Finite-sample corrected generalized estimating equation of population average treatment effects in stepped wedge cluster randomized trials.

PubMed

Scott, JoAnna M; deCamp, Allan; Juraska, Michal; Fay, Michael P; Gilbert, Peter B

2017-04-01

Stepped wedge designs are increasingly commonplace and advantageous for cluster randomized trials when it is both unethical to assign placebo, and it is logistically difficult to allocate an intervention simultaneously to many clusters. We study marginal mean models fit with generalized estimating equations for assessing treatment effectiveness in stepped wedge cluster randomized trials. This approach has advantages over the more commonly used mixed models that (1) the population-average parameters have an important interpretation for public health applications and (2) they avoid untestable assumptions on latent variable distributions and avoid parametric assumptions about error distributions, therefore, providing more robust evidence on treatment effects. However, cluster randomized trials typically have a small number of clusters, rendering the standard generalized estimating equation sandwich variance estimator biased and highly variable and hence yielding incorrect inferences. We study the usual asymptotic generalized estimating equation inferences (i.e., using sandwich variance estimators and asymptotic normality) and four small-sample corrections to generalized estimating equation for stepped wedge cluster randomized trials and for parallel cluster randomized trials as a comparison. We show by simulation that the small-sample corrections provide improvement, with one correction appearing to provide at least nominal coverage even with only 10 clusters per group. These results demonstrate the viability of the marginal mean approach for both stepped wedge and parallel cluster randomized trials. We also study the comparative performance of the corrected methods for stepped wedge and parallel designs, and describe how the methods can accommodate interval censoring of individual failure times and incorporate semiparametric efficient estimators.

Infrared Multiple Photon Dissociation Spectroscopy Of Metal Cluster-Adducts

NASA Astrophysics Data System (ADS)

Cox, D. M.; Kaldor, A.; Zakin, M. R.

1987-01-01

Recent development of the laser vaporization technique combined with mass-selective detection has made possible new studies of the fundamental chemical and physical properties of unsupported transition metal clusters as a function of the number of constituent atoms. A variety of experimental techniques have been developed in our laboratory to measure ionization threshold energies, magnetic moments, and gas phase reactivity of clusters. However, studies have so far been unable to determine the cluster structure or the chemical state of chemisorbed species on gas phase clusters. The application of infrared multiple photon dissociation IRMPD to obtain the IR absorption properties of metal cluster-adsorbate species in a molecular beam is described here. Specifically using a high power, pulsed CO2 laser as the infrared source, the IRMPD spectrum for methanol chemisorbed on small iron clusters is measured as a function of the number of both iron atoms and methanols in the complex for different methanol isotopes. Both the feasibility and potential utility of IRMPD for characterizing metal cluster-adsorbate interactions are demonstrated. The method is generally applicable to any cluster or cluster-adsorbate system dependent only upon the availability of appropriate high power infrared sources.

Free Factories: Unified Infrastructure for Data Intensive Web Services

PubMed Central

Zaranek, Alexander Wait; Clegg, Tom; Vandewege, Ward; Church, George M.

2010-01-01

We introduce the Free Factory, a platform for deploying data-intensive web services using small clusters of commodity hardware and free software. Independently administered virtual machines called Freegols give application developers the flexibility of a general purpose web server, along with access to distributed batch processing, cache and storage services. Each cluster exploits idle RAM and disk space for cache, and reserves disks in each node for high bandwidth storage. The batch processing service uses a variation of the MapReduce model. Virtualization allows every CPU in the cluster to participate in batch jobs. Each 48-node cluster can achieve 4-8 gigabytes per second of disk I/O. Our intent is to use multiple clusters to process hundreds of simultaneous requests on multi-hundred terabyte data sets. Currently, our applications achieve 1 gigabyte per second of I/O with 123 disks by scheduling batch jobs on two clusters, one of which is located in a remote data center. PMID:20514356

Catalysis applications of size-selected cluster deposition

DOE PAGES

Vajda, Stefan; White, Michael G.

2015-10-23

In this Perspective, we review recent studies of size-selected cluster deposition for catalysis applications performed at the U.S. DOE National Laboratories, with emphasis on work at Argonne National Laboratory (ANL) and Brookhaven National Laboratory (BNL). The focus is on the preparation of model supported catalysts in which the number of atoms in the deposited clusters is precisely controlled using a combination of gas-phase cluster ion sources, mass spectrometry, and soft-landing techniques. This approach is particularly effective for investigations of small nanoclusters, 0.5-2 nm (<200 atoms), where the rapid evolution of the atomic and electronic structure makes it essential to havemore » precise control over cluster size. Cluster deposition allows for independent control of cluster size, coverage, and stoichiometry (e.g., the metal-to-oxygen ratio in an oxide cluster) and can be used to deposit on any substrate without constraints of nucleation and growth. Examples are presented for metal, metal oxide, and metal sulfide cluster deposition on a variety of supports (metals, oxides, carbon/diamond) where the reactivity, cluster-support electronic interactions, and cluster stability and morphology are investigated. Both UHV and in situ/operando studies are presented that also make use of surface-sensitive X-ray characterization tools from synchrotron radiation facilities. Novel applications of cluster deposition to electrochemistry and batteries are also presented. This review also highlights the application of modern ab initio electronic structure calculations (density functional theory), which can essentially model the exact experimental system used in the laboratory (i.e., cluster and support) to provide insight on atomic and electronic structure, reaction energetics, and mechanisms. As amply demonstrated in this review, the powerful combination of atomically precise cluster deposition and theory is able to address fundamental aspects of size-effects, cluster-support interactions, and reaction mechanisms of cluster materials that are central to how catalysts function. Lastly, the insight gained from such studies can be used to further the development of novel nanostructured catalysts with high activity and selectivity.« less

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

Fernando, Amendra; Weerawardene, K. L. Dimuthu M.; Karimova, Natalia V.

Here, metal, metal oxide, and metal chalcogenide materials have a wide variety of applications. For example, many metal clusters and nanoparticles are used as catalysts for reactions varying from the oxidation of carbon monoxide to the reduction of protons to hydrogen gas. Noble metal nanoparticles have unique optical properties such as a surface plasmon resonance for large nanoparticles that yield applications in sensing and photonics. In addition, a number of transition metal clusters are magnetic. Metal oxide clusters and surfaces are commonly used as catalysts for reactions such as water splitting. Both metal oxide and metal chalcogenide materials can bemore » semiconducting, which leads to applications in sensors, electronics, and solar cells. Many researchers have been interested in studying nanoparticles and/or small clusters of these materials. Some of the system sizes under investigation have been experimentally synthesized, which enables direct theory–experiment comparison. Other clusters that have been examined theoretically are of interest as models of larger systems or surfaces. Often, the size-dependence of their properties such as their HOMO–LUMO gap, magnetic properties, optical properties, etc., is of interest.« less

Quantum Mechanical Studies of Large Metal, Metal Oxide, and Metal Chalcogenide Nanoparticles and Clusters

DOE PAGES

Fernando, Amendra; Weerawardene, K. L. Dimuthu M.; Karimova, Natalia V.; ...

2015-04-21

Here, metal, metal oxide, and metal chalcogenide materials have a wide variety of applications. For example, many metal clusters and nanoparticles are used as catalysts for reactions varying from the oxidation of carbon monoxide to the reduction of protons to hydrogen gas. Noble metal nanoparticles have unique optical properties such as a surface plasmon resonance for large nanoparticles that yield applications in sensing and photonics. In addition, a number of transition metal clusters are magnetic. Metal oxide clusters and surfaces are commonly used as catalysts for reactions such as water splitting. Both metal oxide and metal chalcogenide materials can bemore » semiconducting, which leads to applications in sensors, electronics, and solar cells. Many researchers have been interested in studying nanoparticles and/or small clusters of these materials. Some of the system sizes under investigation have been experimentally synthesized, which enables direct theory–experiment comparison. Other clusters that have been examined theoretically are of interest as models of larger systems or surfaces. Often, the size-dependence of their properties such as their HOMO–LUMO gap, magnetic properties, optical properties, etc., is of interest.« less

Optimizing Cluster Heads for Energy Efficiency in Large-Scale Heterogeneous Wireless Sensor Networks

DOE PAGES

Gu, Yi; Wu, Qishi; Rao, Nageswara S. V.

2010-01-01

Many complex sensor network applications require deploying a large number of inexpensive and small sensors in a vast geographical region to achieve quality through quantity. Hierarchical clustering is generally considered as an efficient and scalable way to facilitate the management and operation of such large-scale networks and minimize the total energy consumption for prolonged lifetime. Judicious selection of cluster heads for data integration and communication is critical to the success of applications based on hierarchical sensor networks organized as layered clusters. We investigate the problem of selecting sensor nodes in a predeployed sensor network to be the cluster heads tomore » minimize the total energy needed for data gathering. We rigorously derive an analytical formula to optimize the number of cluster heads in sensor networks under uniform node distribution, and propose a Distance-based Crowdedness Clustering algorithm to determine the cluster heads in sensor networks under general node distribution. The results from an extensive set of experiments on a large number of simulated sensor networks illustrate the performance superiority of the proposed solution over the clustering schemes based on k -means algorithm.« less

Coagulation-fragmentation for a finite number of particles and application to telomere clustering in the yeast nucleus

NASA Astrophysics Data System (ADS)

Hozé, Nathanaël; Holcman, David

2012-01-01

We develop a coagulation-fragmentation model to study a system composed of a small number of stochastic objects moving in a confined domain, that can aggregate upon binding to form local clusters of arbitrary sizes. A cluster can also dissociate into two subclusters with a uniform probability. To study the statistics of clusters, we combine a Markov chain analysis with a partition number approach. Interestingly, we obtain explicit formulas for the size and the number of clusters in terms of hypergeometric functions. Finally, we apply our analysis to study the statistical physics of telomeres (ends of chromosomes) clustering in the yeast nucleus and show that the diffusion-coagulation-fragmentation process can predict the organization of telomeres.

Ultra-small Ag clusters in zeolite A4: Antibacterial and thermochromic applications

NASA Astrophysics Data System (ADS)

Horta-Fraijo, P.; Cortez-Valadez, M.; Flores-Lopez, N. S.; Britto Hurtado, R.; Vargas-Ortiz, R. A.; Perez-Rodriguez, A.; Flores-Acosta, M.

2018-03-01

The physical and chemical properties of metal clusters depend on their atomic structure, therefore, it is important to determine the lowest-energy structures of the clusters in order to understand and utilize their properties. In this work, we use the Density Functional Theory (DFT) at the generalized gradient approximation level Becke's three-parameter and the gradient corrected functional of Lee, Yang and Puar (B3LYP) in combination with the basis set LANL2DZ (the effective core potentials and associated double-zeta valence) to determine some of the structural, electronic and vibrational properties of the planar silver clusters (Agn clusters n = 2-24). Additionally, the study reports the experimental synthesis of small silver clusters in synthetic zeolite A4. The synthesis was possible using the ion exchange method with some precursors like silver nitrate (AgNO3) and synthetic zeolite A4. The silver clusters in zeolite powder underwent thermal treatment at 450 °C to release the remaining water or humidity on it. The morphology of the particles was determined by Transmission Electron microscopy. The nanomaterials obtained show thermochromic properties. The structural parameters were correlated theoretically and experimentally.

Auger parameter and Wagner plot studies of small copper clusters

NASA Astrophysics Data System (ADS)

Moretti, Giuliano; Palma, Amedeo; Paparazzo, Ernesto; Satta, Mauro

2016-04-01

We discuss application of the Auger parameter and Wagner plot concepts to the study of small copper clusters deposited on various supports such as C(graphite), SiO2 and Al2O3. We demonstrate that the cluster size and the electronic properties of the support influence the shifts of both the binding energy of the Cu 2p3/2 transition and the kinetic energy of the Cu L3M45M45; 1G Auger transition. We find that the Cu L3M45M45; 1G-2p3/2 Auger parameter and Wagner plot allow one to single out and measure both initial- and final-state effects with a detail which is superior to that achieved in photoemission studies.

Application of Scan Statistics to Detect Suicide Clusters in Australia

PubMed Central

Cheung, Yee Tak Derek; Spittal, Matthew J.; Williamson, Michelle Kate; Tung, Sui Jay; Pirkis, Jane

2013-01-01

Background Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. Methods and Findings Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. Conclusions These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. PMID:23342098

Theoretical study of the electronic and optical properties of photochromic dithienylethene derivatives connected to small gold clusters.

PubMed

Perrier, Aurélie; Maurel, François; Aubard, Jean

2007-10-04

In the course of developing electronic devices on a molecular scale, dithienylethenes photochromic molecules constitute promising candidates for optoelectronic applications such as memories and switches. There is thus a great interest to understand and control the switching behavior of photochromic compounds deposited on metallic surfaces or nanoparticles. Within the framework of the density functional theory, we studied the effect of small gold clusters (Au3 and Au9) on the electronic structure and absorption spectrum of a model dithienylethene molecule. The molecular orbital interactions between the photochromic molecule and the gold cluster made it possible to rationalize some experimental findings (Dulic, D.; van der Molen, S. J.; Kudernac, T.; Jonkman, H. T.; de Jong, J. J. D.; Bowden, T. N.; van Esch, J.; Feringa, B. L.; van Wees, B. J. Phys. Rev. Lett. 2003, 91, 207402). For the closed-ring isomer, grafting a photochromic molecule on a small gold cluster does not change the characteristics of the electronic transition involved in the ring-opening reaction. On the opposite, the absorption spectrum of the photochromic open-ring isomer is strongly modified by the inclusion of the metallic cluster. In agreement with experimental results, our study thus showed that the cycloreversion reaction which involves the closed-ring isomer should be still possible, whereas the ring-closure reaction which involves the open-ring isomer should be inhibited. Connecting a dithienylethene molecule to a small gold cluster hence provides a qualitative comprehension of the photochromic activities of dithienylethenes connected to a gold surface.

Free energy of singular sticky-sphere clusters.

PubMed

Kallus, Yoav; Holmes-Cerfon, Miranda

2017-02-01

Networks of particles connected by springs model many condensed-matter systems, from colloids interacting with a short-range potential and complex fluids near jamming, to self-assembled lattices and various metamaterials. Under small thermal fluctuations the vibrational entropy of a ground state is given by the harmonic approximation if it has no zero-frequency vibrational modes, yet such singular modes are at the epicenter of many interesting behaviors in the systems above. We consider a system of N spherical particles, and directly account for the singularities that arise in the sticky limit where the pairwise interaction is strong and short ranged. Although the contribution to the partition function from singular clusters diverges in the limit, its asymptotic value can be calculated and depends on only two parameters, characterizing the depth and range of the potential. The result holds for systems that are second-order rigid, a geometric characterization that describes all known ground-state (rigid) sticky clusters. To illustrate the applications of our theory we address the question of emergence: how does crystalline order arise in large systems when it is strongly disfavored in small ones? We calculate the partition functions of all known rigid clusters up to N≤21 and show the cluster landscape is dominated by hyperstatic clusters (those with more than 3N-6 contacts); singular and isostatic clusters are far less frequent, despite their extra vibrational and configurational entropies. Since the most hyperstatic clusters are close to fragments of a close-packed lattice, this underlies the emergence of order in sticky-sphere systems, even those as small as N=10.

Free energy of singular sticky-sphere clusters

NASA Astrophysics Data System (ADS)

Kallus, Yoav; Holmes-Cerfon, Miranda

2017-02-01

Networks of particles connected by springs model many condensed-matter systems, from colloids interacting with a short-range potential and complex fluids near jamming, to self-assembled lattices and various metamaterials. Under small thermal fluctuations the vibrational entropy of a ground state is given by the harmonic approximation if it has no zero-frequency vibrational modes, yet such singular modes are at the epicenter of many interesting behaviors in the systems above. We consider a system of N spherical particles, and directly account for the singularities that arise in the sticky limit where the pairwise interaction is strong and short ranged. Although the contribution to the partition function from singular clusters diverges in the limit, its asymptotic value can be calculated and depends on only two parameters, characterizing the depth and range of the potential. The result holds for systems that are second-order rigid, a geometric characterization that describes all known ground-state (rigid) sticky clusters. To illustrate the applications of our theory we address the question of emergence: how does crystalline order arise in large systems when it is strongly disfavored in small ones? We calculate the partition functions of all known rigid clusters up to N ≤21 and show the cluster landscape is dominated by hyperstatic clusters (those with more than 3 N -6 contacts); singular and isostatic clusters are far less frequent, despite their extra vibrational and configurational entropies. Since the most hyperstatic clusters are close to fragments of a close-packed lattice, this underlies the emergence of order in sticky-sphere systems, even those as small as N =10 .

Online clustering algorithms for radar emitter classification.

PubMed

Liu, Jun; Lee, Jim P Y; Senior; Li, Lingjie; Luo, Zhi-Quan; Wong, K Max

2005-08-01

Radar emitter classification is a special application of data clustering for classifying unknown radar emitters from received radar pulse samples. The main challenges of this task are the high dimensionality of radar pulse samples, small sample group size, and closely located radar pulse clusters. In this paper, two new online clustering algorithms are developed for radar emitter classification: One is model-based using the Minimum Description Length (MDL) criterion and the other is based on competitive learning. Computational complexity is analyzed for each algorithm and then compared. Simulation results show the superior performance of the model-based algorithm over competitive learning in terms of better classification accuracy, flexibility, and stability.

High-dimensional cluster analysis with the Masked EM Algorithm

PubMed Central

Kadir, Shabnam N.; Goodman, Dan F. M.; Harris, Kenneth D.

2014-01-01

Cluster analysis faces two problems in high dimensions: first, the “curse of dimensionality” that can lead to overfitting and poor generalization performance; and second, the sheer time taken for conventional algorithms to process large amounts of high-dimensional data. We describe a solution to these problems, designed for the application of “spike sorting” for next-generation high channel-count neural probes. In this problem, only a small subset of features provide information about the cluster member-ship of any one data vector, but this informative feature subset is not the same for all data points, rendering classical feature selection ineffective. We introduce a “Masked EM” algorithm that allows accurate and time-efficient clustering of up to millions of points in thousands of dimensions. We demonstrate its applicability to synthetic data, and to real-world high-channel-count spike sorting data. PMID:25149694

Soft-landing ion mobility of silver clusters for small-molecule matrix-assisted laser desorption ionization mass spectrometry and imaging of latent fingerprints.

PubMed

Walton, Barbara L; Verbeck, Guido F

2014-08-19

Matrix-assisted laser desorption ionization (MALDI) imaging is gaining popularity, but matrix effects such as mass spectral interference and damage to the sample limit its applications. Replacing traditional matrices with silver particles capable of equivalent or increased photon energy absorption from the incoming laser has proven to be beneficial for low mass analysis. Not only can silver clusters be advantageous for low mass compound detection, but they can be used for imaging as well. Conventional matrix application methods can obstruct samples, such as fingerprints, rendering them useless after mass analysis. The ability to image latent fingerprints without causing damage to the ridge pattern is important as it allows for further characterization of the print. The application of silver clusters by soft-landing ion mobility allows for enhanced MALDI and preservation of fingerprint integrity.

Application and Limitations of Nanocasting in Metal–Organic Frameworks

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

Malonzo, Camille D.; Wang, Zhao; Duan, Jiaxin

Nanocasting can be a useful strategy to transfer the catalytic metal clusters in metal-organic frameworks (MOFs) to an all-inorganic support such as silica. The incorporation of silica in the MOF pores as a secondary support has the potential to extend the application of the highly tunable metal-based active sites in MOFs to high temperature catalysis. Here, we demonstrate the applicability of the nanocasting method to a range of MOFs that incorporate catalytically attractive hexazirconium, hexacerium, or pentanickel oxide-based clusters (UiO-66, (Ce)UiO-66, (Ce)UiO-67, (Ce)MOF-808, DUT-9, and In- and Ni-post-metalated NU-1000). We describe, in tutorial form, the challenges associated with nanocasting ofmore » MOFs that are related to their small pore size and to considerations of chemical and mechanical stability, and we provide approaches to overcome some of these challenges. Some of these nanocast materials feature the site-isolated clusters in a porous, thermally stable silica matrix, suitable for catalysis at high temperatures; in others, structural rearrangement of clusters or partial cluster aggregation occurs, but extensive aggregation can be mitigated by the silica skeleton introduced during nanocasting.« less

A scaling theory for number-flux distributions generated during steady-state coagulation and settling and application to particles in Lake Zurich, Switzerland.

PubMed

Boehm, Alexandria B

2002-10-15

In this study, we extend the established scaling theory for cluster size distributions generated during unsteady coagulation to number-flux distributions that arise during steady-state coagulation and settling in an unmixed water mass. The scaling theory predicts self-similar number-flux distributions and power-law decay of total number flux with depth. The shape of the number-flux distributions and the power-law exponent describing the decay of the total number flux are shown to depend on the homogeneity and small i/j limit of the coagulation kernel and the exponent kappa, which describes the variation in settling velocity with cluster volume. Particle field measurements from Lake Zurich, collected by U. Weilenmann and co-workers (Limnol. Oceanogr.34, 1 (1989)), are used to illustrate how the scaling predictions can be applied to a natural system. This effort indicates that within the mid-depth region of Lake Zurich, clusters of the same size preferentially interact and large clusters react with one another more quickly than small ones, indicative of clusters coagulating in a reaction-limited regime.

A method of operation scheduling based on video transcoding for cluster equipment

NASA Astrophysics Data System (ADS)

Zhou, Haojie; Yan, Chun

2018-04-01

Because of the cluster technology in real-time video transcoding device, the application of facing the massive growth in the number of video assignments and resolution and bit rate of diversity, task scheduling algorithm, and analyze the current mainstream of cluster for real-time video transcoding equipment characteristics of the cluster, combination with the characteristics of the cluster equipment task delay scheduling algorithm is proposed. This algorithm enables the cluster to get better performance in the generation of the job queue and the lower part of the job queue when receiving the operation instruction. In the end, a small real-time video transcode cluster is constructed to analyze the calculation ability, running time, resource occupation and other aspects of various algorithms in operation scheduling. The experimental results show that compared with traditional clustering task scheduling algorithm, task delay scheduling algorithm has more flexible and efficient characteristics.

An Unmanned Aerial Vehicle Cluster Network Cruise System for Monitor

NASA Astrophysics Data System (ADS)

Jiang, Jirong; Tao, Jinpeng; Xin, Guipeng

2018-06-01

The existing maritime cruising system mainly uses manned motorboats to monitor the quality of coastal water and patrol and maintenance of the navigation -aiding facility, which has the problems of high energy consumption, small range of cruise for monitoring, insufficient information control and low visualization. In recent years, the application of UAS in the maritime field has alleviated the phenomenon above to some extent. A cluster-based unmanned network monitoring cruise system designed in this project uses the floating small UAV self-powered launching platform as a carrier, applys the idea of cluster, and combines the strong controllability of the multi-rotor UAV and the capability to carry customized modules, constituting a unmanned, visualized and normalized monitoring cruise network to realize the functions of maritime cruise, maintenance of navigational-aiding and monitoring the quality of coastal water.

Defining RNA-Small Molecule Affinity Landscapes Enables Design of a Small Molecule Inhibitor of an Oncogenic Noncoding RNA.

PubMed

Velagapudi, Sai Pradeep; Luo, Yiling; Tran, Tuan; Haniff, Hafeez S; Nakai, Yoshio; Fallahi, Mohammad; Martinez, Gustavo J; Childs-Disney, Jessica L; Disney, Matthew D

2017-03-22

RNA drug targets are pervasive in cells, but methods to design small molecules that target them are sparse. Herein, we report a general approach to score the affinity and selectivity of RNA motif-small molecule interactions identified via selection. Named High Throughput Structure-Activity Relationships Through Sequencing (HiT-StARTS), HiT-StARTS is statistical in nature and compares input nucleic acid sequences to selected library members that bind a ligand via high throughput sequencing. The approach allowed facile definition of the fitness landscape of hundreds of thousands of RNA motif-small molecule binding partners. These results were mined against folded RNAs in the human transcriptome and identified an avid interaction between a small molecule and the Dicer nuclease-processing site in the oncogenic microRNA (miR)-18a hairpin precursor, which is a member of the miR-17-92 cluster. Application of the small molecule, Targapremir-18a, to prostate cancer cells inhibited production of miR-18a from the cluster, de-repressed serine/threonine protein kinase 4 protein (STK4), and triggered apoptosis. Profiling the cellular targets of Targapremir-18a via Chemical Cross-Linking and Isolation by Pull Down (Chem-CLIP), a covalent small molecule-RNA cellular profiling approach, and other studies showed specific binding of the compound to the miR-18a precursor, revealing broadly applicable factors that govern small molecule drugging of noncoding RNAs.

Defining RNA–Small Molecule Affinity Landscapes Enables Design of a Small Molecule Inhibitor of an Oncogenic Noncoding RNA

PubMed Central

2017-01-01

RNA drug targets are pervasive in cells, but methods to design small molecules that target them are sparse. Herein, we report a general approach to score the affinity and selectivity of RNA motif–small molecule interactions identified via selection. Named High Throughput Structure–Activity Relationships Through Sequencing (HiT-StARTS), HiT-StARTS is statistical in nature and compares input nucleic acid sequences to selected library members that bind a ligand via high throughput sequencing. The approach allowed facile definition of the fitness landscape of hundreds of thousands of RNA motif–small molecule binding partners. These results were mined against folded RNAs in the human transcriptome and identified an avid interaction between a small molecule and the Dicer nuclease-processing site in the oncogenic microRNA (miR)-18a hairpin precursor, which is a member of the miR-17-92 cluster. Application of the small molecule, Targapremir-18a, to prostate cancer cells inhibited production of miR-18a from the cluster, de-repressed serine/threonine protein kinase 4 protein (STK4), and triggered apoptosis. Profiling the cellular targets of Targapremir-18a via Chemical Cross-Linking and Isolation by Pull Down (Chem-CLIP), a covalent small molecule–RNA cellular profiling approach, and other studies showed specific binding of the compound to the miR-18a precursor, revealing broadly applicable factors that govern small molecule drugging of noncoding RNAs. PMID:28386598

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications.

PubMed

Karyotis, Vasileios; Tsitseklis, Konstantinos; Sotiropoulos, Konstantinos; Papavassiliou, Symeon

2018-04-15

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan-Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing.

Big Data Clustering via Community Detection and Hyperbolic Network Embedding in IoT Applications

PubMed Central

Sotiropoulos, Konstantinos

2018-01-01

In this paper, we present a novel data clustering framework for big sensory data produced by IoT applications. Based on a network representation of the relations among multi-dimensional data, data clustering is mapped to node clustering over the produced data graphs. To address the potential very large scale of such datasets/graphs that test the limits of state-of-the-art approaches, we map the problem of data clustering to a community detection one over the corresponding data graphs. Specifically, we propose a novel computational approach for enhancing the traditional Girvan–Newman (GN) community detection algorithm via hyperbolic network embedding. The data dependency graph is embedded in the hyperbolic space via Rigel embedding, allowing more efficient computation of edge-betweenness centrality needed in the GN algorithm. This allows for more efficient clustering of the nodes of the data graph in terms of modularity, without sacrificing considerable accuracy. In order to study the operation of our approach with respect to enhancing GN community detection, we employ various representative types of artificial complex networks, such as scale-free, small-world and random geometric topologies, and frequently-employed benchmark datasets for demonstrating its efficacy in terms of data clustering via community detection. Furthermore, we provide a proof-of-concept evaluation by applying the proposed framework over multi-dimensional datasets obtained from an operational smart-city/building IoT infrastructure provided by the Federated Interoperable Semantic IoT/cloud Testbeds and Applications (FIESTA-IoT) testbed federation. It is shown that the proposed framework can be indeed used for community detection/data clustering and exploited in various other IoT applications, such as performing more energy-efficient smart-city/building sensing. PMID:29662043

The effect of different distance measures in detecting outliers using clustering-based algorithm for circular regression model

NASA Astrophysics Data System (ADS)

Di, Nur Faraidah Muhammad; Satari, Siti Zanariah

2017-05-01

Outlier detection in linear data sets has been done vigorously but only a small amount of work has been done for outlier detection in circular data. In this study, we proposed multiple outliers detection in circular regression models based on the clustering algorithm. Clustering technique basically utilizes distance measure to define distance between various data points. Here, we introduce the similarity distance based on Euclidean distance for circular model and obtain a cluster tree using the single linkage clustering algorithm. Then, a stopping rule for the cluster tree based on the mean direction and circular standard deviation of the tree height is proposed. We classify the cluster group that exceeds the stopping rule as potential outlier. Our aim is to demonstrate the effectiveness of proposed algorithms with the similarity distances in detecting the outliers. It is found that the proposed methods are performed well and applicable for circular regression model.

Solid State Digital Propulsion "Cluster Thrusters" For Small Satellites Using High Performance Electrically Controlled Extinguishable Solid Propellants (ECESP)

NASA Technical Reports Server (NTRS)

Sawka, Wayne N.; Katzakian, Arthur; Grix, Charles

2005-01-01

Electrically controlled extinguishable solid propellants (ESCSP) are capable of multiple ignitions, extinguishments and throttle control by the application of electrical power. Both core and end burning no moving parts ECESP grains/motors to three inches in diameter have now been tested. Ongoing research has led to a newer family of even higher performance ECESP providing up to 10% higher performance, manufacturing ease, and significantly higher electrical conduction. The high conductivity was not found to be desirable for larger motors; however it is ideal for downward scaling to micro and pico- propulsion applications with a web thickness of less than 0.125 inch/ diameter. As a solid solution propellant, this ECESP is molecularly uniform, having no granular structure. Because of this homogeneity and workable viscosity it can be directly cast into thin layers or vacuum cast into complex geometries. Both coaxial and grain stacks have been demonstrated. Combining individual propellant coaxial grains and/or grain stacks together form three-dimensional arrays yield modular cluster thrusters. Adoption of fabless manufacturing methods and standards from the electronics industry will provide custom, highly reproducible micro-propulsion arrays and clusters at low costs. These stack and cluster thruster designs provide a small footprint saving spacecraft surface area for solar panels and/or experiments. The simplicity of these thrusters will enable their broad use on micro-pico satellites for primary propulsion, ACS and formation flying applications. Larger spacecraft may find uses for ECESP thrusters on extended booms, on-orbit refueling, pneumatic actuators, and gas generators.

Inference With Difference-in-Differences With a Small Number of Groups: A Review, Simulation Study, and Empirical Application Using SHARE Data.

PubMed

Rokicki, Slawa; Cohen, Jessica; Fink, Günther; Salomon, Joshua A; Landrum, Mary Beth

2018-01-01

Difference-in-differences (DID) estimation has become increasingly popular as an approach to evaluate the effect of a group-level policy on individual-level outcomes. Several statistical methodologies have been proposed to correct for the within-group correlation of model errors resulting from the clustering of data. Little is known about how well these corrections perform with the often small number of groups observed in health research using longitudinal data. First, we review the most commonly used modeling solutions in DID estimation for panel data, including generalized estimating equations (GEE), permutation tests, clustered standard errors (CSE), wild cluster bootstrapping, and aggregation. Second, we compare the empirical coverage rates and power of these methods using a Monte Carlo simulation study in scenarios in which we vary the degree of error correlation, the group size balance, and the proportion of treated groups. Third, we provide an empirical example using the Survey of Health, Ageing, and Retirement in Europe. When the number of groups is small, CSE are systematically biased downwards in scenarios when data are unbalanced or when there is a low proportion of treated groups. This can result in over-rejection of the null even when data are composed of up to 50 groups. Aggregation, permutation tests, bias-adjusted GEE, and wild cluster bootstrap produce coverage rates close to the nominal rate for almost all scenarios, though GEE may suffer from low power. In DID estimation with a small number of groups, analysis using aggregation, permutation tests, wild cluster bootstrap, or bias-adjusted GEE is recommended.

High-throughput platform for the discovery of elicitors of silent bacterial gene clusters.

PubMed

Seyedsayamdost, Mohammad R

2014-05-20

Over the past decade, bacterial genome sequences have revealed an immense reservoir of biosynthetic gene clusters, sets of contiguous genes that have the potential to produce drugs or drug-like molecules. However, the majority of these gene clusters appear to be inactive for unknown reasons prompting terms such as "cryptic" or "silent" to describe them. Because natural products have been a major source of therapeutic molecules, methods that rationally activate these silent clusters would have a profound impact on drug discovery. Herein, a new strategy is outlined for awakening silent gene clusters using small molecule elicitors. In this method, a genetic reporter construct affords a facile read-out for activation of the silent cluster of interest, while high-throughput screening of small molecule libraries provides potential inducers. This approach was applied to two cryptic gene clusters in the pathogenic model Burkholderia thailandensis. The results not only demonstrate a prominent activation of these two clusters, but also reveal that the majority of elicitors are themselves antibiotics, most in common clinical use. Antibiotics, which kill B. thailandensis at high concentrations, act as inducers of secondary metabolism at low concentrations. One of these antibiotics, trimethoprim, served as a global activator of secondary metabolism by inducing at least five biosynthetic pathways. Further application of this strategy promises to uncover the regulatory networks that activate silent gene clusters while at the same time providing access to the vast array of cryptic molecules found in bacteria.

Kinetic Monte Carlo Simulation of the Growth of Various Nanostructures through Atomic and Cluster Deposition: Application to Gold Nanostructure Growth on Graphite

NASA Astrophysics Data System (ADS)

Claassens, C. H.; Hoffman, M. J. H.; Terblans, J. J.; Swart, H. C.

2006-01-01

A Kinetic Monte Carlo (KMC) method is presented to describe the growth of metallic nanostructures through atomic and cluster deposition in the mono -and multilayer regime. The model makes provision for homo- and heteroepitaxial systems with small lattice mismatch. The accuracy of the model is tested with simulations of the growth of gold nanostructures on HOPG and comparisons are made with existing experimental data.

Finding reproducible cluster partitions for the k-means algorithm

PubMed Central

2013-01-01

K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset. PMID:23369085

Finding reproducible cluster partitions for the k-means algorithm.

PubMed

Lisboa, Paulo J G; Etchells, Terence A; Jarman, Ian H; Chambers, Simon J

2013-01-01

K-means clustering is widely used for exploratory data analysis. While its dependence on initialisation is well-known, it is common practice to assume that the partition with lowest sum-of-squares (SSQ) total i.e. within cluster variance, is both reproducible under repeated initialisations and also the closest that k-means can provide to true structure, when applied to synthetic data. We show that this is generally the case for small numbers of clusters, but for values of k that are still of theoretical and practical interest, similar values of SSQ can correspond to markedly different cluster partitions. This paper extends stability measures previously presented in the context of finding optimal values of cluster number, into a component of a 2-d map of the local minima found by the k-means algorithm, from which not only can values of k be identified for further analysis but, more importantly, it is made clear whether the best SSQ is a suitable solution or whether obtaining a consistently good partition requires further application of the stability index. The proposed method is illustrated by application to five synthetic datasets replicating a real world breast cancer dataset with varying data density, and a large bioinformatics dataset.

A comparison of confidence interval methods for the intraclass correlation coefficient in community-based cluster randomization trials with a binary outcome.

PubMed

Braschel, Melissa C; Svec, Ivana; Darlington, Gerarda A; Donner, Allan

2016-04-01

Many investigators rely on previously published point estimates of the intraclass correlation coefficient rather than on their associated confidence intervals to determine the required size of a newly planned cluster randomized trial. Although confidence interval methods for the intraclass correlation coefficient that can be applied to community-based trials have been developed for a continuous outcome variable, fewer methods exist for a binary outcome variable. The aim of this study is to evaluate confidence interval methods for the intraclass correlation coefficient applied to binary outcomes in community intervention trials enrolling a small number of large clusters. Existing methods for confidence interval construction are examined and compared to a new ad hoc approach based on dividing clusters into a large number of smaller sub-clusters and subsequently applying existing methods to the resulting data. Monte Carlo simulation is used to assess the width and coverage of confidence intervals for the intraclass correlation coefficient based on Smith's large sample approximation of the standard error of the one-way analysis of variance estimator, an inverted modified Wald test for the Fleiss-Cuzick estimator, and intervals constructed using a bootstrap-t applied to a variance-stabilizing transformation of the intraclass correlation coefficient estimate. In addition, a new approach is applied in which clusters are randomly divided into a large number of smaller sub-clusters with the same methods applied to these data (with the exception of the bootstrap-t interval, which assumes large cluster sizes). These methods are also applied to a cluster randomized trial on adolescent tobacco use for illustration. When applied to a binary outcome variable in a small number of large clusters, existing confidence interval methods for the intraclass correlation coefficient provide poor coverage. However, confidence intervals constructed using the new approach combined with Smith's method provide nominal or close to nominal coverage when the intraclass correlation coefficient is small (<0.05), as is the case in most community intervention trials. This study concludes that when a binary outcome variable is measured in a small number of large clusters, confidence intervals for the intraclass correlation coefficient may be constructed by dividing existing clusters into sub-clusters (e.g. groups of 5) and using Smith's method. The resulting confidence intervals provide nominal or close to nominal coverage across a wide range of parameters when the intraclass correlation coefficient is small (<0.05). Application of this method should provide investigators with a better understanding of the uncertainty associated with a point estimator of the intraclass correlation coefficient used for determining the sample size needed for a newly designed community-based trial. © The Author(s) 2015.

Photo-induced transformation process at gold clusters-semiconductor interface: Implications for the complexity of gold clusters-based photocatalysis

NASA Astrophysics Data System (ADS)

Liu, Siqi; Xu, Yi-Jun

2016-03-01

The recent thrust in utilizing atomically precise organic ligands protected gold clusters (Au clusters) as photosensitizer coupled with semiconductors for nano-catalysts has led to the claims of improved efficiency in photocatalysis. Nonetheless, the influence of photo-stability of organic ligands protected-Au clusters at the Au/semiconductor interface on the photocatalytic properties remains rather elusive. Taking Au clusters-TiO2 composites as a prototype, we for the first time demonstrate the photo-induced transformation of small molecular-like Au clusters to larger metallic Au nanoparticles under different illumination conditions, which leads to the diverse photocatalytic reaction mechanism. This transformation process undergoes a diffusion/aggregation mechanism accompanied with the onslaught of Au clusters by active oxygen species and holes resulting from photo-excited TiO2 and Au clusters. However, such Au clusters aggregation can be efficiently inhibited by tuning reaction conditions. This work would trigger rational structural design and fine condition control of organic ligands protected-metal clusters-semiconductor composites for diverse photocatalytic applications with long-term photo-stability.

A smart checkpointing scheme for improving the reliability of clustering routing protocols.

PubMed

Min, Hong; Jung, Jinman; Kim, Bongjae; Cho, Yookun; Heo, Junyoung; Yi, Sangho; Hong, Jiman

2010-01-01

In wireless sensor networks, system architectures and applications are designed to consider both resource constraints and scalability, because such networks are composed of numerous sensor nodes with various sensors and actuators, small memories, low-power microprocessors, radio modules, and batteries. Clustering routing protocols based on data aggregation schemes aimed at minimizing packet numbers have been proposed to meet these requirements. In clustering routing protocols, the cluster head plays an important role. The cluster head collects data from its member nodes and aggregates the collected data. To improve reliability and reduce recovery latency, we propose a checkpointing scheme for the cluster head. In the proposed scheme, backup nodes monitor and checkpoint the current state of the cluster head periodically. We also derive the checkpointing interval that maximizes reliability while using the same amount of energy consumed by clustering routing protocols that operate without checkpointing. Experimental comparisons with existing non-checkpointing schemes show that our scheme reduces both energy consumption and recovery latency.

A Smart Checkpointing Scheme for Improving the Reliability of Clustering Routing Protocols

PubMed Central

Min, Hong; Jung, Jinman; Kim, Bongjae; Cho, Yookun; Heo, Junyoung; Yi, Sangho; Hong, Jiman

2010-01-01

In wireless sensor networks, system architectures and applications are designed to consider both resource constraints and scalability, because such networks are composed of numerous sensor nodes with various sensors and actuators, small memories, low-power microprocessors, radio modules, and batteries. Clustering routing protocols based on data aggregation schemes aimed at minimizing packet numbers have been proposed to meet these requirements. In clustering routing protocols, the cluster head plays an important role. The cluster head collects data from its member nodes and aggregates the collected data. To improve reliability and reduce recovery latency, we propose a checkpointing scheme for the cluster head. In the proposed scheme, backup nodes monitor and checkpoint the current state of the cluster head periodically. We also derive the checkpointing interval that maximizes reliability while using the same amount of energy consumed by clustering routing protocols that operate without checkpointing. Experimental comparisons with existing non-checkpointing schemes show that our scheme reduces both energy consumption and recovery latency. PMID:22163389

Issues in ATM Support of High-Performance, Geographically Distributed Computing

NASA Technical Reports Server (NTRS)

Claus, Russell W.; Dowd, Patrick W.; Srinidhi, Saragur M.; Blade, Eric D.G

1995-01-01

This report experimentally assesses the effect of the underlying network in a cluster-based computing environment. The assessment is quantified by application-level benchmarking, process-level communication, and network file input/output. Two testbeds were considered, one small cluster of Sun workstations and another large cluster composed of 32 high-end IBM RS/6000 platforms. The clusters had Ethernet, fiber distributed data interface (FDDI), Fibre Channel, and asynchronous transfer mode (ATM) network interface cards installed, providing the same processors and operating system for the entire suite of experiments. The primary goal of this report is to assess the suitability of an ATM-based, local-area network to support interprocess communication and remote file input/output systems for distributed computing.

Photo-induced transformation process at gold clusters-semiconductor interface: Implications for the complexity of gold clusters-based photocatalysis

PubMed Central

Liu, Siqi; Xu, Yi-Jun

2016-01-01

The recent thrust in utilizing atomically precise organic ligands protected gold clusters (Au clusters) as photosensitizer coupled with semiconductors for nano-catalysts has led to the claims of improved efficiency in photocatalysis. Nonetheless, the influence of photo-stability of organic ligands protected-Au clusters at the Au/semiconductor interface on the photocatalytic properties remains rather elusive. Taking Au clusters–TiO2 composites as a prototype, we for the first time demonstrate the photo-induced transformation of small molecular-like Au clusters to larger metallic Au nanoparticles under different illumination conditions, which leads to the diverse photocatalytic reaction mechanism. This transformation process undergoes a diffusion/aggregation mechanism accompanied with the onslaught of Au clusters by active oxygen species and holes resulting from photo-excited TiO2 and Au clusters. However, such Au clusters aggregation can be efficiently inhibited by tuning reaction conditions. This work would trigger rational structural design and fine condition control of organic ligands protected-metal clusters-semiconductor composites for diverse photocatalytic applications with long-term photo-stability. PMID:26947754

Bayesian performance metrics and small system integration in recent homeland security and defense applications

NASA Astrophysics Data System (ADS)

Jannson, Tomasz; Kostrzewski, Andrew; Patton, Edward; Pradhan, Ranjit; Shih, Min-Yi; Walter, Kevin; Savant, Gajendra; Shie, Rick; Forrester, Thomas

2010-04-01

In this paper, Bayesian inference is applied to performance metrics definition of the important class of recent Homeland Security and defense systems called binary sensors, including both (internal) system performance and (external) CONOPS. The medical analogy is used to define the PPV (Positive Predictive Value), the basic Bayesian metrics parameter of the binary sensors. Also, Small System Integration (SSI) is discussed in the context of recent Homeland Security and defense applications, emphasizing a highly multi-technological approach, within the broad range of clusters ("nexus") of electronics, optics, X-ray physics, γ-ray physics, and other disciplines.

Mass spectrometric identification of intermediates in the O2-driven [4Fe-4S] to [2Fe-2S] cluster conversion in FNR

PubMed Central

Crack, Jason C.; Thomson, Andrew J.

2017-01-01

The iron-sulfur cluster containing protein Fumarate and Nitrate Reduction (FNR) is the master regulator for the switch between anaerobic and aerobic respiration in Escherichia coli and many other bacteria. The [4Fe-4S] cluster functions as the sensory module, undergoing reaction with O2 that leads to conversion to a [2Fe-2S] form with loss of high-affinity DNA binding. Here, we report studies of the FNR cluster conversion reaction using time-resolved electrospray ionization mass spectrometry. The data provide insight into the reaction, permitting the detection of cluster conversion intermediates and products, including a [3Fe-3S] cluster and persulfide-coordinated [2Fe-2S] clusters [[2Fe-2S](S)n, where n = 1 or 2]. Analysis of kinetic data revealed a branched mechanism in which cluster sulfide oxidation occurs in parallel with cluster conversion and not as a subsequent, secondary reaction to generate [2Fe-2S](S)n species. This methodology shows great potential for broad application to studies of protein cofactor–small molecule interactions. PMID:28373574

Tuning the Emission and Quantum Yield of Gold and Silver Nanoclusters Through Ligand Design and Doping

NASA Astrophysics Data System (ADS)

Mishra, Dinesh

Nanoparticles have been extensively studied in the past few decades due to the possibilities they offer in applications ranging from medicine to energy generation. A new class of ultra-small noble metal nanoparticles consisting of tens to hundreds of atoms, commonly known as clusters or nanoclusters, have drawn interest of the research community recently due to their unique optical, electronic and structural properties. Over the past few years, advances have been made in the synthesis of atomically precise noble metal clusters (for example, silver and gold) with distinct optical properties. Their ultra-small size distinguishes them from conventional plasmonic nanoparticles and the properties are very sensitive to the slight variation in the compositon of the cluster, i.e. the number of the metal atoms and/or the nature of the ligands. These clusters are interesting because of their potential applications in field such as sensing, imaging, catalysis, clean energy, photonics, etc. as well as they provide fundamental insight into the evolution of the optical and electronic properties of these clusters. In this project, we explored the strategies to synthesize luminescent metallic clusters of gold and silver and to promote their solubility and stability in aqueous and biological medium. We focused particularly on the thiolate protected clusters due to the higher affinity of gold and silver to sulfur. Lipoic acid (Thioctic acid) is a bio-molecule with a cyclic disulfide ring, which also acts as a chelating ligand. Due to the higher binding affinity of the cyclic disulfide ring to nanocrystal surface, lipoic acid and chemically modified lipoic acid molecules have been widely reported for the synthesis and functionalization of inorganic nanocrystals. Here, we describe the use of bidentate lipoic acid ligands in the one phase growth of luminescent gold and silver nanoclusters. In addition, we have synthesized a new set of monothiol ligands containing PEG and zwitterion for the functionalization of fluorescent clusters. Chapter 1 introduces the fundamental properties of metallic clusters and the origin of these properties from electronic and structural point of view. The optical properties of ultra-small nanocrystals (<2 nm) in comparison to the plasmonic particles is described. In addition, the variation of optical and structural properties from one metal to another as well as one ligand to another is also compared. Chapter 2 describes the synthesis of ultra-small size gold clusters with different optical emission (ranging from blue to red) using photo-activated LA-PEG ligands. The influence of various factors on the growth of the clusters is also studied. Optical properties of the clusters were studied by UV-visible absorption, PL emission and excitation and time resolved fluorescence spectroscopy. XPS and DOSY NMR were used to characterize the oxidation states and sizes of these clusters. The photo-chemical transformation of LA-PEG ligands to thiols and the effect of various experimental parameters such as solvent, oxygen, ligand functional group and effect of acid are described in chapter 3. Thiol yield percentage was quantified using ellman assay. Chapter 4 describes the one phase aqueous synthesis of Ag29 clusters capped with bidentate dihydrolipoic acid (DHLA). We also describe the drastic enhancement of the PL intensity upon gold doping of the Ag29 clusters. Optical properties along with the size characterization by electrospray ionization mass spectrometry is also described. We further describe the growth of these clusters using DHLA-PEG molecules. Chapter 5 describes the synthesis of highly fluorescent Au25-xAgx clusters stabilized with two types of ligands (triphenylphosphine and thiols). We designed a set of monothiolate ligands appended with PEG and zwitterionic moieties. This approach allows to prepare water soluble and stable metallic clusters with enhanced photoluminescence and well defined optical properties. Chapter 6 is the overall summary of our findings and prospects and outlook.

SBA Innovation Clusters

DTIC Science & Technology

2012-03-02

Programs and services to help you start, grow and succeed www.sba.gov U.S. Small Business Administration Your Small Business Resource 1Approved for...Public Release SBA Innovation Clusters RADM Steven G. Smith USN (Ret) Advanced Defense Technology Cluster Coordinator U.S. Small Business ...UNIT NUMBER 7. PERFORMING ORGANIZATION NAME(S) AND ADDRESS(ES) U.S. Small Business Administration ,Advanced Defense Technology Cluster,409 3rd St, SW

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.

Sound field measurement in a double layer cavitation cluster by rugged miniature needle hydrophones.

PubMed

Koch, Christian

2016-03-01

During multi-bubble cavitation the bubbles tend to organize themselves into clusters and thus the understanding of properties and dynamics of clustering is essential for controlling technical applications of cavitation. Sound field measurements are a potential technique to provide valuable experimental information about the status of cavitation clouds. Using purpose-made, rugged, wide band, and small-sized needle hydrophones, sound field measurements in bubble clusters were performed and time-dependent sound pressure waveforms were acquired and analyzed in the frequency domain up to 20 MHz. The cavitation clusters were synchronously observed by an electron multiplying charge-coupled device (EMCCD) camera and the relation between the sound field measurements and cluster behaviour was investigated. Depending on the driving power, three ranges could be identified and characteristic properties were assigned. At low power settings no transient and no or very low stable cavitation activity can be observed. The medium range is characterized by strong pressure peaks and various bubble cluster forms. At high power a stable double layer was observed which grew with further increasing power and became quite dynamic. The sound field was irregular and the fundamental at driving frequency decreased. Between the bubble clouds completely different sound field properties were found in comparison to those in the cloud where the cavitation activity is high. In between the sound field pressure amplitude was quite small and no collapses were detected. Copyright © 2015. Published by Elsevier B.V.

Infrared Spectroscopy of Naphthalene Aggregation and Cluster Formation in Argon Matrices

NASA Technical Reports Server (NTRS)

Roser, J. E.; Allamondola, L. J.

2011-01-01

Fourier-transform mid-infrared absorption spectra of mixed argon/naphthalene matrices at 5 K are shown with ratios of argon-to-naphthalene that vary from 1000 to 0. These spectra show the changes as naphthalene clustering and aggregation occurs, with moderate spectral shifts affecting the C-H vibrational modes and relatively small or no shifts to the C-C and C-C-C vibrational modes. The possible contribution of homogeneous naphthalene clusters to the interstellar unidentified infrared bands is discussed. The contribution of polycyclic aromatic hydrocarbon (PAH) clusters to the 7.7 micron emission plateau and the blue shading of the 12.7 micron emission band are identified as promising candidates for future research. In addition, since PAH clusters are model components of Jupiter and Titan's atmospheres, the information presented here may also be applicable to the spectroscopy of these objects.

Application of TALE-Based Approach for Dissecting Functional MicroRNA-302/367 in Cellular Reprogramming.

PubMed

Zhang, Zhonghui; Wu, Wen-Shu

2018-01-01

MicroRNAs are small 18-24 nt single-stranded noncoding RNA molecules involved in many biological processes, including stemness maintenance and cellular reprogramming. Current methods used in loss-of-function studies of microRNAs have several limitations. Here, we describe a new approach for dissecting miR-302/367 functions by transcription activator-like effectors (TALEs), which are natural effector proteins secreted by Xanthomonas and Ralstonia bacteria. Knockdown of the miR-302/367 cluster uses the Kruppel-associated box repressor domain fused with specific TALEs designed to bind the miR-302/367 cluster promoter. Knockout of the miR-302/367 cluster uses two pairs of TALE nucleases (TALENs) to delete the miR-302/367 cluster in human primary cells. Together, both TALE-based transcriptional repressor and TALENs are two promising approaches for loss-of-function studies of microRNA cluster in human primary cells.

Bright betatron X-ray radiation from a laser-driven-clustering gas target

PubMed Central

Chen, L. M.; Yan, W. C.; Li, D. Z.; Hu, Z. D.; Zhang, L.; Wang, W. M.; Hafz, N.; Mao, J. Y.; Huang, K.; Ma, Y.; Zhao, J. R.; Ma, J. L.; Li, Y. T.; Lu, X.; Sheng, Z. M.; Wei, Z. Y.; Gao, J.; Zhang, J.

2013-01-01

Hard X-ray sources from femtosecond (fs) laser-produced plasmas, including the betatron X-rays from laser wakefield-accelerated electrons, have compact sizes, fs pulse duration and fs pump-probe capability, making it promising for wide use in material and biological sciences. Currently the main problem with such betatron X-ray sources is the limited average flux even with ultra-intense laser pulses. Here, we report ultra-bright betatron X-rays can be generated using a clustering gas jet target irradiated with a small size laser, where a ten-fold enhancement of the X-ray yield is achieved compared to the results obtained using a gas target. We suggest the increased X-ray photon is due to the existence of clusters in the gas, which results in increased total electron charge trapped for acceleration and larger wiggling amplitudes during the acceleration. This observation opens a route to produce high betatron average flux using small but high repetition rate laser facilities for applications. PMID:23715033

Minimum number of clusters and comparison of analysis methods for cross sectional stepped wedge cluster randomised trials with binary outcomes: A simulation study.

PubMed

Barker, Daniel; D'Este, Catherine; Campbell, Michael J; McElduff, Patrick

2017-03-09

Stepped wedge cluster randomised trials frequently involve a relatively small number of clusters. The most common frameworks used to analyse data from these types of trials are generalised estimating equations and generalised linear mixed models. A topic of much research into these methods has been their application to cluster randomised trial data and, in particular, the number of clusters required to make reasonable inferences about the intervention effect. However, for stepped wedge trials, which have been claimed by many researchers to have a statistical power advantage over the parallel cluster randomised trial, the minimum number of clusters required has not been investigated. We conducted a simulation study where we considered the most commonly used methods suggested in the literature to analyse cross-sectional stepped wedge cluster randomised trial data. We compared the per cent bias, the type I error rate and power of these methods in a stepped wedge trial setting with a binary outcome, where there are few clusters available and when the appropriate adjustment for a time trend is made, which by design may be confounding the intervention effect. We found that the generalised linear mixed modelling approach is the most consistent when few clusters are available. We also found that none of the common analysis methods for stepped wedge trials were both unbiased and maintained a 5% type I error rate when there were only three clusters. Of the commonly used analysis approaches, we recommend the generalised linear mixed model for small stepped wedge trials with binary outcomes. We also suggest that in a stepped wedge design with three steps, at least two clusters be randomised at each step, to ensure that the intervention effect estimator maintains the nominal 5% significance level and is also reasonably unbiased.

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

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

Zhang, Jianbao; Ma, Zhongjun, E-mail: mzj1234402@163.com; Chen, Guanrong

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding ormore » deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.« less

Robustness of cluster synchronous patterns in small-world networks with inter-cluster co-competition balance

NASA Astrophysics Data System (ADS)

Zhang, Jianbao; Ma, Zhongjun; Chen, Guanrong

2014-06-01

All edges in the classical Watts and Strogatz's small-world network model are unweighted and cooperative (positive). By introducing competitive (negative) inter-cluster edges and assigning edge weights to mimic more realistic networks, this paper develops a modified model which possesses co-competitive weighted couplings and cluster structures while maintaining the common small-world network properties of small average shortest path lengths and large clustering coefficients. Based on theoretical analysis, it is proved that the new model with inter-cluster co-competition balance has an important dynamical property of robust cluster synchronous pattern formation. More precisely, clusters will neither merge nor split regardless of adding or deleting nodes and edges, under the condition of inter-cluster co-competition balance. Numerical simulations demonstrate the robustness of the model against the increase of the coupling strength and several topological variations.

Message Passing and Shared Address Space Parallelism on an SMP Cluster

NASA Technical Reports Server (NTRS)

Shan, Hongzhang; Singh, Jaswinder P.; Oliker, Leonid; Biswas, Rupak; Biegel, Bryan (Technical Monitor)

2002-01-01

Currently, message passing (MP) and shared address space (SAS) are the two leading parallel programming paradigms. MP has been standardized with MPI, and is the more common and mature approach; however, code development can be extremely difficult, especially for irregularly structured computations. SAS offers substantial ease of programming, but may suffer from performance limitations due to poor spatial locality and high protocol overhead. In this paper, we compare the performance of and the programming effort required for six applications under both programming models on a 32-processor PC-SMP cluster, a platform that is becoming increasingly attractive for high-end scientific computing. Our application suite consists of codes that typically do not exhibit scalable performance under shared-memory programming due to their high communication-to-computation ratios and/or complex communication patterns. Results indicate that SAS can achieve about half the parallel efficiency of MPI for most of our applications, while being competitive for the others. A hybrid MPI+SAS strategy shows only a small performance advantage over pure MPI in some cases. Finally, improved implementations of two MPI collective operations on PC-SMP clusters are presented.

Carbon nitride supported Fe2 cluster catalysts with superior performance for alkene epoxidation.

PubMed

Tian, Shubo; Fu, Qiang; Chen, Wenxing; Feng, Quanchen; Chen, Zheng; Zhang, Jian; Cheong, Weng-Chon; Yu, Rong; Gu, Lin; Dong, Juncai; Luo, Jun; Chen, Chen; Peng, Qing; Draxl, Claudia; Wang, Dingsheng; Li, Yadong

2018-06-15

Sub-nano metal clusters often exhibit unique and unexpected properties, which make them particularly attractive as catalysts. Herein, we report a "precursor-preselected" wet-chemistry strategy to synthesize highly dispersed Fe 2 clusters that are supported on mesoporous carbon nitride (mpg-C 3 N 4 ). The obtained Fe 2 /mpg-C 3 N 4 sample exhibits superior catalytic performance for the epoxidation of trans-stilbene to trans-stilbene oxide, showing outstanding selectivity of 93% at high conversion of 91%. Molecular oxygen is the only oxidant and no aldehyde is used as co-reagent. Under the same condition, by contrast, iron porphyrin, single-atom Fe, and small Fe nanoparticles (ca. 3 nm) are nearly reactively inert. First-principles calculations reveal that the unique reactivity of the Fe 2 clusters originates from the formation of active oxygen species. The general applicability of the synthesis approach is further demonstrated by producing other diatomic clusters like Pd 2 and Ir 2 , which lays the foundation for discovering diatomic cluster catalysts.

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.

Nano-confinement inside molecular metal oxide clusters: Dynamics and modified encapsulation behavior

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

Wang, Zhe; Daemen, Luke L.; Cheng, Yongqiang

Encapsulation behavior, as well as the presence of internal catalytically-active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132} as an encapsulation host and a nano-reactor. Due to its well-defined and tunable cluster structures, and nano-scaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under ultra-confinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton ofmore » the internal ligands. Furthermore, NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size-selective encapsulation and separation.« less

Nano-confinement inside molecular metal oxide clusters: Dynamics and modified encapsulation behavior

DOE PAGES

Wang, Zhe; Daemen, Luke L.; Cheng, Yongqiang; ...

2016-08-19

Encapsulation behavior, as well as the presence of internal catalytically-active sites, has been spurring the applications of a 3 nm hollow spherical metal oxide cluster {Mo 132} as an encapsulation host and a nano-reactor. Due to its well-defined and tunable cluster structures, and nano-scaled internal void space comparable to the volumes of small molecules, this cluster provides a good model to study the dynamics of materials under ultra-confinement. Neutron scattering studies suggest that bulky internal ligands inside the cluster show slower and limited dynamics compared to their counterparts in the bulk state, revealing the rigid nature of the skeleton ofmore » the internal ligands. Furthermore, NMR studies indicate that the rigid internal ligands that partially cover the interfacial pore on the molybdenum oxide shells are able to block some large guest molecules from going inside the capsule cluster, which provides a convincing protocol for size-selective encapsulation and separation.« less

Lasers '81

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

Collins, C.B.

1982-01-01

Progress in lasers is discussed. The subjects addressed include: excimer lasers, surface spectroscopy, modern laser spectroscopy, free electron lasers, cavities and propagation, lasers in medicine, X-ray and gamma ray lasers, laser spectroscopy of small molecules and clusters, optical bistability, excitons, nonlinear optics in the X-ray and gamma ray regions, collective atomic phenomena, tunable IR lasers, far IR/submillimeter lasers, and laser-assisted collisions. Also treated are: special applications, multiphoton processes in atoms and small molecules, nuclear pumped lasers, material processing and applications, polarization, high energy lasers, laser chemistry, IR molecular lasers, laser applications of collision and dissociation phenomena, solid state laser materials,more » phase conjugation, advances in laser technology for fusion, metal vapor lasers, picosecond phenomena, laser ranging and geodesy, and laser photochemistry of complex molecules.« less

Development of Wien filter for small ion gun of surface analysis

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

Bahng, Jungbae; Busan Center, Korea Basic Science Institute, Busan 609-735; Hong, Jonggi

The gas cluster ion beam (GCIB) and liquid metal ion beam have been studied in the context of ion beam usage for analytical equipment in applications such as X-ray photoelectron spectroscopy and secondary ion mass spectroscopy (SIMS). In particular, small ion sources are used for the secondary ion generation and ion etching. To set the context to this study, the SIMS project has been launched to develop ion-gun based analytical equipment for the Korea Basic Science Institute. The objective of the first stage of the project is the generation of argon beams with a GCIB system [A. Kirkpatrick, Nucl. Instrum.more » Methods Phys. Res., Sect. B 206, 830–837 (2003)] that consists of a nozzle, skimmer, ionizer, acceleration tube, separation system, transport system, and target. The Wien filter directs the selected cluster beam to the target system by exploiting the velocity difference of the generated particles from GCIB. In this paper, we present the theoretical modeling and three-dimensional electromagnetic analysis of the Wien filter, which can separate Ar{sup +}{sub 2500} clusters from Ar{sup +}{sub 2400} to Ar{sup +}{sub 2600} clusters with a 1-mm collimator.« less

A class of spherical, truncated, anisotropic models for application to globular clusters

NASA Astrophysics Data System (ADS)

de Vita, Ruggero; Bertin, Giuseppe; Zocchi, Alice

2016-05-01

Recently, a class of non-truncated, radially anisotropic models (the so-called f(ν)-models), originally constructed in the context of violent relaxation and modelling of elliptical galaxies, has been found to possess interesting qualities in relation to observed and simulated globular clusters. In view of new applications to globular clusters, we improve this class of models along two directions. To make them more suitable for the description of small stellar systems hosted by galaxies, we introduce a "tidal" truncation by means of a procedure that guarantees full continuity of the distribution function. The new fT(ν)-models are shown to provide a better fit to the observed photometric and spectroscopic profiles for a sample of 13 globular clusters studied earlier by means of non-truncated models; interestingly, the best-fit models also perform better with respect to the radial-orbit instability. Then, we design a flexible but simple two-component family of truncated models to study the separate issues of mass segregation and multiple populations. We do not aim at a fully realistic description of globular clusters to compete with the description currently obtained by means of dedicated simulations. The goal here is to try to identify the simplest models, that is, those with the smallest number of free parameters, but still have the capacity to provide a reasonable description for clusters that are evidently beyond the reach of one-component models. With this tool, we aim at identifying the key factors that characterize mass segregation or the presence of multiple populations. To reduce the relevant parameter space, we formulate a few physical arguments based on recent observations and simulations. A first application to two well-studied globular clusters is briefly described and discussed.

GibbsCluster: unsupervised clustering and alignment of peptide sequences.

PubMed

Andreatta, Massimo; Alvarez, Bruno; Nielsen, Morten

2017-07-03

Receptor interactions with short linear peptide fragments (ligands) are at the base of many biological signaling processes. Conserved and information-rich amino acid patterns, commonly called sequence motifs, shape and regulate these interactions. Because of the properties of a receptor-ligand system or of the assay used to interrogate it, experimental data often contain multiple sequence motifs. GibbsCluster is a powerful tool for unsupervised motif discovery because it can simultaneously cluster and align peptide data. The GibbsCluster 2.0 presented here is an improved version incorporating insertion and deletions accounting for variations in motif length in the peptide input. In basic terms, the program takes as input a set of peptide sequences and clusters them into meaningful groups. It returns the optimal number of clusters it identified, together with the sequence alignment and sequence motif characterizing each cluster. Several parameters are available to customize cluster analysis, including adjustable penalties for small clusters and overlapping groups and a trash cluster to remove outliers. As an example application, we used the server to deconvolute multiple specificities in large-scale peptidome data generated by mass spectrometry. The server is available at http://www.cbs.dtu.dk/services/GibbsCluster-2.0. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Small-scale characterisation of irradiated nuclear materials: Part I – Microstructure

DOE PAGES

Edmondson, P. D.; London, A.; Xu, A.; ...

2014-11-26

The behaviour of nanometre-scale precipitates in oxide dispersion strengthened (ODS) ferritic alloys and tungsten-rhenium alloys for nuclear applications has been examined by atom probe tomography (APT). Low Re content tungsten alloys showed no evidence of Re clustering following self-ion irradiation whereas the 25 at.% Re resulted in cluster formation. The size and composition of clusters varied depending on the material form during irradiation (pre-sharpened needle or bulk). Lastly, these results highlight the care that must be taken in interpreting data from ion irradiated pre-sharpened needles due to the presence of free surfaces. Self-ion irradiation of the ODS ferritic alloy resultedmore » in a change in the composition of the clusters, indicating a transition from a near-stoichiometric Y 2Ti 2O 7 composition towards a Ti 2YO 5.« less

Unexpected Toxicity of Monolayer Protected Gold Clusters Eliminated by PEG-Thiol Place Exchange Reactions

PubMed Central

Simpson, Carrie A.; Huffman, Brian J.; Gerdon, Aren E.; Cliffel, David E.

2010-01-01

Monolayer protected clusters (MPCs) are small, metal nanoparticles capped with thiolate ligands that have been widely studied for their size-dependent properties and for their ability to be functionalized for biological applications. Common water-soluble MPCs, functionalized by 2-mercaptopropanoyl) amino acetic acid (tiopronin) or glutathione, have been used previously to interface with biological systems. These MPCs are ideal for biological applications not only due to their water-solubility but also their small size (< 5 nm). These characteristics are expected to enable easy biodistribution and clearance. In this report we show an unexpected toxicity is associated with the tiopronin monolayer protected cluster (TMPC), making it incompatible for potential in vivo applications. This toxicity is linked to significant histological damage to the renal tubules, causing mortality at concentrations above 20 μM. We further show how the incorporation of poly-ethylene glycol (PEG) by simple place-exchange reaction eliminates this toxicity. We analyzed gold content within blood and urine and found an increased lifetime of the particle within the bloodstream due to the creation of the mixed monolayer. Also shown was the elimination of kidney damage with the use of the mixed-monolayer particle via Multistix™ analysis, MALDI-TOF MS analysis, and histological examination. Final immunological analysis showed no effect on white blood cell (WBC) count for the unmodified particle and a surprising increase in WBC count with injection of mixed monolayer particles at concentrations higher than 30 μM, suggesting that there may be an immune response to these mixed monolayer nanoparticles at high concentrations; therefore, special attention should be focused on selecting the best capping ligands for use in vivo. These findings make the mixed monolayer an excellent candidate for further biological applications using water-soluble nanoparticles. PMID:20715858

Active galactic nuclei. III - Accretion flow in an externally supplied cluster of black holes

NASA Technical Reports Server (NTRS)

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

1989-01-01

This third paper in the series modeling QSOs and AGNs as clusters of accreting black holes studies the accretion flow within an externally supplied cluster. Significant radiation will be emitted by the cluster core, but the black holes in the outer halo, where the flow is considered spherically symmetric, will not contribute much to the overall luminosity of the source because of their large velocities relative to the infalling gas and therefore their small accretion radii. As a result, the scenario discussed in Paper I will refer to the cluster cores, rather than to entire clusters. This will steepen the high-frequency region of the spectrum unless inverse Compton scattering is effective. In many cases accretion flow in the central part of the cluster will be optically thick to electron scattering, resulting in a spectrum featuring optically thick radiative component in addition to power-law regimes. The fitting of these spectra to QSO and AGN observations is discussed, and application to 3C 273 is worked out as an example.

