Adaptive multi-resolution Modularity for detecting communities in networks
NASA Astrophysics Data System (ADS)
Chen, Shi; Wang, Zhi-Zhong; Bao, Mei-Hua; Tang, Liang; Zhou, Ji; Xiang, Ju; Li, Jian-Ming; Yi, Chen-He
2018-02-01
Community structure is a common topological property of complex networks, which attracted much attention from various fields. Optimizing quality functions for community structures is a kind of popular strategy for community detection, such as Modularity optimization. Here, we introduce a general definition of Modularity, by which several classical (multi-resolution) Modularity can be derived, and then propose a kind of adaptive (multi-resolution) Modularity that can combine the advantages of different Modularity. By applying the Modularity to various synthetic and real-world networks, we study the behaviors of the methods, showing the validity and advantages of the multi-resolution Modularity in community detection. The adaptive Modularity, as a kind of multi-resolution method, can naturally solve the first-type limit of Modularity and detect communities at different scales; it can quicken the disconnecting of communities and delay the breakup of communities in heterogeneous networks; and thus it is expected to generate the stable community structures in networks more effectively and have stronger tolerance against the second-type limit of Modularity.
Convergent evolution of modularity in metabolic networks through different community structures.
Zhou, Wanding; Nakhleh, Luay
2012-09-14
It has been reported that the modularity of metabolic networks of bacteria is closely related to the variability of their living habitats. However, given the dependency of the modularity score on the community structure, it remains unknown whether organisms achieve certain modularity via similar or different community structures. In this work, we studied the relationship between similarities in modularity scores and similarities in community structures of the metabolic networks of 1021 species. Both similarities are then compared against the genetic distances. We revisited the association between modularity and variability of the microbial living environments and extended the analysis to other aspects of their life style such as temperature and oxygen requirements. We also tested both topological and biological intuition of the community structures identified and investigated the extent of their conservation with respect to the taxonomy. We find that similar modularities are realized by different community structures. We find that such convergent evolution of modularity is closely associated with the number of (distinct) enzymes in the organism's metabolome, a consequence of different life styles of the species. We find that the order of modularity is the same as the order of the number of the enzymes under the classification based on the temperature preference but not on the oxygen requirement. Besides, inspection of modularity-based communities reveals that these communities are graph-theoretically meaningful yet not reflective of specific biological functions. From an evolutionary perspective, we find that the community structures are conserved only at the level of kingdoms. Our results call for more investigation into the interplay between evolution and modularity: how evolution shapes modularity, and how modularity affects evolution (mainly in terms of fitness and evolvability). Further, our results call for exploring new measures of modularity and network communities that better correspond to functional categorizations.
Convergent evolution of modularity in metabolic networks through different community structures
2012-01-01
Background It has been reported that the modularity of metabolic networks of bacteria is closely related to the variability of their living habitats. However, given the dependency of the modularity score on the community structure, it remains unknown whether organisms achieve certain modularity via similar or different community structures. Results In this work, we studied the relationship between similarities in modularity scores and similarities in community structures of the metabolic networks of 1021 species. Both similarities are then compared against the genetic distances. We revisited the association between modularity and variability of the microbial living environments and extended the analysis to other aspects of their life style such as temperature and oxygen requirements. We also tested both topological and biological intuition of the community structures identified and investigated the extent of their conservation with respect to the taxomony. Conclusions We find that similar modularities are realized by different community structures. We find that such convergent evolution of modularity is closely associated with the number of (distinct) enzymes in the organism’s metabolome, a consequence of different life styles of the species. We find that the order of modularity is the same as the order of the number of the enzymes under the classification based on the temperature preference but not on the oxygen requirement. Besides, inspection of modularity-based communities reveals that these communities are graph-theoretically meaningful yet not reflective of specific biological functions. From an evolutionary perspective, we find that the community structures are conserved only at the level of kingdoms. Our results call for more investigation into the interplay between evolution and modularity: how evolution shapes modularity, and how modularity affects evolution (mainly in terms of fitness and evolvability). Further, our results call for exploring new measures of modularity and network communities that better correspond to functional categorizations. PMID:22974099
Zhang, Pan; Moore, Cristopher
2014-01-01
Modularity is a popular measure of community structure. However, maximizing the modularity can lead to many competing partitions, with almost the same modularity, that are poorly correlated with each other. It can also produce illusory ‘‘communities’’ in random graphs where none exist. We address this problem by using the modularity as a Hamiltonian at finite temperature and using an efficient belief propagation algorithm to obtain the consensus of many partitions with high modularity, rather than looking for a single partition that maximizes it. We show analytically and numerically that the proposed algorithm works all of the way down to the detectability transition in networks generated by the stochastic block model. It also performs well on real-world networks, revealing large communities in some networks where previous work has claimed no communities exist. Finally we show that by applying our algorithm recursively, subdividing communities until no statistically significant subcommunities can be found, we can detect hierarchical structure in real-world networks more efficiently than previous methods. PMID:25489096
Subcommunities and Their Mutual Relationships in a Transaction Network
NASA Astrophysics Data System (ADS)
Iino, T.; Iyetomi, H.
We investigate a Japanese transaction network consisting ofabout 800 thousand firms (nodes) and four million business relations (links) with focus on its modular structure. Communities detected by maximizing modularity often are dominated by firms with common features or behaviors in the network, such as characterized by regions or industry sectors. However, it is well known that the modularity optimization approach has a resolution limit problem, that is, it fails in identifying fine communities buried in large communities. To unfold such hidden structures, we apply the community detection to each of subnetworks formed by isolating those communities from the whole body. Subcommunities thus identified are composed of firms with finer regions, more specified sectors or business affiliations. Also we introduce a new idea of reduced modularity matrix to measure the strength of relations between (sub)communities.
Optimal multi-community network modularity for information diffusion
NASA Astrophysics Data System (ADS)
Wu, Jiaocan; Du, Ruping; Zheng, Yingying; Liu, Dong
2016-02-01
Studies demonstrate that community structure plays an important role in information spreading recently. In this paper, we investigate the impact of multi-community structure on information diffusion with linear threshold model. We utilize extended GN network that contains four communities and analyze dynamic behaviors of information that spreads on it. And we discover the optimal multi-community network modularity for information diffusion based on the social reinforcement. Results show that, within the appropriate range, multi-community structure will facilitate information diffusion instead of hindering it, which accords with the results derived from two-community network.
Z-Score-Based Modularity for Community Detection in Networks
Miyauchi, Atsushi; Kawase, Yasushi
2016-01-01
Identifying community structure in networks is an issue of particular interest in network science. The modularity introduced by Newman and Girvan is the most popular quality function for community detection in networks. In this study, we identify a problem in the concept of modularity and suggest a solution to overcome this problem. Specifically, we obtain a new quality function for community detection. We refer to the function as Z-modularity because it measures the Z-score of a given partition with respect to the fraction of the number of edges within communities. Our theoretical analysis shows that Z-modularity mitigates the resolution limit of the original modularity in certain cases. Computational experiments using both artificial networks and well-known real-world networks demonstrate the validity and reliability of the proposed quality function. PMID:26808270
Optimal Network Modularity for Information Diffusion
NASA Astrophysics Data System (ADS)
Nematzadeh, Azadeh; Ferrara, Emilio; Flammini, Alessandro; Ahn, Yong-Yeol
2014-08-01
We investigate the impact of community structure on information diffusion with the linear threshold model. Our results demonstrate that modular structure may have counterintuitive effects on information diffusion when social reinforcement is present. We show that strong communities can facilitate global diffusion by enhancing local, intracommunity spreading. Using both analytic approaches and numerical simulations, we demonstrate the existence of an optimal network modularity, where global diffusion requires the minimal number of early adopters.
NASA Astrophysics Data System (ADS)
Makhtar, Siti Noormiza; Senik, Mohd Harizal
2018-02-01
The availability of massive amount of neuronal signals are attracting widespread interest in functional connectivity analysis. Functional interactions estimated by multivariate partial coherence analysis in the frequency domain represent the connectivity strength in this study. Modularity is a network measure for the detection of community structure in network analysis. The discovery of community structure for the functional neuronal network was implemented on multi-electrode array (MEA) signals recorded from hippocampal regions in isoflurane-anaesthetized Lister-hooded rats. The analysis is expected to show modularity changes before and after local unilateral kainic acid (KA)-induced epileptiform activity. The result is presented using color-coded graphic of conditional modularity measure for 19 MEA nodes. This network is separated into four sub-regions to show the community detection within each sub-region. The results show that classification of neuronal signals into the inter- and intra-modular nodes is feasible using conditional modularity analysis. Estimation of segregation properties using conditional modularity analysis may provide further information about functional connectivity from MEA data.
A spectral method to detect community structure based on distance modularity matrix
NASA Astrophysics Data System (ADS)
Yang, Jin-Xuan; Zhang, Xiao-Dong
2017-08-01
There are many community organizations in social and biological networks. How to identify these community structure in complex networks has become a hot issue. In this paper, an algorithm to detect community structure of networks is proposed by using spectra of distance modularity matrix. The proposed algorithm focuses on the distance of vertices within communities, rather than the most weakly connected vertex pairs or number of edges between communities. The experimental results show that our method achieves better effectiveness to identify community structure for a variety of real-world networks and computer generated networks with a little more time-consumption.
Evolutionary method for finding communities in bipartite networks.
Zhan, Weihua; Zhang, Zhongzhi; Guan, Jihong; Zhou, Shuigeng
2011-06-01
An important step in unveiling the relation between network structure and dynamics defined on networks is to detect communities, and numerous methods have been developed separately to identify community structure in different classes of networks, such as unipartite networks, bipartite networks, and directed networks. Here, we show that the finding of communities in such networks can be unified in a general framework-detection of community structure in bipartite networks. Moreover, we propose an evolutionary method for efficiently identifying communities in bipartite networks. To this end, we show that both unipartite and directed networks can be represented as bipartite networks, and their modularity is completely consistent with that for bipartite networks, the detection of modular structure on which can be reformulated as modularity maximization. To optimize the bipartite modularity, we develop a modified adaptive genetic algorithm (MAGA), which is shown to be especially efficient for community structure detection. The high efficiency of the MAGA is based on the following three improvements we make. First, we introduce a different measure for the informativeness of a locus instead of the standard deviation, which can exactly determine which loci mutate. This measure is the bias between the distribution of a locus over the current population and the uniform distribution of the locus, i.e., the Kullback-Leibler divergence between them. Second, we develop a reassignment technique for differentiating the informative state a locus has attained from the random state in the initial phase. Third, we present a modified mutation rule which by incorporating related operations can guarantee the convergence of the MAGA to the global optimum and can speed up the convergence process. Experimental results show that the MAGA outperforms existing methods in terms of modularity for both bipartite and unipartite networks.
Detecting communities using asymptotical surprise
NASA Astrophysics Data System (ADS)
Traag, V. A.; Aldecoa, R.; Delvenne, J.-C.
2015-08-01
Nodes in real-world networks are repeatedly observed to form dense clusters, often referred to as communities. Methods to detect these groups of nodes usually maximize an objective function, which implicitly contains the definition of a community. We here analyze a recently proposed measure called surprise, which assesses the quality of the partition of a network into communities. In its current form, the formulation of surprise is rather difficult to analyze. We here therefore develop an accurate asymptotic approximation. This allows for the development of an efficient algorithm for optimizing surprise. Incidentally, this leads to a straightforward extension of surprise to weighted graphs. Additionally, the approximation makes it possible to analyze surprise more closely and compare it to other methods, especially modularity. We show that surprise is (nearly) unaffected by the well-known resolution limit, a particular problem for modularity. However, surprise may tend to overestimate the number of communities, whereas they may be underestimated by modularity. In short, surprise works well in the limit of many small communities, whereas modularity works better in the limit of few large communities. In this sense, surprise is more discriminative than modularity and may find communities where modularity fails to discern any structure.
Estimating the resolution limit of the map equation in community detection
NASA Astrophysics Data System (ADS)
Kawamoto, Tatsuro; Rosvall, Martin
2015-01-01
A community detection algorithm is considered to have a resolution limit if the scale of the smallest modules that can be resolved depends on the size of the analyzed subnetwork. The resolution limit is known to prevent some community detection algorithms from accurately identifying the modular structure of a network. In fact, any global objective function for measuring the quality of a two-level assignment of nodes into modules must have some sort of resolution limit or an external resolution parameter. However, it is yet unknown how the resolution limit affects the so-called map equation, which is known to be an efficient objective function for community detection. We derive an analytical estimate and conclude that the resolution limit of the map equation is set by the total number of links between modules instead of the total number of links in the full network as for modularity. This mechanism makes the resolution limit much less restrictive for the map equation than for modularity; in practice, it is orders of magnitudes smaller. Furthermore, we argue that the effect of the resolution limit often results from shoehorning multilevel modular structures into two-level descriptions. As we show, the hierarchical map equation effectively eliminates the resolution limit for networks with nested multilevel modular structures.
Clustering algorithm for determining community structure in large networks
NASA Astrophysics Data System (ADS)
Pujol, Josep M.; Béjar, Javier; Delgado, Jordi
2006-07-01
We propose an algorithm to find the community structure in complex networks based on the combination of spectral analysis and modularity optimization. The clustering produced by our algorithm is as accurate as the best algorithms on the literature of modularity optimization; however, the main asset of the algorithm is its efficiency. The best match for our algorithm is Newman’s fast algorithm, which is the reference algorithm for clustering in large networks due to its efficiency. When both algorithms are compared, our algorithm outperforms the fast algorithm both in efficiency and accuracy of the clustering, in terms of modularity. Thus, the results suggest that the proposed algorithm is a good choice to analyze the community structure of medium and large networks in the range of tens and hundreds of thousand vertices.
A new hierarchical method to find community structure in networks
NASA Astrophysics Data System (ADS)
Saoud, Bilal; Moussaoui, Abdelouahab
2018-04-01
Community structure is very important to understand a network which represents a context. Many community detection methods have been proposed like hierarchical methods. In our study, we propose a new hierarchical method for community detection in networks based on genetic algorithm. In this method we use genetic algorithm to split a network into two networks which maximize the modularity. Each new network represents a cluster (community). Then we repeat the splitting process until we get one node at each cluster. We use the modularity function to measure the strength of the community structure found by our method, which gives us an objective metric for choosing the number of communities into which a network should be divided. We demonstrate that our method are highly effective at discovering community structure in both computer-generated and real-world network data.
A network function-based definition of communities in complex networks.
Chauhan, Sanjeev; Girvan, Michelle; Ott, Edward
2012-09-01
We consider an alternate definition of community structure that is functionally motivated. We define network community structure based on the function the network system is intended to perform. In particular, as a specific example of this approach, we consider communities whose function is enhanced by the ability to synchronize and/or by resilience to node failures. Previous work has shown that, in many cases, the largest eigenvalue of the network's adjacency matrix controls the onset of both synchronization and percolation processes. Thus, for networks whose functional performance is dependent on these processes, we propose a method that divides a given network into communities based on maximizing a function of the largest eigenvalues of the adjacency matrices of the resulting communities. We also explore the differences between the partitions obtained by our method and the modularity approach (which is based solely on consideration of network structure). We do this for several different classes of networks. We find that, in many cases, modularity-based partitions do almost as well as our function-based method in finding functional communities, even though modularity does not specifically incorporate consideration of function.
To cut or not to cut? Assessing the modular structure of brain networks.
Chang, Yu-Teng; Pantazis, Dimitrios; Leahy, Richard M
2014-05-01
A wealth of methods has been developed to identify natural divisions of brain networks into groups or modules, with one of the most prominent being modularity. Compared with the popularity of methods to detect community structure, only a few methods exist to statistically control for spurious modules, relying almost exclusively on resampling techniques. It is well known that even random networks can exhibit high modularity because of incidental concentration of edges, even though they have no underlying organizational structure. Consequently, interpretation of community structure is confounded by the lack of principled and computationally tractable approaches to statistically control for spurious modules. In this paper we show that the modularity of random networks follows a transformed version of the Tracy-Widom distribution, providing for the first time a link between module detection and random matrix theory. We compute parametric formulas for the distribution of modularity for random networks as a function of network size and edge variance, and show that we can efficiently control for false positives in brain and other real-world networks. Copyright © 2014 Elsevier Inc. All rights reserved.
Impact of individual interest shift on information dissemination in modular networks
NASA Astrophysics Data System (ADS)
Zhao, Narisa; Cui, Xuelian
2017-01-01
Social networks exhibit strong community structure. Many researches have been done to explore the impacts of community structure on information diffusion but few combined with human behaviors together. In this paper, we focus on how the individual interests' changing behavior impacts the dynamics of information propagation. Firstly, we propose an information dissemination model considering both the community structure and individual interest shift where social reinforcement and time decaying are taken into account. The accuracy of the model is evaluated by comparing the simulation and theoretical results. Further, the numerical results illustrate that both the community structure and the interests changing behavior have effects on the outbreak size of the information dissemination. Specially, lower modularity and higher community connection density will accelerate the speed of information propagation especially when the information maximal lifetime is shorter. In addition, the changes of individual interests in the message have a great impact on the final density of the received through increasing or decreasing the number of satisfied individuals directly. What is more, our findings suggest that when the modularity of the network is higher and the community clustering coefficient is lower individual interest shift behavior will have a heavier effect on the spread scope.
NASA Astrophysics Data System (ADS)
Zhu, Jiajing; Liu, Yongguo; Zhang, Yun; Liu, Xiaofeng; Xiao, Yonghua; Wang, Shidong; Wu, Xindong
2017-11-01
Community structure is one of the most important properties in networks, in which a node shares its most connections with the others in the same community. On the contrary, the anti-community structure means the nodes in the same group have few or no connections with each other. In Traditional Chinese Medicine (TCM), the incompatibility problem of herbs is a challenge to the clinical medication safety. In this paper, we propose a new anti-community detection algorithm, Random non-nEighboring nOde expansioN (REON), to find anti-communities in networks, in which a new evaluation criterion, anti-modularity, is designed to measure the quality of the obtained anti-community structure. In order to establish anti-communities in REON, we expand the node set by non-neighboring node expansion and regard the node set with the highest anti-modularity as an anti-community. Inspired by the phenomenon that the node with higher degree has greater contribution to the anti-modularity, an improved algorithm called REONI is developed by expanding node set by the non-neighboring node with the maximum degree, which greatly enhances the efficiency of REON. Experiments on synthetic and real-world networks demonstrate the superiority of the proposed algorithms over the existing methods. In addition, by applying REONI to the herb network, we find that it can discover incompatible herb combinations.
Online Community Detection for Large Complex Networks
Pan, Gang; Zhang, Wangsheng; Wu, Zhaohui; Li, Shijian
2014-01-01
Complex networks describe a wide range of systems in nature and society. To understand complex networks, it is crucial to investigate their community structure. In this paper, we develop an online community detection algorithm with linear time complexity for large complex networks. Our algorithm processes a network edge by edge in the order that the network is fed to the algorithm. If a new edge is added, it just updates the existing community structure in constant time, and does not need to re-compute the whole network. Therefore, it can efficiently process large networks in real time. Our algorithm optimizes expected modularity instead of modularity at each step to avoid poor performance. The experiments are carried out using 11 public data sets, and are measured by two criteria, modularity and NMI (Normalized Mutual Information). The results show that our algorithm's running time is less than the commonly used Louvain algorithm while it gives competitive performance. PMID:25061683
A novel community detection method in bipartite networks
NASA Astrophysics Data System (ADS)
Zhou, Cangqi; Feng, Liang; Zhao, Qianchuan
2018-02-01
Community structure is a common and important feature in many complex networks, including bipartite networks, which are used as a standard model for many empirical networks comprised of two types of nodes. In this paper, we propose a two-stage method for detecting community structure in bipartite networks. Firstly, we extend the widely-used Louvain algorithm to bipartite networks. The effectiveness and efficiency of the Louvain algorithm have been proved by many applications. However, there lacks a Louvain-like algorithm specially modified for bipartite networks. Based on bipartite modularity, a measure that extends unipartite modularity and that quantifies the strength of partitions in bipartite networks, we fill the gap by developing the Bi-Louvain algorithm that iteratively groups the nodes in each part by turns. This algorithm in bipartite networks often produces a balanced network structure with equal numbers of two types of nodes. Secondly, for the balanced network yielded by the first algorithm, we use an agglomerative clustering method to further cluster the network. We demonstrate that the calculation of the gain of modularity of each aggregation, and the operation of joining two communities can be compactly calculated by matrix operations for all pairs of communities simultaneously. At last, a complete hierarchical community structure is unfolded. We apply our method to two benchmark data sets and a large-scale data set from an e-commerce company, showing that it effectively identifies community structure in bipartite networks.
Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks
NASA Astrophysics Data System (ADS)
Cui, Yaozu; Wang, Xingyuan; Eustace, Justine
2014-12-01
Community structure is a common phenomenon in complex networks, and it has been shown that some communities in complex networks often overlap each other. So in this paper we propose a new algorithm to detect overlapping community structure in complex networks. To identify the overlapping community structure, our algorithm firstly extracts fully connected sub-graphs which are maximal sub-graphs from original networks. Then two maximal sub-graphs having the key pair-vertices can be merged into a new larger sub-graph using some belonging degree functions. Furthermore we extend the modularity function to evaluate the proposed algorithm. In addition, overlapping nodes between communities are founded successfully. Finally we report the comparison between the modularity and the computational complexity of the proposed algorithm with some other existing algorithms. The experimental results show that the proposed algorithm gives satisfactory results.
Network community structure and loop coefficient method
NASA Astrophysics Data System (ADS)
Vragović, I.; Louis, E.
2006-07-01
A modular structure, in which groups of tightly connected nodes could be resolved as separate entities, is a property that can be found in many complex networks. In this paper, we propose a algorithm for identifying communities in networks. It is based on a local measure, so-called loop coefficient that is a generalization of the clustering coefficient. Nodes with a large loop coefficient tend to be core inner community nodes, while other vertices are usually peripheral sites at the borders of communities. Our method gives satisfactory results for both artificial and real-world graphs, if they have a relatively pronounced modular structure. This type of algorithm could open a way of interpreting the role of nodes in communities in terms of the local loop coefficient, and could be used as a complement to other methods.
Characterizing the role benthos plays in large coastal seas and estuaries: A modular approach
Tenore, K.R.; Zajac, R.N.; Terwin, J.; Andrade, F.; Blanton, J.; Boynton, W.; Carey, D.; Diaz, R.; Holland, Austin F.; Lopez-Jamar, E.; Montagna, P.; Nichols, F.; Rosenberg, R.; Queiroga, H.; Sprung, M.; Whitlatch, R.B.
2006-01-01
Ecologists studying coastal and estuarine benthic communities have long taken a macroecological view, by relating benthic community patterns to environmental factors across several spatial scales. Although many general ecological patterns have been established, often a significant amount of the spatial and temporal variation in soft-sediment communities within and among systems remains unexplained. Here we propose a framework that may aid in unraveling the complex influence of environmental factors associated with the different components of coastal systems (i.e. the terrestrial and benthic landscapes, and the hydrological seascape) on benthic communities, and use this information to assess the role played by benthos in coastal ecosystems. A primary component of the approach is the recognition of system modules (e.g. marshes, dendritic systems, tidal rivers, enclosed basins, open bays, lagoons). The modules may differentially interact with key forcing functions (e.g. temperature, salinity, currents) that influence system processes and in turn benthic responses and functions. Modules may also constrain benthic characteristics and related processes within certain ecological boundaries and help explain their overall spatio-temporal variation. We present an example of how benthic community characteristics are related to the modular structure of 14 coastal seas and estuaries, and show that benthic functional group composition is significantly related to the modular structure of these systems. We also propose a framework for exploring the role of benthic communities in coastal systems using this modular approach and offer predictions of how benthic communities may vary depending on the modular composition and characteristics of a coastal system. ?? 2006 Elsevier B.V. All rights reserved.
Beckett, Stephen J.; Williams, Hywel T. P.
2013-01-01
Phage and their bacterial hosts are the most diverse and abundant biological entities in the oceans, where their interactions have a major impact on marine ecology and ecosystem function. The structure of interaction networks for natural phage–bacteria communities offers insight into their coevolutionary origin. At small phylogenetic scales, observed communities typically show a nested structure, in which both hosts and phages can be ranked by their range of resistance and infectivity, respectively. A qualitatively different multi-scale structure is seen at larger phylogenetic scales; a natural assemblage sampled from the Atlantic Ocean displays large-scale modularity and local nestedness within each module. Here, we show that such ‘nested-modular’ interaction networks can be produced by a simple model of host–phage coevolution in which infection depends on genetic matching. Negative frequency-dependent selection causes diversification of hosts (to escape phages) and phages (to track their evolving hosts). This creates a diverse community of bacteria and phage, maintained by kill-the-winner ecological dynamics. When the resulting communities are visualized as bipartite networks of who infects whom, they show the nested-modular structure characteristic of the Atlantic sample. The statistical significance and strength of this observation varies depending on whether the interaction networks take into account the density of the interacting strains, with implications for interpretation of interaction networks constructed by different methods. Our results suggest that the apparently complex community structures associated with marine bacteria and phage may arise from relatively simple coevolutionary origins. PMID:24516719
NASA Astrophysics Data System (ADS)
Perotti, Juan Ignacio; Tessone, Claudio Juan; Caldarelli, Guido
2015-12-01
The quest for a quantitative characterization of community and modular structure of complex networks produced a variety of methods and algorithms to classify different networks. However, it is not clear if such methods provide consistent, robust, and meaningful results when considering hierarchies as a whole. Part of the problem is the lack of a similarity measure for the comparison of hierarchical community structures. In this work we give a contribution by introducing the hierarchical mutual information, which is a generalization of the traditional mutual information and makes it possible to compare hierarchical partitions and hierarchical community structures. The normalized version of the hierarchical mutual information should behave analogously to the traditional normalized mutual information. Here the correct behavior of the hierarchical mutual information is corroborated on an extensive battery of numerical experiments. The experiments are performed on artificial hierarchies and on the hierarchical community structure of artificial and empirical networks. Furthermore, the experiments illustrate some of the practical applications of the hierarchical mutual information, namely the comparison of different community detection methods and the study of the consistency, robustness, and temporal evolution of the hierarchical modular structure of networks.
Covariance, correlation matrix, and the multiscale community structure of networks.
Shen, Hua-Wei; Cheng, Xue-Qi; Fang, Bin-Xing
2010-07-01
Empirical studies show that real world networks often exhibit multiple scales of topological descriptions. However, it is still an open problem how to identify the intrinsic multiple scales of networks. In this paper, we consider detecting the multiscale community structure of network from the perspective of dimension reduction. According to this perspective, a covariance matrix of network is defined to uncover the multiscale community structure through the translation and rotation transformations. It is proved that the covariance matrix is the unbiased version of the well-known modularity matrix. We then point out that the translation and rotation transformations fail to deal with the heterogeneous network, which is very common in nature and society. To address this problem, a correlation matrix is proposed through introducing the rescaling transformation into the covariance matrix. Extensive tests on real world and artificial networks demonstrate that the correlation matrix significantly outperforms the covariance matrix, identically the modularity matrix, as regards identifying the multiscale community structure of network. This work provides a novel perspective to the identification of community structure and thus various dimension reduction methods might be used for the identification of community structure. Through introducing the correlation matrix, we further conclude that the rescaling transformation is crucial to identify the multiscale community structure of network, as well as the translation and rotation transformations.
Sperry, Megan M; Kartha, Sonia; Granquist, Eric J; Winkelstein, Beth A
2018-07-01
Inter-subject networks are used to model correlations between brain regions and are particularly useful for metabolic imaging techniques, like 18F-2-deoxy-2-(18F)fluoro-D-glucose (FDG) positron emission tomography (PET). Since FDG PET typically produces a single image, correlations cannot be calculated over time. Little focus has been placed on the basic properties of inter-subject networks and if they are affected by group size and image normalization. FDG PET images were acquired from rats (n = 18), normalized by whole brain, visual cortex, or cerebellar FDG uptake, and used to construct correlation matrices. Group size effects on network stability were investigated by systematically adding rats and evaluating local network connectivity (node strength and clustering coefficient). Modularity and community structure were also evaluated in the differently normalized networks to assess meso-scale network relationships. Local network properties are stable regardless of normalization region for groups of at least 10. Whole brain-normalized networks are more modular than visual cortex- or cerebellum-normalized network (p < 0.00001); however, community structure is similar at network resolutions where modularity differs most between brain and randomized networks. Hierarchical analysis reveals consistent modules at different scales and clustering of spatially-proximate brain regions. Findings suggest inter-subject FDG PET networks are stable for reasonable group sizes and exhibit multi-scale modularity.
Mass media influence spreading in social networks with community structure
NASA Astrophysics Data System (ADS)
Candia, Julián; Mazzitello, Karina I.
2008-07-01
We study an extension of Axelrod's model for social influence, in which cultural drift is represented as random perturbations, while mass media are introduced by means of an external field. In this scenario, we investigate how the modular structure of social networks affects the propagation of mass media messages across a society. The community structure of social networks is represented by coupled random networks, in which two random graphs are connected by intercommunity links. Considering inhomogeneous mass media fields, we study the conditions for successful message spreading and find a novel phase diagram in the multidimensional parameter space. These findings show that social modularity effects are of paramount importance for designing successful, cost-effective advertising campaigns.
Takemoto, Kazuhiro; Kajihara, Kosuke
2016-01-01
Theoretical studies have indicated that nestedness and modularity-non-random structural patterns of ecological networks-influence the stability of ecosystems against perturbations; as such, climate change and human activity, as well as other sources of environmental perturbations, affect the nestedness and modularity of ecological networks. However, the effects of climate change and human activities on ecological networks are poorly understood. Here, we used a spatial analysis approach to examine the effects of climate change and human activities on the structural patterns of food webs and mutualistic networks, and found that ecological network structure is globally affected by climate change and human impacts, in addition to current climate. In pollination networks, for instance, nestedness increased and modularity decreased in response to increased human impacts. Modularity in seed-dispersal networks decreased with temperature change (i.e., warming), whereas food web nestedness increased and modularity declined in response to global warming. Although our findings are preliminary owing to data-analysis limitations, they enhance our understanding of the effects of environmental change on ecological communities.
Modular and hierarchical structure of social contact networks
NASA Astrophysics Data System (ADS)
Ge, Yuanzheng; Song, Zhichao; Qiu, Xiaogang; Song, Hongbin; Wang, Yong
2013-10-01
Social contact networks exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated nature. We propose a mixing pattern of modular and growing hierarchical structures to reconstruct social contact networks by using an individual’s geospatial distribution information in the real world. The hierarchical structure of social contact networks is defined based on the spatial distance between individuals, and edges among individuals are added in turn from the modular layer to the highest layer. It is a gradual process to construct the hierarchical structure: from the basic modular model up to the global network. The proposed model not only shows hierarchically increasing degree distribution and large clustering coefficients in communities, but also exhibits spatial clustering features of individual distributions. As an evaluation of the method, we reconstruct a hierarchical contact network based on the investigation data of a university. Transmission experiments of influenza H1N1 are carried out on the generated social contact networks, and results show that the constructed network is efficient to reproduce the dynamic process of an outbreak and evaluate interventions. The reproduced spread process exhibits that the spatial clustering of infection is accordant with the clustering of network topology. Moreover, the effect of individual topological character on the spread of influenza is analyzed, and the experiment results indicate that the spread is limited by individual daily contact patterns and local clustering topology rather than individual degree.
Detecting network communities beyond assortativity-related attributes
NASA Astrophysics Data System (ADS)
Liu, Xin; Murata, Tsuyoshi; Wakita, Ken
2014-07-01
In network science, assortativity refers to the tendency of links to exist between nodes with similar attributes. In social networks, for example, links tend to exist between individuals of similar age, nationality, location, race, income, educational level, religious belief, and language. Thus, various attributes jointly affect the network topology. An interesting problem is to detect community structure beyond some specific assortativity-related attributes ρ, i.e., to take out the effect of ρ on network topology and reveal the hidden community structures which are due to other attributes. An approach to this problem is to redefine the null model of the modularity measure, so as to simulate the effect of ρ on network topology. However, a challenge is that we do not know to what extent the network topology is affected by ρ and by other attributes. In this paper, we propose a distance modularity, which allows us to freely choose any suitable function to simulate the effect of ρ. Such freedom can help us probe the effect of ρ and detect the hidden communities which are due to other attributes. We test the effectiveness of distance modularity on synthetic benchmarks and two real-world networks.
Generalized epidemic process on modular networks.
Chung, Kihong; Baek, Yongjoo; Kim, Daniel; Ha, Meesoon; Jeong, Hawoong
2014-05-01
Social reinforcement and modular structure are two salient features observed in the spreading of behavior through social contacts. In order to investigate the interplay between these two features, we study the generalized epidemic process on modular networks with equal-sized finite communities and adjustable modularity. Using the analytical approach originally applied to clique-based random networks, we show that the system exhibits a bond-percolation type continuous phase transition for weak social reinforcement, whereas a discontinuous phase transition occurs for sufficiently strong social reinforcement. Our findings are numerically verified using the finite-size scaling analysis and the crossings of the bimodality coefficient.
Fournier, Bertrand; Mouly, Arnaud; Gillet, François
2016-01-01
Understanding the factors underlying the co-occurrence of multiple species remains a challenge in ecology. Biotic interactions, environmental filtering and neutral processes are among the main mechanisms evoked to explain species co-occurrence. However, they are most often studied separately or even considered as mutually exclusive. This likely hampers a more global understanding of species assembly. Here, we investigate the general hypothesis that the structure of co-occurrence networks results from multiple assembly rules and its potential implications for grassland ecosystems. We surveyed orthopteran and plant communities in 48 permanent grasslands of the French Jura Mountains and gathered functional and phylogenetic data for all species. We constructed a network of plant and orthopteran species co-occurrences and verified whether its structure was modular or nested. We investigated the role of all species in the structure of the network (modularity and nestedness). We also investigated the assembly rules driving the structure of the plant-orthopteran co-occurrence network by using null models on species functional traits, phylogenetic relatedness and environmental conditions. We finally compared our results to abundance-based approaches. We found that the plant-orthopteran co-occurrence network had a modular organization. Community assembly rules differed among modules for plants while interactions with plants best explained the distribution of orthopterans into modules. Few species had a disproportionately high positive contribution to this modular organization and are likely to have a key importance to modulate future changes. The impact of agricultural practices was restricted to some modules (3 out of 5) suggesting that shifts in agricultural practices might not impact the entire plant-orthopteran co-occurrence network. These findings support our hypothesis that multiple assembly rules drive the modular structure of the plant-orthopteran network. This modular structure is likely to play a key role in the response of grassland ecosystems to future changes by limiting the impact of changes in agricultural practices such as intensification to some modules leaving species from other modules poorly impacted. The next step is to understand the importance of this modular structure for the long-term maintenance of grassland ecosystem structure and functions as well as to develop tools to integrate network structure into models to improve their capacity to predict future changes. PMID:27582754
NASA Astrophysics Data System (ADS)
Song, Zhichao; Ge, Yuanzheng; Luo, Lei; Duan, Hong; Qiu, Xiaogang
2015-12-01
Social contact between individuals is the chief factor for airborne epidemic transmission among the crowd. Social contact networks, which describe the contact relationships among individuals, always exhibit overlapping qualities of communities, hierarchical structure and spatial-correlated. We find that traditional global targeted immunization strategy would lose its superiority in controlling the epidemic propagation in the social contact networks with modular and hierarchical structure. Therefore, we propose a hierarchical targeted immunization strategy to settle this problem. In this novel strategy, importance of the hierarchical structure is considered. Transmission control experiments of influenza H1N1 are carried out based on a modular and hierarchical network model. Results obtained indicate that hierarchical structure of the network is more critical than the degrees of the immunized targets and the modular network layer is the most important for the epidemic propagation control. Finally, the efficacy and stability of this novel immunization strategy have been validated as well.
Modeling information diffusion in time-varying community networks
NASA Astrophysics Data System (ADS)
Cui, Xuelian; Zhao, Narisa
2017-12-01
Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.
Resilience of networks formed of interdependent modular networks
NASA Astrophysics Data System (ADS)
Shekhtman, Louis M.; Shai, Saray; Havlin, Shlomo
2015-12-01
Many infrastructure networks have a modular structure and are also interdependent with other infrastructures. While significant research has explored the resilience of interdependent networks, there has been no analysis of the effects of modularity. Here we develop a theoretical framework for attacks on interdependent modular networks and support our results through simulations. We focus, for simplicity, on the case where each network has the same number of communities and the dependency links are restricted to be between pairs of communities of different networks. This is particularly realistic for modeling infrastructure across cities. Each city has its own infrastructures and different infrastructures are dependent only within the city. However, each infrastructure is connected within and between cities. For example, a power grid will connect many cities as will a communication network, yet a power station and communication tower that are interdependent will likely be in the same city. It has previously been shown that single networks are very susceptible to the failure of the interconnected nodes (between communities) (Shai et al 2014 arXiv:1404.4748) and that attacks on these nodes are even more crippling than attacks based on betweenness (da Cunha et al 2015 arXiv:1502.00353). In our example of cities these nodes have long range links which are more likely to fail. For both treelike and looplike interdependent modular networks we find distinct regimes depending on the number of modules, m. (i) In the case where there are fewer modules with strong intraconnections, the system first separates into modules in an abrupt first-order transition and then each module undergoes a second percolation transition. (ii) When there are more modules with many interconnections between them, the system undergoes a single transition. Overall, we find that modular structure can significantly influence the type of transitions observed in interdependent networks and should be considered in attempts to make interdependent networks more resilient.
Practical Exercises for the Study of Community Ecology at Advanced Level.
ERIC Educational Resources Information Center
Putman, R. J.
1984-01-01
Describes a series of short-term modular experiments which focus on community structure (standing crop biomass) and function (system energy flow). One exercise examines decomposers while another shows energy use by individuals. Equipment needed, procedures used, and results obtained are included. (Author/DH)
Lohse, Christian; Bassett, Danielle S; Lim, Kelvin O; Carlson, Jean M
2014-10-01
Human brain anatomy and function display a combination of modular and hierarchical organization, suggesting the importance of both cohesive structures and variable resolutions in the facilitation of healthy cognitive processes. However, tools to simultaneously probe these features of brain architecture require further development. We propose and apply a set of methods to extract cohesive structures in network representations of brain connectivity using multi-resolution techniques. We employ a combination of soft thresholding, windowed thresholding, and resolution in community detection, that enable us to identify and isolate structures associated with different weights. One such mesoscale structure is bipartivity, which quantifies the extent to which the brain is divided into two partitions with high connectivity between partitions and low connectivity within partitions. A second, complementary mesoscale structure is modularity, which quantifies the extent to which the brain is divided into multiple communities with strong connectivity within each community and weak connectivity between communities. Our methods lead to multi-resolution curves of these network diagnostics over a range of spatial, geometric, and structural scales. For statistical comparison, we contrast our results with those obtained for several benchmark null models. Our work demonstrates that multi-resolution diagnostic curves capture complex organizational profiles in weighted graphs. We apply these methods to the identification of resolution-specific characteristics of healthy weighted graph architecture and altered connectivity profiles in psychiatric disease.
Overlapping Modularity at the Critical Point of k-Clique Percolation
NASA Astrophysics Data System (ADS)
Tóth, Bálint; Vicsek, Tamás; Palla, Gergely
2013-05-01
One of the most remarkable social phenomena is the formation of communities in social networks corresponding to families, friendship circles, work teams, etc. Since people usually belong to several different communities at the same time, the induced overlaps result in an extremely complicated web of the communities themselves. Thus, uncovering the intricate community structure of social networks is a non-trivial task with great potential for practical applications, gaining a notable interest in the recent years. The Clique Percolation Method (CPM) is one of the earliest overlapping community finding methods, which was already used in the analysis of several different social networks. In this approach the communities correspond to k-clique percolation clusters, and the general heuristic for setting the parameters of the method is to tune the system just below the critical point of k-clique percolation. However, this rule is based on simple physical principles and its validity was never subject to quantitative analysis. Here we examine the quality of the partitioning in the vicinity of the critical point using recently introduced overlapping modularity measures. According to our results on real social and other networks, the overlapping modularities show a maximum close to the critical point, justifying the original criteria for the optimal parameter settings.
Tripartite community structure in social bookmarking data
NASA Astrophysics Data System (ADS)
Neubauer, Nicolas; Obermayer, Klaus
2011-12-01
Community detection is a branch of network analysis concerned with identifying strongly connected subnetworks. Social bookmarking sites aggregate datasets of often hundreds of millions of triples (document, user, and tag), which, when interpreted as edges of a graph, give rise to special networks called 3-partite, 3-uniform hypergraphs. We identify challenges and opportunities of generalizing community detection and in particular modularity optimization to these structures. Two methods for community detection are introduced that preserve the hypergraph's special structure to different degrees. Their performance is compared on synthetic datasets, showing the benefits of structure preservation. Furthermore, a tool for interactive exploration of the community detection results is introduced and applied to examples from real datasets. We find additional evidence for the importance of structure preservation and, more generally, demonstrate how tripartite community detection can help understand the structure of social bookmarking data.
Incorporating profile information in community detection for online social networks
NASA Astrophysics Data System (ADS)
Fan, W.; Yeung, K. H.
2014-07-01
Community structure is an important feature in the study of complex networks. It is because nodes of the same community may have similar properties. In this paper we extend two popular community detection methods to partition online social networks. In our extended methods, the profile information of users is used for partitioning. We apply the extended methods in several sample networks of Facebook. Compared with the original methods, the community structures we obtain have higher modularity. Our results indicate that users' profile information is consistent with the community structure of their friendship network to some extent. To the best of our knowledge, this paper is the first to discuss how profile information can be used to improve community detection in online social networks.
Structural Preferential Attachment: Network Organization beyond the Link
NASA Astrophysics Data System (ADS)
Hébert-Dufresne, Laurent; Allard, Antoine; Marceau, Vincent; Noël, Pierre-André; Dubé, Louis J.
2011-10-01
We introduce a mechanism which models the emergence of the universal properties of complex networks, such as scale independence, modularity and self-similarity, and unifies them under a scale-free organization beyond the link. This brings a new perspective on network organization where communities, instead of links, are the fundamental building blocks of complex systems. We show how our simple model can reproduce social and information networks by predicting their community structure and more importantly, how their nodes or communities are interconnected, often in a self-similar manner.
Hui, Cang; Richardson, David M.; Pyšek, Petr; Le Roux, Johannes J.; Kučera, Tomáš; Jarošík, Vojtěch
2013-01-01
Species gain membership of regional assemblages by passing through multiple ecological and environmental filters. To capture the potential trajectory of structural changes in regional meta-communities driven by biological invasions, one can categorize species pools into assemblages of different residence times. Older assemblages, having passed through more environmental filters, should become more functionally ordered and structured. Here we calculate the level of compartmentalization (modularity) for three different-aged assemblages (neophytes, introduced after 1500 AD; archaeophytes, introduced before 1500 AD, and natives), including 2,054 species of vascular plants in 302 reserves in central Europe. Older assemblages are more compartmentalized than younger ones, with species composition, phylogenetic structure and habitat characteristics of the modules becoming increasingly distinctive. This sheds light on two mechanisms of how alien species are functionally incorporated into regional species pools: the settling-down hypothesis of diminishing stochasticity with residence time, and the niche-mosaic hypothesis of inlaid neutral modules in regional meta-communities. PMID:24045305
2017-01-01
The authors use four criteria to examine a novel community detection algorithm: (a) effectiveness in terms of producing high values of normalized mutual information (NMI) and modularity, using well-known social networks for testing; (b) examination, meaning the ability to examine mitigating resolution limit problems using NMI values and synthetic networks; (c) correctness, meaning the ability to identify useful community structure results in terms of NMI values and Lancichinetti-Fortunato-Radicchi (LFR) benchmark networks; and (d) scalability, or the ability to produce comparable modularity values with fast execution times when working with large-scale real-world networks. In addition to describing a simple hierarchical arc-merging (HAM) algorithm that uses network topology information, we introduce rule-based arc-merging strategies for identifying community structures. Five well-studied social network datasets and eight sets of LFR benchmark networks were employed to validate the correctness of a ground-truth community, eight large-scale real-world complex networks were used to measure its efficiency, and two synthetic networks were used to determine its susceptibility to two resolution limit problems. Our experimental results indicate that the proposed HAM algorithm exhibited satisfactory performance efficiency, and that HAM-identified and ground-truth communities were comparable in terms of social and LFR benchmark networks, while mitigating resolution limit problems. PMID:29121100
Gadelkarim, Johnson J; Ajilore, Olusola; Schonfeld, Dan; Zhan, Liang; Thompson, Paul M; Feusner, Jamie D; Kumar, Anand; Altshuler, Lori L; Leow, Alex D
2014-05-01
In this article, we present path length associated community estimation (PLACE), a comprehensive framework for studying node-level community structure. Instead of the well-known Q modularity metric, PLACE utilizes a novel metric, Ψ(PL), which measures the difference between intercommunity versus intracommunity path lengths. We compared community structures in human healthy brain networks generated using these two metrics and argued that Ψ(PL) may have theoretical advantages. PLACE consists of the following: (1) extracting community structure using top-down hierarchical binary trees, where a branch at each bifurcation denotes a collection of nodes that form a community at that level, (2) constructing and assessing mean group community structure, and (3) detecting node-level changes in community between groups. We applied PLACE and investigated the structural brain networks obtained from a sample of 25 euthymic bipolar I subjects versus 25 gender- and age-matched healthy controls. Results showed community structural differences in posterior default mode network regions, with the bipolar group exhibiting left-right decoupling. Copyright © 2013 Wiley Periodicals, Inc.
Nayak, Losiana; De, Rajat K
2007-12-01
Signaling pathways are large complex biochemical networks. It is difficult to analyze the underlying mechanism of such networks as a whole. In the present article, we have proposed an algorithm for modularization of signal transduction pathways. Unlike studying a signaling pathway as a whole, this enables one to study the individual modules (less complex smaller units) easily and hence to study the entire pathway better. A comparative study of modules belonging to different species (for the same signaling pathway) has been made, which gives an overall idea about development of the signaling pathways over the taken set of species of calcium and MAPK signaling pathways. The superior performance, in terms of biological significance, of the proposed algorithm over an existing community finding algorithm of Newman [Newman MEJ. Modularity and community structure in networks. Proc Natl Acad Sci USA 2006;103(23):8577-82] has been demonstrated using the aforesaid pathways of H. sapiens.
Hierarchical organization of functional connectivity in the mouse brain: a complex network approach.
Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano
2016-08-18
This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.
Hierarchical organization of functional connectivity in the mouse brain: a complex network approach
NASA Astrophysics Data System (ADS)
Bardella, Giampiero; Bifone, Angelo; Gabrielli, Andrea; Gozzi, Alessandro; Squartini, Tiziano
2016-08-01
This paper represents a contribution to the study of the brain functional connectivity from the perspective of complex networks theory. More specifically, we apply graph theoretical analyses to provide evidence of the modular structure of the mouse brain and to shed light on its hierarchical organization. We propose a novel percolation analysis and we apply our approach to the analysis of a resting-state functional MRI data set from 41 mice. This approach reveals a robust hierarchical structure of modules persistent across different subjects. Importantly, we test this approach against a statistical benchmark (or null model) which constrains only the distributions of empirical correlations. Our results unambiguously show that the hierarchical character of the mouse brain modular structure is not trivially encoded into this lower-order constraint. Finally, we investigate the modular structure of the mouse brain by computing the Minimal Spanning Forest, a technique that identifies subnetworks characterized by the strongest internal correlations. This approach represents a faster alternative to other community detection methods and provides a means to rank modules on the basis of the strength of their internal edges.
Phage-bacteria infection networks: From nestedness to modularity
NASA Astrophysics Data System (ADS)
Flores, Cesar O.; Valverde, Sergi; Weitz, Joshua S.
2013-03-01
Bacteriophages (viruses that infect bacteria) are the most abundant biological life-forms on Earth. However, very little is known regarding the structure of phage-bacteria infections. In a recent study we re-evaluated 38 prior studies and demonstrated that phage-bacteria infection networks tend to be statistically nested in small scale communities (Flores et al 2011). Nestedness is consistent with a hierarchy of infection and resistance within phages and bacteria, respectively. However, we predicted that at large scales, phage-bacteria infection networks should be typified by a modular structure. We evaluate and confirm this hypothesis using the most extensive study of phage-bacteria infections (Moebus and Nattkemper 1981). In this study, cross-infections were evaluated between 215 marine phages and 286 marine bacteria. We develop a novel multi-scale network analysis and find that the Moebus and Nattkemper (1981) study, is highly modular (at the whole network scale), yet also exhibits nestedness and modularity at the within-module scale. We examine the role of geography in driving these modular patterns and find evidence that phage-bacteria interactions can exhibit strong similarity despite large distances between sites. CFG acknowledges the support of CONACyT Foundation. JSW holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund and acknowledges the support of the James S. McDonnell Foundation
Multi-scale modularity and motif distributional effect in metabolic networks.
Gao, Shang; Chen, Alan; Rahmani, Ali; Zeng, Jia; Tan, Mehmet; Alhajj, Reda; Rokne, Jon; Demetrick, Douglas; Wei, Xiaohui
2016-01-01
Metabolism is a set of fundamental processes that play important roles in a plethora of biological and medical contexts. It is understood that the topological information of reconstructed metabolic networks, such as modular organization, has crucial implications on biological functions. Recent interpretations of modularity in network settings provide a view of multiple network partitions induced by different resolution parameters. Here we ask the question: How do multiple network partitions affect the organization of metabolic networks? Since network motifs are often interpreted as the super families of evolved units, we further investigate their impact under multiple network partitions and investigate how the distribution of network motifs influences the organization of metabolic networks. We studied Homo sapiens, Saccharomyces cerevisiae and Escherichia coli metabolic networks; we analyzed the relationship between different community structures and motif distribution patterns. Further, we quantified the degree to which motifs participate in the modular organization of metabolic networks.
NASA Astrophysics Data System (ADS)
Fu, Yu-Hsiang; Huang, Chung-Yuan; Sun, Chuen-Tsai
2016-11-01
Using network community structures to identify multiple influential spreaders is an appropriate method for analyzing the dissemination of information, ideas and infectious diseases. For example, data on spreaders selected from groups of customers who make similar purchases may be used to advertise products and to optimize limited resource allocation. Other examples include community detection approaches aimed at identifying structures and groups in social or complex networks. However, determining the number of communities in a network remains a challenge. In this paper we describe our proposal for a two-phase evolutionary framework (TPEF) for determining community numbers and maximizing community modularity. Lancichinetti-Fortunato-Radicchi benchmark networks were used to test our proposed method and to analyze execution time, community structure quality, convergence, and the network spreading effect. Results indicate that our proposed TPEF generates satisfactory levels of community quality and convergence. They also suggest a need for an index, mechanism or sampling technique to determine whether a community detection approach should be used for selecting multiple network spreaders.
Phase transition of Surprise optimization in community detection
NASA Astrophysics Data System (ADS)
Xiang, Ju; Tang, Yan-Ni; Gao, Yuan-Yuan; Liu, Lang; Hao, Yi; Li, Jian-Ming; Zhang, Yan; Chen, Shi
2018-02-01
Community detection is one of important issues in the research of complex networks. In literatures, many methods have been proposed to detect community structures in the networks, while they also have the scope of application themselves. In this paper, we investigate an important measure for community detection, Surprise (Aldecoa and Marín, Sci. Rep. 3 (2013) 1060), by focusing on the critical points in the merging and splitting of communities. We firstly analyze the critical behavior of Surprise and give the phase diagrams in community-partition transition. The results show that the critical number of communities for Surprise has a super-exponential increase with the increase of the link-density difference, while it is close to that of Modularity for small difference between inter- and intra-community link densities. By directly optimizing Surprise, we experimentally test the results on various networks, following a series of comparisons with other classical methods, and further find that the heterogeneity of networks could quicken the splitting of communities. On the whole, the results show that Surprise tends to split communities due to various reasons such as the heterogeneity in link density, degree and community size, and it thus exhibits higher resolution than other methods, e.g., Modularity, in community detection. Finally, we provide several approaches for enhancing Surprise.
NASA Astrophysics Data System (ADS)
Fan, W.; Yeung, K. H.
2015-03-01
As social networking services are popular, many people may register in more than one online social network. In this paper we study a set of users who have accounts of three online social networks: namely Foursquare, Facebook and Twitter. Community structure of this set of users may be reflected in these three online social networks. Therefore, high correlation between these reflections and the underlying community structure may be observed. In this work, community structures are detected in all three online social networks. Also, we investigate the similarity level of community structures across different networks. It is found that they show strong correlation with each other. The similarity between different networks may be helpful to find a community structure close to the underlying one. To verify this, we propose a method to increase the weights of some connections in networks. With this method, new networks are generated to assist community detection. By doing this, value of modularity can be improved and the new community structure match network's natural structure better. In this paper we also show that the detected community structures of online social networks are correlated with users' locations which are identified on Foursquare. This information may also be useful for underlying community detection.
Community structure in networks
NASA Astrophysics Data System (ADS)
Newman, Mark
2004-03-01
Many networked systems, including physical, biological, social, and technological networks, appear to contain ``communities'' -- groups of nodes within which connections are dense, but between which they are sparser. The ability to find such communities in an automated fashion could be of considerable use. Communities in a web graph for instance might correspond to sets of web sites dealing with related topics, while communities in a biochemical network or an electronic circuit might correspond to functional units of some kind. We present a number of new methods for community discovery, including methods based on ``betweenness'' measures and methods based on modularity optimization. We also give examples of applications of these methods to both computer-generated and real-world network data, and show how our techniques can be used to shed light on the sometimes dauntingly complex structure of networked systems.
Overlapping communities detection based on spectral analysis of line graphs
NASA Astrophysics Data System (ADS)
Gui, Chun; Zhang, Ruisheng; Hu, Rongjing; Huang, Guoming; Wei, Jiaxuan
2018-05-01
Community in networks are often overlapping where one vertex belongs to several clusters. Meanwhile, many networks show hierarchical structure such that community is recursively grouped into hierarchical organization. In order to obtain overlapping communities from a global hierarchy of vertices, a new algorithm (named SAoLG) is proposed to build the hierarchical organization along with detecting the overlap of community structure. SAoLG applies the spectral analysis into line graphs to unify the overlap and hierarchical structure of the communities. In order to avoid the limitation of absolute distance such as Euclidean distance, SAoLG employs Angular distance to compute the similarity between vertices. Furthermore, we make a micro-improvement partition density to evaluate the quality of community structure and use it to obtain the more reasonable and sensible community numbers. The proposed SAoLG algorithm achieves a balance between overlap and hierarchy by applying spectral analysis to edge community detection. The experimental results on one standard network and six real-world networks show that the SAoLG algorithm achieves higher modularity and reasonable community number values than those generated by Ahn's algorithm, the classical CPM and GN ones.
