PRISM 3: expanded prediction of natural product chemical structures from microbial genomes.

PubMed

Skinnider, Michael A; Merwin, Nishanth J; Johnston, Chad W; Magarvey, Nathan A

2017-07-03

Microbial natural products represent a rich resource of pharmaceutically and industrially important compounds. Genome sequencing has revealed that the majority of natural products remain undiscovered, and computational methods to connect biosynthetic gene clusters to their corresponding natural products therefore have the potential to revitalize natural product discovery. Previously, we described PRediction Informatics for Secondary Metabolomes (PRISM), a combinatorial approach to chemical structure prediction for genetically encoded nonribosomal peptides and type I and II polyketides. Here, we present a ground-up rewrite of the PRISM structure prediction algorithm to derive prediction of natural products arising from non-modular biosynthetic paradigms. Within this new version, PRISM 3, natural product scaffolds are modeled as chemical graphs, permitting structure prediction for aminocoumarins, antimetabolites, bisindoles and phosphonate natural products, and building upon the addition of ribosomally synthesized and post-translationally modified peptides. Further, with the addition of cluster detection for 11 new cluster types, PRISM 3 expands to detect 22 distinct natural product cluster types. Other major modifications to PRISM include improved sequence input and ORF detection, user-friendliness and output. Distribution of PRISM 3 over a 300-core server grid improves the speed and capacity of the web application. PRISM 3 is available at http://magarveylab.ca/prism/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Length-independent structural similarities enrich the antibody CDR canonical class model.

PubMed

Nowak, Jaroslaw; Baker, Terry; Georges, Guy; Kelm, Sebastian; Klostermann, Stefan; Shi, Jiye; Sridharan, Sudharsan; Deane, Charlotte M

2016-01-01

Complementarity-determining regions (CDRs) are antibody loops that make up the antigen binding site. Here, we show that all CDR types have structurally similar loops of different lengths. Based on these findings, we created length-independent canonical classes for the non-H3 CDRs. Our length variable structural clusters show strong sequence patterns suggesting either that they evolved from the same original structure or result from some form of convergence. We find that our length-independent method not only clusters a larger number of CDRs, but also predicts canonical class from sequence better than the standard length-dependent approach. To demonstrate the usefulness of our findings, we predicted cluster membership of CDR-L3 sequences from 3 next-generation sequencing datasets of the antibody repertoire (over 1,000,000 sequences). Using the length-independent clusters, we can structurally classify an additional 135,000 sequences, which represents a ∼20% improvement over the standard approach. This suggests that our length-independent canonical classes might be a highly prevalent feature of antibody space, and could substantially improve our ability to accurately predict the structure of novel CDRs identified by next-generation sequencing.

Structure, stability, and properties of the trans peroxo nitrate radical: the importance of nondynamic correlation.

PubMed

Dutta, Achintya Kumar; Dar, Manzoor; Vaval, Nayana; Pal, Sourav

2014-02-27

We report a comparative single-reference and multireference coupled-cluster investigation on the structure, potential energy surface, and IR spectroscopic properties of the trans peroxo nitrate radical, one of the key intermediates in stratospheric NOX chemistry. The previous single-reference ab initio studies predicted an unbound structure for the trans peroxo nitrate radical. However, our Fock space multireference coupled-cluster calculation confirms a bound structure for the trans peroxo nitrate radical, in accordance with the experimental results reported earlier. Further, the analysis of the potential energy surface in FSMRCC method indicates a well-behaved minima, contrary to the shallow minima predicted by the single-reference coupled-cluster method. The harmonic force field analysis, of various possible isomers of peroxo nitrate also reveals that only the trans structure leads to the experimentally observed IR peak at 1840 cm(-1). The present study highlights the critical importance of nondynamic correlation in predicting the structure and properties of high-energy stratospheric NOx radicals.

Structures of undecagold clusters: Ligand effect

NASA Astrophysics Data System (ADS)

Spivey, Kasi; Williams, Joseph I.; Wang, Lichang

2006-12-01

The most stable structure of undecagold, or Au 11, clusters was predicted from our DFT calculations to be planar [L. Xiao, L. Wang, Chem. Phys. Lett. 392 (2004) 452; L. Xiao, B. Tollberg, X. Hu, L. Wang, J. Chem. Phys. 124 (2005) 114309.]. The structures of ligand protected undecagold clusters were shown to be three-dimensional experimentally. In this work, we used DFT calculations to study the ligand effect on the structures of Au 11 clusters. Our results show that the most stable structure of Au 11 is in fact three-dimensional when SCH 3 ligands are attached. This indicates that the structures of small gold clusters are altered substantially in the presence of ligands.

Large-scale model quality assessment for improving protein tertiary structure prediction.

PubMed

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-06-15

Sampling structural models and ranking them are the two major challenges of protein structure prediction. Traditional protein structure prediction methods generally use one or a few quality assessment (QA) methods to select the best-predicted models, which cannot consistently select relatively better models and rank a large number of models well. Here, we develop a novel large-scale model QA method in conjunction with model clustering to rank and select protein structural models. It unprecedentedly applied 14 model QA methods to generate consensus model rankings, followed by model refinement based on model combination (i.e. averaging). Our experiment demonstrates that the large-scale model QA approach is more consistent and robust in selecting models of better quality than any individual QA method. Our method was blindly tested during the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM group. It was officially ranked third out of all 143 human and server predictors according to the total scores of the first models predicted for 78 CASP11 protein domains and second according to the total scores of the best of the five models predicted for these domains. MULTICOM's outstanding performance in the extremely competitive 2014 CASP11 experiment proves that our large-scale QA approach together with model clustering is a promising solution to one of the two major problems in protein structure modeling. The web server is available at: http://sysbio.rnet.missouri.edu/multicom_cluster/human/. © The Author 2015. Published by Oxford University Press.

A grand unified model for liganded gold clusters

NASA Astrophysics Data System (ADS)

Xu, Wen Wu; Zhu, Beien; Zeng, Xiao Cheng; Gao, Yi

2016-12-01

A grand unified model (GUM) is developed to achieve fundamental understanding of rich structures of all 71 liganded gold clusters reported to date. Inspired by the quark model by which composite particles (for example, protons and neutrons) are formed by combining three quarks (or flavours), here gold atoms are assigned three `flavours' (namely, bottom, middle and top) to represent three possible valence states. The `composite particles' in GUM are categorized into two groups: variants of triangular elementary block Au3(2e) and tetrahedral elementary block Au4(2e), all satisfying the duet rule (2e) of the valence shell, akin to the octet rule in general chemistry. The elementary blocks, when packed together, form the cores of liganded gold clusters. With the GUM, structures of 71 liganded gold clusters and their growth mechanism can be deciphered altogether. Although GUM is a predictive heuristic and may not be necessarily reflective of the actual electronic structure, several highly stable liganded gold clusters are predicted, thereby offering GUM-guided synthesis of liganded gold clusters by design.

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

From the Superatom Model to a Diverse Array of Super-Elements: A Systematic Study of Dopant Influence on the Electronic Structure of Thiolate-Protected Gold Clusters.

PubMed

Schacht, Julia; Gaston, Nicola

2016-10-18

The electronic properties of doped thiolate-protected gold clusters are often referred to as tunable, but their study to date, conducted at different levels of theory, does not allow a systematic evaluation of this claim. Here, using density functional theory, the applicability of the superatomic model to these clusters is critically evaluated, and related to the degree of structural distortion and electronic inhomogeneity in the differently doped clusters, with dopant atoms Pd, Pt, Cu, and Ag. The effect of electron number is systematically evaluated by varying the charge on the overall cluster, and the nominal number of delocalized electrons, employed in the superatomic model, is compared to the numbers obtained from Bader analysis of individual atomic charges. We find that the superatomic model is highly applicable to all of these clusters, and is able to predict and explain the changing electronic structure as a function of charge. However, significant perturbations of the model arise due to doping, due to distortions of the core structure of the Au 13 [RS(AuSR) 2 ] 6 - cluster. In addition, analysis of the electronic structure indicates that the superatomic character is distributed further across the ligand shell in the case of the doped clusters, which may have implications for the self-assembly of these clusters into materials. The prediction of appropriate clusters for such superatomic solids relies critically on such quantitative analysis of the tunability of the electronic structure. © 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fe-Cluster Compounds of Chalcogenides: Candidates for Rare-Earth-Free Permanent Magnet and Magnetic Nodal-Line Topological Material.

PubMed

Zhao, Xin; Wang, Cai-Zhuang; Kim, Minsung; Ho, Kai-Ming

2017-12-04

Fe-cluster-based crystal structures are predicted for chalcogenides Fe 3 X 4 (X = S, Se, Te) using an adaptive genetic algorithm. Topologically different from the well-studied layered structures of iron chalcogenides, the newly predicted structures consist of Fe clusters that are either separated by the chalcogen atoms or connected via sharing of the vertex Fe atoms. Using first-principles calculations, we demonstrate that these structures have competitive or even lower formation energies than the experimentally synthesized Fe 3 X 4 compounds and exhibit interesting magnetic and electronic properties. In particular, we show that Fe 3 Te 4 can be a good candidate as a rare-earth-free permanent magnet and Fe 3 S 4 can be a magnetic nodal-line topological material.

Link prediction with node clustering coefficient

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Wang, Jing; Gregory, Steve

2016-06-01

Predicting missing links in incomplete complex networks efficiently and accurately is still a challenging problem. The recently proposed Cannistrai-Alanis-Ravai (CAR) index shows the power of local link/triangle information in improving link-prediction accuracy. Inspired by the idea of employing local link/triangle information, we propose a new similarity index with more local structure information. In our method, local link/triangle structure information can be conveyed by clustering coefficient of common-neighbors directly. The reason why clustering coefficient has good effectiveness in estimating the contribution of a common-neighbor is that it employs links existing between neighbors of a common-neighbor and these links have the same structural position with the candidate link to this common-neighbor. In our experiments, three estimators: precision, AUP and AUC are used to evaluate the accuracy of link prediction algorithms. Experimental results on ten tested networks drawn from various fields show that our new index is more effective in predicting missing links than CAR index, especially for networks with low correlation between number of common-neighbors and number of links between common-neighbors.

New Convex and Spherical Structures of Bare Boron Clusters

NASA Astrophysics Data System (ADS)

Boustani, Ihsan

1997-10-01

New stable structures of bare boron clusters can easily be obtained and constructed with the help of an "Aufbau Principle" suggested by a systematicab initioHF-SCF and direct CI study. It is concluded that boron cluster formation can be established by elemental units of pentagonal and hexagonal pyramids. New convex and small spherical clusters different from the classical known forms of boron crystal structures are obtained by a combination of both basic units. Convex structures simulate boron surfaces which can be considered as segments of open or closed spheres. Both convex clusters B16and B46have energies close to those of their conjugate quasi-planar clusters, which are relatively stable and can be considered to act as a calibration mark. The closed spherical clusters B12, B22, B32, and B42are less stable than the corresponding conjugated quasi-planar structures. As a consequence, highly stable spherical boron clusters can systematically be predicted when their conjugate quasi-planar clusters are determined and energies are compared.

Endohedral beryllium atoms in germanium clusters with eight and fewer vertices: how small can a cluster be and still encapsulate a central atom?

PubMed

Uţă, M M; King, R B

2012-05-31

Structures of the beryllium-centered germanium clusters Be@Ge(n)(z) (n = 8, 7, 6; z = -4, -2, 0, +2) have been investigated by density functional theory to provide some insight regarding the smallest metal cluster that can encapsulate an interstitial atom. The lowest energy structures of the eight-vertex Be@Ge(8)(z) clusters (z = -4, -2, 0, +2) all have the Be atom at the center of a closed polyhedron, namely, a D(4d) square antiprism for Be@Ge(8)(4-), a D(2d) bisdisphenoid for Be@Ge(8)(2-), an ideal O(h) cube for Be@Ge(8), and a C(2v) distorted cube for Be@Ge(8)(2+). The Be-centered cubic structures predicted for Be@Ge(8) and Be@Ge(8)(2+) differ from the previously predicted lowest energy structures for the isoelectronic Ge(8)(2-) and Ge(8). This appears to be related to the larger internal volume of the cube relative to other closed eight-vertex polyhedra. The lowest energy structures for the smaller seven- and six-vertex clusters Be@Ge(n)(z) (n = 7, 6; z = -4, -2, 0, +2) no longer have the Be atom at the center of a closed Ge(n) polyhedron. Instead, either the Ge(n) polyhedron has opened up to provide a larger volume for the Be atom or the Be atom has migrated to the surface of the polyhedron. However, higher energy structures are found in which the Be atom is located at the center of a Ge(n) (n = 7, 6) polyhedron. Examples of such structures are a centered C(2v) capped trigonal prismatic structure for Be@Ge(7)(2-), a centered D(5h) pentagonal bipyramidal structure for Be@Ge(7), a centered D(3h) trigonal prismatic structure for Be@Ge(6)(4-), and a centered octahedral structure for Be@Ge(6). Cluster buildup reactions of the type Be@Ge(n)(z) + Ge(2) → Be@Ge(n+2)(z) (n = 6, 8; z = -4, -2, 0, +2) are all predicted to be highly exothermic. This suggests that interstitial clusters having an endohedral atom inside a bare post transition element polyhedron with eight or fewer vertices are less than the optimum size. This is consistent with the experimental observation of several types of 10-vertex polyhedral bare post transition element clusters with interstitial atoms but the failure to observe such clusters with external polyhedra having eight or fewer vertices.

The stabilities and electron structures of Al-Mg clusters with 18 and 20 valence electrons

NASA Astrophysics Data System (ADS)

Yang, Huihui; Chen, Hongshan

2017-07-01

The spherical jellium model predicts that metal clusters having 18 and 20 valence electrons correspond to the magic numbers and will show specific stabilities. We explore in detail the geometric structures, stabilities and electronic structures of Al-Mg clusters containing 18 and 20 valence electrons by using genetic algorithm combined with density functional theories. The stabilities of the clusters are governed by the electronic configurations and Mg/Al ratios. The clusters with lower Mg/Al ratios are more stable. The molecular orbitals accord with the shell structures predicted by the jellium model but the 2S level interweaves with the 1D levels and the 2S and 1D orbitals form a subgroup. The clusters having 20 valence electrons form closed 1S21P61D102S2 shells and show enhanced stability. The Al-Mg clusters with a valence electron count of 18 do not form closed shells because one 1D orbital is unoccupied. The ionization potential and electron affinity are closely related to the electronic configurations; their values are determined by the subgroups the HOMO or LUMO belong to. Supplementary material in the form of one pdf file available from the Journal web page at http://https://doi.org/10.1140/epjd/e2017-80042-9

RaptorX-Angle: real-value prediction of protein backbone dihedral angles through a hybrid method of clustering and deep learning.

PubMed

Gao, Yujuan; Wang, Sheng; Deng, Minghua; Xu, Jinbo

2018-05-08

Protein dihedral angles provide a detailed description of protein local conformation. Predicted dihedral angles can be used to narrow down the conformational space of the whole polypeptide chain significantly, thus aiding protein tertiary structure prediction. However, direct angle prediction from sequence alone is challenging. In this article, we present a novel method (named RaptorX-Angle) to predict real-valued angles by combining clustering and deep learning. Tested on a subset of PDB25 and the targets in the latest two Critical Assessment of protein Structure Prediction (CASP), our method outperforms the existing state-of-art method SPIDER2 in terms of Pearson Correlation Coefficient (PCC) and Mean Absolute Error (MAE). Our result also shows approximately linear relationship between the real prediction errors and our estimated bounds. That is, the real prediction error can be well approximated by our estimated bounds. Our study provides an alternative and more accurate prediction of dihedral angles, which may facilitate protein structure prediction and functional study.

A grand unified model for liganded gold clusters

PubMed Central

Xu, Wen Wu; Zhu, Beien; Zeng, Xiao Cheng; Gao, Yi

2016-01-01

A grand unified model (GUM) is developed to achieve fundamental understanding of rich structures of all 71 liganded gold clusters reported to date. Inspired by the quark model by which composite particles (for example, protons and neutrons) are formed by combining three quarks (or flavours), here gold atoms are assigned three ‘flavours' (namely, bottom, middle and top) to represent three possible valence states. The ‘composite particles' in GUM are categorized into two groups: variants of triangular elementary block Au3(2e) and tetrahedral elementary block Au4(2e), all satisfying the duet rule (2e) of the valence shell, akin to the octet rule in general chemistry. The elementary blocks, when packed together, form the cores of liganded gold clusters. With the GUM, structures of 71 liganded gold clusters and their growth mechanism can be deciphered altogether. Although GUM is a predictive heuristic and may not be necessarily reflective of the actual electronic structure, several highly stable liganded gold clusters are predicted, thereby offering GUM-guided synthesis of liganded gold clusters by design. PMID:27910848

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment

PubMed Central

2014-01-01

Background Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. Results MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Conclusions Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy. PMID:24731387

Designing and evaluating the MULTICOM protein local and global model quality prediction methods in the CASP10 experiment.

PubMed

Cao, Renzhi; Wang, Zheng; Cheng, Jianlin

2014-04-15

Protein model quality assessment is an essential component of generating and using protein structural models. During the Tenth Critical Assessment of Techniques for Protein Structure Prediction (CASP10), we developed and tested four automated methods (MULTICOM-REFINE, MULTICOM-CLUSTER, MULTICOM-NOVEL, and MULTICOM-CONSTRUCT) that predicted both local and global quality of protein structural models. MULTICOM-REFINE was a clustering approach that used the average pairwise structural similarity between models to measure the global quality and the average Euclidean distance between a model and several top ranked models to measure the local quality. MULTICOM-CLUSTER and MULTICOM-NOVEL were two new support vector machine-based methods of predicting both the local and global quality of a single protein model. MULTICOM-CONSTRUCT was a new weighted pairwise model comparison (clustering) method that used the weighted average similarity between models in a pool to measure the global model quality. Our experiments showed that the pairwise model assessment methods worked better when a large portion of models in the pool were of good quality, whereas single-model quality assessment methods performed better on some hard targets when only a small portion of models in the pool were of reasonable quality. Since digging out a few good models from a large pool of low-quality models is a major challenge in protein structure prediction, single model quality assessment methods appear to be poised to make important contributions to protein structure modeling. The other interesting finding was that single-model quality assessment scores could be used to weight the models by the consensus pairwise model comparison method to improve its accuracy.

Fe-Cluster Compounds of Chalcogenides: Candidates for Rare-Earth-Free Permanent Magnet and Magnetic Nodal-Line Topological Material

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

Zhao, Xin; Wang, Cai-Zhuang; Kim, Minsung

Here, Fe-cluster-based crystal structures are predicted for chalcogenides Fe 3X 4 (X = S, Se, Te) using an adaptive genetic algorithm. Topologically different from the well-studied layered structures of iron chalcogenides, the newly predicted structures consist of Fe clusters that are either separated by the chalcogen atoms or connected via sharing of the vertex Fe atoms. Additionally, using first-principles calculations, we demonstrate that these structures have competitive or even lower formation energies than the experimentally synthesized Fe 3X 4 compounds and exhibit interesting magnetic and electronic properties. In particular, we show that Fe 3X 4 can be a good candidatemore » as a rare-earth-free permanent magnet and Fe 3X 4 can be a magnetic nodal-line topological material.« less

Fe-Cluster Compounds of Chalcogenides: Candidates for Rare-Earth-Free Permanent Magnet and Magnetic Nodal-Line Topological Material

DOE PAGES

Zhao, Xin; Wang, Cai-Zhuang; Kim, Minsung; ...

2017-11-13

Here, Fe-cluster-based crystal structures are predicted for chalcogenides Fe 3X 4 (X = S, Se, Te) using an adaptive genetic algorithm. Topologically different from the well-studied layered structures of iron chalcogenides, the newly predicted structures consist of Fe clusters that are either separated by the chalcogen atoms or connected via sharing of the vertex Fe atoms. Additionally, using first-principles calculations, we demonstrate that these structures have competitive or even lower formation energies than the experimentally synthesized Fe 3X 4 compounds and exhibit interesting magnetic and electronic properties. In particular, we show that Fe 3X 4 can be a good candidatemore » as a rare-earth-free permanent magnet and Fe 3X 4 can be a magnetic nodal-line topological material.« less

Predicting the random drift of MEMS gyroscope based on K-means clustering and OLS RBF Neural Network

NASA Astrophysics Data System (ADS)

Wang, Zhen-yu; Zhang, Li-jie

2017-10-01

Measure error of the sensor can be effectively compensated with prediction. Aiming at large random drift error of MEMS(Micro Electro Mechanical System))gyroscope, an improved learning algorithm of Radial Basis Function(RBF) Neural Network(NN) based on K-means clustering and Orthogonal Least-Squares (OLS) is proposed in this paper. The algorithm selects the typical samples as the initial cluster centers of RBF NN firstly, candidates centers with K-means algorithm secondly, and optimizes the candidate centers with OLS algorithm thirdly, which makes the network structure simpler and makes the prediction performance better. Experimental results show that the proposed K-means clustering OLS learning algorithm can predict the random drift of MEMS gyroscope effectively, the prediction error of which is 9.8019e-007°/s and the prediction time of which is 2.4169e-006s

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 the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

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

Bibby, Jaclyn; Keegan, Ronan M.; Mayans, Olga

2013-11-01

Processing of NMR structures for molecular replacement by AMPLE works well. AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

A complete, multi-level conformational clustering of antibody complementarity-determining regions

PubMed Central

Nikoloudis, Dimitris; Pitts, Jim E.

2014-01-01

Classification of antibody complementarity-determining region (CDR) conformations is an important step that drives antibody modelling and engineering, prediction from sequence, directed mutagenesis and induced-fit studies, and allows inferences on sequence-to-structure relations. Most of the previous work performed conformational clustering on a reduced set of structures or after application of various structure pre-filtering criteria. In this study, it was judged that a clustering of every available CDR conformation would produce a complete and redundant repertoire, increase the number of sequence examples and allow better decisions on structure validity in the future. In order to cope with the potential increase in data noise, a first-level statistical clustering was performed using structure superposition Root-Mean-Square Deviation (RMSD) as a distance-criterion, coupled with second- and third-level clustering that employed Ramachandran regions for a deeper qualitative classification. The classification of a total of 12,712 CDR conformations is thus presented, along with rich annotation and cluster descriptions, and the results are compared to previous major studies. The present repertoire has procured an improved image of our current CDR Knowledge-Base, with a novel nesting of conformational sensitivity and specificity that can serve as a systematic framework for improved prediction from sequence as well as a number of future studies that would aid in knowledge-based antibody engineering such as humanisation. PMID:25071986

OSO-8 X-ray spectra of clusters of galaxies. 2: Discussion. [hot intracluster gas structures

NASA Technical Reports Server (NTRS)

Smith, B. W.; Mushotzky, R. F.; Serlemitsos, P. J.

1978-01-01

X-ray spectral parameters obtained from 2 to 20 keV OSO-8 data on X-ray clusters and optical cluster properties were examined to obtain information for restricting models for hot intracluster gas structures. Topics discussed include the radius of the X-ray core in relation to the galaxy core radius, the viral mass of hotter clusters, and galaxy density and optical central cluster properties. A population of cool, dim X-ray clusters which have not been observed is predicted. The iron abundance determinations recently quoted for intracluster gas are uncertain by 50 to greater than 100 percent from this nonstatistical cause alone.

System-wide analysis of the transcriptional network of human myelomonocytic leukemia cells predicts attractor structure and phorbol-ester-induced differentiation and dedifferentiation transitions

NASA Astrophysics Data System (ADS)

Sakata, Katsumi; Ohyanagi, Hajime; Sato, Shinji; Nobori, Hiroya; Hayashi, Akiko; Ishii, Hideshi; Daub, Carsten O.; Kawai, Jun; Suzuki, Harukazu; Saito, Toshiyuki

2015-02-01

We present a system-wide transcriptional network structure that controls cell types in the context of expression pattern transitions that correspond to cell type transitions. Co-expression based analyses uncovered a system-wide, ladder-like transcription factor cluster structure composed of nearly 1,600 transcription factors in a human transcriptional network. Computer simulations based on a transcriptional regulatory model deduced from the system-wide, ladder-like transcription factor cluster structure reproduced expression pattern transitions when human THP-1 myelomonocytic leukaemia cells cease proliferation and differentiate under phorbol myristate acetate stimulation. The behaviour of MYC, a reprogramming Yamanaka factor that was suggested to be essential for induced pluripotent stem cells during dedifferentiation, could be interpreted based on the transcriptional regulation predicted by the system-wide, ladder-like transcription factor cluster structure. This study introduces a novel system-wide structure to transcriptional networks that provides new insights into network topology.

Computational chemistry of modified [MFe3S4] and [M2Fe2S4] clusters: assessment of trends in electronic structure and properties.

PubMed

Jensen, Kasper P; Ooi, Bee-Lean; Christensen, Hans E M

2008-12-18

The aim of this work is to understand the molecular evolution of iron-sulfur clusters in terms of electronic structure and function. Metal-substituted models of biological [Fe(4)S(4)] clusters in oxidation states [M(x)Fe(4-x)S(4)](3+/2+/1+) have been studied by density functional theory (M = Cr, Mn, Fe, Co, Ni, Cu, Zn, and Pd, with x = 1 or 2). Most of these clusters have not been characterized before. For those that have been characterized experimentally, very good agreement is obtained, implying that also the predicted structures and properties of new clusters are accurate. Mean absolute errors are 0.024 A for bond lengths ([Fe(4)S(4)], [NiFe(3)S(4)], [CoFe(3)S(4)]) and 0.09 V for shifts in reduction potentials relative to the [Fe(4)S(4)] cluster. All structures form cuboidal geometries similar to the all-iron clusters, except the Pd-substituted clusters, which instead form highly distorted trigonal and tetragonal local sites in compromised, pseudocuboidal geometries. In contrast to other electron-transfer sites, cytochromes, blue copper proteins, and smaller iron-sulfur clusters, we find that the [Fe(4)S(4)] clusters are very insensitive to metal substitution, displaying quite small changes in reorganization energies and reduction potentials upon substitution. Thus, the [Fe(4)S(4)] clusters have an evolutionary advantage in being robust to pollution from other metals, still retaining function. We analyze in detail the electronic structure of individual clusters and rationalize spin couplings and redox activity. Often, several configurations are very close in energy, implying possible use as spin-crossover systems, and spin states are predicted accurately in all but one case ([CuFe(3)S(4)]). The results are anticipated to be helpful in defining new molecular systems with catalytic and magnetic properties.

An empirical potential for simulating vacancy clusters in tungsten.

PubMed

Mason, D R; Nguyen-Manh, D; Becquart, C S

2017-12-20

We present an empirical interatomic potential for tungsten, particularly well suited for simulations of vacancy-type defects. We compare energies and structures of vacancy clusters generated with the empirical potential with an extensive new database of values computed using density functional theory, and show that the new potential predicts low-energy defect structures and formation energies with high accuracy. A significant difference to other popular embedded-atom empirical potentials for tungsten is the correct prediction of surface energies. Interstitial properties and short-range pairwise behaviour remain similar to the Ackford-Thetford potential on which it is based, making this potential well-suited to simulations of microstructural evolution following irradiation damage cascades. Using atomistic kinetic Monte Carlo simulations, we predict vacancy cluster dissociation in the range 1100-1300 K, the temperature range generally associated with stage IV recovery.

Site-specific vibrational spectral signatures of water molecules in the magic H3O+(H2O)20 and Cs+(H2O)20 clusters

PubMed Central

Fournier, Joseph A.; Wolke, Conrad T.; Johnson, Christopher J.; Johnson, Mark A.; Heine, Nadja; Gewinner, Sandy; Schöllkopf, Wieland; Esser, Tim K.; Fagiani, Matias R.; Knorke, Harald; Asmis, Knut R.

2014-01-01

Theoretical models of proton hydration with tens of water molecules indicate that the excess proton is embedded on the surface of clathrate-like cage structures with one or two water molecules in the interior. The evidence for these structures has been indirect, however, because the experimental spectra in the critical H-bonding region of the OH stretching vibrations have been too diffuse to provide band patterns that distinguish between candidate structures predicted theoretically. Here we exploit the slow cooling afforded by cryogenic ion trapping, along with isotopic substitution, to quench water clusters attached to the H3O+ and Cs+ ions into structures that yield well-resolved vibrational bands over the entire 215- to 3,800-cm−1 range. The magic H3O+(H2O)20 cluster yields particularly clear spectral signatures that can, with the aid of ab initio predictions, be traced to specific classes of network sites in the predicted pentagonal dodecahedron H-bonded cage with the hydronium ion residing on the surface. PMID:25489068

Site-specific vibrational spectral signatures of water molecules in the magic H 3O +(H 2O) 20 and Cs +(H 2O) 20 clusters

DOE PAGES

Fournier, Joseph A.; Wolke, Conrad T.; Johnson, Christopher J.; ...

2014-12-08

Here, theoretical models of proton hydration with tens of water molecules indicate that the excess proton is embedded on the surface of clathrate-like cage structures with one or two water molecules in the interior. The evidence for these structures has been indirect, however, because the experimental spectra in the critical H-bonding region of the OH stretching vibrations have been too diffuse to provide band patterns that distinguish between candidate structures predicted theoretically. Here we exploit the slow cooling afforded by cryogenic ion trapping, along with isotopic substitution, to quench water clusters attached to the H 3O + and Cs +more » ions into structures that yield well-resolved vibrational bands over the entire 215- to 3,800-cm -1 range. The magic H 3O +(H 2O) 20 cluster yields particularly clear spectral signatures that can, with the aid of ab initio predictions, be traced to specific classes of network sites in the predicted pentagonal dodecahedron H-bonded cage with the hydronium ion residing on the surface.« less

CLUMP-3D: Testing ΛCDM with Galaxy Cluster Shapes

NASA Astrophysics Data System (ADS)

Sereno, Mauro; Umetsu, Keiichi; Ettori, Stefano; Sayers, Jack; Chiu, I.-Non; Meneghetti, Massimo; Vega-Ferrero, Jesús; Zitrin, Adi

2018-06-01

The ΛCDM model of structure formation makes strong predictions on the concentration and shape of dark matter (DM) halos, which are determined by mass accretion processes. Comparison between predicted shapes and observations provides a geometric test of the ΛCDM model. Accurate and precise measurements needs a full three-dimensional (3D) analysis of the cluster mass distribution. We accomplish this with a multi-probe 3D analysis of the X-ray regular Cluster Lensing and Supernova survey with Hubble (CLASH) clusters combining strong and weak lensing, X-ray photometry and spectroscopy, and the Sunyaev–Zel’dovich effect (SZe). The cluster shapes and concentrations are consistent with ΛCDM predictions. The CLASH clusters are randomly oriented, as expected given the sample selection criteria. Shapes agree with numerical results for DM-only halos, which hints at baryonic physics being less effective in making halos rounder.

Tests of Predictions of the Algebraic Cluster Model: the Triangular D 3h Symmetry of 12C

NASA Astrophysics Data System (ADS)

Gai, Moshe

2016-07-01

A new theoretical approach to clustering in the frame of the Algebraic Cluster Model (ACM) has been developed. It predicts rotation-vibration structure with rotational band of an oblate equilateral triangular symmetric spinning top with a D 3h symmetry characterized by the sequence of states: 0+, 2+, 3-, 4±, 5- with a degenerate 4+ and 4- (parity doublet) states. Our measured new 2+ 2 in 12C allows the first study of rotation-vibration structure in 12C. The newly measured 5- state and 4- states fit very well the predicted ground state rotational band structure with the predicted sequence of states: 0+, 2+, 3-, 4±, 5- with almost degenerate 4+ and 4- (parity doublet) states. Such a D 3h symmetry is characteristic of triatomic molecules, but it is observed in the ground state rotational band of 12C for the first time in a nucleus. We discuss predictions of the ACM of other rotation-vibration bands in 12 C such as the (0+) Hoyle band and the (1-) bending mode with prediction of (“missing 3- and 4-”) states that may shed new light on clustering in 12C and light nuclei. In particular, the observation (or non observation) of the predicted (“missing”) states in the Hoyle band will allow us to conclude the geometrical arrangement of the three alpha particles composing the Hoyle state at 7.6542 MeV in 12C. We discuss proposed research programs at the Darmstadt S-DALINAC and at the newly constructed ELI-NP facility near Bucharest to test the predictions of the ACM in isotopes of carbon.

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

SeMPI: a genome-based secondary metabolite prediction and identification web server.

PubMed

Zierep, Paul F; Padilla, Natàlia; Yonchev, Dimitar G; Telukunta, Kiran K; Klementz, Dennis; Günther, Stefan

2017-07-03

The secondary metabolism of bacteria, fungi and plants yields a vast number of bioactive substances. The constantly increasing amount of published genomic data provides the opportunity for an efficient identification of gene clusters by genome mining. Conversely, for many natural products with resolved structures, the encoding gene clusters have not been identified yet. Even though genome mining tools have become significantly more efficient in the identification of biosynthetic gene clusters, structural elucidation of the actual secondary metabolite is still challenging, especially due to as yet unpredictable post-modifications. Here, we introduce SeMPI, a web server providing a prediction and identification pipeline for natural products synthesized by polyketide synthases of type I modular. In order to limit the possible structures of PKS products and to include putative tailoring reactions, a structural comparison with annotated natural products was introduced. Furthermore, a benchmark was designed based on 40 gene clusters with annotated PKS products. The web server of the pipeline (SeMPI) is freely available at: http://www.pharmaceutical-bioinformatics.de/sempi. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Stabilization of Si_60 Cage Structure: The Agony and the Ecstasy

NASA Astrophysics Data System (ADS)

Kawazoe, Y.; Sun, Q.; Wang, Q.; Rao, B. K.; Jena, P.

2003-03-01

The unique role of silicon in the micro-electronics industry has motivated many researchers to find ways to stabilize Si_60 with fullerene structure. In spite of numerous experimental attempts, synthesis of a theoretically predicted C_60-supported Si_60 cluster (C_60@Si_60) has not been possible. Using a state-of-the-art theoretical method, we provide the first answer for this long-standing contradiction between the experimental observation and the theoretical prediction. The flaws in earlier theoretical works are pointed out, and Si_60 is shown to be unstable in the fullerene structure either on its own or when supported on a C_60 fullerene (C_60@Si_60). On the other hand, we show that Si_60 cage can be stabilized by using magic clusters such as Al_12X (X = Si, Ge, Sn, Pb) as endohedral units, which have been identified in recent experiment as stable clusters and as suitable building blocks for cluster-assembled materials.

Clusters of Behaviors and Beliefs Predicting Adolescent Depression: Implications for Prevention

PubMed Central

Paunesku, David; Ellis, Justin; Fogel, Joshua; Kuwabara, Sachiko A; Gollan, Jackie; Gladstone, Tracy; Reinecke, Mark; Van Voorhees, Benjamin W.

2009-01-01

OBJECTIVE Risk factors for various disorders are known to cluster. However, the factor structure for behaviors and beliefs predicting depressive disorder in adolescents is not known. Knowledge of this structure can facilitate prevention planning. METHODS We used the National Longitudinal Study of Adolescent Health (AddHealth) data set to conduct an exploratory factor analysis to identify clusters of behaviors/experiences predicting the onset of major depressive disorder (MDD) at 1-year follow-up (N=4,791). RESULTS Four factors were identified: family/interpersonal relations, self-emancipation, avoidant problem solving/low self-worth, and religious activity. Strong family/interpersonal relations were the most significantly protective against depression at one year follow-up. Avoidant problem solving/low self-worth was not predictive of MDD on its own, but significantly amplified the risks associated with delinquency. CONCLUSION Depression prevention interventions should consider giving family relationships a more central role in their efforts. Programs teaching problem solving skills may be most appropriate for reducing MDD risk in delinquent youth. PMID:20502621

STRUCTURAL PARAMETERS FOR 10 HALO GLOBULAR CLUSTERS IN M33

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

Ma, Jun, E-mail: majun@nao.cas.cn

2015-05-15

In this paper, we present the properties of 10 halo globular clusters (GCs) with luminosities L ≃ 5–7 × 10{sup 5} L{sub ⊙} in the Local Group galaxy M33 using images from the Hubble Space Telescope WFPC2 in the F555W and F814W bands. We obtained the ellipticities, position angles, and surface brightness profiles for each GC. In general, the ellipticities of the M33 sample clusters are similar to those of the M31 clusters. The structural and dynamical parameters are derived by fitting the profiles to three different models combined with mass-to-light ratios (M/L values) from population-synthesis models. The structural parametersmore » include core radii, concentration, half-light radii, and central surface brightness. The dynamical parameters include the integrated cluster mass, integrated binding energy, central surface mass density, and predicted line of sight velocity dispersion at the cluster center. The velocity dispersions of the four clusters predicted here agree well with the observed dispersions by Larsen et al. The results here showed that the majority of the sample halo GCs are better fitted by both the King model and the Wilson model than the Sérsic model. In general, the properties of the clusters in M33, M31, and the Milky Way fall in the same regions of parameter spaces. The tight correlations of cluster properties indicate a “fundamental plane” for clusters, which reflects some universal physical conditions and processes operating at the epoch of cluster formation.« less

Current and Future Tests of the Algebraic Cluster Model of12C

NASA Astrophysics Data System (ADS)

Gai, Moshe

2017-07-01

A new theoretical approach to clustering in the frame of the Algebraic Cluster Model (ACM) has been developed. It predicts, in12C, rotation-vibration structure with rotational bands of an oblate equilateral triangular symmetric spinning top with a D 3h symmetry characterized by the sequence of states: 0+, 2+, 3-, 4±, 5- with a degenerate 4+ and 4- (parity doublet) states. Our newly measured {2}2+ state in12C allows the first study of rotation-vibration structure in12C. The newly measured 5- state and 4- states fit very well the predicted ground state rotational band structure with the predicted sequence of states: 0+, 2+, 3-, 4±, 5- with almost degenerate 4+ and 4- (parity doublet) states. Such a D 3h symmetry is characteristic of triatomic molecules, but it is observed in the ground state rotational band of12C for the first time in a nucleus. We discuss predictions of the ACM of other rotation-vibration bands in12C such as the (0+) Hoyle band and the (1-) bending mode with prediction of (“missing 3- and 4-”) states that may shed new light on clustering in12C and light nuclei. In particular, the observation (or non observation) of the predicted (“missing”) states in the Hoyle band will allow us to conclude the geometrical arrangement of the three alpha particles composing the Hoyle state at 7.6542 MeV in12C. We discuss proposed research programs at the Darmstadt S- DALINAC and at the newly constructed ELI-NP facility near Bucharest to test the predictions of the ACM in isotopes of carbon.

Cluster structure in the correlation coefficient matrix can be characterized by abnormal eigenvalues

NASA Astrophysics Data System (ADS)

Nie, Chun-Xiao

2018-02-01

In a large number of previous studies, the researchers found that some of the eigenvalues of the financial correlation matrix were greater than the predicted values of the random matrix theory (RMT). Here, we call these eigenvalues as abnormal eigenvalues. In order to reveal the hidden meaning of these abnormal eigenvalues, we study the toy model with cluster structure and find that these eigenvalues are related to the cluster structure of the correlation coefficient matrix. In this paper, model-based experiments show that in most cases, the number of abnormal eigenvalues of the correlation matrix is equal to the number of clusters. In addition, empirical studies show that the sum of the abnormal eigenvalues is related to the clarity of the cluster structure and is negatively correlated with the correlation dimension.

Theoretical Prediction of Si 2–Si 33 Absorption Spectra

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

Zhao, Li -Zhen; Lu, Wen -Cai; Qin, Wei

Here, the optical absorption spectra of Si 2–Si 33 clusters were systematically studied by a time-dependent density functional theory approach. The calculations revealed that the absorption spectrum becomes significantly broad with increasing cluster size, stretching from ultraviolet to the infrared region. The absorption spectra are closely related to the structural motifs. With increasing cluster size, the absorption intensity of cage structures gradually increases, but the absorption curves of the prolate and the Y-shaped structures are very sensitive to cluster size. If the transition energy reaches ~12 eV, it is noted that all the clusters have remarkable absorption in deep ultravioletmore » region of 100–200 nm, and the maximum absorption intensity is ~100 times that in the visible region. Further, the optical responses to doping in the Si clusters were studied.« less

Theoretical Prediction of Si 2–Si 33 Absorption Spectra

DOE PAGES

Zhao, Li -Zhen; Lu, Wen -Cai; Qin, Wei; ...

2017-07-07

Here, the optical absorption spectra of Si 2–Si 33 clusters were systematically studied by a time-dependent density functional theory approach. The calculations revealed that the absorption spectrum becomes significantly broad with increasing cluster size, stretching from ultraviolet to the infrared region. The absorption spectra are closely related to the structural motifs. With increasing cluster size, the absorption intensity of cage structures gradually increases, but the absorption curves of the prolate and the Y-shaped structures are very sensitive to cluster size. If the transition energy reaches ~12 eV, it is noted that all the clusters have remarkable absorption in deep ultravioletmore » region of 100–200 nm, and the maximum absorption intensity is ~100 times that in the visible region. Further, the optical responses to doping in the Si clusters were studied.« less

Structures of 38-atom gold-platinum nanoalloy clusters

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

Ong, Yee Pin; Yoon, Tiem Leong; Lim, Thong Leng

2015-04-24

Bimetallic nanoclusters, such as gold-platinum nanoclusters, are nanomaterials promising wide range of applications. We perform a numerical study of 38-atom gold-platinum nanoalloy clusters, Au{sub n}Pt{sub 38−n} (0 ≤ n ≤ 38), to elucidate the geometrical structures of these clusters. The lowest-energy structures of these bimetallic nanoclusters at the semi-empirical level are obtained via a global-minimum search algorithm known as parallel tempering multi-canonical basin hopping plus genetic algorithm (PTMBHGA), in which empirical Gupta many-body potential is used to describe the inter-atomic interactions among the constituent atoms. The structures of gold-platinum nanoalloy clusters are predicted to be core-shell segregated nanoclusters. Gold atomsmore » are observed to preferentially occupy the surface of the clusters, while platinum atoms tend to occupy the core due to the slightly smaller atomic radius of platinum as compared to gold’s. The evolution of the geometrical structure of 38-atom Au-Pt clusters displays striking similarity with that of 38-atom Au-Cu nanoalloy clusters as reported in the literature.« less

A hierarchical linear model for tree height prediction.

Treesearch

Vicente J. Monleon

2003-01-01

Measuring tree height is a time-consuming process. Often, tree diameter is measured and height is estimated from a published regression model. Trees used to develop these models are clustered into stands, but this structure is ignored and independence is assumed. In this study, hierarchical linear models that account explicitly for the clustered structure of the data...

Exploring the atomic structure of 1.8nm monolayer-protected gold clusters with aberration-corrected STEM.

PubMed

Liu, Jian; Jian, Nan; Ornelas, Isabel; Pattison, Alexander J; Lahtinen, Tanja; Salorinne, Kirsi; Häkkinen, Hannu; Palmer, Richard E

2017-05-01

Monolayer-protected (MP) Au clusters present attractive quantum systems with a range of potential applications e.g. in catalysis. Knowledge of the atomic structure is needed to obtain a full understanding of their intriguing physical and chemical properties. Here we employed aberration-corrected scanning transmission electron microscopy (ac-STEM), combined with multislice simulations, to make a round-robin investigation of the atomic structure of chemically synthesised clusters with nominal composition Au 144 (SCH 2 CH 2 Ph) 60 provided by two different research groups. The MP Au clusters were "weighed" by the atom counting method, based on their integrated intensities in the high angle annular dark field (HAADF) regime and calibrated exponent of the Z dependence. For atomic structure analysis, we compared experimental images of hundreds of clusters, with atomic resolution, against a variety of structural models. Across the size range 123-151 atoms, only 3% of clusters matched the theoretically predicted Au 144 (SR) 60 structure, while a large proportion of the clusters were amorphous (i.e. did not match any model structure). However, a distinct ring-dot feature, characteristic of local icosahedral symmetry, was observed in about 20% of the clusters. Copyright © 2017. Published by Elsevier B.V.

Visualizing and Clustering Protein Similarity Networks: Sequences, Structures, and Functions.

PubMed

Mai, Te-Lun; Hu, Geng-Ming; Chen, Chi-Ming

2016-07-01

Research in the recent decade has demonstrated the usefulness of protein network knowledge in furthering the study of molecular evolution of proteins, understanding the robustness of cells to perturbation, and annotating new protein functions. In this study, we aimed to provide a general clustering approach to visualize the sequence-structure-function relationship of protein networks, and investigate possible causes for inconsistency in the protein classifications based on sequences, structures, and functions. Such visualization of protein networks could facilitate our understanding of the overall relationship among proteins and help researchers comprehend various protein databases. As a demonstration, we clustered 1437 enzymes by their sequences and structures using the minimum span clustering (MSC) method. The general structure of this protein network was delineated at two clustering resolutions, and the second level MSC clustering was found to be highly similar to existing enzyme classifications. The clustering of these enzymes based on sequence, structure, and function information is consistent with each other. For proteases, the Jaccard's similarity coefficient is 0.86 between sequence and function classifications, 0.82 between sequence and structure classifications, and 0.78 between structure and function classifications. From our clustering results, we discussed possible examples of divergent evolution and convergent evolution of enzymes. Our clustering approach provides a panoramic view of the sequence-structure-function network of proteins, helps visualize the relation between related proteins intuitively, and is useful in predicting the structure and function of newly determined protein sequences.

Some Unsolved Problems, Questions, and Applications of the Brightsen Nucleon Cluster Model

NASA Astrophysics Data System (ADS)

Smarandache, Florentin

2010-10-01

Brightsen Model is opposite to the Standard Model, and it was build on John Weeler's Resonating Group Structure Model and on Linus Pauling's Close-Packed Spheron Model. Among Brightsen Model's predictions and applications we cite the fact that it derives the average number of prompt neutrons per fission event, it provides a theoretical way for understanding the low temperature / low energy reactions and for approaching the artificially induced fission, it predicts that forces within nucleon clusters are stronger than forces between such clusters within isotopes; it predicts the unmatter entities inside nuclei that result from stable and neutral union of matter and antimatter, and so on. But these predictions have to be tested in the future at the new CERN laboratory.

Structure assignment, electronic properties, and magnetism quenching of endohedrally doped neutral silicon clusters, Si(n)Co (n = 10-12).

PubMed

Li, Yejun; Tam, Nguyen Minh; Claes, Pieterjan; Woodham, Alex P; Lyon, Jonathan T; Ngan, Vu Thi; Nguyen, Minh Tho; Lievens, Peter; Fielicke, André; Janssens, Ewald

2014-09-18

The structures of neutral cobalt-doped silicon clusters have been assigned by a combined experimental and theoretical study. Size-selective infrared spectra of neutral Si(n)Co (n = 10-12) clusters are measured using a tunable IR-UV two-color ionization scheme. The experimental infrared spectra are compared with calculated spectra of low-energy structures predicted at the B3P86 level of theory. It is shown that the Si(n)Co (n = 10-12) clusters have endohedral caged structures, where the silicon frameworks prefer double-layered structures encapsulating the Co atom. Electronic structure analysis indicates that the clusters are stabilized by an ionic interaction between the Co dopant atom and the silicon cage due to the charge transfer from the silicon valence sp orbitals to the cobalt 3d orbitals. Strong hybridization between the Co dopant atom and the silicon host quenches the local magnetic moment on the encapsulated Co atom.

Theoretical predictions of a bucky-diamond SiC cluster.

PubMed

Yu, Ming; Jayanthi, C S; Wu, S Y

2012-06-15

A study of structural relaxations of Si(n)C(m) clusters corresponding to different compositions, different relative arrangements of Si/C atoms, and different types of initial structure, reveals that the Si(n)C(m) bucky-diamond structure can be obtained for an initial network structure constructed from a truncated bulk 3C-SiC for a magic composition corresponding to n = 68 and m = 79. This study was performed using a semi-empirical Hamiltonian (SCED-LCAO) since it allowed an extensive search of different types of initial structures. However, the bucky-diamond structure predicted by this method was also confirmed by a more accurate density functional theory (DFT) based method. The bucky-diamond structure exhibited by a SiC-based system represents an interesting paradigm where a Si atom can form three-coordinated as well as four-coordinated networks with carbon atoms and vice versa and with both types of network co-existing in the same structure. Specifically, the bucky-diamond structure of the Si(68)C(79) cluster consists of a 35-atom diamond-like inner core (four-atom coordinations) suspended inside a 112-atom fullerene-like shell (three-atom coordinations).

Foraging on the potential energy surface: a swarm intelligence-based optimizer for molecular geometry.

PubMed

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D; Sebastiani, Daniel

2012-11-21

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Photoelectron spectroscopy of nitromethane anion clusters

NASA Astrophysics Data System (ADS)

Pruitt, Carrie Jo M.; Albury, Rachael M.; Goebbert, Daniel J.

2016-08-01

Nitromethane anion and nitromethane dimer, trimer, and hydrated cluster anions were studied by photoelectron spectroscopy. Vertical detachment energies, estimated electron affinities, and solvation energies were obtained from the photoelectron spectra. Cluster structures were investigated using theoretical calculations. Predicted detachment energies agreed with experiment. Calculations show water binds to nitromethane anion through two hydrogen bonds. The dimer has a non-linear structure with a single ionic Csbnd H⋯O hydrogen bond. The trimer has two different solvent interactions, but both involve the weak Csbnd H⋯O hydrogen bond.

Foraging on the potential energy surface: A swarm intelligence-based optimizer for molecular geometry

NASA Astrophysics Data System (ADS)

Wehmeyer, Christoph; Falk von Rudorff, Guido; Wolf, Sebastian; Kabbe, Gabriel; Schärf, Daniel; Kühne, Thomas D.; Sebastiani, Daniel

2012-11-01

We present a stochastic, swarm intelligence-based optimization algorithm for the prediction of global minima on potential energy surfaces of molecular cluster structures. Our optimization approach is a modification of the artificial bee colony (ABC) algorithm which is inspired by the foraging behavior of honey bees. We apply our modified ABC algorithm to the problem of global geometry optimization of molecular cluster structures and show its performance for clusters with 2-57 particles and different interatomic interaction potentials.

Infrared detection of (H 2O) 20 isomers of exceptional stability: A drop-like and a face-sharing pentagonal prism cluster

DOE PAGES

Pradzynski, Christoph C.; Dierking, Christoph W.; Zurheide, Florian; ...

2014-09-01

Water clusters containing fully coordinated water molecules are model systems that mimic the local environment of the condensed phase. Present knowledge about the water cluster size regime in which the transition from the allsurface to the fully solvated water molecules occurs is mainly based on theoretical predictions in lieu of the absence of precisely size resolved experimental measurements. Here, we report size and isomer selective infrared (IR) spectra of (H 2O) 20 clusters tagged with a sodium atom by employing IR excitation modulated photoionization spectroscopy. The observed absorption patterns in the OH stretching ”fingerprint” region are consistent with the theoreticallymore » predicted spectra of two structurally distinct isomers: A drop-like cluster with a fully coordinated (interior) water and an edge-sharing pentagonal prism cluster in which all atoms are on the surface. The observed isomers show exceptional stability and are predicted to be nearly isoenergetic.« less

Self-Adaptive Prediction of Cloud Resource Demands Using Ensemble Model and Subtractive-Fuzzy Clustering Based Fuzzy Neural Network

PubMed Central

Chen, Zhijia; Zhu, Yuanchang; Di, Yanqiang; Feng, Shaochong

2015-01-01

In IaaS (infrastructure as a service) cloud environment, users are provisioned with virtual machines (VMs). To allocate resources for users dynamically and effectively, accurate resource demands predicting is essential. For this purpose, this paper proposes a self-adaptive prediction method using ensemble model and subtractive-fuzzy clustering based fuzzy neural network (ESFCFNN). We analyze the characters of user preferences and demands. Then the architecture of the prediction model is constructed. We adopt some base predictors to compose the ensemble model. Then the structure and learning algorithm of fuzzy neural network is researched. To obtain the number of fuzzy rules and the initial value of the premise and consequent parameters, this paper proposes the fuzzy c-means combined with subtractive clustering algorithm, that is, the subtractive-fuzzy clustering. Finally, we adopt different criteria to evaluate the proposed method. The experiment results show that the method is accurate and effective in predicting the resource demands. PMID:25691896

Prediction of Solvent Physical Properties using the Hierarchical Clustering Method

EPA Science Inventory

Recently a QSAR (Quantitative Structure Activity Relationship) method, the hierarchical clustering method, was developed to estimate acute toxicity values for large, diverse datasets. This methodology has now been applied to the estimate solvent physical properties including sur...

Structure and Sequence Analyses of Clustered Protocadherins Reveal Antiparallel Interactions that Mediate Homophilic Specificity.

PubMed

Nicoludis, John M; Lau, Sze-Yi; Schärfe, Charlotta P I; Marks, Debora S; Weihofen, Wilhelm A; Gaudet, Rachelle

2015-11-03

Clustered protocadherin (Pcdh) proteins mediate dendritic self-avoidance in neurons via specific homophilic interactions in their extracellular cadherin (EC) domains. We determined crystal structures of EC1-EC3, containing the homophilic specificity-determining region, of two mouse clustered Pcdh isoforms (PcdhγA1 and PcdhγC3) to investigate the nature of the homophilic interaction. Within the crystal lattices, we observe antiparallel interfaces consistent with a role in trans cell-cell contact. Antiparallel dimerization is supported by evolutionary correlations. Two interfaces, located primarily on EC2-EC3, involve distinctive clustered Pcdh structure and sequence motifs, lack predicted glycosylation sites, and contain residues highly conserved in orthologs but not paralogs, pointing toward their biological significance as homophilic interaction interfaces. These two interfaces are similar yet distinct, reflecting a possible difference in interaction architecture between clustered Pcdh subfamilies. These structures initiate a molecular understanding of clustered Pcdh assemblies that are required to produce functional neuronal networks. Copyright © 2015 Elsevier Ltd. All rights reserved.

Innovative Strategies to Develop Chemical Categories Using a Combination of Structural and Toxicological Properties.

PubMed

Batke, Monika; Gütlein, Martin; Partosch, Falko; Gundert-Remy, Ursula; Helma, Christoph; Kramer, Stefan; Maunz, Andreas; Seeland, Madeleine; Bitsch, Annette

2016-01-01

Interest is increasing in the development of non-animal methods for toxicological evaluations. These methods are however, particularly challenging for complex toxicological endpoints such as repeated dose toxicity. European Legislation, e.g., the European Union's Cosmetic Directive and REACH, demands the use of alternative methods. Frameworks, such as the Read-across Assessment Framework or the Adverse Outcome Pathway Knowledge Base, support the development of these methods. The aim of the project presented in this publication was to develop substance categories for a read-across with complex endpoints of toxicity based on existing databases. The basic conceptual approach was to combine structural similarity with shared mechanisms of action. Substances with similar chemical structure and toxicological profile form candidate categories suitable for read-across. We combined two databases on repeated dose toxicity, RepDose database, and ELINCS database to form a common database for the identification of categories. The resulting database contained physicochemical, structural, and toxicological data, which were refined and curated for cluster analyses. We applied the Predictive Clustering Tree (PCT) approach for clustering chemicals based on structural and on toxicological information to detect groups of chemicals with similar toxic profiles and pathways/mechanisms of toxicity. As many of the experimental toxicity values were not available, this data was imputed by predicting them with a multi-label classification method, prior to clustering. The clustering results were evaluated by assessing chemical and toxicological similarities with the aim of identifying clusters with a concordance between structural information and toxicity profiles/mechanisms. From these chosen clusters, seven were selected for a quantitative read-across, based on a small ratio of NOAEL of the members with the highest and the lowest NOAEL in the cluster (< 5). We discuss the limitations of the approach. Based on this analysis we propose improvements for a follow-up approach, such as incorporation of metabolic information and more detailed mechanistic information. The software enables the user to allocate a substance in a cluster and to use this information for a possible read- across. The clustering tool is provided as a free web service, accessible at http://mlc-reach.informatik.uni-mainz.de.

Prediction of hot regions in protein-protein interaction by combining density-based incremental clustering with feature-based classification.

PubMed

Hu, Jing; Zhang, Xiaolong; Liu, Xiaoming; Tang, Jinshan

2015-06-01

Discovering hot regions in protein-protein interaction is important for drug and protein design, while experimental identification of hot regions is a time-consuming and labor-intensive effort; thus, the development of predictive models can be very helpful. In hot region prediction research, some models are based on structure information, and others are based on a protein interaction network. However, the prediction accuracy of these methods can still be improved. In this paper, a new method is proposed for hot region prediction, which combines density-based incremental clustering with feature-based classification. The method uses density-based incremental clustering to obtain rough hot regions, and uses feature-based classification to remove the non-hot spot residues from the rough hot regions. Experimental results show that the proposed method significantly improves the prediction performance of hot regions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Probing the structural evolution of ruthenium doped germanium clusters: Photoelectron spectroscopy and density functional theory calculations

PubMed Central

Jin, Yuanyuan; Lu, Shengjie; Hermann, Andreas; Kuang, Xiaoyu; Zhang, Chuanzhao; Lu, Cheng; Xu, Hongguang; Zheng, Weijun

2016-01-01

We present a combined experimental and theoretical study of ruthenium doped germanium clusters, RuGen− (n = 3–12), and their corresponding neutral species. Photoelectron spectra of RuGen− clusters are measured at 266 nm. The vertical detachment energies (VDEs) and adiabatic detachment energies (ADEs) are obtained. Unbiased CALYPSO structure searches confirm the low-lying structures of anionic and neutral ruthenium doped germanium clusters in the size range of 3 ≤ n ≤ 12. Subsequent geometry optimizations using density functional theory (DFT) at PW91/LANL2DZ level are carried out to determine the relative stability and electronic properties of ruthenium doped germanium clusters. It is found that most of the anionic and neutral clusters have very similar global features. Although the global minimum structures of the anionic and neutral clusters are different, their respective geometries are observed as the low-lying isomers in either case. In addition, for n > 8, the Ru atom in RuGen−/0 clusters is absorbed endohedrally in the Ge cage. The theoretically predicted vertical and adiabatic detachment energies are in good agreement with the experimental measurements. The excellent agreement between DFT calculations and experiment enables a comprehensive evaluation of the geometrical and electronic structures of ruthenium doped germanium clusters. PMID:27439955

Novel Approach to Classify Plants Based on Metabolite-Content Similarity.

PubMed

Liu, Kang; Abdullah, Azian Azamimi; Huang, Ming; Nishioka, Takaaki; Altaf-Ul-Amin, Md; Kanaya, Shigehiko

2017-01-01

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations.

Novel Approach to Classify Plants Based on Metabolite-Content Similarity

PubMed Central

Abdullah, Azian Azamimi; Huang, Ming; Nishioka, Takaaki

2017-01-01

Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes). This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward's method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations. PMID:28164123

Latent structure modeling underlying theophylline tablet formulations using a Bayesian network based on a self-organizing map clustering.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Obata, Yasuko; Takayama, Kozo

2015-01-01

The "quality by design" concept in pharmaceutical formulation development requires the establishment of a science-based rationale and design space. In this article, we integrate thin-plate spline (TPS) interpolation, Kohonen's self-organizing map (SOM) and a Bayesian network (BN) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline tablets were prepared using a standard formulation. We measured the tensile strength and disintegration time as response variables and the compressibility, cohesion and dispersibility of the pretableting blend as latent variables. We predicted these variables quantitatively using nonlinear TPS, generated a large amount of data on pretableting blends and tablets and clustered these data into several clusters using a SOM. Our results show that we are able to predict the experimental values of the latent and response variables with a high degree of accuracy and are able to classify the tablet data into several distinct clusters. In addition, to visualize the latent structure between the causal and latent factors and the response variables, we applied a BN method to the SOM clustering results. We found that despite having inserted latent variables between the causal factors and response variables, their relation is equivalent to the results for the SOM clustering, and thus we are able to explain the underlying latent structure. Consequently, this technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline tablet formulation.

New symmetry of the cluster model

NASA Astrophysics Data System (ADS)

Gai, Moshe

2015-10-01

A new approach to clustering in the frame of the Algebraic Cluster Model (ACM) has been developed. It predicts rotation-vibration structure with rotational band of an oblate equilateral triangular spinning top with a 𝒟3h symmetry characterized by the sequence of states: 0+, 2+, 3-, 4±, 5- with almost degenerate 4+ and 4- (parity doublet) states. Our measurement of the new 22+ and the measured of the new 5- state in 12C fit very well to the predicted (ground state) rotational band structure with the sequence of states: 0+, 2+, 3-, 4±, 5- with almost degenerate 4+ and 4- (parity doublet) states. Such a 𝒟3h symmetry was observed in triatomic molecules, and it is observed in 12C for the first time in nuclear physics. We discuss a classification of other rotation-vibration bands in 12C such as the (0+) Hoyle band and the (1-) bending mode band and suggest measurements in search of the predicted ("missing") states that may shed new light on clustering in 12C and light nuclei. In particular, the observation (or non observation) of the predicted ("missing") states in the Hoyle band will allow us to conclude the geometrical arrangement of the three alpha particles composing the Hoyle state at 7.654 MeV in 12C.

Fuzzy cluster analysis of simple physicochemical properties of amino acids for recognizing secondary structure in proteins.

PubMed Central

Mocz, G.

1995-01-01

Fuzzy cluster analysis has been applied to the 20 amino acids by using 65 physicochemical properties as a basis for classification. The clustering products, the fuzzy sets (i.e., classical sets with associated membership functions), have provided a new measure of amino acid similarities for use in protein folding studies. This work demonstrates that fuzzy sets of simple molecular attributes, when assigned to amino acid residues in a protein's sequence, can predict the secondary structure of the sequence with reasonable accuracy. An approach is presented for discriminating standard folding states, using near-optimum information splitting in half-overlapping segments of the sequence of assigned membership functions. The method is applied to a nonredundant set of 252 proteins and yields approximately 73% matching for correctly predicted and correctly rejected residues with approximately 60% overall success rate for the correctly recognized ones in three folding states: alpha-helix, beta-strand, and coil. The most useful attributes for discriminating these states appear to be related to size, polarity, and thermodynamic factors. Van der Waals volume, apparent average thickness of surrounding molecular free volume, and a measure of dimensionless surface electron density can explain approximately 95% of prediction results. hydrogen bonding and hydrophobicity induces do not yet enable clear clustering and prediction. PMID:7549882

Line-of-sight structure toward strong lensing galaxy clusters

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

Bayliss, Matthew B.; Johnson, Traci; Sharon, Keren

2014-03-01

We present an analysis of the line-of-sight structure toward a sample of 10 strong lensing cluster cores. Structure is traced by groups that are identified spectroscopically in the redshift range, 0.1 ≤ z ≤ 0.9, and we measure the projected angular and comoving separations between each group and the primary strong lensing clusters in each corresponding line of sight. From these data we measure the distribution of projected angular separations between the primary strong lensing clusters and uncorrelated large-scale structure as traced by groups. We then compare the observed distribution of angular separations for our strong lensing selected lines ofmore » sight against the distribution of groups that is predicted for clusters lying along random lines of sight. There is clear evidence for an excess of structure along the line of sight at small angular separations (θ ≤ 6') along the strong lensing selected lines of sight, indicating that uncorrelated structure is a significant systematic that contributes to producing galaxy clusters with large cross sections for strong lensing. The prevalence of line-of-sight structure is one of several biases in strong lensing clusters that can potentially be folded into cosmological measurements using galaxy cluster samples. These results also have implications for current and future studies—such as the Hubble Space Telescope Frontier Fields—that make use of massive galaxy cluster lenses as precision cosmological telescopes; it is essential that the contribution of line-of-sight structure be carefully accounted for in the strong lens modeling of the cluster lenses.« less

Does objective cluster analysis serve as a useful precursor to seasonal precipitation prediction at local scale? Application to western Ethiopia

NASA Astrophysics Data System (ADS)

Zhang, Ying; Moges, Semu; Block, Paul

2018-01-01

Prediction of seasonal precipitation can provide actionable information to guide management of various sectoral activities. For instance, it is often translated into hydrological forecasts for better water resources management. However, many studies assume homogeneity in precipitation across an entire study region, which may prove ineffective for operational and local-level decisions, particularly for locations with high spatial variability. This study proposes advancing local-level seasonal precipitation predictions by first conditioning on regional-level predictions, as defined through objective cluster analysis, for western Ethiopia. To our knowledge, this is the first study predicting seasonal precipitation at high resolution in this region, where lives and livelihoods are vulnerable to precipitation variability given the high reliance on rain-fed agriculture and limited water resources infrastructure. The combination of objective cluster analysis, spatially high-resolution prediction of seasonal precipitation, and a modeling structure spanning statistical and dynamical approaches makes clear advances in prediction skill and resolution, as compared with previous studies. The statistical model improves versus the non-clustered case or dynamical models for a number of specific clusters in northwestern Ethiopia, with clusters having regional average correlation and ranked probability skill score (RPSS) values of up to 0.5 and 33 %, respectively. The general skill (after bias correction) of the two best-performing dynamical models over the entire study region is superior to that of the statistical models, although the dynamical models issue predictions at a lower resolution and the raw predictions require bias correction to guarantee comparable skills.

Functional region prediction with a set of appropriate homologous sequences-an index for sequence selection by integrating structure and sequence information with spatial statistics

PubMed Central

2012-01-01

Background The detection of conserved residue clusters on a protein structure is one of the effective strategies for the prediction of functional protein regions. Various methods, such as Evolutionary Trace, have been developed based on this strategy. In such approaches, the conserved residues are identified through comparisons of homologous amino acid sequences. Therefore, the selection of homologous sequences is a critical step. It is empirically known that a certain degree of sequence divergence in the set of homologous sequences is required for the identification of conserved residues. However, the development of a method to select homologous sequences appropriate for the identification of conserved residues has not been sufficiently addressed. An objective and general method to select appropriate homologous sequences is desired for the efficient prediction of functional regions. Results We have developed a novel index to select the sequences appropriate for the identification of conserved residues, and implemented the index within our method to predict the functional regions of a protein. The implementation of the index improved the performance of the functional region prediction. The index represents the degree of conserved residue clustering on the tertiary structure of the protein. For this purpose, the structure and sequence information were integrated within the index by the application of spatial statistics. Spatial statistics is a field of statistics in which not only the attributes but also the geometrical coordinates of the data are considered simultaneously. Higher degrees of clustering generate larger index scores. We adopted the set of homologous sequences with the highest index score, under the assumption that the best prediction accuracy is obtained when the degree of clustering is the maximum. The set of sequences selected by the index led to higher functional region prediction performance than the sets of sequences selected by other sequence-based methods. Conclusions Appropriate homologous sequences are selected automatically and objectively by the index. Such sequence selection improved the performance of functional region prediction. As far as we know, this is the first approach in which spatial statistics have been applied to protein analyses. Such integration of structure and sequence information would be useful for other bioinformatics problems. PMID:22643026

Structure, electronic and magnetic properties of Mn{sub n} (n=2-8) clusters: A DFT investigation

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

Kumar, Vipin; Roy, Debesh R., E-mail: drr@ashd.svnit.ac.in

2016-05-06

A detail studyon the stability, electronic and magnetic properties of Mn{sub n} (n=2-8) cluster series is performed under the utilization ofdensity functional theory (DFT). The binding energy (B.E.), HOMO-LUMO energy gap (HLG), chemical hardness (η), ionization potential (I.P.), electron affinity (E.A)and electronegativity (χ) of these clusters are predicted. We have also studied the magnetic moments associated with the stable cluster isomers. The lowest energy structures for each cluster sizes aredetermined with a systematic search imposing all possible initial magnetic configuration on the cluster. All the calculations are carried out using a popular GGA functional PBE as proposed by Pardew, Burkemore » and Ernzerhof and implemented in the VASP program.« less

Stepwise Internal Energy Control for Protonated Methanol Clusters by Using the Inert Gas Tagging

NASA Astrophysics Data System (ADS)

Shimamori, Takuto; Kuo, Jer-Lai; Fujii, Asuka

2016-06-01

Preferred isomer structures of hydrogen-bonded clusters should depend on their temperature because of the entropy term in the free energy. To observe such temperature dependence, we propose a new approach to control the internal energy (vibrational temperature) of protonated clusters in the gas phase. We performed IR spectroscopy of protonated methanol clusters, H+ (CH{_3}OH) {_n}, n= 5 and 7, with the tagging by various inert gas species (Ar, CO{_2}, CO, CS{_2}, C{_2}H{_2}, and C{_6}H{_6}). We found that vibrational temperature of the tagged clusters raises with increase of the interaction energy with the tag species, and the observed cluster structures follow the theoretical prediction of the temperature dependence of the isomer population.

Computational study on the molecular structures and photoelectron spectra of bimetallic oxide clusters MW2O9(-/0) (M=V, Nb, Ta).

PubMed

Chen, Wen-Jie; Zhang, Chang-Fu; Zhang, Xian-Hui; Zhang, Yong-Fan; Huang, Xin

2013-05-15

Density functional theory (DFT) and coupled cluster theory (CCSD(T)) calculations are carried out to investigate the electronic and structural properties of a series of bimetallic oxide clusters MW2O9(-/0) (M=V, Nb, Ta). Generalized Koopmans' theorem is applied to predict the vertical detachment energies (VDEs) and simulate the photoelectron spectra (PES). Theoretical calculations at the B3LYP level yield singlet and doublet ground states for the bimetallic anionic and neutral clusters, respectively. All the clusters present the six-membered ring structures with different symmetries, except that the TaW2O9(-) cluster shows a chained style with a penta-coordinated tantalum atom. Spin density analyses reveal oxygen radical species in all neutral clusters, consistent with their structural characteristics. Moreover, additional calculations are performed to study the oxidation reaction of CO molecule with the W3O9(+) cation and the isoelectronic VW2O9 cluster, and results indicate that the introduction of vanadium at tungsten site can efficiently improve the oxidation reactivity. Copyright © 2013 Elsevier B.V. All rights reserved.

Infrared laser spectroscopy of jet-cooled carbon clusters: structure of triplet C6

NASA Technical Reports Server (NTRS)

Hwang, H. J.; Van Orden, A.; Tanaka, K.; Kuo, E. W.; Heath, J. R.; Saykally, R. J.

1993-01-01

We report the first structural characterization of the triplet isomer of C6. Forty-one rovibrational/fine structure transitions in the nu 4(sigma u) antisymmetric stretch fundamental of the C6 cluster have been measured by diode laser absorption spectroscopy of a supersonic carbon cluster beam. The observed spectrum is characteristic of a centrosymmetric linear triplet state with cumulene-type bonding. The measured ground state rotational constant B0 = 0.048 479 (10)cm-1 and the effective bond length r(eff) = 1.2868 (1) angstroms are in good agreement with ab initio predictions for the linear triplet (3 sigma g-) state of C6.

Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

PubMed

Babcock, Joseph J; Du, Fang; Xu, Kaiping; Wheelan, Sarah J; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays.

Integrated Analysis of Drug-Induced Gene Expression Profiles Predicts Novel hERG Inhibitors

PubMed Central

Babcock, Joseph J.; Du, Fang; Xu, Kaiping; Wheelan, Sarah J.; Li, Min

2013-01-01

Growing evidence suggests that drugs interact with diverse molecular targets mediating both therapeutic and toxic effects. Prediction of these complex interactions from chemical structures alone remains challenging, as compounds with different structures may possess similar toxicity profiles. In contrast, predictions based on systems-level measurements of drug effect may reveal pharmacologic similarities not evident from structure or known therapeutic indications. Here we utilized drug-induced transcriptional responses in the Connectivity Map (CMap) to discover such similarities among diverse antagonists of the human ether-à-go-go related (hERG) potassium channel, a common target of promiscuous inhibition by small molecules. Analysis of transcriptional profiles generated in three independent cell lines revealed clusters enriched for hERG inhibitors annotated using a database of experimental measurements (hERGcentral) and clinical indications. As a validation, we experimentally identified novel hERG inhibitors among the unannotated drugs in these enriched clusters, suggesting transcriptional responses may serve as predictive surrogates of cardiotoxicity complementing existing functional assays. PMID:23936032

Ligand-protected gold clusters: the structure, synthesis and applications

NASA Astrophysics Data System (ADS)

Pichugina, D. A.; Kuz'menko, N. E.; Shestakov, A. F.