Value-based customer grouping from large retail data sets

NASA Astrophysics Data System (ADS)

Strehl, Alexander; Ghosh, Joydeep

2000-04-01

In this paper, we propose OPOSSUM, a novel similarity-based clustering algorithm using constrained, weighted graph- partitioning. Instead of binary presence or absence of products in a market-basket, we use an extended 'revenue per product' measure to better account for management objectives. Typically the number of clusters desired in a database marketing application is only in the teens or less. OPOSSUM proceeds top-down, which is more efficient and takes a small number of steps to attain the desired number of clusters as compared to bottom-up agglomerative clustering approaches. OPOSSUM delivers clusters that are balanced in terms of either customers (samples) or revenue (value). To facilitate data exploration and validation of results we introduce CLUSION, a visualization toolkit for high-dimensional clustering problems. To enable closed loop deployment of the algorithm, OPOSSUM has no user-specified parameters. Thresholding heuristics are avoided and the optimal number of clusters is automatically determined by a search for maximum performance. Results are presented on a real retail industry data-set of several thousand customers and products, to demonstrate the power of the proposed technique.

A comparison of methods for the analysis of binomial clustered outcomes in behavioral research.

PubMed

Ferrari, Alberto; Comelli, Mario

2016-12-01

In behavioral research, data consisting of a per-subject proportion of "successes" and "failures" over a finite number of trials often arise. This clustered binary data are usually non-normally distributed, which can distort inference if the usual general linear model is applied and sample size is small. A number of more advanced methods is available, but they are often technically challenging and a comparative assessment of their performances in behavioral setups has not been performed. We studied the performances of some methods applicable to the analysis of proportions; namely linear regression, Poisson regression, beta-binomial regression and Generalized Linear Mixed Models (GLMMs). We report on a simulation study evaluating power and Type I error rate of these models in hypothetical scenarios met by behavioral researchers; plus, we describe results from the application of these methods on data from real experiments. Our results show that, while GLMMs are powerful instruments for the analysis of clustered binary outcomes, beta-binomial regression can outperform them in a range of scenarios. Linear regression gave results consistent with the nominal level of significance, but was overall less powerful. Poisson regression, instead, mostly led to anticonservative inference. GLMMs and beta-binomial regression are generally more powerful than linear regression; yet linear regression is robust to model misspecification in some conditions, whereas Poisson regression suffers heavily from violations of the assumptions when used to model proportion data. We conclude providing directions to behavioral scientists dealing with clustered binary data and small sample sizes. Copyright © 2016 Elsevier B.V. All rights reserved.

Dynamic behaviour of nanometre-sized defect clusters emitted from an atomic displacement cascade in Au at 50 K

NASA Astrophysics Data System (ADS)

Ono, K.; Miyamoto, M.; Arakawa, K.; Birtcher, R. C.

2017-09-01

We demonstrate the emission of nanometre-sized defect clusters from an isolated displacement cascade formed by irradiation of high-energy self-ions and their subsequent 1-D motion in Au at 50 K, using in situ electron microscopy. The small defect clusters emitted from a displacement cascade exhibited correlated back-and-forth 1-D motion along the [-1 1 0] direction and coalescence which results in their growth and reduction of their mobility. From the analysis of the random 1-D motion, the diffusivity of the small cluster was evaluated. Correlated 1-D motion and coalescence of clusters were understood via elastic interaction between small clusters. These results provide direct experimental evidence of the migration of small defect clusters and defect cascade evolution at low temperature.

Lipid-Mediated Clusters of Guest Molecules in Model Membranes and Their Dissolving in the Presence of Lipid Rafts.

PubMed

Kardash, Maria E; Dzuba, Sergei A

2017-05-25

The clustering of molecules is an important feature of plasma membrane organization. It is challenging to develop methods for quantifying membrane heterogeneities because of their transient nature and small size. Here, we obtained evidence that transient membrane heterogeneities can be frozen at cryogenic temperatures which allows the application of solid-state experimental techniques sensitive to the nanoscale distance range. We employed the pulsed version of electron paramagnetic resonance (EPR) spectroscopy, the electron spin echo (ESE) technique, for spin-labeled molecules in multilamellar lipid bilayers. ESE decays were refined for pure contribution of spin-spin magnetic dipole-dipolar interaction between the labels; these interactions manifest themselves at a nanometer distance range. The bilayers were prepared from different types of saturated and unsaturated lipids and cholesterol (Chol); in all cases, a small amount of guest spin-labeled substances 5-doxyl-stearic-acid (5-DSA) or 3β-doxyl-5α-cholestane (DChl) was added. The local concentration found of 5-DSA and DChl molecules was remarkably higher than the mean concentration in the bilayer, evidencing the formation of lipid-mediated clusters of these molecules. To our knowledge, formation of nanoscale clusters of guest amphiphilic molecules in biological membranes is a new phenomenon suggested only recently. Two-dimensional 5-DSA molecular clusters were found, whereas flat DChl molecules were found to be clustered into stacked one-dimensional structures. These clusters disappear when the Chol content is varied between the boundaries known for lipid raft formation at room temperatures. The room temperature EPR evidenced entrapping of DChl molecules in the rafts.

Unscrambling the Omlette: a New Bubble and Crystal Clustering Mechanism in Chaotically Mixed Magma Flows

NASA Astrophysics Data System (ADS)

Robertson, J.; Metcalfe, G.; Wang, S.; Barnes, S. J.

2014-12-01

The concentration of bubbles, crystals or droplets into small volumes of magma is a key trigger for many interesting magmatic processes. For example, gas slugs driving Strombolian eruptions form from the coalesence of exsolved bubbles within a volcanic conduit, while Ni-Cu-PGE magmatic sulfide deposits require a concentration of dense sulfide droplets from a large volume of magma to form a massive ore body. However the physical mechanism for this clustering remains unresolved - especially since small particles in active magma flows are expected to mostly track flow streamlines rather than clustering. We have uncovered a previously unreported clustering mechanism which is applicable to magmatic flows. This mechanism involves the interaction of particles with two kinds of chaotic flow structure: (a) high-strain regions within the well-mixed chaotic zones of the flow, and (b) unmixed islands of stability within the chaotic flow, known as Kolmogorov-Arnold-Moser (KAM) regions. The first figure shows the difference between chaotic and KAM regions in a chaotic laminar pipe flow. Trapping occurs when particles are scattered from high-strain regions in the chaotic zones and become trapped in the KAM regions, leading to a rapid concentration of particles relative to their original distribution (shown in the second series of figures). Using a combination of these analogue experiments and theoretical analysis we outline the conditions under which this clustering process can occur. We examine the onset of secondary density-related instabilities and the effects of increased particle-particle interaction within the clustered particles, and highlight the impact of particle clustering on the dynamics of magma ascent and emplacement.

Interaction of intense ultrashort pulse lasers with clusters.

NASA Astrophysics Data System (ADS)

Petrov, George

2007-11-01

The last ten years have witnessed an explosion of activity involving the interaction of clusters with intense ultrashort pulse lasers. Atomic or molecular clusters are targets with unique properties, as they are halfway between solid and gases. The intense laser radiation creates hot dense plasma, which can provide a compact source of x-rays and energetic particles. The focus of this investigation is to understand the salient features of energy absorption and Coulomb explosion by clusters. The evolution of clusters is modeled with a relativistic time-dependent 3D Molecular Dynamics (MD) model [1]. The Coulomb interaction between particles is handled by a fast tree algorithm, which allows large number of particles to be used in simulations [2]. The time histories of all particles in a cluster are followed in time and space. The model accounts for ionization-ignition effects (enhancement of the laser field in the vicinity of ions) and a variety of elementary processes for free electrons and charged ions, such as optical field and collisional ionization, outer ionization and electron recapture. The MD model was applied to study small clusters (1-20 nm) irradiated by a high-intensity (10^16-10^20 W/cm^2) sub-picosecond laser pulse. We studied fundamental cluster features such as energy absorption, x-ray emission, particle distribution, average charge per atom, and cluster explosion as a function of initial cluster radius, laser peak intensity and wavelength. Simulations of novel applications, such as table-top nuclear fusion from exploding deuterium clusters [3] and high power synchrotron radiation for biological applications and imaging [4] have been performed. The application for nuclear fusion was motivated by the efficient absorption of laser energy (˜100%) and its high conversion efficiency into ion kinetic energy (˜50%), resulting in neutron yield of 10^6 neutrons/Joule laser energy. Contributors: J. Davis and A. L. Velikovich. [1] G. M. Petrov, et al Phys. Plasmas 12 063103 (2005); 13 033106 (2006) [2] G. M. Petrov, J. Davis, European Phys. J. D 41 629 (2007) [3] G. M. Petrov, J. Davis, A. L. Velikovich, Plasma Phys. Contr. Fusion 48 1721 (2006) [4] G. M. Petrov, J. Davis, A. L. Velikovich, J. Phys. B 39 4617 (2006)

Silver enhancement of nanogold and undecagold

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

Hainfield, J.F.; Furuya, F.R.

1995-07-01

A recent advance in immunogold technology has been the use of molecular gold instead of colloidal gold. A number of advantages are realized by this approach, such as stable covalent, site-specific attachment, small probe size and absence of aggregates for improved penetration. Silver enhancement has led to improved and unique results for electron and light microscopy, as well as their use with blots and gels. Most previous work with immunogold silver staining has been done with colloidal gold particles. More recently, large gold compounds (``clusters``) having a definite number of gold atoms and defined organic shell, have been used, frequentlymore » with improved results. These gold dusters, large compared to simple compounds, are, however, at the small end of the colloidal gold scale in size; undecagold is 0.8 nm and Nanogold is 1.4 nm. They may be used in practically all applications where colloidal gold is used (Light and electron microscopy, dot blots, etc.) and in some unique applications, where at least the larger colloidal golds don`t work, such as running gold labeled proteins on gels (which are later detected by silver enhancement). The main differences between gold clusters and colloidal golds are the small size of the dusters and their covalent attachment to antibodies or other molecules.« less

Graphics Processing Unit (GPU) Acceleration of the Goddard Earth Observing System Atmospheric Model

NASA Technical Reports Server (NTRS)

Putnam, Williama

2011-01-01

The Goddard Earth Observing System 5 (GEOS-5) is the atmospheric model used by the Global Modeling and Assimilation Office (GMAO) for a variety of applications, from long-term climate prediction at relatively coarse resolution, to data assimilation and numerical weather prediction, to very high-resolution cloud-resolving simulations. GEOS-5 is being ported to a graphics processing unit (GPU) cluster at the NASA Center for Climate Simulation (NCCS). By utilizing GPU co-processor technology, we expect to increase the throughput of GEOS-5 by at least an order of magnitude, and accelerate the process of scientific exploration across all scales of global modeling, including: The large-scale, high-end application of non-hydrostatic, global, cloud-resolving modeling at 10- to I-kilometer (km) global resolutions Intermediate-resolution seasonal climate and weather prediction at 50- to 25-km on small clusters of GPUs Long-range, coarse-resolution climate modeling, enabled on a small box of GPUs for the individual researcher After being ported to the GPU cluster, the primary physics components and the dynamical core of GEOS-5 have demonstrated a potential speedup of 15-40 times over conventional processor cores. Performance improvements of this magnitude reduce the required scalability of 1-km, global, cloud-resolving models from an unfathomable 6 million cores to an attainable 200,000 GPU-enabled cores.

Local induction of acetylcholine receptor clustering in myotube cultures using microfluidic application of agrin.

PubMed

Tourovskaia, Anna; Kosar, T Fettah; Folch, Albert

2006-03-15

During neuromuscular synaptogenesis, the exchange of spatially localized signals between nerve and muscle initiates the coordinated focal accumulation of the acetylcholine (ACh) release machinery and the ACh receptors (AChRs). One of the key first steps is the release of the proteoglycan agrin focalized at the axon tip, which induces the clustering of AChRs on the postsynaptic membrane at the neuromuscular junction. The lack of a suitable method for focal application of agrin in myotube cultures has limited the majority of in vitro studies to the application of agrin baths. We used a microfluidic device and surface microengineering to focally stimulate muscle cells with agrin at a small portion of their membrane and at a time and position chosen by the user. The device is used to verify the hypothesis that focal application of agrin to the muscle cell membrane induces local aggregation of AChRs in differentiated C2C12 myotubes.

Analytical network process based optimum cluster head selection in wireless sensor network.

PubMed

Farman, Haleem; Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.

Analytical network process based optimum cluster head selection in wireless sensor network

PubMed Central

Javed, Huma; Jan, Bilal; Ahmad, Jamil; Ali, Shaukat; Khalil, Falak Naz; Khan, Murad

2017-01-01

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process. PMID:28719616

The Distance to the Coma Cluster from the Tully--Fisher Relation

NASA Astrophysics Data System (ADS)

Herter, T.; Vogt, N. P.; Haynes, M. P.; Giovanelli, R.

1993-12-01

As part of a survey to determine the distances to nearby (z < .04) Abell clusters via application of the Tully--Fisher (TF) relation, we have obtained 21 cm HI line widths, optical rotation curves and photometric I--band CCD images of galaxies within and near the Coma cluster. Because spiral galaxies within the cluster itself are HI deficient and thus are detected marginally or not at all in HI, distance determinations using only the radio TF relation exclude true cluster members. Our sample includes eight HI deficient galaxies within 1.5 degrees of the cluster center, for which optical velocity widths are derived from their Hα and [NII] rotation curves. The 21 cm line widths have been extracted using a new algorithm designed to optimize the measurement for TF applications, taking into account the effects of spectral resolution and smoothing. The optical width is constructed from the velocity histogram, and is therefore a global value akin to the HI width. A correction for turbulent broadening of the HI is derived from comparison of the optical and HI widths. Using a combined sample of 260 galaxies in 11 clusters and an additional 30 field objects at comparable distances, we have performed a calibration of the radio and optical analogs of the TF relation. Preliminary results show a clear linear relationship with a small offset between optical and radio widths, and good agreement in deriving Tully--Fisher distances to clusters. Our Coma sample consists of 28 galaxies with optical widths and 42 with HI line widths, with an overlapping set of 20 galaxies. We will present the data on the Coma cluster, and discuss the results of our analysis.

Electronic structure, stability and magnetic properties of small M1-4(M = Fe, Co, Ni) clusters encapsulated inside a (BN)48 cage

NASA Astrophysics Data System (ADS)

Liang, Wenjuan; Jia, Jianfeng; Lv, Jin; Wu, Haishun

2015-02-01

The geometrical structure and magnetic properties of M1-4(M = Fe, Co and Ni) clusters within a (BN)48 cage were calculated at the BPW91/LanL2DZ level. The small M1-4 clusters generally prefer an off-centered position near the hexagonal rings in the (BN)48 cages. The (BN)48 cages can increase the stability of these small magnetic clusters while protecting the magnetic nature of M and M2 clusters.

Applications of colored petri net and genetic algorithms to cluster tool scheduling

NASA Astrophysics Data System (ADS)

Liu, Tung-Kuan; Kuo, Chih-Jen; Hsiao, Yung-Chin; Tsai, Jinn-Tsong; Chou, Jyh-Horng

2005-12-01

In this paper, we propose a method, which uses Coloured Petri Net (CPN) and genetic algorithm (GA) to obtain an optimal deadlock-free schedule and to solve re-entrant problem for the flexible process of the cluster tool. The process of the cluster tool for producing a wafer usually can be classified into three types: 1) sequential process, 2) parallel process, and 3) sequential parallel process. But these processes are not economical enough to produce a variety of wafers in small volume. Therefore, this paper will propose the flexible process where the operations of fabricating wafers are randomly arranged to achieve the best utilization of the cluster tool. However, the flexible process may have deadlock and re-entrant problems which can be detected by CPN. On the other hand, GAs have been applied to find the optimal schedule for many types of manufacturing processes. Therefore, we successfully integrate CPN and GAs to obtain an optimal schedule with the deadlock and re-entrant problems for the flexible process of the cluster tool.

Application of artificial intelligence to search ground-state geometry of clusters

NASA Astrophysics Data System (ADS)

Lemes, Maurício Ruv; Marim, L. R.; dal Pino, A.

2002-08-01

We introduce a global optimization procedure, the neural-assisted genetic algorithm (NAGA). It combines the power of an artificial neural network (ANN) with the versatility of the genetic algorithm. This method is suitable to solve optimization problems that depend on some kind of heuristics to limit the search space. If a reasonable amount of data is available, the ANN can ``understand'' the problem and provide the genetic algorithm with a selected population of elements that will speed up the search for the optimum solution. We tested the method in a search for the ground-state geometry of silicon clusters. We trained the ANN with information about the geometry and energetics of small silicon clusters. Next, the ANN learned how to restrict the configurational space for larger silicon clusters. For Si10 and Si20, we noticed that the NAGA is at least three times faster than the ``pure'' genetic algorithm. As the size of the cluster increases, it is expected that the gain in terms of time will increase as well.

Communication. Kinetics of scavenging of small, nucleating clusters. First nucleation theorem and sum rules

DOE PAGES

Malila, Jussi; McGraw, Robert; Laaksonen, Ari; ...

2015-01-07

Despite recent advances in monitoring nucleation from a vapor at close-to-molecular resolution, the identity of the critical cluster, forming the bottleneck for the nucleation process, remains elusive. During past twenty years, the first nucleation theorem has been often used to extract the size of the critical cluster from nucleation rate measurements. However, derivations of the first nucleation theorem invoke certain questionable assumptions that may fail, e.g., in the case of atmospheric new particle formation, including absence of subcritical cluster losses and heterogeneous nucleation on pre-existing nanoparticles. Here we extend the kinetic derivation of the first nucleation theorem to give amore » general framework to include such processes, yielding sum rules connecting the size dependent particle formation and loss rates to the corresponding loss-free nucleation rate and the apparent critical size from a naïve application of the first nucleation theorem that neglects them.« less

Clustering Coefficients for Correlation Networks.

PubMed

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties.

Clustering Coefficients for Correlation Networks

PubMed Central

Masuda, Naoki; Sakaki, Michiko; Ezaki, Takahiro; Watanabe, Takamitsu

2018-01-01

Graph theory is a useful tool for deciphering structural and functional networks of the brain on various spatial and temporal scales. The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in the assessment of small-worldness of brain networks, which is affected by attentional and cognitive conditions, age, psychiatric disorders and so forth. However, it remains unclear how the clustering coefficient should be measured in a correlation-based network, which is among major representations of brain networks. In the present article, we propose clustering coefficients tailored to correlation matrices. The key idea is to use three-way partial correlation or partial mutual information to measure the strength of the association between the two neighboring nodes of a focal node relative to the amount of pseudo-correlation expected from indirect paths between the nodes. Our method avoids the difficulties of previous applications of clustering coefficient (and other) measures in defining correlational networks, i.e., thresholding on the correlation value, discarding of negative correlation values, the pseudo-correlation problem and full partial correlation matrices whose estimation is computationally difficult. For proof of concept, we apply the proposed clustering coefficient measures to functional magnetic resonance imaging data obtained from healthy participants of various ages and compare them with conventional clustering coefficients. We show that the clustering coefficients decline with the age. The proposed clustering coefficients are more strongly correlated with age than the conventional ones are. We also show that the local variants of the proposed clustering coefficients (i.e., abundance of triangles around a focal node) are useful in characterizing individual nodes. In contrast, the conventional local clustering coefficients were strongly correlated with and therefore may be confounded by the node's connectivity. The proposed methods are expected to help us to understand clustering and lack thereof in correlational brain networks, such as those derived from functional time series and across-participant correlation in neuroanatomical properties. PMID:29599714

Propensity score matching with clustered data. An application to the estimation of the impact of caesarean section on the Apgar score.

PubMed

Arpino, Bruno; Cannas, Massimo

2016-05-30

This article focuses on the implementation of propensity score matching for clustered data. Different approaches to reduce bias due to cluster-level confounders are considered and compared using Monte Carlo simulations. We investigated methods that exploit the clustered structure of the data in two ways: in the estimation of the propensity score model (through the inclusion of fixed or random effects) or in the implementation of the matching algorithm. In addition to a pure within-cluster matching, we also assessed the performance of a new approach, 'preferential' within-cluster matching. This approach first searches for control units to be matched to treated units within the same cluster. If matching is not possible within-cluster, then the algorithm searches in other clusters. All considered approaches successfully reduced the bias due to the omission of a cluster-level confounder. The preferential within-cluster matching approach, combining the advantages of within-cluster and between-cluster matching, showed a relatively good performance both in the presence of big and small clusters, and it was often the best method. An important advantage of this approach is that it reduces the number of unmatched units as compared with a pure within-cluster matching. We applied these methods to the estimation of the effect of caesarean section on the Apgar score using birth register data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Incipient fault detection study for advanced spacecraft systems

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Black, Michael C.; Hovenga, J. Mike; Mcclure, Paul F.

1986-01-01

A feasibility study to investigate the application of vibration monitoring to the rotating machinery of planned NASA advanced spacecraft components is described. Factors investigated include: (1) special problems associated with small, high RPM machines; (2) application across multiple component types; (3) microgravity; (4) multiple fault types; (5) eight different analysis techniques including signature analysis, high frequency demodulation, cepstrum, clustering, amplitude analysis, and pattern recognition are compared; and (6) small sample statistical analysis is used to compare performance by computation of probability of detection and false alarm for an ensemble of repeated baseline and faulted tests. Both detection and classification performance are quantified. Vibration monitoring is shown to be an effective means of detecting the most important problem types for small, high RPM fans and pumps typical of those planned for the advanced spacecraft. A preliminary monitoring system design and implementation plan is presented.

Small-scale Conformity of the Virgo Cluster Galaxies

NASA Astrophysics Data System (ADS)

Lee, Hye-Ran; Lee, Joon Hyeop; Jeong, Hyunjin; Park, Byeong-Gon

2016-06-01

We investigate the small-scale conformity in color between bright galaxies and their faint companions in the Virgo Cluster. Cluster member galaxies are spectroscopically determined using the Extended Virgo Cluster Catalog and the Sloan Digital Sky Survey Data Release 12. We find that the luminosity-weighted mean color of faint galaxies depends on the color of adjacent bright galaxy as well as on the cluster-scale environment (gravitational potential index). From this result for the entire area of the Virgo Cluster, it is not distinguishable whether the small-scale conformity is genuine or if it is artificially produced due to cluster-scale variation of galaxy color. To disentangle this degeneracy, we divide the Virgo Cluster area into three sub-areas so that the cluster-scale environmental dependence is minimized: A1 (central), A2 (intermediate), and A3 (outermost). We find conformity in color between bright galaxies and their faint companions (color-color slope significance S ˜ 2.73σ and correlation coefficient {cc}˜ 0.50) in A2, where the cluster-scale environmental dependence is almost negligible. On the other hand, the conformity is not significant or very marginal (S ˜ 1.75σ and {cc}˜ 0.27) in A1. The conformity is not significant either in A3 (S ˜ 1.59σ and {cc}˜ 0.44), but the sample size is too small in this area. These results are consistent with a scenario in which the small-scale conformity in a cluster is a vestige of infallen groups and these groups lose conformity as they come closer to the cluster center.

Testing the Archivas Cluster (Arc) for Ozone Monitoring Instrument (OMI) Scientific Data Storage

NASA Technical Reports Server (NTRS)

Tilmes, Curt

2005-01-01

The Ozone Monitoring Instrument (OMI) launched on NASA's Aura Spacecraft, the third of the major platforms of the EOS program on July 15,2004. In addition to the long term archive and distribution of the data from OM1 through the Goddard Earth Science Distributed Active Archive Center (GESDAAC), we are evaluating other archive mechanisms that can archive the data in a more immediately available method where it can be used for futher data production and analysis. In 2004, Archivas, Inc. was selected by NASA s Small Business Innovative Research (SBIR) program for the development of their Archivas Cluster (ArC) product. Arc is an online disk based system utilizing self-management and automation on a Linux cluster. Its goal is to produce a low cost solution coupled with the ease of management. The OM1 project is an application partner of the SBIR program, and has deployed a small cluster (5TB) based on the beta Archwas software. We performed extensive testing of the unit using production OM1 data since launch. In 2005, Archivas, Inc. was funded in SBIR Phase II for further development, which will include testing scalability with the deployment of a larger (35TB) cluster at Goddard. We plan to include Arc in the OM1 Team Leader Computing Facility (TLCF) hosting OM1 data for direct access and analysis by the OMI Science Team. This presentation will include a brief technical description of the Archivas Cluster, a summary of the SBIR Phase I beta testing results, and an overview of the OMI ground data processing architecture including its interaction with the Phase II Archivas Cluster and hosting of OMI data for the scientists.

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.

The 2013 Clusters, Nanocrystals & Nanostructures Gordon Research Conference/Gordon Research Seminar

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

Krauss, Todd D.

The fundamental properties of small particles and their potential for groundbreaking applications are among the most exciting areas of study in modern physics, chemistry, and materials science. The Clusters, Nanocrystals & Nanostructures Gordon ResearchConference and Gordon Research Seminar synthesize contributions from these inter-related fields that reflect the pivotal role of nano-particles at the interface between these disciplines. Size-dependent optical, electronic, magnetic and catalytic properties offer prospects for applications in many fields, and possible solutions for many of the grand challenges facing energy generation, consumption, delivery, and storage in the 21st century. The goal of the 2013 Clusters, Nanocrystals & Nanostructuresmore » Gordon Research Conference and Gordon Research Seminar is to continue the historical interdisciplinary tradition of this series and discuss the most recent advances, basic scientific questions, and emerging applications of clusters, nanocrystals, and nanostructures. The Clusters, Nanocrystals & Nanostructures GRC/GRS traditionally brings together the leading scientific groups that have made significant recent advances in one or more fundamental nanoscience or nanotechnology areas. Broad interests of the DOE BES and Solar Photochemistry Program addressed by this meeting include the areas of solar energy to fuels conversion, new photovoltaic systems, fundamental characterization of nanomaterials, magnetism, catalysis, and quantum physics. The vast majority of speakers and attendees will address either directly the topic of nanotechnology for photoinduced charge transfer, charge transport, and catalysis, or will have made significant contributions to related areas that will impact these fields indirectly. These topics have direct relevance to the mission of the DOE BES since it is this cutting-edge basic science that underpins our energy future.« less

A strategy of gene overexpression based on tandem repetitive promoters in Escherichia coli.

PubMed

Li, Mingji; Wang, Junshu; Geng, Yanping; Li, Yikui; Wang, Qian; Liang, Quanfeng; Qi, Qingsheng

2012-02-06

For metabolic engineering, many rate-limiting steps may exist in the pathways of accumulating the target metabolites. Increasing copy number of the desired genes in these pathways is a general method to solve the problem, for example, the employment of the multi-copy plasmid-based expression system. However, this method may bring genetic instability, structural instability and metabolic burden to the host, while integrating of the desired gene into the chromosome may cause inadequate transcription or expression. In this study, we developed a strategy for obtaining gene overexpression by engineering promoter clusters consisted of multiple core-tac-promoters (MCPtacs) in tandem. Through a uniquely designed in vitro assembling process, a series of promoter clusters were constructed. The transcription strength of these promoter clusters showed a stepwise enhancement with the increase of tandem repeats number until it reached the critical value of five. Application of the MCPtacs promoter clusters in polyhydroxybutyrate (PHB) production proved that it was efficient. Integration of the phaCAB genes with the 5CPtacs promoter cluster resulted in an engineered E.coli that can accumulate 23.7% PHB of the cell dry weight in batch cultivation. The transcription strength of the MCPtacs promoter cluster can be greatly improved by increasing the tandem repeats number of the core-tac-promoter. By integrating the desired gene together with the MCPtacs promoter cluster into the chromosome of E. coli, we can achieve high and stale overexpression with only a small size. This strategy has an application potential in many fields and can be extended to other bacteria.

Chassis optimization as a cornerstone for the application of synthetic biology based strategies in microbial secondary metabolism.

PubMed

Beites, Tiago; Mendes, Marta V

2015-01-01

The increased number of bacterial genome sequencing projects has generated over the last years a large reservoir of genomic information. In silico analysis of this genomic data has renewed the interest in bacterial bioprospecting for bioactive compounds by unveiling novel biosynthetic gene clusters of unknown or uncharacterized metabolites. However, only a small fraction of those metabolites is produced under laboratory-controlled conditions; the remaining clusters represent a pool of novel metabolites that are waiting to be "awaken". Activation of the biosynthetic gene clusters that present reduced or no expression (known as cryptic or silent clusters) by heterologous expression has emerged as a strategy for the identification and production of novel bioactive molecules. Synthetic biology, with engineering principles at its core, provides an excellent framework for the development of efficient heterologous systems for the expression of biosynthetic gene clusters. However, a common problem in its application is the host-interference problem, i.e., the unpredictable interactions between the device and the host that can hamper the desired output. Although an effort has been made to develop orthogonal devices, the most proficient way to overcome the host-interference problem is through genome simplification. In this review we present an overview on the strategies and tools used in the development of hosts/chassis for the heterologous expression of specialized metabolites biosynthetic gene clusters. Finally, we introduce the concept of specialized host as the next step of development of expression hosts.

Optimization of self-interstitial clusters in 3C-SiC with genetic algorithm

NASA Astrophysics Data System (ADS)

Ko, Hyunseok; Kaczmarowski, Amy; Szlufarska, Izabela; Morgan, Dane

2017-08-01

Under irradiation, SiC develops damage commonly referred to as black spot defects, which are speculated to be self-interstitial atom clusters. To understand the evolution of these defect clusters and their impacts (e.g., through radiation induced swelling) on the performance of SiC in nuclear applications, it is important to identify the cluster composition, structure, and shape. In this work the genetic algorithm code StructOpt was utilized to identify groundstate cluster structures in 3C-SiC. The genetic algorithm was used to explore clusters of up to ∼30 interstitials of C-only, Si-only, and Si-C mixtures embedded in the SiC lattice. We performed the structure search using Hamiltonians from both density functional theory and empirical potentials. The thermodynamic stability of clusters was investigated in terms of their composition (with a focus on Si-only, C-only, and stoichiometric) and shape (spherical vs. planar), as a function of the cluster size (n). Our results suggest that large Si-only clusters are likely unstable, and clusters are predominantly C-only for n ≤ 10 and stoichiometric for n > 10. The results imply that there is an evolution of the shape of the most stable clusters, where small clusters are stable in more spherical geometries while larger clusters are stable in more planar configurations. We also provide an estimated energy vs. size relationship, E(n), for use in future analysis.

A proximity-based graph clustering method for the identification and application of transcription factor clusters.

PubMed

Spadafore, Maxwell; Najarian, Kayvan; Boyle, Alan P

2017-11-29

Transcription factors (TFs) form a complex regulatory network within the cell that is crucial to cell functioning and human health. While methods to establish where a TF binds to DNA are well established, these methods provide no information describing how TFs interact with one another when they do bind. TFs tend to bind the genome in clusters, and current methods to identify these clusters are either limited in scope, unable to detect relationships beyond motif similarity, or not applied to TF-TF interactions. Here, we present a proximity-based graph clustering approach to identify TF clusters using either ChIP-seq or motif search data. We use TF co-occurrence to construct a filtered, normalized adjacency matrix and use the Markov Clustering Algorithm to partition the graph while maintaining TF-cluster and cluster-cluster interactions. We then apply our graph structure beyond clustering, using it to increase the accuracy of motif-based TFBS searching for an example TF. We show that our method produces small, manageable clusters that encapsulate many known, experimentally validated transcription factor interactions and that our method is capable of capturing interactions that motif similarity methods might miss. Our graph structure is able to significantly increase the accuracy of motif TFBS searching, demonstrating that the TF-TF connections within the graph correlate with biological TF-TF interactions. The interactions identified by our method correspond to biological reality and allow for fast exploration of TF clustering and regulatory dynamics.

Systematic design of active spaces for multi-reference calculations of singlet-triplet gaps of organic diradicals, with benchmarks against doubly electron-attached coupled-cluster data

NASA Astrophysics Data System (ADS)

Stoneburner, Samuel J.; Shen, Jun; Ajala, Adeayo O.; Piecuch, Piotr; Truhlar, Donald G.; Gagliardi, Laura

2017-10-01

Singlet-triplet gaps in diradical organic π-systems are of interest in many applications. In this study, we calculate them in a series of molecules, including cyclobutadiene and its derivatives and cyclopentadienyl cation, by using correlated participating orbitals within the complete active space (CAS) and restricted active space (RAS) self-consistent field frameworks, followed by second-order perturbation theory (CASPT2 and RASPT2). These calculations are evaluated by comparison with the results of doubly electron-attached (DEA) equation-of-motion (EOM) coupled-cluster (CC) calculations with up to 4-particle-2-hole (4p-2h) excitations. We find active spaces that can accurately reproduce the DEA-EOMCC(4p-2h) data while being small enough to be applicable to larger organic diradicals.

Quantifying substructures in Hubble Frontier Field clusters: comparison with ΛCDM simulations

DOE PAGES

Mohammed, Irshad; Saha, Prasenjit; Williams, Liliya L. R.; ...

2016-04-13

The Hubble Frontier Fields (HFF) are six clusters of galaxies, all showing indications of recent mergers, which have recently been observed for lensed images. As such they are the natural laboratories to study the merging history of galaxy clusters. In this work, we explore the 2D power spectrum of the mass distributionmore » $$P_{\\rm M}(k)$$ as a measure of substructure. We compare $$P_{\\rm M}(k)$$ of these clusters (obtained using strong gravitational lensing) to that of $$\\Lambda$$CDM simulated clusters of similar mass. In order to compute lensing $$P_{\\rm M}(k)$$, we produced free-form lensing mass reconstructions of HFF clusters, without any light traces mass (LTM) assumption. Moreover, the inferred power at small scales tends to be larger if (i)~the cluster is at lower redshift, and/or (ii)~there are deeper observations and hence more lensed images. In contrast, lens reconstructions assuming LTM show higher power at small scales even with fewer lensed images; it appears the small scale power in the LTM reconstructions is dominated by light information, rather than the lensing data. The average lensing derived $$P_{\\rm M}(k)$$ shows lower power at small scales as compared to that of simulated clusters at redshift zero, both dark-matter only and hydrodynamical. The possible reasons are: (i)~the available strong lensing data are limited in their effective spatial resolution on the mass distribution, (ii)~HFF clusters have yet to build the small scale power they would have at $$z\\sim 0$$, or (iii)~simulations are somehow overestimating the small scale power.« less

Resolving the problem of galaxy clustering on small scales: any new physics needed?

NASA Astrophysics Data System (ADS)

Kang, X.

2014-02-01

Galaxy clustering sets strong constraints on the physics governing galaxy formation and evolution. However, most current models fail to reproduce the clustering of low-mass galaxies on small scales (r < 1 Mpc h-1). In this paper, we study the galaxy clusterings predicted from a few semi-analytical models. We first compare two Munich versions, Guo et al. and De Lucia & Blaizot. The Guo11 model well reproduces the galaxy stellar mass function, but overpredicts the clustering of low-mass galaxies on small scales. The DLB07 model provides a better fit to the clustering on small scales, but overpredicts the stellar mass function. These seem to be puzzling. The clustering on small scales is dominated by galaxies in the same dark matter halo, and there is slightly more fraction of satellite galaxies residing in massive haloes in the Guo11 model, which is the dominant contribution to the clustering discrepancy between the two models. However, both models still overpredict the clustering at 0.1 < r < 10 Mpc h-1 for low-mass galaxies. This is because both models overpredict the number of satellites by 30 per cent in massive haloes than the data. We show that the Guo11 model could be slightly modified to simultaneously fit the stellar mass function and clusterings, but that cannot be easily achieved in the DLB07 model. The better agreement of DLB07 model with the data actually comes as a coincidence as it predicts too many low-mass central galaxies which are less clustered and thus brings down the total clustering. Finally, we show the predictions from the semi-analytical models of Kang et al. We find that this model can simultaneously fit the stellar mass function and galaxy clustering if the supernova feedback in satellite galaxies is stronger. We conclude that semi-analytical models are now able to solve the small-scales clustering problem, without invoking of any other new physics or changing the dark matter properties, such as the recent favoured warm dark matter.

Cluster randomised crossover trials with binary data and unbalanced cluster sizes: application to studies of near-universal interventions in intensive care.

PubMed

Forbes, Andrew B; Akram, Muhammad; Pilcher, David; Cooper, Jamie; Bellomo, Rinaldo

2015-02-01

Cluster randomised crossover trials have been utilised in recent years in the health and social sciences. Methods for analysis have been proposed; however, for binary outcomes, these have received little assessment of their appropriateness. In addition, methods for determination of sample size are currently limited to balanced cluster sizes both between clusters and between periods within clusters. This article aims to extend this work to unbalanced situations and to evaluate the properties of a variety of methods for analysis of binary data, with a particular focus on the setting of potential trials of near-universal interventions in intensive care to reduce in-hospital mortality. We derive a formula for sample size estimation for unbalanced cluster sizes, and apply it to the intensive care setting to demonstrate the utility of the cluster crossover design. We conduct a numerical simulation of the design in the intensive care setting and for more general configurations, and we assess the performance of three cluster summary estimators and an individual-data estimator based on binomial-identity-link regression. For settings similar to the intensive care scenario involving large cluster sizes and small intra-cluster correlations, the sample size formulae developed and analysis methods investigated are found to be appropriate, with the unweighted cluster summary method performing well relative to the more optimal but more complex inverse-variance weighted method. More generally, we find that the unweighted and cluster-size-weighted summary methods perform well, with the relative efficiency of each largely determined systematically from the study design parameters. Performance of individual-data regression is adequate with small cluster sizes but becomes inefficient for large, unbalanced cluster sizes. When outcome prevalences are 6% or less and the within-cluster-within-period correlation is 0.05 or larger, all methods display sub-nominal confidence interval coverage, with the less prevalent the outcome the worse the coverage. As with all simulation studies, conclusions are limited to the configurations studied. We confined attention to detecting intervention effects on an absolute risk scale using marginal models and did not explore properties of binary random effects models. Cluster crossover designs with binary outcomes can be analysed using simple cluster summary methods, and sample size in unbalanced cluster size settings can be determined using relatively straightforward formulae. However, caution needs to be applied in situations with low prevalence outcomes and moderate to high intra-cluster correlations. © The Author(s) 2014.

Developmental analysis of the dopamine-containing neurons of the Drosophila brain

PubMed Central

Hartenstein, Volker; Cruz, Louie; Lovick, Jennifer K.; Guo, Ming

2016-01-01

The Drosophila dopaminergic (DA) system consists of a relatively small number of neurons clustered throughout the brain and ventral nerve cord. Previous work shows that clusters of DA neurons innervate different brain compartments, which in part accounts for functional diversity of the DA system. In this paper, we analyzed the association between DA neuron clusters and specific brain lineages, developmental and structural units of the Drosophila brain which provide a framework of connections that can be followed throughout development. The hatching larval brain contains six groups of primary DA neurons (born in the embryo), which we assign to six distinct lineages. We can show that all larval DA clusters persist into the adult brain. Some clusters increase in cell number during late larval stages while others do not become DA-positive until early pupa. Ablating neuroblasts with hydroxyurea (HU) prior to onset of larval proliferation (generates secondary neurons) confirms these added DA clusters are primary neurons born in the embryo, rather than secondary neurons. A single cluster that becomes DA-positive in the late pupa, PAM1/lineage DALcm1/2, forms part of a secondary lineage which can be ablated by larval HU application. By supplying lineage information for each DA cluster, our analysis promotes further developmental and functional analyses of this important system of neurons. PMID:27350102

Self-assembly of bimodal particles inside emulsion droplets

NASA Astrophysics Data System (ADS)

Cho, Young-Sang; Yi, Gi-Ra; Yang, Seung-Man; Kim, Young-Kuk; Choi, Chul-Jin

2010-08-01

Colloidal dispersion of bimodal particles were self-organized inside water-in-oil emulsion droplets by evaporationdriven self-assembly method. After droplet shrinkage by heating the complex fluid system, small numbers of microspheres were packed into minimal second moment clusters, which are partially coated with silica nanospheres, resulting in the generation of patchy particles. The patchy particles in this study possess potential applications for selfassembly of non-isotropic particles such as dimmers or tetramers for colloidal photonic crystals with diamond lattice structures. The composite micro-clusters of amidine polystyrene microspheres and titania nanoparticles were also generated by evaporation-driven self-assembly to fabricate nonspherical hollow micro-particles made of titania shell.

Volume shift and charge instability of simple-metal clusters

NASA Astrophysics Data System (ADS)

Brajczewska, M.; Vieira, A.; Fiolhais, C.; Perdew, J. P.

1996-12-01

Experiment indicates that small clusters show changes (mostly contractions) of the bond lengths with respect to bulk values. We use the stabilized jellium model to study the self-expansion and self-compression of spherical clusters (neutral or ionized) of simple metals. Results from Kohn - Sham density functional theory are presented for small clusters of Al and Na, including negatively-charged ones. We also examine the stability of clusters with respect to charging.

Physics of a rapid CD4 lymphocyte count with colloidal gold.

PubMed

Hansen, P; Barry, D; Restell, A; Sylvia, D; Magnin, O; Dombkowski, D; Preffer, F

2012-03-01

The inherent surface charges and small diameters that confer colloidal stability to gold particle conjugates (immunogold) are detrimental to rapid cell surface labeling and distinct cluster definition in flow cytometric light scatter assays. Although the inherent immunogold surface charge prevents self aggregation when stored in liquid suspension, it also slows binding to cells to timeframes of hours and inhibits cell surface coverage. Although the small diameter of immunogold particles prevents settling when in liquid suspension, small particles have small light scattering cross sections and weak light scatter signals. We report a new, small particle lyophilized immunogold reagent that maintains activity after 42°C storage for a year and can be rapidly dissolved into stable liquid suspension for use in labelling cells with larger particle aggregates that have enhanced scattering cross section. Labeling requires less than 1 min at 20°C, which is ∼30 times faster than customary fluorescent antibody labeling. The labeling step involves neutralizing the surface charge of immunogold and creating specifically bound aggregates of gold on the cell surface. This process provides distinct side-scatter cluster separation with blue laser light at 488 nm, which is further improved by using red laser light at 640 nm. Similar comparisons using LED light sources showed less improvement with red light, thereby indicating that coherent light scatter is of significance in enhancing side-scatter cluster separation. The physical principles elucidated here for this technique are compatible with most flow cytometers; however, future studies of its clinical efficacy should be of primary interest in point-of-care applications where robust reagents and rapid results are important. Copyright © 2011 International Society for Advancement of Cytometry.

Assessment of relevant factors and relationships concerning human dermal exposure to pesticides in greenhouse applications.

PubMed

Martínez Vidal, Jose L; Egea González, Francisco J; Garrido Frenich, Antonia; Martínez Galera, María; Aguilera, Pedro A; López Carrique, Enrique

2002-08-01

Principal component analysis (PCA) was applied to the gas chromatographic data obtained from 23 different greenhouse trials. This was used to establish which factors, including application technique (very small, small, medium and large drop-size), crop characteristics (short/tall, thin/dense) and pattern application of the operator (walking towards or away from the treated area) are relevant to the dermal exposure levels of greenhouse applicators. The results showed that the highest exposure by pesticides during field applications in greenhouses, in the climatic conditions and in the crop conditions typical of a southern European country, occurs on the lower legs and front thighs of the applicators. Similar results were obtained by hierarchical cluster analysis (HCA). Drop-size seems to be very important in determining total exposure, while height and density of crops have little influence on total exposure under the conditions of the present study. No pesticide type is a major factor in total exposure. The application of multiple regression analysis (MRA) allowed assessment of the relationships between the pesticide exposure of the less affected parts of the body with the most affected parts.

Solid state and aqueous behavior of uranyl peroxide cage clusters

NASA Astrophysics Data System (ADS)

Pellegrini, Kristi Lynn

Uranyl peroxide cage clusters include a large family of more than 50 published clusters of a variety of sizes, which can incorporate various ligands including pyrophosphate and oxalate. Previous studies have reported that uranyl clusters can be used as a method to separate uranium from a solid matrix, with potential applications in reprocessing of irradiated nuclear fuel. Because of the potential applications of these novel structures in an advanced nuclear fuel cycle and their likely presence in areas of contamination, it is important to understand their behavior in both solid state and aqueous systems, including complex environments where other ions are present. In this thesis, I examine the aqueous behavior of U24Pp 12, as well as aqueous cluster systems with added mono-, di-, and trivalent cations. The resulting solutions were analyzed using dynamic light scattering and ultra-small angle X-ray scattering to evaluate the species in solution. Precipitates of these systems were analyzed using powder X-ray diffraction, X-ray fluorescence spectrometry, and Raman spectroscopy. The results of these analyses demonstrate the importance of cation size, charge, and concentration of added cations on the aqueous behavior of uranium macroions. Specifically, aggregates of various sizes and shapes form rapidly upon addition of cations, and in some cases these aggregates appear to precipitate into an X-ray amorphous material that still contains U24Pp12 clusters. In addition, I probe aggregation of U24Pp12 and U60, another uranyl peroxide cage cluster, in mixed solvent water-alcohol systems. The aggregation of uranyl clusters in water-alcohol systems is a result of hydrogen bonding with polar organic molecules and the reduction of the dielectric constant of the system. Studies of aggregation of uranyl clusters also allow for comparison between the newer uranyl polyoxometalate family and century-old transition metal polyoxometalates. To complement the solution studies of uranyl cage clusters, solid state analyses of U24Pp12 are presented, including single crystal X-ray diffraction and preliminary single crystal neutron diffraction. Solid state analyses are used to probe the complicated bonding environments between U24Pp12 and crystallized counterions, giving further insight into the importance of cluster protonation and counterions in uranyl cluster systems. The combination of solid state and solution techniques provides information about the complicated nature of uranyl peroxide nanoclusters, and insight towards future applications of clusters in the advanced nuclear fuel cycle and the environment.

First principles study of edge carboxylated graphene quantum dots

NASA Astrophysics Data System (ADS)

Abdelsalam, Hazem; Elhaes, Hanan; Ibrahim, Medhat A.

2018-05-01

The structure stability and electronic properties of edge carboxylated hexagonal and triangular graphene quantum dots are investigated using density functional theory. The calculated binding energies show that the hexagonal clusters with armchair edges have the highest stability among all the quantum dots. The binding energy of carboxylated graphene quantum dots increases by increasing the number of carboxyl groups. Our study shows that the total dipole moment significantly increases by adding COOH with the highest value observed in triangular clusters. The edge states in triangular graphene quantum dots with zigzag edges produce completely different energy spectrum from other dots: (a) the energy gap in triangular zigzag is very small as compared to other clusters and (b) the highest occupied molecular orbital is localized at the edges which is in contrast to other clusters where it is distributed over the cluster surface. The enhanced reactivity and the controllable energy gap by shape and edge termination make graphene quantum dots ideal for various nanodevice applications such as sensors. The infrared spectra are presented to confirm the stability of the quantum dots.

Applying Pose Clustering and MD Simulations To Eliminate False Positives in Molecular Docking.

PubMed

Makeneni, Spandana; Thieker, David F; Woods, Robert J

2018-03-26

In this work, we developed a computational protocol that employs multiple molecular docking experiments, followed by pose clustering, molecular dynamic simulations (10 ns), and energy rescoring to produce reliable 3D models of antibody-carbohydrate complexes. The protocol was applied to 10 antibody-carbohydrate co-complexes and three unliganded (apo) antibodies. Pose clustering significantly reduced the number of potential poses. For each system, 15 or fewer clusters out of 100 initial poses were generated and chosen for further analysis. Molecular dynamics (MD) simulations allowed the docked poses to either converge or disperse, and rescoring increased the likelihood that the best-ranked pose was an acceptable pose. This approach is amenable to automation and can be a valuable aid in determining the structure of antibody-carbohydrate complexes provided there is no major side chain rearrangement or backbone conformational change in the H3 loop of the CDR regions. Further, the basic protocol of docking a small ligand to a known binding site, clustering the results, and performing MD with a suitable force field is applicable to any protein ligand system.

Fault Network Reconstruction using Agglomerative Clustering: Applications to South Californian Seismicity

NASA Astrophysics Data System (ADS)

Kamer, Yavor; Ouillon, Guy; Sornette, Didier; Wössner, Jochen

2014-05-01

We present applications of a new clustering method for fault network reconstruction based on the spatial distribution of seismicity. Unlike common approaches that start from the simplest large scale and gradually increase the complexity trying to explain the small scales, our method uses a bottom-up approach, by an initial sampling of the small scales and then reducing the complexity. The new approach also exploits the location uncertainty associated with each event in order to obtain a more accurate representation of the spatial probability distribution of the seismicity. For a given dataset, we first construct an agglomerative hierarchical cluster (AHC) tree based on Ward's minimum variance linkage. Such a tree starts out with one cluster and progressively branches out into an increasing number of clusters. To atomize the structure into its constitutive protoclusters, we initialize a Gaussian Mixture Modeling (GMM) at a given level of the hierarchical clustering tree. We then let the GMM converge using an Expectation Maximization (EM) algorithm. The kernels that become ill defined (less than 4 points) at the end of the EM are discarded. By incrementing the number of initialization clusters (by atomizing at increasingly populated levels of the AHC tree) and repeating the procedure above, we are able to determine the maximum number of Gaussian kernels the structure can hold. The kernels in this configuration constitute our protoclusters. In this setting, merging of any pair will lessen the likelihood (calculated over the pdf of the kernels) but in turn will reduce the model's complexity. The information loss/gain of any possible merging can thus be quantified based on the Minimum Description Length (MDL) principle. Similar to an inter-distance matrix, where the matrix element di,j gives the distance between points i and j, we can construct a MDL gain/loss matrix where mi,j gives the information gain/loss resulting from the merging of kernels i and j. Based on this matrix, merging events resulting in MDL gain are performed in descending order until no gainful merging is possible anymore. We envision that the results of this study could lead to a better understanding of the complex interactions within the Californian fault system and hopefully use the acquired insights for earthquake forecasting.

Sampling in health geography: reconciling geographical objectives and probabilistic methods. An example of a health survey in Vientiane (Lao PDR)

PubMed Central

Vallée, Julie; Souris, Marc; Fournet, Florence; Bochaton, Audrey; Mobillion, Virginie; Peyronnie, Karine; Salem, Gérard

2007-01-01

Background Geographical objectives and probabilistic methods are difficult to reconcile in a unique health survey. Probabilistic methods focus on individuals to provide estimates of a variable's prevalence with a certain precision, while geographical approaches emphasise the selection of specific areas to study interactions between spatial characteristics and health outcomes. A sample selected from a small number of specific areas creates statistical challenges: the observations are not independent at the local level, and this results in poor statistical validity at the global level. Therefore, it is difficult to construct a sample that is appropriate for both geographical and probability methods. Methods We used a two-stage selection procedure with a first non-random stage of selection of clusters. Instead of randomly selecting clusters, we deliberately chose a group of clusters, which as a whole would contain all the variation in health measures in the population. As there was no health information available before the survey, we selected a priori determinants that can influence the spatial homogeneity of the health characteristics. This method yields a distribution of variables in the sample that closely resembles that in the overall population, something that cannot be guaranteed with randomly-selected clusters, especially if the number of selected clusters is small. In this way, we were able to survey specific areas while minimising design effects and maximising statistical precision. Application We applied this strategy in a health survey carried out in Vientiane, Lao People's Democratic Republic. We selected well-known health determinants with unequal spatial distribution within the city: nationality and literacy. We deliberately selected a combination of clusters whose distribution of nationality and literacy is similar to the distribution in the general population. Conclusion This paper describes the conceptual reasoning behind the construction of the survey sample and shows that it can be advantageous to choose clusters using reasoned hypotheses, based on both probability and geographical approaches, in contrast to a conventional, random cluster selection strategy. PMID:17543100

Implementation of spectral clustering on microarray data of carcinoma using k-means algorithm

NASA Astrophysics Data System (ADS)

Frisca, Bustamam, Alhadi; Siswantining, Titin

2017-03-01

Clustering is one of data analysis methods that aims to classify data which have similar characteristics in the same group. Spectral clustering is one of the most popular modern clustering algorithms. As an effective clustering technique, spectral clustering method emerged from the concepts of spectral graph theory. Spectral clustering method needs partitioning algorithm. There are some partitioning methods including PAM, SOM, Fuzzy c-means, and k-means. Based on the research that has been done by Capital and Choudhury in 2013, when using Euclidian distance k-means algorithm provide better accuracy than PAM algorithm. So in this paper we use k-means as our partition algorithm. The major advantage of spectral clustering is in reducing data dimension, especially in this case to reduce the dimension of large microarray dataset. Microarray data is a small-sized chip made of a glass plate containing thousands and even tens of thousands kinds of genes in the DNA fragments derived from doubling cDNA. Application of microarray data is widely used to detect cancer, for the example is carcinoma, in which cancer cells express the abnormalities in his genes. The purpose of this research is to classify the data that have high similarity in the same group and the data that have low similarity in the others. In this research, Carcinoma microarray data using 7457 genes. The result of partitioning using k-means algorithm is two clusters.

A speeded-up saliency region-based contrast detection method for small targets

NASA Astrophysics Data System (ADS)

Li, Zhengjie; Zhang, Haiying; Bai, Jiaojiao; Zhou, Zhongjun; Zheng, Huihuang

2018-04-01

To cope with the rapid development of the real applications for infrared small targets, the researchers have tried their best to pursue more robust detection methods. At present, the contrast measure-based method has become a promising research branch. Following the framework, in this paper, a speeded-up contrast measure scheme is proposed based on the saliency detection and density clustering. First, the saliency region is segmented by saliency detection method, and then, the Multi-scale contrast calculation is carried out on it instead of traversing the whole image. Second, the target with a certain "integrity" property in spatial is exploited to distinguish the target from the isolated noises by density clustering. Finally, the targets are detected by a self-adaptation threshold. Compared with time-consuming MPCM (Multiscale Patch Contrast Map), the time cost of the speeded-up version is within a few seconds. Additional, due to the use of "clustering segmentation", the false alarm caused by heavy noises can be restrained to a lower level. The experiments show that our method has a satisfied FASR (False alarm suppression ratio) and real-time performance compared with the state-of-art algorithms no matter in cloudy sky or sea-sky background.

Comparison of Monte Carlo simulated and measured performance parameters of miniPET scanner

NASA Astrophysics Data System (ADS)

Kis, S. A.; Emri, M.; Opposits, G.; Bükki, T.; Valastyán, I.; Hegyesi, Gy.; Imrek, J.; Kalinka, G.; Molnár, J.; Novák, D.; Végh, J.; Kerek, A.; Trón, L.; Balkay, L.

2007-02-01

In vivo imaging of small laboratory animals is a valuable tool in the development of new drugs. For this purpose, miniPET, an easy to scale modular small animal PET camera has been developed at our institutes. The system has four modules, which makes it possible to rotate the whole detector system around the axis of the field of view. Data collection and image reconstruction are performed using a data acquisition (DAQ) module with Ethernet communication facility and a computer cluster of commercial PCs. Performance tests were carried out to determine system parameters, such as energy resolution, sensitivity and noise equivalent count rate. A modified GEANT4-based GATE Monte Carlo software package was used to simulate PET data analogous to those of the performance measurements. GATE was run on a Linux cluster of 10 processors (64 bit, Xeon with 3.0 GHz) and controlled by a SUN grid engine. The application of this special computer cluster reduced the time necessary for the simulations by an order of magnitude. The simulated energy spectra, maximum rate of true coincidences and sensitivity of the camera were in good agreement with the measured parameters.

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

PubMed Central

Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure

2018-01-01

Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257

Automated clustering of probe molecules from solvent mapping of protein surfaces: new algorithms applied to hot-spot mapping and structure-based drug design

NASA Astrophysics Data System (ADS)

Lerner, Michael G.; Meagher, Kristin L.; Carlson, Heather A.

2008-10-01

Use of solvent mapping, based on multiple-copy minimization (MCM) techniques, is common in structure-based drug discovery. The minima of small-molecule probes define locations for complementary interactions within a binding pocket. Here, we present improved methods for MCM. In particular, a Jarvis-Patrick (JP) method is outlined for grouping the final locations of minimized probes into physical clusters. This algorithm has been tested through a study of protein-protein interfaces, showing the process to be robust, deterministic, and fast in the mapping of protein "hot spots." Improvements in the initial placement of probe molecules are also described. A final application to HIV-1 protease shows how our automated technique can be used to partition data too complicated to analyze by hand. These new automated methods may be easily and quickly extended to other protein systems, and our clustering methodology may be readily incorporated into other clustering packages.

Experiments in clustered neuronal networks: A paradigm for complex modular dynamics

NASA Astrophysics Data System (ADS)

Teller, Sara; Soriano, Jordi

2016-06-01

Uncovering the interplay activity-connectivity is one of the major challenges in neuroscience. To deepen in the understanding of how a neuronal circuit shapes network dynamics, neuronal cultures have emerged as remarkable systems given their accessibility and easy manipulation. An attractive configuration of these in vitro systems consists in an ensemble of interconnected clusters of neurons. Using calcium fluorescence imaging to monitor spontaneous activity in these clustered neuronal networks, we were able to draw functional maps and reveal their topological features. We also observed that these networks exhibit a hierarchical modular dynamics, in which clusters fire in small groups that shape characteristic communities in the network. The structure and stability of these communities is sensitive to chemical or physical action, and therefore their analysis may serve as a proxy for network health. Indeed, the combination of all these approaches is helping to develop models to quantify damage upon network degradation, with promising applications for the study of neurological disorders in vitro.

Waveforms clustering of small magnitude earthquakes recorded in the Northern Sicilian offshore: evidence of multiplets

NASA Astrophysics Data System (ADS)

D'Alessandro, A.; Mangano, G.; D'Anna, G.; Luzio, D.; Selvaggi, G.

2011-12-01

On September 6th 2002 the northern Sicily was hit by a strong earthquake (MW 5.9). In the following six months over a thousand aftershocks were located in the same area. On December 7th 2009, the INGV OBSLab deployed an OBS/H near the epicentral area of the main shock at a depth of 1500 m. The submarine station was recovered after 233 days. During the eight months of the experiment the OBS/H recorded about 250 small magnitude events of clear local origin. In order to identify seismic events generated by the same tectonic structure, we have applied a clustering technique based on the similarity of the waveforms. The similarity matrix was constructed using the maximum of the normalized cross-covariance function. To identify the multiplets, we used a clustering technique based on an agglomerative hierarchical algorithm, based on the nearest neighbor strategy. The results were summarized in the dendrogram of Fig. 1. The partitions have been obtained by "cutting" the dendrogram at a level of distance equal to 0.3. So we have identified 9 multiplets and some doublets and triplets. Fig. 2 shows as example the multiplet 1. The events of this cluster have a high level of similarity; 25 of the 31 micro-events are characterized by a similarity greater than 0.9. In order to locate the micro-earthquakes recorded by the OBS/H only a single station location technique was implemented and applied. Some multiplets have clouds of hypocenters overlapping each other. These clusters, indistinguishable without the application of a waveforms clustering technique, show differences in the waveforms that must be attributed to differences in focal mechanisms which generated the waveforms.

Optimizing CMS build infrastructure via Apache Mesos

NASA Astrophysics Data System (ADS)

Abdurachmanov, David; Degano, Alessandro; Elmer, Peter; Eulisse, Giulio; Mendez, David; Muzaffar, Shahzad

2015-12-01

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux. Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora, and other applications on a dynamically shared pool of nodes. We present how we migrated our continuous integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.

Sound controlled rotation of a cluster of small particles on an ultrasonically vibrating metal strip

NASA Astrophysics Data System (ADS)

Zhang, Xueyi; Zheng, Yun; Hu, Junhui

2008-01-01

We show that a vibrating metal strip, mechanically driven by an ultrasonic transducer, can rotate a cluster of small particles around a fixed point, and the diameter of the cluster of small particles can reach a stable value (steady diameter) for a given driving condition. The rotation is very stable when the vibration of the metal strip is appropriate. The revolution speed, its direction, and steady diameter of the particle cluster can be controlled by the operating frequency of the ultrasonic transducer. For shrimp eggs, a revolution speed up to 360rpm can be obtained.

Theoretical research program to study transition metal trimers and embedded clusters

NASA Technical Reports Server (NTRS)

Walch, S. P.

1984-01-01

Small transition metal clusters were studied at a high level of approximation, including all the valence electrons in the calculation and extensive electron correlation, in order to understand the electronic structure of these small metal clusters. By comparison of dimers, trimers, and possibly higher clusters, the information obtained was used to provide insights into the electronic structure of bulk transition metals. Small metal clusters are currently of considerable experimental interest and some information is becomming available both from matrix electron spin resonance studies and from gas phase spectroscopy. Collaboration between theorists and experimentalists is thus expected to be especially profitable at this time since there is some experimental information which can serve to guide the theoretical work.

Small Projects Rapid Integration and Test Environment (SPRITE): Application for Increasing Robutness

NASA Technical Reports Server (NTRS)

Lee, Ashley; Rakoczy, John; Heather, Daniel; Sanders, Devon

2013-01-01

Over the past few years interest in the development and use of small satellites has rapidly gained momentum with universities, commercial, and government organizations. In a few years we may see networked clusters of dozens or even hundreds of small, cheap, easily replaceable satellites working together in place of the large, expensive and difficult-to-replace satellites now in orbit. Standards based satellite buses and deployment mechanisms, such as the CubeSat and Poly Pico-satellite Orbital Deployer (P-POD), have stimulated growth in this area. The use of small satellites is also proving to be a cost effective capability in many areas traditionally dominated by large satellites, though many challenges remain. Currently many of these small satellites undergo very little testing prior to flight. As these small satellites move from technology demonstration and student projects toward more complex operational assets, it is expected that the standards for verification and validation will increase.

Optical Materials with a Genome: Nanophotonics with DNA-Stabilized Silver Clusters

NASA Astrophysics Data System (ADS)

Copp, Stacy M.

Fluorescent silver clusters with unique rod-like geometries are stabilized by DNA. The sizes and colors of these clusters, or AgN-DNA, are selected by DNA base sequence, which can tune peak emission from blue-green into the near-infrared. Combined with DNA nanostructures, AgN-DNA promise exciting applications in nanophotonics and sensing. Until recently, however, a lack of understanding of the mechanisms controlling AgN-DNA fluorescence has challenged such applications. This dissertation discusses progress toward understanding the role of DNA as a "genome" for silver clusters and toward using DNA to achieve atomic-scale precision of silver cluster size and nanometer-scale precision of silver cluster position on a DNA breadboard. We also investigate sensitivity of AgN-DNA to local solvent environment, with an eye toward applications in chemical and biochemical sensing. Using robotic techniques to generate large data sets, we show that fluorescent silver clusters are templated by certain DNA base motifs that select "magic-sized" cluster cores of enhanced stabilities. The linear arrangement of bases on the phosphate backbone imposes a unique rod-like geometry on the clusters. Harnessing machine learning and bioinformatics techniques, we also demonstrate that sequences of DNA templates can be selected to stabilize silver clusters with desired optical properties, including high fluorescence intensity and specific fluorescence wavelengths, with much higher rates of success as compared to current strategies. The discovered base motifs can be also used to design modular DNA host strands that enable individual silver clusters with atomically precise sizes to bind at specific programmed locations on a DNA nanostructure. We show that DNA-mediated nanoscale arrangement enables near-field coupling of distinct clusters, demonstrated by dual-color cluster assemblies exhibiting resonant energy transfer. These results demonstrate a new degree of control over the optical properties and relative positions of nanoparticles, selected almost solely by the sequence of DNA. AgN-DNA are promising chemical and biochemical sensors due to the sensitivity of their fluorescence to local environment. However, the mechanisms behind many sensing schemes are not understood, and the nature of the excited state of the silver cluster itself remains unknown. To probe the fluorescence mechanisms of AgN-DNA, we investigate the behavior of purified solutions of these clusters in various solvents. We find that standard models for fluorophore solvatochromism, including the Lippert-Mataga model, do not describe AgN-DNA fluorescence because such models neglect specific interactions between the cluster and surrounding solvent molecules. Fluorescence colors are well-modeled by Mie-Gans theory, suggesting that the local dielectric environment of the cluster does play a role in fluorescence, although additional specific solvent interactions and cluster shape changes may also determine fluorescence color and intensity. These results suggest that AgN-DNA may be sensitive to changes in local dielectric environment on nanometer length scales and may also act as sensors for small molecules with affinity for DNA.

Power and money in cluster randomized trials: when is it worth measuring a covariate?

PubMed

Moerbeek, Mirjam

2006-08-15

The power to detect a treatment effect in cluster randomized trials can be increased by increasing the number of clusters. An alternative is to include covariates into the regression model that relates treatment condition to outcome. In this paper, formulae are derived in order to evaluate both strategies on basis of their costs. It is shown that the strategy that uses covariates is more cost-efficient in detecting a treatment effect when the costs to measure these covariates are small and the correlation between the covariates and outcome is sufficiently large. The minimum required correlation depends on the cluster size, and the costs to recruit a cluster and to measure the covariate, relative to the costs to recruit a person. Measuring a covariate that varies at the person level only is recommended when cluster sizes are small and the costs to recruit and measure a cluster are large. Measuring a cluster level covariate is recommended when cluster sizes are large and the costs to recruit and measure a cluster are small. An illustrative example shows the use of the formulae in a practical setting. Copyright 2006 John Wiley & Sons, Ltd.

WFPC2 Observations of Star Clusters in the Magellanic Clouds. Report 2; The Oldest Star Clusters in the Small Magellanic Cloud

NASA Technical Reports Server (NTRS)

Mighell, Kenneth J.; Sarajedini, Ata; French, Rica S.

1998-01-01

We present our analysis of archival Hubble Space Telescope Wide Field Planetary Camera 2 (WFPC2) observations in F45OW ( approximately B) and F555W (approximately V) of the intermediate-age populous star clusters NGC 121, NGC 339, NGC 361, NGC 416, and Kron 3 in the Small Magellanic Cloud. We use published photometry of two other SMC populous star clusters, Lindsay 1 and Lindsay 113, to investigate the age sequence of these seven populous star clusters in order to improve our understanding of the formation chronology of the SMC. We analyzed the V vs B-V and M(sub V) vs (B-V)(sub 0) color-magnitude diagrams of these populous Small Magellanic Cloud star clusters using a variety of techniques and determined their ages, metallicities, and reddenings. These new data enable us to improve the age-metallicity relation of star clusters in the Small Magellanic Cloud. In particular, we find that a closed-box continuous star-formation model does not reproduce the age-metallicity relation adequately. However, a theoretical model punctuated by bursts of star formation is in better agreement with the observational data presented herein.