Emergence of structured communities through evolutionary dynamics.
Shtilerman, Elad; Kessler, David A; Shnerb, Nadav M
2015-10-21
Species-rich communities, in which many competing species coexist in a single trophic level, are quite frequent in nature, but pose a formidable theoretical challenge. In particular, it is known that complex competitive systems become unstable and unfeasible when the number of species is large. Recently, many studies have attributed the stability of natural communities to the structure of the interspecific interaction network, yet the nature of such structures and the underlying mechanisms responsible for them remain open questions. Here we introduce an evolutionary model, based on the generic Lotka-Volterra competitive framework, from which a stable, structured, diverse community emerges spontaneously. The modular structure of the competition matrix reflects the phylogeny of the community, in agreement with the hierarchial taxonomic classification. Closely related species tend to have stronger niche overlap and weaker fitness differences, as opposed to pairs of species from different modules. The competitive-relatedness hypothesis and the idea of emergent neutrality are discussed in the context of this evolutionary model. Copyright © 2015 Elsevier Ltd. All rights reserved.
Watts, Stella; Dormann, Carsten F.; Martín González, Ana M.; Ollerton, Jeff
2016-01-01
Background and Aims Modularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant–pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant–pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization. Methods A total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization. Key Results All networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant–pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas. Conclusions We have demonstrated that the topology of networks in this tropical montane environment was non-random and highly organized. Our findings underline that specialization indices convey different concepts of specialization and hence quantify different aspects, and that measuring specialization requires careful consideration of what defines a specialist. PMID:27562649
Watts, Stella; Dormann, Carsten F; Martín González, Ana M; Ollerton, Jeff
2016-09-01
Modularity is a ubiquitous and important structural property of ecological networks which describes the relative strengths of sets of interacting species and gives insights into the dynamics of ecological communities. However, this has rarely been studied in species-rich, tropical plant-pollinator networks. Working in a biodiversity hotspot in the Peruvian Andes we assessed the structure of quantitative plant-pollinator networks in nine valleys, quantifying modularity among networks, defining the topological roles of species and the influence of floral traits on specialization. A total of 90 transects were surveyed for plants and pollinators at different altitudes and across different life zones. Quantitative modularity (QuanBiMo) was used to detect modularity and six indices were used to quantify specialization. All networks were highly structured, moderately specialized and significantly modular regardless of size. The strongest hubs were Baccharis plants, Apis mellifera, Bombus funebris and Diptera spp., which were the most ubiquitous and abundant species with the longest phenologies. Species strength showed a strong association with the modular structure of plant-pollinator networks. Hubs and connectors were the most centralized participants in the networks and were ranked highest (high generalization) when quantifying specialization with most indices. However, complementary specialization d' quantified hubs and connectors as moderately specialized. Specialization and topological roles of species were remarkably constant across some sites, but highly variable in others. Networks were dominated by ecologically and functionally generalist plant species with open access flowers which are closely related taxonomically with similar morphology and rewards. Plants associated with hummingbirds had the highest level of complementary specialization and exclusivity in modules (functional specialists) and the longest corollas. We have demonstrated that the topology of networks in this tropical montane environment was non-random and highly organized. Our findings underline that specialization indices convey different concepts of specialization and hence quantify different aspects, and that measuring specialization requires careful consideration of what defines a specialist. © The Author 2016. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Maximal Neighbor Similarity Reveals Real Communities in Networks
Žalik, Krista Rizman
2015-01-01
An important problem in the analysis of network data is the detection of groups of densely interconnected nodes also called modules or communities. Community structure reveals functions and organizations of networks. Currently used algorithms for community detection in large-scale real-world networks are computationally expensive or require a priori information such as the number or sizes of communities or are not able to give the same resulting partition in multiple runs. In this paper we investigate a simple and fast algorithm that uses the network structure alone and requires neither optimization of pre-defined objective function nor information about number of communities. We propose a bottom up community detection algorithm in which starting from communities consisting of adjacent pairs of nodes and their maximal similar neighbors we find real communities. We show that the overall advantage of the proposed algorithm compared to the other community detection algorithms is its simple nature, low computational cost and its very high accuracy in detection communities of different sizes also in networks with blurred modularity structure consisting of poorly separated communities. All communities identified by the proposed method for facebook network and E-Coli transcriptional regulatory network have strong structural and functional coherence. PMID:26680448
Modularity, pollination systems, and interaction turnover in plant-pollinator networks across space.
Carstensen, Daniel W; Sabatino, Malena; Morellato, Leonor Patricia C
2016-05-01
Mutualistic interaction networks have been shown to be structurally conserved over space and time while pairwise interactions show high variability. In such networks, modularity is the division of species into compartments, or modules, where species within modules share more interactions with each other than they do with species from other modules. Such a modular structure is common in mutualistic networks and several evolutionary and ecological mechanisms have been proposed as underlying drivers. One prominent explanation is the existence of pollination syndromes where flowers tend to attract certain pollinators as determined by a set of traits. We investigate the modularity of seven community level plant-pollinator networks sampled in rupestrian grasslands, or campos rupestres, in SE Brazil. Defining pollination systems as corresponding groups of flower syndromes and pollinator functional groups, we test the two hypotheses that (1) interacting species from the same pollination system are more often assigned to the same module than interacting species from different pollination systems and; that (2) interactions between species from the same pollination system are more consistent across space than interactions between species from different pollination systems. Specifically we ask (1) whether networks are consistently modular across space; (2) whether interactions among species of the same pollination system occur more often inside modules, compared to interactions among species of different pollination systems, and finally; (3) whether the spatial variation in interaction identity, i.e., spatial interaction rewiring, is affected by trait complementarity among species as indicated by pollination systems. We confirm that networks are consistently modular across space and that interactions within pollination systems principally occur inside modules. Despite a strong tendency, we did not find a significant effect of pollination systems on the spatial consistency of pairwise interactions. These results indicate that the spatial rewiring of interactions could be constrained by pollination systems, resulting in conserved network structures in spite of high variation in pairwise interactions. Our findings suggest a relevant role of pollination systems in structuring plant-pollinator networks and we argue that structural patterns at the sub-network level can help us to fully understand how and why interactions vary across space and time.
Spectral partitioning in equitable graphs.
Barucca, Paolo
2017-06-01
Graph partitioning problems emerge in a wide variety of complex systems, ranging from biology to finance, but can be rigorously analyzed and solved only for a few graph ensembles. Here, an ensemble of equitable graphs, i.e., random graphs with a block-regular structure, is studied, for which analytical results can be obtained. In particular, the spectral density of this ensemble is computed exactly for a modular and bipartite structure. Kesten-McKay's law for random regular graphs is found analytically to apply also for modular and bipartite structures when blocks are homogeneous. An exact solution to graph partitioning for two equal-sized communities is proposed and verified numerically, and a conjecture on the absence of an efficient recovery detectability transition in equitable graphs is suggested. A final discussion summarizes results and outlines their relevance for the solution of graph partitioning problems in other graph ensembles, in particular for the study of detectability thresholds and resolution limits in stochastic block models.
Spectral partitioning in equitable graphs
NASA Astrophysics Data System (ADS)
Barucca, Paolo
2017-06-01
Graph partitioning problems emerge in a wide variety of complex systems, ranging from biology to finance, but can be rigorously analyzed and solved only for a few graph ensembles. Here, an ensemble of equitable graphs, i.e., random graphs with a block-regular structure, is studied, for which analytical results can be obtained. In particular, the spectral density of this ensemble is computed exactly for a modular and bipartite structure. Kesten-McKay's law for random regular graphs is found analytically to apply also for modular and bipartite structures when blocks are homogeneous. An exact solution to graph partitioning for two equal-sized communities is proposed and verified numerically, and a conjecture on the absence of an efficient recovery detectability transition in equitable graphs is suggested. A final discussion summarizes results and outlines their relevance for the solution of graph partitioning problems in other graph ensembles, in particular for the study of detectability thresholds and resolution limits in stochastic block models.
Network community-detection enhancement by proper weighting
NASA Astrophysics Data System (ADS)
Khadivi, Alireza; Ajdari Rad, Ali; Hasler, Martin
2011-04-01
In this paper, we show how proper assignment of weights to the edges of a complex network can enhance the detection of communities and how it can circumvent the resolution limit and the extreme degeneracy problems associated with modularity. Our general weighting scheme takes advantage of graph theoretic measures and it introduces two heuristics for tuning its parameters. We use this weighting as a preprocessing step for the greedy modularity optimization algorithm of Newman to improve its performance. The result of the experiments of our approach on computer-generated and real-world data networks confirm that the proposed approach not only mitigates the problems of modularity but also improves the modularity optimization.
Development of a space universal modular architecture (SUMO)
NASA Astrophysics Data System (ADS)
Collins, Bernie F.
This concept paper proposes that the space community should develop and implement a universal standard for spacecraft modularity - to improve interoperability of spacecraft components. Pursuing a global industry consensus standard for open and modular spacecraft architecture will encourage trade, remove standards-related market barriers, and in the long run increase both value provided to customers and profitability of the space industrial sector. This concept paper sets out: (1) the goals for a SUMO standard and how it will benefit the space community; (2) background on spacecraft modularity and existing related standards; (3) the proposed technical scope of the current standardization effort; and (4) an approach for creating a SUMO standard.
Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng
2014-01-01
Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms. PMID:24723806
Ma, Jingjing; Liu, Jie; Ma, Wenping; Gong, Maoguo; Jiao, Licheng
2014-01-01
Community structure is one of the most important properties in social networks. In dynamic networks, there are two conflicting criteria that need to be considered. One is the snapshot quality, which evaluates the quality of the community partitions at the current time step. The other is the temporal cost, which evaluates the difference between communities at different time steps. In this paper, we propose a decomposition-based multiobjective community detection algorithm to simultaneously optimize these two objectives to reveal community structure and its evolution in dynamic networks. It employs the framework of multiobjective evolutionary algorithm based on decomposition to simultaneously optimize the modularity and normalized mutual information, which quantitatively measure the quality of the community partitions and temporal cost, respectively. A local search strategy dealing with the problem-specific knowledge is incorporated to improve the effectiveness of the new algorithm. Experiments on computer-generated and real-world networks demonstrate that the proposed algorithm can not only find community structure and capture community evolution more accurately, but also be steadier than the two compared algorithms.
López-Carretero, Antonio; Díaz-Castelazo, Cecilia; Boege, Karina; Rico-Gray, Víctor
2014-01-01
Despite the dynamic nature of ecological interactions, most studies on species networks offer static representations of their structure, constraining our understanding of the ecological mechanisms involved in their spatio-temporal stability. This is the first study to evaluate plant-herbivore interaction networks on a small spatio-temporal scale. Specifically, we simultaneously assessed the effect of host plant availability, habitat complexity and seasonality on the structure of plant-herbivore networks in a coastal tropical ecosystem. Our results revealed that changes in the host plant community resulting from seasonality and habitat structure are reflected not only in the herbivore community, but also in the emergent properties (network parameters) of the plant-herbivore interaction network such as connectance, selectiveness and modularity. Habitat conditions and periods that are most stressful favored the presence of less selective and susceptible herbivore species, resulting in increased connectance within networks. In contrast, the high degree of selectivennes (i.e. interaction specialization) and modularity of the networks under less stressful conditions was promoted by the diversification in resource use by herbivores. By analyzing networks at a small spatio-temporal scale we identified the ecological factors structuring this network such as habitat complexity and seasonality. Our research offers new evidence on the role of abiotic and biotic factors in the variation of the properties of species interaction networks. PMID:25340790
Modulated Modularity Clustering as an Exploratory Tool for Functional Genomic Inference
Stone, Eric A.; Ayroles, Julien F.
2009-01-01
In recent years, the advent of high-throughput assays, coupled with their diminishing cost, has facilitated a systems approach to biology. As a consequence, massive amounts of data are currently being generated, requiring efficient methodology aimed at the reduction of scale. Whole-genome transcriptional profiling is a standard component of systems-level analyses, and to reduce scale and improve inference clustering genes is common. Since clustering is often the first step toward generating hypotheses, cluster quality is critical. Conversely, because the validation of cluster-driven hypotheses is indirect, it is critical that quality clusters not be obtained by subjective means. In this paper, we present a new objective-based clustering method and demonstrate that it yields high-quality results. Our method, modulated modularity clustering (MMC), seeks community structure in graphical data. MMC modulates the connection strengths of edges in a weighted graph to maximize an objective function (called modularity) that quantifies community structure. The result of this maximization is a clustering through which tightly-connected groups of vertices emerge. Our application is to systems genetics, and we quantitatively compare MMC both to the hierarchical clustering method most commonly employed and to three popular spectral clustering approaches. We further validate MMC through analyses of human and Drosophila melanogaster expression data, demonstrating that the clusters we obtain are biologically meaningful. We show MMC to be effective and suitable to applications of large scale. In light of these features, we advocate MMC as a standard tool for exploration and hypothesis generation. PMID:19424432
Modularity and the spread of perturbations in complex dynamical systems
NASA Astrophysics Data System (ADS)
Kolchinsky, Artemy; Gates, Alexander J.; Rocha, Luis M.
2015-12-01
We propose a method to decompose dynamical systems based on the idea that modules constrain the spread of perturbations. We find partitions of system variables that maximize "perturbation modularity," defined as the autocovariance of coarse-grained perturbed trajectories. The measure effectively separates the fast intramodular from the slow intermodular dynamics of perturbation spreading (in this respect, it is a generalization of the "Markov stability" method of network community detection). Our approach captures variation of modular organization across different system states, time scales, and in response to different kinds of perturbations: aspects of modularity which are all relevant to real-world dynamical systems. It offers a principled alternative to detecting communities in networks of statistical dependencies between system variables (e.g., "relevance networks" or "functional networks"). Using coupled logistic maps, we demonstrate that the method uncovers hierarchical modular organization planted in a system's coupling matrix. Additionally, in homogeneously coupled map lattices, it identifies the presence of self-organized modularity that depends on the initial state, dynamical parameters, and type of perturbations. Our approach offers a powerful tool for exploring the modular organization of complex dynamical systems.
Modularity and the spread of perturbations in complex dynamical systems.
Kolchinsky, Artemy; Gates, Alexander J; Rocha, Luis M
2015-12-01
We propose a method to decompose dynamical systems based on the idea that modules constrain the spread of perturbations. We find partitions of system variables that maximize "perturbation modularity," defined as the autocovariance of coarse-grained perturbed trajectories. The measure effectively separates the fast intramodular from the slow intermodular dynamics of perturbation spreading (in this respect, it is a generalization of the "Markov stability" method of network community detection). Our approach captures variation of modular organization across different system states, time scales, and in response to different kinds of perturbations: aspects of modularity which are all relevant to real-world dynamical systems. It offers a principled alternative to detecting communities in networks of statistical dependencies between system variables (e.g., "relevance networks" or "functional networks"). Using coupled logistic maps, we demonstrate that the method uncovers hierarchical modular organization planted in a system's coupling matrix. Additionally, in homogeneously coupled map lattices, it identifies the presence of self-organized modularity that depends on the initial state, dynamical parameters, and type of perturbations. Our approach offers a powerful tool for exploring the modular organization of complex dynamical systems.
Parameterized centrality metric for network analysis
NASA Astrophysics Data System (ADS)
Ghosh, Rumi; Lerman, Kristina
2011-06-01
A variety of metrics have been proposed to measure the relative importance of nodes in a network. One of these, alpha-centrality [P. Bonacich, Am. J. Sociol.0002-960210.1086/228631 92, 1170 (1987)], measures the number of attenuated paths that exist between nodes. We introduce a normalized version of this metric and use it to study network structure, for example, to rank nodes and find community structure of the network. Specifically, we extend the modularity-maximization method for community detection to use this metric as the measure of node connectivity. Normalized alpha-centrality is a powerful tool for network analysis, since it contains a tunable parameter that sets the length scale of interactions. Studying how rankings and discovered communities change when this parameter is varied allows us to identify locally and globally important nodes and structures. We apply the proposed metric to several benchmark networks and show that it leads to better insights into network structure than alternative metrics.
A generalised significance test for individual communities in networks.
Kojaku, Sadamori; Masuda, Naoki
2018-05-09
Many empirical networks have community structure, in which nodes are densely interconnected within each community (i.e., a group of nodes) and sparsely across different communities. Like other local and meso-scale structure of networks, communities are generally heterogeneous in various aspects such as the size, density of edges, connectivity to other communities and significance. In the present study, we propose a method to statistically test the significance of individual communities in a given network. Compared to the previous methods, the present algorithm is unique in that it accepts different community-detection algorithms and the corresponding quality function for single communities. The present method requires that a quality of each community can be quantified and that community detection is performed as optimisation of such a quality function summed over the communities. Various community detection algorithms including modularity maximisation and graph partitioning meet this criterion. Our method estimates a distribution of the quality function for randomised networks to calculate a likelihood of each community in the given network. We illustrate our algorithm by synthetic and empirical networks.
Distributed learning automata-based algorithm for community detection in complex networks
NASA Astrophysics Data System (ADS)
Khomami, Mohammad Mehdi Daliri; Rezvanian, Alireza; Meybodi, Mohammad Reza
2016-03-01
Community structure is an important and universal topological property of many complex networks such as social and information networks. The detection of communities of a network is a significant technique for understanding the structure and function of networks. In this paper, we propose an algorithm based on distributed learning automata for community detection (DLACD) in complex networks. In the proposed algorithm, each vertex of network is equipped with a learning automation. According to the cooperation among network of learning automata and updating action probabilities of each automaton, the algorithm interactively tries to identify high-density local communities. The performance of the proposed algorithm is investigated through a number of simulations on popular synthetic and real networks. Experimental results in comparison with popular community detection algorithms such as walk trap, Danon greedy optimization, Fuzzy community detection, Multi-resolution community detection and label propagation demonstrated the superiority of DLACD in terms of modularity, NMI, performance, min-max-cut and coverage.
Kovács, István A.; Palotai, Robin; Szalay, Máté S.; Csermely, Peter
2010-01-01
Background Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction. PMID:20824084
Evidence of community structure in biomedical research grant collaborations.
Nagarajan, Radhakrishnan; Kalinka, Alex T; Hogan, William R
2013-02-01
Recent studies have clearly demonstrated a shift towards collaborative research and team science approaches across a spectrum of disciplines. Such collaborative efforts have also been acknowledged and nurtured by popular extramurally funded programs including the Clinical Translational Science Award (CTSA) conferred by the National Institutes of Health. Since its inception, the number of CTSA awardees has steadily increased to 60 institutes across 30 states. One of the objectives of CTSA is to accelerate translation of research from bench to bedside to community and train a new genre of researchers under the translational research umbrella. Feasibility of such a translation implicitly demands multi-disciplinary collaboration and mentoring. Networks have proven to be convenient abstractions for studying research collaborations. The present study is a part of the CTSA baseline study and investigates existence of possible community-structure in Biomedical Research Grant Collaboration (BRGC) networks across data sets retrieved from the internally developed grants management system, the Automated Research Information Administrator (ARIA) at the University of Arkansas for Medical Sciences (UAMS). Fastgreedy and link-community community-structure detection algorithms were used to investigate the presence of non-overlapping and overlapping community-structure and their variation across years 2006 and 2009. A surrogate testing approach in conjunction with appropriate discriminant statistics, namely: the modularity index and the maximum partition density is proposed to investigate whether the community-structure of the BRGC networks were different from those generated by certain types of random graphs. Non-overlapping as well as overlapping community-structure detection algorithms indicated the presence of community-structure in the BRGC network. Subsequent, surrogate testing revealed that random graph models considered in the present study may not necessarily be appropriate generative mechanisms of the community-structure in the BRGC networks. The discrepancy in the community-structure between the BRGC networks and the random graph surrogates was especially pronounced at 2009 as opposed to 2006 indicating a possible shift towards team-science and formation of non-trivial modular patterns with time. The results also clearly demonstrate presence of inter-departmental and multi-disciplinary collaborations in BRGC networks. While the results are presented on BRGC networks as a part of the CTSA baseline study at UAMS, the proposed methodologies are as such generic with potential to be extended across other CTSA organizations. Understanding the presence of community-structure can supplement more traditional network analysis as they're useful in identifying research teams and their inter-connections as opposed to the role of individual nodes in the network. Such an understanding can be a critical step prior to devising meaningful interventions for promoting team-science, multi-disciplinary collaborations, cross-fertilization of ideas across research teams and identifying suitable mentors. Understanding the temporal evolution of these communities may also be useful in CTSA evaluation. Copyright © 2012. Published by Elsevier Inc.
Modular Power Standard for Space Explorations Missions
NASA Technical Reports Server (NTRS)
Oeftering, Richard C.; Gardner, Brent G.
2016-01-01
Future human space exploration will most likely be composed of assemblies of multiple modular spacecraft elements with interconnected electrical power systems. An electrical system composed of a standardized set modular building blocks provides significant development, integration, and operational cost advantages. The modular approach can also provide the flexibility to configure power systems to meet the mission needs. A primary goal of the Advanced Exploration Systems (AES) Modular Power System (AMPS) project is to establish a Modular Power Standard that is needed to realize these benefits. This paper is intended to give the space exploration community a "first look" at the evolving Modular Power Standard and invite their comments and technical contributions.
Unraveling the disease consequences and mechanisms of modular structure in animal social networks
Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta
2017-01-01
Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living. PMID:28373567
Unraveling the disease consequences and mechanisms of modular structure in animal social networks
Sah, Pratha; Leu, Stephan T.; Cross, Paul C.; Hudson, Peter J.; Bansal, Shweta
2017-01-01
Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.
Unraveling the disease consequences and mechanisms of modular structure in animal social networks.
Sah, Pratha; Leu, Stephan T; Cross, Paul C; Hudson, Peter J; Bansal, Shweta
2017-04-18
Disease risk is a potential cost of group living. Although modular organization is thought to reduce this cost in animal societies, empirical evidence toward this hypothesis has been conflicting. We analyzed empirical social networks from 43 animal species to motivate our study of the epidemiological consequences of modular structure in animal societies. From these empirical studies, we identified the features of interaction patterns associated with network modularity and developed a theoretical network model to investigate when and how subdivisions in social networks influence disease dynamics. Contrary to prior work, we found that disease risk is largely unaffected by modular structure, although social networks beyond a modular threshold experience smaller disease burden and longer disease duration. Our results illustrate that the lowering of disease burden in highly modular social networks is driven by two mechanisms of modular organization: network fragmentation and subgroup cohesion. Highly fragmented social networks with cohesive subgroups are able to structurally trap infections within a few subgroups and also cause a structural delay to the spread of disease outbreaks. Finally, we show that network models incorporating modular structure are necessary only when prior knowledge suggests that interactions within the population are highly subdivided. Otherwise, null networks based on basic knowledge about group size and local contact heterogeneity may be sufficient when data-limited estimates of epidemic consequences are necessary. Overall, our work does not support the hypothesis that modular structure universally mitigates the disease impact of group living.
Comprehensive benefits analysis of steel structure modular residence based on the entropy evaluation
NASA Astrophysics Data System (ADS)
Zhang, Xiaoxiao; Wang, Li; Jiang, Pengming
2017-04-01
Steel structure modular residence is the outstanding residential industrialization. It has many advantages, such as the low whole cost, high resource recovery, a high degree of industrialization. This paper compares the comprehensive benefits of steel structural in modular buildings with prefabricated reinforced concrete residential from economic benefits, environmental benefits, social benefits and technical benefits by the method of entropy evaluation. Finally, it is concluded that the comprehensive benefits of steel structural in modular buildings is better than that of prefabricated reinforced concrete residential. The conclusion of this study will provide certain reference significance to the development of steel structural in modular buildings in China.
Stetz, Gabrielle; Verkhivker, Gennady M.
2017-01-01
Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms. PMID:28095400
Stetz, Gabrielle; Verkhivker, Gennady M
2017-01-01
Allosteric interactions in the Hsp70 proteins are linked with their regulatory mechanisms and cellular functions. Despite significant progress in structural and functional characterization of the Hsp70 proteins fundamental questions concerning modularity of the allosteric interaction networks and hierarchy of signaling pathways in the Hsp70 chaperones remained largely unexplored and poorly understood. In this work, we proposed an integrated computational strategy that combined atomistic and coarse-grained simulations with coevolutionary analysis and network modeling of the residue interactions. A novel aspect of this work is the incorporation of dynamic residue correlations and coevolutionary residue dependencies in the construction of allosteric interaction networks and signaling pathways. We found that functional sites involved in allosteric regulation of Hsp70 may be characterized by structural stability, proximity to global hinge centers and local structural environment that is enriched by highly coevolving flexible residues. These specific characteristics may be necessary for regulation of allosteric structural transitions and could distinguish regulatory sites from nonfunctional conserved residues. The observed confluence of dynamics correlations and coevolutionary residue couplings with global networking features may determine modular organization of allosteric interactions and dictate localization of key mediating sites. Community analysis of the residue interaction networks revealed that concerted rearrangements of local interacting modules at the inter-domain interface may be responsible for global structural changes and a population shift in the DnaK chaperone. The inter-domain communities in the Hsp70 structures harbor the majority of regulatory residues involved in allosteric signaling, suggesting that these sites could be integral to the network organization and coordination of structural changes. Using a network-based formalism of allostery, we introduced a community-hopping model of allosteric communication. Atomistic reconstruction of signaling pathways in the DnaK structures captured a direction-specific mechanism and molecular details of signal transmission that are fully consistent with the mutagenesis experiments. The results of our study reconciled structural and functional experiments from a network-centric perspective by showing that global properties of the residue interaction networks and coevolutionary signatures may be linked with specificity and diversity of allosteric regulation mechanisms.
A host-endoparasite network of Neotropical marine fish: are there organizational patterns?
Bellay, Sybelle; Lima, Dilermando P; Takemoto, Ricardo M; Luque, José L
2011-12-01
Properties of ecological networks facilitate the understanding of interaction patterns in host-parasite systems as well as the importance of each species in the interaction structure of a community. The present study evaluates the network structure, functional role of all species and patterns of parasite co-occurrence in a host-parasite network to determine the organization level of a host-parasite system consisting of 170 taxa of gastrointestinal metazoans of 39 marine fish species on the coast of Brazil. The network proved to be nested and modular, with a low degree of connectance. Host-parasite interactions were influenced by host phylogeny. Randomness in parasite co-occurrence was observed in most modules and component communities, although species segregation patterns were also observed. The low degree of connectance in the network may be the cause of properties such as nestedness and modularity, which indicate the presence of a high number of peripheral species. Segregation patterns among parasite species in modules underscore the role of host specificity. Knowledge of ecological networks allows detection of keystone species for the maintenance of biodiversity and the conduction of further studies on the stability of networks in relation to frequent environmental changes.
Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California
Chew, Robert F; Hsieh, Yuli P; Bieler, Gayle S; Bobashev, Georgiy V; Siege, Christopher; Zarkin, Gary A
2017-01-01
Background Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks. Objectives This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California. Methods From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities. Results The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles. Conclusions The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time. PMID:28676471
NASA Astrophysics Data System (ADS)
Zapata-Mesa, Natalya; Montoya-Bustamante, Sebastián; Murillo-García, Oscar E.
2017-11-01
Mutualistic interactions, such as seed dispersal, are important for the maintenance of structure and stability of tropical communities. However, there is a lack of information about spatial and temporal variation in plant-animal interaction networks. Thus, our goal was to assess the effect of bat's foraging strategies on temporal variation in the structure and robustness of bat-fruit networks in both a dry and a rain tropical forest. We evaluated monthly variation in bat-fruit networks by using seven structure metrics: network size, average path length, nestedness, modularity, complementary specialization, normalized degree and betweenness centrality. Seed dispersal networks showed variations in size, species composition and modularity; did not present nested structures and their complementary specialization was high compared to other studies. Both networks presented short path lengths, and a constantly high robustness, despite their monthly variations. Sedentary bat species were recorded during all the study periods and occupied more central positions than nomadic species. We conclude that foraging strategies are important structuring factors that affect the dynamic of networks by determining the functional roles of frugivorous bats over time; thus sedentary bats are more important than nomadic species for the maintenance of the network structure, and their conservation is a must.
Constant Communities in Complex Networks
NASA Astrophysics Data System (ADS)
Chakraborty, Tanmoy; Srinivasan, Sriram; Ganguly, Niloy; Bhowmick, Sanjukta; Mukherjee, Animesh
2013-05-01
Identifying community structure is a fundamental problem in network analysis. Most community detection algorithms are based on optimizing a combinatorial parameter, for example modularity. This optimization is generally NP-hard, thus merely changing the vertex order can alter their assignments to the community. However, there has been less study on how vertex ordering influences the results of the community detection algorithms. Here we identify and study the properties of invariant groups of vertices (constant communities) whose assignment to communities are, quite remarkably, not affected by vertex ordering. The percentage of constant communities can vary across different applications and based on empirical results we propose metrics to evaluate these communities. Using constant communities as a pre-processing step, one can significantly reduce the variation of the results. Finally, we present a case study on phoneme network and illustrate that constant communities, quite strikingly, form the core functional units of the larger communities.
Network clustering and community detection using modulus of families of loops.
Shakeri, Heman; Poggi-Corradini, Pietro; Albin, Nathan; Scoglio, Caterina
2017-01-01
We study the structure of loops in networks using the notion of modulus of loop families. We introduce an alternate measure of network clustering by quantifying the richness of families of (simple) loops. Modulus tries to minimize the expected overlap among loops by spreading the expected link usage optimally. We propose weighting networks using these expected link usages to improve classical community detection algorithms. We show that the proposed method enhances the performance of certain algorithms, such as spectral partitioning and modularity maximization heuristics, on standard benchmarks.
NASA Astrophysics Data System (ADS)
Li, Hui-Jia; Cheng, Qing; Mao, He-Jin; Wang, Huanian; Chen, Junhua
2017-03-01
The study of community structure is a primary focus of network analysis, which has attracted a large amount of attention. In this paper, we focus on two famous functions, i.e., the Hamiltonian function H and the modularity density measure D, and intend to uncover the effective thresholds of their corresponding resolution parameter γ without resolution limit problem. Two widely used example networks are employed, including the ring network of lumps as well as the ad hoc network. In these two networks, we use discrete convex analysis to study the interval of resolution parameter of H and D that will not cause the misidentification. By comparison, we find that in both examples, for Hamiltonian function H, the larger the value of resolution parameter γ, the less resolution limit the network suffers; while for modularity density D, the less resolution limit the network suffers when we decrease the value of γ. Our framework is mathematically strict and efficient and can be applied in a lot of scientific fields.
Experiments in clustered neuronal networks: A paradigm for complex modular dynamics
NASA Astrophysics Data System (ADS)
Teller, Sara; Soriano, Jordi
2016-06-01
Uncovering the interplay activity-connectivity is one of the major challenges in neuroscience. To deepen in the understanding of how a neuronal circuit shapes network dynamics, neuronal cultures have emerged as remarkable systems given their accessibility and easy manipulation. An attractive configuration of these in vitro systems consists in an ensemble of interconnected clusters of neurons. Using calcium fluorescence imaging to monitor spontaneous activity in these clustered neuronal networks, we were able to draw functional maps and reveal their topological features. We also observed that these networks exhibit a hierarchical modular dynamics, in which clusters fire in small groups that shape characteristic communities in the network. The structure and stability of these communities is sensitive to chemical or physical action, and therefore their analysis may serve as a proxy for network health. Indeed, the combination of all these approaches is helping to develop models to quantify damage upon network degradation, with promising applications for the study of neurological disorders in vitro.
Efficient community-based control strategies in adaptive networks
NASA Astrophysics Data System (ADS)
Yang, Hui; Tang, Ming; Zhang, Hai-Feng
2012-12-01
Most studies on adaptive networks concentrate on the properties of steady state, but neglect transient dynamics. In this study, we pay attention to the emergence of community structure in the transient process and the effects of community-based control strategies on epidemic spreading. First, by normalizing the modularity, we investigate the evolution of community structure during the transient process, and find that a strong community structure is induced by the rewiring mechanism in the early stage of epidemic dynamics, which, remarkably, delays the outbreak of disease. We then study the effects of control strategies started at different stages on the prevalence. Both immunization and quarantine strategies indicate that it is not ‘the earlier, the better’ for the implementation of control measures. And the optimal control effect is obtained if control measures can be efficiently implemented in the period of a strong community structure. For the immunization strategy, immunizing the susceptible nodes on susceptible-infected links and immunizing susceptible nodes randomly have similar control effects. However, for the quarantine strategy, quarantining the infected nodes on susceptible-infected links can yield a far better result than quarantining infected nodes randomly. More significantly, the community-based quarantine strategy performs better than the community-based immunization strategy. This study may shed new light on the forecast and the prevention of epidemics among humans.
Complexity and dynamics of topological and community structure in complex networks
NASA Astrophysics Data System (ADS)
Berec, Vesna
2017-07-01
Complexity is highly susceptible to variations in the network dynamics, reflected on its underlying architecture where topological organization of cohesive subsets into clusters, system's modular structure and resulting hierarchical patterns, are cross-linked with functional dynamics of the system. Here we study connection between hierarchical topological scales of the simplicial complexes and the organization of functional clusters - communities in complex networks. The analysis reveals the full dynamics of different combinatorial structures of q-th-dimensional simplicial complexes and their Laplacian spectra, presenting spectral properties of resulting symmetric and positive semidefinite matrices. The emergence of system's collective behavior from inhomogeneous statistical distribution is induced by hierarchically ordered topological structure, which is mapped to simplicial complex where local interactions between the nodes clustered into subcomplexes generate flow of information that characterizes complexity and dynamics of the full system.
Jessen, Jari Due; Lund, Henrik Hautop
2017-01-19
Loss of functional capabilities due to inactivity is one of the most common reasons for fall accidents, and it has been well established that loss of capabilities can be effectively reduced by physical activity. Pilot studies indicate a possible improvement in functional abilities of community dwelling elderly as a result of short-term playing with an exergame system in the form of interactive modular tiles. Such playful training may be motivational to perform and viewed by the subjects to offer life-fulfilling quality, while providing improvement in physical abilities, e.g. related to prevent fall accidents. The RCT will test for a variety of health parameters of community-dwelling elderly playing on interactive modular tiles. The study will be a single blinded, randomized controlled trial with 60 community-dwelling adults 70+ years. The trial will consist an intervention group of 30 participants training with the interactive modular tiles, and a control group of 30 participants that will receive the usual care provided to non-patient elderly. The intervention period will be 12 weeks. The intervention group will perform group training (4-5 individuals for 1 h training session with each participant receiving 13 min training) on the interactive tiles twice a week. Follow-up tests include 6-min Walk Test (6MWT), the 8-ft Timed Up & Go Test (TUG), and the Chair-Stand Test (CS) from the Senior Fitness Test, along with balancing tests (static test on Wii Board and Line Walk test). Secondary outcomes related to adherence, motivation and acceptability will be investigated through semi-structured interviews. Data will be collected from pre- and post-tests. Data will be analyzed for statistically significant differences by checking that there is a Gaussian distribution and then using paired t-test, otherwise using Wilcoxon signed-rank test. "Intention to treat" analysis will be done. The trial tests for increased mobility, agility, balancing and general fitness of community-dwelling elderly as a result of playing, in this case on modular interactive tiles. A positive outcome may help preventing loss of functional capabilities due to inactivity. ClinicalTrials.gov: Nr. NCT02496702 , Initial Release date 7/7-2015.
Algorithm for parametric community detection in networks.
Bettinelli, Andrea; Hansen, Pierre; Liberti, Leo
2012-07-01
Modularity maximization is extensively used to detect communities in complex networks. It has been shown, however, that this method suffers from a resolution limit: Small communities may be undetectable in the presence of larger ones even if they are very dense. To alleviate this defect, various modifications of the modularity function have been proposed as well as multiresolution methods. In this paper we systematically study a simple model (proposed by Pons and Latapy [Theor. Comput. Sci. 412, 892 (2011)] and similar to the parametric model of Reichardt and Bornholdt [Phys. Rev. E 74, 016110 (2006)]) with a single parameter α that balances the fraction of within community edges and the expected fraction of edges according to the configuration model. An exact algorithm is proposed to find optimal solutions for all values of α as well as the corresponding successive intervals of α values for which they are optimal. This algorithm relies upon a routine for exact modularity maximization and is limited to moderate size instances. An agglomerative hierarchical heuristic is therefore proposed to address parametric modularity detection in large networks. At each iteration the smallest value of α for which it is worthwhile to merge two communities of the current partition is found. Then merging is performed and the data are updated accordingly. An implementation is proposed with the same time and space complexity as the well-known Clauset-Newman-Moore (CNM) heuristic [Phys. Rev. E 70, 066111 (2004)]. Experimental results on artificial and real world problems show that (i) communities are detected by both exact and heuristic methods for all values of the parameter α; (ii) the dendrogram summarizing the results of the heuristic method provides a useful tool for substantive analysis, as illustrated particularly on a Les Misérables data set; (iii) the difference between the parametric modularity values given by the exact method and those given by the heuristic is moderate; (iv) the heuristic version of the proposed parametric method, viewed as a modularity maximization tool, gives better results than the CNM heuristic for large instances.
Saez-Rodriguez, Julio; Gayer, Stefan; Ginkel, Martin; Gilles, Ernst Dieter
2008-08-15
The modularity of biochemical networks in general, and signaling networks in particular, has been extensively studied over the past few years. It has been proposed to be a useful property to analyze signaling networks: by decomposing the network into subsystems, more manageable units are obtained that are easier to analyze. While many powerful algorithms are available to identify modules in protein interaction networks, less attention has been paid to signaling networks de.ned as chemical systems. Such a decomposition would be very useful as most quantitative models are de.ned using the latter, more detailed formalism. Here, we introduce a novel method to decompose biochemical networks into modules so that the bidirectional (retroactive) couplings among the modules are minimized. Our approach adapts a method to detect community structures, and applies it to the so-called retroactivity matrix that characterizes the couplings of the network. Only the structure of the network, e.g. in SBML format, is required. Furthermore, the modularized models can be loaded into ProMoT, a modeling tool which supports modular modeling. This allows visualization of the models, exploiting their modularity and easy generation of models of one or several modules for further analysis. The method is applied to several relevant cases, including an entangled model of the EGF-induced MAPK cascade and a comprehensive model of EGF signaling, demonstrating its ability to uncover meaningful modules. Our approach can thus help to analyze large networks, especially when little a priori knowledge on the structure of the network is available. The decomposition algorithms implemented in MATLAB (Mathworks, Inc.) are freely available upon request. ProMoT is freely available at http://www.mpi-magdeburg.mpg.de/projects/promot. Supplementary data are available at Bioinformatics online.
Nonparametric Bayesian inference of the microcanonical stochastic block model
NASA Astrophysics Data System (ADS)
Peixoto, Tiago P.
2017-01-01
A principled approach to characterize the hidden modular structure of networks is to formulate generative models and then infer their parameters from data. When the desired structure is composed of modules or "communities," a suitable choice for this task is the stochastic block model (SBM), where nodes are divided into groups, and the placement of edges is conditioned on the group memberships. Here, we present a nonparametric Bayesian method to infer the modular structure of empirical networks, including the number of modules and their hierarchical organization. We focus on a microcanonical variant of the SBM, where the structure is imposed via hard constraints, i.e., the generated networks are not allowed to violate the patterns imposed by the model. We show how this simple model variation allows simultaneously for two important improvements over more traditional inference approaches: (1) deeper Bayesian hierarchies, with noninformative priors replaced by sequences of priors and hyperpriors, which not only remove limitations that seriously degrade the inference on large networks but also reveal structures at multiple scales; (2) a very efficient inference algorithm that scales well not only for networks with a large number of nodes and edges but also with an unlimited number of modules. We show also how this approach can be used to sample modular hierarchies from the posterior distribution, as well as to perform model selection. We discuss and analyze the differences between sampling from the posterior and simply finding the single parameter estimate that maximizes it. Furthermore, we expose a direct equivalence between our microcanonical approach and alternative derivations based on the canonical SBM.
Leavesley, G.H.; Markstrom, S.L.; Restrepo, Pedro J.; Viger, R.J.
2002-01-01
A modular approach to model design and construction provides a flexible framework in which to focus the multidisciplinary research and operational efforts needed to facilitate the development, selection, and application of the most robust distributed modelling methods. A variety of modular approaches have been developed, but with little consideration for compatibility among systems and concepts. Several systems are proprietary, limiting any user interaction. The US Geological Survey modular modelling system (MMS) is a modular modelling framework that uses an open source software approach to enable all members of the scientific community to address collaboratively the many complex issues associated with the design, development, and application of distributed hydrological and environmental models. Implementation of a common modular concept is not a trivial task. However, it brings the resources of a larger community to bear on the problems of distributed modelling, provides a framework in which to compare alternative modelling approaches objectively, and provides a means of sharing the latest modelling advances. The concepts and components of the MMS are described and an example application of the MMS, in a decision-support system context, is presented to demonstrate current system capabilities. Copyright ?? 2002 John Wiley and Sons, Ltd.
Brain modularity controls the critical behavior of spontaneous activity.
Russo, R; Herrmann, H J; de Arcangelis, L
2014-03-13
The human brain exhibits a complex structure made of scale-free highly connected modules loosely interconnected by weaker links to form a small-world network. These features appear in healthy patients whereas neurological diseases often modify this structure. An important open question concerns the role of brain modularity in sustaining the critical behaviour of spontaneous activity. Here we analyse the neuronal activity of a model, successful in reproducing on non-modular networks the scaling behaviour observed in experimental data, on a modular network implementing the main statistical features measured in human brain. We show that on a modular network, regardless the strength of the synaptic connections or the modular size and number, activity is never fully scale-free. Neuronal avalanches can invade different modules which results in an activity depression, hindering further avalanche propagation. Critical behaviour is solely recovered if inter-module connections are added, modifying the modular into a more random structure.
Goekoop, Rutger; Goekoop, Jaap G.; Scholte, H. Steven
2012-01-01
Introduction Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. Aim To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). Methods 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. Results At facet level, NCS showed a best match (96.2%) with a ‘confirmatory’ 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with ‘confirmatory’ 5-FS and ‘exploratory’ 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. Conclusion We present the first optimized network graph of personality traits according to the NEO-PI-R: a ‘Personality Web’. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network. PMID:23284713
Goekoop, Rutger; Goekoop, Jaap G; Scholte, H Steven
2012-01-01
Human personality is described preferentially in terms of factors (dimensions) found using factor analysis. An alternative and highly related method is network analysis, which may have several advantages over factor analytic methods. To directly compare the ability of network community detection (NCD) and principal component factor analysis (PCA) to examine modularity in multidimensional datasets such as the neuroticism-extraversion-openness personality inventory revised (NEO-PI-R). 434 healthy subjects were tested on the NEO-PI-R. PCA was performed to extract factor structures (FS) of the current dataset using both item scores and facet scores. Correlational network graphs were constructed from univariate correlation matrices of interactions between both items and facets. These networks were pruned in a link-by-link fashion while calculating the network community structure (NCS) of each resulting network using the Wakita Tsurumi clustering algorithm. NCSs were matched against FS and networks of best matches were kept for further analysis. At facet level, NCS showed a best match (96.2%) with a 'confirmatory' 5-FS. At item level, NCS showed a best match (80%) with the standard 5-FS and involved a total of 6 network clusters. Lesser matches were found with 'confirmatory' 5-FS and 'exploratory' 6-FS of the current dataset. Network analysis did not identify facets as a separate level of organization in between items and clusters. A small-world network structure was found in both item- and facet level networks. We present the first optimized network graph of personality traits according to the NEO-PI-R: a 'Personality Web'. Such a web may represent the possible routes that subjects can take during personality development. NCD outperforms PCA by producing plausible modularity at item level in non-standard datasets, and can identify the key roles of individual items and clusters in the network.
Finding modules and hierarchy in weighted financial network using transfer entropy
NASA Astrophysics Data System (ADS)
Yook, Soon-Hyung; Chae, Huiseung; Kim, Jinho; Kim, Yup
2016-04-01
We study the modular structure of financial network based on the transfer entropy (TE). From the comparison with the obtained modular structure using the cross-correlation (CC), we find that TE and CC both provide well organized modular structure and the hierarchical relationship between each industrial group when the time scale of the measurement is less than one month. However, when the time scale of the measurement becomes larger than one month, we find that the modular structure from CC cannot correctly reflect the known industrial classification and their hierarchy. In addition the measured maximum modularity, Qmax, for TE is always larger than that for CC, which indicates that TE is a better weight measure than CC for the system with asymmetric relationship.
The optimal community detection of software based on complex networks
NASA Astrophysics Data System (ADS)
Huang, Guoyan; Zhang, Peng; Zhang, Bing; Yin, Tengteng; Ren, Jiadong
2016-02-01
The community structure is important for software in terms of understanding the design patterns, controlling the development and the maintenance process. In order to detect the optimal community structure in the software network, a method Optimal Partition Software Network (OPSN) is proposed based on the dependency relationship among the software functions. First, by analyzing the information of multiple execution traces of one software, we construct Software Execution Dependency Network (SEDN). Second, based on the relationship among the function nodes in the network, we define Fault Accumulation (FA) to measure the importance of the function node and sort the nodes with measure results. Third, we select the top K(K=1,2,…) nodes as the core of the primal communities (only exist one core node). By comparing the dependency relationships between each node and the K communities, we put the node into the existing community which has the most close relationship. Finally, we calculate the modularity with different initial K to obtain the optimal division. With experiments, the method OPSN is verified to be efficient to detect the optimal community in various softwares.
ERIC Educational Resources Information Center
Kolko, David J.; Dorn, Lorah D.; Bukstein, Oscar G.; Pardini, Dustin; Holden, Elizabeth A.; Hart, Jonathan
2009-01-01
This study examines the treatment outcomes of 139, 6-11 year-old, clinically referred boys and girls diagnosed with Oppositional Defiant Disorder (ODD) or Conduct Disorder (CD) who were randomly assigned to a modular-based treatment protocol that was applied by research study clinicians either in the community (COMM) or a clinic office (CLINIC).…
Community Detection in Signed Networks: the Role of Negative ties in Different Scales
Esmailian, Pouya; Jalili, Mahdi
2015-01-01
Extracting community structure of complex network systems has many applications from engineering to biology and social sciences. There exist many algorithms to discover community structure of networks. However, it has been significantly under-explored for networks with positive and negative links as compared to unsigned ones. Trying to fill this gap, we measured the quality of partitions by introducing a Map Equation for signed networks. It is based on the assumption that negative relations weaken positive flow from a node towards a community, and thus, external (internal) negative ties increase the probability of staying inside (escaping from) a community. We further extended the Constant Potts Model, providing a map spectrum for signed networks. Accordingly, a partition is selected through balancing between abridgment and expatiation of a signed network. Most importantly, multi-scale spectrum of signed networks revealed how informative are negative ties in different scales, and quantified the topological placement of negative ties between dense positive ones. Moreover, an inconsistency was found in the signed Modularity: as the number of negative ties increases, the density of positive ties is neglected more. These results shed lights on the community structure of signed networks. PMID:26395815
Multiway spectral community detection in networks
NASA Astrophysics Data System (ADS)
Zhang, Xiao; Newman, M. E. J.
2015-11-01
One of the most widely used methods for community detection in networks is the maximization of the quality function known as modularity. Of the many maximization techniques that have been used in this context, some of the most conceptually attractive are the spectral methods, which are based on the eigenvectors of the modularity matrix. Spectral algorithms have, however, been limited, by and large, to the division of networks into only two or three communities, with divisions into more than three being achieved by repeated two-way division. Here we present a spectral algorithm that can directly divide a network into any number of communities. The algorithm makes use of a mapping from modularity maximization to a vector partitioning problem, combined with a fast heuristic for vector partitioning. We compare the performance of this spectral algorithm with previous approaches and find it to give superior results, particularly in cases where community sizes are unbalanced. We also give demonstrative applications of the algorithm to two real-world networks and find that it produces results in good agreement with expectations for the networks studied.
Phylogenetic tree and community structure from a Tangled Nature model.
Canko, Osman; Taşkın, Ferhat; Argın, Kamil
2015-10-07
In evolutionary biology, the taxonomy and origination of species are widely studied subjects. An estimation of the evolutionary tree can be done via available DNA sequence data. The calculation of the tree is made by well-known and frequently used methods such as maximum likelihood and neighbor-joining. In order to examine the results of these methods, an evolutionary tree is pursued computationally by a mathematical model, called Tangled Nature. A relatively small genome space is investigated due to computational burden and it is found that the actual and predicted trees are in reasonably good agreement in terms of shape. Moreover, the speciation and the resulting community structure of the food-web are investigated by modularity. Copyright © 2015 Elsevier Ltd. All rights reserved.
Jacobsen, Rannveig M; Sverdrup-Thygeson, Anne; Kauserud, Håvard; Birkemoe, Tone
2018-04-11
Ecological networks are composed of interacting communities that influence ecosystem structure and function. Fungi are the driving force for ecosystem processes such as decomposition and carbon sequestration in terrestrial habitats, and are strongly influenced by interactions with invertebrates. Yet, interactions in detritivore communities have rarely been considered from a network perspective. In the present study, we analyse the interaction networks between three functional guilds of fungi and insects sampled from dead wood. Using DNA metabarcoding to identify fungi, we reveal a diversity of interactions differing in specificity in the detritivore networks, involving three guilds of fungi. Plant pathogenic fungi were relatively unspecialized in their interactions with insects inhabiting dead wood, while interactions between the insects and wood-decay fungi exhibited the highest degree of specialization, which was similar to estimates for animal-mediated seed dispersal networks in previous studies. The low degree of specialization for insect symbiont fungi was unexpected. In general, the pooled insect-fungus networks were significantly more specialized, more modular and less nested than randomized networks. Thus, the detritivore networks had an unusual anti-nested structure. Future studies might corroborate whether this is a common aspect of networks based on interactions with fungi, possibly owing to their often intense competition for substrate. © 2018 The Author(s).
Modular representation of layered neural networks.
Watanabe, Chihiro; Hiramatsu, Kaoru; Kashino, Kunio
2018-01-01
Layered neural networks have greatly improved the performance of various applications including image processing, speech recognition, natural language processing, and bioinformatics. However, it is still difficult to discover or interpret knowledge from the inference provided by a layered neural network, since its internal representation has many nonlinear and complex parameters embedded in hierarchical layers. Therefore, it becomes important to establish a new methodology by which layered neural networks can be understood. In this paper, we propose a new method for extracting a global and simplified structure from a layered neural network. Based on network analysis, the proposed method detects communities or clusters of units with similar connection patterns. We show its effectiveness by applying it to three use cases. (1) Network decomposition: it can decompose a trained neural network into multiple small independent networks thus dividing the problem and reducing the computation time. (2) Training assessment: the appropriateness of a trained result with a given hyperparameter or randomly chosen initial parameters can be evaluated by using a modularity index. And (3) data analysis: in practical data it reveals the community structure in the input, hidden, and output layers, which serves as a clue for discovering knowledge from a trained neural network. Copyright © 2017 Elsevier Ltd. All rights reserved.
Research on energy stock market associated network structure based on financial indicators
NASA Astrophysics Data System (ADS)
Xi, Xian; An, Haizhong
2018-01-01
A financial market is a complex system consisting of many interacting units. In general, due to the various types of information exchange within the industry, there is a relationship between the stocks that can reveal their clear structural characteristics. Complex network methods are powerful tools for studying the internal structure and function of the stock market, which allows us to better understand the stock market. Applying complex network methodology, a stock associated network model based on financial indicators is created. Accordingly, we set threshold value and use modularity to detect the community network, and we analyze the network structure and community cluster characteristics of different threshold situations. The study finds that the threshold value of 0.7 is the abrupt change point of the network. At the same time, as the threshold value increases, the independence of the community strengthens. This study provides a method of researching stock market based on the financial indicators, exploring the structural similarity of financial indicators of stocks. Also, it provides guidance for investment and corporate financial management.
Parallel heuristics for scalable community detection
Lu, Hao; Halappanavar, Mahantesh; Kalyanaraman, Ananth
2015-08-14
Community detection has become a fundamental operation in numerous graph-theoretic applications. Despite its potential for application, there is only limited support for community detection on large-scale parallel computers, largely owing to the irregular and inherently sequential nature of the underlying heuristics. In this paper, we present parallelization heuristics for fast community detection using the Louvain method as the serial template. The Louvain method is an iterative heuristic for modularity optimization. Originally developed in 2008, the method has become increasingly popular owing to its ability to detect high modularity community partitions in a fast and memory-efficient manner. However, the method ismore » also inherently sequential, thereby limiting its scalability. Here, we observe certain key properties of this method that present challenges for its parallelization, and consequently propose heuristics that are designed to break the sequential barrier. For evaluation purposes, we implemented our heuristics using OpenMP multithreading, and tested them over real world graphs derived from multiple application domains. Compared to the serial Louvain implementation, our parallel implementation is able to produce community outputs with a higher modularity for most of the inputs tested, in comparable number or fewer iterations, while providing real speedups of up to 16x using 32 threads.« less
Energy Landscape of Social Balance
NASA Astrophysics Data System (ADS)
Marvel, Seth A.; Strogatz, Steven H.; Kleinberg, Jon M.
2009-11-01
We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social “balance” allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.
Energy landscape of social balance.
Marvel, Seth A; Strogatz, Steven H; Kleinberg, Jon M
2009-11-06
We model a close-knit community of friends and enemies as a fully connected network with positive and negative signs on its edges. Theories from social psychology suggest that certain sign patterns are more stable than others. This notion of social "balance" allows us to define an energy landscape for such networks. Its structure is complex: numerical experiments reveal a landscape dimpled with local minima of widely varying energy levels. We derive rigorous bounds on the energies of these local minima and prove that they have a modular structure that can be used to classify them.
Complex network analysis of resting-state fMRI of the brain.
Anwar, Abdul Rauf; Hashmy, Muhammad Yousaf; Imran, Bilal; Riaz, Muhammad Hussnain; Mehdi, Sabtain Muhammad Muntazir; Muthalib, Makii; Perrey, Stephane; Deuschl, Gunther; Groppa, Sergiu; Muthuraman, Muthuraman
2016-08-01
Due to the fact that the brain activity hardly ever diminishes in healthy individuals, analysis of resting state functionality of the brain seems pertinent. Various resting state networks are active inside the idle brain at any time. Based on various neuro-imaging studies, it is understood that various structurally distant regions of the brain could be functionally connected. Regions of the brain, that are functionally connected, during rest constitutes to the resting state network. In the present study, we employed the complex network measures to estimate the presence of community structures within a network. Such estimate is named as modularity. Instead of using a traditional correlation matrix, we used a coherence matrix taken from the causality measure between different nodes. Our results show that in prolonged resting state the modularity starts to decrease. This decrease was observed in all the resting state networks and on both sides of the brain. Our study highlights the usage of coherence matrix instead of correlation matrix for complex network analysis.
