show that the sectors that are relatively large in size, defined with three metrics, viz., market capitalization, revenue and number of employees, constitute the core of the return networks, whereas the periphery is mostly populated by relatively smaller sectors. Therefore, sector-level nominal return dynamics are anchored to the real size effect, which ultimately shapes the optimal portfolios for risk management. Our results are reasonably robust across 27 countries of varying degrees of prosperity and across periods of market turbulence (2008-09) as well as periods of relative calmness (2012-13 and 2015-16).

The plasma protein fibrinogen stabilizes clusters of red blood cells in microcapillary flows

NASA Astrophysics Data System (ADS)

Brust, M.; Aouane, O.; Thiébaud, M.; Flormann, D.; Verdier, C.; Kaestner, L.; Laschke, M. W.; Selmi, H.; Benyoussef, A.; Podgorski, T.; Coupier, G.; Misbah, C.; Wagner, C.

2014-03-01

The supply of oxygen and nutrients and the disposal of metabolic waste in the organs depend strongly on how blood, especially red blood cells, flow through the microvascular network. Macromolecular plasma proteins such as fibrinogen cause red blood cells to form large aggregates, called rouleaux, which are usually assumed to be disaggregated in the circulation due to the shear forces present in bulk flow. This leads to the assumption that rouleaux formation is only relevant in the venule network and in arterioles at low shear rates or stasis. Thanks to an excellent agreement between combined experimental and numerical approaches, we show that despite the large shear rates present in microcapillaries, the presence of either fibrinogen or the synthetic polymer dextran leads to an enhanced formation of robust clusters of red blood cells, even at haematocrits as low as 1%. Robust aggregates are shown to exist in microcapillaries even for fibrinogen concentrations within the healthy physiological range. These persistent aggregates should strongly affect cell distribution and blood perfusion in the microvasculature, with putative implications for blood disorders even within apparently asymptomatic subjects.

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

Yu, Kuang; Libisch, Florian; Carter, Emily A., E-mail: eac@princeton.edu

We report a new implementation of the density functional embedding theory (DFET) in the VASP code, using the projector-augmented-wave (PAW) formalism. Newly developed algorithms allow us to efficiently perform optimized effective potential optimizations within PAW. The new algorithm generates robust and physically correct embedding potentials, as we verified using several test systems including a covalently bound molecule, a metal surface, and bulk semiconductors. We show that with the resulting embedding potential, embedded cluster models can reproduce the electronic structure of point defects in bulk semiconductors, thereby demonstrating the validity of DFET in semiconductors for the first time. Compared to ourmore » previous version, the new implementation of DFET within VASP affords use of all features of VASP (e.g., a systematic PAW library, a wide selection of functionals, a more flexible choice of U correction formalisms, and faster computational speed) with DFET. Furthermore, our results are fairly robust with respect to both plane-wave and Gaussian type orbital basis sets in the embedded cluster calculations. This suggests that the density functional embedding method is potentially an accurate and efficient way to study properties of isolated defects in semiconductors.« less

Application of fuzzy c-means clustering to PRTR chemicals uncovering their release and toxicity characteristics.

PubMed

Xue, Mianqiang; Zhou, Liang; Kojima, Naoya; Dos Muchangos, Leticia Sarmento; Machimura, Takashi; Tokai, Akihiro

2018-05-01

Increasing manufacture and usage of chemicals have not been matched by the increase in our understanding of their risks. Pollutant release and transfer register (PRTR) is becoming a popular measure for collecting chemical data and enhancing the public right to know. However, these data are usually in high dimensionality which restricts their wider use. The present study partitions Japanese PRTR chemicals into five fuzzy clusters by fuzzy c-mean clustering (FCM) to explore the implicit information. Each chemical with membership degrees belongs to each cluster. Cluster I features high releases from non-listed industries and the household sector and high environmental toxicity. Cluster II is characterized by high reported releases and transfers from 24 listed industries above the threshold, mutagenicity, and high environmental toxicity. Chemicals in cluster III have characteristics of high releases from non-listed industries and low toxicity. Cluster IV is characterized by high reported releases and transfers from 24 listed industries above the threshold and extremely high environmental toxicity. Cluster V is characterized by low releases yet mutagenicity and high carcinogenicity. Chemicals with the highest membership degree were identified as representatives for each cluster. For the highest membership degree, half of the chemicals have a value higher than 0.74. If we look at both the highest and the second highest membership degrees simultaneously, about 94% of the chemicals have a value higher than 0.5. FCM can serve as an approach to uncover the implicit information of highly complex chemical dataset, which subsequently supports the strategy development for efficient and effective chemical management. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-scale clustering by building a robust and self correcting ultrametric topology on data points.

PubMed

Fushing, Hsieh; Wang, Hui; Vanderwaal, Kimberly; McCowan, Brenda; Koehl, Patrice

2013-01-01

The advent of high-throughput technologies and the concurrent advances in information sciences have led to an explosion in size and complexity of the data sets collected in biological sciences. The biggest challenge today is to assimilate this wealth of information into a conceptual framework that will help us decipher biological functions. A large and complex collection of data, usually called a data cloud, naturally embeds multi-scale characteristics and features, generically termed geometry. Understanding this geometry is the foundation for extracting knowledge from data. We have developed a new methodology, called data cloud geometry-tree (DCG-tree), to resolve this challenge. This new procedure has two main features that are keys to its success. Firstly, it derives from the empirical similarity measurements a hierarchy of clustering configurations that captures the geometric structure of the data. This hierarchy is then transformed into an ultrametric space, which is then represented via an ultrametric tree or a Parisi matrix. Secondly, it has a built-in mechanism for self-correcting clustering membership across different tree levels. We have compared the trees generated with this new algorithm to equivalent trees derived with the standard Hierarchical Clustering method on simulated as well as real data clouds from fMRI brain connectivity studies, cancer genomics, giraffe social networks, and Lewis Carroll's Doublets network. In each of these cases, we have shown that the DCG trees are more robust and less sensitive to measurement errors, and that they provide a better quantification of the multi-scale geometric structures of the data. As such, DCG-tree is an effective tool for analyzing complex biological data sets.

Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm.

PubMed

Tchagang, Alain B; Phan, Sieu; Famili, Fazel; Shearer, Heather; Fobert, Pierre; Huang, Yi; Zou, Jitao; Huang, Daiqing; Cutler, Adrian; Liu, Ziying; Pan, Youlian

2012-04-04

Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space. We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (Plasmodium chabaudi), systemic acquired resistance in Arabidopsis thaliana, similarities and differences between inner and outer cotyledon in Brassica napus during seed development, and to Brassica napus whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples. Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data.

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data.

PubMed

Hsu, Arthur L; Tang, Sen-Lin; Halgamuge, Saman K

2003-11-01

Current Self-Organizing Maps (SOMs) approaches to gene expression pattern clustering require the user to predefine the number of clusters likely to be expected. Hierarchical clustering methods used in this area do not provide unique partitioning of data. We describe an unsupervised dynamic hierarchical self-organizing approach, which suggests an appropriate number of clusters, to perform class discovery and marker gene identification in microarray data. In the process of class discovery, the proposed algorithm identifies corresponding sets of predictor genes that best distinguish one class from other classes. The approach integrates merits of hierarchical clustering with robustness against noise known from self-organizing approaches. The proposed algorithm applied to DNA microarray data sets of two types of cancers has demonstrated its ability to produce the most suitable number of clusters. Further, the corresponding marker genes identified through the unsupervised algorithm also have a strong biological relationship to the specific cancer class. The algorithm tested on leukemia microarray data, which contains three leukemia types, was able to determine three major and one minor cluster. Prediction models built for the four clusters indicate that the prediction strength for the smaller cluster is generally low, therefore labelled as uncertain cluster. Further analysis shows that the uncertain cluster can be subdivided further, and the subdivisions are related to two of the original clusters. Another test performed using colon cancer microarray data has automatically derived two clusters, which is consistent with the number of classes in data (cancerous and normal). JAVA software of dynamic SOM tree algorithm is available upon request for academic use. A comparison of rectangular and hexagonal topologies for GSOM is available from http://www.mame.mu.oz.au/mechatronics/journalinfo/Hsu2003supp.pdf

Identifying eating behavior phenotypes and their correlates: a novel direction toward improving weight management interventions

PubMed Central

Bouhlal, Sofia; McBride, Colleen M.; Trivedi, Niraj S.; Agurs-Collins, Tanya; Persky, Susan

2017-01-01

Common reports of over-response to food cues, difficulties with calorie restriction, and difficulty adhering to dietary guidelines suggest that eating behaviors could be interrelated in ways that influence weight management efforts. The feasibility of identifying robust eating phenotypes (showing face, content, and criterion validity) was explored based on well-validated individual eating behavior assessments. Adults (n=260; mean age 34 years) completed online questionnaires with measurements of nine eating behaviors including: appetite for palatable foods, binge eating, bitter taste sensitivity, disinhibition, food neophobia, pickiness and satiety responsiveness. Discovery-based visualization procedures that have the combined strengths of heatmaps and hierarchical clustering were used to investigate: 1) how eating behaviors cluster, 2) how participants can be grouped within eating behavior clusters, and 3) whether group clustering is associated with body mass index (BMI) and dietary self-efficacy levels. Two distinct eating behavior clusters and participant groups that aligned within these clusters were identified: one with higher drive to eat and another with food avoidance behaviors. Participants’ BMI (p=.0002) and dietary self-efficacy (p<.0001) were associated with cluster membership. Eating behavior clusters showed content and criterion validity based on their association with BMI (associated, but not entirely overlapping) and dietary self-efficacy. Identifying eating behavior phenotypes appears viable. These efforts could be expanded and ultimately inform tailored weight management interventions. PMID:28043857

Measuring the hydrostatic mass bias in galaxy clusters by combining Sunyaev-Zel'dovich and CMB lensing data

NASA Astrophysics Data System (ADS)

Hurier, G.; Angulo, R. E.

2018-02-01

The cosmological parameters preferred by the cosmic microwave background (CMB) primary anisotropies predict many more galaxy clusters than those that have been detected via the thermal Sunyaev-Zeldovich (tSZ) effect. This discrepancy has attracted considerable attention since it might be evidence of physics beyond the simplest ΛCDM model. However, an accurate and robust calibration of the mass-observable relation for clusters is necessary for the comparison, which has been proven difficult to obtain so far. Here, we present new constraints on the mass-pressure relation by combining tSZ and CMB lensing measurements of optically selected clusters. Consequently, our galaxy cluster sample is independent of the data employed to derive cosmological constrains. We estimate an average hydrostatic mass bias of b = 0.26 ± 0.07, with no significant mass or redshift evolution. This value greatly reduces the discrepancy between the predictions of ΛCDM and the observed abundance of tSZ clusters but agrees with recent estimates from tSZ clustering. On the other hand, our value for b is higher than the predictions from hydrodynamical simulations. This suggests mechanisms that drive large departures from hydrostatic equilibrium and that are not included in the latest simulations, and/or unaccounted systematic errors such as biases in the cluster catalogue that are due to the optical selection.