Quantitative pathology in virtual microscopy: history, applications, perspectives.

PubMed

Kayser, Gian; Kayser, Klaus

2013-07-01

With the emerging success of commercially available personal computers and the rapid progress in the development of information technologies, morphometric analyses of static histological images have been introduced to improve our understanding of the biology of diseases such as cancer. First applications have been quantifications of immunohistochemical expression patterns. In addition to object counting and feature extraction, laws of thermodynamics have been applied in morphometric calculations termed syntactic structure analysis. Here, one has to consider that the information of an image can be calculated for separate hierarchical layers such as single pixels, cluster of pixels, segmented small objects, clusters of small objects, objects of higher order composed of several small objects. Using syntactic structure analysis in histological images, functional states can be extracted and efficiency of labor in tissues can be quantified. Image standardization procedures, such as shading correction and color normalization, can overcome artifacts blurring clear thresholds. Morphometric techniques are not only useful to learn more about biological features of growth patterns, they can also be helpful in routine diagnostic pathology. In such cases, entropy calculations are applied in analogy to theoretical considerations concerning information content. Thus, regions with high information content can automatically be highlighted. Analysis of the "regions of high diagnostic value" can deliver in the context of clinical information, site of involvement and patient data (e.g. age, sex), support in histopathological differential diagnoses. It can be expected that quantitative virtual microscopy will open new possibilities for automated histological support. Automated integrated quantification of histological slides also serves for quality assurance. The development and theoretical background of morphometric analyses in histopathology are reviewed, as well as their application and potential future implementation in virtual microscopy. Copyright © 2012 Elsevier GmbH. All rights reserved.

Fast "swarm of detectors" and their application in cosmic rays

NASA Astrophysics Data System (ADS)

Shoziyoev, G. P.; Shoziyoev, Sh. P.

2017-06-01

New opportunities in science appeared with the latest technology of the 21st century. This paper points to creating a new architecture for detection systems of different characteristics in astrophysics and geophysics using the latest technologies related to multicopter cluster systems, alternative energy sources, cluster technologies, cloud computing and big data. The idea of a quick-deployable scaleable dynamic system of a controlled drone with a small set of different detectors for detecting various components of extensive air showers in cosmic rays and in geophysics is very attractive. Development of this type of new system also allows to give a multiplier effect for the development of various sciences and research methods to observe natural phenomena.

Lack of small-scale clustering in 21-cm intensity maps crossed with 2dF galaxy densities at z ~ 0.08

NASA Astrophysics Data System (ADS)

Anderson, Christopher; Luciw, Nicholas; Li, Yi-Chao; Kuo, Cheng-Yu; Yadav, Jaswant; Masui, Kiyoshi; Chang, Tzu-Ching; Chen, Xuelei; Oppermann, Niels; Pen, Ue-Li; Timbie, Peter T.

2017-06-01

I report results from 21-cm intensity maps acquired from the Parkes radio telescope and cross-correlated with galaxy maps from the 2dF galaxy survey. The data span the redshift range 0.057

Extracting Galaxy Cluster Gas Inhomogeneity from X-Ray Surface Brightness: A Statistical Approach and Application to Abell 3667

NASA Astrophysics Data System (ADS)

Kawahara, Hajime; Reese, Erik D.; Kitayama, Tetsu; Sasaki, Shin; Suto, Yasushi

2008-11-01

Our previous analysis indicates that small-scale fluctuations in the intracluster medium (ICM) from cosmological hydrodynamic simulations follow the lognormal probability density function. In order to test the lognormal nature of the ICM directly against X-ray observations of galaxy clusters, we develop a method of extracting statistical information about the three-dimensional properties of the fluctuations from the two-dimensional X-ray surface brightness. We first create a set of synthetic clusters with lognormal fluctuations around their mean profile given by spherical isothermal β-models, later considering polytropic temperature profiles as well. Performing mock observations of these synthetic clusters, we find that the resulting X-ray surface brightness fluctuations also follow the lognormal distribution fairly well. Systematic analysis of the synthetic clusters provides an empirical relation between the three-dimensional density fluctuations and the two-dimensional X-ray surface brightness. We analyze Chandra observations of the galaxy cluster Abell 3667, and find that its X-ray surface brightness fluctuations follow the lognormal distribution. While the lognormal model was originally motivated by cosmological hydrodynamic simulations, this is the first observational confirmation of the lognormal signature in a real cluster. Finally we check the synthetic cluster results against clusters from cosmological hydrodynamic simulations. As a result of the complex structure exhibited by simulated clusters, the empirical relation between the two- and three-dimensional fluctuation properties calibrated with synthetic clusters when applied to simulated clusters shows large scatter. Nevertheless we are able to reproduce the true value of the fluctuation amplitude of simulated clusters within a factor of 2 from their two-dimensional X-ray surface brightness alone. Our current methodology combined with existing observational data is useful in describing and inferring the statistical properties of the three-dimensional inhomogeneity in galaxy clusters.

Approximate treatment of semicore states in GW calculations with application to Au clusters.

PubMed

Xian, Jiawei; Baroni, Stefano; Umari, P

2014-03-28

We address the treatment of transition metal atoms in GW electronic-structure calculations within the plane-wave pseudo-potential formalism. The contributions of s and p semi-core electrons to the self-energy, which are essential to grant an acceptable accuracy, are dealt with using a recently proposed scheme whereby the exchange components are treated exactly at the G0W0 level, whereas a suitable approximation to the correlation components is devised. This scheme is benchmarked for small gold nano-clusters, resulting in ionization potentials, electron affinities, and density of states in very good agreement with those obtained from calculations where s and p semicore states are treated as valence orbitals, and allowing us to apply this same scheme to clusters of intermediate size, Au20 and Au32, that would be otherwise very difficult to deal with.

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing.

PubMed

Leong, Siow Hoo; Ong, Seng Huat

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index.

Approximate treatment of semicore states in GW calculations with application to Au clusters

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

Xian, Jiawei; Baroni, Stefano; CNR-IOM Democritos, Theory-Elettra group, Trieste

We address the treatment of transition metal atoms in GW electronic-structure calculations within the plane-wave pseudo-potential formalism. The contributions of s and p semi-core electrons to the self-energy, which are essential to grant an acceptable accuracy, are dealt with using a recently proposed scheme whereby the exchange components are treated exactly at the G{sub 0}W{sub 0} level, whereas a suitable approximation to the correlation components is devised. This scheme is benchmarked for small gold nano-clusters, resulting in ionization potentials, electron affinities, and density of states in very good agreement with those obtained from calculations where s and p semicore statesmore » are treated as valence orbitals, and allowing us to apply this same scheme to clusters of intermediate size, Au{sub 20} and Au{sub 32}, that would be otherwise very difficult to deal with.« less

Similarity measure and domain adaptation in multiple mixture model clustering: An application to image processing

PubMed Central

Leong, Siow Hoo

2017-01-01

This paper considers three crucial issues in processing scaled down image, the representation of partial image, similarity measure and domain adaptation. Two Gaussian mixture model based algorithms are proposed to effectively preserve image details and avoids image degradation. Multiple partial images are clustered separately through Gaussian mixture model clustering with a scan and select procedure to enhance the inclusion of small image details. The local image features, represented by maximum likelihood estimates of the mixture components, are classified by using the modified Bayes factor (MBF) as a similarity measure. The detection of novel local features from MBF will suggest domain adaptation, which is changing the number of components of the Gaussian mixture model. The performance of the proposed algorithms are evaluated with simulated data and real images and it is shown to perform much better than existing Gaussian mixture model based algorithms in reproducing images with higher structural similarity index. PMID:28686634

Two-Phase and Graph-Based Clustering Methods for Accurate and Efficient Segmentation of Large Mass Spectrometry Images.

PubMed

Dexter, Alex; Race, Alan M; Steven, Rory T; Barnes, Jennifer R; Hulme, Heather; Goodwin, Richard J A; Styles, Iain B; Bunch, Josephine

2017-11-07

Clustering is widely used in MSI to segment anatomical features and differentiate tissue types, but existing approaches are both CPU and memory-intensive, limiting their application to small, single data sets. We propose a new approach that uses a graph-based algorithm with a two-phase sampling method that overcomes this limitation. We demonstrate the algorithm on a range of sample types and show that it can segment anatomical features that are not identified using commonly employed algorithms in MSI, and we validate our results on synthetic MSI data. We show that the algorithm is robust to fluctuations in data quality by successfully clustering data with a designed-in variance using data acquired with varying laser fluence. Finally, we show that this method is capable of generating accurate segmentations of large MSI data sets acquired on the newest generation of MSI instruments and evaluate these results by comparison with histopathology.

Method and apparatus for detecting and/or imaging clusters of small scattering centers in the body

DOEpatents

Perez-Mendez, V.; Sommer, F.G.

1982-07-13

An ultrasonic method and apparatus are provided for detecting and imaging clusters of small scattering centers in the breast wherein periodic pulses are applied to an ultrasound emitting transducer and projected into the body, thereafter being received by at least one receiving transducer positioned to receive scattering from the scattering center clusters. The signals are processed to provide an image showing cluster extent and location. 6 figs.

Method and apparatus for detecting and/or imaging clusters of small scattering centers in the body

DOEpatents

Perez-Mendez, Victor; Sommer, Frank G.

1982-01-01

An ultrasonic method and apparatus are provided for detecting and imaging clusters of small scattering centers in the breast wherein periodic pulses are applied to an ultrasound emitting transducer and projected into the body, thereafter being received by at least one receiving transducer positioned to receive scattering from the scattering center clusters. The signals are processed to provide an image showing cluster extent and location.

Hot and solid gallium clusters: too small to melt.

PubMed

Breaux, Gary A; Benirschke, Robert C; Sugai, Toshiki; Kinnear, Brian S; Jarrold, Martin F

2003-11-21

A novel multicollision induced dissociation scheme is employed to determine the energy content for mass-selected gallium cluster ions as a function of their temperature. Measurements were performed for Ga(+)(n) (n=17 39, and 40) over a 90-720 K temperature range. For Ga+39 and Ga+40 a broad maximum in the heat capacity-a signature of a melting transition for a small cluster-occurs at around 550 K. Thus small gallium clusters melt at substantially above the 302.9 K melting point of bulk gallium, in conflict with expectations that they will remain liquid to below 150 K. No melting transition is observed for Ga+17.

A universal matter-wave interferometer with optical ionization gratings in the time-domain

PubMed Central

Haslinger, Philipp; Dörre, Nadine; Geyer, Philipp; Rodewald, Jonas; Nimmrichter, Stefan; Arndt, Markus

2015-01-01

Matter-wave interferometry with atoms1 and molecules2 has attracted a rapidly growing interest throughout the last two decades both in demonstrations of fundamental quantum phenomena and in quantum-enhanced precision measurements. Such experiments exploit the non-classical superposition of two or more position and momentum states which are coherently split and rejoined to interfere3-11. Here, we present the experimental realization of a universal near-field interferometer built from three short-pulse single-photon ionization gratings12,13. We observe quantum interference of fast molecular clusters, with a composite de Broglie wavelength as small as 275 fm. Optical ionization gratings are largely independent of the specific internal level structure and are therefore universally applicable to different kinds of nanoparticles, ranging from atoms to clusters, molecules and nanospheres. The interferometer is sensitive to fringe shifts as small as a few nanometers and yet robust against velocity-dependent phase shifts, since the gratings exist only for nanoseconds and form an interferometer in the time-domain. PMID:25983851

[Dynamic study of small metallic clusters]; Estudio Dinamico de Pequenos Agregados Metalicos

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

Lopez, M.J.; Jellinek, J.

1995-12-31

We present a brief introduction to computer simulation techniques (particularly to classical molecular dynamics) and their application to the study of the thermodynamic properties of a material system. The basic concepts are illustrated in the study of structural and energetic properties such as the liquid-solid transition and the fragmentation of small clusters of nickel. [Espanol] Presentamos una breve introducci{acute o}n de las t{acute e}cnicas de simulaci{acute o}n por ordenador (en particular de la Din{acute a}mica Molecular cl{acute a}sica) y de su aplicaci{acute o}n al estudio de las propiedades termodin{acute a}micas de un sistema material. Los conceptos b{acute a}sicos se ilustranmore » en el estudio de las propieades estructurales y energ{acute e}ticas, as{acute i} como de la transici{acute o}n de fase s{acute o}lido-l{acute i}quido y de las fragmentaciones de peque{tilde n}os agregados de n{acute i}quel.« less

Supervised group Lasso with applications to microarray data analysis

PubMed Central

Ma, Shuangge; Song, Xiao; Huang, Jian

2007-01-01

Background A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure. Results We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data. Conclusion We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods. PMID:17316436

A note on the kappa statistic for clustered dichotomous data.

PubMed

Zhou, Ming; Yang, Zhao

2014-06-30

The kappa statistic is widely used to assess the agreement between two raters. Motivated by a simulation-based cluster bootstrap method to calculate the variance of the kappa statistic for clustered physician-patients dichotomous data, we investigate its special correlation structure and develop a new simple and efficient data generation algorithm. For the clustered physician-patients dichotomous data, based on the delta method and its special covariance structure, we propose a semi-parametric variance estimator for the kappa statistic. An extensive Monte Carlo simulation study is performed to evaluate the performance of the new proposal and five existing methods with respect to the empirical coverage probability, root-mean-square error, and average width of the 95% confidence interval for the kappa statistic. The variance estimator ignoring the dependence within a cluster is generally inappropriate, and the variance estimators from the new proposal, bootstrap-based methods, and the sampling-based delta method perform reasonably well for at least a moderately large number of clusters (e.g., the number of clusters K ⩾50). The new proposal and sampling-based delta method provide convenient tools for efficient computations and non-simulation-based alternatives to the existing bootstrap-based methods. Moreover, the new proposal has acceptable performance even when the number of clusters is as small as K = 25. To illustrate the practical application of all the methods, one psychiatric research data and two simulated clustered physician-patients dichotomous data are analyzed. Copyright © 2014 John Wiley & Sons, Ltd.

Resource-efficient generation of linear cluster states by linear optics with postselection

DOE PAGES

Uskov, D. B.; Alsing, P. M.; Fanto, M. L.; ...

2015-01-30

Here we report on theoretical research in photonic cluster-state computing. Finding optimal schemes of generating non-classical photonic states is of critical importance for this field as physically implementable photon-photon entangling operations are currently limited to measurement-assisted stochastic transformations. A critical parameter for assessing the efficiency of such transformations is the success probability of a desired measurement outcome. At present there are several experimental groups that are capable of generating multi-photon cluster states carrying more than eight qubits. Separate photonic qubits or small clusters can be fused into a single cluster state by a probabilistic optical CZ gate conditioned on simultaneousmore » detection of all photons with 1/9 success probability for each gate. This design mechanically follows the original theoretical scheme of cluster state generation proposed more than a decade ago by Raussendorf, Browne, and Briegel. The optimality of the destructive CZ gate in application to linear optical cluster state generation has not been analyzed previously. Our results reveal that this method is far from the optimal one. Employing numerical optimization we have identified that the maximal success probability of fusing n unentangled dual-rail optical qubits into a linear cluster state is equal to 1/2 n-1; an m-tuple of photonic Bell pair states, commonly generated via spontaneous parametric down-conversion, can be fused into a single cluster with the maximal success probability of 1/4 m-1.« less

JESPP: Joint Experimentation on Scalable Parallel Processors Supercomputers

DTIC Science & Technology

2010-03-01

were for the relatively small market of scientific and engineering applications. Contrast this with GPUs that are designed to improve the end- user...experience in mass- market arenas such as gaming. In order to get meaningful speed-up using the GPU, it was determined that the data transfer and...Included) Conference Year Effectively using a Large GPGPU-Enhanced Linux Cluster HPCMP UGC 2009 FLOPS per Watt: Heterogeneous-Computing’s Approach

Feasibility of vibration monitoring of small rotating machines for the environmental control and life support systems (ECLSS) of the NASA advanced space craft

NASA Technical Reports Server (NTRS)

Milner, G. Martin; Black, Mike; Hovenga, Mike; Mcclure, Paul; Miller, Patrice

1988-01-01

The application of vibration monitoring to the rotating machinery typical of ECLSS components in advanced NASA spacecraft was studied. It is found that the weighted summation of the accelerometer power spectrum is the most successful detection scheme for a majority of problem types. Other detection schemes studied included high-frequency demodulation, cepstrum, clustering, and amplitude processing.

Depth of focus extended microscope configuration for imaging of incorporated groups of molecules, DNA constructs and clusters inside bacterial cells

NASA Astrophysics Data System (ADS)

Fessl, Tomas; Ben-Yaish, Shai; Vacha, Frantisek; Adamec, Frantisek; Zalevsky, Zeev

2009-07-01

Imaging of small objects such as single molecules, DNA clusters and single bacterial cells is problematic not only due to the lateral resolution that is obtainable in currently existing microscopy but also, and as much fundamentally limiting, due to the lack of sufficient axial depth of focus to have the full object focused simultaneously. Extension in depth of focus is helpful also for single molecule steady state FRET measurements. In this technique it is crucial to obtain data from many well focused molecules, which are often located in different axial depths. In this paper we present the implementation of an all-optical and a real time technique of extension in the depth of focus that may be incorporated in any high NA microscope system and to be used for the above mentioned applications. We demonstrate experimentally how after the integration of special optical element in high NA 100× objective lens of a single molecule imaging microscope system, the depth of focus is significantly improved while maintaining the same lateral resolution in imaging applications of incorporated groups of molecules, DNA constructs and clusters inside bacterial cells.

The Clusters-in-a-Liquid Approach for Solvation: New Insights from the Conformer Specific Gas Phase Spectroscopy and Vibrational Optical Activity Spectroscopy

PubMed Central

Perera, Angelo S.; Thomas, Javix; Poopari, Mohammad R.; Xu, Yunjie

2016-01-01

Vibrational optical activity spectroscopies, namely vibrational circular dichroism (VCD) and Raman optical activity (ROA), have been emerged in the past decade as powerful spectroscopic tools for stereochemical information of a wide range of chiral compounds in solution directly. More recently, their applications in unveiling solvent effects, especially those associated with water solvent, have been explored. In this review article, we first select a few examples to demonstrate the unique sensitivity of VCD spectral signatures to both bulk solvent effects and explicit hydrogen-bonding interactions in solution. Second, we discuss the induced solvent chirality, or chiral transfer, VCD spectral features observed in the water bending band region in detail. From these chirality transfer spectral data, the related conformer specific gas phase spectroscopic studies of small chiral hydration clusters, and the associated matrix isolation VCD experiments of hydrogen-bonded complexes in cold rare gas matrices, a general picture of solvation in aqueous solution emerges. In such an aqueous solution, some small chiral hydration clusters, rather than the chiral solutes themselves, are the dominant species and are the ones that contribute mainly to the experimentally observed VCD features. We then review a series of VCD studies of amino acids and their derivatives in aqueous solution under different pHs to emphasize the importance of the inclusion of the bulk solvent effects. These experimental data and the associated theoretical analyses are the foundation for the proposed “clusters-in-a-liquid” approach to account for solvent effects effectively. We present several approaches to identify and build such representative chiral hydration clusters. Recent studies which applied molecular dynamics simulations and the subsequent snapshot averaging approach to generate the ROA, VCD, electronic CD, and optical rotatory dispersion spectra are also reviewed. Challenges associated with the molecular dynamics snapshot approach are discussed and the successes of the seemingly random “ad hoc explicit solvation” reported before are also explained. To further test and improve the “clusters-in-a-liquid” model in practice, future work in terms of conformer specific gas phase spectroscopy of sequential solvation of a chiral solute, matrix isolation VCD measurements of small chiral hydration clusters, and more sophisticated models for the bulk solvent effects would be highly valuable. PMID:26942177

Magic Numbers in Small Iron Clusters: A First-Principles Study

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

Kim, Eunja; Mohrland, Andrew B.; Weck, Philippe F.

2014-10-03

We perform ab initio spin-polarized density functional calculations of Fen aggregates with n ≤ 17 atoms to reveal the origin of the observed magic numbers, which indicate particularly high stability of clusters with 7, 13 and 15 atoms. Our results clarify the controversy regarding the ground state geometry of clusters such as Fe5and indicate that magnetism plays an important role in determining the stability and magic numbers in small iron clusters.

On the Clustering of Europa's Small Craters

NASA Technical Reports Server (NTRS)

Bierhaus, E. B.; Chapman, C. R.; Merline, W. J.

2001-01-01

We analyze the spatial distribution of Europa's small craters and find that many are too tightly clustered to result from random, primary impacts. Additional information is contained in the original extended abstract.

A new strategy for earthquake focal mechanisms using waveform-correlation-derived relative polarities and cluster analysis: Application to the 2014 Long Valley Caldera earthquake swarm

USGS Publications Warehouse

Shelly, David R.; Hardebeck, Jeanne L.; Ellsworth, William L.; Hill, David P.

2016-01-01

In microseismicity analyses, reliable focal mechanisms can typically be obtained for only a small subset of located events. We address this limitation here, presenting a framework for determining robust focal mechanisms for entire populations of very small events. To achieve this, we resolve relative P and S wave polarities between pairs of waveforms by using their signed correlation coefficients—a by-product of previously performed precise earthquake relocation. We then use cluster analysis to group events with similar patterns of polarities across the network. Finally, we apply a standard mechanism inversion to the grouped data, using either catalog or correlation-derived P wave polarity data sets. This approach has great potential for enhancing analyses of spatially concentrated microseismicity such as earthquake swarms, mainshock-aftershock sequences, and industrial reservoir stimulation or injection-induced seismic sequences. To demonstrate its utility, we apply this technique to the 2014 Long Valley Caldera earthquake swarm. In our analysis, 85% of the events (7212 out of 8494 located by Shelly et al. [2016]) fall within five well-constrained mechanism clusters, more than 12 times the number with network-determined mechanisms. Of the earthquakes we characterize, 3023 (42%) have magnitudes smaller than 0.0. We find that mechanism variations are strongly associated with corresponding hypocentral structure, yet mechanism heterogeneity also occurs where it cannot be resolved by hypocentral patterns, often confined to small-magnitude events. Small (5–20°) rotations between mechanism orientations and earthquake location trends persist when we apply 3-D velocity models and might reflect a geometry of en echelon, interlinked shear, and dilational faulting.

An object-based approach for detecting small brain lesions: application to Virchow-Robin spaces.

PubMed

Descombes, Xavier; Kruggel, Frithjof; Wollny, Gert; Gertz, Hermann Josef

2004-02-01

This paper is concerned with the detection of multiple small brain lesions from magnetic resonance imaging (MRI) data. A model based on the marked point process framework is designed to detect Virchow-Robin spaces (VRSs). These tubular shaped spaces are due to retraction of the brain parenchyma from its supplying arteries. VRS are described by simple geometrical objects that are introduced as small tubular structures. Their radiometric properties are embedded in a data term. A prior model includes interactions describing the clustering property of VRS. A Reversible Jump Markov Chain Monte Carlo algorithm (RJMCMC) optimizes the proposed model, obtained by multiplying the prior and the data model. Example results are shown on T1-weighted MRI datasets of elderly subjects.

Aggregation of luteinizing hormone receptors in granulosa cells: a possible mechanism of desensitization to the hormone.

PubMed Central

Amsterdam, A; Berkowitz, A; Nimrod, A; Kohen, F

1980-01-01

The temporal relationship between redistribution of receptors to lutropin (luteinizing hormone)/human chorionic gonadotropin in cultured rat ovarian granulosa cells and the cellular response to hormonal challenge were studied. Visualization of receptor-bound human chorionic gonadotropin by indirect immunofluorescence, with hormone-specific antibodies after fixation with 2% formaldehyde, revealed the existence of small clusters around the entire cell circumference 5--20 min after exposure to the hormone at 37 degrees C. Such small receptor aggregates were also evident if hormone incubation was at 4 degrees C or if cells were fixed with 2% formaldehyde before incubation. Larger clusters were evident after prolonged incubation with the hormone (2--4 hr) at 37 degrees C. The later change coincided with diminished cyclic AMP accumulation in respose to challenge with fresh hormone. When the fixation step was omitted and antibodies to human chorionic gonadotropin were applied after hormonal binding, acceleration of both receptor clustering and the desensitization process was observed. This maneuver also induced capping of the hormone receptors. In contrast, monovalent Fab' fragments of the antibodies were without effect. Internalization of the bound hormone in lysosomes, and subsequent degradation, was evident 8 hr after hormonal application and was not accelerated by the antibodies. It is suggested that clustering of the luteinizing hormone receptors may play a role in cellular responsiveness to the hormone. Massive aggregation of the receptors may desensitize the cell by interferring with coupling to adenylate cyclase. Images PMID:6251459

Crystallization of glass-forming liquids: Specific surface energy

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

Schmelzer, Jürn W. P., E-mail: juern-w.schmelzer@uni-rostock.de; Abyzov, Alexander S.

2016-08-14

A generalization of the Stefan-Skapski-Turnbull relation for the melt-crystal specific interfacial energy is developed in terms of the generalized Gibbs approach extending its standard formulation to thermodynamic non-equilibrium states. With respect to crystal nucleation, this relation is required in order to determine the parameters of the critical crystal clusters being a prerequisite for the computation of the work of critical cluster formation. As one of its consequences, a relation for the dependence of the specific surface energy of critical clusters on temperature and pressure is derived applicable for small and moderate deviations from liquid-crystal macroscopic equilibrium states. Employing the Stefan-Skapski-Turnbullmore » relation, general expressions for the size and the work of formation of critical crystal clusters are formulated. The resulting expressions are much more complex as compared to the respective relations obtained via the classical Gibbs theory. Latter relations are retained as limiting cases of these more general expressions for moderate undercoolings. By this reason, the formulated, here, general relations for the specification of the critical cluster size and the work of critical cluster formation give a key for an appropriate interpretation of a variety of crystallization phenomena occurring at large undercoolings which cannot be understood in terms of the Gibbs’ classical treatment.« less

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

Ben-Naim, Eli; Krapivsky, Paul

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

Dehydration, Dehydrogenation, and Condensation of Alcohols on Supported Oxide Catalysts Based on Cyclic (WO3)3 and (MoO3)3 Clusters

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

Rousseau, Roger J.; Dixon, David A.; Kay, Bruce D.

2014-01-01

Supported early transition metal oxides have important applications in numerous catalytic reactions. In this article we review preparation and activity of well-defined model WO3 and MoO3 catalysts prepared via deposition of cyclic gas-phase (WO3)3 and (MoO3)3 clusters generated by sublimation of WO3 and MoO3 powders. Conversion of small aliphatic alcohols to alkenes, aldehydes/ketons, and ethers is employed to probe the structure-activity relationships on model WO3 and MoO3 catalysts ranging from unsupported (WO3)3 and (MoO3)3 clusters embedded in alcohol matrices, to (WO3)3 clusters supported on surfaces of other oxides, and epitaxial and nanoporous WO3 films. Detailed theoretical calculations reveal the underlyingmore » reaction mechanisms and provide insight into the origin of the differences in the WO3 and MoO3 reactivity. For the range of interrogated (WO3)3 they further shed light into the role structure and binding of (WO3)3 clusters with the support play in determining their catalytic activity.« less

A nonparametric clustering technique which estimates the number of clusters

NASA Technical Reports Server (NTRS)

Ramey, D. B.

1983-01-01

In applications of cluster analysis, one usually needs to determine the number of clusters, K, and the assignment of observations to each cluster. A clustering technique based on recursive application of a multivariate test of bimodality which automatically estimates both K and the cluster assignments is presented.

Light Scattering by Fractal Dust Aggregates. I. Angular Dependence of Scattering

NASA Astrophysics Data System (ADS)

Tazaki, Ryo; Tanaka, Hidekazu; Okuzumi, Satoshi; Kataoka, Akimasa; Nomura, Hideko

2016-06-01

In protoplanetary disks, micron-sized dust grains coagulate to form highly porous dust aggregates. Because the optical properties of these aggregates are not completely understood, it is important to investigate how porous dust aggregates scatter light. In this study, the light scattering properties of porous dust aggregates were calculated using a rigorous method, the T-matrix method, and the results were then compared with those obtained using the Rayleigh-Gans-Debye (RGD) theory and Mie theory with the effective medium approximation (EMT). The RGD theory is applicable to moderately large aggregates made of nearly transparent monomers. This study considered two types of porous dust aggregates—ballistic cluster-cluster agglomerates (BCCAs) and ballistic particle-cluster agglomerates. First, the angular dependence of the scattered intensity was shown to reflect the hierarchical structure of dust aggregates; the large-scale structure of the aggregates is responsible for the intensity at small scattering angles, and their small-scale structure determines the intensity at large scattering angles. Second, it was determined that the EMT underestimates the backward scattering intensity by multiple orders of magnitude, especially in BCCAs, because the EMT averages the structure within the size of the aggregates. It was concluded that the RGD theory is a very useful method for calculating the optical properties of BCCAs.

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health

PubMed Central

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S. Stanley

2016-01-01

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability. PMID:27213413

Applications of a Novel Clustering Approach Using Non-Negative Matrix Factorization to Environmental Research in Public Health.

PubMed

Fogel, Paul; Gaston-Mathé, Yann; Hawkins, Douglas; Fogel, Fajwel; Luta, George; Young, S Stanley

2016-05-18

Often data can be represented as a matrix, e.g., observations as rows and variables as columns, or as a doubly classified contingency table. Researchers may be interested in clustering the observations, the variables, or both. If the data is non-negative, then Non-negative Matrix Factorization (NMF) can be used to perform the clustering. By its nature, NMF-based clustering is focused on the large values. If the data is normalized by subtracting the row/column means, it becomes of mixed signs and the original NMF cannot be used. Our idea is to split and then concatenate the positive and negative parts of the matrix, after taking the absolute value of the negative elements. NMF applied to the concatenated data, which we call PosNegNMF, offers the advantages of the original NMF approach, while giving equal weight to large and small values. We use two public health datasets to illustrate the new method and compare it with alternative clustering methods, such as K-means and clustering methods based on the Singular Value Decomposition (SVD) or Principal Component Analysis (PCA). With the exception of situations where a reasonably accurate factorization can be achieved using the first SVD component, we recommend that the epidemiologists and environmental scientists use the new method to obtain clusters with improved quality and interpretability.

ClusterControl: a web interface for distributing and monitoring bioinformatics applications on a Linux cluster.

PubMed

Stocker, Gernot; Rieder, Dietmar; Trajanoski, Zlatko

2004-03-22

ClusterControl is a web interface to simplify distributing and monitoring bioinformatics applications on Linux cluster systems. We have developed a modular concept that enables integration of command line oriented program into the application framework of ClusterControl. The systems facilitate integration of different applications accessed through one interface and executed on a distributed cluster system. The package is based on freely available technologies like Apache as web server, PHP as server-side scripting language and OpenPBS as queuing system and is available free of charge for academic and non-profit institutions. http://genome.tugraz.at/Software/ClusterControl

A Population-Based Analysis of Application of WHO Nomenclature in Pathology Reports of Pulmonary Neuroendocrine Tumors.

PubMed

Derks, Jules L; van Suylen, Robert Jan; Thunnissen, Erik; den Bakker, Michael A; Smit, Egbert F; Groen, Harry J M; Speel, Ernst J M; Dingemans, Anne-Marie C

2016-04-01

Pulmonary neuroendocrine tumors (pNETs) are difficult to classify. We performed a population-based analysis to investigate the application of pNET nomenclature in daily pathology practice. Conclusions from pathology reports (2003-2012) describing carcinoids, (large cell) neuroendocrine carcinomas (NECs), and carcinomas with neuroendocrine features/differentiation were retrieved from the Dutch Pathology Registry by queries on location and diagnosis and screened for terminology. Cases with a nonpulmonary or unknown origin and small cell lung cancer were excluded. Diagnoses were clustered into subgroups and the retrieved terminology was compared with the 2015 World Health Organization (WHO) diagnoses. By means of an online questionnaire, interpretation of the non-WHO nomenclature retrieved from pathology reports was evaluated (by 35 physicians and 19 pathologists). A total of 3216 unique pathology report conclusions with 55 different pNET diagnoses (n = 3052) and 20 uncertain diagnoses (n = 164) were analyzed. Non-WHO nomenclature was used in 15% of diagnoses (n = 488). Diagnoses could be clustered into carcinoids (n = 1086), NEC (n = 1316), carcinomas with neuroendocrine features/differentiation (n = 624), and unspecified pNETs (n = 26). Non-WHO nomenclature within these clusters was found for 7% of carcinoids, 20% of NECs, 13% of carcinomas with neuroendocrine features/differentiation, and 100% of unspecified pNETs and was observed more often in conclusions regarding biopsy or cytological specimens (62% and 12%) compared with resection specimens (26%). Analysis of the questionnaire results revealed that 4 of 19 diagnoses based on non-WHO nomenclature were uniformly interpreted (>50% agreement) by physicians, as were 10 of 19 diagnoses by pathologists. In 15% of pNETs other than small cell lung cancer, a non-WHO nomenclature diagnosis was provided, more frequently on the basis of smaller specimens. The interpretation was different between physicians and pathologists. Application of uniform nomenclature among all clinicians is advocated. Copyright © 2016 International Association for the Study of Lung Cancer. Published by Elsevier Inc. All rights reserved.

Whole brain white matter connectivity analysis using machine learning: An application to autism.

PubMed

Zhang, Fan; Savadjiev, Peter; Cai, Weidong; Song, Yang; Rathi, Yogesh; Tunç, Birkan; Parker, Drew; Kapur, Tina; Schultz, Robert T; Makris, Nikos; Verma, Ragini; O'Donnell, Lauren J

2018-05-15

In this paper, we propose an automated white matter connectivity analysis method for machine learning classification and characterization of white matter abnormality via identification of discriminative fiber tracts. The proposed method uses diffusion MRI tractography and a data-driven approach to find fiber clusters corresponding to subdivisions of the white matter anatomy. Features extracted from each fiber cluster describe its diffusion properties and are used for machine learning. The method is demonstrated by application to a pediatric neuroimaging dataset from 149 individuals, including 70 children with autism spectrum disorder (ASD) and 79 typically developing controls (TDC). A classification accuracy of 78.33% is achieved in this cross-validation study. We investigate the discriminative diffusion features based on a two-tensor fiber tracking model. We observe that the mean fractional anisotropy from the second tensor (associated with crossing fibers) is most affected in ASD. We also find that local along-tract (central cores and endpoint regions) differences between ASD and TDC are helpful in differentiating the two groups. These altered diffusion properties in ASD are associated with multiple robustly discriminative fiber clusters, which belong to several major white matter tracts including the corpus callosum, arcuate fasciculus, uncinate fasciculus and aslant tract; and the white matter structures related to the cerebellum, brain stem, and ventral diencephalon. These discriminative fiber clusters, a small part of the whole brain tractography, represent the white matter connections that could be most affected in ASD. Our results indicate the potential of a machine learning pipeline based on white matter fiber clustering. Copyright © 2017 Elsevier Inc. All rights reserved.

Computational Design of Clusters for Catalysis

NASA Astrophysics Data System (ADS)

Jimenez-Izal, Elisa; Alexandrova, Anastassia N.

2018-04-01

When small clusters are studied in chemical physics or physical chemistry, one perhaps thinks of the fundamental aspects of cluster electronic structure, or precision spectroscopy in ultracold molecular beams. However, small clusters are also of interest in catalysis, where the cold ground state or an isolated cluster may not even be the right starting point. Instead, the big question is: What happens to cluster-based catalysts under real conditions of catalysis, such as high temperature and coverage with reagents? Myriads of metastable cluster states become accessible, the entire system is dynamic, and catalysis may be driven by rare sites present only under those conditions. Activity, selectivity, and stability are highly dependent on size, composition, shape, support, and environment. To probe and master cluster catalysis, sophisticated tools are being developed for precision synthesis, operando measurements, and multiscale modeling. This review intends to tell the messy story of clusters in catalysis.

An evaluation of ISOCLS and CLASSY clustering algorithms for forest classification in northern Idaho. [Elk River quadrange of the Clearwater National Forest

NASA Technical Reports Server (NTRS)

Werth, L. F. (Principal Investigator)

1981-01-01

Both the iterative self-organizing clustering system (ISOCLS) and the CLASSY algorithms were applied to forest and nonforest classes for one 1:24,000 quadrangle map of northern Idaho and the classification and mapping accuracies were evaluated with 1:30,000 color infrared aerial photography. Confusion matrices for the two clustering algorithms were generated and studied to determine which is most applicable to forest and rangeland inventories in future projects. In an unsupervised mode, ISOCLS requires many trial-and-error runs to find the proper parameters to separate desired information classes. CLASSY tells more in a single run concerning the classes that can be separated, shows more promise for forest stratification than ISOCLS, and shows more promise for consistency. One major drawback to CLASSY is that important forest and range classes that are smaller than a minimum cluster size will be combined with other classes. The algorithm requires so much computer storage that only data sets as small as a quadrangle can be used at one time.

Close proximity electrostatic effect from small clusters of emitters

NASA Astrophysics Data System (ADS)

Dall'Agnol, Fernando F.; de Assis, Thiago A.

2017-10-01

Using a numerical simulation based on the finite-element technique, this work investigates the field emission properties from clusters of a few emitters at close proximity, by analyzing the properties of the maximum local field enhancement factor (γm ) and the corresponding emission current. At short distances between the emitters, we show the existence of a nonintuitive behavior, which consists of the increasing of γm as the distance c between the emitters decreases. Here we investigate this phenomenon for clusters with 2, 3, 4 and 7 identical emitters and study the influence of the proximity effect in the emission current, considering the role of the aspect ratio of the individual emitters. Importantly, our results show that peripheral emitters with high aspect-ratios in large clusters can, in principle, significantly increase the emitted current as a consequence only of the close proximity electrostatic effect (CPEE). This phenomenon can be seen as a physical mechanism to produce self-oscillations of individual emitters. We discuss new insights for understanding the nature of self-oscillations in emitters based on the CPEE, including applications to nanometric oscillators.

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.

Adsorption and Formation of Small Na Clusters on Pristine and Double-Vacancy Graphene for Anodes of Na-Ion Batteries.

PubMed

Liang, Zhicong; Fan, Xiaofeng; Zheng, Weitao; Singh, David J

2017-05-24

Layered carbon is a likely anode material for Na-ion batteries (NIBs). Graphitic carbon has a low capacity of approximately 35 (mA h)/g due to the formation of NaC 64 . Using first-principles methods including van der Waals interactions, we analyze the adsorption of Na ions and clusters on graphene in the context of anodes. The interaction between Na ions and graphene is found to be weak. Small Na clusters are not stable on the surface of pristine graphene in the electrochemical environment of NIBs. However, we find that Na ions and clusters can be stored effectively on defected graphene that has double vacancies. In addition, the adsorption energy of small Na clusters near a double vacancy is found to decrease with increasing cluster size. With high concentrations of vacancies the capacity of Na on defective graphene is found to be as much as 10-30 times higher than that of graphitic carbon.

Resource Provisioning in SLA-Based Cluster Computing

NASA Astrophysics Data System (ADS)

Xiong, Kaiqi; Suh, Sang

Cluster computing is excellent for parallel computation. It has become increasingly popular. In cluster computing, a service level agreement (SLA) is a set of quality of services (QoS) and a fee agreed between a customer and an application service provider. It plays an important role in an e-business application. An application service provider uses a set of cluster computing resources to support e-business applications subject to an SLA. In this paper, the QoS includes percentile response time and cluster utilization. We present an approach for resource provisioning in such an environment that minimizes the total cost of cluster computing resources used by an application service provider for an e-business application that often requires parallel computation for high service performance, availability, and reliability while satisfying a QoS and a fee negotiated between a customer and the application service provider. Simulation experiments demonstrate the applicability of the approach.

Clustering Methods with Qualitative Data: A Mixed Methods Approach for Prevention Research with Small Samples

PubMed Central

Henry, David; Dymnicki, Allison B.; Mohatt, Nathaniel; Allen, James; Kelly, James G.

2016-01-01

Qualitative methods potentially add depth to prevention research, but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data, but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-Means clustering, and latent class analysis produced similar levels of accuracy with binary data, and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a “real-world” example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities. PMID:25946969

Clustering Methods with Qualitative Data: a Mixed-Methods Approach for Prevention Research with Small Samples.

PubMed

Henry, David; Dymnicki, Allison B; Mohatt, Nathaniel; Allen, James; Kelly, James G

2015-10-01

Qualitative methods potentially add depth to prevention research but can produce large amounts of complex data even with small samples. Studies conducted with culturally distinct samples often produce voluminous qualitative data but may lack sufficient sample sizes for sophisticated quantitative analysis. Currently lacking in mixed-methods research are methods allowing for more fully integrating qualitative and quantitative analysis techniques. Cluster analysis can be applied to coded qualitative data to clarify the findings of prevention studies by aiding efforts to reveal such things as the motives of participants for their actions and the reasons behind counterintuitive findings. By clustering groups of participants with similar profiles of codes in a quantitative analysis, cluster analysis can serve as a key component in mixed-methods research. This article reports two studies. In the first study, we conduct simulations to test the accuracy of cluster assignment using three different clustering methods with binary data as produced when coding qualitative interviews. Results indicated that hierarchical clustering, K-means clustering, and latent class analysis produced similar levels of accuracy with binary data and that the accuracy of these methods did not decrease with samples as small as 50. Whereas the first study explores the feasibility of using common clustering methods with binary data, the second study provides a "real-world" example using data from a qualitative study of community leadership connected with a drug abuse prevention project. We discuss the implications of this approach for conducting prevention research, especially with small samples and culturally distinct communities.

Revealing isomerism in sodium-water clusters: Photoionization spectra of Na(H2O)n (n = 2-90)

NASA Astrophysics Data System (ADS)

Dierking, Christoph W.; Zurheide, Florian; Zeuch, Thomas; Med, Jakub; Parez, Stanislav; Slavíček, Petr

2017-06-01

Soft ionization of sodium tagged polar clusters is increasingly used as a powerful technique for sizing and characterization of small aerosols with possible application, e.g., in atmospheric chemistry or combustion science. Understanding the structure and photoionization of the sodium doped clusters is critical for such applications. In this work, we report on measurements of photoionization spectra for sodium doped water clusters containing 2-90 water molecules. While most of the previous studies focused on the ionization threshold of the Na(H2O)n clusters, we provide for the first time full photoionization spectra, including the high-energy region, which are used as reference for a comparison with theory. As reported in previous work, we have seen an initial drop of the appearance ionization energy with cluster size to values of about 3.2 eV for n <5 . In the size range from n = 5 to n = 15, broad ion yield curves emerge; for larger clusters, a constant range between signal appearance (˜2.8 eV) and signal saturation (˜4.1 eV) has been observed. The measurements are interpreted with ab initio calculations and ab initio molecular dynamics simulations for selected cluster sizes (n ≤ 15). The simulations revealed theory shortfalls when aiming at quantitative agreement but allowed us identifying structural motifs consistent with the observed ionization energy distributions. We found a decrease in the ionization energy with increasing coordination of the Na atom and increasing delocalization of the Na 3s electron cloud. The appearance ionization energy is determined by isomers with fully solvated sodium and a highly delocalized electron cloud, while both fully and incompletely solvated isomers with localized electron clouds can contribute to the high energy part of the photoionization spectrum. Simulations at elevated temperatures show an increased abundance of isomers with low ionization energies, an entropic effect enabling size selective infrared action spectroscopy, based on near threshold photoionization of Na(H2O)n clusters. In addition, simulations of the sodium pick-up process were carried out to study the gradual formation of the hydrated electron which is the basis of the sodium-tagging sizing.

Revealing isomerism in sodium-water clusters: Photoionization spectra of Na(H2O)n (n = 2-90).

PubMed

Dierking, Christoph W; Zurheide, Florian; Zeuch, Thomas; Med, Jakub; Parez, Stanislav; Slavíček, Petr

2017-06-28

Soft ionization of sodium tagged polar clusters is increasingly used as a powerful technique for sizing and characterization of small aerosols with possible application, e.g., in atmospheric chemistry or combustion science. Understanding the structure and photoionization of the sodium doped clusters is critical for such applications. In this work, we report on measurements of photoionization spectra for sodium doped water clusters containing 2-90 water molecules. While most of the previous studies focused on the ionization threshold of the Na(H 2 O) n clusters, we provide for the first time full photoionization spectra, including the high-energy region, which are used as reference for a comparison with theory. As reported in previous work, we have seen an initial drop of the appearance ionization energy with cluster size to values of about 3.2 eV for n<5. In the size range from n = 5 to n = 15, broad ion yield curves emerge; for larger clusters, a constant range between signal appearance (∼2.8 eV) and signal saturation (∼4.1 eV) has been observed. The measurements are interpreted with ab initio calculations and ab initio molecular dynamics simulations for selected cluster sizes (n≤ 15). The simulations revealed theory shortfalls when aiming at quantitative agreement but allowed us identifying structural motifs consistent with the observed ionization energy distributions. We found a decrease in the ionization energy with increasing coordination of the Na atom and increasing delocalization of the Na 3s electron cloud. The appearance ionization energy is determined by isomers with fully solvated sodium and a highly delocalized electron cloud, while both fully and incompletely solvated isomers with localized electron clouds can contribute to the high energy part of the photoionization spectrum. Simulations at elevated temperatures show an increased abundance of isomers with low ionization energies, an entropic effect enabling size selective infrared action spectroscopy, based on near threshold photoionization of Na(H 2 O) n clusters. In addition, simulations of the sodium pick-up process were carried out to study the gradual formation of the hydrated electron which is the basis of the sodium-tagging sizing.

Effect of dose and size on defect engineering in carbon cluster implanted silicon wafers

NASA Astrophysics Data System (ADS)

Okuyama, Ryosuke; Masada, Ayumi; Shigematsu, Satoshi; Kadono, Takeshi; Hirose, Ryo; Koga, Yoshihiro; Okuda, Hidehiko; Kurita, Kazunari

2018-01-01

Carbon-cluster-ion-implanted defects were investigated by high-resolution cross-sectional transmission electron microscopy toward achieving high-performance CMOS image sensors. We revealed that implantation damage formation in the silicon wafer bulk significantly differs between carbon-cluster and monomer ions after implantation. After epitaxial growth, small and large defects were observed in the implanted region of carbon clusters. The electron diffraction pattern of both small and large defects exhibits that from bulk crystalline silicon in the implanted region. On the one hand, we assumed that the silicon carbide structure was not formed in the implanted region, and small defects formed because of the complex of carbon and interstitial silicon. On the other hand, large defects were hypothesized to originate from the recrystallization of the amorphous layer formed by high-dose carbon-cluster implantation. These defects are considered to contribute to the powerful gettering capability required for high-performance CMOS image sensors.

In-Plane Multimagnetron Approach

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

Johnson, Grant E.; Laskin, Julia

2017-04-01

Nanoparticles (NPs) and sub-nanometer clusters containing controlled amounts of different atoms are of interest for a variety of potential applications including catalysis,1, 2 optics,3, 4 magnetics,5-7 sensors,8, 9 and biotheraputics.10, 11 Alloy NPs may possess enhanced physical and chemical properties compared to single metal species due to the additional interplay between their different elemental components. By reducing the quantity of expensive precious metals in alloy NPs by substituting cheaper base metals, it may also be possible to achieve equivalent or even superior performance to pure noble metal NPs for applications such as heterogeneous catalysis at substantially reduced material costs.12 Inmore » addition, alloying of elements that are immiscible in bulk form is possible in NPs because the enthalpy of mixing decreases and becomes negative at small particle sizes.13, 14 As a result, a substantially broader array of alloy species may be generated in the form of NPs and sub-nanometer clusters.« less

Optimizing CMS build infrastructure via Apache Mesos

DOE PAGES

Abdurachmanov, David; Degano, Alessandro; Elmer, Peter; ...

2015-12-23

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux.Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora,more » and other applications on a dynamically shared pool of nodes. Lastly, we present how we migrated our continuous integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.« less

Optimizing CMS build infrastructure via Apache Mesos

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

Abdurachmanov, David; Degano, Alessandro; Elmer, Peter

The Offline Software of the CMS Experiment at the Large Hadron Collider (LHC) at CERN consists of 6M lines of in-house code, developed over a decade by nearly 1000 physicists, as well as a comparable amount of general use open-source code. A critical ingredient to the success of the construction and early operation of the WLCG was the convergence, around the year 2000, on the use of a homogeneous environment of commodity x86-64 processors and Linux.Apache Mesos is a cluster manager that provides efficient resource isolation and sharing across distributed applications, or frameworks. It can run Hadoop, Jenkins, Spark, Aurora,more » and other applications on a dynamically shared pool of nodes. Lastly, we present how we migrated our continuous integration system to schedule jobs on a relatively small Apache Mesos enabled cluster and how this resulted in better resource usage, higher peak performance and lower latency thanks to the dynamic scheduling capabilities of Mesos.« less

Euchromatic Transposon Insertions Trigger Production of Novel Pi- and Endo-siRNAs at the Target Sites in the Drosophila Germline

PubMed Central

Olovnikov, Ivan; Abramov, Yuri; Kalmykova, Alla

2014-01-01

The control of transposable element (TE) activity in germ cells provides genome integrity over generations. A distinct small RNA–mediated pathway utilizing Piwi-interacting RNAs (piRNAs) suppresses TE expression in gonads of metazoans. In the fly, primary piRNAs derive from so-called piRNA clusters, which are enriched in damaged repeated sequences. These piRNAs launch a cycle of TE and piRNA cluster transcript cleavages resulting in the amplification of piRNA and TE silencing. Using genome-wide comparison of TE insertions and ovarian small RNA libraries from two Drosophila strains, we found that individual TEs inserted into euchromatic loci form novel dual-stranded piRNA clusters. Formation of the piRNA-generating loci by active individual TEs provides a more potent silencing response to the TE expansion. Like all piRNA clusters, individual TEs are also capable of triggering the production of endogenous small interfering (endo-si) RNAs. Small RNA production by individual TEs spreads into the flanking genomic regions including coding cellular genes. We show that formation of TE-associated small RNA clusters can down-regulate expression of nearby genes in ovaries. Integration of TEs into the 3′ untranslated region of actively transcribed genes induces piRNA production towards the 3′-end of transcripts, causing the appearance of genic piRNA clusters, a phenomenon that has been reported in different organisms. These data suggest a significant role of TE-associated small RNAs in the evolution of regulatory networks in the germline. PMID:24516406

Reactivity and Catalytic Activity of Hydrogen Atom Chemisorbed Silver Clusters.

PubMed

Manzoor, Dar; Pal, Sourav

2015-06-18

Metal clusters of silver have attracted recent interest of researchers as a result of their potential in different catalytic applications and low cost. However, due to the completely filled d orbital and very high first ionization potential of the silver atom, the silver-based catalysts interact very weakly with the reacting molecules. In the current work, density functional theory calculations were carried out to investigate the effect of hydrogen atom chemisorption on the reactivity and catalytic properties of inert silver clusters. Our results affirm that the hydrogen atom chemisorption leads to enhancement in the binding energy of the adsorbed O2 molecule on the inert silver clusters. The increase in the binding energy is also characterized by the decrease in the Ag-O and increase in the O-O bond lengths in the case of the AgnH silver clusters. Pertinent to the increase in the O-O bond length, a significant red shift in the O-O stretching frequency is also noted in the case of the AgnH silver clusters. Moreover, the hydrogen atom chemisorbed silver clusters show low reaction barriers and high heat of formation of the final products for the environmentally important CO oxidation reaction as compared to the parent catalytically inactive clusters. The obtained results were compared with those of the corresponding gold and hydrogen atom chemisorbed gold clusters obtained at the same level of theory. It is expected the current computational study will provide key insights for future advances in the design of efficient nanosilver-based catalysts through the adsorption of a small atom or a ligand.

Kinetics of Aggregation with Choice

DOE PAGES

Ben-Naim, Eli; Krapivsky, Paul

2016-12-01

Here we generalize the ordinary aggregation process to allow for choice. In ordinary aggregation, two random clusters merge and form a larger aggregate. In our implementation of choice, a target cluster and two candidate clusters are randomly selected and the target cluster merges with the larger of the two candidate clusters.We study the long-time asymptotic behavior and find that as in ordinary aggregation, the size density adheres to the standard scaling form. However, aggregation with choice exhibits a number of different features. First, the density of the smallest clusters exhibits anomalous scaling. Second, both the small-size and the large-size tailsmore » of the density are overpopulated, at the expense of the density of moderate-size clusters. Finally, we also study the complementary case where the smaller candidate cluster participates in the aggregation process and find an abundance of moderate clusters at the expense of small and large clusters. Additionally, we investigate aggregation processes with choice among multiple candidate clusters and a symmetric implementation where the choice is between two pairs of clusters.« less

A roadmap of clustering algorithms: finding a match for a biomedical application.

PubMed

Andreopoulos, Bill; An, Aijun; Wang, Xiaogang; Schroeder, Michael

2009-05-01

Clustering is ubiquitously applied in bioinformatics with hierarchical clustering and k-means partitioning being the most popular methods. Numerous improvements of these two clustering methods have been introduced, as well as completely different approaches such as grid-based, density-based and model-based clustering. For improved bioinformatics analysis of data, it is important to match clusterings to the requirements of a biomedical application. In this article, we present a set of desirable clustering features that are used as evaluation criteria for clustering algorithms. We review 40 different clustering algorithms of all approaches and datatypes. We compare algorithms on the basis of desirable clustering features, and outline algorithms' benefits and drawbacks as a basis for matching them to biomedical applications.

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.

Investigation of Metal and Metal Oxide Clusters Small Enough to Constitute the Critical Size for Gas Phase Nucleation in Combustion Processes.

DTIC Science & Technology

1980-11-01

Ao-A093 950 NORTHWESTERN UNIV EVANSTON IL DEPT OF M4ECHANICAL ND-ETC F/S 7/4 INVESTIGATION OF 1ETAL AND METAL OXIDE CLUSTERS S1ALL ENOUGH TO--ETC(U...34 " 18. SUPPLEMENTARY NOTES 19. KEY WORDS (Continue on reveroe side if necessary snd Identify by block number) Clusters , Nucleation, Molecular Beam, Free...contract a variety of techniques have been employed to study the properties of small atomic and molecular clusters formed in the gas phase via

Ultra-small rhenium clusters supported on graphene.

PubMed

Miramontes, Orlando; Bonafé, Franco; Santiago, Ulises; Larios-Rodriguez, Eduardo; Velázquez-Salazar, Jesús J; Mariscal, Marcelo M; Yacaman, Miguel José

2015-03-28

The adsorption of very small rhenium clusters (2-13 atoms) supported on graphene was studied by high-angle annular dark field-scanning transmission electron microscopy (HAADF-STEM). The atomic structure of the clusters was fully resolved with the aid of density functional theory calculations and STEM simulations. It was found that octahedral and tetrahedral structures work as seeds to obtain more complex morphologies. Finally, a detailed analysis of the electronic structure suggested that a higher catalytic effect can be expected in Re clusters when adsorbed on graphene than in isolated ones.

Ultra-small rhenium clusters supported on graphene

PubMed Central

Miramontes, Orlando; Bonafé, Franco; Santiago, Ulises; Larios-Rodriguez, Eduardo; Velázquez-Salazar, Jesús J.; Mariscal, Marcelo M.; Yacaman, Miguel José

2015-01-01

The adsorption of very small rhenium clusters (2 – 13 atoms) supported on graphene was studied with high annular dark field - scanning transmission electron microscopy (HAADF-STEM). The atomic structure of the clusters was fully resolved with the aid of density functional calculations and STEM simulations. It was found that octahedral and tetrahedral structures work as seeds to obtain more complex morphologies. Finally, a detailed analysis of the electronic structure suggested that a higher catalytic effect can be expected in Re clusters when adsorbed on graphene than in isolated ones. PMID:25721176

Transient regulation of three clustered tomato class-I small heat-shock chaperone genes by ethylene is mediated by SIMADS-RIN transcription factor

USDA-ARS?s Scientific Manuscript database

An intronless cluster of three class I small heat shock protein (sHSP) chaperone genes, Sl17.6, Sl20.0 and Sl20.1, resident on the short arm of chromosome 6 in tomato, was previously characterized (Goyal et al., 2012). This shsp chaperone gene cluster was found decorated with cis sequences known to ...

Cluster-to-cluster transformation among Au6, Au8 and Au11 nanoclusters.

PubMed

Ren, Xiuqing; Fu, Junhong; Lin, Xinzhang; Fu, Xuemei; Yan, Jinghui; Wu, Ren'an; Liu, Chao; Huang, Jiahui

2018-05-22

We present the cluster-to-cluster transformations among three gold nanoclusters, [Au6(dppp)4]2+ (Au6), [Au8(dppp)4Cl2]2+ (Au8) and [Au11(dppp)5]3+ (Au11). The conversion process follows a rule that states that the transformation of a small cluster to a large cluster is achieved through an oxidation process with an oxidizing agent (H2O2) or with heating, while the conversion of a large cluster to a small one occurs through a reduction process with a reducing agent (NaBH4). All the reactions were monitored using UV-Vis spectroscopy and ESI-MS. This work may provide an alternative approach to the synthesis of novel gold nanoclusters and a further understanding of the structural transformation relationship of gold nanoclusters.

Quasi-planar elemental clusters in pair interactions approximation

NASA Astrophysics Data System (ADS)

Chkhartishvili, Levan

2016-01-01

The pair-interactions approximation, when applied to describe elemental clusters, only takes into account bonding between neighboring atoms. According to this approach, isomers of wrapped forms of 2D clusters - nanotubular and fullerene-like structures - and truly 3D clusters, are generally expected to be more stable than their quasi-planar counterparts. This is because quasi-planar clusters contain more peripheral atoms with dangling bonds and, correspondingly, fewer atoms with saturated bonds. However, the differences in coordination numbers between central and peripheral atoms lead to the polarization of bonds. The related corrections to the molar binding energy can make small, quasi-planar clusters more stable than their 2D wrapped allotropes and 3D isomers. The present work provides a general theoretical frame for studying the relative stability of small elemental clusters within the pair interactions approximation.

Myeloid Clusters Are Associated with a Pro-Metastatic Environment and Poor Prognosis in Smoking-Related Early Stage Non-Small Cell Lung Cancer

PubMed Central

Zhang, Wang; Pal, Sumanta K.; Liu, Xueli; Yang, Chunmei; Allahabadi, Sachin; Bhanji, Shaira; Figlin, Robert A.; Yu, Hua; Reckamp, Karen L.

2013-01-01

Background This study aimed to understand the role of myeloid cell clusters in uninvolved regional lymph nodes from early stage non-small cell lung cancer patients. Methods Uninvolved regional lymph node sections from 67 patients with stage I–III resected non-small cell lung cancer were immunostained to detect myeloid clusters, STAT3 activity and occult metastasis. Anthracosis intensity, myeloid cluster infiltration associated with anthracosis and pSTAT3 level were scored and correlated with patient survival. Multivariate Cox regression analysis was performed with prognostic variables. Human macrophages were used for in vitro nicotine treatment. Results CD68+ myeloid clusters associated with anthracosis and with an immunosuppressive and metastasis-promoting phenotype and elevated overall STAT3 activity were observed in uninvolved lymph nodes. In patients with a smoking history, myeloid cluster score significantly correlated with anthracosis intensity and pSTAT3 level (P<0.01). Nicotine activated STAT3 in macrophages in long-term culture. CD68+ myeloid clusters correlated and colocalized with occult metastasis. Myeloid cluster score was an independent prognostic factor (P = 0.049) and was associated with survival by Kaplan-Maier estimate in patients with a history of smoking (P = 0.055). The combination of myeloid cluster score with either lymph node stage or pSTAT3 level defined two populations with a significant difference in survival (P = 0.024 and P = 0.004, respectively). Conclusions Myeloid clusters facilitate a pro-metastatic microenvironment in uninvolved regional lymph nodes and associate with occult metastasis in early stage non-small cell lung cancer. Myeloid cluster score is an independent prognostic factor for survival in patients with a history of smoking, and may present a novel method to inform therapy choices in the adjuvant setting. Further validation studies are warranted. PMID:23717691

First-principles investigation of the dissociation and coupling of methane on small copper clusters: Interplay of collision dynamics and geometric and electronic effects

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

Varghese, Jithin J.; Mushrif, Samir H., E-mail: shmushrif@ntu.edu.sg

Small metal clusters exhibit unique size and morphology dependent catalytic activity. The search for alternate minimum energy pathways and catalysts to transform methane to more useful chemicals and carbon nanomaterials led us to investigate collision induced dissociation of methane on small Cu clusters. We report here for the first time, the free energy barriers for the collision induced activation, dissociation, and coupling of methane on small Cu clusters (Cu{sub n} where n = 2–12) using ab initio molecular dynamics and metadynamics simulations. The collision induced activation of the stretching and bending vibrations of methane significantly reduces the free energy barriermore » for its dissociation. Increase in the cluster size reduces the barrier for dissociation of methane due to the corresponding increase in delocalisation of electron density within the cluster, as demonstrated using the electron localisation function topology analysis. This enables higher probability of favourable alignment of the C–H stretching vibration of methane towards regions of high electron density within the cluster and makes higher number of sites available for the chemisorption of CH{sub 3} and H upon dissociation. These characteristics contribute in lowering the barrier for dissociation of methane. Distortion and reorganisation of cluster geometry due to high temperature collision dynamics disturb electron delocalisation within them and increase the barrier for dissociation. Coupling reactions of CH{sub x} (x = 1–3) species and recombination of H with CH{sub x} have free energy barriers significantly lower than complete dehydrogenation of methane to carbon. Thus, competition favours the former reactions at high hydrogen saturation on the clusters.« less

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

Nielsen, Michael A.; School of Information Technology and Electrical Engineering, University of Queensland, Brisbane, Queensland 4072; Dawson, Christopher M.

The one-way quantum computing model introduced by Raussendorf and Briegel [Phys. Rev. Lett. 86, 5188 (2001)] shows that it is possible to quantum compute using only a fixed entangled resource known as a cluster state, and adaptive single-qubit measurements. This model is the basis for several practical proposals for quantum computation, including a promising proposal for optical quantum computation based on cluster states [M. A. Nielsen, Phys. Rev. Lett. (to be published), quant-ph/0402005]. A significant open question is whether such proposals are scalable in the presence of physically realistic noise. In this paper we prove two threshold theorems which showmore » that scalable fault-tolerant quantum computation may be achieved in implementations based on cluster states, provided the noise in the implementations is below some constant threshold value. Our first threshold theorem applies to a class of implementations in which entangling gates are applied deterministically, but with a small amount of noise. We expect this threshold to be applicable in a wide variety of physical systems. Our second threshold theorem is specifically adapted to proposals such as the optical cluster-state proposal, in which nondeterministic entangling gates are used. A critical technical component of our proofs is two powerful theorems which relate the properties of noisy unitary operations restricted to act on a subspace of state space to extensions of those operations acting on the entire state space. We expect these theorems to have a variety of applications in other areas of quantum-information science.« less

The effect of defect cluster size and interpolation on radiographic image quality

NASA Astrophysics Data System (ADS)

Töpfer, Karin; Yip, Kwok L.

2011-03-01

For digital X-ray detectors, the need to control factory yield and cost invariably leads to the presence of some defective pixels. Recently, a standard procedure was developed to identify such pixels for industrial applications. However, no quality standards exist in medical or industrial imaging regarding the maximum allowable number and size of detector defects. While the answer may be application specific, the minimum requirement for any defect specification is that the diagnostic quality of the images be maintained. A more stringent criterion is to keep any changes in the images due to defects below the visual threshold. Two highly sensitive image simulation and evaluation methods were employed to specify the fraction of allowable defects as a function of defect cluster size in general radiography. First, the most critical situation of the defect being located in the center of the disease feature was explored using image simulation tools and a previously verified human observer model, incorporating a channelized Hotelling observer. Detectability index d' was obtained as a function of defect cluster size for three different disease features on clinical lung and extremity backgrounds. Second, four concentrations of defects of four different sizes were added to clinical images with subtle disease features and then interpolated. Twenty observers evaluated the images against the original on a single display using a 2-AFC method, which was highly sensitive to small changes in image detail. Based on a 50% just-noticeable difference, the fraction of allowed defects was specified vs. cluster size.

Predicting vacancy-mediated diffusion of interstitial solutes in α -Fe

NASA Astrophysics Data System (ADS)

Barouh, Caroline; Schuler, Thomas; Fu, Chu-Chun; Jourdan, Thomas

2015-09-01

Based on a systematic first-principles study, the lowest-energy migration mechanisms and barriers for small vacancy-solute clusters (VnXm ) are determined in α -Fe for carbon, nitrogen, and oxygen, which are the most frequent interstitial solutes in several transition metals. We show that the dominant clusters present at thermal equilibrium (V X and V X2 ) have very reduced mobility compared to isolated solutes, while clusters composed of a solute bound to a small vacancy cluster may be significantly more mobile. In particular, V3X is found to be the fastest cluster for all three solutes. This result relies on the large diffusivity of the most compact trivacancy in a bcc lattice. Therefore, it may also be expected for interstitial solutes in other bcc metals. In the case of iron, we find that V3X may be as fast as or even more mobile than an interstitial solute. At variance with common assumptions, the trapping of interstitial solutes by vacancies does not necessarily decrease the mobility of the solute. Additionally, cluster dynamics simulations are performed considering a simple iron system with supersaturation of vacancies, in order to investigate the impacts of small mobile vacancy-solute clusters on properties such as the transport of solute and the cluster size distributions.

Influence of reactive gas admixture on transition metal cluster nucleation in a gas aggregation cluster source

NASA Astrophysics Data System (ADS)

Peter, Tilo; Polonskyi, Oleksandr; Gojdka, Björn; Mohammad Ahadi, Amir; Strunskus, Thomas; Zaporojtchenko, Vladimir; Biederman, Hynek; Faupel, Franz

2012-12-01

We quantitatively assessed the influence of reactive gases on the formation processes of transition metal clusters in a gas aggregation cluster source. A cluster source based on a 2 in. magnetron is used to study the production rate of titanium and cobalt clusters. Argon served as working gas for the DC magnetron discharge, and a small amount of reactive gas (oxygen and nitrogen) is added to promote reactive cluster formation. We found that the cluster production rate depends strongly on the reactive gas concentration for very small amounts of reactive gas (less than 0.1% of total working gas), and no cluster formation takes place in the absence of reactive species. The influence of discharge power, reactive gas concentration, and working gas pressure are investigated using a quartz micro balance in a time resolved manner. The strong influence of reactive gas is explained by a more efficient formation of nucleation seeds for metal-oxide or nitride than for pure metal.

Mass Distribution in Galaxy Cluster Cores

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

Hogan, M. T.; McNamara, B. R.; Pulido, F.