Modular Courses in British Higher Education: A Critical Assessment
ERIC Educational Resources Information Center
Church, Clive
1975-01-01
The trends towards modular course structures is examined. British conceptions of modularization are compared with American interpretations of modular instruction, the former shown to be concerned almost exclusively with content, the latter attempting more radical changes in students' learning behavior. Rationales for British modular schemes are…
Brough, David B; Wheeler, Daniel; Kalidindi, Surya R
2017-03-01
There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers.
Brough, David B; Wheeler, Daniel; Kalidindi, Surya R.
2017-01-01
There is a critical need for customized analytics that take into account the stochastic nature of the internal structure of materials at multiple length scales in order to extract relevant and transferable knowledge. Data driven Process-Structure-Property (PSP) linkages provide systemic, modular and hierarchical framework for community driven curation of materials knowledge, and its transference to design and manufacturing experts. The Materials Knowledge Systems in Python project (PyMKS) is the first open source materials data science framework that can be used to create high value PSP linkages for hierarchical materials that can be leveraged by experts in materials science and engineering, manufacturing, machine learning and data science communities. This paper describes the main functions available from this repository, along with illustrations of how these can be accessed, utilized, and potentially further refined by the broader community of researchers. PMID:28690971
del Sol, Antonio; Araúzo-Bravo, Marcos J; Amoros, Dolors; Nussinov, Ruth
2007-01-01
Background Allosteric communications are vital for cellular signaling. Here we explore a relationship between protein architectural organization and shortcuts in signaling pathways. Results We show that protein domains consist of modules interconnected by residues that mediate signaling through the shortest pathways. These mediating residues tend to be located at the inter-modular boundaries, which are more rigid and display a larger number of long-range interactions than intra-modular regions. The inter-modular boundaries contain most of the residues centrally conserved in the protein fold, which may be crucial for information transfer between amino acids. Our approach to modular decomposition relies on a representation of protein structures as residue-interacting networks, and removal of the most central residue contacts, which are assumed to be crucial for allosteric communications. The modular decomposition of 100 multi-domain protein structures indicates that modules constitute the building blocks of domains. The analysis of 13 allosteric proteins revealed that modules characterize experimentally identified functional regions. Based on the study of an additional functionally annotated dataset of 115 proteins, we propose that high-modularity modules include functional sites and are the basic functional units. We provide examples (the Gαs subunit and P450 cytochromes) to illustrate that the modular architecture of active sites is linked to their functional specialization. Conclusion Our method decomposes protein structures into modules, allowing the study of signal transmission between functional sites. A modular configuration might be advantageous: it allows signaling proteins to expand their regulatory linkages and may elicit a broader range of control mechanisms either via modular combinations or through modulation of inter-modular linkages. PMID:17531094
NASA Astrophysics Data System (ADS)
Gui, Chun; Zhang, Ruisheng; Zhao, Zhili; Wei, Jiaxuan; Hu, Rongjing
In order to deal with stochasticity in center node selection and instability in community detection of label propagation algorithm, this paper proposes an improved label propagation algorithm named label propagation algorithm based on community belonging degree (LPA-CBD) that employs community belonging degree to determine the number and the center of community. The general process of LPA-CBD is that the initial community is identified by the nodes with the maximum degree, and then it is optimized or expanded by community belonging degree. After getting the rough structure of network community, the remaining nodes are labeled by using label propagation algorithm. The experimental results on 10 real-world networks and three synthetic networks show that LPA-CBD achieves reasonable community number, better algorithm accuracy and higher modularity compared with other four prominent algorithms. Moreover, the proposed algorithm not only has lower algorithm complexity and higher community detection quality, but also improves the stability of the original label propagation algorithm.
24 CFR 3282.12 - Excluded structures-modular homes.
Code of Federal Regulations, 2013 CFR
2013-04-01
... 24 Housing and Urban Development 5 2013-04-01 2013-04-01 false Excluded structures-modular homes... HOUSING AND URBAN DEVELOPMENT MANUFACTURED HOME PROCEDURAL AND ENFORCEMENT REGULATIONS General § 3282.12 Excluded structures—modular homes. (a) The purpose of this section is to provide the certification...
24 CFR 3282.12 - Excluded structures-modular homes.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Excluded structures-modular homes... HOUSING AND URBAN DEVELOPMENT MANUFACTURED HOME PROCEDURAL AND ENFORCEMENT REGULATIONS General § 3282.12 Excluded structures—modular homes. (a) The purpose of this section is to provide the certification...
Cophylogenetic signal is detectable in pollination interactions across ecological scales.
Hutchinson, Matthew C; Cagua, Edgar Fernando; Stouffer, Daniel B
2017-10-01
That evolutionary history can influence the way that species interact is a basic tenet of evolutionary ecology. However, when the role of evolution in determining ecological interactions is investigated, focus typically centers on just one side of the interaction. A cophylogenetic signal, the congruence of evolutionary history across both sides of an ecological interaction, extends these previous explorations and provides a more complete picture of how evolutionary patterns influence the way species interact. To date, cophylogenetic signal has most typically been studied in interactions that occur between fine taxonomic clades that show high intimacy. In this study, we took an alternative approach and made an exhaustive assessment of cophylogeny in pollination interactions. To do so, we assessed the strength of cophylogenetic signal at four distinct scales of pollination interaction: (1) across plant-pollinator associations globally, (2) in local pollination communities, (3) within the modular structure of those communities, and (4) in individual modules. We did so using a globally distributed dataset comprised of 54 pollination networks, over 4000 species, and over 12,000 interactions. Within these data, we detected cophylogenetic signal at all four scales. Cophylogenetic signal was found at the level of plant-pollinator interactions on a global scale and in the majority of pollination communities. At the scale defined by the modular structure within those communities, however, we observed a much weaker cophylogenetic signal. Cophylogenetic signal was detectable in a significant proportion of individual modules and most typically when within-module phylogenetic diversity was low. In sum, the detection of cophylogenetic signal in pollination interactions across scales provides a new dimension to the story of how past evolution shapes extant pollinator-angiosperm interactions. © 2017 by the Ecological Society of America.
Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California.
Peiper, Nicholas C; Baumgartner, Peter M; Chew, Robert F; Hsieh, Yuli P; Bieler, Gayle S; Bobashev, Georgiy V; Siege, Christopher; Zarkin, Gary A
2017-07-04
Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks. This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California. From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities. The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles. The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time. ©Nicholas C Peiper, Peter M Baumgartner, Robert F Chew, Yuli P Hsieh, Gayle S Bieler, Georgiy V Bobashev, Christopher Siege, Gary A Zarkin. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 04.07.2017.
Hierarchical organization of brain functional networks during visual tasks.
Zhuo, Zhao; Cai, Shi-Min; Fu, Zhong-Qian; Zhang, Jie
2011-09-01
The functional network of the brain is known to demonstrate modular structure over different hierarchical scales. In this paper, we systematically investigated the hierarchical modular organizations of the brain functional networks that are derived from the extent of phase synchronization among high-resolution EEG time series during a visual task. In particular, we compare the modular structure of the functional network from EEG channels with that of the anatomical parcellation of the brain cortex. Our results show that the modular architectures of brain functional networks correspond well to those from the anatomical structures over different levels of hierarchy. Most importantly, we find that the consistency between the modular structures of the functional network and the anatomical network becomes more pronounced in terms of vision, sensory, vision-temporal, motor cortices during the visual task, which implies that the strong modularity in these areas forms the functional basis for the visual task. The structure-function relationship further reveals that the phase synchronization of EEG time series in the same anatomical group is much stronger than that of EEG time series from different anatomical groups during the task and that the hierarchical organization of functional brain network may be a consequence of functional segmentation of the brain cortex.
Lee, Seungjae; Park, Jaeseong; Kwak, Euishin; Shon, Sudeok; Kang, Changhoon; Choi, Hosoon
2017-03-06
Modular systems have been mostly researched in relatively low-rise structures but, lately, their applications to mid- to high-rise structures began to be reviewed, and research interest in new modularization subjects has increased. The application of modular systems to mid- to high-rise structures requires the structural stability of the frame and connections that consist of units, and the evaluation of the stiffness of structures that are combined in units. However, the combination of general units causes loss of the cross-section of columns or beams, resulting in low seismic performance and hindering installation works in the field. In addition, the evaluation of a frame considering such a cross-sectional loss is not easy. Therefore, it is necessary to develop a joint that is stable and easy to install. In the study, a rigidly connected modular system was proposed as a moment-resisting frame for a unit modular system, and their joints were developed and their performances were compared. The proposed system changed the ceiling beam into a bracket type to fasten bolts. It can be merged with other seismic force-resisting systems. To verify the seismic performance of the proposed system, a cyclic loading test was conducted, and the rigidly connected joint performance and integrated behavior at the joint of modular units were investigated. From the experimental results, the maximum resisting force of the proposed connection exceeded the theoretical parameters, indicating that a rigid joint structural performance could be secured.
Vick-Majors, Trista J; Priscu, John C; Amaral-Zettler, Linda A
2014-04-01
High-latitude environments, such as the Antarctic McMurdo Dry Valley lakes, are subject to seasonally segregated light-dark cycles, which have important consequences for microbial diversity and function on an annual basis. Owing largely to the logistical difficulties of sampling polar environments during the darkness of winter, little is known about planktonic microbial community responses to the cessation of photosynthetic primary production during the austral sunset, which lingers from approximately February to April. Here, we hypothesized that changes in bacterial, archaeal and eukaryotic community structure, particularly shifts in favor of chemolithotrophs and mixotrophs, would manifest during the transition to polar night. Our work represents the first concurrent molecular characterization, using 454 pyrosequencing of hypervariable regions of the small-subunit ribosomal RNA gene, of bacterial, archaeal and eukaryotic communities in permanently ice-covered lakes Fryxell and Bonney, before and during the polar night transition. We found vertically stratified populations that varied at the community and/or operational taxonomic unit-level between lakes and seasons. Network analysis based on operational taxonomic unit level interactions revealed nonrandomly structured microbial communities organized into modules (groups of taxa) containing key metabolic potential capacities, including photoheterotrophy, mixotrophy and chemolithotrophy, which are likely to be differentially favored during the transition to polar night.
Opinion diversity and community formation in adaptive networks
NASA Astrophysics Data System (ADS)
Yu, Y.; Xiao, G.; Li, G.; Tay, W. P.; Teoh, H. F.
2017-10-01
It is interesting and of significant importance to investigate how network structures co-evolve with opinions. In this article, we show that, a simple model integrating consensus formation, link rewiring, and opinion change allows complex system dynamics to emerge, driving the system into a dynamic equilibrium with the co-existence of diversified opinions. Specifically, similar opinion holders may form into communities yet with no strict community consensus; and rather than being separated into disconnected communities, different communities are connected by a non-trivial proportion of inter-community links. More importantly, we show that the complex dynamics may lead to different numbers of communities at the steady state with a given tolerance between different opinion holders. We construct a framework for theoretically analyzing the co-evolution process. Theoretical analysis and extensive simulation results reveal some useful insights into the complex co-evolution process, including the formation of dynamic equilibrium, the transition between different steady states with different numbers of communities, and the dynamics between opinion distribution and network modularity.
Towards a Formal Basis for Modular Safety Cases
NASA Technical Reports Server (NTRS)
Denney, Ewen; Pai, Ganesh
2015-01-01
Safety assurance using argument-based safety cases is an accepted best-practice in many safety-critical sectors. Goal Structuring Notation (GSN), which is widely used for presenting safety arguments graphically, provides a notion of modular arguments to support the goal of incremental certification. Despite the efforts at standardization, GSN remains an informal notation whereas the GSN standard contains appreciable ambiguity especially concerning modular extensions. This, in turn, presents challenges when developing tools and methods to intelligently manipulate modular GSN arguments. This paper develops the elements of a theory of modular safety cases, leveraging our previous work on formalizing GSN arguments. Using example argument structures we highlight some ambiguities arising through the existing guidance, present the intuition underlying the theory, clarify syntax, and address modular arguments, contracts, well-formedness and well-scopedness of modules. Based on this theory, we have a preliminary implementation of modular arguments in our toolset, AdvoCATE.
Larson, Diane L.; Droege, Sam; Rabie, Paul A.; Larson, Jennifer L.; Devalez, Jelle; Haar, Milton; McDermott-Kubeczko, Margaret
2014-01-01
1. Analyses of flower-visitor interaction networks allow application of community-level information to conservation problems, but management recommendations that ensue from such analyses are not well characterized. Results of modularity analyses, which detect groups of species (modules) that interact more with each other than with species outside their module, may be particularly applicable to management concerns. 2. We conducted modularity analyses of networks surrounding a rare endemic annual plant, Eriogonum visheri, at Badlands National Park, USA, in 2010 and 2011. Plant species visited were determined by pollen on insect bodies and by flower species upon which insects were captured. Roles within modules (network hub, module hub, connector and peripheral, in decreasing order of network structural importance) were determined for each species. 3. Relationships demonstrated by the modularity analysis, in concert with knowledge of pollen species carried by insects, allowed us to infer effects of two invasive species on E. visheri. Sharing a module increased risk of interspecific pollen transfer to E. visheri. Control of invasive Salsola tragus, which shared a module with E. visheri, is therefore a prudent management objective, but lack of control of invasive Melilotus officinalis, which occupied a different module, is unlikely to negatively affect pollination of E. visheri. Eriogonum pauciflorum may occupy a key position in this network, supporting insects from the E. visheri module when E. visheri is less abundant. 4. Year-to-year variation in species' roles suggests management decisions must be based on observations over several years. Information on pollen deposition on stigmas would greatly strengthen inferences made from the modularity analysis. 5. Synthesis and applications: Assessing the consequences of pollination, whether at the community or individual level, is inherently time-consuming. A trade-off exists: rather than an estimate of fitness effects, the network approach provides a broad understanding of the relationships among insect visitors and other plant species that may affect the focal rare plant. Knowledge of such relationships allows managers to detect, target and prioritize control of only the important subset of invasive species present and identify other species that may augment a rare species' population stability, such as E. pauciflorum in our study.
Domain organizations of modular extracellular matrix proteins and their evolution.
Engel, J
1996-11-01
Multidomain proteins which are composed of modular units are a rather recent invention of evolution. Domains are defined as autonomously folding regions of a protein, and many of them are similar in sequence and structure, indicating common ancestry. Their modular nature is emphasized by frequent repetitions in identical or in different proteins and by a large number of different combinations with other domains. The extracellular matrix is perhaps the largest biological system composed of modular mosaic proteins, and its astonishing complexity and diversity are based on them. A cluster of minireviews on modular proteins is being published in Matrix Biology. These deal with the evolution of modular proteins, the three-dimensional structure of domains and the ways in which these interact in a multidomain protein. They discuss structure-function relationships in calcium binding domains, collagen helices, alpha-helical coiled-coil domains and C-lectins. The present minireview is focused on some general aspects and serves as an introduction to the cluster.
Modularization--A Road to Relevance?
ERIC Educational Resources Information Center
Palow, William P.
This paper describes a modular program at a community college for instructing non-science majors in college algebra. The two-course sequence is comprised of four modules each and successful completion of a module is required before a student proceeds to the next. Placement, grading policies, and scheduling are all discussed. A formative evaluation…
Portable or Modular? There Is a Difference....
ERIC Educational Resources Information Center
Morton, Mike
2002-01-01
Describes differences between two types of school facilities: portable (prebuilt, temporary wood structure installed on site) and modular (method of construction for permanent buildings). Provides details of modular construction. (PKP)
Lee, Seungjae; Park, Jaeseong; Kwak, Euishin; Shon, Sudeok; Kang, Changhoon; Choi, Hosoon
2017-01-01
Modular systems have been mostly researched in relatively low-rise structures but, lately, their applications to mid- to high-rise structures began to be reviewed, and research interest in new modularization subjects has increased. The application of modular systems to mid- to high-rise structures requires the structural stability of the frame and connections that consist of units, and the evaluation of the stiffness of structures that are combined in units. However, the combination of general units causes loss of the cross-section of columns or beams, resulting in low seismic performance and hindering installation works in the field. In addition, the evaluation of a frame considering such a cross-sectional loss is not easy. Therefore, it is necessary to develop a joint that is stable and easy to install. In the study, a rigidly connected modular system was proposed as a moment-resisting frame for a unit modular system, and their joints were developed and their performances were compared. The proposed system changed the ceiling beam into a bracket type to fasten bolts. It can be merged with other seismic force-resisting systems. To verify the seismic performance of the proposed system, a cyclic loading test was conducted, and the rigidly connected joint performance and integrated behavior at the joint of modular units were investigated. From the experimental results, the maximum resisting force of the proposed connection exceeded the theoretical parameters, indicating that a rigid joint structural performance could be secured. PMID:28772622
Analysis of the structure of complex networks at different resolution levels
NASA Astrophysics Data System (ADS)
Arenas, A.; Fernández, A.; Gómez, S.
2008-05-01
Modular structure is ubiquitous in real-world complex networks, and its detection is important because it gives insights into the structure-functionality relationship. The standard approach is based on the optimization of a quality function, modularity, which is a relative quality measure for the partition of a network into modules. Recently, some authors (Fortunato and Barthélemy 2007 Proc. Natl Acad. Sci. USA 104 36 and Kumpula et al 2007 Eur. Phys. J. B 56 41) have pointed out that the optimization of modularity has a fundamental drawback: the existence of a resolution limit beyond which no modular structure can be detected even though these modules might have their own entity. The reason is that several topological descriptions of the network coexist at different scales, which is, in general, a fingerprint of complex systems. Here, we propose a method that allows for multiple resolution screening of the modular structure. The method has been validated using synthetic networks, discovering the predefined structures at all scales. Its application to two real social networks allows us to find the exact splits reported in the literature, as well as the substructure beyond the actual split.
Patterns of interactions of a large fish-parasite network in a tropical floodplain.
Lima, Dilermando P; Giacomini, Henrique C; Takemoto, Ricardo M; Agostinho, Angelo A; Bini, Luis M
2012-07-01
1. Describing and explaining the structure of species interaction networks is of paramount importance for community ecology. Yet much has to be learned about the mechanisms responsible for major patterns, such as nestedness and modularity in different kinds of systems, of which large and diverse networks are a still underrepresented and scarcely studied fraction. 2. We assembled information on fishes and their parasites living in a large floodplain of key ecological importance for freshwater ecosystems in the Paraná River basin in South America. The resulting fish-parasite network containing 72 and 324 species of fishes and parasites, respectively, was analysed to investigate the patterns of nestedness and modularity as related to fish and parasite features. 3. Nestedness was found in the entire network and among endoparasites, multiple-host life cycle parasites and native hosts, but not in networks of ectoparasites, single-host life cycle parasites and non-native fishes. All networks were significantly modular. Taxonomy was the major host's attribute influencing both nestedness and modularity: more closely related host species tended to be associated with more nested parasite compositions and had greater chance of belonging to the same network module. Nevertheless, host abundance had a positive relationship with nestedness when only native host species pairs of the same network module were considered for analysis. 4. These results highlight the importance of evolutionary history of hosts in linking patterns of nestedness and formation of modules in the network. They also show that functional attributes of parasites (i.e. parasitism mode and life cycle) and origin of host populations (i.e. natives versus non-natives) are crucial to define the relative contribution of these two network properties and their dependence on other ecological factors (e.g. host abundance), with potential implications for community dynamics and stability. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.
The Involvement of Career and Technical Education Advisory Committees in Modularizing Curriculum
ERIC Educational Resources Information Center
Malosh, Ann M.
2012-01-01
The emergence of modularized curriculum in community college career and technical education (CTE) programs has received substantial attention over the last decade, with researchers suggesting that this type of curriculum redesign may assist with student retention and success. The purpose of this study was to describe advisory committee member…
Diversity and patterns of interaction of an anuran-parasite network in a neotropical wetland.
Campião, K M; Ribas, A; Tavares, L E R
2015-12-01
We describe the diversity and structure of a host-parasite network of 11 anuran species and their helminth parasites in the Pantanal wetland, Brazil. Specifically, we investigate how the heterogeneous use of space by hosts changes parasite community diversity, and how the local pool of parasites exploits sympatric host species of different habits. We examined 229 anuran specimens, interacting with 32 helminth parasite taxa. Mixed effect models indicated the influence of anuran body size, but not habit, as a determinant of parasite species richness. Variation in parasite taxonomic diversity, however, was not significantly correlated with host size or habit. Parasite community composition was not correlated with host phylogeny, indicating no strong effect of the evolutionary relationships among anurans on the similarities in their parasite communities. Host-parasite network showed a nested and non-modular pattern of interaction, which is probably a result of the low host specificity observed for most helminths in this study. Overall, we found host body size was important in determining parasite community richness, whereas low parasite specificity was important to network structure.
Modular chassis simplifies packaging and interconnecting of circuit boards
NASA Technical Reports Server (NTRS)
Arens, W. E.; Boline, K. G.
1964-01-01
A system of modular chassis structures has simplified the design for mounting a number of printed circuit boards. This design is structurally adaptable to computer and industrial control system applications.
Universal phase transition in community detectability under a stochastic block model.
Chen, Pin-Yu; Hero, Alfred O
2015-03-01
We prove the existence of an asymptotic phase-transition threshold on community detectability for the spectral modularity method [M. E. J. Newman, Phys. Rev. E 74, 036104 (2006) and Proc. Natl. Acad. Sci. (USA) 103, 8577 (2006)] under a stochastic block model. The phase transition on community detectability occurs as the intercommunity edge connection probability p grows. This phase transition separates a subcritical regime of small p, where modularity-based community detection successfully identifies the communities, from a supercritical regime of large p where successful community detection is impossible. We show that, as the community sizes become large, the asymptotic phase-transition threshold p* is equal to √[p1p2], where pi(i=1,2) is the within-community edge connection probability. Thus the phase-transition threshold is universal in the sense that it does not depend on the ratio of community sizes. The universal phase-transition phenomenon is validated by simulations for moderately sized communities. Using the derived expression for the phase-transition threshold, we propose an empirical method for estimating this threshold from real-world data.
The Modular need for the Division Signal Battalion
2017-06-09
findings and analyzes them to expand on them. It is with these findings and subsequent analysis that the case studies shape the answer to the three...These case studies focus on the signal leadership development and how it occurred in the pre-modular force structure, during modularity, and the...the comparative case study research. The case studies focus on signal leader development in a pre-modular signal force, a modular signal force, and
Uncovering the community structure in signed social networks based on greedy optimization
NASA Astrophysics Data System (ADS)
Chen, Yan; Yan, Jiaqi; Yang, Yu; Chen, Junhua
2017-05-01
The formality of signed relationships has been recently adopted in a lot of complicated systems. The relations among these entities are complicated and multifarious. We cannot indicate these relationships only by positive links, and signed networks have been becoming more and more universal in the study of social networks when community is being significant. In this paper, to identify communities in signed networks, we exploit a new greedy algorithm, taking signs and the density of these links into account. The main idea of the algorithm is the initial procedure of signed modularity and the corresponding update rules. Specially, we employ the “Asymmetric and Constrained Belief Evolution” procedure to evaluate the optimal number of communities. According to the experimental results, the algorithm is proved to be able to run well. More specifically, the proposed algorithm is very efficient for these networks with medium size, both dense and sparse.
Exploring biomedical ontology mappings with graph theory methods.
Kocbek, Simon; Kim, Jin-Dong
2017-01-01
In the era of semantic web, life science ontologies play an important role in tasks such as annotating biological objects, linking relevant data pieces, and verifying data consistency. Understanding ontology structures and overlapping ontologies is essential for tasks such as ontology reuse and development. We present an exploratory study where we examine structure and look for patterns in BioPortal, a comprehensive publicly available repository of live science ontologies. We report an analysis of biomedical ontology mapping data over time. We apply graph theory methods such as Modularity Analysis and Betweenness Centrality to analyse data gathered at five different time points. We identify communities, i.e., sets of overlapping ontologies, and define similar and closest communities. We demonstrate evolution of identified communities over time and identify core ontologies of the closest communities. We use BioPortal project and category data to measure community coherence. We also validate identified communities with their mutual mentions in scientific literature. With comparing mapping data gathered at five different time points, we identified similar and closest communities of overlapping ontologies, and demonstrated evolution of communities over time. Results showed that anatomy and health ontologies tend to form more isolated communities compared to other categories. We also showed that communities contain all or the majority of ontologies being used in narrower projects. In addition, we identified major changes in mapping data after migration to BioPortal Version 4.
Larson, Diane L.; Rabie, Paul A.; Droege, Sam; Larson, Jennifer L.; Haar, Milton
2016-01-01
The majority of pollinating insects are generalists whose lifetimes overlap flowering periods of many potentially suitable plant species. Such generality is instrumental in allowing exotic plant species to invade pollination networks. The particulars of how existing networks change in response to an invasive plant over the course of its phenology are not well characterized, but may shed light on the probability of long-term effects on plant-pollinator interactions and the stability of network structure. Here we describe changes in network topology and modular structure of infested and non-infested networks during the flowering season of the generalist non-native flowering plant, Cirsium arvense in mixed-grass prairie at Badlands National Park, South Dakota, USA. Objectives were to compare network-level effects of infestation as they propagate over the season in infested and non-infested (with respect to C. arvense) networks. We characterized plant-pollinator networks on 5 non-infested and 7 infested 1-ha plots during 4 sample periods that collectively covered the length of C. arvense flowering period. Two other abundantly-flowering invasive plants were present during this time: Melilotus officinalis had highly variable floral abundance in both C. arvense-infested and non-infested plots andConvolvulus arvensis, which occurred almost exclusively in infested plots and peaked early in the season. Modularity, including roles of individual species, and network topology were assessed for each sample period as well as in pooled infested and non-infested networks. Differences in modularity and network metrics between infested and non-infested networks were limited to the third and fourth sample periods, during flower senescence of C. arvenseand the other invasive species; generality of pollinators rose concurrently, suggesting rewiring of the network and a lag effect of earlier floral abundance. Modularity was lower and number of connectors higher in infested networks, whether they were assessed in individual sample periods or pooled into infested and non-infested networks over the entire blooming period of C.arvense. Connectors typically did not reside within the same modules as C. arvense, suggesting that effects of the other invasive plants may also influence the modularity results, and that effects of infestation extend to co-flowering native plants. We conclude that the presence of abundantly flowering invasive species is associated with greater network stability due to decreased modularity, but whether this is advantageous for the associated native plant-pollinator communities depends on the nature of perturbations they experience.
Modular Approach to Structural Simulation for Vehicle Crashworthiness Prediction
DOT National Transportation Integrated Search
1975-03-01
A modular formulation for simulation of the structural deformation and deceleration of a vehicle for crashworthiness and collision compatibility is presented. This formulation includes three dimensional beam elements, various spring elements, rigid b...
French Modular Impoundment: Final Cost and Performance Evaluation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Drown, Peter; French, Bill
This report comprises the Final Cost and Performance Report for the Department of Energy Award # EE0007244, the French Modular Impoundment (aka the “French Dam”.) The French Dam is a system of applying precast modular construction to water control structures. The “French Dam” is a term used to cover the construction means/methods used to construct or rehabilitate dams, diversion structures, powerhouses, and other hydraulic structures which impound water and are covered under FDE’s existing IP (Patents # US8414223B2; US9103084B2.)
ERIC Educational Resources Information Center
Gardenhire, Alissa; Diamond, John; Headlam, Camielle; Weiss, Michael J.
2016-01-01
Community colleges nationwide are looking for solutions to help students complete developmental (remedial) math--a known barrier to graduation. Some are offering computer-assisted, modular developmental math courses that allow students to earn credits incrementally and move through the curriculum at their own pace. One of these modularized…
NASA Technical Reports Server (NTRS)
1972-01-01
A user's handbook for the modular space station concept is presented. The document is designed to acquaint science personnel with the overall modular space station program, the general nature and capabilities of the station itself, some of the scientific opportunities presented by the station, the general policy governing its operation, and the relationship between the program and participants from the scientific community.
Emergence of bursts and communities in evolving weighted networks.
Jo, Hang-Hyun; Pan, Raj Kumar; Kaski, Kimmo
2011-01-01
Understanding the patterns of human dynamics and social interaction and the way they lead to the formation of an organized and functional society are important issues especially for techno-social development. Addressing these issues of social networks has recently become possible through large scale data analysis of mobile phone call records, which has revealed the existence of modular or community structure with many links between nodes of the same community and relatively few links between nodes of different communities. The weights of links, e.g., the number of calls between two users, and the network topology are found correlated such that intra-community links are stronger compared to the weak inter-community links. This feature is known as Granovetter's "The strength of weak ties" hypothesis. In addition to this inhomogeneous community structure, the temporal patterns of human dynamics turn out to be inhomogeneous or bursty, characterized by the heavy tailed distribution of time interval between two consecutive events, i.e., inter-event time. In this paper, we study how the community structure and the bursty dynamics emerge together in a simple evolving weighted network model. The principal mechanisms behind these patterns are social interaction by cyclic closure, i.e., links to friends of friends and the focal closure, links to individuals sharing similar attributes or interests, and human dynamics by task handling process. These three mechanisms have been implemented as a network model with local attachment, global attachment, and priority-based queuing processes. By comprehensive numerical simulations we show that the interplay of these mechanisms leads to the emergence of heavy tailed inter-event time distribution and the evolution of Granovetter-type community structure. Moreover, the numerical results are found to be in qualitative agreement with empirical analysis results from mobile phone call dataset.
NASA Astrophysics Data System (ADS)
Zhuo, Zhao; Cai, Shi-Min; Tang, Ming; Lai, Ying-Cheng
2018-04-01
One of the most challenging problems in network science is to accurately detect communities at distinct hierarchical scales. Most existing methods are based on structural analysis and manipulation, which are NP-hard. We articulate an alternative, dynamical evolution-based approach to the problem. The basic principle is to computationally implement a nonlinear dynamical process on all nodes in the network with a general coupling scheme, creating a networked dynamical system. Under a proper system setting and with an adjustable control parameter, the community structure of the network would "come out" or emerge naturally from the dynamical evolution of the system. As the control parameter is systematically varied, the community hierarchies at different scales can be revealed. As a concrete example of this general principle, we exploit clustered synchronization as a dynamical mechanism through which the hierarchical community structure can be uncovered. In particular, for quite arbitrary choices of the nonlinear nodal dynamics and coupling scheme, decreasing the coupling parameter from the global synchronization regime, in which the dynamical states of all nodes are perfectly synchronized, can lead to a weaker type of synchronization organized as clusters. We demonstrate the existence of optimal choices of the coupling parameter for which the synchronization clusters encode accurate information about the hierarchical community structure of the network. We test and validate our method using a standard class of benchmark modular networks with two distinct hierarchies of communities and a number of empirical networks arising from the real world. Our method is computationally extremely efficient, eliminating completely the NP-hard difficulty associated with previous methods. The basic principle of exploiting dynamical evolution to uncover hidden community organizations at different scales represents a "game-change" type of approach to addressing the problem of community detection in complex networks.
On the modular structure of the genus-one Type II superstring low energy expansion
NASA Astrophysics Data System (ADS)
D'Hoker, Eric; Green, Michael B.; Vanhove, Pierre
2015-08-01
The analytic contribution to the low energy expansion of Type II string amplitudes at genus-one is a power series in space-time derivatives with coefficients that are determined by integrals of modular functions over the complex structure modulus of the world-sheet torus. These modular functions are associated with world-sheet vacuum Feynman diagrams and given by multiple sums over the discrete momenta on the torus. In this paper we exhibit exact differential and algebraic relations for a certain infinite class of such modular functions by showing that they satisfy Laplace eigenvalue equations with inhomogeneous terms that are polynomial in non-holomorphic Eisenstein series. Furthermore, we argue that the set of modular functions that contribute to the coefficients of interactions up to order are linear sums of functions in this class and quadratic polynomials in Eisenstein series and odd Riemann zeta values. Integration over the complex structure results in coefficients of the low energy expansion that are rational numbers multiplying monomials in odd Riemann zeta values.
Significant Scales in Community Structure
NASA Astrophysics Data System (ADS)
Traag, V. A.; Krings, G.; van Dooren, P.
2013-10-01
Many complex networks show signs of modular structure, uncovered by community detection. Although many methods succeed in revealing various partitions, it remains difficult to detect at what scale some partition is significant. This problem shows foremost in multi-resolution methods. We here introduce an efficient method for scanning for resolutions in one such method. Additionally, we introduce the notion of ``significance'' of a partition, based on subgraph probabilities. Significance is independent of the exact method used, so could also be applied in other methods, and can be interpreted as the gain in encoding a graph by making use of a partition. Using significance, we can determine ``good'' resolution parameters, which we demonstrate on benchmark networks. Moreover, optimizing significance itself also shows excellent performance. We demonstrate our method on voting data from the European Parliament. Our analysis suggests the European Parliament has become increasingly ideologically divided and that nationality plays no role.
Bai, Ren; Wang, Jun-Tao; Deng, Ye; He, Ji-Zheng; Feng, Kai; Zhang, Li-Mei
2017-01-01
Paddy rice fields occupy broad agricultural area in China and cover diverse soil types. Microbial community in paddy soils is of great interest since many microorganisms are involved in soil functional processes. In the present study, Illumina Mi-Seq sequencing and functional gene array (GeoChip 4.2) techniques were combined to investigate soil microbial communities and functional gene patterns across the three soil types including an Inceptisol (Binhai), an Oxisol (Leizhou), and an Ultisol (Taoyuan) along four profile depths (up to 70 cm in depth) in mesocosm incubation columns. Detrended correspondence analysis revealed that distinctly differentiation in microbial community existed among soil types and profile depths, while the manifest variance in functional structure was only observed among soil types and two rice growth stages, but not across profile depths. Along the profile depth within each soil type, Acidobacteria, Chloroflexi, and Firmicutes increased whereas Cyanobacteria, β-proteobacteria, and Verrucomicrobia declined, suggesting their specific ecophysiological properties. Compared to bacterial community, the archaeal community showed a more contrasting pattern with the predominant groups within phyla Euryarchaeota, Thaumarchaeota, and Crenarchaeota largely varying among soil types and depths. Phylogenetic molecular ecological network (pMEN) analysis further indicated that the pattern of bacterial and archaeal communities interactions changed with soil depth and the highest modularity of microbial community occurred in top soils, implying a relatively higher system resistance to environmental change compared to communities in deeper soil layers. Meanwhile, microbial communities had higher connectivity in deeper soils in comparison with upper soils, suggesting less microbial interaction in surface soils. Structure equation models were developed and the models indicated that pH was the most representative characteristics of soil type and identified as the key driver in shaping both bacterial and archaeal community structure, but did not directly affect microbial functional structure. The distinctive pattern of microbial taxonomic and functional composition along soil profiles implied functional redundancy within these paddy soils. PMID:28611747
Bai, Ren; Wang, Jun-Tao; Deng, Ye; He, Ji-Zheng; Feng, Kai; Zhang, Li-Mei
2017-01-01
Paddy rice fields occupy broad agricultural area in China and cover diverse soil types. Microbial community in paddy soils is of great interest since many microorganisms are involved in soil functional processes. In the present study, Illumina Mi-Seq sequencing and functional gene array (GeoChip 4.2) techniques were combined to investigate soil microbial communities and functional gene patterns across the three soil types including an Inceptisol (Binhai), an Oxisol (Leizhou), and an Ultisol (Taoyuan) along four profile depths (up to 70 cm in depth) in mesocosm incubation columns. Detrended correspondence analysis revealed that distinctly differentiation in microbial community existed among soil types and profile depths, while the manifest variance in functional structure was only observed among soil types and two rice growth stages, but not across profile depths. Along the profile depth within each soil type, Acidobacteria , Chloroflexi , and Firmicutes increased whereas Cyanobacteria , β -proteobacteria , and Verrucomicrobia declined, suggesting their specific ecophysiological properties. Compared to bacterial community, the archaeal community showed a more contrasting pattern with the predominant groups within phyla Euryarchaeota , Thaumarchaeota , and Crenarchaeota largely varying among soil types and depths. Phylogenetic molecular ecological network (pMEN) analysis further indicated that the pattern of bacterial and archaeal communities interactions changed with soil depth and the highest modularity of microbial community occurred in top soils, implying a relatively higher system resistance to environmental change compared to communities in deeper soil layers. Meanwhile, microbial communities had higher connectivity in deeper soils in comparison with upper soils, suggesting less microbial interaction in surface soils. Structure equation models were developed and the models indicated that pH was the most representative characteristics of soil type and identified as the key driver in shaping both bacterial and archaeal community structure, but did not directly affect microbial functional structure. The distinctive pattern of microbial taxonomic and functional composition along soil profiles implied functional redundancy within these paddy soils.
A new multi-scale method to reveal hierarchical modular structures in biological networks.
Jiao, Qing-Ju; Huang, Yan; Shen, Hong-Bin
2016-11-15
Biological networks are effective tools for studying molecular interactions. Modular structure, in which genes or proteins may tend to be associated with functional modules or protein complexes, is a remarkable feature of biological networks. Mining modular structure from biological networks enables us to focus on a set of potentially important nodes, which provides a reliable guide to future biological experiments. The first fundamental challenge in mining modular structure from biological networks is that the quality of the observed network data is usually low owing to noise and incompleteness in the obtained networks. The second problem that poses a challenge to existing approaches to the mining of modular structure is that the organization of both functional modules and protein complexes in networks is far more complicated than was ever thought. For instance, the sizes of different modules vary considerably from each other and they often form multi-scale hierarchical structures. To solve these problems, we propose a new multi-scale protocol for mining modular structure (named ISIMB) driven by a node similarity metric, which works in an iteratively converged space to reduce the effects of the low data quality of the observed network data. The multi-scale node similarity metric couples both the local and the global topology of the network with a resolution regulator. By varying this resolution regulator to give different weightings to the local and global terms in the metric, the ISIMB method is able to fit the shape of modules and to detect them on different scales. Experiments on protein-protein interaction and genetic interaction networks show that our method can not only mine functional modules and protein complexes successfully, but can also predict functional modules from specific to general and reveal the hierarchical organization of protein complexes.
Scholes, Edwin
2008-01-01
Ethology is rooted in the idea that behavior is composed of discrete units and sub-units that can be compared among taxa in a phylogenetic framework. This means that behavior, like morphology and genes, is inherently modular. Yet, the concept of modularity is not well integrated into how we envision the behavioral components of phenotype. Understanding ethological modularity, and its implications for animal phenotype organization and evolution, requires that we construct interpretive schemes that permit us to examine it. In this study, I describe the structure and composition of a complex part of the behavioral phenotype of Parotia lawesii Ramsay, 1885--a bird of paradise (Aves: Paradisaeidae) from the forests of eastern New Guinea. I use archived voucher video clips, photographic ethograms, and phenotype ontology diagrams to describe the modular units comprising courtship at various levels of integration. Results show P. lawesii to have 15 courtship and mating behaviors (11 males, 4 females) hierarchically arranged within a complex seven-level structure. At the finest level examined, male displays are comprised of 49 modular sub-units (elements) differentially employed to form more complex modular units (phases and versions) at higher-levels of integration. With its emphasis on hierarchical modularity, this study provides an important conceptual framework for understanding courtship-related phenotypic complexity and provides a solid basis for comparative study of the genus Parotia.
Anggraeni, Melisa R; Connors, Natalie K; Wu, Yang; Chuan, Yap P; Lua, Linda H L; Middelberg, Anton P J
2013-09-13
Biomolecular engineering enables synthesis of improved proteins through synergistic fusion of modules from unrelated biomolecules. Modularization of peptide antigen from an unrelated pathogen for presentation on a modular virus-like particle (VLP) represents a new and promising approach to synthesize safe and efficacious vaccines. Addressing a key knowledge gap in modular VLP engineering, this study investigates the underlying fundamentals affecting the ability of induced antibodies to recognize the native pathogen. Specifically, this quality of immune response is correlated to the peptide antigen module structure. We modularized a helical peptide antigen element, helix 190 (H190) from the influenza hemagglutinin (HA) receptor binding region, for presentation on murine polyomavirus VLP, using two strategies aimed to promote H190 helicity on the VLP. In the first strategy, H190 was flanked by GCN4 structure-promoting elements within the antigen module; in the second, dual H190 copies were arrayed as tandem repeats in the module. Molecular dynamics simulation predicted that tandem repeat arraying would minimize secondary structural deviation of modularized H190 from its native conformation. In vivo testing supported this finding, showing that although both modularization strategies conferred high H190-specific immunogenicity, tandem repeat arraying of H190 led to a strikingly higher immune response quality, as measured by ability to generate antibodies recognizing a recombinant HA domain and split influenza virion. These findings provide new insights into the rational engineering of VLP vaccines, and could ultimately enable safe and efficacious vaccine design as an alternative to conventional approaches necessitating pathogen cultivation. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Jin, Hu; Dong, Erbao; Xu, Min; Xia, Qirong; Liu, Shuai; Li, Weihua; Yang, Jie
2018-01-01
Many shape memory alloy (SMA)-based soft actuators have specific composite structures and manufacture processes, and are therefore unique. However, these exclusive characteristics limit their capabilities and applications, so in this article a soft and smart digital structure (SDS) is proposed that acts like a modular unit to assemble soft actuators by a layered adhesive bonding process. The SDS is a fully soft structure that encapsulates a digital skeleton consisting of four groups of parallel and independently actuated SMA wires capable of outputting a four-channel tunable force. The layered adhesive bonding process modularly bonds several SDSs with an elastic backbone to fabricate a layered soft actuator where the elastic backbone is used to recover the SDSs in a cooling process using the SMA wires. Two kinds of SDS-based soft actuators were modularly assembled, an actuator, SDS-I, with a two-dimensional reciprocal motion, and an actuator, SDS-II, capable of bi-directional reciprocal motion. The thermodynamics and phase transformation modeling of the SDS-based actuator were analyzed. Several extensional soft actuators were also assembled by bonding the SDS with an anomalous elastic backbone or modularly assembling the SDS-Is and SDS-IIs. These modularly assembled soft actuators delivered more output channels and a complicated motion, e.g., an actinomorphic soft actuator with four SDS-Is jumps in a series of hierarchical heights and directional movement by tuning the input channels of the SDSs. This result showed that the SDS can modularly assemble multifarious soft actuators with diverse capabilities, steerability and tunable outputs.
ERIC Educational Resources Information Center
Sellin, Burkart
Discussion of whether and to what extent initial vocational training and adult education in European Community (EC) member countries can assume a modular form hinges on the issue of the module as an organizational principle. In such a context, modules are viewed not as closed teaching and learning units but rather as integral parts of a more…
Bellay, Sybelle; Oliveira, Edson F de; Almeida-Neto, Mário; Abdallah, Vanessa D; Azevedo, Rodney K de; Takemoto, Ricardo M; Luque, José L
2015-07-01
The use of the complex network approach to study host-parasite interactions has helped to improve the understanding of the structure and dynamics of ecological communities. In this study, this network approach is applied to evaluate the patterns of organisation and structure of interactions in a fish-parasite network of a neotropical Atlantic Forest river. The network includes 20 fish species and 73 metazoan parasite species collected from the Guandu River, Rio de Janeiro State, Brazil. According to the usual measures in studies of networks, the organisation of the network was evaluated using measures of host susceptibility, parasite dependence, interaction asymmetry, species strength and complementary specialisation of each species as well as the network. The network structure was evaluated using connectance, nestedness and modularity measures. Host susceptibility typically presented low values, whereas parasite dependence was high. The asymmetry and species strength were correlated with host taxonomy but not with parasite taxonomy. Differences among parasite taxonomic groups in the complementary specialisation of each species on hosts were also observed. However, the complementary specialisation and species strength values were not correlated. The network had a high complementary specialisation, low connectance and nestedness, and high modularity, thus indicating variability in the roles of species in the network organisation and the expected presence of many specialist species. Copyright © 2015 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.
The structural bioinformatics library: modeling in biomolecular science and beyond.
Cazals, Frédéric; Dreyfus, Tom
2017-04-01
Software in structural bioinformatics has mainly been application driven. To favor practitioners seeking off-the-shelf applications, but also developers seeking advanced building blocks to develop novel applications, we undertook the design of the Structural Bioinformatics Library ( SBL , http://sbl.inria.fr ), a generic C ++/python cross-platform software library targeting complex problems in structural bioinformatics. Its tenet is based on a modular design offering a rich and versatile framework allowing the development of novel applications requiring well specified complex operations, without compromising robustness and performances. The SBL involves four software components (1-4 thereafter). For end-users, the SBL provides ready to use, state-of-the-art (1) applications to handle molecular models defined by unions of balls, to deal with molecular flexibility, to model macro-molecular assemblies. These applications can also be combined to tackle integrated analysis problems. For developers, the SBL provides a broad C ++ toolbox with modular design, involving core (2) algorithms , (3) biophysical models and (4) modules , the latter being especially suited to develop novel applications. The SBL comes with a thorough documentation consisting of user and reference manuals, and a bugzilla platform to handle community feedback. The SBL is available from http://sbl.inria.fr. Frederic.Cazals@inria.fr. 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
Dynamic social community detection and its applications.
Nguyen, Nam P; Dinh, Thang N; Shen, Yilin; Thai, My T
2014-01-01
Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods.
Dynamic Social Community Detection and Its Applications
Nguyen, Nam P.; Dinh, Thang N.; Shen, Yilin; Thai, My T.
2014-01-01
Community structure is one of the most commonly observed features of Online Social Networks (OSNs) in reality. The knowledge of this feature is of great advantage: it not only provides helpful insights into developing more efficient social-aware solutions but also promises a wide range of applications enabled by social and mobile networking, such as routing strategies in Mobile Ad Hoc Networks (MANETs) and worm containment in OSNs. Unfortunately, understanding this structure is very challenging, especially in dynamic social networks where social interactions are evolving rapidly. Our work focuses on the following questions: How can we efficiently identify communities in dynamic social networks? How can we adaptively update the network community structure based on its history instead of recomputing from scratch? To this end, we present Quick Community Adaptation (QCA), an adaptive modularity-based framework for not only discovering but also tracing the evolution of network communities in dynamic OSNs. QCA is very fast and efficient in the sense that it adaptively updates and discovers the new community structure based on its history together with the network changes only. This flexible approach makes QCA an ideal framework applicable for analyzing large-scale dynamic social networks due to its lightweight computing-resource requirement. To illustrate the effectiveness of our framework, we extensively test QCA on both synthesized and real-world social networks including Enron, arXiv e-print citation, and Facebook networks. Finally, we demonstrate the applicability of QCA in real applications: (1) A social-aware message forwarding strategy in MANETs, and (2) worm propagation containment in OSNs. Competitive results in comparison with other methods reveal that social-based techniques employing QCA as a community detection core outperform current available methods. PMID:24722164
Individual differences and time-varying features of modular brain architecture.
Liao, Xuhong; Cao, Miao; Xia, Mingrui; He, Yong
2017-05-15
Recent studies have suggested that human brain functional networks are topologically organized into functionally specialized but inter-connected modules to facilitate efficient information processing and highly flexible cognitive function. However, these studies have mainly focused on group-level network modularity analyses using "static" functional connectivity approaches. How these extraordinary modular brain structures vary across individuals and spontaneously reconfigure over time remain largely unknown. Here, we employed multiband resting-state functional MRI data (N=105) from the Human Connectome Project and a graph-based modularity analysis to systematically investigate individual variability and dynamic properties in modular brain networks. We showed that the modular structures of brain networks dramatically vary across individuals, with higher modular variability primarily in the association cortex (e.g., fronto-parietal and attention systems) and lower variability in the primary systems. Moreover, brain regions spontaneously changed their module affiliations on a temporal scale of seconds, which cannot be simply attributable to head motion and sampling error. Interestingly, the spatial pattern of intra-subject dynamic modular variability largely overlapped with that of inter-subject modular variability, both of which were highly reproducible across repeated scanning sessions. Finally, the regions with remarkable individual/temporal modular variability were closely associated with network connectors and the number of cognitive components, suggesting a potential contribution to information integration and flexible cognitive function. Collectively, our findings highlight individual modular variability and the notable dynamic characteristics in large-scale brain networks, which enhance our understanding of the neural substrates underlying individual differences in a variety of cognition and behaviors. Copyright © 2017 Elsevier Inc. All rights reserved.
Redefining the modular organization of the core Mediator complex.
Wang, Xuejuan; Sun, Qianqian; Ding, Zhenrui; Ji, Jinhua; Wang, Jianye; Kong, Xiao; Yang, Jianghong; Cai, Gang
2014-07-01
The Mediator complex plays an essential role in the regulation of eukaryotic transcription. The Saccharomyces cerevisiae core Mediator comprises 21 subunits, which are organized into Head, Middle and Tail modules. Previously, the Head module was assigned to a distinct dense domain at the base, and the Middle and Tail modules were identified to form a tight structure above the Head module, which apparently contradicted findings from many biochemical and functional studies. Here, we compared the structures of the core Mediator and its subcomplexes, especially the first 3D structure of the Head + Middle modules, which permitted an unambiguous assignment of the three modules. Furthermore, nanogold labeling pinpointing four Mediator subunits from different modules conclusively validated the modular assignment, in which the Head and Middle modules fold back on one another and form the upper portion of the core Mediator, while the Tail module forms a distinct dense domain at the base. The new modular model of the core Mediator has reconciled the previous inconsistencies between the structurally and functionally defined Mediator modules. Collectively, these analyses completely redefine the modular organization of the core Mediator, which allow us to integrate the structural and functional information into a coherent mechanism for the Mediator's modularity and regulation in transcription initiation.
Redefining the modular organization of the core Mediator complex
Wang, Xuejuan; Sun, Qianqian; Ding, Zhenrui; Ji, Jinhua; Wang, Jianye; Kong, Xiao; Yang, Jianghong; Cai, Gang
2014-01-01
The Mediator complex plays an essential role in the regulation of eukaryotic transcription. The Saccharomyces cerevisiae core Mediator comprises 21 subunits, which are organized into Head, Middle and Tail modules. Previously, the Head module was assigned to a distinct dense domain at the base, and the Middle and Tail modules were identified to form a tight structure above the Head module, which apparently contradicted findings from many biochemical and functional studies. Here, we compared the structures of the core Mediator and its subcomplexes, especially the first 3D structure of the Head + Middle modules, which permitted an unambiguous assignment of the three modules. Furthermore, nanogold labeling pinpointing four Mediator subunits from different modules conclusively validated the modular assignment, in which the Head and Middle modules fold back on one another and form the upper portion of the core Mediator, while the Tail module forms a distinct dense domain at the base. The new modular model of the core Mediator has reconciled the previous inconsistencies between the structurally and functionally defined Mediator modules. Collectively, these analyses completely redefine the modular organization of the core Mediator, which allow us to integrate the structural and functional information into a coherent mechanism for the Mediator's modularity and regulation in transcription initiation. PMID:24810298
Epidemic outbreaks in growing scale-free networks with local structure
NASA Astrophysics Data System (ADS)
Ni, Shunjiang; Weng, Wenguo; Shen, Shifei; Fan, Weicheng
2008-09-01
The class of generative models has already attracted considerable interest from researchers in recent years and much expanded the original ideas described in BA model. Most of these models assume that only one node per time step joins the network. In this paper, we grow the network by adding n interconnected nodes as a local structure into the network at each time step with each new node emanating m new edges linking the node to the preexisting network by preferential attachment. This successfully generates key features observed in social networks. These include power-law degree distribution pk∼k, where μ=(n-1)/m is a tuning parameter defined as the modularity strength of the network, nontrivial clustering, assortative mixing, and modular structure. Moreover, all these features are dependent in a similar way on the parameter μ. We then study the susceptible-infected epidemics on this network with identical infectivity, and find that the initial epidemic behavior is governed by both of the infection scheme and the network structure, especially the modularity strength. The modularity of the network makes the spreading velocity much lower than that of the BA model. On the other hand, increasing the modularity strength will accelerate the propagation velocity.
Modularity and evolutionary constraints in a baculovirus gene regulatory network
2013-01-01
Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks. PMID:24006890
Designing ECM-mimetic Materials Using Protein Engineering
Cai, Lei; Heilshorn, Sarah C.
2014-01-01
The natural extracellular matrix (ECM), with its multitude of evolved cell-instructive and cell-responsive properties, provides inspiration and guidelines for the design of engineered biomaterials. One strategy to create ECM-mimetic materials is the modular design of protein-based engineered ECM (eECM) scaffolds. This modular design strategy involves combining multiple protein domains with different functionalities into a single, modular polymer sequence, resulting in a multifunctional matrix with independent tunability of the individual domain functions. These eECMs often enable decoupled control over multiple material properties for fundamental studies of cell-matrix interactions. In addition, since the eECMs are frequently composed entirely of bioresorbable amino acids, these matrices have immense clinical potential for a variety of regenerative medicine applications. This brief review demonstrates how fundamental knowledge gained from structure-function studies of native proteins can be exploited in the design of novel protein-engineered biomaterials. While the field of protein-engineered biomaterials has existed for over 20 years, the community is only now beginning to fully explore the diversity of functional peptide modules that can be incorporated into these materials. We have chosen to highlight recent examples that either (1) demonstrate exemplary use as matrices with cell-instructive and cell-responsive properties or (2) demonstrate outstanding creativity in terms of novel molecular-level design and macro-level functionality. PMID:24365704
Emergence of consensus as a modular-to-nested transition in communication dynamics
NASA Astrophysics Data System (ADS)
Borge-Holthoefer, Javier; Baños, Raquel A.; Gracia-Lázaro, Carlos; Moreno, Yamir
2017-01-01
Online social networks have transformed the way in which humans communicate and interact, leading to a new information ecosystem where people send and receive information through multiple channels, including traditional communication media. Despite many attempts to characterize the structure and dynamics of these techno-social systems, little is known about fundamental aspects such as how collective attention arises and what determines the information life-cycle. Current approaches to these problems either focus on human temporal dynamics or on semiotic dynamics. In addition, as recently shown, information ecosystems are highly competitive, with humans and memes striving for scarce resources -visibility and attention, respectively. Inspired by similar problems in ecology, here we develop a methodology that allows to cast all the previous aspects into a compact framework and to characterize, using microblogging data, information-driven systems as mutualistic networks. Our results show that collective attention around a topic is reached when the user-meme network self-adapts from a modular to a nested structure, which ultimately allows minimizing competition and attaining consensus. Beyond a sociological interpretation, we explore such resemblance to natural mutualistic communities via well-known dynamics of ecological systems.
Emergence of consensus as a modular-to-nested transition in communication dynamics.