2015-11-01

Modern concepts of the structure and properties of atomic gold clusters protected by thiolate, selenolate, phosphine and phenylacetylene ligands are analyzed. Within the framework of the superatom theory, the 'divide and protect' approach and the structure rule, the stability and composition of a cluster are determined by the structure of the cluster core, the type of ligands and the total number of valence electrons. Methods of selective synthesis of gold clusters in solution and on the surface of inorganic composites based, in particular, on the reaction of Aun with RS, RSe, PhC≡C, Hal ligands or functional groups of proteins, on stabilization of clusters in cavities of the α-, β and γ-cyclodextrin molecules (Au15 and Au25) and on anchorage to a support surface (Au25/SiO2, Au20/C, Au10/FeOx) are reviewed. Problems in this field are also discussed. Among the methods for cluster structure prediction, particular attention is given to the theoretical approaches based on the density functional theory (DFT). The structures of a number of synthesized clusters are described using the results obtained by X-ray diffraction analysis and DFT calculations. A possible mechanism of formation of the SR(AuSR)n 'staple' units in the cluster shell is proposed. The structure and properties of bimetallic clusters MxAunLm (M=Pd, Pt, Ag, Cu) are discussed. The Pd or Pt atom is located at the centre of the cluster, whereas Ag and Cu atoms form bimetallic compounds in which the heteroatom is located on the surface of the cluster core or in the 'staple' units. The optical properties, fluorescence and luminescence of ligand-protected gold clusters originate from the quantum effects of the Au atoms in the cluster core and in the oligomeric SR(AuSR)x units in the cluster shell. Homogeneous and heterogeneous reactions catalyzed by atomic gold clusters are discussed in the context of the reaction mechanism and the nature of the active sites. The bibliography includes 345 references.

Density-functional study of the structures and properties of holmium-doped silicon clusters HoSi n (n = 3-9) and their anions.

PubMed

Hou, Liyuan; Yang, Jucai; Liu, Yuming

2017-04-01

The structures and properties of Ho-doped Si clusters, including their adiabatic electron affinities (AEAs), simulated photoelectron spectra (PESs), stabilities, magnetic moments, and charge-transfer characteristics, were systematically investigated using four density-functional methods. The results show that the double-hybrid functional (which includes an MP2 correlation component) can accurately predict the ground-state structure and properties of Ho-doped Si clusters. The ground-state structures of HoSi n (n = 3-9) are sextuplet electronic states. The structures of these Ho-doped Si clusters (aside from HoSi 7 ) are substitutional. The ground-state structures of HoSi n - are quintuplet electronic states. Their predicted AEAs are in excellent agreement with the experimental ones. The mean absolute error in the theoretical AEAs of HoSi n (n = 4-9) is only 0.04 eV. The simulated PESs for HoSi n - (n = 5-9) are in good agreement with the experimental PESs. Based on its simulated PES and theoretical AEA, we reassigned the experimental PES of HoSi 4 - and obtained an experimental AEA of 2.2 ± 0.1 eV. The dissociation energies of Ho from HoSi n and HoSi n - (n = 3-9) were evaluated to test the relative stabilities of the clusters. HOMO-LUMO gap analysis indicated that doping the Si clusters with the rare-earth metal atom significantly increases their photochemical reactivity. Natural population analysis showed that the magnetic moments of HoSi n (n = 3-9) and their anions derive mainly from the Ho atom. It was also found that the magnetic moments of Ho in the HoSi n clusters are larger than the magnetic moment of an isolated Ho atom.

Complex networks as a unified framework for descriptive analysis and predictive modeling in climate

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

Steinhaeuser, Karsten J K; Chawla, Nitesh; Ganguly, Auroop R

The analysis of climate data has relied heavily on hypothesis-driven statistical methods, while projections of future climate are based primarily on physics-based computational models. However, in recent years a wealth of new datasets has become available. Therefore, we take a more data-centric approach and propose a unified framework for studying climate, with an aim towards characterizing observed phenomena as well as discovering new knowledge in the climate domain. Specifically, we posit that complex networks are well-suited for both descriptive analysis and predictive modeling tasks. We show that the structural properties of climate networks have useful interpretation within the domain. Further,more » we extract clusters from these networks and demonstrate their predictive power as climate indices. Our experimental results establish that the network clusters are statistically significantly better predictors than clusters derived using a more traditional clustering approach. Using complex networks as data representation thus enables the unique opportunity for descriptive and predictive modeling to inform each other.« less

First-Principles Study of Structural, Electronic and Magnetic Properties of Metal-Centered Tetrahexahedral V15+ Cluster

PubMed Central

Ren, Hongjiang; Huang, Xinwei; Li, Shuna

2017-01-01

The V-centered bicapped hexagonal antiprism structure (A), as the most stable geometry of the cationic V15+ cluster, is determined by using infrared multiple photo dissociation (IR-MPD) in combination with density functional theory computations. It is found that the A structure can be stabilized by 18 delocalized 3c-2e σ-bonds on outer V3 triangles of the bicapped hexagonal antiprism surface and 12 delocalized 4c-2e σ-bonds on inner trigonal pyramidal V4 moiety, and the features are related to the strong p-d hybridization of the cluster. The total magnetic moments on the cluster are predicted to be 2.0 µB, which come mainly from the central vanadium atom. PMID:28665337

Dynamic stabilities of icosahedral-like clusters and their ability to form quasicrystals

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

Liang, Xiaogang; Hamid, Ilyar; Duan, Haiming, E-mail: dhm@xju.edu.cn

2016-06-15

The dynamic stabilities of the icosahedral-like clusters containing up to 2200 atoms are investigated for 15 metal elements. The clusters originate from five different initial structures (icosahedron, truncated decahedron, octahedron, closed-shell fragment of an HCP structure, and non-closed-shell fragment of an HCP structure). The obtained order of the dynamic stabilities of the icosahedral-like clusters can be assigned to three groups, from stronger to weaker, according to the size ranges involved: (Zr, Al, Ti) > (Cu, Fe, Co, Ni, Mg, Ag) > (Pb, Au, Pd, Pt, Rh, Ir), which correspond to the predicted formation ability of the quasicrystals. The differences ofmore » the sequences can be explained by analyzing the parameters of the Gupta-type many-body inter-atomic potentials.« less

Fast structure similarity searches among protein models: efficient clustering of protein fragments

PubMed Central

2012-01-01

Background For many predictive applications a large number of models is generated and later clustered in subsets based on structure similarity. In most clustering algorithms an all-vs-all root mean square deviation (RMSD) comparison is performed. Most of the time is typically spent on comparison of non-similar structures. For sets with more than, say, 10,000 models this procedure is very time-consuming and alternative faster algorithms, restricting comparisons only to most similar structures would be useful. Results We exploit the inverse triangle inequality on the RMSD between two structures given the RMSDs with a third structure. The lower bound on RMSD may be used, when restricting the search of similarity to a reasonably low RMSD threshold value, to speed up similarity searches significantly. Tests are performed on large sets of decoys which are widely used as test cases for predictive methods, with a speed-up of up to 100 times with respect to all-vs-all comparison depending on the set and parameters used. Sample applications are shown. Conclusions The algorithm presented here allows fast comparison of large data sets of structures with limited memory requirements. As an example of application we present clustering of more than 100000 fragments of length 5 from the top500H dataset into few hundred representative fragments. A more realistic scenario is provided by the search of similarity within the very large decoy sets used for the tests. Other applications regard filtering nearly-indentical conformation in selected CASP9 datasets and clustering molecular dynamics snapshots. Availability A linux executable and a Perl script with examples are given in the supplementary material (Additional file 1). The source code is available upon request from the authors. PMID:22642815

Insights into an original pocket-ligand pair classification: a promising tool for ligand profile prediction.

PubMed

Pérot, Stéphanie; Regad, Leslie; Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A; Villoutreix, Bruno O; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket properties for ligand binding.

Insights into an Original Pocket-Ligand Pair Classification: A Promising Tool for Ligand Profile Prediction

PubMed Central

Reynès, Christelle; Spérandio, Olivier; Miteva, Maria A.; Villoutreix, Bruno O.; Camproux, Anne-Claude

2013-01-01

Pockets are today at the cornerstones of modern drug discovery projects and at the crossroad of several research fields, from structural biology to mathematical modeling. Being able to predict if a small molecule could bind to one or more protein targets or if a protein could bind to some given ligands is very useful for drug discovery endeavors, anticipation of binding to off- and anti-targets. To date, several studies explore such questions from chemogenomic approach to reverse docking methods. Most of these studies have been performed either from the viewpoint of ligands or targets. However it seems valuable to use information from both ligands and target binding pockets. Hence, we present a multivariate approach relating ligand properties with protein pocket properties from the analysis of known ligand-protein interactions. We explored and optimized the pocket-ligand pair space by combining pocket and ligand descriptors using Principal Component Analysis and developed a classification engine on this paired space, revealing five main clusters of pocket-ligand pairs sharing specific and similar structural or physico-chemical properties. These pocket-ligand pair clusters highlight correspondences between pocket and ligand topological and physico-chemical properties and capture relevant information with respect to protein-ligand interactions. Based on these pocket-ligand correspondences, a protocol of prediction of clusters sharing similarity in terms of recognition characteristics is developed for a given pocket-ligand complex and gives high performances. It is then extended to cluster prediction for a given pocket in order to acquire knowledge about its expected ligand profile or to cluster prediction for a given ligand in order to acquire knowledge about its expected pocket profile. This prediction approach shows promising results and could contribute to predict some ligand properties critical for binding to a given pocket, and conversely, some key pocket properties for ligand binding. PMID:23840299

Infrared laser spectroscopy of the linear C13 carbon cluster

NASA Technical Reports Server (NTRS)

Giesen, T. F.; Van Orden, A.; Hwang, H. J.; Fellers, R. S.; Provencal, R. A.; Saykally, R. J.

1994-01-01

The infrared absorption spectrum of a linear, 13-atom carbon cluster (C13) has been observed by using a supersonic cluster beam-diode laser spectrometer. Seventy-six rovibrational transitions were measured near 1809 wave numbers and assigned to an antisymmetric stretching fundamental in the 1 sigma g+ ground state of C13. This definitive structural characterization of a carbon cluster in the intermediate size range between C10 and C20 is in apparent conflict with theoretical calculations, which predict that clusters of this size should exist as planar monocyclic rings.

Galaxy clusters in the cosmic web

NASA Astrophysics Data System (ADS)

Acebrón, A.; Durret, F.; Martinet, N.; Adami, C.; Guennou, L.

2014-12-01

Simulations of large scale structure formation in the universe predict that matter is essentially distributed along filaments at the intersection of which lie galaxy clusters. We have analysed 9 clusters in the redshift range 0.4

Predicting lower mantle heterogeneity from 4-D Earth models

NASA Astrophysics Data System (ADS)

Flament, Nicolas; Williams, Simon; Müller, Dietmar; Gurnis, Michael; Bower, Dan J.

2016-04-01

The Earth's lower mantle is characterized by two large-low-shear velocity provinces (LLSVPs), approximately ˜15000 km in diameter and 500-1000 km high, located under Africa and the Pacific Ocean. The spatial stability and chemical nature of these LLSVPs are debated. Here, we compare the lower mantle structure predicted by forward global mantle flow models constrained by tectonic reconstructions (Bower et al., 2015) to an analysis of five global tomography models. In the dynamic models, spanning 230 million years, slabs subducting deep into the mantle deform an initially uniform basal layer containing 2% of the volume of the mantle. Basal density, convective vigour (Rayleigh number Ra), mantle viscosity, absolute plate motions, and relative plate motions are varied in a series of model cases. We use cluster analysis to classify a set of equally-spaced points (average separation ˜0.45°) on the Earth's surface into two groups of points with similar variations in present-day temperature between 1000-2800 km depth, for each model case. Below ˜2400 km depth, this procedure reveals a high-temperature cluster in which mantle temperature is significantly larger than ambient and a low-temperature cluster in which mantle temperature is lower than ambient. The spatial extent of the high-temperature cluster is in first-order agreement with the outlines of the African and Pacific LLSVPs revealed by a similar cluster analysis of five tomography models (Lekic et al., 2012). Model success is quantified by computing the accuracy and sensitivity of the predicted temperature clusters in predicting the low-velocity cluster obtained from tomography (Lekic et al., 2012). In these cases, the accuracy varies between 0.61-0.80, where a value of 0.5 represents the random case, and the sensitivity ranges between 0.18-0.83. The largest accuracies and sensitivities are obtained for models with Ra ≈ 5 x 107, no asthenosphere (or an asthenosphere restricted to the oceanic domain), and a basal layer ˜ 4% denser than ambient mantle. Increasing convective vigour (Ra ≈ 5 x 108) or decreasing the density of the basal layer decreases both the accuracy and sensitivity of the predicted lower mantle structure. References: D. J. Bower, M. Gurnis, N. Flament, Assimilating lithosphere and slab history in 4-D Earth models. Phys. Earth Planet. Inter. 238, 8-22 (2015). V. Lekic, S. Cottaar, A. Dziewonski, B. Romanowicz, Cluster analysis of global lower mantle tomography: A new class of structure and implications for chemical heterogeneity. Earth Planet. Sci. Lett. 357, 68-77 (2012).

A combined experimental and theoretical spectroscopic protocol for determination of the structure of heterogeneous catalysts: developing the information content of the resonance Raman spectra of M1 MoVO x .

PubMed

Kubas, Adam; Noak, Johannes; Trunschke, Annette; Schlögl, Robert; Neese, Frank; Maganas, Dimitrios

2017-09-01

Absorption and multiwavelength resonance Raman spectroscopy are widely used to investigate the electronic structure of transition metal centers in coordination compounds and extended solid systems. In combination with computational methodologies that have predictive accuracy, they define powerful protocols to study the spectroscopic response of catalytic materials. In this work, we study the absorption and resonance Raman spectra of the M1 MoVO x catalyst. The spectra were calculated by time-dependent density functional theory (TD-DFT) in conjunction with the independent mode displaced harmonic oscillator model (IMDHO), which allows for detailed bandshape predictions. For this purpose cluster models with up to 9 Mo and V metallic centers are considered to represent the bulk structure of MoVO x . Capping hydrogens were used to achieve valence saturation at the edges of the cluster models. The construction of model structures was based on a thorough bonding analysis which involved conventional DFT and local coupled cluster (DLPNO-CCSD(T)) methods. Furthermore the relationship of cluster topology to the computed spectral features is discussed in detail. It is shown that due to the local nature of the involved electronic transitions, band assignment protocols developed for molecular systems can be applied to describe the calculated spectral features of the cluster models as well. The present study serves as a reference for future applications of combined experimental and computational protocols in the field of solid-state heterogeneous catalysis.

Self-assembled clusters of spheres related to spherical codes.

PubMed

Phillips, Carolyn L; Jankowski, Eric; Marval, Michelle; Glotzer, Sharon C

2012-10-01

We consider the thermodynamically driven self-assembly of spheres onto the surface of a central sphere. This assembly process forms self-limiting, or terminal, anisotropic clusters (N-clusters) with well-defined structures. We use Brownian dynamics to model the assembly of N-clusters varying in size from two to twelve outer spheres and free energy calculations to predict the expected cluster sizes and shapes as a function of temperature and inner particle diameter. We show that the arrangements of outer spheres at finite temperatures are related to spherical codes, an ideal mathematical sequence of points corresponding to the densest possible sphere packings. We demonstrate that temperature and the ratio of the diameters of the inner and outer spheres dictate cluster morphology. We present a surprising result for the equilibrium structure of a 5-cluster, for which the square pyramid arrangement is preferred over a more symmetric structure. We show this result using Brownian dynamics, a Monte Carlo simulation, and a free energy approximation. Our results suggest a promising way to assemble anisotropic building blocks from constituent colloidal spheres.

Synthesis of borophenes: Anisotropic, two-dimensional boron polymorphs

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

Mannix, A. J.; Zhou, X. -F.; Kiraly, B.

At the atomic-cluster scale, pure boron is markedly similar to carbon, forming simple planar molecules and cage-like fullerenes. Theoretical studies predict that two-dimensional (2D) boron sheets will adopt an atomic configuration similar to that of boron atomic clusters. We synthesized atomically thin, crystalline 2D boron sheets (i.e., borophene) on silver surfaces under ultrahigh-vacuum conditions. Atomic-scale characterization, supported by theoretical calculations, revealed structures reminiscent of fused boron clusters with multiple scales of anisotropic, out-of-plane buckling. Unlike bulk boron allotropes, borophene shows metallic characteristics that are consistent with predictions of a highly anisotropic, 2D metal.

Clues to the Formation of Spiral Structure in M51 from the Ages and Locations of Star Clusters

NASA Astrophysics Data System (ADS)

Chandar, Rupali; Chien, L.-H.; Meidt, Sharon; Querejeta, Miguel; Dobbs, Clare; Schinnerer, Eva; Whitmore, Bradley C.; Calzetti, Daniela; Dinino, Daiana; Kennicutt, Robert C.; Regan, Michael

2017-08-01

We determine the spatial distributions of star clusters at different ages in the grand-design spiral galaxy M51 using a new catalog based on multi-band images taken with the Hubble Space Telescope (HST). These distributions, when compared with the spiral structure defined by molecular gas, dust, young and old stars, show the following sequence in the inner arms: dense molecular gas (and dust) defines the inner edge of the spiral structure, followed by an overdensity of old stars and then young stellar clusters. The offset between gas and young clusters in the inner arms is consistent with the expectations for a density wave. Clusters as old as a few hundred Myr remain concentrated close to the spiral arms, although the distributions are broader than those for the youngest clusters, which is also consistent with predictions from density wave simulations. The outermost portion of the west arm is different from the rest of the spiral structure in that it contains primarily intermediate-age (≈ 100{--}400 {Myr}) clusters; we believe that this is a “material” arm. We have identified four “feathers,” stellar structures beyond the inner arms that have a larger pitch angle than the arms. We do not find age gradients along any of the feathers, but the least coherent feathers appear to have the largest range of cluster ages.

UQlust: combining profile hashing with linear-time ranking for efficient clustering and analysis of big macromolecular data.

PubMed

Adamczak, Rafal; Meller, Jarek

2016-12-28

Advances in computing have enabled current protein and RNA structure prediction and molecular simulation methods to dramatically increase their sampling of conformational spaces. The quickly growing number of experimentally resolved structures, and databases such as the Protein Data Bank, also implies large scale structural similarity analyses to retrieve and classify macromolecular data. Consequently, the computational cost of structure comparison and clustering for large sets of macromolecular structures has become a bottleneck that necessitates further algorithmic improvements and development of efficient software solutions. uQlust is a versatile and easy-to-use tool for ultrafast ranking and clustering of macromolecular structures. uQlust makes use of structural profiles of proteins and nucleic acids, while combining a linear-time algorithm for implicit comparison of all pairs of models with profile hashing to enable efficient clustering of large data sets with a low memory footprint. In addition to ranking and clustering of large sets of models of the same protein or RNA molecule, uQlust can also be used in conjunction with fragment-based profiles in order to cluster structures of arbitrary length. For example, hierarchical clustering of the entire PDB using profile hashing can be performed on a typical laptop, thus opening an avenue for structural explorations previously limited to dedicated resources. The uQlust package is freely available under the GNU General Public License at https://github.com/uQlust . uQlust represents a drastic reduction in the computational complexity and memory requirements with respect to existing clustering and model quality assessment methods for macromolecular structure analysis, while yielding results on par with traditional approaches for both proteins and RNAs.

The adsorption of helium atoms on small cationic gold clusters.

PubMed

Goulart, Marcelo; Gatchell, Michael; Kranabetter, Lorenz; Kuhn, Martin; Martini, Paul; Gitzl, Norbert; Rainer, Manuel; Postler, Johannes; Scheier, Paul; Ellis, Andrew M

2018-04-04

Adducts formed between small gold cluster cations and helium atoms are reported for the first time. These binary ions, Aun+Hem, were produced by electron ionization of helium nanodroplets doped with neutral gold clusters and were detected using mass spectrometry. For a given value of n, the distribution of ions as a function of the number of added helium atoms, m, has been recorded. Peaks with anomalously high intensities, corresponding to so-called magic number ions, are identified and interpreted in terms of the geometric structures of the underlying Aun+ ions. These features can be accounted for by planar structures for Aun+ ions with n ≤ 7, with the addition of helium having no significant effect on the structures of the underlying gold cluster ions. According to ion mobility studies and some theoretical predictions, a 3-D structure is expected for Au8+. However, the findings for Au8+ in this work are more consistent with a planar structure.

A new neuro-fuzzy training algorithm for identifying dynamic characteristics of smart dampers

NASA Astrophysics Data System (ADS)

Dzung Nguyen, Sy; Choi, Seung-Bok

2012-08-01

This paper proposes a new algorithm, named establishing neuro-fuzzy system (ENFS), to identify dynamic characteristics of smart dampers such as magnetorheological (MR) and electrorheological (ER) dampers. In the ENFS, data clustering is performed based on the proposed algorithm named partitioning data space (PDS). Firstly, the PDS builds data clusters in joint input-output data space with appropriate constraints. The role of these constraints is to create reasonable data distribution in clusters. The ENFS then uses these clusters to perform the following tasks. Firstly, the fuzzy sets expressing characteristics of data clusters are established. The structure of the fuzzy sets is adjusted to be suitable for features of the data set. Secondly, an appropriate structure of neuro-fuzzy (NF) expressed by an optimal number of labeled data clusters and the fuzzy-set groups is determined. After the ENFS is introduced, its effectiveness is evaluated by a prediction-error-comparative work between the proposed method and some other methods in identifying numerical data sets such as ‘daily data of stock A’, or in identifying a function. The ENFS is then applied to identify damping force characteristics of the smart dampers. In order to evaluate the effectiveness of the ENFS in identifying the damping forces of the smart dampers, the prediction errors are presented by comparing with experimental results.

Environment-based selection effects of Planck clusters

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

Kosyra, R.; Gruen, D.; Seitz, S.

2015-07-24

We investigate whether the large-scale structure environment of galaxy clusters imprints a selection bias on Sunyaev–Zel'dovich (SZ) catalogues. Such a selection effect might be caused by line of sight (LoS) structures that add to the SZ signal or contain point sources that disturb the signal extraction in the SZ survey. We use the Planck PSZ1 union catalogue in the Sloan Digital Sky Survey (SDSS) region as our sample of SZ-selected clusters. We calculate the angular two-point correlation function (2pcf) for physically correlated, foreground and background structure in the RedMaPPer SDSS DR8 catalogue with respect to each cluster. We compare ourmore » results with an optically selected comparison cluster sample and with theoretical predictions. In contrast to the hypothesis of no environment-based selection, we find a mean 2pcf for background structures of -0.049 on scales of ≲40 arcmin, significantly non-zero at ~4σ, which means that Planck clusters are more likely to be detected in regions of low background density. We hypothesize this effect arises either from background estimation in the SZ survey or from radio sources in the background. We estimate the defect in SZ signal caused by this effect to be negligibly small, of the order of ~10 -4 of the signal of a typical Planck detection. Analogously, there are no implications on X-ray mass measurements. However, the environmental dependence has important consequences for weak lensing follow up of Planck galaxy clusters: we predict that projection effects account for half of the mass contained within a 15 arcmin radius of Planck galaxy clusters. We did not detect a background underdensity of CMASS LRGs, which also leaves a spatially varying redshift dependence of the Planck SZ selection function as a possible cause for our findings.« less

Thermodynamic stability and structural properties of cluster crystals formed by amphiphilic dendrimers

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

Lenz, Dominic A.; Likos, Christos N.; Blaak, Ronald

We pursue the goal of finding real-world examples of macromolecular aggregates that form cluster crystals, which have been predicted on the basis of coarse-grained, ultrasoft pair potentials belonging to a particular mathematical class [B. M. Mladek et al., Phys. Rev. Lett. 46, 045701 (2006)]. For this purpose, we examine in detail the phase behavior and structural properties of model amphiphilic dendrimers of the second generation by means of monomer-resolved computer simulations. On augmenting the density of these systems, a fluid comprised of clusters that contain several overlapping and penetrating macromolecules is spontaneously formed. Upon further compression of the system, amore » transition to multi-occupancy crystals takes place, the thermodynamic stability of which is demonstrated by means of free-energy calculations, and where the FCC is preferred over the BCC-phase. Contrary to predictions for coarse-grained theoretical models in which the particles interact exclusively by effective pair potentials, the internal degrees of freedom of these molecules cause the lattice constant to be density-dependent. Furthermore, the mechanical stability of monodisperse BCC and FCC cluster crystals is restricted to a bounded region in the plane of cluster occupation number versus density. The structural properties of the dendrimers in the dense crystals, including their overall sizes and the distribution of monomers are also thoroughly analyzed.« less

Insights into geometries, stabilities, electronic structures, reactivity descriptors, and magnetic properties of bimetallic Nim Cun-m (m = 1, 2; n = 3-13) clusters: Comparison with pure copper clusters.

PubMed

Singh, Raman K; Iwasa, Takeshi; Taketsugu, Tetsuya

2018-05-25

A long-range corrected density functional theory (LC-DFT) was applied to study the geometric structures, relative stabilities, electronic structures, reactivity descriptors and magnetic properties of the bimetallic NiCu n -1 and Ni 2 Cu n -2 (n = 3-13) clusters, obtained by doping one or two Ni atoms to the lowest energy structures of Cu n , followed by geometry optimizations. The optimized geometries revealed that the lowest energy structures of the NiCu n -1 and Ni 2 Cu n -2 clusters favor the Ni atom(s) situated at the most highly coordinated position of the host copper clusters. The averaged binding energy, the fragmentation energies and the second-order energy differences signified that the Ni doped clusters can continue to gain an energy during the growth process. The electronic structures revealed that the highest occupied molecular orbital and the lowest unoccupied molecular orbital energies of the LC-DFT are reliable and can be used to predict the vertical ionization potential and the vertical electron affinity of the systems. The reactivity descriptors such as the chemical potential, chemical hardness and electrophilic power, and the reactivity principle such as the minimum polarizability principle are operative for characterizing and rationalizing the electronic structures of these clusters. Moreover, doping of Ni atoms into the copper clusters carry most of the total spin magnetic moment. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.

Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

PubMed

Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

2014-05-01

This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Genome Neighborhood Network Reveals Insights into Enediyne Biosynthesis and Facilitates Prediction and Prioritization for Discovery

PubMed Central

Rudolf, Jeffrey D.; Yan, Xiaohui; Shen, Ben

2015-01-01

The enediynes are one of the most fascinating families of bacterial natural products given their unprecedented molecular architecture and extraordinary cytotoxicity. Enediynes are rare with only 11 structurally characterized members and four additional members isolated in their cycloaromatized form. Recent advances in DNA sequencing have resulted in an explosion of microbial genomes. A virtual survey of the GenBank and JGI genome databases revealed 87 enediyne biosynthetic gene clusters from 78 bacteria strains, implying enediynes are more common than previously thought. Here we report the construction and analysis of an enediyne genome neighborhood network (GNN) as a high-throughput approach to analyze secondary metabolite gene clusters. Analysis of the enediyne GNN facilitated rapid gene cluster annotation, revealed genetic trends in enediyne biosynthetic gene clusters resulting in a simple prediction scheme to determine 9- vs 10-membered enediyne gene clusters, and supported a genomic-based strain prioritization method for enediyne discovery. PMID:26318027

Methanol clusters (CH3OH)n: putative global minimum-energy structures from model potentials and dispersion-corrected density functional theory.

PubMed

Kazachenko, Sergey; Bulusu, Satya; Thakkar, Ajit J

2013-06-14

Putative global minima are reported for methanol clusters (CH3OH)n with n ≤ 15. The predictions are based on global optimization of three intermolecular potential energy models followed by local optimization and single-point energy calculations using two variants of dispersion-corrected density functional theory. Recurring structural motifs include folded and/or twisted rings, folded rings with a short branch, and stacked rings. Many of the larger structures are stabilized by weak C-H···O bonds.

Lattice animals in diffusion limited binary colloidal system

NASA Astrophysics Data System (ADS)

Shireen, Zakiya; Babu, Sujin B.

2017-08-01

In a soft matter system, controlling the structure of the amorphous materials has been a key challenge. In this work, we have modeled irreversible diffusion limited cluster aggregation of binary colloids, which serves as a model for chemical gels. Irreversible aggregation of binary colloidal particles leads to the formation of a percolating cluster of one species or both species which are also called bigels. Before the formation of the percolating cluster, the system forms a self-similar structure defined by a fractal dimension. For a one component system when the volume fraction is very small, the clusters are far apart from each other and the system has a fractal dimension of 1.8. Contrary to this, we will show that for the binary system, we observe the presence of lattice animals which has a fractal dimension of 2 irrespective of the volume fraction. When the clusters start inter-penetrating, we observe a fractal dimension of 2.5, which is the same as in the case of the one component system. We were also able to predict the formation of bigels using a simple inequality relation. We have also shown that the growth of clusters follows the kinetic equations introduced by Smoluchowski for diffusion limited cluster aggregation. We will also show that the chemical distance of a cluster in the flocculation regime will follow the same scaling law as predicted for the lattice animals. Further, we will also show that irreversible binary aggregation comes under the universality class of the percolation theory.

Distribution and cluster analysis of predicted intrinsically disordered protein Pfam domains

PubMed Central

Williams, Robert W; Xue, Bin; Uversky, Vladimir N; Dunker, A Keith

2013-01-01

The Pfam database groups regions of proteins by how well hidden Markov models (HMMs) can be trained to recognize similarities among them. Conservation pressure is probably in play here. The Pfam seed training set includes sequence and structure information, being drawn largely from the PDB. A long standing hypothesis among intrinsically disordered protein (IDP) investigators has held that conservation pressures are also at play in the evolution of different kinds of intrinsic disorder, but we find that predicted intrinsic disorder (PID) is not always conserved across Pfam domains. Here we analyze distributions and clusters of PID regions in 193024 members of the version 23.0 Pfam seed database. To include the maximum information available for proteins that remain unfolded in solution, we employ the 10 linearly independent Kidera factors1–3 for the amino acids, combined with PONDR4 predictions of disorder tendency, to transform the sequences of these Pfam members into an 11 column matrix where the number of rows is the length of each Pfam region. Cluster analyses of the set of all regions, including those that are folded, show 6 groupings of domains. Cluster analyses of domains with mean VSL2b scores greater than 0.5 (half predicted disorder or more) show at least 3 separated groups. It is hypothesized that grouping sets into shorter sequences with more uniform length will reveal more information about intrinsic disorder and lead to more finely structured and perhaps more accurate predictions. HMMs could be trained to include this information. PMID:28516017

Revealing how network structure affects accuracy of link prediction

NASA Astrophysics Data System (ADS)

Yang, Jin-Xuan; Zhang, Xiao-Dong

2017-08-01

Link prediction plays an important role in network reconstruction and network evolution. The network structure affects the accuracy of link prediction, which is an interesting problem. In this paper we use common neighbors and the Gini coefficient to reveal the relation between them, which can provide a good reference for the choice of a suitable link prediction algorithm according to the network structure. Moreover, the statistical analysis reveals correlation between the common neighbors index, Gini coefficient index and other indices to describe the network structure, such as Laplacian eigenvalues, clustering coefficient, degree heterogeneity, and assortativity of network. Furthermore, a new method to predict missing links is proposed. The experimental results show that the proposed algorithm yields better prediction accuracy and robustness to the network structure than existing currently used methods for a variety of real-world networks.

Locating Bound Structures in the Accelerating Universe

NASA Astrophysics Data System (ADS)

Pearson, David; Batuski, D. J.

2013-01-01

Given the overwhelming evidence of the universe’s accelerating expansion, the question of what structures are gravitationally bound becomes one of utmost interest. Dunner et al. 2006 (D06) and Busha et al. 2003 (B03) set out to answer this question analytically, and they arrived at fairly different answers owing to the differences in their assumptions of velocities at the present epoch. Applying their criteria to different superclusters, it’s possible to make predictions about what structures may be bound. We apply the criteria of D06 and B03 to the Aquarius, Microscopium, Corona Borealis, and Shapley superclusters to make predictions about what structures might be bound and compare with the results of simple N-body simulations to determine which method is a better predictor and to determine the likelihood that parts or all of the superclusters listed above are bound. We find that D06 tend to predict more structure to be bound than B03, and the results of the N-body simulations usually lie somewhere in between the two sets of predictions. Observational evidence, and simulation data suggests that pairs of clusters in Aquarius and Microscopium are gravitationally bound, and that Shapley contains a large complex of clusters that are bound, along with some additional bound pairs. The likelihood that any of the clusters in Corona Borealis are bound to one another is very small, contrary to the claims of Small et al. 1998, who claimed that the entire supercluster is likely gravitationally bound. Busha M. T., Adams F. C., Wechsler R. H., Evrard A. E., 2003, ApJ, 596, 713 Dunner R., Araya P. A., Meza A., Reisenegger A., 2006, MNRAS, 306, 803 Small T. A., Ma C., Sargent W. L. W., Hamilton D., 1998, ApJ, 492, 45

Modelling the Tox21 10 K chemical profiles for in vivo toxicity prediction and mechanism characterization

PubMed Central

Huang, Ruili; Xia, Menghang; Sakamuru, Srilatha; Zhao, Jinghua; Shahane, Sampada A.; Attene-Ramos, Matias; Zhao, Tongan; Austin, Christopher P.; Simeonov, Anton

2016-01-01

Target-specific, mechanism-oriented in vitro assays post a promising alternative to traditional animal toxicology studies. Here we report the first comprehensive analysis of the Tox21 effort, a large-scale in vitro toxicity screening of chemicals. We test ∼10,000 chemicals in triplicates at 15 concentrations against a panel of nuclear receptor and stress response pathway assays, producing more than 50 million data points. Compound clustering by structure similarity and activity profile similarity across the assays reveals structure–activity relationships that are useful for the generation of mechanistic hypotheses. We apply structural information and activity data to build predictive models for 72 in vivo toxicity end points using a cluster-based approach. Models based on in vitro assay data perform better in predicting human toxicity end points than animal toxicity, while a combination of structural and activity data results in better models than using structure or activity data alone. Our results suggest that in vitro activity profiles can be applied as signatures of compound mechanism of toxicity and used in prioritization for more in-depth toxicological testing. PMID:26811972

The velocity field of clusters of galaxies within 100 megaparsecs. II - Northern clusters

NASA Technical Reports Server (NTRS)

Mould, J. R.; Akeson, R. L.; Bothun, G. D.; Han, M.; Huchra, J. P.; Roth, J.; Schommer, R. A.

1993-01-01

Distances and peculiar velocities for galaxies in eight clusters and groups have been determined by means of the near-infrared Tully-Fisher relation. With the possible exception of a group halfway between us and the Hercules Cluster, we observe peculiar velocities of the same order as the measuring errors of about 400 km/s. The present sample is drawn from the northern Galactic hemisphere and delineates a quiet region in the Hubble flow. This contrasts with the large-scale flows seen in the Hydra-Centaurus and Perseus-Pisces regions. We compare the observed peculiar velocities with predictions based upon the gravity field inferred from the IRAS redshift survey. The differences between the observed and predicted peculiar motions are generally small, except near dense structures, where the observed motions exceed the predictions by significant amounts. Kinematic models of the velocity field are also compared with the data. We cannot distinguish between parameterized models with a great attractor or models with a bulk flow.

Examining the relationship between coping strategies and suicidal desire in a sample of United States military personnel.

PubMed

Khazem, Lauren R; Law, Keyne C; Green, Bradley A; Anestis, Michael D

2015-02-01

Suicidal desire in the military has been previously examined through the lens of the Interpersonal-Psychological Theory of Suicide (IPTS). However, no research has examined the impact of specific coping strategies on perceived burdensomeness, thwarted belongingness, and suicidal ideation in a large population of individuals serving in the US military. Furthermore, the factor structure of previously utilized coping clusters did not apply to our sample of military personnel. Therefore, we found a three-factor solution to be tested in this sample. We hypothesized that specific types of coping behavior clusters (Adaptive and Maladaptive) would predict both IPTS constructs and suicidal ideation. Results indicated that Adaptive and Maladaptive coping clusters predicted the IPTS constructs in the hypothesized directions. However, only the Maladaptive cluster predicted suicidal ideation. These findings implicate the need for further research and suicide prevention efforts focusing on coping strategies, specifically those that are maladaptive in nature, in relation to suicidal ideation in military members. Copyright © 2014 Elsevier Inc. All rights reserved.

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces

DOE PAGES

Bordner, Andrew J.; Gorin, Andrey A.

2008-05-12

Here, protein-protein interactions are ubiquitous and essential for cellular processes. High-resolution X-ray crystallographic structures of protein complexes can elucidate the details of their function and provide a basis for many computational and experimental approaches. Here we demonstrate that existing annotations of protein complexes, including those provided by the Protein Data Bank (PDB) itself, contain a significant fraction of incorrect annotations. Results: We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster ismore » relevant based on a diverse set of properties; and (4) finally combining these scores for each entry in order to predict the complex structure. Unlike previous annotation methods, consistent prediction of complexes with identical or almost identical protein content is insured. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions.« less

Synthesis of borophenes: Anisotropic, two-dimensional boron polymorphs.

PubMed

Mannix, Andrew J; Zhou, Xiang-Feng; Kiraly, Brian; Wood, Joshua D; Alducin, Diego; Myers, Benjamin D; Liu, Xiaolong; Fisher, Brandon L; Santiago, Ulises; Guest, Jeffrey R; Yacaman, Miguel Jose; Ponce, Arturo; Oganov, Artem R; Hersam, Mark C; Guisinger, Nathan P

2015-12-18

At the atomic-cluster scale, pure boron is markedly similar to carbon, forming simple planar molecules and cage-like fullerenes. Theoretical studies predict that two-dimensional (2D) boron sheets will adopt an atomic configuration similar to that of boron atomic clusters. We synthesized atomically thin, crystalline 2D boron sheets (i.e., borophene) on silver surfaces under ultrahigh-vacuum conditions. Atomic-scale characterization, supported by theoretical calculations, revealed structures reminiscent of fused boron clusters with multiple scales of anisotropic, out-of-plane buckling. Unlike bulk boron allotropes, borophene shows metallic characteristics that are consistent with predictions of a highly anisotropic, 2D metal. Copyright © 2015, American Association for the Advancement of Science.

Self-consistent clustering analysis: an efficient multiscale scheme for inelastic heterogeneous materials

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

Liu, Z.; Bessa, M. A.; Liu, W.K.

A predictive computational theory is shown for modeling complex, hierarchical materials ranging from metal alloys to polymer nanocomposites. The theory can capture complex mechanisms such as plasticity and failure that span across multiple length scales. This general multiscale material modeling theory relies on sound principles of mathematics and mechanics, and a cutting-edge reduced order modeling method named self-consistent clustering analysis (SCA) [Zeliang Liu, M.A. Bessa, Wing Kam Liu, “Self-consistent clustering analysis: An efficient multi-scale scheme for inelastic heterogeneous materials,” Comput. Methods Appl. Mech. Engrg. 306 (2016) 319–341]. SCA reduces by several orders of magnitude the computational cost of micromechanical andmore » concurrent multiscale simulations, while retaining the microstructure information. This remarkable increase in efficiency is achieved with a data-driven clustering method. Computationally expensive operations are performed in the so-called offline stage, where degrees of freedom (DOFs) are agglomerated into clusters. The interaction tensor of these clusters is computed. In the online or predictive stage, the Lippmann-Schwinger integral equation is solved cluster-wise using a self-consistent scheme to ensure solution accuracy and avoid path dependence. To construct a concurrent multiscale model, this scheme is applied at each material point in a macroscale structure, replacing a conventional constitutive model with the average response computed from the microscale model using just the SCA online stage. A regularized damage theory is incorporated in the microscale that avoids the mesh and RVE size dependence that commonly plagues microscale damage calculations. The SCA method is illustrated with two cases: a carbon fiber reinforced polymer (CFRP) structure with the concurrent multiscale model and an application to fatigue prediction for additively manufactured metals. For the CFRP problem, a speed up estimated to be about 43,000 is achieved by using the SCA method, as opposed to FE2, enabling the solution of an otherwise computationally intractable problem. The second example uses a crystal plasticity constitutive law and computes the fatigue potency of extrinsic microscale features such as voids. This shows that local stress and strain are capture sufficiently well by SCA. This model has been incorporated in a process-structure-properties prediction framework for process design in additive manufacturing.« less

Atomic-scale structure and electronic properties of GaN/GaAs superlattices

NASA Astrophysics Data System (ADS)

Goldman, R. S.; Feenstra, R. M.; Briner, B. G.; O'Steen, M. L.; Hauenstein, R. J.

1996-12-01

We have investigated the atomic-scale structure and electronic properties of GaN/GaAs superlattices produced by nitridation of a molecular beam epitaxially grown GaAs surface. Using cross-sectional scanning tunneling microscopy (STM) and spectroscopy, we show that the nitrided layers are laterally inhomogeneous, consisting of groups of atomic-scale defects and larger clusters. Analysis of x-ray diffraction data in terms of fractional area of clusters (determined by STM), reveals a cluster lattice constant similar to bulk GaN. In addition, tunneling spectroscopy on the defects indicates a conduction band state associated with an acceptor level of NAs in GaAs. Therefore, we identify the clusters and defects as nearly pure GaN and NAs, respectively. Together, the results reveal phase segregation in these arsenide/nitride structures, in agreement with the large miscibility gap predicted for GaAsN.

Identifying Few-Molecule Water Clusters with High Precision on Au(111) Surface.

PubMed

Dong, Anning; Yan, Lei; Sun, Lihuan; Yan, Shichao; Shan, Xinyan; Guo, Yang; Meng, Sheng; Lu, Xinghua

2018-06-01

Revealing the nature of a hydrogen-bond network in water structures is one of the imperative objectives of science. With the use of a low-temperature scanning tunneling microscope, water clusters on a Au(111) surface were directly imaged with molecular resolution by a functionalized tip. The internal structures of the water clusters as well as the geometry variations with the increase of size were identified. In contrast to a buckled water hexamer predicted by previous theoretical calculations, our results present deterministic evidence for a flat configuration of water hexamers on Au(111), corroborated by density functional theory calculations with properly implemented van der Waals corrections. The consistency between the experimental observations and improved theoretical calculations not only renders the internal structures of absorbed water clusters unambiguously, but also directly manifests the crucial role of van der Waals interactions in constructing water-solid interfaces.

The formation and structure of Fe-Mn-Ni-Si solute clusters and G-phase precipitates in steels

NASA Astrophysics Data System (ADS)

King, D. J. M.; Burr, P. A.; Middleburgh, S. C.; Whiting, T. M.; Burke, M. G.; Wenman, M. R.

2018-07-01

Solute clustering and G-phase precipitation cause hardening phenomena observed in some low alloy and stainless steels, respectively. Density functional theory was used to investigate the energetic driving force for the formation of these precipitates, capturing temperature effects through analysis of the system's configurational and magnetic entropies. It is shown that enrichment of Mn, Ni and Si is thermodynamically favourable compared to the dilute ferrite matrix of a typical A508 low alloy steel. We predict the ordered G-phase to form preferentially rather than a structure with B2-type ordering when the Fe content of the system falls below 10-18 at. %. The B2 → G-phase transformation is predicted to occur spontaneously when vacancies are introduced into the B2 structure in the absence of Fe.

B38: an all-boron fullerene analogue

NASA Astrophysics Data System (ADS)

Lv, Jian; Wang, Yanchao; Zhu, Li; Ma, Yanming

2014-09-01

Fullerene-like structures formed by elements other than carbon have long been sought. Finding all-boron (B) fullerene-like structures is challenging due to the geometrical frustration arising from competitions among various structural motifs. We report here the prediction of a B38 fullerene analogue found through first-principles swarm structure searching calculations. The structure is highly symmetric and consists of 56 triangles and four hexagons, which provide an optimal void in the center of the cage. Energetically, it is more favorable than the planar and tubular structures, and possesses an unusually high chemical stability: a large energy gap (~2.25 eV) and a high double aromaticity, superior to those of most aromatic quasi-planar B12 and double-ring B20 clusters. Our findings represent a key step forward towards to the understanding of structures of medium-sized B clusters and map out the experimental direction of the synthesis of an all-B fullerene analogue.Fullerene-like structures formed by elements other than carbon have long been sought. Finding all-boron (B) fullerene-like structures is challenging due to the geometrical frustration arising from competitions among various structural motifs. We report here the prediction of a B38 fullerene analogue found through first-principles swarm structure searching calculations. The structure is highly symmetric and consists of 56 triangles and four hexagons, which provide an optimal void in the center of the cage. Energetically, it is more favorable than the planar and tubular structures, and possesses an unusually high chemical stability: a large energy gap (~2.25 eV) and a high double aromaticity, superior to those of most aromatic quasi-planar B12 and double-ring B20 clusters. Our findings represent a key step forward towards to the understanding of structures of medium-sized B clusters and map out the experimental direction of the synthesis of an all-B fullerene analogue. Electronic supplementary information (ESI) available. See DOI: 10.1039/c4nr01846j

[Comparative analysis of clustered regularly interspaced short palindromic repeats (CRISPRs) loci in the genomes of halophilic archaea].

PubMed

Zhang, Fan; Zhang, Bing; Xiang, Hua; Hu, Songnian

2009-11-01

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) is a widespread system that provides acquired resistance against phages in bacteria and archaea. Here we aim to genome-widely analyze the CRISPR in extreme halophilic archaea, of which the whole genome sequences are available at present time. We used bioinformatics methods including alignment, conservation analysis, GC content and RNA structure prediction to analyze the CRISPR structures of 7 haloarchaeal genomes. We identified the CRISPR structures in 5 halophilic archaea and revealed a conserved palindromic motif in the flanking regions of these CRISPR structures. In addition, we found that the repeat sequences of large CRISPR structures in halophilic archaea were greatly conserved, and two types of predicted RNA secondary structures derived from the repeat sequences were likely determined by the fourth base of the repeat sequence. Our results support the proposal that the leader sequence may function as recognition site by having palindromic structures in flanking regions, and the stem-loop secondary structure formed by repeat sequences may function in mediating the interaction between foreign genetic elements and CAS-encoded proteins.

Discovery of new enzymes and metabolic pathways by using structure and genome context.

PubMed

Zhao, Suwen; Kumar, Ritesh; Sakai, Ayano; Vetting, Matthew W; Wood, B McKay; Brown, Shoshana; Bonanno, Jeffery B; Hillerich, Brandan S; Seidel, Ronald D; Babbitt, Patricia C; Almo, Steven C; Sweedler, Jonathan V; Gerlt, John A; Cronan, John E; Jacobson, Matthew P

2013-10-31

Assigning valid functions to proteins identified in genome projects is challenging: overprediction and database annotation errors are the principal concerns. We and others are developing computation-guided strategies for functional discovery with 'metabolite docking' to experimentally derived or homology-based three-dimensional structures. Bacterial metabolic pathways often are encoded by 'genome neighbourhoods' (gene clusters and/or operons), which can provide important clues for functional assignment. We recently demonstrated the synergy of docking and pathway context by 'predicting' the intermediates in the glycolytic pathway in Escherichia coli. Metabolite docking to multiple binding proteins and enzymes in the same pathway increases the reliability of in silico predictions of substrate specificities because the pathway intermediates are structurally similar. Here we report that structure-guided approaches for predicting the substrate specificities of several enzymes encoded by a bacterial gene cluster allowed the correct prediction of the in vitro activity of a structurally characterized enzyme of unknown function (PDB 2PMQ), 2-epimerization of trans-4-hydroxy-L-proline betaine (tHyp-B) and cis-4-hydroxy-D-proline betaine (cHyp-B), and also the correct identification of the catabolic pathway in which Hyp-B 2-epimerase participates. The substrate-liganded pose predicted by virtual library screening (docking) was confirmed experimentally. The enzymatic activities in the predicted pathway were confirmed by in vitro assays and genetic analyses; the intermediates were identified by metabolomics; and repression of the genes encoding the pathway by high salt concentrations was established by transcriptomics, confirming the osmolyte role of tHyp-B. This study establishes the utility of structure-guided functional predictions to enable the discovery of new metabolic pathways.

Genetic effect of interleukin-1 beta (C-511T) polymorphism on the structural covariance network and white matter integrity in Alzheimer's disease.

PubMed

Huang, Chi-Wei; Hsu, Shih-Wei; Tsai, Shih-Jen; Chen, Nai-Ching; Liu, Mu-En; Lee, Chen-Chang; Huang, Shu-Hua; Chang, Weng-Neng; Chang, Ya-Ting; Tsai, Wan-Chen; Chang, Chiung-Chih

2017-01-18

Inflammatory processes play a pivotal role in the degenerative process of Alzheimer's disease. In humans, a biallelic (C/T) polymorphism in the promoter region (position-511) (rs16944) of the interleukin-1 beta gene has been significantly associated with differences in the secretory capacity of interleukin-1 beta. In this study, we investigated whether this functional polymorphism mediates the brain networks in patients with Alzheimer's disease. We enrolled a total of 135 patients with Alzheimer's disease (65 males, 70 females), and investigated their gray matter structural covariance networks using 3D T1 magnetic resonance imaging and their white matter macro-structural integrities using fractional anisotropy. The patients were classified into two genotype groups: C-carriers (n = 108) and TT-carriers (n = 27), and the structural covariance networks were constructed using seed-based analysis focusing on the default mode network medial temporal or dorsal medial subsystem, salience network and executive control network. Neurobehavioral scores were used as the major outcome factors for clinical correlations. There were no differences between the two genotype groups in the cognitive test scores, seed, or peak cluster volumes and white matter fractional anisotropy. The covariance strength showing C-carriers > TT-carriers was the entorhinal-cingulum axis. There were two peak clusters (Brodmann 6 and 10) in the salience network and four peak clusters (superior prefrontal, precentral, fusiform, and temporal) in the executive control network that showed C-carriers < TT-carriers in covariance strength. The salience network and executive control network peak clusters in the TT group and the default mode network peak clusters in the C-carriers strongly predicted the cognitive test scores. Interleukin-1 beta C-511 T polymorphism modulates the structural covariance strength on the anterior brain network and entorhinal-interconnected network which were independent of the white matter tract integrity. Depending on the specific C-511 T genotype, different network clusters could predict the cognitive tests.

Quantum chemical ab initio prediction of proton exchange barriers between CH{sub 4} and different H-zeolites

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

Tuma, Christian; Sauer, Joachim, E-mail: js@chemie.hu-berlin.de

2015-09-14

A hybrid MP2:DFT (second-order Møller–Plesset perturbation theory–density functional theory) method that combines MP2 calculations for cluster models with DFT calculations for the full periodic structure is used to localize minima and transition structures for proton jumps at different Brønsted sites in different frameworks (chabazite, faujasite, ferrierite, and ZSM-5) and at different crystallographic positions of a given framework. The MP2 limit for the periodic structures is obtained by extrapolating the results of a series of cluster models of increasing size. A coupled-cluster (CCSD(T)) correction to MP2 energies is calculated for cluster models consisting of three tetrahedra. For the adsorption energies, thismore » difference is small, between 0.1 and 0.9 kJ/mol, but for the intrinsic proton exchange barriers, this difference makes a significant (10.85 ± 0.25 kJ/mol) and almost constant contribution across different systems. The total values of the adsorption energies vary between 22 and 34 kJ/mol, whereas the total proton exchange energy barriers fall in the narrow range of 152–156 kJ/mol. After adding nuclear motion contributions (harmonic approximation, 298 K), intrinsic enthalpy barriers between 134 and 141 kJ/mol and apparent energy barriers between 105 and 118 kJ/mol are predicted for the different sites examined for the different frameworks. These predictions are consistent with experimental results available for faujasite, ferrierite, and ZSM-5.« less

New insights from cluster analysis methods for RNA secondary structure prediction

PubMed Central

Rogers, Emily; Heitsch, Christine

2016-01-01

A widening gap exists between the best practices for RNA secondary structure prediction developed by computational researchers and the methods used in practice by experimentalists. Minimum free energy (MFE) predictions, although broadly used, are outperformed by methods which sample from the Boltzmann distribution and data mine the results. In particular, moving beyond the single structure prediction paradigm yields substantial gains in accuracy. Furthermore, the largest improvements in accuracy and precision come from viewing secondary structures not at the base pair level but at lower granularity/higher abstraction. This suggests that random errors affecting precision and systematic ones affecting accuracy are both reduced by this “fuzzier” view of secondary structures. Thus experimentalists who are willing to adopt a more rigorous, multilayered approach to secondary structure prediction by iterating through these levels of granularity will be much better able to capture fundamental aspects of RNA base pairing. PMID:26971529

ClusPro: an automated docking and discrimination method for the prediction of protein complexes.

PubMed

Comeau, Stephen R; Gatchell, David W; Vajda, Sandor; Camacho, Carlos J

2004-01-01

Predicting protein interactions is one of the most challenging problems in functional genomics. Given two proteins known to interact, current docking methods evaluate billions of docked conformations by simple scoring functions, and in addition to near-native structures yield many false positives, i.e. structures with good surface complementarity but far from the native. We have developed a fast algorithm for filtering docked conformations with good surface complementarity, and ranking them based on their clustering properties. The free energy filters select complexes with lowest desolvation and electrostatic energies. Clustering is then used to smooth the local minima and to select the ones with the broadest energy wells-a property associated with the free energy at the binding site. The robustness of the method was tested on sets of 2000 docked conformations generated for 48 pairs of interacting proteins. In 31 of these cases, the top 10 predictions include at least one near-native complex, with an average RMSD of 5 A from the native structure. The docking and discrimination method also provides good results for a number of complexes that were used as targets in the Critical Assessment of PRedictions of Interactions experiment. The fully automated docking and discrimination server ClusPro can be found at http://structure.bu.edu

Structural changes in white matter are uniquely related to children’s reading development

PubMed Central

Myers, Chelsea A.; Vandermosten, Maaike; Farris, Emily A.; Hancock, Roeland; Gimenez, Paul; Black, Jessica M.; Casto, Brandi; Drahos, Miroslav; Tumber, Mandeep; Hendren, Robert L.; Hulme, Charles; Hoeft, Fumiko

2014-01-01

This study examined whether variations in brain development between kindergarten and Grade 3 predicted individual differences in reading ability at the latter time point. Structural MRI measurements indicated that increases in volume of two left temporo-parietal white matter clusters are unique predictors of reading outcome at Grade 3. Using diffusion MRI, the larger of these two clusters was identified as a location where fibers of the long segment of arcuate fasciculus and superior corona radiata intersect, and the smaller cluster as the posterior arcuate fasciculus. Bias-free regression analyses using regions-of-interest from prior literature revealed white matter volume changes in temporo-parietal white matter, together with preliteracy measures, predicted 56% of the variance in reading outcomes. Our findings demonstrate the important contribution of developmental differences in areas of left dorsal white matter, often implicated in phonological processing, as a sensitive early biomarker for later reading abilities, and by extension, reading difficulties. PMID:25212581

A new clustering of antibody CDR loop conformations

PubMed Central

North, Benjamin; Lehmann, Andreas; Dunbrack, Roland L.

2010-01-01

Previous analyses of the complementarity determining regions (CDRs) of antibodies have focused on a small number of “canonical” conformations for each loop. This is primarily the result of the work of Chothia and colleagues, most recently in 1997. Because of the widespread utility of antibodies, we have revisited the clustering of conformations of the six CDR loops with the much larger amount of structural information currently available. In this work, we were careful to use a high-quality data set by eliminating low-resolution structures and CDRs with high B-factors or high conformational energies. We used a distance function based on directional statistics and an effective clustering algorithm using affinity propagation. With this data set of over 300 non-redundant antibody structures, we were able to cover 28 CDR-length combinations (e.g., L1 length 11, or “L1-11” in our nomenclature) for L1, L2, L3, H1 and H2. The Chothia analysis covered only 20 CDR-lengths. Only four of these had more than one conformational cluster, of which two could easily be distinguished by gene source (mouse/human; κ/λ) and one purely by the presence and positions of Pro residues (L3-9). Thus using the Chothia analysis does not require the complicated set of “structure-determining residues” that is often assumed. Of our 28 CDR-lengths, 15 of them have multiple conformational clusters including ten for which Chothia had only one canonical class. We have a total of 72 clusters for the non-H3 CDRs; approximately 85% of the non-H3 sequences can be assigned to a conformational cluster based on gene source and/or sequence. We found that earlier predictions of “bulged” vs. “non-bulged” conformations based on the presence or absence of anchor residues Arg/Lys94 and Asp101 of H3 have not held up, since all four combinations lead to a majority of conformations that are bulged. Thus the earlier analyses have been significantly enhanced by the increased data. We believe the new classification will lead to improved methods for antibody structure prediction and design. PMID:21035459

Predictive coupled-cluster isomer orderings for some Si{sub n}C{sub m} (m, n ≤ 12) clusters: A pragmatic comparison between DFT and complete basis limit coupled-cluster benchmarks

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

Byrd, Jason N., E-mail: byrd.jason@ensco.com; ENSCO, Inc., 4849 North Wickham Road, Melbourne, Florida 32940; Lutz, Jesse J., E-mail: jesse.lutz.ctr@afit.edu

The accurate determination of the preferred Si{sub 12}C{sub 12} isomer is important to guide experimental efforts directed towards synthesizing SiC nano-wires and related polymer structures which are anticipated to be highly efficient exciton materials for the opto-electronic devices. In order to definitively identify preferred isomeric structures for silicon carbon nano-clusters, highly accurate geometries, energies, and harmonic zero point energies have been computed using coupled-cluster theory with systematic extrapolation to the complete basis limit for set of silicon carbon clusters ranging in size from SiC{sub 3} to Si{sub 12}C{sub 12}. It is found that post-MBPT(2) correlation energy plays a significant rolemore » in obtaining converged relative isomer energies, suggesting that predictions using low rung density functional methods will not have adequate accuracy. Utilizing the best composite coupled-cluster energy that is still computationally feasible, entailing a 3-4 SCF and coupled-cluster theory with singles and doubles extrapolation with triple-ζ (T) correlation, the closo Si{sub 12}C{sub 12} isomer is identified to be the preferred isomer in the support of previous calculations [X. F. Duan and L. W. Burggraf, J. Chem. Phys. 142, 034303 (2015)]. Additionally we have investigated more pragmatic approaches to obtaining accurate silicon carbide isomer energies, including the use of frozen natural orbital coupled-cluster theory and several rungs of standard and double-hybrid density functional theory. Frozen natural orbitals as a way to compute post-MBPT(2) correlation energy are found to be an excellent balance between efficiency and accuracy.« less

Applying the Coupled-Cluster Ansatz to Solids and Surfaces in the Thermodynamic Limit

NASA Astrophysics Data System (ADS)

Gruber, Thomas; Liao, Ke; Tsatsoulis, Theodoros; Hummel, Felix; Grüneis, Andreas

2018-04-01

Modern electronic structure theories can predict and simulate a wealth of phenomena in surface science and solid-state physics. In order to allow for a direct comparison with experiment, such ab initio predictions have to be made in the thermodynamic limit, substantially increasing the computational cost of many-electron wave-function theories. Here, we present a method that achieves thermodynamic limit results for solids and surfaces using the "gold standard" coupled cluster ansatz of quantum chemistry with unprecedented efficiency. We study the energy difference between carbon diamond and graphite crystals, adsorption energies of water on h -BN, as well as the cohesive energy of the Ne solid, demonstrating the increased efficiency and accuracy of coupled cluster theory for solids and surfaces.

A multi-populations multi-strategies differential evolution algorithm for structural optimization of metal nanoclusters

NASA Astrophysics Data System (ADS)

Fan, Tian-E.; Shao, Gui-Fang; Ji, Qing-Shuang; Zheng, Ji-Wen; Liu, Tun-dong; Wen, Yu-Hua

2016-11-01

Theoretically, the determination of the structure of a cluster is to search the global minimum on its potential energy surface. The global minimization problem is often nondeterministic-polynomial-time (NP) hard and the number of local minima grows exponentially with the cluster size. In this article, a multi-populations multi-strategies differential evolution algorithm has been proposed to search the globally stable structure of Fe and Cr nanoclusters. The algorithm combines a multi-populations differential evolution with an elite pool scheme to keep the diversity of the solutions and avoid prematurely trapping into local optima. Moreover, multi-strategies such as growing method in initialization and three differential strategies in mutation are introduced to improve the convergence speed and lower the computational cost. The accuracy and effectiveness of our algorithm have been verified by comparing the results of Fe clusters with Cambridge Cluster Database. Meanwhile, the performance of our algorithm has been analyzed by comparing the convergence rate and energy evaluations with the classical DE algorithm. The multi-populations, multi-strategies mutation and growing method in initialization in our algorithm have been considered respectively. Furthermore, the structural growth pattern of Cr clusters has been predicted by this algorithm. The results show that the lowest-energy structure of Cr clusters contains many icosahedra, and the number of the icosahedral rings rises with increasing size.

Structure determination in 55-atom Li-Na and Na-K nanoalloys.

PubMed

Aguado, Andrés; López, José M

2010-09-07

The structure of 55-atom Li-Na and Na-K nanoalloys is determined through combined empirical potential (EP) and density functional theory (DFT) calculations. The potential energy surface generated by the EP model is extensively sampled by using the basin hopping technique, and a wide diversity of structural motifs is reoptimized at the DFT level. A composition comparison technique is applied at the DFT level in order to make a final refinement of the global minimum structures. For dilute concentrations of one of the alkali atoms, the structure of the pure metal cluster, namely, a perfect Mackay icosahedron, remains stable, with the minority component atoms entering the host cluster as substitutional impurities. At intermediate concentrations, the nanoalloys adopt instead a core-shell polyicosahedral (p-Ih) packing, where the element with smaller atomic size and larger cohesive energy segregates to the cluster core. The p-Ih structures show a marked prolate deformation, in agreement with the predictions of jelliumlike models. The electronic preference for a prolate cluster shape, which is frustrated in the 55-atom pure clusters due to the icosahedral geometrical shell closing, is therefore realized only in the 55-atom nanoalloys. An analysis of the electronic densities of states suggests that photoelectron spectroscopy would be a sufficiently sensitive technique to assess the structures of nanoalloys with fixed size and varying compositions.

A combined experimental and theoretical spectroscopic protocol for determination of the structure of heterogeneous catalysts: developing the information content of the resonance Raman spectra of M1 MoVOx † †Electronic supplementary information (ESI) available. See DOI: 10.1039/c7sc01771e Click here for additional data file.

PubMed Central

Kubas, Adam; Noak, Johannes

2017-01-01

Absorption and multiwavelength resonance Raman spectroscopy are widely used to investigate the electronic structure of transition metal centers in coordination compounds and extended solid systems. In combination with computational methodologies that have predictive accuracy, they define powerful protocols to study the spectroscopic response of catalytic materials. In this work, we study the absorption and resonance Raman spectra of the M1 MoVOx catalyst. The spectra were calculated by time-dependent density functional theory (TD-DFT) in conjunction with the independent mode displaced harmonic oscillator model (IMDHO), which allows for detailed bandshape predictions. For this purpose cluster models with up to 9 Mo and V metallic centers are considered to represent the bulk structure of MoVOx. Capping hydrogens were used to achieve valence saturation at the edges of the cluster models. The construction of model structures was based on a thorough bonding analysis which involved conventional DFT and local coupled cluster (DLPNO-CCSD(T)) methods. Furthermore the relationship of cluster topology to the computed spectral features is discussed in detail. It is shown that due to the local nature of the involved electronic transitions, band assignment protocols developed for molecular systems can be applied to describe the calculated spectral features of the cluster models as well. The present study serves as a reference for future applications of combined experimental and computational protocols in the field of solid-state heterogeneous catalysis. PMID:28989667

Discovery of a Giant, 200,000 Light-year Long Wave Rolling Through the Perseus Galaxy Cluster

NASA Astrophysics Data System (ADS)

Walker, Stephen; Hlavacek-Larrondo, Julie; Gendon-Marsolais, Marie-Lou; Fabian, Andy; Intema, Huib; Sanders, Jeremy

2018-01-01

Deep observations of nearby galaxy clusters with Chandra have revealed concave 'bay' structures in a number of clusters (Perseus, Centaurus and Abell 1795), which have similar X-ray and radio properties. These bays have all the properties of cold fronts brought about by minor mergers causing the cluster gas to slosh around in the gravitational potential. At these cold fronts the temperature rises and density falls sharply. Unusually, in the case of the 'bays' these cold fronts are concave rather than convex. By comparing to simulations of gas sloshing, we find that the bay in the Perseus cluster bears a striking resemblance in its size, location and thermal structure, to a giant (≈50 kpc) wave resulting from Kelvin-Helmholtz instabilities. Such instabilities are commonly seen on far smaller scales in nature, from billow clouds in the Earth's atmosphere, to structures in the cloud belts of gas giant planets. Here we are witnessing this phenomenon on the largest scale ever seen, twice the size of the Milky Way galaxy. The morphology of this structure seen in Perseus can be compared to simulations to put constraints on the initial magnetic pressure throughout the overall cluster before the sloshing occurs. Such Kelvin-Helmholtz features in galaxy clusters have long been predicted by simulations, but it is only now that they have finally been observed, opening up an important new way to probe the physics of the intracluster medium, which contains the majority of the baryonic matter in clusters.

KELVIN-HELMHOLTZ INSTABILITIES AT THE SLOSHING COLD FRONTS IN THE VIRGO CLUSTER AS A MEASURE FOR THE EFFECTIVE INTRACLUSTER MEDIUM VISCOSITY

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

Roediger, E.; Kraft, R. P.; Forman, W. R.

2013-02-10

Sloshing cold fronts (CFs) arise from minor merger triggered gas sloshing. Their detailed structure depends on the properties of the intracluster medium (ICM): hydrodynamical simulations predict the CFs to be distorted by Kelvin-Helmholtz instabilities (KHIs), but aligned magnetic fields, viscosity, or thermal conduction can suppress the KHIs. Thus, observing the detailed structure of sloshing CFs can be used to constrain these ICM properties. Both smooth and distorted sloshing CFs have been observed, indicating that the KHI is suppressed in some clusters, but not in all. Consequently, we need to address at least some sloshing clusters individually before drawing general conclusionsmore » about the ICM properties. We present the first detailed attempt to constrain the ICM properties in a specific cluster from the structure of its sloshing CF. Proximity and brightness make the Virgo Cluster an ideal target. We combine observations and Virgo-specific hydrodynamical sloshing simulations. Here, we focus on a Spitzer-like temperature-dependent viscosity as a mechanism to suppress the KHI, but discuss the alternative mechanisms in detail. We identify the CF at 90 kpc north and northeast of the Virgo center as the best location in the cluster to observe a possible KHI suppression. For viscosities {approx}> 10% of the Spitzer value KHIs at this CF are suppressed. We describe in detail the observable signatures at low and high viscosities, i.e., in the presence or the absence of KHIs. We find indications for a low ICM viscosity in archival XMM-Newton data and demonstrate the detectability of the predicted features in deep Chandra observations.« less

CONFOLD2: improved contact-driven ab initio protein structure modeling.

PubMed

Adhikari, Badri; Cheng, Jianlin

2018-01-25

Contact-guided protein structure prediction methods are becoming more and more successful because of the latest advances in residue-residue contact prediction. To support contact-driven structure prediction, effective tools that can quickly build tertiary structural models of good quality from predicted contacts need to be developed. We develop an improved contact-driven protein modelling method, CONFOLD2, and study how it may be effectively used for ab initio protein structure prediction with predicted contacts as input. It builds models using various subsets of input contacts to explore the fold space under the guidance of a soft square energy function, and then clusters the models to obtain the top five models. CONFOLD2 obtains an average reconstruction accuracy of 0.57 TM-score for the 150 proteins in the PSICOV contact prediction dataset. When benchmarked on the CASP11 contacts predicted using CONSIP2 and CASP12 contacts predicted using Raptor-X, CONFOLD2 achieves a mean TM-score of 0.41 on both datasets. CONFOLD2 allows to quickly generate top five structural models for a protein sequence when its secondary structures and contacts predictions at hand. The source code of CONFOLD2 is publicly available at https://github.com/multicom-toolbox/CONFOLD2/ .

Structure-related clustering of gene expression fingerprints of thp-1 cells exposed to smaller polycyclic aromatic hydrocarbons.

PubMed

Wan, B; Yarbrough, J W; Schultz, T W

2008-01-01

This study was undertaken to test the hypothesis that structurally similar PAHs induce similar gene expression profiles. THP-1 cells were exposed to a series of 12 selected PAHs at 50 microM for 24 hours and gene expressions profiles were analyzed using both unsupervised and supervised methods. Clustering analysis of gene expression profiles revealed that the 12 tested chemicals were grouped into five clusters. Within each cluster, the gene expression profiles are more similar to each other than to the ones outside the cluster. One-methylanthracene and 1-methylfluorene were found to have the most similar profiles; dibenzothiophene and dibenzofuran were found to share common profiles with fluorine. As expression pattern comparisons were expanded, similarity in genomic fingerprint dropped off dramatically. Prediction analysis of microarrays (PAM) based on the clustering pattern generated 49 predictor genes that can be used for sample discrimination. Moreover, a significant analysis of Microarrays (SAM) identified 598 genes being modulated by tested chemicals with a variety of biological processes, such as cell cycle, metabolism, and protein binding and KEGG pathways being significantly (p < 0.05) affected. It is feasible to distinguish structurally different PAHs based on their genomic fingerprints, which are mechanism based.

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers.

PubMed

Cao, Han; Ng, Marcus C K; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W I

2017-09-01

[Formula: see text]-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM . Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

NASA Astrophysics Data System (ADS)

Cao, Han; Ng, Marcus C. K.; Jusoh, Siti Azma; Tai, Hio Kuan; Siu, Shirley W. I.

2017-09-01

α-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577-585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at https://cbbio.cis.umac.mo/TMDIM. Website is implemented in PHP, MySQL and Apache, with all major browsers supported.

Synoptic Factors Affecting Structure Predictability of Hurricane Alex (2016)

NASA Astrophysics Data System (ADS)

Gonzalez-Aleman, J. J.; Evans, J. L.; Kowaleski, A. M.

2016-12-01

On January 7, 2016, a disturbance formed over the western North Atlantic basin. After undergoing tropical transition, the system became the first hurricane of 2016 - and the first North Atlantic hurricane to form in January since 1938. Already an extremely rare hurricane event, Alex then underwent extratropical transition [ET] just north of the Azores Islands. We examine the factors affecting Alex's structural evolution through a new technique called path-clustering. In this way, 51 ensembles from the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System (ECMWF-EPS) are grouped based on similarities in the storm's path through the Cyclone Phase Space (CPS). The differing clusters group various possible scenarios of structural development represented in the ensemble forecasts. As a result, it is possible to shed light on the role of the synoptic scale in changing the structure of this hurricane in the midlatitudes through intercomparison of the most "realistic" forecast of the evolution of Alex and the other physically plausible modes of its development.

Cluster formation in precompound nuclei in the time-dependent framework

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

Schuetrumpf, B.; Nazarewicz, W.

Background: Modern applications of nuclear time-dependent density functional theory (TDDFT) are often capable of providing quantitative description of heavy ion reactions. However, the structures of precompound (preequilibrium, prefission) states produced in heavy ion reactions are difficult to assess theoretically in TDDFT as the single-particle density alone is a weak indicator of shell structure and cluster states. Purpose: We employ the time-dependent nucleon localization function (NLF) to reveal the structure of precompound states in nuclear reactions involving light and medium-mass ions. We primarily focus on spin saturated systems with N = Z . Furthermore, we study reactions with oxygen and carbonmore » ions, for which some experimental evidence for α clustering in precompound states exists. Method: We utilize the symmetry-free TDDFT approach with the Skyrme energy density functional UNEDF1 and compute the time-dependent NLFs to describe 16O + 16O, 40Ca + 16O, 40Ca + 40Ca , and 16,18O + 12C collisions at energies above the Coulomb barrier. Results: We show that NLFs reveal a variety of time-dependent modes involving cluster structures. For instance, the 16O + 16O collision results in a vibrational mode of a quasimolecular α - 12 C - 12 C- α state. For heavier ions, a variety of cluster configurations are predicted. For the collision of 16,18O + 12C, we showed that the precompound system has a tendency to form α clusters. This result supports the experimental findings that the presence of cluster structures in the projectile and target nuclei gives rise to strong entrance channel effects and enhanced α emission. Conclusion: The time-dependent nucleon localization measure is a very good indicator of cluster structures in complex precompound states formed in heavy-ion fusion reactions. Finally, the localization reveals the presence of collective vibrations involving cluster structures, which dominate the initial dynamics of the fusing system.« less

Cluster formation in precompound nuclei in the time-dependent framework

DOE PAGES

Schuetrumpf, B.; Nazarewicz, W.