Many processes within galaxy clusters, such as those believed to govern the onset of thermally unstable cooling and active galactic nucleus feedback, are dependent upon local dynamical timescales. However, accurate mapping of the mass distribution within individual clusters is challenging, particularly toward cluster centers where the total mass budget has substantial radially dependent contributions from the stellar ( M {sub *}), gas ( M {sub gas}), and dark matter ( M {sub DM}) components. In this paper we use a small sample of galaxy clusters with deep Chandra observations and good ancillary tracers of their gravitating mass at both largemore » and small radii to develop a method for determining mass profiles that span a wide radial range and extend down into the central galaxy. We also consider potential observational pitfalls in understanding cooling in hot cluster atmospheres, and find tentative evidence for a relationship between the radial extent of cooling X-ray gas and nebular H α emission in cool-core clusters. At large radii the entropy profiles of our clusters agree with the baseline power law of K ∝ r {sup 1.1} expected from gravity alone. At smaller radii our entropy profiles become shallower but continue with a power law of the form K ∝ r {sup 0.67} down to our resolution limit. Among this small sample of cool-core clusters we therefore find no support for the existence of a central flat “entropy floor.”.« less

Focus-based filtering + clustering technique for power-law networks with small world phenomenon

NASA Astrophysics Data System (ADS)

Boutin, François; Thièvre, Jérôme; Hascoët, Mountaz

2006-01-01

Realistic interaction networks usually present two main properties: a power-law degree distribution and a small world behavior. Few nodes are linked to many nodes and adjacent nodes are likely to share common neighbors. Moreover, graph structure usually presents a dense core that is difficult to explore with classical filtering and clustering techniques. In this paper, we propose a new filtering technique accounting for a user-focus. This technique extracts a tree-like graph with also power-law degree distribution and small world behavior. Resulting structure is easily drawn with classical force-directed drawing algorithms. It is also quickly clustered and displayed into a multi-level silhouette tree (MuSi-Tree) from any user-focus. We built a new graph filtering + clustering + drawing API and report a case study.

SLUG - stochastically lighting up galaxies - III. A suite of tools for simulated photometry, spectroscopy, and Bayesian inference with stochastic stellar populations

NASA Astrophysics Data System (ADS)

Krumholz, Mark R.; Fumagalli, Michele; da Silva, Robert L.; Rendahl, Theodore; Parra, Jonathan

2015-09-01

Stellar population synthesis techniques for predicting the observable light emitted by a stellar population have extensive applications in numerous areas of astronomy. However, accurate predictions for small populations of young stars, such as those found in individual star clusters, star-forming dwarf galaxies, and small segments of spiral galaxies, require that the population be treated stochastically. Conversely, accurate deductions of the properties of such objects also require consideration of stochasticity. Here we describe a comprehensive suite of modular, open-source software tools for tackling these related problems. These include the following: a greatly-enhanced version of the SLUG code introduced by da Silva et al., which computes spectra and photometry for stochastically or deterministically sampled stellar populations with nearly arbitrary star formation histories, clustering properties, and initial mass functions; CLOUDY_SLUG, a tool that automatically couples SLUG-computed spectra with the CLOUDY radiative transfer code in order to predict stochastic nebular emission; BAYESPHOT, a general-purpose tool for performing Bayesian inference on the physical properties of stellar systems based on unresolved photometry; and CLUSTER_SLUG and SFR_SLUG, a pair of tools that use BAYESPHOT on a library of SLUG models to compute the mass, age, and extinction of mono-age star clusters, and the star formation rate of galaxies, respectively. The latter two tools make use of an extensive library of pre-computed stellar population models, which are included in the software. The complete package is available at http://www.slugsps.com.

Patterned growth of p-type MoS 2 atomic layers using sol-gel as precursor

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

Zheng, Wei; Lin, Junhao; Feng, Wei

2D layered MoS 2 has drawn intense attention for its applications in flexible electronic, optoelectronic, and spintronic devices. Most of the MoS 2 atomic layers grown by conventional chemical vapor deposition techniques are n-type due to the abundant sulfur vacancies. Facile production of MoS 2 atomic layers with p-type behavior, however, remains challenging. Here, a novel one-step growth has been developed to attain p-type MoS 2 layers in large scale by using Mo-containing sol–gel, including 1% tungsten (W). Atomic-resolution electron microscopy characterization reveals that small tungsten oxide clusters are commonly present on the as-grown MoS 2 film due to themore » incomplete reduction of W precursor at the reaction temperature. These omnipresent small tungsten oxide clusters contribute to the p-type behavior, as verified by density functional theory calculations, while preserving the crystallinity of the MoS 2 atomic layers. The Mo containing sol–gel precursor is compatible with the soft-lithography techniques, which enables patterned growth of p-type MoS 2 atomic layers into regular arrays with different shapes, holding great promise for highly integrated device applications. Lastly, an atomically thin p–n junction is fabricated by the as-prepared MoS 2, which shows strong rectifying behavior.« less

Patterned growth of p-type MoS 2 atomic layers using sol-gel as precursor

DOE PAGES

Zheng, Wei; Lin, Junhao; Feng, Wei; ...

2016-07-19

2D layered MoS 2 has drawn intense attention for its applications in flexible electronic, optoelectronic, and spintronic devices. Most of the MoS 2 atomic layers grown by conventional chemical vapor deposition techniques are n-type due to the abundant sulfur vacancies. Facile production of MoS 2 atomic layers with p-type behavior, however, remains challenging. Here, a novel one-step growth has been developed to attain p-type MoS 2 layers in large scale by using Mo-containing sol–gel, including 1% tungsten (W). Atomic-resolution electron microscopy characterization reveals that small tungsten oxide clusters are commonly present on the as-grown MoS 2 film due to themore » incomplete reduction of W precursor at the reaction temperature. These omnipresent small tungsten oxide clusters contribute to the p-type behavior, as verified by density functional theory calculations, while preserving the crystallinity of the MoS 2 atomic layers. The Mo containing sol–gel precursor is compatible with the soft-lithography techniques, which enables patterned growth of p-type MoS 2 atomic layers into regular arrays with different shapes, holding great promise for highly integrated device applications. Lastly, an atomically thin p–n junction is fabricated by the as-prepared MoS 2, which shows strong rectifying behavior.« less

Perturbative treatment of spin-orbit-coupling within spin-free exact two-component theory using equation-of-motion coupled-cluster methods

NASA Astrophysics Data System (ADS)

Cheng, Lan; Wang, Fan; Stanton, John F.; Gauss, Jürgen

2018-01-01

A scheme is reported for the perturbative calculation of spin-orbit coupling (SOC) within the spin-free exact two-component theory in its one-electron variant (SFX2C-1e) in combination with the equation-of-motion coupled-cluster singles and doubles method. Benchmark calculations of the spin-orbit splittings in 2Π and 2P radicals show that the accurate inclusion of scalar-relativistic effects using the SFX2C-1e scheme extends the applicability of the perturbative treatment of SOC to molecules that contain heavy elements. The contributions from relaxation of the coupled-cluster amplitudes are shown to be relatively small; significant contributions from correlating the inner-core orbitals are observed in calculations involving third-row and heavier elements. The calculation of term energies for the low-lying electronic states of the PtH radical, which serves to exemplify heavy transition-metal containing systems, further demonstrates the quality that can be achieved with the pragmatic approach presented here.

Role of excess ligand and effect of thermal treatment in hybrid inorganic-organic EUV resists

NASA Astrophysics Data System (ADS)

Mattson, Eric C.; Rupich, Sara M.; Cabrera, Yasiel; Chabal, Yves J.

2018-03-01

The chemical structure and thermal reactivity of recently discovered inorganic-organic hybrid resist materials are characterized using a combination of in situ and ex situ infrared (IR) spectroscopy and x-ray photoemission spectroscopy (XPS). The materials are comprised of a small HfOx core capped with methacrylic acid ligands that form a combined hybrid cluster, HfMAA. The observed IR modes are consistent with the calculated modes predicted from the previously determined x-ray crystal structure of the HfMAA-12 cluster, but also contain extrinsic hydroxyl groups. We find that the water content of the films is dependent on the concentration of excess ligand added to the solution. The effect of environment used during post-application baking (PAB) is studied and correlated to changes in solubility of the films. In doing so, we find that hydroxylation of the clusters results in formation of additional Hf-O-Hf linkages upon heating, which in turn impacts the solubility of the films.

Construction of Hyaluronic Tetrasaccharide Clusters Modified Polyamidoamine siRNA Delivery System.

PubMed

Ma, Yingcong; Sha, Meng; Cheng, Shixuan; Yao, Wang; Li, Zhongjun; Qi, Xian-Rong

2018-06-14

The CD44 protein, as a predominant receptor for hyaluronan (HA), is highly expressed on the surface of multiple tumor cells. HA, as a targeting molecule for a CD44-contained delivery system, increases intracellular drug concentration in tumor tissue. However, due to the weak binding ability of hyaluronan oligosaccharide to CD44, targeting for tumor drug delivery has been restricted. In this study, we first use a HA tetrasaccharide cluster as the target ligand to enhance the binding ability to CD44. A polyamidoamine (PAMAM) dendrimer was modified by a HA tetrasaccharide cluster as a nonviral vector for small interfering RNA (siRNA) delivery. The dendrimer/siRNA nanocomplexes increased the cellular uptake capacity of siRNA through the CD44 receptor-mediated endocytosis pathway, allowing the siRNA to successfully escape the endosome/lysosome. Compared with the control group, nanocomplexes effectively reduced the expression of GFP protein and mRNA in MDA-MB-231-GFP cells. This delivery system provides a foundation to increase the clinical applications of PAMAM nanomaterials.

Two-component density functional theory calculations of positron lifetimes for small vacancy clusters in silicon

NASA Astrophysics Data System (ADS)

Makhov, D. V.; Lewis, Laurent J.

2005-05-01

The positron lifetimes for various vacancy clusters in silicon are calculated within the framework of the two-component electron-positron density functional theory. The effect of the trapped positron on the electron density and on the relaxation of the structure is investigated. Our calculations show that, contrary to the usual assumption, the positron-induced forces do not compensate in general for electronic inward forces. Thus, geometry optimization is required in order to determine positron lifetime accurately. For the monovacancy and the divacancy, the results of our calculations are in good agreement with the experimental positron lifetimes, suggesting that this approach gives good estimates of positron lifetimes for larger vacancy clusters, required for their correct identification with positron annihilation spectroscopy. As an application, our calculations show that fourfold trivacancies and symmetric fourfold tetravacancies have positron lifetimes similar to monovacancies and divacancies, respectively, and can thus be confused in the interpretation of positron annihilation experiments.

Stability and minimum size of colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2012-02-01

A vertical force applied to each of two colloids, trapped at a liquid-air interface, induces their logarithmic pairwise attraction. I recently showed [Phys. Rev. E 79, 011407 (2009)] that in clusters of size R much larger than the capillary length λ, the attraction changes to that of a power law and is much stronger due to a many-body effect, and I derived two equations that describe the equilibrium coarse-grained meniscus profile and colloid density in such clusters. In this paper, this theory is shown also to describe small clusters with R≪ λ provided the number N of colloids therein is sufficiently large. An analytical solution for a small circular cluster with an arbitrary short-range power-law pairwise repulsion is found. The energy of a cluster is obtained as a function of its radius R and colloid number N. As in large clusters, the attraction force and energy universally scale with the distance L between colloids as L(-3) and L(-2), respectively, for any repulsion forces. The states of an equilibrium cluster, predicted by the theory, are shown to be stable with respect to small perturbations of the meniscus profile and colloid density. The minimum number of colloids in a circular cluster, which sustains the thermal motion, is estimated. For standard parameters, it can be very modest, e.g., in the range 20-200, which is in line with experimental findings on reversible clusterization on a liquid-air interface. © 2012 American Physical Society

Small traveling clusters in attractive and repulsive Hamiltonian mean-field models.

PubMed

Barré, Julien; Yamaguchi, Yoshiyuki Y

2009-03-01

Long-lasting small traveling clusters are studied in the Hamiltonian mean-field model by comparing between attractive and repulsive interactions. Nonlinear Landau damping theory predicts that a Gaussian momentum distribution on a spatially homogeneous background permits the existence of traveling clusters in the repulsive case, as in plasma systems, but not in the attractive case. Nevertheless, extending the analysis to a two-parameter family of momentum distributions of Fermi-Dirac type, we theoretically predict the existence of traveling clusters in the attractive case; these findings are confirmed by direct N -body numerical simulations. The parameter region with the traveling clusters is much reduced in the attractive case with respect to the repulsive case.

A Genetic Algorithm That Exchanges Neighboring Centers for Fuzzy c-Means Clustering

ERIC Educational Resources Information Center

Chahine, Firas Safwan

2012-01-01

Clustering algorithms are widely used in pattern recognition and data mining applications. Due to their computational efficiency, partitional clustering algorithms are better suited for applications with large datasets than hierarchical clustering algorithms. K-means is among the most popular partitional clustering algorithm, but has a major…

ClusterCAD: a computational platform for type I modular polyketide synthase design

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

Eng, Clara H.; Backman, Tyler W H; Bailey, Constance B.

Here, we present ClusterCAD, a web-based toolkit designed to leverage the collinear structure and deterministic logic of type I modular polyketide synthases (PKSs) for synthetic biology applications. The unique organization of these megasynthases, combined with the diversity of their catalytic domain building blocks, has fueled an interest in harnessing the biosynthetic potential of PKSs for the microbial production of both novel natural product analogs and industrially relevant small molecules. However, a limited theoretical understanding of the determinants of PKS fold and function poses a substantial barrier to the design of active variants, and identifying strategies to reliably construct functional PKSmore » chimeras remains an active area of research. In this work, we formalize a paradigm for the design of PKS chimeras and introduce ClusterCAD as a computational platform to streamline and simplify the process of designing experiments to test strategies for engineering PKS variants. ClusterCAD provides chemical structures with stereochemistry for the intermediates generated by each PKS module, as well as sequence- and structure-based search tools that allow users to identify modules based either on amino acid sequence or on the chemical structure of the cognate polyketide intermediate. ClusterCAD can be accessed at https://clustercad.jbei.org and at http://clustercad.igb.uci.edu.« less

Bonding properties of FCC-like Au 44 (SR) 28 clusters from X-ray absorption spectroscopy

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

Yang, Rui; Chevrier, Daniel M.; Zeng, Chenjie

Thiolate-protected gold clusters with precisely controlled atomic composition have recently emerged as promising candidates for a variety of applications because of their unique optical, electronic, and catalytic properties. The recent discovery of the Au44(SR)28 total structure is considered as an interesting finding in terms of the face-centered cubic (FCC)-like core structure in small gold-thiolate clusters. Herein, the unique bonding properties of Au44(SR)28 is analyzed using temperature-dependent X-ray absorption spectroscopy (XAS) measurements at the Au L3-edge and compared with other FCC-like clusters such as Au36(SR)24 and Au28(SR)20. A negative thermal expansion was detected for the Au–Au bonds of the metal coremore » (the first Au–Au shell) and was interpreted based on the unique Au core structure consisting of the Au4 units. EXAFS fitting results from Au28(SR)20, Au36(SR)24, and Au44(SR)28 show a size-dependent negative thermal expansion behavior in the first Au–Au shell, further highlighting the importance of the Au4 units in determining the Au core bonding properties and shedding light on the growth mechanism of these FCC-like Au clusters.« less

Tuning electronic and magnetic properties of Mn-mullite oxide sub-nanoclusters via MnOn polyhedron units.

PubMed

Li, Hui; Cho, Kyeongjae; Li, Shunfang; Wang, Weichao

2018-06-13

Ternary oxide nano-clusters compared to unary metallic and binary ones potentially exhibit more remarkable properties due to their higher stoichiometric flexibility in addition to cluster size variations. Herein, by combining with the structural searching scheme CALYPSO, we have built a series of Mn-mullite oxide clusters (SmxMnyOz)n {(xyz) = (125); (115); n = 1-4, 8} prior to investigation of their geometric and electronic structures via first-principles calculations. In small size regime (n < 4), (SmxMnyOz)n prefer nonstoichiometric (Sm1Mn1O5)n phases composed of nonmagnetic MnO4 tetrahedrons. When n ≧ 4, the clusters tend to develop as stoichiometric (Sm1Mn2O5)n species, including magnetic MnOn polyhedrons and Mn-Mn dimers, which contribute 3d-orbitals (dz2 and/or dx2-y2) around the Fermi levels. The different magnetic behaviors of nonstoichiometric and stoichiometric species originate from the distinct couplings of MnOn polyhedronal units, wherein Mn atoms experience different ligand fields and thus display different spin states. Such findings enable the tuning of electronic properties and potential applications in heterogeneous catalysis, electrochemical catalysis, and the related fields via engineering cluster size and stoichiometry.

ClusterCAD: a computational platform for type I modular polyketide synthase design

DOE PAGES

Eng, Clara H.; Backman, Tyler W H; Bailey, Constance B.; ...

2017-10-11

Here, we present ClusterCAD, a web-based toolkit designed to leverage the collinear structure and deterministic logic of type I modular polyketide synthases (PKSs) for synthetic biology applications. The unique organization of these megasynthases, combined with the diversity of their catalytic domain building blocks, has fueled an interest in harnessing the biosynthetic potential of PKSs for the microbial production of both novel natural product analogs and industrially relevant small molecules. However, a limited theoretical understanding of the determinants of PKS fold and function poses a substantial barrier to the design of active variants, and identifying strategies to reliably construct functional PKSmore » chimeras remains an active area of research. In this work, we formalize a paradigm for the design of PKS chimeras and introduce ClusterCAD as a computational platform to streamline and simplify the process of designing experiments to test strategies for engineering PKS variants. ClusterCAD provides chemical structures with stereochemistry for the intermediates generated by each PKS module, as well as sequence- and structure-based search tools that allow users to identify modules based either on amino acid sequence or on the chemical structure of the cognate polyketide intermediate. ClusterCAD can be accessed at https://clustercad.jbei.org and at http://clustercad.igb.uci.edu.« less

Cherry-picking functionally relevant substates from long md trajectories using a stratified sampling approach.

PubMed

Chandramouli, Balasubramanian; Mancini, Giordano

2016-01-01

Classical Molecular Dynamics (MD) simulations can provide insights at the nanoscopic scale into protein dynamics. Currently, simulations of large proteins and complexes can be routinely carried out in the ns-μs time regime. Clustering of MD trajectories is often performed to identify selective conformations and to compare simulation and experimental data coming from different sources on closely related systems. However, clustering techniques are usually applied without a careful validation of results and benchmark studies involving the application of different algorithms to MD data often deal with relatively small peptides instead of average or large proteins; finally clustering is often applied as a means to analyze refined data and also as a way to simplify further analysis of trajectories. Herein, we propose a strategy to classify MD data while carefully benchmarking the performance of clustering algorithms and internal validation criteria for such methods. We demonstrate the method on two showcase systems with different features, and compare the classification of trajectories in real and PCA space. We posit that the prototype procedure adopted here could be highly fruitful in clustering large trajectories of multiple systems or that resulting especially from enhanced sampling techniques like replica exchange simulations. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.

Theoretical and experimental insights into the origin of the catalytic activity of subnanometric gold clusters: attempts to predict reactivity with clusters and nanoparticles of gold.

PubMed

Boronat, Mercedes; Leyva-Pérez, Antonio; Corma, Avelino

2014-03-18

Particle size is one of the key parameters determining the unexpected catalytic activity of gold, with reactivity improving as the particle gets smaller. While this is valid in the 1-5 nm range, chemists are now investigating the influence of particle size in the subnanometer regime. This is due to recent advances in both characterization techniques and synthetic routes capable of stabilizing these size-controlled gold clusters. Researchers reported in early studies that small clusters or aggregates of a few atoms can be extremely active in some reactions, while 1-2 nm nanoparticles are catalytically more efficient for other reactions. Furthermore, the possibility that small gold clusters generated in situ from gold salts or complexes could be the real active species in homogeneous gold-catalyzed organic reactions should be considered. In this Account, we address two questions. First, what is the origin of the enhanced reactivity of gold clusters on the subnanometer scale? And second, how can we predict the reactions where small clusters should work better than larger nanoparticles? Both geometric factors and electronic or quantum size effects become important in the subnanometer regime. Geometric reasons play a key role in hydrogenation reactions, where only accessible low coordinated neutral Au atoms are needed to dissociate H2. The quantum size effects of gold clusters are important as well, as clusters formed by only a few atoms have discrete molecule-like electronic states and their chemical reactivity is related to interactions between the cluster's frontier molecular orbitals and those of the reactant molecules. From first principles calculations, we predict an enhanced reactivity of small planar clusters for reactions involving activation of CC multiple bonds in alkenes and alkynes through Lewis acid-base interactions, and a better catalytic performance of 3D gold nanoparticles in redox reactions involving bond dissociation by oxidative addition and new bond formation by reductive elimination. In oxidation reactions with molecular O2, initial dissociation of O2 into basic oxygen atoms would be more effectively catalyzed by gold nanoparticles of ∼1 nm diameter. In contrast, small planar clusters should be more active for reactions following a radical pathway involving peroxo or hydroperoxo intermediates. We have experimentally confirmed these predictions for a series of Lewis acid and oxidation reactions catalyzed by gold clusters and nanoparticles either in solution or supported on solid carriers.

Cluster Free Energies from Simple Simulations of Small Numbers of Aggregants: Nucleation of Liquid MTBE from Vapor and Aqueous Phases.

PubMed

Patel, Lara A; Kindt, James T

2017-03-14

We introduce a global fitting analysis method to obtain free energies of association of noncovalent molecular clusters using equilibrated cluster size distributions from unbiased constant-temperature molecular dynamics (MD) simulations. Because the systems simulated are small enough that the law of mass action does not describe the aggregation statistics, the method relies on iteratively determining a set of cluster free energies that, using appropriately weighted sums over all possible partitions of N monomers into clusters, produces the best-fit size distribution. The quality of these fits can be used as an objective measure of self-consistency to optimize the cutoff distance that determines how clusters are defined. To showcase the method, we have simulated a united-atom model of methyl tert-butyl ether (MTBE) in the vapor phase and in explicit water solution over a range of system sizes (up to 95 MTBE in the vapor phase and 60 MTBE in the aqueous phase) and concentrations at 273 K. The resulting size-dependent cluster free energy functions follow a form derived from classical nucleation theory (CNT) quite well over the full range of cluster sizes, although deviations are more pronounced for small cluster sizes. The CNT fit to cluster free energies yielded surface tensions that were in both cases lower than those for the simulated planar interfaces. We use a simple model to derive a condition for minimizing non-ideal effects on cluster size distributions and show that the cutoff distance that yields the best global fit is consistent with this condition.

Delivery of Iron-Sulfur Clusters to the Hydrogen-Oxidizing [NiFe]-Hydrogenases in Escherichia coli Requires the A-Type Carrier Proteins ErpA and IscA

PubMed Central

Pinske, Constanze; Sawers, R. Gary

2012-01-01

During anaerobic growth Escherichia coli synthesizes two membrane-associated hydrogen-oxidizing [NiFe]-hydrogenases, termed hydrogenase 1 and hydrogenase 2. Each enzyme comprises a catalytic subunit containing the [NiFe] cofactor, an electron-transferring small subunit with a particular complement of [Fe-S] (iron-sulfur) clusters and a membrane-anchor subunit. How the [Fe-S] clusters are delivered to the small subunit of these enzymes is unclear. A-type carrier (ATC) proteins of the Isc (iron-sulfur-cluster) and Suf (sulfur mobilization) [Fe-S] cluster biogenesis pathways are proposed to traffic pre-formed [Fe-S] clusters to apoprotein targets. Mutants that could not synthesize SufA had active hydrogenase 1 and hydrogenase 2 enzymes, thus demonstrating that the Suf machinery is not required for hydrogenase maturation. In contrast, mutants devoid of the IscA, ErpA or IscU proteins of the Isc machinery had no detectable hydrogenase 1 or 2 activities. Lack of activity of both enzymes correlated with the absence of the respective [Fe-S]-cluster-containing small subunit, which was apparently rapidly degraded. During biosynthesis the hydrogenase large subunits receive their [NiFe] cofactor from the Hyp maturation machinery. Subsequent to cofactor insertion a specific C-terminal processing step occurs before association of the large subunit with the small subunit. This processing step is independent of small subunit maturation. Using western blotting experiments it could be shown that although the amount of each hydrogenase large subunit was strongly reduced in the iscA and erpA mutants, some maturation of the large subunit still occurred. Moreover, in contrast to the situation in Isc-proficient strains, these processed large subunits were not membrane-associated. Taken together, our findings demonstrate that both IscA and ErpA are required for [Fe-S] cluster delivery to the small subunits of the hydrogen-oxidizing hydrogenases; however, delivery of the Fe atom to the active site might have different requirements. PMID:22363723

The Gap Procedure: for the identification of phylogenetic clusters in HIV-1 sequence data.

PubMed

Vrbik, Irene; Stephens, David A; Roger, Michel; Brenner, Bluma G

2015-11-04

In the context of infectious disease, sequence clustering can be used to provide important insights into the dynamics of transmission. Cluster analysis is usually performed using a phylogenetic approach whereby clusters are assigned on the basis of sufficiently small genetic distances and high bootstrap support (or posterior probabilities). The computational burden involved in this phylogenetic threshold approach is a major drawback, especially when a large number of sequences are being considered. In addition, this method requires a skilled user to specify the appropriate threshold values which may vary widely depending on the application. This paper presents the Gap Procedure, a distance-based clustering algorithm for the classification of DNA sequences sampled from individuals infected with the human immunodeficiency virus type 1 (HIV-1). Our heuristic algorithm bypasses the need for phylogenetic reconstruction, thereby supporting the quick analysis of large genetic data sets. Moreover, this fully automated procedure relies on data-driven gaps in sorted pairwise distances to infer clusters, thus no user-specified threshold values are required. The clustering results obtained by the Gap Procedure on both real and simulated data, closely agree with those found using the threshold approach, while only requiring a fraction of the time to complete the analysis. Apart from the dramatic gains in computational time, the Gap Procedure is highly effective in finding distinct groups of genetically similar sequences and obviates the need for subjective user-specified values. The clusters of genetically similar sequences returned by this procedure can be used to detect patterns in HIV-1 transmission and thereby aid in the prevention, treatment and containment of the disease.

Advanced Electrochemistry of Individual Metal Clusters Electrodeposited Atom by Atom to Nanometer by Nanometer.

PubMed

Kim, Jiyeon; Dick, Jeffrey E; Bard, Allen J

2016-11-15

Metal clusters are very important as building blocks for nanoparticles (NPs) for electrocatalysis and electroanalysis in both fundamental and applied electrochemistry. Attention has been given to understanding of traditional nucleation and growth of metal clusters and to their catalytic activities for various electrochemical applications in energy harvesting as well as analytical sensing. Importantly, understanding the properties of these clusters, primarily the relationship between catalysis and morphology, is required to optimize catalytic function. This has been difficult due to the heterogeneities in the size, shape, and surface properties. Thus, methods that address these issues are necessary to begin understanding the reactivity of individual catalytic centers as opposed to ensemble measurements, where the effect of size and morphology on the catalysis is averaged out in the measurement. This Account introduces our advanced electrochemical approaches to focus on each isolated metal cluster, where we electrochemically fabricated clusters or NPs atom by atom to nanometer by nanometer and explored their electrochemistry for their kinetic and catalytic behavior. Such approaches expand the dimensions of analysis, to include the electrochemistry of (1) a discrete atomic cluster, (2) solely a single NP, or (3) individual NPs in the ensemble sample. Specifically, we studied the electrocatalysis of atomic metal clusters as a nascent electrocatalyst via direct electrodeposition on carbon ultramicroelectrode (C UME) in a femtomolar metal ion precursor. In addition, we developed tunneling ultramicroelectrodes (TUMEs) to study electron transfer (ET) kinetics of a redox probe at a single metal NP electrodeposited on this TUME. Owing to the small dimension of a NP as an active area of a TUME, extremely high mass transfer conditions yielded a remarkably high standard ET rate constant, k 0 , of 36 cm/s for outer-sphere ET reaction. Most recently, we advanced nanoscale scanning electrochemical microscopy (SECM) imaging to resolve the electrocatalytic activity of individual electrodeposited NPs within an ensemble sample yielding consistent high k 0 values of ≥2 cm/s for the hydrogen oxidation reaction (HOR) at different NPs. We envision that our advanced electrochemical approaches will enable us to systematically address structure effects on the catalytic activity, thus providing a quantitative guideline for electrocatalysts in energy-related applications.

Magnetic nanostructures.

PubMed

Bennemann, K

2010-06-23

Characteristic results of magnetism in small particles, thin films and tunnel junctions are presented. As a consequence of the reduced atomic coordination in small clusters and thin films the electronic states and density of states are modified. Thus, magnetic moments and magnetization are affected. Generally, in clusters and thin films magnetic anisotropy plays a special role. In tunnel junctions the interplay of magnetism, spin currents and superconductivity are of particular interest. In ring-like mesoscopic systems Aharonov-Bohm-induced currents are studied. Results are given for single transition metal clusters, cluster ensembles, thin films, mesoscopic structures and tunnel systems. © 2010 IOP Publishing Ltd

Analysis of radiation-induced small Cu particle cluster formation in aqueous CuCl2

USGS Publications Warehouse

Jayanetti, Sumedha; Mayanovic, Robert A.; Anderson, Alan J.; Bassett, William A.; Chou, I.-Ming

2001-01-01

Radition-induced small Cu particle cluster formation in aqueous CuCl2 was analyzed. It was noticed that nearest neighbor distance increased with the increase in the time of irradiation. This showed that the clusters approached the lattice dimension of bulk copper. As the average cluster size approached its bulk dimensions, an increase in the nearest neighbor coordination number was found with the decrease in the surface to volume ratio. Radiolysis of water by incident x-ray beam led to the reduction of copper ions in the solution to themetallic state.

Manganese ferrite nanoparticle micellar nanocomposites as MRI contrast agent for liver imaging.

PubMed

Lu, Jian; Ma, Shuli; Sun, Jiayu; Xia, Chunchao; Liu, Chen; Wang, Zhiyong; Zhao, Xuna; Gao, Fabao; Gong, Qiyong; Song, Bin; Shuai, Xintao; Ai, Hua; Gu, Zhongwei

2009-05-01

Iron oxide nanoparticles are effective contrast agents for enhancement of magnetic resonance imaging at tissue, cellular or even molecular levels. In this study, manganese doped superparamagnetic iron oxide (Mn-SPIO) nanoparticles were used to form ultrasensitive MRI contrast agents for liver imaging. Hydrophobic Mn-SPIO nanoparticles are synthesized in organic phase and then transferred into water with the help of block copolymer mPEG-b-PCL. These Mn-SPIO nanoparticles are self-assembled into small clusters (mean diameter approximately 80nm) inside micelles as revealed by transmission electron microscopy. Mn-SPIO nanoparticles inside micelles decrease PCL crystallization temperatures, as verified from differential scanning calorimetry and Fourier transform infrared spectroscopy. The Mn-SPIO based nanocomposites are superparamagnetic at room temperature. At the magnetic field of 1.5T, Mn-SPIO nanoparticle clustering micelles have a T(2) relaxivity of 270 (Mn+Fe)mM(-1)s(-1), which is much higher than single Mn-SPIO nanoparticle containing lipid-PEG micelles. This clustered nanocomposite has brought significant liver contrast with signal intensity changes of -80% at 5min after intravenous administration. The time window for enhanced-MRI can last about 36h with obvious contrast on liver images. This sensitive MRI contrast agent may find applications in identification of small liver lesions, evaluation of the degree of liver cirrhosis, and differential diagnosis of other liver diseases.

Monogenetic Volcano Clusters within the wider Michoacán-Guanajuato Volcanic Field (México) and their Significance

NASA Astrophysics Data System (ADS)

Siebe, C.

2017-12-01

The Trans-Mexican Volcanic Belt, one of the most complex and active continental arcs worldwide, displays several volcanic fields dominated by monogenetic volcanoes. Of these, the Plio-Quaternary Michoacán-Guanajuato Volcanic Field (MGVF) situated in central Mexico, is the largest monogenetic volcanic field in the world and includes more than 1000 scoria cones and associated lava flows and about 400 medium-sized volcanoes (Mexican shields). The smaller monogenetic vents occur either isolated or form small clusters within the wider MGVF. The recent identification of small clusters comprising several monogenetic volcanoes that erupted in a sequence of geologically short time intervals (hundreds to few thousands of years) in small areas within the much wider MGVF opens several questions in regard to future volcanic hazard assessments in this region: Are the youngest (Holocene) clusters still "active" and is a new eruption likely to occur within their surroundings? How long are such clusters "active"? Will the next monogenetic eruption in the MGVF be a single short-lived isolated eruption, or the beginning of a cluster? Furthermore, is it possible that the historic eruptions of Jorullo (1759) and Paricutin (1943) represent each the beginning of a cluster and should a new eruption in their proximity be expected in the future? In order to address these questions, two Holocene clusters, namely Tacámbaro and Malpaís de Zacapu are currently under study and preliminary results will be presented. Each comprises four monogenetic vents that erupted in a sequence of geologically short time intervals (hundreds to few thousands of years) within a small area (few tens of km2) Geologic mapping, geochemical analyses, radiometric dating, and paleomagnetic studies will help to establish the sequence of eruption of the different vents, and shed more light on the conditions that allow several magma sources to be formed and then tapped in close temporal and spatial proximity to each other and produce such small "flare-ups".

Cluster size dependence of high-order harmonic generation

NASA Astrophysics Data System (ADS)

Tao, Y.; Hagmeijer, R.; Bastiaens, H. M. J.; Goh, S. J.; van der Slot, P. J. M.; Biedron, S. G.; Milton, S. V.; Boller, K.-J.

2017-08-01

We investigate high-order harmonic generation (HHG) from noble gas clusters in a supersonic gas jet. To identify the contribution of harmonic generation from clusters versus that from gas monomers, we measure the high-order harmonic output over a broad range of the total atomic number density in the jet (from 3×1016 to 3 × 1018 {{cm}}-3) at two different reservoir temperatures (303 and 363 K). For the first time in the evaluation of the harmonic yield in such measurements, the variation of the liquid mass fraction, g, versus pressure and temperature is taken into consideration, which we determine, reliably and consistently, to be below 20% within our range of experimental parameters. By comparing the measured harmonic yield from a thin jet with the calculated corresponding yield from monomers alone, we find an increased emission of the harmonics when the average cluster size is less than 3000. Using g, under the assumption that the emission from monomers and clusters add up coherently, we calculate the ratio of the average single-atom response of an atom within a cluster to that of a monomer and find an enhancement of around 100 for very small average cluster size (∼200). We do not find any dependence of the cut-off frequency on the composition of the cluster jet. This implies that HHG in clusters is based on electrons that return to their parent ions and not to neighboring ions in the cluster. To fully employ the enhanced average single-atom response found for small average cluster sizes (∼200), the nozzle producing the cluster jet must provide a large liquid mass fraction at these small cluster sizes for increasing the harmonic yield. Moreover, cluster jets may allow for quasi-phase matching, as the higher mass of clusters allows for a higher density contrast in spatially structuring the nonlinear medium.

Tantalum induced butterfly-like clusters on Si (111)-7 × 7 surface: STM/STS study at low coverage

NASA Astrophysics Data System (ADS)

Shukrynau, Pavel; Mutombo, Pingo; Švec, Martin; Hietschold, Michael; Cháb, Vladimír

2012-02-01

The adsorption of the small amounts of tantalum on Si (111)-7 × 7 reconstructed surface is investigated systematically using scanning tunneling microscopy and tunneling spectroscopy combined with first-principles density functional theory calculations. We find out that the moderate annealing of the Ta covered surface results in the formation of clusters of the butterfly-like shape. The clusters are sporadically distributed over the surface and their density is metal coverage dependent. Filled and empty state STM images of the clusters differ strongly suggesting the existence of covalent bonds within the cluster. Tunneling spectroscopy measurements reveal small energy gap, showing semiconductor-like behavior of the constituent atoms. The cluster model based on experimental images and theoretical calculations has been proposed and discussed. Presented results show that Ta joins the family of adsorbates, that are known to form magic clusters on Si (111)-7 × 7, but its magic cluster has the structural and electronic properties that are different from those reported before.

Detecting grizzly bear use of ungulate carcasses using global positioning system telemetry and activity data

USGS Publications Warehouse

Ebinger, Michael R.; Haroldson, Mark A.; van Manen, Frank T.; Costello, Cecily M.; Bjornlie, Daniel D.; Thompson, Daniel J.; Gunther, Kerry A.; Fortin, Jennifer K.; Teisberg, Justin E.; Pils, Shannon R; White, P J; Cain, Steven L.; Cross, Paul C.

2016-01-01

Global positioning system (GPS) wildlife collars have revolutionized wildlife research. Studies of predation by free-ranging carnivores have particularly benefited from the application of location clustering algorithms to determine when and where predation events occur. These studies have changed our understanding of large carnivore behavior, but the gains have concentrated on obligate carnivores. Facultative carnivores, such as grizzly/brown bears (Ursus arctos), exhibit a variety of behaviors that can lead to the formation of GPS clusters. We combined clustering techniques with field site investigations of grizzly bear GPS locations (n = 732 site investigations; 2004–2011) to produce 174 GPS clusters where documented behavior was partitioned into five classes (large-biomass carcass, small-biomass carcass, old carcass, non-carcass activity, and resting). We used multinomial logistic regression to predict the probability of clusters belonging to each class. Two cross-validation methods—leaving out individual clusters, or leaving out individual bears—showed that correct prediction of bear visitation to large-biomass carcasses was 78–88%, whereas the false-positive rate was 18–24%. As a case study, we applied our predictive model to a GPS data set of 266 bear-years in the Greater Yellowstone Ecosystem (2002–2011) and examined trends in carcass visitation during fall hyperphagia (September–October). We identified 1997 spatial GPS clusters, of which 347 were predicted to be large-biomass carcasses. We used the clustered data to develop a carcass visitation index, which varied annually, but more than doubled during the study period. Our study demonstrates the effectiveness and utility of identifying GPS clusters associated with carcass visitation by a facultative carnivore.

Detecting grizzly bear use of ungulate carcasses using global positioning system telemetry and activity data.

PubMed

Ebinger, Michael R; Haroldson, Mark A; van Manen, Frank T; Costello, Cecily M; Bjornlie, Daniel D; Thompson, Daniel J; Gunther, Kerry A; Fortin, Jennifer K; Teisberg, Justin E; Pils, Shannon R; White, P J; Cain, Steven L; Cross, Paul C

2016-07-01

Global positioning system (GPS) wildlife collars have revolutionized wildlife research. Studies of predation by free-ranging carnivores have particularly benefited from the application of location clustering algorithms to determine when and where predation events occur. These studies have changed our understanding of large carnivore behavior, but the gains have concentrated on obligate carnivores. Facultative carnivores, such as grizzly/brown bears (Ursus arctos), exhibit a variety of behaviors that can lead to the formation of GPS clusters. We combined clustering techniques with field site investigations of grizzly bear GPS locations (n = 732 site investigations; 2004-2011) to produce 174 GPS clusters where documented behavior was partitioned into five classes (large-biomass carcass, small-biomass carcass, old carcass, non-carcass activity, and resting). We used multinomial logistic regression to predict the probability of clusters belonging to each class. Two cross-validation methods-leaving out individual clusters, or leaving out individual bears-showed that correct prediction of bear visitation to large-biomass carcasses was 78-88 %, whereas the false-positive rate was 18-24 %. As a case study, we applied our predictive model to a GPS data set of 266 bear-years in the Greater Yellowstone Ecosystem (2002-2011) and examined trends in carcass visitation during fall hyperphagia (September-October). We identified 1997 spatial GPS clusters, of which 347 were predicted to be large-biomass carcasses. We used the clustered data to develop a carcass visitation index, which varied annually, but more than doubled during the study period. Our study demonstrates the effectiveness and utility of identifying GPS clusters associated with carcass visitation by a facultative carnivore.

The preparation and characterization of novel Pt/C electrocatalysts with controlled porosity and cluster size

DOE PAGES

Coker, Eric N.; Steen, William A.; Miller, Jeffrey T.; ...

2007-05-23

Small platinum clusters have been prepared in zeolite hosts through ion exchange and controlled calcination/reduction processes. In order to enable electrochemical application, the pores of the Pt-zeolite were filled with electrically conductive carbon via infiltration with carbon precursors, polymerization, and pyrolysis. The zeolite host was then removed by acid washing, to leave a Pt/C electrocatalyst possessing quasi-zeolitic porosity and Pt clusters of well-controlled size. The electrocatalysts were characterized by TEM, XRD, EXAFS, nitrogen adsorption and electrochemical techniques. Depending on the synthesis conditions, average Pt cluster sizes in the Pt/C catalysts ranged from 1.3 to 2.0 nm. The presence of orderedmore » porosity/structure in the catalysts was evident in TEM images as lattice fringes, and in XRD as a low-angle diffraction peak with d-spacing similar to the parent zeolite. The catalysts possess micro- and meso-porosity, with pore size distributions that depend upon synthesis variables. Finally, electroactive surface areas as high as 112 m 2 g Pt -1 have been achieved in Pt/C electrocatalysts which show oxygen reduction performance comparable to standard industrial catalysts.« less

Local Higher-Order Graph Clustering

PubMed Central

Yin, Hao; Benson, Austin R.; Leskovec, Jure; Gleich, David F.

2018-01-01

Local graph clustering methods aim to find a cluster of nodes by exploring a small region of the graph. These methods are attractive because they enable targeted clustering around a given seed node and are faster than traditional global graph clustering methods because their runtime does not depend on the size of the input graph. However, current local graph partitioning methods are not designed to account for the higher-order structures crucial to the network, nor can they effectively handle directed networks. Here we introduce a new class of local graph clustering methods that address these issues by incorporating higher-order network information captured by small subgraphs, also called network motifs. We develop the Motif-based Approximate Personalized PageRank (MAPPR) algorithm that finds clusters containing a seed node with minimal motif conductance, a generalization of the conductance metric for network motifs. We generalize existing theory to prove the fast running time (independent of the size of the graph) and obtain theoretical guarantees on the cluster quality (in terms of motif conductance). We also develop a theory of node neighborhoods for finding sets that have small motif conductance, and apply these results to the case of finding good seed nodes to use as input to the MAPPR algorithm. Experimental validation on community detection tasks in both synthetic and real-world networks, shows that our new framework MAPPR outperforms the current edge-based personalized PageRank methodology. PMID:29770258

Cost/Performance Ratio Achieved by Using a Commodity-Based Cluster

NASA Technical Reports Server (NTRS)

Lopez, Isaac

2001-01-01

Researchers at the NASA Glenn Research Center acquired a commodity cluster based on Intel Corporation processors to compare its performance with a traditional UNIX cluster in the execution of aeropropulsion applications. Since the cost differential of the clusters was significant, a cost/performance ratio was calculated. After executing a propulsion application on both clusters, the researchers demonstrated a 9.4 cost/performance ratio in favor of the Intel-based cluster. These researchers utilize the Aeroshark cluster as one of the primary testbeds for developing NPSS parallel application codes and system software. The Aero-shark cluster provides 64 Intel Pentium II 400-MHz processors, housed in 32 nodes. Recently, APNASA - a code developed by a Government/industry team for the design and analysis of turbomachinery systems was used for a simulation on Glenn's Aeroshark cluster.

Tuberculosis outbreaks predicted by characteristics of first patients in a DNA fingerprint cluster.

PubMed

Kik, Sandra V; Verver, Suzanne; van Soolingen, Dick; de Haas, Petra E W; Cobelens, Frank G; Kremer, Kristin; van Deutekom, Henk; Borgdorff, Martien W

2008-07-01

Some clusters of patients who have Mycobacterium tuberculosis isolates with identical DNA fingerprint patterns grow faster than others. It is unclear what predictors determine cluster growth. To assess whether the development of a tuberculosis (TB) outbreak can be predicted by the characteristics of its first two patients. Demographic and clinical data of all culture-confirmed patients with TB in the Netherlands from 1993 through 2004 were combined with DNA fingerprint data. Clusters were restricted to cluster episodes of 2 years to only detect newly arising clusters. Characteristics of the first two patients were compared between small (2-4 cases) and large (5 or more cases) cluster episodes. Of 5,454 clustered cases, 1,756 (32%) were part of a cluster episode of 2 years. Of 622 cluster episodes, 54 (9%) were large and 568 (91%) were small episodes. Independent predictors for large cluster episodes were as follows: less than 3 months' time between the diagnosis of the first two patients, one or both patients were young (<35 yr), both patients lived in an urban area, and both patients came from sub-Saharan Africa. In the Netherlands, patients in new cluster episodes should be screened for these risk factors. When the risk pattern applies, targeted interventions (e.g., intensified contact investigation) should be considered to prevent further cluster expansion.

Automatic Segmentation of Granular Objects in Images: Combining Local Density Clustering and Gradient-Barrier Watershed

DTIC Science & Technology

2014-01-01

in applications, such as the recognition of biological cells [12,17], cell nuclei [8–10], colonies, and pollen [34,35], as well as nanoparticles [6... pollen image shown in Fig. 8, we see that two pollen grains on the upper-right are merged in the gradient-weighted distance trans- form watershed...10.1016/j.patcog.2013.11.004i images, pollen images, as well as physical nanoparticle images. This is only a small selection of this approach’s

Analysis of the electron density features of small boron clusters and the effects of doping with C, P, Al, Si, and Zn: Magic B7P and B8Si clusters

NASA Astrophysics Data System (ADS)

Saha, P.; Rahane, A. B.; Kumar, V.; Sukumar, N.

2016-05-01

Boron atomic clusters show several interesting and unusual size-dependent features due to the small covalent radius, electron deficiency, and higher coordination number of boron as compared to carbon. These include aromaticity and a diverse array of structures such as quasi-planar, ring or tubular shaped, and fullerene-like. In the present work, we have analyzed features of the computed electron density distributions of small boron clusters having up to 11 boron atoms, and investigated the effect of doping with C, P, Al, Si, and Zn atoms on their structural and physical properties, in order to understand the bonding characteristics and discern trends in bonding and stability. We find that in general there are covalent bonds as well as delocalized charge distribution in these clusters. We associate the strong stability of some of these planar/quasiplanar disc-type clusters with the electronic shell closing with effectively twelve delocalized valence electrons using a disc-shaped jellium model. {{{{B}}}9}-, B10, B7P, and B8Si, in particular, are found to be exceptional with very large gaps between the highest occupied molecular orbital and the lowest unoccupied molecular orbital, and these are suggested to be magic clusters.

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

Lupi, Laura; Kastelowitz, Noah; Molinero, Valeria, E-mail: Valeria.Molinero@utah.edu

Carbonaceous surfaces are a major source of atmospheric particles and could play an important role in the formation of ice. Here we investigate through molecular simulations the stability, metastability, and molecular pathways of deposition of amorphous ice, bilayer ice, and ice I from water vapor on graphitic and atomless Lennard-Jones surfaces as a function of temperature. We find that bilayer ice is the most stable ice polymorph for small cluster sizes, nevertheless it can grow metastable well above its region of thermodynamic stability. In agreement with experiments, the simulations predict that on increasing temperature the outcome of water deposition ismore » amorphous ice, bilayer ice, ice I, and liquid water. The deposition nucleation of bilayer ice and ice I is preceded by the formation of small liquid clusters, which have two wetting states: bilayer pancake-like (wetting) at small cluster size and droplet-like (non-wetting) at larger cluster size. The wetting state of liquid clusters determines which ice polymorph is nucleated: bilayer ice nucleates from wetting bilayer liquid clusters and ice I from non-wetting liquid clusters. The maximum temperature for nucleation of bilayer ice on flat surfaces, T{sub B}{sup max} is given by the maximum temperature for which liquid water clusters reach the equilibrium melting line of bilayer ice as wetting bilayer clusters. Increasing water-surface attraction stabilizes the pancake-like wetting state of liquid clusters leading to larger T{sub B}{sup max} for the flat non-hydrogen bonding surfaces of this study. The findings of this study should be of relevance for the understanding of ice formation by deposition mode on carbonaceous atmospheric particles, including soot.« less

Interactions of small platinum clusters with the TiC(001) surface

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

Mao, Jianjun; Li, Shasha; Chu, Xingli

2015-11-14

Density functional theory calculations are used to elucidate the interactions of small platinum clusters (Pt{sub n}, n = 1–5) with the TiC(001) surface. The results are analyzed in terms of geometric, energetic, and electronic properties. It is found that a single Pt atom prefers to be adsorbed at the C-top site, while a Pt{sub 2} cluster prefers dimerization and a Pt{sub 3} cluster forms a linear structure on the TiC(001). As for the Pt{sub 4} cluster, the three-dimensional distorted tetrahedral structure and the two-dimensional square structure almost have equal stability. In contrast with the two-dimensional isolated Pt{sub 5} cluster, the adsorbed Pt{submore » 5} cluster prefers a three-dimensional structure on TiC(001). Substantial charge transfer takes place from TiC(001) surface to the adsorbed Pt{sub n} clusters, resulting in the negatively charged Pt{sub n} clusters. At last, the d-band centers of the absorbed Pt atoms and their implications in the catalytic activity are discussed.« less

Spectroscopic determination of fundamental parameters of small angular diameter galactic open clusters

NASA Astrophysics Data System (ADS)

Ahumada, A. V.; Claria, J. J.; Bica, E.; Parisi, M. C.; Torres, M. C.; Pavani, D. B.

We present integrated spectra obtained at CASLEO (Argentina) for 9 galactic open clusters of small angular diameter. Two of them (BH 55 and Rup 159) have not been the target of previous research. The flux-calibrated spectra cover the spectral range approx. 3600-6900 A. Using the equivalent widths (EWs) of the Balmer lines and comparing the cluster spectra with template spectra, we determined E(B-V) colour excesses and ages for the present cluster sample. The parameters obtained for 6 of the clusters show good agreement with previous determinations based mainly on photometric methods. This is not the case, however, for BH 90, a scarcely reddened cluster, for which Moffat and Vogt (1975, Astron. and Astroph. SS, 20, 125) derived E(B-V) = 0.51. We explain and justify the strong discrepancy found for this object. According to the present analysis, 3 clusters are very young (Bo 14, Tr 15 and Tr 27), 2 are moderately young (NGC 6268 and BH 205), 3 are Hyades-like clusters (Rup 164, BH 90 and BH 55) and only one is an intermediate-age cluster (Rup 159).

Internal velocity and mass distributions in simulated clusters of galaxies for a variety of cosmogonic models

NASA Technical Reports Server (NTRS)

Cen, Renyue

1994-01-01

The mass and velocity distributions in the outskirts (0.5-3.0/h Mpc) of simulated clusters of galaxies are examined for a suite of cosmogonic models (two Omega(sub 0) = 1 and two Omega(sub 0) = 0.2 models) utilizing large-scale particle-mesh (PM) simulations. Through a series of model computations, designed to isolate the different effects, we find that both Omega(sub 0) and P(sub k) (lambda less than or = 16/h Mpc) are important to the mass distributions in clusters of galaxies. There is a correlation between power, P(sub k), and density profiles of massive clusters; more power tends to point to the direction of a stronger correlation between alpha and M(r less than 1.5/h Mpc); i.e., massive clusters being relatively extended and small mass clusters being relatively concentrated. A lower Omega(sub 0) universe tends to produce relatively concentrated massive clusters and relatively extended small mass clusters compared to their counterparts in a higher Omega(sub 0) model with the same power. Models with little (initial) small-scale power, such as the hot dark matter (HDM) model, produce more extended mass distributions than the isothermal distribution for most of the mass clusters. But the cold dark matter (CDM) models show mass distributions of most of the clusters more concentrated than the isothermal distribution. X-ray and gravitational lensing observations are beginning providing useful information on the mass distribution in and around clusters; some interesting constraints on Omega(sub 0) and/or the (initial) power of the density fluctuations on scales lambda less than or = 16/h Mpc (where linear extrapolation is invalid) can be obtained when larger observational data sets, such as the Sloan Digital Sky Survey, become available.

Coupled multipolar interactions in small-particle metallic clusters.

PubMed

Pustovit, Vitaly N; Sotelo, Juan A; Niklasson, Gunnar A

2002-03-01

We propose a new formalism for computing the optical properties of small clusters of particles. It is a generalization of the coupled dipole-dipole particle-interaction model and allows one in principle to take into account all multipolar interactions in the long-wavelength limit. The method is illustrated by computations of the optical properties of N = 6 particle clusters for different multipolar approximations. We examine the effect of separation between particles and compare the optical spectra with the discrete-dipole approximation and the generalized Mie theory.

A Wsbnd Ne interatomic potential for simulation of neon implantation in tungsten

NASA Astrophysics Data System (ADS)

Backman, Marie; Juslin, Niklas; Huang, Guiyang; Wirth, Brian D.

2016-08-01

An interatomic pair potential for Wsbnd Ne is developed for atomistic molecular dynamics simulations of neon implantation in tungsten. The new potential predicts point defect energies and binding energies of small clusters that are in good agreement with electronic structure calculations. Molecular dynamics simulations of small neon clusters in tungsten show that trap mutation, in which an interstitial neon cluster displaces a tungsten atom from its lattice site, occurs for clusters of three or more neon atoms. However, near a free surface, trap mutation can occur at smaller sizes, including even a single neon interstitial in close proximity to a (100) or (110) surface.

Commodity Cluster Computing for Remote Sensing Applications using Red Hat LINUX

NASA Technical Reports Server (NTRS)

Dorband, John

2003-01-01

Since 1994, we have been doing research at Goddard Space Flight Center on implementing a wide variety of applications on commodity based computing clusters. This talk is about these clusters and haw they are used on these applications including ones for remote sensing.

Relative dispersion of clustered drifters in a small micro-tidal estuary

NASA Astrophysics Data System (ADS)

Suara, Kabir; Chanson, Hubert; Borgas, Michael; Brown, Richard J.

2017-07-01

Small tide-dominated estuaries are affected by large scale flow structures which combine with the underlying bed generated smaller scale turbulence to significantly increase the magnitude of horizontal diffusivity. Field estimates of horizontal diffusivity and its associated scales are however rare due to limitations in instrumentation. Data from multiple deployments of low and high resolution clusters of GPS-drifters are used to examine the dynamics of a surface flow in a small micro-tidal estuary through relative dispersion analyses. During the field study, cluster diffusivity, which combines both large- and small-scale processes ranged between, 0.01 and 3.01 m2/s for spreading clusters and, -0.06 and -4.2 m2/s for contracting clusters. Pair-particle dispersion, Dp2, was scale dependent and grew as Dp2 ∼ t1.83 in streamwise and Dp2 ∼ t0.8 in cross-stream directions. At small separation scale, pair-particle (d < 0.5 m) relative diffusivity followed the Richardson's 4/3 power law and became weaker as separation scale increases. Pair-particle diffusivity was described as Kp ∼ d1.01 and Kp ∼ d0.85 in the streamwise and cross-stream directions, respectively for separation scales ranging from 0.1 to 10 m. Two methods were used to identify the mechanism responsible for dispersion within the channel. The results clearly revealed the importance of strain fields (stretching and shearing) in the spreading of particles within a small micro-tidal channel. The work provided input for modelling dispersion of passive particle in shallow micro-tidal estuaries where these were not previously experimentally studied.

Critical behavior of the contact process on small-world networks

NASA Astrophysics Data System (ADS)

Ferreira, Ronan S.; Ferreira, Silvio C.

2013-11-01

We investigate the role of clustering on the critical behavior of the contact process (CP) on small-world networks using the Watts-Strogatz (WS) network model with an edge rewiring probability p. The critical point is well predicted by a homogeneous cluster-approximation for the limit of vanishing clustering ( p → 1). The critical exponents and dimensionless moment ratios of the CP are in agreement with those predicted by the mean-field theory for any p > 0. This independence on the network clustering shows that the small-world property is a sufficient condition for the mean-field theory to correctly predict the universality of the model. Moreover, we compare the CP dynamics on WS networks with rewiring probability p = 1 and random regular networks and show that the weak heterogeneity of the WS network slightly changes the critical point but does not alter other critical quantities of the model.

Dating star clusters in the Small Magellanic Cloud by means of integrated spectra

NASA Astrophysics Data System (ADS)

Ahumada, A. V.; Clariá, J. J.; Bica, E.; Dutra, C. M.

2002-10-01

In this study flux-calibrated integrated spectra in the range (3600-6800) Å are presented for 16 concentrated star clusters in the Small Magellanic Cloud (SMC), approximately half of which constitute unstudied objects. We have estimated ages and foreground interstellar reddening values from the comparison of the line strengths and continuum distribution of the cluster spectra with those of template cluster spectra with known parameters. Most of the sample clusters are young blue clusters (6-50 Myr), while L 28, NGC 643 and L 114 are found to be intermediate-age clusters (1-6 Gyr). One well known SMC cluster (NGC 416) was observed for comparison purposes. The sample includes clusters in the surroundings and main body of the SMC, and the derived foreground reddening values are in the range 0.00 <= E(B-V) <= 0.15. The present data also make up a cluster spectral library at SMC metallicity. Based on observations made at Complejo Astronómico El Leoncito, which is operated under agreement between the Consejo Nacional de Investigaciones Científicas y Técnicas de la República Argentina and the National Universities of La Plata, Córdoba and San Juan, Argentina.

Preface

NASA Astrophysics Data System (ADS)

Landman, Uzi; Yannouleas, Constantine

2001-09-01

This special volume of The European Physical Journal D contains papers presented at the 10th International Symposium on Small Particles and Inorganic Clusters, ISSPIC 10, which was held from October 11th to 15th, 2000, in Atlanta, Georgia, USA. The meeting was attended by over 300 scientists from all over the world, and in it 45 invited and hot-topic lectures were given, and 330 posters were presented. In keeping with the tradition of the ISSPIC meetings, the 10th anniversary symposium was devoted to a broad and balanced overview of new results, emerging trends and perspectives pertaining to the physics and chemistry of clusters. The meeting covered experimental and theoretical investigations of gas-phase and supported clusters, nanoscale cluster-based materials, and nanometer. The sessions at ISSPIC 10 were organized as mini-symposia, and topics included: electronic and structural properties of clusters, charged clusters and photoelectron spectroscopy, fast laser spectroscopy and dynamics, cluster-surface interactions and cluster deposition, helium clusters and spectroscopy, structural evolution and thermodynamics of clusters, cluster reactivity and nano-catalysis, two-dimensional quantum dots, nano-crystals and self-assembly, mechanical, electronic and transport properties of carbon nanotubes, structure and conductance properties of nanowires, formation and stability of droplets and jets, and medical applications of colloidal clusters. Most importantly, the symposium provided an interdisciplinary forum for presentation and discussion of fundamental and methodological aspects as well as technologically oriented developments. The opening session of ISSPIC 10 was dedicated to the memory of Professor Walter D. Knight, a pioneer in the field of clusters. The work of Walter and his research group at Berkeley on electronic shells in metal clusters opened new avenues in cluster science and contributed significantly to the rapid growth of this field. We would like to take this opportunity to gratefully acknowledge the financial assistance extended to the symposium by the Georgia Institute of Technology and by the United States Air Force Office of Scientific Research. We also thank the participants for contributing to the success of ISSPIC 10 through communicating their latest scientific results during the meeting and via the papers appearing in these proceedings.

Off-road truck-related accidents in U.S. mines

PubMed Central

Dindarloo, Saeid R.; Pollard, Jonisha P.; Siami-Irdemoosa, Elnaz

2016-01-01

Introduction Off-road trucks are one of the major sources of equipment-related accidents in the U.S. mining industries. A systematic analysis of all off-road truck-related accidents, injuries, and illnesses, which are reported and published by the Mine Safety and Health Administration (MSHA), is expected to provide practical insights for identifying the accident patterns and trends in the available raw database. Therefore, appropriate safety management measures can be administered and implemented based on these accident patterns/trends. Methods A hybrid clustering-classification methodology using K-means clustering and gene expression programming (GEP) is proposed for the analysis of severe and non-severe off-road truck-related injuries at U.S. mines. Using the GEP sub-model, a small subset of the 36 recorded attributes was found to be correlated to the severity level. Results Given the set of specified attributes, the clustering sub-model was able to cluster the accident records into 5 distinct groups. For instance, the first cluster contained accidents related to minerals processing mills and coal preparation plants (91%). More than two-thirds of the victims in this cluster had less than 5 years of job experience. This cluster was associated with the highest percentage of severe injuries (22 severe accidents, 3.4%). Almost 50% of all accidents in this cluster occurred at stone operations. Similarly, the other four clusters were characterized to highlight important patterns that can be used to determine areas of focus for safety initiatives. Conclusions The identified clusters of accidents may play a vital role in the prevention of severe injuries in mining. Further research into the cluster attributes and identified patterns will be necessary to determine how these factors can be mitigated to reduce the risk of severe injuries. Practical application Analyzing injury data using data mining techniques provides some insight into attributes that are associated with high accuracies for predicting injury severity. PMID:27620937

Effect of Self-Assembly of Fullerene Nano-Particles on Lipid Membrane

PubMed Central

Zhang, Saiqun; Mu, Yuguang; Zhang, John Z. H.; Xu, Weixin

2013-01-01

Carbon nanoparticles can penetrate the cell membrane and cause cytotoxicity. The diffusion feature and translocation free energy of fullerene through lipid membranes is well reported. However, the knowledge on self-assembly of fullerenes and resulting effects on lipid membrane is poorly addressed. In this work, the self-assembly of fullerene nanoparticles and the resulting influence on the dioleoylphosphtidylcholine (DOPC) model membrane were studied by using all-atom molecular dynamics simulations with explicit solvents. Our simulation results confirm that gathered small fullerene cluster can invade lipid membrane. Simulations show two pathways: 1) assembly process is completely finished before penetration; 2) assembly process coincides with penetration. Simulation results also demonstrate that in the membrane interior, fullerene clusters tend to stay at the position which is 1.0 nm away from the membrane center. In addition, the diverse microscopic stacking mode (i.e., equilateral triangle, tetrahedral pentahedral, trigonal bipyramid and octahedron) of these small fullerene clusters are well characterized. Thus our simulations provide a detailed high-resolution characterization of the microscopic structures of the small fullerene clusters. Further, we found the gathered small fullerene clusters have significant adverse disturbances to the local structure of the membrane, but no great influence on the global integrity of the lipid membrane, which suggests the prerequisite of high-content fullerene for cytotoxicity. PMID:24204827

The origin of low mass particles within and beyond the dust coma envelopes of Comet Halley

NASA Technical Reports Server (NTRS)

Simpson, J. A.; Rabinowitz, D.; Tuzzolino, A. J.; Ksanfomality, L. V.; Sagdeev, R. Z.

1987-01-01

Measurements from the Dust Counter and Mass Analyzer (DUCMA) instruments on VEGA-1 and -2 revealed unexpected fluxes of low mass (up to 10 to the minus 13th power g) dust particles at very great distances from the nucleus (300,000 to 600,000 km). These particles are detected in clusters (10 sec duration), preceded and followed by relatively long time intervals during which no dust is detected. This cluster phenomenon also occurs inside the envelope boundaries. Clusters of low mass particles are intermixed with the overall dust distribution throughout the coma. The clusters account for many of the short-term small-scale intensity enhancements previously ascribed to microjets in the coma. The origin of these clusters appears to be emission from the nucleus of large conglomerates which disintegrate in the coma to yield clusters of discrete, small particles continuing outward to the distant coma.

Equilibrium geometries, electronic and magnetic properties of small AunNi- (n = 1-9) clusters

NASA Astrophysics Data System (ADS)

Tang, Cui-Ming; Chen, Xiao-Xu; Yang, Xiang-Dong

2014-05-01

Geometrical, electronic and magnetic properties of small AunNi- (n = 1-9) clusters have been investigated based on density functional theory (DFT) at PW91P86 level. An extensive structural search shows that the relative stable structures of AunNi- (n = 1-9) clusters adopt 2D structure for n = 1-5, 7 and 3D structure for n = 6, 8-9. And the substitution of a Ni atom for an Au atom in the Au-n+1 cluster obviously changes the structure of the host cluster. Moreover, an odd-even alternation phenomenon has been found for HOMO-LUMO energy gaps, indicating that the relative stable structures of the AunNi- clusters with odd-numbered gold atoms have a higher relative stability. Finally, the natural population analysis (NPA) and the vertical detachment energies (VDE) are studied, respectively. The theoretical values of VDE are reported for the first time to our best knowledge.

Thermodynamic properties of small aggregates of rare-gas atoms

NASA Technical Reports Server (NTRS)

Etters, R. D.; Kaelberer, J.

1975-01-01

The present work reports on the equilibrium thermodynamic properties of small clusters of xenon, krypton, and argon atoms, determined from a biased random-walk Monte Carlo procedure. Cluster sizes ranged from 3 to 13 atoms. Each cluster was found to have an abrupt liquid-gas phase transition at a temperature much less than for the bulk material. An abrupt solid-liquid transition is observed for thirteen- and eleven-particle clusters. For cluster sizes smaller than 11, a gradual transition from solid to liquid occurred over a fairly broad range of temperatures. Distribution of number of bond lengths as a function of bond length was calculated for several systems at various temperatures. The effects of box boundary conditions are discussed. Results show the importance of a correct description of boundary conditions. A surprising result is the slow rate at which system properties approach bulk behavior as cluster size is increased.

Cluster Analysis of Time-Dependent Crystallographic Data: Direct Identification of Time-Independent Structural Intermediates

PubMed Central

Kostov, Konstantin S.; Moffat, Keith

2011-01-01

The initial output of a time-resolved macromolecular crystallography experiment is a time-dependent series of difference electron density maps that displays the time-dependent changes in underlying structure as a reaction progresses. The goal is to interpret such data in terms of a small number of crystallographically refinable, time-independent structures, each associated with a reaction intermediate; to establish the pathways and rate coefficients by which these intermediates interconvert; and thereby to elucidate a chemical kinetic mechanism. One strategy toward achieving this goal is to use cluster analysis, a statistical method that groups objects based on their similarity. If the difference electron density at a particular voxel in the time-dependent difference electron density (TDED) maps is sensitive to the presence of one and only one intermediate, then its temporal evolution will exactly parallel the concentration profile of that intermediate with time. The rationale is therefore to cluster voxels with respect to the shapes of their TDEDs, so that each group or cluster of voxels corresponds to one structural intermediate. Clusters of voxels whose TDEDs reflect the presence of two or more specific intermediates can also be identified. From such groupings one can then infer the number of intermediates, obtain their time-independent difference density characteristics, and refine the structure of each intermediate. We review the principles of cluster analysis and clustering algorithms in a crystallographic context, and describe the application of the method to simulated and experimental time-resolved crystallographic data for the photocycle of photoactive yellow protein. PMID:21244840

Dynamic Reactive Ionization with Cluster Secondary Ion Mass Spectrometry

NASA Astrophysics Data System (ADS)

Tian, Hua; Wucher, Andreas; Winograd, Nicholas

2016-02-01

Gas cluster ion beams (GCIB) have been tuned to enhance secondary ion yields by doping small gas molecules such as CH4, CO2, and O2 into an Ar cluster projectile, Arn + ( n = 1000-10,000) to form a mixed cluster. The `tailored beam' has the potential to expand the application of secondary ion mass spectrometry for two- and three-dimensional molecular specific imaging. Here, we examine the possibility of further enhancing the ionization by doping HCl into the Ar cluster. Water deposited on the target surface facilitates the dissociation of HCl. This concerted effect, occurring only at the impact site of the cluster, arises since the HCl is chemically induced to ionize to H+ and Cl- , allowing improved protonation of neutral molecular species. This hypothesis is confirmed by depth profiling through a trehalose thin film exposed to D2O vapor, resulting in ~20-fold increase in protonated molecules. The results show that it is possible to dynamically maintain optimum ionization conditions during depth profiling by proper adjustment of the water vapor pressure. H-D exchange in the trehalose molecule M was monitored upon deposition of D2O on the target surface, leading to the observation of [Mn* + H]+ or [Mn* + D]+ ions, where n = 1-8 hydrogen atoms in the trehalose molecule M have been replaced by deuterium. In general, we discuss the role of surface chemistry and dynamic reactive ionization of organic molecules in increasing the secondary ion yield.