Borge-Holthoefer, Javier; Baños, Raquel A; Gracia-Lázaro, Carlos; Moreno, Yamir
2017-01-30
Online social networks have transformed the way in which humans communicate and interact, leading to a new information ecosystem where people send and receive information through multiple channels, including traditional communication media. Despite many attempts to characterize the structure and dynamics of these techno-social systems, little is known about fundamental aspects such as how collective attention arises and what determines the information life-cycle. Current approaches to these problems either focus on human temporal dynamics or on semiotic dynamics. In addition, as recently shown, information ecosystems are highly competitive, with humans and memes striving for scarce resources -visibility and attention, respectively. Inspired by similar problems in ecology, here we develop a methodology that allows to cast all the previous aspects into a compact framework and to characterize, using microblogging data, information-driven systems as mutualistic networks. Our results show that collective attention around a topic is reached when the user-meme network self-adapts from a modular to a nested structure, which ultimately allows minimizing competition and attaining consensus. Beyond a sociological interpretation, we explore such resemblance to natural mutualistic communities via well-known dynamics of ecological systems.
Emergence of consensus as a modular-to-nested transition in communication dynamics
Borge-Holthoefer, Javier; Baños, Raquel A.; Gracia-Lázaro, Carlos; Moreno, Yamir
2017-01-01
Online social networks have transformed the way in which humans communicate and interact, leading to a new information ecosystem where people send and receive information through multiple channels, including traditional communication media. Despite many attempts to characterize the structure and dynamics of these techno-social systems, little is known about fundamental aspects such as how collective attention arises and what determines the information life-cycle. Current approaches to these problems either focus on human temporal dynamics or on semiotic dynamics. In addition, as recently shown, information ecosystems are highly competitive, with humans and memes striving for scarce resources –visibility and attention, respectively. Inspired by similar problems in ecology, here we develop a methodology that allows to cast all the previous aspects into a compact framework and to characterize, using microblogging data, information-driven systems as mutualistic networks. Our results show that collective attention around a topic is reached when the user-meme network self-adapts from a modular to a nested structure, which ultimately allows minimizing competition and attaining consensus. Beyond a sociological interpretation, we explore such resemblance to natural mutualistic communities via well-known dynamics of ecological systems. PMID:28134358
Modular organization and hospital performance.
Kuntz, Ludwig; Vera, Antonio
2007-02-01
The concept of modularization represents a modern form of organization, which contains the vertical disaggregation of the firm and the use of market mechanisms within hierarchies. The objective of this paper is to examine whether the use of modular structures has a positive effect on hospital performance. The empirical section makes use of multiple regression analyses and leads to the main result that modularization does not have a positive effect on hospital performance. However, the analysis also finds out positive efficiency effects of two central ideas of modularization, namely process orientation and internal market mechanisms.
Inference and Analysis of Population Structure Using Genetic Data and Network Theory
Greenbaum, Gili; Templeton, Alan R.; Bar-David, Shirli
2016-01-01
Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition’s modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). PMID:26888080
Inference and Analysis of Population Structure Using Genetic Data and Network Theory.
Greenbaum, Gili; Templeton, Alan R; Bar-David, Shirli
2016-04-01
Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). Copyright © 2016 by the Genetics Society of America.
Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome.
Pavlovic, Dragana M; Vértes, Petra E; Bullmore, Edward T; Schafer, William R; Nichols, Thomas E
2014-01-01
Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4-5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the "core-in-modules" decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems.
Manufactured Housing--The Modular Home in Texas.
ERIC Educational Resources Information Center
Sindt, Roger P.
This report deals principally with modular homes (permanently sited structures) although it also presents some recent information on mobile homes. In 1976, modular home construction companies were surveyed in Texas and across the United States to assess the extent of their construction activity and market penetration and to gather some insight…
Chuan, Yap P; Wibowo, Nani; Connors, Natalie K; Wu, Yang; Hughes, Fiona K; Batzloff, Michael R; Lua, Linda H L; Middelberg, Anton P J
2014-06-01
Effective and low-cost vaccines are essential to control severe group A streptococcus (GAS) infections prevalent in low-income nations and the Australian aboriginal communities. Highly diverse and endemic circulating GAS strains mandate broad-coverage and customized vaccines. This study describes an approach to deliver cross-reactive antigens from endemic GAS strains using modular virus-like particle (VLP) and capsomere systems. The antigens studied were three heterologous N-terminal peptides (GAS1, GAS2, and GAS3) from the GAS surface M-protein that are specific to endemic strains in Australia Northern Territory Aboriginal communities. In vivo data presented here demonstrated salient characteristics of the modular delivery systems in the context of GAS vaccine design. First, the antigenic peptides, when delivered by unadjuvanted modular VLPs or adjuvanted capsomeres, induced high titers of peptide-specific IgG antibodies (over 1 × 10(4) ). Second, delivery by capsomere was superior to VLP for one of the peptides investigated (GAS3), demonstrating that the delivery system relative effectiveness was antigen-dependant. Third, significant cross-reactivity of GAS2-induced IgG with GAS1 was observed using either VLP or capsomere, showing the possibility of broad-coverage vaccine design using these delivery systems and cross-reactive antigens. Fourth, a formulation containing three pre-mixed modular VLPs, each at a low dose of 5 μg (corresponding to <600 ng of each GAS peptide), induced significant titers of IgGs specific to each peptide, demonstrating that a multivalent, broad-coverage VLP vaccine formulation was possible. In summary, the modular VLPs and capsomeres reported here demonstrate, with promising preliminary data, innovative ways to design GAS vaccines using VLP and capsomere delivery systems amenable to microbial synthesis, potentially adoptable by developing countries. © 2013 Wiley Periodicals, Inc.
General software design for multisensor data fusion
NASA Astrophysics Data System (ADS)
Zhang, Junliang; Zhao, Yuming
1999-03-01
In this paper a general method of software design for multisensor data fusion is discussed in detail, which adopts object-oriented technology under UNIX operation system. The software for multisensor data fusion is divided into six functional modules: data collection, database management, GIS, target display and alarming data simulation etc. Furthermore, the primary function, the components and some realization methods of each modular is given. The interfaces among these functional modular relations are discussed. The data exchange among each functional modular is performed by interprocess communication IPC, including message queue, semaphore and shared memory. Thus, each functional modular is executed independently, which reduces the dependence among functional modules and helps software programing and testing. This software for multisensor data fusion is designed as hierarchical structure by the inheritance character of classes. Each functional modular is abstracted and encapsulated through class structure, which avoids software redundancy and enhances readability.
Modularity in protein structures: study on all-alpha proteins.
Khan, Taushif; Ghosh, Indira
2015-01-01
Modularity is known as one of the most important features of protein's robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism's growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein's secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or "building blocks" in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.
Modular structure of functional networks in olfactory memory.
Meunier, David; Fonlupt, Pierre; Saive, Anne-Lise; Plailly, Jane; Ravel, Nadine; Royet, Jean-Pierre
2014-07-15
Graph theory enables the study of systems by describing those systems as a set of nodes and edges. Graph theory has been widely applied to characterize the overall structure of data sets in the social, technological, and biological sciences, including neuroscience. Modular structure decomposition enables the definition of sub-networks whose components are gathered in the same module and work together closely, while working weakly with components from other modules. This processing is of interest for studying memory, a cognitive process that is widely distributed. We propose a new method to identify modular structure in task-related functional magnetic resonance imaging (fMRI) networks. The modular structure was obtained directly from correlation coefficients and thus retained information about both signs and weights. The method was applied to functional data acquired during a yes-no odor recognition memory task performed by young and elderly adults. Four response categories were explored: correct (Hit) and incorrect (False alarm, FA) recognition and correct and incorrect rejection. We extracted time series data for 36 areas as a function of response categories and age groups and calculated condition-based weighted correlation matrices. Overall, condition-based modular partitions were more homogeneous in young than elderly subjects. Using partition similarity-based statistics and a posteriori statistical analyses, we demonstrated that several areas, including the hippocampus, caudate nucleus, and anterior cingulate gyrus, belonged to the same module more frequently during Hit than during all other conditions. Modularity values were negatively correlated with memory scores in the Hit condition and positively correlated with bias scores (liberal/conservative attitude) in the Hit and FA conditions. We further demonstrated that the proportion of positive and negative links between areas of different modules (i.e., the proportion of correlated and anti-correlated areas) accounted for most of the observed differences in signed modularity. Taken together, our results provided some evidence that the neural networks involved in odor recognition memory are organized into modules and that these modular partitions are linked to behavioral performance and individual strategies. Copyright © 2014 Elsevier Inc. All rights reserved.
Community detection in complex networks by using membrane algorithm
NASA Astrophysics Data System (ADS)
Liu, Chuang; Fan, Linan; Liu, Zhou; Dai, Xiang; Xu, Jiamei; Chang, Baoren
Community detection in complex networks is a key problem of network analysis. In this paper, a new membrane algorithm is proposed to solve the community detection in complex networks. The proposed algorithm is based on membrane systems, which consists of objects, reaction rules, and a membrane structure. Each object represents a candidate partition of a complex network, and the quality of objects is evaluated according to network modularity. The reaction rules include evolutionary rules and communication rules. Evolutionary rules are responsible for improving the quality of objects, which employ the differential evolutionary algorithm to evolve objects. Communication rules implement the information exchanged among membranes. Finally, the proposed algorithm is evaluated on synthetic, real-world networks with real partitions known and the large-scaled networks with real partitions unknown. The experimental results indicate the superior performance of the proposed algorithm in comparison with other experimental algorithms.
Directional selection can drive the evolution of modularity in complex traits
Melo, Diogo; Marroig, Gabriel
2015-01-01
Modularity is a central concept in modern biology, providing a powerful framework for the study of living organisms on many organizational levels. Two central and related questions can be posed in regard to modularity: How does modularity appear in the first place, and what forces are responsible for keeping and/or changing modular patterns? We approached these questions using a quantitative genetics simulation framework, building on previous results obtained with bivariate systems and extending them to multivariate systems. We developed an individual-based model capable of simulating many traits controlled by many loci with variable pleiotropic relations between them, expressed in populations subject to mutation, recombination, drift, and selection. We used this model to study the problem of the emergence of modularity, and hereby show that drift and stabilizing selection are inefficient at creating modular variational structures. We also demonstrate that directional selection can have marked effects on the modular structure between traits, actively promoting a restructuring of genetic variation in the selected population and potentially facilitating the response to selection. Furthermore, we give examples of complex covariation created by simple regimes of combined directional and stabilizing selection and show that stabilizing selection is important in the maintenance of established covariation patterns. Our results are in full agreement with previous results for two-trait systems and further extend them to include scenarios of greater complexity. Finally, we discuss the evolutionary consequences of modular patterns being molded by directional selection. PMID:25548154
Directional selection can drive the evolution of modularity in complex traits.
Melo, Diogo; Marroig, Gabriel
2015-01-13
Modularity is a central concept in modern biology, providing a powerful framework for the study of living organisms on many organizational levels. Two central and related questions can be posed in regard to modularity: How does modularity appear in the first place, and what forces are responsible for keeping and/or changing modular patterns? We approached these questions using a quantitative genetics simulation framework, building on previous results obtained with bivariate systems and extending them to multivariate systems. We developed an individual-based model capable of simulating many traits controlled by many loci with variable pleiotropic relations between them, expressed in populations subject to mutation, recombination, drift, and selection. We used this model to study the problem of the emergence of modularity, and hereby show that drift and stabilizing selection are inefficient at creating modular variational structures. We also demonstrate that directional selection can have marked effects on the modular structure between traits, actively promoting a restructuring of genetic variation in the selected population and potentially facilitating the response to selection. Furthermore, we give examples of complex covariation created by simple regimes of combined directional and stabilizing selection and show that stabilizing selection is important in the maintenance of established covariation patterns. Our results are in full agreement with previous results for two-trait systems and further extend them to include scenarios of greater complexity. Finally, we discuss the evolutionary consequences of modular patterns being molded by directional selection.
On developing the local research environment of the 1990s - The Space Station era
NASA Technical Reports Server (NTRS)
Chase, Robert; Ziel, Fred
1989-01-01
A requirements analysis for the Space Station's polar platform data system has been performed. Based upon this analysis, a cluster, layered cluster, and layered-modular implementation of one specific module within the Eos Data and Information System (EosDIS), an active data base for satellite remote sensing research has been developed. It is found that a distributed system based on a layered-modular architecture and employing current generation work station technologies has the requisite attributes ascribed by the remote sensing research community. Although, based on benchmark testing, probabilistic analysis, failure analysis and user-survey technique analysis, it is found that this architecture presents some operational shortcomings that will not be alleviated with new hardware or software developments. Consequently, the potential of a fully-modular layered architectural design for meeting the needs of Eos researchers has also been evaluated, concluding that it would be well suited to the evolving requirements of this multidisciplinary research community.
Going Modular--For Better or Worse? AIR 1994 Annual Forum Paper.
ERIC Educational Resources Information Center
McLachlan, Jeffrey E.; Wood, Vivienne
A modular system for undergraduate programs was implemented in three degree programs at Napier University in Scotland. This paper describes the degree course structure prior to 1992-93 and factors leading to change, including university response to government policy encouraging wider access to higher education. A rationale for modularization is…
Modular, Hierarchical Learning By Artificial Neural Networks
NASA Technical Reports Server (NTRS)
Baldi, Pierre F.; Toomarian, Nikzad
1996-01-01
Modular and hierarchical approach to supervised learning by artificial neural networks leads to neural networks more structured than neural networks in which all neurons fully interconnected. These networks utilize general feedforward flow of information and sparse recurrent connections to achieve dynamical effects. The modular organization, sparsity of modular units and connections, and fact that learning is much more circumscribed are all attractive features for designing neural-network hardware. Learning streamlined by imitating some aspects of biological neural networks.
CIM-EARTH: Community Integrated Model of Economic and Resource Trajectories for Humankind
NASA Astrophysics Data System (ADS)
Foster, I.; Elliott, J.; Munson, T.; Judd, K.; Moyer, E. J.; Sanstad, A. H.
2010-12-01
We report here on the development of an open source software framework termed CIM-EARTH that is intended to aid decision-making in climate and energy policy. Numerical modeling in support of evaluating policies to address climate change is difficult not only because of inherent uncertainties but because of the differences in scale and modeling approach required for various subcomponents of the system. Economic and climate models are structured quite differently, and while climate forcing can be assumed to be roughly global, climate impacts and the human response to them occur on small spatial scales. Mitigation policies likewise can be applied on scales ranging from the better part of a continent (e.g. a carbon cap-and-trade program for the entire U.S.) to a few hundred km (e.g. statewide renewable portfolio standards and local gasoline taxes). Both spatial and time resolution requirements can be challenging for global economic models. CIM-EARTH is a modular framework based around dynamic general equilibrium models. It is designed as a community tool that will enable study of the environmental benefits, transition costs, capitalization effects, and other consequences of both mitigation policies and unchecked climate change. Modularity enables both integration of highly resolved component sub-models for energy and other key systems and also user-directed choice of tradeoffs between e.g. spatial, sectoral, and time resolution. This poster describes the framework architecture, the current realized version, and plans for future releases. As with other open-source models familiar to the climate community (e.g. CCSM), deliverables will be made publicly available on a regular schedule, and community input is solicited for development of new features and modules.
Modular Building Institute 2002 Educational Showcase.
ERIC Educational Resources Information Center
Modular Building Inst., Charlottesville, VA.
This publication contains brief articles concerned with modular school structures. Some articles offer examples of such structures at actual schools. The articles in this issue are: (1) "Re-Educating Schools" (Chuck Savage); (2) "Tax-Exempt Financing for Public Schools" (John Kennedy); (3) "Help Us Rebuild America" (Michael Roman); (4) "Case…
7 CFR Exhibit B to Subpart A of... - Requirements for Modular/Panelized Housing Units
Code of Federal Regulations, 2013 CFR
2013-01-01
... Regional Letters of Acceptance (RLA), Truss Connector Bulletins (TCB): and, Mechanical Engineering... issued by HUD include: Structural Engineering Bulletins (SEB) on a national basis, Area Letters of... Category III housing (modular/panelized housing that does not have to have a Structural Engineering...
7 CFR Exhibit B to Subpart A of... - Requirements for Modular/Panelized Housing Units
Code of Federal Regulations, 2014 CFR
2014-01-01
... Regional Letters of Acceptance (RLA), Truss Connector Bulletins (TCB): and, Mechanical Engineering... issued by HUD include: Structural Engineering Bulletins (SEB) on a national basis, Area Letters of... Category III housing (modular/panelized housing that does not have to have a Structural Engineering...
7 CFR Exhibit B to Subpart A of... - Requirements for Modular/Panelized Housing Units
Code of Federal Regulations, 2012 CFR
2012-01-01
... Regional Letters of Acceptance (RLA), Truss Connector Bulletins (TCB): and, Mechanical Engineering... issued by HUD include: Structural Engineering Bulletins (SEB) on a national basis, Area Letters of... Category III housing (modular/panelized housing that does not have to have a Structural Engineering...
Modular shipbuilding and its relevance to construction of nuclear power plants. Master's thesis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Seubert, T.W.
1988-05-01
The modern techniques of modular shipbuilding based on the Product Work Breakdown Structure as developed at the Ishikawajima-Harima Heavy Industries Co., Ltd. of Japan are examined and compared to conventional shipbuilding methods. The application of the Product Work Breakdown Structure in the building of the U.S. Navy's DDG-51 class ship at Bath Iron Works is described and compared to Japanese shipbuilding practices. Implementation of the Product Work Breakdown Structure at Avondale Shipyards, Incorporated is discussed and compared to Bath Iron Works shipbuilding practices. A proposed generic implementation of the Product Work Breakdown Structure to the modular construction of nuclear powermore » plants is described. Specific conclusions for the application of Product Work Breakdown Structure to the construction of a light water reactor nuclear power plant are discussed.« less
Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali
2010-12-01
The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Unimodularity criteria for Poisson structures on foliated manifolds
NASA Astrophysics Data System (ADS)
Pedroza, Andrés; Velasco-Barreras, Eduardo; Vorobiev, Yury
2018-03-01
We study the behavior of the modular class of an orientable Poisson manifold and formulate some unimodularity criteria in the semilocal context, around a (singular) symplectic leaf. Our results generalize some known unimodularity criteria for regular Poisson manifolds related to the notion of the Reeb class. In particular, we show that the unimodularity of the transverse Poisson structure of the leaf is a necessary condition for the semilocal unimodular property. Our main tool is an explicit formula for a bigraded decomposition of modular vector fields of a coupling Poisson structure on a foliated manifold. Moreover, we also exploit the notion of the modular class of a Poisson foliation and its relationship with the Reeb class.
Product modular design incorporating preventive maintenance issues
NASA Astrophysics Data System (ADS)
Gao, Yicong; Feng, Yixiong; Tan, Jianrong
2016-03-01
Traditional modular design methods lead to product maintenance problems, because the module form of a system is created according to either the function requirements or the manufacturing considerations. For solving these problems, a new modular design method is proposed with the considerations of not only the traditional function related attributes, but also the maintenance related ones. First, modularity parameters and modularity scenarios for product modularity are defined. Then the reliability and economic assessment models of product modularity strategies are formulated with the introduction of the effective working age of modules. A mathematical model used to evaluate the difference among the modules of the product so that the optimal module of the product can be established. After that, a multi-objective optimization problem based on metrics for preventive maintenance interval different degrees and preventive maintenance economics is formulated for modular optimization. Multi-objective GA is utilized to rapidly approximate the Pareto set of optimal modularity strategy trade-offs between preventive maintenance cost and preventive maintenance interval difference degree. Finally, a coordinate CNC boring machine is adopted to depict the process of product modularity. In addition, two factorial design experiments based on the modularity parameters are constructed and analyzed. These experiments investigate the impacts of these parameters on the optimal modularity strategies and the structure of module. The research proposes a new modular design method, which may help to improve the maintainability of product in modular design.
Analysis of Functional Dynamics of Modular Multidomain Proteins by SAXS and NMR.
Thompson, Matthew K; Ehlinger, Aaron C; Chazin, Walter J
2017-01-01
Multiprotein machines drive virtually all primary cellular processes. Modular multidomain proteins are widely distributed within these dynamic complexes because they provide the flexibility needed to remodel structure as well as rapidly assemble and disassemble components of the machinery. Understanding the functional dynamics of modular multidomain proteins is a major challenge confronting structural biology today because their structure is not fixed in time. Small-angle X-ray scattering (SAXS) and nuclear magnetic resonance (NMR) spectroscopy have proven particularly useful for the analysis of the structural dynamics of modular multidomain proteins because they provide highly complementary information for characterizing the architectural landscape accessible to these proteins. SAXS provides a global snapshot of all architectural space sampled by a molecule in solution. Furthermore, SAXS is sensitive to conformational changes, organization and oligomeric states of protein assemblies, and the existence of flexibility between globular domains in multiprotein complexes. The power of NMR to characterize dynamics provides uniquely complementary information to the global snapshot of the architectural ensemble provided by SAXS because it can directly measure domain motion. In particular, NMR parameters can be used to define the diffusion of domains within modular multidomain proteins, connecting the amplitude of interdomain motion to the architectural ensemble derived from SAXS. Our laboratory has been studying the roles of modular multidomain proteins involved in human DNA replication using SAXS and NMR. Here, we present the procedure for acquiring and analyzing SAXS and NMR data, using DNA primase and replication protein A as examples. © 2017 Elsevier Inc. All rights reserved.
A mathematical programming approach for sequential clustering of dynamic networks
NASA Astrophysics Data System (ADS)
Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia
2016-02-01
A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.
How is the fitness landscaped upon which life evolves selected?
NASA Astrophysics Data System (ADS)
Deem, Michael
2008-03-01
We investigate the selective forces that promote the emergence of modularity in nature. We demonstrate the spontaneous emergence of modularity in a population of individuals that evolve in a changing environment. We show that the level of modularity correlates with the rapidity and severity of environmental change. The modularity arises as a synergistic response to the noise in the environment in the presence of horizontal gene transfer. We suggest that the hierarchical structure observed in the natural world may be a broken symmetry state, which generically results from evolution in a changing environment. The existence of such structure, therefore, need not necessarily rest on intelligent design or the anthropic principle. 1) J. Sun and M. W. Deem, Phys. Rev. Lett., to appear., arXiv:0710.3436
Modular container assembled from fiber reinforced thermoplastic sandwich panels
Donnelly, Mathew William; Kasoff, William Andrew; Mcculloch, Patrick Carl; Williams, Frederick Truman
2007-12-25
An improved, load bearing, modular design container structure assembled from thermoformed FRTP sandwich panels in which is utilized the unique core-skin edge configuration of the present invention in consideration of improved load bearing performance, improved useful load volume, reduced manufacturing costs, structural weight savings, impact and damage tolerance and repair and replace issues.
Curriculum Management Using an Interdisciplinary Matrix Structure and a Modular/Credit System
ERIC Educational Resources Information Center
Walsh, Edward M.
1977-01-01
The operation and results of an experiment at The National Institute for Higher Education, Limerick, Ireland, are described. A matrix structure, consisting of interdisciplines and departments responsible for academic policy and operation, is used with a U.S.-style modular credit system for curriculum management and development. (Author/LBH)
Review of the Modular Administrative Structure.
ERIC Educational Resources Information Center
Grand Valley State Colleges, Allendale, MI. Office of Institutional Analysis.
The modular administrative structure implemented at Grand Valley State Colleges in 1973 is described as a system in which administrative affairs are divided into functional self-contained units called modules, each of which has a head or acting head who is responsible for the management of the functions contained within the module. A long-range…
Algorithmic detectability threshold of the stochastic block model
NASA Astrophysics Data System (ADS)
Kawamoto, Tatsuro
2018-03-01
The assumption that the values of model parameters are known or correctly learned, i.e., the Nishimori condition, is one of the requirements for the detectability analysis of the stochastic block model in statistical inference. In practice, however, there is no example demonstrating that we can know the model parameters beforehand, and there is no guarantee that the model parameters can be learned accurately. In this study, we consider the expectation-maximization (EM) algorithm with belief propagation (BP) and derive its algorithmic detectability threshold. Our analysis is not restricted to the community structure but includes general modular structures. Because the algorithm cannot always learn the planted model parameters correctly, the algorithmic detectability threshold is qualitatively different from the one with the Nishimori condition.
Li, Wenjun; Douglas Ward, B; Liu, Xiaolin; Chen, Gang; Jones, Jennifer L; Antuono, Piero G; Li, Shi-Jiang; Goveas, Joseph S
2015-10-01
The topological architecture of the whole-brain functional networks in those with and without late-life depression (LLD) and amnestic mild cognitive impairment (aMCI) are unknown. To investigate the differences in the small-world measures and the modular community structure of the functional networks between patients with LLD and aMCI when occurring alone or in combination and cognitively healthy non-depressed controls. 79 elderly participants (LLD (n=23), aMCI (n=18), comorbid LLD and aMCI (n=13), and controls (n=25)) completed neuropsychiatric assessments. Graph theoretical methods were employed on resting-state functional connectivity MRI data. LLD and aMCI comorbidity was associated with the greatest disruptions in functional integration measures (decreased global efficiency and increased path length); both LLD groups showed abnormal functional segregation (reduced local efficiency). The modular network organisation was most variable in the comorbid group, followed by patients with LLD-only. Decreased mean global, local and nodal efficiency metrics were associated with greater depressive symptom severity but not memory performance. Considering the whole brain as a complex network may provide unique insights on the neurobiological underpinnings of LLD with and without cognitive impairment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Conceptual design for the space station Freedom modular combustion facility
NASA Technical Reports Server (NTRS)
1989-01-01
A definition study and conceptual design for a combustion science facility that will be located in the Space Station Freedom's baseline U.S. Laboratory module is being performed. This modular, user-friendly facility, called the Modular Combustion Facility, will be available for use by industry, academic, and government research communities in the mid-1990's. The Facility will support research experiments dealing with the study of combustion and its byproducts. Because of the lack of gravity-induced convection, research into the mechanisms of combustion in the absence of gravity will help to provide a better understanding of the fundamentals of the combustion process. The background, current status, and future activities of the effort are covered.
Eggo, Rosalind M; Lenczner, Michael
2015-01-01
Background Multiple waves of transmission during infectious disease epidemics represent a major public health challenge, but the ecological and behavioral drivers of epidemic resurgence are poorly understood. In theory, community structure—aggregation into highly intraconnected and loosely interconnected social groups—within human populations may lead to punctuated outbreaks as diseases progress from one community to the next. However, this explanation has been largely overlooked in favor of temporal shifts in environmental conditions and human behavior and because of the difficulties associated with estimating large-scale contact patterns. Objective The aim was to characterize naturally arising patterns of human contact that are capable of producing simulated epidemics with multiple wave structures. Methods We used an extensive dataset of proximal physical contacts between users of a public Wi-Fi Internet system to evaluate the epidemiological implications of an empirical urban contact network. We characterized the modularity (community structure) of the network and then estimated epidemic dynamics under a percolation-based model of infectious disease spread on the network. We classified simulated epidemics as multiwave using a novel metric and we identified network structures that were critical to the network’s ability to produce multiwave epidemics. Results We identified robust community structure in a large, empirical urban contact network from which multiwave epidemics may emerge naturally. This pattern was fueled by a special kind of insularity in which locally popular individuals were not the ones forging contacts with more distant social groups. Conclusions Our results suggest that ordinary contact patterns can produce multiwave epidemics at the scale of a single urban area without the temporal shifts that are usually assumed to be responsible. Understanding the role of community structure in epidemic dynamics allows officials to anticipate epidemic resurgence without having to forecast future changes in hosts, pathogens, or the environment. PMID:26156032
A modular approach to adaptive structures.
Pagitz, Markus; Pagitz, Manuel; Hühne, Christian
2014-10-07
A remarkable property of nastic, shape changing plants is their complete fusion between actuators and structure. This is achieved by combining a large number of cells whose geometry, internal pressures and material properties are optimized for a given set of target shapes and stiffness requirements. An advantage of such a fusion is that cell walls are prestressed by cell pressures which increases, decreases the overall structural stiffness, weight. Inspired by the nastic movement of plants, Pagitz et al (2012 Bioinspir. Biomim. 7) published a novel concept for pressure actuated cellular structures. This article extends previous work by introducing a modular approach to adaptive structures. An algorithm that breaks down any continuous target shapes into a small number of standardized modules is presented. Furthermore it is shown how cytoskeletons within each cell enhance the properties of adaptive modules. An adaptive passenger seat and an aircrafts leading, trailing edge is used to demonstrate the potential of a modular approach.
Los Alamos National Laboratory Modular Pumped Hydro Feasibility Study for Santa Fe Community College
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bibeault, Mark Leonide
Report on the Economic Energy Assessment for a community college in Santa Fe, New Mexico. Report shows graphically the demand for energy in the month of September, and illustrates the production of electricity as it goes onto the grid for use.
New ARCH: Future Generation Internet Architecture
2004-08-01
a vocabulary to talk about a system . This provides a framework ( a “reference model ...layered model Modularity and abstraction are central tenets of Computer Science thinking. Modularity breaks a system into parts, normally to permit...this complexity is hidden. Abstraction suggests a structure for the system . A popular and simple structure is a layered model : lower layer
Modularization and Structured Markup for Learning Content in an Academic Environment
ERIC Educational Resources Information Center
Schluep, Samuel; Bettoni, Marco; Schar, Sissel Guttormsen
2006-01-01
This article aims to present a flexible component model for modular, web-based learning content, and a simple structured markup schema for the separation of content and presentation. The article will also contain an overview of the dynamic Learning Content Management System (dLCMS) project, which implements these concepts. Content authors are a…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Evans, Leland B.; Cannon, Daniel C.; Hobbs, Jacob A.
Loki-Infect 3 is a desktop application intended for use by community-level decision makers. It allows rapid construction of small-scale studies of emerging or hypothetical infectious diseases in their communities and evaluation of the potential effectiveness of various containment strategies. It was designed with an emphasis on modularity, portability, and ease of use. Our goal is to make this program freely available to community workers across the world.
NASA Technical Reports Server (NTRS)
Simon, Matthew A.; Toups, Larry; Smitherman, David
2012-01-01
Evaluating preliminary concepts of a Deep Space Habitat (DSH) enabling long duration crewed exploration of asteroids, the Moon, and Mars is a technically challenging problem. Sufficient habitat volumes and equipment, necessary to ensure crew health and functionality, increase propellant requirements and decrease launch flexibility to deliver multiple elements on a single launch vehicle; both of which increase overall mission cost. Applying modularity in the design of the habitat structures and subsystems can alleviate these difficulties by spreading the build-up of the overall habitation capability across several smaller parts. This allows for a more flexible habitation approach that accommodates various crew mission durations and levels of functionality. This paper provides a technical analysis of how various modular habitation approaches can impact the parametric design of a DSH with potential benefits in mass, packaging volume, and architectural flexibility. This includes a description of the desired long duration habitation capability, the definition of a baseline model for comparison, a small trade study to investigate alternatives, and commentary on potentially advantageous configurations to enable different levels of habitability. The approaches investigated include modular pressure vessel strategies, modular subsystems, and modular manufacturing approaches to habitat structure. The paper also comments upon the possibility of an integrated habitation strategy using modular components to create all short and long duration habitation elements required in the current exploration architectures.
Truong, Cong-Doan; Kwon, Yung-Keun
2017-12-21
Biological networks consisting of molecular components and interactions are represented by a graph model. There have been some studies based on that model to analyze a relationship between structural characteristics and dynamical behaviors in signaling network. However, little attention has been paid to changes of modularity and robustness in mutant networks. In this paper, we investigated the changes of modularity and robustness by edge-removal mutations in three signaling networks. We first observed that both the modularity and robustness increased on average in the mutant network by the edge-removal mutations. However, the modularity change was negatively correlated with the robustness change. This implies that it is unlikely that both the modularity and the robustness values simultaneously increase by the edge-removal mutations. Another interesting finding is that the modularity change was positively correlated with the degree, the number of feedback loops, and the edge betweenness of the removed edges whereas the robustness change was negatively correlated with them. We note that these results were consistently observed in randomly structure networks. Additionally, we identified two groups of genes which are incident to the highly-modularity-increasing and the highly-robustness-decreasing edges with respect to the edge-removal mutations, respectively, and observed that they are likely to be central by forming a connected component of a considerably large size. The gene-ontology enrichment of each of these gene groups was significantly different from the rest of genes. Finally, we showed that the highly-robustness-decreasing edges can be promising edgetic drug-targets, which validates the usefulness of our analysis. Taken together, the analysis of changes of robustness and modularity against edge-removal mutations can be useful to unravel novel dynamical characteristics underlying in signaling networks.
ERIC Educational Resources Information Center
Allan, Blaine W., Comp.
The procedures, forms, and philosophy of the computerized modular scheduling program developed at Virgin Valley High School are outlined. The modular concept is eveloped as a new approach to course structure with explanations, examples, and worksheets included. Examples of courses of study, input information for the data processing center, output…
Textural break foundation wall construction modules
Phillips, Steven J.
1990-01-01
Below-grade, textural-break foundation wall structures are provided for inhibiting diffusion and advection of liquids and gases into and out from a surrounding hydrogeologic environment. The foundation wall structure includes a foundation wall having an interior and exterior surface and a porous medium disposed around a portion of the exterior surface. The structure further includes a modular barrier disposed around a portion of the porous medium. The modular barrier is substantially removable from the hydrogeologic environment.
Hernanz-Koers, Miguel; Gandía, Mónica; Garrigues, Sandra; Manzanares, Paloma; Yenush, Lynne; Orzaez, Diego; Marcos, Jose F
2018-07-01
Current challenges in the study and biotechnological exploitation of filamentous fungi are the optimization of DNA cloning and fungal genetic transformation beyond model fungi, the open exchange of ready-to-use and standardized genetic elements among the research community, and the availability of universal synthetic biology tools and rules. The GoldenBraid (GB) cloning framework is a Golden Gate-based DNA cloning system developed for plant synthetic biology through Agrobacterium tumefaciens-mediated genetic transformation (ATMT). In this study, we develop reagents for the adaptation of GB version 3.0 from plants to filamentous fungi through: (i) the expansion of the GB toolbox with the domestication of fungal-specific genetic elements; (ii) the design of fungal-specific GB structures; and (iii) the ATMT and gene disruption of the plant pathogen Penicillium digitatum as a proof of concept. Genetic elements domesticated into the GB entry vector pUPD2 include promoters, positive and negative selection markers and terminators. Interestingly, some GB elements can be directly exchanged between plants and fungi, as demonstrated with the marker hph for Hyg R or the fluorescent protein reporter YFP. The iterative modular assembly of elements generates an endless number of diverse transcriptional units and other higher order combinations in the pDGB3α/pDGB3Ω destination vectors. Furthermore, the original plant GB syntax was adapted here to incorporate specific GB structures for gene disruption through homologous recombination and dual selection. We therefore have successfully adapted the GB technology for the ATMT of fungi. We propose the name of FungalBraid (FB) for this new branch of the GB technology that provides open, exchangeable and collaborative resources to the fungal research community. Copyright © 2018 Elsevier Inc. All rights reserved.
Albrecht, Matthias; Padrón, Benigno; Bartomeus, Ignasi; Traveset, Anna
2014-01-01
Compartmentalization—the organization of ecological interaction networks into subsets of species that do not interact with other subsets (true compartments) or interact more frequently among themselves than with other species (modules)—has been identified as a key property for the functioning, stability and evolution of ecological communities. Invasions by entomophilous invasive plants may profoundly alter the way interaction networks are compartmentalized. We analysed a comprehensive dataset of 40 paired plant–pollinator networks (invaded versus uninvaded) to test this hypothesis. We show that invasive plants have higher generalization levels with respect to their pollinators than natives. The consequences for network topology are that—rather than displacing native species from the network—plant invaders attracting pollinators into invaded modules tend to play new important topological roles (i.e. network hubs, module hubs and connectors) and cause role shifts in native species, creating larger modules that are more connected among each other. While the number of true compartments was lower in invaded compared with uninvaded networks, the effect of invasion on modularity was contingent on the study system. Interestingly, the generalization level of the invasive plants partially explains this pattern, with more generalized invaders contributing to a lower modularity. Our findings indicate that the altered interaction structure of invaded networks makes them more robust against simulated random secondary species extinctions, but more vulnerable when the typically highly connected invasive plants go extinct first. The consequences and pathways by which biological invasions alter the interaction structure of plant–pollinator communities highlighted in this study may have important dynamical and functional implications, for example, by influencing multi-species reciprocal selection regimes and coevolutionary processes. PMID:24943368
Dáttilo, Wesley; Lara-Rodríguez, Nubia; Jordano, Pedro; Guimarães, Paulo R; Thompson, John N; Marquis, Robert J; Medeiros, Lucas P; Ortiz-Pulido, Raul; Marcos-García, Maria A; Rico-Gray, Victor
2016-11-30
Trying to unravel Darwin's entangled bank further, we describe the architecture of a network involving multiple forms of mutualism (pollination by animals, seed dispersal by birds and plant protection by ants) and evaluate whether this multi-network shows evidence of a structure that promotes robustness. We found that species differed strongly in their contributions to the organization of the multi-interaction network, and that only a few species contributed to the structuring of these patterns. Moreover, we observed that the multi-interaction networks did not enhance community robustness compared with each of the three independent mutualistic networks when analysed across a range of simulated scenarios of species extinction. By simulating the removal of highly interacting species, we observed that, overall, these species enhance network nestedness and robustness, but decrease modularity. We discuss how the organization of interlinked mutualistic networks may be essential for the maintenance of ecological communities, and therefore the long-term ecological and evolutionary dynamics of interactive, species-rich communities. We suggest that conserving these keystone mutualists and their interactions is crucial to the persistence of species-rich mutualistic assemblages, mainly because they support other species and shape the network organization. © 2016 The Author(s).
Fleck, David E; Welge, Jeffrey A; Eliassen, James C; Adler, Caleb M; DelBello, Melissa P; Strakowski, Stephen M
2018-07-01
The neurophysiological substrates of cognition and emotion, as seen with fMRI, are generally explained using modular structures. The present study was designed to probe the modular structure of cognitive-emotional processing in bipolar and healthy individuals using factor analysis and compare the results with current conceptions of the neurophysiology of bipolar disorder. Exploratory factor analysis was used to assess patterns of covariation among brain regions-of-interest activated during the Continuous Performance Task with Emotional and Neutral Distractors in healthy and bipolar individuals without a priori constraints on the number or composition of latent factors. Results indicated a common cognitive-emotional network consisting of prefrontal, medial temporal, limbic, parietal, anterior cingulate and posterior cingulate modules. However, reduced brain activation to emotional stimuli in the frontal, medial temporal and limbic modules was apparent in the bipolar relative to the healthy group, potentially accounting for emotional dysregulation in bipolar disorder. This study is limited by a relatively small sample size recruited at a single site. The results have yet to be validated on a larger independent sample. Although the modular structure of cognitive-emotional processing is similar in bipolar and healthy individuals, activation in response to emotional/neutral cues varies. These findings are not only consistent with recent conceptions of mood regulation in bipolar disorder, but also suggest that regional activation can be considered within tighter modular structures without compromising data interpretation. This demonstration may serve as a template for data reduction in future region-of-interest analyses to increase statistical power. Copyright © 2018 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Klotz, Dorothy E.; Wright, Thomas A.
2017-01-01
This article highlights a best practice approach that showcases the highly successful deployment of a hybrid course delivery structure for an Operations core course in an Executive MBA Program. A key design element of the approach was the modular design of both the course itself and the learning materials. While other hybrid deployments may stress…
Solar Power Satellite Development: Advances in Modularity and Mechanical Systems
NASA Technical Reports Server (NTRS)
Belvin, W. Keith; Dorsey, John T.; Watson, Judith J.
2010-01-01
Space solar power satellites require innovative concepts in order to achieve economically and technically feasible designs. The mass and volume constraints of current and planned launch vehicles necessitate highly efficient structural systems be developed. In addition, modularity and in-space deployment will be enabling design attributes. This paper reviews the current challenges of launching and building very large space systems. A building block approach is proposed in order to achieve near-term solar power satellite risk reduction while promoting the necessary long-term technology advances. Promising mechanical systems technologies anticipated in the coming decades including modularity, material systems, structural concepts, and in-space operations are described
Systems and methods for improved telepresence
Anderson, Matthew O.; Willis, W. David; Kinoshita, Robert A.
2005-10-25
The present invention provides a modular, flexible system for deploying multiple video perception technologies. The telepresence system of the present invention is capable of allowing an operator to control multiple mono and stereo video inputs in a hands-free manner. The raw data generated by the input devices is processed into a common zone structure that corresponds to the commands of the user, and the commands represented by the zone structure are transmitted to the appropriate device. This modularized approach permits input devices to be easily interfaced with various telepresence devices. Additionally, new input devices and telepresence devices are easily added to the system and are frequently interchangeable. The present invention also provides a modular configuration component that allows an operator to define a plurality of views each of which defines the telepresence devices to be controlled by a particular input device. The present invention provides a modular flexible system for providing telepresence for a wide range of applications. The modularization of the software components combined with the generalized zone concept allows the systems and methods of the present invention to be easily expanded to encompass new devices and new uses.
Demonstration of a Small Modular Biopower System Using Poultry Litter-Final Report
DOE Office of Scientific and Technical Information (OSTI.GOV)
John Reardon; Art Lilley
2004-06-15
On-farm conversion of poultry litter into energy is a unique market connected opportunity for commercialization of small modular bioenergy systems. The United States Department of Energy recognized the need in the poultry industry for alternative litter management as an opportunity for bioenergy. The DOE created a relevant topic in the December 2000 release of the small business innovative research (SBIR) grant solicitation. Community Power Corporation responded to this solicitation by proposing the development of a small modular gasification and gas cleanup system to produce separate value streams of clean producer gas and mineral rich solids. This phase II report describesmore » our progress in the development of an on-farm litter to energy system.« less
Stochastic Blockmodeling of the Modules and Core of the Caenorhabditis elegans Connectome
Pavlovic, Dragana M.; Vértes, Petra E.; Bullmore, Edward T.; Schafer, William R.; Nichols, Thomas E.
2014-01-01
Recently, there has been much interest in the community structure or mesoscale organization of complex networks. This structure is characterised either as a set of sparsely inter-connected modules or as a highly connected core with a sparsely connected periphery. However, it is often difficult to disambiguate these two types of mesoscale structure or, indeed, to summarise the full network in terms of the relationships between its mesoscale constituents. Here, we estimate a community structure with a stochastic blockmodel approach, the Erdős-Rényi Mixture Model, and compare it to the much more widely used deterministic methods, such as the Louvain and Spectral algorithms. We used the Caenorhabditis elegans (C. elegans) nervous system (connectome) as a model system in which biological knowledge about each node or neuron can be used to validate the functional relevance of the communities obtained. The deterministic algorithms derived communities with 4–5 modules, defined by sparse inter-connectivity between all modules. In contrast, the stochastic Erdős-Rényi Mixture Model estimated a community with 9 blocks or groups which comprised a similar set of modules but also included a clearly defined core, made of 2 small groups. We show that the “core-in-modules” decomposition of the worm brain network, estimated by the Erdős-Rényi Mixture Model, is more compatible with prior biological knowledge about the C. elegans nervous system than the purely modular decomposition defined deterministically. We also show that the blockmodel can be used both to generate stochastic realisations (simulations) of the biological connectome, and to compress network into a small number of super-nodes and their connectivity. We expect that the Erdős-Rényi Mixture Model may be useful for investigating the complex community structures in other (nervous) systems. PMID:24988196
Some Analogies of the Banach Contraction Principle in Fuzzy Modular Spaces
Wongkum, Kittipong; Chaipunya, Parin; Kumam, Poom
2013-01-01
We established some theorems under the aim of deriving variants of the Banach contraction principle, using the classes of inner contractions and outer contractions, on the structure of fuzzy modular spaces. PMID:23766681
Facile "modular assembly" for fast construction of a highly oriented crystalline MOF nanofilm.
Xu, Gang; Yamada, Teppei; Otsubo, Kazuya; Sakaida, Shun; Kitagawa, Hiroshi
2012-10-10
The preparation of crystalline, ordered thin films of metal-organic frameworks (MOFs) will be a critical process for MOF-based nanodevices in the future. MOF thin films with perfect orientation and excellent crystallinity were formed with novel nanosheet-structured components, Cu-TCPP [TCPP = 5,10,15,20-tetrakis(4-carboxyphenyl)porphyrin], by a new "modular assembly" strategy. The modular assembly process involves two steps: a "modularization" step is used to synthesize highly crystalline "modules" with a nanosized structure that can be conveniently assembled into a thin film in the following "assembly" step. With this method, MOF thin films can easily be set up on different substrates at very high speed with controllable thickness. This new approach also enabled us to prepare highly oriented crystalline thin films of MOFs that cannot be prepared in thin-film form by traditional techniques.
Revealing in-block nestedness: Detection and benchmarking
NASA Astrophysics Data System (ADS)
Solé-Ribalta, Albert; Tessone, Claudio J.; Mariani, Manuel S.; Borge-Holthoefer, Javier
2018-06-01
As new instances of nested organization—beyond ecological networks—are discovered, scholars are debating the coexistence of two apparently incompatible macroscale architectures: nestedness and modularity. The discussion is far from being solved, mainly for two reasons. First, nestedness and modularity appear to emerge from two contradictory dynamics, cooperation and competition. Second, existing methods to assess the presence of nestedness and modularity are flawed when it comes to the evaluation of concurrently nested and modular structures. In this work, we tackle the latter problem, presenting the concept of in-block nestedness, a structural property determining to what extent a network is composed of blocks whose internal connectivity exhibits nestedness. We then put forward a set of optimization methods that allow us to identify such organization successfully, in synthetic and in a large number of real networks. These findings challenge our understanding of the topology of ecological and social systems, calling for new models to explain how such patterns emerge.
Social cost considerations and legal constraints in implementing modular integrated utility systems
NASA Technical Reports Server (NTRS)
Lede, N. W.; Dixon, H. W.; King, O.; Hill, D. K.
1974-01-01
Social costs associated with the design, demonstration, and implementation of the Modular Integrated Utility System are considered including the social climate of communities, leadership patterns, conflicts and cleavages, specific developmental values, MIUS utility goal assessment, and the suitability of certian alternative options for use in a program of implementation. General considerations are discussed in the field of socio-technological planning. These include guidelines for understanding the conflict and diversity; some relevant goal choices and ideas useful to planners of the MIUS facility.
Gokul, Jarishma K; Hodson, Andrew J; Saetnan, Eli R; Irvine-Fynn, Tristram D L; Westall, Philippa J; Detheridge, Andrew P; Takeuchi, Nozomu; Bussell, Jennifer; Mur, Luis A J; Edwards, Arwyn
2016-08-01
Microbial colonization of glacial ice surfaces incurs feedbacks which affect the melting rate of the ice surface. Ecosystems formed as microbe-mineral aggregates termed cryoconite locally reduce ice surface albedo and represent foci of biodiversity and biogeochemical cycling. Consequently, greater understanding the ecological processes in the formation of functional cryoconite ecosystems upon glacier surfaces is sought. Here, we present the first bacterial biogeography of an ice cap, evaluating the respective roles of dispersal, environmental and biotic filtration occurring at local scales in the assembly of cryoconite microbiota. 16S rRNA gene amplicon semiconductor sequencing of cryoconite colonizing a Svalbard ice cap coupled with digital elevation modelling of physical parameters reveals the bacterial community is dominated by a ubiquitous core of generalist taxa, with evidence for a moderate pairwise distance-decay relationship. While geographic position and melt season duration are prominent among environmental predictors of community structure, the core population of taxa appears highly influential in structuring the bacterial community. Taxon co-occurrence network analysis reveals a highly modular community structured by positive interactions with bottleneck taxa, predominantly Actinobacteria affiliated to isolates from soil humus. In contrast, the filamentous cyanobacterial taxon (assigned to Leptolyngbya/Phormidesmis pristleyi) which dominates the community and binds together granular cryoconite are poorly connected to other taxa. While our study targeted one ice cap, the prominent role of generalist core taxa with close environmental relatives across the global cryosphere indicate discrete roles for cosmopolitan Actinobacteria and Cyanobacteria as respective keystone taxa and ecosystem engineers of cryoconite ecosystems colonizing ice caps. © 2016 John Wiley & Sons Ltd.
Fronto-Parietal Subnetworks Flexibility Compensates For Cognitive Decline Due To Mental Fatigue.
Taya, Fumihiko; Dimitriadis, Stavros I; Dragomir, Andrei; Lim, Julian; Sun, Yu; Wong, Kian Foong; Thakor, Nitish V; Bezerianos, Anastasios
2018-04-24
Fronto-parietal subnetworks were revealed to compensate for cognitive decline due to mental fatigue by community structure analysis. Here, we investigate changes in topology of subnetworks of resting-state fMRI networks due to mental fatigue induced by prolonged performance of a cognitively demanding task, and their associations with cognitive decline. As it is well established that brain networks have modular organization, community structure analyses can provide valuable information about mesoscale network organization and serve as a bridge between standard fMRI approaches and brain connectomics that quantify the topology of whole brain networks. We developed inter- and intramodule network metrics to quantify topological characteristics of subnetworks, based on our hypothesis that mental fatigue would impact on functional relationships of subnetworks. Functional networks were constructed with wavelet correlation and a data-driven thresholding scheme based on orthogonal minimum spanning trees, which allowed detection of communities with weak connections. A change from pre- to posttask runs was found for the intermodule density between the frontal and the temporal subnetworks. Seven inter- or intramodule network metrics, mostly at the frontal or the parietal subnetworks, showed significant predictive power of individual cognitive decline, while the network metrics for the whole network were less effective in the predictions. Our results suggest that the control-type fronto-parietal networks have a flexible topological architecture to compensate for declining cognitive ability due to mental fatigue. This community structure analysis provides valuable insight into connectivity dynamics under different cognitive states including mental fatigue. © 2018 Wiley Periodicals, Inc.
EPA's Models-3 CMAQ system is intended to provide a community modeling paradigm that allows continuous improvement of the one-atmosphere modeling capability in a unified fashion. CMAQ's modular design promotes incorporation of several sets of science process modules representing ...
Modular spectral imaging system for discrimination of pigments in cells and microbial communities.
Polerecky, Lubos; Bissett, Andrew; Al-Najjar, Mohammad; Faerber, Paul; Osmers, Harald; Suci, Peter A; Stoodley, Paul; de Beer, Dirk
2009-02-01
Here we describe a spectral imaging system for minimally invasive identification, localization, and relative quantification of pigments in cells and microbial communities. The modularity of the system allows pigment detection on spatial scales ranging from the single-cell level to regions whose areas are several tens of square centimeters. For pigment identification in vivo absorption and/or autofluorescence spectra are used as the analytical signals. Along with the hardware, which is easy to transport and simple to assemble and allows rapid measurement, we describe newly developed software that allows highly sensitive and pigment-specific analyses of the hyperspectral data. We also propose and describe a number of applications of the system for microbial ecology, including identification of pigments in living cells and high-spatial-resolution imaging of pigments and the associated phototrophic groups in complex microbial communities, such as photosynthetic endolithic biofilms, microbial mats, and intertidal sediments. This system provides new possibilities for studying the role of spatial organization of microorganisms in the ecological functioning of complex benthic microbial communities or for noninvasively monitoring changes in the spatial organization and/or composition of a microbial community in response to changing environmental factors.
Detecting Network Communities: An Application to Phylogenetic Analysis
Andrade, Roberto F. S.; Rocha-Neto, Ivan C.; Santos, Leonardo B. L.; de Santana, Charles N.; Diniz, Marcelo V. C.; Lobão, Thierry Petit; Goés-Neto, Aristóteles; Pinho, Suani T. R.; El-Hani, Charbel N.
2011-01-01
This paper proposes a new method to identify communities in generally weighted complex networks and apply it to phylogenetic analysis. In this case, weights correspond to the similarity indexes among protein sequences, which can be used for network construction so that the network structure can be analyzed to recover phylogenetically useful information from its properties. The analyses discussed here are mainly based on the modular character of protein similarity networks, explored through the Newman-Girvan algorithm, with the help of the neighborhood matrix . The most relevant networks are found when the network topology changes abruptly revealing distinct modules related to the sets of organisms to which the proteins belong. Sound biological information can be retrieved by the computational routines used in the network approach, without using biological assumptions other than those incorporated by BLAST. Usually, all the main bacterial phyla and, in some cases, also some bacterial classes corresponded totally (100%) or to a great extent (>70%) to the modules. We checked for internal consistency in the obtained results, and we scored close to 84% of matches for community pertinence when comparisons between the results were performed. To illustrate how to use the network-based method, we employed data for enzymes involved in the chitin metabolic pathway that are present in more than 100 organisms from an original data set containing 1,695 organisms, downloaded from GenBank on May 19, 2007. A preliminary comparison between the outcomes of the network-based method and the results of methods based on Bayesian, distance, likelihood, and parsimony criteria suggests that the former is as reliable as these commonly used methods. We conclude that the network-based method can be used as a powerful tool for retrieving modularity information from weighted networks, which is useful for phylogenetic analysis. PMID:21573202
Modular Track System For Positioning Mobile Robots
NASA Technical Reports Server (NTRS)
Miller, Jeff
1995-01-01
Conceptual system for positioning mobile robotic manipulators on large main structure includes modular tracks and ancillary structures assembled easily along with main structure. System, called "tracked robotic location system" (TROLS), originally intended for application to platforms in outer space, but TROLS concept might also prove useful on Earth; for example, to position robots in factories and warehouses. T-cross-section rail keeps mobile robot on track. Bar codes mark locations along track. Each robot equipped with bar-code-recognizing circuitry so it quickly finds way to assigned location.
Timóteo, Sérgio; Correia, Marta; Rodríguez-Echeverría, Susana; Freitas, Helena; Heleno, Ruben
2018-01-10
Species interaction networks are traditionally explored as discrete entities with well-defined spatial borders, an oversimplification likely impairing their applicability. Using a multilayer network approach, explicitly accounting for inter-habitat connectivity, we investigate the spatial structure of seed-dispersal networks across the Gorongosa National Park, Mozambique. We show that the overall seed-dispersal network is composed by spatially explicit communities of dispersers spanning across habitats, functionally linking the landscape mosaic. Inter-habitat connectivity determines spatial structure, which cannot be accurately described with standard monolayer approaches either splitting or merging habitats. Multilayer modularity cannot be predicted by null models randomizing either interactions within each habitat or those linking habitats; however, as habitat connectivity increases, random processes become more important for overall structure. The importance of dispersers for the overall network structure is captured by multilayer versatility but not by standard metrics. Highly versatile species disperse many plant species across multiple habitats, being critical to landscape functional cohesion.