2017-12-15

Background: Modern applications of nuclear time-dependent density functional theory (TDDFT) are often capable of providing quantitative description of heavy ion reactions. However, the structures of precompound (preequilibrium, prefission) states produced in heavy ion reactions are difficult to assess theoretically in TDDFT as the single-particle density alone is a weak indicator of shell structure and cluster states. Purpose: We employ the time-dependent nucleon localization function (NLF) to reveal the structure of precompound states in nuclear reactions involving light and medium-mass ions. We primarily focus on spin saturated systems with N = Z . Furthermore, we study reactions with oxygen and carbonmore » ions, for which some experimental evidence for α clustering in precompound states exists. Method: We utilize the symmetry-free TDDFT approach with the Skyrme energy density functional UNEDF1 and compute the time-dependent NLFs to describe 16O + 16O, 40Ca + 16O, 40Ca + 40Ca , and 16,18O + 12C collisions at energies above the Coulomb barrier. Results: We show that NLFs reveal a variety of time-dependent modes involving cluster structures. For instance, the 16O + 16O collision results in a vibrational mode of a quasimolecular α - 12 C - 12 C- α state. For heavier ions, a variety of cluster configurations are predicted. For the collision of 16,18O + 12C, we showed that the precompound system has a tendency to form α clusters. This result supports the experimental findings that the presence of cluster structures in the projectile and target nuclei gives rise to strong entrance channel effects and enhanced α emission. Conclusion: The time-dependent nucleon localization measure is a very good indicator of cluster structures in complex precompound states formed in heavy-ion fusion reactions. Finally, the localization reveals the presence of collective vibrations involving cluster structures, which dominate the initial dynamics of the fusing system.« less

Cluster formation in precompound nuclei in the time-dependent framework

NASA Astrophysics Data System (ADS)

Schuetrumpf, B.; Nazarewicz, W.

2017-12-01

Background: Modern applications of nuclear time-dependent density functional theory (TDDFT) are often capable of providing quantitative description of heavy ion reactions. However, the structures of precompound (preequilibrium, prefission) states produced in heavy ion reactions are difficult to assess theoretically in TDDFT as the single-particle density alone is a weak indicator of shell structure and cluster states. Purpose: We employ the time-dependent nucleon localization function (NLF) to reveal the structure of precompound states in nuclear reactions involving light and medium-mass ions. We primarily focus on spin saturated systems with N =Z . Furthermore, we study reactions with oxygen and carbon ions, for which some experimental evidence for α clustering in precompound states exists. Method: We utilize the symmetry-free TDDFT approach with the Skyrme energy density functional UNEDF1 and compute the time-dependent NLFs to describe 16O + 16O,40Ca + 16O, 40Ca + 40Ca, and O,1816 + 12C collisions at energies above the Coulomb barrier. Results: We show that NLFs reveal a variety of time-dependent modes involving cluster structures. For instance, the 16O + 16O collision results in a vibrational mode of a quasimolecular α - 12C - 12C-α state. For heavier ions, a variety of cluster configurations are predicted. For the collision of O,1816 + 12C, we showed that the precompound system has a tendency to form α clusters. This result supports the experimental findings that the presence of cluster structures in the projectile and target nuclei gives rise to strong entrance channel effects and enhanced α emission. Conclusion: The time-dependent nucleon localization measure is a very good indicator of cluster structures in complex precompound states formed in heavy-ion fusion reactions. The localization reveals the presence of collective vibrations involving cluster structures, which dominate the initial dynamics of the fusing system.

Long-range correlations improve understanding of the influence of network structure on contact dynamics.

PubMed

Peyrard, N; Dieckmann, U; Franc, A

2008-05-01

Models of infectious diseases are characterized by a phase transition between extinction and persistence. A challenge in contemporary epidemiology is to understand how the geometry of a host's interaction network influences disease dynamics close to the critical point of such a transition. Here we address this challenge with the help of moment closures. Traditional moment closures, however, do not provide satisfactory predictions close to such critical points. We therefore introduce a new method for incorporating longer-range correlations into existing closures. Our method is technically simple, remains computationally tractable and significantly improves the approximation's performance. Our extended closures thus provide an innovative tool for quantifying the influence of interaction networks on spatially or socially structured disease dynamics. In particular, we examine the effects of a network's clustering coefficient, as well as of new geometrical measures, such as a network's square clustering coefficients. We compare the relative performance of different closures from the literature, with or without our long-range extension. In this way, we demonstrate that the normalized version of the Bethe approximation-extended to incorporate long-range correlations according to our method-is an especially good candidate for studying influences of network structure. Our numerical results highlight the importance of the clustering coefficient and the square clustering coefficient for predicting disease dynamics at low and intermediate values of transmission rate, and demonstrate the significance of path redundancy for disease persistence.

From sticky-hard-sphere to Lennard-Jones-type clusters

NASA Astrophysics Data System (ADS)

Trombach, Lukas; Hoy, Robert S.; Wales, David J.; Schwerdtfeger, Peter

2018-04-01

A relation MSHS →LJ between the set of nonisomorphic sticky-hard-sphere clusters MSHS and the sets of local energy minima ML J of the (m ,n ) -Lennard-Jones potential Vmn LJ(r ) =ɛ/n -m [m r-n-n r-m] is established. The number of nonisomorphic stable clusters depends strongly and nontrivially on both m and n and increases exponentially with increasing cluster size N for N ≳10 . While the map from MSHS→MSHS →LJ is noninjective and nonsurjective, the number of Lennard-Jones structures missing from the map is relatively small for cluster sizes up to N =13 , and most of the missing structures correspond to energetically unfavorable minima even for fairly low (m ,n ) . Furthermore, even the softest Lennard-Jones potential predicts that the coordination of 13 spheres around a central sphere is problematic (the Gregory-Newton problem). A more realistic extended Lennard-Jones potential chosen from coupled-cluster calculations for a rare gas dimer leads to a substantial increase in the number of nonisomorphic clusters, even though the potential curve is very similar to a (6,12)-Lennard-Jones potential.

From sticky-hard-sphere to Lennard-Jones-type clusters.

PubMed

Trombach, Lukas; Hoy, Robert S; Wales, David J; Schwerdtfeger, Peter

2018-04-01

A relation M_{SHS→LJ} between the set of nonisomorphic sticky-hard-sphere clusters M_{SHS} and the sets of local energy minima M_{LJ} of the (m,n)-Lennard-Jones potential V_{mn}^{LJ}(r)=ɛ/n-m[mr^{-n}-nr^{-m}] is established. The number of nonisomorphic stable clusters depends strongly and nontrivially on both m and n and increases exponentially with increasing cluster size N for N≳10. While the map from M_{SHS}→M_{SHS→LJ} is noninjective and nonsurjective, the number of Lennard-Jones structures missing from the map is relatively small for cluster sizes up to N=13, and most of the missing structures correspond to energetically unfavorable minima even for fairly low (m,n). Furthermore, even the softest Lennard-Jones potential predicts that the coordination of 13 spheres around a central sphere is problematic (the Gregory-Newton problem). A more realistic extended Lennard-Jones potential chosen from coupled-cluster calculations for a rare gas dimer leads to a substantial increase in the number of nonisomorphic clusters, even though the potential curve is very similar to a (6,12)-Lennard-Jones potential.

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.

Search for α-Cluster Structure in Exotic Nuclei with the Prototype Active-Target Time-Projection Chamber

NASA Astrophysics Data System (ADS)

Fritsch, A.; Ayyad, Y.; Bazin, D.; Beceiro-Novo, S.; Bradt, J.; Carpenter, L.; Cortesi, M.; Mittig, W.; Suzuki, D.; Ahn, T.; Kolata, J. J.; Becchetti, F. D.; Howard, A. M.

2016-03-01

Some exotic nuclei appear to exhibit α-cluster structure. While various theoretical models currently describe such clustering, more experimental data are needed to constrain model predictions. The Prototype Active-Target Time-Projection Chamber (PAT-TPC) has low-energy thresholds for charged-particle decay and a high luminosity due to its thick gaseous active target volume, making it well-suited to search for low-energy α-cluster reactions. Radioactive-ion beams produced by the TwinSol facility at the University of Notre Dame were delivered to the PAT-TPC to study nuclei including 14C and 14O via α-resonant scattering. Differential cross sections and excitation functions were measured. Preliminary results from our recent experiments will be presented. This work is supported by the U.S. National Science Foundation.

Hydration of a Large Anionic Charge Distribution - Naphthalene-Water Cluster Anions

NASA Astrophysics Data System (ADS)

Weber, J. Mathias; Adams, Christopher L.

2010-06-01

We report the infrared spectra of anionic clusters of naphthalene with up to three water molecules. Comparison of the experimental infrared spectra with theoretically predicted spectra from quantum chemistry calculations allow conclusions regarding the structures of the clusters under study. The first water molecule forms two hydrogen bonds with the π electron system of the naphthalene moiety. Subsequent water ligands interact with both the naphthalene and the other water ligands to form hydrogen bonded networks, similar to other hydrated anion clusters. Naphthalene-water anion clusters illustrate how water interacts with negative charge delocalized over a large π electron system. The clusters are interesting model systems that are discussed in the context of wetting of graphene surfaces and polyaromatic hydrocarbons.

H/C atomic ratio as a smart linkage between pyrolytic temperatures, aromatic clusters and sorption properties of biochars derived from diverse precursory materials

PubMed Central

Xiao, Xin; Chen, Zaiming; Chen, Baoliang

2016-01-01

Biochar is increasingly gaining attention due to multifunctional roles in soil amelioration, pollution mitigation and carbon sequestration. It is a significant challenge to compare the reported results from world-wide labs regarding the structure and sorption of biochars derived from various precursors under different pyrolytic conditions due to a lack of a simple linkage. By combining the published works on various biochars, we established a quantitative relationship between H/C atomic ratio and pyrolytic temperature (T), aromatic structure, and sorption properties for naphthalene and phenanthrene. A reverse sigmoid shape between T and the H/C ratio was observed, which was independent of the precursors of biochars, including the ash contents. Linear correlations of Freundlich parameters (N, log Kf) and sorption amount (log Qe, log QA) with H/C ratios were found. A rectangle-like model was proposed to predict the aromatic cluster sizes of biochars from their H/C ratios, and then a good structure-sorption relationship was derived. These quantitative relationships indicate that the H/C atomic ratio is a universal linkage to predict pyrolytic temperatures, aromatic cluster sizes, and sorption characteristics. This study would guide the global study of biochars toward being comparable, and then the development of the structure-sorption relationships will benefit the structural design and environmental application of biochars. PMID:26940984

Alternative states of a semiarid grassland ecosystem: implications for ecosystem services

USGS Publications Warehouse

Miller, Mark E.; Belote, R. Travis; Bowker, Matthew A.; Garman, Steven L.

2011-01-01

Ecosystems can shift between alternative states characterized by persistent differences in structure, function, and capacity to provide ecosystem services valued by society. We examined empirical evidence for alternative states in a semiarid grassland ecosystem where topographic complexity and contrasting management regimes have led to spatial variations in levels of livestock grazing. Using an inventory data set, we found that plots (n = 72) cluster into three groups corresponding to generalized alternative states identified in an a priori conceptual model. One cluster (biocrust) is notable for high coverage of a biological soil crust functional group in addition to vascular plants. Another (grass-bare) lacks biological crust but retains perennial grasses at levels similar to the biocrust cluster. A third (annualized-bare) is dominated by invasive annual plants. Occurrence of grass-bare and annualized-bare conditions in areas where livestock have been excluded for over 30 years demonstrates the persistence of these states. Significant differences among all three clusters were found for percent bare ground, percent total live cover, and functional group richness. Using data for vegetation structure and soil erodibility, we also found large among-cluster differences in average levels of dust emissions predicted by a wind-erosion model. Predicted emissions were highest for the annualized-bare cluster and lowest for the biocrust cluster, which was characterized by zero or minimal emissions even under conditions of extreme wind. Results illustrate potential trade-offs among ecosystem services including livestock production, soil retention, carbon storage, and biodiversity conservation. Improved understanding of these trade-offs may assist ecosystem managers when evaluating alternative management strategies.

Selected AB4 2−/− (A = C, Si, Ge; B = Al, Ga, In) ions: a battle between covalency and aromaticity, and prediction of square planar Si in SiIn4 2−/−†

PubMed Central

Alexandrova, Anastassia N.; Nayhouse, Michael J.; Huynh, Mioy T.; Kuo, Jonathan L.; Melkonian, Arek V.; Chavez, Gerardo; Hernando, Nina M.; Kowal, Matthew D.; Liu, Chi-Ping

2012-01-01

CAl4 2−/− (D4h, 1A1g) is a cluster ion that has been established to be planar, aromatic, and contain a tetracoordinate planar C atom. Valence isoelectronic substitution of C with Si and Ge in this cluster leads to a radical change of structure toward distorted pentagonal species. We find that this structural change goes together with the cluster acquiring partial covalency of bonding between Si/Ge and Al4, facilitated by hybridization of the atomic orbitals (AOs). Counter intuitively, for the AAl4 2−/− (A = C, Si, Ge) clusters, hybridization in the dopant atom is strengthened from C, to Si, and to Ge, even though typically AOs are more likely to hybridize if they are closer in energy (i.e. in earlier elements in the Periodic Table). The trend is explained by the better overlap of the hybrids of the heavier dopants with the orbitals of Al4. From the thus understood trend, it is inferred that covalency in such clusters can be switched off, by varying the relative sizes of the AOs of the main element and the dopant. Using this mechanism, we then successfully killed covalency in Si, and predicted a new aromatic cluster ion containing a tetracoordinate square planar Si, SiIn4 2−/−. PMID:22868353

Density-based clustering of small peptide conformations sampled from a molecular dynamics simulation.

PubMed

Kim, Minkyoung; Choi, Seung-Hoon; Kim, Junhyoung; Choi, Kihang; Shin, Jae-Min; Kang, Sang-Kee; Choi, Yun-Jaie; Jung, Dong Hyun

2009-11-01

This study describes the application of a density-based algorithm to clustering small peptide conformations after a molecular dynamics simulation. We propose a clustering method for small peptide conformations that enables adjacent clusters to be separated more clearly on the basis of neighbor density. Neighbor density means the number of neighboring conformations, so if a conformation has too few neighboring conformations, then it is considered as noise or an outlier and is excluded from the list of cluster members. With this approach, we can easily identify clusters in which the members are densely crowded in the conformational space, and we can safely avoid misclustering individual clusters linked by noise or outliers. Consideration of neighbor density significantly improves the efficiency of clustering of small peptide conformations sampled from molecular dynamics simulations and can be used for predicting peptide structures.

Infrared absorption of methanol-water clusters (CH3OH)n(H2O), n = 1-4, recorded with the VUV-ionization/IR-depletion technique

NASA Astrophysics Data System (ADS)

Lee, Yu-Fang; Kelterer, Anne-Marie; Matisz, Gergely; Kunsági-Máté, Sándor; Chung, Chao-Yu; Lee, Yuan-Pern

2017-04-01

We recorded infrared (IR) spectra in the CH- and OH-stretching regions of size-selected clusters of methanol (M) with one water molecule (W), represented as MnW, n = 1-4, in a pulsed supersonic jet using the photoionization/IR-depletion technique. Vacuum ultraviolet emission at 118 nm served as the source of ionization in a time-of-flight mass spectrometer to detect clusters MnW as protonated forms Mn-1WH+. The variations in intensities of Mn-1WH+ were monitored as the wavelength of the IR laser light was tuned across the range 2700-3800 cm-1. IR spectra of size-selected clusters were obtained on processing of the observed action spectra of the related cluster-ions according to a mechanism that takes into account the production and loss of each cluster due to IR photodissociation. Spectra of methanol-water clusters in the OH region show significant variations as the number of methanol molecules increases, whereas those in the CH region are similar for all clusters. Scaled harmonic vibrational wavenumbers and relative IR intensities predicted with the M06-2X/aug-cc-pVTZ method for the methanol-water clusters are consistent with our experimental results. For dimers, absorption bands of a structure WM with H2O as a hydrogen-bond donor were observed at 3570, 3682, and 3722 cm-1, whereas weak bands of MW with methanol as a hydrogen-bond donor were observed at 3611 and 3753 cm-1. For M2W, the free OH band of H2O was observed at 3721 cm-1, whereas a broad feature was deconvoluted to three bands near 3425, 3472, and 3536 cm-1, corresponding to the three hydrogen-bonded OH-stretching modes in a cyclic structure. For M3W, the free OH shifted to 3715 cm-1, and the hydrogen-bonded OH-stretching bands became much broader, with a weak feature near 3179 cm-1 corresponding to the symmetric OH-stretching mode of a cyclic structure. For M4W, the observed spectrum agrees unsatisfactorily with predictions for the most stable cyclic structure, indicating significant contributions from branched isomers, which is distinctly different from M5 of which the cyclic form dominates.

Infrared absorption of methanol-water clusters (CH3OH)n(H2O), n = 1-4, recorded with the VUV-ionization/IR-depletion technique.

PubMed

Lee, Yu-Fang; Kelterer, Anne-Marie; Matisz, Gergely; Kunsági-Máté, Sándor; Chung, Chao-Yu; Lee, Yuan-Pern

2017-04-14

We recorded infrared (IR) spectra in the CH- and OH-stretching regions of size-selected clusters of methanol (M) with one water molecule (W), represented as M n W, n = 1-4, in a pulsed supersonic jet using the photoionization/IR-depletion technique. Vacuum ultraviolet emission at 118 nm served as the source of ionization in a time-of-flight mass spectrometer to detect clusters M n W as protonated forms M n-1 WH + . The variations in intensities of M n-1 WH + were monitored as the wavelength of the IR laser light was tuned across the range 2700-3800 cm -1 . IR spectra of size-selected clusters were obtained on processing of the observed action spectra of the related cluster-ions according to a mechanism that takes into account the production and loss of each cluster due to IR photodissociation. Spectra of methanol-water clusters in the OH region show significant variations as the number of methanol molecules increases, whereas those in the CH region are similar for all clusters. Scaled harmonic vibrational wavenumbers and relative IR intensities predicted with the M06-2X/aug-cc-pVTZ method for the methanol-water clusters are consistent with our experimental results. For dimers, absorption bands of a structure WM with H 2 O as a hydrogen-bond donor were observed at 3570, 3682, and 3722 cm -1 , whereas weak bands of MW with methanol as a hydrogen-bond donor were observed at 3611 and 3753 cm -1 . For M 2 W, the free OH band of H 2 O was observed at 3721 cm -1 , whereas a broad feature was deconvoluted to three bands near 3425, 3472, and 3536 cm -1 , corresponding to the three hydrogen-bonded OH-stretching modes in a cyclic structure. For M 3 W, the free OH shifted to 3715 cm -1 , and the hydrogen-bonded OH-stretching bands became much broader, with a weak feature near 3179 cm -1 corresponding to the symmetric OH-stretching mode of a cyclic structure. For M 4 W, the observed spectrum agrees unsatisfactorily with predictions for the most stable cyclic structure, indicating significant contributions from branched isomers, which is distinctly different from M 5 of which the cyclic form dominates.

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

ERIC Educational Resources Information Center

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Ferromagnetic ordering in superatomic solids.

PubMed

Lee, Chul-Ho; Liu, Lian; Bejger, Christopher; Turkiewicz, Ari; Goko, Tatsuo; Arguello, Carlos J; Frandsen, Benjamin A; Cheung, Sky C; Medina, Teresa; Munsie, Timothy J S; D'Ortenzio, Robert; Luke, Graeme M; Besara, Tiglet; Lalancette, Roger A; Siegrist, Theo; Stephens, Peter W; Crowther, Andrew C; Brus, Louis E; Matsuo, Yutaka; Nakamura, Eiichi; Uemura, Yasutomo J; Kim, Philip; Nuckolls, Colin; Steigerwald, Michael L; Roy, Xavier

2014-12-03

In order to realize significant benefits from the assembly of solid-state materials from molecular cluster superatomic building blocks, several criteria must be met. Reproducible syntheses must reliably produce macroscopic amounts of pure material; the cluster-assembled solids must show properties that are more than simply averages of those of the constituent subunits; and rational changes to the chemical structures of the subunits must result in predictable changes in the collective properties of the solid. In this report we show that we can meet these requirements. Using a combination of magnetometry and muon spin relaxation measurements, we demonstrate that crystallographically defined superatomic solids assembled from molecular nickel telluride clusters and fullerenes undergo a ferromagnetic phase transition at low temperatures. Moreover, we show that when we modify the constituent superatoms, the cooperative magnetic properties change in predictable ways.

HotRegion: a database of predicted hot spot clusters.

PubMed

Cukuroglu, Engin; Gursoy, Attila; Keskin, Ozlem

2012-01-01

Hot spots are energetically important residues at protein interfaces and they are not randomly distributed across the interface but rather clustered. These clustered hot spots form hot regions. Hot regions are important for the stability of protein complexes, as well as providing specificity to binding sites. We propose a database called HotRegion, which provides the hot region information of the interfaces by using predicted hot spot residues, and structural properties of these interface residues such as pair potentials of interface residues, accessible surface area (ASA) and relative ASA values of interface residues of both monomer and complex forms of proteins. Also, the 3D visualization of the interface and interactions among hot spot residues are provided. HotRegion is accessible at http://prism.ccbb.ku.edu.tr/hotregion.

DEVELOPMENT OF QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIPS (QSARS) TO PREDICT TOXICITY FOR A VARIETY OF HUMAN AND ECOLOGICAL ENDPOINTS

EPA Science Inventory

In general, the accuracy of a predicted toxicity value increases with increase in similarity between the query chemical and the chemicals used to develop a QSAR model. A toxicity estimation methodology employing this finding has been developed. A hierarchical based clustering t...

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2017-01-01

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

Importance of many-body dispersion and temperature effects on gas-phase gold cluster (meta)stability

NASA Astrophysics Data System (ADS)

Goldsmith, Bryan R.; Gruene, Philipp; Lyon, Jonathan T.; Rayner, David M.; Fielicke, André; Scheffler, Matthias; Ghiringhelli, Luca M.

Gold clusters in the gas phase exhibit many structural isomers that are shown to intercovert frequently, even at room temperature. We performed ab initio replica-exchange molecular dynamics (REMD) calculations on gold clusters (of sizes 5-14 atoms) to identify metastable states and their relative populations at finite temperature, as well as to examine the importance of temperature and van der Waals (vdW) on their isomer energetic ordering. Free energies of the gold cluster isomers are optimally estimated using the Multistate Bennett Acceptance Ratio. The distribution of bond coordination numbers and radius of gyration are used to address the challenge of discriminating isomers along their dynamical trajectories. Dispersion effects are important for stabilizing three-dimensional structures relative to planar structures and brings isomer energetic predictions to closer quantitative agreement compared with RPA@PBE calculations. We find that higher temperatures typically stabilize metastable three-dimensional structures relative to planar/quasiplanar structures. Computed IR spectra of low free energy Au9, Au10, and Au12 isomers are in agreement with experimental spectra obtained by far-IR multiple photon dissociation in a molecular beam at 100 K.

Helix-packing motifs in membrane proteins.

PubMed

Walters, R F S; DeGrado, W F

2006-09-12

The fold of a helical membrane protein is largely determined by interactions between membrane-imbedded helices. To elucidate recurring helix-helix interaction motifs, we dissected the crystallographic structures of membrane proteins into a library of interacting helical pairs. The pairs were clustered according to their three-dimensional similarity (rmsd

Cooperative effects in the structuring of fluoride water clusters: Ab initio hybrid quantum mechanical/molecular mechanical model incorporating polarizable fluctuating charge solvent

NASA Astrophysics Data System (ADS)

Bryce, Richard A.; Vincent, Mark A.; Malcolm, Nathaniel O. J.; Hillier, Ian H.; Burton, Neil A.

1998-08-01

A new hybrid quantum mechanical/molecular mechanical model of solvation is developed and used to describe the structure and dynamics of small fluoride/water clusters, using an ab initio wave function to model the ion and a fluctuating charge potential to model the waters. Appropriate parameters for the water-water and fluoride-water interactions are derived, with the fluoride anion being described by density functional theory and a large Gaussian basis. The role of solvent polarization in determining the structure and energetics of F(H2O)4- clusters is investigated, predicting a slightly greater stability of the interior compared to the surface structure, in agreement with ab initio studies. An extended Lagrangian treatment of the polarizable water, in which the water atomic charges fluctuate dynamically, is used to study the dynamics of F(H2O)4- cluster. A simulation using a fixed solvent charge distribution indicates principally interior, solvated states for the cluster. However, a preponderance of trisolvated configurations is observed using the polarizable model at 300 K, which involves only three direct fluoride-water hydrogen bonds. Ab initio calculations confirm this trisolvated species as a thermally accessible state at room temperature, in addition to the tetrasolvated interior and surface structures. Extension of this polarizable water model to fluoride clusters with five and six waters gave less satisfactory agreement with experimental energies and with ab initio geometries. However, our results do suggest that a quantitative model of solvent polarization is fundamental for an accurate understanding of the properties of anionic water clusters.

A novel polyketide biosynthesis gene cluster is involved in fruiting body morphogenesis in the filamentous fungi Sordaria macrospora and Neurospora crassa.

PubMed

Nowrousian, Minou

2009-04-01

During fungal fruiting body development, hyphae aggregate to form multicellular structures that protect and disperse the sexual spores. Analysis of microarray data revealed a gene cluster strongly upregulated during fruiting body development in the ascomycete Sordaria macrospora. Real time PCR analysis showed that the genes from the orthologous cluster in Neurospora crassa are also upregulated during development. The cluster encodes putative polyketide biosynthesis enzymes, including a reducing polyketide synthase. Analysis of knockout strains of a predicted dehydrogenase gene from the cluster showed that mutants in N. crassa and S. macrospora are delayed in fruiting body formation. In addition to the upregulated cluster, the N. crassa genome comprises another cluster containing a polyketide synthase gene, and five additional reducing polyketide synthase (rpks) genes that are not part of clusters. To study the role of these genes in sexual development, expression of the predicted rpks genes in S. macrospora (five genes) and N. crassa (six genes) was analyzed; all but one are upregulated during sexual development. Analysis of knockout strains for the N. crassa rpks genes showed that one of them is essential for fruiting body formation. These data indicate that polyketides produced by RPKSs are involved in sexual development in filamentous ascomycetes.

Nanoscale alloys and core-shell materials: Model predictions of the nanostructure and mechanical properties

NASA Astrophysics Data System (ADS)

Zhurkin, E. E.; van Hoof, T.; Hou, M.

2007-06-01

Atomic scale modeling methods are used to investigate the relationship between the properties of clusters of nanometer size and the materials that can be synthesized by assembling them. The examples of very different bimetallic systems are used. The first one is the Ni3Al ordered alloy and the second is the AgCo core-shell system. While the Ni3Al cluster assembled materials modeling is already reported in our previous work, here we focus on the prediction of new materials synthesized by low energy deposition and accumulation of AgCo clusters. It is found that the core-shell structure is preserved by deposition with energies typical of low energy cluster beam deposition, although deposition may induce substantial cluster deformation. In contrast with Ni3Al deposited cluster assemblies, no grain boundary between clusters survives deposition and the silver shells merge into a noncrystalline system with a layered structure, in which the fcc Co grains are embedded. To our knowledge, such a material has not yet been synthesized experimentally. Mechanical properties are discussed by confronting the behaviors of Ni3Al and AgCo under the effect of a uniaxial load. To this end, a molecular dynamics scheme is established in view of circumventing rate effects inherent to short term modeling and thereby allowing to examine large plastic deformation mechanisms. Although the mechanisms are different, large plastic deformations are found to improve the elastic properties of both the Ni3Al and AgCo systems by stabilizing their nanostructure. Beyond this improvement, when the load is further increased, the Ni3Al system displays reduced ductility while the AgCo system is superplastic. The superplasticity is explained by the fact that the layered structure of the Ag system is not modified by the deformation. Some coalescence of the Co grains is identified as a geometrical effect and is suggested to be a limiting factor to superplasticity.

Structural, electronic and vibrational properties of small GaxNy (x+y = 2 5) nanoclusters: a B3LYP-DFT study

NASA Astrophysics Data System (ADS)

Yadav, P. S.; Yadav, R. K.; Agrawal, B. K.

2007-02-01

An ab initio study of the stability, structural and electronic properties has been made for 49 gallium nitride nanoclusters, GaxNy (x+y = 2-5). Among the various configurations corresponding to a fixed x+y = n value, the configuration possessing the maximum value of binding energy (BE) is named as the most stable structure. The vibrational and optical properties have been investigated only for the most stable structures. A B3LYP-DFT/6-311G(3df) method has been employed to optimize the geometries of the nanoclusters fully. The binding energies (BEs), highest-occupied and lowest-unoccupied molecular orbital (HOMO-LUMO) gaps and the bond lengths have been obtained for all the clusters. We have considered the zero-point energy (ZPE) corrections ignored by the earlier workers. The adiabatic and vertical ionization potentials (IPs) and electron affinities (EAs), charge on atoms, dipole moments, vibrational frequencies, infrared intensities (IR Int.), relative infrared intensities (Rel. IR Int.) and Raman scattering activities have been investigated for the most stable structures. The configurations containing the N atoms in majority are seen to be the most stable structures. The strong N-N bond has an important role in stabilizing the clusters. For clusters containing one Ga atom and all the others as N atoms, the BE increases monotonically with the number of the N atoms. The HOMO-LUMO gap and IP fluctuate with the cluster size n, having larger values for the clusters containing odd number of N atoms. On the other hand, the EA decreases with the cluster size up to n = 3, and shows slow fluctuations thereafter for the larger clusters. In general, the adiabatic IP (EA) is smaller (greater) than the vertical IP (EA) because of the lower energies of the most stable ground state of the cationic (anionic) clusters. The optical absorption spectrum or electron energy loss spectrum (EELS) is unique for every cluster, and may be used to characterize a specific cluster. All the predicted physical quantities are in good agreement with the experimental data wherever available. The growth of these most stable structures should be possible in experiments.

iDBPs: a web server for the identification of DNA binding proteins.

PubMed

Nimrod, Guy; Schushan, Maya; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2010-03-01

The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. http://idbps.tau.ac.il/

Consequences of localized frustration for the folding mechanism of the IM7 protein

PubMed Central

Sutto, Ludovico; Lätzer, Joachim; Hegler, Joseph A.; Ferreiro, Diego U.; Wolynes, Peter G.

2007-01-01

In the laboratory, IM7 has been found to have an unusual folding mechanism in which an “on-pathway” intermediate with nonnative interactions is formed. We show that this intermediate is a consequence of an unusual cluster of highly frustrated interactions in the native structure. This cluster is involved in the binding of IM7 to its target, Colicin E7. Redesign of residues in this cluster to eliminate frustration is predicted by simulations to lead to faster folding without the population of an intermediate ensemble. PMID:18077415

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.

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

Ceder, Gerbrand

Novel materials are often the enabler for new energy technologies. In ab-initio computational materials science, method are developed to predict the behavior of materials starting from the laws of physics, so that properties can be predicted before compounds have to be synthesized and tested. As such, a virtual materials laboratory can be constructed, saving time and money. The objectives of this program were to develop first-principles theory to predict the structure and thermodynamic stability of materials. Since its inception the program focused on the development of the cluster expansion to deal with the increased complexity of complex oxides. This researchmore » led to the incorporation of vibrational degrees of freedom in ab-initio thermodynamics, developed methods for multi-component cluster expansions, included the explicit configurational degrees of freedom of localized electrons, developed the formalism for stability in aqueous environments, and culminated in the first ever approach to produce exact ground state predictions of the cluster expansion. Many of these methods have been disseminated to the larger theory community through the Materials Project, pymatgen software, or individual codes. We summarize three of the main accomplishments.« less

Construction of crystal structure prototype database: methods and applications.

PubMed

Su, Chuanxun; Lv, Jian; Li, Quan; Wang, Hui; Zhang, Lijun; Wang, Yanchao; Ma, Yanming

2017-04-26

Crystal structure prototype data have become a useful source of information for materials discovery in the fields of crystallography, chemistry, physics, and materials science. This work reports the development of a robust and efficient method for assessing the similarity of structures on the basis of their interatomic distances. Using this method, we proposed a simple and unambiguous definition of crystal structure prototype based on hierarchical clustering theory, and constructed the crystal structure prototype database (CSPD) by filtering the known crystallographic structures in a database. With similar method, a program structure prototype analysis package (SPAP) was developed to remove similar structures in CALYPSO prediction results and extract predicted low energy structures for a separate theoretical structure database. A series of statistics describing the distribution of crystal structure prototypes in the CSPD was compiled to provide an important insight for structure prediction and high-throughput calculations. Illustrative examples of the application of the proposed database are given, including the generation of initial structures for structure prediction and determination of the prototype structure in databases. These examples demonstrate the CSPD to be a generally applicable and useful tool for materials discovery.

Construction of crystal structure prototype database: methods and applications

NASA Astrophysics Data System (ADS)

Su, Chuanxun; Lv, Jian; Li, Quan; Wang, Hui; Zhang, Lijun; Wang, Yanchao; Ma, Yanming

2017-04-01

Crystal structure prototype data have become a useful source of information for materials discovery in the fields of crystallography, chemistry, physics, and materials science. This work reports the development of a robust and efficient method for assessing the similarity of structures on the basis of their interatomic distances. Using this method, we proposed a simple and unambiguous definition of crystal structure prototype based on hierarchical clustering theory, and constructed the crystal structure prototype database (CSPD) by filtering the known crystallographic structures in a database. With similar method, a program structure prototype analysis package (SPAP) was developed to remove similar structures in CALYPSO prediction results and extract predicted low energy structures for a separate theoretical structure database. A series of statistics describing the distribution of crystal structure prototypes in the CSPD was compiled to provide an important insight for structure prediction and high-throughput calculations. Illustrative examples of the application of the proposed database are given, including the generation of initial structures for structure prediction and determination of the prototype structure in databases. These examples demonstrate the CSPD to be a generally applicable and useful tool for materials discovery.

Prediction of tautomer ratios by embedded-cluster integral equation theory

NASA Astrophysics Data System (ADS)

Kast, Stefan M.; Heil, Jochen; Güssregen, Stefan; Schmidt, K. Friedemann

2010-04-01

The "embedded cluster reference interaction site model" (EC-RISM) approach combines statistical-mechanical integral equation theory and quantum-chemical calculations for predicting thermodynamic data for chemical reactions in solution. The electronic structure of the solute is determined self-consistently with the structure of the solvent that is described by 3D RISM integral equation theory. The continuous solvent-site distribution is mapped onto a set of discrete background charges ("embedded cluster") that represent an additional contribution to the molecular Hamiltonian. The EC-RISM analysis of the SAMPL2 challenge set of tautomers proceeds in three stages. Firstly, the group of compounds for which quantitative experimental free energy data was provided was taken to determine appropriate levels of quantum-chemical theory for geometry optimization and free energy prediction. Secondly, the resulting workflow was applied to the full set, allowing for chemical interpretations of the results. Thirdly, disclosure of experimental data for parts of the compounds facilitated a detailed analysis of methodical issues and suggestions for future improvements of the model. Without specifically adjusting parameters, the EC-RISM model yields the smallest value of the root mean square error for the first set (0.6 kcal mol-1) as well as for the full set of quantitative reaction data (2.0 kcal mol-1) among the SAMPL2 participants.

Search for α -Cluster Structure in Exotic Nuclei with the Prototype Active-Target Time-Projection Chamber

NASA Astrophysics Data System (ADS)

Fritsch, A.; Ayyad, Y.; Bazin, D.; Beceiro-Novo, S.; Bradt, J.; Carpenter, L.; Cortesi, M.; Mittig, W.; Suzuki, D.; Ahn, T.; Kolata, J. J.; Howard, A. M.; Becchetti, F. D.; Wolff, M.

Some exotic nuclei appear to exhibit α -cluster structure, which may impact nucleosynthesis reaction rates. While various theoretical models currently describe such clustering, more experimental data are needed to constrain model predictions. The Prototype Active-Target Time-Projection Chamber (PAT-TPC) has low-energy thresholds for charged-particle decay and a high detection efficiency due to its thick gaseous active target volume, making it well-suited to search for low-energy α -cluster reactions. Radioactive-ion beams produced by the TwinSol facility at the University of Notre Dame were delivered to the PAT-TPC to study 14C via α -resonant scattering. Differential cross sections and excitation functions were measured and show evidence of three-body exit channels. Additional data were measured with an updated Micromegas detector more sensitive to three-body decay. Preliminary results are presented.

Soil shapes community structure through fire.

PubMed

Ojeda, Fernando; Pausas, Juli G; Verdú, Miguel

2010-07-01

Recurrent wildfires constitute a major selecting force in shaping the structure of plant communities. At the regional scale, fire favours phenotypic and phylogenetic clustering in Mediterranean woody plant communities. Nevertheless, the incidence of fire within a fire-prone region may present strong variations at the local, landscape scale. This study tests the prediction that woody communities on acid, nutrient-poor soils should exhibit more pronounced phenotypic and phylogenetic clustering patterns than woody communities on fertile soils, as a consequence of their higher flammability and, hence, presumably higher propensity to recurrent fire. Results confirm the predictions and show that habitat filtering driven by fire may be detected even in local communities from an already fire-filtered regional flora. They also provide a new perspective from which to consider a preponderant role of fire as a key evolutionary force in acid, infertile Mediterranean heathlands.

Performance of MDockPP in CAPRI rounds 28-29 and 31-35 including the prediction of water-mediated interactions.

PubMed

Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Ma, Zhiwei; Grinter, Sam Z; Zou, Xiaoqin

2017-03-01

Protein-protein interactions are either through direct contacts between two binding partners or mediated by structural waters. Both direct contacts and water-mediated interactions are crucial to the formation of a protein-protein complex. During the recent CAPRI rounds, a novel parallel searching strategy for predicting water-mediated interactions is introduced into our protein-protein docking method, MDockPP. Briefly, a FFT-based docking algorithm is employed in generating putative binding modes, and an iteratively derived statistical potential-based scoring function, ITScorePP, in conjunction with biological information is used to assess and rank the binding modes. Up to 10 binding modes are selected as the initial protein-protein complex structures for MD simulations in explicit solvent. Water molecules near the interface are clustered based on the snapshots extracted from independent equilibrated trajectories. Then, protein-ligand docking is employed for a parallel search for water molecules near the protein-protein interface. The water molecules generated by ligand docking and the clustered water molecules generated by MD simulations are merged, referred to as the predicted structural water molecules. Here, we report the performance of this protocol for CAPRI rounds 28-29 and 31-35 containing 20 valid docking targets and 11 scoring targets. In the docking experiments, we predicted correct binding modes for nine targets, including one high-accuracy, two medium-accuracy, and six acceptable predictions. Regarding the two targets for the prediction of water-mediated interactions, we achieved models ranked as "excellent" in accordance with the CAPRI evaluation criteria; one of these two targets is considered as a difficult target for structural water prediction. Proteins 2017; 85:424-434. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Comprehensive inventory of protein complexes in the Protein Data Bank from consistent classification of interfaces.

PubMed

Bordner, Andrew J; Gorin, Andrey A

2008-05-12

Protein-protein interactions are ubiquitous and essential for all cellular processes. High-resolution X-ray crystallographic structures of protein complexes can reveal the details of their function and provide a basis for many computational and experimental approaches. Differentiation between biological and non-biological contacts and reconstruction of the intact complex is a challenging computational problem. A successful solution can provide additional insights into the fundamental principles of biological recognition and reduce errors in many algorithms and databases utilizing interaction information extracted from the Protein Data Bank (PDB). We have developed a method for identifying protein complexes in the PDB X-ray structures by a four step procedure: (1) comprehensively collecting all protein-protein interfaces; (2) clustering similar protein-protein interfaces together; (3) estimating the probability that each cluster is relevant based on a diverse set of properties; and (4) combining these scores for each PDB entry in order to predict the complex structure. The resulting clusters of biologically relevant interfaces provide a reliable catalog of evolutionary conserved protein-protein interactions. These interfaces, as well as the predicted protein complexes, are available from the Protein Interface Server (PInS) website (see Availability and requirements section). Our method demonstrates an almost two-fold reduction of the annotation error rate as evaluated on a large benchmark set of complexes validated from the literature. We also estimate relative contributions of each interface property to the accurate discrimination of biologically relevant interfaces and discuss possible directions for further improving the prediction method.

Analyzing ZnO clusters through the density-functional theory.

PubMed

Zaragoza, Irineo-Pedro; Soriano-Agueda, Luis-Antonio; Hernández-Esparza, Raymundo; Vargas, Rubicelia; Garza, Jorge

2018-06-16

The potential energy surface of Zn n O n clusters (n = 2, 4, 6, 8) has been explored by using a simulated annealing method. For n = 2, 4, and 6, the CCSD(T)/TZP method was used as the reference, and from here it is shown that the M06-2X/TZP method gives the lowest deviations over PBE, PBE0, B3LYP, M06, and MP2 methods. Thus, with the M06-2X method we predict isomers of Zn n O n clusters, which coincide with some isomers reported previously. By using the atoms in molecules analysis, possible contacts between Zn and O atoms were found for all structures studied in this article. The bond paths involved in several clusters suggest that Zn n O n clusters can be obtained from the zincite (ZnO crystal), such an observation was confirmed for clusters with n = 2 - 9,18 and 20. The structure with n = 23 was obtained by the procedure presented here, from crystal information, which could be important to confirm experimental data delivered for n = 18 and 23.

Ternary alloy material prediction using genetic algorithm and cluster expansion

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

Chen, Chong

2015-12-01

This thesis summarizes our study on the crystal structures prediction of Fe-V-Si system using genetic algorithm and cluster expansion. Our goal is to explore and look for new stable compounds. We started from the current ten known experimental phases, and calculated formation energies of those compounds using density functional theory (DFT) package, namely, VASP. The convex hull was generated based on the DFT calculations of the experimental known phases. Then we did random search on some metal rich (Fe and V) compositions and found that the lowest energy structures were body centered cube (bcc) underlying lattice, under which we didmore » our computational systematic searches using genetic algorithm and cluster expansion. Among hundreds of the searched compositions, thirteen were selected and DFT formation energies were obtained by VASP. The stability checking of those thirteen compounds was done in reference to the experimental convex hull. We found that the composition, 24-8-16, i.e., Fe 3VSi 2 is a new stable phase and it can be very inspiring to the future experiments.« less

Size resolved infrared spectroscopy of Na(CH3OH)n (n = 4-7) clusters in the OH stretching region: unravelling the interaction of methanol clusters with a sodium atom and the emergence of the solvated electron.

PubMed

Forck, Richard M; Pradzynski, Christoph C; Wolff, Sabine; Ončák, Milan; Slavíček, Petr; Zeuch, Thomas

2012-03-07

Size resolved IR action spectra of neutral sodium doped methanol clusters have been measured using IR excitation modulated photoionisation mass spectroscopy. The Na(CH(3)OH)(n) clusters were generated in a supersonic He seeded expansion of methanol by subsequent Na doping in a pick-up cell. A combined analysis of IR action spectra, IP evolutions and harmonic predictions of IR spectra (using density functional theory) of the most stable structures revealed that for n = 4, 5 structures with an exterior Na atom showing high ionisation potentials (IPs) of ~4 eV dominate, while for n = 6, 7 clusters with lower IPs (~3.2 eV) featuring fully solvated Na atoms and solvated electrons emerge and dominate the IR action spectra. For n = 4 simulations of photoionisation spectra using an ab initio MD approach confirm the dominance of exterior structures and explain the previously reported appearance IP of 3.48 eV by small fractions of clusters with partly solvated Na atoms. Only for this cluster size a shift in the isomer composition with cluster temperature has been observed, which may be related to kinetic stabilisation of less Na solvated clusters at low temperatures. Features of slow fragmentation dynamics of cationic Na(+)(CH(3)OH)(6) clusters have been observed for the photoionisation near the adiabatic limit. This finding points to the relevance of previously proposed non-vertical photoionisation dynamics of this system.

Detecting treatment-subgroup interactions in clustered data with generalized linear mixed-effects model trees.

PubMed

Fokkema, M; Smits, N; Zeileis, A; Hothorn, T; Kelderman, H

2017-10-25

Identification of subgroups of patients for whom treatment A is more effective than treatment B, and vice versa, is of key importance to the development of personalized medicine. Tree-based algorithms are helpful tools for the detection of such interactions, but none of the available algorithms allow for taking into account clustered or nested dataset structures, which are particularly common in psychological research. Therefore, we propose the generalized linear mixed-effects model tree (GLMM tree) algorithm, which allows for the detection of treatment-subgroup interactions, while accounting for the clustered structure of a dataset. The algorithm uses model-based recursive partitioning to detect treatment-subgroup interactions, and a GLMM to estimate the random-effects parameters. In a simulation study, GLMM trees show higher accuracy in recovering treatment-subgroup interactions, higher predictive accuracy, and lower type II error rates than linear-model-based recursive partitioning and mixed-effects regression trees. Also, GLMM trees show somewhat higher predictive accuracy than linear mixed-effects models with pre-specified interaction effects, on average. We illustrate the application of GLMM trees on an individual patient-level data meta-analysis on treatments for depression. We conclude that GLMM trees are a promising exploratory tool for the detection of treatment-subgroup interactions in clustered datasets.

Firefly Algorithm for Structural Search.

PubMed

Avendaño-Franco, Guillermo; Romero, Aldo H

2016-07-12

The problem of computational structure prediction of materials is approached using the firefly (FF) algorithm. Starting from the chemical composition and optionally using prior knowledge of similar structures, the FF method is able to predict not only known stable structures but also a variety of novel competitive metastable structures. This article focuses on the strengths and limitations of the algorithm as a multimodal global searcher. The algorithm has been implemented in software package PyChemia ( https://github.com/MaterialsDiscovery/PyChemia ), an open source python library for materials analysis. We present applications of the method to van der Waals clusters and crystal structures. The FF method is shown to be competitive when compared to other population-based global searchers.

Multi-scale, Hierarchically Nested Young Stellar Structures in LEGUS Galaxies

NASA Astrophysics Data System (ADS)

Thilker, David A.; LEGUS Team

2017-01-01

The study of star formation in galaxies has predominantly been limited to either young stellar clusters and HII regions, or much larger kpc-scale morphological features such as spiral arms. The HST Legacy ExtraGalactic UV Survey (LEGUS) provides a rare opportunity to link these scales in a diverse sample of nearby galaxies and obtain a more comprehensive understanding of their co-evolution for comparison against model predictions. We have utilized LEGUS stellar photometry to identify young, resolved stellar populations belonging to several age bins and then defined nested hierarchical structures as traced by these subsamples of stars. Analagous hierarchical structures were also defined using LEGUS catalogs of unresolved young stellar clusters. We will present our emerging results concerning the physical properties (e.g. area, star counts, stellar mass, star formation rate, ISM characteristics), occupancy statistics (e.g. clusters per substructure versus age and scale, parent/child demographics) and relation to overall galaxy morphology/mass for these building blocks of hierarchical star-forming structure.

Clustering of transmutation elements tantalum, rhenium and osmium in tungsten in a fusion environment

NASA Astrophysics Data System (ADS)

You, Yu-Wei; Kong, Xiang-Shan; Wu, Xuebang; Liu, C. S.; Fang, Q. F.; Chen, J. L.; Luo, G.-N.

2017-08-01

The formation of transmutation solute-rich precipitates has been reported to seriously degrade the mechanical properties of tungsten in a fusion environment. However, the underlying mechanisms controlling the formation of the precipitates are still unknown. In this study, first-principles calculations are therefore performed to systemically determine the stable structures and binding energies of solute clusters in tungsten consisting of tantalum, rhenium and osmium atoms as well as irradiation-induced vacancies. These clusters are known to act as precursors for the formation of precipitates. We find that osmium can easily segregate to form clusters even in defect-free tungsten alloys, whereas extremely high tantalum and rhenium concentrations are required for the formation of clusters. Vacancies greatly facilitate the clustering of rhenium and osmium, while tantalum is an exception. The binding energies of vacancy-osmium clusters are found to be much higher than those of vacancy-tantalum and vacancy-rhenium clusters. Osmium is observed to strongly promote the formation of vacancy-rhenium clusters, while tantalum can suppress the formation of vacancy-rhenium and vacancy-osmium clusters. The local strain and electronic structure are analyzed to reveal the underlying mechanisms governing the cluster formation. Employing the law of mass action, we predict the evolution of the relative concentration of vacancy-rhenium clusters. This work presents a microscopic picture describing the nucleation and growth of solute clusters in tungsten alloys in a fusion reactor environment, and thereby explains recent experimental phenomena.

The expanding universe of thiolated gold nanoclusters and beyond.

PubMed

Jiang, De-en

2013-08-21

Thiolated gold nanoclusters form a universe of their own. Researchers in this field are constantly pushing the boundary of this universe by identifying new compositions and in a few "lucky" cases, solving their structures. Such solved structures, even if there are only few, provide important hints for predicting the many identified compositions that are yet to be crystallized or structure determined. Structure prediction is the most pressing issue for a computational chemist in this field. The success of the density functional theory method in gauging the energetic ordering of isomers for thiolated gold clusters has been truly remarkable, but to predict the most stable structure for a given composition remains a great challenge. In this feature article from a computational chemist's point of view, the author shows how one understands and predicts structures for thiolated gold nanoclusters based on his old and new results. To further entertain the reader, the author also offers several "imaginative" structures, claims, and challenges for this field.

Hydrophobic cluster analysis of G protein-coupled receptors: a powerful tool to derive structural and functional information from 2D-representation of protein sequences.

PubMed

Lentes, K U; Mathieu, E; Bischoff, R; Rasmussen, U B; Pavirani, A

1993-01-01

Current methods for comparative analyses of protein sequences are 1D-alignments of amino acid sequences based on the maximization of amino acid identity (homology) and the prediction of secondary structure elements. This method has a major drawback once the amino acid identity drops below 20-25%, since maximization of a homology score does not take into account any structural information. A new technique called Hydrophobic Cluster Analysis (HCA) has been developed by Lemesle-Varloot et al. (Biochimie 72, 555-574), 1990). This consists of comparing several sequences simultaneously and combining homology detection with secondary structure analysis. HCA is primarily based on the detection and comparison of structural segments constituting the hydrophobic core of globular protein domains, with or without transmembrane domains. We have applied HCA to the analysis of different families of G-protein coupled receptors, such as catecholamine receptors as well as peptide hormone receptors. Utilizing HCA the thrombin receptor, a new and as yet unique member of the family of G-protein coupled receptors, can be clearly classified as being closely related to the family of neuropeptide receptors rather than to the catecholamine receptors for which the shape of the hydrophobic clusters and the length of their third cytoplasmic loop are very different. Furthermore, the potential of HCA to predict relationships between new putative and already characterized members of this family of receptors will be presented.

Spectroscopic and computational studies of ionic clusters as models of solvation and atmospheric reactions

NASA Astrophysics Data System (ADS)

Kuwata, Keith T.

Ionic clusters are useful as model systems for the study of fundamental processes in solution and in the atmosphere. Their structure and reactivity can be studied in detail using vibrational predissociation spectroscopy, in conjunction with high level ab initio calculations. This thesis presents the applications of infrared spectroscopy and computation to a variety of gas-phase cluster systems. A crucial component of the process of stratospheric ozone depletion is the action of polar stratospheric clouds (PSCs) to convert the reservoir species HCl and chlorine nitrate (ClONO2) to photochemically labile compounds. Quantum chemistry was used to explore one possible mechanism by which this activation is effected: Cl- + ClONO2 /to Cl2 + NO3- eqno(1)Correlated ab initio calculations predicted that the direct reaction of chloride ion with ClONO2 is facile, which was confirmed in an experimental kinetics study. In the reaction a weakly bound intermediate Cl2-NO3- is formed, with ~70% of the charge localized on the nitrate moiety. This enables the Cl2-NO3- cluster to be well solvated even in bulk solution, allowing (1) to be facile on PSCs. Quantum chemistry was also applied to the hydration of nitrosonium ion (NO+), an important process in the ionosphere. The calculations, in conjunction with an infrared spectroscopy experiment, revealed the structure of the gas-phase clusters NO+(H2O)n. The large degree of covalent interaction between NO+ and the lone pairs of the H2O ligands is contrasted with the weak electrostatic bonding between iodide ion and H2O. Finally, the competition between ion solvation and solvent self-association is explored for the gas-phase clusters Cl/-(H2O)n and Cl-(NH3)n. For the case of water, vibrational predissociation spectroscopy reveals less hydrogen bonding among H2O ligands than predicted by ab initio calculations. Nevertheless, for n /ge 5, cluster structure is dominated by water-water interactions, with Cl- only partially solvated by the water cluster. Preliminary infrared spectra and computations on Cl- (NH3)n indicate that NH3 preferentially binds to Cl- ion instead of forming inter-solvent networks.

Prediction of Fracture Behavior in Rock and Rock-like Materials Using Discrete Element Models

NASA Astrophysics Data System (ADS)

Katsaga, T.; Young, P.

2009-05-01

The study of fracture initiation and propagation in heterogeneous materials such as rock and rock-like materials are of principal interest in the field of rock mechanics and rock engineering. It is crucial to study and investigate failure prediction and safety measures in civil and mining structures. Our work offers a practical approach to predict fracture behaviour using discrete element models. In this approach, the microstructures of materials are presented through the combination of clusters of bonded particles with different inter-cluster particle and bond properties, and intra-cluster bond properties. The geometry of clusters is transferred from information available from thin sections, computed tomography (CT) images and other visual presentation of the modeled material using customized AutoCAD built-in dialog- based Visual Basic Application. Exact microstructures of the tested sample, including fractures, faults, inclusions and void spaces can be duplicated in the discrete element models. Although the microstructural fabrics of rocks and rock-like structures may have different scale, fracture formation and propagation through these materials are alike and will follow similar mechanics. Synthetic material provides an excellent condition for validating the modelling approaches, as fracture behaviours are known with the well-defined composite's properties. Calibration of the macro-properties of matrix material and inclusions (aggregates), were followed with the overall mechanical material responses calibration by adjusting the interfacial properties. The discrete element model predicted similar fracture propagation features and path as that of the real sample material. The path of the fractures and matrix-inclusion interaction was compared using computed tomography images. Initiation and fracture formation in the model and real material were compared using Acoustic Emission data. Analysing the temporal and spatial evolution of AE events, collected during the sample testing, in relation to the CT images allows the precise reconstruction of the failure sequence. Our proposed modelling approach illustrates realistic fracture formation and growth predictions at different loading conditions.

Nuclear quantum effects in water clusters: the role of the molecular flexibility.

PubMed

González, Briesta S; Noya, Eva G; Vega, Carlos; Sesé, Luis M

2010-02-25

With the objective of establishing the importance of water flexibility in empirical models which explicitly include nuclear quantum effects, we have carried out path integral Monte Carlo simulations in water clusters with up to seven molecules. Two recently developed models have been used for comparison: the rigid TIP4PQ/2005 and the flexible q-TIP4P/F models, both inspired by the rigid TIP4P/2005 model. To obtain a starting configuration for our simulations, we have located the global minima for the rigid TIP4P/2005 and TIP4PQ/2005 models and for the flexible q-TIP4P/F model. All the structures are similar to those predicted by the rigid TIP4P potential showing that the charge distribution mainly determines the global minimum structure. For the flexible q-TIP4P/F model, we have studied the geometrical distortion upon isotopic substitution by studying tritiated water clusters. Our results show that tritiated water clusters exhibit an r(OT) distance shorter than the r(OH) distance in water clusters, not significant changes in the Phi(HOH) angle, and a lower average dipole moment than water clusters. We have also carried out classical simulations with the rigid TIP4PQ/2005 model showing that the rotational kinetic energy is greatly affected by quantum effects, but the translational kinetic energy is only slightly modified. The potential energy is also noticeably higher than in classical simulations. Finally, as a concluding remark, we have calculated the formation energies of water clusters using both models, finding that the formation energies predicted by the rigid TIP4PQ/2005 model are lower by roughly 0.6 kcal/mol than those of the flexible q-TIP4P/F model for clusters of moderate size, the origin of this difference coming mainly from the geometrical distortion of the water molecule in the clusters that causes an increase in the intramolecular potential energy.

Distributions of Gas and Galaxies from Galaxy Clusters to Larger Scales

NASA Astrophysics Data System (ADS)

Patej, Anna

2017-01-01

We address the distributions of gas and galaxies on three scales: the outskirts of galaxy clusters, the clustering of galaxies on large scales, and the extremes of the galaxy distribution. In the outskirts of galaxy clusters, long-standing analytical models of structure formation and recent simulations predict the existence of density jumps in the gas and dark matter profiles. We use these features to derive models for the gas density profile, obtaining a simple fiducial model that is in agreement with both observations of cluster interiors and simulations of the outskirts. We next consider the galaxy density profiles of clusters; under the assumption that the galaxies in cluster outskirts follow similar collisionless dynamics as the dark matter, their distribution should show a steep jump as well. We examine the profiles of a low-redshift sample of clusters and groups, finding evidence for the jump in some of these clusters. Moving to larger scales where massive galaxies of different types are expected to trace the same large-scale structure, we present a test of this prediction by measuring the clustering of red and blue galaxies at z 0.6, finding low stochasticity between the two populations. These results address a key source of systematic uncertainty - understanding how target populations of galaxies trace large-scale structure - in galaxy redshift surveys. Such surveys use baryon acoustic oscillations (BAO) as a cosmological probe, but are limited by the expense of obtaining sufficiently dense spectroscopy. With the intention of leveraging upcoming deep imaging data, we develop a new method of detecting the BAO in sparse spectroscopic samples via cross-correlation with a dense photometric catalog. This method will permit the extension of BAO measurements to higher redshifts than possible with the existing spectroscopy alone. Lastly, we connect galaxies near and far: the Local Group dwarfs and the high redshift galaxies observed by Hubble and Spitzer. We examine how the local dwarfs may have appeared in the past and compare their properties to the detection limits of the upcoming James Webb Space Telescope (JWST), finding that JWST should be able to detect galaxies similar to the progenitors of a few of the brightest of the local galaxies, revealing a hitherto unobserved population of galaxies at high redshifts.

Integrated HI emission in galaxy groups and clusters

NASA Astrophysics Data System (ADS)

Ai, Mei; Zhu, Ming; Fu, Jian

2017-09-01

The integrated HI emission from hierarchical structures such as groups and clusters of galaxies can be detected by FAST at intermediate redshifts. Here we propose to use FAST to study the evolution of the global HI content of clusters and groups over cosmic time by measuring their integrated HI emissions. We use the Virgo Cluster as an example to estimate the detection limit of FAST, and have estimated the integration time to detect a Virgo type cluster at different redshifts (from z = 0.1 to z = 1.5).We have also employed a semi-analytic model (SAM) to simulate the evolution of HI contents in galaxy clusters. Our simulations suggest that the HI mass of a Virgo-like cluster could be 2-3 times higher and the physical size could be more than 50% smaller when redshift increases from z = 0.3 to z = 1. Thus the integration time could be reduced significantly and gas rich clusters at intermediate redshifts can be detected by FAST in less than 2 hours of integration time. For the local Universe, we have also used SAM simulations to create mock catalogs of clusters to predict the outcomes from FAST all sky surveys. Comparing with the optically selected catalogs derived by cross matching the galaxy catalogs from the SDSS survey and the ALFALFA survey, we find that the HI mass distribution of the mock catalog with 20 s of integration time agrees well with that of observations. However, the mock catalog with 120 s of integration time predicts many more groups and clusters that contain a population of low mass HI galaxies not detected by the ALFALFA survey. A future deep HI blind sky survey with FAST would be able to test such prediction and set constraints on the numerical simulation models. The observational strategy and sample selections for future FAST observations of galaxy clusters at high redshifts are also discussed.

Au13(8e): A secondary block for describing a special group of liganded gold clusters containing icosahedral Au13 motifs

NASA Astrophysics Data System (ADS)

Xu, Wen Wu; Zeng, Xiao Cheng; Gao, Yi

2017-05-01

A grand unified model (GUM) has been proposed recently to understand structure anatomy and evolution of liganded gold clusters. In this work, besides the two types of elementary blocks (triangular Au3(2e) and tetrahedral Au4(2e)), we introduce a secondary block, namely, the icosahedral Au13 with 8e valence electrons, noted as Au13(8e). Using this secondary block, structural anatomy and evolution of a special group of liganded gold nanoclusters containing icosahedral Au13 motifs can be conveniently analyzed. In addition, a new ligand-protected cluster Au49(PR3)10(SR)15Cl2 is predicted to exhibit high chemical and thermal stability, suggesting likelihood of its synthesis in the laboratory.

Al6H18: A baby crystal of γ-AlH3

NASA Astrophysics Data System (ADS)

Kiran, B.; Kandalam, Anil K.; Xu, Jing; Ding, Y. H.; Sierka, M.; Bowen, K. H.; Schnöckel, H.

2012-10-01

Using global-minima search methods based on the density functional theory calculations of (AlH3)n (n = 1-8) clusters, we show that the growth pattern of alanes for n ≥ 4 is dominated by structures containing hexa-coordinated Al atoms. This is in contrast to the earlier studies where either linear or ring structures of AlH3 were predicted to be the preferred structures in which the Al atoms can have a maximum of five-fold coordination. Our calculations also reveal that the Al6H18 cluster, with its hexa-coordination of the Al atoms, resembles the unit-cell of γ-AlH3, thus Al6H18 is designated as the "baby crystal." The fragmentation energies of the (AlH3)n (n = 2-8) along with the dimerization energies for even n clusters indicate an enhanced stability of the Al6H18 cluster. Both covalent (hybridization) and ionic (charge) contribution to the bonding are the driving factors in stabilizing the isomers containing hexa-coordinated Al atoms.

Lattice and Valence Electronic Structures of Crystalline Octahedral Molybdenum Halide Clusters-Based Compounds, Cs2[Mo6X14] (X = Cl, Br, I), Studied by Density Functional Theory Calculations.

PubMed

Saito, Norio; Cordier, Stéphane; Lemoine, Pierric; Ohsawa, Takeo; Wada, Yoshiki; Grasset, Fabien; Cross, Jeffrey S; Ohashi, Naoki

2017-06-05

The electronic and crystal structures of Cs 2 [Mo 6 X 14 ] (X = Cl, Br, I) cluster-based compounds were investigated by density functional theory (DFT) simulations and experimental methods such as powder X-ray diffraction, ultraviolet-visible spectroscopy, and X-ray photoemission spectroscopy (XPS). The experimentally determined lattice parameters were in good agreement with theoretically optimized ones, indicating the usefulness of DFT calculations for the structural investigation of these clusters. The calculated band gaps of these compounds reproduced those experimentally determined by UV-vis reflectance within an error of a few tenths of an eV. Core-level XPS and effective charge analyses indicated bonding states of the halogens changed according to their sites. The XPS valence spectra were fairly well reproduced by simulations based on the projected electron density of states weighted with cross sections of Al K α , suggesting that DFT calculations can predict the electronic properties of metal-cluster-based crystals with good accuracy.

Critical Features of Fragment Libraries for Protein Structure Prediction

PubMed Central

dos Santos, Karina Baptista

2017-01-01

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction. PMID:28085928

Critical Features of Fragment Libraries for Protein Structure Prediction.

PubMed

Trevizani, Raphael; Custódio, Fábio Lima; Dos Santos, Karina Baptista; Dardenne, Laurent Emmanuel

2017-01-01

The use of fragment libraries is a popular approach among protein structure prediction methods and has proven to substantially improve the quality of predicted structures. However, some vital aspects of a fragment library that influence the accuracy of modeling a native structure remain to be determined. This study investigates some of these features. Particularly, we analyze the effect of using secondary structure prediction guiding fragments selection, different fragments sizes and the effect of structural clustering of fragments within libraries. To have a clearer view of how these factors affect protein structure prediction, we isolated the process of model building by fragment assembly from some common limitations associated with prediction methods, e.g., imprecise energy functions and optimization algorithms, by employing an exact structure-based objective function under a greedy algorithm. Our results indicate that shorter fragments reproduce the native structure more accurately than the longer. Libraries composed of multiple fragment lengths generate even better structures, where longer fragments show to be more useful at the beginning of the simulations. The use of many different fragment sizes shows little improvement when compared to predictions carried out with libraries that comprise only three different fragment sizes. Models obtained from libraries built using only sequence similarity are, on average, better than those built with a secondary structure prediction bias. However, we found that the use of secondary structure prediction allows greater reduction of the search space, which is invaluable for prediction methods. The results of this study can be critical guidelines for the use of fragment libraries in protein structure prediction.

Structural motif screening reveals a novel, conserved carbohydrate-binding surface in the pathogenesis-related protein PR-5d.

PubMed

Doxey, Andrew C; Cheng, Zhenyu; Moffatt, Barbara A; McConkey, Brendan J

2010-08-03

Aromatic amino acids play a critical role in protein-glycan interactions. Clusters of surface aromatic residues and their features may therefore be useful in distinguishing glycan-binding sites as well as predicting novel glycan-binding proteins. In this work, a structural bioinformatics approach was used to screen the Protein Data Bank (PDB) for coplanar aromatic motifs similar to those found in known glycan-binding proteins. The proteins identified in the screen were significantly associated with carbohydrate-related functions according to gene ontology (GO) enrichment analysis, and predicted motifs were found frequently within novel folds and glycan-binding sites not included in the training set. In addition to numerous binding sites predicted in structural genomics proteins of unknown function, one novel prediction was a surface motif (W34/W36/W192) in the tobacco pathogenesis-related protein, PR-5d. Phylogenetic analysis revealed that the surface motif is exclusive to a subfamily of PR-5 proteins from the Solanaceae family of plants, and is absent completely in more distant homologs. To confirm PR-5d's insoluble-polysaccharide binding activity, a cellulose-pulldown assay of tobacco proteins was performed and PR-5d was identified in the cellulose-binding fraction by mass spectrometry. Based on the combined results, we propose that the putative binding site in PR-5d may be an evolutionary adaptation of Solanaceae plants including potato, tomato, and tobacco, towards defense against cellulose-containing pathogens such as species of the deadly oomycete genus, Phytophthora. More generally, the results demonstrate that coplanar aromatic clusters on protein surfaces are a structural signature of glycan-binding proteins, and can be used to computationally predict novel glycan-binding proteins from 3 D structure.

Cosmological Simulations of Galaxy Clusters

NASA Astrophysics Data System (ADS)

Borgani, Stefano; Kravtsov, Andrey

2011-02-01

We review recent progress in the description of the formation and evolution of galaxy clusters in a cosmological context by using state-of-art numerical simulations. We focus our presentation on the comparison between simulated and observed X-ray properties, while we will also discuss numerical predictions on properties of the galaxy population in clusters, as observed in the optical band. Many of the salient observed properties of clusters, such as scaling relations between X-ray observables and total mass, radial profiles of entropy and density of the intracluster gas, and radial distribution of galaxies are reproduced quite well. In particular, the outer regions of cluster at radii beyond about 10 per cent of the virial radius are quite regular and exhibit scaling with mass remarkably close to that expected in the simplest case in which only the action of gravity determines the evolution of the intra-cluster gas. However, simulations generally fail at reproducing the observed "cool core" structure of clusters: simulated clusters generally exhibit a significant excess of gas cooling in their central regions, which causes both an overestimate of the star formation in the cluster centers and incorrect temperature and entropy profiles. The total baryon fraction in clusters is below the mean universal value, by an amount which depends on the cluster-centric distance and the physics included in the simulations, with interesting tensions between observed stellar and gas fractions in clusters and predictions of simulations. Besides their important implications for the cosmological application of clusters, these puzzles also point towards the important role played by additional physical processes, beyond those already included in the simulations. We review the role played by these processes, along with the difficulty for their implementation, and discuss the outlook for the future progress in numerical modeling of clusters.

B38: an all-boron fullerene analogue.

PubMed

Lv, Jian; Wang, Yanchao; Zhu, Li; Ma, Yanming

2014-10-21

Fullerene-like structures formed by elements other than carbon have long been sought. Finding all-boron (B) fullerene-like structures is challenging due to the geometrical frustration arising from competitions among various structural motifs. We report here the prediction of a B38 fullerene analogue found through first-principles swarm structure searching calculations. The structure is highly symmetric and consists of 56 triangles and four hexagons, which provide an optimal void in the center of the cage. Energetically, it is more favorable than the planar and tubular structures, and possesses an unusually high chemical stability: a large energy gap (∼2.25 eV) and a high double aromaticity, superior to those of most aromatic quasi-planar B12 and double-ring B20 clusters. Our findings represent a key step forward towards to the understanding of structures of medium-sized B clusters and map out the experimental direction of the synthesis of an all-B fullerene analogue.

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

Yu, Chongqi; Harbich, Wolfgang; Sementa, Luca

Ligand-protected Au clusters are non-bleaching fluorescence markers in bio- and medical applications. We show that their fluorescence is an intrinsic property of the Au cluster itself. We find a very intense and sharp fluorescence peak located at λ =739.2 nm (1.68 eV) for Au20 clusters in a Ne matrix held at 6 K. The fluorescence reflects the HOMO-LUMO diabatic bandgap of the cluster. The cluster shows a very rich absorption fine structure reminiscent of well defined molecule-like quantum levels. These levels are resolved since Au20 has only one stable isomer (tetrahedral), therefore our sample is mono-disperse in cluster size andmore » conformation. Density-functional theory (DFT) and time-dependent DFT calculations clarify the nature of optical absorptionand predict both main absorption peaks and intrinsic fluorescence in good agreement with experiment.« less

Constraints on Cosmology and Gravity from the Growth of X-ray Luminous Galaxy Clusters

NASA Astrophysics Data System (ADS)

Mantz, Adam; Allen, S. W.; Rapetti, D.; Ebeling, H.; Drlica-Wagner, A.

2010-03-01

I will present simultaneous constraints on galaxy cluster X-ray scaling relations and models of cosmology and gravity obtained from observations of the growth of massive clusters. The data set consists of 238 flux-selected clusters at redshifts z≤0.5 drawn from the ROSAT All-Sky Survey, and incorporates extensive Chandra follow-up observations. Our results on the scaling relations are consistent with excess heating of the intracluster medium, although the evolution of the relations remains consistent with the predictions of simple gravitational collapse models. For spatially flat, constant-w cosmological models, the cluster data yield Ωm=0.23±0.04, σ8=0.82±0.05, and w=-1.01±0.20, including conservative allowances for systematic uncertainties. Our results are consistent and competitive with a variety of independent cosmological data. In evolving-w models, marginalizing over transition redshifts in the range 0.05-1, the combination of the growth of structure data with the cosmic microwave background, supernovae, cluster gas mass fractions and baryon acoustic oscillations constrains the dark energy equation of state at late and early times to be respectively w0=-0.88±0.21 and wet=-1.05+0.20-0.36. Applying this combination of data to the problem of determining fundamental neutrino properties, we place an upper limit on the species-summed neutrino mass at 0.33eV (95% CL) and constrain the effective number of relativistic species to 3.4±0.6. In addition to dark energy and related problems, such data can be used to test the predictions of General Relativity. Introducing the standard Peebles/Linder parametrization of the linear growth rate, we use the cluster data to constrain the growth of structure, independent of the expansion of the Universe. Our analysis provides a tight constraint on the combination γ(σ8/0.8)6.8=0.55+0.13-0.10, and is simultaneously consistent with the predictions of relativity (γ=0.55) and the cosmological constant expansion model. This work was funded by NASA, the U.S. Department of Energy, and Stanford University.

Camps 2.0: exploring the sequence and structure space of prokaryotic, eukaryotic, and viral membrane proteins.