Application of a three-feature dispersed-barrier hardening model to neutron-irradiated Fe-Cr model alloys

NASA Astrophysics Data System (ADS)

Bergner, F.; Pareige, C.; Hernández-Mayoral, M.; Malerba, L.; Heintze, C.

2014-05-01

An attempt is made to quantify the contributions of different types of defect-solute clusters to the total irradiation-induced yield stress increase in neutron-irradiated (300 °C, 0.6 dpa), industrial-purity Fe-Cr model alloys (target Cr contents of 2.5, 5, 9 and 12 at.% Cr). Former work based on the application of transmission electron microscopy, atom probe tomography, and small-angle neutron scattering revealed the formation of dislocation loops, NiSiPCr-enriched clusters and α‧-phase particles, which act as obstacles to dislocation glide. The values of the dimensionless obstacle strength are estimated in the framework of a three-feature dispersed-barrier hardening model. Special attention is paid to the effect of measuring errors, experimental details and model details on the estimates. The three families of obstacles and the hardening model are well capable of reproducing the observed yield stress increase as a function of Cr content, suggesting that the nanostructural features identified experimentally are the main, if not the only, causes of irradiation hardening in these model alloys.

Complex magnetic orders in small cobalt-benzene molecules.

PubMed

González, J W; Alonso-Lanza, T; Delgado, F; Aguilera-Granja, F; Ayuela, A

2017-06-07

Organometallic clusters based on transition metal atoms are interesting because of their possible applications in spintronics and quantum information processing. In addition to the enhanced magnetism at the nanoscale, the organic ligands may provide a natural shield against unwanted magnetic interactions with the matrices required for applications. Here we show that the organic ligands may lead to non-collinear magnetic order as well as the expected quenching of the magnetic moments. We use different density functional theory (DFT) methods to study the experimentally relevant three cobalt atoms surrounded by benzene rings (Co 3 Bz 3 ). We found that the benzene rings induce a ground state with non-collinear magnetization, with the magnetic moments localized on the cobalt centers and lying on the plane formed by the three cobalt atoms. We further analyze the magnetism of such a cluster using an anisotropic Heisenberg model where the involved parameters are obtained by a comparison with the DFT results. These results may also explain the recent observation of the null magnetic moment of Co 3 Bz 3 + . Moreover, we propose an additional experimental verification based on electron paramagnetic resonance.

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

Laskin, Julia; Johnson, Grant E.; Prabhakaran, Venkateshkumar

Immobilization of complex molecules and clusters on supports plays an important role in a variety of disciplines including materials science, catalysis and biochemistry. In particular, deposition of clusters on surfaces has attracted considerable attention due to their non-scalable, highly size-dependent properties. The ability to precisely control the composition and morphology of clusters and small nanoparticles on surfaces is crucial for the development of next generation materials with rationally tailored properties. Soft- and reactive landing of ions onto solid or liquid surfaces introduces unprecedented selectivity into surface modification by completely eliminating the effect of solvent and sample contamination on the qualitymore » of the film. The ability to select the mass-to-charge ratio of the precursor ion, its kinetic energy and charge state along with precise control of the size, shape and position of the ion beam on the deposition target makes soft-landing an attractive approach for surface modification. High-purity uniform thin films on surfaces generated using mass-selected ion deposition facilitate understanding of critical interfacial phenomena relevant to catalysis, energy generation and storage, and materials science. Our efforts have been directed toward understanding charge retention by soft-landed metal and metal-oxide cluster ions, which may affect both their structure and reactivity. Specifically, we have examined the effect of the surface on charge retention by both positively and negatively charged cluster ions. We found that the electronic properties of the surface play an important role in charge retention by cluster cations. Meanwhile, the electron binding energy is a key factor determining charge retention by cluster anions. These findings provide the scientific foundation for the rational design of interfaces for advanced catalysts and energy storage devices. Further optimization of electrode-electrolyte interfaces for applications in energy storage and electrocatalysis may be achieved by understanding and controlling the properties of soft-landed cluster ions.« less

Extracting magnetic cluster size and its distributions in advanced perpendicular recording media with shrinking grain size using small angle x-ray scattering

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

Mehta, Virat; Ikeda, Yoshihiro; Takano, Ken

2015-05-18

We analyze the magnetic cluster size (MCS) and magnetic cluster size distribution (MCSD) in a variety of perpendicular magnetic recording (PMR) media designs using resonant small angle x-ray scattering at the Co L{sub 3} absorption edge. The different PMR media flavors considered here vary in grain size between 7.5 and 9.5 nm as well as in lateral inter-granular exchange strength, which is controlled via the segregant amount. While for high inter-granular exchange, the MCS increases rapidly for grain sizes below 8.5 nm, we show that for increased amount of segregant with less exchange the MCS remains relatively small, even for grain sizesmore » of 7.5 and 8 nm. However, the MCSD still increases sharply when shrinking grains from 8 to 7.5 nm. We show evidence that recording performance such as signal-to-noise-ratio on the spin stand correlates well with the product of magnetic cluster size and magnetic cluster size distribution.« less

A DFT study of the stability of SIAs and small SIA clusters in the vicinity of solute atoms in Fe

NASA Astrophysics Data System (ADS)

Becquart, C. S.; Ngayam Happy, R.; Olsson, P.; Domain, C.

2018-03-01

The energetics, defect volume and magnetic properties of single SIAs and small SIA clusters up to size 6 have been calculated by DFT for different configurations like the parallel 〈110〉 dumbbell, the non parallel 〈110〉 dumbbell and the C15 structure. The most stable configurations of each type have been further analyzed to determine the influence on their stability of various solute atoms (Ti, V, Cr, Mn, Co, Ni, Cu, Mo, W, Pd, Al, Si, P), relevant for steels used under irradiation. The results show that the presence of solute atoms does not change the relative stability order among SIA clusters. The small SIA clusters investigated can bind to both undersized and oversized solutes. Several descriptors have been considered to derive interesting trends from results. It appears that the local atomic volume available for the solute is the main physical quantity governing the binding energy evolution, whatever the solute type (undersized or oversized) and the cluster configuration (size and type).

Computational Thermochemistry of Jet Fuels and Rocket Propellants

NASA Technical Reports Server (NTRS)

Crawford, T. Daniel

2002-01-01

The design of new high-energy density molecules as candidates for jet and rocket fuels is an important goal of modern chemical thermodynamics. The NASA Glenn Research Center is home to a database of thermodynamic data for over 2000 compounds related to this goal, in the form of least-squares fits of heat capacities, enthalpies, and entropies as functions of temperature over the range of 300 - 6000 K. The chemical equilibrium with applications (CEA) program written and maintained by researchers at NASA Glenn over the last fifty years, makes use of this database for modeling the performance of potential rocket propellants. During its long history, the NASA Glenn database has been developed based on experimental results and data published in the scientific literature such as the standard JANAF tables. The recent development of efficient computational techniques based on quantum chemical methods provides an alternative source of information for expansion of such databases. For example, it is now possible to model dissociation or combustion reactions of small molecules to high accuracy using techniques such as coupled cluster theory or density functional theory. Unfortunately, the current applicability of reliable computational models is limited to relatively small molecules containing only around a dozen (non-hydrogen) atoms. We propose to extend the applicability of coupled cluster theory- often referred to as the 'gold standard' of quantum chemical methods- to molecules containing 30-50 non-hydrogen atoms. The centerpiece of this work is the concept of local correlation, in which the description of the electron interactions- known as electron correlation effects- are reduced to only their most important localized components. Such an advance has the potential to greatly expand the current reach of computational thermochemistry and thus to have a significant impact on the theoretical study of jet and rocket propellants.

Effects of manganese doping on the structure evolution of small-sized boron clusters

NASA Astrophysics Data System (ADS)

Zhao, Lingquan; Qu, Xin; Wang, Yanchao; Lv, Jian; Zhang, Lijun; Hu, Ziyu; Gu, Guangrui; Ma, Yanming

2017-07-01

Atomic doping of clusters is known as an effective approach to stabilize or modify the structures and properties of resulting doped clusters. We herein report the effect of manganese (Mn) doping on the structure evolution of small-sized boron (B) clusters. The global minimum structures of both neutral and charged Mn doped B cluster \\text{MnB}nQ (n  =  10-20 and Q  =  0, ±1) have been proposed through extensive first-principles swarm-intelligence based structure searches. It is found that Mn doping has significantly modified the grow behaviors of B clusters, leading to two novel structural transitions from planar to tubular and then to cage-like B structures in both neutral and charged species. Half-sandwich-type structures are most favorable for small \\text{MnB}n-/0/+ (n  ⩽  13) clusters and gradually transform to Mn-centered double-ring tubular structures at \\text{MnB}16-/0/+ clusters with superior thermodynamic stabilities compared with their neighbors. Most strikingly, endohedral cages become the ground-state structures for larger \\text{MnB}n-/0/+ (n  ⩾  19) clusters, among which \\text{MnB}20+ adopts a highly symmetric structure with superior thermodynamic stability and a large HOMO-LUMO gap of 4.53 eV. The unique stability of the endohedral \\text{MnB}\\text{20}+ cage is attributed to the geometric fit and formation of 18-electron closed-shell configuration. The results significantly advance our understanding about the structure and bonding of B-based clusters and strongly suggest transition-metal doping as a viable route to synthesize intriguing B-based nanomaterials.

Vapor deposition of water on graphitic surfaces: formation of amorphous ice, bilayer ice, ice I, and liquid water.

PubMed

Lupi, Laura; Kastelowitz, Noah; Molinero, Valeria

2014-11-14

Carbonaceous surfaces are a major source of atmospheric particles and could play an important role in the formation of ice. Here we investigate through molecular simulations the stability, metastability, and molecular pathways of deposition of amorphous ice, bilayer ice, and ice I from water vapor on graphitic and atomless Lennard-Jones surfaces as a function of temperature. We find that bilayer ice is the most stable ice polymorph for small cluster sizes, nevertheless it can grow metastable well above its region of thermodynamic stability. In agreement with experiments, the simulations predict that on increasing temperature the outcome of water deposition is amorphous ice, bilayer ice, ice I, and liquid water. The deposition nucleation of bilayer ice and ice I is preceded by the formation of small liquid clusters, which have two wetting states: bilayer pancake-like (wetting) at small cluster size and droplet-like (non-wetting) at larger cluster size. The wetting state of liquid clusters determines which ice polymorph is nucleated: bilayer ice nucleates from wetting bilayer liquid clusters and ice I from non-wetting liquid clusters. The maximum temperature for nucleation of bilayer ice on flat surfaces, T(B)(max) is given by the maximum temperature for which liquid water clusters reach the equilibrium melting line of bilayer ice as wetting bilayer clusters. Increasing water-surface attraction stabilizes the pancake-like wetting state of liquid clusters leading to larger T(B)(max) for the flat non-hydrogen bonding surfaces of this study. The findings of this study should be of relevance for the understanding of ice formation by deposition mode on carbonaceous atmospheric particles, including soot.

A Comparison of Heuristic Procedures for Minimum within-Cluster Sums of Squares Partitioning

ERIC Educational Resources Information Center

Brusco, Michael J.; Steinley, Douglas

2007-01-01

Perhaps the most common criterion for partitioning a data set is the minimization of the within-cluster sums of squared deviation from cluster centroids. Although optimal solution procedures for within-cluster sums of squares (WCSS) partitioning are computationally feasible for small data sets, heuristic procedures are required for most practical…

Why do gallium clusters have a higher melting point than the bulk?

PubMed

Chacko, S; Joshi, Kavita; Kanhere, D G; Blundell, S A

2004-04-02

Density functional molecular dynamical simulations have been performed on Ga17 and Ga13 clusters to understand the recently observed higher-than-bulk melting temperatures in small gallium clusters [Phys. Rev. Lett. 91, 215508 (2003)

Sparsity enabled cluster reduced-order models for control

NASA Astrophysics Data System (ADS)

Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

2018-01-01

Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

Irradiation-induced microchemical changes in highly irradiated 316 stainless steel

NASA Astrophysics Data System (ADS)

Fujii, K.; Fukuya, K.

2016-02-01

Cold-worked 316 stainless steel specimens irradiated to 74 dpa in a pressurized water reactor (PWR) were analyzed by atom probe tomography (APT) to extend knowledge of solute clusters and segregation at higher doses. The analyses confirmed that those clusters mainly enriched in Ni-Si or Ni-Si-Mn were formed at high number density. The clusters were divided into three types based on their size and Mn content; small Ni-Si clusters (3-4 nm in diameter), and large Ni-Si and Ni-Si-Mn clusters (8-10 nm in diameter). The total cluster number density was 7.7 × 1023 m-3. The fraction of large clusters was almost 1/10 of the total density. The average composition (in at%) for small clusters was: Fe, 54; Cr, 12; Mn, 1; Ni, 22; Si, 11; Mo, 1, and for large clusters it was: Fe, 44; Cr, 9; Mn, 2; Ni, 29; Si, 14; Mo,1. It was likely that some of the Ni-Si clusters correspond to γ‧ phase precipitates while the Ni-Si-Mn clusters were precursors of G phase precipitates. The APT analyses at grain boundaries confirmed enrichment of Ni, Si, P and Cu and depletion of Fe, Cr, Mo and Mn. The segregation behavior was consistent with previous knowledge of radiation induced segregation.

The Au(n) cluster probe in secondary ion mass spectrometry: influence of the projectile size and energy on the desorption/ionization rate from biomolecular solids.

PubMed

Novikov, Alexey; Caroff, Martine; Della-Negra, Serge; Depauw, Joël; Fallavier, Mireille; Le Beyec, Yvon; Pautrat, Michèle; Schultz, J Albert; Tempez, Agnès; Woods, Amina S

2005-01-01

A Au-Si liquid metal ion source which produces Au(n) clusters over a large range of sizes was used to study the dependence of both the molecular ion desorption yield and the damage cross-section on the size (n = 1 to 400) and on the kinetic energy (E = 10 to 500 keV) of the clusters used to bombard bioorganic surfaces. Three pure peptides with molecular masses between 750 and 1200 Da were used without matrix. [M+H](+) and [M+cation](+) ion emission yields were enhanced by as much as three orders of magnitude when bombarding with Au(400) (4+) instead of monatomic Au(+), yet very little damage was induced in the samples. A 100-fold increase in the molecular ion yield was observed when the incident energy of Au(9) (+) was varied from 10 to 180 keV. Values of emission yields and damage cross-sections are presented as a function of cluster size and energy. The possibility to adjust both cluster size and energy, depending on the application, makes the analysis of biomolecules by secondary ion mass spectrometry an extremely powerful and flexible technique, particularly when combined with orthogonal time-of-flight mass spectrometry that then allows fast measurements using small primary ion beam currents. Copyright (c) 2005 John Wiley & Sons, Ltd.

Application of hybrid clustering using parallel k-means algorithm and DIANA algorithm

NASA Astrophysics Data System (ADS)

Umam, Khoirul; Bustamam, Alhadi; Lestari, Dian

2017-03-01

DNA is one of the carrier of genetic information of living organisms. Encoding, sequencing, and clustering DNA sequences has become the key jobs and routine in the world of molecular biology, in particular on bioinformatics application. There are two type of clustering, hierarchical clustering and partitioning clustering. In this paper, we combined two type clustering i.e. K-Means (partitioning clustering) and DIANA (hierarchical clustering), therefore it called Hybrid clustering. Application of hybrid clustering using Parallel K-Means algorithm and DIANA algorithm used to clustering DNA sequences of Human Papillomavirus (HPV). The clustering process is started with Collecting DNA sequences of HPV are obtained from NCBI (National Centre for Biotechnology Information), then performing characteristics extraction of DNA sequences. The characteristics extraction result is store in a matrix form, then normalize this matrix using Min-Max normalization and calculate genetic distance using Euclidian Distance. Furthermore, the hybrid clustering is applied by using implementation of Parallel K-Means algorithm and DIANA algorithm. The aim of using Hybrid Clustering is to obtain better clusters result. For validating the resulted clusters, to get optimum number of clusters, we use Davies-Bouldin Index (DBI). In this study, the result of implementation of Parallel K-Means clustering is data clustered become 5 clusters with minimal IDB value is 0.8741, and Hybrid Clustering clustered data become 13 sub-clusters with minimal IDB values = 0.8216, 0.6845, 0.3331, 0.1994 and 0.3952. The IDB value of hybrid clustering less than IBD value of Parallel K-Means clustering only that perform at 1ts stage. Its means clustering using Hybrid Clustering have the better result to clustered DNA sequence of HPV than perform parallel K-Means Clustering only.

Development of small scale cluster computer for numerical analysis

NASA Astrophysics Data System (ADS)

Zulkifli, N. H. N.; Sapit, A.; Mohammed, A. N.

2017-09-01

In this study, two units of personal computer were successfully networked together to form a small scale cluster. Each of the processor involved are multicore processor which has four cores in it, thus made this cluster to have eight processors. Here, the cluster incorporate Ubuntu 14.04 LINUX environment with MPI implementation (MPICH2). Two main tests were conducted in order to test the cluster, which is communication test and performance test. The communication test was done to make sure that the computers are able to pass the required information without any problem and were done by using simple MPI Hello Program where the program written in C language. Additional, performance test was also done to prove that this cluster calculation performance is much better than single CPU computer. In this performance test, four tests were done by running the same code by using single node, 2 processors, 4 processors, and 8 processors. The result shows that with additional processors, the time required to solve the problem decrease. Time required for the calculation shorten to half when we double the processors. To conclude, we successfully develop a small scale cluster computer using common hardware which capable of higher computing power when compare to single CPU processor, and this can be beneficial for research that require high computing power especially numerical analysis such as finite element analysis, computational fluid dynamics, and computational physics analysis.

Electronic structures and thermochemical properties of the small silicon-doped boron clusters B(n)Si (n=1-7) and their anions.

PubMed

Tai, Truong Ba; Kadłubański, Paweł; Roszak, Szczepan; Majumdar, Devashis; Leszczynski, Jerzy; Nguyen, Minh Tho

2011-11-18

We perform a systematic investigation on small silicon-doped boron clusters B(n)Si (n=1-7) in both neutral and anionic states using density functional (DFT) and coupled-cluster (CCSD(T)) theories. The global minima of these B(n)Si(0/-) clusters are characterized together with their growth mechanisms. The planar structures are dominant for small B(n)Si clusters with n≤5. The B(6)Si molecule represents a geometrical transition with a quasi-planar geometry, and the first 3D global minimum is found for the B(7)Si cluster. The small neutral B(n)Si clusters can be formed by substituting the single boron atom of B(n+1) by silicon. The Si atom prefers the external position of the skeleton and tends to form bonds with its two neighboring B atoms. The larger B(7)Si cluster is constructed by doping Si-atoms on the symmetry axis of the B(n) host, which leads to the bonding of the silicon to the ring boron atoms through a number of hyper-coordination. Calculations of the thermochemical properties of B(n)Si(0/-) clusters, such as binding energies (BE), heats of formation at 0 K (ΔH(f)(0)) and 298 K (ΔH(f)([298])), adiabatic (ADE) and vertical (VDE) detachment energies, and dissociation energies (D(e)), are performed using the high accuracy G4 and complete basis-set extrapolation (CCSD(T)/CBS) approaches. The differences of heats of formation (at 0 K) between the G4 and CBS approaches for the B(n)Si clusters vary in the range of 0.0-4.6 kcal mol(-1). The largest difference between two approaches for ADE values is 0.15 eV. Our theoretical predictions also indicate that the species B(2)Si, B(4)Si, B(3)Si(-) and B(7)Si(-) are systems with enhanced stability, exhibiting each a double (σ and π) aromaticity. B(5)Si(-) and B(6)Si are doubly antiaromatic (σ and π) with lower stability. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Application of adaptive cluster sampling to low-density populations of freshwater mussels

USGS Publications Warehouse

Smith, D.R.; Villella, R.F.; Lemarie, D.P.

2003-01-01

Freshwater mussels appear to be promising candidates for adaptive cluster sampling because they are benthic macroinvertebrates that cluster spatially and are frequently found at low densities. We applied adaptive cluster sampling to estimate density of freshwater mussels at 24 sites along the Cacapon River, WV, where a preliminary timed search indicated that mussels were present at low density. Adaptive cluster sampling increased yield of individual mussels and detection of uncommon species; however, it did not improve precision of density estimates. Because finding uncommon species, collecting individuals of those species, and estimating their densities are important conservation activities, additional research is warranted on application of adaptive cluster sampling to freshwater mussels. However, at this time we do not recommend routine application of adaptive cluster sampling to freshwater mussel populations. The ultimate, and currently unanswered, question is how to tell when adaptive cluster sampling should be used, i.e., when is a population sufficiently rare and clustered for adaptive cluster sampling to be efficient and practical? A cost-effective procedure needs to be developed to identify biological populations for which adaptive cluster sampling is appropriate.

Subaru Weak-Lensing Survey II: Multi-Object Spectroscopy and Cluster Masses

NASA Astrophysics Data System (ADS)

Hamana, Takashi; Miyazaki, Satoshi; Kashikawa, Nobunari; Ellis, Richard S.; Massey, Richard J.; Refregier, Alexandre; Taylor, James E.

2009-08-01

We present the first results of a multi-object spectroscopic campaign to follow up cluster candidates located via weak lensing. Our main goals are to search for spatial concentrations of galaxies that are plausible optical counterparts of the weak-lensing signals, and to determine the cluster redshifts from those of member galaxies. Around each of 36 targeted cluster candidates, we obtained 15-32 galaxy redshifts. For 28 of these targets, we confirmed a secure cluster identification, with more than five spectroscopic galaxies within a velocity of ±3000km s-1. This includes three cases where two clusters at different redshifts are projected along the same line-of-sight. In 6 of the 8 unconfirmed targets, we found multiple small galaxy concentrations at different redshifts, each containing at least three spectroscopic galaxies. The weak-lensing signal around those systems was thus probably created by the projection of groups or small clusters along the same line-of-sight. In both of the remaining two targets, a single small galaxy concentration was found. In some candidate super-cluster systems, we found additional evidence of filaments connecting the main density peak to an additional nearby structure. For a subsample of our most cleanly measured clusters, we investigated the statistical relation between their weak-lensing mass (MNFW, σSIS) and the velocity dispersion of their member galaxies (σv), comparing our sample with optically and X-ray selected samples from the literature. Our lensing-selected clusters are consistent with σv = σSIS, with a similar scatter to that of optically and X-ray selected clusters. We also derived an empirical relation between the cluster mass and the galaxy velocity dispersion, M200E(z) = 11.0 × 1014 × (σv/1000km s-1)3.0 h-1 Modot, which is in reasonable agreement with predictions of N-body simulations in the Λ CDM cosmology.

Age determination of 15 old to intermediate-age small Magellanic cloud star clusters

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

Parisi, M. C.; Clariá, J. J.; Piatti, A. E.

2014-04-01

We present color-magnitude diagrams in the V and I bands for 15 star clusters in the Small Magellanic Cloud (SMC) based on data taken with the Very Large Telescope (VLT, Chile). We selected these clusters from our previous work, wherein we derived cluster radial velocities and metallicities from calcium II infrared triplet (CaT) spectra also taken with the VLT. We discovered that the ages of six of our clusters have been appreciably underestimated by previous studies, which used comparatively small telescopes, graphically illustrating the need for large apertures to obtain reliable ages of old and intermediate-age SMC star clusters. Inmore » particular, three of these clusters, L4, L6, and L110, turn out to be among the oldest SMC clusters known, with ages of 7.9 ± 1.1, 8.7 ± 1.2, and 7.6 ± 1.0 Gyr, respectively, helping to fill a possible 'SMC cluster age gap'. Using the current ages and metallicities from Parisi et al., we analyze the age distribution, age gradient, and age-metallicity relation (AMR) of a sample of SMC clusters measured homogeneously. There is a suggestion of bimodality in the age distribution but it does not show a constant slope for the first 4 Gyr, and we find no evidence for an age gradient. Due to the improved ages of our cluster sample, we find that our AMR is now better represented in the intermediate/old period than we had derived in Parisi et al., where we simply took ages available in the literature. Additionally, clusters younger than ∼4 Gyr now show better agreement with the bursting model of Pagel and Tautvaišienė, but we confirm that this model is not a good representation of the AMR during the intermediate/old period. A more complicated model is needed to explain the SMC chemical evolution in that period.« less

Shield fields: Concentrations of small volcanic edifices on Venus

NASA Technical Reports Server (NTRS)

Aubele, J. C.; Crumpler, L. S.

1992-01-01

Pre-Magellan analysis of the Venera 15/16 data indicated the existence of abundant small volcanic edifices, each less than or equal to 20 km diameter, interpreted to be predominantly shield volcanoes and occurring throughout the plains terrain, most common in equidimensional clusters. With the analysis of Magellan data, these clusters of greater than average concentration of small volcanic edifices have been called 'shield fields'. Although individual small shields can and do occur almost everywhere on the plains terrain of Venus, they most commonly occur in fields that are well-defined, predominantly equant, clusters of edifices. Major questions include why the edifices are concentrated in this way, how they relate to the source of the eruptive material, and what the possible relationship of shield fields to plains terrain is. There are three possible models for the origin of fields and small shields: (1) a field represents an 'island' of higher topography subsequently surrounded by later plains material; and (2) a field represents the area of magma reservoir.

Hydrogen bonding interaction of small acetaldehyde clusters studied with core-electron excitation spectroscopy in the oxygen K-edge region

NASA Astrophysics Data System (ADS)

Tabayashi, K.; Chohda, M.; Yamanaka, T.; Tsutsumi, Y.; Takahashi, O.; Yoshida, H.; Taniguchi, M.

2010-06-01

In order to examine inner-shell electron excitation spectra of molecular clusters with strong multipole interactions, excitation spectra and time-of-flight (TOF) fragment-mass spectra of small acetaldehyde (AA) clusters have been studied under the beam conditions. The TOF spectra at the oxygen K-edge region showed an intense growth of the protonated clusters, MnH+ (M=CH3CHO) in the cluster beams. "cluster-specific" excitation spectra could be generated by monitoring partial-ion-yields of the protonated clusters. The most intense band of O1s→π*CO was found to shift to a higher energy by 0.15 eV relative to the monomer band upon clusterization. X-ray absorption spectra (XAS) were also calculated for the representative dimer configurations using a computer modelling program based on the density functional theory. The XAS prediction for the most stable (non-planar) configuration was found to give a close comparison with the cluster-band shift observed. The band shift was interpreted as being due to the HOMO-LUMO interaction within the complex where a contribution of vibrationally blue-shifting hydrogen bonding could be identified.

Ab initio calculations of optical properties of silver clusters: cross-over from molecular to nanoscale behavior

NASA Astrophysics Data System (ADS)

Titantah, John T.; Karttunen, Mikko

2016-05-01

Electronic and optical properties of silver clusters were calculated using two different ab initio approaches: (1) based on all-electron full-potential linearized-augmented plane-wave method and (2) local basis function pseudopotential approach. Agreement is found between the two methods for small and intermediate sized clusters for which the former method is limited due to its all-electron formulation. The latter, due to non-periodic boundary conditions, is the more natural approach to simulate small clusters. The effect of cluster size is then explored using the local basis function approach. We find that as the cluster size increases, the electronic structure undergoes a transition from molecular behavior to nanoparticle behavior at a cluster size of 140 atoms (diameter ~1.7 nm). Above this cluster size the step-like electronic structure, evident as several features in the imaginary part of the polarizability of all clusters smaller than Ag147, gives way to a dominant plasmon peak localized at wavelengths 350 nm ≤ λ ≤ 600 nm. It is, thus, at this length-scale that the conduction electrons' collective oscillations that are responsible for plasmonic resonances begin to dominate the opto-electronic properties of silver nanoclusters.

Mitochondrial filaments and clusters as intracellular power-transmitting cables.

PubMed

Skulachev, V P

2001-01-01

Mitochondria exist in two interconverting forms; as small isolated particles, and as extended filaments, networks or clusters connected with intermitochondrial junctions. Extended mitochondria can represent electrically united systems, which can facilitate energy delivery from the cell periphery to the cell core and organize antioxidant defence of the cell interior when O2 is consumed by mitochondrial clusters near the the outer cell membrane, and protonic potential is transmitted to the cell core mitochondria to form ATP. As to small mitochondria, they might represent a transportable form of these organelles.

Comparisons of fish species traits from small streams to large rivers

USGS Publications Warehouse

Goldstein, R.M.; Meador, M.R.

2004-01-01

To examine the relations between fish community function and stream size, we classified 429 lotic freshwater fish species based on multiple categories within six species traits: (1) substrate preference, (2) geomorphic preference, (3) trophic ecology, (4) locomotion morphology, (5) reproductive strategy, and (6) stream size preference. Stream size categories included small streams, small, medium, and large rivers, and no size preference. The frequencies of each species trait category were determined for each stream size category based on life history information from the literature. Cluster analysis revealed the presence of covarying groups of species trait categories. One cluster (RUN) included the traits of planktivore and herbivore feeding ecology, migratory reproductive behavior and broadcast spawning, preferences for main-channel habitats, and a lack of preferences for substrate type. The frequencies of classifications for the RUN cluster varied significantly across stream size categories (P = 0.009), being greater for large rivers than for small streams and rivers. Another cluster (RIFFLE) included the traits of invertivore feeding ecology, simple nester reproductive behavior, a preference for riffles, and a preference for bedrock, boulder, and cobble-rubble substrate. No significant differences in the frequency of classifications among stream size categories were detected for the RIFFLE cluster (P = 0.328). Our results suggest that fish community function is structured by large-scale differences in habitat and is different for large rivers than for small streams and rivers. Our findings support theoretical predictions of variation in species traits among stream reaches based on ecological frameworks such as landscape filters, habitat templates, and the river continuum concept. We believe that the species trait classifications presented here provide an opportunity for further examination of fish species' relations to physical, chemical, and biological factors in lotic habitats ranging from small streams to large rivers.

Second harmonic generation from small particle aggregates

NASA Astrophysics Data System (ADS)

Mochan, W. Luis; Ortiz, Guillermo P.; Mendoza, Bernardo S.; Brudny, Vera L.

2001-03-01

Novel nanofabrication techniques are capable of producing nanoparticles with controled structures which include small clusters, self-assembled particles, quantum dots, vesicles, etc. The non-linear optical scattering of these structures are important for applications, and can be used for their physical characterization. The second harmonic (SH) field radiated by a single small spherical particle has surface and bulk, dipolar and quadrupolar contributions of similar intensities and is strongly dependent of the local environment of the particle [1], in contrast to the linear case. In this work we calculate the nonlinear scattering by particle aggregates and we investigate the effects on the SH generation of the disorder induced field fluctuations and of the localization of light. We acknowledge the partial support from DGAPA-UNAM (grant IN110999), Conacyt (31120-E and 26651-E), CIP and UBACyT. [1] Vera L. Brudny, Bernardo S. Mendoza, and W. Luis Mochán, Phys. Rev. B 62, 11152 (2000).

Predicting the points of interaction of small molecules in the NF-κB pathway

PubMed Central

2011-01-01

Background The similarity property principle has been used extensively in drug discovery to identify small compounds that interact with specific drug targets. Here we show it can be applied to identify the interactions of small molecules within the NF-κB signalling pathway. Results Clusters that contain compounds with a predominant interaction within the pathway were created, which were then used to predict the interaction of compounds not included in the clustering analysis. Conclusions The technique successfully predicted the points of interactions of compounds that are known to interact with the NF-κB pathway. The method was also shown to be successful when compounds for which the interaction points were unknown were included in the clustering analysis. PMID:21342508

Giant Faraday Rotation through Ultrasmall Fe0 n Clusters in Superparamagnetic FeO-SiO2 Vitreous Films.

PubMed

Nakatsuka, Yuko; Pollok, Kilian; Wieduwilt, Torsten; Langenhorst, Falko; Schmidt, Markus A; Fujita, Koji; Murai, Shunsuke; Tanaka, Katsuhisa; Wondraczek, Lothar

2017-04-01

Magnetooptical (MO) glasses and, in particular, Faraday rotators are becoming key components in lasers and optical information processing, light switching, coding, filtering, and sensing. The common design of such Faraday rotator materials follows a simple path: high Faraday rotation is achieved by maximizing the concentration of paramagnetic ion species in a given matrix material. However, this approach has reached its limits in terms of MO performance; hence, glass-based materials can presently not be used efficiently in thin film MO applications. Here, a novel strategy which overcomes this limitation is demonstrated. Using vitreous films of x FeO·(100 - x )SiO 2 , unusually large Faraday rotation has been obtained, beating the performance of any other glassy material by up to two orders of magnitude. It is shown that this is due to the incorporation of small, ferromagnetic clusters of atomic iron which are generated in line during laser deposition and rapid condensation of the thin film, generating superparamagnetism. The size of these clusters underbids the present record of metallic Fe incorporation and experimental verification in glass matrices.

Clustering More than Two Million Biomedical Publications: Comparing the Accuracies of Nine Text-Based Similarity Approaches

PubMed Central

Boyack, Kevin W.; Newman, David; Duhon, Russell J.; Klavans, Richard; Patek, Michael; Biberstine, Joseph R.; Schijvenaars, Bob; Skupin, André; Ma, Nianli; Börner, Katy

2011-01-01

Background We investigate the accuracy of different similarity approaches for clustering over two million biomedical documents. Clustering large sets of text documents is important for a variety of information needs and applications such as collection management and navigation, summary and analysis. The few comparisons of clustering results from different similarity approaches have focused on small literature sets and have given conflicting results. Our study was designed to seek a robust answer to the question of which similarity approach would generate the most coherent clusters of a biomedical literature set of over two million documents. Methodology We used a corpus of 2.15 million recent (2004-2008) records from MEDLINE, and generated nine different document-document similarity matrices from information extracted from their bibliographic records, including titles, abstracts and subject headings. The nine approaches were comprised of five different analytical techniques with two data sources. The five analytical techniques are cosine similarity using term frequency-inverse document frequency vectors (tf-idf cosine), latent semantic analysis (LSA), topic modeling, and two Poisson-based language models – BM25 and PMRA (PubMed Related Articles). The two data sources were a) MeSH subject headings, and b) words from titles and abstracts. Each similarity matrix was filtered to keep the top-n highest similarities per document and then clustered using a combination of graph layout and average-link clustering. Cluster results from the nine similarity approaches were compared using (1) within-cluster textual coherence based on the Jensen-Shannon divergence, and (2) two concentration measures based on grant-to-article linkages indexed in MEDLINE. Conclusions PubMed's own related article approach (PMRA) generated the most coherent and most concentrated cluster solution of the nine text-based similarity approaches tested, followed closely by the BM25 approach using titles and abstracts. Approaches using only MeSH subject headings were not competitive with those based on titles and abstracts. PMID:21437291

Cluster-specific small airway modeling for imaging-based CFD analysis of pulmonary air flow and particle deposition in COPD smokers

NASA Astrophysics Data System (ADS)

Haghighi, Babak; Choi, Jiwoong; Choi, Sanghun; Hoffman, Eric A.; Lin, Ching-Long

2017-11-01

Accurate modeling of small airway diameters in patients with chronic obstructive pulmonary disease (COPD) is a crucial step toward patient-specific CFD simulations of regional airflow and particle transport. We proposed to use computed tomography (CT) imaging-based cluster membership to identify structural characteristics of airways in each cluster and use them to develop cluster-specific airway diameter models. We analyzed 284 COPD smokers with airflow limitation, and 69 healthy controls. We used multiscale imaging-based cluster analysis (MICA) to classify smokers into 4 clusters. With representative cluster patients and healthy controls, we performed multiple regressions to quantify variation of airway diameters by generation as well as by cluster. The cluster 2 and 4 showed more diameter decrease as generation increases than other clusters. The cluster 4 had more rapid decreases of airway diameters in the upper lobes, while cluster 2 in the lower lobes. We then used these regression models to estimate airway diameters in CT unresolved regions to obtain pressure-volume hysteresis curves using a 1D resistance model. These 1D flow solutions can be used to provide the patient-specific boundary conditions for 3D CFD simulations in COPD patients. Support for this study was provided, in part, by NIH Grants U01-HL114494, R01-HL112986 and S10-RR022421.

Instability timescale for the inclination instability in the solar system

NASA Astrophysics Data System (ADS)

Zderic, Alexander; Madigan, Ann-Marie; Fleisig, Jacob

2018-04-01

The gravitational influence of small bodies is often neglected in the study of solar system dynamics. However, this is not always an appropriate assumption. For example, mutual secular torques between low mass particles on eccentric orbits can result in a self-gravity instability (`inclination instability'; Madigan & McCourt 2016). During the instability, inclinations increase exponentially, eccentricities decrease (detachment), and orbits cluster in argument of perihelion. In the solar system, the orbits of the most distant objects show all three of these characteristics (high inclination: Volk & Malhotra (2017), detachment: Delsanti & Jewitt (2006), and argument of perihelion clustering: Trujillo & Sheppard (2014)). The inclination instability is a natural explanation for these phenomena.Unfortunately, full N-body simulations of the solar system are unfeasible (N ≈ O(1012)), and the behavior of the instability depends on N, prohibiting the direct application of lower N simulations. Here we present the instability timescale's functional dependence on N, allowing us to extrapolate our simulation results to that appropriate for the solar system. We show that ~5 MEarth of small icy bodies in the Sedna region is sufficient for the inclination instability to occur in the outer solar system.

Scale-free Graphs for General Aviation Flight Schedules

NASA Technical Reports Server (NTRS)

Alexandov, Natalia M. (Technical Monitor); Kincaid, Rex K.

2003-01-01

In the late 1990s a number of researchers noticed that networks in biology, sociology, and telecommunications exhibited similar characteristics unlike standard random networks. In particular, they found that the cummulative degree distributions of these graphs followed a power law rather than a binomial distribution and that their clustering coefficients tended to a nonzero constant as the number of nodes, n, became large rather than O(1/n). Moreover, these networks shared an important property with traditional random graphs as n becomes large the average shortest path length scales with log n. This latter property has been coined the small-world property. When taken together these three properties small-world, power law, and constant clustering coefficient describe what are now most commonly referred to as scale-free networks. Since 1997 at least six books and over 400 articles have been written about scale-free networks. In this manuscript an overview of the salient characteristics of scale-free networks. Computational experience will be provided for two mechanisms that grow (dynamic) scale-free graphs. Additional computational experience will be given for constructing (static) scale-free graphs via a tabu search optimization approach. Finally, a discussion of potential applications to general aviation networks is given.

Globally maximizing, locally minimizing: unsupervised discriminant projection with applications to face and palm biometrics.

PubMed

Yang, Jian; Zhang, David; Yang, Jing-Yu; Niu, Ben

2007-04-01

This paper develops an unsupervised discriminant projection (UDP) technique for dimensionality reduction of high-dimensional data in small sample size cases. UDP can be seen as a linear approximation of a multimanifolds-based learning framework which takes into account both the local and nonlocal quantities. UDP characterizes the local scatter as well as the nonlocal scatter, seeking to find a projection that simultaneously maximizes the nonlocal scatter and minimizes the local scatter. This characteristic makes UDP more intuitive and more powerful than the most up-to-date method, Locality Preserving Projection (LPP), which considers only the local scatter for clustering or classification tasks. The proposed method is applied to face and palm biometrics and is examined using the Yale, FERET, and AR face image databases and the PolyU palmprint database. The experimental results show that UDP consistently outperforms LPP and PCA and outperforms LDA when the training sample size per class is small. This demonstrates that UDP is a good choice for real-world biometrics applications.

Stressful jobs and non-stressful jobs: a cluster analysis of office jobs.

PubMed

Carayon, P

1994-02-01

The purpose of the study was to determine if office jobs could be characterized by a small number of combinations of stressors that could be related to job-title information and self-report of psychological strain. Two-hundred-and-sixty-two office workers from three public service organizations provided data on nine job stressors and seven indicators of psychological strain. Using cluster analysis on the nine stressors, office jobs were classified into three clusters. The first cluster included jobs with high skill utilization, task clarity, job control and social support and low future ambiguity, but also high on job demands such as quantitative work-load, attention and work pressure. The second cluster included jobs with high demands and future ambiguity and low skill utilization, task clarity, job control and social support. The third cluster was intermediary between the first two clusters. The three clusters were related to job-title information. The second cluster was the highest on a range of psychological strain indicators, while the other two clusters were high on certain strain indicators but low on others. The study showed that office jobs could be characterized by a small number of combinations of stressors that were related to job-title information and psychological strain.

Towards a comprehensive knowledge of the star cluster population in the Small Magellanic Cloud

NASA Astrophysics Data System (ADS)

Piatti, A. E.

2018-07-01

The Small Magellanic Cloud (SMC) has recently been found to harbour an increase of more than 200 per cent in its known cluster population. Here, we provide solid evidence that this unprecedented number of clusters could be greatly overestimated. On the one hand, the fully automatic procedure used to identify such an enormous cluster candidate sample did not recover ˜50 per cent, on average, of the known relatively bright clusters located in the SMC main body. On the other hand, the number of new cluster candidates per time unit as a function of time is noticeably different from the intrinsic SMC cluster frequency (CF), which should not be the case if these new detections were genuine physical systems. We found additionally that the SMC CF varies spatially, in such a way that it resembles an outside-in process coupled with the effects of a relatively recent interaction with the Large Magellanic Cloud. By assuming that clusters and field stars share the same formation history, we showed for the first time that the cluster dissolution rate also depends on position in the galaxy. The cluster dissolution becomes higher as the concentration of galaxy mass increases or if external tidal forces are present.

Universal clustering of dark matter in phase space

NASA Astrophysics Data System (ADS)

Zavala, Jesús; Afshordi, Niayesh

2016-03-01

We have recently introduced a novel statistical measure of dark matter clustering in phase space, the particle phase-space average density (P2SAD). In a two-paper series, we studied the structure of P2SAD in the Milky Way-size Aquarius haloes, constructed a physically motivated model to describe it, and illustrated its potential as a powerful tool to predict signals sensitive to the nanostructure of dark matter haloes. In this work, we report a remarkable universality of the clustering of dark matter in phase space as measured by P2SAD within the subhaloes of host haloes across different environments covering a range from dwarf-size to cluster-size haloes (1010-1015 M⊙). Simulations show that the universality of P2SAD holds for more than seven orders of magnitude, over a 2D phase space, covering over three orders of magnitude in distance/velocity, with a simple functional form that can be described by our model. Invoking the universality of P2SAD, we can accurately predict the non-linear power spectrum of dark matter at small scales all the way down to the decoupling mass limit of cold dark matter particles. As an application, we compute the subhalo boost to the annihilation of dark matter in a wide range of host halo masses.

Galaxy And Mass Assembly (GAMA): the signatures of galaxy interactions as viewed from small scale galaxy clustering

NASA Astrophysics Data System (ADS)

Gunawardhana, M. L. P.; Norberg, P.; Zehavi, I.; Farrow, D. J.; Loveday, J.; Hopkins, A. M.; Davies, L. J. M.; Wang, L.; Alpaslan, M.; Bland-Hawthorn, J.; Brough, S.; Holwerda, B. W.; Owers, M. S.; Wright, A. H.

2018-06-01

Statistical studies of galaxy-galaxy interactions often utilise net change in physical properties of progenitors as a function of the separation between their nuclei to trace both the strength and the observable timescale of their interaction. In this study, we use two-point auto, cross and mark correlation functions to investigate the extent to which small-scale clustering properties of star forming galaxies can be used to gain physical insight into galaxy-galaxy interactions between galaxies of similar optical brightness and stellar mass. The Hα star formers, drawn from the highly spatially complete Galaxy And Mass Assembly (GAMA) survey, show an increase in clustering on small separations. Moreover, the clustering strength shows a strong dependence on optical brightness and stellar mass, where (1) the clustering amplitude of optically brighter galaxies at a given separation is larger than that of optically fainter systems, (2) the small scale clustering properties (e.g. the strength, the scale at which the signal relative to the fiducial power law plateaus) of star forming galaxies appear to differ as a function of increasing optical brightness of galaxies. According to cross and mark correlation analyses, the former result is largely driven by the increased dust content in optically bright star forming galaxies. The latter could be interpreted as evidence of a correlation between interaction-scale and optical brightness of galaxies, where physical evidence of interactions between optically bright star formers, likely hosted within relatively massive halos, persist over larger separations than those between optically faint star formers.

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.

Bioinspired principles for large-scale networked sensor systems: an overview.

PubMed

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy.

Adiabatic invariants in stellar dynamics. 2: Gravitational shocking

NASA Technical Reports Server (NTRS)

Weinberg, Martin D.

1994-01-01

A new theory of gravitational shocking based on time-dependent perturbation theory shows that the changes in energy and angular momentum due to a slowly varying disturbance are not exponentially small for stellar dynamical systems in general. It predicts significant shock heating by slowly varying perturbations previously thought to be negligible according to the adiabatic criterion. The theory extends the scenarios traditionally computed only with the impulse approximation and is applicable to a wide class of disturbances. The approach is applied specifically to the problem of disk shocking of star clusters.

Design of an ectoine-responsive AraC mutant and its application in metabolic engineering of ectoine biosynthesis.

PubMed

Chen, Wei; Zhang, Shan; Jiang, Peixia; Yao, Jun; He, Yongzhi; Chen, Lincai; Gui, Xiwu; Dong, Zhiyang; Tang, Shuang-Yan

2015-07-01

Advanced high-throughput screening methods for small molecules may have important applications in the metabolic engineering of the biosynthetic pathways of these molecules. Ectoine is an excellent osmoprotectant that has been widely used in cosmetics. In this study, the Escherichia coli regulatory protein AraC was engineered to recognize ectoine as its non-natural effector and to activate transcription upon ectoine binding. As an endogenous reporter of ectoine, the mutated AraC protein was successfully incorporated into high-throughput screening of ectoine hyper-producing strains. The ectoine biosynthetic cluster from Halomonas elongata was cloned into E. coli. By engineering the rate-limiting enzyme L-2,4-diaminobutyric acid (DABA) aminotransferase (EctB), ectoine production and the specific activity of the EctB mutant were increased. Thus, these results demonstrated the effectiveness of engineering regulatory proteins into sensitive and rapid screening tools for small molecules and highlighted the importance and efficacy of directed evolution strategies applied to the engineering of genetic components for yield improvement in the biosynthesis of small molecules. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

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

Sun, Shengtong; Chevrier, Daniel M.; Zhang, Peng

Amorphous intermediate phases are vital precursors in the crystallization of many biogenic minerals. While inherent short-range orders have been found in amorphous calcium carbonates (ACCs) relating to different crystalline forms, it has never been clarified experimentally whether such orders already exist in very small clusters less than 2 nm in size. Here, we studied the stability and structure of 10,12-pentacosadiynoic acid (PCDA) protected ACC clusters with a core size of ca. 1.4 nm consisting of only seven CaCO 3 units. Ligand concentration and structure are shown to be key factors in stabilizing the ACC clusters. More importantly, even in suchmore » small CaCO 3 entities, a proto-calcite short-range order can be identified but with a relatively high degree of disorder that arises from the very small size of the CaCO 3 core. Our findings support the notion of a structural link between prenucleation clusters, amorphous intermediates, and final crystalline polymorphs, which appears central to the understanding of polymorph selection.« less

Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

NASA Astrophysics Data System (ADS)

Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar

2011-03-01

Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.

VizieR Online Data Catalog: Shape parameters for 154 Galactic open clusters (Zhai+, 2017)

NASA Astrophysics Data System (ADS)

Zhai, M.; Abt, H.; Zhao, G.; Li, C.

2017-06-01

The data used are from database WEBDA (http://www.univie.ac.at/webda/). We have found 946 open clusters with equatorial coordinates for each cluster member. Since cluster members are easily contaminated by field stars, we have only adopted stars with membership probabilities higher than 70% as cluster members. It is rarely possible to determine a cluster's shape with a small number of members, so we have only considered relatively richer clusters, which host more than 20 of the most probable member stars. After these selections, there are 154 clusters left. (1 data file).

Web Program for Development of GUIs for Cluster Computers

NASA Technical Reports Server (NTRS)

Czikmantory, Akos; Cwik, Thomas; Klimeck, Gerhard; Hua, Hook; Oyafuso, Fabiano; Vinyard, Edward

2003-01-01

WIGLAF (a Web Interface Generator and Legacy Application Facade) is a computer program that provides a Web-based, distributed, graphical-user-interface (GUI) framework that can be adapted to any of a broad range of application programs, written in any programming language, that are executed remotely on any cluster computer system. WIGLAF enables the rapid development of a GUI for controlling and monitoring a specific application program running on the cluster and for transferring data to and from the application program. The only prerequisite for the execution of WIGLAF is a Web-browser program on a user's personal computer connected with the cluster via the Internet. WIGLAF has a client/server architecture: The server component is executed on the cluster system, where it controls the application program and serves data to the client component. The client component is an applet that runs in the Web browser. WIGLAF utilizes the Extensible Markup Language to hold all data associated with the application software, Java to enable platform-independent execution on the cluster system and the display of a GUI generator through the browser, and the Java Remote Method Invocation software package to provide simple, effective client/server networking.

Vacancy clustering and acceptor activation in nitrogen-implanted ZnO

NASA Astrophysics Data System (ADS)

Børseth, Thomas Moe; Tuomisto, Filip; Christensen, Jens S.; Monakhov, Edouard V.; Svensson, Bengt G.; Kuznetsov, Andrej Yu.

2008-01-01

The role of vacancy clustering and acceptor activation on resistivity evolution in N ion-implanted n -type hydrothermally grown bulk ZnO has been investigated by positron annihilation spectroscopy, resistivity measurements, and chemical profiling. Room temperature 220keV N implantation using doses in the low 1015cm-2 range induces small and big vacancy clusters containing at least 2 and 3-4 Zn vacancies, respectively. The small clusters are present already in as-implanted samples and remain stable up to 1000°C with no significant effect on the resistivity evolution. In contrast, formation of the big clusters at 600°C is associated with a significant increase in the free electron concentration attributed to gettering of amphoteric Li impurities by these clusters. Further annealing at 800°C results in a dramatic decrease in the free electron concentration correlated with activation of 1016-1017cm-3 acceptors likely to be N and/or Li related. The samples remain n type, however, and further annealing at 1000°C results in passivation of the acceptor states while the big clusters dissociate.

Symmetries and stability of chimera states in small, globally-coupled networks

NASA Astrophysics Data System (ADS)

Hart, Joseph D.; Bansal, Kanika; Murphy, Thomas E.; Roy, Rajarshi

It has recently been demonstrated that symmetries in a network's topology can help predict the patterns of synchronized clusters that can emerge in a network of coupled oscillators. This and related discoveries have led to increased interest in both network symmetries and cluster synchronization. In parallel with these discoveries, interest in chimera states-dynamical patterns in which a network separates into coherent and incoherent portions-has grown, and chimeras have now been observed in a variety of experimental systems. We present an opto-electronic experiment in which both chimera states and synchronized clusters are observed in a small, globally-coupled network. We show that the symmetries and sub-symmetries of the network permit the formation of the chimera and cluster states. A recently developed group theoretical approach enables us to predict the stability of the observed chimera and cluster states, and highlights the close relationship between chimera and cluster states as belonging to the broader phenomenon of partial synchronization.

Size dependent fragmentation of argon clusters in the soft x-ray ionization regime

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

Gisselbrecht, Mathieu; Lindgren, Andreas; Burmeister, Florian

Photofragmentation of argon clusters of average size ranging from 10 up to 1000 atoms is studied using soft x-ray radiation below the 2p threshold and multicoincidence mass spectroscopy technique. For small clusters (=10), ionization induces fast fragmentation with neutral emission imparting a large amount of energy. While the primary dissociation takes place on a picosecond time scale, the fragments undergo slow degradation in the spectrometer on a microsecond time scale. For larger clusters ({>=}100) we believe that we observe the fragmentation pattern of multiply charged species on a time-scale which lasts a few hundred nanoseconds. The reason for these slowermore » processes is the large number of neutral atoms which act as an efficient cooling bath where the excess energy ('heat') dissipates among all degrees of freedom. Further degradation of the photoionic cluster in spectrometer then takes place on the microsecond time scale, similar to small clusters.« less

Polymorphism in magic-sized Au144(SR)60 clusters

NASA Astrophysics Data System (ADS)

Jensen, Kirsten M. Ø.; Juhas, Pavol; Tofanelli, Marcus A.; Heinecke, Christine L.; Vaughan, Gavin; Ackerson, Christopher J.; Billinge, Simon J. L.

2016-06-01

Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. Here we present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. The study reveals structural polymorphism in these archetypal nanoclusters. In addition to confirming the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. The discovery of polymorphism may open up a new dimension in nanoscale engineering.

Application of cluster technology in location-based service

NASA Astrophysics Data System (ADS)

Chen, Jing; Wang, Xiaoman; Gong, Jianya

2005-10-01

This paper introduces the principle, algorithmic and realization of the Load Balancing Technology. It also designs a clustered method in the application of Location-Based Service (LBS), and explains its function characteristics and its whole system structure, followed by some experimental comparisons, showing that the Cluster Technology could ensure a LBS's continuous running and the sharing of fault-tolerance and cluster.

Cooperative network clustering and task allocation for heterogeneous small satellite network

NASA Astrophysics Data System (ADS)

Qin, Jing

The research of small satellite has emerged as a hot topic in recent years because of its economical prospects and convenience in launching and design. Due to the size and energy constraints of small satellites, forming a small satellite network(SSN) in which all the satellites cooperate with each other to finish tasks is an efficient and effective way to utilize them. In this dissertation, I designed and evaluated a weight based dominating set clustering algorithm, which efficiently organizes the satellites into stable clusters. The traditional clustering algorithms of large monolithic satellite networks, such as formation flying and satellite swarm, are often limited on automatic formation of clusters. Therefore, a novel Distributed Weight based Dominating Set(DWDS) clustering algorithm is designed to address the clustering problems in the stochastically deployed SSNs. Considering the unique features of small satellites, this algorithm is able to form the clusters efficiently and stably. In this algorithm, satellites are separated into different groups according to their spatial characteristics. A minimum dominating set is chosen as the candidate cluster head set based on their weights, which is a weighted combination of residual energy and connection degree. Then the cluster heads admit new neighbors that accept their invitations into the cluster, until the maximum cluster size is reached. Evaluated by the simulation results, in a SSN with 200 to 800 nodes, the algorithm is able to efficiently cluster more than 90% of nodes in 3 seconds. The Deadline Based Resource Balancing (DBRB) task allocation algorithm is designed for efficient task allocations in heterogeneous LEO small satellite networks. In the task allocation process, the dispatcher needs to consider the deadlines of the tasks as well as the residue energy of different resources for best energy utilization. We assume the tasks adopt a Map-Reduce framework, in which a task can consist of multiple subtasks. The DBRB algorithm is deployed on the head node of a cluster. It gathers the status from each cluster member and calculates their Node Importance Factors (NIFs) from the carried resources, residue power and compute capacity. The algorithm calculates the number of concurrent subtasks based on the deadlines, and allocates the subtasks to the nodes according to their NIF values. The simulation results show that when cluster members carry multiple resources, resource are more balanced and rare resources serve longer in DBRB than in the Earliest Deadline First algorithm. We also show that the algorithm performs well in service isolation by serving multiple tasks with different deadlines. Moreover, the average task response time with various cluster size settings is well controlled within deadlines as well. Except non-realtime tasks, small satellites may execute realtime tasks as well. The location-dependent tasks, such as image capturing, data transmission and remote sensing tasks are realtime tasks that are required to be started / finished on specific time. The resource energy balancing algorithm for realtime and non-realtime mixed workload is developed to efficiently schedule the tasks for best system performance. It calculates the residue energy for each resource type and tries to preserve resources and node availability when distributing tasks. Non-realtime tasks can be preempted by realtime tasks to provide better QoS to realtime tasks. I compared the performance of proposed algorithm with a random-priority scheduling algorithm, with only realtime tasks, non-realtime tasks and mixed tasks. It shows the resource energy reservation algorithm outperforms the latter one with both balanced and imbalanced workloads. Although the resource energy balancing task allocation algorithm for mixed workload provides preemption mechanism for realtime tasks, realtime tasks can still fail due to resource exhaustion. For LEO small satellite flies around the earth on stable orbits, the location-dependent realtime tasks can be considered as periodical tasks. Therefore, it is possible to reserve energy for these realtime tasks. The resource energy reservation algorithm preserves energy for the realtime tasks when the execution routine of periodical realtime tasks is known. In order to reserve energy for tasks starting very early in each period that the node does not have enough energy charged, an energy wrapping mechanism is also designed to calculate the residue energy from the previous period. The simulation results show that without energy reservation, realtime task failure rate can reach more than 60% when the workload is highly imbalanced. In contrast, the resource energy reservation produces zero RT task failures and leads to equal or better aggregate system throughput than the non-reservation algorithm. The proposed algorithm also preserves more energy because it avoids task preemption. (Abstract shortened by ProQuest.).

Description and typology of intensive Chios dairy sheep farms in Greece.

PubMed

Gelasakis, A I; Valergakis, G E; Arsenos, G; Banos, G

2012-06-01

The aim was to assess the intensified dairy sheep farming systems of the Chios breed in Greece, establishing a typology that may properly describe and characterize them. The study included the total of the 66 farms of the Chios sheep breeders' cooperative Macedonia. Data were collected using a structured direct questionnaire for in-depth interviews, including questions properly selected to obtain a general description of farm characteristics and overall management practices. A multivariate statistical analysis was used on the data to obtain the most appropriate typology. Initially, principal component analysis was used to produce uncorrelated variables (principal components), which would be used for the consecutive cluster analysis. The number of clusters was decided using hierarchical cluster analysis, whereas, the farms were allocated in 4 clusters using k-means cluster analysis. The identified clusters were described and afterward compared using one-way ANOVA or a chi-squared test. The main differences were evident on land availability and use, facility and equipment availability and type, expansion rates, and application of preventive flock health programs. In general, cluster 1 included newly established, intensive, well-equipped, specialized farms and cluster 2 included well-established farms with balanced sheep and feed/crop production. In cluster 3 were assigned small flock farms focusing more on arable crops than on sheep farming with a tendency to evolve toward cluster 2, whereas cluster 4 included farms representing a rather conservative form of Chios sheep breeding with low/intermediate inputs and choosing not to focus on feed/crop production. In the studied set of farms, 4 different farmer attitudes were evident: 1) farming disrupts sheep breeding; feed should be purchased and economies of scale will decrease costs (mainly cluster 1), 2) only exercise/pasture land is necessary; at least part of the feed (pasture) must be home-grown to decrease costs (clusters 1 and 4), 3) providing pasture to sheep is essential; on-farm feed production decreases costs (mainly cluster 3), and 4) large-scale farming (feed production and cash crops) does not disrupt sheep breeding; all feed must be produced on-farm to decrease costs (mainly cluster 3). Conducting a profitability analysis among different clusters, exploring and discovering the most beneficial levels of intensified management and capital investment should now be considered. Copyright © 2012 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

The Cluster Environment of Two High-mass Protostars

NASA Astrophysics Data System (ADS)

Montes, Virginie; Hofner, Peter

2017-06-01

Characterizing the environment and stellar population in which high-mass stars form is an important step to decide between the main massive star formation theories. In the monolithic collapse model, the mass of the core will determine the final stellar mass (e.g., McKee & Tan 2003). In contrast, in the competitive accretion model (e.g., Bonnell & Bate 2006), the mass of the high-mass star is related to the properties of the cluster. As dynamical processes substantially affect the appearance of a cluster, we study early stages of high-mass star formation. These regions often show extended emission from hot dust at infrared wavelengths, which can cause difficulties to define the cluster. We use a multi-wavelength technique to study nearby high-mass star clusters, based on X-ray observations with the Chandra X-Ray Telescope, in conjunction with infrared data and VLA data. The technique relies on the fact that YSOs are particularly bright in X-ray and that contamination is relatively small. X-ray observations allow us to determine the cluster size. The cluster membership and YSOs classification is established using infrared identification of the X-ray sources, and color-color and color-magnitude diagrams.In this talk, I will present our findings on the cluster study of two high-mass star forming regions: IRAS 20126+4104 and IRAS 16562-3959. While most massive stars appear to be formed in rich a cluster environment, those two sources are candidates for the formation of massive stars in a relatively poor cluster. In contrast to what was found in previous studies (Qiu et al. 2008), the dominant B0-type protostar in IRAS 20126+4104 is associated with a small cluster of low-mass stars. I will also show our current work on IRAS 16562-3959, which contains one of the most luminous O-type protostars in the Galaxy. In the vicinity of this particularly interesting region there is a multitude of small clusters, for which I will present how their stellar population differ from the high-mass star-forming cluster IRAS 16562-3959.

Species collapse via hybridization in Darwin's tree finches.

PubMed

Kleindorfer, Sonia; O'Connor, Jody A; Dudaniec, Rachael Y; Myers, Steven A; Robertson, Jeremy; Sulloway, Frank J

2014-03-01

Species hybridization can lead to fitness costs, species collapse, and novel evolutionary trajectories in changing environments. Hybridization is predicted to be more common when environmental conditions change rapidly. Here, we test patterns of hybridization in three sympatric tree finch species (small tree finch Camarhynchus parvulus, medium tree finch Camarhynchus pauper, and large tree finch: Camarhynchus psittacula) that are currently recognized on Floreana Island, Galápagos Archipelago. Genetic analysis of microsatellite data from contemporary samples showed two genetic populations and one hybrid cluster in both 2005 and 2010; hybrid individuals were derived from genetic population 1 (small morph) and genetic population 2 (large morph). Females of the large and rare species were more likely to pair with males of the small common species. Finch populations differed in morphology in 1852-1906 compared with 2005/2010. An unsupervised clustering method showed (a) support for three morphological clusters in the historical tree finch sample (1852-1906), which is consistent with current species recognition; (b) support for two or three morphological clusters in 2005 with some (19%) hybridization; and (c) support for just two morphological clusters in 2010 with frequent (41%) hybridization. We discuss these findings in relation to species demarcations of Camarhynchus tree finches on Floreana Island.

First principles investigations of small bimetallic PdGa clusters as catalysts for hydrogen dissociation

NASA Astrophysics Data System (ADS)

Kaul, Indu; Ghosh, Prasenjit

2017-04-01

Using first principles density functional theory based calculations, we have studied hydrogen dissociation on sub nanometer bimetallic clusters formed from d-block (Pd) and p-block (Ga) elements in gas phase to explore the feasibility of using them as cheap catalysts for hydrogen dissociation. Our calculations show that the dimers, trimers and tetramers of these clusters are thermodynamically more stable than the pure ones for all Ga concentrations. For a given cluster size, we find that the clusters containing equal amount of Pd and Ga are the most stable ones. In contrast to bulk PdGa, the contribution of Pd-d states to the highest occupied molecular orbitals of the bimetallic clusters are either very small or absent. Study of adsorption of hydrogen molecule on these clusters show that hydrogen binds in an activated form only on the Pd rich clusters. From the calculations of hydrogen dissociation barriers on tetramers of pure Pd, 25% Ga (Pd3Ga) and 50% Ga (Pd2Ga2) we find that Pd3Ga is the most efficient catalyst for hydrogen dissociation with barriers even lower than that on the PdGa surfaces.

Observation of small cluster formation in concentrated monoclonal antibody solutions and its implications to solution viscosity.

PubMed

Yearley, Eric J; Godfrin, Paul D; Perevozchikova, Tatiana; Zhang, Hailiang; Falus, Peter; Porcar, Lionel; Nagao, Michihiro; Curtis, Joseph E; Gawande, Pradad; Taing, Rosalynn; Zarraga, Isidro E; Wagner, Norman J; Liu, Yun

2014-04-15

Monoclonal antibodies (mAbs) are a major class of biopharmaceuticals. It is hypothesized that some concentrated mAb solutions exhibit formation of a solution phase consisting of reversibly self-associated aggregates (or reversible clusters), which is speculated to be responsible for their distinct solution properties. Here, we report direct observation of reversible clusters in concentrated solutions of mAbs using neutron spin echo. Specifically, a stable mAb solution is studied across a transition from dispersed monomers in dilute solution to clustered states at more concentrated conditions, where clusters of a preferred size are observed. Once mAb clusters have formed, their size, in contrast to that observed in typical globular protein solutions, is observed to remain nearly constant over a wide range of concentrations. Our results not only conclusively establish a clear relationship between the undesirable high viscosity of some mAb solutions and the formation of reversible clusters with extended open structures, but also directly observe self-assembled mAb protein clusters of preferred small finite size similar to that in micelle formation that dominate the properties of concentrated mAb solutions. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Defect processes in Be12X (X = Ti, Mo, V, W)

NASA Astrophysics Data System (ADS)

Jackson, M. L.; Burr, P. A.; Grimes, R. W.

2017-08-01

The stability of intrinsic point defects in Be12X intermetallics (where X  =  Ti, V, Mo or W) are predicted using density functional theory simulations and discussed with respect to fusion energy applications. Schottky disorder is found to be the lowest energy complete disorder process, closely matched by Be Frenkel disorder in the cases of Be12V and Be12Ti. Antitisite and X Frenkel disorder are of significantly higher energy. Small clusters of point defects including Be divacancies, Be di-interstitials and accommodation of the X species on two Be sites were considered. Some di-interstitial, divacancy and X2Be combinations exhibit negative binding enthalpy (i.e. clustering is favourable), although this is orientationally dependent. None of the Be12X intermetallics are predicted to exhibit significant non-stoichiometry, ruling out non-stoichiometry as a mechanism for accommodating Be depletion due to neutron transmutation.

Effect of Boron Clusters on the Ignition Reaction of HNO3 and Dicynanamide-Based Ionic Liquids.

PubMed

Schmidt, Michael W; Gordon, Mark S

2017-10-19

Many ionic liquids containing the dicynamide anion (DCA - , formula N(CN) 2 - ) exhibit hypergolic ignition when exposed to the common oxidizer nitric acid. However, the ignition delay is often about 10 times longer than the desired 5 ms for rocket applications, so that improvements are desired. Experiments in the past decade have suggested both a mechanism for the early reaction steps and also that additives such as decaborane can reduce the ignition delay. The mechanisms for reactions of nitric acid with both DCA - and protonated DCAH are considered here, using accurate wave function methods. Complexation of DCA - or DCAH with borane clusters B 10 H 14 or B 9 H 14 - is found to modify these mechanisms slightly by changing the nature of some of the intermediate saddle points and by small reductions in the reaction barriers.

Near-Infrared Spectroscopy of Small Protonated Water Clusters

NASA Astrophysics Data System (ADS)

Wagner, J. Philipp; McDonald, David C., II; McCoy, Anne B.; Duncan, Michael A.