Layer-by-layer strippable Ag multilayer films fabricated by modular assembly.
Li, Yan; Chen, Xiaoyan; Li, Qianqian; Song, Kai; Wang, Shihui; Chen, Xiaoyan; Zhang, Kai; Fu, Yu; Jiao, Yong-Hua; Sun, Ting; Liu, Fu-Chun; Han, En-Hou
2014-01-21
We have developed a new method to fabricate multilayer films, which uses prepared thin films as modular blocks and transfer as operation mode to build up multilayer structures. In order to distinguish it from the in situ fabrication manner, this method is called modular assembly in this study. On the basis of such concept, we have fabricated a multilayer film using the silver mirror film as the modular block and poly(lactic acid) as the transfer tool. Due to the special double-layer structure of the silver mirror film, the resulting multilayer film had a well-defined stratified architecture with alternate porous/compact layers. As a consequence of the distinct structure, the interaction between the adjacent layers was so weak that the multilayer film could be layer-by-layer stripped. In addition, the top layer in the film could provide an effective protection on the morphology and surface property of the underlying layers. This suggests that if the surface of the film was deteriorated, the top layer could be peeled off and the freshly exposed surface would still maintain the original function. The successful preparation of the layer-by-layer strippable silver multilayer demonstrates that modular assembly is a feasible and effective method to build up multilayer films capable of creating novel and attractive micro/nanostructures, having great potential in the fabrication of nanodevices and coatings.
Tinaz, Sule; Lauro, Peter M; Ghosh, Pritha; Lungu, Codrin; Horovitz, Silvina G
2017-01-01
Parkinson's disease (PD) leads to dysfunction in multiple cortico-striatal circuits. The neurodegeneration has also been associated with impaired white matter integrity. This structural and functional "disconnection" in PD needs further characterization. We investigated the structural and functional organization of the PD whole brain connectome consisting of 200 nodes using diffusion tensor imaging and resting-state functional MRI, respectively. Data from 20 non-demented PD patients on dopaminergic medication and 20 matched controls were analyzed using graph theory-based methods. We focused on node strength, clustering coefficient, and local efficiency as measures of local network properties; and network modularity as a measure of information flow. PD patients showed reduced white matter connectivity in frontoparietal-striatal nodes compared to controls, but no change in modular organization of the white matter tracts. PD group also showed reduction in functional local network metrics in many nodes distributed across the connectome. There was also decreased functional modularity in the core cognitive networks including the default mode and dorsal attention networks, and sensorimotor network, as well as a lack of modular distinction in the orbitofrontal and basal ganglia nodes in the PD group compared to controls. Our results suggest that despite subtle white matter connectivity changes, the overall structural organization of the PD connectome remains robust at relatively early disease stages. However, there is a breakdown in the functional modular organization of the PD connectome.
Model of community emergence in weighted social networks
NASA Astrophysics Data System (ADS)
Kumpula, J. M.; Onnela, J.-P.; Saramäki, J.; Kertész, J.; Kaski, K.
2009-04-01
Over the years network theory has proven to be rapidly expanding methodology to investigate various complex systems and it has turned out to give quite unparalleled insight to their structure, function, and response through data analysis, modeling, and simulation. For social systems in particular the network approach has empirically revealed a modular structure due to interplay between the network topology and link weights between network nodes or individuals. This inspired us to develop a simple network model that could catch some salient features of mesoscopic community and macroscopic topology formation during network evolution. Our model is based on two fundamental mechanisms of network sociology for individuals to find new friends, namely cyclic closure and focal closure, which are mimicked by local search-link-reinforcement and random global attachment mechanisms, respectively. In addition we included to the model a node deletion mechanism by removing all its links simultaneously, which corresponds for an individual to depart from the network. Here we describe in detail the implementation of our model algorithm, which was found to be computationally efficient and produce many empirically observed features of large-scale social networks. Thus this model opens a new perspective for studying such collective social phenomena as spreading, structure formation, and evolutionary processes.
Programmable formation of catalytic RNA triangles and squares by assembling modular RNA enzymes.
Oi, Hiroki; Fujita, Daisuke; Suzuki, Yuki; Sugiyama, Hiroshi; Endo, Masayuki; Matsumura, Shigeyoshi; Ikawa, Yoshiya
2017-05-01
RNA is a biopolymer that is attractive for constructing nano-scale objects with complex structures. Three-dimensional (3D) structures of naturally occurring RNAs often have modular architectures. The 3D structure of a group I (GI) ribozyme from Tetrahymena has a typical modular architecture, which can be separated into two structural modules (ΔP5 and P5abc). The fully active ribozyme can be reconstructed by assembling the two separately prepared modules through highly specific and strong assembly between ΔP5 ribozyme and P5abc RNA. Such non-covalent assembly of the two modules allows the design of polygonal RNA nano-structures. Through rational redesign of the parent GI ribozyme, we constructed variant GI ribozymes as unit RNAs for polygonal-shaped (closed) oligomers with catalytic activity. Programmed trimerization and tetramerization of the unit RNAs afforded catalytically active nano-sized RNA triangles and squares, the structures of which were directly observed by atomic force microscopy (AFM). © The Authors 2017. Published by Oxford University Press on behalf of the Japanese Biochemical Society. All rights reserved.
Lesicko, Alexandria M.H.; Hristova, Teodora S.; Maigler, Kathleen C.
2016-01-01
The lateral cortex of the inferior colliculus receives information from both auditory and somatosensory structures and is thought to play a role in multisensory integration. Previous studies in the rat have shown that this nucleus contains a series of distinct anatomical modules that stain for GAD-67 as well as other neurochemical markers. In the present study, we sought to better characterize these modules in the mouse inferior colliculus and determine whether the connectivity of other neural structures with the lateral cortex is spatially related to the distribution of these neurochemical modules. Staining for GAD-67 and other markers revealed a single modular network throughout the rostrocaudal extent of the mouse lateral cortex. Somatosensory inputs from the somatosensory cortex and dorsal column nuclei were found to terminate almost exclusively within these modular zones. However, projections from the auditory cortex and central nucleus of the inferior colliculus formed patches that interdigitate with the GAD-67-positive modules. These results suggest that the lateral cortex of the mouse inferior colliculus exhibits connectional as well as neurochemical modularity and may contain multiple segregated processing streams. This finding is discussed in the context of other brain structures in which neuroanatomical and connectional modularity have functional consequences. SIGNIFICANCE STATEMENT Many brain regions contain subnuclear microarchitectures, such as the matrix-striosome organization of the basal ganglia or the patch-interpatch organization of the visual cortex, that shed light on circuit complexities. In the present study, we demonstrate the presence of one such micro-organization in the rodent inferior colliculus. While this structure is typically viewed as an auditory integration center, its lateral cortex appears to be involved in multisensory operations and receives input from somatosensory brain regions. We show here that the lateral cortex can be further subdivided into multiple processing streams: modular regions, which are targeted by somatosensory inputs, and extramodular zones that receive auditory information. PMID:27798184
Waneesorn, Jarurin; Wibowo, Nani; Bingham, John; Middelberg, Anton P J; Lua, Linda H L
2018-05-24
Highly pathogenic avian influenza (HPAI) viruses cause a severe and lethal infection in domestic birds. The increasing number of HPAI outbreaks has demonstrated the lack of capabilities to control the rapid spread of avian influenza. Poultry vaccination has been shown to not only reduce the virus spread in animals but also reduce the virus transmission to humans, preventing potential pandemic development. However, existing vaccine technologies cannot respond to a new virus outbreak rapidly and at a cost and scale that is commercially viable for poultry vaccination. Here, we developed modular capsomere, subunits of virus-like particle, as a low-cost poultry influenza vaccine. Modified murine polyomavirus (MuPyV) VP1 capsomere was used to present structural-based influenza Hemagglutinin (HA1) antigen. Six constructs of modular capsomeres presenting three truncated versions of HA1 and two constructs of modular capsomeres presenting non-modified HA1 have been generated. These modular capsomeres were successfully produced in stable forms using Escherichia coli, without the need for protein refolding. Based on ELISA, this adjuvanted modular capsomere (CaptHA1-3C) induced strong antibody response (almost 10 5 endpoint titre) when administered into chickens, similar to titres obtained in the group administered with insect cell-based HA1 proteins. Chickens that received adjuvanted CaptHA1-3C followed by challenge with HPAI virus were fully protected. The results presented here indicate that this platform for bacterially-produced modular capsomere could potentially translate into a rapid-response and low-cost vaccine manufacturing technology suitable for poultry vaccination. Copyright © 2016 Elsevier Ltd. All rights reserved.
Safety concerns related to modular/prefabricated building construction.
Fard, Maryam Mirhadi; Terouhid, Seyyed Amin; Kibert, Charles J; Hakim, Hamed
2017-03-01
The US construction industry annually experiences a relatively high rate of fatalities and injuries; therefore, improving safety practices should be considered a top priority for this industry. Modular/prefabricated building construction is a construction strategy that involves manufacturing of the whole building or some of its components off-site. This research focuses on the safety performance of the modular/prefabricated building construction sector during both manufacturing and on-site processes. This safety evaluation can serve as the starting point for improving the safety performance of this sector. Research was conducted based on Occupational Safety and Health Administration investigated accidents. The study found 125 accidents related to modular/prefabricated building construction. The details of each accident were closely examined to identify the types of injury and underlying causes. Out of 125 accidents, there were 48 fatalities (38.4%), 63 hospitalized injuries (50.4%), and 14 non-hospitalized injuries (11.2%). It was found that, the most common type of injury in modular/prefabricated construction was 'fracture', and the most common cause of accidents was 'fall'. The most frequent cause of cause (underlying and root cause) was 'unstable structure'. In this research, the accidents were also examined in terms of corresponding location, occupation, equipment as well as activities during which the accidents occurred. For improving safety records of the modular/prefabricated construction sector, this study recommends that future research be conducted on stabilizing structures during their lifting, storing, and permanent installation, securing fall protection systems during on-site assembly of components while working from heights, and developing training programmes and standards focused on modular/prefabricated construction.
Molecular ecological network analyses.
Deng, Ye; Jiang, Yi-Huei; Yang, Yunfeng; He, Zhili; Luo, Feng; Zhou, Jizhong
2012-05-30
Understanding the interaction among different species within a community and their responses to environmental changes is a central goal in ecology. However, defining the network structure in a microbial community is very challenging due to their extremely high diversity and as-yet uncultivated status. Although recent advance of metagenomic technologies, such as high throughout sequencing and functional gene arrays, provide revolutionary tools for analyzing microbial community structure, it is still difficult to examine network interactions in a microbial community based on high-throughput metagenomics data. Here, we describe a novel mathematical and bioinformatics framework to construct ecological association networks named molecular ecological networks (MENs) through Random Matrix Theory (RMT)-based methods. Compared to other network construction methods, this approach is remarkable in that the network is automatically defined and robust to noise, thus providing excellent solutions to several common issues associated with high-throughput metagenomics data. We applied it to determine the network structure of microbial communities subjected to long-term experimental warming based on pyrosequencing data of 16 S rRNA genes. We showed that the constructed MENs under both warming and unwarming conditions exhibited topological features of scale free, small world and modularity, which were consistent with previously described molecular ecological networks. Eigengene analysis indicated that the eigengenes represented the module profiles relatively well. In consistency with many other studies, several major environmental traits including temperature and soil pH were found to be important in determining network interactions in the microbial communities examined. To facilitate its application by the scientific community, all these methods and statistical tools have been integrated into a comprehensive Molecular Ecological Network Analysis Pipeline (MENAP), which is open-accessible now (http://ieg2.ou.edu/MENA). The RMT-based molecular ecological network analysis provides powerful tools to elucidate network interactions in microbial communities and their responses to environmental changes, which are fundamentally important for research in microbial ecology and environmental microbiology.
Lightweight composites for modular panelized construction
NASA Astrophysics Data System (ADS)
Vaidya, Amol S.
Rapid advances in construction materials technology have enabled civil engineers to achieve impressive gains in the safety, economy, and functionality of structures built to serve the common needs of society. Modular building systems is a fast-growing modern, form of construction gaining recognition for its increased efficiency and ability to apply modern technology to the needs of the market place. In the modular construction technique, a single structural panel can perform a number of functions such as providing thermal insulation, vibration damping, and structural strength. These multifunctional panels can be prefabricated in a manufacturing facility and then transferred to the construction site. A system that uses prefabricated panels for construction is called a "panelized construction system". This study focuses on the development of pre-cast, lightweight, multifunctional sandwich composite panels to be used for panelized construction. Two thermoplastic composite panels are proposed in this study, namely Composite Structural Insulated Panels (CSIPs) for exterior walls, floors and roofs, and Open Core Sandwich composite for multifunctional interior walls of a structure. Special manufacturing techniques are developed for manufacturing these panels. The structural behavior of these panels is analyzed based on various building design codes. Detailed descriptions of the design, cost analysis, manufacturing, finite element modeling and structural testing of these proposed panels are included in this study in the of form five peer-reviewed journal articles. The structural testing of the proposed panels involved in this study included flexural testing, axial compression testing, and low and high velocity impact testing. Based on the current study, the proposed CSIP wall and floor panels were found satisfactory, based on building design codes ASCE-7-05 and ACI-318-05. Joining techniques are proposed in this study for connecting the precast panels on the construction site. Keywords: Modular panelized construction, sandwich composites, composite structural insulated panels (CSIPs).
Brain connectome modularity in weight-restored anorexia nervosa and body dysmorphic disorder
Zhang, A; Leow, A; Zhan, L; GadElkarim, J; Moody, T; Khalsa, S; Strober, M; Feusner, JD
2017-01-01
Background Anorexia nervosa (AN) and body dysmorphic disorder (BDD) frequently co-occur, and have several overlapping phenomenological features. Little is known about their shared neurobiology. Aims To compare modular organization of brain structural connectivity. Methods We acquired diffusion-weighted magnetic resonance imaging data on unmedicated individuals with BDD (n=29), weight-restored AN (n=24), and healthy controls (HC) (n=31). We constructed connectivity matrices using whole-brain white matter tractography, and compared modular structures across groups. Results AN showed abnormal modularity involving frontal, basal ganglia, and posterior cingulate nodes. There was a trend in BDD for similar abnormalities, but no significant differences compared with AN. In AN, poor insight correlated with longer path length in right caudal anterior cingulate and right posterior cingulate. Conclusions Abnormal network organization patterns in AN, partially shared with BDD, may have implications for understanding integration between reward and habit/ritual formation, as well as conflict monitoring/error detection. PMID:27429183
Fujita, Yuki; Ishikawa, Junya; Furuta, Hiroyuki; Ikawa, Yoshiya
2010-08-26
In vitro selection with long random RNA libraries has been used as a powerful method to generate novel functional RNAs, although it often requires laborious structural analysis of isolated RNA molecules. Rational RNA design is an attractive alternative to avoid this laborious step, but rational design of catalytic modules is still a challenging task. A hybrid strategy of in vitro selection and rational design has been proposed. With this strategy termed "design and selection," new ribozymes can be generated through installation of catalytic modules onto RNA scaffolds with defined 3D structures. This approach, the concept of which was inspired by the modular architecture of naturally occurring ribozymes, allows prediction of the overall architectures of the resulting ribozymes, and the structural modularity of the resulting ribozymes allows modification of their structures and functions. In this review, we summarize the design, generation, properties, and engineering of four classes of ligase ribozyme generated by design and selection.
NASA Astrophysics Data System (ADS)
Wu, Z.; Zheng, Y.; Wang, K. W.
2018-02-01
We present an approach to achieve adaptable band structures and nonreciprocal wave propagation by exploring and exploiting the concept of metastable modular metastructures. Through studying the dynamics of wave propagation in a chain composed of finite metastable modules, we provide experimental and analytical results on nonreciprocal wave propagation and unveil the underlying mechanisms that facilitate such unidirectional energy transmission. In addition, we demonstrate that via transitioning among the numerous metastable states, the proposed metastructure is endowed with a large number of bandgap reconfiguration possibilities. As a result, we illustrate that unprecedented adaptable nonreciprocal wave propagation can be realized using the metastable modular metastructure. Overall, this research elucidates the rich dynamics attainable through the combinations of periodicity, nonlinearity, spatial asymmetry, and metastability and creates a class of adaptive structural and material systems capable of realizing tunable bandgaps and nonreciprocal wave transmissions.
2012-01-01
Visualization and analysis of molecular networks are both central to systems biology. However, there still exists a large technological gap between them, especially when assessing multiple network levels or hierarchies. Here we present RedeR, an R/Bioconductor package combined with a Java core engine for representing modular networks. The functionality of RedeR is demonstrated in two different scenarios: hierarchical and modular organization in gene co-expression networks and nested structures in time-course gene expression subnetworks. Our results demonstrate RedeR as a new framework to deal with the multiple network levels that are inherent to complex biological systems. RedeR is available from http://bioconductor.org/packages/release/bioc/html/RedeR.html. PMID:22531049
Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization.
Westphal, Andrew J; Wang, Siliang; Rissman, Jesse
2017-03-29
Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity-a measure of network segregation-is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. Copyright © 2017 the authors 0270-6474/17/373523-09$15.00/0.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sanchez, R.; Mondot, J.; Stankovski, Z.
1988-11-01
APOLLO II is a new, multigroup transport code under development at the Commissariat a l'Energie Atomique. The code has a modular structure and uses sophisticated software for data structuralization, dynamic memory management, data storage, and user macrolanguage. This paper gives an overview of the main methods used in the code for (a) multidimensional collision probability calculations, (b) leakage calculations, and (c) homogenization procedures. Numerical examples are given to demonstrate the potential of the modular structure of the code and the novel multilevel flat-flux representation used in the calculation of the collision probabilities.
Multiple D3-Instantons and Mock Modular Forms II
NASA Astrophysics Data System (ADS)
Alexandrov, Sergei; Banerjee, Sibasish; Manschot, Jan; Pioline, Boris
2018-03-01
We analyze the modular properties of D3-brane instanton corrections to the hypermultiplet moduli space in type IIB string theory compactified on a Calabi-Yau threefold. In Part I, we found a necessary condition for the existence of an isometric action of S-duality on this moduli space: the generating function of DT invariants in the large volume attractor chamber must be a vector-valued mock modular form with specified modular properties. In this work, we prove that this condition is also sufficient at two-instanton order. This is achieved by producing a holomorphic action of {SL(2,Z)} on the twistor space which preserves the holomorphic contact structure. The key step is to cancel the anomalous modular variation of the Darboux coordinates by a local holomorphic contact transformation, which is generated by a suitable indefinite theta series. For this purpose we introduce a new family of theta series of signature (2, n - 2), find their modular completion, and conjecture sufficient conditions for their convergence, which may be of independent mathematical interest.
ERIC Educational Resources Information Center
Moss, Lincoln
2000-01-01
Discusses a holistic approach to preventing moisture penetration of exterior walls in modular school buildings. The problem of roof leaks in modular structures is examined as are approaches to water management, roof waterproofing, the problem of condensation, and the design of heating, ventilation, and air conditioning systems as it affects water…
Transition from Longitudinal to Block Structure of Preclinical Courses: Outcomes and Experiences
Marinović, Darko; Hren, Darko; Sambunjak, Dario; Rašić, Ivan; Škegro, Ivan; Marušić, Ana; Marušić, Matko
2009-01-01
Aim To evaluate the transition from a longitudinal to block/modular structure of preclinical courses in a medical school adapting to the process of higher education harmonization in Europe. Methods Average grades and the exam pass rates were compared for 11 preclinical courses before and after the transition from the longitudinal (academic years 1999/2000 to 2001/2002) to block/modular curriculum (academic years 2002/2003 to 2004/2005) at Zagreb University School of Medicine, Croatia. Attitudes of teachers toward the 2 curriculum structures were assessed by a semantic differential scale, and the experiences during the transition were explored in focus groups of students and teachers. Results With the introduction of the block/modular curriculum, average grades mostly increased, except in 3 major courses: Anatomy, Physiology, and Pathology. The proportion of students who passed the exams at first attempt decreased in most courses, but the proportion of students who successfully passed the exam by the end of the summer exam period increased. Teachers generally had more positive attitudes toward the longitudinal (median [C]±intequartile range [Q], 24 ± 16) than block/modular curriculum (C±Q, 38 ± 26) (P = 0.001, Wilcoxon signed rank test). The qualitative inquiry indicated that the dissatisfaction of students and teachers with the block/modular preclinical curriculum was caused by perceived hasty introduction of the reform under pressure and without much adaptation of the teaching program and materials, which reflected negatively on the learning processes and outcomes. Conclusion Any significant alteration in the temporal structure of preclinical courses should be paralleled by a change in the content and teaching methodology, and carefully planned and executed in order to achieve better academic outcomes. PMID:19839073
CosmoSIS: Modular cosmological parameter estimation
Zuntz, J.; Paterno, M.; Jennings, E.; ...
2015-06-09
Cosmological parameter estimation is entering a new era. Large collaborations need to coordinate high-stakes analyses using multiple methods; furthermore such analyses have grown in complexity due to sophisticated models of cosmology and systematic uncertainties. In this paper we argue that modularity is the key to addressing these challenges: calculations should be broken up into interchangeable modular units with inputs and outputs clearly defined. Here we present a new framework for cosmological parameter estimation, CosmoSIS, designed to connect together, share, and advance development of inference tools across the community. We describe the modules already available in CosmoSIS, including CAMB, Planck, cosmicmore » shear calculations, and a suite of samplers. Lastly, we illustrate it using demonstration code that you can run out-of-the-box with the installer available at http://bitbucket.org/joezuntz/cosmosis« less
Configurable Aperture Space Telescope
NASA Technical Reports Server (NTRS)
Ennico, Kimberly; Vassigh, Kenny; Bendek, Selman; Young, Zion W; Lynch, Dana H.
2015-01-01
In December 2014, we were awarded Center Innovation Fund to evaluate an optical and mechanical concept for a novel implementation of a segmented telescope based on modular, interconnected small sats (satlets). The concept is called CAST, a Configurable Aperture Space Telescope. With a current TRL is 2 we will aim to reach TLR 3 in Sept 2015 by demonstrating a 2x2 mirror system to validate our optical model and error budget, provide strawman mechanical architecture and structural damping analyses, and derive future satlet-based observatory performance requirements. CAST provides an alternative access to visible andor UV wavelength space telescope with 1-meter or larger aperture for NASA SMD Astrophysics and Planetary Science community after the retirement of HST.
The PLUTO code for astrophysical gasdynamics .
NASA Astrophysics Data System (ADS)
Mignone, A.
Present numerical codes appeal to a consolidated theory based on finite difference and Godunov-type schemes. In this context we have developed a versatile numerical code, PLUTO, suitable for the solution of high-mach number flow in 1, 2 and 3 spatial dimensions and different systems of coordinates. Different hydrodynamic modules and algorithms may be independently selected to properly describe Newtonian, relativistic, MHD, or relativistic MHD fluids. The modular structure exploits a general framework for integrating a system of conservation laws, built on modern Godunov-type shock-capturing schemes. The code is freely distributed under the GNU public license and it is available for download to the astrophysical community at the URL http://plutocode.to.astro.it.
Configurable Aperture Space Telescope
NASA Technical Reports Server (NTRS)
Ennico, Kimberly; Bendek, Eduardo
2015-01-01
In December 2014, we were awarded Center Innovation Fund to evaluate an optical and mechanical concept for a novel implementation of a segmented telescope based on modular, interconnected small sats (satlets). The concept is called CAST, a Configurable Aperture Space Telescope. With a current TRL is 2 we will aim to reach TLR 3 in Sept 2015 by demonstrating a 2x2 mirror system to validate our optical model and error budget, provide straw man mechanical architecture and structural damping analyses, and derive future satlet-based observatory performance requirements. CAST provides an alternative access to visible and/or UV wavelength space telescope with 1-meter or larger aperture for NASA SMD Astrophysics and Planetary Science community after the retirement of HST
Cosbey, Simon; Elliott, Simon; Paterson, Sue
2017-01-01
The current status of forensic toxicology in the United Kingdom is discussed with an emphasis on professional training and development. Best practice is proposed using a blend of modular foundation knowledge training, continuing professional development, academic study, research & development and ongoing analytical practice. The need for establishing a professional career structure is also discussed along with a suggested example of a suitable model. The issues discussed in this paper are intended to provoke discussion within the forensic toxicology community, industry regulators and other government bodies responsible for the administration of justice. Copyright © 2016 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.
Modular Spectral Imaging System for Discrimination of Pigments in Cells and Microbial Communities▿ †
Polerecky, Lubos; Bissett, Andrew; Al-Najjar, Mohammad; Faerber, Paul; Osmers, Harald; Suci, Peter A.; Stoodley, Paul; de Beer, Dirk
2009-01-01
Here we describe a spectral imaging system for minimally invasive identification, localization, and relative quantification of pigments in cells and microbial communities. The modularity of the system allows pigment detection on spatial scales ranging from the single-cell level to regions whose areas are several tens of square centimeters. For pigment identification in vivo absorption and/or autofluorescence spectra are used as the analytical signals. Along with the hardware, which is easy to transport and simple to assemble and allows rapid measurement, we describe newly developed software that allows highly sensitive and pigment-specific analyses of the hyperspectral data. We also propose and describe a number of applications of the system for microbial ecology, including identification of pigments in living cells and high-spatial-resolution imaging of pigments and the associated phototrophic groups in complex microbial communities, such as photosynthetic endolithic biofilms, microbial mats, and intertidal sediments. This system provides new possibilities for studying the role of spatial organization of microorganisms in the ecological functioning of complex benthic microbial communities or for noninvasively monitoring changes in the spatial organization and/or composition of a microbial community in response to changing environmental factors. PMID:19074609
Teleoperated Modular Robots for Lunar Operations
NASA Technical Reports Server (NTRS)
Globus, Al; Hornby, Greg; Larchev, Greg; Hancher, Matt; Cannon, Howard; Lohn, Jason
2004-01-01
Solar system exploration is currently carried out by special purpose robots exquisitely designed for the anticipated tasks. However, all contingencies for in situ resource utilization (ISRU), human habitat preparation, and exploration will be difficult to anticipate. Furthermore, developing the necessary special purpose mechanisms for deployment and other capabilities is difficult and error prone. For example, the Galileo high gain antenna never opened, severely restricting the quantity of data returned by the spacecraft. Also, deployment hardware is used only once. To address these problems, we are developing teleoperated modular robots for lunar missions, including operations in transit from Earth. Teleoperation of lunar systems from Earth involves a three second speed-of-light delay, but experiment suggests that interactive operations are feasible.' Modular robots typically consist of many identical modules that pass power and data between them and can be reconfigured for different tasks providing great flexibility, inherent redundancy and graceful degradation as modules fail. Our design features a number of different hub, link, and joint modules to simplify the individual modules, lower structure cost, and provide specialized capabilities. Modular robots are well suited for space applications because of their extreme flexibility, inherent redundancy, high-density packing, and opportunities for mass production. Simple structural modules can be manufactured from lunar regolith in situ using molds or directed solar sintering. Software to direct and control modular robots is difficult to develop. We have used genetic algorithms to evolve both the morphology and control system for walking modular robots3 We are currently using evolvable system technology to evolve controllers for modular robots in the ISS glove box. Development of lunar modular robots will require software and physical simulators, including regolith simulation, to enable design and test of robot software and hardware, particularly automation software. Ready access to these simulators could provide opportunities for contest-driven development ala RoboCup (http://www.robocup.org/). Licensing of module designs could provide opportunities in the toy market and for spin-off applications.
Astegiano, Julia; Altermatt, Florian; Massol, François
2017-11-13
Species establish different interactions (e.g. antagonistic, mutualistic) with multiple species, forming multilayer ecological networks. Disentangling network co-structure in multilayer networks is crucial to predict how biodiversity loss may affect the persistence of multispecies assemblages. Existing methods to analyse multilayer networks often fail to consider network co-structure. We present a new method to evaluate the modular co-structure of multilayer networks through the assessment of species degree co-distribution and network module composition. We focus on modular structure because of its high prevalence among ecological networks. We apply our method to two Lepidoptera-plant networks, one describing caterpillar-plant herbivory interactions and one representing adult Lepidoptera nectaring on flowers, thereby possibly pollinating them. More than 50% of the species established either herbivory or visitation interactions, but not both. These species were over-represented among plants and lepidopterans, and were present in most modules in both networks. Similarity in module composition between networks was high but not different from random expectations. Our method clearly delineates the importance of interpreting multilayer module composition similarity in the light of the constraints imposed by network structure to predict the potential indirect effects of species loss through interconnected modular networks.
Selforganization of modular activity of grid cells
Urdapilleta, Eugenio; Si, Bailu
2017-01-01
Abstract A unique topographical representation of space is found in the concerted activity of grid cells in the rodent medial entorhinal cortex. Many among the principal cells in this region exhibit a hexagonal firing pattern, in which each cell expresses its own set of place fields (spatial phases) at the vertices of a triangular grid, the spacing and orientation of which are typically shared with neighboring cells. Grid spacing, in particular, has been found to increase along the dorso‐ventral axis of the entorhinal cortex but in discrete steps, that is, with a modular structure. In this study, we show that such a modular activity may result from the self‐organization of interacting units, which individually would not show discrete but rather continuously varying grid spacing. Within our “adaptation” network model, the effect of a continuously varying time constant, which determines grid spacing in the isolated cell model, is modulated by recurrent collateral connections, which tend to produce a few subnetworks, akin to magnetic domains, each with its own grid spacing. In agreement with experimental evidence, the modular structure is tightly defined by grid spacing, but also involves grid orientation and distortion, due to interactions across modules. Thus, our study sheds light onto a possible mechanism, other than simply assuming separate networks a priori, underlying the formation of modular grid representations. PMID:28768062
Model validation of simple-graph representations of metabolism
Holme, Petter
2009-01-01
The large-scale properties of chemical reaction systems, such as metabolism, can be studied with graph-based methods. To do this, one needs to reduce the information, lists of chemical reactions, available in databases. Even for the simplest type of graph representation, this reduction can be done in several ways. We investigate different simple network representations by testing how well they encode information about one biologically important network structure—network modularity (the propensity for edges to be clustered into dense groups that are sparsely connected between each other). To achieve this goal, we design a model of reaction systems where network modularity can be controlled and measure how well the reduction to simple graphs captures the modular structure of the model reaction system. We find that the network types that best capture the modular structure of the reaction system are substrate–product networks (where substrates are linked to products of a reaction) and substance networks (with edges between all substances participating in a reaction). Furthermore, we argue that the proposed model for reaction systems with tunable clustering is a general framework for studies of how reaction systems are affected by modularity. To this end, we investigate statistical properties of the model and find, among other things, that it recreates correlations between degree and mass of the molecules. PMID:19158012
Improving resolution of dynamic communities in human brain networks through targeted node removal
Turner, Benjamin O.; Miller, Michael B.; Carlson, Jean M.
2017-01-01
Current approaches to dynamic community detection in complex networks can fail to identify multi-scale community structure, or to resolve key features of community dynamics. We propose a targeted node removal technique to improve the resolution of community detection. Using synthetic oscillator networks with well-defined “ground truth” communities, we quantify the community detection performance of a common modularity maximization algorithm. We show that the performance of the algorithm on communities of a given size deteriorates when these communities are embedded in multi-scale networks with communities of different sizes, compared to the performance in a single-scale network. We demonstrate that targeted node removal during community detection improves performance on multi-scale networks, particularly when removing the most functionally cohesive nodes. Applying this approach to network neuroscience, we compare dynamic functional brain networks derived from fMRI data taken during both repetitive single-task and varied multi-task experiments. After the removal of regions in visual cortex, the most coherent functional brain area during the tasks, community detection is better able to resolve known functional brain systems into communities. In addition, node removal enables the algorithm to distinguish clear differences in brain network dynamics between these experiments, revealing task-switching behavior that was not identified with the visual regions present in the network. These results indicate that targeted node removal can improve spatial and temporal resolution in community detection, and they demonstrate a promising approach for comparison of network dynamics between neuroscientific data sets with different resolution parameters. PMID:29261662
ADVANCED SEISMIC BASE ISOLATION METHODS FOR MODULAR REACTORS
DOE Office of Scientific and Technical Information (OSTI.GOV)
E. Blanford; E. Keldrauk; M. Laufer
2010-09-20
Advanced technologies for structural design and construction have the potential for major impact not only on nuclear power plant construction time and cost, but also on the design process and on the safety, security and reliability of next generation of nuclear power plants. In future Generation IV (Gen IV) reactors, structural and seismic design should be much more closely integrated with the design of nuclear and industrial safety systems, physical security systems, and international safeguards systems. Overall reliability will be increased, through the use of replaceable and modular equipment, and through design to facilitate on-line monitoring, in-service inspection, maintenance, replacement,more » and decommissioning. Economics will also receive high design priority, through integrated engineering efforts to optimize building arrangements to minimize building heights and footprints. Finally, the licensing approach will be transformed by becoming increasingly performance based and technology neutral, using best-estimate simulation methods with uncertainty and margin quantification. In this context, two structural engineering technologies, seismic base isolation and modular steel-plate/concrete composite structural walls, are investigated. These technologies have major potential to (1) enable standardized reactor designs to be deployed across a wider range of sites, (2) reduce the impact of uncertainties related to site-specific seismic conditions, and (3) alleviate reactor equipment qualification requirements. For Gen IV reactors the potential for deliberate crashes of large aircraft must also be considered in design. This report concludes that base-isolated structures should be decoupled from the reactor external event exclusion system. As an example, a scoping analysis is performed for a rectangular, decoupled external event shell designed as a grillage. This report also reviews modular construction technology, particularly steel-plate/concrete construction using factory prefabricated structural modules, for application to external event shell and base isolated structures.« less
A Community Publication and Dissemination System for Hydrology Education Materials
NASA Astrophysics Data System (ADS)
Ruddell, B. L.
2015-12-01
Hosted by CUAHSI and the Science Education Resource Center (SERC), federated by the National Science Digital Library (NSDL), and allied with the Water Data Center (WDC), Hydrologic Information System (HIS), and HydroShare projects, a simple cyberinfrastructure has been launched for the publication and dissemination of data and model driven university hydrology education materials. This lightweight system's metadata describes learning content as a data-driven module with defined data inputs and outputs. This structure allows a user to mix and match modules to create sequences of content that teach both hydrology and computer learning outcomes. Importantly, this modular infrastructure allows an instructor to substitute a module based on updated computer methods for one based on outdated computer methods, hopefully solving the problem of rapid obsolescence that has hampered previous community efforts. The prototype system is now available from CUAHSI and SERC, with some example content. The system is designed to catalog, link to, make visible, and make accessible the existing and future contributions of the community; this system does not create content. Submissions from hydrology educators are eagerly solicited, especially for existing content.
Analysis of the Use of Frame Construction and Modular Additions in City Centre
NASA Astrophysics Data System (ADS)
Milwicz, Roman; Milwicz, Natalia; Dubas, Sebastian
2017-10-01
The living urban fabric can be characterized by the continuous introduction of changes and additions. The city centre is subject to specific restrictions due to the conservation protection and high demand on aesthetics aspect, thermal insulation, construction cost and the ratio of usable area of the building area. This article presents a comparative analysis of traditional construction with light frame and modular construction for the above-mentioned issues. Timber frame structure technology was suggested as effective, economic and innovative solutions for modular additions on buildings in city centres.
Clearing the skies over modular polyketide synthases.
Sherman, David H; Smith, Janet L
2006-09-19
Modular polyketide synthases (PKSs) are large multifunctional proteins that synthesize complex polyketide metabolites in microbial cells. A series of recent studies confirm the close protein structural relationship between catalytic domains in the type I mammalian fatty acid synthase (FAS) and the basic synthase unit of the modular PKS. They also establish a remarkable similarity in the overall organization of the type I FAS and the PKS module. This information provides important new conclusions about catalytic domain architecture, function, and molecular recognition that are essential for future efforts to engineer useful polyketide metabolites with valuable biological activities.
Leclerc-Laronze, Nathalie; Marrot, Jérôme; Thouvenot, René; Cadot, Emmanuel
2009-01-01
Linked to the Pentagon: The addition of molybdate to [HBW(11)O(39)](8-) ions leads to the formation of mixed pentagonal units {W(Mo(5))} and {W(WMo(4))} trapped as linkers in the resulting modular assemblies, thus establishing the first link between the conventional Keggin ion derivatives and the giant molybdenum oxide and keplerate ions.
Modular space station phase B extension program master plan
NASA Technical Reports Server (NTRS)
Munsey, E. H.
1971-01-01
The project is defined for design, development, fabrication, test, and pre-mission and mission operations of a shuttle-launched modular space station. The project management approach is described in terms of organization, management requirements, work breakdown structure, schedule, time-phased logic, implementation plans, manpower, and funding. The programmatic and technical problems are identified.
Supervisory Control System Architecture for Advanced Small Modular Reactors
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cetiner, Sacit M; Cole, Daniel L; Fugate, David L
2013-08-01
This technical report was generated as a product of the Supervisory Control for Multi-Modular SMR Plants project within the Instrumentation, Control and Human-Machine Interface technology area under the Advanced Small Modular Reactor (SMR) Research and Development Program of the U.S. Department of Energy. The report documents the definition of strategies, functional elements, and the structural architecture of a supervisory control system for multi-modular advanced SMR (AdvSMR) plants. This research activity advances the state-of-the art by incorporating decision making into the supervisory control system architectural layers through the introduction of a tiered-plant system approach. The report provides a brief history ofmore » hierarchical functional architectures and the current state-of-the-art, describes a reference AdvSMR to show the dependencies between systems, presents a hierarchical structure for supervisory control, indicates the importance of understanding trip setpoints, applies a new theoretic approach for comparing architectures, identifies cyber security controls that should be addressed early in system design, and describes ongoing work to develop system requirements and hardware/software configurations.« less
Akiki, Teddy J; Averill, Christopher L; Wrocklage, Kristen M; Scott, J Cobb; Averill, Lynnette A; Schweinsburg, Brian; Alexander-Bloch, Aaron; Martini, Brenda; Southwick, Steven M; Krystal, John H; Abdallah, Chadi G
2018-08-01
Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing of connectivity in this region. The DMN measures established in this study may serve as a biomarker of disease severity and could have potential utility in developing circuit-based therapeutics. Published by Elsevier Inc.
Crystal structure of modular sodium-rich and low-iron eudialyte from Lovozero alkaline massif
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rozenberg, K. A.; Rastsvetaeva, R. K., E-mail: rast@ns.crys.ras.ru; Aksenov, S. M.
2016-09-15
The structure of the sodium-rich representative of the eudialyte group found by A.P. Khomyakov at the Lovozero massif (Kola Peninsula) is studied by X-ray diffraction. The trigonal cell parameters are: a = 14.2032(1) and c = 60.612(1) Å, V = 10589.13 Å3, space group R3m. The structure is refined to the final R = 5.0% in the anisotropic approximation of atomic displacement parameters using 3742|F| > 3σ(F). The idealized formula (Z = 3) is Na{sub 37}Ca{sub 10}Mn{sub 2}FeZr{sub 6}Si{sub 50}(Ti, Nb){sub 2}O{sub 144}(OH){sub 5}Cl{sub 3} · H{sub 2}O. Like other 24-layer minerals of the eudialyte group, this mineral has amore » modular structure. Its structure contains two modules, namely, “alluaivite” (with an admixture of “eudialyte”) and “kentbrooksite,” called according to the main structural fragments of alluaivite, eudialyte, and kentbrooksite. The mineral found at the Lovozero alkaline massif shows some chemical and symmetry-structural distinctions from the close-in-composition labyrinthite modular mineral from the Khibiny massif. The difference between the minerals stems from different geochemical conditions of mineral formation in the two regions.« less
Model of brain activation predicts the neural collective influence map of the brain
Morone, Flaviano; Roth, Kevin; Min, Byungjoon; Makse, Hernán A.
2017-01-01
Efficient complex systems have a modular structure, but modularity does not guarantee robustness, because efficiency also requires an ingenious interplay of the interacting modular components. The human brain is the elemental paradigm of an efficient robust modular system interconnected as a network of networks (NoN). Understanding the emergence of robustness in such modular architectures from the interconnections of its parts is a longstanding challenge that has concerned many scientists. Current models of dependencies in NoN inspired by the power grid express interactions among modules with fragile couplings that amplify even small shocks, thus preventing functionality. Therefore, we introduce a model of NoN to shape the pattern of brain activations to form a modular environment that is robust. The model predicts the map of neural collective influencers (NCIs) in the brain, through the optimization of the influence of the minimal set of essential nodes responsible for broadcasting information to the whole-brain NoN. Our results suggest intervention protocols to control brain activity by targeting influential neural nodes predicted by network theory. PMID:28351973
Episodic Memory Retrieval Benefits from a Less Modular Brain Network Organization
2017-01-01
Most complex cognitive tasks require the coordinated interplay of multiple brain networks, but the act of retrieving an episodic memory may place especially heavy demands for communication between the frontoparietal control network (FPCN) and the default mode network (DMN), two networks that do not strongly interact with one another in many task contexts. We applied graph theoretical analysis to task-related fMRI functional connectivity data from 20 human participants and found that global brain modularity—a measure of network segregation—is markedly reduced during episodic memory retrieval relative to closely matched analogical reasoning and visuospatial perception tasks. Individual differences in modularity were correlated with memory task performance, such that lower modularity levels were associated with a lower false alarm rate. Moreover, the FPCN and DMN showed significantly elevated coupling with each other during the memory task, which correlated with the global reduction in brain modularity. Both networks also strengthened their functional connectivity with the hippocampus during the memory task. Together, these results provide a novel demonstration that reduced modularity is conducive to effective episodic retrieval, which requires close collaboration between goal-directed control processes supported by the FPCN and internally oriented self-referential processing supported by the DMN. SIGNIFICANCE STATEMENT Modularity, an index of the degree to which nodes of a complex system are organized into discrete communities, has emerged as an important construct in the characterization of brain connectivity dynamics. We provide novel evidence that the modularity of the human brain is reduced when individuals engage in episodic memory retrieval, relative to other cognitive tasks, and that this state of lower modularity is associated with improved memory performance. We propose a neural systems mechanism for this finding where the nodes of the frontoparietal control network and default mode network strengthen their interaction with one another during episodic retrieval. Such across-network communication likely facilitates effective access to internally generated representations of past event knowledge. PMID:28242796
NASA Technical Reports Server (NTRS)
Seasly, Elaine
2015-01-01
To combat contamination of physical assets and provide reliable data to decision makers in the space and missile defense community, a modular open system architecture for creation of contamination models and standards is proposed. Predictive tools for quantifying the effects of contamination can be calibrated from NASA data of long-term orbiting assets. This data can then be extrapolated to missile defense predictive models. By utilizing a modular open system architecture, sensitive data can be de-coupled and protected while benefitting from open source data of calibrated models. This system architecture will include modules that will allow the designer to trade the effects of baseline performance against the lifecycle degradation due to contamination while modeling the lifecycle costs of alternative designs. In this way, each member of the supply chain becomes an informed and active participant in managing contamination risk early in the system lifecycle.
Winter, Jaclyn M.; Cascio, Duilio; Dietrich, David; ...
2015-07-14
Modular collaboration between iterative fungal polyketide synthases (IPKSs) is an important mechanism for generating structural diversity of polyketide natural products. Inter-PKS communication and substrate channeling are controlled in large by the starter unit acyl carrier protein transacylase (SAT) domain found in the accepting IPKS module. Here in this study, we reconstituted the modular biosynthesis of the benzaldehyde core of the chaetoviridin and chaetomugilin azaphilone natural products using the IPKSs CazF and CazM. Our studies revealed a critical role of CazM’s SAT domain in selectively transferring a highly reduced triketide product from CazF. In contrast, a more oxidized triketide that ismore » also produced by CazF and required in later stages of biosynthesis of the final product is not recognized by the SAT domain. The structural basis for the acyl unit selectivity was uncovered by the first X-ray structure of a fungal SAT domain, highlighted by a covalent hexanoyl thioester intermediate in the SAT active site. Finally, the crystal structure of SAT domain will enable protein engineering efforts aimed at mixing and matching different IPKS modules for the biosynthesis of new compounds.« less
Digital Material Assembly by Passive Means and Modular Isotropic Lattice Extruder System
NASA Technical Reports Server (NTRS)
Gershenfeld, Neil (Inventor); Carney, Matthew Eli (Inventor); Jenett, Benjamin (Inventor)
2017-01-01
A set of machines and related systems build structures by the additive assembly of discrete parts. These digital material assemblies constrain the constituent parts to a discrete set of possible positions and orientations. In doing so, the structures exhibit many of the properties inherent in digital communication such as error correction, fault tolerance and allow the assembly of precise structures with comparatively imprecise tools. Assembly of discrete cellular lattices by a Modular Isotropic Lattice Extruder System (MILES) is implemented by pulling strings of lattice elements through a forming die that enforces geometry constraints that lock the elements into a rigid structure that can then be pushed against and extruded out of the die as an assembled, loadbearing structure.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi
A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less
Wireless Sensor Needs in the Space Shuttle and CEV Structures Communities
NASA Technical Reports Server (NTRS)
James, George H., III
2007-01-01
This presentation will clarify some of the structural measurement needs of NASA's Space Shuttle and Crew Exploration Vehicles. Emerging technologies in wireless sensor systems can be of some advantage in both Programs. The presentation will address how wireless instrumentation has helped in the past and what has gone unmeasured on Shuttle due to various limitations. Finally, it will address the needs of the CEV program that can be met with reliable wireless systems, if modular avionics interfaces are provided to accommodate the usual evolving needs of an ambitious space vehicle development program. Examples of the advantages of flight data to support flight certification engineering analyses and of areas where add-on wireless instrumentation can be used will be shown. Without flight instrumentation, it is necessary to retain the conservative assumptions used in the design process. It will be shown how the lessons learned on Space Shuttle for wired and wireless structural measurements apply to the Orion Crew Exploration Vehicle (CEV), which is currently being designed.
Popova, Evdokia; Rodgers, Theron M.; Gong, Xinyi; ...
2017-03-13
A novel data science workflow is developed and demonstrated to extract process-structure linkages (i.e., reduced-order model) for microstructure evolution problems when the final microstructure depends on (simulation or experimental) processing parameters. Our workflow consists of four main steps: data pre-processing, microstructure quantification, dimensionality reduction, and extraction/validation of process-structure linkages. These methods that can be employed within each step vary based on the type and amount of available data. In this paper, this data-driven workflow is applied to a set of synthetic additive manufacturing microstructures obtained using the Potts-kinetic Monte Carlo (kMC) approach. Additive manufacturing techniques inherently produce complex microstructures thatmore » can vary significantly with processing conditions. Using the developed workflow, a low-dimensional data-driven model was established to correlate process parameters with the predicted final microstructure. In addition, the modular workflows developed and presented in this work facilitate easy dissemination and curation by the broader community.« less
Flexible Electronics-Based Transformers for Extreme Environments
NASA Technical Reports Server (NTRS)
Quadrelli, Marco B.; Stoica, Adrian; Ingham, Michel; Thakur, Anubhav
2015-01-01
This paper provides a survey of the use of modular multifunctional systems, called Flexible Transformers, to facilitate the exploration of extreme and previously inaccessible environments. A novel dynamics and control model of a modular algorithm for assembly, folding, and unfolding of these innovative structural systems is also described, together with the control model and the simulation results.
Design and Evaluation of Energy Efficient Modular Classroom Structures.
ERIC Educational Resources Information Center
Brown, G. Z.; And Others
This paper describes a study that developed innovations that would enable modular builders to improve the energy performance of their classrooms without increasing their first cost. The Modern Building Systems' classroom building conforms to the stringent Oregon and Washington energy codes, and, at $18 per square foot, it is at the low end of the…
Modular microfluidic valve structures based on reversible thermoresponsive ionogel actuators.
Benito-Lopez, Fernando; Antoñana-Díez, Marta; Curto, Vincenzo F; Diamond, Dermot; Castro-López, Vanessa
2014-09-21
This paper reports for the first time the use of a cross-linked poly(N-isopropylacrylamide) ionogel encapsulating the ionic liquid 1-ethyl-3-methylimidazolium ethyl sulphate as a thermoresponsive and modular microfluidic valve. The ionogel presents superior actuation behaviour to its equivalent hydrogel. Ionogel swelling and shrinking mechanisms and kinetics are investigated as well as the performance of the ionogel when integrated as a valve in a microfluidic device. The modular microfluidic valve demonstrates fully a reversible on-off behaviour without failure for up to eight actuation cycles and a pressure resistance of 1100 mbar.
Modular survivable satellite support
NASA Astrophysics Data System (ADS)
Wagner, R. E.
The development of a highly mobile, survivable satellite system from the Transportable Mobile Ground Station (T/MGS) is proposed. The addition of advanced capabilities to the T/MGS such as telemetry processing equipment, and the flexibility of a modularly designed system are examined. The need to increase survivability and mobility while reducing life cycle costs is discussed. A modular survivable satellite support system which consists of a 40-foot van, a diesel tractor, and a multimedia communications subsystem is described. The use of planar and phased arrays to improve transportability and new materials and structural designs to enhance hardness are discussed. Diagrams of the system are provided.
Moreira-Filho, Carlos Alberto; Bando, Silvia Yumi; Bertonha, Fernanda Bernardi; Silva, Filipi Nascimento; da Fontoura Costa, Luciano; Ferreira, Leandro Rodrigues; Furlanetto, Glaucio; Chacur, Paulo; Zerbini, Maria Claudia Nogueira; Carneiro-Sampaio, Magda
2016-01-01
Trisomy 21-driven transcriptional alterations in human thymus were characterized through gene coexpression network (GCN) and miRNA-target analyses. We used whole thymic tissue - obtained at heart surgery from Down syndrome (DS) and karyotipically normal subjects (CT) - and a network-based approach for GCN analysis that allows the identification of modular transcriptional repertoires (communities) and the interactions between all the system's constituents through community detection. Changes in the degree of connections observed for hierarchically important hubs/genes in CT and DS networks corresponded to community changes. Distinct communities of highly interconnected genes were topologically identified in these networks. The role of miRNAs in modulating the expression of highly connected genes in CT and DS was revealed through miRNA-target analysis. Trisomy 21 gene dysregulation in thymus may be depicted as the breakdown and altered reorganization of transcriptional modules. Leading networks acting in normal or disease states were identified. CT networks would depict the “canonical” way of thymus functioning. Conversely, DS networks represent a “non-canonical” way, i.e., thymic tissue adaptation under trisomy 21 genomic dysregulation. This adaptation is probably driven by epigenetic mechanisms acting at chromatin level and through the miRNA control of transcriptional programs involving the networks' high-hierarchy genes. PMID:26848775
SA-SOM algorithm for detecting communities in complex networks
NASA Astrophysics Data System (ADS)
Chen, Luogeng; Wang, Yanran; Huang, Xiaoming; Hu, Mengyu; Hu, Fang
2017-10-01
Currently, community detection is a hot topic. This paper, based on the self-organizing map (SOM) algorithm, introduced the idea of self-adaptation (SA) that the number of communities can be identified automatically, a novel algorithm SA-SOM of detecting communities in complex networks is proposed. Several representative real-world networks and a set of computer-generated networks by LFR-benchmark are utilized to verify the accuracy and the efficiency of this algorithm. The experimental findings demonstrate that this algorithm can identify the communities automatically, accurately and efficiently. Furthermore, this algorithm can also acquire higher values of modularity, NMI and density than the SOM algorithm does.
Elmetwaly, Shereef; Schlick, Tamar
2014-01-01
Graph representations have been widely used to analyze and design various economic, social, military, political, and biological networks. In systems biology, networks of cells and organs are useful for understanding disease and medical treatments and, in structural biology, structures of molecules can be described, including RNA structures. In our RNA-As-Graphs (RAG) framework, we represent RNA structures as tree graphs by translating unpaired regions into vertices and helices into edges. Here we explore the modularity of RNA structures by applying graph partitioning known in graph theory to divide an RNA graph into subgraphs. To our knowledge, this is the first application of graph partitioning to biology, and the results suggest a systematic approach for modular design in general. The graph partitioning algorithms utilize mathematical properties of the Laplacian eigenvector (µ2) corresponding to the second eigenvalues (λ2) associated with the topology matrix defining the graph: λ2 describes the overall topology, and the sum of µ2′s components is zero. The three types of algorithms, termed median, sign, and gap cuts, divide a graph by determining nodes of cut by median, zero, and largest gap of µ2′s components, respectively. We apply these algorithms to 45 graphs corresponding to all solved RNA structures up through 11 vertices (∼220 nucleotides). While we observe that the median cut divides a graph into two similar-sized subgraphs, the sign and gap cuts partition a graph into two topologically-distinct subgraphs. We find that the gap cut produces the best biologically-relevant partitioning for RNA because it divides RNAs at less stable connections while maintaining junctions intact. The iterative gap cuts suggest basic modules and assembly protocols to design large RNA structures. Our graph substructuring thus suggests a systematic approach to explore the modularity of biological networks. In our applications to RNA structures, subgraphs also suggest design strategies for novel RNA motifs. PMID:25188578
A modular reactor to simulate biofilm development in orthopedic materials.
Barros, Joana; Grenho, Liliana; Manuel, Cândida M; Ferreira, Carla; Melo, Luís F; Nunes, Olga C; Monteiro, Fernando J; Ferraz, Maria P
2013-09-01
Surfaces of medical implants are generally designed to encourage soft- and/or hard-tissue adherence, eventually leading to tissue- or osseo-integration. Unfortunately, this feature may also encourage bacterial adhesion and biofilm formation. To understand the mechanisms of bone tissue infection associated with contaminated biomaterials, a detailed understanding of bacterial adhesion and subsequent biofilm formation on biomaterial surfaces is needed. In this study, a continuous-flow modular reactor composed of several modular units placed in parallel was designed to evaluate the activity of circulating bacterial suspensions and thus their predilection for biofilm formation during 72 h of incubation. Hydroxyapatite discs were placed in each modular unit and then removed at fixed times to quantify biofilm accumulation. Biofilm formation on each replicate of material, unchanged in structure, morphology, or cell density, was reproducibly observed. The modular reactor therefore proved to be a useful tool for following mature biofilm formation on different surfaces and under conditions similar to those prevailing near human-bone implants.
NASA Astrophysics Data System (ADS)
Baroroh, D. K.; Alfiah, D.
2018-05-01
The electric vehicle is one of the innovations to reduce the pollution of the vehicle. Nevertheless, it still has a problem, especially for disposal stage. In supporting product design and development strategy, which is the idea of sustainable design or problem solving of disposal stage, assessment of modularity architecture from electric vehicle in recovery process needs to be done. This research used Design Structure Matrix (DSM) approach to deciding interaction of components and assessment of modularity architecture using the calculation of value from 3 variables, namely Module Independence (MI), Module Similarity (MS), and Modularity for End of Life Stage (MEOL). The result of this research shows that existing design of electric vehicles has the architectural design which has a high value of modularity for recovery process on disposal stage. Accordingly, so it can be reused and recycled in component level or module without disassembly process to support the product that is environmentally friendly (sustainable design) and able reduce disassembly cost.
Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor
2015-01-01
Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization.
Non-polynomial closed string field theory: loops and conformal maps
NASA Astrophysics Data System (ADS)
Hua, Long; Kaku, Michio
1990-11-01
Recently, we proposed the complete classical action for the non-polynomial closed string field theory, which succesfully reproduced all closed string tree amplitudes. (The action was simultaneously proposed by the Kyoto group). In this paper, we analyze the structure of the theory. We (a) compute the explicit conformal map for all g-loop, p-puncture diagrams, (b) compute all one-loop, two-puncture maps in terms of hyper-elliptic functions, and (c) analyze their modular structure. We analyze, but do not resolve, the question of modular invariance.
Modular fuel-cell stack assembly
Patel, Pinakin [Danbury, CT; Urko, Willam [West Granby, CT
2008-01-29
A modular multi-stack fuel-cell assembly in which the fuel-cell stacks are situated within a containment structure and in which a gas distributor is provided in the structure and distributes received fuel and oxidant gases to the stacks and receives exhausted fuel and oxidant gas from the stacks so as to realize a desired gas flow distribution and gas pressure differential through the stacks. The gas distributor is centrally and symmetrically arranged relative to the stacks so that it itself promotes realization of the desired gas flow distribution and pressure differential.
Wang, Sheng-Jun; Hilgetag, Claus C.; Zhou, Changsong
2010-01-01
Cerebral cortical brain networks possess a number of conspicuous features of structure and dynamics. First, these networks have an intricate, non-random organization. In particular, they are structured in a hierarchical modular fashion, from large-scale regions of the whole brain, via cortical areas and area subcompartments organized as structural and functional maps to cortical columns, and finally circuits made up of individual neurons. Second, the networks display self-organized sustained activity, which is persistent in the absence of external stimuli. At the systems level, such activity is characterized by complex rhythmical oscillations over a broadband background, while at the cellular level, neuronal discharges have been observed to display avalanches, indicating that cortical networks are at the state of self-organized criticality (SOC). We explored the relationship between hierarchical neural network organization and sustained dynamics using large-scale network modeling. Previously, it was shown that sparse random networks with balanced excitation and inhibition can sustain neural activity without external stimulation. We found that a hierarchical modular architecture can generate sustained activity better than random networks. Moreover, the system can simultaneously support rhythmical oscillations and SOC, which are not present in the respective random networks. The mechanism underlying the sustained activity is that each dense module cannot sustain activity on its own, but displays SOC in the presence of weak perturbations. Therefore, the hierarchical modular networks provide the coupling among subsystems with SOC. These results imply that the hierarchical modular architecture of cortical networks plays an important role in shaping the ongoing spontaneous activity of the brain, potentially allowing the system to take advantage of both the sensitivity of critical states and the predictability and timing of oscillations for efficient information processing. PMID:21852971
Robinson, Kathryn M; Hauzy, Céline; Loeuille, Nicolas; Albrectsen, Benedicte R
2015-01-01
Nestedness and modularity are measures of ecological networks whose causative effects are little understood. We analyzed antagonistic plant–herbivore bipartite networks using common gardens in two contrasting environments comprised of aspen trees with differing evolutionary histories of defence against herbivores. These networks were tightly connected owing to a high level of specialization of arthropod herbivores that spend a large proportion of the life cycle on aspen. The gardens were separated by ten degrees of latitude with resultant differences in abiotic conditions. We evaluated network metrics and reported similar connectance between gardens but greater numbers of links per species in the northern common garden. Interaction matrices revealed clear nestedness, indicating subsetting of the bipartite interactions into specialist divisions, in both the environmental and evolutionary aspen groups, although nestedness values were only significant in the northern garden. Variation in plant vulnerability, measured as the frequency of herbivore specialization in the aspen population, was significantly partitioned by environment (common garden) but not by evolutionary origin of the aspens. Significant values of modularity were observed in all network matrices. Trait-matching indicated that growth traits, leaf morphology, and phenolic metabolites affected modular structure in both the garden and evolutionary groups, whereas extra-floral nectaries had little influence. Further examination of module configuration revealed that plant vulnerability explained considerable variance in web structure. The contrasting conditions between the two gardens resulted in bottom-up effects of the environment, which most strongly influenced the overall network architecture, however, the aspen groups with dissimilar evolutionary history also showed contrasting degrees of nestedness and modularity. Our research therefore shows that, while evolution does affect the structure of aspen–herbivore bipartite networks, the role of environmental variations is a dominant constraint. PMID:26306175
NASA Astrophysics Data System (ADS)
Tandon, K.; Egbert, G.; Siripunvaraporn, W.
2003-12-01
We are developing a modular system for three-dimensional inversion of electromagnetic (EM) induction data, using an object oriented programming approach. This approach allows us to modify the individual components of the inversion scheme proposed, and also reuse the components for variety of problems in earth science computing howsoever diverse they might be. In particular, the modularity allows us to (a) change modeling codes independently of inversion algorithm details; (b) experiment with new inversion algorithms; and (c) modify the way prior information is imposed in the inversion to test competing hypothesis and techniques required to solve an earth science problem. Our initial code development is for EM induction equations on a staggered grid, using iterative solution techniques in 3D. An example illustrated here is an experiment with the sensitivity of 3D magnetotelluric inversion to uncertainties in the boundary conditions required for regional induction problems. These boundary conditions should reflect the large-scale geoelectric structure of the study area, which is usually poorly constrained. In general for inversion of MT data, one fixes boundary conditions at the edge of the model domain, and adjusts the earth?s conductivity structure within the modeling domain. Allowing for errors in specification of the open boundary values is simple in principle, but no existing inversion codes that we are aware of have this feature. Adding a feature such as this is straightforward within the context of the modular approach. More generally, a modular approach provides an efficient methodology for setting up earth science computing problems to test various ideas. As a concrete illustration relevant to EM induction problems, we investigate the sensitivity of MT data near San Andreas Fault at Parkfield (California) to uncertainties in the regional geoelectric structure.
ISCE: A Modular, Reusable Library for Scalable SAR/InSAR Processing
NASA Astrophysics Data System (ADS)
Agram, P. S.; Lavalle, M.; Gurrola, E. M.; Sacco, G. F.; Rosen, P. A.
2016-12-01
Traditional community SAR/InSAR processing software tools have primarily focused on differential interferometry and Solid Earth applications. The InSAR Scientific Computing Environment (ISCE) was specifically designed to support the Earth Sciences user community as well as large scale operational processing tasks, thanks to its two-layered (Python+C/Fortran) architecture and modular framework. ISCE is freely distributed as a source tarball, allowing advanced users to modify and extend it for their research purposes and developing exploratory applications, while providing a relatively simple user interface for novice users to perform routine data analysis efficiently. Modular design of the ISCE library also enables easier development of applications to address the needs of Ecosystems, Cryosphere and Disaster Response communities in addition to the traditional Solid Earth applications. In this talk, we would like to emphasize the broader purview of the ISCE library and some of its unique features that sets it apart from other freely available community software like GMTSAR and DORIS, including: Support for multiple geometry regimes - Native Doppler (ALOS-1) as well Zero Doppler (ESA missions) systems. Support for data acquired by airborne platforms - e.g, JPL's UAVSAR and AirMOSS, DLR's F-SAR. Radiometric Terrain Correction - Auxiliary output layers from the geometry modules include projection angles, incidence angles, shadow-layover masks. Dense pixel offsets - Parallelized amplitude cross correlation for cryosphere / ionospheric correction applications. Rubber sheeting - Pixel-by-pixel offsets fields for resampling slave imagery for geometric co-registration/ ionospheric corrections. Preliminary Tandem-X processing support - Bistatic geometry modules. Extensibility to support other non-Solid Earth missions - Modules can be directly adopted for use with other SAR missions, e.g., SWOT. Preliminary support for multi-dimensional data products- multi-polarization, multi-frequency, multi-temporal, multi-baseline stacks via the PLANT and GIAnT toolboxes. Rapid prototyping - Geometry manipulation functionality at the python level allows users to prototype and test processing modules at the interpreter level before optimal implementation in C/C++/Fortran.
Design and evaluation of a modular lower limb exoskeleton for rehabilitation.
Dos Santos, Wilian M; Nogueira, Samuel L; de Oliveira, Gustavo C; Pena, Guido G; Siqueira, Adriano A G
2017-07-01
This paper deals with the evaluation of an exoskeleton designed for assisting individuals to rehabilitate compromised lower limb movements resulting from stroke or incomplete spinal cord injury. The exoskeleton is composed of lightweight tubular structures and six free joints that provide a modular feature to the system. This feature allows the exoskeleton to be adapted to assist the movement of one or more patient joints. The actuation of the exoskeleton is also modular, and can be performed passively, by means of springs and dampers, or actively through actuators. In addition, its telescopic tubular links, developed to adjust the size of the links in order to align the joints of the exoskeleton with patient joints, allows the exoskeleton to be adjustable to fit different patients. Experiments considering the interaction between a healthy subject and the exoskeleton are performed to evaluate the influence of the exoskeleton structure on kinematic and muscular activity profiles during walking.
Topological dimension tunes activity patterns in hierarchical modular networks
NASA Astrophysics Data System (ADS)
Safari, Ali; Moretti, Paolo; Muñoz, Miguel A.
2017-11-01
Connectivity patterns of relevance in neuroscience and systems biology can be encoded in hierarchical modular networks (HMNs). Recent studies highlight the role of hierarchical modular organization in shaping brain activity patterns, providing an excellent substrate to promote both segregation and integration of neural information. Here, we propose an extensive analysis of the critical spreading rate (or ‘epidemic’ threshold)—separating a phase with endemic persistent activity from one in which activity ceases—on diverse HMNs. By employing analytical and computational techniques we determine the nature of such a threshold and scrutinize how it depends on general structural features of the underlying HMN. We critically discuss the extent to which current graph-spectral methods can be applied to predict the onset of spreading in HMNs and, most importantly, we elucidate the role played by the network topological dimension as a relevant and unifying structural parameter, controlling the epidemic threshold.
Research on Self-Reconfigurable Modular Robot System
NASA Astrophysics Data System (ADS)
Kamimura, Akiya; Murata, Satoshi; Yoshida, Eiichi; Kurokawa, Haruhisa; Tomita, Kohji; Kokaji, Shigeru
Growing complexity of artificial systems arises reliability and flexibility issues of large system design. Robots are not exception of this, and many attempts have been made to realize reliable and flexible robot systems. Distributed modular composition of robot is one of the most effective approaches to attain such abilities and has a potential to adapt to its surroundings by changing its configuration autonomously according to information of surroundings. In this paper, we propose a novel three-dimensional self-reconfigurable robotic module. Each module has a very simple structure that consists of two semi-cylindrical parts connected by a link. The modular system is capable of not only building static structure but also generating dynamic robotic motion. We present details of the mechanical/electrical design of the developed module and its control system architecture. Experiments using ten modules with centralized control demonstrate robotic configuration change, crawling locomotion and three types of quadruped locomotion.
Integrating Innovation: Keeping the Leading Edge
2015-08-01
access inside Army com- mand posts. Commercial innovation also can be built directly into our con- tract structure. Just as today’s smartphones ...moving to publish detailed guidance this year on how gov- ernment and industry partners will comply with the Modular Open Systems Architecture...which outlines design principles and interface characteristics allowing for modular hardware While the Army cannot predict the future or design
Gauvin, Robert; Khademhosseini, Ali
2011-01-01
Micro- and nanoscale technologies have emerged as powerful tools in the fabrication of engineered tissues and organs. Here we focus on the application of these techniques to improve engineered tissue architecture and function using modular and directed self-assembly and highlight the emergence of this new class of materials for biomedical applications. PMID:21627163
NASA Astrophysics Data System (ADS)
Yan, Qi; Liu, Weiliang; Duan, Shujie; Sun, Cuiting; Zhang, Shuo; Han, Zhihang; Jin, Xiren; Zhao, Lei; Geng, Tao; Sun, Weimin; Yuan, Libo
2018-05-01
In this paper, a new cascade structure is presented to measure temperature and strain simultaneously. It is made of a CO2-laser-notched long-period fiber grating (CO2-LFPG) and a modular LFPG. Experiments prove that the temperature sensitivity of the modular LPFG is about 5 times lower than that of the CO2-LFPG. Before and after connecting the modular LPFG and the CO2-LPFG together, the experimental results indicate that the temperature and the strain sensitivities of them almost have no change and are retained. The temperature and the strain sensitivities of modular LPFG (resonance wavelength at 1258 nm) are -15.4 pm/°C and -1.2 pm/με, respectively. And the temperature and the strain sensitivities of CO2-LPFG (resonance wavelength at 1356 nm) are 58.3 pm/°C and -0.5 pm/με, respectively. Through the experiments, the feasibility of using the proposed sensor to measure strain and temperature simultaneously has been verified. Therefore, it is strongly believed that the proposed sensor can be used to achieve simultaneous measurement of strain and temperature.
The Dichotomy in Degree Correlation of Biological Networks
Hao, Dapeng; Li, Chuanxing
2011-01-01
Most complex networks from different areas such as biology, sociology or technology, show a correlation on node degree where the possibility of a link between two nodes depends on their connectivity. It is widely believed that complex networks are either disassortative (links between hubs are systematically suppressed) or assortative (links between hubs are enhanced). In this paper, we analyze a variety of biological networks and find that they generally show a dichotomous degree correlation. We find that many properties of biological networks can be explained by this dichotomy in degree correlation, including the neighborhood connectivity, the sickle-shaped clustering coefficient distribution and the modularity structure. This dichotomy distinguishes biological networks from real disassortative networks or assortative networks such as the Internet and social networks. We suggest that the modular structure of networks accounts for the dichotomy in degree correlation and vice versa, shedding light on the source of modularity in biological networks. We further show that a robust and well connected network necessitates the dichotomy of degree correlation, suggestive of an evolutionary motivation for its existence. Finally, we suggest that a dichotomous degree correlation favors a centrally connected modular network, by which the integrity of network and specificity of modules might be reconciled. PMID:22164269
Alcalde Cuesta, Fernando; González Sequeiros, Pablo; Lozano Rojo, Álvaro
2016-02-10
For a network, the accomplishment of its functions despite perturbations is called robustness. Although this property has been extensively studied, in most cases, the network is modified by removing nodes. In our approach, it is no longer perturbed by site percolation, but evolves after site invasion. The process transforming resident/healthy nodes into invader/mutant/diseased nodes is described by the Moran model. We explore the sources of robustness (or its counterpart, the propensity to spread favourable innovations) of the US high-voltage power grid network, the Internet2 academic network, and the C. elegans connectome. We compare them to three modular and non-modular benchmark networks, and samples of one thousand random networks with the same degree distribution. It is found that, contrary to what happens with networks of small order, fixation probability and robustness are poorly correlated with most of standard statistics, but they depend strongly on the degree distribution. While community detection techniques are able to detect the existence of a central core in Internet2, they are not effective in detecting hierarchical structures whose topological complexity arises from the repetition of a few rules. Box counting dimension and Rent's rule are applied to show a subtle trade-off between topological and wiring complexity.
Alcalde Cuesta, Fernando; González Sequeiros, Pablo; Lozano Rojo, Álvaro
2016-01-01
For a network, the accomplishment of its functions despite perturbations is called robustness. Although this property has been extensively studied, in most cases, the network is modified by removing nodes. In our approach, it is no longer perturbed by site percolation, but evolves after site invasion. The process transforming resident/healthy nodes into invader/mutant/diseased nodes is described by the Moran model. We explore the sources of robustness (or its counterpart, the propensity to spread favourable innovations) of the US high-voltage power grid network, the Internet2 academic network, and the C. elegans connectome. We compare them to three modular and non-modular benchmark networks, and samples of one thousand random networks with the same degree distribution. It is found that, contrary to what happens with networks of small order, fixation probability and robustness are poorly correlated with most of standard statistics, but they depend strongly on the degree distribution. While community detection techniques are able to detect the existence of a central core in Internet2, they are not effective in detecting hierarchical structures whose topological complexity arises from the repetition of a few rules. Box counting dimension and Rent’s rule are applied to show a subtle trade-off between topological and wiring complexity. PMID:26861189
Mello, Marco A. R.; Bronstein, Judith L.; Guerra, Tadeu J.; Muylaert, Renata L.; Leite, Alice C.; Neves, Frederico S.
2016-01-01
Ant-plant associations are an outstanding model to study the entangled ecological interactions that structure communities. However, most studies of plant-animal networks focus on only one type of resource that mediates these interactions (e.g, nectar or fruits), leading to a biased understanding of community structure. New approaches, however, have made possible to study several interaction types simultaneously through multilayer networks models. Here, we use this approach to ask whether the structural patterns described to date for ant-plant networks hold when multiple interactions with plant-derived food rewards are considered. We tested whether networks characterized by different resource types differ in specialization and resource partitioning among ants, and whether the identity of the core ant species is similar among resource types. We monitored ant interactions with extrafloral nectaries, flowers, and fruits, as well as trophobiont hemipterans feeding on plants, for one year, in seven rupestrian grassland (campo rupestre) sites in southeastern Brazil. We found a highly tangled ant-plant network in which plants offering different resource types are connected by a few central ant species. The multilayer network had low modularity and specialization, but ant specialization and niche overlap differed according to the type of resource used. Beyond detecting structural differences across networks, our study demonstrates empirically that the core of most central ant species is similar across them. We suggest that foraging strategies of ant species, such as massive recruitment, may determine specialization and resource partitioning in ant-plant interactions. As this core of ant species is involved in multiple ecosystem functions, it may drive the diversity and evolution of the entire campo rupestre community. PMID:27911919
Rational Modular RNA Engineering Based on In Vivo Profiling of Structural Accessibility.
Leistra, Abigail N; Amador, Paul; Buvanendiran, Aishwarya; Moon-Walker, Alex; Contreras, Lydia M
2017-12-15
Bacterial small RNAs (sRNAs) have been established as powerful parts for controlling gene expression. However, development and application of engineered sRNAs has primarily focused on regulating novel synthetic targets. In this work, we demonstrate a rational modular RNA engineering approach that uses in vivo structural accessibility measurements to tune the regulatory activity of a multisubstrate sRNA for differential control of its native target network. Employing the CsrB global sRNA regulator as a model system, we use published in vivo structural accessibility data to infer the contribution of its local structures (substructures) to function and select a subset for engineering. We then modularly recombine the selected substructures, differentially representing those of presumed high or low functional contribution, to build a library of 21 CsrB variants. Using fluorescent translational reporter assays, we demonstrate that the CsrB variants achieve a 5-fold gradient of control of well-characterized Csr network targets. Interestingly, results suggest that less conserved local structures within long, multisubstrate sRNAs may represent better targets for rational engineering than their well-conserved counterparts. Lastly, mapping the impact of sRNA variants on a signature Csr network phenotype indicates the potential of this approach for tuning the activity of global sRNA regulators in the context of metabolic engineering applications.
Ray, Sumanta; Maulik, Ujjwal
2016-12-20
Detecting perturbation in modular structure during HIV-1 disease progression is an important step to understand stage specific infection pattern of HIV-1 virus in human cell. In this article, we proposed a novel methodology on integration of multiple biological information to identify such disruption in human gene module during different stages of HIV-1 infection. We integrate three different biological information: gene expression information, protein-protein interaction information and gene ontology information in single gene meta-module, through non negative matrix factorization (NMF). As the identified metamodules inherit those information so, detecting perturbation of these, reflects the changes in expression pattern, in PPI structure and in functional similarity of genes during the infection progression. To integrate modules of different data sources into strong meta-modules, NMF based clustering is utilized here. Perturbation in meta-modular structure is identified by investigating the topological and intramodular properties and putting rank to those meta-modules using a rank aggregation algorithm. We have also analyzed the preservation structure of significant GO terms in which the human proteins of the meta-modules participate. Moreover, we have performed an analysis to show the change of coregulation pattern of identified transcription factors (TFs) over the HIV progression stages.
Inferring species roles in metacommunity structure from species co-occurrence networks
Borthagaray, Ana I.; Arim, Matías; Marquet, Pablo A.
2014-01-01
A long-standing question in community ecology is what determines the identity of species that coexist across local communities or metacommunity assembly. To shed light upon this question, we used a network approach to analyse the drivers of species co-occurrence patterns. In particular, we focus on the potential roles of body size and trophic status as determinants of metacommunity cohesion because of their link to resource use and dispersal ability. Small-sized individuals at low-trophic levels, and with limited dispersal potential, are expected to form highly linked subgroups, whereas large-size individuals at higher trophic positions, and with good dispersal potential, will foster the spatial coupling of subgroups and the cohesion of the whole metacommunity. By using modularity analysis, we identified six modules of species with similar responses to ecological conditions and high co-occurrence across local communities. Most species either co-occur with species from a single module or are connectors of the whole network. Among the latter are carnivorous species of intermediate body size, which by virtue of their high incidence provide connectivity to otherwise isolated communities playing the role of spatial couplers. Our study also demonstrates that the incorporation of network tools to the analysis of metacommunity ecology can help unveil the mechanisms underlying patterns and processes in metacommunity assembly. PMID:25143039
NASA Astrophysics Data System (ADS)
Wagener, T.; Kelleher, C.; Weiler, M.; McGlynn, B.; Gooseff, M.; Marshall, L.; Meixner, T.; McGuire, K.; Gregg, S.; Sharma, P.; Zappe, S.
2012-09-01
Protection from hydrological extremes and the sustainable supply of hydrological services in the presence of changing climate and lifestyles as well as rocketing population pressure in many parts of the world are the defining societal challenges for hydrology in the 21st century. A review of the existing literature shows that these challenges and their educational consequences for hydrology were foreseeable and were even predicted by some. However, surveys of the current educational basis for hydrology also clearly demonstrate that hydrology education is not yet ready to prepare students to deal with these challenges. We present our own vision of the necessary evolution of hydrology education, which we implemented in the Modular Curriculum for Hydrologic Advancement (MOCHA). The MOCHA project is directly aimed at developing a community-driven basis for hydrology education. In this paper we combine literature review, community survey, discussion and assessment to provide a holistic baseline for the future of hydrology education. The ultimate objective of our educational initiative is to enable educators to train a new generation of "renaissance hydrologists," who can master the holistic nature of our field and of the problems we encounter.
Modular assembly of thick multifunctional cardiac patches
Fleischer, Sharon; Shapira, Assaf; Feiner, Ron; Dvir, Tal
2017-01-01
In cardiac tissue engineering cells are seeded within porous biomaterial scaffolds to create functional cardiac patches. Here, we report on a bottom-up approach to assemble a modular tissue consisting of multiple layers with distinct structures and functions. Albumin electrospun fiber scaffolds were laser-patterned to create microgrooves for engineering aligned cardiac tissues exhibiting anisotropic electrical signal propagation. Microchannels were patterned within the scaffolds and seeded with endothelial cells to form closed lumens. Moreover, cage-like structures were patterned within the scaffolds and accommodated poly(lactic-co-glycolic acid) (PLGA) microparticulate systems that controlled the release of VEGF, which promotes vascularization, or dexamethasone, an anti-inflammatory agent. The structure, morphology, and function of each layer were characterized, and the tissue layers were grown separately in their optimal conditions. Before transplantation the tissue and microparticulate layers were integrated by an ECM-based biological glue to form thick 3D cardiac patches. Finally, the patches were transplanted in rats, and their vascularization was assessed. Because of the simple modularity of this approach, we believe that it could be used in the future to assemble other multicellular, thick, 3D, functional tissues. PMID:28167795
Method for hierarchical modeling of the command of flexible manufacturing systems
NASA Astrophysics Data System (ADS)
Ausfelder, Christian; Castelain, Emmanuel; Gentina, Jean-Claude
1994-04-01
The present paper focuses on the modeling of the command and proposes a hierarchical and modular approach which is oriented on the physical structure of FMS. The requirements issuing from monitoring of FMS are discussed and integrated in the proposed model. Its modularity makes the approach open for extensions concerning as well the production resources as the products. As a modeling tool, we have chosen Object Petri nets. The first part of the paper describes desirable features of an FMS command such as safety, robustness, and adaptability. As it is shown, these features result from the flexibility of the installation. The modeling method presented in the second part of the paper begins with a structural analysis of FMS and defines a natural command hierarchy, where the coordination of the production process, the synchronization of production resources on products, and the internal coordination are treated separately. The method is rigorous and leads to a structured and modular Petri net model which can be used for FMS simulation or translated into the final command code.
Teaching Anthropology at the College Level
ERIC Educational Resources Information Center
Moore, Dward A., Jr.; And Others
1976-01-01
Presents two articles: "Modular Flexibility in an Individualized Introductory Cultural Anthropology Course," by Daniel D. Whitney and Patrick J. Dubbs, and, "Physical Anthropology as a Laboratory Science Course in a Community College," by Yechiel M. Lehavy. The former describes an individualized approach to anthropology, whereas the latter…
Technology-based design and scaling for RTGs for space exploration in the 100 W range
NASA Astrophysics Data System (ADS)
Summerer, Leopold; Pierre Roux, Jean; Pustovalov, Alexey; Gusev, Viacheslav; Rybkin, Nikolai
2011-04-01
This paper presents the results of a study on design considerations for a 100 W radioisotope thermo-electric generator (RTG). Special emphasis has been put on designing a modular, multi-purpose system with high overall TRL levels and making full use of the extensive Russian heritage in the design of radioisotope power systems. The modular approach allowed insight into the scaling of such RTGs covering the electric power range from 50 to 200 W e (EoL). The retained concept is based on a modular thermal block structure, a radiative inner-RTG heat transfer and using a two-stage thermo-electric conversion system.
Yuzawa, Satoshi; Keasling, Jay D; Katz, Leonard
2017-04-01
Complex polyketides comprise a large number of natural products that have broad application in medicine and agriculture. They are produced in bacteria and fungi from large enzyme complexes named type I modular polyketide synthases (PKSs) that are composed of multifunctional polypeptides containing discrete enzymatic domains organized into modules. The modular nature of PKSs has enabled a multitude of efforts to engineer the PKS genes to produce novel polyketides of predicted structure. We have repurposed PKSs to produce a number of short-chain mono- and di-carboxylic acids and ketones that could have applications as fuels or industrial chemicals.
Controlled recovery of phylogenetic communities from an evolutionary model using a network approach
NASA Astrophysics Data System (ADS)
Sousa, Arthur M. Y. R.; Vieira, André P.; Prado, Carmen P. C.; Andrade, Roberto F. S.
2016-04-01
This works reports the use of a complex network approach to produce a phylogenetic classification tree of a simple evolutionary model. This approach has already been used to treat proteomic data of actual extant organisms, but an investigation of its reliability to retrieve a traceable evolutionary history is missing. The used evolutionary model includes key ingredients for the emergence of groups of related organisms by differentiation through random mutations and population growth, but purposefully omits other realistic ingredients that are not strictly necessary to originate an evolutionary history. This choice causes the model to depend only on a small set of parameters, controlling the mutation probability and the population of different species. Our results indicate that for a set of parameter values, the phylogenetic classification produced by the used framework reproduces the actual evolutionary history with a very high average degree of accuracy. This includes parameter values where the species originated by the evolutionary dynamics have modular structures. In the more general context of community identification in complex networks, our model offers a simple setting for evaluating the effects, on the efficiency of community formation and identification, of the underlying dynamics generating the network itself.
Characteristics of detectors for prevention of nuclear radiation terrorism
NASA Astrophysics Data System (ADS)
Kolesnikov, S. V.; Ryabeva, E. V.; Samosadny, V. T.
2017-01-01
There is description of one type of detectors in use for the task of nuclear terrorism cases prevention to determine the direction to the radioactive source and geometrical structure of radiation field. This type is a modular detector with anisotropic sensitivity. The principle of work of a modular detecting device is the simultaneous operation of several detecting modules with anisotropic sensitivity to gamma radiation.
Modular assembly of metal-organic super-containers incorporating calixarenes
Wang, Zhenqiang; Dai, Feng-Rong
2018-01-16
A new strategy to design container molecules is presented. Sulfonylcalix[4]arenes, which are synthetic macrocyclic containers, are used as building blocks that are combined with various metal ions and tricarboxylate ligands to construct metal-organic `super-containers` (MOSCs). These MOSCs possess both endo and exo cavities and thus mimic the structure of viruses. The synthesis of MOSCs is highly modular, robust, and predictable.
Pires, Mathias M; Galetti, Mauro; Donatti, Camila I; Pizo, Marco A; Dirzo, Rodolfo; Guimarães, Paulo R
2014-08-01
The late Quaternary megafaunal extinction impacted ecological communities worldwide, and affected key ecological processes such as seed dispersal. The traits of several species of large-seeded plants are thought to have evolved in response to interactions with extinct megafauna, but how these extinctions affected the organization of interactions in seed-dispersal systems is poorly understood. Here, we combined ecological and paleontological data and network analyses to investigate how the structure of a species-rich seed-dispersal network could have changed from the Pleistocene to the present and examine the possible consequences of such changes. Our results indicate that the seed-dispersal network was organized into modules across the different time periods but has been reconfigured in different ways over time. The episode of megafaunal extinction and the arrival of humans changed how seed dispersers were distributed among network modules. However, the recent introduction of livestock into the seed-dispersal system partially restored the original network organization by strengthening the modular configuration. Moreover, after megafaunal extinctions, introduced species and some smaller native mammals became key components for the structure of the seed-dispersal network. We hypothesize that such changes in network structure affected both animal and plant assemblages, potentially contributing to the shaping of modern ecological communities. The ongoing extinction of key large vertebrates will lead to a variety of context-dependent rearranged ecological networks, most certainly affecting ecological and evolutionary processes.
Detecting phenotype-driven transitions in regulatory network structure.
Padi, Megha; Quackenbush, John
2018-01-01
Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure. Here, we describe ALPACA (ALtered Partitions Across Community Architectures), a method for comparing two genome-scale networks derived from different phenotypic states to identify condition-specific modules. In simulations, ALPACA leads to more nuanced, sensitive, and robust module discovery than currently available network comparison methods. As an application, we use ALPACA to compare transcriptional networks in three contexts: angiogenic and non-angiogenic subtypes of ovarian cancer, human fibroblasts expressing transforming viral oncogenes, and sexual dimorphism in human breast tissue. In each case, ALPACA identifies modules enriched for processes relevant to the phenotype. For example, modules specific to angiogenic ovarian tumors are enriched for genes associated with blood vessel development, and modules found in female breast tissue are enriched for genes involved in estrogen receptor and ERK signaling. The functional relevance of these new modules suggests that not only can ALPACA identify structural changes in complex networks, but also that these changes may be relevant for characterizing biological phenotypes.
NASA Technical Reports Server (NTRS)
Tesar, Delbert; Butler, Michael S.
1989-01-01
Most robotic systems today are designed one at a time, at a high cost of time and money. This wasteful approach has been necessary because the industry has not established a foundation for the continued evolution of intelligent machines. The next generation of robots will have to be generic, versatile machines capable of absorbing new technology rapidly and economically. This approach is demonstrated in the success of the personal computer, which can be upgraded or expanded with new software and hardware at virtually every level. Modularity is perceived as a major opportunity to reduce the 6 to 7 year design cycle time now required for new robotic manipulators, greatly increasing the breadth and speed of diffusion of robotic systems in manufacturing. Modularity and its crucial role in the next generation of intelligent machines are the focus of interest. The main advantages that modularity provides are examined; types of modules needed to create a generic robot are discussed. Structural modules designed by the robotics group at the University of Texas at Austin are examined to demonstrate the advantages of modular design.
Tien, Kai-Wen; Kulvatunyou, Boonserm; Jung, Kiwook; Prabhu, Vittaldas
2017-01-01
As cloud computing is increasingly adopted, the trend is to offer software functions as modular services and compose them into larger, more meaningful ones. The trend is attractive to analytical problems in the manufacturing system design and performance improvement domain because 1) finding a global optimization for the system is a complex problem; and 2) sub-problems are typically compartmentalized by the organizational structure. However, solving sub-problems by independent services can result in a sub-optimal solution at the system level. This paper investigates the technique called Analytical Target Cascading (ATC) to coordinate the optimization of loosely-coupled sub-problems, each may be modularly formulated by differing departments and be solved by modular analytical services. The result demonstrates that ATC is a promising method in that it offers system-level optimal solutions that can scale up by exploiting distributed and modular executions while allowing easier management of the problem formulation.
NASA Technical Reports Server (NTRS)
By, Andre Bernard; Caron, Ken; Rothenberg, Michael; Sales, Vic
1994-01-01
This paper presents the first phase results of a collaborative effort between university researchers and a flexible assembly systems integrator to implement a comprehensive modular approach to flexible assembly automation. This approach, named MARAS (Modular Automated Reconfigurable Assembly System), has been structured to support multiple levels of modularity in terms of both physical components and system control functions. The initial focus of the MARAS development has been on parts gauging and feeding operations for cylinder lock assembly. This phase is nearing completion and has resulted in the development of a highly configurable system for vision gauging functions on a wide range of small components (2 mm to 100 mm in size). The reconfigurable concepts implemented in this adaptive Vision Gauging Module (VGM) are now being extended to applicable aspects of the singulating, selecting, and orienting functions required for the flexible feeding of similar mechanical components and assemblies.
Solar Technology Curriculum, 1980.
ERIC Educational Resources Information Center
Seward County Community Coll., Liberal, KS.
This curriculum guide contains lecture outlines and handouts for training solar technicians in the installation, maintenance, and repair of solar energy hot water and space heating systems. The curriculum consists of four modular units developed to provide a model through which community colleges and area vocational/technical schools can respond…
Iplt--image processing library and toolkit for the electron microscopy community.
Philippsen, Ansgar; Schenk, Andreas D; Stahlberg, Henning; Engel, Andreas
2003-01-01
We present the foundation for establishing a modular, collaborative, integrated, open-source architecture for image processing of electron microscopy images, named iplt. It is designed around object oriented paradigms and implemented using the programming languages C++ and Python. In many aspects it deviates from classical image processing approaches. This paper intends to motivate developers within the community to participate in this on-going project. The iplt homepage can be found at http://www.iplt.org.
A Modular Aero-Propulsion System Simulation of a Large Commercial Aircraft Engine
NASA Technical Reports Server (NTRS)
DeCastro, Jonathan A.; Litt, Jonathan S.; Frederick, Dean K.
2008-01-01
A simulation of a commercial engine has been developed in a graphical environment to meet the increasing need across the controls and health management community for a common research and development platform. This paper describes the Commercial Modular Aero Propulsion System Simulation (C-MAPSS), which is representative of a 90,000-lb thrust class two spool, high bypass ratio commercial turbofan engine. A control law resembling the state-of-the-art on board modern aircraft engines is included, consisting of a fan-speed control loop supplemented by relevant engine limit protection regulator loops. The objective of this paper is to provide a top-down overview of the complete engine simulation package.
NASA Technical Reports Server (NTRS)
Beckham, W. S., Jr.; Keune, F. A.
1974-01-01
The MIUS (Modular Integrated Utility System) concept is to be an energy-conserving, economically feasible, integrated community utility system to provide five necessary services: electricity generation, space heating and air conditioning, solid waste processing, liquid waste processing, and residential water purification. The MIST (MIUS Integration and Subsystem Test) integrated system testbed constructed at the Johnson Space Center in Houston includes subsystems for power generation, heating, ventilation, and air conditioning (HVAC), wastewater management, solid waste management, and control and monitoring. The key design issues under study include thermal integration and distribution techniques, thermal storage, integration of subsystems controls and displays, incinerator performance, effluent characteristics, and odor control.
Advanced capabilities for materials modelling with Quantum ESPRESSO
NASA Astrophysics Data System (ADS)
Giannozzi, P.; Andreussi, O.; Brumme, T.; Bunau, O.; Buongiorno Nardelli, M.; Calandra, M.; Car, R.; Cavazzoni, C.; Ceresoli, D.; Cococcioni, M.; Colonna, N.; Carnimeo, I.; Dal Corso, A.; de Gironcoli, S.; Delugas, P.; DiStasio, R. A., Jr.; Ferretti, A.; Floris, A.; Fratesi, G.; Fugallo, G.; Gebauer, R.; Gerstmann, U.; Giustino, F.; Gorni, T.; Jia, J.; Kawamura, M.; Ko, H.-Y.; Kokalj, A.; Küçükbenli, E.; Lazzeri, M.; Marsili, M.; Marzari, N.; Mauri, F.; Nguyen, N. L.; Nguyen, H.-V.; Otero-de-la-Roza, A.; Paulatto, L.; Poncé, S.; Rocca, D.; Sabatini, R.; Santra, B.; Schlipf, M.; Seitsonen, A. P.; Smogunov, A.; Timrov, I.; Thonhauser, T.; Umari, P.; Vast, N.; Wu, X.; Baroni, S.
2017-11-01
Quantum EXPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the-art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudopotential and projector-augmented-wave approaches. Quantum EXPRESSO owes its popularity to the wide variety of properties and processes it allows to simulate, to its performance on an increasingly broad array of hardware architectures, and to a community of researchers that rely on its capabilities as a core open-source development platform to implement their ideas. In this paper we describe recent extensions and improvements, covering new methodologies and property calculators, improved parallelization, code modularization, and extended interoperability both within the distribution and with external software.
Advanced capabilities for materials modelling with Quantum ESPRESSO.
Giannozzi, P; Andreussi, O; Brumme, T; Bunau, O; Buongiorno Nardelli, M; Calandra, M; Car, R; Cavazzoni, C; Ceresoli, D; Cococcioni, M; Colonna, N; Carnimeo, I; Dal Corso, A; de Gironcoli, S; Delugas, P; DiStasio, R A; Ferretti, A; Floris, A; Fratesi, G; Fugallo, G; Gebauer, R; Gerstmann, U; Giustino, F; Gorni, T; Jia, J; Kawamura, M; Ko, H-Y; Kokalj, A; Küçükbenli, E; Lazzeri, M; Marsili, M; Marzari, N; Mauri, F; Nguyen, N L; Nguyen, H-V; Otero-de-la-Roza, A; Paulatto, L; Poncé, S; Rocca, D; Sabatini, R; Santra, B; Schlipf, M; Seitsonen, A P; Smogunov, A; Timrov, I; Thonhauser, T; Umari, P; Vast, N; Wu, X; Baroni, S
2017-10-24
Quantum EXPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the-art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudopotential and projector-augmented-wave approaches. Quantum EXPRESSO owes its popularity to the wide variety of properties and processes it allows to simulate, to its performance on an increasingly broad array of hardware architectures, and to a community of researchers that rely on its capabilities as a core open-source development platform to implement their ideas. In this paper we describe recent extensions and improvements, covering new methodologies and property calculators, improved parallelization, code modularization, and extended interoperability both within the distribution and with external software.
Advanced capabilities for materials modelling with Quantum ESPRESSO.
Andreussi, Oliviero; Brumme, Thomas; Bunau, Oana; Buongiorno Nardelli, Marco; Calandra, Matteo; Car, Roberto; Cavazzoni, Carlo; Ceresoli, Davide; Cococcioni, Matteo; Colonna, Nicola; Carnimeo, Ivan; Dal Corso, Andrea; de Gironcoli, Stefano; Delugas, Pietro; DiStasio, Robert; Ferretti, Andrea; Floris, Andrea; Fratesi, Guido; Fugallo, Giorgia; Gebauer, Ralph; Gerstmann, Uwe; Giustino, Feliciano; Gorni, Tommaso; Jia, Junteng; Kawamura, Mitsuaki; Ko, Hsin-Yu; Kokalj, Anton; Küçükbenli, Emine; Lazzeri, Michele; Marsili, Margherita; Marzari, Nicola; Mauri, Francesco; Nguyen, Ngoc Linh; Nguyen, Huy-Viet; Otero-de-la-Roza, Alberto; Paulatto, Lorenzo; Poncé, Samuel; Giannozzi, Paolo; Rocca, Dario; Sabatini, Riccardo; Santra, Biswajit; Schlipf, Martin; Seitsonen, Ari Paavo; Smogunov, Alexander; Timrov, Iurii; Thonhauser, Timo; Umari, Paolo; Vast, Nathalie; Wu, Xifan; Baroni, Stefano
2017-09-27
Quantum ESPRESSO is an integrated suite of open-source computer codes for quantum simulations of materials using state-of-the art electronic-structure techniques, based on density-functional theory, density-functional perturbation theory, and many-body perturbation theory, within the plane-wave pseudo-potential and projector-augmented-wave approaches. Quantum ESPRESSO owes its popularity to the wide variety of properties and processes it allows to simulate, to its performance on an increasingly broad array of hardware architectures, and to a community of researchers that rely on its capabilities as a core open-source development platform to implement theirs ideas. In this paper we describe recent extensions and improvements, covering new methodologies and property calculators, improved parallelization, code modularization, and extended interoperability both within the distribution and with external software. © 2017 IOP Publishing Ltd.
Tutorial: Asteroseismic Stellar Modelling with AIMS
NASA Astrophysics Data System (ADS)
Lund, Mikkel N.; Reese, Daniel R.
The goal of aims (Asteroseismic Inference on a Massive Scale) is to estimate stellar parameters and credible intervals/error bars in a Bayesian manner from a set of asteroseismic frequency data and so-called classical constraints. To achieve reliable parameter estimates and computational efficiency, it searches through a grid of pre-computed models using an MCMC algorithm—interpolation within the grid of models is performed by first tessellating the grid using a Delaunay triangulation and then doing a linear barycentric interpolation on matching simplexes. Inputs for the modelling consist of individual frequencies from peak-bagging, which can be complemented with classical spectroscopic constraints. aims is mostly written in Python with a modular structure to facilitate contributions from the community. Only a few computationally intensive parts have been rewritten in Fortran in order to speed up calculations.
Development of modular control software for construction 3D-printer
NASA Astrophysics Data System (ADS)
Bazhanov, A.; Yudin, D.; Porkhalo, V.
2018-03-01
This article discusses the approach to developing modular software for real-time control of an industrial construction 3D printer. The proposed structure of a two-level software solution is implemented for a robotic system that moves in a Cartesian coordinate system with multi-axis interpolation. An algorithm for the formation and analysis of a path is considered to enable the most effective control of printing through dynamic programming.
Intelligence is associated with the modular structure of intrinsic brain networks.
Hilger, Kirsten; Ekman, Matthias; Fiebach, Christian J; Basten, Ulrike
2017-11-22
General intelligence is a psychological construct that captures in a single metric the overall level of behavioural and cognitive performance in an individual. While previous research has attempted to localise intelligence in circumscribed brain regions, more recent work focuses on functional interactions between regions. However, even though brain networks are characterised by substantial modularity, it is unclear whether and how the brain's modular organisation is associated with general intelligence. Modelling subject-specific brain network graphs from functional MRI resting-state data (N = 309), we found that intelligence was not associated with global modularity features (e.g., number or size of modules) or the whole-brain proportions of different node types (e.g., connector hubs or provincial hubs). In contrast, we observed characteristic associations between intelligence and node-specific measures of within- and between-module connectivity, particularly in frontal and parietal brain regions that have previously been linked to intelligence. We propose that the connectivity profile of these regions may shape intelligence-relevant aspects of information processing. Our data demonstrate that not only region-specific differences in brain structure and function, but also the network-topological embedding of fronto-parietal as well as other cortical and subcortical brain regions is related to individual differences in higher cognitive abilities, i.e., intelligence.
Final Report: Self Consolidating Concrete Construction for Modular Units
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gentry, Russell; Kahn, Lawrence; Kurtis, Kimberly
This report outlines the development of a self-consolidating concrete (also termed “self-compacting concrete” or SCC) so that concrete placement can be made into steel plate composite (SC) modular structures without the need for continuous concrete placement. As part of the research, SCC mixtures were developed and validated to ensure sufficient shear capacity across cold-joints, while minimizing shrinkage and temperature increase during curing to enhance concrete bonding with the steel plate construction found in modular units. The self-roughening concrete produced as part of this research was assessed in SC structures at three scales: small-scale shear-friction specimens, mid-scale beams tested in in-planemore » and out-of-plane bending, and a full-scale validation test using an SC module produced by Westinghouse as part of the Plant Vogtle expansion. The experiments show that the self-roughening concrete can produce a cold-joint surface of 0.25 inches (6 mm) without external vibration during concrete placement. The experiments and subsequent analysis show that the shear friction provisions of ACI 318-14, Section 22.9 can be used to assess the shear capacity of the cold-joints in SC modular construction, and that friction coefficient of 1.35 is appropriate for use with these provisions.« less
Split green fluorescent protein as a modular binding partner for protein crystallization
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nguyen, Hau B.; Hung, Li-Wei; Yeates, Todd O.
2013-12-01
A strategy using a new split green fluorescent protein (GFP) as a modular binding partner to form stable protein complexes with a target protein is presented. The modular split GFP may open the way to rapidly creating crystallization variants. A modular strategy for protein crystallization using split green fluorescent protein (GFP) as a crystallization partner is demonstrated. Insertion of a hairpin containing GFP β-strands 10 and 11 into a surface loop of a target protein provides two chain crossings between the target and the reconstituted GFP compared with the single connection afforded by terminal GFP fusions. This strategy was testedmore » by inserting this hairpin into a loop of another fluorescent protein, sfCherry. The crystal structure of the sfCherry-GFP(10–11) hairpin in complex with GFP(1–9) was determined at a resolution of 2.6 Å. Analysis of the complex shows that the reconstituted GFP is attached to the target protein (sfCherry) in a structurally ordered way. This work opens the way to rapidly creating crystallization variants by reconstituting a target protein bearing the GFP(10–11) hairpin with a variety of GFP(1–9) mutants engineered for favorable crystallization.« less
Raherison, Elie S M; Giguère, Isabelle; Caron, Sébastien; Lamara, Mebarek; MacKay, John J
2015-07-01
Transcript profiling has shown the molecular bases of several biological processes in plants but few studies have developed an understanding of overall transcriptome variation. We investigated transcriptome structure in white spruce (Picea glauca), aiming to delineate its modular organization and associated functional and evolutionary attributes. Microarray analyses were used to: identify and functionally characterize groups of co-expressed genes; investigate expressional and functional diversity of vascular tissue preferential genes which were conserved among Picea species, and identify expression networks underlying wood formation. We classified 22 857 genes as variable (79%; 22 coexpression groups) or invariant (21%) by profiling across several vegetative tissues. Modular organization and complex transcriptome restructuring among vascular tissue preferential genes was revealed by their assignment to coexpression groups with partially overlapping profiles and partially distinct functions. Integrated analyses of tissue-based and temporally variable profiles identified secondary xylem gene networks, showed their remodelling over a growing season and identified PgNAC-7 (no apical meristerm (NAM), Arabidopsis transcription activation factor (ATAF) and cup-shaped cotyledon (CUC) transcription factor 007 in Picea glauca) as a major hub gene specific to earlywood formation. Reference profiling identified comprehensive, statistically robust coexpressed groups, revealing that modular organization underpins the evolutionary conservation of the transcriptome structure. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.
What Is AV Doing in a Humanities Degree?
ERIC Educational Resources Information Center
Thorn, Richard L.
1981-01-01
Describes the Communication module of the B.A. (Honors) Humanities modular degree at Bristol Polytechnic which involves non-Art and Design students in practical audiovisual media work as they undertake "live" projects for clients in the community, e.g., teachers, social workers, or charities. Five references are appended. (Author/LLS)
Orbiting propellent depot safety. Volume 2: Technical discussion
NASA Technical Reports Server (NTRS)
1971-01-01
The results of a study assessing the gross requirements and concomitant safety hazards associated with the operation of several configurations of orbiting propellant depots (OPD) are presented. The major structural and operational aspects of the integral, semimodular, and modular concepts are described. The concepts are evaluated to determine their safety hazards, and emphasis is placed on propellant transfer to and from the OPD. The study indicates that a modular mode of depot resupply is desirable regardless of the OPD configuration. This resupply mode requires no flow transfer to resupply either the semimodular or modular OPD. Of the three concepts, the semimodular appears to provide the best operational advantage and lowest safety risk.
Modular multimorphic kinematic arm structure and pitch and yaw joint for same
Martin, H. Lee; Williams, Daniel M.; Holt, W. Eugene
1989-01-01
A multimorphic kinematic manipulator arm is provided with seven degrees of freedom and modular kinematic redundancy through identical pitch/yaw, shoulder, elbow and wrist joints and a wrist roll device at the wrist joint, which further provides to the manipulator arm an obstacle avoidance capability. The modular pitch/yaw joints are traction drive devices which provide backlash free operation with smooth torque transmission and enhanced rigidity. A dual input drive arrangement is provided for each joint resulting in a reduction of the load required to be assumed by each drive and providing selective pitch and yaw motions by control of the relative rotational directions of the input drive.
Two modular neuro-fuzzy system for mobile robot navigation
NASA Astrophysics Data System (ADS)
Bobyr, M. V.; Titov, V. S.; Kulabukhov, S. A.; Syryamkin, V. I.
2018-05-01
The article considers the fuzzy model for navigation of a mobile robot operating in two modes. In the first mode the mobile robot moves along a line. In the second mode, the mobile robot looks for an target in unknown space. Structural and schematic circuit of four-wheels mobile robot are presented in the article. The article describes the movement of a mobile robot based on two modular neuro-fuzzy system. The algorithm of neuro-fuzzy inference used in two modular control system for movement of a mobile robot is given in the article. The experimental model of the mobile robot and the simulation of the neuro-fuzzy algorithm used for its control are presented in the article.
Modular multimorphic kinematic arm structure and pitch and yaw joint for same
Martin, H.L.; Williams, D.M.; Holt, W.E.
1987-04-21
A multimorphic kinematic manipulator arm is provided with seven degrees of freedom and modular kinematic redundancy through identical pitch/yaw, shoulder, elbow and wrist joints and a wrist roll device at the wrist joint, which further provides to the manipulator arm an obstacle avoidance capability. The modular pitch/yaw joints are traction drive devices which provide backlash free operation with smooth torque transmission and enhanced rigidity. A dual input drive arrangement is provided for each joint resulting in a reduction of the load required to be assumed by each drive means and providing selective pitch and yaw motions by control of the relative rotational directions of the input drive means. 12 figs.
Finding Correlation between Protein Protein Interaction Modules Using Semantic Web Techniques
NASA Astrophysics Data System (ADS)
Kargar, Mehdi; Moaven, Shahrouz; Abolhassani, Hassan
Many complex networks such as social networks and computer show modular structures, where edges between nodes are much denser within modules than between modules. It is strongly believed that cellular networks are also modular, reflecting the relative independence and coherence of different functional units in a cell. In this paper we used a human curated dataset. In this paper we consider each module in the PPI network as ontology. Using techniques in ontology alignment, we compare each pair of modules in the network. We want to see that is there a correlation between the structure of each module or they have totally different structures. Our results show that there is no correlation between proteins in a protein protein interaction network.
Charged structure constants from modularity
NASA Astrophysics Data System (ADS)
Das, Diptarka; Datta, Shouvik; Pal, Sridip
2017-11-01
We derive a universal formula for the average heavy-heavy-light structure constants for 2 d CFTs with non-vanishing u(1) charge. The derivation utilizes the modular properties of one-point functions on the torus. Refinements in N=2 SCFTs, show that the resulting Cardy-like formula for the structure constants has precisely the same shifts in the central charge as that of the thermodynamic entropy found earlier. This analysis generalizes the recent results by Kraus and Maloney for CFTs with an additional global u(1) symmetry [1]. Our results at large central charge are also shown to match with computations from the holographic dual, which suggest that the averaged CFT three-point coefficient also serves as a useful probe of detecting black hole hair.
Bipartite Community Structure of eQTLs.
Platig, John; Castaldi, Peter J; DeMeo, Dawn; Quackenbush, John
2016-09-01
Genome Wide Association Studies (GWAS) and expression quantitative trait locus (eQTL) analyses have identified genetic associations with a wide range of human phenotypes. However, many of these variants have weak effects and understanding their combined effect remains a challenge. One hypothesis is that multiple SNPs interact in complex networks to influence functional processes that ultimately lead to complex phenotypes, including disease states. Here we present CONDOR, a method that represents both cis- and trans-acting SNPs and the genes with which they are associated as a bipartite graph and then uses the modular structure of that graph to place SNPs into a functional context. In applying CONDOR to eQTLs in chronic obstructive pulmonary disease (COPD), we found the global network "hub" SNPs were devoid of disease associations through GWAS. However, the network was organized into 52 communities of SNPs and genes, many of which were enriched for genes in specific functional classes. We identified local hubs within each community ("core SNPs") and these were enriched for GWAS SNPs for COPD and many other diseases. These results speak to our intuition: rather than single SNPs influencing single genes, we see groups of SNPs associated with the expression of families of functionally related genes and that disease SNPs are associated with the perturbation of those functions. These methods are not limited in their application to COPD and can be used in the analysis of a wide variety of disease processes and other phenotypic traits.
Schwarz, Adam J; Gozzi, Alessandro; Bifone, Angelo
2009-08-01
In the study of functional connectivity, fMRI data can be represented mathematically as a network of nodes and links, where image voxels represent the nodes and the connections between them reflect a degree of correlation or similarity in their response. Here we show that, within this framework, functional imaging data can be partitioned into 'communities' of tightly interconnected voxels corresponding to maximum modularity within the overall network. We evaluated this approach systematically in application to networks constructed from pharmacological MRI (phMRI) of the rat brain in response to acute challenge with three different compounds with distinct mechanisms of action (d-amphetamine, fluoxetine, and nicotine) as well as vehicle (physiological saline). This approach resulted in bilaterally symmetric sub-networks corresponding to meaningful anatomical and functional connectivity pathways consistent with the purported mechanism of action of each drug. Interestingly, common features across all three networks revealed two groups of tightly coupled brain structures that responded as functional units independent of the specific neurotransmitter systems stimulated by the drug challenge, including a network involving the prefrontal cortex and sub-cortical regions extending from the striatum to the amygdala. This finding suggests that each of these networks includes general underlying features of the functional organization of the rat brain.
Torak, L.J.