PubMed

Neumann, Sindy; Hartmann, Holger; Martin-Galiano, Antonio J; Fuchs, Angelika; Frishman, Dmitrij

2012-03-01

Structural bioinformatics of membrane proteins is still in its infancy, and the picture of their fold space is only beginning to emerge. Because only a handful of three-dimensional structures are available, sequence comparison and structure prediction remain the main tools for investigating sequence-structure relationships in membrane protein families. Here we present a comprehensive analysis of the structural families corresponding to α-helical membrane proteins with at least three transmembrane helices. The new version of our CAMPS database (CAMPS 2.0) covers nearly 1300 eukaryotic, prokaryotic, and viral genomes. Using an advanced classification procedure, which is based on high-order hidden Markov models and considers both sequence similarity as well as the number of transmembrane helices and loop lengths, we identified 1353 structurally homogeneous clusters roughly corresponding to membrane protein folds. Only 53 clusters are associated with experimentally determined three-dimensional structures, and for these clusters CAMPS is in reasonable agreement with structure-based classification approaches such as SCOP and CATH. We therefore estimate that ∼1300 structures would need to be determined to provide a sufficient structural coverage of polytopic membrane proteins. CAMPS 2.0 is available at http://webclu.bio.wzw.tum.de/CAMPS2.0/. Copyright © 2011 Wiley Periodicals, Inc.

Photoelectron spectroscopic study of the anionic transition metalorganic complexes [Fe(1,2)(COT)](-) and [Co(COT)](-).

PubMed

Li, Xiang; Eustis, Soren N; Bowen, Kit H; Kandalam, Anil

2008-09-28

The gas-phase, iron and cobalt cyclooctatetraene cluster anions, [Fe(1,2)(COT)](-) and [Co(COT)](-), were generated using a laser vaporization source and studied using mass spectrometry and anion photoelectron spectroscopy. Density functional theory was employed to compute the structures and spin multiplicities of these cluster anions as well as those of their corresponding neutrals. Both experimental and theoretically predicted electron affinities and photodetachment transition energies are in good agreement, authenticating the structures and spin multiplicities predicted by theory. The implied spin magnetic moments of these systems suggest that [Fe(COT)], [Fe(2)(COT)], and [Co(COT)] retain the magnetic moments of the Fe atom, the Fe(2) dimer, and the Co atom, respectively. Thus, the interaction of these transition metal, atomic and dimeric moieties with a COT molecule does not quench their magnetic moments, leading to the possibility that these combinations may be useful in forming novel magnetic materials.

The Next Generation Virgo Cluster Survey. IV. NGC 4216: A Bombarded Spiral in the Virgo Cluster

NASA Astrophysics Data System (ADS)

Paudel, Sanjaya; Duc, Pierre-Alain; Côté, Patrick; Cuillandre, Jean-Charles; Ferrarese, Laura; Ferriere, Etienne; Gwyn, Stephen D. J.; Mihos, J. Christopher; Vollmer, Bernd; Balogh, Michael L.; Carlberg, Ray G.; Boissier, Samuel; Boselli, Alessandro; Durrell, Patrick R.; Emsellem, Eric; MacArthur, Lauren A.; Mei, Simona; Michel-Dansac, Leo; van Driel, Wim

2013-04-01

The final stages of mass assembly of present-day massive galaxies are expected to occur through the accretion of multiple satellites. Cosmological simulations thus predict a high frequency of stellar streams resulting from this mass accretion around the massive galaxies in the Local Volume. Such tidal streams are difficult to observe, especially in dense cluster environments, where they are readily destroyed. We present an investigation into the origins of a series of interlaced narrow filamentary stellar structures, loops and plumes in the vicinity of the Virgo Cluster, edge-on spiral galaxy, NGC 4216 that were previously identified by the Blackbird telescope. Using the deeper, higher-resolution, and precisely calibrated optical CFHT/MegaCam images obtained as part of the Next Generation Virgo Cluster Survey (NGVS), we confirm the previously identified features and identify a few additional structures. The NGVS data allowed us to make a physical study of these low surface brightness features and investigate their origin. The likely progenitors of the structures were identified as either already cataloged Virgo Cluster Catalog dwarfs or newly discovered satellites caught in the act of being destroyed. They have the same g - i color index and likely contain similar stellar populations. The alignment of three dwarfs along an apparently single stream is intriguing, and we cannot totally exclude that these are second-generation dwarf galaxies being born inside the filament from the debris of an original dwarf. The observed complex structures, including in particular a stream apparently emanating from a satellite of a satellite, point to a high rate of ongoing dwarf destruction/accretion in the region of the Virgo Cluster where NGC 4216 is located. We discuss the age of the interactions and whether they occurred in a group that is just falling into the cluster and shows signs of the so-called pre-processing before it gets affected by the cluster environment, or in a group which already ventured toward the central regions of Virgo Cluster. In any case, compared to the other spiral galaxies in the Virgo Cluster, but also to those located in lower density environments, NGC 4216 seems to suffer an unusually heavy bombardment. Further studies will be needed to determine whether, given the surface brightness limit of our survey, about 29 mag arcsec-2, the number of observed streams around that galaxy is as predicted by cosmological simulations or conversely, whether the possible lack of similar structures in other galaxies poses a challenge to the merger-based model of galaxy mass assembly. Based on observations obtained with MegaPrime/MegaCam, a joint project of Canada-France-Hawaii Telescope (CFHT) and CEA/DAPNIA, at the CFHT which is operated by the National Research Council (NRC) of Canada, the Institut National des Sciences de l'Univers of the Centre National de la Recherche Scientifique of France, and the University of Hawaii.

Dispersed metal cluster catalysts by design. Synthesis, characterization, structure, and performance

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

Arslan, Ilke; Dixon, David A.; Gates, Bruce C.

2015-09-30

To understand the class of metal cluster catalysts better and to lay a foundation for the prediction of properties leading to improved catalysts, we have synthesized metal catalysts with well-defined structures and varied the cluster structures and compositions systematically—including the ligands bonded to the metals. These ligands include supports and bulky organics that are being tuned to control both the electron transfer to or from the metal and the accessibility of reactants to influence catalytic properties. We have developed novel syntheses to prepare these well-defined catalysts with atomic-scale control the environment by choice and placement of ligands and applied state-of-themore » art spectroscopic, microscopic, and computational methods to determine their structures, reactivities, and catalytic properties. The ligands range from nearly flat MgO surfaces to enveloping zeolites to bulky calixarenes to provide controlled coverages of the metal clusters, while also enforcing unprecedented degrees of coordinative unsaturation at the metal site—thereby facilitating bonding and catalysis events at exposed metal atoms. With this wide range of ligand properties and our arsenal of characterization tools, we worked to achieve a deep, fundamental understanding of how to synthesize robust supported and ligand-modified metal clusters with controlled catalytic properties, thereby bridging the gap between active site structure and function in unsupported and supported metal catalysts. We used methods of organometallic and inorganic chemistry combined with surface chemistry for the precise synthesis of metal clusters and nanoparticles, characterizing them at various stages of preparation and under various conditions (including catalytic reaction conditions) and determining their structures and reactivities and how their catalytic properties depend on their compositions and structures. Key characterization methods included IR, NMR, and EXAFS spectroscopies to identify ligands on the metals and their reactions; EXAFS spectroscopy and high-resolution STEM to determine cluster framework structures and changes resulting from reactant treatment and locations of metal atoms on support surfaces; X-ray diffraction crystallography to determine full structures of cluster-ligand combinations in the absence of a support, and TEM with tomographic methods to observe individual metal atoms and determine three-dimensional structures of catalysts. Electronic structure calculations were used to verify and interpret spectra and extend the understanding of reactivity beyond what is measurable experimentally.« less

Kassiopeia: a database and web application for the analysis of mutually exclusive exomes of eukaryotes

PubMed Central

2014-01-01

Background Alternative splicing is an important process in higher eukaryotes that allows obtaining several transcripts from one gene. A specific case of alternative splicing is mutually exclusive splicing, in which exactly one exon out of a cluster of neighbouring exons is spliced into the mature transcript. Recently, a new algorithm for the prediction of these exons has been developed based on the preconditions that the exons of the cluster have similar lengths, sequence homology, and conserved splice sites, and that they are translated in the same reading frame. Description In this contribution we introduce Kassiopeia, a database and web application for the generation, storage, and presentation of genome-wide analyses of mutually exclusive exomes. Currently, Kassiopeia provides access to the mutually exclusive exomes of twelve Drosophila species, the thale cress Arabidopsis thaliana, the flatworm Caenorhabditis elegans, and human. Mutually exclusive spliced exons (MXEs) were predicted based on gene reconstructions from Scipio. Based on the standard prediction values, with which 83.5% of the annotated MXEs of Drosophila melanogaster were reconstructed, the exomes contain surprisingly more MXEs than previously supposed and identified. The user can search Kassiopeia using BLAST or browse the genes of each species optionally adjusting the parameters used for the prediction to reveal more divergent or only very similar exon candidates. Conclusions We developed a pipeline to predict MXEs in the genomes of several model organisms and a web interface, Kassiopeia, for their visualization. For each gene Kassiopeia provides a comprehensive gene structure scheme, the sequences and predicted secondary structures of the MXEs, and, if available, further evidence for MXE candidates from cDNA/EST data, predictions of MXEs in homologous genes of closely related species, and RNA secondary structure predictions. Kassiopeia can be accessed at http://www.motorprotein.de/kassiopeia. PMID:24507667

Insulin Resistance: Regression and Clustering

PubMed Central

Yoon, Sangho; Assimes, Themistocles L.; Quertermous, Thomas; Hsiao, Chin-Fu; Chuang, Lee-Ming; Hwu, Chii-Min; Rajaratnam, Bala; Olshen, Richard A.

2014-01-01

In this paper we try to define insulin resistance (IR) precisely for a group of Chinese women. Our definition deliberately does not depend upon body mass index (BMI) or age, although in other studies, with particular random effects models quite different from models used here, BMI accounts for a large part of the variability in IR. We accomplish our goal through application of Gauss mixture vector quantization (GMVQ), a technique for clustering that was developed for application to lossy data compression. Defining data come from measurements that play major roles in medical practice. A precise statement of what the data are is in Section 1. Their family structures are described in detail. They concern levels of lipids and the results of an oral glucose tolerance test (OGTT). We apply GMVQ to residuals obtained from regressions of outcomes of an OGTT and lipids on functions of age and BMI that are inferred from the data. A bootstrap procedure developed for our family data supplemented by insights from other approaches leads us to believe that two clusters are appropriate for defining IR precisely. One cluster consists of women who are IR, and the other of women who seem not to be. Genes and other features are used to predict cluster membership. We argue that prediction with “main effects” is not satisfactory, but prediction that includes interactions may be. PMID:24887437

Predicting surface fuel models and fuel metrics using lidar and CIR imagery in a dense mixed conifer forest

Treesearch

Marek K. Jakubowksi; Qinghua Guo; Brandon Collins; Scott Stephens; Maggi Kelly

2013-01-01

We compared the ability of several classification and regression algorithms to predict forest stand structure metrics and standard surface fuel models. Our study area spans a dense, topographically complex Sierra Nevada mixed-conifer forest. We used clustering, regression trees, and support vector machine algorithms to analyze high density (average 9 pulses/m

An Ecological Analysis of the Effects of Deviant Peer Clustering on Sexual Promiscuity, Problem Behavior, and Childbearing from Early Adolescence to Adulthood: An Enhancement of the Life History Framework

PubMed Central

Dishion, Thomas J.; Ha, Thao; Véronneau, Marie-Hélène

2012-01-01

This study proposes the inclusion of peer relationships in a life history perspective on adolescent problem behavior. Longitudinal analyses were used to examine deviant peer clustering as the mediating link between attenuated family ties, peer marginalization, and social disadvantage in early adolescence and sexual promiscuity in middle adolescence and childbearing by early adulthood. Specifically, 998 youth and their families were assessed at age 11 years and periodically through age 24 years. Structural equation modeling revealed that the peer-enhanced life history model provided a good fit to the longitudinal data, with deviant peer clustering strongly predicting adolescent sexual promiscuity and other correlated problem behaviors. Sexual promiscuity, as expected, also strongly predicted the number of children by age 22–24 years. Consistent with a life history perspective, family social disadvantage directly predicted deviant peer clustering and number of children in early adulthood, controlling for all other variables in the model. These data suggest that deviant peer clustering is a core dimension of a fast life history strategy, with strong links to sexual activity and childbearing. The implications of these findings are discussed with respect to the need to integrate an evolutionary-based model of self-organized peer groups in developmental and intervention science. PMID:22409765

An ecological analysis of the effects of deviant peer clustering on sexual promiscuity, problem behavior, and childbearing from early adolescence to adulthood: an enhancement of the life history framework.

PubMed

Dishion, Thomas J; Ha, Thao; Véronneau, Marie-Hélène

2012-05-01

The authors propose that peer relationships should be included in a life history perspective on adolescent problem behavior. Longitudinal analyses were used to examine deviant peer clustering as the mediating link between attenuated family ties, peer marginalization, and social disadvantage in early adolescence and sexual promiscuity in middle adolescence and childbearing by early adulthood. Specifically, 998 youths, along with their families, were assessed at age 11 years and periodically through age 24 years. Structural equation modeling revealed that the peer-enhanced life history model provided a good fit to the longitudinal data, with deviant peer clustering strongly predicting adolescent sexual promiscuity and other correlated problem behaviors. Sexual promiscuity, as expected, also strongly predicted the number of children by ages 22-24 years. Consistent with a life history perspective, family social disadvantage directly predicted deviant peer clustering and number of children in early adulthood, controlling for all other variables in the model. These data suggest that deviant peer clustering is a core dimension of a fast life history strategy, with strong links to sexual activity and childbearing. The implications of these findings are discussed with respect to the need to integrate an evolutionary-based model of self-organized peer groups in developmental and intervention science.

ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network.

PubMed

Wang, Jianxin; Zhong, Jiancheng; Chen, Gang; Li, Min; Wu, Fang-xiang; Pan, Yi

2015-01-01

Cluster analysis of biological networks is one of the most important approaches for identifying functional modules and predicting protein functions. Furthermore, visualization of clustering results is crucial to uncover the structure of biological networks. In this paper, ClusterViz, an APP of Cytoscape 3 for cluster analysis and visualization, has been developed. In order to reduce complexity and enable extendibility for ClusterViz, we designed the architecture of ClusterViz based on the framework of Open Services Gateway Initiative. According to the architecture, the implementation of ClusterViz is partitioned into three modules including interface of ClusterViz, clustering algorithms and visualization and export. ClusterViz fascinates the comparison of the results of different algorithms to do further related analysis. Three commonly used clustering algorithms, FAG-EC, EAGLE and MCODE, are included in the current version. Due to adopting the abstract interface of algorithms in module of the clustering algorithms, more clustering algorithms can be included for the future use. To illustrate usability of ClusterViz, we provided three examples with detailed steps from the important scientific articles, which show that our tool has helped several research teams do their research work on the mechanism of the biological networks.

iDBPs: a web server for the identification of DNA binding proteins

PubMed Central

Nimrod, Guy; Schushan, Maya; Szilágyi, András; Leslie, Christina; Ben-Tal, Nir

2010-01-01

Summary: The iDBPs server uses the three-dimensional (3D) structure of a query protein to predict whether it binds DNA. First, the algorithm predicts the functional region of the protein based on its evolutionary profile; the assumption is that large clusters of conserved residues are good markers of functional regions. Next, various characteristics of the predicted functional region as well as global features of the protein are calculated, such as the average surface electrostatic potential, the dipole moment and cluster-based amino acid conservation patterns. Finally, a random forests classifier is used to predict whether the query protein is likely to bind DNA and to estimate the prediction confidence. We have trained and tested the classifier on various datasets and shown that it outperformed related methods. On a dataset that reflects the fraction of DNA binding proteins (DBPs) in a proteome, the area under the ROC curve was 0.90. The application of the server to an updated version of the N-Func database, which contains proteins of unknown function with solved 3D-structure, suggested new putative DBPs for experimental studies. Availability: http://idbps.tau.ac.il/ Contact: NirB@tauex.tau.ac.il Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20089514

Eb&D: A new clustering approach for signed social networks based on both edge-betweenness centrality and density of subgraphs

NASA Astrophysics Data System (ADS)

Qi, Xingqin; Song, Huimin; Wu, Jianliang; Fuller, Edgar; Luo, Rong; Zhang, Cun-Quan

2017-09-01

Clustering algorithms for unsigned social networks which have only positive edges have been studied intensively. However, when a network has like/dislike, love/hate, respect/disrespect, or trust/distrust relationships, unsigned social networks with only positive edges are inadequate. Thus we model such kind of networks as signed networks which can have both negative and positive edges. Detecting the cluster structures of signed networks is much harder than for unsigned networks, because it not only requires that positive edges within clusters are as many as possible, but also requires that negative edges between clusters are as many as possible. Currently, we have few clustering algorithms for signed networks, and most of them requires the number of final clusters as an input while it is actually hard to predict beforehand. In this paper, we will propose a novel clustering algorithm called Eb &D for signed networks, where both the betweenness of edges and the density of subgraphs are used to detect cluster structures. A hierarchically nested system will be constructed to illustrate the inclusion relationships of clusters. To show the validity and efficiency of Eb &D, we test it on several classical social networks and also hundreds of synthetic data sets, and all obtain better results compared with other methods. The biggest advantage of Eb &D compared with other methods is that the number of clusters do not need to be known prior.

Thermodynamic prediction of protein neutrality.

PubMed

Bloom, Jesse D; Silberg, Jonathan J; Wilke, Claus O; Drummond, D Allan; Adami, Christoph; Arnold, Frances H

2005-01-18

We present a simple theory that uses thermodynamic parameters to predict the probability that a protein retains the wild-type structure after one or more random amino acid substitutions. Our theory predicts that for large numbers of substitutions the probability that a protein retains its structure will decline exponentially with the number of substitutions, with the severity of this decline determined by properties of the structure. Our theory also predicts that a protein can gain extra robustness to the first few substitutions by increasing its thermodynamic stability. We validate our theory with simulations on lattice protein models and by showing that it quantitatively predicts previously published experimental measurements on subtilisin and our own measurements on variants of TEM1 beta-lactamase. Our work unifies observations about the clustering of functional proteins in sequence space, and provides a basis for interpreting the response of proteins to substitutions in protein engineering applications.

Thermodynamic prediction of protein neutrality

PubMed Central

Bloom, Jesse D.; Silberg, Jonathan J.; Wilke, Claus O.; Drummond, D. Allan; Adami, Christoph; Arnold, Frances H.

2005-01-01

We present a simple theory that uses thermodynamic parameters to predict the probability that a protein retains the wild-type structure after one or more random amino acid substitutions. Our theory predicts that for large numbers of substitutions the probability that a protein retains its structure will decline exponentially with the number of substitutions, with the severity of this decline determined by properties of the structure. Our theory also predicts that a protein can gain extra robustness to the first few substitutions by increasing its thermodynamic stability. We validate our theory with simulations on lattice protein models and by showing that it quantitatively predicts previously published experimental measurements on subtilisin and our own measurements on variants of TEM1 β-lactamase. Our work unifies observations about the clustering of functional proteins in sequence space, and provides a basis for interpreting the response of proteins to substitutions in protein engineering applications. PMID:15644440

On the applicability of one- and many-electron quantum chemistry models for hydrated electron clusters

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

Turi, László, E-mail: turi@chem.elte.hu

2016-04-21

We evaluate the applicability of a hierarchy of quantum models in characterizing the binding energy of excess electrons to water clusters. In particular, we calculate the vertical detachment energy of an excess electron from water cluster anions with methods that include one-electron pseudopotential calculations, density functional theory (DFT) based calculations, and ab initio quantum chemistry using MP2 and eom-EA-CCSD levels of theory. The examined clusters range from the smallest cluster size (n = 2) up to nearly nanosize clusters with n = 1000 molecules. The examined cluster configurations are extracted from mixed quantum-classical molecular dynamics trajectories of cluster anions withmore » n = 1000 water molecules using two different one-electron pseudopotenial models. We find that while MP2 calculations with large diffuse basis set provide a reasonable description for the hydrated electron system, DFT methods should be used with precaution and only after careful benchmarking. Strictly tested one-electron psudopotentials can still be considered as reasonable alternatives to DFT methods, especially in large systems. The results of quantum chemistry calculations performed on configurations, that represent possible excess electron binding motifs in the clusters, appear to be consistent with the results using a cavity structure preferring one-electron pseudopotential for the hydrated electron, while they are in sharp disagreement with the structural predictions of a non-cavity model.« less

On the applicability of one- and many-electron quantum chemistry models for hydrated electron clusters

NASA Astrophysics Data System (ADS)

Turi, László

2016-04-01

We evaluate the applicability of a hierarchy of quantum models in characterizing the binding energy of excess electrons to water clusters. In particular, we calculate the vertical detachment energy of an excess electron from water cluster anions with methods that include one-electron pseudopotential calculations, density functional theory (DFT) based calculations, and ab initio quantum chemistry using MP2 and eom-EA-CCSD levels of theory. The examined clusters range from the smallest cluster size (n = 2) up to nearly nanosize clusters with n = 1000 molecules. The examined cluster configurations are extracted from mixed quantum-classical molecular dynamics trajectories of cluster anions with n = 1000 water molecules using two different one-electron pseudopotenial models. We find that while MP2 calculations with large diffuse basis set provide a reasonable description for the hydrated electron system, DFT methods should be used with precaution and only after careful benchmarking. Strictly tested one-electron psudopotentials can still be considered as reasonable alternatives to DFT methods, especially in large systems. The results of quantum chemistry calculations performed on configurations, that represent possible excess electron binding motifs in the clusters, appear to be consistent with the results using a cavity structure preferring one-electron pseudopotential for the hydrated electron, while they are in sharp disagreement with the structural predictions of a non-cavity model.

Understanding boron through size-selected clusters: structure, chemical bonding, and fluxionality.

PubMed

Sergeeva, Alina P; Popov, Ivan A; Piazza, Zachary A; Li, Wei-Li; Romanescu, Constantin; Wang, Lai-Sheng; Boldyrev, Alexander I

2014-04-15

Boron is an interesting element with unusual polymorphism. While three-dimensional (3D) structural motifs are prevalent in bulk boron, atomic boron clusters are found to have planar or quasi-planar structures, stabilized by localized two-center-two-electron (2c-2e) σ bonds on the periphery and delocalized multicenter-two-electron (nc-2e) bonds in both σ and π frameworks. Electron delocalization is a result of boron's electron deficiency and leads to fluxional behavior, which has been observed in B13(+) and B19(-). A unique capability of the in-plane rotation of the inner atoms against the periphery of the cluster in a chosen direction by employing circularly polarized infrared radiation has been suggested. Such fluxional behaviors in boron clusters are interesting and have been proposed as molecular Wankel motors. The concepts of aromaticity and antiaromaticity have been extended beyond organic chemistry to planar boron clusters. The validity of these concepts in understanding the electronic structures of boron clusters is evident in the striking similarities of the π-systems of planar boron clusters to those of polycyclic aromatic hydrocarbons, such as benzene, naphthalene, coronene, anthracene, or phenanthrene. Chemical bonding models developed for boron clusters not only allowed the rationalization of the stability of boron clusters but also lead to the design of novel metal-centered boron wheels with a record-setting planar coordination number of 10. The unprecedented highly coordinated borometallic molecular wheels provide insights into the interactions between transition metals and boron and expand the frontier of boron chemistry. Another interesting feature discovered through cluster studies is boron transmutation. Even though it is well-known that B(-), formed by adding one electron to boron, is isoelectronic to carbon, cluster studies have considerably expanded the possibilities of new structures and new materials using the B(-)/C analogy. It is believed that the electronic transmutation concept will be effective and valuable in aiding the design of new boride materials with predictable properties. The study of boron clusters with intermediate properties between those of individual atoms and bulk solids has given rise to a unique opportunity to broaden the frontier of boron chemistry. Understanding boron clusters has spurred experimentalists and theoreticians to find new boron-based nanomaterials, such as boron fullerenes, nanotubes, two-dimensional boron, and new compounds containing boron clusters as building blocks. Here, a brief and timely overview is presented addressing the recent progress made on boron clusters and the approaches used in the authors' laboratories to determine the structure, stability, and chemical bonding of size-selected boron clusters by joint photoelectron spectroscopy and theoretical studies. Specifically, key findings on all-boron hydrocarbon analogues, metal-centered boron wheels, and electronic transmutation in boron clusters are summarized.

Understanding Boron through Size-Selected Clusters: Structure, Chemical Bonding, and Fluxionality

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

Sergeeva, Alina P.; Popov, Ivan A.; Piazza, Zachary A.

Conspectus Boron is an interesting element with unusual polymorphism. While three-dimensional (3D) structural motifs are prevalent in bulk boron, atomic boron clusters are found to have planar or quasi-planar structures, stabilized by localized two-center–two-electron (2c–2e) σ bonds on the periphery and delocalized multicenter–two-electron (nc–2e) bonds in both σ and π frameworks. Electron delocalization is a result of boron’s electron deficiency and leads to fluxional behavior, which has been observed in B13+ and B19–. A unique capability of the in-plane rotation of the inner atoms against the periphery of the cluster in a chosen direction by employing circularly polarized infrared radiationmore » has been suggested. Such fluxional behaviors in boron clusters are interesting and have been proposed as molecular Wankel motors. The concepts of aromaticity and antiaromaticity have been extended beyond organic chemistry to planar boron clusters. The validity of these concepts in understanding the electronic structures of boron clusters is evident in the striking similarities of the π-systems of planar boron clusters to those of polycyclic aromatic hydrocarbons, such as benzene, naphthalene, coronene, anthracene, or phenanthrene. Chemical bonding models developed for boron clusters not only allowed the rationalization of the stability of boron clusters but also lead to the design of novel metal-centered boron wheels with a record-setting planar coordination number of 10. The unprecedented highly coordinated borometallic molecular wheels provide insights into the interactions between transition metals and boron and expand the frontier of boron chemistry. Another interesting feature discovered through cluster studies is boron transmutation. Even though it is well-known that B–, formed by adding one electron to boron, is isoelectronic to carbon, cluster studies have considerably expanded the possibilities of new structures and new materials using the B–/C analogy. It is believed that the electronic transmutation concept will be effective and valuable in aiding the design of new boride materials with predictable properties. The study of boron clusters with intermediate properties between those of individual atoms and bulk solids has given rise to a unique opportunity to broaden the frontier of boron chemistry. Understanding boron clusters has spurred experimentalists and theoreticians to find new boron-based nanomaterials, such as boron fullerenes, nanotubes, two-dimensional boron, and new compounds containing boron clusters as building blocks. Here, a brief and timely overview is presented addressing the recent progress made on boron clusters and the approaches used in the authors’ laboratories to determine the structure, stability, and chemical bonding of size-selected boron clusters by joint photoelectron spectroscopy and theoretical studies. Specifically, key findings on all-boron hydrocarbon analogues, metal-centered boron wheels, and electronic transmutation in boron clusters are summarized.« less

Cosmology and astrophysics from relaxed galaxy clusters - V. Consistency with cold dark matter structure formation

NASA Astrophysics Data System (ADS)

Mantz, A. B.; Allen, S. W.; Morris, R. G.

2016-10-01

This is the fifth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. We present constraints on the concentration-mass relation for massive clusters, finding a power-law mass dependence with a slope of κm = -0.16 ± 0.07, in agreement with CDM predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κζ = -0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ˜50 kpc-1 Mpc), and test for departures from the simple Navarro-Frenk-White (NFW) form, for which the logarithmic slope of the density profile tends to -1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σβ = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σα = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.

Cosmology and astrophysics from relaxed galaxy clusters – V. Consistency with cold dark matter structure formation

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

Mantz, A. B.; Allen, S. W.; Morris, R. G.

This is the fifth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. In addition, we present constraints on the concentration–mass relation for massive clusters, finding a power-law mass dependence with a slope of κ m = –0.16 ± 0.07, in agreement with CDMmore » predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κ ζ = –0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ~50 kpc–1 Mpc), and test for departures from the simple Navarro–Frenk–White (NFW) form, for which the logarithmic slope of the density profile tends to –1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σ β = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σ α = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.« less

Cosmology and astrophysics from relaxed galaxy clusters – V. Consistency with cold dark matter structure formation

DOE PAGES

Mantz, A. B.; Allen, S. W.; Morris, R. G.

2016-07-15

This is the fifth in a series of papers studying the astrophysics and cosmology of massive, dynamically relaxed galaxy clusters. Our sample comprises 40 clusters identified as being dynamically relaxed and hot in Papers I and II of this series. Here we use constraints on cluster mass profiles from X-ray data to test some of the basic predictions of cosmological structure formation in the cold dark matter (CDM) paradigm. In addition, we present constraints on the concentration–mass relation for massive clusters, finding a power-law mass dependence with a slope of κ m = –0.16 ± 0.07, in agreement with CDMmore » predictions. For this relaxed sample, the relation is consistent with a constant as a function of redshift (power-law slope with 1 + z of κ ζ = –0.17 ± 0.26), with an intrinsic scatter of σln c = 0.16 ± 0.03. We investigate the shape of cluster mass profiles over the radial range probed by the data (typically ~50 kpc–1 Mpc), and test for departures from the simple Navarro–Frenk–White (NFW) form, for which the logarithmic slope of the density profile tends to –1 at small radii. Specifically, we consider as alternatives the generalized NFW (GNFW) and Einasto parametrizations. For the GNFW model, we find an average value of (minus) the logarithmic inner slope of β = 1.02 ± 0.08, with an intrinsic scatter of σ β = 0.22 ± 0.07, while in the Einasto case we constrain the average shape parameter to be α = 0.29 ± 0.04 with an intrinsic scatter of σ α = 0.12 ± 0.04. Our results are thus consistent with the simple NFW model on average, but we clearly detect the presence of intrinsic, cluster-to-cluster scatter about the average.« less

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation

PubMed Central

Casadio, Rita

2017-01-01

Abstract BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. PMID:28453653

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

Alexandrova, Anastassia N.; Nayhouse, Michael J.; Huynh, Mioy T.

CAl₄²-/- (D₄h, ¹A₁g) is is a cluster ion that has been established to be planar, aromatic, and contain a tetracoordinate planar C atom. Valence isoelectronic substitution of C with Si and Ge in this cluster leads to a radical change of structure toward distorted pentagonal species. We find that this structural change goes together with the cluster acquiring partial covalency of bonding between Si/Ge and Al₄, facilitated by hybridization of the atomic orbitals (AOs). Counter intuitively, for the AAl₄²-/- (A = C, Si, Ge) clusters, hybridization in the dopant atom is strengthened from C, to Si, and to Ge, evenmore » though typically AOs are more likely to hybridize if they are closer in energy (i.e. in earlier elements in the Periodic Table). The trend is explained by the better overlap of the hybrids of the heavier dopants with the orbitals of Al₄. From the thus understood trend, it is inferred that covalency in such clusters can be switched off, by varying the relative sizes of the AOs of the main element and the dopant. Using this mechanism, we then successfully killed covalency in Si, and predicted a new aromatic cluster ion containing a tetracoordinate square planar Si, SiIn₄²-/-.« less

Assessment of the Density Functional Tight Binding Method for Protic Ionic Liquids

PubMed Central

2015-01-01

Density functional tight binding (DFTB), which is ∼100–1000 times faster than full density functional theory (DFT), has been used to simulate the structure and properties of protic ionic liquid (IL) ions, clusters of ions and the bulk liquid. Proton affinities for a wide range of IL cations and anions determined using DFTB generally reproduce G3B3 values to within 5–10 kcal/mol. The structures and thermodynamic stabilities of n-alkyl ammonium nitrate clusters (up to 450 quantum chemical atoms) predicted with DFTB are in excellent agreement with those determined using DFT. The IL bulk structure simulated using DFTB with periodic boundary conditions is in excellent agreement with published neutron diffraction data. PMID:25328497

Fragile sites, dysfunctional telomere and chromosome fusions: What is 5S rDNA role?

PubMed

Barros, Alain Victor; Wolski, Michele Andressa Vier; Nogaroto, Viviane; Almeida, Mara Cristina; Moreira-Filho, Orlando; Vicari, Marcelo Ricardo

2017-04-15

Repetitive DNA regions are known as fragile chromosomal sites which present a high flexibility and low stability. Our focus was characterize fragile sites in 5S rDNA regions. The Ancistrus sp. species shows a diploid number of 50 and an indicative Robertsonian fusion at chromosomal pair 1. Two sequences of 5S rDNA were identified: 5S.1 rDNA and 5S.2 rDNA. The first sequence gathers the necessary structures to gene expression and shows a functional secondary structure prediction. Otherwise, the 5S.2 rDNA sequence does not contain the upstream sequences that are required to expression, furthermore its structure prediction reveals a nonfunctional ribosomal RNA. The chromosomal mapping revealed several 5S.1 and 5S.2 rDNA clusters. In addition, the 5S.2 rDNA clusters were found in acrocentric and metacentric chromosomes proximal regions. The pair 1 5S.2 rDNA cluster is co-located with interstitial telomeric sites (ITS). Our results indicate that its clusters are hotspots to chromosomal breaks. During the meiotic prophase bouquet arrangement, double strand breaks (DSBs) at proximal 5S.2 rDNA of acrocentric chromosomes could lead to homologous and non-homologous repair mechanisms as Robertsonian fusions. Still, ITS sites provides chromosomal instability, resulting in telomeric recombination via TRF2 shelterin protein and a series of breakage-fusion-bridge cycles. Our proposal is that 5S rDNA derived sequences, act as chromosomal fragile sites in association with some chromosomal rearrangements of Loricariidae. Copyright © 2017 Elsevier B.V. All rights reserved.

Identifying and reducing error in cluster-expansion approximations of protein energies.

PubMed

Hahn, Seungsoo; Ashenberg, Orr; Grigoryan, Gevorg; Keating, Amy E

2010-12-01

Protein design involves searching a vast space for sequences that are compatible with a defined structure. This can pose significant computational challenges. Cluster expansion is a technique that can accelerate the evaluation of protein energies by generating a simple functional relationship between sequence and energy. The method consists of several steps. First, for a given protein structure, a training set of sequences with known energies is generated. Next, this training set is used to expand energy as a function of clusters consisting of single residues, residue pairs, and higher order terms, if required. The accuracy of the sequence-based expansion is monitored and improved using cross-validation testing and iterative inclusion of additional clusters. As a trade-off for evaluation speed, the cluster-expansion approximation causes prediction errors, which can be reduced by including more training sequences, including higher order terms in the expansion, and/or reducing the sequence space described by the cluster expansion. This article analyzes the sources of error and introduces a method whereby accuracy can be improved by judiciously reducing the described sequence space. The method is applied to describe the sequence-stability relationship for several protein structures: coiled-coil dimers and trimers, a PDZ domain, and T4 lysozyme as examples with computationally derived energies, and SH3 domains in amphiphysin-1 and endophilin-1 as examples where the expanded pseudo-energies are obtained from experiments. Our open-source software package Cluster Expansion Version 1.0 allows users to expand their own energy function of interest and thereby apply cluster expansion to custom problems in protein design. © 2010 Wiley Periodicals, Inc.

Exact hierarchical clustering in one dimension. [in universe

NASA Technical Reports Server (NTRS)

Williams, B. G.; Heavens, A. F.; Peacock, J. A.; Shandarin, S. F.

1991-01-01

The present adhesion model-based one-dimensional simulations of gravitational clustering have yielded bound-object catalogs applicable in tests of analytical approaches to cosmological structure formation. Attention is given to Press-Schechter (1974) type functions, as well as to their density peak-theory modifications and the two-point correlation function estimated from peak theory. The extent to which individual collapsed-object locations can be predicted by linear theory is significant only for objects of near-characteristic nonlinear mass.

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

NASA Astrophysics Data System (ADS)

Grasha, K.; Elmegreen, B. G.; Calzetti, D.; Adamo, A.; Aloisi, A.; Bright, S. N.; Cook, D. O.; Dale, D. A.; Fumagalli, M.; Gallagher, J. S., III; Gouliermis, D. A.; Grebel, E. K.; Kahre, L.; Kim, H.; Krumholz, M. R.; Lee, J. C.; Messa, M.; Ryon, J. E.; Ubeda, L.

2017-06-01

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25-0.6 power, and that the maximum size over which star formation is physically correlated ranges from ˜200 pc to ˜1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are close to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.

Infrared spectra of seeded hydrogen clusters: (para-H2)N-N2O and (ortho-H2)N-N2O, N = 2-13.

PubMed

Tang, Jian; McKellar, A R W

2005-09-15

High-resolution infrared spectra of clusters containing para-H2 and/or ortho-H2 and a single nitrous oxide molecule are studied in the 2225-cm(-1) region of the upsilon1 fundamental band of N2O. The clusters are formed in pulsed supersonic jet expansions from a cooled nozzle and probed using a tunable infrared diode laser spectrometer. The simple symmetric rotor-type spectra generally show no resolved K structure, with prominent Q-branch features for ortho-H2 but not para-H2 clusters. The observed vibrational shifts and rotational constants are reported. There is no obvious indication of superfluid effects for para-H2 clusters up to N=13. Sharp transitions due to even larger clusters are observed, but no definite assignments are possible. Mixed (para-H2)N-(ortho-H2)M-N2O cluster line positions can be well predicted by linear interpolation between the corresponding transitions of the pure clusters.

Thermodynamics of Small Alkali Metal Halide Cluster Ions: Comparison of Classical Molecular Simulations with Experiment and Quantum Chemistry

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

Vlcek, Lukas; Uhlik, Filip; Moucka, Filip

We evaluate the ability of selected classical molecular models to describe the thermodynamic and structural aspects of gas-phase hydration of alkali halide ions and the formation of small water clusters. To understand the effect of many-body interactions (polarization) and charge penetration effects on the accuracy of a force field, we perform Monte Carlo simulations with three rigid water models using different functional forms to account for these effects: (i) point charge non-polarizable SPC/E, (ii) Drude point charge polarizable SWM4- DP, and (iii) Drude Gaussian charge polarizable BK3. Model predictions are compared with experimental Gibbs free energies and enthalpies of ionmore » hydration, and with microscopic structural properties obtained from quantum DFT calculations. We find that all three models provide comparable predictions for pure water clusters and cation hydration, but differ significantly in their description of anion hydration. None of the investigated classical force fields can consistently and quantitatively reproduce the experimental gas phase hydration thermodynamics. The outcome of this study highlights the relation between the functional form that describes the effective intermolecular interactions and the accuracy of the resulting ion hydration properties.« less

Magnetic cluster expansion model for random and ordered magnetic face-centered cubic Fe-Ni-Cr alloys

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

Lavrentiev, M. Yu., E-mail: Mikhail.Lavrentiev@ukaea.uk; Nguyen-Manh, D.; Dudarev, S. L.

A Magnetic Cluster Expansion model for ternary face-centered cubic Fe-Ni-Cr alloys has been developed, using DFT data spanning binary and ternary alloy configurations. Using this Magnetic Cluster Expansion model Hamiltonian, we perform Monte Carlo simulations and explore magnetic structures of alloys over the entire range of compositions, considering both random and ordered alloy structures. In random alloys, the removal of magnetic collinearity constraint reduces the total magnetic moment but does not affect the predicted range of compositions where the alloys adopt low-temperature ferromagnetic configurations. During alloying of ordered fcc Fe-Ni compounds with Cr, chromium atoms tend to replace nickel rathermore » than iron atoms. Replacement of Ni by Cr in ordered alloys with high iron content increases the Curie temperature of the alloys. This can be explained by strong antiferromagnetic Fe-Cr coupling, similar to that found in bcc Fe-Cr solutions, where the Curie temperature increase, predicted by simulations as a function of Cr concentration, is confirmed by experimental observations. In random alloys, both magnetization and the Curie temperature decrease abruptly with increasing chromium content, in agreement with experiment.« less

The Robustness of Cluster Expansion: Assessing the Role of Relaxation

NASA Astrophysics Data System (ADS)

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

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

On the multi-scale description of micro-structured fluids composed of aggregating rods

NASA Astrophysics Data System (ADS)

Perez, Marta; Scheuer, Adrien; Abisset-Chavanne, Emmanuelle; Ammar, Amine; Chinesta, Francisco; Keunings, Roland

2018-05-01

When addressing the flow of concentrated suspensions composed of rods, dense clusters are observed. Thus, the adequate modelling and simulation of such a flow requires addressing the kinematics of these dense clusters and their impact on the flow in which they are immersed. In a former work, we addressed a first modelling framework of these clusters, assumed so dense that they were considered rigid and their kinematics (flow-induced rotation) were totally defined by a symmetric tensor c with unit trace representing the cluster conformation. Then, the rigid nature of the clusters was relaxed, assuming them deformable, and a model giving the evolution of both the cluster shape and its microstructural orientation descriptor (the so-called shape and orientation tensors) was proposed. This paper compares the predictions coming from those models with finer-scale discrete simulations inspired from molecular dynamics modelling.

Formation of prismatic loops from C15 Laves phase interstitial clusters in body-centered cubic iron

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

Zhang, Yongfeng; Bai, Xian-Ming; Tonks, Michael R.

2015-03-01

This Letter reports the transition of C15 phase self-interstitial clusters to loops in body-centered-cubic Iron. Molecular dynamics simulations are performed to evaluate the relative stabilities of difference interstitial cluster configurations including C15 phase structure and <100> and <111>/2 loops. Within a certain size range, C15 cluster are found more stable than loops, and the relative stabilities are reversed beyond that range. In accordance to the crossover in relative stabilities, C15 clusters may grow by absorbing individual interstitials at small sizes and transitions into loops eventually. The transition takes place by nucleation and reaction of <111>/2 loop segments. These observations explainmore » the absence of C15 phase interstitial clusters predicted by density-functional-theory calculations in previous experimental observations. More importantly, the current results provide a new formation mechanism of <100> loops which requires no interaction of loops.« less

Estimating the concrete compressive strength using hard clustering and fuzzy clustering based regression techniques.

PubMed

Nagwani, Naresh Kumar; Deo, Shirish V

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm.

Estimating the Concrete Compressive Strength Using Hard Clustering and Fuzzy Clustering Based Regression Techniques

PubMed Central

Nagwani, Naresh Kumar; Deo, Shirish V.

2014-01-01

Understanding of the compressive strength of concrete is important for activities like construction arrangement, prestressing operations, and proportioning new mixtures and for the quality assurance. Regression techniques are most widely used for prediction tasks where relationship between the independent variables and dependent (prediction) variable is identified. The accuracy of the regression techniques for prediction can be improved if clustering can be used along with regression. Clustering along with regression will ensure the more accurate curve fitting between the dependent and independent variables. In this work cluster regression technique is applied for estimating the compressive strength of the concrete and a novel state of the art is proposed for predicting the concrete compressive strength. The objective of this work is to demonstrate that clustering along with regression ensures less prediction errors for estimating the concrete compressive strength. The proposed technique consists of two major stages: in the first stage, clustering is used to group the similar characteristics concrete data and then in the second stage regression techniques are applied over these clusters (groups) to predict the compressive strength from individual clusters. It is found from experiments that clustering along with regression techniques gives minimum errors for predicting compressive strength of concrete; also fuzzy clustering algorithm C-means performs better than K-means algorithm. PMID:25374939

Visualization and unsupervised predictive clustering of high-dimensional multimodal neuroimaging data.

PubMed

Mwangi, Benson; Soares, Jair C; Hasan, Khader M

2014-10-30

Neuroimaging machine learning studies have largely utilized supervised algorithms - meaning they require both neuroimaging scan data and corresponding target variables (e.g. healthy vs. diseased) to be successfully 'trained' for a prediction task. Noticeably, this approach may not be optimal or possible when the global structure of the data is not well known and the researcher does not have an a priori model to fit the data. We set out to investigate the utility of an unsupervised machine learning technique; t-distributed stochastic neighbour embedding (t-SNE) in identifying 'unseen' sample population patterns that may exist in high-dimensional neuroimaging data. Multimodal neuroimaging scans from 92 healthy subjects were pre-processed using atlas-based methods, integrated and input into the t-SNE algorithm. Patterns and clusters discovered by the algorithm were visualized using a 2D scatter plot and further analyzed using the K-means clustering algorithm. t-SNE was evaluated against classical principal component analysis. Remarkably, based on unlabelled multimodal scan data, t-SNE separated study subjects into two very distinct clusters which corresponded to subjects' gender labels (cluster silhouette index value=0.79). The resulting clusters were used to develop an unsupervised minimum distance clustering model which identified 93.5% of subjects' gender. Notably, from a neuropsychiatric perspective this method may allow discovery of data-driven disease phenotypes or sub-types of treatment responders. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification of structural damage using wavelet-based data classification

NASA Astrophysics Data System (ADS)

Koh, Bong-Hwan; Jeong, Min-Joong; Jung, Uk

2008-03-01

Predicted time-history responses from a finite-element (FE) model provide a baseline map where damage locations are clustered and classified by extracted damage-sensitive wavelet coefficients such as vertical energy threshold (VET) positions having large silhouette statistics. Likewise, the measured data from damaged structure are also decomposed and rearranged according to the most dominant positions of wavelet coefficients. Having projected the coefficients to the baseline map, the true localization of damage can be identified by investigating the level of closeness between the measurement and predictions. The statistical confidence of baseline map improves as the number of prediction cases increases. The simulation results of damage detection in a truss structure show that the approach proposed in this study can be successfully applied for locating structural damage even in the presence of a considerable amount of process and measurement noise.

THE STRUCTURE OF THE MERGING RCS 231953+00 SUPERCLUSTER AT z {approx} 0.9

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

Faloon, A. J.; Webb, T. M. A.; Geach, J. E.

2013-05-10

The RCS 2319+00 supercluster is a massive supercluster at z = 0.9 comprising three optically selected, spectroscopically confirmed clusters separated by <3 Mpc on the plane of the sky. This supercluster is one of a few known examples of the progenitors of present-day massive clusters (10{sup 15} M{sub Sun} by z {approx} 0.5). We present an extensive spectroscopic campaign carried out on the supercluster field resulting, in conjunction with previously published data, in 1961 high-confidence galaxy redshifts. We find 302 structure members spanning three distinct redshift walls separated from one another by {approx}65 Mpc ({Delta} z = 0.03). The componentmore » clusters have spectroscopic redshifts of 0.901, 0.905, and 0.905. The velocity dispersions are consistent with those predicted from X-ray data, giving estimated cluster masses of {approx}10{sup 14.5}-10{sup 14.9} M{sub Sun }. The Dressler-Shectman test finds evidence of substructure in the supercluster field and a friends-of-friends analysis identified five groups in the supercluster, including a filamentary structure stretching between two cluster cores previously identified in the infrared by Coppin et al. The galaxy colors further show this filamentary structure to be a unique region of activity within the supercluster, comprised mainly of blue galaxies compared to the {approx}43%-77% red-sequence galaxies present in the other groups and cluster cores. Richness estimates from stacked luminosity function fits result in average group mass estimates consistent with {approx}10{sup 13} M{sub Sun} halos. Currently, 22% of our confirmed members reside in {approx}> 10{sup 13} M{sub Sun} groups/clusters destined to merge onto the most massive cluster, in agreement with the massive halo galaxy fractions important in cluster galaxy pre-processing in N-body simulation merger tree studies.« less

IRAS galaxies and the large-scale structure in the CfA slice

NASA Technical Reports Server (NTRS)

Babul, Arif; Postman, Marc

1990-01-01

The spatial distributions of the IRAS and the optical galaxies in the first CfA slice are compared. The IRAS galaxies are generally less clustered than optical ones, but their distribution is essentially identical to that of late-type optical galaxies. The discrepancy between the clustering properties of the IRAS and optical samples in the CfA slice region is found to be entirely due to the paucity of IRAS galaxies in the core of the Coma cluster. The spatial distributions of the IRAS and the optical galaxies, both late and early types, outside the dense core of the Coma cluster are entirely consistent with each other. This conflicts with the prediction of the linear biasing scenario.

Effect of a chameleon scalar field on the cosmic microwave background

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

Davis, Anne-Christine; Schelpe, Camilla A. O.; Shaw, Douglas J.

2009-09-15

We show that a direct coupling between a chameleonlike scalar field and photons can give rise to a modified Sunyaev-Zel'dovich (SZ) effect in the cosmic microwave background (CMB). The coupling induces a mixing between chameleon particles and the CMB photons when they pass through the magnetic field of a galaxy cluster. Both the intensity and the polarization of the radiation are modified. The degree of modification depends strongly on the properties of the galaxy cluster such as magnetic field strength and electron number density. Existing SZ measurements of the Coma cluster enable us to place constraints on the photon-chameleon coupling.more » The constrained conversion probability in the cluster is P{sub Coma}(204 GHz)<6.2x10{sup -5} at 95% confidence, corresponding to an upper bound on the coupling strength of g{sub eff}{sup (cell)}<2.2x10{sup -8} GeV{sup -1} or g{sub eff}{sup (Kolmo)}<(7.2-32.5)x10{sup -10} GeV{sup -1}, depending on the model that is assumed for the cluster magnetic field structure. We predict the radial profile of the chameleonic CMB intensity decrement. We find that the chameleon effect extends farther toward the edges of the cluster than the thermal SZ effect. Thus we might see a discrepancy between the x-ray emission data and the observed SZ intensity decrement. We further predict the expected change to the CMB polarization arising from the existence of a chameleonlike scalar field. These predictions could be verified or constrained by future CMB experiments.« less

Spatio-Temporal Structure, Path Characteristics, and Perceptual Grouping in Immediate Serial Spatial Recall

PubMed Central

De Lillo, Carlo; Kirby, Melissa; Poole, Daniel

2016-01-01

Immediate serial spatial recall measures the ability to retain sequences of locations in short-term memory and is considered the spatial equivalent of digit span. It is tested by requiring participants to reproduce sequences of movements performed by an experimenter or displayed on a monitor. Different organizational factors dramatically affect serial spatial recall but they are often confounded or underspecified. Untangling them is crucial for the characterization of working-memory models and for establishing the contribution of structure and memory capacity to spatial span. We report five experiments assessing the relative role and independence of factors that have been reported in the literature. Experiment 1 disentangled the effects of spatial clustering and path-length by manipulating the distance of items displayed on a touchscreen monitor. Long-path sequences segregated by spatial clusters were compared with short-path sequences not segregated by clusters. Recall was more accurate for sequences segregated by clusters independently from path-length. Experiment 2 featured conditions where temporal pauses were introduced between or within cluster boundaries during the presentation of sequences with the same paths. Thus, the temporal structure of the sequences was either consistent or inconsistent with a hierarchical representation based on segmentation by spatial clusters but the effect of structure could not be confounded with effects of path-characteristics. Pauses at cluster boundaries yielded more accurate recall, as predicted by a hierarchical model. In Experiment 3, the systematic manipulation of sequence structure, path-length, and presence of path-crossings of sequences showed that structure explained most of the variance, followed by the presence/absence of path-crossings, and path-length. Experiments 4 and 5 replicated the results of the previous experiments in immersive virtual reality navigation tasks where the viewpoint of the observer changed dynamically during encoding and recall. This suggested that the effects of structure in spatial span are not dependent on perceptual grouping processes induced by the aerial view of the stimulus array typically afforded by spatial recall tasks. These results demonstrate the independence of coding strategies based on structure from effects of path characteristics and perceptual grouping in immediate serial spatial recall. PMID:27891101

Cluster approach to the prediction of thermodynamic and transport properties of ionic liquids

NASA Astrophysics Data System (ADS)

Seeger, Zoe L.; Kobayashi, Rika; Izgorodina, Ekaterina I.

2018-05-01

The prediction of physicochemical properties of ionic liquids such as conductivity and melting point would substantially aid the targeted design of ionic liquids for specific applications ranging from solvents for extraction of valuable chemicals to biowaste to electrolytes in alternative energy devices. The previously published study connecting the interaction energies of single ion pairs (1 IP) of ionic liquids to their thermodynamic and transport properties has been extended to larger systems consisting of two ion pairs (2 IPs), in which many-body and same-ion interactions are included. Routinely used cations, of the imidazolium and pyrrolidinium families, were selected in the study coupled with chloride, tetrafluoroborate, and dicyanamide. Their two ion pair clusters were subjected to extensive configuration screening to establish most stable structures. Interaction energies of these clusters were calculated at the spin-ratio scaled MP2 (SRS-MP2) level for the correlation interaction energy, and a newly developed scaled Hartree-Fock method for the rest of energetic contributions to interaction energy. A full geometry screening for each cation-anion combination resulted in 192 unique structures, whose stability was assessed using two criteria—widely used interaction energy and total electronic energy. Furthermore, the ratio of interaction energy to its dispersion component was correlated with experimentally observed melting points in 64 energetically favourable structures. These systems were also used to test the correlation of the dispersion contribution to interaction energy with measured conductivity.

Relationship between global structural parameters and Enzyme Commission hierarchy: implications for function prediction.

PubMed

Boareto, Marcelo; Yamagishi, Michel E B; Caticha, Nestor; Leite, Vitor B P

2012-10-01

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multiple Aromaticity and Antiaromaticity in Silicon Clusters

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

Zhai, Hua JIN.; Kuznetsov, A E.; Boldyrev, Alexander I.

A series of silicon clusters containing four atoms but with different charge states (Si{sub 4}{sup 2+}, Si{sub 4}, Si{sub 4}{sup 2-}, and NaSi{sub 4}{sup -}) were studied by photoelectron spectroscopy and ab initio calculations. Structure evolution and chemical bonding in this series were interpreted in terms of aromaticity and antiaromaticity, which allowed the prediction of how structures of the four-atom silicon clusters change upon addition or removal of two electrons. It is shown that Si{sub 4}{sup 2+} is square-planar, analogous to the recently discovered aromatic Al{sub 4}{sup 2-} cluster. Upon addition of two electrons, neutral Si{sub 4} becomes {sigma}-antiaromatic andmore » exhibits a rhombus distortion. Adding two more electrons to Si{sub 4} leads to two energetically close structures of Si{sub 4}{sup 2-}: either a double antiaromatic parallelogram structure or an aromatic system with a butterfly distortion. Because of the electronic instability of doubly charged Si{sub 4}{sup 2-}, a stabilizing cation (Na{sup +}) was used to produce Si{sub 4}{sup 2-} in the gas phase in the form of Na{sup +}[Si{sub 4}{sup 2-}], which was characterized experimentally by photoelectron spectroscopy. Multiple antiaromaticity in the parallelogram Na{sup +}[Si{sub 4}{sup 2-}] species is highly unusual.« less

Diverse assembly behavior in colloidal Platonic polyhedral sphere clusters

NASA Astrophysics Data System (ADS)

Marson, Ryan; Teich, Erin; Dshemuchadse, Julia; Glotzer, Sharon; Larson, Ronald

We simulate the self-assembly of colloidal ``polyhedral sphere clusters (PSCs)'', which consist of equal-sized spheres placed at the vertices of a polyhedron such that they just touch along each edge. These colloidal building blocks have recently been experimentally fabricated; here we predict crystal structures that would appear in the phase diagram of resulting particle assemblies. We use Brownian dynamics (BD) simulations of rigid body clusters performed in the open-source GPU-based HOOMD-Blue particle simulation package to show the assembly behavior of the 5 Platonic PSCs. The simulations contain as many as 4096 individual polyhedra, across over 30 different densities per cluster geometry, with some ordered phases possessing unit cells with 20 or more particles. We observe the formation of not only traditional cubic structures such as BCC and FCC, but also more complex phases having structure symmetries with Pearson symbols - hP7, cP20, cI2, mP6, and hR3. The observations reported here will serve as a guide for future colloidal assembly experiments using an expanded library of PSCs, consisting of other regular and irregular polyhedra, allowing researchers to target specific arrangements of ``halo'' and ``core'' particles for technologically relevant applications including photonics and structural color.

Conformation, structure and molecular solvation: a spectroscopic and computational study of 2-phenoxy ethanol and its singly and multiply hydrated clusters

NASA Astrophysics Data System (ADS)

Macleod, Neil A.; Simons, John P.

2002-10-01

The conformational landscapes of 2-phenoxy ethanol (POX) and its hydrated clusters have been studied in the gas-phase, providing a model for pharmaceutical β-blockers. A combination of experimental techniques, including resonant two-photon ionisation (R2PI), laser-induced-fluorescence (LIF) and resonant ion-dip infra-red spectroscopy (RIDIRS), coupled with high-level ab initio calculations has allowed the assignment of the individually resolved spectral features to discrete conformational and supra-molecular structures. Assignments were made by comparison of experimental vibrational spectra and partially resolved ultra-violet rotational band contours with those predicted from quantum chemical calculations. The isolated molecule displays a solitary structure with an extended geometry of the side-chain which is stabilised by an intramolecular hydrogen-bond between the alcohol (proton donor) and the ether (proton acceptor) groups of the side-chain. In singly hydrated clusters the water molecule is accommodated by insertion into the intramolecular hydrogen-bond. In the doubly hydrated and higher clusters cyclic structures are generated which incorporate both the water molecules and the terminal OH group of the side-chain; additional (weak) hydrogen bonded interactions with the phenoxy group provide a degree of selectivity but essentially, the water 'droplet' forms on the end of the alcohol side-chain.

Octupole deformation in neutron-rich actinides and superheavy nuclei and the role of nodal structure of single-particle wavefunctions in extremely deformed structures of light nuclei

NASA Astrophysics Data System (ADS)

Afanasjev, A. V.; Abusara, H.; Agbemava, S. E.

2018-03-01

Octupole deformed shapes in neutron-rich actinides and superheavy nuclei as well as extremely deformed shapes of the N∼ Z light nuclei have been investigated within the framework of covariant density functional theory. We confirmed the presence of new region of octupole deformation in neutron-rich actinides with the center around Z∼ 96,N∼ 196 but our calculations do not predict octupole deformation in the ground states of superheavy Z≥slant 108 nuclei. As exemplified by the study of 36Ar, the nodal structure of the wavefunction of occupied single-particle orbitals in extremely deformed structures allows to understand the formation of the α-clusters in very light nuclei, the suppression of the α-clusterization with the increase of mass number, the formation of ellipsoidal mean-field type structures and nuclear molecules.

Structure Elucidation of Mixed-Linker Zeolitic Imidazolate Frameworks by Solid-State (1)H CRAMPS NMR Spectroscopy and Computational Modeling.

PubMed

Jayachandrababu, Krishna C; Verploegh, Ross J; Leisen, Johannes; Nieuwendaal, Ryan C; Sholl, David S; Nair, Sankar

2016-06-15

Mixed-linker zeolitic imidazolate frameworks (ZIFs) are nanoporous materials that exhibit continuous and controllable tunability of properties like effective pore size, hydrophobicity, and organophilicity. The structure of mixed-linker ZIFs has been studied on macroscopic scales using gravimetric and spectroscopic techniques. However, it has so far not been possible to obtain information on unit-cell-level linker distribution, an understanding of which is key to predicting and controlling their adsorption and diffusion properties. We demonstrate the use of (1)H combined rotation and multiple pulse spectroscopy (CRAMPS) NMR spin exchange measurements in combination with computational modeling to elucidate potential structures of mixed-linker ZIFs, particularly the ZIF 8-90 series. All of the compositions studied have structures that have linkers mixed at a unit-cell-level as opposed to separated or highly clustered phases within the same crystal. Direct experimental observations of linker mixing were accomplished by measuring the proton spin exchange behavior between functional groups on the linkers. The data were then fitted to a kinetic spin exchange model using proton positions from candidate mixed-linker ZIF structures that were generated computationally using the short-range order (SRO) parameter as a measure of the ordering, clustering, or randomization of the linkers. The present method offers the advantages of sensitivity without requiring isotope enrichment, a straightforward NMR pulse sequence, and an analysis framework that allows one to relate spin diffusion behavior to proposed atomic positions. We find that structures close to equimolar composition of the two linkers show a greater tendency for linker clustering than what would be predicted based on random models. Using computational modeling we have also shown how the window-type distribution in experimentally synthesized mixed-linker ZIF-8-90 materials varies as a function of their composition. The structural information thus obtained can be further used for predicting, screening, or understanding the tunable adsorption and diffusion behavior of mixed-linker ZIFs, for which the knowledge of linker distributions in the framework is expected to be important.

Quantum chemical study of the structure, spectroscopy and reactivity of NO+.(H2O)n=1-5 clusters

NASA Astrophysics Data System (ADS)

Linton, Kirsty A.; Wright, Timothy G.; Besley, Nicholas A.

2018-03-01

Quantum chemical methods including Møller-Plesset perturbation (MP2) theory and density functional theory (DFT) have been used to study the structure, spectroscopy and reactivity of NO+.(H2O)n=1-5 clusters. MP2/6-311++G** calculations are shown to describe the structure and spectroscopy of the clusters well. DFT calculations with exchange-correlation functionals with a low fraction of Hartree-Fock exchange give a binding energy of NO+.(H2O) that is too high and incorrectly predict the lowest energy structure of NO+.(H2O)2, and this error may be associated with a delocalization of charge onto the water molecule directly binding to NO+. Ab initio molecular dynamics (AIMD) simulations were performed to study the NO+.(H2O)5 H+.(H2O)4 + HONO reaction to investigate the formation of HONO from NO+.(H2O)5. Whether an intracluster reaction to form HONO is observed depends on the level of electronic structure theory used. Of note is that methods that accurately describe the relative energies of the product and reactant clusters did not show reactions on the timescales studied. This suggests that in the upper atmosphere the reaction may occur owing to the energy present in the NO+.(H2O)5 complex following its formation. This article is part of the theme issue `Modern theoretical chemistry'.

Improving local clustering based top-L link prediction methods via asymmetric link clustering information

NASA Astrophysics Data System (ADS)

Wu, Zhihao; Lin, Youfang; Zhao, Yiji; Yan, Hongyan

2018-02-01

Networks can represent a wide range of complex systems, such as social, biological and technological systems. Link prediction is one of the most important problems in network analysis, and has attracted much research interest recently. Many link prediction methods have been proposed to solve this problem with various techniques. We can note that clustering information plays an important role in solving the link prediction problem. In previous literatures, we find node clustering coefficient appears frequently in many link prediction methods. However, node clustering coefficient is limited to describe the role of a common-neighbor in different local networks, because it cannot distinguish different clustering abilities of a node to different node pairs. In this paper, we shift our focus from nodes to links, and propose the concept of asymmetric link clustering (ALC) coefficient. Further, we improve three node clustering based link prediction methods via the concept of ALC. The experimental results demonstrate that ALC-based methods outperform node clustering based methods, especially achieving remarkable improvements on food web, hamster friendship and Internet networks. Besides, comparing with other methods, the performance of ALC-based methods are very stable in both globalized and personalized top-L link prediction tasks.

Theoretical studies on photoelectron and IR spectral properties of Br2.-(H2O)n clusters.

PubMed

Pathak, A K; Mukherjee, T; Maity, D K

2007-07-28

We report vertical detachment energy (VDE) and IR spectra of Br2.-.(H2O)n clusters (n=1-8) based on first principles electronic structure calculations. Cluster structures and IR spectra are calculated at Becke's half-and-half hybrid exchange-correlation functional (BHHLYP) with a triple split valence basis function, 6-311++G(d,p). VDE for the hydrated clusters is calculated based on second order Moller-Plesset perturbation (MP2) theory with the same set of basis function. On full geometry optimization, it is observed that conformers having interwater hydrogen bonding among solvent water molecules are more stable than the structures having double or single hydrogen bonded structures between the anionic solute, Br2.-, and solvent water molecules. Moreover, a conformer having cyclic interwater hydrogen bonded network is predicted to be more stable for each size hydrated cluster. It is also noticed that up to four solvent H2O units can reside around the solute in a cyclic interwater hydrogen bonded network. The excess electron in these hydrated clusters is localized over the solute atoms. Weighted average VDE is calculated for each size (n) cluster based on statistical population of the conformers at 150 K. A linear relationship is obtained for VDE versus (n+3)(-1/3) and bulk VDE of Br2.- aqueous solution is calculated as 10.01 eV at MP2 level of theory. BHHLYP density functional is seen to make a systematic overestimation in VDE values by approximately 0.5 eV compared to MP2 data in all the hydrated clusters. It is observed that hydration increases VDE of bromine dimer anion system by approximately 6.4 eV. Calculated IR spectra show that the formation of Br2.--water clusters induces large shifts from the normal O-H stretching bands of isolated water keeping bending modes rather insensitive. Hydrated clusters, Br2.-.(H2O)n, show characteristic sharp features of O-H stretching bands of water in the small size clusters.

Theoretical studies on photoelectron and IR spectral properties of Br2.-(H2O)n clusters

NASA Astrophysics Data System (ADS)

Pathak, A. K.; Mukherjee, T.; Maity, D. K.

2007-07-01

We report vertical detachment energy (VDE) and IR spectra of Br2•-•(H2O)n clusters (n=1-8) based on first principles electronic structure calculations. Cluster structures and IR spectra are calculated at Becke's half-and-half hybrid exchange-correlation functional (BHHLYP) with a triple split valence basis function, 6-311++G(d,p). VDE for the hydrated clusters is calculated based on second order Moller-Plesset perturbation (MP2) theory with the same set of basis function. On full geometry optimization, it is observed that conformers having interwater hydrogen bonding among solvent water molecules are more stable than the structures having double or single hydrogen bonded structures between the anionic solute, Br2•-, and solvent water molecules. Moreover, a conformer having cyclic interwater hydrogen bonded network is predicted to be more stable for each size hydrated cluster. It is also noticed that up to four solvent H2O units can reside around the solute in a cyclic interwater hydrogen bonded network. The excess electron in these hydrated clusters is localized over the solute atoms. Weighted average VDE is calculated for each size (n) cluster based on statistical population of the conformers at 150K. A linear relationship is obtained for VDE versus (n+3)-1/3 and bulk VDE of Br2•- aqueous solution is calculated as 10.01eV at MP2 level of theory. BHHLYP density functional is seen to make a systematic overestimation in VDE values by ˜0.5eV compared to MP2 data in all the hydrated clusters. It is observed that hydration increases VDE of bromine dimer anion system by ˜6.4eV. Calculated IR spectra show that the formation of Br2•--water clusters induces large shifts from the normal O-H stretching bands of isolated water keeping bending modes rather insensitive. Hydrated clusters, Br2•-•(H2O)n, show characteristic sharp features of O-H stretching bands of water in the small size clusters.

Structures of cage, prism, and book isomers of water hexamer from broadband rotational spectroscopy.

PubMed

Pérez, Cristóbal; Muckle, Matt T; Zaleski, Daniel P; Seifert, Nathan A; Temelso, Berhane; Shields, George C; Kisiel, Zbigniew; Pate, Brooks H

2012-05-18

Theory predicts the water hexamer to be the smallest water cluster with a three-dimensional hydrogen-bonding network as its minimum energy structure. There are several possible low-energy isomers, and calculations with different methods and basis sets assign them different relative stabilities. Previous experimental work has provided evidence for the cage, book, and cyclic isomers, but no experiment has identified multiple coexisting structures. Here, we report that broadband rotational spectroscopy in a pulsed supersonic expansion unambiguously identifies all three isomers; we determined their oxygen framework structures by means of oxygen-18-substituted water (H(2)(18)O). Relative isomer populations at different expansion conditions establish that the cage isomer is the minimum energy structure. Rotational spectra consistent with predicted heptamer and nonamer structures have also been identified.

Geometric, electronic, and bonding properties of AuNM (N = 1-7, M = Ni, Pd, Pt) clusters.

PubMed

Yuan, D W; Wang, Yang; Zeng, Zhi

2005-03-15

Employing first-principles methods, based on density functional theory, we report the ground state geometric and electronic structures of gold clusters doped with platinum group atoms, Au(N)M (N = 1-7, M = Ni, Pd, Pt). The stability and electronic properties of Ni-doped gold clusters are similar to that of pure gold clusters with an enhancement of bond strength. Due to the strong d-d or s-d interplay between impurities and gold atoms originating in the relativistic effects and unique properties of dopant delocalized s-electrons in Pd- and Pt-doped gold clusters, the dopant atoms markedly change the geometric and electronic properties of gold clusters, and stronger bond energies are found in Pt-doped clusters. The Mulliken populations analysis of impurities and detailed decompositions of bond energies as well as a variety of density of states of the most stable dopant gold clusters are given to understand the different effects of individual dopant atom on bonding and electronic properties of dopant gold clusters. From the electronic properties of dopant gold clusters, the different chemical reactivity toward O(2), CO, or NO molecule is predicted in transition metal-doped gold clusters compared to pure gold clusters.

Role and Regulation of the Flp/Tad Pilus in the Virulence of Pectobacterium atrosepticum SCRI1043 and Pectobacterium wasabiae SCC3193

PubMed Central

Nykyri, Johanna; Mattinen, Laura; Niemi, Outi; Adhikari, Satish; Kõiv, Viia; Somervuo, Panu; Fang, Xin; Auvinen, Petri; Mäe, Andres; Palva, E. Tapio; Pirhonen, Minna

2013-01-01

In this study, we characterized a putative Flp/Tad pilus-encoding gene cluster, and we examined its regulation at the transcriptional level and its role in the virulence of potato pathogenic enterobacteria of the genus Pectobacterium. The Flp/Tad pilus-encoding gene clusters in Pectobacterium atrosepticum, Pectobacterium wasabiae and Pectobacterium aroidearum were compared to previously characterized flp/tad gene clusters, including that of the well-studied Flp/Tad pilus model organism Aggregatibacter actinomycetemcomitans, in which this pilus is a major virulence determinant. Comparative analyses revealed substantial protein sequence similarity and open reading frame synteny between the previously characterized flp/tad gene clusters and the cluster in Pectobacterium, suggesting that the predicted flp/tad gene cluster in Pectobacterium encodes a Flp/Tad pilus-like structure. We detected genes for a novel two-component system adjacent to the flp/tad gene cluster in Pectobacterium, and mutant analysis demonstrated that this system has a positive effect on the transcription of selected Flp/Tad pilus biogenesis genes, suggesting that this response regulator regulate the flp/tad gene cluster. Mutagenesis of either the predicted regulator gene or selected Flp/Tad pilus biogenesis genes had a significant impact on the maceration ability of the bacterial strains in potato tubers, indicating that the Flp/Tad pilus-encoding gene cluster represents a novel virulence determinant in Pectobacterium. Soft-rot enterobacteria in the genera Pectobacterium and Dickeya are of great agricultural importance, and an investigation of the virulence of these pathogens could facilitate improvements in agricultural practices, thus benefiting farmers, the potato industry and consumers. PMID:24040039

Role and regulation of the Flp/Tad pilus in the virulence of Pectobacterium atrosepticum SCRI1043 and Pectobacterium wasabiae SCC3193.

PubMed

Nykyri, Johanna; Mattinen, Laura; Niemi, Outi; Adhikari, Satish; Kõiv, Viia; Somervuo, Panu; Fang, Xin; Auvinen, Petri; Mäe, Andres; Palva, E Tapio; Pirhonen, Minna

2013-01-01

In this study, we characterized a putative Flp/Tad pilus-encoding gene cluster, and we examined its regulation at the transcriptional level and its role in the virulence of potato pathogenic enterobacteria of the genus Pectobacterium. The Flp/Tad pilus-encoding gene clusters in Pectobacterium atrosepticum, Pectobacterium wasabiae and Pectobacterium aroidearum were compared to previously characterized flp/tad gene clusters, including that of the well-studied Flp/Tad pilus model organism Aggregatibacter actinomycetemcomitans, in which this pilus is a major virulence determinant. Comparative analyses revealed substantial protein sequence similarity and open reading frame synteny between the previously characterized flp/tad gene clusters and the cluster in Pectobacterium, suggesting that the predicted flp/tad gene cluster in Pectobacterium encodes a Flp/Tad pilus-like structure. We detected genes for a novel two-component system adjacent to the flp/tad gene cluster in Pectobacterium, and mutant analysis demonstrated that this system has a positive effect on the transcription of selected Flp/Tad pilus biogenesis genes, suggesting that this response regulator regulate the flp/tad gene cluster. Mutagenesis of either the predicted regulator gene or selected Flp/Tad pilus biogenesis genes had a significant impact on the maceration ability of the bacterial strains in potato tubers, indicating that the Flp/Tad pilus-encoding gene cluster represents a novel virulence determinant in Pectobacterium. Soft-rot enterobacteria in the genera Pectobacterium and Dickeya are of great agricultural importance, and an investigation of the virulence of these pathogens could facilitate improvements in agricultural practices, thus benefiting farmers, the potato industry and consumers.