2017-06-01

Small protonated water clusters and their argon tagged analogues of the general formula H^{+}(H_{2}O)_{n}Ar_{m} have been generated in a pulsed electric discharge source. Clusters containing n=1-8 water molecules were mass-selected and their absorptions in the near-infrared were probed with a tunable Nd/colonYAG pumped OPA/OPA laser system in the region from 4850-7350 cm^{-1}. A doublet corresponding to overtones of the free O-H stretches of the external waters was observed around 7200 cm^{-1} that was continuously decreasing in intensity with increasing cluster size. Broad, mostly featureless absorptions were found around 5300 cm^{-1} associated with stretch/bend combinations and with the hydrogen bonded waters in the core of the clusters. Vibrational assignments were substantiated by comparison to anharmonic frequency computations via second-order vibrational perturbation theory (VPT2) at the MP2/aug-cc-pVTZ level of theory.

Elucidation of Proton-Assisted Fluxionality in Transition-Metal Oxide Clusters

NASA Astrophysics Data System (ADS)

Ramabhadran, Raghunath O.; Mayhall, Nicholas J.; Becher, Edwin L. Becher, Iii; Chowdhury, Arefin; Raghavachari, Krishnan

2012-06-01

The phenomenon of fluxionality in the reactions of transition-metal oxide clusters provides many opportunities in various industrial and catalytic processes. We present an electronic structure investigation of the fluxionality pathways when anionic W3O6- and Mo3O6- clusters react with three small molecules - water, ammonia and hydrogen sulfide. The presentation features a detailed understanding of (a) how the fluxionality pathway occurs and (b) the various factors that affect the fluxionality pathway - such as the metal, different spin-states and the nature of the non-metal in the reacting small molecule.

Formation of positive cluster ions Li(n) Br (n = 2-7) and ionization energies studied by thermal ionization mass spectrometry.

PubMed

Veličković, S R; Đustebek, J B; Veljković, F M; Veljković, M V

2012-05-01

Clusters of the type Li(n)X (X = halides) can be considered as potential building blocks of cluster-assembly materials. In this work, Li(n)Br (n = 2-7) clusters were obtained by a thermal ionization source of modified design and selected by a magnetic sector mass spectrometer. Positive ions of the Li(n)Br (n = 4-7) cluster were detected for the first time. The order of ion intensities was Li(2)Br(+) > Li(4)Br(+) > Li(5)Br(+) > Li(6)Br(+) > Li(3)Br(+). The ionization energies (IEs) were measured and found to be 3.95 ± 0.20 eV for Li(2)Br, 3.92 ± 0.20 eV for Li(3)Br, 3.93 ± 0.20 eV for Li(4)Br, 4.08 ± 0.20 eV for Li(5)Br, 4.14 ± 0.20 eV for Li(6)Br and 4.19 ± 0.20 eV for Li(7)Br. All of these clusters have a much lower ionization potential than that of the lithium atom, so they belong to the superalkali class. The IEs of Li(n)Br (n = 2-4) are slightly lower than those in the corresponding small Li(n) or Li(n)H clusters, whereas the IEs of Li(n)Br are very similar to those of Li(n) or Li(n)H for n = 5 and 6. The thermal ionization source of modified design is an important means for simultaneously obtaining and measuring the IEs of Li(n)Br (n = 2-7) clusters (because their ions are hermodynamically stable with respect to the loss of lithium atoms in the gas phase) and increasingly contributes toward the development of clusters for practical applications. Copyright © 2012 John Wiley & Sons, Ltd.

Facile Syntheses of Monodisperse Ultra-Small Au Clusters

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

Bertino, Massimo F.; Sun, Zhong-Ming; Zhang, Rui

2006-11-02

During our effort to synthesize the tetrahedral Au20 cluster, we found a facile synthetic route to prepare monodisperse suspensions of ultra-small Au clusters AuN (N<12) using diphosphine ligands. In our monophasic and single-pot synthesis, a Au precursor ClAu(I)PPh3 and a bidentate phosphine ligand P(Ph)2(CH2)MP(Ph)2 (Ph = phenyl) are dissolved in an organic solvent. Au(I) is reduced slowly by a borane-tert-butylamine complex to form Au clusters coordinated by the diphosphine ligand. The Au clusters are characterized by both high resolution mass spectrometry and UV-Vis absorption spectroscopy. We found that the mean cluster size obtained depends on the chain length M ofmore » the ligand. In particular, a single monodispersed Au11 cluster is obtained with the P(Ph)2(CH2)3P(Ph)2 ligand, whereas P(Ph)2(CH2)MP(Ph)2 ligands with M = 5 and 6 yield Au10 and Au8 clusters. The simplicity of our synthetic method makes it suitable for large-scale production of nearly monodisperse ultrasmall Au clusters. It is suggested that diphosphines provide a set of flexible ligands to allow size-controlled synthesis of Au nanoparticles.« less

Construction and application of Red5 cluster based on OpenStack

NASA Astrophysics Data System (ADS)

Wang, Jiaqing; Song, Jianxin

2017-08-01

With the application and development of cloud computing technology in various fields, the resource utilization rate of the data center has been improved obviously, and the system based on cloud computing platform has also improved the expansibility and stability. In the traditional way, Red5 cluster resource utilization is low and the system stability is poor. This paper uses cloud computing to efficiently calculate the resource allocation ability, and builds a Red5 server cluster based on OpenStack. Multimedia applications can be published to the Red5 cloud server cluster. The system achieves the flexible construction of computing resources, but also greatly improves the stability of the cluster and service efficiency.

Binomial outcomes in dataset with some clusters of size two: can the dependence of twins be accounted for? A simulation study comparing the reliability of statistical methods based on a dataset of preterm infants.

PubMed

Sauzet, Odile; Peacock, Janet L

2017-07-20

The analysis of perinatal outcomes often involves datasets with some multiple births. These are datasets mostly formed of independent observations and a limited number of clusters of size two (twins) and maybe of size three or more. This non-independence needs to be accounted for in the statistical analysis. Using simulated data based on a dataset of preterm infants we have previously investigated the performance of several approaches to the analysis of continuous outcomes in the presence of some clusters of size two. Mixed models have been developed for binomial outcomes but very little is known about their reliability when only a limited number of small clusters are present. Using simulated data based on a dataset of preterm infants we investigated the performance of several approaches to the analysis of binomial outcomes in the presence of some clusters of size two. Logistic models, several methods of estimation for the logistic random intercept models and generalised estimating equations were compared. The presence of even a small percentage of twins means that a logistic regression model will underestimate all parameters but a logistic random intercept model fails to estimate the correlation between siblings if the percentage of twins is too small and will provide similar estimates to logistic regression. The method which seems to provide the best balance between estimation of the standard error and the parameter for any percentage of twins is the generalised estimating equations. This study has shown that the number of covariates or the level two variance do not necessarily affect the performance of the various methods used to analyse datasets containing twins but when the percentage of small clusters is too small, mixed models cannot capture the dependence between siblings.

Representative landscapes in the forested area of Canada.

PubMed

Cardille, Jeffrey A; White, Joanne C; Wulder, Mike A; Holland, Tara

2012-01-01

Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada's land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative-or "exemplar"-from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada's ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada's forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach.

Representative Landscapes in the Forested Area of Canada

NASA Astrophysics Data System (ADS)

Cardille, Jeffrey A.; White, Joanne C.; Wulder, Mike A.; Holland, Tara

2012-01-01

Canada is a large nation with forested ecosystems that occupy over 60% of the national land base, and knowledge of the patterns of Canada's land cover is important to proper environmental management of this vast resource. To this end, a circa 2000 Landsat-derived land cover map of the forested ecosystems of Canada has created a new window into understanding the composition and configuration of land cover patterns in forested Canada. Strategies for summarizing such large expanses of land cover are increasingly important, as land managers work to study and preserve distinctive areas, as well as to identify representative examples of current land-cover and land-use assemblages. Meanwhile, the development of extremely efficient clustering algorithms has become increasingly important in the world of computer science, in which billions of pieces of information on the internet are continually sifted for meaning for a vast variety of applications. One recently developed clustering algorithm quickly groups large numbers of items of any type in a given data set while simultaneously selecting a representative—or "exemplar"—from each cluster. In this context, the availability of both advanced data processing methods and a nationally available set of landscape metrics presents an opportunity to identify sets of representative landscapes to better understand landscape pattern, variation, and distribution across the forested area of Canada. In this research, we first identify and provide context for a small, interpretable set of exemplar landscapes that objectively represent land cover in each of Canada's ten forested ecozones. Then, we demonstrate how this approach can be used to identify flagship and satellite long-term study areas inside and outside protected areas in the province of Ontario. These applications aid our understanding of Canada's forest while augmenting its management toolbox, and may signal a broad range of applications for this versatile approach.

Effect of small versus large clusters of fish school on the yield of a purse-seine small pelagic fishery including a marine protected area.

PubMed

Hieu, Nguyen Trong; Brochier, Timothée; Tri, Nguyen-Huu; Auger, Pierre; Brehmer, Patrice

2014-09-01

We consider a fishery model with two sites: (1) a marine protected area (MPA) where fishing is prohibited and (2) an area where the fish population is harvested. We assume that fish can migrate from MPA to fishing area at a very fast time scale and fish spatial organisation can change from small to large clusters of school at a fast time scale. The growth of the fish population and the catch are assumed to occur at a slow time scale. The complete model is a system of five ordinary differential equations with three time scales. We take advantage of the time scales using aggregation of variables methods to derive a reduced model governing the total fish density and fishing effort at the slow time scale. We analyze this aggregated model and show that under some conditions, there exists an equilibrium corresponding to a sustainable fishery. Our results suggest that in small pelagic fisheries the yield is maximum for a fish population distributed among both small and large clusters of school.

Measurement of the spectral signature of small carbon clusters at near and far infrared wavelengths

NASA Technical Reports Server (NTRS)

Tarter, J.; Saykally, R.

1991-01-01

A significant percentage of the carbon inventory of the circumstellar and interstellar media may be in the form of large refractory molecules (or small grains) referred to as carbon clusters. At the small end, uneven numbers of carbon atoms seem to be preferred, whereas above 12 atoms, clusters containing an even number of carbon atoms appear to be preferred in laboratory chemistry. In the lab, the cluster C-60 appears to be a particularly stable form and has been nicknamed Bucky Balls because of its resemblance to a soccer ball and to geodesic domes designed by Buckminster Fuller. In order to investigate the prevalence of these clusters, and their relationship to the polycyclic aromatic hydrocarbons (PAHs) that have become the newest focus of IR astronomy, it is necessary to determine the spectroscopic characteristics of these clusters at near and far infrared wavelengths. Described here is the construction of a near to far IR laser magnetic resonance spectrometer that has been built at the University of California Berkeley in order to detect and characterize these spectra. The equipment produces carbon clusters by laser evaporation of a graphitic target. The clusters are then cooled in a supersonic expansion beam in order to simulate conditions in the interstellar medium (ISM). The expansion beam feeds into the spectrometer chamber and permits concentrations of clusters sufficiently high as to permit ultra-high resolution spectroscopy at near and far IR wavelengths. The first successful demonstration of this apparatus occurred last year when the laboratory studies permitted the observational detection of C-5 in the stellar outflow surrounding IRC+10216 in the near-IR. Current efforts focus on reducing the temperature of the supersonic expansion beam that transport the C clusters evaporated from a graphite target into the spectrometer down to temperatures as low as 1 K.

A hierarchical cluster analysis of normal-tension glaucoma using spectral-domain optical coherence tomography parameters.

PubMed

Bae, Hyoung Won; Ji, Yongwoo; Lee, Hye Sun; Lee, Naeun; Hong, Samin; Seong, Gong Je; Sung, Kyung Rim; Kim, Chan Yun

2015-01-01

Normal-tension glaucoma (NTG) is a heterogenous disease, and there is still controversy about subclassifications of this disorder. On the basis of spectral-domain optical coherence tomography (SD-OCT), we subdivided NTG with hierarchical cluster analysis using optic nerve head (ONH) parameters and retinal nerve fiber layer (RNFL) thicknesses. A total of 200 eyes of 200 NTG patients between March 2011 and June 2012 underwent SD-OCT scans to measure ONH parameters and RNFL thicknesses. We classified NTG into homogenous subgroups based on these variables using a hierarchical cluster analysis, and compared clusters to evaluate diverse NTG characteristics. Three clusters were found after hierarchical cluster analysis. Cluster 1 (62 eyes) had the thickest RNFL and widest rim area, and showed early glaucoma features. Cluster 2 (60 eyes) was characterized by the largest cup/disc ratio and cup volume, and showed advanced glaucomatous damage. Cluster 3 (78 eyes) had small disc areas in SD-OCT and were comprised of patients with significantly younger age, longer axial length, and greater myopia than the other 2 groups. A hierarchical cluster analysis of SD-OCT scans divided NTG patients into 3 groups based upon ONH parameters and RNFL thicknesses. It is anticipated that the small disc area group comprised of younger and more myopic patients may show unique features unlike the other 2 groups.

Low-temperature cluster catalysis.

PubMed

Judai, Ken; Abbet, Stéphane; Wörz, Anke S; Heiz, Ulrich; Henry, Claude R

2004-03-10

Free and supported metal clusters reveal unique chemical and physical properties, which vary as a function of size as each cluster possesses a characteristic electron confinement. Several previous experimental results showed that the outcome of a given chemical reaction can be controlled by tuning the cluster size. However, none of the examples indicate that clusters prepared in the gas phase and then deposited on a support material are indeed catalytically active over several reaction cycles nor that their catalytic properties remain constant during such a catalytic process. In this work we report turn-over frequencies (TOF) for Pd(n) (n = 4, 8, 30) clusters using pulsed molecular beam experiments. The obtained results illustrate that the catalytic reactivity for the NO reduction by CO (CO + NO --> 1/2N(2) + CO(2)) is indeed a function of cluster size and that the measured TOF remain constant at a given temperature. More interestingly, the temperature of maximal reactivity is at least 100 K lower than observed for palladium nanoparticles or single crystals. One reason for this surprising observation is the character of the binding sites of these small clusters: N(2) forms already at relatively low temperatures (400 and 450 K) and therefore poisoning by adsorbed nitrogen adatoms is prevented. Thus, small clusters not only open the possibility of tuning a catalytic process by changing cluster size, but also of catalyzing chemical reactions at low temperatures.

The Aftermath of a Suicide Cluster in the Age of Online Social Networking: A Qualitative Analysis of Adolescent Grief Reactions

ERIC Educational Resources Information Center

Heffel, Carly J.; Riggs, Shelley A.; Ruiz, John M.; Ruggles, Mark

2015-01-01

Although suicide clusters have been identified in many populations, research exploring the role of online communication in the aftermath of a suicide cluster is extremely limited. This study used the Consensual Qualitative Research method to analyze interviews with ten high school students 1 year after a suicide cluster in a small suburban school…

Properties of Diamond and Diamond-Like Clusters in Nanometric Dimensions

NASA Technical Reports Server (NTRS)

Halicioglu, Timur; Langhoff, Stephen R. (Technical Monitor)

1996-01-01

Variations in materials properties of small clusters of nanometric dimensions were investigated. Investigations were carried out for diamond and diamond-like particles in spherical shapes. Calculations were performed for clusters containing over 1000 carbon atoms. Results indicate that as the cluster size diminishes, (i) the average cohesive energy becomes weaker, (ii) the excess surface energy increases, and (iii) the value for stiffness decreases.

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.

Investigating the role of small vent volcanism during the development of Tharsis Province, Mars

NASA Astrophysics Data System (ADS)

Richardson, J. A.; Bleacher, J. E.; Connor, C.; Connor, L.; Glaze, L. S.

2014-12-01

Clusters of tens to hundreds of small volcanic vents have recently been recognized as a major component of Tharsis Province volcanism. These volcanic fields are formed from distributed-style, possibly monogenetic, volcanism and are composed of low sloped edifices with diameters of tens of kilometers and heights of tens to hundreds of meters. We report a new catalog of these small volcanic vents, now available through the USGS Astrogeology Science Center. This catalog was created with the use of gridded topographic data from the Mars Orbiter Laser Altimeter (MOLA) and images from the Thermal Emission Imaging System (THEMIS) and the High Resolution Stereo Camera (HRSC). We are now investigating isolated clusters of distributed volcanism in Tharsis with this dataset. We hypothesize that these clusters are formed from significant magmatic events that played a large role in the development of Tharsis. Currently, the catalog contains 1075 unique volcanic vents in the Tharsis Province. With the catalog, potentially isolated volcano clusters are identified with vent density estimation. Vent intensity for clusters is found to be 1 vent per 1000 sq km or less. Crater retention rates for one such cluster, Syria Planum, indicates that these distributed volcanic systems might continue as long as 700 Ma, or that monogenetic volcanic systems overprint older systems. Using a modified basal outlining algorithm with MOLA gridded data, shield volumes are found to be between 1-20 cubic km. Current results show distributed-style volcanism occuring in Tharsis orders of magnitude more dispersed than analogous volcano clusers on Earth, while individual edifices are found to be an order of magnitude larger than volcanoes in Earth clusters. Proof of concept results are reported for three identified clusters: Arsia Mons Caldera, Syria Planum, and Southern Pavonis Mons.

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

Adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique algorithm for tackling binary imbalanced datasets in biomedical data classification.

PubMed

Li, Jinyan; Fong, Simon; Sung, Yunsick; Cho, Kyungeun; Wong, Raymond; Wong, Kelvin K L

2016-01-01

An imbalanced dataset is defined as a training dataset that has imbalanced proportions of data in both interesting and uninteresting classes. Often in biomedical applications, samples from the stimulating class are rare in a population, such as medical anomalies, positive clinical tests, and particular diseases. Although the target samples in the primitive dataset are small in number, the induction of a classification model over such training data leads to poor prediction performance due to insufficient training from the minority class. In this paper, we use a novel class-balancing method named adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique (ASCB_DmSMOTE) to solve this imbalanced dataset problem, which is common in biomedical applications. The proposed method combines under-sampling and over-sampling into a swarm optimisation algorithm. It adaptively selects suitable parameters for the rebalancing algorithm to find the best solution. Compared with the other versions of the SMOTE algorithm, significant improvements, which include higher accuracy and credibility, are observed with ASCB_DmSMOTE. Our proposed method tactfully combines two rebalancing techniques together. It reasonably re-allocates the majority class in the details and dynamically optimises the two parameters of SMOTE to synthesise a reasonable scale of minority class for each clustered sub-imbalanced dataset. The proposed methods ultimately overcome other conventional methods and attains higher credibility with even greater accuracy of the classification model.

Polymorphism in magic-sized Au144(SR)60 clusters

DOE PAGES

Jensen, Kirsten M. O.; Juhas, Pavol; Tofanelli, Marcus A.; ...

2016-06-14

Ultra-small, magic-sized metal nanoclusters represent an important new class of materials with properties between molecules and particles. However, their small size challenges the conventional methods for structure characterization. We present the structure of ultra-stable Au144(SR)60 magic-sized nanoclusters obtained from atomic pair distribution function analysis of X-ray powder diffraction data. Our study reveals structural polymorphism in these archetypal nanoclusters. Additionally, in order to confirm the theoretically predicted icosahedral-cored cluster, we also find samples with a truncated decahedral core structure, with some samples exhibiting a coexistence of both cluster structures. Although the clusters are monodisperse in size, structural diversity is apparent. Finally,more » the discovery of polymorphism may open up a new dimension in nanoscale engineering.« less

Information Clustering Based on Fuzzy Multisets.

ERIC Educational Resources Information Center

Miyamoto, Sadaaki

2003-01-01

Proposes a fuzzy multiset model for information clustering with application to information retrieval on the World Wide Web. Highlights include search engines; term clustering; document clustering; algorithms for calculating cluster centers; theoretical properties concerning clustering algorithms; and examples to show how the algorithms work.…

Innovative Improvement and Intensification of Business Relationships Supported by Cooperative Networks

NASA Astrophysics Data System (ADS)

Vančová, Viera; Čambál, Miloš; Cagáňová, Dagmar

2012-12-01

Nowadays, the opportunity for companies to be involved in cluster initiatives and international business associations is a major factor that contributes to the increase of their innovative potential. Companies organized in technological clusters have greater access to mutual business contacts, faster information transfer and deployment of advanced technologies. These companies cooperate more frequently with universities and research - development institutions on innovative projects. An important benefit of cluster associations is that they create a suitable environment for innovation and the transfer of knowledge by means of international cooperation and networking. This supportive environment is not easy to access for different small and mediumsized companies, who are not members of any clusters or networks. Supplier-customer business channels expand by means of transnational networks and exchanges of experience. Knowledge potential is broadened and joint innovative projects are developed. Reflecting the growing importance of clusters as driving forces of economic and regional development, a number of cluster policies and initiatives have emerged in the last few decades, oriented to encourage the establishment of new clusters, to support existing clusters, or to assist the development of transnational cooperation. To achieve the goals of the Europe 2020 Strategy, European countries should have an interest in building strong clusters and developing cluster cooperation by sharing specialized research infrastructures and testing facilities and facilitating knowledge transfer for crossborder cooperation. This requires developing a long term joint strategy in order to facilitate the development of open global clusters and innovative small and medium entrepreneurs.

Detecting cancer clusters in a regional population with local cluster tests and Bayesian smoothing methods: a simulation study

PubMed Central

2013-01-01

Background There is a rising public and political demand for prospective cancer cluster monitoring. But there is little empirical evidence on the performance of established cluster detection tests under conditions of small and heterogeneous sample sizes and varying spatial scales, such as are the case for most existing population-based cancer registries. Therefore this simulation study aims to evaluate different cluster detection methods, implemented in the open soure environment R, in their ability to identify clusters of lung cancer using real-life data from an epidemiological cancer registry in Germany. Methods Risk surfaces were constructed with two different spatial cluster types, representing a relative risk of RR = 2.0 or of RR = 4.0, in relation to the overall background incidence of lung cancer, separately for men and women. Lung cancer cases were sampled from this risk surface as geocodes using an inhomogeneous Poisson process. The realisations of the cancer cases were analysed within small spatial (census tracts, N = 1983) and within aggregated large spatial scales (communities, N = 78). Subsequently, they were submitted to the cluster detection methods. The test accuracy for cluster location was determined in terms of detection rates (DR), false-positive (FP) rates and positive predictive values. The Bayesian smoothing models were evaluated using ROC curves. Results With moderate risk increase (RR = 2.0), local cluster tests showed better DR (for both spatial aggregation scales > 0.90) and lower FP rates (both < 0.05) than the Bayesian smoothing methods. When the cluster RR was raised four-fold, the local cluster tests showed better DR with lower FPs only for the small spatial scale. At a large spatial scale, the Bayesian smoothing methods, especially those implementing a spatial neighbourhood, showed a substantially lower FP rate than the cluster tests. However, the risk increases at this scale were mostly diluted by data aggregation. Conclusion High resolution spatial scales seem more appropriate as data base for cancer cluster testing and monitoring than the commonly used aggregated scales. We suggest the development of a two-stage approach that combines methods with high detection rates as a first-line screening with methods of higher predictive ability at the second stage. PMID:24314148

Volume dependence of N-body bound states

NASA Astrophysics Data System (ADS)

König, Sebastian; Lee, Dean

2018-04-01

We derive the finite-volume correction to the binding energy of an N-particle quantum bound state in a cubic periodic volume. Our results are applicable to bound states with arbitrary composition and total angular momentum, and in any number of spatial dimensions. The only assumptions are that the interactions have finite range. The finite-volume correction is a sum of contributions from all possible breakup channels. In the case where the separation is into two bound clusters, our result gives the leading volume dependence up to exponentially small corrections. If the separation is into three or more clusters, there is a power-law factor that is beyond the scope of this work, however our result again determines the leading exponential dependence. We also present two independent methods that use finite-volume data to determine asymptotic normalization coefficients. The coefficients are useful to determine low-energy capture reactions into weakly bound states relevant for nuclear astrophysics. Using the techniques introduced here, one can even extract the infinite-volume energy limit using data from a single-volume calculation. The derived relations are tested using several exactly solvable systems and numerical examples. We anticipate immediate applications to lattice calculations of hadronic, nuclear, and cold atomic systems.

Semi-Supervised Clustering for High-Dimensional and Sparse Features

ERIC Educational Resources Information Center

Yan, Su

2010-01-01

Clustering is one of the most common data mining tasks, used frequently for data organization and analysis in various application domains. Traditional machine learning approaches to clustering are fully automated and unsupervised where class labels are unknown a priori. In real application domains, however, some "weak" form of side…

Synthesis and Ligand-Exchange Reactions of a Tri-Tungsten Cluster with Applications in Biomedical Imaging

ERIC Educational Resources Information Center

Noey, Elizabeth; Curtis, Jeff C.; Tam, Sylvia; Pham, David M.; Jones, Ella F.

2011-01-01

In this experiment students are exposed to concepts in inorganic synthesis and various spectroscopies as applied to a tri-tungsten cluster with applications in biomedical imaging. The tungsten-acetate cluster, Na[W[superscript 3](mu-O)[subscript 2](CH[superscript 3]COO)[superscript 9

Conversion of Methane into Methanol and Ethanol over Nickel Oxide on Ceria-Zirconia Catalysts in a Single Reactor

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

Okolie, Chukwuemeka; Belhseine, Yasmeen F.; Lyu, Yimeng

Direct conversion of methane into alcohols is a promising technology for converting stranded methane reserves into liquids that can be transported in pipelines and upgraded to value-added chemicals. We demonstrate that a catalyst consisting of small nickel oxide clusters supported on ceria-zirconia (NiO/CZ) can selectively oxidize methane to methanol and ethanol in a single, steady-state process at 723 K using O2 as an abundantly available oxidant. The presence of steam is required to obtain alcohols rather than CO2 as the product of catalytic combustion. The unusual activity of this catalyst is attributed to the synergy between the small Lewis acidicmore » NiO clusters and the redox-active CZ support, which also stabilizes the small NiO clusters.« less

Conversion of Methane to Methanol and Ethanol over Nickel Oxide on Ceria-Zirconia Catalysts in a Single Reactor

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

Okolie, Chukwuemeka; Belhseine, Yasmeen F.; Lyu, Yimeng

Here, the conversion of methane into alcohols under moderate reaction conditions is a promising technology for converting stranded methane reserves into liquids that can be transported in pipelines and upgraded to value-added chemicals. We demonstrate that a catalyst consisting of small nickel oxide clusters supported on ceria-zirconia (NiO/CZ) can convert methane to methanol and ethanol in a single, steady-state process at 723 K using O 2 as an abundantly available oxidant. The presence of steam is required to obtain alcohols rather than CO 2 as the product of catalytic combustion. The unusual activity of this catalyst is attributed to themore » synergy between the small Lewis acidic NiO clusters and the redox-active CZ support, which also stabilizes the small NiO clusters.« less

Conversion of Methane to Methanol and Ethanol over Nickel Oxide on Ceria-Zirconia Catalysts in a Single Reactor

DOE PAGES

Okolie, Chukwuemeka; Belhseine, Yasmeen F.; Lyu, Yimeng; ...

2017-08-08

Here, the conversion of methane into alcohols under moderate reaction conditions is a promising technology for converting stranded methane reserves into liquids that can be transported in pipelines and upgraded to value-added chemicals. We demonstrate that a catalyst consisting of small nickel oxide clusters supported on ceria-zirconia (NiO/CZ) can convert methane to methanol and ethanol in a single, steady-state process at 723 K using O 2 as an abundantly available oxidant. The presence of steam is required to obtain alcohols rather than CO 2 as the product of catalytic combustion. The unusual activity of this catalyst is attributed to themore » synergy between the small Lewis acidic NiO clusters and the redox-active CZ support, which also stabilizes the small NiO clusters.« less

New Theoretical Developments in Exploring Electronically Excited States: Including Localized Configuration Interaction Singles and Application to Large Helium Clusters

NASA Astrophysics Data System (ADS)

Closser, Kristina Danielle

This thesis presents new developments in excited state electronic structure theory. Contrasted with the ground state, the electronically excited states of atoms and molecules often are unstable and have short lifetimes, exhibit a greater diversity of character and are generally less well understood. The very unusual excited states of helium clusters motivated much of this work. These clusters consist of large numbers of atoms (experimentally 103--109 atoms) and bands of nearly degenerate excited states. For an isolated atom the lowest energy excitation energies are from 1s → 2s and 1s → 2 p transitions, and in clusters describing the lowest energy band minimally requires four states per atom. In the ground state the clusters are weakly bound by van der Waals interactions, however in the excited state they can form well-defined covalent bonds. The computational cost of quantum chemical calculations rapidly becomes prohibitive as the size of the systems increase. Standard excited-state methods such as configuration interaction singles (CIS) and time-dependent density functional theory (TD-DFT) can be used with ≈100 atoms, and are optimized to treat only a few states. Thus, one of our primary aims is to develop a method which can treat these large systems with large numbers of nearly degenerate excited states. Additionally, excited states are generally formed far from their equilibrium structures. Vertical excitations from the ground state induce dynamics in the excited states. Thus, another focus of this work is to explore the results of these forces and the fate of the excited states. Very little was known about helium cluster excited states when this work began, thus we first investigated the excitations in small helium clusters consisting of 7 or 25 atoms using CIS. The character of these excited states was determined using attachment/detachment density analysis and we found that in the n = 2 manifold the excitations could generally be interpreted as superpositions of atomic states with surface states appearing close to the atomic excitation energies and interior states being blue shifted by up to ≈2 eV. The dynamics resulting from excitation of He_7 were subsequently explored using ab initio molecular dynamics (AIMD). These simulations were performed with classical adiabatic dynamics coupled to a new state-following algorithm on CIS potential energy surfaces. Most clusters were found to completely dissociate and resulted in a single excited atomic state (90%), however, some trajectories formed bound, He*2 (3%), and a few yielded excited trimers (<0.5%). Comparisons were made with available experimental information on much larger clusters. Various applications of this state following algorithm are also presented. In addition to AIMD, these include excited-state geometry optimization and minimal energy path finding via the growing string method. When using state following we demonstrate that more physical results can be obtained with AIMD calculations. Also, the optimized geometries of three excited states of cytosine, two of which were not found without state following, and the minimal energy path between the lowest two singlet excited states of protonated formaldimine are offered as example applications. Finally, to address large clusters, a local variation of CIS was developed. This method exploits the properties of absolutely localized molecular orbitals (ALMOs) to limit the total number of excitations to scaling only linearly with cluster size, which results in formal scaling with the third power of the system size. The derivation of the equations and design of the algorithm are discussed in detail, and computational timings as well as a pilot application to the size dependence of the helium cluster spectrum are presented.

A comparative hidden Markov model analysis pipeline identifies proteins characteristic of cereal-infecting fungi

PubMed Central

2013-01-01

Background Fungal pathogens cause devastating losses in economically important cereal crops by utilising pathogen proteins to infect host plants. Secreted pathogen proteins are referred to as effectors and have thus far been identified by selecting small, cysteine-rich peptides from the secretome despite increasing evidence that not all effectors share these attributes. Results We take advantage of the availability of sequenced fungal genomes and present an unbiased method for finding putative pathogen proteins and secreted effectors in a query genome via comparative hidden Markov model analyses followed by unsupervised protein clustering. Our method returns experimentally validated fungal effectors in Stagonospora nodorum and Fusarium oxysporum as well as the N-terminal Y/F/WxC-motif from the barley powdery mildew pathogen. Application to the cereal pathogen Fusarium graminearum reveals a secreted phosphorylcholine phosphatase that is characteristic of hemibiotrophic and necrotrophic cereal pathogens and shares an ancient selection process with bacterial plant pathogens. Three F. graminearum protein clusters are found with an enriched secretion signal. One of these putative effector clusters contains proteins that share a [SG]-P-C-[KR]-P sequence motif in the N-terminal and show features not commonly associated with fungal effectors. This motif is conserved in secreted pathogenic Fusarium proteins and a prime candidate for functional testing. Conclusions Our pipeline has successfully uncovered conservation patterns, putative effectors and motifs of fungal pathogens that would have been overlooked by existing approaches that identify effectors as small, secreted, cysteine-rich peptides. It can be applied to any pathogenic proteome data, such as microbial pathogen data of plants and other organisms. PMID:24252298

Crystalline embryos at ice-vapor interfaces

NASA Technical Reports Server (NTRS)

Bartley, D. L.

1976-01-01

The nucleation of small monolayer ice-like clusters at the basal and prism ice-vapor interfaces is considered. It is found that the basal surfaces prefer triangular embryos with an orientation that reverses from layer to layer, whereas the most stable clusters on the prism surfaces are rectangular in configuration. At any given saturation ratio, the preferred prism clusters are found to have a critical energy of formation significantly lower than that of the basal clusters, basically because of differences in cluster corner free energies.

Collision-Induced Dissociation of Electrosprayed NaCl Clusters: Using Molecular Dynamics Simulations to Visualize Reaction Cascades in the Gas Phase

NASA Astrophysics Data System (ADS)

Schachel, Tilo D.; Metwally, Haidy; Popa, Vlad; Konermann, Lars

2016-11-01

Infusion of NaCl solutions into an electrospray ionization (ESI) source produces [Na( n+1)Cl n ]+ and other gaseous clusters. The n = 4, 13, 22 magic number species have cuboid ground state structures and exhibit elevated abundance in ESI mass spectra. Relatively few details are known regarding the mechanisms whereby these clusters undergo collision-induced dissociation (CID). The current study examines to what extent molecular dynamics (MD) simulations can be used to garner insights into the sequence of events taking place during CID. Experiments on singly charged clusters reveal that the loss of small neutrals is the dominant fragmentation pathway. MD simulations indicate that the clusters undergo extensive structural fluctuations prior to decomposition. Consistent with the experimentally observed behavior, most of the simulated dissociation events culminate in ejection of small neutrals ([NaCl] i , with i = 1, 2, 3). The MD data reveal that the prevalence of these dissociation channels is linked to the presence of short-lived intermediates where a relatively compact core structure carries a small [NaCl] i protrusion. The latter can separate from the parent cluster via cleavage of a single Na-Cl contact. Fragmentation events of this type are kinetically favored over other dissociation channels that would require the quasi-simultaneous rupture of multiple electrostatic contacts. The CID behavior of NaCl cluster ions bears interesting analogies to that of collisionally activated protein complexes. Overall, it appears that MD simulations represent a valuable tool for deciphering the dissociation of noncovalently bound systems in the gas phase.

Towards Accurate Modelling of Galaxy Clustering on Small Scales: Testing the Standard ΛCDM + Halo Model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

2018-04-01

Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter halos. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the "accurate" regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard ΛCDM + halo model against the clustering of SDSS DR7 galaxies. Specifically, we use the projected correlation function, group multiplicity function and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir halos) matches the clustering of low luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the "standard" halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

Inherent size effects on XANES of nanometer metal clusters: Size-selected platinum clusters on silica

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

Dai, Yang; Gorey, Timothy J.; Anderson, Scott L.

2016-12-12

X-ray absorption near-edge structure (XANES) is commonly used to probe the oxidation state of metal-containing nanomaterials, however, as the particle size in the material drops below a few nanometers, it becomes important to consider inherent size effects on the electronic structure of the materials. In this paper, we analyze a series of size-selected Pt n/SiO 2 samples, using X-ray photoelectron spectroscopy (XPS), low energy ion scattering, grazing-incidence small angle X-ray scattering, and XANES. The oxidation state and morphology are characterized both as-deposited in UHV, and after air/O 2 exposure and annealing in H 2. Here, the clusters are found tomore » be stable during deposition and upon air exposure, but sinter if heated above ~150 °C. XANES shows shifts in the Pt L 3 edge, relative to bulk Pt, that increase with decreasing cluster size, and the cluster samples show high white line intensity. Reference to bulk standards would suggest that the clusters are oxidized, however, XPS shows that they are not. Instead, the XANES effects are attributable to development of a band gap and localization of empty state wavefunctions in small clusters.« less

Developing cluster strategy of apples dodol SMEs by integration K-means clustering and analytical hierarchy process method

NASA Astrophysics Data System (ADS)

Mustaniroh, S. A.; Effendi, U.; Silalahi, R. L. R.; Sari, T.; Ala, M.

2018-03-01

The purposes of this research were to determine the grouping of apples dodol small and medium enterprises (SMEs) in Batu City and to determine an appropriate development strategy for each cluster. The methods used for clustering SMEs was k-means. The Analytical Hierarchy Process (AHP) approach was then applied to determine the development strategy priority for each cluster. The variables used in grouping include production capacity per month, length of operation, investment value, average sales revenue per month, amount of SMEs assets, and the number of workers. Several factors were considered in AHP include industry cluster, government, as well as related and supporting industries. Data was collected using the methods of questionaire and interviews. SMEs respondents were selected among SMEs appels dodol in Batu City using purposive sampling. The result showed that two clusters were formed from five apples dodol SMEs. The 1stcluster of apples dodol SMEs, classified as small enterprises, included SME A, SME C, and SME D. The 2ndcluster of SMEs apples dodol, classified as medium enterprises, consisted of SME B and SME E. The AHP results indicated that the priority development strategy for the 1stcluster of apples dodol SMEs was improving quality and the product standardisation, while for the 2nd cluster was increasing the marketing access.

Frequency-sensitive competitive learning for scalable balanced clustering on high-dimensional hyperspheres.

PubMed

Banerjee, Arindam; Ghosh, Joydeep

2004-05-01

Competitive learning mechanisms for clustering, in general, suffer from poor performance for very high-dimensional (>1000) data because of "curse of dimensionality" effects. In applications such as document clustering, it is customary to normalize the high-dimensional input vectors to unit length, and it is sometimes also desirable to obtain balanced clusters, i.e., clusters of comparable sizes. The spherical kmeans (spkmeans) algorithm, which normalizes the cluster centers as well as the inputs, has been successfully used to cluster normalized text documents in 2000+ dimensional space. Unfortunately, like regular kmeans and its soft expectation-maximization-based version, spkmeans tends to generate extremely imbalanced clusters in high-dimensional spaces when the desired number of clusters is large (tens or more). This paper first shows that the spkmeans algorithm can be derived from a certain maximum likelihood formulation using a mixture of von Mises-Fisher distributions as the generative model, and in fact, it can be considered as a batch-mode version of (normalized) competitive learning. The proposed generative model is then adapted in a principled way to yield three frequency-sensitive competitive learning variants that are applicable to static data and produced high-quality and well-balanced clusters for high-dimensional data. Like kmeans, each iteration is linear in the number of data points and in the number of clusters for all the three algorithms. A frequency-sensitive algorithm to cluster streaming data is also proposed. Experimental results on clustering of high-dimensional text data sets are provided to show the effectiveness and applicability of the proposed techniques. Index Terms-Balanced clustering, expectation maximization (EM), frequency-sensitive competitive learning (FSCL), high-dimensional clustering, kmeans, normalized data, scalable clustering, streaming data, text clustering.

CA II TRIPLET SPECTROSCOPY OF SMALL MAGELLANIC CLOUD RED GIANTS. III. ABUNDANCES AND VELOCITIES FOR A SAMPLE OF 14 CLUSTERS

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

Parisi, M. C.; Clariá, J. J.; Marcionni, N.

2015-05-15

We obtained spectra of red giants in 15 Small Magellanic Cloud (SMC) clusters in the region of the Ca ii lines with FORS2 on the Very Large Telescope. We determined the mean metallicity and radial velocity with mean errors of 0.05 dex and 2.6 km s{sup −1}, respectively, from a mean of 6.5 members per cluster. One cluster (B113) was too young for a reliable metallicity determination and was excluded from the sample. We combined the sample studied here with 15 clusters previously studied by us using the same technique, and with 7 clusters whose metallicities determined by other authorsmore » are on a scale similar to ours. This compilation of 36 clusters is the largest SMC cluster sample currently available with accurate and homogeneously determined metallicities. We found a high probability that the metallicity distribution is bimodal, with potential peaks at −1.1 and −0.8 dex. Our data show no strong evidence of a metallicity gradient in the SMC clusters, somewhat at odds with recent evidence from Ca ii triplet spectra of a large sample of field stars. This may be revealing possible differences in the chemical history of clusters and field stars. Our clusters show a significant dispersion of metallicities, whatever age is considered, which could be reflecting the lack of a unique age–metallicity relation in this galaxy. None of the chemical evolution models currently available in the literature satisfactorily represents the global chemical enrichment processes of SMC clusters.« less

Dependence of the clustering properties of galaxies on stellar velocity dispersion in the Main galaxy sample of SDSS DR10

NASA Astrophysics Data System (ADS)

Deng, Xin-Fa; Song, Jun; Chen, Yi-Qing; Jiang, Peng; Ding, Ying-Ping

2014-08-01

Using two volume-limited Main galaxy samples of the Sloan Digital Sky Survey Data Release 10 (SDSS DR10), we investigate the dependence of the clustering properties of galaxies on stellar velocity dispersion by cluster analysis. It is found that in the luminous volume-limited Main galaxy sample, except at r=1.2, richer and larger systems can be more easily formed in the large stellar velocity dispersion subsample, while in the faint volume-limited Main galaxy sample, at r≥0.9, an opposite trend is observed. According to statistical analyses of the multiplicity functions, we conclude in two volume-limited Main galaxy samples: small stellar velocity dispersion galaxies preferentially form isolated galaxies, close pairs and small group, while large stellar velocity dispersion galaxies preferentially inhabit the dense groups and clusters. However, we note the difference between two volume-limited Main galaxy samples: in the faint volume-limited Main galaxy sample, at r≥0.9, the small stellar velocity dispersion subsample has a higher proportion of galaxies in superclusters ( n≥200) than the large stellar velocity dispersion subsample.

The fate of NGC602, an intense region of star-formation in the Wing of the SMC

NASA Astrophysics Data System (ADS)

Sabbi, Elena

2017-08-01

This is a small 2 orbit proposal designed to measure the internal dynamics of NGC602, a small region of intense star formation in the Wing of the SMC, with a low gas and dust density that has been often considered an unfavorable place for star formation. Small regions of massive star formation are important to study for our understanding of the process of star and cluster formation, the ionization of the interstellar medium, and the injection of energy and momentum into their host galaxy. By combining our new observations with archival ACS/WFC data acquired in July 2004, we will be able to measure the relative proper motions of the NGC602 sub-structures better than 2.3 km/s and investigate the nature of the apparently isolated massive stars found around NGC602. This study will provide unique observational data to characterize the early phase of cluster evolution and test cluster formation theories. It will also address significant open issues in star formation, cluster dynamics and the origin of isolated supernovae and GRBs.

The Organization of Children's Same-Sex Peer Relationships.

ERIC Educational Resources Information Center

Benenson, Joyce; Apostoleris, Nicholas; Parnass, Jodi

1998-01-01

Uses a sociometric analysis to explore the differential organization of boys' and girls' peer groups. Finds that boys structure their peer groups by creating a large central cluster composed of smaller integrated clusters, whereas girls form small clusters unrelated to one another. Nevertheless, girls are aware of and sensitive to the status of…

Platinum clusters with precise numbers of atoms for preparative-scale catalysis.

PubMed

Imaoka, Takane; Akanuma, Yuki; Haruta, Naoki; Tsuchiya, Shogo; Ishihara, Kentaro; Okayasu, Takeshi; Chun, Wang-Jae; Takahashi, Masaki; Yamamoto, Kimihisa

2017-09-25

Subnanometer noble metal clusters have enormous potential, mainly for catalytic applications. Because a difference of only one atom may cause significant changes in their reactivity, a preparation method with atomic-level precision is essential. Although such a precision with enough scalability has been achieved by gas-phase synthesis, large-scale preparation is still at the frontier, hampering practical applications. We now show the atom-precise and fully scalable synthesis of platinum clusters on a milligram scale from tiara-like platinum complexes with various ring numbers (n = 5-13). Low-temperature calcination of the complexes on a carbon support under hydrogen stream affords monodispersed platinum clusters, whose atomicity is equivalent to that of the precursor complex. One of the clusters (Pt 10 ) exhibits high catalytic activity in the hydrogenation of styrene compared to that of the other clusters. This method opens an avenue for the application of these clusters to preparative-scale catalysis.The catalytic activity of a noble metal nanocluster is tied to its atomicity. Here, the authors report an atom-precise, fully scalable synthesis of platinum clusters from molecular ring precursors, and show that a variation of only one atom can dramatically change a cluster's reactivity.

Charge transfer and formation of reduced Ce3+ upon adsorption of metal atoms at the ceria (110) surface.

PubMed

Nolan, Michael

2012-04-07

The modification of cerium dioxide with nanoscale metal clusters is intensely researched for catalysis applications, with gold, silver, and copper having been particularly well studied. The interaction of the metal cluster with ceria is driven principally by a localised interaction between a small number of metal atoms (as small as one) and the surface and understanding the fundamentals of the interaction of metal atoms with ceria surfaces is therefore of great interest. Much attention has been focused on the interaction of metals with the (111) surface of ceria, since this is the most stable surface and can be grown as films, which are probed experimentally. However, nanostructures exposing other surfaces such as (110) show high activity for reactions including CO oxidation and require further study; these nanostructures could be modified by deposition of metal atoms or small clusters, but there is no information to date on the atomic level details of metal-ceria interactions involving the (110) surface. This paper presents the results of density functional theory (DFT) corrected for on-site Coulomb interactions (DFT+U) calculations of the adsorption of a number of different metal atoms at an extended ceria (110) surface; the metals are Au, Ag, Cu, Al, Ga, In, La, Ce, V, Cr, and Fe. Upon adsorption all metals are oxidised, transferring electron(s) to the surface, resulting in localised surface distortions. The precise details depend on the identity of the metal atom. Au, Ag, Cu each transfer one electron to the surface, reducing one Ce ion to Ce(3+), while of the trivalent metals, Al and La are fully oxidised, but Ga and In are only partially oxidised. Ce and the transition metals are also partially oxidised, with the number of reduced Ce ions possible in this surface no more than three per adsorbed metal atom. The predicted oxidation states of the adsorbed metal atoms should be testable in experiments on ceria nanostructures modified with metal atoms.

Proposal for grid computing for nuclear applications

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

Idris, Faridah Mohamad; Ismail, Saaidi; Haris, Mohd Fauzi B.

2014-02-12

The use of computer clusters for computational sciences including computational physics is vital as it provides computing power to crunch big numbers at a faster rate. In compute intensive applications that requires high resolution such as Monte Carlo simulation, the use of computer clusters in a grid form that supplies computational power to any nodes within the grid that needs computing power, has now become a necessity. In this paper, we described how the clusters running on a specific application could use resources within the grid, to run the applications to speed up the computing process.

Evolution of the properties of Al(n)N(n) clusters with size.

PubMed

Costales, Aurora; Blanco, M A; Francisco, E; Pandey, Ravindra; Martín Pendás, A

2005-12-29

A global optimization of stoichiometric (AlN)(n) clusters (n = 1-25, 30, 35, ..., 95, 100) has been performed using the basin-hopping (BH) method and describing the interactions with simple and yet realistic interatomic potentials. The results for the smaller isomers agree with those of previous electronic structure calculations, thus validating the present scheme. The lowest-energy isomers found can be classified in three different categories according to their structural motifs: (i) small clusters (n = 2-5), with planar ring structures and 2-fold coordination, (ii) medium clusters (n = 6-40), where a competition between stacked rings and globular-like empty cages exists, and (iii) large clusters (n > 40), large enough to mix different elements of the previous stage. All the atoms in small and medium-sized clusters are in the surface, while large clusters start to display interior atoms. Large clusters display a competition between tetrahedral and octahedral-like features: the former lead to a lower energy interior in the cluster, while the latter allow for surface terminations with a lower energy. All of the properties studied present different regimes according to the above classification. It is of particular interest that the local properties of the interior atoms do converge to the bulk limit. The isomers with n = 6 and 12 are specially stable with respect to the gain or loss of AlN molecules.

Chemical Complexity in the Eu-enhanced Monometallic Globular NGC 5986

NASA Astrophysics Data System (ADS)

Johnson, Christian I.; Caldwell, Nelson; Rich, R. Michael; Mateo, Mario; Bailey, John I., III; Olszewski, Edward W.; Walker, Matthew G.

2017-06-01

NGC 5986 is a poorly studied but relatively massive Galactic globular cluster that shares several physical and morphological characteristics with “iron-complex” clusters known to exhibit significant metallicity and heavy-element dispersions. In order to determine whether NGC 5986 joins the iron-complex cluster class, we investigated the chemical composition of 25 red giant branch and asymptotic giant branch cluster stars using high-resolution spectra obtained with the Magellan-M2FS instrument. Cluster membership was verified using a combination of radial velocity and [Fe/H] measurements, and we found the cluster to have a mean heliocentric radial velocity of +99.76 km s-1 (σ = 7.44 km s-1). We derived a mean metallicity of [Fe/H] = -1.54 dex (σ = 0.08 dex), but the cluster’s small dispersion in [Fe/H] and low [La/Eu] abundance preclude it from being an iron-complex cluster. NGC 5986 has < [{Eu}/{Fe}]> =+0.76 {dex} (σ = 0.08 dex), which is among the highest ratios detected in a Galactic cluster, but the small [Eu/Fe] dispersion is puzzling because such high values near [Fe/H] ˜ -1.5 are typically only found in dwarf galaxies exhibiting large [Eu/Fe] variations. NGC 5986 exhibits classical globular cluster characteristics, such as uniformly enhanced [α/Fe] ratios, a small dispersion in Fe-peak abundances, and (anti)correlated light-element variations. Similar to NGC 2808, we find evidence that NGC 5986 may host at least four to five populations with distinct light-element compositions, and the presence of a clear Mg-Al anticorrelation along with an Al-Si correlation suggests that the cluster gas experienced processing at temperatures ≳65-70 MK. However, the current data do not support burning temperatures exceeding ˜100 MK. We find some evidence that the first- and second-generation stars in NGC 5986 may be fully spatially mixed, which could indicate that the cluster has lost a significant fraction of its original mass. This paper includes data gathered with the 6.5 m Magellan Telescopes located at Las Campanas Observatory, Chile.

Kentucky DOE EPSCoR Program

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

Grulke, Eric; Stencel, John

2011-09-13

The KY DOE EPSCoR Program supports two research clusters. The Materials Cluster uses unique equipment and computational methods that involve research expertise at the University of Kentucky and University of Louisville. This team determines the physical, chemical and mechanical properties of nanostructured materials and examines the dominant mechanisms involved in the formation of new self-assembled nanostructures. State-of-the-art parallel computational methods and algorithms are used to overcome current limitations of processing that otherwise are restricted to small system sizes and short times. The team also focuses on developing and applying advanced microtechnology fabrication techniques and the application of microelectrornechanical systems (MEMS)more » for creating new materials, novel microdevices, and integrated microsensors. The second research cluster concentrates on High Energy and Nuclear Physics. lt connects research and educational activities at the University of Kentucky, Eastern Kentucky University and national DOE research laboratories. Its vision is to establish world-class research status dedicated to experimental and theoretical investigations in strong interaction physics. The research provides a forum, facilities, and support for scientists to interact and collaborate in subatomic physics research. The program enables increased student involvement in fundamental physics research through the establishment of graduate fellowships and collaborative work.« less

PDB-Ligand: a ligand database based on PDB for the automated and customized classification of ligand-binding structures.

PubMed

Shin, Jae-Min; Cho, Doo-Ho

2005-01-01

PDB-Ligand (http://www.idrtech.com/PDB-Ligand/) is a three-dimensional structure database of small molecular ligands that are bound to larger biomolecules deposited in the Protein Data Bank (PDB). It is also a database tool that allows one to browse, classify, superimpose and visualize these structures. As of May 2004, there are about 4870 types of small molecular ligands, experimentally determined as a complex with protein or DNA in the PDB. The proteins that a given ligand binds are often homologous and present the same binding structure to the ligand. However, there are also many instances wherein a given ligand binds to two or more unrelated proteins, or to the same or homologous protein in different binding environments. PDB-Ligand serves as an interactive structural analysis and clustering tool for all the ligand-binding structures in the PDB. PDB-Ligand also provides an easier way to obtain a number of different structure alignments of many related ligand-binding structures based on a simple and flexible ligand clustering method. PDB-Ligand will be a good resource for both a better interpretation of ligand-binding structures and the development of better scoring functions to be used in many drug discovery applications.

LIGHT SCATTERING BY FRACTAL DUST AGGREGATES. I. ANGULAR DEPENDENCE OF SCATTERING

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

Tazaki, Ryo; Tanaka, Hidekazu; Okuzumi, Satoshi

2016-06-01

In protoplanetary disks, micron-sized dust grains coagulate to form highly porous dust aggregates. Because the optical properties of these aggregates are not completely understood, it is important to investigate how porous dust aggregates scatter light. In this study, the light scattering properties of porous dust aggregates were calculated using a rigorous method, the T -matrix method, and the results were then compared with those obtained using the Rayleigh–Gans–Debye (RGD) theory and Mie theory with the effective medium approximation (EMT). The RGD theory is applicable to moderately large aggregates made of nearly transparent monomers. This study considered two types of porousmore » dust aggregates—ballistic cluster–cluster agglomerates (BCCAs) and ballistic particle–cluster agglomerates. First, the angular dependence of the scattered intensity was shown to reflect the hierarchical structure of dust aggregates; the large-scale structure of the aggregates is responsible for the intensity at small scattering angles, and their small-scale structure determines the intensity at large scattering angles. Second, it was determined that the EMT underestimates the backward scattering intensity by multiple orders of magnitude, especially in BCCAs, because the EMT averages the structure within the size of the aggregates. It was concluded that the RGD theory is a very useful method for calculating the optical properties of BCCAs.« less

A Linear Algebra Measure of Cluster Quality.

ERIC Educational Resources Information Center

Mather, Laura A.

2000-01-01

Discussion of models for information retrieval focuses on an application of linear algebra to text clustering, namely, a metric for measuring cluster quality based on the theory that cluster quality is proportional to the number of terms that are disjoint across the clusters. Explains term-document matrices and clustering algorithms. (Author/LRW)

Molecular-dynamics analysis of mobile helium cluster reactions near surfaces of plasma-exposed tungsten

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

Hu, Lin; Maroudas, Dimitrios, E-mail: maroudas@ecs.umass.edu; Hammond, Karl D.

We report the results of a systematic atomic-scale analysis of the reactions of small mobile helium clusters (He{sub n}, 4 ≤ n ≤ 7) near low-Miller-index tungsten (W) surfaces, aiming at a fundamental understanding of the near-surface dynamics of helium-carrying species in plasma-exposed tungsten. These small mobile helium clusters are attracted to the surface and migrate to the surface by Fickian diffusion and drift due to the thermodynamic driving force for surface segregation. As the clusters migrate toward the surface, trap mutation (TM) and cluster dissociation reactions are activated at rates higher than in the bulk. TM produces W adatoms and immobile complexes ofmore » helium clusters surrounding W vacancies located within the lattice planes at a short distance from the surface. These reactions are identified and characterized in detail based on the analysis of a large number of molecular-dynamics trajectories for each such mobile cluster near W(100), W(110), and W(111) surfaces. TM is found to be the dominant cluster reaction for all cluster and surface combinations, except for the He{sub 4} and He{sub 5} clusters near W(100) where cluster partial dissociation following TM dominates. We find that there exists a critical cluster size, n = 4 near W(100) and W(111) and n = 5 near W(110), beyond which the formation of multiple W adatoms and vacancies in the TM reactions is observed. The identified cluster reactions are responsible for important structural, morphological, and compositional features in the plasma-exposed tungsten, including surface adatom populations, near-surface immobile helium-vacancy complexes, and retained helium content, which are expected to influence the amount of hydrogen re-cycling and tritium retention in fusion tokamaks.« less

Choosing appropriate analysis methods for cluster randomised cross-over trials with a binary outcome.

PubMed

Morgan, Katy E; Forbes, Andrew B; Keogh, Ruth H; Jairath, Vipul; Kahan, Brennan C

2017-01-30

In cluster randomised cross-over (CRXO) trials, clusters receive multiple treatments in a randomised sequence over time. In such trials, there is usual correlation between patients in the same cluster. In addition, within a cluster, patients in the same period may be more similar to each other than to patients in other periods. We demonstrate that it is necessary to account for these correlations in the analysis to obtain correct Type I error rates. We then use simulation to compare different methods of analysing a binary outcome from a two-period CRXO design. Our simulations demonstrated that hierarchical models without random effects for period-within-cluster, which do not account for any extra within-period correlation, performed poorly with greatly inflated Type I errors in many scenarios. In scenarios where extra within-period correlation was present, a hierarchical model with random effects for cluster and period-within-cluster only had correct Type I errors when there were large numbers of clusters; with small numbers of clusters, the error rate was inflated. We also found that generalised estimating equations did not give correct error rates in any scenarios considered. An unweighted cluster-level summary regression performed best overall, maintaining an error rate close to 5% for all scenarios, although it lost power when extra within-period correlation was present, especially for small numbers of clusters. Results from our simulation study show that it is important to model both levels of clustering in CRXO trials, and that any extra within-period correlation should be accounted for. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

First Operational Experience With a High-Energy Physics Run Control System Based on Web Technologies

NASA Astrophysics Data System (ADS)

Bauer, Gerry; Beccati, Barbara; Behrens, Ulf; Biery, Kurt; Branson, James; Bukowiec, Sebastian; Cano, Eric; Cheung, Harry; Ciganek, Marek; Cittolin, Sergio; Coarasa Perez, Jose Antonio; Deldicque, Christian; Erhan, Samim; Gigi, Dominique; Glege, Frank; Gomez-Reino, Robert; Gulmini, Michele; Hatton, Derek; Hwong, Yi Ling; Loizides, Constantin; Ma, Frank; Masetti, Lorenzo; Meijers, Frans; Meschi, Emilio; Meyer, Andreas; Mommsen, Remigius K.; Moser, Roland; O'Dell, Vivian; Oh, Alexander; Orsini, Luciano; Paus, Christoph; Petrucci, Andrea; Pieri, Marco; Racz, Attila; Raginel, Olivier; Sakulin, Hannes; Sani, Matteo; Schieferdecker, Philipp; Schwick, Christoph; Shpakov, Dennis; Simon, Michal; Sumorok, Konstanty; Yoon, Andre Sungho

2012-08-01

Run control systems of modern high-energy particle physics experiments have requirements similar to those of today's Internet applications. The Compact Muon Solenoid (CMS) collaboration at CERN's Large Hadron Collider (LHC) therefore decided to build the run control system for its detector based on web technologies. The system is composed of Java Web Applications distributed over a set of Apache Tomcat servlet containers that connect to a database back-end. Users interact with the system through a web browser. The present paper reports on the successful scaling of the system from a small test setup to the production data acquisition system that comprises around 10.000 applications running on a cluster of about 1600 hosts. We report on operational aspects during the first phase of operation with colliding beams including performance, stability, integration with the CMS Detector Control System and tools to guide the operator.

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.

Does Core Area Theory Apply to STIs in Rural Environments?

PubMed Central

Gesink, Dionne C; Sullivan, Ashleigh B; Norwood, Todd; Serre, Marc L; Miller, William C

2012-01-01

Background Our objective was to determine the extent to which geographical core areas for gonorrhea and syphilis are located in rural areas, as compared to urban areas. Methods Incident gonorrhea (January 1, 2005 to December 31, 2010) and syphilis (January 1, 1999 to December 31, 2010) rates were estimated and mapped by census tract and quarter. Rurality was measured using percent rural and rural-urban commuting area (RUCA; rural, small town, micropolitan, or urban). SaTScan was used to identify spatiotemporal clusters of significantly elevated rates of infection. Clusters lasting five years or longer were considered core areas; clusters of shorter duration were considered outbreaks. Clusters were overlaid on maps of rurality and qualitatively assessed for correlation. Results Twenty gonorrhea core areas were identified; 65% in urban centers, 25% in micropolitan areas, and the remaining 10% were geographically large capturing combinations of urban, micropolitan, small town and rural environments. Ten syphilis core areas were identified with 80% in urban centers and 20% capturing two or more RUCAs. All ten of the syphilis core areas (100%) overlapped with gonorrhea core areas. Conclusions Gonorrhea and syphilis rates were high for rural parts of North Carolina; however, no core areas were identified exclusively for small towns or rural areas. The main pathway of rural STI transmission may be through the interconnectedness of urban, micropolitan, small town and rural areas. Directly addressing STIs in urban and micropolitan communities may also indirectly help address STI rates in rural and small town communities. PMID:23254115

Clean Water State Revolving Fund (CWSRF): Decentralized Wastewater Treatment

EPA Pesticide Factsheets

Decentralized wastewater treatment is an onsite or clustered system used to collect, treat, and disperse or reclaim wastewater from a small community or service area (e.g., septic systems, cluster systems, lagoons).

FAST TRACK COMMUNICATION A DFT + DMFT approach for nanosystems

NASA Astrophysics Data System (ADS)

Turkowski, Volodymyr; Kabir, Alamgir; Nayyar, Neha; Rahman, Talat S.

2010-11-01

We propose a combined density-functional-theory-dynamical-mean-field-theory (DFT + DMFT) approach for reliable inclusion of electron-electron correlation effects in nanosystems. Compared with the widely used DFT + U approach, this method has several advantages, the most important of which is that it takes into account dynamical correlation effects. The formalism is illustrated through different calculations of the magnetic properties of a set of small iron clusters (number of atoms 2 <= N <= 5). It is shown that the inclusion of dynamical effects leads to a reduction in the cluster magnetization (as compared to results from DFT + U) and that, even for such small clusters, the magnetization values agree well with experimental estimations. These results justify confidence in the ability of the method to accurately describe the magnetic properties of clusters of interest to nanoscience.

A quasichemical approach for protein-cluster free energies in dilute solution

NASA Astrophysics Data System (ADS)

Young, Teresa M.; Roberts, Christopher J.

2007-10-01

Reversible formation of protein oligomers or small clusters is a key step in processes such as protein polymerization, fibril formation, and protein phase separation from dilute solution. A straightforward, statistical mechanical approach to accurately calculate cluster free energies in solution is presented using a cell-based, quasichemical (QC) approximation for the partition function of proteins in an implicit solvent. The inputs to the model are the protein potential of mean force (PMF) and the corresponding subcell degeneracies up to relatively low particle densities. The approach is tested using simple two and three dimensional lattice models in which proteins interact with either isotropic or anisotropic nearest-neighbor attractions. Comparison with direct Monte Carlo simulation shows that cluster probabilities and free energies of oligomer formation (ΔGi0) are quantitatively predicted by the QC approach for protein volume fractions ˜10-2 (weight/volume concentration ˜10gl-1) and below. For small clusters, ΔGi0 depends weakly on the strength of short-ranged attractive interactions for most experimentally relevant values of the normalized osmotic second virial coefficient (b2*). For larger clusters (i ≫2), there is a small but non-negligible b2* dependence. The results suggest that nonspecific, hydrophobic attractions may not significantly stabilize prenuclei in processes such as non-native aggregation. Biased Monte Carlo methods are shown to accurately provide subcell degeneracies that are intractable to obtain analytically or by direct enumeration, and so offer a means to generalize the approach to mixtures and proteins with more complex PMFs.

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data.

PubMed

Manzi, Alessandro; Dario, Paolo; Cavallo, Filippo

2017-05-11

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context.

Numerical Simulations of Single and Multiple Scattering by Fractal Ice Clusters

NASA Technical Reports Server (NTRS)

Dlugach, Janna M.; Mishchenko, Michael I.; Mackowski, Daniel W.

2011-01-01

We consider the scattering model in the form of a vertically and horizontally homogeneous particulate slab of an arbitrary optical thickness composed of widely separated fractal aggregates built of small spherical ice monomers. The aggregates are generated by applying three different approaches, including simulated cluster-cluster aggregation (CCA) and diffusion-limited aggregation (DLA) procedures. Having in mind radar remote-sensing applications, we report and analyze the results of computations of the backscattering circular polarization ratio obtained using efficient superposition T-matrix and vector radiative-transfer codes. The computations have been performed at a wavelength of 12.6 cm for fractal aggregates with the following characteristics: monomer refractive index m=1.78+i0.003, monomer radius r=1 cm, monomer packing density p=0.2, overall aggregate radii R in the range 4<=R<=10 cm and fractal dimensions D(sub f) 2.5 and 3. We show that for aggregates generated with simulated CCA and DLA procedures, the respective values of the backscattering circular polarization ratio differ weakly for D(sub f) 2.5, but the differences can increase somewhat for D(sub f)3, especially in case of an optically semi-infinite medium. For aggregates with a spheroidal overall shape, the dependence of the circular polarization ratio on the cluster morphology can be quite significant and increases with increasing the aspect ratio of the circumscribing spheroid.

Angle-Resolved Photoemission of Solvated Electrons in Sodium-Doped Clusters.

PubMed

West, Adam H C; Yoder, Bruce L; Luckhaus, David; Saak, Clara-Magdalena; Doppelbauer, Maximilian; Signorell, Ruth

2015-04-16

Angle-resolved photoelectron spectroscopy of the unpaired electron in sodium-doped water, methanol, ammonia, and dimethyl ether clusters is presented. The experimental observations and the complementary calculations are consistent with surface electrons for the cluster size range studied. Evidence against internally solvated electrons is provided by the photoelectron angular distribution. The trends in the ionization energies seem to be mainly determined by the degree of hydrogen bonding in the solvent and the solvation of the ion core. The onset ionization energies of water and methanol clusters do not level off at small cluster sizes but decrease slightly with increasing cluster size.

The applicability and effectiveness of cluster analysis

NASA Technical Reports Server (NTRS)

Ingram, D. S.; Actkinson, A. L.

1973-01-01

An insight into the characteristics which determine the performance of a clustering algorithm is presented. In order for the techniques which are examined to accurately cluster data, two conditions must be simultaneously satisfied. First the data must have a particular structure, and second the parameters chosen for the clustering algorithm must be correct. By examining the structure of the data from the Cl flight line, it is clear that no single set of parameters can be used to accurately cluster all the different crops. The effectiveness of either a noniterative or iterative clustering algorithm to accurately cluster data representative of the Cl flight line is questionable. Thus extensive a prior knowledge is required in order to use cluster analysis in its present form for applications like assisting in the definition of field boundaries and evaluating the homogeneity of a field. New or modified techniques are necessary for clustering to be a reliable tool.

SpectralNET – an application for spectral graph analysis and visualization

PubMed Central

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-01-01

Background Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Results Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). Conclusion SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from . Source code is available upon request. PMID:16236170

SpectralNET--an application for spectral graph analysis and visualization.

PubMed

Forman, Joshua J; Clemons, Paul A; Schreiber, Stuart L; Haggarty, Stephen J

2005-10-19

Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks. Available both as a standalone .NET executable and as an ASP.NET web application, SpectralNET was designed specifically with the analysis of graph-theoretic metrics in mind, a computational task not easily accessible using currently available applications. Users can choose either to upload a network for analysis using a variety of input formats, or to have SpectralNET generate an idealized random network for comparison to a real-world dataset. Whichever graph-generation method is used, SpectralNET displays detailed information about each connected component of the graph, including graphs of degree distribution, clustering coefficient by degree, and average distance by degree. In addition, extensive information about the selected vertex is shown, including degree, clustering coefficient, various distance metrics, and the corresponding components of the adjacency, Laplacian, and normalized Laplacian eigenvectors. SpectralNET also displays several graph visualizations, including a linear dimensionality reduction for uploaded datasets (Principal Components Analysis) and a non-linear dimensionality reduction that provides an elegant view of global graph structure (Laplacian eigenvectors). SpectralNET provides an easily accessible means of analyzing graph-theoretic metrics for data modeling and dimensionality reduction. SpectralNET is publicly available as both a .NET application and an ASP.NET web application from http://chembank.broad.harvard.edu/resources/. Source code is available upon request.