1993-01-01
A MODular Finite-Element, digital-computer program (MODFE) was developed to simulate steady or unsteady-state, two-dimensional or axisymmetric ground-water-flow. The modular structure of MODFE places the computationally independent tasks that are performed routinely by digital-computer programs simulating ground-water flow into separate subroutines, which are executed from the main program by control statements. Each subroutine consists of complete sets of computations, or modules, which are identified by comment statements, and can be modified by the user without affecting unrelated computations elsewhere in the program. Simulation capabilities can be added or modified by either adding or modifying subroutines that perform specific computational tasks, and the modular-program structure allows the user to create versions of MODFE that contain only the simulation capabilities that pertain to the ground-water problem of interest. MODFE is written in a Fortran programming language that makes it virtually device independent and compatible with desk-top personal computers and large mainframes. MODFE uses computer storage and execution time efficiently by taking advantage of symmetry and sparseness within the coefficient matrices of the finite-element equations. Parts of the matrix coefficients are computed and stored as single-subscripted variables, which are assembled into a complete coefficient just prior to solution. Computer storage is reused during simulation to decrease storage requirements. Descriptions of subroutines that execute the computational steps of the modular-program structure are given in tables that cross reference the subroutines with particular versions of MODFE. Programming details of linear and nonlinear hydrologic terms are provided. Structure diagrams for the main programs show the order in which subroutines are executed for each version and illustrate some of the linear and nonlinear versions of MODFE that are possible. Computational aspects of changing stresses and boundary conditions with time and of mass-balance and error terms are given for each hydrologic feature. Program variables are listed and defined according to their occurrence in the main programs and in subroutines. Listings of the main programs and subroutines are given.
Modular reflector concept study
NASA Technical Reports Server (NTRS)
Vaughan, D. H.
1981-01-01
A study was conducted to evaluate the feasibility of space erecting a 100 meter paraboloidal radio frequency reflector by joining a number of individually deployed structural modules. Three module design concepts were considered: (1) the deployable cell module (DCM); (2) the modular paraboloidal erectable truss antenna (Mod-PETA); and (3) the modular erectable truss antenna (META). With the space shuttle (STS) as the launch system, the methodology of packaging and stowing in the orbiter, and of dispensing, deploying and joining, in orbit, were studied and the necessary support equipment identified. The structural performance of the completed reflectors was evaluated and their overall operational capability and feasibility were evaluated and compared. The potential of the three concepts to maintain stable shape in the space environment was determined. Their ability to operate at radio frequencies of 1 GHz and higher was assessed assuming the reflector surface to consist of a number of flat, hexagonal facets. A parametric study was performed to determine figure degradation as a function of reflector size, flat facet size, and f/D ratio.
NASA Astrophysics Data System (ADS)
Wang, Faming; Del Ferraro, Simona; Molinaro, Vincenzo; Morrissey, Matthew; Rossi, René
2014-09-01
Regional sweating patterns and body surface temperature differences exist between genders. Traditional sportswear made from one material and/or one fabric structure has a limited ability to provide athletes sufficient local wear comfort. Body mapping sportswear consists of one piece of multiple knit structure fabric or of different fabric pieces that may provide athletes better wear comfort. In this study, the `modular' body mapping sportswear was designed and subsequently assessed on a `Newton' type sweating manikin that operated in both constant temperature mode and thermophysiological model control mode. The performance of the modular body mapping sportswear kit and commercial products were also compared. The results demonstrated that such a modular body mapping sportswear kit can meet multiple wear/thermal comfort requirements in various environmental conditions. All body mapping clothing (BMC) presented limited global thermophysiological benefits for the wearers. Nevertheless, BMC showed evident improvements in adjusting local body heat exchanges and local thermal sensations.
Wang, Faming; Del Ferraro, Simona; Molinaro, Vincenzo; Morrissey, Matthew; Rossi, René
2014-09-01
Regional sweating patterns and body surface temperature differences exist between genders. Traditional sportswear made from one material and/or one fabric structure has a limited ability to provide athletes sufficient local wear comfort. Body mapping sportswear consists of one piece of multiple knit structure fabric or of different fabric pieces that may provide athletes better wear comfort. In this study, the 'modular' body mapping sportswear was designed and subsequently assessed on a 'Newton' type sweating manikin that operated in both constant temperature mode and thermophysiological model control mode. The performance of the modular body mapping sportswear kit and commercial products were also compared. The results demonstrated that such a modular body mapping sportswear kit can meet multiple wear/thermal comfort requirements in various environmental conditions. All body mapping clothing (BMC) presented limited global thermophysiological benefits for the wearers. Nevertheless, BMC showed evident improvements in adjusting local body heat exchanges and local thermal sensations.
De novo design of protein homo-oligomers with modular hydrogen bond network-mediated specificity
Boyken, Scott E.; Chen, Zibo; Groves, Benjamin; Langan, Robert A.; Oberdorfer, Gustav; Ford, Alex; Gilmore, Jason; Xu, Chunfu; DiMaio, Frank; Pereira, Jose Henrique; Sankaran, Banumathi; Seelig, Georg; Zwart, Peter H.; Baker, David
2017-01-01
In nature, structural specificity in DNA and proteins is encoded quite differently: in DNA, specificity arises from modular hydrogen bonds in the core of the double helix, whereas in proteins, specificity arises largely from buried hydrophobic packing complemented by irregular peripheral polar interactions. Here we describe a general approach for designing a wide range of protein homo-oligomers with specificity determined by modular arrays of central hydrogen bond networks. We use the approach to design dimers, trimers, and tetramers consisting of two concentric rings of helices, including previously not seen triangular, square, and supercoiled topologies. X-ray crystallography confirms that the structures overall, and the hydrogen bond networks in particular, are nearly identical to the design models, and the networks confer interaction specificity in vivo. The ability to design extensive hydrogen bond networks with atomic accuracy is a milestone for protein design and enables the programming of protein interaction specificity for a broad range of synthetic biology applications. PMID:27151862
Hembry, David H; Raimundo, Rafael L G; Newman, Erica A; Atkinson, Lesje; Guo, Chang; Guimarães, Paulo R; Gillespie, Rosemary G
2018-04-25
Biological intimacy-the degree of physical proximity or integration of partner taxa during their life cycles-is thought to promote the evolution of reciprocal specialization and modularity in the networks formed by co-occurring mutualistic species, but this hypothesis has rarely been tested. Here, we test this "biological intimacy hypothesis" by comparing the network architecture of brood pollination mutualisms, in which specialized insects are simultaneously parasites (as larvae) and pollinators (as adults) of their host plants to that of other mutualisms which vary in their biological intimacy (including ant-myrmecophyte, ant-extrafloral nectary, plant-pollinator and plant-seed disperser assemblages). We use a novel dataset sampled from leafflower trees (Phyllanthaceae: Phyllanthus s. l. [Glochidion]) and their pollinating leafflower moths (Lepidoptera: Epicephala) on three oceanic islands (French Polynesia) and compare it to equivalent published data from congeners on continental islands (Japan). We infer taxonomic diversity of leafflower moths using multilocus molecular phylogenetic analysis and examine several network structural properties: modularity (compartmentalization), reciprocality (symmetry) of specialization and algebraic connectivity. We find that most leafflower-moth networks are reciprocally specialized and modular, as hypothesized. However, we also find that two oceanic island networks differ in their modularity and reciprocal specialization from the others, as a result of a supergeneralist moth taxon which interacts with nine of 10 available hosts. Our results generally support the biological intimacy hypothesis, finding that leafflower-moth networks (usually) share a reciprocally specialized and modular structure with other intimate mutualisms such as ant-myrmecophyte symbioses, but unlike nonintimate mutualisms such as seed dispersal and nonintimate pollination. Additionally, we show that generalists-common in nonintimate mutualisms-can also evolve in intimate mutualisms, and that their effect is similar in both types of assemblages: once generalists emerge they reshape the network organization by connecting otherwise isolated modules. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.
mcaGUI: microbial community analysis R-Graphical User Interface (GUI).
Copeland, Wade K; Krishnan, Vandhana; Beck, Daniel; Settles, Matt; Foster, James A; Cho, Kyu-Chul; Day, Mitch; Hickey, Roxana; Schütte, Ursel M E; Zhou, Xia; Williams, Christopher J; Forney, Larry J; Abdo, Zaid
2012-08-15
Microbial communities have an important role in natural ecosystems and have an impact on animal and human health. Intuitive graphic and analytical tools that can facilitate the study of these communities are in short supply. This article introduces Microbial Community Analysis GUI, a graphical user interface (GUI) for the R-programming language (R Development Core Team, 2010). With this application, researchers can input aligned and clustered sequence data to create custom abundance tables and perform analyses specific to their needs. This GUI provides a flexible modular platform, expandable to include other statistical tools for microbial community analysis in the future. The mcaGUI package and source are freely available as part of Bionconductor at http://www.bioconductor.org/packages/release/bioc/html/mcaGUI.html
Modular Chemical Descriptor Language (MCDL): Stereochemical modules
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gakh, Andrei A; Burnett, Michael N; Trepalin, Sergei V.
2011-01-01
In our previous papers we introduced the Modular Chemical Descriptor Language (MCDL) for providing a linear representation of chemical information. A subsequent development was the MCDL Java Chemical Structure Editor which is capable of drawing chemical structures from linear representations and generating MCDL descriptors from structures. In this paper we present MCDL modules and accompanying software that incorporate unique representation of molecular stereochemistry based on Cahn-Ingold-Prelog and Fischer ideas in constructing stereoisomer descriptors. The paper also contains additional discussions regarding canonical representation of stereochemical isomers, and brief algorithm descriptions of the open source LINDES, Java applet, and Open Babel MCDLmore » processing module software packages. Testing of the upgraded MCDL Java Chemical Structure Editor on compounds taken from several large and diverse chemical databases demonstrated satisfactory performance for storage and processing of stereochemical information in MCDL format.« less
Using Hydrazine to Link Ferrocene with Re(CO)3: A Modular Approach.
Chanawanno, Kullapa; Rhoda, Hannah M; Hasheminasab, Abed; Crandall, Laura A; King, Alexander J; Herrick, Richard S; Nemykin, Victor N; Ziegler, Christopher J
2016-09-01
Acetyl ferrocene and diacetyl ferrocene both readily react with an excess of hydrazine to afford the corresponding hydrazone compounds. These compounds can then be linked to Re(CO) 3 via a metal-mediated Schiff base reaction, resulting in a series of ferrocene-Re(CO) 3 conjugates with different stoichiometries. Conjugates with 1:1, 1:2, and 2:1 ferrocene: Re(CO) 3 ratios can be produced via this "modular" type synthesis approach. Several examples of these conjugates were structurally characterized, and their spectroscopic, electrochemical, and spectroelectrochemical behaviors were investigated. The electronic structures of these compounds were also probed using DFT and TDDFT calculations.
A parallel and modular deformable cell Car-Parrinello code
NASA Astrophysics Data System (ADS)
Cavazzoni, Carlo; Chiarotti, Guido L.
1999-12-01
We have developed a modular parallel code implementing the Car-Parrinello [Phys. Rev. Lett. 55 (1985) 2471] algorithm including the variable cell dynamics [Europhys. Lett. 36 (1994) 345; J. Phys. Chem. Solids 56 (1995) 510]. Our code is written in Fortran 90, and makes use of some new programming concepts like encapsulation, data abstraction and data hiding. The code has a multi-layer hierarchical structure with tree like dependences among modules. The modules include not only the variables but also the methods acting on them, in an object oriented fashion. The modular structure allows easier code maintenance, develop and debugging procedures, and is suitable for a developer team. The layer structure permits high portability. The code displays an almost linear speed-up in a wide range of number of processors independently of the architecture. Super-linear speed up is obtained with a "smart" Fast Fourier Transform (FFT) that uses the available memory on the single node (increasing for a fixed problem with the number of processing elements) as temporary buffer to store wave function transforms. This code has been used to simulate water and ammonia at giant planet conditions for systems as large as 64 molecules for ˜50 ps.
Xiao, Fei; Song, Jibin; Gao, Hongcai; Zan, Xiaoli; Xu, Rong; Duan, Hongwei
2012-01-24
The development of flexible electrodes is of considerable current interest because of the increasing demand for modern electronics, portable medical products, and compact energy devices. We report a modular approach to fabricating high-performance flexible electrodes by structurally integrating 2D-assemblies of nanoparticles with freestanding graphene paper. We have shown that the 2D array of gold nanoparticles at oil-water interfaces can be transferred on freestanding graphene oxide paper, leading to a monolayer of densely packed gold nanoparticles of uniform sizes loaded on graphene oxide paper. One major finding is that the postassembly electrochemical reduction of graphene oxide paper restores the ordered structure and electron-transport properties of graphene, and gives rise to robust and biocompatible freestanding electrodes with outstanding electrocatalytic activities, which have been manifested by the sensitive and selective detection of two model analytes: glucose and hydrogen peroxide (H(2)O(2)) secreted by live cells. The modular nature of this approach coupled with recent progress in nanocrystal synthesis and surface engineering opens new possibilities to systematically study the dependence of catalytic performance on the structural parameters and chemical compositions of the nanocrystals. © 2011 American Chemical Society
The modular architecture of protein-protein binding interfaces.
Reichmann, D; Rahat, O; Albeck, S; Meged, R; Dym, O; Schreiber, G
2005-01-04
Protein-protein interactions are essential for life. Yet, our understanding of the general principles governing binding is not complete. In the present study, we show that the interface between proteins is built in a modular fashion; each module is comprised of a number of closely interacting residues, with few interactions between the modules. The boundaries between modules are defined by clustering the contact map of the interface. We show that mutations in one module do not affect residues located in a neighboring module. As a result, the structural and energetic consequences of the deletion of entire modules are surprisingly small. To the contrary, within their module, mutations cause complex energetic and structural consequences. Experimentally, this phenomenon is shown on the interaction between TEM1-beta-lactamase and beta-lactamase inhibitor protein (BLIP) by using multiple-mutant analysis and x-ray crystallography. Replacing an entire module of five interface residues with Ala created a large cavity in the interface, with no effect on the detailed structure of the remaining interface. The modular architecture of binding sites, which resembles human engineering design, greatly simplifies the design of new protein interactions and provides a feasible view of how these interactions evolved.
24 CFR 3282.12 - Excluded structures-modular homes.
Code of Federal Regulations, 2012 CFR
2012-04-01
... is designed only for erection or installation on a site-built permanent foundation; (i) A structure... structure, including but not limited to designs, drawings, and installation or erection instructions...) Capable of transferring all design loads imposed by or upon the structure into soil or bedrock without...
24 CFR 3282.12 - Excluded structures-modular homes.
Code of Federal Regulations, 2014 CFR
2014-04-01
... is designed only for erection or installation on a site-built permanent foundation; (i) A structure... structure, including but not limited to designs, drawings, and installation or erection instructions...) Capable of transferring all design loads imposed by or upon the structure into soil or bedrock without...
24 CFR 3282.12 - Excluded structures-modular homes.
Code of Federal Regulations, 2011 CFR
2011-04-01
... is designed only for erection or installation on a site-built permanent foundation; (i) A structure... structure, including but not limited to designs, drawings, and installation or erection instructions...) Capable of transferring all design loads imposed by or upon the structure into soil or bedrock without...
Zhu, Tao; Scalvenzi, Thibault; Sassoon, Nathalie; Lu, Xuefeng; Gugger, Muriel
2018-07-01
Cyanobacteria can synthesize alkanes and alkenes, which are considered to be infrastructure-compatible biofuels. In terms of physiological function, cyanobacterial hydrocarbons are thought to be essential for membrane flexibility for cell division, size, and growth. The genetic basis for the biosynthesis of terminal olefins (1-alkenes) is a modular type I polyketide synthase (PKS) termed olefin synthase (Ols). The modular architectures of Ols and structural characteristics of alkenes have been investigated only in a few species of the small percentage (approximately 10%) of cyanobacteria that harbor putative Ols pathways. In this study, investigations of the domains, modular architectures, and phylogenies of Ols in 28 cyanobacterial strains suggested distinctive pathway evolution. Structural feature analyses revealed 1-alkenes with three carbon chain lengths (C 15 , C 17 , and C 19 ). In addition, the total cellular fatty acid profile revealed the diversity of the carbon chain lengths, while the fatty acid feeding assay indicated substrate carbon chain length specificity of cyanobacterial Ols enzymes. Finally, in silico analyses suggested that the N terminus of the modular Ols enzyme exhibited characteristics typical of a fatty acyl-adenylate ligase (FAAL), suggesting a mechanism of fatty acid activation via the formation of acyl-adenylates. Our results shed new light on the diversity of cyanobacterial terminal olefins and a mechanism for substrate activation in the biosynthesis of these olefins. IMPORTANCE Cyanobacterial terminal olefins are hydrocarbons with promising applications as advanced biofuels. Despite the basic understanding of the genetic basis of olefin biosynthesis, the structural diversity and phylogeny of the key modular olefin synthase (Ols) have been poorly explored. An overview of the chemical structural traits of terminal olefins in cyanobacteria is provided in this study. In addition, we demonstrated by in vivo fatty acid feeding assays that cyanobacterial Ols enzymes might exhibit substrate carbon chain length specificity. Furthermore, by performing bioinformatic analyses, we observed that the substrate activation domain of Ols exhibited features typical of a fatty acyl-adenylate ligase (FAAL), which activates fatty acids by converting them to fatty acyl-adenylates. Our results provide further insight into the chemical structures of terminal olefins and further elucidate the mechanism of substrate activation for terminal olefin biosynthesis in cyanobacteria. Copyright © 2018 American Society for Microbiology.
Standardized Modular Power Interfaces for Future Space Explorations Missions
NASA Technical Reports Server (NTRS)
Oeftering, Richard
2015-01-01
Earlier studies show that future human explorations missions are composed of multi-vehicle assemblies with interconnected electric power systems. Some vehicles are often intended to serve as flexible multi-purpose or multi-mission platforms. This drives the need for power architectures that can be reconfigured to support this level of flexibility. Power system developmental costs can be reduced, program wide, by utilizing a common set of modular building blocks. Further, there are mission operational and logistics cost benefits of using a common set of modular spares. These benefits are the goals of the Advanced Exploration Systems (AES) Modular Power System (AMPS) project. A common set of modular blocks requires a substantial level of standardization in terms of the Electrical, Data System, and Mechanical interfaces. The AMPS project is developing a set of proposed interface standards that will provide useful guidance for modular hardware developers but not needlessly constrain technology options, or limit future growth in capability. In 2015 the AMPS project focused on standardizing the interfaces between the elements of spacecraft power distribution and energy storage. The development of the modular power standard starts with establishing mission assumptions and ground rules to define design application space. The standards are defined in terms of AMPS objectives including Commonality, Reliability-Availability, Flexibility-Configurability and Supportability-Reusability. The proposed standards are aimed at assembly and sub-assembly level building blocks. AMPS plans to adopt existing standards for spacecraft command and data, software, network interfaces, and electrical power interfaces where applicable. Other standards including structural encapsulation, heat transfer, and fluid transfer, are governed by launch and spacecraft environments and bound by practical limitations of weight and volume. Developing these mechanical interface standards is more difficult but an essential part of defining physical building blocks of modular power. This presentation describes the AMPS projects progress towards standardized modular power interfaces.
Exposing the structure of an Arctic food web.
Wirta, Helena K; Vesterinen, Eero J; Hambäck, Peter A; Weingartner, Elisabeth; Rasmussen, Claus; Reneerkens, Jeroen; Schmidt, Niels M; Gilg, Olivier; Roslin, Tomas
2015-09-01
How food webs are structured has major implications for their stability and dynamics. While poorly studied to date, arctic food webs are commonly assumed to be simple in structure, with few links per species. If this is the case, then different parts of the web may be weakly connected to each other, with populations and species united by only a low number of links. We provide the first highly resolved description of trophic link structure for a large part of a high-arctic food web. For this purpose, we apply a combination of recent techniques to describing the links between three predator guilds (insectivorous birds, spiders, and lepidopteran parasitoids) and their two dominant prey orders (Diptera and Lepidoptera). The resultant web shows a dense link structure and no compartmentalization or modularity across the three predator guilds. Thus, both individual predators and predator guilds tap heavily into the prey community of each other, offering versatile scope for indirect interactions across different parts of the web. The current description of a first but single arctic web may serve as a benchmark toward which to gauge future webs resolved by similar techniques. Targeting an unusual breadth of predator guilds, and relying on techniques with a high resolution, it suggests that species in this web are closely connected. Thus, our findings call for similar explorations of link structure across multiple guilds in both arctic and other webs. From an applied perspective, our description of an arctic web suggests new avenues for understanding how arctic food webs are built and function and of how they respond to current climate change. It suggests that to comprehend the community-level consequences of rapid arctic warming, we should turn from analyses of populations, population pairs, and isolated predator-prey interactions to considering the full set of interacting species.
An Extensible Processing Framework for Eddy-covariance Data
NASA Astrophysics Data System (ADS)
Durden, D.; Fox, A. M.; Metzger, S.; Sturtevant, C.; Durden, N. P.; Luo, H.
2016-12-01
The evolution of large data collecting networks has not only led to an increase of available information, but also in the complexity of analyzing the observations. Timely dissemination of readily usable data products necessitates a streaming processing framework that is both automatable and flexible. Tower networks, such as ICOS, Ameriflux, and NEON, exemplify this issue by requiring large amounts of data to be processed from dispersed measurement sites. Eddy-covariance data from across the NEON network are expected to amount to 100 Gigabytes per day. The complexity of the algorithmic processing necessary to produce high-quality data products together with the continued development of new analysis techniques led to the development of a modular R-package, eddy4R. This allows algorithms provided by NEON and the larger community to be deployed in streaming processing, and to be used by community members alike. In order to control the processing environment, provide a proficient parallel processing structure, and certify dependencies are available during processing, we chose Docker as our "Development and Operations" (DevOps) platform. The Docker framework allows our processing algorithms to be developed, maintained and deployed at scale. Additionally, the eddy4R-Docker framework fosters community use and extensibility via pre-built Docker images and the Github distributed version control system. The capability to process large data sets is reliant upon efficient input and output of data, data compressibility to reduce compute resource loads, and the ability to easily package metadata. The Hierarchical Data Format (HDF5) is a file format that can meet these needs. A NEON standard HDF5 file structure and metadata attributes allow users to explore larger data sets in an intuitive "directory-like" structure adopting the NEON data product naming conventions.
Kallus, Zsófia; Barankai, Norbert; Szüle, János; Vattay, Gábor
2015-01-01
Human interaction networks inferred from country-wide telephone activity recordings were recently used to redraw political maps by projecting their topological partitions into geographical space. The results showed remarkable spatial cohesiveness of the network communities and a significant overlap between the redrawn and the administrative borders. Here we present a similar analysis based on one of the most popular online social networks represented by the ties between more than 5.8 million of its geo-located users. The worldwide coverage of their measured activity allowed us to analyze the large-scale regional subgraphs of entire continents and an extensive set of examples for single countries. We present results for North and South America, Europe and Asia. In our analysis we used the well-established method of modularity clustering after an aggregation of the individual links into a weighted graph connecting equal-area geographical pixels. Our results show fingerprints of both of the opposing forces of dividing local conflicts and of uniting cross-cultural trends of globalization. PMID:25993329
Goel, S; Singh, R J; Tripathy, J P
2015-01-01
National Tobacco Control Programme was launched in India in year 2007-08. It was realized that community health workers can play an important role of agents for positive change to bring down the tobacco morbidity and mortality in the country. Keeping this in view, a health worker guide was developed by the Government of India, Ministry of Health and Family Welfare (GOI) in collaboration with The Union South-East Asia (The Union) in the year 2010. The guide provides the information needed by the most basic level of health workers to effectively address the problem of tobacco use in the community. A modular training was conducted in two jurisdictions in India (namely, Chandigarh and Hamirpur (Himachal Pradesh)) to assess the usefulness of the guide as training material for community health workers in undertaking tobacco control activities at community and village levels. A total of 271 participants were trained, which included 133 from Chandigarh and 138 from Hamirpur. The pre and post-training assessment of knowledge of health worker was done. There was marked increase in post-test scores as compared to the pretest scores. The health workers scoring more than 60% increased from 40% in the pretest to over 80% in the post-test. Only three workers had a post-test score of less than 30% against 54 workers in the pretest. The understanding on tobacco control had increased significantly after the training in each group. It is strongly recommended that such training should be replicated to all community health workers across all the states in India.
Modular evolution of the Cetacean vertebral column.
Buchholtz, Emily A
2007-01-01
Modular theory predicts that hierarchical developmental processes generate hierarchical phenotypic units that are capable of independent modification. The vertebral column is an overtly modular structure, and its rapid phenotypic transformation in cetacean evolution provides a case study for modularity. Terrestrial mammals have five morphologically discrete vertebral series that are now known to be coincident with Hox gene expression patterns. Here, I present the hypothesis that in living Carnivora and Artiodactyla, and by inference in the terrestrial ancestors of whales, the series are themselves components of larger precaudal and caudal modular units. Column morphology in a series of fossil and living whales is used to predict the type and sequence of developmental changes responsible for modification of that ancestral pattern. Developmental innovations inferred include independent meristic additions to the precaudal column in basal archaeocetes and basilosaurids, stepwise homeotic reduction of the sacral series in protocetids, and dissociation of the caudal series into anterior tail and fluke subunits in basilosaurids. The most dramatic change was the novel association of lumbar and anterior caudal vertebrae in a module that crosses the precaudal/caudal boundary. This large unit is defined by shared patterns of vertebral morphology, count, and size in all living whales (Neoceti).
NASA Astrophysics Data System (ADS)
Lan, Tian; Kong, Liang; Wen, Xiao-Gang
2017-04-01
A finite bosonic or fermionic symmetry can be described uniquely by a symmetric fusion category E. In this work, we propose that 2+1D topological/SPT orders with a fixed finite symmetry E are classified, up to {E_8} quantum Hall states, by the unitary modular tensor categories C over E and the modular extensions of each C. In the case C=E, we prove that the set M_{ext}(E) of all modular extensions of E has a natural structure of a finite abelian group. We also prove that the set M_{ext}(C) of all modular extensions of E, if not empty, is equipped with a natural M_{ext}(C)-action that is free and transitive. Namely, the set M_{ext}(C) is an M_{ext}(E)-torsor. As special cases, we explain in detail how the group M_{ext}(E) recovers the well-known group-cohomology classification of the 2+1D bosonic SPT orders and Kitaev's 16 fold ways. We also discuss briefly the behavior of the group M_{ext}(E) under the symmetry-breaking processes and its relation to Witt groups.
Structured FORTRAN Preprocessor
NASA Technical Reports Server (NTRS)
Flynn, J. A.; Lawson, C. L.; Van Snyder, W.; Tsitsivas, H. N.
1985-01-01
SFTRAN3 supports structured programing in FORTRAN environment. Language intended particularly to support two aspects of structured programing -- nestable single-entry control structures and modularization and top-down organization of code. Code designed and written using these SFTRAN3 facilities have fewer initial errors, easier to understand and less expensive to maintain and modify.
24 CFR 3280.7 - Excluded structures.
Code of Federal Regulations, 2010 CFR
2010-04-01
... 24 Housing and Urban Development 5 2010-04-01 2010-04-01 false Excluded structures. 3280.7 Section... DEVELOPMENT MANUFACTURED HOME CONSTRUCTION AND SAFETY STANDARDS General § 3280.7 Excluded structures. Certain structures may be excluded from these Standards as modular homes under 24 CFR 3282.12. [52 FR 4581, Feb. 12...
Hao, Dapeng; Ren, Cong; Li, Chuanxing
2012-05-01
A central idea in biology is the hierarchical organization of cellular processes. A commonly used method to identify the hierarchical modular organization of network relies on detecting a global signature known as variation of clustering coefficient (so-called modularity scaling). Although several studies have suggested other possible origins of this signature, it is still widely used nowadays to identify hierarchical modularity, especially in the analysis of biological networks. Therefore, a further and systematical investigation of this signature for different types of biological networks is necessary. We analyzed a variety of biological networks and found that the commonly used signature of hierarchical modularity is actually the reflection of spoke-like topology, suggesting a different view of network architecture. We proved that the existence of super-hubs is the origin that the clustering coefficient of a node follows a particular scaling law with degree k in metabolic networks. To study the modularity of biological networks, we systematically investigated the relationship between repulsion of hubs and variation of clustering coefficient. We provided direct evidences for repulsion between hubs being the underlying origin of the variation of clustering coefficient, and found that for biological networks having no anti-correlation between hubs, such as gene co-expression network, the clustering coefficient doesn't show dependence of degree. Here we have shown that the variation of clustering coefficient is neither sufficient nor exclusive for a network to be hierarchical. Our results suggest the existence of spoke-like modules as opposed to "deterministic model" of hierarchical modularity, and suggest the need to reconsider the organizational principle of biological hierarchy.
Coming of Age in America. VERCAP: A Guide for High School Students.
ERIC Educational Resources Information Center
Bever, James A.
Guidelines are provided for implementing the modular Voter Education, Registration, Community Action Program (VERCAP) in high schools. VERCAP was developed in 1976 by the National Association of Secondary School Principals. The purposes of VERCAP are to help students become informed, active citizens who can understand the mechanics of registering…
Probability & Statistics: Modular Learning Exercises. Student Edition
ERIC Educational Resources Information Center
Actuarial Foundation, 2012
2012-01-01
The purpose of these modules is to provide an introduction to the world of probability and statistics to accelerated mathematics students at the high school level. The materials are centered on the fictional town of Happy Shores, a coastal community which is at risk for hurricanes. Actuaries at an insurance company figure out the risks and…
Online Collaborative Mentoring for Technology Integration in Pre-Service Teacher Education
ERIC Educational Resources Information Center
Dorner, Helga; Kumar, Swapna
2016-01-01
The Mentored Innovation Model is an online collaborative mentoring model developed in Hungary to help teachers integrate technology in their classrooms in meaningful ways. It combines an online modular approach of formal pedagogical ICT training with an informal online community experience of sharing, developing and critiquing of shared learning…
ERIC Educational Resources Information Center
Wyne, Mudasser F.
2010-01-01
It is hard to define a single set of ethics that will cover an entire computer users community. In this paper, the issue is addressed in reference to code of ethics implemented by various professionals, institutes and organizations. The paper presents a higher level model using hierarchical approach. The code developed using this approach could be…
Modular synchronization in complex networks.
Oh, E; Rho, K; Hong, H; Kahng, B
2005-10-01
We study the synchronization transition (ST) of a modified Kuramoto model on two different types of modular complex networks. It is found that the ST depends on the type of intermodular connections. For the network with decentralized (centralized) intermodular connections, the ST occurs at finite coupling constant (behaves abnormally). Such distinct features are found in the yeast protein interaction network and the Internet, respectively. Moreover, by applying the finite-size scaling analysis to an artificial network with decentralized intermodular connections, we obtain the exponent associated with the order parameter of the ST to be beta approximately 1 different from beta(MF) approximately 1/2 obtained from the scale-free network with the same degree distribution but the absence of modular structure, corresponding to the mean field value.
Modular thrust subsystem approaches to solar electric propulsion module design
NASA Technical Reports Server (NTRS)
Cake, J. E.; Sharp, G. R.; Oglebay, J. C.; Shaker, F. J.; Zavesky, R. J.
1976-01-01
Three approaches are presented for packaging the elements of a 30 cm ion thruster subsystem into a modular thrust subsystem. The individual modules, when integrated into a conceptual solar electric propulsion module are applicable to a multimission set of interplanetary flights with the space shuttle interim upper stage as the launch vehicle. The emphasis is on the structural and thermal integration of the components into the modular thrust subsystems. Thermal control for the power processing units is either by direct radiation through louvers in combination with heat pipes or an all heat pipe system. The propellant storage and feed system and thruster gimbal system concepts are presented. The three approaches are compared on the basis of mass, cost, testing, interfaces, simplicity, reliability, and maintainability.
Modular thrust subsystem approaches to solar electric propulsion module design
NASA Technical Reports Server (NTRS)
Cake, J. E.; Sharp, G. R.; Oglebay, J. C.; Shaker, F. J.; Zevesky, R. J.
1976-01-01
Three approaches are presented for packaging the elements of a 30 cm ion thrustor subsystem into a modular thrust subsystem. The individual modules, when integrated into a conceptual solar electric propulsion module are applicable to a multimission set of interplanetary flights with the Space Shuttle/Interim Upper Stage as the launch vehicle. The emphasis is on the structural and thermal integration of the components into the modular thrust subsystems. Thermal control for the power processing units is either by direct radiation through louvers in combination with heat pipes of an all heat pipe system. The propellant storage and feed system and thrustor gimbal system concepts are presented. The three approaches are compared on the basis of mass, cost, testing, interfaces, simplicity, reliability, and maintainability.
Stochastic fluctuations and the detectability limit of network communities.
Floretta, Lucio; Liechti, Jonas; Flammini, Alessandro; De Los Rios, Paolo
2013-12-01
We have analyzed the detectability limits of network communities in the framework of the popular Girvan and Newman benchmark. By carefully taking into account the inevitable stochastic fluctuations that affect the construction of each and every instance of the benchmark, we come to the conclusion that the native, putative partition of the network is completely lost even before the in-degree/out-degree ratio becomes equal to that of a structureless Erdös-Rényi network. We develop a simple iterative scheme, analytically well described by an infinite branching process, to provide an estimate of the true detectability limit. Using various algorithms based on modularity optimization, we show that all of them behave (semiquantitatively) in the same way, with the same functional form of the detectability threshold as a function of the network parameters. Because the same behavior has also been found by further modularity-optimization methods and for methods based on different heuristics implementations, we conclude that indeed a correct definition of the detectability limit must take into account the stochastic fluctuations of the network construction.
NASA Astrophysics Data System (ADS)
Oztekin, Halit; Temurtas, Feyzullah; Gulbag, Ali
The Arithmetic and Logic Unit (ALU) design is one of the important topics in Computer Architecture and Organization course in Computer and Electrical Engineering departments. There are ALU designs that have non-modular nature to be used as an educational tool. As the programmable logic technology has developed rapidly, it is feasible that ALU design based on Field Programmable Gate Array (FPGA) is implemented in this course. In this paper, we have adopted the modular approach to ALU design based on FPGA. All the modules in the ALU design are realized using schematic structure on Altera's Cyclone II Development board. Under this model, the ALU content is divided into four distinct modules. These are arithmetic unit except for multiplication and division operations, logic unit, multiplication unit and division unit. User can easily design any size of ALU unit since this approach has the modular nature. Then, this approach was applied to microcomputer architecture design named BZK.SAU.FPGA10.0 instead of the current ALU unit.
Modular space station phase B extension preliminary system design. Volume 7: Ancillary studies
NASA Technical Reports Server (NTRS)
Jones, A. L.
1972-01-01
Sortie mission analysis and reduced payloads size impact studies are presented. In the sortie mission analysis, a modular space station oriented experiment program to be flown by the space shuttle during the period prior to space station IOC is discussed. Experiments are grouped into experiment packages. Mission payloads are derived by grouping experiment packages and by adding support subsystems and structure. The operational and subsystems analyses of these payloads are described. Requirements, concepts, and shuttle interfaces are integrated. The sortie module/station module commonality and a sortie laboratory concept are described. In the payloads size analysis, the effect on the modular space station concept of reduced diameter and reduced length of the shuttle cargo bay is discussed. Design concepts are presented for reduced sizes of 12 by 60 ft, 14 by 40 ft, and 12 by 40 ft. Comparisons of these concepts with the modular station (14 by 60 ft) are made to show the impact of payload size changes.
Evolution of a modular software network
Fortuna, Miguel A.; Bonachela, Juan A.; Levin, Simon A.
2011-01-01
“Evolution behaves like a tinkerer” (François Jacob, Science, 1977). Software systems provide a singular opportunity to understand biological processes using concepts from network theory. The Debian GNU/Linux operating system allows us to explore the evolution of a complex network in a unique way. The modular design detected during its growth is based on the reuse of existing code in order to minimize costs during programming. The increase of modularity experienced by the system over time has not counterbalanced the increase in incompatibilities between software packages within modules. This negative effect is far from being a failure of design. A random process of package installation shows that the higher the modularity, the larger the fraction of packages working properly in a local computer. The decrease in the relative number of conflicts between packages from different modules avoids a failure in the functionality of one package spreading throughout the entire system. Some potential analogies with the evolutionary and ecological processes determining the structure of ecological networks of interacting species are discussed. PMID:22106260
NASA Astrophysics Data System (ADS)
Aufdenkampe, A. K.; Damiano, S. G.; Hicks, S.; Horsburgh, J. S.
2017-12-01
EnviroDIY is a community for do-it-yourself environmental science and monitoring (https://envirodiy.org), largely focused on sharing ideas for developing Arduino-compatible open-source sensor stations, similar to the EnviroDIY Mayfly datalogger (http://envirodiy.org/mayfly/). Here we present the ModularSensors Arduino code library (https://github.com/EnviroDIY/ModularSensors), deisigned to give all sensors and variables a common interface of functions and returns and to make it very easy to iterate through and log data from many sensors and variables. This library was written primarily for the EnviroDIY Mayfly, but we have begun to test it on other Arduino based boards. We will show the large number of developed sensor interfaces, and examples of using this library code to stream near real time data to the new EnviroDIY Water Quality Data Portal (http://data.envirodiy.org/), a data and software system based on the Observations Data Model v2 (http://www.odm2.org).
Design and Control of Modular Spine-Like Tensegrity Structures
NASA Technical Reports Server (NTRS)
Mirletz, Brian T.; Park, In-Won; Flemons, Thomas E.; Agogino, Adrian K.; Quinn, Roger D.; SunSpiral, Vytas
2014-01-01
We present a methodology enabled by the NASA Tensegrity Robotics Toolkit (NTRT) for the rapid structural design of tensegrity robots in simulation and an approach for developing control systems using central pattern generators, local impedance controllers, and parameter optimization techniques to determine effective locomotion strategies for the robot. Biomimetic tensegrity structures provide advantageous properties to robotic locomotion and manipulation tasks, such as their adaptability and force distribution properties, flexibility, energy efficiency, and access to extreme terrains. While strides have been made in designing insightful static biotensegrity structures, gaining a clear understanding of how a particular structure can efficiently move has been an open problem. The tools in the NTRT enable the rapid exploration of the dynamics of a given morphology, and the links between structure, controllability, and resulting gait efficiency. To highlight the effectiveness of the NTRT at this exploration of morphology and control, we will provide examples from the designs and locomotion of four different modular spine-like tensegrity robots.
Toward an Online Community of Educators: The Modular Curriculum for Hydrologic Advancement (MOCHA)
NASA Astrophysics Data System (ADS)
Kelleher, C.; Wagener, T.; Gooseff, M. N.; Gregg, S.; McGlynn, B. L.; Sharma, P.; Meixner, T.; Marshall, L. A.; McGuire, K. J.; Weiler, M.
2009-12-01
The field of hydrology encompasses a wide range of departments and disciplines, ranging from civil engineering to geography to geosciences. As a consequence, in-class hydrology education is often strongly biased towards the background of a single instructor, limiting the educational experience of the students and not allowing for a holistic approach to hydrology education. Recently established, the Modular Curriculum for Hydrologic Advancement (MOCHA) creates an online community of hydrologists from a range of backgrounds and disciplines to define the boundaries of an unbiased hydrology education and to jointly develop resources to overcome previous instructional limitations (http://www.mocha.psu.edu/). Our first objective is to create an evolving core curriculum for hydrology education freely available to, developed, evolved and reviewed by the worldwide hydrologic community. On a larger scale, we hope to raise the standard of hydrology education and to foster international collaboration and exchange. Our work began with an initial survey including over 100 hydrology educators to assess the state of current hydrology education. Based on the survey results, the MOCHA project was designed and implemented, and initial teaching material and pedagogical guidelines for good practice in teaching were prepared. This past fall and spring, we piloted the website and teaching material across several universities. The web-based MOCHA project has recently been opened to solicit contributions from the global hydrology community. Our presentation will focus on the overall vision behind MOCHA, lessons learned from our initial piloting, and current steps to achieve our vision.
An introduction to the Astro Edge solar array
NASA Technical Reports Server (NTRS)
Spence, B. R.; Marks, G. W.
1994-01-01
The Astro Edge solar array is a new and innovative low concentrator power generating system which has been developed for applications requiring high specific power, high stiffness, low risk, light modular construction which utilizes conventional materials and technology, and standard photovoltaic solar cells and laydown processes. Mechanisms, restraint/release devices, wiring harnesses, substrates, and support structures are designed to be simple, functional, lightweight, and modular. A brief overview of the Astro Edge solar array is discussed.
Force Structure: Preliminary Observations on Army Plans to Implement and Fund Modular Forces
2005-03-16
affect the size and composition of the modular force as well as its cost. First, the Army’s Campaign Plan calls for a potential decision by fiscal year...upgrading existing active brigades, or other support and command elements; and • accounted for construction of temporary , relocatable facilities...Kevin Handley, Joah Iannotta, Harry Jobes, Joseph Kirschbaum, Eric Theus, Jason Venner , and J. Andrew Walker.Page 11 GAO-05-443T (350683) GAO’s
Status and Plans for the Vienna VLBI and Satellite Software (VieVS 3.0)
NASA Astrophysics Data System (ADS)
Gruber, Jakob; Böhm, Johannes; Böhm, Sigrid; Girdiuk, Anastasiia; Hellerschmied, Andreas; Hofmeister, Armin; Krásná, Hana; Kwak, Younghee; Landskron, Daniel; Madzak, Matthias; Mayer, David; McCallum, Jamie; Plank, Lucia; Schartner, Matthias; Shabala, Stas; Teke, Kamil; Sun, Jing
2017-04-01
The Vienna VLBI and Satellite Software (VieVS) is a geodetic analysis software developed and maintained at Technische Universität Wien (TU Wien) with contributions from groups all over the world. It is used for both academic purposes in university courses as well as for providing Very Long Baseline Interferometry (VLBI) analysis results to the geodetic community. Written in a modular structure in Matlab, VieVS offers easy access to the source code and the possibility to adapt the programs for particular purposes. The new version 3.0, released in early 2017, includes several new features, e.g., improved scheduling capabilities for observing quasars and satellites. This poster gives an overview of all VLBI-related activities in Vienna and provides an outlook to future plans concerning the Vienna VLBI and Satellite Software (VieVS).
Modular electronics packaging system
NASA Technical Reports Server (NTRS)
Hunter, Don J. (Inventor)
2001-01-01
A modular electronics packaging system includes multiple packaging slices that are mounted horizontally to a base structure. The slices interlock to provide added structural support. Each packaging slice includes a rigid and thermally conductive housing having four side walls that together form a cavity to house an electronic circuit. The chamber is enclosed on one end by an end wall, or web, that isolates the electronic circuit from a circuit in an adjacent packaging slice. The web also provides a thermal path between the electronic circuit and the base structure. Each slice also includes a mounting bracket that connects the packaging slice to the base structure. Four guide pins protrude from the slice into four corresponding receptacles in an adjacent slice. A locking element, such as a set screw, protrudes into each receptacle and interlocks with the corresponding guide pin. A conduit is formed in the slice to allow electrical connection to the electronic circuit.
NASA Astrophysics Data System (ADS)
Ma, Fei; Yao, Bing
2017-10-01
It is always an open, demanding and difficult task for generating available model to simulate dynamical functions and reveal inner principles from complex systems and networks. In this article, due to lots of real-life and artificial networks are built from series of simple and small groups (components), we discuss some interesting and helpful network-operation to generate more realistic network models. In view of community structure (modular topology), we present a class of sparse network models N(t , m) . At the moment, we capture the fact the N(t , 4) has not only scale-free feature, which means that the probability that a randomly selected vertex with degree k decays as a power-law, following P(k) ∼k-γ, where γ is the degree exponent, but also small-world property, which indicates that the typical distance between two uniform randomly chosen vertices grows proportionally to logarithm of the order of N(t , 4) , namely, relatively shorter diameter and lower average path length, simultaneously displays higher clustering coefficient. Next, as a new topological parameter correlating to reliability, synchronization capability and diffusion properties of networks, the number of spanning trees over a network is studied in more detail, an exact analytical solution for the number of spanning trees of the N(t , 4) is obtained. Based on the network-operation, part hub-vertex linking with each other will be helpful for structuring various network models and investigating the rules related with real-life networks.
The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.
Diehl, Alexander D; Meehan, Terrence F; Bradford, Yvonne M; Brush, Matthew H; Dahdul, Wasila M; Dougall, David S; He, Yongqun; Osumi-Sutherland, David; Ruttenberg, Alan; Sarntivijai, Sirarat; Van Slyke, Ceri E; Vasilevsky, Nicole A; Haendel, Melissa A; Blake, Judith A; Mungall, Christopher J
2016-07-04
The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies. Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning. The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs. The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community.
Animal social networks as substrate for cultural behavioural diversity.
Whitehead, Hal; Lusseau, David
2012-02-07
We used individual-based stochastic models to examine how social structure influences the diversity of socially learned behaviour within a non-human population. For continuous behavioural variables we modelled three forms of dyadic social learning, averaging the behavioural value of the two individuals, random transfer of information from one individual to the other, and directional transfer from the individual with highest behavioural value to the other. Learning had potential error. We also examined the transfer of categorical behaviour between individuals with random directionality and two forms of error, the adoption of a randomly chosen existing behavioural category or the innovation of a new type of behaviour. In populations without social structuring the diversity of culturally transmitted behaviour increased with learning error and population size. When the populations were structured socially either by making individuals members of permanent social units or by giving them overlapping ranges, behavioural diversity increased with network modularity under all scenarios, although the proportional increase varied considerably between continuous and categorical behaviour, with transmission mechanism, and population size. Although functions of the form e(c)¹(m)⁻(c)² + (c)³(Log(N)) predicted the mean increase in diversity with modularity (m) and population size (N), behavioural diversity could be highly unpredictable both between simulations with the same set of parameters, and within runs. Errors in social learning and social structuring generally promote behavioural diversity. Consequently, social learning may be considered to produce culture in populations whose social structure is sufficiently modular. Copyright © 2011 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dolgopolova, Ekaterina A.; Ejegbavwo, Otega A.; Martin, Corey R.
Growing necessity for efficient nuclear waste management is a driving force for development of alternative architectures towards fundamental understanding of mechanisms involved in actinide integration inside extended structures. In this manuscript, metal-organic frameworks (MOFs) were investigated as a model system for engineering radionuclide containing materials through utilization of unprecedented MOF modularity, which cannot be replicated in any other type of materials. Through the implementation of recent synthetic advances in the MOF field, hierarchical complexity of An-materials were built stepwise, which was only feasible due to preparation of the first examples of actinide-based frameworks with “unsaturated” metal nodes. The first successfulmore » attempts of solid-state metathesis and metal node extension in An-MOFs are reported, and the results of the former approach revealed drastic differences in chemical behavior of extended structures versus molecular species. Successful utilization of MOF modularity also allowed us to structurally characterize the first example of bimetallic An-An nodes. To the best of our knowledge, through combination of solid-state metathesis, guest incorporation, and capping linker installation, we were able to achieve the highest Th wt% in mono- and bi-actinide frameworks with minimal structural density. Overall, combination of a multistep synthetic approach with homogeneous actinide distribution and moderate solvothermal conditions could make MOFs an exceptionally powerful tool to address fundamental questions responsible for chemical behavior of An-based extended structures, and therefore, shed light on possible optimization of nuclear waste administration.« less
Dolgopolova, Ekaterina A; Ejegbavwo, Otega A; Martin, Corey R; Smith, Mark D; Setyawan, Wahyu; Karakalos, Stavros G; Henager, Charles H; Zur Loye, Hans-Conrad; Shustova, Natalia B
2017-11-22
Growing necessity for efficient nuclear waste management is a driving force for development of alternative architectures toward fundamental understanding of mechanisms involved in actinide (An) integration inside extended structures. In this manuscript, metal-organic frameworks (MOFs) were investigated as a model system for engineering radionuclide containing materials through utilization of unprecedented MOF modularity, which cannot be replicated in any other type of materials. Through the implementation of recent synthetic advances in the MOF field, hierarchical complexity of An-materials was built stepwise, which was only feasible due to preparation of the first examples of actinide-based frameworks with "unsaturated" metal nodes. The first successful attempts of solid-state metathesis and metal node extension in An-MOFs are reported, and the results of the former approach revealed drastic differences in chemical behavior of extended structures versus molecular species. Successful utilization of MOF modularity also allowed us to structurally characterize the first example of bimetallic An-An nodes. To the best of our knowledge, through combination of solid-state metathesis, guest incorporation, and capping linker installation, we were able to achieve the highest Th wt % in mono- and biactinide frameworks with minimal structural density. Overall, the combination of a multistep synthetic approach with homogeneous actinide distribution and moderate solvothermal conditions could make MOFs an exceptionally powerful tool to address fundamental questions responsible for chemical behavior of An-based extended structures and, therefore, shed light on possible optimization of nuclear waste administration.
Skinnider, Michael A; Dejong, Chris A; Franczak, Brian C; McNicholas, Paul D; Magarvey, Nathan A
2017-08-16
Natural products represent a prominent source of pharmaceutically and industrially important agents. Calculating the chemical similarity of two molecules is a central task in cheminformatics, with applications at multiple stages of the drug discovery pipeline. Quantifying the similarity of natural products is a particularly important problem, as the biological activities of these molecules have been extensively optimized by natural selection. The large and structurally complex scaffolds of natural products distinguish their physical and chemical properties from those of synthetic compounds. However, no analysis of the performance of existing methods for molecular similarity calculation specific to natural products has been reported to date. Here, we present LEMONS, an algorithm for the enumeration of hypothetical modular natural product structures. We leverage this algorithm to conduct a comparative analysis of molecular similarity methods within the unique chemical space occupied by modular natural products using controlled synthetic data, and comprehensively investigate the impact of diverse biosynthetic parameters on similarity search. We additionally investigate a recently described algorithm for natural product retrobiosynthesis and alignment, and find that when rule-based retrobiosynthesis can be applied, this approach outperforms conventional two-dimensional fingerprints, suggesting it may represent a valuable approach for the targeted exploration of natural product chemical space and microbial genome mining. Our open-source algorithm is an extensible method of enumerating hypothetical natural product structures with diverse potential applications in bioinformatics.
Attitude control of the space construction base: A modular approach
NASA Technical Reports Server (NTRS)
Oconnor, D. A.
1982-01-01
A planar model of a space base and one module is considered. For this simplified system, a feedback controller which is compatible with the modular construction method is described. The systems dynamics are decomposed into two parts corresponding to base and module. The information structure of the problem is non-classical in that not all system information is supplied to each controller. The base controller is designed to accommodate structural changes that occur as the module is added and the module controller is designed to regulate its own states and follow commands from the base. Overall stability of the system is checked by Liapunov analysis and controller effectiveness is verified by computer simulation.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mauro, N.A.; Kelton, K.F.
2011-10-27
High-energy x-ray diffraction studies of metallic liquids provide valuable information about structural evolution on the atomic length scale, leading to insights into the origin of the nucleation barrier and the processes of supercooling and glass formation. The containerless processing of the beamline electrostatic levitation (BESL) facility allows coordinated thermophysical and structural studies of equilibrium and supercooled liquids to be made in a contamination-free, high-vacuum ({approx}10{sup -8} Torr) environment. To date, the incorporation of electrostatic levitation facilities into synchrotron beamlines has been difficult due to the large footprint of the apparatus and the difficulties associated with its transportation and implementation. Here,more » we describe a modular levitation facility that is optimized for diffraction studies of high-temperature liquids at high-energy synchrotron beamlines. The modular approach used in the apparatus design allows it to be easily transported and quickly setup. Unlike most previous electrostatic levitation facilities, BESL can be operated by a single user instead of a user team.« less
Thermal Characterization for a Modular 3-D Multichip Module
NASA Technical Reports Server (NTRS)
Fan, Mark S.; Plante, Jeannette; Shaw, Harry
2000-01-01
NASA Goddard Space Flight Center has designed a high-density modular 3-D multichip module (MCM) for future spaceflight use. This MCM features a complete modular structure, i.e., each stack can be removed from the package without damaging the structure. The interconnection to the PCB is through the Column Grid Array (CGA) technology. Because of its high-density nature, large power dissipation from multiple layers of circuitry is anticipated and CVD diamond films are used in the assembly for heat conduction enhancement. Since each stacked layer dissipates certain amount of heat, designing effective heat conduction paths through each stack and balancing the heat dissipation within each stack for optimal thermal performance become a challenging task. To effectively remove the dissipated heat from the package, extensive thermal analysis has been performed with finite element methods. Through these analyses, we are able to improve the thermal design and increase the total wattage of the package for maximum electrical performance. This paper provides details on the design-oriented thermal analysis and performance enhancement. It also addresses issues relating to contact thermal resistance between the diamond film and the metallic heat conduction paths.
Bowsher, Clive G
2011-02-15
Understanding the encoding and propagation of information by biochemical reaction networks and the relationship of such information processing properties to modular network structure is of fundamental importance in the study of cell signalling and regulation. However, a rigorous, automated approach for general biochemical networks has not been available, and high-throughput analysis has therefore been out of reach. Modularization Identification by Dynamic Independence Algorithms (MIDIA) is a user-friendly, extensible R package that performs automated analysis of how information is processed by biochemical networks. An important component is the algorithm's ability to identify exact network decompositions based on both the mass action kinetics and informational properties of the network. These modularizations are visualized using a tree structure from which important dynamic conditional independence properties can be directly read. Only partial stoichiometric information needs to be used as input to MIDIA, and neither simulations nor knowledge of rate parameters are required. When applied to a signalling network, for example, the method identifies the routes and species involved in the sequential propagation of information between its multiple inputs and outputs. These routes correspond to the relevant paths in the tree structure and may be further visualized using the Input-Output Path Matrix tool. MIDIA remains computationally feasible for the largest network reconstructions currently available and is straightforward to use with models written in Systems Biology Markup Language (SBML). The package is distributed under the GNU General Public License and is available, together with a link to browsable Supplementary Material, at http://code.google.com/p/midia. Further information is at www.maths.bris.ac.uk/~macgb/Software.html.
NASA Astrophysics Data System (ADS)
Jeon, Gyuhyeon; Park, Juyong
2017-02-01
In the common jury-contestant competition format, a jury consisting of multiple judges grade contestants on their performances to determine their ranking. Unlike in another common competition format where two contestants play a head-to-head match to produce the winner such as in football or basketball, the objectivity of judges are often called into question, potentially undermining the public's trust in the fairness of the competition. In this work we show, by modeling the jury-contestant competition format as a weighted bipartite network, how one can identify biased scores and how they impact the competition and its structure. Analyzing the prestigious International Chopin Piano Competition of 2015 as an example with a well-publicized scoring controversy, we show that the presence of even a very small fraction of biased edges can gravely distort our inference of the network structure —in the example a single biased edge is shown to lead to an incorrect “solution” that also wrongly appears to be robust exclusively, dominating other reasonable solutions— highlighting the importance of bias detection and elimination in network inference. In the process our work also presents a modified modularity measure for the one-mode projection of weighted complete bipartite networks.
3D printed Lego®-like modular microfluidic devices based on capillary driving.