Overview of T.E.S.T. (Toxicity Estimation Software Tool)

EPA Science Inventory

This talk provides an overview of T.E.S.T. (Toxicity Estimation Software Tool). T.E.S.T. predicts toxicity values and physical properties using a variety of different QSAR (quantitative structure activity relationship) approaches including hierarchical clustering, group contribut...

Speckle lithography for fabricating Gaussian, quasi-random 2D structures and black silicon structures.

PubMed

Bingi, Jayachandra; Murukeshan, Vadakke Matham

2015-12-18

Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices.

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

Jiang, Deen

A profound connection has been found between the structures of thiolated gold clusters and the combinatorial problem of pairing up dots on a surface. The bridge is the concept of staple fitness: the fittest combination corresponds to the experimental structure. This connection has been demonstrated for both Au{sub 25}(SR){sub 18} and Au{sub 38}(SR){sub 24} (-SR being a thiolate group) and applied to predict a promising structure for the recently synthesized Au{sub 19}(SR){sub 13}.

Exploring the Structure of Spatial Representations

PubMed Central

Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela

2016-01-01

It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

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

Tjong, Harianto; Li, Wenyuan; Kalhor, Reza

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Here, our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm themore » presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.« less

Population-based 3D genome structure analysis reveals driving forces in spatial genome organization

DOE PAGES

Tjong, Harianto; Li, Wenyuan; Kalhor, Reza; ...

2016-03-07

Conformation capture technologies (e.g., Hi-C) chart physical interactions between chromatin regions on a genome-wide scale. However, the structural variability of the genome between cells poses a great challenge to interpreting ensemble-averaged Hi-C data, particularly for long-range and interchromosomal interactions. Here, we present a probabilistic approach for deconvoluting Hi-C data into a model population of distinct diploid 3D genome structures, which facilitates the detection of chromatin interactions likely to co-occur in individual cells. Here, our approach incorporates the stochastic nature of chromosome conformations and allows a detailed analysis of alternative chromatin structure states. For example, we predict and experimentally confirm themore » presence of large centromere clusters with distinct chromosome compositions varying between individual cells. The stability of these clusters varies greatly with their chromosome identities. We show that these chromosome-specific clusters can play a key role in the overall chromosome positioning in the nucleus and stabilizing specific chromatin interactions. By explicitly considering genome structural variability, our population-based method provides an important tool for revealing novel insights into the key factors shaping the spatial genome organization.« less

A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure.

PubMed

Hebels, Dennie G A J; Rasche, Axel; Herwig, Ralf; van Westen, Gerard J P; Jennen, Danyel G J; Kleinjans, Jos C S

2016-01-01

When evaluating compound similarity, addressing multiple sources of information to reach conclusions about common pharmaceutical and/or toxicological mechanisms of action is a crucial strategy. In this chapter, we describe a systems biology approach that incorporates analyses of hepatotoxicant data for 33 compounds from three different sources: a chemical structure similarity analysis based on the 3D Tanimoto coefficient, a chemical structure-based protein target prediction analysis, and a cross-study/cross-platform meta-analysis of in vitro and in vivo human and rat transcriptomics data derived from public resources (i.e., the diXa data warehouse). Hierarchical clustering of the outcome scores of the separate analyses did not result in a satisfactory grouping of compounds considering their known toxic mechanism as described in literature. However, a combined analysis of multiple data types may hypothetically compensate for missing or unreliable information in any of the single data types. We therefore performed an integrated clustering analysis of all three data sets using the R-based tool iClusterPlus. This indeed improved the grouping results. The compound clusters that were formed by means of iClusterPlus represent groups that show similar gene expression while simultaneously integrating a similarity in structure and protein targets, which corresponds much better with the known mechanism of action of these toxicants. Using an integrative systems biology approach may thus overcome the limitations of the separate analyses when grouping liver toxicants sharing a similar mechanism of toxicity.

Atoll-scale patterns in coral reef community structure: Human signatures on Ulithi Atoll, Micronesia.

PubMed

Crane, Nicole L; Nelson, Peter; Abelson, Avigdor; Precoda, Kristin; Rulmal, John; Bernardi, Giacomo; Paddack, Michelle

2017-01-01

The dynamic relationship between reefs and the people who utilize them at a subsistence level is poorly understood. This paper characterizes atoll-scale patterns in shallow coral reef habitat and fish community structure, and correlates these with environmental characteristics and anthropogenic factors, critical to conservation efforts for the reefs and the people who depend on them. Hierarchical clustering analyses by site for benthic composition and fish community resulted in the same 3 major clusters: cluster 1-oceanic (close proximity to deep water) and uninhabited (low human impact); cluster 2-oceanic and inhabited (high human impact); and cluster 3-lagoonal (facing the inside of the lagoon) and inhabited (highest human impact). Distance from village, reef exposure to deep water and human population size had the greatest effect in predicting the fish and benthic community structure. Our study demonstrates a strong association between benthic and fish community structure and human use across the Ulithi Atoll (Yap State, Federated States of Micronesia) and confirms a pattern observed by local people that an 'opportunistic' scleractinian coral (Montipora sp.) is associated with more highly impacted reefs. Our findings suggest that small human populations (subsistence fishing) can nevertheless have considerable ecological impacts on reefs due, in part, to changes in fishing practices rather than overfishing per se, as well as larger global trends. Findings from this work can assist in building local capacity to manage reef resources across an atoll-wide scale, and illustrates the importance of anthropogenic impact even in small communities.

Do Staphylococcus epidermidis Genetic Clusters Predict Isolation Sources?

PubMed Central

Tolo, Isaiah; Thomas, Jonathan C.; Fischer, Rebecca S. B.; Brown, Eric L.; Gray, Barry M.

2016-01-01

Staphylococcus epidermidis is a ubiquitous colonizer of human skin and a common cause of medical device-associated infections. The extent to which the population genetic structure of S. epidermidis distinguishes commensal from pathogenic isolates is unclear. Previously, Bayesian clustering of 437 multilocus sequence types (STs) in the international database revealed a population structure of six genetic clusters (GCs) that may reflect the species' ecology. Here, we first verified the presence of six GCs, including two (GC3 and GC5) with significant admixture, in an updated database of 578 STs. Next, a single nucleotide polymorphism (SNP) assay was developed that accurately assigned 545 (94%) of 578 STs to GCs. Finally, the hypothesis that GCs could distinguish isolation sources was tested by SNP typing and GC assignment of 154 isolates from hospital patients with bacteremia and those with blood culture contaminants and from nonhospital carriage. GC5 was isolated almost exclusively from hospital sources. GC1 and GC6 were isolated from all sources but were overrepresented in isolates from nonhospital and infection sources, respectively. GC2, GC3, and GC4 were relatively rare in this collection. No association was detected between fdh-positive isolates (GC2 and GC4) and nonhospital sources. Using a machine learning algorithm, GCs predicted hospital and nonhospital sources with 80% accuracy and predicted infection and contaminant sources with 45% accuracy, which was comparable to the results seen with a combination of five genetic markers (icaA, IS256, sesD [bhp], mecA, and arginine catabolic mobile element [ACME]). Thus, analysis of population structure with subgenomic data shows the distinction of hospital and nonhospital sources and the near-inseparability of sources within a hospital. PMID:27076664

The Bologna Annotation Resource (BAR 3.0): improving protein functional annotation.

PubMed

Profiti, Giuseppe; Martelli, Pier Luigi; Casadio, Rita

2017-07-03

BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints. BAR 3.0 includes 28 869 663 sequences in 1 361 773 clusters, of which 22.2% (22 241 661 sequences) and 47.4% (24 555 055 sequences) have at least one validated GO term and one PFAM domain, respectively. 1.4% of the clusters (36% of all sequences) include PDB structures and the cluster is associated to a hidden Markov model that allows building template-target alignment suitable for structural modeling. Some other 3 399 026 sequences are singletons. BAR 3.0 offers an improved search interface, allowing queries by UniProtKB-accession, Fasta sequence, GO-term, PFAM-domain, organism, PDB and ligand/s. When evaluated on the CAFA2 targets, BAR 3.0 largely outperforms our previous version and scores among state-of-the-art methods. BAR 3.0 is publicly available and accessible at http://bar.biocomp.unibo.it/bar3. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity.

PubMed

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-09-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. © 2015 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Comparison of topological clustering within protein networks using edge metrics that evaluate full sequence, full structure, and active site microenvironment similarity

PubMed Central

Leuthaeuser, Janelle B; Knutson, Stacy T; Kumar, Kiran; Babbitt, Patricia C; Fetrow, Jacquelyn S

2015-01-01

The development of accurate protein function annotation methods has emerged as a major unsolved biological problem. Protein similarity networks, one approach to function annotation via annotation transfer, group proteins into similarity-based clusters. An underlying assumption is that the edge metric used to identify such clusters correlates with functional information. In this contribution, this assumption is evaluated by observing topologies in similarity networks using three different edge metrics: sequence (BLAST), structure (TM-Align), and active site similarity (active site profiling, implemented in DASP). Network topologies for four well-studied protein superfamilies (enolase, peroxiredoxin (Prx), glutathione transferase (GST), and crotonase) were compared with curated functional hierarchies and structure. As expected, network topology differs, depending on edge metric; comparison of topologies provides valuable information on structure/function relationships. Subnetworks based on active site similarity correlate with known functional hierarchies at a single edge threshold more often than sequence- or structure-based networks. Sequence- and structure-based networks are useful for identifying sequence and domain similarities and differences; therefore, it is important to consider the clustering goal before deciding appropriate edge metric. Further, conserved active site residues identified in enolase and GST active site subnetworks correspond with published functionally important residues. Extension of this analysis yields predictions of functionally determinant residues for GST subgroups. These results support the hypothesis that active site similarity-based networks reveal clusters that share functional details and lay the foundation for capturing functionally relevant hierarchies using an approach that is both automatable and can deliver greater precision in function annotation than current similarity-based methods. PMID:26073648

Integrated Theory of Planned Behavior with Extrinsic Motivation to Predict Intention Not to Use Illicit Drugs by Fifth-Grade Students in Taiwan

ERIC Educational Resources Information Center

Liao, Jung-Yu; Chang, Li-Chun; Hsu, Hsiao-Pei; Huang, Chiu-Mieh; Huang, Su-Fei; Guo, Jong-Long

2017-01-01

This study assessed the effects of a model that integrated the theory of planned behavior (TPB) with extrinsic motivation (EM) in predicting the intentions of fifth-grade students to not use illicit drugs. A cluster-sampling design was adopted in a cross-sectional survey (N = 571). The structural equation modeling results showed that the model…

Microhydration and the Enhanced Acidity of Free Radicals.

PubMed

Walton, John C

2018-02-14

Recent theoretical research employing a continuum solvent model predicted that radical centers would enhance the acidity (RED-shift) of certain proton-donor molecules. Microhydration studies employing a DFT method are reported here with the aim of establishing the effect of the solvent micro-structure on the acidity of radicals with and without RED-shifts. Microhydration cluster structures were obtained for carboxyl, carboxy-ethynyl, carboxy-methyl, and hydroperoxyl radicals. The numbers of water molecules needed to induce spontaneous ionization were determined. The hydration clusters formed primarily round the CO₂ units of the carboxylate-containing radicals. Only 4 or 5 water molecules were needed to induce ionization of carboxyl and carboxy-ethynyl radicals, thus corroborating their large RED-shifts.

CASP10-BCL::Fold efficiently samples topologies of large proteins.

PubMed

Heinze, Sten; Putnam, Daniel K; Fischer, Axel W; Kohlmann, Tim; Weiner, Brian E; Meiler, Jens

2015-03-01

During CASP10 in summer 2012, we tested BCL::Fold for prediction of free modeling (FM) and template-based modeling (TBM) targets. BCL::Fold assembles the tertiary structure of a protein from predicted secondary structure elements (SSEs) omitting more flexible loop regions early on. This approach enables the sampling of conformational space for larger proteins with more complex topologies. In preparation of CASP11, we analyzed the quality of CASP10 models throughout the prediction pipeline to understand BCL::Fold's ability to sample the native topology, identify native-like models by scoring and/or clustering approaches, and our ability to add loop regions and side chains to initial SSE-only models. The standout observation is that BCL::Fold sampled topologies with a GDT_TS score > 33% for 12 of 18 and with a topology score > 0.8 for 11 of 18 test cases de novo. Despite the sampling success of BCL::Fold, significant challenges still exist in clustering and loop generation stages of the pipeline. The clustering approach employed for model selection often failed to identify the most native-like assembly of SSEs for further refinement and submission. It was also observed that for some β-strand proteins model refinement failed as β-strands were not properly aligned to form hydrogen bonds removing otherwise accurate models from the pool. Further, BCL::Fold samples frequently non-natural topologies that require loop regions to pass through the center of the protein. © 2015 Wiley Periodicals, Inc.

The structure of clusters of galaxies

NASA Astrophysics Data System (ADS)

Fox, David Charles

When infalling gas is accreted onto a cluster of galaxies, its kinetic energy is converted to thermal energy in a shock, heating the ions. Using a self-similar spherical model, we calculate the collisional heating of the electrons by the ions, and predict the electron and ion temperature profiles. While there are significant differences between the two, they occur at radii larger than currently observable, and too large to explain observed X-ray temperature declines in clusters. Numerical simulations by Navarro, Frenk, & White (1996) predict a universal dark matter density profile. We calculate the expected number of multiply-imaged background galaxies in the Hubble Deep Field due to foreground groups and clusters with this profile. Such groups are up to 1000 times less efficient at lensing than the standard singular isothermal spheres. However, with either profile, the expected number of galaxies lensed by groups in the Hubble Deep Field is at most one, consistent with the lack of clearly identified group lenses. X-ray and Sunyaev-Zel'dovich (SZ) effect observations can be combined to determine the distance to clusters of galaxies, provided the clusters are spherical. When applied to an aspherical cluster, this method gives an incorrect distance. We demonstrate a method for inferring the three-dimensional shape of a cluster and its correct distance from X-ray, SZ effect, and weak gravitational lensing observations, under the assumption of hydrostatic equilibrium. We apply this method to simple, analytic models of clusters, and to a numerically simulated cluster. Using artificial observations based on current X-ray and SZ effect instruments, we recover the true distance without detectable bias and with uncertainties of 4 percent.

Population substructure and space use of Foxe Basin polar bears.

PubMed

Sahanatien, Vicki; Peacock, Elizabeth; Derocher, Andrew E

2015-07-01

Climate change has been identified as a major driver of habitat change, particularly for sea ice-dependent species such as the polar bear (Ursus maritimus). Population structure and space use of polar bears have been challenging to quantify because of their circumpolar distribution and tendency to range over large areas. Knowledge of movement patterns, home range, and habitat is needed for conservation and management. This is the first study to examine the spatial ecology of polar bears in the Foxe Basin management unit of Nunavut, Canada. Foxe Basin is in the mid-Arctic, part of the seasonal sea ice ecoregion and it is being negatively affected by climate change. Our objectives were to examine intrapopulation spatial structure, to determine movement patterns, and to consider how polar bear movements may respond to changing sea ice habitat conditions. Hierarchical and fuzzy cluster analyses were used to assess intrapopulation spatial structure of geographic position system satellite-collared female polar bears. Seasonal and annual movement metrics (home range, movement rates, time on ice) and home-range fidelity (static and dynamic overlap) were compared to examine the influence of regional sea ice on movements. The polar bears were distributed in three spatial clusters, and there were differences in the movement metrics between clusters that may reflect sea ice habitat conditions. Within the clusters, bears moved independently of each other. Annual and seasonal home-range fidelity was observed, and the bears used two movement patterns: on-ice range residency and annual migration. We predict that home-range fidelity may decline as the spatial and temporal predictability of sea ice changes. These new findings also provide baseline information for managing and monitoring this polar bear population.

Role of childhood traumatic experience in personality disorders in China.

PubMed

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

2012-08-01

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

Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) for Conformational Space Search of Peptide and Miniprotein

PubMed Central

Hao, Ge-Fei; Xu, Wei-Fang; Yang, Sheng-Gang; Yang, Guang-Fu

2015-01-01

Protein and peptide structure predictions are of paramount importance for understanding their functions, as well as the interactions with other molecules. However, the use of molecular simulation techniques to directly predict the peptide structure from the primary amino acid sequence is always hindered by the rough topology of the conformational space and the limited simulation time scale. We developed here a new strategy, named Multiple Simulated Annealing-Molecular Dynamics (MSA-MD) to identify the native states of a peptide and miniprotein. A cluster of near native structures could be obtained by using the MSA-MD method, which turned out to be significantly more efficient in reaching the native structure compared to continuous MD and conventional SA-MD simulation. PMID:26492886

El paradigma jerarquico de formacion de estructuras

NASA Astrophysics Data System (ADS)

Lambas, D. G.

This contribution aims at showing our current understanding of the hierarchical clustering scenario for structure formation, its main success in terms of agreement of theoretical predictions and observations, and the most direct tests that provide confidence on the validity of the paradigm. FULL TEXT IN SPANISH

Studies of Copper, Silver, and Gold Cluster Anions: Evidence of Electronic Shell Structure.

NASA Astrophysics Data System (ADS)

Pettiette, Claire Lynn

A new Ultraviolet Magnetic Time-of-Flight Photoelectron Spectrometer (MTOFPES) has been developed for the study of the electronic structure of clusters produced in a pulsed supersonic molecular beam. This is the first technique which has been successful in probing the valence electronic states of metal clusters. The ultraviolet photoelectron spectra of negative cluster ions of the noble metals have been taken at several different photon energies. These are presented along with the electron affinity and HOMO-LUMO gap measurements for Cu_6^- to Cu_ {41}^-, using 4.66 eV and 6.42 eV detachment energies; Ag_3^- to Ag_{21}^-, using 6.42 eV detachment energy; and Au_3^ - to Au_{21}^-, using 6.42 eV and 7.89 eV detachment energies. The spectra provide the first detailed probes of the s valence electrons of the noble metal clusters. In addition, the 6.42 eV and 7.89 eV spectra probe the first one to two electron volts of the molecular orbitals of the d valence electrons of copper and gold clusters. The electron affinity and HOMO-LUMO gap measurements of the noble metal clusters agree with the predictions of the ellipsoidal shell model for mono-valent metal clusters. In particular, cluster numbers 8, 20, and 40--which correspond to the spherical shell closings of this model--have low electron affinities and large HOMO-LUMO gaps. The spectra of the gold cluster ions indicate that the molecular orbital energies of the cluster valence electrons are more widely spaced for gold than for copper or silver. This is to be expected for the heavy atom clusters when relativistic effects are taken into account.

Strong collective attraction in colloidal clusters on a liquid-air interface.

PubMed

Pergamenshchik, V M

2009-01-01

It is shown that in a cluster of many colloids, trapped at a liquid-air interface, the well-known vertical-force-induced pairwise logarithmic attraction changes to a strongly enhanced power-law attraction. In large two-dimensional clusters, the attraction energy scales as the inverse square of the distance between colloids. The enhancement is given by the ratio eta = (square of the capillary length) / (interface surface area per colloid) and can be as large as 10;{5} . This explains why a very small vertical force on colloids, which is too weak to bring two of them together, can stabilize many-body structures on a liquid-air interface. The profile of a cluster is shown to consist of a large slow collective envelope modulated by a fast low-amplitude perturbation due to individual colloids. A closed equation for the slow envelope, which incorporates an arbitrary power-law repulsion between colloids, is derived. For example, this equation is solved for a large circular cluster with the hard-core colloid repulsion. It is suggested that the predicted effect is responsible for mysterious stabilization of colloidal structures observed in experiments on a surface of isotropic liquid and nematic liquid crystal.

Quantum-chemical study of the effect of ligands on the structure and properties of gold clusters

NASA Astrophysics Data System (ADS)

Golosnaya, M. N.; Pichugina, D. A.; Oleinichenko, A. V.; Kuz'menko, N. E.

2017-02-01

The structures of [Au4(dpmp)2X2]2+clusters, where X =-C≡CH,-CH3,-SCH3,-F,-Cl,-Br,-I, dpmp is bis((diphenylphosphino)methyl)(phenyl)phosphine, are calculated at the level of density functional theory with the PBE functional and a modified Dirac-Coulomb-Breit Hamiltonian in an all-electron basis set (Λ). Using the example of [Au4(dpmp)2(C≡CC6H5)2]2+, the interatomic distances and bond angles calculated by means of PBE0/LANL2DZ, TPSS/LANL2DZ, TPSSh/LANL2DZ, and PBE/Λ are compared to X-ray crystallography data. It is shown that PBE/Λ yields the most accurate calculation of the geometrical parameters of this cluster. The ligand effect on the electronic stability of a cluster and the stability in reactions of decomposition into different fragments is studied, along with the capability of ligand exchange. Stability is predicted for [Au4(dpmp)2F2]2+ and [Au4(dpmp)2(SCH3)2]2+, while [Au4(dpmp)2I2]2+ cluster is unstable and its decomposes into two identical fragments is supposed.

PSPP: A Protein Structure Prediction Pipeline for Computing Clusters

DTIC Science & Technology

2009-07-01

Evanseck JD, et al. (1998) All-atom empirical potential for molecular modeling and dynamics studies of proteins. Journal of Physical Chemistry B 102...dimensional (3-D) protein structures are critical for the understanding of molecular mechanisms of living systems. Traditionally, X-ray crystallography...disordered proteins are often responsible for molecular recognition, molecular assembly, protein modifica- tion, and entropic chain activities in organisms [26

First-principles calculated decomposition pathways for LiBH4 nanoclusters

PubMed Central

Huang, Zhi-Quan; Chen, Wei-Chih; Chuang, Feng-Chuan; Majzoub, Eric H.; Ozoliņš, Vidvuds

2016-01-01

We analyze thermodynamic stability and decomposition pathways of LiBH4 nanoclusters using grand-canonical free-energy minimization based on total energies and vibrational frequencies obtained from density-functional theory (DFT) calculations. We consider (LiBH4)n nanoclusters with n = 2 to 12 as reactants, while the possible products include (Li)n, (B)n, (LiB)n, (LiH)n, and Li2BnHn; off-stoichiometric LinBnHm (m ≤ 4n) clusters were considered for n = 2, 3, and 6. Cluster ground-state configurations have been predicted using prototype electrostatic ground-state (PEGS) and genetic algorithm (GA) based structural optimizations. Free-energy calculations show hydrogen release pathways markedly differ from those in bulk LiBH4. While experiments have found that the bulk material decomposes into LiH and B, with Li2B12H12 as a kinetically inhibited intermediate phase, (LiBH4)n nanoclusters with n ≤ 12 are predicted to decompose into mixed LinBn clusters via a series of intermediate clusters of LinBnHm (m ≤ 4n). The calculated pressure-composition isotherms and temperature-pressure isobars exhibit sloping plateaus due to finite size effects on reaction thermodynamics. Generally, decomposition temperatures of free-standing clusters are found to increase with decreasing cluster size due to thermodynamic destabilization of reaction products. PMID:27189731

First-principles calculated decomposition pathways for LiBH 4 nanoclusters

DOE PAGES

Huang, Zhi -Quan; Chen, Wei -Chih; Chuang, Feng -Chuan; ...

2016-05-18

Here, we analyze thermodynamic stability and decomposition pathways of LiBH 4 nanoclusters using grand-canonical free-energy minimization based on total energies and vibrational frequencies obtained from density-functional theory (DFT) calculations. We consider (LiBH 4) n nanoclusters with n = 2 to 12 as reactants, while the possible products include (Li) n, (B) n, (LiB) n, (LiH) n, and Li 2B nH n; off-stoichiometric LinBnHm (m ≤ 4n) clusters were considered for n = 2, 3, and 6. Cluster ground-state configurations have been predicted using prototype electrostatic ground-state (PEGS) and genetic algorithm (GA) based structural optimizations. Free-energy calculations show hydrogen release pathwaysmore » markedly differ from those in bulk LiBH 4. While experiments have found that the bulk material decomposes into LiH and B, with Li 2B 12H 12 as a kinetically inhibited intermediate phase, (LiBH 4) n nanoclusters with n ≤ 12 are predicted to decompose into mixed Li nB n clusters via a series of intermediate clusters of Li nB nH m (m ≤ 4n). The calculated pressure-composition isotherms and temperature-pressure isobars exhibit sloping plateaus due to finite size effects on reaction thermodynamics. Generally, decomposition temperatures of free-standing clusters are found to increase with decreasing cluster size due to thermodynamic destabilization of reaction products.« less

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

Huang, Zhi -Quan; Chen, Wei -Chih; Chuang, Feng -Chuan

Here, we analyze thermodynamic stability and decomposition pathways of LiBH 4 nanoclusters using grand-canonical free-energy minimization based on total energies and vibrational frequencies obtained from density-functional theory (DFT) calculations. We consider (LiBH 4) n nanoclusters with n = 2 to 12 as reactants, while the possible products include (Li) n, (B) n, (LiB) n, (LiH) n, and Li 2B nH n; off-stoichiometric LinBnHm (m ≤ 4n) clusters were considered for n = 2, 3, and 6. Cluster ground-state configurations have been predicted using prototype electrostatic ground-state (PEGS) and genetic algorithm (GA) based structural optimizations. Free-energy calculations show hydrogen release pathwaysmore » markedly differ from those in bulk LiBH 4. While experiments have found that the bulk material decomposes into LiH and B, with Li 2B 12H 12 as a kinetically inhibited intermediate phase, (LiBH 4) n nanoclusters with n ≤ 12 are predicted to decompose into mixed Li nB n clusters via a series of intermediate clusters of Li nB nH m (m ≤ 4n). The calculated pressure-composition isotherms and temperature-pressure isobars exhibit sloping plateaus due to finite size effects on reaction thermodynamics. Generally, decomposition temperatures of free-standing clusters are found to increase with decreasing cluster size due to thermodynamic destabilization of reaction products.« less

Incorporation of local structure into kriging models for the prediction of atomistic properties in the water decamer.

PubMed

Davie, Stuart J; Di Pasquale, Nicodemo; Popelier, Paul L A

2016-10-15

Machine learning algorithms have been demonstrated to predict atomistic properties approaching the accuracy of quantum chemical calculations at significantly less computational cost. Difficulties arise, however, when attempting to apply these techniques to large systems, or systems possessing excessive conformational freedom. In this article, the machine learning method kriging is applied to predict both the intra-atomic and interatomic energies, as well as the electrostatic multipole moments, of the atoms of a water molecule at the center of a 10 water molecule (decamer) cluster. Unlike previous work, where the properties of small water clusters were predicted using a molecular local frame, and where training set inputs (features) were based on atomic index, a variety of feature definitions and coordinate frames are considered here to increase prediction accuracy. It is shown that, for a water molecule at the center of a decamer, no single method of defining features or coordinate schemes is optimal for every property. However, explicitly accounting for the structure of the first solvation shell in the definition of the features of the kriging training set, and centring the coordinate frame on the atom-of-interest will, in general, return better predictions than models that apply the standard methods of feature definition, or a molecular coordinate frame. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc. © 2016 The Authors. Journal of Computational Chemistry Published by Wiley Periodicals, Inc.

Protein complex prediction in large ontology attributed protein-protein interaction networks.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian; Li, Yanpeng; Xu, Bo

2013-01-01

Protein complexes are important for unraveling the secrets of cellular organization and function. Many computational approaches have been developed to predict protein complexes in protein-protein interaction (PPI) networks. However, most existing approaches focus mainly on the topological structure of PPI networks, and largely ignore the gene ontology (GO) annotation information. In this paper, we constructed ontology attributed PPI networks with PPI data and GO resource. After constructing ontology attributed networks, we proposed a novel approach called CSO (clustering based on network structure and ontology attribute similarity). Structural information and GO attribute information are complementary in ontology attributed networks. CSO can effectively take advantage of the correlation between frequent GO annotation sets and the dense subgraph for protein complex prediction. Our proposed CSO approach was applied to four different yeast PPI data sets and predicted many well-known protein complexes. The experimental results showed that CSO was valuable in predicting protein complexes and achieved state-of-the-art performance.

Improving Prediction of Large-scale Regime Transitions

NASA Astrophysics Data System (ADS)

Gyakum, J. R.; Roebber, P.; Bosart, L. F.; Honor, A.; Bunker, E.; Low, Y.; Hart, J.; Bliankinshtein, N.; Kolly, A.; Atallah, E.; Huang, Y.

2017-12-01

Cool season atmospheric predictability over the CONUS on subseasonal times scales (1-4 weeks) is critically dependent upon the structure, configuration, and evolution of the North Pacific jet stream (NPJ). The NPJ can be perturbed on its tropical side on synoptic time scales by recurving and transitioning tropical cyclones (TCs) and on subseasonal time scales by longitudinally varying convection associated with the Madden-Julian Oscillation (MJO). Likewise, the NPJ can be perturbed on its poleward side on synoptic time scales by midlatitude and polar disturbances that originate over the Asian continent. These midlatitude and polar disturbances can often trigger downstream Rossby wave propagation across the North Pacific, North America, and the North Atlantic. The project team is investigating the following multiscale processes and features: the spatiotemporal distribution of cyclone clustering over the Northern Hemisphere; cyclone clustering as influenced by atmospheric blocking and the phases and amplitudes of the major teleconnection indices, ENSO and the MJO; composite and case study analyses of representative cyclone clustering events to establish the governing dynamics; regime change predictability horizons associated with cyclone clustering events; Arctic air mass generation and modification; life cycles of the MJO; and poleward heat and moisture transports of subtropical air masses. A critical component of the study is weather regime classification. These classifications are defined through: the spatiotemporal clustering of surface cyclogenesis; a general circulation metric combining data at 500-hPa and the dynamic tropopause; Self Organizing Maps (SOM), constructed from dynamic tropopause and 850 hPa equivalent potential temperature data. The resultant lattice of nodes is used to categorize synoptic classes and their predictability, as well as to determine the robustness of the CFSv2 model climate relative to observations. Transition pathways between these synoptic classes, both in the observations and the CFSv2, are investigated. At a future point in the project, the results from these multiscale investigations will be integrated in the form of a prediction tool for important variables (temperatures, precipitation and their extremes) for the 1-4 week timeframe.

Asymmetric Top Rotors in Superfluid Para-Hydrogen Nano-Clusters

NASA Astrophysics Data System (ADS)

Zeng, Tao; Li, Hui; Roy, Pierre-Nicholas

2012-06-01

We present the first simulation study of bosonic clusters doped with an asymmetric top molecule. A variation of the path-integral Monte Carlo method is developed to study a para-water (pH_2O) impurity in para-hydrogen (pH_2) clusters. The growth pattern of the doped clusters is similar in nature to that of the pure clusters. The pH_2O molecule appears to rotate freely in the cluster due to its large rotational constants and the lack of adiabatic following. The presence of pH_2O substantially quenches the superfluid response of pH_2 with respect to the space fixed frame. We also study the behaviour of a sulphur dioxide (32S16O_2) dopant in the pH_2 clusters. For such a heavy rotor, the adiabatic following of the pH_2 molecules is established and the superfluid renormalization of the rotational constants is observed. The rotational structure of the SO_2-p(H_2)_N clusters' ro-vibrational spectra is predicted. The connection between the superfluid response respect to the external boundary rotation and the dopant rotation is discussed.

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

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

Grasha, K.; Calzetti, D.; Elmegreen, B. G.

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25–0.6 power, and that the maximum size over which star formation is physically correlated ranges from ∼200 pc to ∼1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are closemore » to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.« less

Role of distortion in the hcp vs fcc competition in rare-gas solids

NASA Astrophysics Data System (ADS)

Krainyukova, N. V.

2011-05-01

As a prototype of an initial or intermediate structure between hcp and fcc lattices we consider a distorted bcc crystal. We calculate the temperature and pressure dependences of the lattice parameters for the heavier rare gas solids Ar, Kr, Xe in a quasiharmonic approximation with Aziz potentials, and confirm earlier predictions that the hcp structure predominates over fcc in the bulk within wide ranges of P and T. The situation is different for confined clusters with up to 105 atoms, where, owing to the specific surface energetics and terminations, structures with five-fold symmetry made up of fcc fragments are dominant. As a next step we consider the free relaxation of differently distorted bcc clusters, and show that two types (monoclinic and orthorhombic) of initial distortion are a driving force for the final hcp vs fcc configurations. Possible energy relationships between the initial and final structures are obtained and analyzed.

Machine learning approaches for estimation of prediction interval for the model output.

PubMed

Shrestha, Durga L; Solomatine, Dimitri P

2006-03-01

A novel method for estimating prediction uncertainty using machine learning techniques is presented. Uncertainty is expressed in the form of the two quantiles (constituting the prediction interval) of the underlying distribution of prediction errors. The idea is to partition the input space into different zones or clusters having similar model errors using fuzzy c-means clustering. The prediction interval is constructed for each cluster on the basis of empirical distributions of the errors associated with all instances belonging to the cluster under consideration and propagated from each cluster to the examples according to their membership grades in each cluster. Then a regression model is built for in-sample data using computed prediction limits as targets, and finally, this model is applied to estimate the prediction intervals (limits) for out-of-sample data. The method was tested on artificial and real hydrologic data sets using various machine learning techniques. Preliminary results show that the method is superior to other methods estimating the prediction interval. A new method for evaluating performance for estimating prediction interval is proposed as well.

Mystery solved: discovery of extended radio emission in the merging galaxy cluster Abell 2146

NASA Astrophysics Data System (ADS)

Hlavacek-Larrondo, J.; Gendron-Marsolais, M.-L.; Fecteau-Beaucage, D.; van Weeren, R. J.; Russell, H. R.; Edge, A.; Olamaie, M.; Rumsey, C.; King, L.; Fabian, A. C.; McNamara, B.; Hogan, M.; Mezcua, M.; Taylor, G.

2018-04-01

Abell 2146 (z = 0.232) is a massive galaxy cluster currently undergoing a spectacular merger in the plane of the sky with a bullet-like morphology. It was the first system in which both the bow and upstream shock fronts were detected at X-ray wavelengths (Mach ˜2), yet deep Giant MetreWave Telescope 325 MHz observations failed to detect extended radio emission associated with the cluster as is typically seen in such systems. We present new, multiconfiguration 1-2 GHz Karl G. Jansky Very Large Array (VLA) observations of Abell 2146 totalling 16 h of observations. These data reveal for the first time the presence of an extended (≈850 kpc), faint radio structure associated with Abell 2146. The structure appears to harbour multiple components, one associated with the upstream shock that we classify as a radio relic and one associated with the subcluster core that is consisted as being a radio halo bounded by the bow shock. The newly detected structures have some of the lowest radio powers detected thus far in any cluster (P1.4 GHz, halo = 2.4 ± 0.2 × 1023 W Hz-1 and P1.4 GHz, relic = 2.2 ± 0.2 × 1023 W Hz-1). The flux measurement of the halo, as well as its morphology, also suggests that the halo was recently created (≈0.3 Gyr after core passage), consistent with the dynamical state of the cluster. These observations demonstrate the capacity of the upgraded VLA to detect extremely faint and extended radio structures. Based on these observations, we predict that many more radio relics and radio haloes in merging clusters should be detected by future radio facilities such as the Square Kilometre Array.

Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data

DOE PAGES

Hsu, David

2015-09-27

Clustering methods are often used to model energy consumption for two reasons. First, clustering is often used to process data and to improve the predictive accuracy of subsequent energy models. Second, stable clusters that are reproducible with respect to non-essential changes can be used to group, target, and interpret observed subjects. However, it is well known that clustering methods are highly sensitive to the choice of algorithms and variables. This can lead to misleading assessments of predictive accuracy and mis-interpretation of clusters in policymaking. This paper therefore introduces two methods to the modeling of energy consumption in buildings: clusterwise regression,more » also known as latent class regression, which integrates clustering and regression simultaneously; and cluster validation methods to measure stability. Using a large dataset of multifamily buildings in New York City, clusterwise regression is compared to common two-stage algorithms that use K-means and model-based clustering with linear regression. Predictive accuracy is evaluated using 20-fold cross validation, and the stability of the perturbed clusters is measured using the Jaccard coefficient. These results show that there seems to be an inherent tradeoff between prediction accuracy and cluster stability. This paper concludes by discussing which clustering methods may be appropriate for different analytical purposes.« less

Modular structural elements in the replication origin region of Tetrahymena rDNA.

PubMed Central

Du, C; Sanzgiri, R P; Shaiu, W L; Choi, J K; Hou, Z; Benbow, R M; Dobbs, D L

1995-01-01

Computer analyses of the DNA replication origin region in the amplified rRNA genes of Tetrahymena thermophila identified a potential initiation zone in the 5'NTS [Dobbs, Shaiu and Benbow (1994), Nucleic Acids Res. 22, 2479-2489]. This region consists of a putative DNA unwinding element (DUE) aligned with predicted bent DNA segments, nuclear matrix or scaffold associated region (MAR/SAR) consensus sequences, and other common modular sequence elements previously shown to be clustered in eukaryotic chromosomal origin regions. In this study, two mung bean nuclease-hypersensitive sites in super-coiled plasmid DNA were localized within the major DUE-like element predicted by thermodynamic analyses. Three restriction fragments of the 5'NTS region predicted to contain bent DNA segments exhibited anomalous migration characteristic of bent DNA during electrophoresis on polyacrylamide gels. Restriction fragments containing the 5'NTS region bound Tetrahymena nuclear matrices in an in vitro binding assay, consistent with an association of the replication origin region with the nuclear matrix in vivo. The direct demonstration in a protozoan origin region of elements previously identified in Drosophila, chick and mammalian origin regions suggests that clusters of modular structural elements may be a conserved feature of eukaryotic chromosomal origins of replication. Images PMID:7784181

Weak Lensing by Galaxy Clusters: from Pixels to Cosmology

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

Gruen, Daniel

The story of the origin and evolution of our Universe is told, equivalently, by space-time itself and by the structures that grow inside of it. Clusters of galaxies are the frontier of bottom-up structure formation. They are the most massive objects to have collapsed at the present epoch. By that virtue, their abundance and structural parameters are highly sensitive to the composition and evolution of the Universe. The most common probe of cluster cosmology, abundance, uses samples of clusters selected by some observable. Applying a mass-observable relation (MOR), cosmological parameters can be constrained by comparing the sample to predicted clustermore » abundances as a function of observable and redshift. Arguably, however, cluster probes have not yet entered the era of per cent level precision cosmology. The primary reason for this is our imperfect understanding of the MORs. The overall normalization, the slope of mass vs. observable, the redshift evolution, and the degree and correlation of intrinsic scatters of observables at fixed mass have to be constrained for interpreting abundances correctly. Mass measurement of clusters by means of the differential deflection of light from background sources in their gravitational field, i.e. weak lensing, is a powerful approach for achieving this. This thesis presents new methods for and scientific results of weak lensing measurements of clusters of galaxies. The former include, on the data reduction side, (i) the correction of CCD images for non-linear effects due to the electric fields of accumulated charges and (ii) a method for masking artifact features in sets of overlapping images of the sky by comparison to the median image. Also, (iii) I develop a method for the selection of background galaxy samples based on their color and apparent magnitude that includes a new correction for contamination with cluster member galaxies. The main scientific results are the following. (i) For the Hubble Frontier Field cluster RXC J2248.7--4431 our lensing analysis constrains mass and concentration of the cluster halo and we confirm the large mass predicted by X-ray and Sunyaev-Zel’dovich (SZ) observations. The study of cluster members shows the relation of galaxy morphology to luminosity and environment. (ii) Our lensing mass measurements for 12 clusters are consistent with X-ray masses derived under the assumption of hydrostatic equilibrium of the intra-cluster gas. We confirm the MORs derived by the South Pole Telescope collaboration for the detection significance of the cluster SZ signal in their survey. We find discrepancies, however, with the Planck SZ MOR. We hypothesize that these are related either to a shallower slope of the MOR or a size-, redshift- or noise-dependent bias in SZ signal extraction. (iii) Finally, using a combination of simulations and theoretical models for the variation of cluster profiles at fixed mass, we find that the latter is a significant contribution to the uncertainty of cluster lensing mass measurements. A cosmic variance model, such as the one we develop, is necessary for MOR constraints to be accurate at the level required for future surveys.« less

Intrinsic alignments in redMaPPer clusters - I. Central galaxy alignments and angular segregation of satellites

NASA Astrophysics Data System (ADS)

Huang, Hung-Jin; Mandelbaum, Rachel; Freeman, Peter E.; Chen, Yen-Chi; Rozo, Eduardo; Rykoff, Eli; Baxter, Eric J.

2016-11-01

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes and the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Finally, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.

Intrinsic alignments in redMaPPer clusters – I. Central galaxy alignments and angular segregation of satellites

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

Huang, Hung -Jin; Mandelbaum, Rachel; Freeman, Peter E.

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes andmore » the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Lastly, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.« less

Intrinsic alignments in redMaPPer clusters – I. Central galaxy alignments and angular segregation of satellites

DOE PAGES

Huang, Hung -Jin; Mandelbaum, Rachel; Freeman, Peter E.; ...

2016-08-11

The shapes of cluster central galaxies are not randomly oriented, but rather exhibit coherent alignments with the shapes of their parent clusters as well as with the surrounding large-scale structures. In this work, we aim to identify the galaxy and cluster quantities that most strongly predict the central galaxy alignment phenomenon among a large parameter space with a sample of 8237 clusters and 94 817 members within 0.1 < z < 0.35, based on the red-sequence Matched-filter Probabilistic Percolation cluster catalogue constructed from the Sloan Digital Sky Survey. We first quantify the alignment between the projected central galaxy shapes andmore » the distribution of member satellites, to understand what central galaxy and cluster properties most strongly correlate with these alignments. Next, we investigate the angular segregation of satellites with respect to their central galaxy major axis directions, to identify the satellite properties that most strongly predict their angular segregation. We find that central galaxies are more aligned with their member galaxy distributions in clusters that are more elongated and have higher richness, and for central galaxies with larger physical size, higher luminosity and centring probability, and redder colour. Satellites with redder colour, higher luminosity, located closer to the central galaxy, and with smaller ellipticity show a stronger angular segregation towards their central galaxy major axes. Lastly, we provide physical explanations for some of the identified correlations, and discuss the connection to theories of central galaxy alignments, the impact of primordial alignments with tidal fields, and the importance of anisotropic accretion.« less

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

PubMed

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

2016-01-04

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

Bioinformatics study of the mangrove actin genes

NASA Astrophysics Data System (ADS)

Basyuni, M.; Wasilah, M.; Sumardi

2017-01-01

This study describes the bioinformatics methods to analyze eight actin genes from mangrove plants on DDBJ/EMBL/GenBank as well as predicted the structure, composition, subcellular localization, similarity, and phylogenetic. The physical and chemical properties of eight mangroves showed variation among the genes. The percentage of the secondary structure of eight mangrove actin genes followed the order of a helix > random coil > extended chain structure for BgActl, KcActl, RsActl, and A. corniculatum Act. In contrast to this observation, the remaining actin genes were random coil > extended chain structure > a helix. This study, therefore, shown the prediction of secondary structure was performed for necessary structural information. The values of chloroplast or signal peptide or mitochondrial target were too small, indicated that no chloroplast or mitochondrial transit peptide or signal peptide of secretion pathway in mangrove actin genes. These results suggested the importance of understanding the diversity and functional of properties of the different amino acids in mangrove actin genes. To clarify the relationship among the mangrove actin gene, a phylogenetic tree was constructed. Three groups of mangrove actin genes were formed, the first group contains B. gymnorrhiza BgAct and R. stylosa RsActl. The second cluster which consists of 5 actin genes the largest group, and the last branch consist of one gene, B. sexagula Act. The present study, therefore, supported the previous results that plant actin genes form distinct clusters in the tree.

Replicability and 40-Year Predictive Power of Childhood ARC Types

PubMed Central

Chapman, Benjamin P.; Goldberg, Lewis R.

2011-01-01

We examined three questions surrounding the Undercontrolled, Overcontrolled, and Resilient--or Asendorpf-Robins-Caspi (ARC)--personality types originally identified by Block (1971). In analyses of the teacher personality assessments of over 2,000 children in 1st through 6th grade in 1959-1967, and follow-up data on general and cardiovascular health outcomes in over 1,100 adults recontacted 40 years later, we found: (1) Bootstrapped internal replication clustering suggested that Big Five scores were best characterized by a tripartite cluster structure corresponding to the ARC types; (2) this cluster structure was fuzzy, rather than discrete, indicating that ARC constructs are best represented as gradients of similarity to three prototype Big Five profiles; and (3) ARC types and degrees of ARC prototypicality showed associations with multiple health outcomes 40 years later. ARC constructs were more parsimonious, but neither better nor more consistent predictors than the dimensional Big Five traits. Forty-year incident cases of heart disease could be correctly identified with 68% accuracy by personality information alone, a figure approaching the 12-year accuracy of a leading medical cardiovascular risk model. Findings support the theoretical validity of ARC constructs, their treatment as continua of prototypicality rather than discrete categories, and the need for further understanding the robust predictive power of childhood personality traits for mid-life health. PMID:21744975

a Study on 4 Reactions Forming 46Ti*

NASA Astrophysics Data System (ADS)

Cicerchia, M.; Marchi, T.; Gramegna, F.; Cinausero, M.; Fabris, D.; Mantovani, G.; Degerlier, M.; Morelli, L.; Bruno, M.; DAgostino, M.; Frosin, C.; Barlini, S.; Piantelli, S.; Valdrè, S.; Bini, M.; Pasquali, G.; Casini, G.; Pastore, G.; Gruyer, D.; Ottanelli, P.; Camaiani, A.; Gelli, N.; Olmi, A.; Poggi, G.; Lombardo, I.; Dell'Aquila, D.; Cieplicka-Orynczak, N.

2018-02-01

The NUCL-EX collaboration is carrying out an extensive research program on preequilibrium emission of light charged particles from hot nuclei. The ultimate goal is to study how cluster structures affect nuclear reactions [1,2,3,4]. Indeed, a strong correlation between nuclear structure and reaction dynamics emerges when some nucleons or clusters of nucleons are emitted or captured [5]. At this purpose, the four reactions 16O+30Si, 16O+30Si, 18O+28Si and 19F +27Al have been measured at about 120 MeV projectile energy. Experimental data were collected at Legnaro National Laboratories, using the GARFIELD+RCo array, fully equipped with digital electronics [6]. Following an initial identification of particles and the energy calibration procedures, the complete analysis is being performed on an event-by-event basis. Experimental data are then compared to the theoretical predictions where events are generated by numerical codes based on pre-equilibrium and statistical models and then filtered through a software replica of the setup. Differences between the experimental data and the predicted data put into evidence effects related to the entrance channel and to the cluster nature of the colliding ions. After a general introduction on the experimental campaign, this contribution will focus on the preliminary results obtained so far.

RosettaHoles: rapid assessment of protein core packing for structure prediction, refinement, design, and validation.

PubMed

Sheffler, Will; Baker, David

2009-01-01

We present a novel method called RosettaHoles for visual and quantitative assessment of underpacking in the protein core. RosettaHoles generates a set of spherical cavity balls that fill the empty volume between atoms in the protein interior. For visualization, the cavity balls are aggregated into contiguous overlapping clusters and small cavities are discarded, leaving an uncluttered representation of the unfilled regions of space in a structure. For quantitative analysis, the cavity ball data are used to estimate the probability of observing a given cavity in a high-resolution crystal structure. RosettaHoles provides excellent discrimination between real and computationally generated structures, is predictive of incorrect regions in models, identifies problematic structures in the Protein Data Bank, and promises to be a useful validation tool for newly solved experimental structures.

RosettaHoles: Rapid assessment of protein core packing for structure prediction, refinement, design, and validation

PubMed Central

Sheffler, Will; Baker, David

2009-01-01

We present a novel method called RosettaHoles for visual and quantitative assessment of underpacking in the protein core. RosettaHoles generates a set of spherical cavity balls that fill the empty volume between atoms in the protein interior. For visualization, the cavity balls are aggregated into contiguous overlapping clusters and small cavities are discarded, leaving an uncluttered representation of the unfilled regions of space in a structure. For quantitative analysis, the cavity ball data are used to estimate the probability of observing a given cavity in a high-resolution crystal structure. RosettaHoles provides excellent discrimination between real and computationally generated structures, is predictive of incorrect regions in models, identifies problematic structures in the Protein Data Bank, and promises to be a useful validation tool for newly solved experimental structures. PMID:19177366

Comparative analysis of machine learning methods in ligand-based virtual screening of large compound libraries.

PubMed

Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z

2009-05-01

Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Synchrotron Emission from Dark Matter Annihilation: Predictions for Constraints from Non-detections of Galaxy Clusters with New Radio Surveys

NASA Astrophysics Data System (ADS)

Storm, Emma; Jeltema, Tesla E.; Splettstoesser, Megan; Profumo, Stefano

2017-04-01

The annihilation of dark matter particles is expected to yield a broad radiation spectrum via the production of Standard Model particles in astrophysical environments. In particular, electrons and positrons from dark matter annihilation produce synchrotron radiation in the presence of magnetic fields. Galaxy clusters are the most massive collapsed structures in the universe, and are known to host ˜μG-scale magnetic fields. They are therefore ideal targets to search for, or to constrain the synchrotron signal from dark matter annihilation. In this work, we use the expected sensitivities of several planned surveys from the next generation of radio telescopes to predict the constraints on dark matter annihilation models which will be achieved in the case of non-detections of diffuse radio emission from galaxy clusters. Specifically, we consider the Tier 1 survey planned for the Low Frequency Array (LOFAR) at 120 MHz, the Evolutionary Map of the Universe (EMU) survey planned for the Australian Square Kilometre Array Pathfinder (ASKAP) at 1.4 GHz, and planned surveys for Aperture Tile in Focus (APERTIF) at 1.4 GHz. We find that, for massive clusters and dark matter masses ≲ 100 {GeV}, the predicted limits on the annihilation cross section would rule out vanilla thermal relic models for even the shallow LOFAR Tier 1, ASKAP, and APERTIF surveys.

A New Secondary Structure Assignment Algorithm Using Cα Backbone Fragments

PubMed Central

Cao, Chen; Wang, Guishen; Liu, An; Xu, Shutan; Wang, Lincong; Zou, Shuxue

2016-01-01

The assignment of secondary structure elements in proteins is a key step in the analysis of their structures and functions. We have developed an algorithm, SACF (secondary structure assignment based on Cα fragments), for secondary structure element (SSE) assignment based on the alignment of Cα backbone fragments with central poses derived by clustering known SSE fragments. The assignment algorithm consists of three steps: First, the outlier fragments on known SSEs are detected. Next, the remaining fragments are clustered to obtain the central fragments for each cluster. Finally, the central fragments are used as a template to make assignments. Following a large-scale comparison of 11 secondary structure assignment methods, SACF, KAKSI and PROSS are found to have similar agreement with DSSP, while PCASSO agrees with DSSP best. SACF and PCASSO show preference to reducing residues in N and C cap regions, whereas KAKSI, P-SEA and SEGNO tend to add residues to the terminals when DSSP assignment is taken as standard. Moreover, our algorithm is able to assign subtle helices (310-helix, π-helix and left-handed helix) and make uniform assignments, as well as to detect rare SSEs in β-sheets or long helices as outlier fragments from other programs. The structural uniformity should be useful for protein structure classification and prediction, while outlier fragments underlie the structure–function relationship. PMID:26978354

Effects of the bipartite structure of a network on performance of recommenders

NASA Astrophysics Data System (ADS)

Wang, Qing-Xian; Li, Jian; Luo, Xin; Xu, Jian-Jun; Shang, Ming-Sheng

2018-02-01

Recommender systems aim to predict people's preferences for online items by analyzing their historical behaviors. A recommender can be modeled as a high-dimensional and sparse bipartite network, where the key issue is to understand the relation between the network structure and a recommender's performance. To address this issue, we choose three network characteristics, clustering coefficient, network density and user-item ratio, as the analyzing targets. For the cluster coefficient, we adopt the Degree-preserving rewiring algorithm to obtain a series of bipartite network with varying cluster coefficient, while the degree of user and item keep unchanged. Furthermore, five state-of-the-art recommenders are applied on two real datasets. The performances of recommenders are measured by both numerical and physical metrics. These results show that a recommender's performance is positively related to the clustering coefficient of a bipartite network. Meanwhile, higher density of a bipartite network can provide more accurate but less diverse or novel recommendations. Furthermore, the user-item ratio is positively correlated with the accuracy metrics but negatively correlated with the diverse and novel metrics.

Assessing an ensemble docking-based virtual screening strategy for kinase targets by considering protein flexibility.

PubMed

Tian, Sheng; Sun, Huiyong; Pan, Peichen; Li, Dan; Zhen, Xuechu; Li, Youyong; Hou, Tingjun

2014-10-27

In this study, to accommodate receptor flexibility, based on multiple receptor conformations, a novel ensemble docking protocol was developed by using the naïve Bayesian classification technique, and it was evaluated in terms of the prediction accuracy of docking-based virtual screening (VS) of three important targets in the kinase family: ALK, CDK2, and VEGFR2. First, for each target, the representative crystal structures were selected by structural clustering, and the capability of molecular docking based on each representative structure to discriminate inhibitors from non-inhibitors was examined. Then, for each target, 50 ns molecular dynamics (MD) simulations were carried out to generate an ensemble of the conformations, and multiple representative structures/snapshots were extracted from each MD trajectory by structural clustering. On average, the representative crystal structures outperform the representative structures extracted from MD simulations in terms of the capabilities to separate inhibitors from non-inhibitors. Finally, by using the naïve Bayesian classification technique, an integrated VS strategy was developed to combine the prediction results of molecular docking based on different representative conformations chosen from crystal structures and MD trajectories. It was encouraging to observe that the integrated VS strategy yields better performance than the docking-based VS based on any single rigid conformation. This novel protocol may provide an improvement over existing strategies to search for more diverse and promising active compounds for a target of interest.

GAtor: A First-Principles Genetic Algorithm for Molecular Crystal Structure Prediction.

PubMed

Curtis, Farren; Li, Xiayue; Rose, Timothy; Vázquez-Mayagoitia, Álvaro; Bhattacharya, Saswata; Ghiringhelli, Luca M; Marom, Noa

2018-04-10

We present the implementation of GAtor, a massively parallel, first-principles genetic algorithm (GA) for molecular crystal structure prediction. GAtor is written in Python and currently interfaces with the FHI-aims code to perform local optimizations and energy evaluations using dispersion-inclusive density functional theory (DFT). GAtor offers a variety of fitness evaluation, selection, crossover, and mutation schemes. Breeding operators designed specifically for molecular crystals provide a balance between exploration and exploitation. Evolutionary niching is implemented in GAtor by using machine learning to cluster the dynamically updated population by structural similarity and then employing a cluster-based fitness function. Evolutionary niching promotes uniform sampling of the potential energy surface by evolving several subpopulations, which helps overcome initial pool biases and selection biases (genetic drift). The various settings offered by GAtor increase the likelihood of locating numerous low-energy minima, including those located in disconnected, hard to reach regions of the potential energy landscape. The best structures generated are re-relaxed and re-ranked using a hierarchy of increasingly accurate DFT functionals and dispersion methods. GAtor is applied to a chemically diverse set of four past blind test targets, characterized by different types of intermolecular interactions. The experimentally observed structures and other low-energy structures are found for all four targets. In particular, for Target II, 5-cyano-3-hydroxythiophene, the top ranked putative crystal structure is a Z' = 2 structure with P1̅ symmetry and a scaffold packing motif, which has not been reported previously.

A Giant Warm Baryonic Halo for the Coma Cluster

NASA Technical Reports Server (NTRS)

Bonamente, Max; Lieu, Richard; Joy, Marshall K.; Six, N. Frank (Technical Monitor)

2002-01-01

Several deep PSPC observations of the Coma cluster unveil a very large-scale halo of soft X-ray emission, substantially in excess of the well know radiation from the hot intra-cluster medium. The excess emission, previously reported in the central cluster regions through lower-sensitivity EUVE and ROSAT data, is now evident out to a radius of 2.5 Mpc, demonstrating that the soft excess radiation from clusters is a phenomenon of cosmological significance. The spectrum at these large radii cannot be modeled non-thermally, but is consistent with the original scenario of thermal emission at warm temperatures. The mass of this plasma is at least on par with that of the hot X-ray emitting plasma, and significantly more massive if the plasma resides in low-density filamentary structures. Thus the data lend vital support to current theories of cosmic evolution, which predict greater than 50 percent by mass of today's baryons reside in warm-hot filaments converging at clusters of galaxies.

Helium segregation on surfaces of plasma-exposed tungsten

DOE PAGES

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; ...

2016-01-21

Here we report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He-n (1 <= n <= 7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides themore » thermodynamic driving force for surface segregation. Elastic interaction force induces drift fluxes of these mobile Hen clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters' drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. Moreover, these near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.« less

Ion mobility spectrometry-mass spectrometry examination of the structures, stabilities, and extents of hydration of dimethylamine-sulfuric acid clusters.

PubMed

Thomas, Jikku M; He, Siqin; Larriba-Andaluz, Carlos; DePalma, Joseph W; Johnston, Murray V; Hogan, Christopher J

2016-08-17

We applied an atmospheric pressure differential mobility analyzer (DMA) coupled to a time-of-flight mass spectrometer to examine the stability, mass-mobility relationship, and extent of hydration of dimethylamine-sulfuric acid cluster ions, which are of relevance to nucleation in ambient air. Cluster ions were generated by electrospray ionization and were of the form: [H((CH3)2NH)x(H2SO4)y](+) and [(HSO4)((CH3)2NH)x(H2SO4)y](-), where 4 ≤ x ≤ 8, and 5 ≤ y ≤ 12. Under dry conditions, we find that positively charged cluster ions dissociated via loss of both multiple dimethylamine and sulfuric acid molecules after mobility analysis but prior to mass analysis, and few parent ions were detected in the mass spectrometer. Dissociation also occurred for negative ions, but to a lesser extent than for positive ions for the same mass spectrometer inlet conditions. Under humidified conditions (relative humidities up to 30% in the DMA), positively charged cluster ion dissociation in the mass spectrometer inlet was mitigated and occurred primarily by H2SO4 loss from ions containing excess acid molecules. DMA measurements were used to infer collision cross sections (CCSs) for all identifiable cluster ions. Stokes-Millikan equation and diffuse/inelastic gas molecule scattering predicted CCSs overestimate measured CCSs by more than 15%, while elastic-specular collision model predictions are in good agreement with measurements. Finally, cluster ion hydration was examined by monitoring changes in CCSs with increasing relative humidity. All examined cluster ions showed a modest amount of water molecule adsorption, with percentage increases in CCS smaller than 10%. The extent of hydration correlates directly with cluster ion acidity for positive ions.

Multipolar moments of weak lensing signal around clusters. Weighing filaments in harmonic space

NASA Astrophysics Data System (ADS)

Gouin, C.; Gavazzi, R.; Codis, S.; Pichon, C.; Peirani, S.; Dubois, Y.

2017-09-01

Context. Upcoming weak lensing surveys such as Euclid will provide an unprecedented opportunity to quantify the geometry and topology of the cosmic web, in particular in the vicinity of lensing clusters. Aims: Understanding the connectivity of the cosmic web with unbiased mass tracers, such as weak lensing, is of prime importance to probe the underlying cosmology, seek dynamical signatures of dark matter, and quantify environmental effects on galaxy formation. Methods: Mock catalogues of galaxy clusters are extracted from the N-body PLUS simulation. For each cluster, the aperture multipolar moments of the convergence are calculated in two annuli (inside and outside the virial radius). By stacking their modulus, a statistical estimator is built to characterise the angular mass distribution around clusters. The moments are compared to predictions from perturbation theory and spherical collapse. Results: The main weakly chromatic excess of multipolar power on large scales is understood as arising from the contraction of the primordial cosmic web driven by the growing potential well of the cluster. Besides this boost, the quadrupole prevails in the cluster (ellipsoidal) core, while at the outskirts, harmonic distortions are spread on small angular modes, and trace the non-linear sharpening of the filamentary structures. Predictions for the signal amplitude as a function of the cluster-centric distance, mass, and redshift are presented. The prospects of measuring this signal are estimated for current and future lensing data sets. Conclusions: The Euclid mission should provide all the necessary information for studying the cosmic evolution of the connectivity of the cosmic web around lensing clusters using multipolar moments and probing unique signatures of, for example, baryons and warm dark matter.

Quantum chemical study of the structure, spectroscopy and reactivity of NO+.(H2O) n=1-5 clusters.

PubMed

Linton, Kirsty A; Wright, Timothy G; Besley, Nicholas A

2018-03-13

Quantum chemical methods including Møller-Plesset perturbation (MP2) theory and density functional theory (DFT) have been used to study the structure, spectroscopy and reactivity of NO + (H 2 O) n =1-5 clusters. MP2/6-311++G** calculations are shown to describe the structure and spectroscopy of the clusters well. DFT calculations with exchange-correlation functionals with a low fraction of Hartree-Fock exchange give a binding energy of NO + (H 2 O) that is too high and incorrectly predict the lowest energy structure of NO + (H 2 O) 2 , and this error may be associated with a delocalization of charge onto the water molecule directly binding to NO + Ab initio molecular dynamics (AIMD) simulations were performed to study the NO + (H 2 O) 5 [Formula: see text] H + (H 2 O) 4 + HONO reaction to investigate the formation of HONO from NO + (H 2 O) 5 Whether an intracluster reaction to form HONO is observed depends on the level of electronic structure theory used. Of note is that methods that accurately describe the relative energies of the product and reactant clusters did not show reactions on the timescales studied. This suggests that in the upper atmosphere the reaction may occur owing to the energy present in the NO + (H 2 O) 5 complex following its formation.This article is part of the theme issue 'Modern theoretical chemistry'. © 2018 The Author(s).

Excitation energy shift and size difference of low-energy levels in p -shell Λ hypernuclei

NASA Astrophysics Data System (ADS)

Kanada-En'yo, Yoshiko

2018-02-01

Structures of low-lying 0 s -orbit Λ states in p -shell Λ hypernuclei (ZAΛ) are investigated by applying microscopic cluster models for nuclear structure and a single-channel folding potential model for a Λ particle. For A >10 systems, the size reduction of core nuclei is small, and the core polarization effect is regarded as a higher-order perturbation in the Λ binding. The present calculation qualitatively describes the systematic trend of experimental data for excitation energy change from Z-1A to ZAΛ, in A >10 systems. The energy change shows a clear correlation with the nuclear size difference between the ground and excited states. In Li7Λ and Be9Λ, the significant shrinkage of cluster structures occurs consistently with the prediction of other calculations.

N-body simulations of gravitational redshifts and other relativistic distortions of galaxy clustering

NASA Astrophysics Data System (ADS)

Zhu, Hongyu; Alam, Shadab; Croft, Rupert A. C.; Ho, Shirley; Giusarma, Elena

2017-10-01

Large redshift surveys of galaxies and clusters are providing the first opportunities to search for distortions in the observed pattern of large-scale structure due to such effects as gravitational redshift. We focus on non-linear scales and apply a quasi-Newtonian approach using N-body simulations to predict the small asymmetries in the cross-correlation function of two galaxy different populations. Following recent work by Bonvin et al., Zhao and Peacock and Kaiser on galaxy clusters, we include effects which enter at the same order as gravitational redshift: the transverse Doppler effect, light-cone effects, relativistic beaming, luminosity distance perturbation and wide-angle effects. We find that all these effects cause asymmetries in the cross-correlation functions. Quantifying these asymmetries, we find that the total effect is dominated by the gravitational redshift and luminosity distance perturbation at small and large scales, respectively. By adding additional subresolution modelling of galaxy structure to the large-scale structure information, we find that the signal is significantly increased, indicating that structure on the smallest scales is important and should be included. We report on comparison of our simulation results with measurements from the SDSS/BOSS galaxy redshift survey in a companion paper.

Identification and Analysis of the Biosynthetic Gene Cluster Encoding the Thiopeptide Antibiotic Cyclothiazomycin in Streptomyces hygroscopicus 10-22▿ †

PubMed Central

Wang, Jiang; Yu, Yi; Tang, Kexuan; Liu, Wen; He, Xinyi; Huang, Xi; Deng, Zixin

2010-01-01

Thiopeptide antibiotics are an important class of natural products resulting from posttranslational modifications of ribosomally synthesized peptides. Cyclothiazomycin is a typical thiopeptide antibiotic that has a unique bridged macrocyclic structure derived from an 18-amino-acid structural peptide. Here we reported cloning, sequencing, and heterologous expression of the cyclothiazomycin biosynthetic gene cluster from Streptomyces hygroscopicus 10-22. Remarkably, successful heterologous expression of a 22.7-kb gene cluster in Streptomyces lividans 1326 suggested that there is a minimum set of 15 open reading frames that includes all of the functional genes required for cyclothiazomycin production. Six genes of these genes, cltBCDEFG flanking the structural gene cltA, were predicted to encode the enzymes required for the main framework of cyclothiazomycin, and two enzymes encoded by a putative operon, cltMN, were hypothesized to participate in the tailoring step to generate the tertiary thioether, leading to the final cyclization of the bridged macrocyclic structure. This rigorous bioinformatics analysis based on heterologous expression of cyclothiazomycin resulted in an ideal biosynthetic model for us to understand the biosynthesis of thiopeptides. PMID:20154110

Maneuvering thermal conductivity of magnetic nanofluids by tunable magnetic fields

NASA Astrophysics Data System (ADS)

Patel, Jaykumar; Parekh, Kinnari; Upadhyay, R. V.

2015-06-01

We report an experimental investigation of magnetic field dependent thermal conductivity of a transformer oil base magnetic fluid as a function of volume fractions. In the absence of magnetic field, thermal conductivity increases linearly with an increase in volume fraction, and magnitude of thermal conductivity thus obtained is lower than that predicted by Maxwell's theory. This reveals the presence of clusters/oligomers in the system. On application of magnetic field, it exhibits a non-monotonous increase in thermal conductivity. The results are interpreted using the concept of a two-step homogenization method (which is based on differential effective medium theory). The results show a transformation of particle cluster configuration from long chain like prolate shape to the aggregated drop-like structure with increasing concentration as well as a magnetic field. The aggregated drop-like structure for concentrated system is supported by optical microscopic images. This shape change of clusters reduces thermal conductivity enhancement. Moreover, this structure formation is observed as a dynamic phenomenon, and at 226 mT field, the length of the structure extends with time, becomes maximum, and then reduces. This change results in the increase or decrease of thermal conductivity.

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

Multiple receptor conformation docking and dock pose clustering as tool for CoMFA and CoMSIA analysis - a case study on HIV-1 protease inhibitors.

PubMed

Sivan, Sree Kanth; Manga, Vijjulatha

2012-02-01

Multiple receptors conformation docking (MRCD) and clustering of dock poses allows seamless incorporation of receptor binding conformation of the molecules on wide range of ligands with varied structural scaffold. The accuracy of the approach was tested on a set of 120 cyclic urea molecules having HIV-1 protease inhibitory activity using 12 high resolution X-ray crystal structures and one NMR resolved conformation of HIV-1 protease extracted from protein data bank. A cross validation was performed on 25 non-cyclic urea HIV-1 protease inhibitor having varied structures. The comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were generated using 60 molecules in the training set by applying leave one out cross validation method, r (loo) (2) values of 0.598 and 0.674 for CoMFA and CoMSIA respectively and non-cross validated regression coefficient r(2) values of 0.983 and 0.985 were obtained for CoMFA and CoMSIA respectively. The predictive ability of these models was determined using a test set of 60 cyclic urea molecules that gave predictive correlation (r (pred) (2) ) of 0.684 and 0.64 respectively for CoMFA and CoMSIA indicating good internal predictive ability. Based on this information 25 non-cyclic urea molecules were taken as a test set to check the external predictive ability of these models. This gave remarkable out come with r (pred) (2) of 0.61 and 0.53 for CoMFA and CoMSIA respectively. The results invariably show that this method is useful for performing 3D QSAR analysis on molecules having different structural motifs.

Simulating protein folding initiation sites using an alpha-carbon-only knowledge-based force field

PubMed Central

Buck, Patrick M.; Bystroff, Christopher

2015-01-01

Protein folding is a hierarchical process where structure forms locally first, then globally. Some short sequence segments initiate folding through strong structural preferences that are independent of their three-dimensional context in proteins. We have constructed a knowledge-based force field in which the energy functions are conditional on local sequence patterns, as expressed in the hidden Markov model for local structure (HMMSTR). Carbon-alpha force field (CALF) builds sequence specific statistical potentials based on database frequencies for α-carbon virtual bond opening and dihedral angles, pairwise contacts and hydrogen bond donor-acceptor pairs, and simulates folding via Brownian dynamics. We introduce hydrogen bond donor and acceptor potentials as α-carbon probability fields that are conditional on the predicted local sequence. Constant temperature simulations were carried out using 27 peptides selected as putative folding initiation sites, each 12 residues in length, representing several different local structure motifs. Each 0.6 μs trajectory was clustered based on structure. Simulation convergence or representativeness was assessed by subdividing trajectories and comparing clusters. For 21 of the 27 sequences, the largest cluster made up more than half of the total trajectory. Of these 21 sequences, 14 had cluster centers that were at most 2.6 Å root mean square deviation (RMSD) from their native structure in the corresponding full-length protein. To assess the adequacy of the energy function on nonlocal interactions, 11 full length native structures were relaxed using Brownian dynamics simulations. Equilibrated structures deviated from their native states but retained their overall topology and compactness. A simple potential that folds proteins locally and stabilizes proteins globally may enable a more realistic understanding of hierarchical folding pathways. PMID:19137613

THE ARCHES CLUSTER: EXTENDED STRUCTURE AND TIDAL RADIUS

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

Hosek, Matthew W. Jr.; Lu, Jessica R.; Anderson, Jay

At a projected distance of ∼26 pc from Sgr A*, the Arches cluster provides insight into star formation in the extreme Galactic center (GC) environment. Despite its importance, many key properties, such as the cluster’s internal structure and orbital history, are not well known. We present an astrometric and photometric study of the outer region of the Arches cluster ( R > 6.″25) using Hubble Space Telescope WFC3IR. Using proper motions, we calculate membership probabilities for stars down to F153M = 20 mag (∼2.5 M {sub ⊙}) over a 120″ × 120″ field of view, an area 144 times largermore » than previous astrometric studies of the cluster. We construct the radial profile of the Arches to a radius of 75″ (∼3 pc at 8 kpc), which can be well described by a single power law. From this profile we place a 3 σ lower limit of 2.8 pc on the observed tidal radius, which is larger than the predicted tidal radius (1–2.5 pc). Evidence of mass segregation is observed throughout the cluster, and no tidal tail structures are apparent along the orbital path. The absence of breaks in the profile suggests that the Arches has not likely experienced its closest approach to the GC between ∼0.2 and 1 Myr ago. If accurate, this constraint indicates that the cluster is on a prograde orbit and is located in front of the sky plane that intersects Sgr A*. However, further simulations of clusters in the GC potential are required to interpret the observed profile with more confidence.« less

Atoll-scale patterns in coral reef community structure: Human signatures on Ulithi Atoll, Micronesia

PubMed Central

Nelson, Peter; Abelson, Avigdor; Precoda, Kristin; Rulmal, John; Bernardi, Giacomo; Paddack, Michelle

2017-01-01

The dynamic relationship between reefs and the people who utilize them at a subsistence level is poorly understood. This paper characterizes atoll-scale patterns in shallow coral reef habitat and fish community structure, and correlates these with environmental characteristics and anthropogenic factors, critical to conservation efforts for the reefs and the people who depend on them. Hierarchical clustering analyses by site for benthic composition and fish community resulted in the same 3 major clusters: cluster 1–oceanic (close proximity to deep water) and uninhabited (low human impact); cluster 2–oceanic and inhabited (high human impact); and cluster 3–lagoonal (facing the inside of the lagoon) and inhabited (highest human impact). Distance from village, reef exposure to deep water and human population size had the greatest effect in predicting the fish and benthic community structure. Our study demonstrates a strong association between benthic and fish community structure and human use across the Ulithi Atoll (Yap State, Federated States of Micronesia) and confirms a pattern observed by local people that an ‘opportunistic’ scleractinian coral (Montipora sp.) is associated with more highly impacted reefs. Our findings suggest that small human populations (subsistence fishing) can nevertheless have considerable ecological impacts on reefs due, in part, to changes in fishing practices rather than overfishing per se, as well as larger global trends. Findings from this work can assist in building local capacity to manage reef resources across an atoll-wide scale, and illustrates the importance of anthropogenic impact even in small communities. PMID:28489903

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

PubMed

Janson, Harald; Kjelsberg, Ellen

2006-01-01

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

Quantitative radiomic profiling of glioblastoma represents transcriptomic expression.