Clustering of disulfide-rich peptides provides scaffolds for hit discovery by phage display: application to interleukin-23.

PubMed

Barkan, David T; Cheng, Xiao-Li; Celino, Herodion; Tran, Tran T; Bhandari, Ashok; Craik, Charles S; Sali, Andrej; Smythe, Mark L

2016-11-23

Disulfide-rich peptides (DRPs) are found throughout nature. They are suitable scaffolds for drug development due to their small cores, whose disulfide bonds impart extraordinary chemical and biological stability. A challenge in developing a DRP therapeutic is to engineer binding to a specific target. This challenge can be overcome by (i) sampling the large sequence space of a given scaffold through a phage display library and by (ii) panning multiple libraries encoding structurally distinct scaffolds. Here, we implement a protocol for defining these diverse scaffolds, based on clustering structurally defined DRPs according to their conformational similarity. We developed and applied a hierarchical clustering protocol based on DRP structural similarity, followed by two post-processing steps, to classify 806 unique DRP structures into 81 clusters. The 20 most populated clusters comprised 85% of all DRPs. Representative scaffolds were selected from each of these clusters; the representatives were structurally distinct from one another, but similar to other DRPs in their respective clusters. To demonstrate the utility of the clusters, phage libraries were constructed for three of the representative scaffolds and panned against interleukin-23. One library produced a peptide that bound to this target with an IC 50 of 3.3 μM. Most DRP clusters contained members that were diverse in sequence, host organism, and interacting proteins, indicating that cluster members were functionally diverse despite having similar structure. Only 20 peptide scaffolds accounted for most of the natural DRP structural diversity, providing suitable starting points for seeding phage display experiments. Through selection of the scaffold surface to vary in phage display, libraries can be designed that present sequence diversity in architecturally distinct, biologically relevant combinations of secondary structures. We supported this hypothesis with a proof-of-concept experiment in which three phage libraries were constructed and panned against the IL-23 target, resulting in a single-digit μM hit and suggesting that a collection of libraries based on the full set of 20 scaffolds increases the potential to identify efficiently peptide binders to a protein target in a drug discovery program.

Asteroid clusters similar to asteroid pairs

NASA Astrophysics Data System (ADS)

Pravec, Petr; Vokrouhlicky, David; Fatka, Petr; Kusnirák, Peter; Hornoch, Kamil; Galád, Adrián

2016-10-01

We study five small, tight and young clusters of asteroids. They are placed around following largest (primary) bodies: (11842) Kap'bos, (14627) Emilkowalski, (16598) 1992 YC2, (21509) Lucascavin and (39991) 1998 HR37. Each cluster has 2-4 secondaries that are tightly clustered around the primary body, with distance in the 5-dimensional space of mean orbital elements mostly within 10 m/s, and always < 23 m/s. Backward orbital integrations indicate that they formed between 105 and 106 yr ago. In the P1-q space, where P1 is the primary's spin period and q = Σ Mj/M1 is the total secondary-to-primary mass ratio, the clusters lie in the same range as asteroid pairs formed by rotational fission. We have extended the model of a proto-system separation after rotational fission by Pravec et al. (2010) for application to systems with more than one secondary and found a perfect match for the five tight clusters. We find these clusters to be similar to asteroid pairs and we suggest that they are "extended pairs", having 2-4 escaped secondaries rather than just one secondary as in the case of an asteroid pair. We compare them to six young mini-families (1270) Datura, (2384) Schulhof, (3152) Jones, (6825) Irvine, (10321) Rampo and (20674) 1999 VT1. These mini-families have similar ages, but they have a higher number of members and/or they show a significantly larger spread in the mean orbital elements (dmean on an order of tens m/s) than the five tight clusters. In the P1-q space, all but one of the mini-families lie in the same range as asteroid pairs and the tight clusters; the exception is the mini-family of (3152) Jones which appears to be a collisional family. A possibility that the other five mini-families were also formed by rotational fission as we suggest for the tight clusters ("extended asteroid pairs") is being explored.Reference:Pravec, P., et al. Formation of asteroid pairs by rotational fission. Nature 466, 1085-1088.

Ab initio investigation on hydrogen adsorption capability in Zn and Cu-based metal organic frameworks

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

Tanuwijaya, V. V., E-mail: viny.veronika@gmail.com; Hidayat, N. N., E-mail: avantgarde.vee@gmail.com; Agusta, M. K., E-mail: kemal@fti.itb.ac.id

2015-09-30

One of the biggest challenge in material technology for hydrogen storage application is to increase hydrogen uptake in room temperature and pressure. As a class of highly porous material, Metal-Organic Frameworks (MOF) holds great potential with its tunable structure. However, little is known about the effect of metal cluster to its hydrogen storage capability. Investigation on this matter has been carried out carefully on small cluster of Zn and Cu-based MOF using first principles method. The calculation of two distinct building units of MOFs, namely octahedral and paddle-wheel models, have been done with B3LYP density functional method using 6-31G(d,p) andmore » LANL2DZ basis sets. From geometry optimization of Zn-based MOF linked by benzene-dicarboxylate (MOF-5), it is found that hydrogen tends to keep distance from metal cluster group and stays above benzene ring. In the other hand, hydrogen molecule prefers to stay atop of the exposed Cu atom in Cu-based MOF system linked by the same linker group (Cu-bdc). Calculated hydrogen binding enthalpies for Zn and Cu octahedral cages at ZnO{sub 3} sites are 1.64kJ/mol and 2.73kJ/mol respectively, while hydrogen binding enthalpies for Zn and Cu paddle-wheel cages calculated on top of metal atoms are found to be at 6.05kJ/mol and 6.10kJ/mol respectively. Major difference between Zn-MOF-5 and Cu-bdc hydrogen uptake performance might be caused by unsaturated metal sites present in Cu-bdc system and the influence of their geometric structures, although a small difference on binding energy in the type of transition metal used is also observed. The comparison between Zn and Cu-based MOF may contribute to a comprehensive understanding of metal clusters and the importance of selecting best transition metal for design and synthesis of metal-organic frameworks.« less

Bioinspired Principles for Large-Scale Networked Sensor Systems: An Overview

PubMed Central

Jacobsen, Rune Hylsberg; Zhang, Qi; Toftegaard, Thomas Skjødeberg

2011-01-01

Biology has often been used as a source of inspiration in computer science and engineering. Bioinspired principles have found their way into network node design and research due to the appealing analogies between biological systems and large networks of small sensors. This paper provides an overview of bioinspired principles and methods such as swarm intelligence, natural time synchronization, artificial immune system and intercellular information exchange applicable for sensor network design. Bioinspired principles and methods are discussed in the context of routing, clustering, time synchronization, optimal node deployment, localization and security and privacy. PMID:22163841

Cosmology and particle physics

NASA Astrophysics Data System (ADS)

Barrow, J. D.

A brief overview is given of recent work that integrates cosmology and particle physics. The observational data regarding the abundance of matter and radiation in the universe is described. The manner in which the cosmological survival density of stable massive particles can be calculated is discussed along with the process of cosmological nucleosynthesis. Several applications of these general arguments are given with reference to the survival density of nucleons, neutrinos and unconfined fractionally charge particles. The use of nucleosynthesis to limit the number of lepton generations is described together with the implications of a small neutrino mass for the origin of galaxies and clusters.

Clusters of Galaxies at High Redshift

NASA Astrophysics Data System (ADS)

Fort, Bernard

For a long time, the small number of clusters at z > 0.3 in the Abell survey catalogue and simulations of the standard CDM formation of large scale structures provided a paradigm where clusters were considered as young merging structures. At earlier times, loose concentrations of galaxy clumps were mostly anticipated. Recent observations broke the taboo. Progressively we became convinced that compact and massive clusters at z = 1 or possibly beyond exist and should be searched for.

M87 at 90 Centimeters: A Different Picture

DTIC Science & Technology

2000-06-15

as is envisioned in the cooling Ñow model. Subject headings : cooling Ñows È galaxies : active È galaxies : clusters : individual ( Virgo ) È galaxies...atmosphere of the Virgo Cluster (Fabricant, Lecar, & Gorenstein 1980). The X-ray atmosphere has a simple, apparently undis- turbed, morphology with a central...of a small set of amorphous central radio galaxies in other, similar, cooling-core clusters ? 4. PHYSICAL PICTURE : THE CLUSTER CORE The Virgo X-ray

ROSAT PSPC Observations of CL0016+16

NASA Technical Reports Server (NTRS)

Hughes, John P. (Principal Investigator)

1996-01-01

Several ROSAT observations concerning with complex spatial structures in Sunyaev-Zel'dovich decrement clusters Abell 665 and CL0016+16, discovery of Be/X-ray stars in two supernova remnants in the Small Magellanic Cloud, a new transient pulsar in the Small Magellanic Cloud with an unusual x-ray spectrum, a new x-ray-discovered cluster of galaxies associated with CL0016+16, and the distance to CL0016+16 vs. the Hubble constant, are presented.

Structures, electronic properties and reaction paths from Fe(CO)5 molecule to small Fe clusters

NASA Astrophysics Data System (ADS)

Li, Zhi; Zhao, Zhen

2018-04-01

The geometries, electrical characters and reaction paths from Fe(CO)5 molecule to small Fe clusters were investigated by using all-electron density functional theory. The results show that in the decomposition process of pentacarbonyl-iron, Fe(CO)5 molecule prefers to remove a carbon monoxide and adsorb another Fe(CO)5 molecule to produce nonacarbonyldiiron Fe2(CO)9 then Fe2(CO)9 gradually removes carbon monoxide to produce small Fe clusters. As It can be seen from the highest occupied molecule orbital-lowest unoccupied molecule orbital gap curves, the Fe(CO)n=3, and 5 and Fe2(CO)n=3, 7 and 9 intermediates have higher chemical stability than their neighbors. The local magnetic moment of the carbon monoxide is aligning anti-ferromagnetic. The effect of external magnetic field to the initial decomposition products of Fe(CO)5 can be ignored.

Small indels induced by CRISPR/Cas9 in the 5' region of microRNA lead to its depletion and Drosha processing retardance.

PubMed

Jiang, Qian; Meng, Xing; Meng, Lingwei; Chang, Nannan; Xiong, Jingwei; Cao, Huiqing; Liang, Zicai

2014-01-01

MicroRNA knockout by genome editing technologies is promising. In order to extend the application of the technology and to investigate the function of a specific miRNA, we used CRISPR/Cas9 to deplete human miR-93 from a cluster by targeting its 5' region in HeLa cells. Various small indels were induced in the targeted region containing the Drosha processing site and seed sequences. Interestingly, we found that even a single nucleotide deletion led to complete knockout of the target miRNA with high specificity. Functional knockout was confirmed by phenotype analysis. Furthermore, de novo microRNAs were not found by RNA-seq. Nevertheless, expression of the pri-microRNAs was increased. When combined with structural analysis, the data indicated that biogenesis was impaired. Altogether, we showed that small indels in the 5' region of a microRNA result in sequence depletion as well as Drosha processing retard.

Application of Fuzzy c-Means and Joint-Feature-Clustering to Detect Redundancies of Image-Features in Drug Combinations Studies of Breast Cancer

NASA Astrophysics Data System (ADS)

Brandl, Miriam B.; Beck, Dominik; Pham, Tuan D.

2011-06-01

The high dimensionality of image-based dataset can be a drawback for classification accuracy. In this study, we propose the application of fuzzy c-means clustering, cluster validity indices and the notation of a joint-feature-clustering matrix to find redundancies of image-features. The introduced matrix indicates how frequently features are grouped in a mutual cluster. The resulting information can be used to find data-derived feature prototypes with a common biological meaning, reduce data storage as well as computation times and improve the classification accuracy.

Novel Functional Genomics Approaches: A Promising Future in the Combat Against Plant Viruses.

PubMed

Fondong, Vincent N; Nagalakshmi, Ugrappa; Dinesh-Kumar, Savithramma P

2016-10-01

Advances in functional genomics and genome editing approaches have provided new opportunities and potential to accelerate plant virus control efforts through modification of host and viral genomes in a precise and predictable manner. Here, we discuss application of RNA-based technologies, including artificial micro RNA, transacting small interfering RNA, and Cas9 (clustered regularly interspaced short palindromic repeat-associated protein 9), which are currently being successfully deployed in generating virus-resistant plants. We further discuss the reverse genetics approach, targeting induced local lesions in genomes (TILLING) and its variant, known as EcoTILLING, that are used in the identification of plant virus recessive resistance gene alleles. In addition to describing specific applications of these technologies in plant virus control, this review discusses their advantages and limitations.

Exploiting CRISPR/Cas: Interference Mechanisms and Applications

PubMed Central

Richter, Hagen; Randau, Lennart; Plagens, André

2013-01-01

The discovery of biological concepts can often provide a framework for the development of novel molecular tools, which can help us to further understand and manipulate life. One recent example is the elucidation of the prokaryotic adaptive immune system, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) that protects bacteria and archaea against viruses or conjugative plasmids. The immunity is based on small RNA molecules that are incorporated into versatile multi-domain proteins or protein complexes and specifically target viral nucleic acids via base complementarity. CRISPR/Cas interference machines are utilized to develop novel genome editing tools for different organisms. Here, we will review the latest progress in the elucidation and application of prokaryotic CRISPR/Cas systems and discuss possible future approaches to exploit the potential of these interference machineries. PMID:23857052

Exploiting CRISPR/Cas: interference mechanisms and applications.

PubMed

Richter, Hagen; Randau, Lennart; Plagens, André

2013-07-12

The discovery of biological concepts can often provide a framework for the development of novel molecular tools, which can help us to further understand and manipulate life. One recent example is the elucidation of the prokaryotic adaptive immune system, clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) that protects bacteria and archaea against viruses or conjugative plasmids. The immunity is based on small RNA molecules that are incorporated into versatile multi-domain proteins or protein complexes and specifically target viral nucleic acids via base complementarity. CRISPR/Cas interference machines are utilized to develop novel genome editing tools for different organisms. Here, we will review the latest progress in the elucidation and application of prokaryotic CRISPR/Cas systems and discuss possible future approaches to exploit the potential of these interference machineries.

On the Partitioning of Squared Euclidean Distance and Its Applications in Cluster Analysis.

ERIC Educational Resources Information Center

Carter, Randy L.; And Others

1989-01-01

The partitioning of squared Euclidean--E(sup 2)--distance between two vectors in M-dimensional space into the sum of squared lengths of vectors in mutually orthogonal subspaces is discussed. Applications to specific cluster analysis problems are provided (i.e., to design Monte Carlo studies for performance comparisons of several clustering methods…

Theoretical research program to study chemical reactions in AOTV bow shock tubes

NASA Technical Reports Server (NTRS)

Taylor, Peter R.

1993-01-01

The main focus was the development, implementation, and calibration of methods for performing molecular electronic structure calculations to high accuracy. These various methods were then applied to a number of chemical reactions and species of interest to NASA, notably in the area of combustion chemistry. Among the development work undertaken was a collaborative effort to develop a program to efficiently predict molecular structures and vibrational frequencies using energy derivatives. Another major development effort involved the design of new atomic basis sets for use in chemical studies: these sets were considerably more accurate than those previously in use. Much effort was also devoted to calibrating methods for computing accurate molecular wave functions, including the first reliable calibrations for realistic molecules using full CI results. A wide variety of application calculations were undertaken. One area of interest was the spectroscopy and thermochemistry of small molecules, including establishing small molecule binding energies to an accuracy rivaling, or even on occasion surpassing, the experiment. Such binding energies are essential input to modeling chemical reaction processes, such as combustion. Studies of large molecules and processes important in both hydrogen and hydrocarbon combustion chemistry were also carried out. Finally, some effort was devoted to the structure and spectroscopy of small metal clusters, with applications to materials science problems.

Applications of Nanoparticle-Containing Plasmas for High-Order Harmonic Generation of Laser Radiation

NASA Astrophysics Data System (ADS)

Ganeev, Rashid A.

The use of nanoparticles for efficient conversion of the wavelength of ultrashort laser toward the deep UV spectral range through harmonic generation is an attractive application of cluster-containing plasmas. Note that earlier observations of HHG in nanoparticles were limited by using the exotic gas clusters formed during fast cooling of atomic flow from the gas jets 1-4. One can assume the difficulties in definition of the structure of such clusters and the ratio between nanoparticles and atoms/ions in the gas flow. The characterization of gas phase cluster production was currently improved using the sophisticated techniques (e.g., a control of nanoparticle mass and spatial distribution, see the review 5). In the meantime, the plasma nanoparticle HHG has demonstrated some advantages over gas cluster HHG 6. The application of commercially available nanopowders allowed for precisely defining the sizes and structure of these clusters in the plume. The laser ablation technique made possible the predictable manipulation of plasma characteristics, which led to the creation of laser plumes containing mainly nanoparticles with known spatial structure. The latter allows the application of such plumes in nonlinear optics, X-ray emission of clusters, deposition of nanoparticles with fixed parameters on the substrates for semiconductor industry, production of nanostructured and nanocomposite films, etc.

Theoretical research program to study transition metal trimers and embedded clusters

NASA Technical Reports Server (NTRS)

Walch, Stephen P.

1987-01-01

The results of ab-initio calculations are reported for (1) small transition metal clusters and (2) potential energy surfaces for chemical reactions important in hydrogen combustion and high temperature air chemistry.

Mini-clusters

NASA Technical Reports Server (NTRS)

Chinellato, J. A.; Dobrigkeit, C.; Bellandifilho, J.; Lattes, C. M. G.; Menon, M. J.; Navia, C. E.; Pamilaju, A.; Sawayanagi, K.; Shibuya, E. H.; Turtelli, A., Jr.

1985-01-01

Experimental results of mini-clusters observed in Chacaltaya emulsion chamber no.19 are summarized. The study was made on 54 single core shower upper and 91 shower clusters of E(gamma) 10 TeV from 30 families which are visible energy greater than 80 TeV and penetrate through both upper and lower detectors of the two-story chamber. The association of hadrons in mini-cluster is made clear from their penetrative nature and microscopic observation of shower continuation in lower chamber. Small P sub t (gamma) of hadrons in mini-clusters remained in puzzle.

Star Clusters in the Magellanic Clouds

NASA Astrophysics Data System (ADS)

Gallagher, J. S., III

2014-09-01

The Magellanic Clouds (MC) are prime locations for studies of star clusters covering a full range in age and mass. This contribution briefly reviews selected properties of Magellanic star clusters, by focusing first on young systems that show evidence for hierarchical star formation. The structures and chemical abundance patterns of older intermediate age star clusters in the Small Magellanic Cloud (SMC) are a second topic. These suggest a complex history has affected the chemical enrichment in the SMC and that low tidal stresses in the SMC foster star cluster survival.

Towards accurate modelling of galaxy clustering on small scales: testing the standard ΛCDM + halo model

NASA Astrophysics Data System (ADS)

Sinha, Manodeep; Berlind, Andreas A.; McBride, Cameron K.; Scoccimarro, Roman; Piscionere, Jennifer A.; Wibking, Benjamin D.

2018-07-01

Interpreting the small-scale clustering of galaxies with halo models can elucidate the connection between galaxies and dark matter haloes. Unfortunately, the modelling is typically not sufficiently accurate for ruling out models statistically. It is thus difficult to use the information encoded in small scales to test cosmological models or probe subtle features of the galaxy-halo connection. In this paper, we attempt to push halo modelling into the `accurate' regime with a fully numerical mock-based methodology and careful treatment of statistical and systematic errors. With our forward-modelling approach, we can incorporate clustering statistics beyond the traditional two-point statistics. We use this modelling methodology to test the standard Λ cold dark matter (ΛCDM) + halo model against the clustering of Sloan Digital Sky Survey (SDSS) seventh data release (DR7) galaxies. Specifically, we use the projected correlation function, group multiplicity function, and galaxy number density as constraints. We find that while the model fits each statistic separately, it struggles to fit them simultaneously. Adding group statistics leads to a more stringent test of the model and significantly tighter constraints on model parameters. We explore the impact of varying the adopted halo definition and cosmological model and find that changing the cosmology makes a significant difference. The most successful model we tried (Planck cosmology with Mvir haloes) matches the clustering of low-luminosity galaxies, but exhibits a 2.3σ tension with the clustering of luminous galaxies, thus providing evidence that the `standard' halo model needs to be extended. This work opens the door to adding interesting freedom to the halo model and including additional clustering statistics as constraints.

Clustering on very small scales from a large sample of confirmed quasar pairs: does quasar clustering track from Mpc to kpc scales?

NASA Astrophysics Data System (ADS)

Eftekharzadeh, S.; Myers, A. D.; Hennawi, J. F.; Djorgovski, S. G.; Richards, G. T.; Mahabal, A. A.; Graham, M. J.

2017-06-01

We present the most precise estimate to date of the clustering of quasars on very small scales, based on a sample of 47 binary quasars with magnitudes of g < 20.85 and proper transverse separations of ˜25 h-1 kpc. Our sample of binary quasars, which is about six times larger than any previous spectroscopically confirmed sample on these scales, is targeted using a kernel density estimation (KDE) technique applied to Sloan Digital Sky Survey (SDSS) imaging over most of the SDSS area. Our sample is 'complete' in that all of the KDE target pairs with 17.0 ≲ R ≲ 36.2 h-1 kpc in our area of interest have been spectroscopically confirmed from a combination of previous surveys and our own long-slit observational campaign. We catalogue 230 candidate quasar pairs with angular separations of <8 arcsec, from which our binary quasars were identified. We determine the projected correlation function of quasars (\\bar{W}_p) in four bins of proper transverse scale over the range 17.0 ≲ R ≲ 36.2 h-1 kpc. The implied small-scale quasar clustering amplitude from the projected correlation function, integrated across our entire redshift range, is A = 24.1 ± 3.6 at ˜26.6 h-1 kpc. Our sample is the first spectroscopically confirmed sample of quasar pairs that is sufficiently large to study how quasar clustering evolves with redshift at ˜25 h-1 kpc. We find that empirical descriptions of how quasar clustering evolves with redshift at ˜25 h-1 Mpc also adequately describe the evolution of quasar clustering at ˜25 h-1 kpc.

Low-rank network decomposition reveals structural characteristics of small-world networks

NASA Astrophysics Data System (ADS)

Barranca, Victor J.; Zhou, Douglas; Cai, David

2015-12-01

Small-world networks occur naturally throughout biological, technological, and social systems. With their prevalence, it is particularly important to prudently identify small-world networks and further characterize their unique connection structure with respect to network function. In this work we develop a formalism for classifying networks and identifying small-world structure using a decomposition of network connectivity matrices into low-rank and sparse components, corresponding to connections within clusters of highly connected nodes and sparse interconnections between clusters, respectively. We show that the network decomposition is independent of node indexing and define associated bounded measures of connectivity structure, which provide insight into the clustering and regularity of network connections. While many existing network characterizations rely on constructing benchmark networks for comparison or fail to describe the structural properties of relatively densely connected networks, our classification relies only on the intrinsic network structure and is quite robust with respect to changes in connection density, producing stable results across network realizations. Using this framework, we analyze several real-world networks and reveal new structural properties, which are often indiscernible by previously established characterizations of network connectivity.

Emergent patterns in interacting neuronal sub-populations

NASA Astrophysics Data System (ADS)

Kamal, Neeraj Kumar; Sinha, Sudeshna

2015-05-01

We investigate an ensemble of coupled model neurons, consisting of groups of varying sizes and intrinsic dynamics, ranging from periodic to chaotic, where the inter-group coupling interaction is effectively like a dynamic signal from a different sub-population. We observe that the minority group can significantly influence the majority group. For instance, when a small chaotic group is coupled to a large periodic group, the chaotic group de-synchronizes. However, counter-intuitively, when a small periodic group couples strongly to a large chaotic group, it leads to complete synchronization in the majority chaotic population, which also spikes at the frequency of the small periodic group. It then appears that the small group of periodic neurons can act like a pacemaker for the whole network. Further, we report the existence of varied clustering patterns, ranging from sets of synchronized clusters to anti-phase clusters, governed by the interplay of the relative sizes and dynamics of the sub-populations. So these results have relevance in understanding how a group can influence the synchrony of another group of dynamically different elements, reminiscent of event-related synchronization/de-synchronization in complex networks.

Nanoscale Decoration of Electrode Surfaces with an STM

DTIC Science & Technology

1999-05-30

covered gold electrode surfaces at predetermined positions. First, metal is deposited electrochemically onto the STM tip, then the clusters are formed by a...onto the tip, the jump-to-contact occurs in the opposite direction leaving holes in the gold surface. The stability of the metal clusters against anodic...deposition, clusters, a surprisingly high stability of the small Ag Hg/HgSO4 for Ag deposition and a Pt wire for Ni clusters on gold against anodic

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

DOE PAGES

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.; ...

2017-11-23

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. Here, we find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 10 5–6 M ⊙ collectively to high density, at which point it rapidly turns into stars beforemore » stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ~420 Myr till the end of the simulation. Finally, because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.« less

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

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

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. Here, we find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 10 5–6 M ⊙ collectively to high density, at which point it rapidly turns into stars beforemore » stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ~420 Myr till the end of the simulation. Finally, because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.« less

Effect of Spin Multiplicity in O2 Adsorption and Dissociation on Small Bimetallic AuAg Clusters.

PubMed

García-Cruz, Raúl; Poulain, Enrique; Hernández-Pérez, Isaías; Reyes-Nava, Juan A; González-Torres, Julio C; Rubio-Ponce, A; Olvera-Neria, Oscar

2017-08-17

To dispose of atomic oxygen, it is necessary the O 2 activation; however, an energy barrier must be overcome to break the O-O bond. This work presents theoretical calculations of the O 2 adsorption and dissociation on small pure Au n and Ag m and bimetallic Au n Ag m (n + m ≤ 6) clusters using the density functional theory (DFT) and the zeroth-order regular approximation (ZORA) to explicitly include scalar relativistic effects. The most stable Au n Ag m clusters contain a higher concentration of Au with Ag atoms located in the center of the cluster. The O 2 adsorption energy on pure and bimetallic clusters and the ensuing geometries depend on the spin multiplicity of the system. For a doublet multiplicity, O 2 is adsorbed in a bridge configuration, whereas for a triplet only one O-metal bond is formed. The charge transfer from metal toward O 2 occupies the σ* O-O antibonding natural bond orbital, which weakens the oxygen bond. The Au 3 ( 2 A) cluster presents the lowest activation energy to dissociate O 2 , whereas the opposite applies to the AuAg ( 3 A) system. In the O 2 activation, bimetallic clusters are not as active as pure Au n clusters due to the charge donated by Ag atoms being shared between O 2 and Au atoms.

Formation of globular cluster candidates in merging proto-galaxies at high redshift: a view from the FIRE cosmological simulations

NASA Astrophysics Data System (ADS)

Kim, Ji-hoon; Ma, Xiangcheng; Grudić, Michael Y.; Hopkins, Philip F.; Hayward, Christopher C.; Wetzel, Andrew; Faucher-Giguère, Claude-André; Kereš, Dušan; Garrison-Kimmel, Shea; Murray, Norman

2018-03-01

Using a state-of-the-art cosmological simulation of merging proto-galaxies at high redshift from the FIRE project, with explicit treatments of star formation and stellar feedback in the interstellar medium, we investigate the formation of star clusters and examine one of the formation hypotheses of present-day metal-poor globular clusters. We find that frequent mergers in high-redshift proto-galaxies could provide a fertile environment to produce long-lasting bound star clusters. The violent merger event disturbs the gravitational potential and pushes a large gas mass of ≳ 105-6 M⊙ collectively to high density, at which point it rapidly turns into stars before stellar feedback can stop star formation. The high dynamic range of the reported simulation is critical in realizing such dense star-forming clouds with a small dynamical time-scale, tff ≲ 3 Myr, shorter than most stellar feedback time-scales. Our simulation then allows us to trace how clusters could become virialized and tightly bound to survive for up to ˜420 Myr till the end of the simulation. Because the cluster's tightly bound core was formed in one short burst, and the nearby older stars originally grouped with the cluster tend to be preferentially removed, at the end of the simulation the cluster has a small age spread.

A comprehensive photometric study of dynamically evolved small van den Bergh-Hagen open clusters

NASA Astrophysics Data System (ADS)

Piatti, Andrés E.

2016-12-01

We present results from Johnson UBV, Kron-Cousins RI and Washington CT1T2 photometries for seven van den Bergh-Hagen (vdBH) open clusters, namely, vdBH 1, 10, 31, 72, 87, 92, and 118. The high-quality, multiband photometric data sets were used to trace the cluster stellar density radial profiles and to build colour-magnitude diagrams and colour-colour diagrams from which we estimated their structural parameters and fundamental astrophysical properties. The clusters in our sample cover a wide age range, from ˜60 Myr up to 2.8 Gyr, are of relatively small size (˜1-6 pc) and are placed at distances from the Sun which vary between 1.8 and 6.3 kpc, respectively. We also estimated lower limits for the cluster present-day masses as well as half-mass relaxation times (tr). The resulting values in combination with the structural parameter values suggest that the studied clusters are in advanced stages of their internal dynamical evolution (age/tr ˜ 20-320), possibly in the typical phase of those tidally filled with mass segregation in their core regions. Compared to open clusters in the solar neighbourhood, the seven vdBH clusters are within more massive (˜80-380 M⊙), with higher concentration parameter values (c ˜ 0.75-1.15) and dynamically evolved ones.

Structural and electronic properties Te62+ and Te82+: A DFT study

NASA Astrophysics Data System (ADS)

Sharma, Tamanna; Tamboli, Rohit; Kanhere, D. G.; Sharma, Raman

2018-05-01

Structural and electronic properties of Tellurium cluster (Ten) and their cations (Ten2+) (n = 6, 8) have been studied theoretically using VASP within generalized gradient approximation. Ground state geometries and higher energy isomers of these clusters have been examined on the basis of total free energy calculations. Lowest energy isomers of neutral clusters are ring like structures whereas the lowest energy isomers of cations are polyhedral cages. HOMO-LUMO gap in cationic clusters is small compared to its neutral clusters. Removal of two electrons from the neutral cluster raises the free energy. Analysis of free energy, HOMO-LUMO gap and density of states (DOS) show that neutral cluster are more stable than their cations.

Development of a small-scale computer cluster

NASA Astrophysics Data System (ADS)

Wilhelm, Jay; Smith, Justin T.; Smith, James E.

2008-04-01

An increase in demand for computing power in academia has necessitated the need for high performance machines. Computing power of a single processor has been steadily increasing, but lags behind the demand for fast simulations. Since a single processor has hard limits to its performance, a cluster of computers can have the ability to multiply the performance of a single computer with the proper software. Cluster computing has therefore become a much sought after technology. Typical desktop computers could be used for cluster computing, but are not intended for constant full speed operation and take up more space than rack mount servers. Specialty computers that are designed to be used in clusters meet high availability and space requirements, but can be costly. A market segment exists where custom built desktop computers can be arranged in a rack mount situation, gaining the space saving of traditional rack mount computers while remaining cost effective. To explore these possibilities, an experiment was performed to develop a computing cluster using desktop components for the purpose of decreasing computation time of advanced simulations. This study indicates that small-scale cluster can be built from off-the-shelf components which multiplies the performance of a single desktop machine, while minimizing occupied space and still remaining cost effective.

Nanoclusters first: a hierarchical phase transformation in a novel Mg alloy

NASA Astrophysics Data System (ADS)

Okuda, Hiroshi; Yamasaki, Michiaki; Kawamura, Yoshihito; Tabuchi, Masao; Kimizuka, Hajime

2015-09-01

The Mg-Y-Zn ternary alloy system contains a series of novel structures known as long-period stacking ordered (LPSO) structures. The formation process and its key concept from a viewpoint of phase transition are not yet clear. The current study reveals that the phase transformation process is not a traditional spinodal decomposition or structural transformation but, rather a novel hierarchical phase transformation. In this transformation, clustering occurs first, and the spatial rearrangement of the clusters induce a secondary phase transformation that eventually lead to two-dimensional ordering of the clusters. The formation process was examined using in situ synchrotron radiation small-angle X-ray scattering (SAXS). Rapid quenching from liquid alloy into thin ribbons yielded strongly supersaturated amorphous samples. The samples were heated at a constant rate of 10 K/min. and the scattering patterns were acquired. The SAXS analysis indicated that small clusters grew to sizes of 0.2 nm after they crystallized. The clusters distributed randomly in space grew and eventually transformed into a microstructure with two well-defined cluster-cluster distances, one for the segregation periodicity of LPSO and the other for the in-plane ordering in segregated layer. This transformation into the LPSO structure concomitantly introduces the periodical stacking fault required for the 18R structures.

Atomically precise cluster catalysis towards quantum controlled catalysts

PubMed Central

Watanabe, Yoshihide

2014-01-01

Catalysis of atomically precise clusters supported on a substrate is reviewed in relation to the type of reactions. The catalytic activity of supported clusters has generally been discussed in terms of electronic structure. Several lines of evidence have indicated that the electronic structure of clusters and the geometry of clusters on a support, including the accompanying cluster-support interaction, are strongly correlated with catalytic activity. The electronic states of small clusters would be easily affected by cluster–support interactions. Several studies have suggested that it is possible to tune the electronic structure through atomic control of the cluster size. It is promising to tune not only the number of cluster atoms, but also the hybridization between the electronic states of the adsorbed reactant molecules and clusters in order to realize a quantum-controlled catalyst. PMID:27877723

First-principles melting of gallium clusters down to nine atoms: structural and electronic contributions to melting.

PubMed

Steenbergen, Krista G; Gaston, Nicola

2013-10-07

First-principles Born-Oppenheimer molecular dynamics simulations of small gallium clusters, including parallel tempering, probe the distinction between cluster and molecule in the size range of 7-12 atoms. In contrast to the larger sizes, dynamic measures of structural change at finite temperature demonstrate that Ga7 and Ga8 do not melt, suggesting a size limit to melting in gallium exists at 9 atoms. Analysis of electronic structure further supports this size limit, additionally demonstrating that a covalent nature cannot be identified for clusters larger than the gallium dimer. Ga9, Ga10 and Ga11 melt at greater-than-bulk temperatures, with no evident covalent character. As Ga12 represents the first small gallium cluster to melt at a lower-than-bulk temperature, we examine the structural properties of each cluster at finite temperature in order to probe both the origins of greater-than-bulk melting, as well as the significant differences in melting temperatures induced by a single atom addition. Size-sensitive melting temperatures can be explained by both energetic and entropic differences between the solid and liquid phases for each cluster. We show that the lower-than-bulk melting temperature of the 12-atom cluster can be attributed to persistent pair bonding, reminiscent of the pairing observed in α-gallium. This result supports the attribution of greater-than-bulk melting in gallium clusters to the anomalously low melting temperature of the bulk, due to its dimeric structure.

Kinetic energy spectra in thermionic emission from small tungsten cluster anions: evidence for nonclassical electron capture.

PubMed

Concina, Bruno; Baguenard, Bruno; Calvo, Florent; Bordas, Christian

2010-03-14

The delayed electron emission from small mass-selected anionic tungsten clusters W(n)(-) has been studied for sizes in the range 9 < or = n < or = 21. Kinetic energy spectra have been measured for delays of about 100 ns after laser excitation by a velocity-map imaging spectrometer. They are analyzed in the framework of microreversible statistical theories. The low-energy behavior shows some significant deviations with respect to the classical Langevin capture model, which we interpret as possibly due to the influence of quantum dynamical effects such as tunneling through the centrifugal barrier, rather than shape effects. The cluster temperature has been extracted from both the experimental kinetic energy spectrum and the absolute decay rate. Discrepancies between the two approaches suggest that the sticking probability can be as low as a few percent for the smallest clusters.

EDITORIAL: Cluster issue on microplasmas

NASA Astrophysics Data System (ADS)

Chao, Chih C.; Liao, Jiunn-Der; Chang, Juu-En

2008-10-01

Ever since the first Workshop on Microplasmas, held in Japan in 2003, plasma scientists and engineers worldwide have been meeting approximately every 18 months to exchange and discuss the results of scientific research and technical applications of this unique type of plasma. Microplasmas are generally described as stable plasmas confined to spatial dimensions below about 1 mm that can be operated at pressures up to and exceeding atmospheric pressure. By their nature, this presents a wide range of opportunities and many advantages in practical applications, just a few examples being low energy consumption, small size, flexibility of use and ease of assembly into a user-friendly package. Nevertheless, there still remain several unanswered basic science questions and a largely untapped potential for environmental, biomedical and industrial applications. The fourth International Workshop on Microplasmas, held during 28-31 October 2007 in Tainan, Taiwan, continued the trend of previous Workshops with an orientation towards industrial and environmental applications. Many high-quality papers on microplasmas and microdischarges were presented and selected full papers were submitted to Journal of Physics D: Applied Physics for assessment by the editors and reviewers in accordance with the usual standards of quality and novelty. This Cluster Issue contains twelve accepted papers, covering four categories: fundamentals and basics, and environmental, biomedical and industrial applications. Fundamentals and basics includes coverage of the physics and microstructure of electrode discharge (Yu A Lebedev et al), the characteristics of low current discharge (Z Lj Petrović et al), plasma ignition (R Gesche et al), novel optical diagnostics (Schulz-von der Gathen et al), plasma generation and micronozzle flow (T Takahashi et al) and the relation between RF-power and atomic oxygen density distribution (N Knake et al). Environmental applications are represented by vapour-phase discharges in liquid capillaries (P Bruggeman et al) and biomedical applications by antibacterial treatment (K D Weltmann et al). Industrial applications include on-chip microplasma reactors (A Agiral et al), miniaturized atmospheric pressure plasma jets (J Schäfer et al and A V Pipa et al) and microplasma stamps (N Lucas et al). All of these represent important findings and advances in microplasma research and applications. We would like to thank the Publisher of the journal, Sarah Quin, and the editorial staff for their support and management of the publication. It is sincerely hoped that the contents of this Cluster Issue will promote understanding of microplasmas and microdischarges, and inspire further research towards industrial applications.

Investigation of point and extended defects in electron irradiated silicon—Dependence on the particle energy

NASA Astrophysics Data System (ADS)

Radu, R.; Pintilie, I.; Nistor, L. C.; Fretwurst, E.; Lindstroem, G.; Makarenko, L. F.

2015-04-01

This work is focusing on generation, time evolution, and impact on the electrical performance of silicon diodes impaired by radiation induced active defects. n-type silicon diodes had been irradiated with electrons ranging from 1.5 MeV to 27 MeV. It is shown that the formation of small clusters starts already after irradiation with high fluence of 1.5 MeV electrons. An increase of the introduction rates of both point defects and small clusters with increasing energy is seen, showing saturation for electron energies above ˜15 MeV. The changes in the leakage current at low irradiation fluence-values proved to be determined by the change in the configuration of the tri-vacancy (V3). Similar to V3, other cluster related defects are showing bistability indicating that they might be associated with larger vacancy clusters. The change of the space charge density with irradiation and with annealing time after irradiation is fully described by accounting for the radiation induced trapping centers. High resolution electron microscopy investigations correlated with the annealing experiments revealed changes in the spatial structure of the defects. Furthermore, it is shown that while the generation of point defects is well described by the classical Non Ionizing Energy Loss (NIEL), the formation of small defect clusters is better described by the "effective NIEL" using results from molecular dynamics simulations.

InCHlib - interactive cluster heatmap for web applications.

PubMed

Skuta, Ctibor; Bartůněk, Petr; Svozil, Daniel

2014-12-01

Hierarchical clustering is an exploratory data analysis method that reveals the groups (clusters) of similar objects. The result of the hierarchical clustering is a tree structure called dendrogram that shows the arrangement of individual clusters. To investigate the row/column hierarchical cluster structure of a data matrix, a visualization tool called 'cluster heatmap' is commonly employed. In the cluster heatmap, the data matrix is displayed as a heatmap, a 2-dimensional array in which the colour of each element corresponds to its value. The rows/columns of the matrix are ordered such that similar rows/columns are near each other. The ordering is given by the dendrogram which is displayed on the side of the heatmap. We developed InCHlib (Interactive Cluster Heatmap Library), a highly interactive and lightweight JavaScript library for cluster heatmap visualization and exploration. InCHlib enables the user to select individual or clustered heatmap rows, to zoom in and out of clusters or to flexibly modify heatmap appearance. The cluster heatmap can be augmented with additional metadata displayed in a different colour scale. In addition, to further enhance the visualization, the cluster heatmap can be interconnected with external data sources or analysis tools. Data clustering and the preparation of the input file for InCHlib is facilitated by the Python utility script inchlib_clust . The cluster heatmap is one of the most popular visualizations of large chemical and biomedical data sets originating, e.g., in high-throughput screening, genomics or transcriptomics experiments. The presented JavaScript library InCHlib is a client-side solution for cluster heatmap exploration. InCHlib can be easily deployed into any modern web application and configured to cooperate with external tools and data sources. Though InCHlib is primarily intended for the analysis of chemical or biological data, it is a versatile tool which application domain is not limited to the life sciences only.

Equilibrium structure and atomic vibrations of Nin clusters

NASA Astrophysics Data System (ADS)

Borisova, Svetlana D.; Rusina, Galina G.

2017-12-01

The equilibrium bond lengths and binding energy, second differences in energy and vibrational frequencies of free clusters Nin (2 ≤ n ≤ 20) were calculated with the use of the interaction potential obtained in the tight-binding approximation (TBA). The results show that the minimum vibration frequency plays a significant role in the evaluation of the dynamic stability of the clusters. A nonmonotonic dependence of the minimum vibration frequency of clusters on their size and the extreme values for the number of atoms in a cluster n = 4, 6, 13, and 19 are demonstrated. This result agrees with the theoretical and experimental data on stable structures of small metallic clusters.

A Bimodal Hybrid Model for Time-Dependent Probabilistic Seismic Hazard Analysis

NASA Astrophysics Data System (ADS)

Yaghmaei-Sabegh, Saman; Shoaeifar, Nasser; Shoaeifar, Parva

2018-03-01

The evaluation of evidence provided by geological studies and historical catalogs indicates that in some seismic regions and faults, multiple large earthquakes occur in cluster. Then, the occurrences of large earthquakes confront with quiescence and only the small-to-moderate earthquakes take place. Clustering of large earthquakes is the most distinguishable departure from the assumption of constant hazard of random occurrence of earthquakes in conventional seismic hazard analysis. In the present study, a time-dependent recurrence model is proposed to consider a series of large earthquakes that occurs in clusters. The model is flexible enough to better reflect the quasi-periodic behavior of large earthquakes with long-term clustering, which can be used in time-dependent probabilistic seismic hazard analysis with engineering purposes. In this model, the time-dependent hazard results are estimated by a hazard function which comprises three parts. A decreasing hazard of last large earthquake cluster and an increasing hazard of the next large earthquake cluster, along with a constant hazard of random occurrence of small-to-moderate earthquakes. In the final part of the paper, the time-dependent seismic hazard of the New Madrid Seismic Zone at different time intervals has been calculated for illustrative purpose.

Fast and automated functional classification with MED-SuMo: an application on purine-binding proteins.

PubMed

Doppelt-Azeroual, Olivia; Delfaud, François; Moriaud, Fabrice; de Brevern, Alexandre G

2010-04-01

Ligand-protein interactions are essential for biological processes, and precise characterization of protein binding sites is crucial to understand protein functions. MED-SuMo is a powerful technology to localize similar local regions on protein surfaces. Its heuristic is based on a 3D representation of macromolecules using specific surface chemical features associating chemical characteristics with geometrical properties. MED-SMA is an automated and fast method to classify binding sites. It is based on MED-SuMo technology, which builds a similarity graph, and it uses the Markov Clustering algorithm. Purine binding sites are well studied as drug targets. Here, purine binding sites of the Protein DataBank (PDB) are classified. Proteins potentially inhibited or activated through the same mechanism are gathered. Results are analyzed according to PROSITE annotations and to carefully refined functional annotations extracted from the PDB. As expected, binding sites associated with related mechanisms are gathered, for example, the Small GTPases. Nevertheless, protein kinases from different Kinome families are also found together, for example, Aurora-A and CDK2 proteins which are inhibited by the same drugs. Representative examples of different clusters are presented. The effectiveness of the MED-SMA approach is demonstrated as it gathers binding sites of proteins with similar structure-activity relationships. Moreover, an efficient new protocol associates structures absent of cocrystallized ligands to the purine clusters enabling those structures to be associated with a specific binding mechanism. Applications of this classification by binding mode similarity include target-based drug design and prediction of cross-reactivity and therefore potential toxic side effects.

Fast and automated functional classification with MED-SuMo: An application on purine-binding proteins

PubMed Central

Doppelt-Azeroual, Olivia; Delfaud, François; Moriaud, Fabrice; de Brevern, Alexandre G

2010-01-01

Ligand–protein interactions are essential for biological processes, and precise characterization of protein binding sites is crucial to understand protein functions. MED-SuMo is a powerful technology to localize similar local regions on protein surfaces. Its heuristic is based on a 3D representation of macromolecules using specific surface chemical features associating chemical characteristics with geometrical properties. MED-SMA is an automated and fast method to classify binding sites. It is based on MED-SuMo technology, which builds a similarity graph, and it uses the Markov Clustering algorithm. Purine binding sites are well studied as drug targets. Here, purine binding sites of the Protein DataBank (PDB) are classified. Proteins potentially inhibited or activated through the same mechanism are gathered. Results are analyzed according to PROSITE annotations and to carefully refined functional annotations extracted from the PDB. As expected, binding sites associated with related mechanisms are gathered, for example, the Small GTPases. Nevertheless, protein kinases from different Kinome families are also found together, for example, Aurora-A and CDK2 proteins which are inhibited by the same drugs. Representative examples of different clusters are presented. The effectiveness of the MED-SMA approach is demonstrated as it gathers binding sites of proteins with similar structure-activity relationships. Moreover, an efficient new protocol associates structures absent of cocrystallized ligands to the purine clusters enabling those structures to be associated with a specific binding mechanism. Applications of this classification by binding mode similarity include target-based drug design and prediction of cross-reactivity and therefore potential toxic side effects. PMID:20162627

A Spatiotemporal Indexing Approach for Efficient Processing of Big Array-Based Climate Data with MapReduce

NASA Technical Reports Server (NTRS)

Li, Zhenlong; Hu, Fei; Schnase, John L.; Duffy, Daniel Q.; Lee, Tsengdar; Bowen, Michael K.; Yang, Chaowei

2016-01-01

Climate observations and model simulations are producing vast amounts of array-based spatiotemporal data. Efficient processing of these data is essential for assessing global challenges such as climate change, natural disasters, and diseases. This is challenging not only because of the large data volume, but also because of the intrinsic high-dimensional nature of geoscience data. To tackle this challenge, we propose a spatiotemporal indexing approach to efficiently manage and process big climate data with MapReduce in a highly scalable environment. Using this approach, big climate data are directly stored in a Hadoop Distributed File System in its original, native file format. A spatiotemporal index is built to bridge the logical array-based data model and the physical data layout, which enables fast data retrieval when performing spatiotemporal queries. Based on the index, a data-partitioning algorithm is applied to enable MapReduce to achieve high data locality, as well as balancing the workload. The proposed indexing approach is evaluated using the National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA) climate reanalysis dataset. The experimental results show that the index can significantly accelerate querying and processing (10 speedup compared to the baseline test using the same computing cluster), while keeping the index-to-data ratio small (0.0328). The applicability of the indexing approach is demonstrated by a climate anomaly detection deployed on a NASA Hadoop cluster. This approach is also able to support efficient processing of general array-based spatiotemporal data in various geoscience domains without special configuration on a Hadoop cluster.

Numerical investigation of depth profiling capabilities of helium and neon ions in ion microscopy

PubMed Central

Rzeznik, Lukasz; Wirtz, Tom

2016-01-01

The analysis of polymers by secondary ion mass spectrometry (SIMS) has been a topic of interest for many years. In recent years, the primary ion species evolved from heavy monatomic ions to cluster and massive cluster primary ions in order to preserve a maximum of organic information. The progress in less-damaging sputtering goes along with a loss in lateral resolution for 2D and 3D imaging. By contrast the development of a mass spectrometer as an add-on tool for the helium ion microscope (HIM), which uses finely focussed He+ or Ne+ beams, allows for the analysis of secondary ions and small secondary cluster ions with unprecedented lateral resolution. Irradiation induced damage and depth profiling capabilities obtained with these light rare gas species have been far less investigated than ion species used classically in SIMS. In this paper we simulated the sputtering of multi-layered polymer samples using the BCA (binary collision approximation) code SD_TRIM_SP to study preferential sputtering and atomic mixing in such samples up to a fluence of 1018 ions/cm2. Results show that helium primary ions are completely inappropriate for depth profiling applications with this kind of sample materials while results for neon are similar to argon. The latter is commonly used as primary ion species in SIMS. For the two heavier species, layers separated by 10 nm can be distinguished for impact energies of a few keV. These results are encouraging for 3D imaging applications where lateral and depth information are of importance. PMID:28144525

Silver Clusters in Zeolites: From Self-Assembly to Ground-Breaking Luminescent Properties.

PubMed

Coutiño-Gonzalez, Eduardo; Baekelant, Wouter; Steele, Julian A; Kim, Cheol Woong; Roeffaers, Maarten B J; Hofkens, Johan

2017-09-19

Interest for functional silver clusters (Ag-CLs) has rapidly grown over years due to large advances in the field of nanoscale fabrication and materials science. The continuous development of strategies to fabricate small-scale silver clusters, together with their interesting physicochemical properties (molecule-like discrete energy levels, for example), make them very attractive for a wide variety of applied research fields, from biotechnology and the environmental sciences to fundamental chemistry and physics. Apart from useful catalytic properties, silver clusters (Ag n , n < 10) were recently shown to also exhibit exceptional optical properties. The optical properties and performance of Ag-CLs offer strong potential for their integration into appealing micro(nano)-optoelectronic devices. To date, however, the rational design and directed synthesis of Ag-CLs with specific functionalities has remained elusive. The inability for rational design stems mainly from a lack of understanding of their novel atomic-scale phenomena. This is because accurately studying silver cluster systems at such a scale is hindered by the perturbations introduced during exposure to various experimental probes. For instance, silver possesses a strong tendency to cluster and form ever-larger Ag aggregates while probed with high-energy electron beams and X-ray irradiation. As well, there exists a need to provide a stabilizing environment for which Ag n δ+ clusters can persist, setting up a complex interacting guest-host system, as isolated silver clusters are confined within a suitable hosting medium. Fundamental research into Ag n δ+ formation mechanisms and their important optical properties is paramount to establishing truly informed synthesis protocols. Over recent years, we have developed several protocols for the ship-in-a-bottle synthesis of highly luminescent Ag-CLs within the microporous interiors of zeolite frameworks. This approach has yielded materials displaying a wide variety of optical properties, offering a spectrum of possible applications, from nano(micro)photonic devices to smart luminescent labels and sensors. The versatility of the Ag-zeolite multicomponent system is directly related to the intrinsic and complex tunability of the system as a whole. There are several key zeolite parameters that confer properties to the clusters, namely, the framework Si/Al ratio, choice of counterbalancing ions, silver loading, and zeolite topology, and cannot be overlooked. This Account is intended to shed light on the current state-of-the-art of luminescent Ag-CLs confined in zeolitic matrices, emphasizing the use of combinatorial approaches to overcome problems associated with the correct characterization and correlation of their structural, electronic, and photoluminescence properties, all to establish the important design principles for developing functional silver-zeolite-based materials. Additionally, examples of emerging applications and future perspectives for functional luminescent Ag-zeolite materials are addressed in this Account.

Adsorption of Bromine on Gold Nanoclusters

NASA Astrophysics Data System (ADS)

Salvo, Christopher; Keagy, Josiah; Yarmoff, Jory

Small metal nanoclusters are extremely effective as catalysts, with rates that rival those of enzymes in biological systems. The first step in a catalytic reaction is the adsorption of a precursor molecule. The neutralization of alkali projectiles during low energy ion scattering (LEIS), which is acutely sensitive to the local electrostatic potential a few Å's above the surface, is used here to probe Au nanoclusters grown on SiO2 as they are reacted with Br2. Previous work had demonstrated very efficient neutralization in scattering from small catalytically active Au clusters, which was interpreted as an indication that the bare clusters are negatively charged. X-ray photoelectron spectroscopy and LEIS show little or no Br signal after exposing SiO2 and Au foil to Br2, suggesting that adsorption does not occur because the Br-Br bond does not break. Dissociative adsorption occurs rapidly, however, when small Au nanoclusters are reacted with Br2. 1.5 keV Na+ ions scattered from the Au clusters show a decrease in the neutralization probability as Br is reacted, indicating that adsorption results in charge being transferred from the cluster to the Br adatom. This material is based upon work supported by the National Science Foundation under CHE - 1611563.

Harmony in the small-world

NASA Astrophysics Data System (ADS)

Marchiori, Massimo; Latora, Vito

2000-10-01

The small-world phenomenon, popularly known as six degrees of separation, has been mathematically formalized by Watts and Strogatz in a study of the topological properties of a network. Small-world networks are defined in terms of two quantities: they have a high clustering coefficient C like regular lattices and a short characteristic path length L typical of random networks. Physical distances are of fundamental importance in applications to real cases; nevertheless, this basic ingredient is missing in the original formulation. Here, we introduce a new concept, the connectivity length D, that gives harmony to the whole theory. D can be evaluated on a global and on a local scale and plays in turn the role of L and 1/ C. Moreover, it can be computed for any metrical network and not only for the topological cases. D has a precise meaning in terms of information propagation and describes in a unified way, both the structural and the dynamical aspects of a network: small-worlds are defined by a small global and local D, i.e., by a high efficiency in propagating information both on a local and global scale. The neural system of the nematode C. elegans, the collaboration graph of film actors, and the oldest US subway system, can now be studied also as metrical networks and are shown to be small-worlds.

A broad survey reveals substitution tolerance of residues ligating FeS clusters in [NiFe] hydrogenase

PubMed Central

2014-01-01

Background In order to understand the effects of FeS cluster attachment in [NiFe] hydrogenase, we undertook a study to substitute all 12 amino acid positions normally ligating the three FeS clusters in the hydrogenase small subunit. Using the hydrogenase from Alteromonas macleodii “deep ecotype” as a model, we substituted one of four amino acids (Asp, His, Asn, Gln) at each of the 12 ligating positions because these amino acids are alternative coordinating residues in otherwise conserved-cysteine positions found in a broad survey of NiFe hydrogenase sequences. We also hoped to discover an enzyme with elevated hydrogen evolution activity relative to a previously reported “G1” (H230C/P285C) improved enzyme in which the medial FeS cluster Pro and the distal FeS cluster His were each substituted for Cys. Results Among all the substitutions screened, aspartic acid substitutions were generally well-tolerated, and examination suggests that the observed deficiency in enzyme activity may be largely due to misprocessing of the small subunit of the enzyme. Alignment of hydrogenase sequences from sequence databases revealed many rare substitutions; the five substitutions present in databases that we tested all exhibited measurable hydrogen evolution activity. Select substitutions were purified and tested, supporting the results of the screening assay. Analysis of these results confirms the importance of small subunit processing. Normalizing activity to quantity of mature small subunit, indicative of total enzyme maturation, weakly suggests an improvement over the “G1” enzyme. Conclusions We have comprehensively screened 48 amino acid substitutions of the hydrogenase from A. macleodii “deep ecotype”, to understand non-canonical ligations of amino acids to FeS clusters and to improve hydrogen evolution activity of this class of hydrogenase. Our studies show that non-canonical ligations can be functional and also suggests a new limiting factor in the production of active enzyme. PMID:24934472

Kimberlites of the Man craton, West Africa

NASA Astrophysics Data System (ADS)

Skinner, E. M. W.; Apter, D. B.; Morelli, C.; Smithson, N. K.

2004-09-01

The Man craton in West Africa is an Archaean craton formerly joined to the Guyana craton (South America) that was rifted apart in the Mesozoic. Kimberlites of the Man craton include three Jurassic-aged clusters in Guinea, two Jurassic-aged clusters in Sierra Leone, and in Liberia two clusters of unknown age and one Neoproterozoic cluster recently dated at ∼800 Ma. All of the kimberlites irrespective of age occur as small pipes and prolific dykes. Some of the Banankoro cluster pipes in Guinea, the Koidu pipes in Sierra Leone and small pipes in the Weasua cluster in Liberia contain hypabyssal-facies kimberlite and remnants of the so-called transitional-facies and diatreme-facies kimberlite. Most of the Man craton kimberlites are mineralogically classified as phlogopite kimberlites, although potassium contents are relatively low. They are chemically similar to mica-poor Group 1A Southern African examples. The Jurassic kimberlites are considered to represent one province of kimberlites that track from older bodies in Guinea (Droujba 153 Ma) to progressively younger kimberlites in Sierra Leone (Koidu, 146 Ma and Tongo, 140 Ma). The scarcity of diatreme-facies kimberlites relative to hypabyssal-facies kimberlites and the presence of the so-called transitional-facies indicate that the pipes have been eroded down to the interface between the root and diatreme zones. From this observation, it is concluded that extensive erosion (1-2 km) has occurred since the Jurassic. In addition to erosion, the presence of abundant early crystallizing phlogopite is considered to have had an effect on the relatively small sizes of the Man craton kimberlites.

Kinematics of AWM and MKW Poor Clusters

NASA Astrophysics Data System (ADS)

Koranyi, Daniel M.; Geller, Margaret J.

2002-01-01

We have measured 1365 redshifts to a limiting magnitude of R~15.5 in 15 AWM/MKW clusters and have collected another 203 from the literature in MKW 4s, MKW 2, and MKW 2s. In AWM 7 we have extended the redshift sample to R~18 in the cluster center. We have identified 704 cluster members in 17 clusters; 201 are newly identified. We summarize the kinematics and distributions of the cluster galaxies and provide an initial discussion of substructure, mass and luminosity segregation, spectral segregation, velocity-dispersion profiles, and the relation of the central galaxy to global cluster properties. We compute optical mass estimates, which we compare with X-ray mass determinations from the literature. The clusters are in a variety of dynamical states, reflected in the three classes of behavior of the velocity-dispersion profile in the core: rising, falling, or flat/ambiguous. The velocity dispersion of the emission-line galaxy population significantly exceeds that of the absorption-line galaxies in almost all of the clusters, and the presence of emission-line galaxies at small projected radii suggests continuing infall of galaxies onto the clusters. The presence of a cD galaxy does not constrain the global cluster properties; these clusters are similar to other poor clusters that contain no cD. We use the similarity of the velocity-dispersion profiles at small radii and the cD-like galaxies' internal velocity dispersions to argue that cD formation is a local phenomenon. Our sample establishes an empirical observational baseline of poor clusters for comparison with simulations of similar systems. Observations reported in this paper were obtained at the Multiple Mirror Telescope Observatory, a facility operated jointly by the University of Arizona and the Smithsonian Institution; at the Whipple Observatory, a facility operated jointly by the Smithsonian Astrophysical Observatory and Harvard University; and at the WIYN Observatory, a joint facility of the University of Wisconsin-Madison, Indiana University, Yale University, and the National Optical Astronomy Observatories.

A novel artificial immune algorithm for spatial clustering with obstacle constraint and its applications.

PubMed

Sun, Liping; Luo, Yonglong; Ding, Xintao; Zhang, Ji

2014-01-01

An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect.

A new clustering algorithm applicable to multispectral and polarimetric SAR images

NASA Technical Reports Server (NTRS)

Wong, Yiu-Fai; Posner, Edward C.

1993-01-01

We describe an application of a scale-space clustering algorithm to the classification of a multispectral and polarimetric SAR image of an agricultural site. After the initial polarimetric and radiometric calibration and noise cancellation, we extracted a 12-dimensional feature vector for each pixel from the scattering matrix. The clustering algorithm was able to partition a set of unlabeled feature vectors from 13 selected sites, each site corresponding to a distinct crop, into 13 clusters without any supervision. The cluster parameters were then used to classify the whole image. The classification map is much less noisy and more accurate than those obtained by hierarchical rules. Starting with every point as a cluster, the algorithm works by melting the system to produce a tree of clusters in the scale space. It can cluster data in any multidimensional space and is insensitive to variability in cluster densities, sizes and ellipsoidal shapes. This algorithm, more powerful than existing ones, may be useful for remote sensing for land use.

A Fast Density-Based Clustering Algorithm for Real-Time Internet of Things Stream

PubMed Central

Ying Wah, Teh

2014-01-01

Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets. PMID:25110753

A fast density-based clustering algorithm for real-time Internet of Things stream.

PubMed

Amini, Amineh; Saboohi, Hadi; Wah, Teh Ying; Herawan, Tutut

2014-01-01

Data streams are continuously generated over time from Internet of Things (IoT) devices. The faster all of this data is analyzed, its hidden trends and patterns discovered, and new strategies created, the faster action can be taken, creating greater value for organizations. Density-based method is a prominent class in clustering data streams. It has the ability to detect arbitrary shape clusters, to handle outlier, and it does not need the number of clusters in advance. Therefore, density-based clustering algorithm is a proper choice for clustering IoT streams. Recently, several density-based algorithms have been proposed for clustering data streams. However, density-based clustering in limited time is still a challenging issue. In this paper, we propose a density-based clustering algorithm for IoT streams. The method has fast processing time to be applicable in real-time application of IoT devices. Experimental results show that the proposed approach obtains high quality results with low computation time on real and synthetic datasets.

Neural activity in relation to empirically derived personality syndromes in depression using a psychodynamic fMRI paradigm

PubMed Central

Taubner, Svenja; Wiswede, Daniel; Kessler, Henrik

2013-01-01

Objective: The heterogeneity between patients with depression cannot be captured adequately with existing descriptive systems of diagnosis and neurobiological models of depression. Furthermore, considering the highly individual nature of depression, the application of general stimuli in past research efforts may not capture the essence of the disorder. This study aims to identify subtypes of depression by using empirically derived personality syndromes, and to explore neural correlates of the derived personality syndromes. Materials and Methods: In the present exploratory study, an individually tailored and psychodynamically based functional magnetic resonance imaging paradigm using dysfunctional relationship patterns was presented to 20 chronically depressed patients. Results from the Shedler–Westen Assessment Procedure (SWAP-200) were analyzed by Q-factor analysis to identify clinically relevant subgroups of depression and related brain activation. Results: The principle component analysis of SWAP-200 items from all 20 patients lead to a two-factor solution: “Depressive Personality” and “Emotional-Hostile-Externalizing Personality.” Both factors were used in a whole-brain correlational analysis but only the second factor yielded significant positive correlations in four regions: a large cluster in the right orbitofrontal cortex (OFC), the left ventral striatum, a small cluster in the left temporal pole, and another small cluster in the right middle frontal gyrus. Discussion: The degree to which patients with depression score high on the factor “Emotional-Hostile-Externalizing Personality” correlated with relatively higher activity in three key areas involved in emotion processing, evaluation of reward/punishment, negative cognitions, depressive pathology, and social knowledge (OFC, ventral striatum, temporal pole). Results may contribute to an alternative description of neural correlates of depression showing differential brain activation dependent on the extent of specific personality syndromes in depression. PMID:24363644

High Performance Geostatistical Modeling of Biospheric Resources

NASA Astrophysics Data System (ADS)

Pedelty, J. A.; Morisette, J. T.; Smith, J. A.; Schnase, J. L.; Crosier, C. S.; Stohlgren, T. J.

2004-12-01

We are using parallel geostatistical codes to study spatial relationships among biospheric resources in several study areas. For example, spatial statistical models based on large- and small-scale variability have been used to predict species richness of both native and exotic plants (hot spots of diversity) and patterns of exotic plant invasion. However, broader use of geostastics in natural resource modeling, especially at regional and national scales, has been limited due to the large computing requirements of these applications. To address this problem, we implemented parallel versions of the kriging spatial interpolation algorithm. The first uses the Message Passing Interface (MPI) in a master/slave paradigm on an open source Linux Beowulf cluster, while the second is implemented with the new proprietary Xgrid distributed processing system on an Xserve G5 cluster from Apple Computer, Inc. These techniques are proving effective and provide the basis for a national decision support capability for invasive species management that is being jointly developed by NASA and the US Geological Survey.

Classification of ligand molecules in PDB with fast heuristic graph match algorithm COMPLIG.

PubMed

Saito, Mihoko; Takemura, Naomi; Shirai, Tsuyoshi

2012-12-14

A fast heuristic graph-matching algorithm, COMPLIG, was devised to classify the small-molecule ligands in the Protein Data Bank (PDB), which are currently not properly classified on structure basis. By concurrently classifying proteins and ligands, we determined the most appropriate parameter for categorizing ligands to be more than 60% identity of atoms and bonds between molecules, and we classified 11,585 types of ligands into 1946 clusters. Although the large clusters were composed of nucleotides or amino acids, a significant presence of drug compounds was also observed. Application of the system to classify the natural ligand status of human proteins in the current database suggested that, at most, 37% of the experimental structures of human proteins were in complex with natural ligands. However, protein homology- and/or ligand similarity-based modeling was implied to provide models of natural interactions for an additional 28% of the total, which might be used to increase the knowledge of intrinsic protein-metabolite interactions. Copyright © 2012 Elsevier Ltd. All rights reserved.

Clustering-based energy-saving algorithm in ultra-dense network

NASA Astrophysics Data System (ADS)

Huang, Junwei; Zhou, Pengguang; Teng, Deyang; Zhang, Renchi; Xu, Hao

2017-06-01

In Ultra-dense Networks (UDN), dense deployment of low power small base stations will cause serious small cells interference and a large amount of energy consumption. The purpose of this paper is to explore the method of reducing small cells interference and energy saving system in UDN, and we innovatively propose a sleep-waking-active (SWA) scheme. The scheme decreases the user outage causing by failure to detect users’ service requests, shortens the opening time of active base stations directly switching to sleep mode; we further proposes a Vertex Surrounding Clustering(VSC) algorithm, which first colours the small cells with the most strongest interference and next extends to the adjacent small cells. VSC algorithm can use the least colour to stain the small cell, reduce the number of iterations and promote the efficiency of colouring. The simulation results show that SWA scheme can effectively improve the system Energy Efficiency (EE), the VSC algorithm can reduce the small cells interference and optimize the users’ Spectrum Efficiency (SE) and throughput.

The UAV take-off and landing system used for small areas of mobile vehicles

NASA Astrophysics Data System (ADS)

Ren, Tian-Yu; Duanmu, Qing-Duo; Wu, Bo-Qi

2018-03-01

In order to realize an UAV formation cluster system based on the current GPS and the fault and insufficiency of Beidou integrated navigation system in strong jamming environment. Due to the impact of the compass on the plane crash, navigation system error caused by the mobile area to help reduce the need for large landing sites and not in the small fast moving area to achieve the reality of the landing. By using Strapdown inertial and all-optical system to form Composite UAV flight control system, the photoelectric composite strapdown inertial coupling is realized, and through the laser and microwave telemetry link compound communication mechanism, using all-optical strapdown inertial and visual navigation system to solve the deviation of take-off and landing caused by electromagnetic interference, all-optical bidirectional data link realizes two-way position correction of landing site and aircraft, thus achieves the accurate recovery of UAV formation cluster in the mobile narrow area which the traditional navigation system can't realize. This system is a set of efficient unmanned aerial vehicle Group Take-off/descending system, which is suitable for many tasks, and not only realizes the reliable continuous navigation under the complex electromagnetic interference environment, moreover, the intelligent flight and Take-off and landing of unmanned aerial vehicles relative to the fast moving and small recovery sites in complex electromagnetic interference environment can not only improve the safe operation rate of unmanned aerial vehicle, but also guarantee the operation safety of the aircraft, and the more has important social value for the application foreground of the aircraft.

Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

PubMed

Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

2009-07-01

Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

Chromium: A Stress-Processing Framework for Interactive Rendering on Clusters

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

Humphreys, G,; Houston, M.; Ng, Y.-R.

2002-01-11

We describe Chromium, a system for manipulating streams of graphics API commands on clusters of workstations. Chromium's stream filters can be arranged to create sort-first and sort-last parallel graphics architectures that, in many cases, support the same applications while using only commodity graphics accelerators. In addition, these stream filters can be extended programmatically, allowing the user to customize the stream transformations performed by nodes in a cluster. Because our stream processing mechanism is completely general, any cluster-parallel rendering algorithm can be either implemented on top of or embedded in Chromium. In this paper, we give examples of real-world applications thatmore » use Chromium to achieve good scalability on clusters of workstations, and describe other potential uses of this stream processing technology. By completely abstracting the underlying graphics architecture, network topology, and API command processing semantics, we allow a variety of applications to run in different environments.« less

Optical mapping of prefrontal brain connectivity and activation during emotion anticipation.

PubMed

Wang, Meng-Yun; Lu, Feng-Mei; Hu, Zhishan; Zhang, Juan; Yuan, Zhen

2018-09-17

Accumulated neuroimaging evidence shows that the dorsal lateral prefrontal cortex (dlPFC) is activated during emotion anticipation. The aim of this work is to examine the brain connectivity and activation differences in dlPFC between the positive, neutral and negative emotion anticipation by using functional near-infrared spectroscopy (fNIRS). The hemodynamic responses were first assessed for all subjects during the performance of various emotion anticipation tasks. And then small-world analysis was performed, in which the small-world network indicators including the clustering coefficient, average path length, average node degree, and measure of small-world index were calculated for the functional brain networks associated with the positive, neutral and negative emotion anticipation, respectively. We discovered that compared to negative and neutral emotion anticipation, the positive one exhibited enhanced brain activation in the left dlPFC. Although the functional brain networks for the three emotion anticipation cases manifested the small-world properties regarding the clustering coefficient, average path length, average node degree, and measure of small-world index, the positive one showed significantly higher clustering coefficient and shorter average path length than those from the neutral and negative cases. Consequently, the small-world network indicators and brain activation in dlPPC were able to distinguish well between the positive, neutral and negative emotion anticipation. Copyright © 2018 Elsevier B.V. All rights reserved.

Energy Characteristics of Small Metal Clusters Containing Vacancies

NASA Astrophysics Data System (ADS)

Reva, V. I.; Pogosov, V. V.

2018-02-01

Self-consistent calculations of spatial distributions of electrons, potentials, and energies of dissociation, cohesion, vacancy formation, and electron attachment, as well as the ionization potential of solid Al N , Na N clusters ( N ≥ 254), and clusters containing a vacancy ( N ≥ 12) have been performed using a model of stable jellium. The contribution of a monovacancy to the energy of the cluster, the size dependences of the characteristics, and their asymptotic forms have been considered. The calculations have been performed on the SKIT-3 cluster at the Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine (Rpeak = 7.4 Tflops).

Orbital magnetism: pros and cons for enhancing the cluster magnetism.

PubMed

Andriotis, Antonis N; Menon, Madhu

2004-07-09

The discrepancy seen in the experimental and theoretical results on the magnetic moment of a small magnetic cluster has been attributed to the contribution arising from orbital magnetism. In this Letter we show that the magnetic states with large orbital magnetic moment are not always energetically favorable; they could, however, be realizable by coating the cluster or deposing it on appropriate substrates. More importantly, our work shows that the crucial factors that determine the cluster magnetism are found to be the intrinsic, and consequently, the extrinsic properties of the constituent atoms of the cluster.

Poly-Small Ubiquitin-like Modifier (PolySUMO)-binding Proteins Identified through a String Search*

PubMed Central

Sun, Huaiyu; Hunter, Tony

2012-01-01

Polysumoylation is a crucial cellular response to stresses against genomic integrity or proteostasis. Like the small ubiquitin-like modifier (SUMO)-targeted ubiquitin ligase RNF4, proteins with clustered SUMO-interacting motifs (SIMs) can be important signal transducers downstream of polysumoylation. To identify novel polySUMO-binding proteins, we conducted a computational string search with a custom Python script. We found clustered SIMs in another RING domain protein Arkadia/RNF111. Detailed biochemical analysis of the Arkadia SIMs revealed that dominant SIMs in a SIM cluster often contain a pentameric VIDLT ((V/I/L/F/Y)(V/I)DLT) core sequence that is also found in the SIMs in PIAS family E3s and is likely the best-fitted structure for SUMO recognition. This idea led to the identification of additional novel SIM clusters in FLASH/CASP8AP2, C5orf25, and SOBP/JXC1. We suggest that the clustered SIMs in these proteins form distinct SUMO binding domains to recognize diverse forms of protein sumoylation. PMID:23086935

Generating clustered scale-free networks using Poisson based localization of edges

NASA Astrophysics Data System (ADS)

Türker, İlker

2018-05-01

We introduce a variety of network models using a Poisson-based edge localization strategy, which result in clustered scale-free topologies. We first verify the success of our localization strategy by realizing a variant of the well-known Watts-Strogatz model with an inverse approach, implying a small-world regime of rewiring from a random network through a regular one. We then apply the rewiring strategy to a pure Barabasi-Albert model and successfully achieve a small-world regime, with a limited capacity of scale-free property. To imitate the high clustering property of scale-free networks with higher accuracy, we adapted the Poisson-based wiring strategy to a growing network with the ingredients of both preferential attachment and local connectivity. To achieve the collocation of these properties, we used a routine of flattening the edges array, sorting it, and applying a mixing procedure to assemble both global connections with preferential attachment and local clusters. As a result, we achieved clustered scale-free networks with a computational fashion, diverging from the recent studies by following a simple but efficient approach.

Classification of ligand molecules in PDB with graph match-based structural superposition.

PubMed

Shionyu-Mitsuyama, Clara; Hijikata, Atsushi; Tsuji, Toshiyuki; Shirai, Tsuyoshi

2016-12-01

The fast heuristic graph match algorithm for small molecules, COMPLIG, was improved by adding a structural superposition process to verify the atom-atom matching. The modified method was used to classify the small molecule ligands in the Protein Data Bank (PDB) by their three-dimensional structures, and 16,660 types of ligands in the PDB were classified into 7561 clusters. In contrast, a classification by a previous method (without structure superposition) generated 3371 clusters from the same ligand set. The characteristic feature in the current classification system is the increased number of singleton clusters, which contained only one ligand molecule in a cluster. Inspections of the singletons in the current classification system but not in the previous one implied that the major factors for the isolation were differences in chirality, cyclic conformations, separation of substructures, and bond length. Comparisons between current and previous classification systems revealed that the superposition-based classification was effective in clustering functionally related ligands, such as drugs targeted to specific biological processes, owing to the strictness of the atom-atom matching.

Multiple co-clustering based on nonparametric mixture models with heterogeneous marginal distributions

PubMed Central

Yoshimoto, Junichiro; Shimizu, Yu; Okada, Go; Takamura, Masahiro; Okamoto, Yasumasa; Yamawaki, Shigeto; Doya, Kenji

2017-01-01

We propose a novel method for multiple clustering, which is useful for analysis of high-dimensional data containing heterogeneous types of features. Our method is based on nonparametric Bayesian mixture models in which features are automatically partitioned (into views) for each clustering solution. This feature partition works as feature selection for a particular clustering solution, which screens out irrelevant features. To make our method applicable to high-dimensional data, a co-clustering structure is newly introduced for each view. Further, the outstanding novelty of our method is that we simultaneously model different distribution families, such as Gaussian, Poisson, and multinomial distributions in each cluster block, which widens areas of application to real data. We apply the proposed method to synthetic and real data, and show that our method outperforms other multiple clustering methods both in recovering true cluster structures and in computation time. Finally, we apply our method to a depression dataset with no true cluster structure available, from which useful inferences are drawn about possible clustering structures of the data. PMID:29049392

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

Clustering effects in ionic polymers: Molecular dynamics simulations.

PubMed

Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S

2015-08-01

Ionic clusters control the structure, dynamics, and transport in soft matter. Incorporating a small fraction of ionizable groups in polymers substantially reduces the mobility of the macromolecules in melts. These ionic groups often associate into random clusters in melts, where the distribution and morphology of the clusters impact the transport in these materials. Here, using molecular dynamic simulations we demonstrate a clear correlation between cluster size and morphology with the polymer mobility in melts of sulfonated polystyrene. We show that in low dielectric media ladderlike clusters that are lower in energy compared with spherical assemblies are formed. Reducing the electrostatic interactions by enhancing the dielectric constant leads to morphological transformation from ladderlike clusters to globular assemblies. Decrease in electrostatic interaction significantly enhances the mobility of the polymer.

Global optimization of small bimetallic Pd-Co binary nanoalloy clusters: a genetic algorithm approach at the DFT level.

PubMed

Aslan, Mikail; Davis, Jack B A; Johnston, Roy L

2016-03-07

The global optimisation of small bimetallic PdCo binary nanoalloys are systematically investigated using the Birmingham Cluster Genetic Algorithm (BCGA). The effect of size and composition on the structures, stability, magnetic and electronic properties including the binding energies, second finite difference energies and mixing energies of Pd-Co binary nanoalloys are discussed. A detailed analysis of Pd-Co structural motifs and segregation effects is also presented. The maximal mixing energy corresponds to Pd atom compositions for which the number of mixed Pd-Co bonds is maximised. Global minimum clusters are distinguished from transition states by vibrational frequency analysis. HOMO-LUMO gap, electric dipole moment and vibrational frequency analyses are made to enable correlation with future experiments.

Coevolutionary dynamics of opinion propagation and social balance: The key role of small-worldness

NASA Astrophysics Data System (ADS)

Chen, Yan; Chen, Lixue; Sun, Xian; Zhang, Kai; Zhang, Jie; Li, Ping

2014-03-01

The propagation of various opinions in social networks, which influences human inter-relationships and even social structure, and hence is a most important part of social life. We have incorporated social balance into opinion propagation in social networks are influenced by social balance. The edges in networks can represent both friendly or hostile relations, and change with the opinions of individual nodes. We introduce a model to characterize the coevolutionary dynamics of these two dynamical processes on Watts-Strogatz (WS) small-world network. We employ two distinct evolution rules (i) opinion renewal; and (ii) relation adjustment. By changing the rewiring probability, and thus the small-worldness of the WS network, we found that the time for the system to reach balanced states depends critically on both the average path length and clustering coefficient of the network, which is different than other networked process like epidemic spreading. In particular, the system equilibrates most quickly when the underlying network demonstrates strong small-worldness, i.e., small average path lengths and large clustering coefficient. We also find that opinion clusters emerge in the process of the network approaching the global equilibrium, and a measure of global contrariety is proposed to quantify the balanced state of a social network.

Significance of clustering and classification applications in digital and physical libraries

NASA Astrophysics Data System (ADS)

Triantafyllou, Ioannis; Koulouris, Alexandros; Zervos, Spiros; Dendrinos, Markos; Giannakopoulos, Georgios

2015-02-01

Applications of clustering and classification techniques can be proved very significant in both digital and physical (paper-based) libraries. The most essential application, document classification and clustering, is crucial for the content that is produced and maintained in digital libraries, repositories, databases, social media, blogs etc., based on various tags and ontology elements, transcending the traditional library-oriented classification schemes. Other applications with very useful and beneficial role in the new digital library environment involve document routing, summarization and query expansion. Paper-based libraries can benefit as well since classification combined with advanced material characterization techniques such as FTIR (Fourier Transform InfraRed spectroscopy) can be vital for the study and prevention of material deterioration. An improved two-level self-organizing clustering architecture is proposed in order to enhance the discrimination capacity of the learning space, prior to classification, yielding promising results when applied to the above mentioned library tasks.

Country clustering applied to the water & sanitation sector: a new tool with potential applications in research & policy

PubMed Central

Onda, Kyle; Crocker, Jonny; Kayser, Georgia Lyn; Bartram, Jamie

2013-01-01

The fields of global health and international development commonly cluster countries by geography and income to target resources and describe progress. For any given sector of interest, a range of relevant indicators can serve as a more appropriate basis for classification. We create a new typology of country clusters specific to the water and sanitation (WatSan) sector based on similarities across multiple WatSan-related indicators. After a literature review and consultation with experts in the WatSan sector, nine indicators were selected. Indicator selection was based on relevance to and suggested influence on national water and sanitation service delivery, and to maximize data availability across as many countries as possible. A hierarchical clustering method and a gap statistic analysis were used to group countries into a natural number of relevant clusters. Two stages of clustering resulted in five clusters, representing 156 countries or 6.75 billion people. The five clusters were not well explained by income or geography, and were unique from existing country clusters used in international development. Analysis of these five clusters revealed that they were more compact and well separated than United Nations and World Bank country clusters. This analysis and resulting country typology suggest that previous geography- or income-based country groupings can be improved upon for applications in the WatSan sector by utilizing globally available WatSan-related indicators. Potential applications include guiding and discussing research, informing policy, improving resource targeting, describing sector progress, and identifying critical knowledge gaps in the WatSan sector. PMID:24054545

Application of Artificial Intelligence For Euler Solutions Clustering

NASA Astrophysics Data System (ADS)

Mikhailov, V.; Galdeano, A.; Diament, M.; Gvishiani, A.; Agayan, S.; Bogoutdinov, Sh.; Graeva, E.; Sailhac, P.

Results of Euler deconvolution strongly depend on the selection of viable solutions. Synthetic calculations using multiple causative sources show that Euler solutions clus- ter in the vicinity of causative bodies even when they do not group densely about perimeter of the bodies. We have developed a clustering technique to serve as a tool for selecting appropriate solutions. The method RODIN, employed in this study, is based on artificial intelligence and was originally designed for problems of classification of large data sets. It is based on a geometrical approach to study object concentration in a finite metric space of any dimension. The method uses a formal definition of cluster and includes free parameters that facilitate the search for clusters of given proper- ties. Test on synthetic and real data showed that the clustering technique successfully outlines causative bodies more accurate than other methods of discriminating Euler solutions. In complicated field cases such as the magnetic field in the Gulf of Saint Malo region (Brittany, France), the method provides geologically insightful solutions. Other advantages of the clustering method application are: - Clusters provide solutions associated with particular bodies or parts of bodies permitting the analysis of different clusters of Euler solutions separately. This may allow computation of average param- eters for individual causative bodies. - Those measurements of the anomalous field that yield clusters also form dense clusters themselves. The application of cluster- ing technique thus outlines areas where the influence of different causative sources is more prominent. This allows one to focus on areas for reinterpretation, using different window sizes, structural indices and so on.

Micro-scale Spatial Clustering of Cholera Risk Factors in Urban Bangladesh.

PubMed

Bi, Qifang; Azman, Andrew S; Satter, Syed Moinuddin; Khan, Azharul Islam; Ahmed, Dilruba; Riaj, Altaf Ahmed; Gurley, Emily S; Lessler, Justin

2016-02-01

Close interpersonal contact likely drives spatial clustering of cases of cholera and diarrhea, but spatial clustering of risk factors may also drive this pattern. Few studies have focused specifically on how exposures for disease cluster at small spatial scales. Improving our understanding of the micro-scale clustering of risk factors for cholera may help to target interventions and power studies with cluster designs. We selected sets of spatially matched households (matched-sets) near cholera case households between April and October 2013 in a cholera endemic urban neighborhood of Tongi Township in Bangladesh. We collected data on exposures to suspected cholera risk factors at the household and individual level. We used intra-class correlation coefficients (ICCs) to characterize clustering of exposures within matched-sets and households, and assessed if clustering depended on the geographical extent of the matched-sets. Clustering over larger spatial scales was explored by assessing the relationship between matched-sets. We also explored whether different exposures tended to appear together in individuals, households, and matched-sets. Household level exposures, including: drinking municipal supplied water (ICC = 0.97, 95%CI = 0.96, 0.98), type of latrine (ICC = 0.88, 95%CI = 0.71, 1.00), and intermittent access to drinking water (ICC = 0.96, 95%CI = 0.87, 1.00) exhibited strong clustering within matched-sets. As the geographic extent of matched-sets increased, the concordance of exposures within matched-sets decreased. Concordance between matched-sets of exposures related to water supply was elevated at distances of up to approximately 400 meters. Household level hygiene practices were correlated with infrastructure shown to increase cholera risk. Co-occurrence of different individual level exposures appeared to mostly reflect the differing domestic roles of study participants. Strong spatial clustering of exposures at a small spatial scale in a cholera endemic population suggests a possible role for highly targeted interventions. Studies with cluster designs in areas with strong spatial clustering of exposures should increase sample size to account for the correlation of these exposures.

How large are the consequences of covariate imbalance in cluster randomized trials: a simulation study with a continuous outcome and a binary covariate at the cluster level.

PubMed

Moerbeek, Mirjam; van Schie, Sander

2016-07-11

The number of clusters in a cluster randomized trial is often low. It is therefore likely random assignment of clusters to treatment conditions results in covariate imbalance. There are no studies that quantify the consequences of covariate imbalance in cluster randomized trials on parameter and standard error bias and on power to detect treatment effects. The consequences of covariance imbalance in unadjusted and adjusted linear mixed models are investigated by means of a simulation study. The factors in this study are the degree of imbalance, the covariate effect size, the cluster size and the intraclass correlation coefficient. The covariate is binary and measured at the cluster level; the outcome is continuous and measured at the individual level. The results show covariate imbalance results in negligible parameter bias and small standard error bias in adjusted linear mixed models. Ignoring the possibility of covariate imbalance while calculating the sample size at the cluster level may result in a loss in power of at most 25 % in the adjusted linear mixed model. The results are more severe for the unadjusted linear mixed model: parameter biases up to 100 % and standard error biases up to 200 % may be observed. Power levels based on the unadjusted linear mixed model are often too low. The consequences are most severe for large clusters and/or small intraclass correlation coefficients since then the required number of clusters to achieve a desired power level is smallest. The possibility of covariate imbalance should be taken into account while calculating the sample size of a cluster randomized trial. Otherwise more sophisticated methods to randomize clusters to treatments should be used, such as stratification or balance algorithms. All relevant covariates should be carefully identified, be actually measured and included in the statistical model to avoid severe levels of parameter and standard error bias and insufficient power levels.

CRISPR-Cas systems: prokaryotes upgrade to adaptive immunity

PubMed Central

Barrangou, Rodolphe; Marraffini, Luciano A.

2014-01-01

Summary Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR), and associated proteins (Cas) comprise the CRISPR-Cas system, which confers adaptive immunity against exogenic elements in many bacteria and most archaea. CRISPR-mediated immunization occurs through the uptake of DNA from invasive genetic elements such as plasmids and viruses, followed by its integration into CRISPR loci. These loci are subsequently transcribed and processed into small interfering RNAs that guide nucleases for specific cleavage of complementary sequences. Conceptually, CRISPR-Cas shares functional features with the mammalian adaptive immune system, while also exhibiting characteristics of Lamarckian evolution. Because immune markers spliced from exogenous agents are integrated iteratively in CRISPR loci, they constitute a genetic record of vaccination events and reflect environmental conditions and changes over time. Cas endonucleases, which can be reprogrammed by small guide RNAs have shown unprecedented potential and flexibility for genome editing, and can be repurposed for numerous DNA targeting applications including transcriptional control. PMID:24766887

Towards Effective Clustering Techniques for the Analysis of Electric Power Grids

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

Hogan, Emilie A.; Cotilla Sanchez, Jose E.; Halappanavar, Mahantesh

2013-11-30

Clustering is an important data analysis technique with numerous applications in the analysis of electric power grids. Standard clustering techniques are oblivious to the rich structural and dynamic information available for power grids. Therefore, by exploiting the inherent topological and electrical structure in the power grid data, we propose new methods for clustering with applications to model reduction, locational marginal pricing, phasor measurement unit (PMU or synchrophasor) placement, and power system protection. We focus our attention on model reduction for analysis based on time-series information from synchrophasor measurement devices, and spectral techniques for clustering. By comparing different clustering techniques onmore » two instances of realistic power grids we show that the solutions are related and therefore one could leverage that relationship for a computational advantage. Thus, by contrasting different clustering techniques we make a case for exploiting structure inherent in the data with implications for several domains including power systems.« less

Membership determination of open clusters based on a spectral clustering method

NASA Astrophysics Data System (ADS)

Gao, Xin-Hua

2018-06-01

We present a spectral clustering (SC) method aimed at segregating reliable members of open clusters in multi-dimensional space. The SC method is a non-parametric clustering technique that performs cluster division using eigenvectors of the similarity matrix; no prior knowledge of the clusters is required. This method is more flexible in dealing with multi-dimensional data compared to other methods of membership determination. We use this method to segregate the cluster members of five open clusters (Hyades, Coma Ber, Pleiades, Praesepe, and NGC 188) in five-dimensional space; fairly clean cluster members are obtained. We find that the SC method can capture a small number of cluster members (weak signal) from a large number of field stars (heavy noise). Based on these cluster members, we compute the mean proper motions and distances for the Hyades, Coma Ber, Pleiades, and Praesepe clusters, and our results are in general quite consistent with the results derived by other authors. The test results indicate that the SC method is highly suitable for segregating cluster members of open clusters based on high-precision multi-dimensional astrometric data such as Gaia data.

Time-resolved in situ XAS study of the preparation of supported gold clusters.

PubMed

Bus, Eveline; Prins, Roel; van Bokhoven, Jeroen A

2007-07-07

Incipient-wetness impregnation of gamma-Al(2)O(3) with HAuCl(4) and subsequent removal of chlorine with NaOH, and deposition-precipitation of HAuCl(4) on TiO(2) at pH 7 resulted in supported Au(3+) species. Time-resolved in situ XAS at the Au L(3) edge showed that the Al(2)O(3)-supported oxidic or hydroxidic species were reduced in hydrogen at 440 K to yield small metallic gold clusters. The Au(3+) precursor decomposed to metallic gold in inert atmosphere at 573 K and in oxidizing atmosphere above 623 K. In all atmospheres, initially small clusters were formed that gradually grew with increasing temperature. The TiO(2)-supported species were considerably less stable. In hydrogen and carbon monoxide, Au(0) clusters of 1 to 1.5 nm were formed at room temperature, which was the lowest temperature studied. In inert and oxidizing atmosphere, the Au(3+) precursor decomposed fully to metallic gold at 530 K, as shown by XAS and temperature-programmed experiments. Large clusters were obtained already in the initial stage of reduction. Residual chlorine inhibited the reduction and led to sintering of the gold clusters. Exposure of the TiO(2)-supported catalyst precursor to light or the X-ray beam led to partial reduction, and STEM showed that storage of the reduced gold clusters under ambient conditions led to agglomeration and bimodal cluster-size distributions.

Recommendations for choosing an analysis method that controls Type I error for unbalanced cluster sample designs with Gaussian outcomes.

PubMed

Johnson, Jacqueline L; Kreidler, Sarah M; Catellier, Diane J; Murray, David M; Muller, Keith E; Glueck, Deborah H

2015-11-30

We used theoretical and simulation-based approaches to study Type I error rates for one-stage and two-stage analytic methods for cluster-randomized designs. The one-stage approach uses the observed data as outcomes and accounts for within-cluster correlation using a general linear mixed model. The two-stage model uses the cluster specific means as the outcomes in a general linear univariate model. We demonstrate analytically that both one-stage and two-stage models achieve exact Type I error rates when cluster sizes are equal. With unbalanced data, an exact size α test does not exist, and Type I error inflation may occur. Via simulation, we compare the Type I error rates for four one-stage and six two-stage hypothesis testing approaches for unbalanced data. With unbalanced data, the two-stage model, weighted by the inverse of the estimated theoretical variance of the cluster means, and with variance constrained to be positive, provided the best Type I error control for studies having at least six clusters per arm. The one-stage model with Kenward-Roger degrees of freedom and unconstrained variance performed well for studies having at least 14 clusters per arm. The popular analytic method of using a one-stage model with denominator degrees of freedom appropriate for balanced data performed poorly for small sample sizes and low intracluster correlation. Because small sample sizes and low intracluster correlation are common features of cluster-randomized trials, the Kenward-Roger method is the preferred one-stage approach. Copyright © 2015 John Wiley & Sons, Ltd.

Hubble Sees an Ancient Globular Cluster

NASA Image and Video Library

2017-12-08

This image captures the stunning NGC 6535, a globular cluster 22,000 light-years away in the constellation of Serpens (The Serpent) that measures one light-year across. Globular clusters are tightly bound groups of stars which orbit galaxies. The large mass in the rich stellar centre of the globular cluster pulls the stars inward to form a ball of stars. The word globulus, from which these clusters take their name, is Latin for small sphere. Globular clusters are generally very ancient objects formed around the same time as their host galaxy. To date, no new star formation has been observed within a globular cluster, which explains the abundance of aging yellow stars in this image, most of them containing very few heavy elements. NGC 6535 was first discovered in 1852 by English astronomer John Russell Hind. The cluster would have appeared to Hind as a small, faint smudge through his telescope. Now, over 160 years later, instruments like the Advanced Camera for Surveys (ACS) and Wide Field Camera 3 (WFC3) on the NASA/ European Space Agency (ESA) Hubble Space Telescope allow us to marvel at the cluster and its contents in greater detail. Credit: ESA/Hubble & NASA, Acknowledgement: Gilles Chapdelaine NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Effects of small-scale clustering of flowers on pollinator foraging behaviour and flower visitation rate.

PubMed

Akter, Asma; Biella, Paolo; Klecka, Jan

2017-01-01

Plants often grow in clusters of various sizes and have a variable number of flowers per inflorescence. This small-scale spatial clustering affects insect foraging strategies and plant reproductive success. In our study, we aimed to determine how visitation rate and foraging behaviour of pollinators depend on the number of flowers per plant and on the size of clusters of multiple plants using Dracocephalum moldavica (Lamiaceae) as a target species. We measured flower visitation rate by observations of insects visiting single plants and clusters of plants with different numbers of flowers. Detailed data on foraging behaviour within clusters of different sizes were gathered for honeybees, Apis mellifera, the most abundant visitor of Dracocephalum in the experiments. We found that the total number of flower visitors increased with the increasing number of flowers on individual plants and in larger clusters, but less then proportionally. Although individual honeybees visited more flowers in larger clusters, they visited a smaller proportion of flowers, as has been previously observed. Consequently, visitation rate per flower and unit time peaked in clusters with an intermediate number of flowers. These patterns do not conform to expectations based on optimal foraging theory and the ideal free distribution model. We attribute this discrepancy to incomplete information about the distribution of resources. Detailed observations and video recordings of individual honeybees also showed that the number of flowers had no effect on handling time of flowers by honeybees. We evaluated the implications of these patterns for insect foraging biology and plant reproduction.

Effects of small-scale clustering of flowers on pollinator foraging behaviour and flower visitation rate

PubMed Central

2017-01-01

Plants often grow in clusters of various sizes and have a variable number of flowers per inflorescence. This small-scale spatial clustering affects insect foraging strategies and plant reproductive success. In our study, we aimed to determine how visitation rate and foraging behaviour of pollinators depend on the number of flowers per plant and on the size of clusters of multiple plants using Dracocephalum moldavica (Lamiaceae) as a target species. We measured flower visitation rate by observations of insects visiting single plants and clusters of plants with different numbers of flowers. Detailed data on foraging behaviour within clusters of different sizes were gathered for honeybees, Apis mellifera, the most abundant visitor of Dracocephalum in the experiments. We found that the total number of flower visitors increased with the increasing number of flowers on individual plants and in larger clusters, but less then proportionally. Although individual honeybees visited more flowers in larger clusters, they visited a smaller proportion of flowers, as has been previously observed. Consequently, visitation rate per flower and unit time peaked in clusters with an intermediate number of flowers. These patterns do not conform to expectations based on optimal foraging theory and the ideal free distribution model. We attribute this discrepancy to incomplete information about the distribution of resources. Detailed observations and video recordings of individual honeybees also showed that the number of flowers had no effect on handling time of flowers by honeybees. We evaluated the implications of these patterns for insect foraging biology and plant reproduction. PMID:29136042

Intrinsic scatter of caustic masses and hydrostatic bias: An observational study

NASA Astrophysics Data System (ADS)

Andreon, S.; Trinchieri, G.; Moretti, A.; Wang, J.

2017-10-01

All estimates of cluster mass have some intrinsic scatter and perhaps some bias with true mass even in the absence of measurement errors for example caused by cluster triaxiality and large scale structure. Knowledge of the bias and scatter values is fundamental for both cluster cosmology and astrophysics. In this paper we show that the intrinsic scatter of a mass proxy can be constrained by measurements of the gas fraction because masses with higher values of intrinsic scatter with true mass produce more scattered gas fractions. Moreover, the relative bias of two mass estimates can be constrained by comparing the mean gas fraction at the same (nominal) cluster mass. Our observational study addresses the scatter between caustic (I.e., dynamically estimated) and true masses, and the relative bias of caustic and hydrostatic masses. For these purposes, we used the X-ray Unbiased Cluster Sample, a cluster sample selected independently from the intracluster medium content with reliable masses: 34 galaxy clusters in the nearby (0.050 < z < 0.135) Universe, mostly with 14 < log M500/M⊙ ≲ 14.5, and with caustic masses. We found a 35% scatter between caustic and true masses. Furthermore, we found that the relative bias between caustic and hydrostatic masses is small, 0.06 ± 0.05 dex, improving upon past measurements. The small scatter found confirms our previous measurements of a highly variable amount of feedback from cluster to cluster, which is the cause of the observed large variety of core-excised X-ray luminosities and gas masses.

On the absence of radio haloes in clusters with double relics

NASA Astrophysics Data System (ADS)

Bonafede, A.; Cassano, R.; Brüggen, M.; Ogrean, G. A.; Riseley, C. J.; Cuciti, V.; de Gasperin, F.; Golovich, N.; Kale, R.; Venturi, T.; van Weeren, R. J.; Wik, D. R.; Wittman, D.

2017-09-01

Pairs of radio relics are believed to form during cluster mergers, and are best observed when the merger occurs in the plane of the sky. Mergers can also produce radio haloes, through complex processes likely linked to turbulent re-acceleration of cosmic ray electrons. However, only some clusters with double relics also show a radio halo. Here, we present a novel method to derive upper limits on the radio halo emission, and analyse archival X-ray Chandra data, as well as galaxy velocity dispersions and lensing data, in order to understand the key parameter that switches on radio halo emission. We place upper limits on the halo power below the P1.4 GHz-M500 correlation for some clusters, confirming that clusters with double relics have different radio properties. Computing X-ray morphological indicators, we find that clusters with double relics are associated with the most disturbed clusters. We also investigate the role of different mass-ratios and time-since-merger. Data do not indicate that the merger mass-ratio has an impact on the presence or absence of radio haloes (the null hypothesis that the clusters belong to the same group cannot be rejected). However, the data suggest that the absence of radio haloes could be associated with early and late mergers, but the sample is too small to perform a statistical test. Our study is limited by the small number of clusters with double relics. Future surveys with LOFAR, ASKAP, MeerKat and SKA will provide larger samples to better address this issue.

Thermodynamically accessible titanium clusters TiN, N = 2-32.

PubMed

Lazauskas, Tomas; Sokol, Alexey A; Buckeridge, John; Catlow, C Richard A; Escher, Susanne G E T; Farrow, Matthew R; Mora-Fonz, David; Blum, Volker W; Phaahla, Tshegofatso M; Chauke, Hasani R; Ngoepe, Phuti E; Woodley, Scott M

2018-05-10

We have performed a genetic algorithm search on the tight-binding interatomic potential energy surface (PES) for small TiN (N = 2-32) clusters. The low energy candidate clusters were further refined using density functional theory (DFT) calculations with the PBEsol exchange-correlation functional and evaluated with the PBEsol0 hybrid functional. The resulting clusters were analysed in terms of their structural features, growth mechanism and surface area. The results suggest a growth mechanism that is based on forming coordination centres by interpenetrating icosahedra, icositetrahedra and Frank-Kasper polyhedra. We identify centres of coordination, which act as centres of bulk nucleation in medium sized clusters and determine the morphological features of the cluster.

Concept design and cluster control of advanced space connectable intelligent microsatellite

NASA Astrophysics Data System (ADS)

Wang, Xiaohui; Li, Shuang; She, Yuchen

2017-12-01

In this note, a new type of advanced space connectable intelligent microsatellite is presented to extend the range of potential application of microsatellite and improve the efficiency of cooperation. First, the overall concept of the micro satellite cluster is described, which is characterized by autonomously connecting with each other and being able to realize relative rotation through the external interfaces. Second, the multi-satellite autonomous assembly algorithm and control algorithm of the cluster motion are developed to make the cluster system combine into a variety of configurations in order to achieve different types of functionality. Finally, the design of the satellite cluster system is proposed, and the possible applications are discussed.

Design and Control of Functional Microbubbles for Medical Applications of Ultrasound

NASA Astrophysics Data System (ADS)

Takagi, Shu; Osaki, Taichi; Ariyoshi, Takuya; Azuma, Takashi; Ichiyanagi, Mitsuhisa; Kinefuchi, Ikuya

2015-11-01

Microbubbles are used as a contrast agent for ultrasound diagnosis. It is also expected to be use for the treatment. One of the possible applications is microbubble DDS. For that purpose, microbubbles need to be well-controlled for the generating process and manipulation. In this talk, for the design and control of the functional microbubbles, an experimental study on generation and surface modification of microbubbles are explained. Using a T-junction type microchannel, small bubbles about 5 μm size are successfully generated. For the surface modification, Biotin-coated microbubbles are tried to adhere the Avidin-coated wall. Furthermore, the manipulation of the microbubbles using ultrasound is also discussed. Plane-wave and focused ultrasound is used to manipulate a microbubble and bubble clusters. The experimental results are shown in the presentation. Supported by JSPS KAKENHI Grant Number 15K13865.

Mammographic images segmentation based on chaotic map clustering algorithm

PubMed Central

2014-01-01

Background This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. Methods The image is divided into pixels subsets characterized by a set of conveniently chosen features and each of the corresponding points in the feature space is associated to a map. A mutual coupling strength between the maps depending on the associated distance between feature space points is subsequently introduced. On the system of maps, the simulated evolution through chaotic dynamics leads to its natural partitioning, which corresponds to a particular segmentation scheme of the initial mammographic image. Results The system provides a high recognition rate for small mass lesions (about 94% correctly segmented inside the breast) and the reproduction of the shape of regions with denser micro-calcifications in about 2/3 of the cases, while being less effective on identification of larger mass lesions. Conclusions We can summarize our analysis by asserting that due to the particularities of the mammographic images, the chaotic map clustering algorithm should not be used as the sole method of segmentation. It is rather the joint use of this method along with other segmentation techniques that could be successfully used for increasing the segmentation performance and for providing extra information for the subsequent analysis stages such as the classification of the segmented ROI. PMID:24666766

The application of time series models to cloud field morphology analysis

NASA Technical Reports Server (NTRS)

Chin, Roland T.; Jau, Jack Y. C.; Weinman, James A.

1987-01-01

A modeling method for the quantitative description of remotely sensed cloud field images is presented. A two-dimensional texture modeling scheme based on one-dimensional time series procedures is adopted for this purpose. The time series procedure used is the seasonal autoregressive, moving average (ARMA) process in Box and Jenkins. Cloud field properties such as directionality, clustering and cloud coverage can be retrieved by this method. It has been demonstrated that a cloud field image can be quantitatively defined by a small set of parameters and synthesized surrogates can be reconstructed from these model parameters. This method enables cloud climatology to be studied quantitatively.

Blocked inverted indices for exact clustering of large chemical spaces.

PubMed

Thiel, Philipp; Sach-Peltason, Lisa; Ottmann, Christian; Kohlbacher, Oliver

2014-09-22

The calculation of pairwise compound similarities based on fingerprints is one of the fundamental tasks in chemoinformatics. Methods for efficient calculation of compound similarities are of the utmost importance for various applications like similarity searching or library clustering. With the increasing size of public compound databases, exact clustering of these databases is desirable, but often computationally prohibitively expensive. We present an optimized inverted index algorithm for the calculation of all pairwise similarities on 2D fingerprints of a given data set. In contrast to other algorithms, it neither requires GPU computing nor yields a stochastic approximation of the clustering. The algorithm has been designed to work well with multicore architectures and shows excellent parallel speedup. As an application example of this algorithm, we implemented a deterministic clustering application, which has been designed to decompose virtual libraries comprising tens of millions of compounds in a short time on current hardware. Our results show that our implementation achieves more than 400 million Tanimoto similarity calculations per second on a common desktop CPU. Deterministic clustering of the available chemical space thus can be done on modern multicore machines within a few days.

The optimal design of stepped wedge trials with equal allocation to sequences and a comparison to other trial designs.

PubMed

Thompson, Jennifer A; Fielding, Katherine; Hargreaves, James; Copas, Andrew

2017-12-01

Background/Aims We sought to optimise the design of stepped wedge trials with an equal allocation of clusters to sequences and explored sample size comparisons with alternative trial designs. Methods We developed a new expression for the design effect for a stepped wedge trial, assuming that observations are equally correlated within clusters and an equal number of observations in each period between sequences switching to the intervention. We minimised the design effect with respect to (1) the fraction of observations before the first and after the final sequence switches (the periods with all clusters in the control or intervention condition, respectively) and (2) the number of sequences. We compared the design effect of this optimised stepped wedge trial to the design effects of a parallel cluster-randomised trial, a cluster-randomised trial with baseline observations, and a hybrid trial design (a mixture of cluster-randomised trial and stepped wedge trial) with the same total cluster size for all designs. Results We found that a stepped wedge trial with an equal allocation to sequences is optimised by obtaining all observations after the first sequence switches and before the final sequence switches to the intervention; this means that the first sequence remains in the control condition and the last sequence remains in the intervention condition for the duration of the trial. With this design, the optimal number of sequences is [Formula: see text], where [Formula: see text] is the cluster-mean correlation, [Formula: see text] is the intracluster correlation coefficient, and m is the total cluster size. The optimal number of sequences is small when the intracluster correlation coefficient and cluster size are small and large when the intracluster correlation coefficient or cluster size is large. A cluster-randomised trial remains more efficient than the optimised stepped wedge trial when the intracluster correlation coefficient or cluster size is small. A cluster-randomised trial with baseline observations always requires a larger sample size than the optimised stepped wedge trial. The hybrid design can always give an equally or more efficient design, but will be at most 5% more efficient. We provide a strategy for selecting a design if the optimal number of sequences is unfeasible. For a non-optimal number of sequences, the sample size may be reduced by allowing a proportion of observations before the first or after the final sequence has switched. Conclusion The standard stepped wedge trial is inefficient. To reduce sample sizes when a hybrid design is unfeasible, stepped wedge trial designs should have no observations before the first sequence switches or after the final sequence switches.

Ionization heating in rare-gas clusters under intense XUV laser pulses

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

Arbeiter, Mathias; Fennel, Thomas

The interaction of intense extreme ultraviolet (XUV) laser pulses ({lambda}=32 nm, I=10{sup 11}-10{sup 14} W/cm{sup 2}) with small rare-gas clusters (Ar{sub 147}) is studied by quasiclassical molecular dynamics simulations. Our analysis supports a very general picture of the charging and heating dynamics in finite samples under short-wavelength radiation that is of relevance for several applications of free-electron lasers. First, up to a certain photon flux, ionization proceeds as a series of direct photoemission events producing a jellium-like cluster potential and a characteristic plateau in the photoelectron spectrum as observed in Bostedt et al. [Phys. Rev. Lett. 100, 133401 (2008)]. Second,more » beyond the onset of photoelectron trapping, nanoplasma formation leads to evaporative electron emission with a characteristic thermal tail in the electron spectrum. A detailed analysis of this transition is presented. Third, in contrast to the behavior in the infrared or low vacuum ultraviolet range, the nanoplasma energy capture proceeds via ionization heating, i.e., inner photoionization of localized electrons, whereas collisional heating of conduction electrons is negligible up to high laser intensities. A direct consequence of the latter is a surprising evolution of the mean energy of emitted electrons as function of laser intensity.« less

DOVIS: an implementation for high-throughput virtual screening using AutoDock.

PubMed

Zhang, Shuxing; Kumar, Kamal; Jiang, Xiaohui; Wallqvist, Anders; Reifman, Jaques

2008-02-27

Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. However, the development of an integrated HPC system that makes efficient use of its elements is not trivial. We have developed an application termed DOVIS that uses AutoDock (version 3) as the docking engine and runs in parallel on a Linux cluster. DOVIS can efficiently dock large numbers (millions) of small molecules (ligands) to a receptor, screening 500 to 1,000 compounds per processor per day. Furthermore, in DOVIS, the docking session is fully integrated and automated in that the inputs are specified via a graphical user interface, the calculations are fully integrated with a Linux cluster queuing system for parallel processing, and the results can be visualized and queried. DOVIS removes most of the complexities and organizational problems associated with large-scale high-throughput virtual screening, and provides a convenient and efficient solution for AutoDock users to use this software in a Linux cluster platform.

High Performance Distributed Computing in a Supercomputer Environment: Computational Services and Applications Issues

NASA Technical Reports Server (NTRS)

Kramer, Williams T. C.; Simon, Horst D.

1994-01-01

This tutorial proposes to be a practical guide for the uninitiated to the main topics and themes of high-performance computing (HPC), with particular emphasis to distributed computing. The intent is first to provide some guidance and directions in the rapidly increasing field of scientific computing using both massively parallel and traditional supercomputers. Because of their considerable potential computational power, loosely or tightly coupled clusters of workstations are increasingly considered as a third alternative to both the more conventional supercomputers based on a small number of powerful vector processors, as well as high massively parallel processors. Even though many research issues concerning the effective use of workstation clusters and their integration into a large scale production facility are still unresolved, such clusters are already used for production computing. In this tutorial we will utilize the unique experience made at the NAS facility at NASA Ames Research Center. Over the last five years at NAS massively parallel supercomputers such as the Connection Machines CM-2 and CM-5 from Thinking Machines Corporation and the iPSC/860 (Touchstone Gamma Machine) and Paragon Machines from Intel were used in a production supercomputer center alongside with traditional vector supercomputers such as the Cray Y-MP and C90.

A Genome Wide Survey of SNP Variation Reveals the Genetic Structure of Sheep Breeds

PubMed Central

Kijas, James W.; Townley, David; Dalrymple, Brian P.; Heaton, Michael P.; Maddox, Jillian F.; McGrath, Annette; Wilson, Peter; Ingersoll, Roxann G.; McCulloch, Russell; McWilliam, Sean; Tang, Dave; McEwan, John; Cockett, Noelle; Oddy, V. Hutton; Nicholas, Frank W.; Raadsma, Herman

2009-01-01

The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identifying the first genome-wide set of SNP for sheep, we report on levels of genetic variability both within and between a diverse sample of ovine populations. Then, using cluster analysis and the partitioning of genetic variation, we demonstrate sheep are characterised by weak phylogeographic structure, overlapping genetic similarity and generally low differentiation which is consistent with their short evolutionary history. The degree of population substructure was, however, sufficient to cluster individuals based on geographic origin and known breed history. Specifically, African and Asian populations clustered separately from breeds of European origin sampled from Australia, New Zealand, Europe and North America. Furthermore, we demonstrate the presence of stratification within some, but not all, ovine breeds. The results emphasize that careful documentation of genetic structure will be an essential prerequisite when mapping the genetic basis of complex traits. Furthermore, the identification of a subset of SNP able to assign individuals into broad groupings demonstrates even a small panel of markers may be suitable for applications such as traceability. PMID:19270757

The Effect of Attractive Interactions and Macromolecular Crowding on Crystallins Association

PubMed Central

Wei, Jiachen; Dobnikar, Jure; Curk, Tine; Song, Fan

2016-01-01

In living systems proteins are typically found in crowded environments where their effective interactions strongly depend on the surrounding medium. Yet, their association and dissociation needs to be robustly controlled in order to enable biological function. Uncontrolled protein aggregation often causes disease. For instance, cataract is caused by the clustering of lens proteins, i.e., crystallins, resulting in enhanced light scattering and impaired vision or blindness. To investigate the molecular origins of cataract formation and to design efficient treatments, a better understanding of crystallin association in macromolecular crowded environment is needed. Here we present a theoretical study of simple coarse grained colloidal models to characterize the general features of how the association equilibrium of proteins depends on the magnitude of intermolecular attraction. By comparing the analytic results to the available experimental data on the osmotic pressure in crystallin solutions, we identify the effective parameters regimes applicable to crystallins. Moreover, the combination of two models allows us to predict that the number of binding sites on crystallin is small, i.e. one to three per protein, which is different from previous estimates. We further observe that the crowding factor is sensitive to the size asymmetry between the reactants and crowding agents, the shape of the protein clusters, and to small variations of intermolecular attraction. Our work may provide general guidelines on how to steer the protein interactions in order to control their association. PMID:26954357

Cluster Computing For Real Time Seismic Array Analysis.

NASA Astrophysics Data System (ADS)

Martini, M.; Giudicepietro, F.

A seismic array is an instrument composed by a dense distribution of seismic sen- sors that allow to measure the directional properties of the wavefield (slowness or wavenumber vector) radiated by a seismic source. Over the last years arrays have been widely used in different fields of seismological researches. In particular they are applied in the investigation of seismic sources on volcanoes where they can be suc- cessfully used for studying the volcanic microtremor and long period events which are critical for getting information on the volcanic systems evolution. For this reason arrays could be usefully employed for the volcanoes monitoring, however the huge amount of data produced by this type of instruments and the processing techniques which are quite time consuming limited their potentiality for this application. In order to favor a direct application of arrays techniques to continuous volcano monitoring we designed and built a small PC cluster able to near real time computing the kinematics properties of the wavefield (slowness or wavenumber vector) produced by local seis- mic source. The cluster is composed of 8 Intel Pentium-III bi-processors PC working at 550 MHz, and has 4 Gigabytes of RAM memory. It runs under Linux operating system. The developed analysis software package is based on the Multiple SIgnal Classification (MUSIC) algorithm and is written in Fortran. The message-passing part is based upon the LAM programming environment package, an open-source imple- mentation of the Message Passing Interface (MPI). The developed software system includes modules devote to receiving date by internet and graphical applications for the continuous displaying of the processing results. The system has been tested with a data set collected during a seismic experiment conducted on Etna in 1999 when two dense seismic arrays have been deployed on the northeast and the southeast flanks of this volcano. A real time continuous acquisition system has been simulated by a pro- gram which reads data from disk files and send them to a remote host by using the Internet protocols.

CHARGING AND COAGULATION OF DUST IN PROTOPLANETARY PLASMA ENVIRONMENTS

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

Matthews, L. S.; Land, V.; Hyde, T. W., E-mail: lorin_matthews@baylor.edu

2012-01-01

Combining a particle-particle, particle-cluster, and cluster-cluster agglomeration model with an aggregate charging model, the coagulation and charging of dust particles in plasma environments relevant for protoplanetary disks have been investigated, including the effect of electron depletion in high dust density environments. The results show that charged aggregates tend to grow by adding small particles and clusters to larger particles and clusters, and that cluster-cluster aggregation is significantly more effective than particle-cluster aggregation. Comparisons of the grain structure show that with increasing aggregate charge the compactness factor, {phi}{sub {sigma}}, decreases and has a narrower distribution, indicating a fluffier structure. Neutral aggregatesmore » are more compact, with larger {phi}{sub {sigma}}, and exhibit a larger variation in fluffiness. Overall, increased aggregate charge leads to larger, fluffier, and more massive aggregates.« less

Different types of small volcanos on Venus

NASA Technical Reports Server (NTRS)

Slyuta, E. N.; Shalimov, I. V.; Nikishin, A. M.

1992-01-01

One of the studies of volcanic activity on Venus is the comparison of that with the analogous volcanic activity on Earth. The preliminary report of such a comparison and description of a small cluster of small venusian volcanos is represented in detail in this paper.

Single-cell RNA-sequencing reveals a distinct population of proglucagon-expressing cells specific to the mouse upper small intestine.

PubMed

Glass, Leslie L; Calero-Nieto, Fernando J; Jawaid, Wajid; Larraufie, Pierre; Kay, Richard G; Göttgens, Berthold; Reimann, Frank; Gribble, Fiona M

2017-10-01

To identify sub-populations of intestinal preproglucagon-expressing (PPG) cells producing Glucagon-like Peptide-1, and their associated expression profiles of sensory receptors, thereby enabling the discovery of therapeutic strategies that target these cell populations for the treatment of diabetes and obesity. We performed single cell RNA sequencing of PPG-cells purified by flow cytometry from the upper small intestine of 3 GLU-Venus mice. Cells from 2 mice were sequenced at low depth, and from the third mouse at high depth. High quality sequencing data from 234 PPG-cells were used to identify clusters by tSNE analysis. qPCR was performed to compare the longitudinal and crypt/villus locations of cluster-specific genes. Immunofluorescence and mass spectrometry were used to confirm protein expression. PPG-cells formed 3 major clusters: a group with typical characteristics of classical L-cells, including high expression of Gcg and Pyy (comprising 51% of all PPG-cells); a cell type overlapping with Gip-expressing K-cells (14%); and a unique cluster expressing Tph1 and Pzp that was predominantly located in proximal small intestine villi and co-produced 5-HT (35%). Expression of G-protein coupled receptors differed between clusters, suggesting the cell types are differentially regulated and would be differentially targetable. Our findings support the emerging concept that many enteroendocrine cell populations are highly overlapping, with individual cells producing a range of peptides previously assigned to distinct cell types. Different receptor expression profiles across the clusters highlight potential drug targets to increase gut hormone secretion for the treatment of diabetes and obesity. Copyright © 2017 The Authors. Published by Elsevier GmbH.. All rights reserved.

Mapping Emission from Clusters of CdSe/ZnS Nanoparticles

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

Ryan, Duncan P.; Goodwin, Peter M.; Sheehan, Chris J.

In this paper, we have carried out correlated super-resolution and SEM imaging studies of clusters of CdSe/ZnS nanoparticles containing up to ten particles to explore how the fluorescence behavior of these clusters depends on the number of particles, the specific cluster geometry, the shell thickness, and the technique used to produce the clusters. The total emission yield was less than proportional to the number of particles in the clusters for both thick and thin shells. With super-resolution imaging, the emission center of the cluster could be spatially resolved at distance scales on the order of the cluster size. The intrinsicmore » fluorescence intermittency of the nanoparticles altered the emission distribution across the cluster, which enabled the identification of relative emission intensities of individual particles or small groups of particles within the cluster. Finally, for clusters undergoing interparticle energy transfer, donor/acceptor pairs and regions where energy was funneled could be identified.« less

Mapping Emission from Clusters of CdSe/ZnS Nanoparticles

DOE PAGES

Ryan, Duncan P.; Goodwin, Peter M.; Sheehan, Chris J.; ...

2018-01-24

In this paper, we have carried out correlated super-resolution and SEM imaging studies of clusters of CdSe/ZnS nanoparticles containing up to ten particles to explore how the fluorescence behavior of these clusters depends on the number of particles, the specific cluster geometry, the shell thickness, and the technique used to produce the clusters. The total emission yield was less than proportional to the number of particles in the clusters for both thick and thin shells. With super-resolution imaging, the emission center of the cluster could be spatially resolved at distance scales on the order of the cluster size. The intrinsicmore » fluorescence intermittency of the nanoparticles altered the emission distribution across the cluster, which enabled the identification of relative emission intensities of individual particles or small groups of particles within the cluster. Finally, for clusters undergoing interparticle energy transfer, donor/acceptor pairs and regions where energy was funneled could be identified.« less

Synchronization as Aggregation: Cluster Kinetics of Pulse-Coupled Oscillators.

PubMed

O'Keeffe, Kevin P; Krapivsky, P L; Strogatz, Steven H

2015-08-07

We consider models of identical pulse-coupled oscillators with global interactions. Previous work showed that under certain conditions such systems always end up in sync, but did not quantify how small clusters of synchronized oscillators progressively coalesce into larger ones. Using tools from the study of aggregation phenomena, we obtain exact results for the time-dependent distribution of cluster sizes as the system evolves from disorder to synchrony.

Helium behavior in oxide dispersion strengthened (ODS) steel: Insights from ab initio modeling

NASA Astrophysics Data System (ADS)

Sun, Dan; Li, Ruihuan; Ding, Jianhua; Huang, Shaosong; Zhang, Pengbo; Lu, Zheng; Zhao, Jijun

2018-02-01

Using first-principles calculations, we systemically investigate the energetics and stability behavior of helium (He) atoms and small Hen (n = 2-4) clusters inside oxide dispersion strengthened (ODS) steel, as well as the incorporation of large amount of He atoms inside Y2O3 crystal. From the energetic point of view, He atom inside Y2O3 cluster is most stable, followed by the interstitial sites at the α-Fe/Y2O3 interface, and the tetrahedral interstitial sites inside α-Fe region. We further consider Hen (n = 2-4) clusters at the tetrahedral interstitial site surrounded by four Y atoms, which is the most stable site in the ODS steel model. The incorporation energies of all these Hen clusters are lower than that of single He atom in α-Fe, while the binding energy between two He atoms is relatively small. With insertion of 15 He atoms into 80-atom unit cell of Y2O3 crystal, the incorporation energy of He atoms is still lower than that of He4 cluster in α-Fe crystal. These theoretical results suggest that He atoms tend to aggregate inside Y2O3 clusters or at the α-Fe/Y2O3 interface, which is beneficial to prevent the He embrittlement in ODS steels.

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

Speaker Linking and Applications using Non-Parametric Hashing Methods

DTIC Science & Technology

2016-09-08

clustering method based on hashing—canopy- clustering . We apply this method to a large corpus of speaker recordings, demonstrate performance tradeoffs...and compare to other hash- ing methods. Index Terms: speaker recognition, clustering , hashing, locality sensitive hashing. 1. Introduction We assume...speaker in our corpus. Second, given a QBE method, how can we perform speaker clustering —each clustering should be a single speaker, and a cluster should

New data clustering for RBF classifier of agriculture products from x-ray images

NASA Astrophysics Data System (ADS)

Casasent, David P.; Chen, Xuewen

1999-08-01

Classification of real-time x-ray images of randomly oriented touching pistachio nuts is discussed. The ultimate objective is the development of a subsystem for automated non-invasive detection of defective product items on a conveyor belt. We discuss the use of clustering and how it is vital to achieve useful classification. New clustering methods using class identify and new cluster classes are advanced and shown to be of use for this application. Radial basis function neural net classifiers are emphasized. We expect our results to be of use for other classifiers and applications.

Cluster structures influenced by interaction with a surface.

PubMed

Witt, Christopher; Dieterich, Johannes M; Hartke, Bernd

2018-05-30

Clusters on surfaces are vitally important for nanotechnological applications. Clearly, cluster-surface interactions heavily influence the preferred cluster structures, compared to clusters in vacuum. Nevertheless, systematic explorations and an in-depth understanding of these interactions and how they determine the cluster structures are still lacking. Here we present an extension of our well-established non-deterministic global optimization package OGOLEM from isolated clusters to clusters on surfaces. Applying this approach to intentionally simple Lennard-Jones test systems, we produce a first systematic exploration that relates changes in cluster-surface interactions to resulting changes in adsorbed cluster structures.

Voronoi distance based prospective space-time scans for point data sets: a dengue fever cluster analysis in a southeast Brazilian town

PubMed Central

2011-01-01

Background The Prospective Space-Time scan statistic (PST) is widely used for the evaluation of space-time clusters of point event data. Usually a window of cylindrical shape is employed, with a circular or elliptical base in the space domain. Recently, the concept of Minimum Spanning Tree (MST) was applied to specify the set of potential clusters, through the Density-Equalizing Euclidean MST (DEEMST) method, for the detection of arbitrarily shaped clusters. The original map is cartogram transformed, such that the control points are spread uniformly. That method is quite effective, but the cartogram construction is computationally expensive and complicated. Results A fast method for the detection and inference of point data set space-time disease clusters is presented, the Voronoi Based Scan (VBScan). A Voronoi diagram is built for points representing population individuals (cases and controls). The number of Voronoi cells boundaries intercepted by the line segment joining two cases points defines the Voronoi distance between those points. That distance is used to approximate the density of the heterogeneous population and build the Voronoi distance MST linking the cases. The successive removal of edges from the Voronoi distance MST generates sub-trees which are the potential space-time clusters. Finally, those clusters are evaluated through the scan statistic. Monte Carlo replications of the original data are used to evaluate the significance of the clusters. An application for dengue fever in a small Brazilian city is presented. Conclusions The ability to promptly detect space-time clusters of disease outbreaks, when the number of individuals is large, was shown to be feasible, due to the reduced computational load of VBScan. Instead of changing the map, VBScan modifies the metric used to define the distance between cases, without requiring the cartogram construction. Numerical simulations showed that VBScan has higher power of detection, sensitivity and positive predicted value than the Elliptic PST. Furthermore, as VBScan also incorporates topological information from the point neighborhood structure, in addition to the usual geometric information, it is more robust than purely geometric methods such as the elliptic scan. Those advantages were illustrated in a real setting for dengue fever space-time clusters. PMID:21513556

Unsupervised classification of multivariate geostatistical data: Two algorithms

NASA Astrophysics Data System (ADS)

Romary, Thomas; Ors, Fabien; Rivoirard, Jacques; Deraisme, Jacques

2015-12-01

With the increasing development of remote sensing platforms and the evolution of sampling facilities in mining and oil industry, spatial datasets are becoming increasingly large, inform a growing number of variables and cover wider and wider areas. Therefore, it is often necessary to split the domain of study to account for radically different behaviors of the natural phenomenon over the domain and to simplify the subsequent modeling step. The definition of these areas can be seen as a problem of unsupervised classification, or clustering, where we try to divide the domain into homogeneous domains with respect to the values taken by the variables in hand. The application of classical clustering methods, designed for independent observations, does not ensure the spatial coherence of the resulting classes. Image segmentation methods, based on e.g. Markov random fields, are not adapted to irregularly sampled data. Other existing approaches, based on mixtures of Gaussian random functions estimated via the expectation-maximization algorithm, are limited to reasonable sample sizes and a small number of variables. In this work, we propose two algorithms based on adaptations of classical algorithms to multivariate geostatistical data. Both algorithms are model free and can handle large volumes of multivariate, irregularly spaced data. The first one proceeds by agglomerative hierarchical clustering. The spatial coherence is ensured by a proximity condition imposed for two clusters to merge. This proximity condition relies on a graph organizing the data in the coordinates space. The hierarchical algorithm can then be seen as a graph-partitioning algorithm. Following this interpretation, a spatial version of the spectral clustering algorithm is also proposed. The performances of both algorithms are assessed on toy examples and a mining dataset.

Hierarchically clustered adaptive quantization CMAC and its learning convergence.

PubMed

Teddy, S D; Lai, E M K; Quek, C

2007-11-01

The cerebellar model articulation controller (CMAC) neural network (NN) is a well-established computational model of the human cerebellum. Nevertheless, there are two major drawbacks associated with the uniform quantization scheme of the CMAC network. They are the following: (1) a constant output resolution associated with the entire input space and (2) the generalization-accuracy dilemma. Moreover, the size of the CMAC network is an exponential function of the number of inputs. Depending on the characteristics of the training data, only a small percentage of the entire set of CMAC memory cells is utilized. Therefore, the efficient utilization of the CMAC memory is a crucial issue. One approach is to quantize the input space nonuniformly. For existing nonuniformly quantized CMAC systems, there is a tradeoff between memory efficiency and computational complexity. Inspired by the underlying organizational mechanism of the human brain, this paper presents a novel CMAC architecture named hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC). HCAQ-CMAC employs hierarchical clustering for the nonuniform quantization of the input space to identify significant input segments and subsequently allocating more memory cells to these regions. The stability of the HCAQ-CMAC network is theoretically guaranteed by the proof of its learning convergence. The performance of the proposed network is subsequently benchmarked against the original CMAC network, as well as two other existing CMAC variants on two real-life applications, namely, automated control of car maneuver and modeling of the human blood glucose dynamics. The experimental results have demonstrated that the HCAQ-CMAC network offers an efficient memory allocation scheme and improves the generalization and accuracy of the network output to achieve better or comparable performances with smaller memory usages. Index Terms-Cerebellar model articulation controller (CMAC), hierarchical clustering, hierarchically clustered adaptive quantization CMAC (HCAQ-CMAC), learning convergence, nonuniform quantization.

Aryl-Aryl Interactions in Designed Peptide Folds: Spectroscopic Characteristics and Placement Issues for Optimal Structure Stabilization

PubMed Central

Anderson, Jordan M.; Kier, Brandon; Jurban, Brice; Byrne, Aimee; Shu, Irene; Eidenschink, Lisa A.; Shcherbakov, Alexander A.; Hudson, Mike; Fesinmeyer, R. M.; Andersen, Niels H.

2017-01-01

We have extended our studies of Trp/Trp to other Aryl/Aryl through-space interactions that stabilize hairpins and other small polypeptide folds. Herein we detail the NMR and CD spectroscopic features of these types of interactions. NMR data remains the best diagnostic for characterizing the common T-shape orientation. Designated as an edge-to-face (EtF or FtE) interaction, large ring current shifts are produced at the edge aryl ring hydrogens and, in most cases, large exciton couplets appear in the far UV circular dichroic (CD) spectrum. The preference for the face aryl in FtE clusters is W≫Y≥F (there are some exceptions in the Y/F order); this sequence corresponds to the order of fold stability enhancement and always predicts the amplitude of the lower energy feature of the exciton couplet in the CD spectrum. The CD spectra for FtE W/W, W/Y, Y/W, and Y/Y pairs all include an intense feature at 225–232 nm. An additional couplet feature seen for W/Y, W/F, Y/Y and F/Y clusters, is a negative feature at 197–200 nm. Tyr/Tyr (as well as F/Y and F/F) interactions produce much smaller exciton couplet amplitudes. The Trp-cage fold was employed to search for the CD effects of other Trp/Trp and Trp/Tyr cluster geometries: several were identified. In this account, we provide additional examples of the application of cross-strand aryl/aryl clusters for the design of stable β-sheet models and a scale of fold stability increments associated with all possible FtE Ar/Ar clusters in several structural contexts. PMID:26850220

Multiscale Computer Simulation of Tensile and Compressive Strain in Polymer- Coated Silica Aerogels

NASA Technical Reports Server (NTRS)

Good, Brian

2009-01-01

While the low thermal conductivities of silica aerogels have made them of interest to the aerospace community as lightweight thermal insulation, the application of conformal polymer coatings to these gels increases their strength significantly, making them potentially useful as structural materials as well. In this work we perform multiscale computer simulations to investigate the tensile and compressive strain behavior of silica and polymer-coated silica aerogels. Aerogels are made up of clusters of interconnected particles of amorphous silica of less than bulk density. We simulate gel nanostructure using a Diffusion Limited Cluster Aggregation (DLCA) procedure, which produces aggregates that exhibit fractal dimensions similar to those observed in real aerogels. We have previously found that model gels obtained via DLCA exhibited stress-strain curves characteristic of the experimentally observed brittle failure. However, the strain energetics near the expected point of failure were not consistent with such failure. This shortcoming may be due to the fact that the DLCA process produces model gels that are lacking in closed-loop substructures, compared with real gels. Our model gels therefore contain an excess of dangling strands, which tend to unravel under tensile strain, producing non-brittle failure. To address this problem, we have incorporated a modification to the DLCA algorithm that specifically produces closed loops in the model gels. We obtain the strain energetics of interparticle connections via atomistic molecular statics, and abstract the collective energy of the atomic bonds into a Morse potential scaled to describe gel particle interactions. Polymer coatings are similarly described. We apply repeated small uniaxial strains to DLCA clusters, and allow relaxation of the center eighty percent of the cluster between strains. The simulations produce energetics and stress-strain curves for looped and nonlooped clusters, for a variety of densities and interaction parameters.

Clustering effects in ionic polymers: Molecular dynamics simulations

DOE PAGES

Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.

2015-08-18

Ionic clusters control the structure, dynamics, and transport in soft matter. Incorporating a small fraction of ionizable groups in polymers substantially reduces the mobility of the macromolecules in melts. Furthermore, these ionic groups often associate into random clusters in melts, where the distribution and morphology of the clusters impact the transport in these materials. Here, using molecular dynamic simulations we demonstrate a clear correlation between cluster size and morphology with the polymer mobility in melts of sulfonated polystyrene. We show that in low dielectric media ladderlike clusters that are lower in energy compared with spherical assemblies are formed. Reducing themore » electrostatic interactions by enhancing the dielectric constant leads to morphological transformation from ladderlike clusters to globular assemblies. Finally, decrease in electrostatic interaction significantly enhances the mobility of the polymer.« less

Evaluation of Potential Locations for Siting Small Modular Reactors near Federal Energy Clusters to Support Federal Clean Energy Goals

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

Belles, Randy J.; Omitaomu, Olufemi A.

2014-09-01

Geographic information systems (GIS) technology was applied to analyze federal energy demand across the contiguous US. Several federal energy clusters were previously identified, including Hampton Roads, Virginia, which was subsequently studied in detail. This study provides an analysis of three additional diverse federal energy clusters. The analysis shows that there are potential sites in various federal energy clusters that could be evaluated further for placement of an integral pressurized-water reactor (iPWR) to support meeting federal clean energy goals.

Co-existence of monomers and clusters in concentrated protein solutions

NASA Astrophysics Data System (ADS)

Chinchalikar, Akshay J.; Kumar, Sugam; Aswal, V. K.; Callow, P.; Wagh, A. G.

2012-06-01

Small-angle neutron scattering (SANS) measurements have been performed on concentrated protein solutions in order to study aggregation of lysozyme molecules at different pH. The variation of correlation peak in concentration (C) dependent SANS data shows deviation from C1/3 behavior suggesting the aggregation phenomena in these systems. The aggregates or clusters coexist along with monomers with cluster fraction proportional to protein concentration. The clustering is also favored at higher pH approaching isoelectric point (pI) because of decrease in charge on the protein molecule.

Properties of small Ar sub N-1 K/+/ ionic clusters

NASA Technical Reports Server (NTRS)

Etters, R. D.; Danilowicz, R.; Dugan, J.

1977-01-01

A self-consistent formalism is developed that, based upon a many-body potential, dynamically determines the thermodynamic properties of ionic clusters without an a priori designation of the equilibrium structures. Aggregates consisting of a single closed shell K(+) ion and N-1 isoelectronic argon atoms were studied. The clusters form crystallites at low temperatures, and melting transitions and spontaneous dissociations are indicated. The results confirm experimental evidence that shows that ionic clusters become less stable with increasing N. The crystallite structures formed by four different clusters are isosceles triangle, skewed form, octahedron with ion in the middle, and icosahedron with the ion in the middle.