PubMed

Kong, Doo-Sik; Kim, Junhyung; Ryu, Gyuha; You, Hye-Jin; Sung, Joon Kyung; Han, Yong Hee; Shin, Hye-Mi; Lee, In-Hee; Kim, Sung-Tae; Park, Chul-Kee; Choi, Seung Hong; Choi, Jeong Won; Seol, Ho Jun; Lee, Jung-Il; Nam, Do-Hyun

2018-01-19

Quantitative imaging biomarkers have increasingly emerged in the field of research utilizing available imaging modalities. We aimed to identify good surrogate radiomic features that can represent genetic changes of tumors, thereby establishing noninvasive means for predicting treatment outcome. From May 2012 to June 2014, we retrospectively identified 65 patients with treatment-naïve glioblastoma with available clinical information from the Samsung Medical Center data registry. Preoperative MR imaging data were obtained for all 65 patients with primary glioblastoma. A total of 82 imaging features including first-order statistics, volume, and size features, were semi-automatically extracted from structural and physiologic images such as apparent diffusion coefficient and perfusion images. Using commercially available software, NordicICE, we performed quantitative imaging analysis and collected the dataset composed of radiophenotypic parameters. Unsupervised clustering methods revealed that the radiophenotypic dataset was composed of three clusters. Each cluster represented a distinct molecular classification of glioblastoma; classical type, proneural and neural types, and mesenchymal type. These clusters also reflected differential clinical outcomes. We found that extracted imaging signatures does not represent copy number variation and somatic mutation. Quantitative radiomic features provide a potential evidence to predict molecular phenotype and treatment outcome. Radiomic profiles represents transcriptomic phenotypes more well.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks.

PubMed

Li, Min; Li, Dongyan; Tang, Yu; Wu, Fangxiang; Wang, Jianxin

2017-08-31

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster.

CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks

PubMed Central

Li, Min; Li, Dongyan; Tang, Yu; Wang, Jianxin

2017-01-01

Nowadays, cluster analysis of biological networks has become one of the most important approaches to identifying functional modules as well as predicting protein complexes and network biomarkers. Furthermore, the visualization of clustering results is crucial to display the structure of biological networks. Here we present CytoCluster, a cytoscape plugin integrating six clustering algorithms, HC-PIN (Hierarchical Clustering algorithm in Protein Interaction Networks), OH-PIN (identifying Overlapping and Hierarchical modules in Protein Interaction Networks), IPCA (Identifying Protein Complex Algorithm), ClusterONE (Clustering with Overlapping Neighborhood Expansion), DCU (Detecting Complexes based on Uncertain graph model), IPC-MCE (Identifying Protein Complexes based on Maximal Complex Extension), and BinGO (the Biological networks Gene Ontology) function. Users can select different clustering algorithms according to their requirements. The main function of these six clustering algorithms is to detect protein complexes or functional modules. In addition, BinGO is used to determine which Gene Ontology (GO) categories are statistically overrepresented in a set of genes or a subgraph of a biological network. CytoCluster can be easily expanded, so that more clustering algorithms and functions can be added to this plugin. Since it was created in July 2013, CytoCluster has been downloaded more than 9700 times in the Cytoscape App store and has already been applied to the analysis of different biological networks. CytoCluster is available from http://apps.cytoscape.org/apps/cytocluster. PMID:28858211

Thermally stable solids based on endohedrally doped ZnS clusters.

PubMed

Matxain, Jon M; Piris, Mario; Lopez, Xabier; Ugalde, Jesus M

2009-01-01

The existence of inorganic, hollow, fullerene-like ZnS clusters has been theoretically predicted and then recently confirmed experimentally. These clusters were observed to trap alkali metals and halogens because the ionization energies (IE) of alkali metals are very similar to the electron affinities (EA) of halogens. This opens the possibility of forming molecular solids composed of these fullerene building blocks because the energy released due to the difference between the IE and EA would be very small. Herein we have focused on assembling bare Zn(12)S(12) and endohedral X@Zn(12)S(12)-Y@Zn(12)S(12) dimers (X = Na, K; Y = Cl, Br) by considering the square-faces-square orientation of every two adjacent clusters, which leads to a fcc cubic crystal structure in the solid. The structures were fully optimized in all cases, and their thermal stability was confirmed by ab initio thermal molecular dynamics calculations. The optimum lattice parameter of the solids was found to be around 13.8 A, which corresponds to distances of about 2.5 A between monomers, which is typical of covalent Zn-S bonds. The resulting solids are nanoporous materials similar to B(12)N(12). Due to their nanoporous structure, these zeolite-shaped solids could be used in heterogeneous catalysis and as storage materials and molecular sieves.

Solid-state NMR/NQR and first-principles study of two niobium halide cluster compounds.

PubMed

Perić, Berislav; Gautier, Régis; Pickard, Chris J; Bosiočić, Marko; Grbić, Mihael S; Požek, Miroslav

2014-01-01

Two hexanuclear niobium halide cluster compounds with a [Nb6X12](2+) (X=Cl, Br) diamagnetic cluster core, have been studied by a combination of experimental solid-state NMR/NQR techniques and PAW/GIPAW calculations. For niobium sites the NMR parameters were determined by using variable Bo field static broadband NMR measurements and additional NQR measurements. It was found that they possess large positive chemical shifts, contrary to majority of niobium compounds studied so far by solid-state NMR, but in accordance with chemical shifts of (95)Mo nuclei in structurally related compounds containing [Mo6Br8](4+) cluster cores. Experimentally determined δiso((93)Nb) values are in the range from 2,400 to 3,000 ppm. A detailed analysis of geometrical relations between computed electric field gradient (EFG) and chemical shift (CS) tensors with respect to structural features of cluster units was carried out. These tensors on niobium sites are almost axially symmetric with parallel orientation of the largest EFG and the smallest CS principal axes (Vzz and δ33) coinciding with the molecular four-fold axis of the [Nb6X12](2+) unit. Bridging halogen sites are characterized by large asymmetry of EFG and CS tensors, the largest EFG principal axis (Vzz) is perpendicular to the X-Nb bonds, while intermediate EFG principal axis (Vyy) and the largest CS principal axis (δ11) are oriented in the radial direction with respect to the center of the cluster unit. For more symmetrical bromide compound the PAW predictions for EFG parameters are in better correspondence with the NMR/NQR measurements than in the less symmetrical chlorine compound. Theoretically predicted NMR parameters of bridging halogen sites were checked by (79/81)Br NQR and (35)Cl solid-state NMR measurements. Copyright © 2014 Elsevier Inc. All rights reserved.

IMG-ABC: A Knowledge Base To Fuel Discovery of Biosynthetic Gene Clusters and Novel Secondary Metabolites.

PubMed

Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; Ratner, Anna; Palaniappan, Krishna; Szeto, Ernest; Huang, Jinghua; Reddy, T B K; Cimermančič, Peter; Fischbach, Michael A; Ivanova, Natalia N; Markowitz, Victor M; Kyrpides, Nikos C; Pati, Amrita

2015-07-14

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of "big" genomic data for discovering small molecules. IMG-ABC relies on IMG's comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve as the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC's focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in Alphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG's extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world. Copyright © 2015 Hadjithomas et al.

Theoretical study on the spectroscopic properties of CO3(*-).nH2O clusters: extrapolation to bulk.

PubMed

Pathak, Arup K; Mukherjee, Tulsi; Maity, Dilip K

2008-10-24

Vertical detachment energies (VDE) and UV/Vis absorption spectra of hydrated carbonate radical anion clusters, CO(3)(*-).nH(2)O (n=1-8), are determined by means of ab initio electronic structure theory. The VDE values of the hydrated clusters are calculated with second-order Moller-Plesset perturbation (MP2) and coupled cluster theory using the 6-311++G(d,p) set of basis functions. The bulk VDE value of an aqueous carbonate radical anion solution is predicted to be 10.6 eV from the calculated weighted average VDE values of the CO(3)(*-).nH(2)O clusters. UV/Vis absorption spectra of the hydrated clusters are calculated by means of time-dependent density functional theory using the Becke three-parameter nonlocal exchange and the Lee-Yang-Parr nonlocal correlation functional (B3LYP). The simulated UV/Vis spectrum of the CO(3)(*-).8H(2)O cluster is in excellent agreement with the reported experimental spectrum for CO(3)(*-) (aq), obtained based on pulse radiolysis experiments.

Time-efficient simulations of tight-binding electronic structures with Intel Xeon PhiTM many-core processors

NASA Astrophysics Data System (ADS)

Ryu, Hoon; Jeong, Yosang; Kang, Ji-Hoon; Cho, Kyu Nam

2016-12-01

Modelling of multi-million atomic semiconductor structures is important as it not only predicts properties of physically realizable novel materials, but can accelerate advanced device designs. This work elaborates a new Technology-Computer-Aided-Design (TCAD) tool for nanoelectronics modelling, which uses a sp3d5s∗ tight-binding approach to describe multi-million atomic structures, and simulate electronic structures with high performance computing (HPC), including atomic effects such as alloy and dopant disorders. Being named as Quantum simulation tool for Advanced Nanoscale Devices (Q-AND), the tool shows nice scalability on traditional multi-core HPC clusters implying the strong capability of large-scale electronic structure simulations, particularly with remarkable performance enhancement on latest clusters of Intel Xeon PhiTM coprocessors. A review of the recent modelling study conducted to understand an experimental work of highly phosphorus-doped silicon nanowires, is presented to demonstrate the utility of Q-AND. Having been developed via Intel Parallel Computing Center project, Q-AND will be open to public to establish a sound framework of nanoelectronics modelling with advanced HPC clusters of a many-core base. With details of the development methodology and exemplary study of dopant electronics, this work will present a practical guideline for TCAD development to researchers in the field of computational nanoelectronics.

Photoelectron spectroscopy of B4O4-: Dual 3c-4e π hyperbonds and rhombic 4c-4e o-bond in boron oxide clusters

NASA Astrophysics Data System (ADS)

Tian, Wen-Juan; Zhao, Li-Juan; Chen, Qiang; Ou, Ting; Xu, Hong-Guang; Zheng, Wei-Jun; Zhai, Hua-Jin; Li, Si-Dian

2015-04-01

Gas-phase anion photoelectron spectroscopy (PES) is combined with global structural searches and electronic structure calculations at the hybrid Becke 3-parameter exchange functional and Lee-Yang-Parr correlation functional (B3LYP) and single-point coupled-cluster with single, double, and perturbative triple excitations (CCSD(T)) levels to probe the structural and electronic properties and chemical bonding of the B4O40/- clusters. The measured PES spectra of B4O4- exhibit a major band with the adiabatic and vertical detachment energies (ADE and VDE) of 2.64 ± 0.10 and 2.81 ± 0.10 eV, respectively, as well as a weak peak with the ADE and VDE of 1.42 ± 0.08 and 1.48 ± 0.08 eV. The former band proves to correspond to the Y-shaped global minimum of Cs B4O4- (2A″), with the calculated ADE/VDE of 2.57/2.84 eV at the CCSD(T) level, whereas the weak band is associated with the second lowest-energy, rhombic isomer of D2h B4O4- (2B2g) with the predicted ADE/VDE of 1.43/1.49 eV. Both anion structures are planar, featuring a B atom or a B2O2 core bonded with terminal BO and/or BO2 groups. The same Y-shaped and rhombic structures are also located for the B4O4 neutral cluster, albeit with a reversed energy order. Bonding analyses reveal dual three-center four-electron (3c-4e) π hyperbonds in the Y-shaped B4O40/- clusters and a four-center four-electron (4c-4e) π bond, that is, the so-called o-bond in the rhombic B4O40/- clusters. This work is the first experimental study on a molecular system with an o-bond.

Structure-based design of broadly protective group a streptococcal M protein-based vaccines.

PubMed

Dale, James B; Smeesters, Pierre R; Courtney, Harry S; Penfound, Thomas A; Hohn, Claudia M; Smith, Jeremy C; Baudry, Jerome Y

2017-01-03

A major obstacle to the development of broadly protective M protein-based group A streptococcal (GAS) vaccines is the variability within the N-terminal epitopes that evoke potent bactericidal antibodies. The concept of M type-specific protective immune responses has recently been challenged based on the observation that multivalent M protein vaccines elicited cross-reactive bactericidal antibodies against a number of non-vaccine M types of GAS. Additionally, a new "cluster-based" typing system of 175M proteins identified a limited number of clusters containing closely related M proteins. In the current study, we used the emm cluster typing system, in combination with computational structure-based peptide modeling, as a novel approach to the design of potentially broadly protective M protein-based vaccines. M protein sequences (AA 16-50) from the E4 cluster containing 17 emm types of GAS were analyzed using de novo 3-D structure prediction tools and the resulting structures subjected to chemical diversity analysis to identify sequences that were the most representative of the 3-D physicochemical properties of the M peptides in the cluster. Five peptides that spanned the range of physicochemical attributes of all 17 peptides were used to formulate synthetic and recombinant vaccines. Rabbit antisera were assayed for antibodies that cross-reacted with E4 peptides and whole bacteria by ELISA and for bactericidal activity against all E4GAS. The synthetic vaccine rabbit antisera reacted with all 17 E4M peptides and demonstrated bactericidal activity against 15/17 E4GAS. A recombinant hybrid vaccine containing the same E4 peptides also elicited antibodies that cross-reacted with all E4M peptides. Comprehensive studies using structure-based design may result in a broadly protective M peptide vaccine that will elicit cluster-specific and emm type-specific antibody responses against the majority of clinically relevant emm types of GAS. Copyright © 2016 Elsevier Ltd. All rights reserved.

Improving hot region prediction by parameter optimization of density clustering in PPI.

PubMed

Hu, Jing; Zhang, Xiaolong

2016-11-01

This paper proposed an optimized algorithm which combines density clustering of parameter selection with feature-based classification for hot region prediction. First, all the residues are classified by SVM to remove non-hot spot residues, then density clustering of parameter selection is used to find hot regions. In the density clustering, this paper studies how to select input parameters. There are two parameters radius and density in density-based incremental clustering. We firstly fix density and enumerate radius to find a pair of parameters which leads to maximum number of clusters, and then we fix radius and enumerate density to find another pair of parameters which leads to maximum number of clusters. Experiment results show that the proposed method using both two pairs of parameters provides better prediction performance than the other method, and compare these two predictive results, the result by fixing radius and enumerating density have slightly higher prediction accuracy than that by fixing density and enumerating radius. Copyright © 2016. Published by Elsevier Inc.

Structural, electronic and vibrational properties of GexCy (x+y=2-5) nanoclusters: A B3LYP-DFT study

NASA Astrophysics Data System (ADS)

Goswami, Sohini; Saha, Sushmita; Yadav, R. K.

2015-11-01

An ab-initio study of the stability, structural and electronic properties has been made for 84 germanium carbide nanoclusters, GexCy (x+y=2-5). The configuration possessing the maximum value of final binding energy (FBE), among the various configurations corresponding to a fixed x+y=n value, is named as the most stable structure. The vibrational and optical properties have been investigated only for the most stable structures. A B3LYP-DFT/6-311G(3df) method has been employed to optimize fully the geometries of the nanoclusters. The binding energies (BE), highest-occupied and lowest-unoccupied molecular orbital (HOMO-LUMO) gaps have been obtained for all the clusters and the bond lengths have been reported for the most stable clusters. We have considered the zero point energy (ZPE) corrections. The adiabatic and vertical ionization potentials (IPs) and electron affinities (EAs), charge on atoms, dipole moments, vibrational frequencies, infrared intensities (IR Int.), relative infrared intensities (Rel. IR Int.) and Raman scattering activities have also been investigated for the most stable structures. The configurations containing the carbon atoms in majority are seen to be the most stable structures. The strong C-C bond has important role in stabilizing the clusters. For the clusters containing one germanium atom and all the other as carbon atoms, the BE increases monotonically with the number of the carbon atoms. The HOMO-LUMO gap, IPs and EAs fluctuates with increase in the number of atoms. The nanoclusters containing even number of carbon atoms have large HOMO-LUMO gaps and IPs, whereas the nanoclusters containing even number of carbon atoms have small EAs. In general, the adiabatic IP (EA) is smaller (greater) than the vertical IP (EA). The optical absorption spectrum or electron energy loss spectrum (EELS) is unique for every cluster, and may be used to characterize a specific cluster. All the predicted physical quantities are in good agreement with the experimental data wherever available. The growth of these most stable structures should be possible in the experiments.

Microforms in gravel bed rivers: Formation, disintegration, and effects on bedload transport

USGS Publications Warehouse

Strom, K.; Papanicolaou, A.N.; Evangelopoulos, N.; Odeh, M.

2004-01-01

This research aims to advance current knowledge on cluster formation and evolution by tackling some of the aspects associated with cluster microtopography and the effects of clusters on bedload transport. The specific objectives of the study are (1) to identify the bed shear stress range in which clusters form and disintegrate, (2) to quantitatively describe the spacing characteristics and orientation of clusters with respect to flow characteristics, (3) to quantify the effects clusters have on the mean bedload rate, and (4) to assess the effects of clusters on the pulsating nature of bedload. In order to meet the objectives of this study, two main experimental scenarios, namely, Test Series A and B (20 experiments overall) are considered in a laboratory flume under well-controlled conditions. Series A tests are performed to address objectives (1) and (2) while Series B is designed to meet objectives (3) and (4). Results show that cluster microforms develop in uniform sediment at 1.25 to 2 times the Shields parameter of an individual particle and start disintegrating at about 2.25 times the Shields parameter. It is found that during an unsteady flow event, effects of clusters on bedload transport rate can be classified in three different phases: a sink phase where clusters absorb incoming sediment, a neutral phase where clusters do not affect bedload, and a source phase where clusters release particles. Clusters also increase the magnitude of the fluctuations in bedload transport rate, showing that clusters amplify the unsteady nature of bedload transport. A fourth-order autoregressive, autoregressive integrated moving average model is employed to describe the time series of bedload and provide a predictive formula for predicting bedload at different periods. Finally, a change-point analysis enhanced with a binary segmentation procedure is performed to identify the abrupt changes in the bedload statistic characteristics due to the effects of clusters and detect the different phases in bedload time series using probability theory. The analysis verifies the experimental findings that three phases are detected in the bedload rate time series structure, namely, sink, neutral, and source. ?? ASCE / JUNE 2004.

Speckle lithography for fabricating Gaussian, quasi-random 2D structures and black silicon structures

PubMed Central

Bingi, Jayachandra; Murukeshan, Vadakke Matham

2015-01-01

Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices. PMID:26679513

Population genetic structure of Patagonian toothfish (Dissostichus eleginoides) in the Southeast Pacific and Southwest Atlantic Ocean

PubMed Central

Canales-Aguirre, Cristian B.; Galleguillos, Ricardo; Oyarzun, Fernanda X.; Hernández, Cristián E.

2018-01-01

Previous studies of population genetic structure in Dissostichus eleginoides have shown that oceanographic and geographic discontinuities drive in this species population differentiation. Studies have focused on the genetics of D. eleginoides in the Southern Ocean; however, there is little knowledge of their genetic variation along the South American continental shelf. In this study, we used a panel of six microsatellites to test whether D. eleginoides shows population genetic structuring in this region. We hypothesized that this species would show zero or very limited genetic structuring due to the habitat continuity along the South American shelf from Peru in the Pacific Ocean to the Falkland Islands in the Atlantic Ocean. We used Bayesian and traditional analyses to evaluate population genetic structure, and we estimated the number of putative migrants and effective population size. Consistent with our predictions, our results showed no significant genetic structuring among populations of the South American continental shelf but supported two significant and well-defined genetic clusters of D. eleginoides between regions (South American continental shelf and South Georgia clusters). Genetic connectivity between these two clusters was 11.3% of putative migrants from the South American cluster to the South Georgia Island and 0.7% in the opposite direction. Effective population size was higher in locations from the South American continental shelf as compared with the South Georgia Island. Overall, our results support that the continuity of the deep-sea habitat along the continental shelf and the biological features of the study species are plausible drivers of intraspecific population genetic structuring across the distribution of D. eleginoides on the South American continental shelf. PMID:29362690

Quantifying Biomass from Point Clouds by Connecting Representations of Ecosystem Structure

NASA Astrophysics Data System (ADS)

Hendryx, S. M.; Barron-Gafford, G.

2017-12-01

Quantifying terrestrial ecosystem biomass is an essential part of monitoring carbon stocks and fluxes within the global carbon cycle and optimizing natural resource management. Point cloud data such as from lidar and structure from motion can be effective for quantifying biomass over large areas, but significant challenges remain in developing effective models that allow for such predictions. Inference models that estimate biomass from point clouds are established in many environments, yet, are often scale-dependent, needing to be fitted and applied at the same spatial scale and grid size at which they were developed. Furthermore, training such models typically requires large in situ datasets that are often prohibitively costly or time-consuming to obtain. We present here a scale- and sensor-invariant framework for efficiently estimating biomass from point clouds. Central to this framework, we present a new algorithm, assignPointsToExistingClusters, that has been developed for finding matches between in situ data and clusters in remotely-sensed point clouds. The algorithm can be used for assessing canopy segmentation accuracy and for training and validating machine learning models for predicting biophysical variables. We demonstrate the algorithm's efficacy by using it to train a random forest model of above ground biomass in a shrubland environment in Southern Arizona. We show that by learning a nonlinear function to estimate biomass from segmented canopy features we can reduce error, especially in the presence of inaccurate clusterings, when compared to a traditional, deterministic technique to estimate biomass from remotely measured canopies. Our random forest on cluster features model extends established methods of training random forest regressions to predict biomass of subplots but requires significantly less training data and is scale invariant. The random forest on cluster features model reduced mean absolute error, when evaluated on all test data in leave one out cross validation, by 40.6% from deterministic mesquite allometry and 35.9% from the inferred ecosystem-state allometric function. Our framework should allow for the inference of biomass more efficiently than common subplot methods and more accurately than individual tree segmentation methods in densely vegetated environments.

Unification of [FeFe]-hydrogenases into three structural and functional groups.

PubMed

Poudel, Saroj; Tokmina-Lukaszewska, Monika; Colman, Daniel R; Refai, Mohammed; Schut, Gerrit J; King, Paul W; Maness, Pin-Ching; Adams, Michael W W; Peters, John W; Bothner, Brian; Boyd, Eric S

2016-09-01

[FeFe]-hydrogenases (Hyd) are structurally diverse enzymes that catalyze the reversible oxidation of hydrogen (H2). Recent biochemical data demonstrate new functional roles for these enzymes, including those that function in electron bifurcation where an exergonic reaction is coupled with an endergonic reaction to drive the reversible oxidation/production of H2. To identify the structural determinants that underpin differences in enzyme functionality, a total of 714 homologous sequences of the catalytic subunit, HydA, were compiled. Bioinformatics approaches informed by biochemical data were then used to characterize differences in inferred quaternary structure, HydA active site protein environment, accessory iron-sulfur clusters in HydA, and regulatory proteins encoded in HydA gene neighborhoods. HydA homologs were clustered into one of three classification groups, Group 1 (G1), Group 2 (G2), and Group 3 (G3). G1 enzymes were predicted to be monomeric while those in G2 and G3 were predicted to be multimeric and include HydB, HydC (G2/G3) and HydD (G3) subunits. Variation in the HydA active site and accessory iron-sulfur clusters did not vary by group type. Group-specific regulatory genes were identified in the gene neighborhoods of both G2 and G3 Hyd. Analyses of purified G2 and G3 enzymes by mass spectrometry strongly suggest that they are post-translationally modified by phosphorylation. These results suggest that bifurcation capability is dictated primarily by the presence of both HydB and HydC in Hyd complexes, rather than by variation in HydA. This classification scheme provides a framework for future biochemical and mutagenesis studies to elucidate the functional role of Hyd enzymes. Copyright © 2016 Elsevier B.V. All rights reserved.

Unification of [FeFe]-hydrogenases into three structural and functional groups

DOE PAGES

Poudel, Saroj; Tokmina-Lukaszewska, Monika; Colman, Daniel R.; ...

2016-05-27

[FeFe]-hydrogenases (Hyd) are structurally diverse enzymes that catalyze the reversible oxidation of hydrogen (H 2). Recent biochemical data demonstrate new functional roles for these enzymes, including those that function in electron bifurcation where an exergonic reaction is coupled with an endergonic reaction to drive the reversible oxidation/production of H 2. To identify the structural determinants that underpin differences in enzyme functionality, a total of 714 homologous sequences of the catalytic subunit, HydA, were compiled. Bioinformatics approaches informed by biochemical data were then used to characterize differences in inferred quaternary structure, HydA active site protein environment, accessory iron-sulfur clusters in HydA,more » and regulatory proteins encoded in HydA gene neighborhoods. HydA homologs were clustered into one of three classification groups, Group 1 (G1), Group 2 (G2), and Group 3 (G3). G1 enzymes were predicted to be monomeric while those in G2 and G3 were predicted to be multimeric and include HydB, HydC (G2/G3) and HydD (G3) subunits. Variation in the HydA active site and accessory iron-sulfur clusters did not vary by group type. Group-specific regulatory genes were identified in the gene neighborhoods of both G2 and G3 Hyd. Analyses of purified G2 and G3 enzymes by mass spectrometry strongly suggests that they are post-translationally modified by phosphorylation. In conclusion, these results suggest that bifurcation capability is dictated primarily by the presence of both HydB and HydC in Hyd complexes, rather than by variation in HydA.« less

Helium segregation on surfaces of plasma-exposed tungsten

NASA Astrophysics Data System (ADS)

Maroudas, Dimitrios; Blondel, Sophie; Hu, Lin; Hammond, Karl D.; Wirth, Brian D.

2016-02-01

We report a hierarchical multi-scale modeling study of implanted helium segregation on surfaces of tungsten, considered as a plasma facing component in nuclear fusion reactors. We employ a hierarchy of atomic-scale simulations based on a reliable interatomic interaction potential, including molecular-statics simulations to understand the origin of helium surface segregation, targeted molecular-dynamics (MD) simulations of near-surface cluster reactions, and large-scale MD simulations of implanted helium evolution in plasma-exposed tungsten. We find that small, mobile He n (1  ⩽  n  ⩽  7) clusters in the near-surface region are attracted to the surface due to an elastic interaction force that provides the thermodynamic driving force for surface segregation. This elastic interaction force induces drift fluxes of these mobile He n clusters, which increase substantially as the migrating clusters approach the surface, facilitating helium segregation on the surface. Moreover, the clusters’ drift toward the surface enables cluster reactions, most importantly trap mutation, in the near-surface region at rates much higher than in the bulk material. These near-surface cluster dynamics have significant effects on the surface morphology, near-surface defect structures, and the amount of helium retained in the material upon plasma exposure. We integrate the findings of such atomic-scale simulations into a properly parameterized and validated spatially dependent, continuum-scale reaction-diffusion cluster dynamics model, capable of predicting implanted helium evolution, surface segregation, and its near-surface effects in tungsten. This cluster-dynamics model sets the stage for development of fully atomistically informed coarse-grained models for computationally efficient simulation predictions of helium surface segregation, as well as helium retention and surface morphological evolution, toward optimal design of plasma facing components.

Virality Prediction and Community Structure in Social Networks

NASA Astrophysics Data System (ADS)

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-08-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

Virality Prediction and Community Structure in Social Networks

PubMed Central

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-01-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications. PMID:23982106

Virality prediction and community structure in social networks.

PubMed

Weng, Lilian; Menczer, Filippo; Ahn, Yong-Yeol

2013-01-01

How does network structure affect diffusion? Recent studies suggest that the answer depends on the type of contagion. Complex contagions, unlike infectious diseases (simple contagions), are affected by social reinforcement and homophily. Hence, the spread within highly clustered communities is enhanced, while diffusion across communities is hampered. A common hypothesis is that memes and behaviors are complex contagions. We show that, while most memes indeed spread like complex contagions, a few viral memes spread across many communities, like diseases. We demonstrate that the future popularity of a meme can be predicted by quantifying its early spreading pattern in terms of community concentration. The more communities a meme permeates, the more viral it is. We present a practical method to translate data about community structure into predictive knowledge about what information will spread widely. This connection contributes to our understanding in computational social science, social media analytics, and marketing applications.

Bioinformatics analysis of the predicted polyprenol reductase genes in higher plants

NASA Astrophysics Data System (ADS)

Basyuni, M.; Wati, R.

2018-03-01

The present study evaluates the bioinformatics methods to analyze twenty-four predicted polyprenol reductase genes from higher plants on GenBank as well as predicted the structure, composition, similarity, subcellular localization, and phylogenetic. The physicochemical properties of plant polyprenol showed diversity among the observed genes. The percentage of the secondary structure of plant polyprenol genes followed the ratio order of α helix > random coil > extended chain structure. The values of chloroplast but not signal peptide were too low, indicated that few chloroplast transit peptide in plant polyprenol reductase genes. The possibility of the potential transit peptide showed variation among the plant polyprenol reductase, suggested the importance of understanding the variety of peptide components of plant polyprenol genes. To clarify this finding, a phylogenetic tree was drawn. The phylogenetic tree shows several branches in the tree, suggested that plant polyprenol reductase genes grouped into divergent clusters in the tree.

Structure and thermodynamics of a mixture of patchy and spherical colloids: A multi-body association theory with complete reference fluid information

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

Bansal, Artee; Asthagiri, D.; Cox, Kenneth R.

A mixture of solvent particles with short-range, directional interactions and solute particles with short-range, isotropic interactions that can bond multiple times is of fundamental interest in understanding liquids and colloidal mixtures. Because of multi-body correlations, predicting the structure and thermodynamics of such systems remains a challenge. Earlier Marshall and Chapman [J. Chem. Phys. 139, 104904 (2013)] developed a theory wherein association effects due to interactions multiply the partition function for clustering of particles in a reference hard-sphere system. The multi-body effects are incorporated in the clustering process, which in their work was obtained in the absence of the bulk medium.more » The bulk solvent effects were then modeled approximately within a second order perturbation approach. However, their approach is inadequate at high densities and for large association strengths. Based on the idea that the clustering of solvent in a defined coordination volume around the solute is related to occupancy statistics in that defined coordination volume, we develop an approach to incorporate the complete information about hard-sphere clustering in a bulk solvent at the density of interest. The occupancy probabilities are obtained from enhanced sampling simulations but we also develop a concise parametric form to model these probabilities using the quasichemical theory of solutions. We show that incorporating the complete reference information results in an approach that can predict the bonding state and thermodynamics of the colloidal solute for a wide range of system conditions.« less

New Techniques for Ancient Proteins: Direct Coupling Analysis Applied on Proteins Involved in Iron Sulfur Cluster Biogenesis

PubMed Central

Fantini, Marco; Malinverni, Duccio; De Los Rios, Paolo; Pastore, Annalisa

2017-01-01

Direct coupling analysis (DCA) is a powerful statistical inference tool used to study protein evolution. It was introduced to predict protein folds and protein-protein interactions, and has also been applied to the prediction of entire interactomes. Here, we have used it to analyze three proteins of the iron-sulfur biogenesis machine, an essential metabolic pathway conserved in all organisms. We show that DCA can correctly reproduce structural features of the CyaY/frataxin family (a protein involved in the human disease Friedreich's ataxia) despite being based on the relatively small number of sequences allowed by its genomic distribution. This result gives us confidence in the method. Its application to the iron-sulfur cluster scaffold protein IscU, which has been suggested to function both as an ordered and a disordered form, allows us to distinguish evolutionary traces of the structured species, suggesting that, if present in the cell, the disordered form has not left evolutionary imprinting. We observe instead, for the first time, direct indications of how the protein can dimerize head-to-head and bind 4Fe4S clusters. Analysis of the alternative scaffold protein IscA provides strong support to a coordination of the cluster by a dimeric form rather than a tetramer, as previously suggested. Our analysis also suggests the presence in solution of a mixture of monomeric and dimeric species, and guides us to the prevalent one. Finally, we used DCA to analyze interactions between some of these proteins, and discuss the potentials and limitations of the method. PMID:28664160

Pt/Au nanoalloy supported on alumina and chlorided alumina: DFT and experimental analysis

NASA Astrophysics Data System (ADS)

Sharifi, N.; Falamaki, C.; Ghorbanzadeh Ahangari, M.

2018-04-01

Density functional theory (DFT) was used to explore the adsorption of Pt/Au nanoalloy onto a pure and chlorided γ-Al2O3(110) surface, which has been applied in numerous catalytic reactions. First, we considered the adsorption properties of Pt clusters (n ≤ 5) onto the Al2O3(110) surface to determine the most stable Pt cluster on alumina surface in reforming processes. After full structural relaxations of Pt clusters at various configurations on alumina, our computed results expressed that the minimum binding energy (‑5.67 eV) is accrued for Pt4 cluster and the distance between the nearest Pt atom in the cluster to the alumina surface is equal to 1.13 Å. Then, we investigated the binding energies, geometries, and electronic properties of adsorbed Aun clusters (n ≤ 6) on the γ-Al2O3(110) surface. Our studied showed that Au5 was the most thermodynamically stable structure on γ-Al2O3. Finally, we inspected these properties for adsorbed Au clusters onto the Pt4-decorated alumina (Aun/Pt4-alumina) system. The binding energy of the Au4/Pt4-alumina system was ‑5.01 eV, and the distance between Au4 cluster and Pt4-alumina was 1.33 Å. The Au4/Pt4alumina system was found to be the most stable nanometer-sized catalyst design. At last, our first-principles calculations predicted that the best position of embedment Cl on the Au4/Pt4-alumina.

Root Structure and Functioning for Efficient Acquisition of Phosphorus: Matching Morphological and Physiological Traits

PubMed Central

LAMBERS, HANS; SHANE, MICHAEL W.; CRAMER, MICHAEL D.; PEARSE, STUART J.; VENEKLAAS, ERIK J.

2006-01-01

• Background Global phosphorus (P) reserves are being depleted, with half-depletion predicted to occur between 2040 and 2060. Most of the P applied in fertilizers may be sorbed by soil, and not be available for plants lacking specific adaptations. On the severely P-impoverished soils of south-western Australia and the Cape region in South Africa, non-mycorrhizal species exhibit highly effective adaptations to acquire P. A wide range of these non-mycorrhizal species, belonging to two monocotyledonous and eight dicotyledonous families, produce root clusters. Non-mycorrhizal species with root clusters appear to be particularly effective at accessing P when its availability is extremely low. • Scope There is a need to develop crops that are highly effective at acquiring inorganic P (Pi) from P-sorbing soils. Traits such as those found in non-mycorrhizal root-cluster-bearing species in Australia, South Africa and other P-impoverished environments are highly desirable for future crops. Root clusters combine a specialized structure with a specialized metabolism. Native species with such traits could be domesticated or crossed with existing crop species. An alternative approach would be to develop future crops with root clusters based on knowledge of the genes involved in development and functioning of root clusters. • Conclusions Root clusters offer enormous potential for future research of both a fundamental and a strategic nature. New discoveries of the development and functioning of root clusters in both monocotyledonous and dicotyledonous families are essential to produce new crops with superior P-acquisition traits. PMID:16769731

Unveiling the Synchrotron Cosmic Web: Pilot Study

NASA Astrophysics Data System (ADS)

Brown, Shea; Rudnick, Lawrence; Pfrommer, Christoph; Jones, Thomas

2011-10-01

The overall goal of this project is to challenge our current theoretical understanding of the relativistic particle populations in the inter-galactic medium (IGM) through deep 1.4 GHz observations of 13 massive, high-redshift clusters of galaxies. Designed to compliment/extend the GMRT radio halo survey (Venturi et al. 2007), these observations will attempt to detect the peaks of the purported synchrotron cosmic-web, and place serious limits on models of CR acceleration and magnetic field amplification during large-scale structure formation. The primary goals of this survey are: 1) Confirm the bi-modal nature of the radio halo population, which favors turbulent re-acceleration of cosmic-ray electrons (CRe) during cluster mergers as the source of the diffuse radio emission; 2) Directly test hadronic secondary models which predict the presence of cosmic-ray protons (CRp) in the cores of massive X-ray clusters; 3) Search in polarization for shock structures, a potential source of CR acceleration in the IGM.

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.

Cluster-mediated assembly enables step-growth copolymerization from binary nanoparticle mixtures with rationally designed architectures† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c8sc00220g

PubMed Central

Zhang, Xianfeng; Lv, Longfei; Wu, Guanhong; Yang, Dong

2018-01-01

Directed co-assembly of binary nanoparticles (NPs) into one-dimensional copolymer-like chains is fascinating but challenging in the realm of material science. While many strategies have been developed to induce the polymerization of NPs, it remains a grand challenge to produce colloidal copolymers with widely tailored compositions and precisely controlled architectures. Herein we report a robust colloidal polymerization strategy, which enables the growth of sophisticated NP chains with elaborately designed structures. By quantifying NP assembly statistics and kinetics, we establish that the linear assembly of colloidal NPs, with the assistance of PbSO4 clusters, follows a step-growth polymerization mechanism, and on the basis of this, we design and fabricate NP chains structurally analogous to random, block, and alternating copolymers, respectively. Our studies offer mechanistic insights into cluster-mediated colloidal polymerization, paving the way toward the rational synthesis of colloidal copolymers with quantitatively predicted architectures and functionalities. PMID:29862003

The XXL Survey. II. The bright cluster sample: catalogue and luminosity function

NASA Astrophysics Data System (ADS)

Pacaud, F.; Clerc, N.; Giles, P. A.; Adami, C.; Sadibekova, T.; Pierre, M.; Maughan, B. J.; Lieu, M.; Le Fèvre, J. P.; Alis, S.; Altieri, B.; Ardila, F.; Baldry, I.; Benoist, C.; Birkinshaw, M.; Chiappetti, L.; Démoclès, J.; Eckert, D.; Evrard, A. E.; Faccioli, L.; Gastaldello, F.; Guennou, L.; Horellou, C.; Iovino, A.; Koulouridis, E.; Le Brun, V.; Lidman, C.; Liske, J.; Maurogordato, S.; Menanteau, F.; Owers, M.; Poggianti, B.; Pomarède, D.; Pompei, E.; Ponman, T. J.; Rapetti, D.; Reiprich, T. H.; Smith, G. P.; Tuffs, R.; Valageas, P.; Valtchanov, I.; Willis, J. P.; Ziparo, F.

2016-06-01

Context. The XXL Survey is the largest survey carried out by the XMM-Newton satellite and covers a total area of 50 square degrees distributed over two fields. It primarily aims at investigating the large-scale structures of the Universe using the distribution of galaxy clusters and active galactic nuclei as tracers of the matter distribution. The survey will ultimately uncover several hundreds of galaxy clusters out to a redshift of ~2 at a sensitivity of ~10-14 erg s-1 cm-2 in the [0.5-2] keV band. Aims: This article presents the XXL bright cluster sample, a subsample of 100 galaxy clusters selected from the full XXL catalogue by setting a lower limit of 3 × 10-14 erg s-1 cm-2 on the source flux within a 1' aperture. Methods: The selection function was estimated using a mixture of Monte Carlo simulations and analytical recipes that closely reproduce the source selection process. An extensive spectroscopic follow-up provided redshifts for 97 of the 100 clusters. We derived accurate X-ray parameters for all the sources. Scaling relations were self-consistently derived from the same sample in other publications of the series. On this basis, we study the number density, luminosity function, and spatial distribution of the sample. Results: The bright cluster sample consists of systems with masses between M500 = 7 × 1013 and 3 × 1014 M⊙, mostly located between z = 0.1 and 0.5. The observed sky density of clusters is slightly below the predictions from the WMAP9 model, and significantly below the prediction from the Planck 2015 cosmology. In general, within the current uncertainties of the cluster mass calibration, models with higher values of σ8 and/or ΩM appear more difficult to accommodate. We provide tight constraints on the cluster differential luminosity function and find no hint of evolution out to z ~ 1. We also find strong evidence for the presence of large-scale structures in the XXL bright cluster sample and identify five new superclusters. Based on observations obtained with XMM-Newton, an ESA science mission with instruments and contributions directly funded by ESA Member States and NASA. Based on observations made with ESO Telescopes at the La Silla and Paranal Observatories under programme ID 089.A-0666 and LP191.A-0268.The Master Catalogue is available at the CDS via anonymous ftp to http://cdsarc.u-strasbg.fr (http://130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/qcat?J/A+A/592/A2

Measurements of resonant scattering in the Perseus Cluster core with Hitomi SXS

NASA Astrophysics Data System (ADS)

Hitomi Collaboration; Aharonian, Felix; Akamatsu, Hiroki; Akimoto, Fumie; Allen, Steven W.; Angelini, Lorella; Audard, Marc; Awaki, Hisamitsu; Axelsson, Magnus; Bamba, Aya; Bautz, Marshall W.; Blandford, Roger; Brenneman, Laura W.; Brown, Gregory V.; Bulbul, Esra; Cackett, Edward M.; Chernyakova, Maria; Chiao, Meng P.; Coppi, Paolo S.; Costantini, Elisa; de Plaa, Jelle; de Vries, Cor P.; den Herder, Jan-Willem; Done, Chris; Dotani, Tadayasu; Ebisawa, Ken; Eckart, Megan E.; Enoto, Teruaki; Ezoe, Yuichiro; Fabian, Andrew C.; Ferrigno, Carlo; Foster, Adam R.; Fujimoto, Ryuichi; Fukazawa, Yasushi; Furukawa, Maki; Furuzawa, Akihiro; Galeazzi, Massimiliano; Gallo, Luigi C.; Gandhi, Poshak; Giustini, Margherita; Goldwurm, Andrea; Gu, Liyi; Guainazzi, Matteo; Haba, Yoshito; Hagino, Kouichi; Hamaguchi, Kenji; Harrus, Ilana M.; Hatsukade, Isamu; Hayashi, Katsuhiro; Hayashi, Takayuki; Hayashida, Kiyoshi; Hiraga, Junko S.; Hornschemeier, Ann; Hoshino, Akio; Hughes, John P.; Ichinohe, Yuto; Iizuka, Ryo; Inoue, Hajime; Inoue, Yoshiyuki; Ishida, Manabu; Ishikawa, Kumi; Ishisaki, Yoshitaka; Iwai, Masachika; Kaastra, Jelle; Kallman, Tim; Kamae, Tsuneyoshi; Kataoka, Jun; Katsuda, Satoru; Kawai, Nobuyuki; Kelley, Richard L.; Kilbourne, Caroline A.; Kitaguchi, Takao; Kitamoto, Shunji; Kitayama, Tetsu; Kohmura, Takayoshi; Kokubun, Motohide; Koyama, Katsuji; Koyama, Shu; Kretschmar, Peter; Krimm, Hans A.; Kubota, Aya; Kunieda, Hideyo; Laurent, Philippe; Lee, Shiu-Hang; Leutenegger, Maurice A.; Limousin, Olivier O.; Loewenstein, Michael; Long, Knox S.; Lumb, David; Madejski, Greg; Maeda, Yoshitomo; Maier, Daniel; Makishima, Kazuo; Markevitch, Maxim; Matsumoto, Hironori; Matsushita, Kyoko; McCammon, Dan; McNamara, Brian R.; Mehdipour, Missagh; Miller, Eric D.; Miller, Jon M.; Mineshige, Shin; Mitsuda, Kazuhisa; Mitsuishi, Ikuyuki; Miyazawa, Takuya; Mizuno, Tsunefumi; Mori, Hideyuki; Mori, Koji; Mukai, Koji; Murakami, Hiroshi; Mushotzky, Richard F.; Nakagawa, Takao; Nakajima, Hiroshi; Nakamori, Takeshi; Nakashima, Shinya; Nakazawa, Kazuhiro; Nobukawa, Kumiko K.; Nobukawa, Masayoshi; Noda, Hirofumi; Odaka, Hirokazu; Ogorzalek, Anna; Ohashi, Takaya; Ohno, Masanori; Okajima, Takashi; Ota, Naomi; Ozaki, Masanobu; Paerels, Frits; Paltani, Stéphane; Petre, Robert; Pinto, Ciro; Porter, Frederick S.; Pottschmidt, Katja; Reynolds, Christopher S.; Safi-Harb, Samar; Saito, Shinya; Sakai, Kazuhiro; Sasaki, Toru; Sato, Goro; Sato, Kosuke; Sato, Rie; Sawada, Makoto; Schartel, Norbert; Serlemtsos, Peter J.; Seta, Hiromi; Shidatsu, Megumi; Simionescu, Aurora; Smith, Randall K.; Soong, Yang; Stawarz, Łukasz; Sugawara, Yasuharu; Sugita, Satoshi; Szymkowiak, Andrew; Tajima, Hiroyasu; Takahashi, Hiromitsu; Takahashi, Tadayuki; Takeda, Shiníchiro; Takei, Yoh; Tamagawa, Toru; Tamura, Takayuki; Tanaka, Takaaki; Tanaka, Yasuo; Tanaka, Yasuyuki T.; Tashiro, Makoto S.; Tawara, Yuzuru; Terada, Yukikatsu; Terashima, Yuichi; Tombesi, Francesco; Tomida, Hiroshi; Tsuboi, Yohko; Tsujimoto, Masahiro; Tsunemi, Hiroshi; Tsuru, Takeshi Go; Uchida, Hiroyuki; Uchiyama, Hideki; Uchiyama, Yasunobu; Ueda, Shutaro; Ueda, Yoshihiro; Uno, Shiníchiro; Urry, C. Megan; Ursino, Eugenio; Watanabe, Shin; Werner, Norbert; Wilkins, Dan R.; Williams, Brian J.; Yamada, Shinya; Yamaguchi, Hiroya; Yamaoka, Kazutaka; Yamasaki, Noriko Y.; Yamauchi, Makoto; Yamauchi, Shigeo; Yaqoob, Tahir; Yatsu, Yoichi; Yonetoku, Daisuke; Zhuravleva, Irina; Zoghbi, Abderahmen

2018-03-01

Thanks to its high spectral resolution (˜5 eV at 6 keV), the Soft X-ray Spectrometer (SXS) on board Hitomi enables us to measure the detailed structure of spatially resolved emission lines from highly ionized ions in galaxy clusters for the first time. In this series of papers, using the SXS we have measured the velocities of gas motions, metallicities and the multi-temperature structure of the gas in the core of the Perseus Cluster. Here, we show that when inferring physical properties from line emissivities in systems like Perseus, the resonant scattering effect should be taken into account. In the Hitomi waveband, resonant scattering mostly affects the Fe XXV Heα line (w)—the strongest line in the spectrum. The flux measured by Hitomi in this line is suppressed by a factor of ˜1.3 in the inner ˜30 kpc, compared to predictions for an optically thin plasma; the suppression decreases with the distance from the center. The w line also appears slightly broader than other lines from the same ion. The observed distortions of the w line flux, shape, and distance dependence are all consistent with the expected effect of the resonant scattering in the Perseus core. By measuring the ratio of fluxes in optically thick (w) and thin (Fe XXV forbidden, Heβ, Lyα) lines, and comparing these ratios with predictions from Monte Carlo radiative transfer simulations, the velocities of gas motions have been obtained. The results are consistent with the direct measurements of gas velocities from line broadening described elsewhere in this series, although the systematic and statistical uncertainties remain significant. Further improvements in the predictions of line emissivities in plasma models, and deeper observations with future X-ray missions offering similar or better capabilities to the Hitomi SXS, will enable resonant scattering measurements to provide powerful constraints on the amplitude and anisotropy of cluster gas motions.

Endohedral gallide cluster superconductors and superconductivity in ReGa5.

PubMed

Xie, Weiwei; Luo, Huixia; Phelan, Brendan F; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph

2015-12-22

We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures.

Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM)

PubMed Central

Skinnider, Michael A.; Dejong, Chris A.; Rees, Philip N.; Johnston, Chad W.; Li, Haoxin; Webster, Andrew L. H.; Wyatt, Morgan A.; Magarvey, Nathan A.

2015-01-01

Microbial natural products are an invaluable source of evolved bioactive small molecules and pharmaceutical agents. Next-generation and metagenomic sequencing indicates untapped genomic potential, yet high rediscovery rates of known metabolites increasingly frustrate conventional natural product screening programs. New methods to connect biosynthetic gene clusters to novel chemical scaffolds are therefore critical to enable the targeted discovery of genetically encoded natural products. Here, we present PRISM, a computational resource for the identification of biosynthetic gene clusters, prediction of genetically encoded nonribosomal peptides and type I and II polyketides, and bio- and cheminformatic dereplication of known natural products. PRISM implements novel algorithms which render it uniquely capable of predicting type II polyketides, deoxygenated sugars, and starter units, making it a comprehensive genome-guided chemical structure prediction engine. A library of 57 tailoring reactions is leveraged for combinatorial scaffold library generation when multiple potential substrates are consistent with biosynthetic logic. We compare the accuracy of PRISM to existing genomic analysis platforms. PRISM is an open-source, user-friendly web application available at http://magarveylab.ca/prism/. PMID:26442528

Search For Star Cluster Age Gradients Across Spiral Arms of Three LEGUS Disk Galaxies

NASA Astrophysics Data System (ADS)

Shabani, F.; Grebel, E. K.; Pasquali, A.; D'Onghia, E.; Gallagher, J. S.; Adamo, A.; Messa, M.; Elmegreen, B. G.; Dobbs, C.; Gouliermis, D. A.; Calzetti, D.; Grasha, K.; Elmegreen, D. M.; Cignoni, M.; Dale, D. A.; Aloisi, A.; Smith, L. J.; Tosi, M.; Thilker, D. A.; Lee, J. C.; Sabbi, E.; Kim, H.; Pellerin, A.

2018-05-01

One of the main theories for explaining the formation of spiral arms in galaxies is the stationary density wave theory. This theory predicts the existence of an age gradient across the arms. We use the stellar cluster catalogues of the galaxies NGC 1566, M51a, and NGC 628 from the Legacy Extragalactic UV Survey (LEGUS) program. In order to test for the possible existence of an age sequence across the spiral arms, we quantified the azimuthal offset between star clusters of different ages in our target galaxies. We found that NGC 1566, a grand-design spiral galaxy with bisymmetric arms and a strong bar, shows a significant age gradient across the spiral arms that appears to be consistent with the prediction of the stationary density wave theory. In contrast, M51a with its two well-defined spiral arms and a weaker bar does not show an age gradient across the arms. In addition, a comparison with non-LEGUS star cluster catalogues for M51a yields similar results. We believe that the spiral structure of M51a is not the result of a stationary density wave with a fixed pattern speed. Instead, tidal interactions could be the dominant mechanism for the formation of spiral arms. We also found no offset in the azimuthal distribution of star clusters with different ages across the weak spiral arms of NGC 628.

Galaxy Clusters, Near and Far, Have a Lot in Common

NASA Astrophysics Data System (ADS)

2005-04-01

Using two orbiting X-ray telescopes, a team of international astronomers has examined distant galaxy clusters in order to compare them with their counterparts that are relatively close by. Speaking today at the RAS National Astronomy Meeting in Birmingham, Dr. Ben Maughan (Harvard-Smithsonian Center for Astrophysics), presented the results of this new analysis. The observations indicate that, despite the great expansion that the Universe has undergone since the Big Bang, galaxy clusters both local and distant have a great deal in common. This discovery could eventually lead to a better understanding of how to "weigh" these enormous structures, and, in so doing, answer important questions about the nature and structure of the Universe. Clusters of galaxies, the largest known gravitationally-bound objects, are the knots in the cosmic web of structure that permeates the Universe. Theoretical models make predictions about the number, distribution and properties of these clusters. Scientists can test and improve models of the Universe by comparing these predictions with observations. The most powerful way of doing this is to measure the masses of galaxy clusters, particularly those in the distant Universe. However, weighing galaxy clusters is extremely difficult. One relatively easy way to weigh a galaxy cluster is to use simple laws ("scaling relations") to estimate its weight from properties that are easy to observe, like its luminosity (brightness) or temperature. This is like estimating someone's weight from their height if you didn't have any scales. Over the last 3 years, a team of researchers, led by Ben Maughan, has observed 11 distant galaxy clusters with ESA's XMM-Newton and NASA's Chandra X-ray Observatory. The clusters have redshifts of z = 0.6-1.0, which corresponds to distances of 6 to 8 billion light years. This means that we see them as they were when the Universe was half its present age. The survey included two unusual systems, one in which two massive clusters are merging and another extremely massive cluster which appears very "relaxed" and undisturbed. The X-ray data allowed the scientists to measure the temperatures and luminosities of the gas in the clusters. They were then able to infer their total masses, which varied between 200 and 1,100 times the mass of our Milky Way galaxy. These measurements were then used to test whether galaxy clusters of different sizes and located at different distances from us are simply scaled versions of each other -- a condition known as being "self-similar." This is an important characteristic for astronomers to identify if they hope to get the true weights of galaxy clusters. "For example, chocolate bars are strongly self-similar," said Maughan. "If you shrank a king-size bar to a fun-size bar, they would be identical versions of each other but just different sizes." "However, if you shrank a castle to the size of a bungalow, they would be very different structures, despite being the same size. This means that they are not strongly self-similar objects." Another possible type of relationship between clusters is what scientists call "weakly self-similar." In this case, galaxy clusters in the distant universe and those nearby are almost identical to each other, but not exactly the same. (The only differences between them can be accounted for by the expansion of the Universe since the Big Bang.) Although astronomers have known for some time that galaxy clusters are not strongly self-similar, the question of whether or not they are weakly self-similar has remained open. The new results show that as long as astronomers take into account the continuous expansion of the Universe, then galaxy clusters are, in fact, weakly self-similar. This means that the same scaling relations used to weigh nearby galaxy clusters hold true for these very distant clusters. "Our results mean that weighing distant galaxy clusters could become as easy as converting from Fahrenheit to Celsius," said Maughan. "This will help to answer important questions about the nature and structure of the Universe." The other members of the team were: Laurence Jones (University of Birmingham, UK) Harald Ebeling (Institute for Astronomy, HI, USA), and Caleb Scharf (Columbia Astrophysics Laboratory, NY, USA). The observations were made with the European Photon Imaging Camera (EPIC) on XMM and the Advanced Camera for Imaging and Spectroscopy (ACIS) on Chandra. They were part of the WARPS survey of distant galaxy clusters detected by chance in observations made with the UK-US-Dutch ROSAT X-ray satellite. Additional information and images are available at: http://www.sr.bham.ac.uk/~habib/nampr/

Self-Assembly of Trimer Colloids: Effect of Shape and Interaction Range†

PubMed Central

Hatch, Harold W.; Yang, Seung-Yeob; Mittal, Jeetain; Shen, Vincent K.

2016-01-01

Trimers with one attractive bead and two repulsive beads, similar to recently synthesized trimer patchy colloids, were simulated with flat-histogram Monte Carlo methods to obtain the stable self-assembled structures for different shapes and interaction potentials. Extended corresponding states principle was successfully applied to self-assembling systems in order to approximately collapse the results for models with the same shape, but different interaction range. This helps us directly compare simulation results with previous experiment, and good agreement was found between the two. In addition, a variety of self-assembled structures were observed by varying the trimer geometry, including spherical clusters, elongated clusters, monolayers, and spherical shells. In conclusion, our results help to compare simulations and experiments, via extended corresponding states, and we predict the formation of self-assembled structures for trimer shapes that have not been experimentally synthesized. PMID:27087490

Accumulation of transposable elements in Hox gene clusters during adaptive radiation of Anolis lizards.

PubMed

Feiner, Nathalie

2016-10-12

Transposable elements (TEs) are DNA sequences that can insert elsewhere in the genome and modify genome structure and gene regulation. The role of TEs in evolution is contentious. One hypothesis posits that TE activity generates genomic incompatibilities that can cause reproductive isolation between incipient species. This predicts that TEs will accumulate during speciation events. Here, I tested the prediction that extant lineages with a relatively high rate of speciation have a high number of TEs in their genomes. I sequenced and analysed the TE content of a marker genomic region (Hox clusters) in Anolis lizards, a classic case of an adaptive radiation. Unlike other vertebrates, including closely related lizards, Anolis lizards have high numbers of TEs in their Hox clusters, genomic regions that regulate development of the morphological adaptations that characterize habitat specialists in these lizards. Following a burst of TE activity in the lineage leading to extant Anolis, TEs have continued to accumulate during or after speciation events, resulting in a positive relationship between TE density and lineage speciation rate. These results are consistent with the prediction that TE activity contributes to adaptive radiation by promoting speciation. Although there was no evidence that TE density per se is associated with ecological morphology, the activity of TEs in Hox clusters could have been a rich source for phenotypic variation that may have facilitated the rapid parallel morphological adaptation to microhabitats seen in extant Anolis lizards. © 2016 The Author(s).

Accumulation of transposable elements in Hox gene clusters during adaptive radiation of Anolis lizards

PubMed Central

2016-01-01

Transposable elements (TEs) are DNA sequences that can insert elsewhere in the genome and modify genome structure and gene regulation. The role of TEs in evolution is contentious. One hypothesis posits that TE activity generates genomic incompatibilities that can cause reproductive isolation between incipient species. This predicts that TEs will accumulate during speciation events. Here, I tested the prediction that extant lineages with a relatively high rate of speciation have a high number of TEs in their genomes. I sequenced and analysed the TE content of a marker genomic region (Hox clusters) in Anolis lizards, a classic case of an adaptive radiation. Unlike other vertebrates, including closely related lizards, Anolis lizards have high numbers of TEs in their Hox clusters, genomic regions that regulate development of the morphological adaptations that characterize habitat specialists in these lizards. Following a burst of TE activity in the lineage leading to extant Anolis, TEs have continued to accumulate during or after speciation events, resulting in a positive relationship between TE density and lineage speciation rate. These results are consistent with the prediction that TE activity contributes to adaptive radiation by promoting speciation. Although there was no evidence that TE density per se is associated with ecological morphology, the activity of TEs in Hox clusters could have been a rich source for phenotypic variation that may have facilitated the rapid parallel morphological adaptation to microhabitats seen in extant Anolis lizards. PMID:27733546

Complete genome sequence of Nitrosospira multiformis, an ammonia-oxidizing bacterium from the soil environment

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

Norton, Jeanette M.; Klotz, Martin G; Stein, Lisa Y

2008-01-01

The complete genome of the ammonia-oxidizing bacterium, Nitrosospira multiformis (ATCC 25196T), consists of a circular chromosome and three small plasmids totaling 3,234,309 bp and encoding 2827 putative proteins. Of these, 2026 proteins have predicted functions and 801 are without conserved functional domains, yet 747 of these have similarity to other predicted proteins in databases. Gene homologs from Nitrosomonas europaea and N. eutropha were the best match for 42% of the predicted genes in N. multiformis. The genome contains three nearly identical copies of amo and hao gene clusters as large repeats. Distinguishing features compared to N. europaea include: the presencemore » of gene clusters encoding urease and hydrogenase, a RuBisCO-encoding operon of distinctive structure and phylogeny, and a relatively small complement of genes related to Fe acquisition. Systems for synthesis of a pyoverdine-like siderophore and for acyl-homoserine lactone were unique to N. multiformis among the sequenced AOB genomes. Gene clusters encoding proteins associated with outer membrane and cell envelope functions including transporters, porins, exopolysaccharide synthesis, capsule formation and protein sorting/export were abundant. Numerous sensory transduction and response regulator gene systems directed towards sensing of the extracellular environment are described. Gene clusters for glycogen, polyphosphate and cyanophycin storage and utilization were identified providing mechanisms for meeting energy requirements under substrate-limited conditions. The genome of N. multiformis encodes the core pathways for chemolithoautotrophy along with adaptations for surface growth and survival in soil environments.« less

π-Stacking, C-H/π, and halogen bonding interactions in bromobenzene and mixed bromobenzene-benzene clusters.

PubMed

Reid, Scott A; Nyambo, Silver; Muzangwa, Lloyd; Uhler, Brandon

2013-12-19

Noncovalent interactions play an important role in many chemical and biochemical processes. Building upon our recent study of the homoclusters of chlorobenzene, where π-π stacking and CH/π interactions were identified as the most important binding motifs, in this work we present a study of bromobenzene (PhBr) and mixed bromobenzene-benzene clusters. Electronic spectra in the region of the PhBr monomer S0-S1 (ππ*) transition were obtained using resonant two-photon ionization (R2PI) methods combined with time-of-flight mass analysis. As previously found for related systems, the PhBr cluster spectra show a broad feature whose center is red-shifted from the monomer absorption, and electronic structure calculations indicate the presence of multiple isomers and Franck-Condon activity in low-frequency intermolecular modes. Calculations at the M06-2X/aug-cc-pVDZ level find in total eight minimum energy structures for the PhBr dimer: four π-stacked structures differing in the relative orientation of the Br atoms (denoted D1-D4), one T-shaped structure (D5), and three halogen bonded structures (D6-D8). The calculated binding energies of these complexes, corrected for basis set superposition error (BSSE) and zero-point energy (ZPE), are in the range of -6 to -24 kJ/mol. Time-dependent density functional theory (TDDFT) calculations predict that these isomers absorb over a range that is roughly consistent with the breadth of the experimental spectrum. To examine the influence of dipole-dipole interaction, R2PI spectra were also obtained for the mixed PhBr···benzene dimer, where the spectral congestion is reduced and clear vibrational structure is observed. This structure is well-simulated by Franck-Condon calculations that incorporate the lowest frequency intermolecular modes. Calculations find four minimum energy structures for the mixed dimer and predict that the binding energy of the global minimum is reduced by ~30% relative to the global minimum PhBr dimer structure.

Ancestry prediction in Singapore population samples using the Illumina ForenSeq kit.

PubMed

Ramani, Anantharaman; Wong, Yongxun; Tan, Si Zhen; Shue, Bing Hong; Syn, Christopher

2017-11-01

The ability to predict bio-geographic ancestry can be valuable to generate investigative leads towards solving crimes. Ancestry informative marker (AIM) sets include large numbers of SNPs to predict an ancestral population. Massively parallel sequencing has enabled forensic laboratories to genotype a large number of such markers in a single assay. Illumina's ForenSeq DNA Signature Kit includes the ancestry informative SNPs reported by Kidd et al. In this study, the ancestry prediction capabilities of the ForenSeq kit through sequencing on the MiSeq FGx were evaluated in 1030 unrelated Singapore population samples of Chinese, Malay and Indian origin. A total of 59 ancestry SNPs and phenotypic SNPs with AIM properties were selected. The bio-geographic ancestry of the 1030 samples, as predicted by Illumina's ForenSeq Universal Analysis Software (UAS), was determined. 712 of the genotyped samples were used as a training sample set for the generation of an ancestry prediction model using STRUCTURE and Snipper. The performance of the prediction model was tested by both methods with the remaining 318 samples. Ancestry prediction in UAS was able to correctly classify the Singapore Chinese as part of the East Asian cluster, while Indians clustered with Ad-mixed Americans and Malays clustered in-between these two reference populations. Principal component analyses showed that the 59 SNPs were only able to account for 26% of the variation between the Singapore sub-populations. Their discriminatory potential was also found to be lower (G ST =0.085) than that reported in ALFRED (F ST =0.357). The Snipper algorithm was able to correctly predict bio-geographic ancestry in 91% of Chinese and Indian, and 88% of Malay individuals, while the success rates for the STRUCTURE algorithm were 94% in Chinese, 80% in Malay, and 91% in Indian individuals. Both these algorithms were able to provide admixture proportions when present. Ancestry prediction accuracy (in terms of likelihood ratio) was generally high in the absence of admixture. Misclassification occurred in admixed individuals, who were likely offspring of inter-ethnic marriages, and hence whose self-reported bio-geographic ancestries were dependent on that of their fathers, and in individuals of minority sub-populations with inter-ethnic beliefs. The ancestry prediction capabilities of the 59 SNPs on the ForenSeq kit were reasonably effective in differentiating the Singapore Chinese, Malay and Indian sub-populations, and will be of use for investigative purposes. However, there is potential for more accurate prediction through the evaluation of other AIM sets. Copyright © 2017 Elsevier B.V. All rights reserved.

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms.

PubMed

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S

2006-12-21

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H(+)(H(2)O)(7). For H(+)(H(2)O)(7) the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Moller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H(+)(H(2)O)(7) [though nearly isoenergetic to the 3D structure for D(+)(D(2)O)(7)]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

Structure and spectral features of H+(H2O)7: Eigen versus Zundel forms

NASA Astrophysics Data System (ADS)

Shin, Ilgyou; Park, Mina; Min, Seung Kyu; Lee, Eun Cheol; Suh, Seung Bum; Kim, Kwang S.

2006-12-01

The two dimensional (2D) to three dimensional (3D) transition for the protonated water cluster has been controversial, in particular, for H+(H2O)7. For H+(H2O)7 the 3D structure is predicted to be lower in energy than the 2D structure at most levels of theory without zero-point energy (ZPE) correction. On the other hand, with ZPE correction it is predicted to be either 2D or 3D depending on the calculational levels. Although the ZPE correction favors the 3D structure at the level of coupled cluster theory with singles, doubles, and perturbative triples excitations [CCSD(T)] using the aug-cc-pVDZ basis set, the result based on the anharmonic zero-point vibrational energy correction favors the 2D structure. Therefore, the authors investigated the energies based on the complete basis set limit scheme (which we devised in an unbiased way) at the resolution of the identity approximation Møller-Plesset second order perturbation theory and CCSD(T) levels, and found that the 2D structure has the lowest energy for H+(H2O)7 [though nearly isoenergetic to the 3D structure for D+(D2O)7]. This structure has the Zundel-type configuration, but it shows the quantum probabilistic distribution including some of the Eigen-type configuration. The vibrational spectra of MP2/aug-cc-pVDZ calculations and Car-Parrinello molecular dynamics simulations, taking into account the thermal and dynamic effects, show that the 2D Zundel-type form is in good agreement with experiments.

DARK MATTER SUBHALOS AND THE X-RAY MORPHOLOGY OF THE COMA CLUSTER

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

Andrade-Santos, Felipe; Nulsen, Paul E. J.; Kraft, Ralph P.

2013-04-01

Structure formation models predict that clusters of galaxies contain numerous massive subhalos. The gravity of a subhalo in a cluster compresses the surrounding intracluster gas and enhances its X-ray emission. We present a simple model, which treats subhalos as slow moving and gasless, for computing this effect. Recent weak lensing measurements by Okabe et al. have determined masses of {approx}10{sup 13} M{sub Sun} for three mass concentrations projected within 300 kpc of the center of the Coma Cluster, two of which are centered on the giant elliptical galaxies NGC 4889 and NGC 4874. Adopting a smooth spheroidal {beta}-model for themore » gas distribution in the unperturbed cluster, we model the effect of these subhalos on the X-ray morphology of the Coma Cluster, comparing our results to Chandra and XMM-Newton X-ray data. The agreement between the models and the X-ray morphology of the central Coma Cluster is striking. With subhalo parameters from the lensing measurements, the distances of the three subhalos from the Coma Cluster midplane along our line of sight are all tightly constrained. Using the model to fit the subhalo masses for NGC 4889 and NGC 4874 gives 9.1 Multiplication-Sign 10{sup 12} M{sub Sun} and 7.6 Multiplication-Sign 10{sup 12} M{sub Sun }, respectively, in good agreement with the lensing masses. These results lend strong support to the argument that NGC 4889 and NGC 4874 are each associated with a subhalo that resides near the center of the Coma Cluster. In addition to constraining the masses and 3-d location of subhalos, the X-ray data show promise as a means of probing the structure of central subhalos.« less

Characterization of a Large Cluster of Influenza A(H1N1)pdm09 Viruses Cross-Resistant to Oseltamivir and Peramivir during the 2013-2014 Influenza Season in Japan

PubMed Central

Takashita, Emi; Kiso, Maki; Fujisaki, Seiichiro; Yokoyama, Masaru; Nakamura, Kazuya; Shirakura, Masayuki; Sato, Hironori; Odagiri, Takato; Kawaoka, Yoshihiro

2015-01-01

Between September 2013 and July 2014, 2,482 influenza 2009 pandemic A(H1N1) [A(H1N1)pdm09] viruses were screened in Japan for the H275Y substitution in their neuraminidase (NA) protein, which confers cross-resistance to oseltamivir and peramivir. We found that a large cluster of the H275Y mutant virus was present prior to the main influenza season in Sapporo/Hokkaido, with the detection rate for this mutant virus reaching 29% in this area. Phylogenetic analysis suggested the clonal expansion of a single mutant virus in Sapporo/Hokkaido. To understand the reason for this large cluster, we examined the in vitro and in vivo properties of the mutant virus. We found that it grew well in cell culture, with growth comparable to that of the wild-type virus. The cluster virus also replicated well in the upper respiratory tract of ferrets and was transmitted efficiently between ferrets by way of respiratory droplets. Almost all recently circulating A(H1N1)pdm09 viruses, including the cluster virus, possessed two substitutions in NA, V241I and N369K, which are known to increase replication and transmission fitness. A structural analysis of NA predicted that a third substitution (N386K) in the NA of the cluster virus destabilized the mutant NA structure in the presence of the V241I and N369K substitutions. Our results suggest that the cluster virus retained viral fitness to spread among humans and, accordingly, caused the large cluster in Sapporo/Hokkaido. However, the mutant NA structure was less stable than that of the wild-type virus. Therefore, once the wild-type virus began to circulate in the community, the mutant virus could not compete and faded out. PMID:25691635

Age-Related Declines in the Fidelity of Newly Acquired Category Representations

ERIC Educational Resources Information Center

Davis, Tyler; Love, Bradley C.; Maddox, W. Todd

2012-01-01

We present a theory suggesting that the ability to build category representations that reflect the nuances of category structures in the environment depends upon clustering mechanisms instantiated in an MTL-PFC-based circuit. Because function in this circuit declines with age, we predict that the ability to build category representations will be…

Complexity of major UK companies between 2006 and 2010: Hierarchical structure method approach

NASA Astrophysics Data System (ADS)

Ulusoy, Tolga; Keskin, Mustafa; Shirvani, Ayoub; Deviren, Bayram; Kantar, Ersin; Çaǧrı Dönmez, Cem

2012-11-01

This study reports on topology of the top 40 UK companies that have been analysed for predictive verification of markets for the period 2006-2010, applying the concept of minimal spanning tree and hierarchical tree (HT) analysis. Construction of the minimal spanning tree (MST) and the hierarchical tree (HT) is confined to a brief description of the methodology and a definition of the correlation function between a pair of companies based on the London Stock Exchange (LSE) index in order to quantify synchronization between the companies. A derivation of hierarchical organization and the construction of minimal-spanning and hierarchical trees for the 2006-2008 and 2008-2010 periods have been used and the results validate the predictive verification of applied semantics. The trees are known as useful tools to perceive and detect the global structure, taxonomy and hierarchy in financial data. From these trees, two different clusters of companies in 2006 were detected. They also show three clusters in 2008 and two between 2008 and 2010, according to their proximity. The clusters match each other as regards their common production activities or their strong interrelationship. The key companies are generally given by major economic activities as expected. This work gives a comparative approach between MST and HT methods from statistical physics and information theory with analysis of financial markets that may give new valuable and useful information of the financial market dynamics.

Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

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

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna

Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

The OGCleaner: filtering false-positive homology clusters.

PubMed

Fujimoto, M Stanley; Suvorov, Anton; Jensen, Nicholas O; Clement, Mark J; Snell, Quinn; Bybee, Seth M

2017-01-01

Detecting homologous sequences in organisms is an essential step in protein structure and function prediction, gene annotation and phylogenetic tree construction. Heuristic methods are often employed for quality control of putative homology clusters. These heuristics, however, usually only apply to pairwise sequence comparison and do not examine clusters as a whole. We present the Orthology Group Cleaner (the OGCleaner), a tool designed for filtering putative orthology groups as homology or non-homology clusters by considering all sequences in a cluster. The OGCleaner relies on high-quality orthologous groups identified in OrthoDB to train machine learning algorithms that are able to distinguish between true-positive and false-positive homology groups. This package aims to improve the quality of phylogenetic tree construction especially in instances of lower-quality transcriptome assemblies. https://github.com/byucsl/ogcleaner CONTACT: sfujimoto@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Molecular Networking and Pattern-Based Genome Mining Improves Discovery of Biosynthetic Gene Clusters and their Products from Salinispora Species

DOE PAGES

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna; ...

2015-04-09

Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. In this paper, we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains, including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated themore » identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. Finally, these efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches.« less

Extending Stability Through Hierarchical Clusters in Echo State Networks

PubMed Central

Jarvis, Sarah; Rotter, Stefan; Egert, Ulrich

2009-01-01

Echo State Networks (ESN) are reservoir networks that satisfy well-established criteria for stability when constructed as feedforward networks. Recent evidence suggests that stability criteria are altered in the presence of reservoir substructures, such as clusters. Understanding how the reservoir architecture affects stability is thus important for the appropriate design of any ESN. To quantitatively determine the influence of the most relevant network parameters, we analyzed the impact of reservoir substructures on stability in hierarchically clustered ESNs, as they allow a smooth transition from highly structured to increasingly homogeneous reservoirs. Previous studies used the largest eigenvalue of the reservoir connectivity matrix (spectral radius) as a predictor for stable network dynamics. Here, we evaluate the impact of clusters, hierarchy and intercluster connectivity on the predictive power of the spectral radius for stability. Both hierarchy and low relative cluster sizes extend the range of spectral radius values, leading to stable networks, while increasing intercluster connectivity decreased maximal spectral radius. PMID:20725523

Molecular Networking and Pattern-Based Genome Mining Improves discovery of biosynthetic gene clusters and their products from Salinispora species

PubMed Central

Duncan, Katherine R.; Crüsemann, Max; Lechner, Anna; Sarkar, Anindita; Li, Jie; Ziemert, Nadine; Wang, Mingxun; Bandeira, Nuno; Moore, Bradley S.; Dorrestein, Pieter C.; Jensen, Paul R.

2015-01-01

Summary Genome sequencing has revealed that bacteria contain many more biosynthetic gene clusters than predicted based on the number of secondary metabolites discovered to date. While this biosynthetic reservoir has fostered interest in new tools for natural product discovery, there remains a gap between gene cluster detection and compound discovery. Here we apply molecular networking and the new concept of pattern-based genome mining to 35 Salinispora strains including 30 for which draft genome sequences were either available or obtained for this study. The results provide a method to simultaneously compare large numbers of complex microbial extracts, which facilitated the identification of media components, known compounds and their derivatives, and new compounds that could be prioritized for structure elucidation. These efforts revealed considerable metabolite diversity and led to several molecular family-gene cluster pairings, of which the quinomycin-type depsipeptide retimycin A was characterized and linked to gene cluster NRPS40 using pattern-based bioinformatic approaches. PMID:25865308

Confirmation of general relativity on large scales from weak lensing and galaxy velocities.

PubMed

Reyes, Reinabelle; Mandelbaum, Rachel; Seljak, Uros; Baldauf, Tobias; Gunn, James E; Lombriser, Lucas; Smith, Robert E

2010-03-11

Although general relativity underlies modern cosmology, its applicability on cosmological length scales has yet to be stringently tested. Such a test has recently been proposed, using a quantity, E(G), that combines measures of large-scale gravitational lensing, galaxy clustering and structure growth rate. The combination is insensitive to 'galaxy bias' (the difference between the clustering of visible galaxies and invisible dark matter) and is thus robust to the uncertainty in this parameter. Modified theories of gravity generally predict values of E(G) different from the general relativistic prediction because, in these theories, the 'gravitational slip' (the difference between the two potentials that describe perturbations in the gravitational metric) is non-zero, which leads to changes in the growth of structure and the strength of the gravitational lensing effect. Here we report that E(G) = 0.39 +/- 0.06 on length scales of tens of megaparsecs, in agreement with the general relativistic prediction of E(G) approximately 0.4. The measured value excludes a model within the tensor-vector-scalar gravity theory, which modifies both Newtonian and Einstein gravity. However, the relatively large uncertainty still permits models within f(R) theory, which is an extension of general relativity. A fivefold decrease in uncertainty is needed to rule out these models.

Confirmation of general relativity on large scales from weak lensing and galaxy velocities

NASA Astrophysics Data System (ADS)

Reyes, Reinabelle; Mandelbaum, Rachel; Seljak, Uros; Baldauf, Tobias; Gunn, James E.; Lombriser, Lucas; Smith, Robert E.

2010-03-01

Although general relativity underlies modern cosmology, its applicability on cosmological length scales has yet to be stringently tested. Such a test has recently been proposed, using a quantity, EG, that combines measures of large-scale gravitational lensing, galaxy clustering and structure growth rate. The combination is insensitive to `galaxy bias' (the difference between the clustering of visible galaxies and invisible dark matter) and is thus robust to the uncertainty in this parameter. Modified theories of gravity generally predict values of EG different from the general relativistic prediction because, in these theories, the `gravitational slip' (the difference between the two potentials that describe perturbations in the gravitational metric) is non-zero, which leads to changes in the growth of structure and the strength of the gravitational lensing effect. Here we report that EG = 0.39+/-0.06 on length scales of tens of megaparsecs, in agreement with the general relativistic prediction of EG~0.4. The measured value excludes a model within the tensor-vector-scalar gravity theory, which modifies both Newtonian and Einstein gravity. However, the relatively large uncertainty still permits models within f() theory, which is an extension of general relativity. A fivefold decrease in uncertainty is needed to rule out these models.

Impact of Neutrinos on Dark Matter Halo Environment

NASA Astrophysics Data System (ADS)

Court, Travis; Villaescusa-Navarro, Francisco

2018-01-01

The spatial clustering of galaxies is commonly used to infer the shape of the matter power spectrum and therefore to place constraints on the value of the cosmological parameters. In order to extract the maximum information from galaxy surveys it is required to provide accurate theoretical predictions. The first step to model galaxy clustering is to understand the spatial distribution of the structures where they reside: dark matter halos. I will show that the clustering of halos does not depend only on mass, but on other quantities like local matter overdensity. I will point out that halo clustering is also sensitive to the local overdensity of the cosmic neutrino background. I will show that splitting halos according to neutrino overdensity induces a very large scale-dependence bias, an effect that may lead to a new technique to constraint the sum of the neutrino masses.

Radiation-Induced Chemical Dynamics in Ar Clusters Exposed to Strong X-Ray Pulses.

PubMed

Kumagai, Yoshiaki; Jurek, Zoltan; Xu, Weiqing; Fukuzawa, Hironobu; Motomura, Koji; Iablonskyi, Denys; Nagaya, Kiyonobu; Wada, Shin-Ichi; Mondal, Subhendu; Tachibana, Tetsuya; Ito, Yuta; Sakai, Tsukasa; Matsunami, Kenji; Nishiyama, Toshiyuki; Umemoto, Takayuki; Nicolas, Christophe; Miron, Catalin; Togashi, Tadashi; Ogawa, Kanade; Owada, Shigeki; Tono, Kensuke; Yabashi, Makina; Son, Sang-Kil; Ziaja, Beata; Santra, Robin; Ueda, Kiyoshi

2018-06-01

We show that electron and ion spectroscopy reveals the details of the oligomer formation in Ar clusters exposed to an x-ray free electron laser (XFEL) pulse, i.e., chemical dynamics triggered by x rays. With guidance from a dedicated molecular dynamics simulation tool, we find that van der Waals bonding, the oligomer formation mechanism, and charge transfer among the cluster constituents significantly affect ionization dynamics induced by an XFEL pulse of moderate fluence. Our results clearly demonstrate that XFEL pulses can be used not only to "damage and destroy" molecular assemblies but also to modify and transform their molecular structure. The accuracy of the predictions obtained makes it possible to apply the cluster spectroscopy, in connection with the respective simulations, for estimation of the XFEL pulse fluence in the fluence regime below single-atom multiple-photon absorption, which is hardly accessible with other diagnostic tools.

Radiation-Induced Chemical Dynamics in Ar Clusters Exposed to Strong X-Ray Pulses

NASA Astrophysics Data System (ADS)

Kumagai, Yoshiaki; Jurek, Zoltan; Xu, Weiqing; Fukuzawa, Hironobu; Motomura, Koji; Iablonskyi, Denys; Nagaya, Kiyonobu; Wada, Shin-ichi; Mondal, Subhendu; Tachibana, Tetsuya; Ito, Yuta; Sakai, Tsukasa; Matsunami, Kenji; Nishiyama, Toshiyuki; Umemoto, Takayuki; Nicolas, Christophe; Miron, Catalin; Togashi, Tadashi; Ogawa, Kanade; Owada, Shigeki; Tono, Kensuke; Yabashi, Makina; Son, Sang-Kil; Ziaja, Beata; Santra, Robin; Ueda, Kiyoshi

2018-06-01

We show that electron and ion spectroscopy reveals the details of the oligomer formation in Ar clusters exposed to an x-ray free electron laser (XFEL) pulse, i.e., chemical dynamics triggered by x rays. With guidance from a dedicated molecular dynamics simulation tool, we find that van der Waals bonding, the oligomer formation mechanism, and charge transfer among the cluster constituents significantly affect ionization dynamics induced by an XFEL pulse of moderate fluence. Our results clearly demonstrate that XFEL pulses can be used not only to "damage and destroy" molecular assemblies but also to modify and transform their molecular structure. The accuracy of the predictions obtained makes it possible to apply the cluster spectroscopy, in connection with the respective simulations, for estimation of the XFEL pulse fluence in the fluence regime below single-atom multiple-photon absorption, which is hardly accessible with other diagnostic tools.

Prediction (early recognition) of emerging flu strain clusters

NASA Astrophysics Data System (ADS)

Li, X.; Phillips, J. C.

2017-08-01

Early detection of incipient dominant influenza strains is one of the key steps in the design and manufacture of an effective annual influenza vaccine. Here we report the most current results for pandemic H3N2 flu vaccine design. A 2006 model of dimensional reduction (compaction) of viral mutational complexity derives two-dimensional Cartesian mutational maps (2DMM) that exhibit an emergent dominant strain as a small and distinct cluster of as few as 10 strains. We show that recent extensions of this model can detect incipient strains one year or more in advance of their dominance in the human population. Our structural interpretation of our unexpectedly rich 2DMM involves sialic acid, and is based on nearly 6000 strains in a series of recent 3-year time windows. Vaccine effectiveness is predicted best by analyzing dominant mutational epitopes.

An Automated Strategy for Binding-Pose Selection and Docking Assessment in Structure-Based Drug Design.

PubMed

Ballante, Flavio; Marshall, Garland R

2016-01-25

Molecular docking is a widely used technique in drug design to predict the binding pose of a candidate compound in a defined therapeutic target. Numerous docking protocols are available, each characterized by different search methods and scoring functions, thus providing variable predictive capability on a same ligand-protein system. To validate a docking protocol, it is necessary to determine a priori the ability to reproduce the experimental binding pose (i.e., by determining the docking accuracy (DA)) in order to select the most appropriate docking procedure and thus estimate the rate of success in docking novel compounds. As common docking programs use generally different root-mean-square deviation (RMSD) formulas, scoring functions, and format results, it is both difficult and time-consuming to consistently determine and compare their predictive capabilities in order to identify the best protocol to use for the target of interest and to extrapolate the binding poses (i.e., best-docked (BD), best-cluster (BC), and best-fit (BF) poses) when applying a given docking program over thousands/millions of molecules during virtual screening. To reduce this difficulty, two new procedures called Clusterizer and DockAccessor have been developed and implemented for use with some common and "free-for-academics" programs such as AutoDock4, AutoDock4(Zn), AutoDock Vina, DOCK, MpSDockZn, PLANTS, and Surflex-Dock to automatically extrapolate BD, BC, and BF poses as well as to perform consistent cluster and DA analyses. Clusterizer and DockAccessor (code available over the Internet) represent two novel tools to collect computationally determined poses and detect the most predictive docking approach. Herein an application to human lysine deacetylase (hKDAC) inhibitors is illustrated.

Microwave-assisted synthesis of water-soluble, fluorescent gold nanoclusters capped with small organic molecules and a revealing fluorescence and X-ray absorption study

NASA Astrophysics Data System (ADS)

Helmbrecht, C.; Lützenkirchen-Hecht, D.; Frank, W.

2015-03-01

Colourless solutions of blue light-emitting, water-soluble gold nanoclusters (AuNC) were synthesized from gold colloids under microwave irradiation using small organic molecules as ligands. Stabilized by 1,3,5-triaza-7-phosphaadamantane (TPA) or l-glutamine (GLU), fluorescence quantum yields up to 5% were obtained. AuNC are considered to be very promising for biological labelling, optoelectronic devices and light-emitting materials but the structure-property relationships have still not been fully clarified. To expand the knowledge about the AuNC apart from their fluorescent properties they were studied by X-ray absorption spectroscopy elucidating the oxidation state of the nanoclusters' gold atoms. Based on curve fitting of the XANES spectra in comparison to several gold references, optically transparent fluorescent AuNC are predicted to be ligand-stabilized Au5+ species. Additionally, their near edge structure compared with analogous results of polynuclear clusters known from the literature discloses an increasing intensity of the feature close to the absorption edge with decreasing cluster size. As a result, a linear relationship between the cluster size and the X-ray absorption coefficient can be established for the first time.Colourless solutions of blue light-emitting, water-soluble gold nanoclusters (AuNC) were synthesized from gold colloids under microwave irradiation using small organic molecules as ligands. Stabilized by 1,3,5-triaza-7-phosphaadamantane (TPA) or l-glutamine (GLU), fluorescence quantum yields up to 5% were obtained. AuNC are considered to be very promising for biological labelling, optoelectronic devices and light-emitting materials but the structure-property relationships have still not been fully clarified. To expand the knowledge about the AuNC apart from their fluorescent properties they were studied by X-ray absorption spectroscopy elucidating the oxidation state of the nanoclusters' gold atoms. Based on curve fitting of the XANES spectra in comparison to several gold references, optically transparent fluorescent AuNC are predicted to be ligand-stabilized Au5+ species. Additionally, their near edge structure compared with analogous results of polynuclear clusters known from the literature discloses an increasing intensity of the feature close to the absorption edge with decreasing cluster size. As a result, a linear relationship between the cluster size and the X-ray absorption coefficient can be established for the first time. Electronic supplementary information (ESI) available: The deconvoluted reference spectra are given in ESI Fig. 1-9. See DOI: 10.1039/c4nr07051h

Robustness of atomistic Gō models in predicting native-like folding intermediates

NASA Astrophysics Data System (ADS)

Estácio, S. G.; Fernandes, C. S.; Krobath, H.; Faísca, P. F. N.; Shakhnovich, E. I.

2012-08-01

Gō models are exceedingly popular tools in computer simulations of protein folding. These models are native-centric, i.e., they are directly constructed from the protein's native structure. Therefore, it is important to understand up to which extent the atomistic details of the native structure dictate the folding behavior exhibited by Gō models. Here we address this challenge by performing exhaustive discrete molecular dynamics simulations of a Gō potential combined with a full atomistic protein representation. In particular, we investigate the robustness of this particular type of Gō models in predicting the existence of intermediate states in protein folding. We focus on the N47G mutational form of the Spc-SH3 folding domain (x-ray structure) and compare its folding pathway with that of alternative native structures produced in silico. Our methodological strategy comprises equilibrium folding simulations, structural clustering, and principal component analysis.

Machine learning prediction for classification of outcomes in local minimisation

NASA Astrophysics Data System (ADS)

Das, Ritankar; Wales, David J.

2017-01-01

Machine learning schemes are employed to predict which local minimum will result from local energy minimisation of random starting configurations for a triatomic cluster. The input data consists of structural information at one or more of the configurations in optimisation sequences that converge to one of four distinct local minima. The ability to make reliable predictions, in terms of the energy or other properties of interest, could save significant computational resources in sampling procedures that involve systematic geometry optimisation. Results are compared for two energy minimisation schemes, and for neural network and quadratic functions of the inputs.

COVARIATE-ADAPTIVE CLUSTERING OF EXPOSURES FOR AIR POLLUTION EPIDEMIOLOGY COHORTS*

PubMed Central

Keller, Joshua P.; Drton, Mathias; Larson, Timothy; Kaufman, Joel D.; Sandler, Dale P.; Szpiro, Adam A.

2017-01-01

Cohort studies in air pollution epidemiology aim to establish associations between health outcomes and air pollution exposures. Statistical analysis of such associations is complicated by the multivariate nature of the pollutant exposure data as well as the spatial misalignment that arises from the fact that exposure data are collected at regulatory monitoring network locations distinct from cohort locations. We present a novel clustering approach for addressing this challenge. Specifically, we present a method that uses geographic covariate information to cluster multi-pollutant observations and predict cluster membership at cohort locations. Our predictive k-means procedure identifies centers using a mixture model and is followed by multi-class spatial prediction. In simulations, we demonstrate that predictive k-means can reduce misclassification error by over 50% compared to ordinary k-means, with minimal loss in cluster representativeness. The improved prediction accuracy results in large gains of 30% or more in power for detecting effect modification by cluster in a simulated health analysis. In an analysis of the NIEHS Sister Study cohort using predictive k-means, we find that the association between systolic blood pressure (SBP) and long-term fine particulate matter (PM2.5) exposure varies significantly between different clusters of PM2.5 component profiles. Our cluster-based analysis shows that for subjects assigned to a cluster located in the Midwestern U.S., a 10 μg/m3 difference in exposure is associated with 4.37 mmHg (95% CI, 2.38, 6.35) higher SBP. PMID:28572869

Self-organizing map analysis using multivariate data from theophylline powders predicted by a thin-plate spline interpolation.

PubMed

Yasuda, Akihito; Onuki, Yoshinori; Kikuchi, Shingo; Takayama, Kozo

2010-11-01

The quality by design concept in pharmaceutical formulation development requires establishment of a science-based rationale and a design space. We integrated thin-plate spline (TPS) interpolation and Kohonen's self-organizing map (SOM) to visualize the latent structure underlying causal factors and pharmaceutical responses. As a model pharmaceutical product, theophylline powders were prepared based on the standard formulation. The angle of repose, compressibility, cohesion, and dispersibility were measured as the response variables. These responses were predicted quantitatively on the basis of a nonlinear TPS. A large amount of data on these powders was generated and classified into several clusters using an SOM. The experimental values of the responses were predicted with high accuracy, and the data generated for the powders could be classified into several distinctive clusters. The SOM feature map allowed us to analyze the global and local correlations between causal factors and powder characteristics. For instance, the quantities of microcrystalline cellulose (MCC) and magnesium stearate (Mg-St) were classified distinctly into each cluster, indicating that the quantities of MCC and Mg-St were crucial for determining the powder characteristics. This technique provides a better understanding of the relationships between causal factors and pharmaceutical responses in theophylline powder formulations. © 2010 Wiley-Liss, Inc. and the American Pharmacists Association

Structures and Energetics of (MgCO 3 ) n Clusters ( n ≤ 16)

DOE PAGES

Chen, Mingyang; Jackson, Virgil E.; Felmy, Andrew R.; ...

2015-03-13

There is significant interest in the role of carbonate minerals for the storage of CO 2 and the role of prenucleation dusters in their formation. Global minima for (MgCO 3) n (n ≤ 16) structures were optimized using a tree growth-hybrid genetic algorithm in conjunction with MNDO/MNDO/d semiempirical molecular orbital calculations followed by density functional theory geometry optimizations with the B3LYP functional. The most stable isomers for (MgCO 3) n (n < 5) are approximately 2-dimensional. Mg can be bonded to one or two 0 atoms of a CO 3 2-, and the 1-O bonding scheme is more favored asmore » the cluster becomes larger. The average C-Mg coordination number increases as the cluster size increases, and at n = 16, the average C-Mg coordination number was calculated to be 5.2. The normalized dissociation energy to form monomers increases as n increases. At n = 16, the normalized dissociation energy is calculated to be 116.2 kcal/mol, as compared to the bulk value of 153.9 kcal/mol. The adiabatic reaction energies for the recombination reactions of (MgO) nclusters and CO 2 to form (MgCO 3) n were calculated. The exothermicity of the normalized recombination energy < RE >(CO 2) decreases as n increases and converged to the experimental bulk limit rapidly. The normalized recombination energy < RE >(CO 2) was calculated to be -52.2 kcal/mol for the monomer and -30.7 kcal/mol for n = 16, as compared to the experimental value of -27.9 kcal/mol for the solid phase reaction. Infrared spectra for the lowest energy isomers were calculated, and absorption bands in the previous experimental infrared studies were assigned with our density functional theory predictions. The 13C, 17O, and 25Mg NMR chemical shifts for the clusters were predicted. We found that the results provide insights into the structural and energetic transitions from nanoclusters of (MgCO 3) n to the bulk and the spectroscopic properties of clusters for their experimental identification.« less

Structural and biochemical analysis of nuclease domain of clustered regularly interspaced short palindromic repeat (CRISPR)-associated protein 3 (Cas3).

PubMed

Mulepati, Sabin; Bailey, Scott

2011-09-09

RNA transcribed from clustered regularly interspaced short palindromic repeats (CRISPRs) protects many prokaryotes from invasion by foreign DNA such as viruses, conjugative plasmids, and transposable elements. Cas3 (CRISPR-associated protein 3) is essential for this CRISPR protection and is thought to mediate cleavage of the foreign DNA through its N-terminal histidine-aspartate (HD) domain. We report here the 1.8 Å crystal structure of the HD domain of Cas3 from Thermus thermophilus HB8. Structural and biochemical studies predict that this enzyme binds two metal ions at its active site. We also demonstrate that the single-stranded DNA endonuclease activity of this T. thermophilus domain is activated not by magnesium but by transition metal ions such as manganese and nickel. Structure-guided mutagenesis confirms the importance of the metal-binding residues for the nuclease activity and identifies other active site residues. Overall, these results provide a framework for understanding the role of Cas3 in the CRISPR system.

[Bioinformatics Analysis of Clustered Regularly Interspaced Short Palindromic Repeats in the Genomes of Shigella].

PubMed

Wang, Pengfei; Wang, Yingfang; Duan, Guangcai; Xue, Zerun; Wang, Linlin; Guo, Xiangjiao; Yang, Haiyan; Xi, Yuanlin

2015-04-01

This study was aimed to explore the features of clustered regularly interspaced short palindromic repeats (CRISPR) structures in Shigella by using bioinformatics. We used bioinformatics methods, including BLAST, alignment and RNA structure prediction, to analyze the CRISPR structures of Shigella genomes. The results showed that the CRISPRs existed in the four groups of Shigella, and the flanking sequences of upstream CRISPRs could be classified into the same group with those of the downstream. We also found some relatively conserved palindromic motifs in the leader sequences. Repeat sequences had the same group with corresponding flanking sequences, and could be classified into two different types by their RNA secondary structures, which contain "stem" and "ring". Some spacers were found to homologize with part sequences of plasmids or phages. The study indicated that there were correlations between repeat sequences and flanking sequences, and the repeats might act as a kind of recognition mechanism to mediate the interaction between foreign genetic elements and Cas proteins.

Strand swapping regulates the iron-sulfur cluster in the diabetes drug target mitoNEET

PubMed Central

Baxter, Elizabeth Leigh; Jennings, Patricia A.; Onuchic, José N.

2012-01-01

MitoNEET is a recently identified diabetes drug target that coordinates a transferable 2Fe-2S cluster, and additionally contains an unusual strand swap. In this manuscript, we use a dual basin structure-based model to predict and characterize the folding and functionality of strand swapping in mitoNEET. We demonstrate that a strand unswapped conformation is kinetically accessible and that multiple levels of control are employed to regulate the conformational dynamics of the system. Environmental factors such as temperature can shift route preference toward the unswapped pathway. Additionally we see that a region recently identified as contributing to frustration in folding acts as a regulatory hinge loop that modulates conformational balance. Interestingly, strand unswapping transfers strain specifically to cluster-coordinating residues, opening the cluster-coordinating pocket. Strengthening contacts within the cluster-coordinating pocket opens a new pathway between the swapped and unswapped conformation that utilizes cracking to bypass the unfolded basin. These results suggest that local control within distinct regions affect motions important in regulating mitoNEET’s 2Fe-2S clusters. PMID:22308404

Condensed Matter Cluster Reactions in LENR Power Cells for a Radical New Type of Space Power Source

NASA Astrophysics Data System (ADS)

Yang, Xiaoling; Miley, George H.; Hora, Heinz

2009-03-01

This paper reviews previous theoretical and experimental study on the possibility of nuclear events in multilayer thin film electrodes (Lipson et al., 2004 and 2005; Miley et al., 2007), including the correlation between excess heat and transmutations (Miley and Shrestha, 2003) and the cluster theory that predicts it. As a result of this added understanding of cluster reactions, a new class of electrodes is under development at the University of Illinois. These electrodes are designed to enhance cluster formation and subsequent reactions. Two approaches are under development. The first employs improved loading-unloading techniques, intending to obtain a higher volumetric density of sites favoring cluster formation. The second is designed to create nanostructures on the electrode where the cluster state is formed by electroless deposition of palladium on nickel micro structures. Power units employing these electrodes should offer unique advantages for space applications. This is a fundamental new nuclear energy source that is environmentally compatible with a minimum of radiation involvement, high specific power, very long lifetime, and scalable from micro power to kilowatts.

Structure and Electronic Properties of Ionized PAH Clusters

NASA Astrophysics Data System (ADS)

Joblin, Christine; Kokkin, Damian L.; Sabbah, Hassan; Bonnamy, Anthony; Dontot, Leo; Rapacioli, Mathias; Simon, Aude; Spiegelman, Fernand; Parneix, Pascal; Pino, Thomas; Pirali, Olivier; Falvo, Cyril; Gamboa, Antonio; Brechignac, Philippe; Garcia, Gustavo A.; Nahon, Laurent

2014-06-01

Polycyclic aromatic hydrocarbon (PAH) clusters have been proposed as candidates for evaporating very small grains that are revealed by their mid-IR emission at the surface of UV-irradiated clouds in interstellar space. This suggestion is a motivation for further characterization of the properties of these clusters in particular when they are ionized. We have used a molecular beam coupled to the photoelectron-photoion coincidence spectrometer DELICIOUS II/ III at the VUV beamline DESIRS of the synchrotron SOLEIL to characterize the electronic properties of cationic coronene (C24H12) and pyrene (C16H10) clusters up to the pentamer and heptamer, respectively. These experimental results are analysed in the light of electronic structure calculations. Simulations of the properties of ionized PAH clusters are faced with the difficulty of describing charge delocalization in these large systems. We will show that recent developments combining a Density Functional Tight Binding method with Configuration Interaction scheme is successful in simulating the ionization potential, which gives strong confidence into the predicted structures for these PAH clusters. We will also present current effort to study charge transfer states by performing complementary measurements with the PIRENEA ion trap set-up. Joint ANR project GASPARIM, ANR-10-BLAN-501 M. Rapacioli, C. Joblin and P. Boissel Astron. & Astrophys., 429 (2005), 193-204. G. Garcia, H. Soldi-Lose and L. Nahon Rev. Sci. Instrum., 80 (2009), 023102; G. Garcia, B. Cunha de Miranda, M. Tia, S. Daly, L. Nahon, Rev. Sci. Instrum., 84 (2013), 053112 M. Rapacioli, A. Simon, L. Dontot and F. Spiegelman Phys. Status Solidi B, 249 (2) (2012), 245-258; L. Dontot, M. Rapacioli and F. Spiegelman (2014) submitted

Looping and clustering model for the organization of protein-DNA complexes on the bacterial genome

NASA Astrophysics Data System (ADS)

Walter, Jean-Charles; Walliser, Nils-Ole; David, Gabriel; Dorignac, Jérôme; Geniet, Frédéric; Palmeri, John; Parmeggiani, Andrea; Wingreen, Ned S.; Broedersz, Chase P.

2018-03-01

The bacterial genome is organized by a variety of associated proteins inside a structure called the nucleoid. These proteins can form complexes on DNA that play a central role in various biological processes, including chromosome segregation. A prominent example is the large ParB-DNA complex, which forms an essential component of the segregation machinery in many bacteria. ChIP-Seq experiments show that ParB proteins localize around centromere-like parS sites on the DNA to which ParB binds specifically, and spreads from there over large sections of the chromosome. Recent theoretical and experimental studies suggest that DNA-bound ParB proteins can interact with each other to condense into a coherent 3D complex on the DNA. However, the structural organization of this protein-DNA complex remains unclear, and a predictive quantitative theory for the distribution of ParB proteins on DNA is lacking. Here, we propose the looping and clustering model, which employs a statistical physics approach to describe protein-DNA complexes. The looping and clustering model accounts for the extrusion of DNA loops from a cluster of interacting DNA-bound proteins that is organized around a single high-affinity binding site. Conceptually, the structure of the protein-DNA complex is determined by a competition between attractive protein interactions and loop closure entropy of this protein-DNA cluster on the one hand, and the positional entropy for placing loops within the cluster on the other. Indeed, we show that the protein interaction strength determines the ‘tightness’ of the loopy protein-DNA complex. Thus, our model provides a theoretical framework for quantitatively computing the binding profiles of ParB-like proteins around a cognate (parS) binding site.

Electrophobic interaction induced impurity clustering in metals

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

Zhou, Hong-Bo; Wang, Jin-Long; Jiang, W.

2016-10-01

We introduce the concept of electrophobic interaction, analogous to hydrophobic interaction, for describing the behavior of impurity atoms in a metal, a 'solvent of electrons'. We demonstrate that there exists a form of electrophobic interaction between impurities with closed electron shell structure, which governs their dissolution behavior in a metal. Using He, Be and Ar as examples, we predict by first-principles calculations that the electrophobic interaction drives He, Be or Ar to form a close-packed cluster with a clustering energy that follows a universal power-law scaling with the number of atoms (N) dissolved in a free electron gas, as wellmore » as W or Al lattice, as Ec is proportional to (N2/3-N). This new concept unifies the explanation for a series of experimental observations of close-packed inert-gas bubble formation in metals, and significantly advances our fundamental understanding and capacity to predict the solute behavior of impurities in metals, a useful contribution to be considered in future material design of metals for nuclear, metallurgical, and energy applications.« less

Prediction of Protein Structure by Template-Based Modeling Combined with the UNRES Force Field.

PubMed

Krupa, Paweł; Mozolewska, Magdalena A; Joo, Keehyoung; Lee, Jooyoung; Czaplewski, Cezary; Liwo, Adam

2015-06-22

A new approach to the prediction of protein structures that uses distance and backbone virtual-bond dihedral angle restraints derived from template-based models and simulations with the united residue (UNRES) force field is proposed. The approach combines the accuracy and reliability of template-based methods for the segments of the target sequence with high similarity to those having known structures with the ability of UNRES to pack the domains correctly. Multiplexed replica-exchange molecular dynamics with restraints derived from template-based models of a given target, in which each restraint is weighted according to the accuracy of the prediction of the corresponding section of the molecule, is used to search the conformational space, and the weighted histogram analysis method and cluster analysis are applied to determine the families of the most probable conformations, from which candidate predictions are selected. To test the capability of the method to recover template-based models from restraints, five single-domain proteins with structures that have been well-predicted by template-based methods were used; it was found that the resulting structures were of the same quality as the best of the original models. To assess whether the new approach can improve template-based predictions with incorrectly predicted domain packing, four such targets were selected from the CASP10 targets; for three of them the new approach resulted in significantly better predictions compared with the original template-based models. The new approach can be used to predict the structures of proteins for which good templates can be found for sections of the sequence or an overall good template can be found for the entire sequence but the prediction quality is remarkably weaker in putative domain-linker regions.

Theory vs. experiment for molecular clusters: Spectra of OCS trimers and tetramers

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

Evangelisti, Luca; Dipartimento di Chimica “G. Ciamician,” University of Bologna, Via Selmi 2, Bologna 40126; Perez, Cristobal

All singly substituted {sup 13}C, {sup 18}O, and {sup 34}S isotopomers of the previously known OCS trimer are observed in natural abundance in a broad-band spectrum measured with a chirped-pulse Fourier transform microwave spectrometer. The complete substitution structure thus obtained critically tests (and confirms) the common assumption that monomers tend to retain their free structure in a weakly bound cluster. A new OCS trimer isomer is also observed, and its structure is determined to be barrel-shaped but with the monomers all approximately aligned, in contrast to the original trimer which is barrel-shaped with two monomers aligned and one anti-aligned. Anmore » OCS tetramer spectrum is assigned for the first time, and the tetramer structure resembles an original trimer with an OCS monomer added at the end with two sulfur atoms. Infrared spectra observed in the region of the OCS ν{sub 1} fundamental (≈2060 cm{sup −1}) are assigned to the same OCS tetramer, and another infrared band is tentatively assigned to a different tetramer isomer. The experimental results are compared and contrasted with theoretical predictions from the literature and from new cluster calculations which use an accurate OCS pair potential and assume pairwise additivity.« less

Characterizing the spatial structure of endangered species habitat using geostatistical analysis of IKONOS imagery

USGS Publications Warehouse

Wallace, C.S.A.; Marsh, S.E.

2005-01-01

Our study used geostatistics to extract measures that characterize the spatial structure of vegetated landscapes from satellite imagery for mapping endangered Sonoran pronghorn habitat. Fine spatial resolution IKONOS data provided information at the scale of individual trees or shrubs that permitted analysis of vegetation structure and pattern. We derived images of landscape structure by calculating local estimates of the nugget, sill, and range variogram parameters within 25 ?? 25-m image windows. These variogram parameters, which describe the spatial autocorrelation of the 1-m image pixels, are shown in previous studies to discriminate between different species-specific vegetation associations. We constructed two independent models of pronghorn landscape preference by coupling the derived measures with Sonoran pronghorn sighting data: a distribution-based model and a cluster-based model. The distribution-based model used the descriptive statistics for variogram measures at pronghorn sightings, whereas the cluster-based model used the distribution of pronghorn sightings within clusters of an unsupervised classification of derived images. Both models define similar landscapes, and validation results confirm they effectively predict the locations of an independent set of pronghorn sightings. Such information, although not a substitute for field-based knowledge of the landscape and associated ecological processes, can provide valuable reconnaissance information to guide natural resource management efforts. ?? 2005 Taylor & Francis Group Ltd.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome.

PubMed

Lalonde, Michel; Wells, R Glenn; Birnie, David; Ruddy, Terrence D; Wassenaar, Richard

2014-07-01

Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. About 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.

Development and optimization of SPECT gated blood pool cluster analysis for the prediction of CRT outcome

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

Lalonde, Michel, E-mail: mlalonde15@rogers.com; Wassenaar, Richard; Wells, R. Glenn

2014-07-15

Purpose: Phase analysis of single photon emission computed tomography (SPECT) radionuclide angiography (RNA) has been investigated for its potential to predict the outcome of cardiac resynchronization therapy (CRT). However, phase analysis may be limited in its potential at predicting CRT outcome as valuable information may be lost by assuming that time-activity curves (TAC) follow a simple sinusoidal shape. A new method, cluster analysis, is proposed which directly evaluates the TACs and may lead to a better understanding of dyssynchrony patterns and CRT outcome. Cluster analysis algorithms were developed and optimized to maximize their ability to predict CRT response. Methods: Aboutmore » 49 patients (N = 27 ischemic etiology) received a SPECT RNA scan as well as positron emission tomography (PET) perfusion and viability scans prior to undergoing CRT. A semiautomated algorithm sampled the left ventricle wall to produce 568 TACs from SPECT RNA data. The TACs were then subjected to two different cluster analysis techniques, K-means, and normal average, where several input metrics were also varied to determine the optimal settings for the prediction of CRT outcome. Each TAC was assigned to a cluster group based on the comparison criteria and global and segmental cluster size and scores were used as measures of dyssynchrony and used to predict response to CRT. A repeated random twofold cross-validation technique was used to train and validate the cluster algorithm. Receiver operating characteristic (ROC) analysis was used to calculate the area under the curve (AUC) and compare results to those obtained for SPECT RNA phase analysis and PET scar size analysis methods. Results: Using the normal average cluster analysis approach, the septal wall produced statistically significant results for predicting CRT results in the ischemic population (ROC AUC = 0.73;p < 0.05 vs. equal chance ROC AUC = 0.50) with an optimal operating point of 71% sensitivity and 60% specificity. Cluster analysis results were similar to SPECT RNA phase analysis (ROC AUC = 0.78, p = 0.73 vs cluster AUC; sensitivity/specificity = 59%/89%) and PET scar size analysis (ROC AUC = 0.73, p = 1.0 vs cluster AUC; sensitivity/specificity = 76%/67%). Conclusions: A SPECT RNA cluster analysis algorithm was developed for the prediction of CRT outcome. Cluster analysis results produced results equivalent to those obtained from Fourier and scar analysis.« less

First principles absorption spectra of Cu{sub n} (n = 2 - 20) clusters.

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

Baishya, K.; Idrobo, J. C.; Ogut, S.

2011-06-17

Optical absorption spectra for the computed ground state structures of copper clusters (Cu{sub n}, n = 2-20) are investigated from first principles using time-dependent density functional theory in the adiabatic local density approximation (TDLDA). The results are compared with available experimental data, existing calculations, and with results from our previous computations on silver and gold clusters. The main effects of d electrons on the absorption spectra, quenching the oscillator strengths, and getting directly involved in low-energy excitations increase in going from Ag{sub n} to Au{sub n} to Cu{sub n} due to the increase in the hybridization of the occupied, yetmore » shallow, d orbitals and the partially occupied s orbitals. We predict that while Cu nanoparticles of spherical or moderately ellipsoidal shape do not exhibit Mie (surface plasmon) resonances, unlike the case for Ag and Au, extremely prolate or oblate Cu nanoparticles with eccentricities near unity should give rise to Mie resonances in the lower end of the visible range and in the infrared. This tunable resonance predicted by the classical Mie-Gans theory is reproduced with remarkable accuracy by our TDLDA computations on hypothetical Cu clusters in the form of zigzag chains with as few as 6 to 20 atoms.« less

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.

Small Water Cluster Cations

NASA Astrophysics Data System (ADS)

Novakovskaya, Yu. V.; Stepanov, N. F.

Structures of water cluster cations (H_{2}O)^{+}_{n} with n ≤ 5 are optimized at the unrestricted Hartree-Fock level with the 4 - 31 + +G** basis set. Energetic characteristics of the cations are then estimated taking into account the second order perturbation corrections (MP2). After the electron detachment from a neutral cluster, the structure of the latter substantially changes, so that OH and H3O+ fragments can be distinguished in it. In some cations H3O+ is so strongly bonded to water molecules that it is reasonable to speak of the [H2n-1On-1]+ fragments. According to the position of OH, the structures form two groups. In one group, OH acts exclusively as the proton acceptor in H-bonds with water molecules, thus being terminal in the chain-like structures; in the other group it is directly bonded to H3O and, as a proton donor, forms an H-bond with water molecule. Cluster cations do not tend to dissociate into the fragments. However, an external influence of ≤ 0.4 eV is sufficient for the cations of the first group to dissociate into a free OH radical and a protonated cluster H+(H2O)n-1. Extrapolation of the calculated adiabatic ionization potentials of the water clusters to n → ∞ provides a value of 8.6 eV, which can be considered as an estimation of the electron work function of water. This value is close to the experimental photoelectric thresholds of amorphous ice (8.7 ± 0.1 eV) and water (9.39 ± 0.3 eV). Solvation of the electron lowers the value, and an energy of 7 eV can be sufficient for initiating conductivity. This prediction is in accord with the experiment: irradiating ice with ultraviolet light of the photon energy 6.5-6.8 eV initiates photoconductivity, and hydrogen peroxide and H3O+ ions are observed.

Divergent electronic structures of isoelectronic metalloclusters: tungsten(II) halides and rhenium(III) chalcogenide halides.

PubMed

Gray, Thomas G

2009-03-02

Same but different: DFT calculations on hexanuclear tungsten(II) halide clusters [W(6)X(8)X'(6)](2-) (X, X'=Cl, Br, I) indicate a breakdown in the isoelectronic analogy between themselves and the isostructural rhenium(III) chalcogenide clusters [Re(6)S(8)X(6)](4-) (see figure).The hexanuclear tungsten(II) halide clusters and the sulfido-halide clusters of rhenium(III) are subsets of a broad system of 24-electron metal-metal bonded assemblies that share a common structure. Tungsten(II) halide clusters and rhenium(III) sulfide clusters luminesce from triplet excited states upon ultraviolet or visible excitation; emission from both cluster series has been extensively characterized elsewhere. Reported here are density-functional theory studies of the nine permutations of [W(6)X(8)X'(6)](2-) (X, X'=Cl, Br, I). Ground-state properties including geometries, harmonic vibrational frequencies, and orbital energy-level diagrams, have been calculated. Comparison is made to the sulfide clusters of rhenium(III), of which [Re(6)S(8)Cl(6)](4-) is representative. [W(6)X(8)X'(6)](2-) and [Re(6)S(8)Cl(6)](4-) possess disparate electronic structures owing to the greater covalency of the metal-sulfur bond and hence of the [Re(6)S(8)](2+) core. Low-lying virtual orbitals are raised in energy in [Re(6)S(8)Cl(6)](4-) with the result that the LUMO+7 (or LUMO+8 in some cases) of tungsten(II) halide clusters is the LUMO of [Re(6)S(8)Cl(6)](4-) species. An inversion of the HOMO and HOMO-1 between the two cluster series also occurs. Time-dependent density-functional calculations using asymptotically correct functionals do not recapture the experimentally observed periodic trend in [W(6)X(14)](2-) luminescence (E(em) increasing in the order [W(6)Cl(14)](2-) < [W(6)Br(14)](2-) < [W(6)I(14)](2-)), predicting instead that emission energies decrease with incorporation of the heavier halides. This circumstance is either a gross failure of the time-dependent formalism of DFT or it indicates extensive multistate emission in [W(6)X(8)X'(6)](2-) clusters. The inapplicability of isoelectronic analogies between clusters of Group 6 and Group 7 is emphasized.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra

NASA Astrophysics Data System (ADS)

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-04-01

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models’ performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Variable selection based on clustering analysis for improvement of polyphenols prediction in green tea using synchronous fluorescence spectra.

PubMed

Shan, Jiajia; Wang, Xue; Zhou, Hao; Han, Shuqing; Riza, Dimas Firmanda Al; Kondo, Naoshi

2018-03-13

Synchronous fluorescence spectra, combined with multivariate analysis were used to predict flavonoids content in green tea rapidly and nondestructively. This paper presented a new and efficient spectral intervals selection method called clustering based partial least square (CL-PLS), which selected informative wavelengths by combining clustering concept and partial least square (PLS) methods to improve models' performance by synchronous fluorescence spectra. The fluorescence spectra of tea samples were obtained and k-means and kohonen-self organizing map clustering algorithms were carried out to cluster full spectra into several clusters, and sub-PLS regression model was developed on each cluster. Finally, CL-PLS models consisting of gradually selected clusters were built. Correlation coefficient (R) was used to evaluate the effect on prediction performance of PLS models. In addition, variable influence on projection partial least square (VIP-PLS), selectivity ratio partial least square (SR-PLS), interval partial least square (iPLS) models and full spectra PLS model were investigated and the results were compared. The results showed that CL-PLS presented the best result for flavonoids prediction using synchronous fluorescence spectra.

Measuring the Mass Distribution in Z is Approximately 0.2 Cluster Lenses with XMM, HST and CFHT

NASA Technical Reports Server (NTRS)

2004-01-01

Being the most massive gravitationally bound objects in the Universe, clusters of galaxies are prime targets for studies of structure formation and evolution. Specifically the comoving space density of virialized clusters of a given mass (or X-ray temperature), but also the frequency and degree of substructure, as well as the shape of the cluster mass profile are quantities whose current values and evolution as a function of lookback time can provide important constraints on the cosmological and physical parameters of structure formation theories. The project funded by NASA grant NAG 5-10041 intended to take such studies to a new level by combining observations of a well-selected cluster sample by three state-of-the-art telescopes: HST, to accurately measure the mass distribution in the cluster core (approx. 0.5 h(sup -1)(sub 50) Mpc) via strong gravitational lensing; CFHT, to measure the large scale mass distribution out to approx. 3 Mpc via weak lensing; and XMM, to measure the gas density and temperature distribution accurately on intermediate scales < 1.5 Mpc. XMM plays a pivotal role in this context as the calibration of X-ray mass measurements through accurate, spatially resolved X-ray temperature measurements (particularly in the cosmologically most sensitive range of kT> 5 keV) is central to the questions outlined above. This set of observations promised to yield the best cluster mass measurements obtained so far for a representative sample, thus allowing us to: 1) Measure the high-mass end of the local cluster mass function; 2) Test predictions of a universal cluster mass profile; 3) calibrate the mass-temperature and temperature-luminosity relations for clusters and the scatter around these relations, which is vital for studies of cluster evolution using the X-ray temperature and X-ray luminosity functions.

Manifestation of α clustering in 10Be via α -knockout reaction

NASA Astrophysics Data System (ADS)

Lyu, Mengjiao; Yoshida, Kazuki; Kanada-En'yo, Yoshiko; Ogata, Kazuyuki

2018-04-01

Background: Proton-induced α -knockout reactions may allow direct experimental observation of α clustering in nuclei. This is obtained by relating the theoretical descriptions of clustering states to the experimental reaction observables. It is desired to introduce microscopic structure models into the theoretical frameworks for α -knockout reactions. Purpose: Our goal is to probe the α clustering in the 10Be nucleus by proton-induced α -knockout reaction observables. Method: We adopt an extended version of the Tohsaki-Horiuchi-Schuck-Röpke wave function of 10Be and integrate it with the distorted-wave impulse approximation framework for the calculation of (p ,p α ) -knockout reactions. Results: We make the first calculation for the 10Be(p ,p α )6He reaction at 250 MeV by implementing a microscopic α -cluster wave function, and we predict the triple-differential cross section (TDX). Furthermore, by constructing artificial states of the target nucleus 10Be with compact or dilute spatial distributions, the TDX is found to be highly sensitive to the extent of clustering in the target nuclei. Conclusions: These results provide reliable manifestation of α clustering in 10Be.

Infrared spectra of CO2-doped hydrogen clusters, (H2)N-CO2.

PubMed

McKellar, A R W

2012-03-07

Clusters of para-H(2) and/or ortho-H(2) containing a single carbon dioxide molecule are studied by high resolution infrared spectroscopy in the 2300 cm(-1) region of the CO(2) ν(3) fundamental band. The (H(2))(N)-CO(2) clusters are formed in a pulsed supersonic jet expansion from a cooled nozzle and probed using a rapid scan tunable diode laser. Simple symmetric rotor type spectra are observed with little or no resolved K-structure, and prominent Q-branch features for ortho-H(2) but not para-H(2). Observed rotational constants and vibrational shifts are reported for ortho-H(2) up to N = 7 and para-H(2) up to N = 15, with the N > 7 assignments only made possible with the help of theoretical simulations. The para-H(2) cluster with N = 12 shows clear evidence for superfluid effects, in good agreement with theory. The presence of larger clusters with N > 15 is evident in the spectra, but specific assignments are not possible. Mixed para- + ortho-H(2) cluster transitions are well predicted by linear interpolation between corresponding pure cluster line positions. © 2012 American Institute of Physics

Testing prediction methods: Earthquake clustering versus the Poisson model

USGS Publications Warehouse

Michael, A.J.

1997-01-01

Testing earthquake prediction methods requires statistical techniques that compare observed success to random chance. One technique is to produce simulated earthquake catalogs and measure the relative success of predicting real and simulated earthquakes. The accuracy of these tests depends on the validity of the statistical model used to simulate the earthquakes. This study tests the effect of clustering in the statistical earthquake model on the results. Three simulation models were used to produce significance levels for a VLF earthquake prediction method. As the degree of simulated clustering increases, the statistical significance drops. Hence, the use of a seismicity model with insufficient clustering can lead to overly optimistic results. A successful method must pass the statistical tests with a model that fully replicates the observed clustering. However, a method can be rejected based on tests with a model that contains insufficient clustering. U.S. copyright. Published in 1997 by the American Geophysical Union.

A stochastic locomotor control model for the nurse shark, Ginglymostoma cirratum.

PubMed

Gerald, K B; Matis, J H; Kleerekoper, H

1978-06-12

The locomotor behavior of the nurse shark (Ginglymostoma cirratum) is characterized by 17 variables (frequency and ratios of left, right, and total turns; their radians; straight paths (steps); distance travelled; and velocity) Within each of these variables there is an internal time dependency the structure of which was elaborated together with an improved statistical model predicting their behavior within 90% confidence limits. The model allows for the sensitive detection of subtle locomotor response to sensory stimulation as values of variables may exceed the established confidence limits within minutes after onset of the stimulus. The locomotor activity is well described by an autoregression time series model and can be predicted by only seven variables. Six of these form two independently operating clusters. The first one consists of: the number of right turns, the distance travelled and the mean velocity; the second one of: the mean size of right turns, of left turns, and of all turns. The same clustering is obtained independently by a cluster analysis of cross-sections of the seven time series. It is apparent that, among a total of 17 locomotor variables, seven behave as individually independent agents, presumably controlled by seven separate and independent centers. The output of each center can only be predicted by its own behavior. In spite of the individual of the seven variables, their internal structure is similar in important aspects which may result from control by a common command center. The shark locomotor model differs in important aspects from the previously constructed for the goldfish. The interdependence of the locomotor variables in both species may be related to the control mechanisms postulated by von Holst for the coordination of rhythmic fin movements in fishes. A locomotor control model for the nurse shark is proposed.

Power spectrum for the small-scale Universe

NASA Astrophysics Data System (ADS)

Widrow, Lawrence M.; Elahi, Pascal J.; Thacker, Robert J.; Richardson, Mark; Scannapieco, Evan

2009-08-01

The first objects to arise in a cold dark matter (CDM) universe present a daunting challenge for models of structure formation. In the ultra small-scale limit, CDM structures form nearly simultaneously across a wide range of scales. Hierarchical clustering no longer provides a guiding principle for theoretical analyses and the computation time required to carry out credible simulations becomes prohibitively high. To gain insight into this problem, we perform high-resolution (N = 7203-15843) simulations of an Einstein-de Sitter cosmology where the initial power spectrum is P(k) ~ kn, with -2.5 <= n <= - 1. Self-similar scaling is established for n = -1 and -2 more convincingly than in previous, lower resolution simulations and for the first time, self-similar scaling is established for an n = -2.25 simulation. However, finite box-size effects induce departures from self-similar scaling in our n = -2.5 simulation. We compare our results with the predictions for the power spectrum from (one-loop) perturbation theory and demonstrate that the renormalization group approach suggested by McDonald improves perturbation theory's ability to predict the power spectrum in the quasi-linear regime. In the non-linear regime, our power spectra differ significantly from the widely used fitting formulae of Peacock & Dodds and Smith et al. and a new fitting formula is presented. Implications of our results for the stable clustering hypothesis versus halo model debate are discussed. Our power spectra are inconsistent with predictions of the stable clustering hypothesis in the high-k limit and lend credence to the halo model. Nevertheless, the fitting formula advocated in this paper is purely empirical and not derived from a specific formulation of the halo model.

Modeling Spatial Dependencies and Semantic Concepts in Data Mining

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

Vatsavai, Raju

Data mining is the process of discovering new patterns and relationships in large datasets. However, several studies have shown that general data mining techniques often fail to extract meaningful patterns and relationships from the spatial data owing to the violation of fundamental geospatial principles. In this tutorial, we introduce basic principles behind explicit modeling of spatial and semantic concepts in data mining. In particular, we focus on modeling these concepts in the widely used classification, clustering, and prediction algorithms. Classification is the process of learning a structure or model (from user given inputs) and applying the known model to themore » new data. Clustering is the process of discovering groups and structures in the data that are ``similar,'' without applying any known structures in the data. Prediction is the process of finding a function that models (explains) the data with least error. One common assumption among all these methods is that the data is independent and identically distributed. Such assumptions do not hold well in spatial data, where spatial dependency and spatial heterogeneity are a norm. In addition, spatial semantics are often ignored by the data mining algorithms. In this tutorial we cover recent advances in explicitly modeling of spatial dependencies and semantic concepts in data mining.« less

Genomic characterization of a new endophytic Streptomyces kebangsaanensis identifies biosynthetic pathway gene clusters for novel phenazine antibiotic production

PubMed Central

Remali, Juwairiah; Sarmin, Nurul ‘Izzah Mohd; Ng, Chyan Leong; Tiong, John J.L.; Aizat, Wan M.; Keong, Loke Kok

2017-01-01

Background Streptomyces are well known for their capability to produce many bioactive secondary metabolites with medical and industrial importance. Here we report a novel bioactive phenazine compound, 6-((2-hydroxy-4-methoxyphenoxy) carbonyl) phenazine-1-carboxylic acid (HCPCA) extracted from Streptomyces kebangsaanensis, an endophyte isolated from the ethnomedicinal Portulaca oleracea. Methods The HCPCA chemical structure was determined using nuclear magnetic resonance spectroscopy. We conducted whole genome sequencing for the identification of the gene cluster(s) believed to be responsible for phenazine biosynthesis in order to map its corresponding pathway, in addition to bioinformatics analysis to assess the potential of S. kebangsaanensis in producing other useful secondary metabolites. Results The S. kebangsaanensis genome comprises an 8,328,719 bp linear chromosome with high GC content (71.35%) consisting of 12 rRNA operons, 81 tRNA, and 7,558 protein coding genes. We identified 24 gene clusters involved in polyketide, nonribosomal peptide, terpene, bacteriocin, and siderophore biosynthesis, as well as a gene cluster predicted to be responsible for phenazine biosynthesis. Discussion The HCPCA phenazine structure was hypothesized to derive from the combination of two biosynthetic pathways, phenazine-1,6-dicarboxylic acid and 4-methoxybenzene-1,2-diol, originated from the shikimic acid pathway. The identification of a biosynthesis pathway gene cluster for phenazine antibiotics might facilitate future genetic engineering design of new synthetic phenazine antibiotics. Additionally, these findings confirm the potential of S. kebangsaanensis for producing various antibiotics and secondary metabolites. PMID:29201559

Three-dimensional structural modelling and calculation of electrostatic potentials of HLA Bw4 and Bw6 epitopes to explain the molecular basis for alloantibody binding: toward predicting HLA antigenicity and immunogenicity.

PubMed

Mallon, Dermot H; Bradley, J Andrew; Winn, Peter J; Taylor, Craig J; Kosmoliaptsis, Vasilis

2015-02-01

We have previously shown that qualitative assessment of surface electrostatic potential of HLA class I molecules helps explain serological patterns of alloantibody binding. We have now used a novel computational approach to quantitate differences in surface electrostatic potential of HLA B-cell epitopes and applied this to explain HLA Bw4 and Bw6 antigenicity. Protein structure models of HLA class I alleles expressing either the Bw4 or Bw6 epitope (defined by sequence motifs at positions 77 to 83) were generated using comparative structure prediction. The electrostatic potential in 3-dimensional space encompassing the Bw4/Bw6 epitope was computed by solving the Poisson-Boltzmann equation and quantitatively compared in a pairwise, all-versus-all fashion to produce distance matrices that cluster epitopes with similar electrostatics properties. Quantitative comparison of surface electrostatic potential at the carboxyl terminal of the α1-helix of HLA class I alleles, corresponding to amino acid sequence motif 77 to 83, produced clustering of HLA molecules in 3 principal groups according to Bw4 or Bw6 epitope expression. Remarkably, quantitative differences in electrostatic potential reflected known patterns of serological reactivity better than Bw4/Bw6 amino acid sequence motifs. Quantitative assessment of epitope electrostatic potential allowed the impact of known amino acid substitutions (HLA-B*07:02 R79G, R82L, G83R) that are critical for antibody binding to be predicted. We describe a novel approach for quantitating differences in HLA B-cell epitope electrostatic potential. Proof of principle is provided that this approach enables better assessment of HLA epitope antigenicity than amino acid sequence data alone, and it may allow prediction of HLA immunogenicity.

A Search for Cosmic String Loops Using GADGET-2 Cosmological N-Body Simulator

NASA Astrophysics Data System (ADS)

Braverman, William; Cousins, Bryce; Jia, Hewei

2018-01-01

Cosmic string loops are an extremely elusive hypothetical entity that have eluded the grasp of physicists and astronomers since their existence was postulated in the 1970’s. Finding evidence of their existence could be the first empirical evidence of string theory.Simulating their basic motion in a cold dark matter background using GADGET-2 allows us to predict where they may cluster during large scale structure formation (if they cluster at all). Here, we present our progress in placing cosmic strings into GADGET-2 with their basic equations of motion to lay a ground work for more complex simulations to find where these strings cluster. Ultimately, these simulations could lay a groundwork as to where future microlensing and gravitational wave observatories should look for cosmic strings.

IMG-ABC: An Atlas of Biosynthetic Gene Clusters to Fuel the Discovery of Novel Secondary Metabolites

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

Chen, I-Min; Chu, Ken; Ratner, Anna

2014-10-28

In the discovery of secondary metabolites (SMs), large-scale analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of relevant computational resources. We present IMG-ABC (https://img.jgi.doe.gov/abc/) -- An Atlas of Biosynthetic gene Clusters within the Integrated Microbial Genomes (IMG) system1. IMG-ABC is a rich repository of both validated and predicted biosynthetic clusters (BCs) in cultured isolates, single-cells and metagenomes linked with the SM chemicals they produce and enhanced with focused analysis tools within IMG. The underlying scalable framework enables traversal of phylogenetic dark matter and chemical structure space -- serving as a doorwaymore » to a new era in the discovery of novel molecules.« less

Allosteric control in a metalloprotein dramatically alters function

PubMed Central

Baxter, Elizabeth Leigh; Zuris, John A.; Wang, Charles; Vo, Phu Luong T.; Axelrod, Herbert L.; Cohen, Aina E.; Paddock, Mark L.; Nechushtai, Rachel; Onuchic, Jose N.; Jennings, Patricia A.

2013-01-01

Metalloproteins (MPs) comprise one-third of all known protein structures. This diverse set of proteins contain a plethora of unique inorganic moieties capable of performing chemistry that would otherwise be impossible using only the amino acids found in nature. Most of the well-studied MPs are generally viewed as being very rigid in structure, and it is widely thought that the properties of the metal centers are primarily determined by the small fraction of amino acids that make up the local environment. Here we examine both theoretically and experimentally whether distal regions can influence the metal center in the diabetes drug target mitoNEET. We demonstrate that a loop (L2) 20 Å away from the metal center exerts allosteric control over the cluster binding domain and regulates multiple properties of the metal center. Mutagenesis of L2 results in significant shifts in the redox potential of the [2Fe-2S] cluster and orders of magnitude effects on the rate of [2Fe-2S] cluster transfer to an apo-acceptor protein. These surprising effects occur in the absence of any structural changes. An examination of the native basin dynamics of the protein using all-atom simulations shows that twisting in L2 controls scissoring in the cluster binding domain and results in perturbations to one of the cluster-coordinating histidines. These allosteric effects are in agreement with previous folding simulations that predicted L2 could communicate with residues surrounding the metal center. Our findings suggest that long-range dynamical changes in the protein backbone can have a significant effect on the functional properties of MPs. PMID:23271805

Development of an Evolutionary Algorithm for the ab Initio Discovery of Two-Dimensional Materials

NASA Astrophysics Data System (ADS)

Revard, Benjamin Charles

Crystal structure prediction is an important first step on the path toward computational materials design. Increasingly robust methods have become available in recent years for computing many materials properties, but because properties are largely a function of crystal structure, the structure must be known before these methods can be brought to bear. In addition, structure prediction is particularly useful for identifying low-energy structures of subperiodic materials, such as two-dimensional (2D) materials, which may adopt unexpected structures that differ from those of the corresponding bulk phases. Evolutionary algorithms, which are heuristics for global optimization inspired by biological evolution, have proven to be a fruitful approach for tackling the problem of crystal structure prediction. This thesis describes the development of an improved evolutionary algorithm for structure prediction and several applications of the algorithm to predict the structures of novel low-energy 2D materials. The first part of this thesis contains an overview of evolutionary algorithms for crystal structure prediction and presents our implementation, including details of extending the algorithm to search for clusters, wires, and 2D materials, improvements to efficiency when running in parallel, improved composition space sampling, and the ability to search for partial phase diagrams. We then present several applications of the evolutionary algorithm to 2D systems, including InP, the C-Si and Sn-S phase diagrams, and several group-IV dioxides. This thesis makes use of the Cornell graduate school's "papers" option. Chapters 1 and 3 correspond to the first-author publications of Refs. [131] and [132], respectively, and chapter 2 will soon be submitted as a first-author publication. The material in chapter 4 is taken from Ref. [144], in which I share joint first-authorship. In this case I have included only my own contributions.

Two-Year Predictive Validity of Conduct Disorder Subtypes in Early Adolescence: A Latent Class Analysis of a Canadian Longitudinal Sample

ERIC Educational Resources Information Center

Lacourse, Eric; Baillargeon, Raymond; Dupere, Veronique; Vitaro, Frank; Romano, Elisa; Tremblay, Richard

2010-01-01

Background: Investigating the latent structure of conduct disorder (CD) can help clarify how symptoms related to aggression, property destruction, theft, and serious violations of rules cluster in individuals with this disorder. Discovering homogeneous subtypes can be useful for etiologic, treatment, and prevention purposes depending on the…

Discovery of a Large-Scale Filament Connected to the Massive Galaxy Cluster MACS J0717.5+3745 at z=0.551,

NASA Astrophysics Data System (ADS)

Ebeling, H.; Barrett, E.; Donovan, D.

2004-07-01

We report the detection of a 4 h-170 Mpc long large-scale filament leading into the massive galaxy cluster MACS J0717.5+3745. The extent of this object well beyond the cluster's nominal virial radius (~2.3 Mpc) rules out prior interaction between its constituent galaxies and the cluster and makes it a prime candidate for a genuine filament as opposed to a merger remnant or a double cluster. The structure was discovered as a pronounced overdensity of galaxies selected to have V-R colors close to the cluster red sequence. Extensive spectroscopic follow-up of over 300 of these galaxies in a region covering the filament and the cluster confirms that the entire structure is located at the cluster redshift of z=0.545. Featuring galaxy surface densities of typically 15 Mpc-2 down to luminosities of 0.13L*V, the most diffuse parts of the filament are comparable in density to the clumps of red galaxies found around A851 in the only similar study carried out to date (Kodama et al.). Our direct detection of an extended large-scale filament funneling matter onto a massive distant cluster provides a superb target for in-depth studies of the evolution of galaxies in environments of greatly varying density and supports the predictions from theoretical models and numerical simulations of structure formation in a hierarchical picture. Some of the data presented herein were obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and the National Aeronautics and Space Administration. The observatory was made possible by the generous financial support of the W. M. Keck Foundation. Based partly on observations obtained at the Gemini Observatory, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (US), the Particle Physics and Astronomy Research Council (UK), the National Research Council (Canada), CONICYT (Chile), the Australian Research Council (Australia), CNP (Brazil), and CONICET (Argentina).

Analysis and Modeling of Structure Formation in Granular and Fluid-Solid Flows

NASA Astrophysics Data System (ADS)

Murphy, Eric

Granular and multiphase flows are encountered in a number of industrial processes with particular emphasis in this manuscript given to the particular applications in cement pumping, pneumatic conveying, fluid catalytic cracking, CO2 capture, and fast pyrolysis of bio-materials. These processes are often modeled using averaged equations that may be simulated using computational fluid dynamics. Closure models are then required that describe the average forces that arise from both interparticle interactions, e.g. shear stress, and interphase interactions, such as mean drag. One of the biggest hurdles to this approach is the emergence of non-trivial spatio-temporal structures in the particulate phase, which can significantly modify the qualitative behavior of these forces and the resultant flow phenomenology. For example, the formation of large clusters in cohesive granular flows is responsible for a transition from solid-like to fluid-like rheology. Another example is found in gas-solid systems, where clustering at small scales is observed to significantly lower in the observed drag. Moreover, there remains the possibility that structure formation may occur at all scales, leading to a lack of scale separation required for traditional averaging approaches. In this context, several modeling problems are treated 1) first-principles based modeling of the rheology of cement slurries, 2) modeling the mean solid-solid drag experienced by polydisperse particles undergoing segregation, and 3) modeling clustering in homogeneous gas-solid flows. The first and third components are described in greater detail. In the study on the rheology of cements, several sub-problems are introduced, which systematically increase in the number and complexity of interparticle interactions. These interparticle interactions include inelasticity, friction, cohesion, and fluid interactions. In the first study, the interactions between cohesive inelastic particles was fully characterized for the first time. Next, kinetic theory was used to predict the cooling of a gas of such particles. DEM was then used to validate this approach. A study on the rheology of dry cohesive granules with and without friction was then carried out, where the physics of different flow phenomenology was exhaustively explored. Lastly, homogeneous cement slurry simulations were carried out, and compared with vane-rheometer experiments. Qualitative agreement between simulation and experiment were observed. Lastly, the physics of clustering in homogeneous gas-solid flows is explored in the hopes of gaining a mechanistic explanation of how particle-fluid interactions lead to clustering. Exact equations are derived, detailing the evolution of the two particle density, which may be closed using high-fidelity particle-resolved direct numerical simulation. Two canonical gas-solid flows are then addressed, the homogeneously cooling gas-solid flow (HCGSF) and sedimenting gas-solid flow (SGSF). A mechanism responsible for clustering in the HCGSF is identified. Clustering of plane-wave like structures is observed in the SGSF, and the exact terms are quantified. A method for modeling the dynamics of clustering in these systems is proposed, which may aid in the prediction of clustering and other correlation length-scales useful for less expensive computations.

GOLDRUSH. III. A systematic search for protoclusters at z ˜ 4 based on the >100 deg2 area

NASA Astrophysics Data System (ADS)

Toshikawa, Jun; Uchiyama, Hisakazu; Kashikawa, Nobunari; Ouchi, Masami; Overzier, Roderik; Ono, Yoshiaki; Harikane, Yuichi; Ishikawa, Shogo; Kodama, Tadayuki; Matsuda, Yuichi; Lin, Yen-Ting; Onoue, Masafusa; Tanaka, Masayuki; Nagao, Tohru; Akiyama, Masayuki; Komiyama, Yutaka; Goto, Tomotsugu; Lee, Chien-Hsiu

2018-01-01

We conduct a systematic search for galaxy protoclusters at z ˜ 3.8 based on the latest internal data release (S16A) of the Hyper Suprime-Cam Subaru strategic program (HSC-SSP). In the Wide layer of the HSC-SSP, we investigate the large-scale projected sky distribution of g-dropout galaxies over an area of 121 deg2, and identify 216 large-scale overdense regions (>4 σ overdensity significance) that are likely protocluster candidates. Of these, 37 are located within 8΄ (3.4 physical Mpc) of other protocluster candidates of higher overdensity, and are expected to merge into a single massive structure by z = 0. Therefore, we find 179 unique protocluster candidates in our survey. A cosmological simulation that includes projection effects predicts that more than 76% of these candidates will evolve into galaxy clusters with halo masses of at least 1014 M⊙ by z = 0. The unprecedented size of our protocluster candidate catalog allows us to perform, for the first time, an angular clustering analysis of the systematic sample of protocluster candidates. We find a correlation length of 35.0 h-1 Mpc. The relation between correlation length and number density of z ˜ 3.8 protocluster candidates is consistent with the prediction of the ΛCDM model, and the correlation length is similar to that of rich clusters in the local universe. This result suggests that our protocluster candidates are tracing similar spatial structures to those expected from the progenitors of rich clusters, and enhances the confidence that our method for identifying protoclusters at high redshifts is robust. In years to come, our protocluster search will be extended to the entire HSC-SSP Wide sky coverage of ˜ 1400 deg2 to probe cluster formation over a wide redshift range of z ˜ 2-6.

Infrared Absorption of Methanol-Water Clusters Mn(H2O), n = 1-4, Recorded with the Vuv-Ionization Techniques

NASA Astrophysics Data System (ADS)

Lee, Yu-Fang; Lee, Yuan-Pern

2016-06-01

We investigated IR spectra in the CH- and OH-stretching regions of size-selected methanol-water clusters, Mn(H_2O) with M representing CH_3OH and n = 1-4, in a pulsed supersonic jet by using the VUV (vacuum-ultraviolet)-ionization/IR-depletion technique. The VUV light at 118 nm served as the source of ionization in a time-of-flight mass spectrometer. The tunable IR laser served as a source of dissociation for clusters before ionization. Spectra of methanol-water clusters in the OH region show significant variations as the number of methanol molecules increase, whereas spectra in the CH region are similar. For M(H_2O), absorption of a structure with H_2O as a proton donor was observed at 3570, 3682, and 3722 wn, whereas that of methanol as a proton donor was observed at 3611 and 3753 wn. For M2(H_2O), the OH-stretching band of the dangling OH of H_2O was observed at 3721 wn, whereas overlapped bands near 3425, 3472, and 3536 wn correspond to the OH-stretching modes of three hydrogen-bonded OH in a cyclic structure. For M3(H_2O), the dangling OH shifts to 3715 wn, and the hydrogen-bonded OH-stretching bands become much broader, with a band near 3179 wn having the smallest wavenumber. Scaled harmonic vibrational wavenumbers and relative IR intensities predicted for the methanol-water clusters with the M06-2X/aug-cc-pVTZ method are consistent with our experimental results. For M4(H_2O), observed spectrum agree less with theoretical predictions, indicating the presence of isomers other than the most stable cyclic one. Spectra of Mn(H_2O) and Mn+1 are compared and the cooperative hydrogen-bonding is discussed.

Endohedral gallide cluster superconductors and superconductivity in ReGa5

PubMed Central

Xie, Weiwei; Luo, Huixia; Phelan, Brendan F.; Klimczuk, Tomasz; Cevallos, Francois Alexandre; Cava, Robert Joseph

2015-01-01

We present transition metal-embedded (T@Gan) endohedral Ga-clusters as a favorable structural motif for superconductivity and develop empirical, molecule-based, electron counting rules that govern the hierarchical architectures that the clusters assume in binary phases. Among the binary T@Gan endohedral cluster systems, Mo8Ga41, Mo6Ga31, Rh2Ga9, and Ir2Ga9 are all previously known superconductors. The well-known exotic superconductor PuCoGa5 and related phases are also members of this endohedral gallide cluster family. We show that electron-deficient compounds like Mo8Ga41 prefer architectures with vertex-sharing gallium clusters, whereas electron-rich compounds, like PdGa5, prefer edge-sharing cluster architectures. The superconducting transition temperatures are highest for the electron-poor, corner-sharing architectures. Based on this analysis, the previously unknown endohedral cluster compound ReGa5 is postulated to exist at an intermediate electron count and a mix of corner sharing and edge sharing cluster architectures. The empirical prediction is shown to be correct and leads to the discovery of superconductivity in ReGa5. The Fermi levels for endohedral gallide cluster compounds are located in deep pseudogaps in the electronic densities of states, an important factor in determining their chemical stability, while at the same time limiting their superconducting transition temperatures. PMID:26644566

Clustering Suicide Attempters: Impulsive-Ambivalent, Well-Planned, or Frequent.

PubMed

Lopez-Castroman, Jorge; Nogue, Erika; Guillaume, Sebastien; Picot, Marie Christine; Courtet, Philippe

2016-06-01

Attempts to predict suicidal behavior within high-risk populations have so far shown insufficient accuracy. Although several psychosocial and clinical features have been consistently associated with suicide attempts, investigations of latent structure in well-characterized populations of suicide attempters are lacking. We analyzed a sample of 1,009 hospitalized suicide attempters that were recruited between 1999 and 2012. Eleven clinically relevant items related to the characteristics of suicidal behavior were submitted to a Hierarchical Ascendant Classification. Phenotypic profiles were compared between the resulting clusters. A decisional tree was constructed to facilitate the differentiation of individuals classified within the first 2 clusters. Most individuals were included in a cluster characterized by less lethal means and planning ("impulse-ambivalent"). A second cluster featured more carefully planned attempts ("well-planned"), more alcohol or drug use before the attempt, and more precautions to avoid interruptions. Finally, a small, third cluster included individuals reporting more attempts ("frequent"), more often serious or violent attempts, and an earlier age at first attempt. Differences across clusters by demographic and clinical characteristics were also found, particularly with the third cluster whose participants had experienced high levels of childhood abuse. Cluster analysis consistently supported 3 distinct clusters of individuals with specific features in their suicidal behaviors and phenotypic profiles that could help clinicians to better focus prevention strategies. © Copyright 2016 Physicians Postgraduate Press, Inc.

Prediction of operon-like gene clusters in the Arabidopsis thaliana genome based on co-expression analysis of neighboring genes.

PubMed

Wada, Masayoshi; Takahashi, Hiroki; Altaf-Ul-Amin, Md; Nakamura, Kensuke; Hirai, Masami Y; Ohta, Daisaku; Kanaya, Shigehiko

2012-07-15

Operon-like arrangements of genes occur in eukaryotes ranging from yeasts and filamentous fungi to nematodes, plants, and mammals. In plants, several examples of operon-like gene clusters involved in metabolic pathways have recently been characterized, e.g. the cyclic hydroxamic acid pathways in maize, the avenacin biosynthesis gene clusters in oat, the thalianol pathway in Arabidopsis thaliana, and the diterpenoid momilactone cluster in rice. Such operon-like gene clusters are defined by their co-regulation or neighboring positions within immediate vicinity of chromosomal regions. A comprehensive analysis of the expression of neighboring genes therefore accounts a crucial step to reveal the complete set of operon-like gene clusters within a genome. Genome-wide prediction of operon-like gene clusters should contribute to functional annotation efforts and provide novel insight into evolutionary aspects acquiring certain biological functions as well. We predicted co-expressed gene clusters by comparing the Pearson correlation coefficient of neighboring genes and randomly selected gene pairs, based on a statistical method that takes false discovery rate (FDR) into consideration for 1469 microarray gene expression datasets of A. thaliana. We estimated that A. thaliana contains 100 operon-like gene clusters in total. We predicted 34 statistically significant gene clusters consisting of 3 to 22 genes each, based on a stringent FDR threshold of 0.1. Functional relationships among genes in individual clusters were estimated by sequence similarity and functional annotation of genes. Duplicated gene pairs (determined based on BLAST with a cutoff of E<10(-5)) are included in 27 clusters. Five clusters are associated with metabolism, containing P450 genes restricted to the Brassica family and predicted to be involved in secondary metabolism. Operon-like clusters tend to include genes encoding bio-machinery associated with ribosomes, the ubiquitin/proteasome system, secondary metabolic pathways, lipid and fatty-acid metabolism, and the lipid transfer system. Copyright © 2012 Elsevier B.V. All rights reserved.

Domain Selectivity in the Parahippocampal Gyrus Is Predicted by the Same Structural Connectivity Patterns in Blind and Sighted Individuals.

PubMed

Wang, Xiaoying; He, Chenxi; Peelen, Marius V; Zhong, Suyu; Gong, Gaolang; Caramazza, Alfonso; Bi, Yanchao

2017-05-03

Human ventral occipital temporal cortex contains clusters of neurons that show domain-preferring responses during visual perception. Recent studies have reported that some of these clusters show surprisingly similar domain selectivity in congenitally blind participants performing nonvisual tasks. An important open question is whether these functional similarities are driven by similar innate connections in blind and sighted groups. Here we addressed this question focusing on the parahippocampal gyrus (PHG), a region that is selective for large objects and scenes. Based on the assumption that patterns of long-range connectivity shape local computation, we examined whether domain selectivity in PHG is driven by similar structural connectivity patterns in the two populations. Multiple regression models were built to predict the selectivity of PHG voxels for large human-made objects from white matter (WM) connectivity patterns in both groups. These models were then tested using independent data from participants with similar visual experience (two sighted groups) and using data from participants with different visual experience (blind and sighted groups). Strikingly, the WM-based predictions between blind and sighted groups were as successful as predictions between two independent sighted groups. That is, the functional selectivity for large objects of a PHG voxel in a blind participant could be accurately predicted by its WM pattern using the connection-to-function model built from the sighted group data, and vice versa. Regions that significantly predicted PHG selectivity were located in temporal and frontal cortices in both sighted and blind populations. These results show that the large-scale network driving domain selectivity in PHG is independent of vision. SIGNIFICANCE STATEMENT Recent studies have reported intriguingly similar domain selectivity in sighted and congenitally blind individuals in regions within the ventral visual cortex. To examine whether these similarities originate from similar innate connectional roots, we investigated whether the domain selectivity in one population could be predicted by the structural connectivity pattern of the other. We found that the selectivity for large objects of a PHG voxel in a blind participant could be predicted by its structural connectivity pattern using the connection-to-function model built from the sighted group data, and vice versa. These results reveal that the structural connectivity underlying domain selectivity in the PHG is independent of visual experience, providing evidence for nonvisual representations in this region. Copyright © 2017 the authors 0270-6474/17/374706-12$15.00/0.

antiSMASH 3.0—a comprehensive resource for the genome mining of biosynthetic gene clusters

PubMed Central

Blin, Kai; Duddela, Srikanth; Krug, Daniel; Kim, Hyun Uk; Bruccoleri, Robert; Lee, Sang Yup; Fischbach, Michael A; Müller, Rolf; Wohlleben, Wolfgang; Breitling, Rainer; Takano, Eriko

2015-01-01

Abstract Microbial secondary metabolism constitutes a rich source of antibiotics, chemotherapeutics, insecticides and other high-value chemicals. Genome mining of gene clusters that encode the biosynthetic pathways for these metabolites has become a key methodology for novel compound discovery. In 2011, we introduced antiSMASH, a web server and stand-alone tool for the automatic genomic identification and analysis of biosynthetic gene clusters, available at http://antismash.secondarymetabolites.org. Here, we present version 3.0 of antiSMASH, which has undergone major improvements. A full integration of the recently published ClusterFinder algorithm now allows using this probabilistic algorithm to detect putative gene clusters of unknown types. Also, a new dereplication variant of the ClusterBlast module now identifies similarities of identified clusters to any of 1172 clusters with known end products. At the enzyme level, active sites of key biosynthetic enzymes are now pinpointed through a curated pattern-matching procedure and Enzyme Commission numbers are assigned to functionally classify all enzyme-coding genes. Additionally, chemical structure prediction has been improved by incorporating polyketide reduction states. Finally, in order for users to be able to organize and analyze multiple antiSMASH outputs in a private setting, a new XML output module allows offline editing of antiSMASH annotations within the Geneious software. PMID:25948579

A Model for Protostellar Cluster Luminosities and the Impact on the CO–H2 Conversion Factor

NASA Astrophysics Data System (ADS)

Gaches, Brandt A. L.; Offner, Stella S. R.

2018-02-01

We construct a semianalytic model to study the effect of far-ultraviolet (FUV) radiation on gas chemistry from embedded protostars. We use the protostellar luminosity function (PLF) formalism of Offner & McKee to calculate the total, FUV, and ionizing cluster luminosity for various protostellar accretion histories and cluster sizes. We2 compare the model predictions with surveys of Gould Belt star-forming regions and find that the tapered turbulent core model matches best the mean luminosities and the spread in the data. We combine the cluster model with the photodissociation region astrochemistry code, 3D-PDR, to compute the impact of the FUV luminosity from embedded protostars on the CO-to-H2 conversion factor, X CO, as a function of cluster size, gas mass, and star formation efficiency. We find that X CO has a weak dependence on the FUV radiation from embedded sources for large clusters owing to high cloud optical depths. In smaller and more efficient clusters the embedded FUV increases X CO to levels consistent with the average Milky Way values. The internal physical and chemical structures of the cloud are significantly altered, and X CO depends strongly on the protostellar cluster mass for small efficient clouds.

A first-principles study of the influence of helium atoms on the optical response of small silver clusters.

PubMed

Pereiro, M; Baldomir, D; Arias, J E

2011-02-28

Optical excitation spectra of Ag(n) and Ag(n)@He(60) (n = 2, 8) clusters are investigated in the framework of the time-dependent density functional theory (TDDFT) within the linear response regime. We have performed the ab initio calculations for two different exact exchange functionals (GGA-exact and LDA-exact). The computed spectra of Ag(n)@He(60) clusters with the GGA-exact functional accounting for exchange-correlation effects are found to be generally in a relatively good agreement with the experiment. A strategy is proposed to obtain the ground-state structures of the Ag(n)@He(60) clusters and in the initial process of the geometry optimization, the He environment is simulated with buckyballs. A redshift of the silver clusters spectra is observed in the He environment with respect to the ones of bare silver clusters. This observation is discussed and explained in terms of a contraction of the Ag-He bonding length and a consequent confinement of the s valence electrons in silver clusters. Likewise, the Mie-Gans predictions combined with our TDDFT calculations also show that the dielectric effect produced by the He matrix is considerably less important in explaining the redshifting observed in the optical spectra of Ag(n)@He(60) clusters.

A Kinematic Survey in the Perseus Molecular Cloud: Results from the APOGEE Infrared Survey of Young Nebulous Clusters (IN-SYNC)

NASA Astrophysics Data System (ADS)

Covey, Kevin R.; Cottaar, M.; Foster, J. B.; Nidever, D. L.; Meyer, M.; Tan, J.; Da Rio, N.; Flaherty, K. M.; Stassun, K.; Frinchaboy, P. M.; Majewski, S.; APOGEE IN-SYNC Team

2014-01-01

Demographic studies of stellar clusters indicate that relatively few persist as bound structures for 100 Myrs or longer. If cluster dispersal is a 'violent' process, it could strongly influence the formation and early evolution of stellar binaries and planetary systems. Unfortunately, measuring the dynamical state of 'typical' (i.e., ~300-1000 member) young star clusters has been difficult, particularly for clusters still embedded within their parental molecular cloud. The near-infrared spectrograph for the Apache Point Observatory Galactic Evolution Experiment (APOGEE), which can measure precise radial velocities for 230 cluster stars simultaneously, is uniquely suited to diagnosing the dynamics of Galactic star formation regions. We give an overview of the INfrared Survey of Young Nebulous Clusters (IN-SYNC), an APOGEE ancillary science program that is carrying out a comparative study of young clusters in the Perseus molecular cloud: NGC 1333, a heavily embedded cluster, and IC 348, which has begun to disperse its surrounding molecular gas. These observations appear to rule out a significantly super-virial velocity dispersion in IC 348, contrary to predictions of models where a cluster's dynamics is strongly influenced by the dispersal of its primordial gas. We also summarize the properties of two newly identified spectroscopic binaries; binary systems such as these play a key role in the dynamical evolution of young clusters, and introduce velocity offsets that must be accounted for in measuring cluster velocity dispersions.

Structure, stability, thermodynamic properties, and IR spectra of the protonated water decamer H+(H2O)10.

PubMed

Karthikeyan, S; Kim, Kwang S

2009-08-13

Protonated water clusters H+(H2O)n favor two-dimensional (2D) structures for n < or = 7 at low temperatures. At 0 K, the 2D and three-dimensional (3D) structures for n = 8 are almost isoenergetic, and the 3D structures for n > 9 tend to be more stable. However, for n = 9, the netlike structures are likely to be more stable above 150 K. In this regard, we investigate the case of n = 10 to find which structure is more stable between the 3D structure and the netlike structure around 150 and 250 K. We use density functional theory, Møller-Plesset second-order perturbation theory, and coupled cluster theory with single, double, and perturbative triple excitations (CCSD(T)). At the complete basis set limit for the CCSD(T) level of theory, three isomers of 3D cage structure are much more stable in zero point energy corrected binding energy and in free binding energies at 150 K than the lowest energy netlike structures, while the netlike structure would be more stable around approximately 250 K. The predicted vibrational spectra are in good agreement with the experiment. One of the three isomers explains the experimental IR observation of an acceptor (A) type peak of a dangling hydrogen atom.

Photoelectron spectroscopy of B4O4 (-): Dual 3c-4e π hyperbonds and rhombic 4c-4e o-bond in boron oxide clusters.

PubMed

Tian, Wen-Juan; Zhao, Li-Juan; Chen, Qiang; Ou, Ting; Xu, Hong-Guang; Zheng, Wei-Jun; Zhai, Hua-Jin; Li, Si-Dian

2015-04-07

Gas-phase anion photoelectron spectroscopy (PES) is combined with global structural searches and electronic structure calculations at the hybrid Becke 3-parameter exchange functional and Lee-Yang-Parr correlation functional (B3LYP) and single-point coupled-cluster with single, double, and perturbative triple excitations (CCSD(T)) levels to probe the structural and electronic properties and chemical bonding of the B4O4 (0/-) clusters. The measured PES spectra of B4O4 (-) exhibit a major band with the adiabatic and vertical detachment energies (ADE and VDE) of 2.64 ± 0.10 and 2.81 ± 0.10 eV, respectively, as well as a weak peak with the ADE and VDE of 1.42 ± 0.08 and 1.48 ± 0.08 eV. The former band proves to correspond to the Y-shaped global minimum of Cs B4O4 (-) ((2)A″), with the calculated ADE/VDE of 2.57/2.84 eV at the CCSD(T) level, whereas the weak band is associated with the second lowest-energy, rhombic isomer of D2h B4O4 (-) ((2)B2g) with the predicted ADE/VDE of 1.43/1.49 eV. Both anion structures are planar, featuring a B atom or a B2O2 core bonded with terminal BO and/or BO2 groups. The same Y-shaped and rhombic structures are also located for the B4O4 neutral cluster, albeit with a reversed energy order. Bonding analyses reveal dual three-center four-electron (3c-4e) π hyperbonds in the Y-shaped B4O4 (0/-) clusters and a four-center four-electron (4c-4e) π bond, that is, the so-called o-bond in the rhombic B4O4 (0/-) clusters. This work is the first experimental study on a molecular system with an o-bond.

As Simple As Possible, but Not Simpler: Exploring the Fidelity of Coarse-Grained Protein Models for Simulated Force Spectroscopy

PubMed Central

Rottler, Jörg; Plotkin, Steven S.

2016-01-01

Mechanical unfolding of a single domain of loop-truncated superoxide dismutase protein has been simulated via force spectroscopy techniques with both all-atom (AA) models and several coarse-grained models having different levels of resolution: A Gō model containing all heavy atoms in the protein (HA-Gō), the associative memory, water mediated, structure and energy model (AWSEM) which has 3 interaction sites per amino acid, and a Gō model containing only one interaction site per amino acid at the Cα position (Cα-Gō). To systematically compare results across models, the scales of time, energy, and force had to be suitably renormalized in each model. Surprisingly, the HA-Gō model gives the softest protein, exhibiting much smaller force peaks than all other models after the above renormalization. Clustering to render a structural taxonomy as the protein unfolds showed that the AA, HA-Gō, and Cα-Gō models exhibit a single pathway for early unfolding, which eventually bifurcates repeatedly to multiple branches only after the protein is about half-unfolded. The AWSEM model shows a single dominant unfolding pathway over the whole range of unfolding, in contrast to all other models. TM alignment, clustering analysis, and native contact maps show that the AWSEM pathway has however the most structural similarity to the AA model at high nativeness, but the least structural similarity to the AA model at low nativeness. In comparison to the AA model, the sequence of native contact breakage is best predicted by the HA-Gō model. All models consistently predict a similar unfolding mechanism for early force-induced unfolding events, but diverge in their predictions for late stage unfolding events when the protein is more significantly disordered. PMID:27898663

As Simple As Possible, but Not Simpler: Exploring the Fidelity of Coarse-Grained Protein Models for Simulated Force Spectroscopy.

PubMed

Habibi, Mona; Rottler, Jörg; Plotkin, Steven S

2016-11-01

Mechanical unfolding of a single domain of loop-truncated superoxide dismutase protein has been simulated via force spectroscopy techniques with both all-atom (AA) models and several coarse-grained models having different levels of resolution: A Gō model containing all heavy atoms in the protein (HA-Gō), the associative memory, water mediated, structure and energy model (AWSEM) which has 3 interaction sites per amino acid, and a Gō model containing only one interaction site per amino acid at the Cα position (Cα-Gō). To systematically compare results across models, the scales of time, energy, and force had to be suitably renormalized in each model. Surprisingly, the HA-Gō model gives the softest protein, exhibiting much smaller force peaks than all other models after the above renormalization. Clustering to render a structural taxonomy as the protein unfolds showed that the AA, HA-Gō, and Cα-Gō models exhibit a single pathway for early unfolding, which eventually bifurcates repeatedly to multiple branches only after the protein is about half-unfolded. The AWSEM model shows a single dominant unfolding pathway over the whole range of unfolding, in contrast to all other models. TM alignment, clustering analysis, and native contact maps show that the AWSEM pathway has however the most structural similarity to the AA model at high nativeness, but the least structural similarity to the AA model at low nativeness. In comparison to the AA model, the sequence of native contact breakage is best predicted by the HA-Gō model. All models consistently predict a similar unfolding mechanism for early force-induced unfolding events, but diverge in their predictions for late stage unfolding events when the protein is more significantly disordered.

Fast Geometric Consensus Approach for Protein Model Quality Assessment

PubMed Central

Adamczak, Rafal; Pillardy, Jaroslaw; Vallat, Brinda K.

2011-01-01

Abstract Model quality assessment (MQA) is an integral part of protein structure prediction methods that typically generate multiple candidate models. The challenge lies in ranking and selecting the best models using a variety of physical, knowledge-based, and geometric consensus (GC)-based scoring functions. In particular, 3D-Jury and related GC methods assume that well-predicted (sub-)structures are more likely to occur frequently in a population of candidate models, compared to incorrectly folded fragments. While this approach is very successful in the context of diversified sets of models, identifying similar substructures is computationally expensive since all pairs of models need to be superimposed using MaxSub or related heuristics for structure-to-structure alignment. Here, we consider a fast alternative, in which structural similarity is assessed using 1D profiles, e.g., consisting of relative solvent accessibilities and secondary structures of equivalent amino acid residues in the respective models. We show that the new approach, dubbed 1D-Jury, allows to implicitly compare and rank N models in O(N) time, as opposed to quadratic complexity of 3D-Jury and related clustering-based methods. In addition, 1D-Jury avoids computationally expensive 3D superposition of pairs of models. At the same time, structural similarity scores based on 1D profiles are shown to correlate strongly with those obtained using MaxSub. In terms of the ability to select the best models as top candidates 1D-Jury performs on par with other GC methods. Other potential applications of the new approach, including fast clustering of large numbers of intermediate structures generated by folding simulations, are discussed as well. PMID:21244273

Thermodynamic and Structural Properties of Methanol-Water Solutions Using Non-Additive Interaction Models

PubMed Central

Zhong, Yang; Warren, G. Lee; Patel, Sandeep

2014-01-01

We study bulk structural and thermodynamic properties of methanol-water solutions via molecular dynamics simulations using novel interaction potentials based on the charge equilibration (fluctuating charge) formalism to explicitly account for molecular polarization at the atomic level. The study uses the TIP4P-FQ potential for water-water interactions, and the CHARMM-based (Chemistry at HARvard Molecular Mechanics) fluctuating charge potential for methanol-methanol and methanol-water interactions. In terms of bulk solution properties, we discuss liquid densities, enthalpies of mixing, dielectric constants, self-diffusion constants, as well as structural properties related to local hydrogen bonding structure as manifested in radial distribution functions and cluster analysis. We further explore the electronic response of water and methanol in the differing local environments established by the interaction of each species predominantly with molecules of the other species. The current force field for the alcohol-water interaction performs reasonably well for most properties, with the greatest deviation from experiment observed for the excess mixing enthalpies, which are predicted to be too favorable. This is qualitatively consistent with the overestimation of the methanol-water gas-phase interaction energy for the lowest-energy conformer (methanol as proton donor). Hydration free energies for methanol in TIP4P-FQ water are predicted to be −5.6±0.2 kcal/mole, in respectable agreement with the experimental value of −5.1 kcal/mole. With respect to solution micro-structure, the present cluster analysis suggests that the micro-scale environment for concentrations where select thermodynamic quantities reach extremal values is described by a bi-percolating network structure. PMID:18074339

An Ab Initio Study of CuCO

NASA Technical Reports Server (NTRS)

Bauschlicher, Charles W., Jr.

1994-01-01

Modified coupled-pair functional (MCPF) calculations and coupled cluster singles and doubles calculations, which include a perturbational estimate of the connected triples [CCSD(T)], yield a bent structure for CuCO, thus, supporting the prediction of a nonlinear structure based on density functional (DF) calculations. Our best estimate for the binding energy is 4.9 +/- 1.4 kcal/mol; this is in better agreement with experiment (6.0 +/- 1.2 kcal/mol) than the DF approach which yields a value (19.6 kcal/mol) significantly larger than experiment.

Construction of ontology augmented networks for protein complex prediction.

PubMed

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

Mechanistic Details and Reactivity Descriptors in Oxidation and Acid Catalysis of Methanol

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

Deshlahra, Prashant; Carr, Robert T.; Chai, Song-Hai

2015-02-06

Acid and redox reaction rates of CH₃OH-O₂ mixtures on polyoxometalate (POM) clusters, together with isotopic, spectroscopic, and theoretical assessments of catalyst properties and reaction pathways, were used to define rigorous descriptors of reactivity and to probe the compositional effects for oxidative dehydrogenation (ODH) and dehydration reactions. ³¹P-MAS NMR, transmission electron microscopy and titrations of protons with di-tert-butylpyridine during catalysis showed that POM clusters retained their Keggin structure upon dispersion on SiO₂ and after use in CH₃OH reactions. The effects of CH₃OH and O₂ pressures and of D-substitution on ODH rates show that C-H activation in molecularly adsorbed CH₃OH is themore » sole kinetically relevant step and leads to reduced centers as intermediates present at low coverages; their concentrations, measured from UV-vis spectra obtained during catalysis, are consistent with the effects of CH₃OH/O₂ ratios predicted from the elementary steps proposed. First-order ODH rate constants depend strongly on the addenda atoms (Mo vs W) but weakly on the central atom (P vs Si) in POM clusters, because C-H activation steps inject electrons into the lowest unoccupied molecular orbitals (LUMO) of the clusters, which are the d-orbitals at Mo⁶⁺ and W⁶⁺ centers. H-atom addition energies (HAE) at O-atoms in POM clusters represent the relevant theoretical probe of the LUMO energies and of ODH reactivity. The calculated energies of ODH transition states at each O-atom depend linearly on their HAE values with slopes near unity, as predicted for late transition states in which electron transfer and C-H cleavage are essentially complete. HAE values averaged over all accessible O-atoms in POM clusters provide the appropriate reactivity descriptor for oxides whose known structures allow accurate HAE calculations. CH₃OH dehydration proceeds via parallel pathways mediated by late carbenium-ion transition states; effects of composition on dehydration reactivity reflect changes in charge reorganizations and electrostatic forces that stabilize protons at Brønsted acid sites.« less

IMG-ABC. A knowledge base to fuel discovery of biosynthetic gene clusters and novel secondary metabolites

DOE PAGES

Hadjithomas, Michalis; Chen, I-Min Amy; Chu, Ken; ...

2015-07-14

In the discovery of secondary metabolites, analysis of sequence data is a promising exploration path that remains largely underutilized due to the lack of computational platforms that enable such a systematic approach on a large scale. In this work, we present IMG-ABC (https://img.jgi.doe.gov/abc), an atlas of biosynthetic gene clusters within the Integrated Microbial Genomes (IMG) system, which is aimed at harnessing the power of “big” genomic data for discovering small molecules. IMG-ABC relies on IMG’s comprehensive integrated structural and functional genomic data for the analysis of biosynthetic gene clusters (BCs) and associated secondary metabolites (SMs). SMs and BCs serve asmore » the two main classes of objects in IMG-ABC, each with a rich collection of attributes. A unique feature of IMG-ABC is the incorporation of both experimentally validated and computationally predicted BCs in genomes as well as metagenomes, thus identifying BCs in uncultured populations and rare taxa. We demonstrate the strength of IMG-ABC’s focused integrated analysis tools in enabling the exploration of microbial secondary metabolism on a global scale, through the discovery of phenazine-producing clusters for the first time in lphaproteobacteria. IMG-ABC strives to fill the long-existent void of resources for computational exploration of the secondary metabolism universe; its underlying scalable framework enables traversal of uncovered phylogenetic and chemical structure space, serving as a doorway to a new era in the discovery of novel molecules. IMG-ABC is the largest publicly available database of predicted and experimental biosynthetic gene clusters and the secondary metabolites they produce. The system also includes powerful search and analysis tools that are integrated with IMG’s extensive genomic/metagenomic data and analysis tool kits. As new research on biosynthetic gene clusters and secondary metabolites is published and more genomes are sequenced, IMG-ABC will continue to expand, with the goal of becoming an essential component of any bioinformatic exploration of the secondary metabolism world.« less

Acidity in DMSO from the embedded cluster integral equation quantum solvation model.

PubMed

Heil, Jochen; Tomazic, Daniel; Egbers, Simon; Kast, Stefan M

2014-04-01

The embedded cluster reference interaction site model (EC-RISM) is applied to the prediction of acidity constants of organic molecules in dimethyl sulfoxide (DMSO) solution. EC-RISM is based on a self-consistent treatment of the solute's electronic structure and the solvent's structure by coupling quantum-chemical calculations with three-dimensional (3D) RISM integral equation theory. We compare available DMSO force fields with reference calculations obtained using the polarizable continuum model (PCM). The results are evaluated statistically using two different approaches to eliminating the proton contribution: a linear regression model and an analysis of pK(a) shifts for compound pairs. Suitable levels of theory for the integral equation methodology are benchmarked. The results are further analyzed and illustrated by visualizing solvent site distribution functions and comparing them with an aqueous environment.

Clusters, Assemble: Growth of Intermetallic Compounds from Metal Flux Reactions.

PubMed

Latturner, Susan E

2018-01-16

Metal flux synthesis involves the reaction of metals and metalloids in a large excess of a low-melting metal that acts as a solvent. This technique makes use of an unusual temperature regime (above the temperatures used for solvothermal methods and below the temperatures used in traditional solid state synthesis) and facilitates the growth of products as large crystals. It has proven to be a fruitful method to discover new intermetallic compounds. However, little is known about the chemistry occurring within a molten metal solvent; without an understanding of the nature of precursor formation and assembly, it is difficult to predict product structures and target properties. Organic chemists have a vast toolbox of well-known reagents and reaction mechanisms to use in directing their synthesis toward a desired molecular structure. This is not yet the case for the synthesis of inorganic extended structures. We have carried out extensive explorations of the growth of new magnetic intermetallic compounds from a variety of metal fluxes. This Account presents a review of some of our results and recent reports by other groups; this work indicates that products with common building blocks and homologous series with identical structural motifs are repeatedly seen in metal flux chemistry. For instance, fluorite-type layers comprised of transition metals coordinated by eight main group metal atoms are found in the Th 2 (Au x Si 1-x )[AuAl 2 ] n Si 2 and R[AuAl 2 ] n Al 2 (Au x Si 1-x ) 2 series grown from aluminum flux, the Ce n PdIn 3n+2 series grown from indium flux, and CePdGa 6 and Ce 2 PdGa 10 grown from gallium flux. Similarly, our investigations of reactions of heavy main group metals, M, in rare earth/transition metal eutectic fluxes reveal that the R/T/M/M' products usually feature M-centered rare earth clusters M@R 8-12 , which share faces to form layers and networks that surround transition metal building blocks. These structural trends, temperature dependence of products formed in the flux, and interconversions observed by differential scanning calorimetry support the idea that these clusters likely form in the melt, existing as precursors and assembling into different crystalline products depending on time, temperature, and reaction ratio. Proof of this mechanism will require future investigations using techniques such as pair distribution function analysis of flux melts to observe cluster formation and in situ diffraction during cooling to detect various phases as they crystallize and interconvert. These data will aid in understanding the parameters that control cluster formation and assembly in metal melts, allow for prediction of products of flux reactions, and will potentially enable the tailoring of reaction conditions to promote the formation of structures with desirable properties.

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.

Basketball Teams as Strategic Networks

PubMed Central

Fewell, Jennifer H.; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S.

2012-01-01

We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as “uphill/downhill” flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness. PMID:23139744

Basketball teams as strategic networks.

PubMed

Fewell, Jennifer H; Armbruster, Dieter; Ingraham, John; Petersen, Alexander; Waters, James S

2012-01-01

We asked how team dynamics can be captured in relation to function by considering games in the first round of the NBA 2010 play-offs as networks. Defining players as nodes and ball movements as links, we analyzed the network properties of degree centrality, clustering, entropy and flow centrality across teams and positions, to characterize the game from a network perspective and to determine whether we can assess differences in team offensive strategy by their network properties. The compiled network structure across teams reflected a fundamental attribute of basketball strategy. They primarily showed a centralized ball distribution pattern with the point guard in a leadership role. However, individual play-off teams showed variation in their relative involvement of other players/positions in ball distribution, reflected quantitatively by differences in clustering and degree centrality. We also characterized two potential alternate offensive strategies by associated variation in network structure: (1) whether teams consistently moved the ball towards their shooting specialists, measured as "uphill/downhill" flux, and (2) whether they distributed the ball in a way that reduced predictability, measured as team entropy. These network metrics quantified different aspects of team strategy, with no single metric wholly predictive of success. However, in the context of the 2010 play-offs, the values of clustering (connectedness across players) and network entropy (unpredictability of ball movement) had the most consistent association with team advancement. Our analyses demonstrate the utility of network approaches in quantifying team strategy and show that testable hypotheses can be evaluated using this approach. These analyses also highlight the richness of basketball networks as a dataset for exploring the relationships between network structure and dynamics with team organization and effectiveness.

Correlating the magic numbers of inorganic nanomolecular assemblies with a {Pd84} molecular-ring Rosetta Stone

PubMed Central

Xu, Feng; Miras, Haralampos N.; Scullion, Rachel A.; Long, De-Liang; Thiel, Johannes; Cronin, Leroy

2012-01-01

Molecular self-assembly has often been suggested as the ultimate route for the bottom-up construction of building blocks atom-by-atom for functional nanotechnology, yet structural design or prediction of nanomolecular assemblies is still far from reach. Whereas nature uses complex machinery such as the ribosome, chemists use painstakingly engineered step-by-step approaches to build complex molecules but the size and complexity of such molecules, not to mention the accessible yields, can be limited. Herein we present the discovery of a palladium oxometalate {Pd84}-ring cluster 3.3 nm in diameter; [Pd84O42(OAc)28(PO4)42]70- ({Pd84} ≡ {Pd12}7) that is formed in water just by mixing two reagents at room temperature, giving crystals of the compound in just a few days. The structure of the {Pd84}-ring has sevenfold symmetry, comprises 196 building blocks, and we also show, using mass spectrometry, that a large library of other related nanostructures is present in solution. Finally, by analysis of the symmetry and the building block library that construct the {Pd84} we show that the correlation of the symmetry, subunit number, and overall cluster nuclearity can be used as a “Rosetta Stone” to rationalize the “magic numbers” defining a number of other systems. This is because the discovery of {Pd84} allows the relationship between seemingly unrelated families of molecular inorganic nanosystems to be decoded from the overall cluster magic-number nuclearity, to the symmetry and building blocks that define such structures allowing the prediction of other members of these nanocluster families. PMID:22753516

Online interactive analysis of protein structure ensembles with Bio3D-web.

PubMed

Skjærven, Lars; Jariwala, Shashank; Yao, Xin-Qiu; Grant, Barry J

2016-11-15

Bio3D-web is an online application for analyzing the sequence, structure and conformational heterogeneity of protein families. Major functionality is provided for identifying protein structure sets for analysis, their alignment and refined structure superposition, sequence and structure conservation analysis, mapping and clustering of conformations and the quantitative comparison of their predicted structural dynamics. Bio3D-web is based on the Bio3D and Shiny R packages. All major browsers are supported and full source code is available under a GPL2 license from http://thegrantlab.org/bio3d-web CONTACT: bjgrant@umich.edu or lars.skjarven@uib.no. © The Author 2016. Published by Oxford University Press.

Genomes to natural products PRediction Informatics for Secondary Metabolomes (PRISM).

PubMed

Skinnider, Michael A; Dejong, Chris A; Rees, Philip N; Johnston, Chad W; Li, Haoxin; Webster, Andrew L H; Wyatt, Morgan A; Magarvey, Nathan A

2015-11-16

Microbial natural products are an invaluable source of evolved bioactive small molecules and pharmaceutical agents. Next-generation and metagenomic sequencing indicates untapped genomic potential, yet high rediscovery rates of known metabolites increasingly frustrate conventional natural product screening programs. New methods to connect biosynthetic gene clusters to novel chemical scaffolds are therefore critical to enable the targeted discovery of genetically encoded natural products. Here, we present PRISM, a computational resource for the identification of biosynthetic gene clusters, prediction of genetically encoded nonribosomal peptides and type I and II polyketides, and bio- and cheminformatic dereplication of known natural products. PRISM implements novel algorithms which render it uniquely capable of predicting type II polyketides, deoxygenated sugars, and starter units, making it a comprehensive genome-guided chemical structure prediction engine. A library of 57 tailoring reactions is leveraged for combinatorial scaffold library generation when multiple potential substrates are consistent with biosynthetic logic. We compare the accuracy of PRISM to existing genomic analysis platforms. PRISM is an open-source, user-friendly web application available at http://magarveylab.ca/prism/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Compilation of mRNA Polyadenylation Signals in Arabidopsis Revealed a New Signal Element and Potential Secondary Structures1[w

PubMed Central

Loke, Johnny C.; Stahlberg, Eric A.; Strenski, David G.; Haas, Brian J.; Wood, Paul Chris; Li, Qingshun Quinn

2005-01-01

Using a novel program, SignalSleuth, and a database containing authenticated polyadenylation [poly(A)] sites, we analyzed the composition of mRNA poly(A) signals in Arabidopsis (Arabidopsis thaliana), and reevaluated previously described cis-elements within the 3′-untranslated (UTR) regions, including near upstream elements and far upstream elements. As predicted, there are absences of high-consensus signal patterns. The AAUAAA signal topped the near upstream elements patterns and was found within the predicted location to only approximately 10% of 3′-UTRs. More importantly, we identified a new set, named cleavage elements, of poly(A) signals flanking both sides of the cleavage site. These cis-elements were not previously revealed by conventional mutagenesis and are contemplated as a cluster of signals for cleavage site recognition. Moreover, a single-nucleotide profile scan on the 3′-UTR regions unveiled a distinct arrangement of alternate stretches of U and A nucleotides, which led to a prediction of the formation of secondary structures. Using an RNA secondary structure prediction program, mFold, we identified three main types of secondary structures on the sequences analyzed. Surprisingly, these observed secondary structures were all interrupted in previously constructed mutations in these regions. These results will enable us to revise the current model of plant poly(A) signals and to develop tools to predict 3′-ends for gene annotation. PMID:15965016

Analysis of the E2 transitions for /sup 3/H-/alpha/ cluster states of /sup 7/Li by the resonating group method

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

Xu Pu; Zhao Xuan; Zeng Fanan

1989-07-01

It is suggested that the ground state and the 1st, 2nd, and 3rd excited states of /sup 7/Li are /sup 3/H-/alpha/ cluster-structure states. Using the resonating group method (RGM), the eigenvalues and eigenfunctions of these states as well as the reduced E2 transition probabilities between these states are calculated and are consistent with the experimental values. The results show that the RGM is much better than the harmonic oscillator model used by Bernheim /ital et/ /ital al/. in predicting the E2 transition rates.

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

PubMed Central

Madaoui, Hocine; Guerois, Raphaël

2008-01-01

Protein surfaces are under significant selection pressure to maintain interactions with their partners throughout evolution. Capturing how selection pressure acts at the interfaces of protein–protein complexes is a fundamental issue with high interest for the structural prediction of macromolecular assemblies. We tackled this issue under the assumption that, throughout evolution, mutations should minimally disrupt the physicochemical compatibility between specific clusters of interacting residues. This constraint drove the development of the so-called Surface COmplementarity Trace in Complex History score (SCOTCH), which was found to discriminate with high efficiency the structure of biological complexes. SCOTCH performances were assessed not only with respect to other evolution-based approaches, such as conservation and coevolution analyses, but also with respect to statistically based scoring methods. Validated on a set of 129 complexes of known structure exhibiting both permanent and transient intermolecular interactions, SCOTCH appears as a robust strategy to guide the prediction of protein–protein complex structures. Of particular interest, it also provides a basic framework to efficiently track how protein surfaces could evolve while keeping their partners in contact. PMID:18511568

Conformational equilibria of alkanes in aqueous solution: relationship to water structure near hydrophobic solutes.

PubMed Central

Ashbaugh, H S; Garde, S; Hummer, G; Kaler, E W; Paulaitis, M E

1999-01-01

Conformational free energies of butane, pentane, and hexane in water are calculated from molecular simulations with explicit waters and from a simple molecular theory in which the local hydration structure is estimated based on a proximity approximation. This proximity approximation uses only the two nearest carbon atoms on the alkane to predict the local water density at a given point in space. Conformational free energies of hydration are subsequently calculated using a free energy perturbation method. Quantitative agreement is found between the free energies obtained from simulations and theory. Moreover, free energy calculations using this proximity approximation are approximately four orders of magnitude faster than those based on explicit water simulations. Our results demonstrate the accuracy and utility of the proximity approximation for predicting water structure as the basis for a quantitative description of n-alkane conformational equilibria in water. In addition, the proximity approximation provides a molecular foundation for extending predictions of water structure and hydration thermodynamic properties of simple hydrophobic solutes to larger clusters or assemblies of hydrophobic solutes. PMID:10423414

Interaction of Gas Phase Oxalic Acid with Ammonia and its Atmospheric Implications

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

Peng, Xiu-Qiu; Liu, Yi-Rong; Huang, Teng

Oxalic acid is believed to play an important role in the formation and growth of atmospheric organic aerosols. However, as a common organic acid, the understanding of the larger clusters formed by gas phase oxalic acid with multiple ammonia molecules is incomplete. In this work, the structural characteristics and thermodynamics of oxalic acid clusters with up to six ammonia molecules have been investigated at the PW91PW91/6-311++G(3df,3pd) level of theory. We found that oxalic acid forms relatively stable clusters with ammonia molecules, and that ionization events play a key role. The analyses of the thermodynamics and atmospheric relevance indicate that themore » heterodimer (H2C2O4)(NH3) shows an obvious relative concentration in the atmosphere, and thus likely participates in new particle formation. However, with increasing number of ammonia molecules, the concentration of clusters decreases gradually. Additionally, clusters of oxalic acid with ammonia molecules are predicted to form favorably in low temperature conditions and show high Rayleigh scattering intensities.« less

Scalable properties of metal clusters: A comparative study of modern exchange-correlation functionals

NASA Astrophysics Data System (ADS)

Koitz, Ralph; Soini, Thomas M.; Genest, Alexander; Trickey, S. B.; Rösch, Notker

2012-07-01

The performance of eight generalized gradient approximation exchange-correlation (xc) functionals is assessed by a series of scalar relativistic all-electron calculations on octahedral palladium model clusters Pdn with n = 13, 19, 38, 55, 79, 147 and the analogous clusters Aun (for n up through 79). For these model systems, we determined the cohesive energies and average bond lengths of the optimized octahedral structures. We extrapolate these values to the bulk limits and compare with the corresponding experimental values. While the well-established functionals BP, PBE, and PW91 are the most accurate at predicting energies, the more recent forms PBEsol, VMTsol, and VT{84}sol significantly improve the accuracy of geometries. The observed trends are largely similar for both Pd and Au. In the same spirit, we also studied the scalability of the ionization potentials and electron affinities of the Pd clusters, and extrapolated those quantities to estimates of the work function. Overall, the xc functionals can be classified into four distinct groups according to the accuracy of the computed parameters. These results allow a judicious selection of xc approximations for treating transition metal clusters.

Close packing of rods on spherical surfaces

NASA Astrophysics Data System (ADS)

Smallenburg, Frank; Löwen, Hartmut

2016-04-01

We study the optimal packing of short, hard spherocylinders confined to lie tangential to a spherical surface, using simulated annealing and molecular dynamics simulations. For clusters of up to twelve particles, we map out the changes in the geometry of the closest-packed configuration as a function of the aspect ratio L/D, where L is the cylinder length and D the diameter of the rods. We find a rich variety of cluster structures. For larger clusters, we find that the best-packed configurations up to around 100 particles are highly dependent on the exact number of particles and aspect ratio. For even larger clusters, we find largely disordered clusters for very short rods (L/D = 0.25), while slightly longer rods (L/D = 0.5 or 1) prefer a global baseball-like geometry of smectic-like domains, similar to the behavior of large-scale nematic shells. Intriguingly, we observe that when compared to their optimal flat-plane packing, short rods adapt to the spherical geometry more efficiently than both spheres and longer rods. Our results provide predictions for experimentally realizable systems of colloidal rods trapped at the interface of emulsion droplets.

A Massive Warm Baryonic Halo in the Coma Cluster

NASA Technical Reports Server (NTRS)

Bonamente, Massimiliano; Joy, Marshall K.; Lieu, Richard

2003-01-01

Several deep PSPC observations of the Coma Cluster reveal a very large scale halo of soft X-ray emission, substantially in excess of the well-known radiation from the hot intracluster medium. The excess emission, previously reported in the central region of the cluster using lower sensitivity Extreme Ultraviolet Explorer (EUVE) and ROSAT data, is now evident out to a radius of 2.6 Mpc, demonstrating that the soft excess radiation from clusters is a phenomenon of cosmological significance. The X-ray spectrum at these large radii cannot be modeled nonthermally but is consistent with the original scenario of thermal emission from warm gas at approx. 10(exp 6) K. The mass of the warm gas is on par with that of the hot X-ray-emitting plasma and significantly more massive if the warm gas resides in low-density filamentary structures. Thus, the data lend vital support to current theories of cosmic evolution, which predict that at low redshift approx. 30%-40% of the baryons reside in warm filaments converging at clusters of galaxies.

Structure based alignment and clustering of proteins (STRALCP)

DOEpatents

Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.

2013-06-18

Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses

PubMed Central

Cho, Sun-Joo; Preacher, Kristopher J.; Bottge, Brian A.

2015-01-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test–post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences. PMID:29881032

Detecting Intervention Effects in a Cluster-Randomized Design Using Multilevel Structural Equation Modeling for Binary Responses.

PubMed

Cho, Sun-Joo; Preacher, Kristopher J; Bottge, Brian A

2015-11-01

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test-post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test scores that are most often used in MLM are summed item responses (or total scores). In prior research, there have been concerns regarding measurement error in the use of total scores in using MLM. To correct for measurement error in the covariate and outcome, a theoretical justification for the use of multilevel structural equation modeling (MSEM) has been established. However, MSEM for binary responses has not been widely applied to detect intervention effects (group differences) in intervention studies. In this article, the use of MSEM for intervention studies is demonstrated and the performance of MSEM is evaluated via a simulation study. Furthermore, the consequences of using MLM instead of MSEM are shown in detecting group differences. Results of the simulation study showed that MSEM performed adequately as the number of clusters, cluster size, and intraclass correlation increased and outperformed MLM for the detection of group differences.

Molecular dynamics simulation study of the early stages of nucleation of iron oxyhydroxide nanoparticles in aqueous solutions

DOE PAGES

Zhang, Hengzhong; Waychunas, Glenn A.; Banfield, Jillian F.

2015-07-29

Nucleation is a fundamental step in crystal growth. Of environmental and materials relevance are reactions that lead to nucleation of iron oxyhydroxides in aqueous solutions. These reactions are difficult to study experimentally due to their rapid kinetics. Here, we used classical molecular dynamics simulations to investigate nucleation of iron hydroxide/oxyhydroxide nanoparticles in aqueous solutions. Results show that in a solution containing ferric ions and hydroxyl groups, iron–hydroxyl molecular clusters form by merging ferric monomers, dimers, and other oligomers, driven by strong affinity of ferric ions to hydroxyls. When deprotonation reactions are not considered in the simulations, these clusters aggregate tomore » form small iron hydroxide nanocrystals with a six-membered ring-like layered structure allomeric to gibbsite. By comparison, in a solution containing iron chloride and sodium hydroxide, the presence of chlorine drives cluster assembly along a different direction to form long molecular chains (rather than rings) composed of Fe–O octahedra linked by edge sharing. Further, in chlorine-free solutions, when deprotonation reactions are considered, the simulations predict ultimate formation of amorphous iron oxyhydroxide nanoparticles with local atomic structure similar to that of ferrihydrite nanoparticles. Overall, our simulation results reveal that nucleation of iron oxyhydroxide nanoparticles proceeds via a cluster aggregation-based nonclassical pathway.« less

A flexible data-driven comorbidity feature extraction framework.

PubMed

Sideris, Costas; Pourhomayoun, Mohammad; Kalantarian, Haik; Sarrafzadeh, Majid

2016-06-01

Disease and symptom diagnostic codes are a valuable resource for classifying and predicting patient outcomes. In this paper, we propose a novel methodology for utilizing disease diagnostic information in a predictive machine learning framework. Our methodology relies on a novel, clustering-based feature extraction framework using disease diagnostic information. To reduce the data dimensionality, we identify disease clusters using co-occurrence statistics. We optimize the number of generated clusters in the training set and then utilize these clusters as features to predict patient severity of condition and patient readmission risk. We build our clustering and feature extraction algorithm using the 2012 National Inpatient Sample (NIS), Healthcare Cost and Utilization Project (HCUP) which contains 7 million hospital discharge records and ICD-9-CM codes. The proposed framework is tested on Ronald Reagan UCLA Medical Center Electronic Health Records (EHR) from 3041 Congestive Heart Failure (CHF) patients and the UCI 130-US diabetes dataset that includes admissions from 69,980 diabetic patients. We compare our cluster-based feature set with the commonly used comorbidity frameworks including Charlson's index, Elixhauser's comorbidities and their variations. The proposed approach was shown to have significant gains between 10.7-22.1% in predictive accuracy for CHF severity of condition prediction and 4.65-5.75% in diabetes readmission prediction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Computational chemistry calculations of stability for bismuth nanotubes, fullerene-like structures and hydrogen-containing nanostructures.

PubMed

Kharissova, Oxana V; Osorio, Mario; Vázquez, Mario Sánchez; Kharisov, Boris I

2012-08-01

Using molecular mechanics (MM+), semi-empirical (PM6) and density functional theory (DFT) (B3LYP) methods we characterized bismuth nanotubes. In addition, we predicted the bismuth clusters {Bi(20)(C(5V)), Bi(24)(C(6v)), Bi(28)(C(1)), B(32)(D(3H)), Bi(60)(C(I))} and calculated their conductor properties.

Formation of met-cars and face-centered cubic structures. Thermodynamically or kinetically controlled

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

Wei, S.; Guo, B.C.; Deng, H.T.

1994-05-18

On the basis of a series of experimental studies from our laboratory, it is well established that metallocarbohedrenes, or Met-Cars for short, are a stable class of cluster materials. To account for their exceptional stability, we initially proposed a pentagonal dodecahedron structure. This cage-like structure is consistent with all the experimental findings. In general, there are two possible structures that can be developed in these metal-carbon systems, i.e., Met-Cars and cubes. Since only one structural pattern is generally observed for one particular cluster system, it has been suggested that their thermodynamical stabilities might be responsible for the selective formation ofmore » specific structures, e.g., Met-Cars or fcc structures. Herein, we present new experimental results on the system of Nb[sub m]C[sub n] under various conditions. It is shown that the experimental conditions are extremely critical for the formation of either Met-Cars or cubic structures, as predicted by Reddy and Khanma. Moreover, the new data show that the cubic structures do not develop on top of Met-Cars, but rather, they grow independently. The experiments were performed by using both time-of-flight and quadrupole mass spectrometer techniques coupled with a laser vaporization source. 23 refs., 1 fig.« less

Comparative analysis of prophages in Streptococcus mutans genomes

PubMed Central

Fu, Tiwei; Fan, Xiangyu; Long, Quanxin; Deng, Wanyan; Song, Jinlin

2017-01-01

Prophages have been considered genetic units that have an intimate association with novel phenotypic properties of bacterial hosts, such as pathogenicity and genomic variation. Little is known about the genetic information of prophages in the genome of Streptococcus mutans, a major pathogen of human dental caries. In this study, we identified 35 prophage-like elements in S. mutans genomes and performed a comparative genomic analysis. Comparative genomic and phylogenetic analyses of prophage sequences revealed that the prophages could be classified into three main large clusters: Cluster A, Cluster B, and Cluster C. The S. mutans prophages in each cluster were compared. The genomic sequences of phismuN66-1, phismuNLML9-1, and phismu24-1 all shared similarities with the previously reported S. mutans phages M102, M102AD, and ϕAPCM01. The genomes were organized into seven major gene clusters according to the putative functions of the predicted open reading frames: packaging and structural modules, integrase, host lysis modules, DNA replication/recombination modules, transcriptional regulatory modules, other protein modules, and hypothetical protein modules. Moreover, an integrase gene was only identified in phismuNLML9-1 prophages. PMID:29158986

The role of extended Fe4S4 cluster ligands in mediating sulfite reductase hemoprotein activity.

PubMed

Cepeda, Marisa R; McGarry, Lauren; Pennington, Joseph M; Krzystek, J; Elizabeth Stroupe, M

2018-05-28

The siroheme-containing subunit from the multimeric hemoflavoprotein NADPH-dependent sulfite reductase (SiR/SiRHP) catalyzes the six electron-reduction of SO 3 2- to S 2- . Siroheme is an iron-containing isobacteriochlorin that is found in sulfite and homologous siroheme-containing nitrite reductases. Siroheme does not work alone but is covalently coupled to a Fe 4 S 4 cluster through one of the cluster's ligands. One long-standing hypothesis predicted from this observation is that the environment of one iron-containing cofactor influences the properties of the other. We tested this hypothesis by identifying three amino acids (F437, M444, and T477) that interact with the Fe 4 S 4 cluster and probing the effect of altering them to alanine on the function and structure of the resulting enzymes by use of activity assays, X-ray crystallographic analysis, and EPR spectroscopy. We showed that F437 and M444 gate access for electron transfer to the siroheme-cluster assembly and the direct hydrogen bond between T477 and one of the cluster sulfides is important for determining the geometry of the siroheme active site. Copyright © 2018. Published by Elsevier B.V.

Predicted electric-field-induced hexatic structure in an ionomer membrane

NASA Astrophysics Data System (ADS)

Allahyarov, Elshad; Taylor, Philip L.

2009-08-01

Coarse-grained molecular-dynamics simulations were used to study the morphological changes induced in a Nafion®-like ionomer by the imposition of a strong electric field. We observe the formation of structures aligned along the direction of the applied field. The polar head groups of the ionomer sidechains aggregate into clusters, which then form rodlike formations which assemble into a hexatic array aligned with the direction of the field. Occasionally these lines of sulfonates and protons form a helical structure. Upon removal of the electric field, the hexatic array of rodlike structures persists and has a lower calculated free energy than the original isotropic morphology.

Moving beyond Stylized Economic Network Models: The Hybrid World of the Indian Firm Ownership Network1

PubMed Central

Mani, Dalhia; Moody, James

2014-01-01

A central theme of economic sociology has been to highlight the complexity and diversity of real world markets, but many network models of economic social structure ignore this feature and rely instead on stylized one-dimensional characterizations. Here, the authors return to the basic insight of structural diversity in economic sociology. Using the Indian interorganizational ownership network as their case, they discover a composite—or “hybrid”—model of economic networks that combines elements of prior stylized models. The network contains a disconnected periphery conforming closely to a “transactional” model; a semiperiphery characterized by small, dense clusters with sporadic links, as predicted in “small-world” models; and finally a nested core composed of clusters connected via multiple independent paths. The authors then show how a firm’s position within the mesolevel structure is associated with demographic features such as age and industry and differences in the extent to which firms engage in multiplex and high-value exchanges. PMID:25418990

Modeling the coevolution of topology and traffic on weighted technological networks

NASA Astrophysics Data System (ADS)

Xie, Yan-Bo; Wang, Wen-Xu; Wang, Bing-Hong

2007-02-01

For many technological networks, the network structures and the traffic taking place on them mutually interact. The demands of traffic increment spur the evolution and growth of the networks to maintain their normal and efficient functioning. In parallel, a change of the network structure leads to redistribution of the traffic. In this paper, we perform an extensive numerical and analytical study, extending results of Wang [Phys. Rev. Lett. 94, 188702 (2005)]. By introducing a general strength-coupling interaction driven by the traffic increment between any pair of vertices, our model generates networks of scale-free distributions of strength, weight, and degree. In particular, the obtained nonlinear correlation between vertex strength and degree, and the disassortative property demonstrate that the model is capable of characterizing weighted technological networks. Moreover, the generated graphs possess both dense clustering structures and an anticorrelation between vertex clustering and degree, which are widely observed in real-world networks. The corresponding theoretical predictions are well consistent with simulation results.

Machine-learned cluster identification in high-dimensional data.

PubMed

Ultsch, Alfred; Lötsch, Jörn

2017-02-01

High-dimensional biomedical data are frequently clustered to identify subgroup structures pointing at distinct disease subtypes. It is crucial that the used cluster algorithm works correctly. However, by imposing a predefined shape on the clusters, classical algorithms occasionally suggest a cluster structure in homogenously distributed data or assign data points to incorrect clusters. We analyzed whether this can be avoided by using emergent self-organizing feature maps (ESOM). Data sets with different degrees of complexity were submitted to ESOM analysis with large numbers of neurons, using an interactive R-based bioinformatics tool. On top of the trained ESOM the distance structure in the high dimensional feature space was visualized in the form of a so-called U-matrix. Clustering results were compared with those provided by classical common cluster algorithms including single linkage, Ward and k-means. Ward clustering imposed cluster structures on cluster-less "golf ball", "cuboid" and "S-shaped" data sets that contained no structure at all (random data). Ward clustering also imposed structures on permuted real world data sets. By contrast, the ESOM/U-matrix approach correctly found that these data contain no cluster structure. However, ESOM/U-matrix was correct in identifying clusters in biomedical data truly containing subgroups. It was always correct in cluster structure identification in further canonical artificial data. Using intentionally simple data sets, it is shown that popular clustering algorithms typically used for biomedical data sets may fail to cluster data correctly, suggesting that they are also likely to perform erroneously on high dimensional biomedical data. The present analyses emphasized that generally established classical hierarchical clustering algorithms carry a considerable tendency to produce erroneous results. By contrast, unsupervised machine-learned analysis of cluster structures, applied using the ESOM/U-matrix method, is a viable, unbiased method to identify true clusters in the high-dimensional space of complex data. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Clustering of low-valence particles: structure and kinetics.

PubMed

Markova, Olga; Alberts, Jonathan; Munro, Edwin; Lenne, Pierre-François

2014-08-01

We compute the structure and kinetics of two systems of low-valence particles with three or six freely oriented bonds in two dimensions. The structure of clusters formed by trivalent particles is complex with loops and holes, while hexavalent particles self-organize into regular and compact structures. We identify the elementary structures which compose the clusters of trivalent particles. At initial stages of clustering, the clusters of trivalent particles grow with a power-law time dependence. Yet at longer times fusion and fission of clusters equilibrates and clusters form a heterogeneous phase with polydispersed sizes. These results emphasize the role of valence in the kinetics and stability of finite-size clusters.

Community detection in sequence similarity networks based on attribute clustering

DOE PAGES

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

2017-07-24

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less

Community detection in sequence similarity networks based on attribute clustering

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

Chowdhary, Janamejaya; Loeffler, Frank E.; Smith, Jeremy C.

Networks are powerful tools for the presentation and analysis of interactions in multi-component systems. A commonly studied mesoscopic feature of networks is their community structure, which arises from grouping together similar nodes into one community and dissimilar nodes into separate communities. Here in this paper, the community structure of protein sequence similarity networks is determined with a new method: Attribute Clustering Dependent Communities (ACDC). Sequence similarity has hitherto typically been quantified by the alignment score or its expectation value. However, pair alignments with the same score or expectation value cannot thus be differentiated. To overcome this deficiency, the method constructs,more » for pair alignments, an extended alignment metric, the link attribute vector, which includes the score and other alignment characteristics. Rescaling components of the attribute vectors qualitatively identifies a systematic variation of sequence similarity within protein superfamilies. The problem of community detection is then mapped to clustering the link attribute vectors, selection of an optimal subset of links and community structure refinement based on the partition density of the network. ACDC-predicted communities are found to be in good agreement with gold standard sequence databases for which the "ground truth" community structures (or families) are known. ACDC is therefore a community detection method for sequence similarity networks based entirely on pair similarity information. A serial implementation of ACDC is available from https://cmb.ornl.gov/resources/developments« less

Are polynuclear superhalogens without halogen atoms probable? A high-level ab initio case study on triple-bridged binuclear anions with cyanide ligands

NASA Astrophysics Data System (ADS)

Yin, Bing; Li, Teng; Li, Jin-Feng; Yu, Yang; Li, Jian-Li; Wen, Zhen-Yi; Jiang, Zhen-Yi

2014-03-01

The first theoretical exploration of superhalogen properties of polynuclear structures based on pseudohalogen ligand is reported here via a case study on eight triply-bridged [Mg2(CN)5]- clusters. From our high-level ab initio results, all these clusters are superhalogens due to their high vertical electron detachment energies (VDE), of which the largest value is 8.67 eV at coupled-cluster single double triple (CCSD(T)) level. Although outer valence Green's function results are consistent with CCSD(T) in most cases, it overestimates the VDEs of three anions dramatically by more than 1 eV. Therefore, the combined usage of several theoretical methods is important for the accuracy of purely theoretical prediction of superhalogen properties of new structures. Spatial distribution of the extra electron of high-VDE anions here indicates two features: remarkable aggregation on bridging CN units and non-negligible distribution on every CN unit. These two features lower the potential and kinetic energies of the extra electron respectively and thus lead to high VDE. Besides superhalogen properties, the structures, relative stabilities and thermodynamic stabilities with respect to detachment of CN-1 were also investigated for these anions. The collection of these results indicates that polynuclear structures based on pseudohalogen ligand are promising candidates for new superhalogens with enhanced properties.

Are polynuclear superhalogens without halogen atoms probable? A high-level ab initio case study on triple-bridged binuclear anions with cyanide ligands.

PubMed

Yin, Bing; Li, Teng; Li, Jin-Feng; Yu, Yang; Li, Jian-Li; Wen, Zhen-Yi; Jiang, Zhen-Yi

2014-03-07

The first theoretical exploration of superhalogen properties of polynuclear structures based on pseudohalogen ligand is reported here via a case study on eight triply-bridged [Mg2(CN)5](-) clusters. From our high-level ab initio results, all these clusters are superhalogens due to their high vertical electron detachment energies (VDE), of which the largest value is 8.67 eV at coupled-cluster single double triple (CCSD(T)) level. Although outer valence Green's function results are consistent with CCSD(T) in most cases, it overestimates the VDEs of three anions dramatically by more than 1 eV. Therefore, the combined usage of several theoretical methods is important for the accuracy of purely theoretical prediction of superhalogen properties of new structures. Spatial distribution of the extra electron of high-VDE anions here indicates two features: remarkable aggregation on bridging CN units and non-negligible distribution on every CN unit. These two features lower the potential and kinetic energies of the extra electron respectively and thus lead to high VDE. Besides superhalogen properties, the structures, relative stabilities and thermodynamic stabilities with respect to detachment of CN(-1) were also investigated for these anions. The collection of these results indicates that polynuclear structures based on pseudohalogen ligand are promising candidates for new superhalogens with enhanced properties.

Massive integration of diverse protein quality assessment methods to improve template based modeling in CASP11

PubMed Central

Cao, Renzhi; Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2015-01-01

Model evaluation and selection is an important step and a big challenge in template-based protein structure prediction. Individual model quality assessment methods designed for recognizing some specific properties of protein structures often fail to consistently select good models from a model pool because of their limitations. Therefore, combining multiple complimentary quality assessment methods is useful for improving model ranking and consequently tertiary structure prediction. Here, we report the performance and analysis of our human tertiary structure predictor (MULTICOM) based on the massive integration of 14 diverse complementary quality assessment methods that was successfully benchmarked in the 11th Critical Assessment of Techniques of Protein Structure prediction (CASP11). The predictions of MULTICOM for 39 template-based domains were rigorously assessed by six scoring metrics covering global topology of Cα trace, local all-atom fitness, side chain quality, and physical reasonableness of the model. The results show that the massive integration of complementary, diverse single-model and multi-model quality assessment methods can effectively leverage the strength of single-model methods in distinguishing quality variation among similar good models and the advantage of multi-model quality assessment methods of identifying reasonable average-quality models. The overall excellent performance of the MULTICOM predictor demonstrates that integrating a large number of model quality assessment methods in conjunction with model clustering is a useful approach to improve the accuracy, diversity, and consequently robustness of template-based protein structure prediction. PMID:26369671

ERRATUM: 'MAPPING THE GAS TURBULENCE IN THE COMA CLUSTER: PREDICTIONS FOR ASTRO-H'

NASA Technical Reports Server (NTRS)

Zuhone, J. A.; Markevitch, M.; Zhuravleva, I.

2016-01-01

The published version of this paper contained an error in Figure 5. This figure is intended to show the effect on the structure function of subtracting the bias induced by the statistical and systematic errors on the line shift. The filled circles show the bias-subtracted structure function. The positions of these points in the left panel of the original figure were calculated incorrectly. The figure is reproduced below (with the original caption) with the correct values for the bias-subtracted structure function. No other computations or figures in the original manuscript are affected.

Spatial complementarity and the coexistence of species.

PubMed

Velázquez, Jorge; Garrahan, Juan P; Eichhorn, Markus P

2014-01-01

Coexistence of apparently similar species remains an enduring paradox in ecology. Spatial structure has been predicted to enable coexistence even when population-level models predict competitive exclusion if it causes each species to limit its own population more than that of its competitor. Nevertheless, existing hypotheses conflict with regard to whether clustering favours or precludes coexistence. The spatial segregation hypothesis predicts that in clustered populations the frequency of intra-specific interactions will be increased, causing each species to be self-limiting. Alternatively, individuals of the same species might compete over greater distances, known as heteromyopia, breaking down clusters and opening space for a second species to invade. In this study we create an individual-based model in homogeneous two-dimensional space for two putative sessile species differing only in their demographic rates and the range and strength of their competitive interactions. We fully characterise the parameter space within which coexistence occurs beyond population-level predictions, thereby revealing a region of coexistence generated by a previously-unrecognised process which we term the triadic mechanism. Here coexistence occurs due to the ability of a second generation of offspring of the rarer species to escape competition from their ancestors. We diagnose the conditions under which each of three spatial coexistence mechanisms operates and their characteristic spatial signatures. Deriving insights from a novel metric - ecological pressure - we demonstrate that coexistence is not solely determined by features of the numerically-dominant species. This results in a common framework for predicting, given any pair of species and knowledge of the relevant parameters, whether they will coexist, the mechanism by which they will do so, and the resultant spatial pattern of the community. Spatial coexistence arises from complementary combinations of traits in each species rather than solely through self-limitation.

Spatial Complementarity and the Coexistence of Species

PubMed Central

Velázquez, Jorge; Garrahan, Juan P.; Eichhorn, Markus P.

2014-01-01

Coexistence of apparently similar species remains an enduring paradox in ecology. Spatial structure has been predicted to enable coexistence even when population-level models predict competitive exclusion if it causes each species to limit its own population more than that of its competitor. Nevertheless, existing hypotheses conflict with regard to whether clustering favours or precludes coexistence. The spatial segregation hypothesis predicts that in clustered populations the frequency of intra-specific interactions will be increased, causing each species to be self-limiting. Alternatively, individuals of the same species might compete over greater distances, known as heteromyopia, breaking down clusters and opening space for a second species to invade. In this study we create an individual-based model in homogeneous two-dimensional space for two putative sessile species differing only in their demographic rates and the range and strength of their competitive interactions. We fully characterise the parameter space within which coexistence occurs beyond population-level predictions, thereby revealing a region of coexistence generated by a previously-unrecognised process which we term the triadic mechanism. Here coexistence occurs due to the ability of a second generation of offspring of the rarer species to escape competition from their ancestors. We diagnose the conditions under which each of three spatial coexistence mechanisms operates and their characteristic spatial signatures. Deriving insights from a novel metric — ecological pressure — we demonstrate that coexistence is not solely determined by features of the numerically-dominant species. This results in a common framework for predicting, given any pair of species and knowledge of the relevant parameters, whether they will coexist, the mechanism by which they will do so, and the resultant spatial pattern of the community. Spatial coexistence arises from complementary combinations of traits in each species rather than solely through self-limitation. PMID:25532018

Studying the varied shapes of gold clusters by an elegant optimization algorithm that hybridizes the density functional tight-binding theory and the density functional theory

NASA Astrophysics Data System (ADS)

Yen, Tsung-Wen; Lim, Thong-Leng; Yoon, Tiem-Leong; Lai, S. K.

2017-11-01

We combined a new parametrized density functional tight-binding (DFTB) theory (Fihey et al. 2015) with an unbiased modified basin hopping (MBH) optimization algorithm (Yen and Lai 2015) and applied it to calculate the lowest energy structures of Au clusters. From the calculated topologies and their conformational changes, we find that this DFTB/MBH method is a necessary procedure for a systematic study of the structural development of Au clusters but is somewhat insufficient for a quantitative study. As a result, we propose an extended hybridized algorithm. This improved algorithm proceeds in two steps. In the first step, the DFTB theory is employed to calculate the total energy of the cluster and this step (through running DFTB/MBH optimization for given Monte-Carlo steps) is meant to efficiently bring the Au cluster near to the region of the lowest energy minimum since the cluster as a whole has explicitly considered the interactions of valence electrons with ions, albeit semi-quantitatively. Then, in the second succeeding step, the energy-minimum searching process will continue with a skilledly replacement of the energy function calculated by the DFTB theory in the first step by one calculated in the full density functional theory (DFT). In these subsequent calculations, we couple the DFT energy also with the MBH strategy and proceed with the DFT/MBH optimization until the lowest energy value is found. We checked that this extended hybridized algorithm successfully predicts the twisted pyramidal structure for the Au40 cluster and correctly confirms also the linear shape of C8 which our previous DFTB/MBH method failed to do so. Perhaps more remarkable is the topological growth of Aun: it changes from a planar (n =3-11) → an oblate-like cage (n =12-15) → a hollow-shape cage (n =16-18) and finally a pyramidal-like cage (n =19, 20). These varied forms of the cluster's shapes are consistent with those reported in the literature.

Analysis of local bond-orientational order for liquid gallium at ambient pressure: Two types of cluster structures.

PubMed

Chen, Lin-Yuan; Tang, Ping-Han; Wu, Ten-Ming

2016-07-14

In terms of the local bond-orientational order (LBOO) parameters, a cluster approach to analyze local structures of simple liquids was developed. In this approach, a cluster is defined as a combination of neighboring seeds having at least nb local-orientational bonds and their nearest neighbors, and a cluster ensemble is a collection of clusters with a specified nb and number of seeds ns. This cluster analysis was applied to investigate the microscopic structures of liquid Ga at ambient pressure (AP). The liquid structures studied were generated through ab initio molecular dynamics simulations. By scrutinizing the static structure factors (SSFs) of cluster ensembles with different combinations of nb and ns, we found that liquid Ga at AP contained two types of cluster structures, one characterized by sixfold orientational symmetry and the other showing fourfold orientational symmetry. The SSFs of cluster structures with sixfold orientational symmetry were akin to the SSF of a hard-sphere fluid. On the contrary, the SSFs of cluster structures showing fourfold orientational symmetry behaved similarly as the anomalous SSF of liquid Ga at AP, which is well known for exhibiting a high-q shoulder. The local structures of a highly LBOO cluster whose SSF displayed a high-q shoulder were found to be more similar to the structure of β-Ga than those of other solid phases of Ga. More generally, the cluster structures showing fourfold orientational symmetry have an inclination to resemble more to β-Ga.

Formalized classification of moss litters in swampy spruce forests of intermontane depressions of Kuznetsk Alatau

NASA Astrophysics Data System (ADS)

Efremova, T. T.; Avrova, A. F.; Efremov, S. P.

2016-09-01

The approaches of multivariate statistics have been used for the numerical classification of morphogenetic types of moss litters in swampy spruce forests according to their physicochemical properties (the ash content, decomposition degree, bulk density, pH, mass, and thickness). Three clusters of moss litters— peat, peaty, and high-ash peaty—have been specified. The functions of classification for identification of new objects have been calculated and evaluated. The degree of decomposition and the ash content are the main classification parameters of litters, though all other characteristics are also statistically significant. The final prediction accuracy of the assignment of a litter to a particular cluster is 86%. Two leading factors participating in the clustering of litters have been determined. The first factor—the degree of transformation of plant remains (quality)—specifies 49% of the total variance, and the second factor—the accumulation rate (quantity)— specifies 26% of the total variance. The morphogenetic structure and physicochemical properties of the clusters of moss litters are characterized.

First results from the IllustrisTNG simulations: matter and galaxy clustering

NASA Astrophysics Data System (ADS)

Springel, Volker; Pakmor, Rüdiger; Pillepich, Annalisa; Weinberger, Rainer; Nelson, Dylan; Hernquist, Lars; Vogelsberger, Mark; Genel, Shy; Torrey, Paul; Marinacci, Federico; Naiman, Jill

2018-03-01

Hydrodynamical simulations of galaxy formation have now reached sufficient volume to make precision predictions for clustering on cosmologically relevant scales. Here, we use our new IllustrisTNG simulations to study the non-linear correlation functions and power spectra of baryons, dark matter, galaxies, and haloes over an exceptionally large range of scales. We find that baryonic effects increase the clustering of dark matter on small scales and damp the total matter power spectrum on scales up to k ˜ 10 h Mpc-1 by 20 per cent. The non-linear two-point correlation function of the stellar mass is close to a power-law over a wide range of scales and approximately invariant in time from very high redshift to the present. The two-point correlation function of the simulated galaxies agrees well with Sloan Digital Sky Survey at its mean redshift z ≃ 0.1, both as a function of stellar mass and when split according to galaxy colour, apart from a mild excess in the clustering of red galaxies in the stellar mass range of109-1010 h-2 M⊙. Given this agreement, the TNG simulations can make valuable theoretical predictions for the clustering bias of different galaxy samples. We find that the clustering length of the galaxy autocorrelation function depends strongly on stellar mass and redshift. Its power-law slope γ is nearly invariant with stellar mass, but declines from γ ˜ 1.8 at redshift z = 0 to γ ˜ 1.6 at redshift z ˜ 1, beyond which the slope steepens again. We detect significant scale dependences in the bias of different observational tracers of large-scale structure, extending well into the range of the baryonic acoustic oscillations and causing nominal (yet fortunately correctable) shifts of the acoustic peaks of around ˜ 5 per cent.

Stable clustering and the resolution of dissipationless cosmological N-body simulations

NASA Astrophysics Data System (ADS)

Benhaiem, David; Joyce, Michael; Sylos Labini, Francesco

2017-10-01

The determination of the resolution of cosmological N-body simulations, I.e. the range of scales in which quantities measured in them represent accurately the continuum limit, is an important open question. We address it here using scale-free models, for which self-similarity provides a powerful tool to control resolution. Such models also provide a robust testing ground for the so-called stable clustering approximation, which gives simple predictions for them. Studying large N-body simulations of such models with different force smoothing, we find that these two issues are in fact very closely related: our conclusion is that the accuracy of two-point statistics in the non-linear regime starts to degrade strongly around the scale at which their behaviour deviates from that predicted by the stable clustering hypothesis. Physically the association of the two scales is in fact simple to understand: stable clustering fails to be a good approximation when there are strong interactions of structures (in particular merging) and it is precisely such non-linear processes which are sensitive to fluctuations at the smaller scales affected by discretization. Resolution may be further degraded if the short distance gravitational smoothing scale is larger than the scale to which stable clustering can propagate. We examine in detail the very different conclusions of studies by Smith et al. and Widrow et al. and find that the strong deviations from stable clustering reported by these works are the results of over-optimistic assumptions about scales resolved accurately by the measured power spectra, and the reliance on Fourier space analysis. We emphasize the much poorer resolution obtained with the power spectrum compared to the two-point correlation function.