Nie, Jing; Gao, Qing; Qiu, Jing-Jiang; Sun, Miao; Liu, An; Shao, Lei; Fu, Jian-Zhong; Zhao, Peng; He, Yong
2018-03-12
The field of how to rapidly assemble microfluidics with modular components continuously attracts researchers' attention, however, extra efforts must be devoted to solving the problems of leaking and aligning between individual modules. This paper presents a novel type of modular microfluidic device, driven by capillary force. There is no necessity for a strict seal or special alignment, and its open structures make it easy to integrate various stents and reactants. The key rationale for this method is to print different functional modules with a low-cost three-dimensional (3D) printer, then fill the channels with capillary materials and assemble them with plugs like Lego ® bricks. This rapidly reconstructed modular microfluidic device consists of a variety of common functional modules and other personalized modules, each module having a unified standard interface for easy assembly. As it can be printed by a desktop 3D printer, the manufacturing process is simple and efficient, with controllable regulation of the flow channel scale. Through diverse combinations of different modules, a variety of different functions can be achieved, without duplicating the manufacturing process. A single module can also be taken out for testing and analysis. What's more, combined with basic circuit components, it can serve as a low-cost Lego ® -like modular microfluidic circuits. As a proof of concept, the modular microfluidic device has been successfully demonstrated and used for stent degradation and cell cultures, revealing the potential use of this method in both chemical and biological research.
Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Kwak, Dochan (Technical Monitor)
2002-01-01
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel supercomputers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
Development and Applications of a Modular Parallel Process for Large Scale Fluid/Structures Problems
NASA Technical Reports Server (NTRS)
Guruswamy, Guru P.; Byun, Chansup; Kwak, Dochan (Technical Monitor)
2001-01-01
A modular process that can efficiently solve large scale multidisciplinary problems using massively parallel super computers is presented. The process integrates disciplines with diverse physical characteristics by retaining the efficiency of individual disciplines. Computational domain independence of individual disciplines is maintained using a meta programming approach. The process integrates disciplines without affecting the combined performance. Results are demonstrated for large scale aerospace problems on several supercomputers. The super scalability and portability of the approach is demonstrated on several parallel computers.
New Approach to Road Construction in Oil-Producing Regions of Western Siberia
NASA Astrophysics Data System (ADS)
Piirainen, V. Y.; Estrin, Y.
2017-10-01
This article presents, as a polemic exercise, a new approach to road construction in marshland areas of oil and gas producing regions of Western Siberia. The approach is based on the use of novel modular elements that can be assembled into an integral structure by means of topological interlocking. The use of modern superlight concrete in conjunction with the new design systems based on the modular principle opens up new avenues to solving problems of road construction in regions with unstable, boggy soils.
A multilevel control approach for a modular structured space platform
NASA Technical Reports Server (NTRS)
Chichester, F. D.; Borelli, M. T.
1981-01-01
A three axis mathematical representation of a modular assembled space platform consisting of interconnected discrete masses, including a deployable truss module, was derived for digital computer simulation. The platform attitude control system as developed to provide multilevel control utilizing the Gauss-Seidel second level formulation along with an extended form of linear quadratic regulator techniques. The objectives of the multilevel control are to decouple the space platform's spatial axes and to accommodate the modification of the platform's configuration for each of the decoupled axes.
Ong, Luvena L; Ke, Yonggang
2017-01-01
DNA nanostructures are a useful technology for precisely organizing and manipulating nanomaterials. The DNA bricks method is a modular and versatile platform for applications requiring discrete or periodic structures with complex three-dimensional features. Here, we describe how structures are designed from the fundamental strand architecture through assembly and characterization of the formed structures.
Nickel-hydrogen battery integration study for the Multimission Modular Spacecraft
NASA Technical Reports Server (NTRS)
Mueller, V. C.
1980-01-01
A study has been performed to determine the feasibility of using nickel-hydrogen batteries as replacements for the nickel-cadmium batteries currently used for energy storage in the Multimission Modular Spacecraft under a contract with NASA Goddard Space Flight Center. The battery configuration was selected such that it meets volumetric and mounting constraints of the existing battery location, interfaces electrically with existing power conditioning and distribution equipment, and maintains acceptable cell operating temperatures. The battery contains 21, 50 ampere-hour cells in a cast aluminum structural frame. Cells used in the battery design are those developed under the Air Force's Aero Propulsion Laboratory funding and direction. Modifications of the thermal control system were necessary to increase the average output power capability of the Modular Power Subsystem.
2010-05-17
System), or American company with factory in Malaysia (Smart Modular) Technology Is A Focal Point Of Attacks Who is behind data breaches ? 74% resulted...military style community of hackers learning from each other. 8 8 * Source – 2009 Verizon Data Breach Investigations Report 38% 32% There are also 100,000
Improving long-term care provision: towards demand-based care by means of modularity
2010-01-01
Background As in most fields of health care, societal and political changes encourage suppliers of long-term care to put their clients at the center of care and service provision and become more responsive towards client needs and requirements. However, the diverse, multiple and dynamic nature of demand for long-term care complicates the movement towards demand-based care provision. This paper aims to advance long-term care practice and, to that end, examines the application of modularity. This concept is recognized in a wide range of product and service settings for its ability to design demand-based products and processes. Methods Starting from the basic dimensions of modularity, we use qualitative research to explore the use and application of modularity principles in the current working practices and processes of four organizations in the field of long-term care for the elderly. In-depth semi-structured interviews were conducted with 38 key informants and triangulated with document research and observation. Data was analyzed thematically by means of coding and subsequent exploration of patterns. Data analysis was facilitated by qualitative analysis software. Results Our data suggest that a modular setup of supply is employed in the arrangement of care and service supply and assists providers of long-term care in providing their clients with choice options and variation. In addition, modularization of the needs assessment and package specification process allows the case organizations to manage client involvement but still provide customized packages of care and services. Conclusion The adequate setup of an organization's supply and its specification phase activities are indispensible for long-term care providers who aim to do better in terms of quality and efficiency. Moreover, long-term care providers could benefit from joint provision of care and services by means of modular working teams. Based upon our findings, we are able to elaborate on how to further enable demand-based provision of long-term care by means of modularity. PMID:20858256
Improving long-term care provision: towards demand-based care by means of modularity.
de Blok, Carolien; Luijkx, Katrien; Meijboom, Bert; Schols, Jos
2010-09-21
As in most fields of health care, societal and political changes encourage suppliers of long-term care to put their clients at the center of care and service provision and become more responsive towards client needs and requirements. However, the diverse, multiple and dynamic nature of demand for long-term care complicates the movement towards demand-based care provision. This paper aims to advance long-term care practice and, to that end, examines the application of modularity. This concept is recognized in a wide range of product and service settings for its ability to design demand-based products and processes. Starting from the basic dimensions of modularity, we use qualitative research to explore the use and application of modularity principles in the current working practices and processes of four organizations in the field of long-term care for the elderly. In-depth semi-structured interviews were conducted with 38 key informants and triangulated with document research and observation. Data was analyzed thematically by means of coding and subsequent exploration of patterns. Data analysis was facilitated by qualitative analysis software. Our data suggest that a modular setup of supply is employed in the arrangement of care and service supply and assists providers of long-term care in providing their clients with choice options and variation. In addition, modularization of the needs assessment and package specification process allows the case organizations to manage client involvement but still provide customized packages of care and services. The adequate setup of an organization's supply and its specification phase activities are indispensible for long-term care providers who aim to do better in terms of quality and efficiency. Moreover, long-term care providers could benefit from joint provision of care and services by means of modular working teams. Based upon our findings, we are able to elaborate on how to further enable demand-based provision of long-term care by means of modularity.
The dawn of the RNA World: Toward functional complexity through ligation of random RNA oligomers
Briones, Carlos; Stich, Michael; Manrubia, Susanna C.
2009-01-01
A main unsolved problem in the RNA World scenario for the origin of life is how a template-dependent RNA polymerase ribozyme emerged from short RNA oligomers obtained by random polymerization on mineral surfaces. A number of computational studies have shown that the structural repertoire yielded by that process is dominated by topologically simple structures, notably hairpin-like ones. A fraction of these could display RNA ligase activity and catalyze the assembly of larger, eventually functional RNA molecules retaining their previous modular structure: molecular complexity increases but template replication is absent. This allows us to build up a stepwise model of ligation-based, modular evolution that could pave the way to the emergence of a ribozyme with RNA replicase activity, step at which information-driven Darwinian evolution would be triggered. PMID:19318464
Jenett, Benjamin; Calisch, Sam; Cellucci, Daniel; Cramer, Nick; Gershenfeld, Neil; Swei, Sean; Cheung, Kenneth C
2017-03-01
We describe an approach for the discrete and reversible assembly of tunable and actively deformable structures using modular building block parts for robotic applications. The primary technical challenge addressed by this work is the use of this method to design and fabricate low density, highly compliant robotic structures with spatially tuned stiffness. This approach offers a number of potential advantages over more conventional methods for constructing compliant robots. The discrete assembly reduces manufacturing complexity, as relatively simple parts can be batch-produced and joined to make complex structures. Global mechanical properties can be tuned based on sub-part ordering and geometry, because local stiffness and density can be independently set to a wide range of values and varied spatially. The structure's intrinsic modularity can significantly simplify analysis and simulation. Simple analytical models for the behavior of each building block type can be calibrated with empirical testing and synthesized into a highly accurate and computationally efficient model of the full compliant system. As a case study, we describe a modular and reversibly assembled wing that performs continuous span-wise twist deformation. It exhibits high performance aerodynamic characteristics, is lightweight and simple to fabricate and repair. The wing is constructed from discrete lattice elements, wherein the geometric and mechanical attributes of the building blocks determine the global mechanical properties of the wing. We describe the mechanical design and structural performance of the digital morphing wing, including their relationship to wind tunnel tests that suggest the ability to increase roll efficiency compared to a conventional rigid aileron system. We focus here on describing the approach to design, modeling, and construction as a generalizable approach for robotics that require very lightweight, tunable, and actively deformable structures.
Digital Morphing Wing: Active Wing Shaping Concept Using Composite Lattice-Based Cellular Structures
Jenett, Benjamin; Calisch, Sam; Cellucci, Daniel; Cramer, Nick; Gershenfeld, Neil; Swei, Sean
2017-01-01
Abstract We describe an approach for the discrete and reversible assembly of tunable and actively deformable structures using modular building block parts for robotic applications. The primary technical challenge addressed by this work is the use of this method to design and fabricate low density, highly compliant robotic structures with spatially tuned stiffness. This approach offers a number of potential advantages over more conventional methods for constructing compliant robots. The discrete assembly reduces manufacturing complexity, as relatively simple parts can be batch-produced and joined to make complex structures. Global mechanical properties can be tuned based on sub-part ordering and geometry, because local stiffness and density can be independently set to a wide range of values and varied spatially. The structure's intrinsic modularity can significantly simplify analysis and simulation. Simple analytical models for the behavior of each building block type can be calibrated with empirical testing and synthesized into a highly accurate and computationally efficient model of the full compliant system. As a case study, we describe a modular and reversibly assembled wing that performs continuous span-wise twist deformation. It exhibits high performance aerodynamic characteristics, is lightweight and simple to fabricate and repair. The wing is constructed from discrete lattice elements, wherein the geometric and mechanical attributes of the building blocks determine the global mechanical properties of the wing. We describe the mechanical design and structural performance of the digital morphing wing, including their relationship to wind tunnel tests that suggest the ability to increase roll efficiency compared to a conventional rigid aileron system. We focus here on describing the approach to design, modeling, and construction as a generalizable approach for robotics that require very lightweight, tunable, and actively deformable structures. PMID:28289574
Lebon, Eric; Pellegrino, Anne; Tardieu, Francois; Lecoeur, Jeremie
2004-03-01
Shoot architecture variability in grapevine (Vitis vinifera) was analysed using a generic modelling approach based on thermal time developed for annual herbaceous species. The analysis of shoot architecture was based on various levels of shoot organization, including pre-existing and newly formed parts of the stem, and on the modular structure of the stem, which consists of a repeated succession of three phytomers (P0-P1-P2). Four experiments were carried out using the cultivar 'Grenache N': two on potted vines (one of which was carried out in a glasshouse) and two on mature vines in a vineyard. These experiments resulted in a broad diversity of environmental conditions, but none of the plants experienced soil water deficit. Development of the main axis was highly dependent on air temperature, being linearly related to thermal time for all stages of leaf development from budbreak to veraison. The stable progression of developmental stages along the main stem resulted in a thermal-time based programme of leaf development. Leaf expansion rate varied with trophic competition (shoot and cluster loads) and environmental conditions (solar radiation, VPD), accounting for differences in final leaf area. Branching pattern was highly variable. Classification of the branches according to ternary modular structure increased the accuracy of the quantitative analysis of branch development. The rate and duration of leaf production were higher for branches derived from P0 phytomers than for branches derived from P1 or P2 phytomers. Rates of leaf production, expressed as a -function of thermal time, were not stable and depended on trophic competition and environmental conditions such as solar radiation or VPD. The application to grapevine of a generic model developed in annual plants made it possible to identify constants in main stem development and to determine the hierarchical structure of branches with respect to the modular structure of the stem in response to intra- and inter-shoot trophic competition.
Plug-and-play design approach to smart harness for modular small satellites
NASA Astrophysics Data System (ADS)
Mughal, M. Rizwan; Ali, Anwar; Reyneri, Leonardo M.
2014-02-01
A typical satellite involves many different components that vary in bandwidth demand. Sensors that require a very low data rate may reside on a simple two- or three-wire interface such as I2C, SPI, etc. Complex sensors that require high data rate and bandwidth may reside on an optical interface. The AraMiS architecture is an enhanced capability architecture with different satellite configurations. Although keeping the low-cost and COTS approach of CubeSats, it extends the modularity concept as it also targets different satellite shapes and sizes. But modularity moves beyond the mechanical structure: the tiles also have thermo-mechanical, harness and signal-processing functionalities. Further modularizing the system, every tile can also host a variable number of small sensors, actuators or payloads, connected using a plug-and-play approach. Every subsystem is housed in a small daughter board and is supplied, by the main tile, with power and data distribution functions, power and data harness, mechanical support and is attached and interconnected with space-grade spring-loaded connectors. The tile software is also modular and allows a quick adaptation to specific subsystems. The basic software for the CPU is properly hardened to guarantee high level of radiation tolerance at very low cost.
Static Aeroelastic Analysis with an Inviscid Cartesian Method
NASA Technical Reports Server (NTRS)
Rodriguez, David L.; Aftosmis, Michael J.; Nemec, Marian; Smith, Stephen C.
2014-01-01
An embedded-boundary Cartesian-mesh flow solver is coupled with a three degree-offreedom structural model to perform static, aeroelastic analysis of complex aircraft geometries. The approach solves the complete system of aero-structural equations using a modular, loosely-coupled strategy which allows the lower-fidelity structural model to deform the highfidelity CFD model. The approach uses an open-source, 3-D discrete-geometry engine to deform a triangulated surface geometry according to the shape predicted by the structural model under the computed aerodynamic loads. The deformation scheme is capable of modeling large deflections and is applicable to the design of modern, very-flexible transport wings. The interface is modular so that aerodynamic or structural analysis methods can be easily swapped or enhanced. This extended abstract includes a brief description of the architecture, along with some preliminary validation of underlying assumptions and early results on a generic 3D transport model. The final paper will present more concrete cases and validation of the approach. Preliminary results demonstrate convergence of the complete aero-structural system and investigate the accuracy of the approximations used in the formulation of the structural model.
A modular case-mix classification system for medical rehabilitation illustrated.
Stineman, M G; Granger, C V
1997-01-01
The authors present a modular set of patient classification systems designed for medical rehabilitation that predict resource use and outcomes for clinically similar groups of individuals. The systems, based on the Functional Independence Measure, are referred to as Function-Related Groups (FIM-FRGs). Using data from 23,637 lower extremity fracture patients from 458 inpatient medical rehabilitation facilities, 1995 benchmarks are provided and illustrated for length of stay, functional outcome, and discharge to home and skilled nursing facilities (SNFs). The FIM-FRG modules may be used in parallel to study interactions between resource use and quality and could ultimately yield an integrated strategy for payment and outcomes measurement. This could position the rehabilitation community to take a pioneering role in the application of outcomes-based clinical indicators.
NASA Astrophysics Data System (ADS)
Marzeion, B.; Maussion, F.
2017-12-01
Mountain glaciers are one of the few remaining sub-systems of the global climate system for which no globally applicable, open source, community-driven model exists. Notable examples from the ice sheet community include the Parallel Ice Sheet Model or Elmer/Ice. While the atmospheric modeling community has a long tradition of sharing models (e.g. the Weather Research and Forecasting model) or comparing them (e.g. the Coupled Model Intercomparison Project or CMIP), recent initiatives originating from the glaciological community show a new willingness to better coordinate global research efforts following the CMIP example (e.g. the Glacier Model Intercomparison Project or the Glacier Ice Thickness Estimation Working Group). In the recent past, great advances have been made in the global availability of data and methods relevant for glacier modeling, spanning glacier outlines, automatized glacier centerline identification, bed rock inversion methods, and global topographic data sets. Taken together, these advances now allow the ice dynamics of glaciers to be modeled on a global scale, provided that adequate modeling platforms are available. Here, we present the Open Global Glacier Model (OGGM), developed to provide a global scale, modular, and open source numerical model framework for consistently simulating past and future global scale glacier change. Global not only in the sense of leading to meaningful results for all glaciers combined, but also for any small ensemble of glaciers, e.g. at the headwater catchment scale. Modular to allow combinations of different approaches to the representation of ice flow and surface mass balance, enabling a new kind of model intercomparison. Open source so that the code can be read and used by anyone and so that new modules can be added and discussed by the community, following the principles of open governance. Consistent in order to provide uncertainty measures at all realizable scales.
Moussa, Malaak Nasser; Wesley, Michael J; Porrino, Linda J; Hayasaka, Satoru; Bechara, Antoine; Burdette, Jonathan H; Laurienti, Paul J
2014-04-01
Human decision making is dependent on not only the function of several brain regions but also their synergistic interaction. The specific function of brain areas within the ventromedial prefrontal cortex has long been studied in an effort to understand choice evaluation and decision making. These data specifically focus on whole-brain functional interconnectivity using the principles of network science. The Iowa Gambling Task (IGT) was the first neuropsychological task used to model real-life decisions in a way that factors reward, punishment, and uncertainty. Clinically, it has been used to detect decision-making impairments characteristic of patients with prefrontal cortex lesions. Here, we used performance on repeated blocks of the IGT as a behavioral measure of advantageous and disadvantageous decision making in young and mature adults. Both adult groups performed poorly by predominately making disadvantageous selections in the beginning stages of the task. In later phases of the task, young adults shifted to more advantageous selections and outperformed mature adults. Modularity analysis revealed stark underlying differences in visual, sensorimotor and medial prefrontal cortex community structure. In addition, changes in orbitofrontal cortex connectivity predicted behavioral deficits in IGT performance. Contrasts were driven by a difference in age but may also prove relevant to neuropsychiatric disorders associated with poor decision making, including the vulnerability to alcohol and/or drug addiction.
NASA Astrophysics Data System (ADS)
Hsu, Charles; Viazanko, Michael; O'Looney, Jimmy; Szu, Harold
2009-04-01
Modularity Biometric System (MBS) is an approach to support AiTR of the cooperated and/or non-cooperated standoff biometric in an area persistent surveillance. Advanced active and passive EOIR and RF sensor suite is not considered here. Neither will we consider the ROC, PD vs. FAR, versus the standoff POT in this paper. Our goal is to catch the "most wanted (MW)" two dozens, separately furthermore ad hoc woman MW class from man MW class, given their archrivals sparse front face data basis, by means of various new instantaneous input called probing faces. We present an advanced algorithm: mini-Max classifier, a sparse sample realization of Cramer-Rao Fisher bound of the Maximum Likelihood classifier that minimize the dispersions among the same woman classes and maximize the separation among different man-woman classes, based on the simple feature space of MIT Petland eigen-faces. The original aspect consists of a modular structured design approach at the system-level with multi-level architectures, multiple computing paradigms, and adaptable/evolvable techniques to allow for achieving a scalable structure in terms of biometric algorithms, identification quality, sensors, database complexity, database integration, and component heterogenity. MBS consist of a number of biometric technologies including fingerprints, vein maps, voice and face recognitions with innovative DSP algorithm, and their hardware implementations such as using Field Programmable Gate arrays (FPGAs). Biometric technologies and the composed modularity biometric system are significant for governmental agencies, enterprises, banks and all other organizations to protect people or control access to critical resources.
[Anterograde declarative memory and its models].
Barbeau, E-J; Puel, M; Pariente, J
2010-01-01
Patient H.M.'s recent death provides the opportunity to highlight the importance of his contribution to a better understanding of the anterograde amnesic syndrome. The thorough study of this patient over five decades largely contributed to shape the unitary model of declarative memory. This model holds that declarative memory is a single system that cannot be fractionated into subcomponents. As a system, it depends mainly on medial temporal lobes structures. The objective of this review is to present the main characteristics of different modular models that have been proposed as alternatives to the unitary model. It is also an opportunity to present different patients, who, although less famous than H.M., helped make signification contribution to the field of memory. The characteristics of the five main modular models are presented, including the most recent one (the perceptual-mnemonic model). The differences as well as how these models converge are highlighted. Different possibilities that could help reconcile unitary and modular approaches are considered. Although modular models differ significantly in many aspects, all converge to the notion that memory for single items and semantic memory could be dissociated from memory for complex material and context-rich episodes. In addition, these models converge concerning the involvement of critical brain structures for these stages: Item and semantic memory, as well as familiarity, are thought to largely depend on anterior subhippocampal areas, while relational, context-rich memory and recollective experiences are thought to largely depend on the hippocampal formation. Copyright © 2010 Elsevier Masson SAS. All rights reserved.
Gyurko, David M; Soti, Csaba; Stetak, Attila; Csermely, Peter
2014-05-01
During the last decade, network approaches became a powerful tool to describe protein structure and dynamics. Here, we describe first the protein structure networks of molecular chaperones, then characterize chaperone containing sub-networks of interactomes called as chaperone-networks or chaperomes. We review the role of molecular chaperones in short-term adaptation of cellular networks in response to stress, and in long-term adaptation discussing their putative functions in the regulation of evolvability. We provide a general overview of possible network mechanisms of adaptation, learning and memory formation. We propose that changes of network rigidity play a key role in learning and memory formation processes. Flexible network topology provides ' learning-competent' state. Here, networks may have much less modular boundaries than locally rigid, highly modular networks, where the learnt information has already been consolidated in a memory formation process. Since modular boundaries are efficient filters of information, in the 'learning-competent' state information filtering may be much smaller, than after memory formation. This mechanism restricts high information transfer to the 'learning competent' state. After memory formation, modular boundary-induced segregation and information filtering protect the stored information. The flexible networks of young organisms are generally in a 'learning competent' state. On the contrary, locally rigid networks of old organisms have lost their 'learning competent' state, but store and protect their learnt information efficiently. We anticipate that the above mechanism may operate at the level of both protein-protein interaction and neuronal networks.
Trapping in scale-free networks with hierarchical organization of modularity.
Zhang, Zhongzhi; Lin, Yuan; Gao, Shuyang; Zhou, Shuigeng; Guan, Jihong; Li, Mo
2009-11-01
A wide variety of real-life networks share two remarkable generic topological properties: scale-free behavior and modular organization, and it is natural and important to study how these two features affect the dynamical processes taking place on such networks. In this paper, we investigate a simple stochastic process--trapping problem, a random walk with a perfect trap fixed at a given location, performed on a family of hierarchical networks that exhibit simultaneously striking scale-free and modular structure. We focus on a particular case with the immobile trap positioned at the hub node having the largest degree. Using a method based on generating functions, we determine explicitly the mean first-passage time (MFPT) for the trapping problem, which is the mean of the node-to-trap first-passage time over the entire network. The exact expression for the MFPT is calculated through the recurrence relations derived from the special construction of the hierarchical networks. The obtained rigorous formula corroborated by extensive direct numerical calculations exhibits that the MFPT grows algebraically with the network order. Concretely, the MFPT increases as a power-law function of the number of nodes with the exponent much less than 1. We demonstrate that the hierarchical networks under consideration have more efficient structure for transport by diffusion in contrast with other analytically soluble media including some previously studied scale-free networks. We argue that the scale-free and modular topologies are responsible for the high efficiency of the trapping process on the hierarchical networks.
Intelligent Reconfigurable System with Self-Dammage Assessmentand Control Stress Capabilities
NASA Astrophysics Data System (ADS)
Trivailo, P.; Plotnikova, L.; Kao, T. W.
2002-01-01
Modern space structures are constructed using a modular approach that facilitates their transportation and assembly in space. Modular architecture of space structures also enables reconfiguration of large structures such that they can adapt to possible changes in environment, and also allows use of the limited structural resources available in space for completion of a much larger variety of tasks. An increase in size and complexity demands development of materials with a "smart" or active structural modulus and also of effective control algorithms to control the motion of large flexible structures. This challenging task has generated a lot of interest amongst scientists and engineers during the last two decades, however, research into the development of control schemes which can adapt to structural configuration changes has received less attention. This is possibly due to the increased complexity caused by alterations in geometry, which inevitably lead to changes in the dynamic properties of the system. This paper presents results of the application of a decentralized control approach for active control of large flexible structures undergoing significant reconfigurations. The Control Component Synthesis methodology was used to build controlled components and to assemble them into a controlled flexible structure that meets required performance specifications. To illustrate the efficiency of the method, numerical simulations were conducted for 2D and 3D modular truss structures and a multi-link beam system. In each case the performance of the decentralized control system has been evaluated using pole location maps, step and impulse response simulations and frequency response analysis. The performance of the decentralized control system has been measured against the optimal centralised control system for various excitation scenarios. A special case where one of the local component controllers fails was also examined. For better interpretation of the efficiency of the designed controllers, results of the simulations are illustrated using a Virtual Reality computer environment, offering advanced visual effects. Plotnikova@rmit.edu.au # Tsunwah@hotmail.com
Retroactivity in the Context of Modularly Structured Biomolecular Systems
Pantoja-Hernández, Libertad; Martínez-García, Juan Carlos
2015-01-01
Synthetic biology has intensively promoted the technical implementation of modular strategies in the fabrication of biological devices. Modules are considered as networks of reactions. The behavior displayed by biomolecular systems results from the information processes carried out by the interconnection of the involved modules. However, in natural systems, module wiring is not a free-of-charge process; as a consequence of interconnection, a reactive phenomenon called retroactivity emerges. This phenomenon is characterized by signals that propagate from downstream modules (the modules that receive the incoming signals upon interconnection) to upstream ones (the modules that send the signals upon interconnection). Such retroactivity signals, depending of their strength, may change and sometimes even disrupt the behavior of modular biomolecular systems. Thus, analysis of retroactivity effects in natural biological and biosynthetic systems is crucial to achieve a deeper understanding of how this interconnection between functionally characterized modules takes place and how it impacts the overall behavior of the involved cell. By discussing the modules interconnection in natural and synthetic biomolecular systems, we propose that such systems should be considered as quasi-modular. PMID:26137457
NASA Astrophysics Data System (ADS)
Sun, Jiuce; Sanz, Santiago; Neumann, Holger
2015-12-01
Superconducting generators show the potential to reduce the head mass of large offshore wind turbines. A 10 MW offshore superconducting wind turbine has been investigated in the SUPRAPOWER project. The superconducting coils based on MgB2 tapes are supposed to work at cryogenic temperature of 20 K. In this paper, a novel modular rotating cryostat was presented for one single coil of the superconducting wind turbine. The modular concept and cryogen-free cooling method were proposed to fulfil the requirements of handling, maintenance, reliability of long term and offshore operations. Two stage Gifford-McMahon cryocoolers were used to provide cooling source. Supporting rods made of titanium alloy were selected as support structures of the cryostat in aim of reducing the heat load. The thermal performance in the modular cryostat was carefully investigated. The heat load applied to the cryocooler second stage was 2.17 W@20 K per coil. The corresponding temperature difference along the superconducting coil was only around 1 K.
NASA Astrophysics Data System (ADS)
Liu, Chen; Wang, Jiang; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok
2013-09-01
The combined effects of the information transmission delay and the ratio of the electrical and chemical synapses on the synchronization transitions in the hybrid modular neuronal network are investigated in this paper. Numerical results show that the synchronization of neuron activities can be either promoted or destroyed as the information transmission delay increases, irrespective of the probability of electrical synapses in the hybrid-synaptic network. Interestingly, when the number of the electrical synapses exceeds a certain level, further increasing its proportion can obviously enhance the spatiotemporal synchronization transitions. Moreover, the coupling strength has a significant effect on the synchronization transition. The dominated type of the synapse always has a more profound effect on the emergency of the synchronous behaviors. Furthermore, the results of the modular neuronal network structures demonstrate that excessive partitioning of the modular network may result in the dramatic detriment of neuronal synchronization. Considering that information transmission delays are inevitable in intra- and inter-neuronal networks communication, the obtained results may have important implications for the exploration of the synchronization mechanism underlying several neural system diseases such as Parkinson's Disease.
Dynamic burstiness of word-occurrence and network modularity in textbook systems
NASA Astrophysics Data System (ADS)
Cui, Xue-Mei; Yoon, Chang No; Youn, Hyejin; Lee, Sang Hoon; Jung, Jean S.; Han, Seung Kee
2017-12-01
We show that the dynamic burstiness of word occurrence in textbook systems is attributed to the modularity of the word association networks. At first, a measure of dynamic burstiness is introduced to quantify burstiness of word occurrence in a textbook. The advantage of this measure is that the dynamic burstiness is decomposable into two contributions: one coming from the inter-event variance and the other from the memory effects. Comparing network structures of physics textbook systems with those of surrogate random textbooks without the memory or variance effects are absent, we show that the network modularity increases systematically with the dynamic burstiness. The intra-connectivity of individual word representing the strength of a tie with which a node is bound to a module accordingly increases with the dynamic burstiness, suggesting individual words with high burstiness are strongly bound to one module. Based on the frequency and dynamic burstiness, physics terminology is classified into four categories: fundamental words, topical words, special words, and common words. In addition, we test the correlation between the dynamic burstiness of word occurrence and network modularity using a two-state model of burst generation.
Construction concepts and validation of the 3D printed UST_2 modular stellarator
NASA Astrophysics Data System (ADS)
Queral, V.
2015-03-01
High accuracy, geometric complexity and thus high cost of stellarators tend to hinder the advance of stellarator research. Nowadays, new manufacturing methods might be developed for the production of small and middle-size stellarators. The methods should demonstrate advantages with respect common fabrication methods, like casting, cutting, forging and welding, for the construction of advanced highly convoluted modular stellarators. UST2 is a small modular three period quasi-isodynamic stellarator of major radius 0.26 m and plasma volume 10 litres being currently built to validate additive manufacturing (3D printing) for stellarator construction. The modular coils are wound in grooves defined on six 3D printed half period frames designed as light truss structures filled by a strong filler. A geometrically simple assembling configuration has been concocted for UST2 so as to try to lower the cost of the device while keeping the positioning accuracy of the different elements. The paper summarizes the construction and assembling concepts developed, the devised positioning methodology, the design of the coil frames and positioning elements and, an initial validation of the assembling of the components.
NASA Technical Reports Server (NTRS)
Nein, M. E.; Davis, B. G.
1982-01-01
The Coherent Optical System of Modular Imaging Collectors (COSMIC) is the design concept for a phase-coherent optical telescope array that may be placed in earth orbit by the Space Shuttle in the 1990s. The initial system module is a minimum redundancy array whose photon collecting area is three times larger than that of the Space Telescope, and possesses a one-dimensional resoution of better than 0.01 arcsec in the visible range. Thermal structural requirements are assessed. Although the coherent beam combination requirements will be met by an active control system, the COSMIC structural/thermal design must meet more stringent performance criteria than even those of the Space Telescope.
Modularity and design principles in the sea urchin embryo gene regulatory network
Peter, Isabelle S.; Davidson, Eric H.
2010-01-01
The gene regulatory network (GRN) established experimentally for the pre-gastrular sea urchin embryo provides causal explanations of the biological functions required for spatial specification of embryonic regulatory states. Here we focus on the structure of the GRN which controls the progressive increase in complexity of territorial regulatory states during embryogenesis; and on the types of modular subcircuits of which the GRN is composed. Each of these subcircuit topologies executes a particular operation of spatial information processing. The GRN architecture reflects the particular mode of embryogenesis represented by sea urchin development. Network structure not only specifies the linkages constituting the genomic regulatory code for development, but also indicates the various regulatory requirements of regional developmental processes. PMID:19932099
2017-01-01
Both natural and human-related foraging strategies by the common bottlenose dolphin (Tursiops truncatus) have resulted in social segregation in several areas of the world. Bottlenose dolphins near Savannah, Georgia beg at an unprecedented rate and also forage behind commercial shrimp trawlers, providing an opportunity to study the social ramifications of two human-related foraging behaviors within the same group of animals. Dolphins were photo-identified via surveys conducted throughout estuarine waterways around Savannah in the summers of 2009–2011. Mean half-weight indices (HWI) were calculated for each foraging class, and community division by modularity was used to cluster animals based on association indices. Pairs of trawler dolphins had a higher mean HWI (0.20 ± 0.07) than pairs of non-trawler dolphins (0.04 ± 0.02) or mixed pairs (0.02 ± 0.02). In contrast, pairs of beggars, non-beggars, and mixed pairs all had similar means, with HWI between 0.05–0.07. Community division by modularity produced a useful division (0.307) with 6 clusters. Clusters were predominately divided according to trawler status; however, beggars and non-beggars were mixed throughout clusters. Both the mean HWI and social clusters revealed that the social structure of common bottlenose dolphins near Savannah, Georgia was differentiated based on trawler status but not beg status. This finding may indicate that foraging in association with trawlers is a socially learned behavior, while the mechanisms for the propagation of begging are less clear. This study highlights the importance of taking into account the social parameters of a foraging behavior, such as how group size or competition for resources may affect how the behavior spreads. The positive or negative ramifications of homophily may influence whether the behaviors are exhibited by individuals within the same social clusters and should be considered in future studies examining social relationships and foraging behaviors. PMID:28146563
Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin
2015-01-01
Systematic reviews (SRs) provide high quality evidence for clinical practice, but the article screening process is time and labor intensive. As SRs aim to identify relevant articles with a specific scope, we propose that a pre-defined article relationship, using similarity metrics, could accelerate this process. In this study, we established the article relationship using MEDLINE element similarities and visualized the article network with the Force Atlas layout. We also analyzed the article networks with graph diameter, closeness centrality, and module classes. The results revealed the distribution of articles and found that included articles tended to aggregate together in some module classes, providing further evidence of the existence of strong relationships among included articles. This approach can be utilized to facilitate the articles selection process through early identification of these dominant module classes. We are optimistic that the use of article network visualization can help better SR work prioritization.
Ji, Xiaonan; Machiraju, Raghu; Ritter, Alan; Yen, Po-Yin
2015-01-01
Systematic reviews (SRs) provide high quality evidence for clinical practice, but the article screening process is time and labor intensive. As SRs aim to identify relevant articles with a specific scope, we propose that a pre-defined article relationship, using similarity metrics, could accelerate this process. In this study, we established the article relationship using MEDLINE element similarities and visualized the article network with the Force Atlas layout. We also analyzed the article networks with graph diameter, closeness centrality, and module classes. The results revealed the distribution of articles and found that included articles tended to aggregate together in some module classes, providing further evidence of the existence of strong relationships among included articles. This approach can be utilized to facilitate the articles selection process through early identification of these dominant module classes. We are optimistic that the use of article network visualization can help better SR work prioritization. PMID:26958292
Automatization of hardware configuration for plasma diagnostic system
NASA Astrophysics Data System (ADS)
Wojenski, A.; Pozniak, K. T.; Kasprowicz, G.; Kolasinski, P.; Krawczyk, R. D.; Zabolotny, W.; Linczuk, P.; Chernyshova, M.; Czarski, T.; Malinowski, K.
2016-09-01
Soft X-ray plasma measurement systems are mostly multi-channel, high performance systems. In case of the modular construction it is necessary to perform sophisticated system discovery in parallel with automatic system configuration. In the paper the structure of the modular system designed for tokamak plasma soft X-ray measurements is described. The concept of the system discovery and further automatic configuration is also presented. FCS application (FMC/ FPGA Configuration Software) is used for running sophisticated system setup with automatic verification of proper configuration. In order to provide flexibility of further system configurations (e.g. user setup), common communication interface is also described. The approach presented here is related to the automatic system firmware building presented in previous papers. Modular construction and multichannel measurements are key requirement in term of SXR diagnostics with use of GEM detectors.
ERIC Educational Resources Information Center
Pardos, Zachary A.; Whyte, Anthony; Kao, Kevin
2016-01-01
In this paper, we address issues of transparency, modularity, and privacy with the introduction of an open source, web-based data repository and analysis tool tailored to the Massive Open Online Course community. The tool integrates data request/authorization and distribution workflow features as well as provides a simple analytics module upload…
ERIC Educational Resources Information Center
Lindhiem, Oliver; Kolko, David J.
2010-01-01
In this study, we examined trajectories of symptom reduction and family engagement during the modular treatment phase of a clinical trial for early-onset disruptive behavior disorders that was applied either in community settings or a clinic. Participants (N = 139) were 6-11 year-old children with diagnoses of Oppositional Defiant Disorder (ODD)…
Modular structure of the full-length DNA gyrase B subunit revealed by small-angle X-ray scattering.
Costenaro, Lionel; Grossmann, J Günter; Ebel, Christine; Maxwell, Anthony
2007-03-01
DNA gyrase, the only topoisomerase able to introduce negative supercoils into DNA, is essential for bacterial transcription and replication; absent from humans, it is a successful target for antibacterials. From biophysical experiments in solution, we report a structural model at approximately 12-15 A resolution of the full-length B subunit (GyrB). Analytical ultracentrifugation shows that GyrB is mainly a nonglobular monomer. Ab initio modeling of small-angle X-ray scattering data for GyrB consistently yields a "tadpole"-like envelope. It allows us to propose an organization of GyrB into three domains-ATPase, Toprim, and Tail-based on their crystallographic and modeled structures. Our study reveals the modular organization of GyrB and points out its potential flexibility, needed during the gyrase catalytic cycle. It provides important insights into the supercoiling mechanism by gyrase and suggests new lines of research.
Validation of a wireless modular monitoring system for structures
NASA Astrophysics Data System (ADS)
Lynch, Jerome P.; Law, Kincho H.; Kiremidjian, Anne S.; Carryer, John E.; Kenny, Thomas W.; Partridge, Aaron; Sundararajan, Arvind
2002-06-01
A wireless sensing unit for use in a Wireless Modular Monitoring System (WiMMS) has been designed and constructed. Drawing upon advanced technological developments in the areas of wireless communications, low-power microprocessors and micro-electro mechanical system (MEMS) sensing transducers, the wireless sensing unit represents a high-performance yet low-cost solution to monitoring the short-term and long-term performance of structures. A sophisticated reduced instruction set computer (RISC) microcontroller is placed at the core of the unit to accommodate on-board computations, measurement filtering and data interrogation algorithms. The functionality of the wireless sensing unit is validated through various experiments involving multiple sensing transducers interfaced to the sensing unit. In particular, MEMS-based accelerometers are used as the primary sensing transducer in this study's validation experiments. A five degree of freedom scaled test structure mounted upon a shaking table is employed for system validation.
Social Contact Networks and Mixing among Students in K-12 Schools in Pittsburgh, PA
Guclu, Hasan; Read, Jonathan; Vukotich, Charles J.; Galloway, David D.; Gao, Hongjiang; Rainey, Jeanette J.; Uzicanin, Amra; Zimmer, Shanta M.; Cummings, Derek A. T.
2016-01-01
Students attending schools play an important role in the transmission of influenza. In this study, we present a social network analysis of contacts among 1,828 students in eight different schools in urban and suburban areas in and near Pittsburgh, Pennsylvania, United States of America, including elementary, elementary-middle, middle, and high schools. We collected social contact information of students who wore wireless sensor devices that regularly recorded other devices if they are within a distance of 3 meters. We analyzed these networks to identify patterns of proximal student interactions in different classes and grades, to describe community structure within the schools, and to assess the impact of the physical environment of schools on proximal contacts. In the elementary and middle schools, we observed a high number of intra-grade and intra-classroom contacts and a relatively low number of inter-grade contacts. However, in high schools, contact networks were well connected and mixed across grades. High modularity of lower grades suggests that assumptions of homogeneous mixing in epidemic models may be inappropriate; whereas lower modularity in high schools suggests that homogenous mixing assumptions may be more acceptable in these settings. The results suggest that interventions targeting subsets of classrooms may work better in elementary schools than high schools. Our work presents quantitative measures of age-specific, school-based contacts that can be used as the basis for constructing models of the transmission of infections in schools. PMID:26978780
Social Contact Networks and Mixing among Students in K-12 Schools in Pittsburgh, PA.
Guclu, Hasan; Read, Jonathan; Vukotich, Charles J; Galloway, David D; Gao, Hongjiang; Rainey, Jeanette J; Uzicanin, Amra; Zimmer, Shanta M; Cummings, Derek A T
2016-01-01
Students attending schools play an important role in the transmission of influenza. In this study, we present a social network analysis of contacts among 1,828 students in eight different schools in urban and suburban areas in and near Pittsburgh, Pennsylvania, United States of America, including elementary, elementary-middle, middle, and high schools. We collected social contact information of students who wore wireless sensor devices that regularly recorded other devices if they are within a distance of 3 meters. We analyzed these networks to identify patterns of proximal student interactions in different classes and grades, to describe community structure within the schools, and to assess the impact of the physical environment of schools on proximal contacts. In the elementary and middle schools, we observed a high number of intra-grade and intra-classroom contacts and a relatively low number of inter-grade contacts. However, in high schools, contact networks were well connected and mixed across grades. High modularity of lower grades suggests that assumptions of homogeneous mixing in epidemic models may be inappropriate; whereas lower modularity in high schools suggests that homogenous mixing assumptions may be more acceptable in these settings. The results suggest that interventions targeting subsets of classrooms may work better in elementary schools than high schools. Our work presents quantitative measures of age-specific, school-based contacts that can be used as the basis for constructing models of the transmission of infections in schools.
Contour interpolation: A case study in Modularity of Mind.
Keane, Brian P
2018-05-01
In his monograph Modularity of Mind (1983), philosopher Jerry Fodor argued that mental architecture can be partly decomposed into computational organs termed modules, which were characterized as having nine co-occurring features such as automaticity, domain specificity, and informational encapsulation. Do modules exist? Debates thus far have been framed very generally with few, if any, detailed case studies. The topic is important because it has direct implications on current debates in cognitive science and because it potentially provides a viable framework from which to further understand and make hypotheses about the mind's structure and function. Here, the case is made for the modularity of contour interpolation, which is a perceptual process that represents non-visible edges on the basis of how surrounding visible edges are spatiotemporally configured. There is substantial evidence that interpolation is domain specific, mandatory, fast, and developmentally well-sequenced; that it produces representationally impoverished outputs; that it relies upon a relatively fixed neural architecture that can be selectively impaired; that it is encapsulated from belief and expectation; and that its inner workings cannot be fathomed through conscious introspection. Upon differentiating contour interpolation from a higher-order contour representational ability ("contour abstraction") and upon accommodating seemingly inconsistent experimental results, it is argued that interpolation is modular to the extent that the initiating conditions for interpolation are strong. As interpolated contours become more salient, the modularity features emerge. The empirical data, taken as a whole, show that at least certain parts of the mind are modularly organized. Copyright © 2018 Elsevier B.V. All rights reserved.
Mining the modular structure of protein interaction networks.
Berenstein, Ariel José; Piñero, Janet; Furlong, Laura Inés; Chernomoretz, Ariel
2015-01-01
Cluster-based descriptions of biological networks have received much attention in recent years fostered by accumulated evidence of the existence of meaningful correlations between topological network clusters and biological functional modules. Several well-performing clustering algorithms exist to infer topological network partitions. However, due to respective technical idiosyncrasies they might produce dissimilar modular decompositions of a given network. In this contribution, we aimed to analyze how alternative modular descriptions could condition the outcome of follow-up network biology analysis. We considered a human protein interaction network and two paradigmatic cluster recognition algorithms, namely: the Clauset-Newman-Moore and the infomap procedures. We analyzed to what extent both methodologies yielded different results in terms of granularity and biological congruency. In addition, taking into account Guimera's cartographic role characterization of network nodes, we explored how the adoption of a given clustering methodology impinged on the ability to highlight relevant network meso-scale connectivity patterns. As a case study we considered a set of aging related proteins and showed that only the high-resolution modular description provided by infomap, could unveil statistically significant associations between them and inter/intra modular cartographic features. Besides reporting novel biological insights that could be gained from the discovered associations, our contribution warns against possible technical concerns that might affect the tools used to mine for interaction patterns in network biology studies. In particular our results suggested that sub-optimal partitions from the strict point of view of their modularity levels might still be worth being analyzed when meso-scale features were to be explored in connection with external source of biological knowledge.
Status and plans for the future of the Vienna VLBI Software
NASA Astrophysics Data System (ADS)
Madzak, Matthias; Böhm, Johannes; Böhm, Sigrid; Girdiuk, Anastasiia; Hellerschmied, Andreas; Hofmeister, Armin; Krasna, Hana; Kwak, Younghee; Landskron, Daniel; Mayer, David; McCallum, Jamie; Plank, Lucia; Schönberger, Caroline; Shabala, Stanislav; Sun, Jing; Teke, Kamil
2016-04-01
The Vienna VLBI Software (VieVS) is a VLBI analysis software developed and maintained at Technische Universität Wien (TU Wien) since 2008 with contributions from groups all over the world. It is used for both academic purposes in university courses as well as for providing VLBI analysis results to the geodetic community. Written in a modular structure in Matlab, VieVS offers easy access to the source code and the possibility to adapt the programs for particular purposes. The new version 2.3, released in December 2015, includes several new parameters to be estimated in the global solution, such as tidal ERP variation coefficients. The graphical user interface was slightly modified for an improved user functionality and, e.g., the possibility of deriving baseline length repeatabilities. The scheduling of satellite observations was refined, the simulator newly includes the effect of source structure which can also be corrected for in the analysis. This poster gives an overview of all VLBI-related activities in Vienna and provides an outlook to future plans concerning the Vienna VLBI Software.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ficko-Blean, E.; Gregg, K; Adams, J
2009-01-01
Common features of the extracellular carbohydrate-active virulence factors involved in host-pathogen interactions are their large sizes and modular complexities. This has made them recalcitrant to structural analysis, and therefore our understanding of the significance of modularity in these important proteins is lagging. Clostridium perfringens is a prevalent human pathogen that harbors a wide array of large, extracellular carbohydrate-active enzymes and is an excellent and relevant model system to approach this problem. Here we describe the complete structure of C. perfringens GH84C (NagJ), a 1001-amino acid multimodular homolog of the C. perfringens ?-toxin, which was determined using a combination of smallmore » angle x-ray scattering and x-ray crystallography. The resulting structure reveals unprecedented insight into how catalysis, carbohydrate-specific adherence, and the formation of molecular complexes with other enzymes via an ultra-tight protein-protein interaction are spatially coordinated in an enzyme involved in a host-pathogen interaction.« less
How to remain nonfolded and pliable: the linkers in modular α-amylases as a case study.
Feller, Georges; Dehareng, Dominique; Lage, Jean-Luc Da
2011-07-01
The primary structure of linkers in a new class of modular α-amylases constitutes a paradigm of the structural basis that allows a polypeptide to remain nonfolded, extended and pliable. Unfolding is mediated through a depletion of hydrophobic residues and an enrichment of hydrophilic residues, amongst which Ser and Thr are over-represented. An extended and flexible conformation is promoted by the sequential arrangement of Pro and Gly, which are the most abundant residues in these linkers. This is complemented by charge repulsion, charge clustering and disulfide-bridged loops. Molecular dynamics simulations suggest the existence of conformational transitions resulting from a transient and localized hydrophobic collapse, arising from the peculiar composition of the linkers. Accordingly, these linkers should not be regarded as fully disordered, but rather as possessing various discrete structural patterns allowing them to fulfill their biological function as a free energy reservoir for concerted motions between structured domains. © 2011 The Authors Journal compilation © 2011 FEBS.
Engineering modular polyketide synthases for production of biofuels and industrial chemicals.
Cai, Wenlong; Zhang, Wenjun
2018-04-01
Polyketide synthases (PKSs) are one of the most profound biosynthetic factories for producing polyketides with diverse structures and biological activities. These enzymes have been historically studied and engineered to make un-natural polyketides for drug discovery, and have also recently been explored for synthesizing biofuels and industrial chemicals due to their versatility and customizability. Here, we review recent advances in the mechanistic understanding and engineering of modular PKSs for producing polyketide-derived chemicals, and provide perspectives on this relatively new application of PKSs. Copyright © 2017 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yuzawa, Satoshi; Keasling, Jay D.; Katz, Leonard
Complex polyketides comprise a large number of natural products that have broad application in medicine and agriculture. They are produced in bacteria and fungi from large enzyme complexes named type I modular polyketide synthases (PKSs) that are composed of multifunctional polypeptides containing discrete enzymatic domains organized into modules. The modular nature of PKSs has enabled a multitude of efforts to engineer the PKS genes to produce novel polyketides of predicted structure. Finally, we have repurposed PKSs to produce a number of short-chain mono- and di-carboxylic acids and ketones that could have applications as fuels or industrial chemicals.
MICCA: a complete and accurate software for taxonomic profiling of metagenomic data.
Albanese, Davide; Fontana, Paolo; De Filippo, Carlotta; Cavalieri, Duccio; Donati, Claudio
2015-05-19
The introduction of high throughput sequencing technologies has triggered an increase of the number of studies in which the microbiota of environmental and human samples is characterized through the sequencing of selected marker genes. While experimental protocols have undergone a process of standardization that makes them accessible to a large community of scientist, standard and robust data analysis pipelines are still lacking. Here we introduce MICCA, a software pipeline for the processing of amplicon metagenomic datasets that efficiently combines quality filtering, clustering of Operational Taxonomic Units (OTUs), taxonomy assignment and phylogenetic tree inference. MICCA provides accurate results reaching a good compromise among modularity and usability. Moreover, we introduce a de-novo clustering algorithm specifically designed for the inference of Operational Taxonomic Units (OTUs). Tests on real and synthetic datasets shows that thanks to the optimized reads filtering process and to the new clustering algorithm, MICCA provides estimates of the number of OTUs and of other common ecological indices that are more accurate and robust than currently available pipelines. Analysis of public metagenomic datasets shows that the higher consistency of results improves our understanding of the structure of environmental and human associated microbial communities. MICCA is an open source project.
MICCA: a complete and accurate software for taxonomic profiling of metagenomic data
Albanese, Davide; Fontana, Paolo; De Filippo, Carlotta; Cavalieri, Duccio; Donati, Claudio
2015-01-01
The introduction of high throughput sequencing technologies has triggered an increase of the number of studies in which the microbiota of environmental and human samples is characterized through the sequencing of selected marker genes. While experimental protocols have undergone a process of standardization that makes them accessible to a large community of scientist, standard and robust data analysis pipelines are still lacking. Here we introduce MICCA, a software pipeline for the processing of amplicon metagenomic datasets that efficiently combines quality filtering, clustering of Operational Taxonomic Units (OTUs), taxonomy assignment and phylogenetic tree inference. MICCA provides accurate results reaching a good compromise among modularity and usability. Moreover, we introduce a de-novo clustering algorithm specifically designed for the inference of Operational Taxonomic Units (OTUs). Tests on real and synthetic datasets shows that thanks to the optimized reads filtering process and to the new clustering algorithm, MICCA provides estimates of the number of OTUs and of other common ecological indices that are more accurate and robust than currently available pipelines. Analysis of public metagenomic datasets shows that the higher consistency of results improves our understanding of the structure of environmental and human associated microbial communities. MICCA is an open source project. PMID:25988396
Bahrami, Mohsen; Laurienti, Paul J; Quandt, Sara A; Talton, Jennifer; Pope, Carey N; Summers, Phillip; Burdette, Jonathan H; Chen, Haiying; Liu, Jing; Howard, Timothy D; Arcury, Thomas A; Simpson, Sean L
2017-09-01
Latino immigrants that work on farms experience chronic exposures to potential neurotoxicants, such as pesticides, as part of their work. For tobacco farmworkers there is the additional risk of exposure to moderate to high doses of nicotine. Pesticide and nicotine exposures have been associated with neurological changes in the brain. Long-term exposure to cholinesterase-inhibiting pesticides, such as organophosphates and carbamates, and nicotine place this vulnerable population at risk for developing neurological dysfunction. In this study we examined whole-brain connectivity patterns and brain network properties of Latino immigrant workers. Comparisons were made between farmworkers and non-farmworkers using resting-state functional magnetic resonance imaging data and a mixed-effects modeling framework. We also evaluated how measures of pesticide and nicotine exposures contributed to the findings. Our results indicate that despite having the same functional connectivity density and strength, brain networks in farmworkers had more clustered and modular structures when compared to non-farmworkers. Our findings suggest increased functional specificity and decreased functional integration in farmworkers when compared to non-farmworkers. Cholinesterase activity was associated with population differences in community structure and the strength of brain network functional connections. Urinary cotinine, a marker of nicotine exposure, was associated with the differences in network community structure. Brain network differences between farmworkers and non-farmworkers, as well as pesticide and nicotine exposure effects on brain functional connections in this study, may illuminate underlying mechanisms that cause neurological implications in later life. Copyright © 2017 Elsevier B.V. All rights reserved.
Chebib, Jobran; Guillaume, Frédéric
2017-10-01
Phenotypic traits do not always respond to selection independently from each other and often show correlated responses to selection. The structure of a genotype-phenotype map (GP map) determines trait covariation, which involves variation in the degree and strength of the pleiotropic effects of the underlying genes. It is still unclear, and debated, how much of that structure can be deduced from variational properties of quantitative traits that are inferred from their genetic (co) variance matrix (G-matrix). Here we aim to clarify how the extent of pleiotropy and the correlation among the pleiotropic effects of mutations differentially affect the structure of a G-matrix and our ability to detect genetic constraints from its eigen decomposition. We show that the eigenvectors of a G-matrix can be predictive of evolutionary constraints when they map to underlying pleiotropic modules with correlated mutational effects. Without mutational correlation, evolutionary constraints caused by the fitness costs associated with increased pleiotropy are harder to infer from evolutionary metrics based on a G-matrix's geometric properties because uncorrelated pleiotropic effects do not affect traits' genetic correlations. Correlational selection induces much weaker modular partitioning of traits' genetic correlations in absence then in presence of underlying modular pleiotropy. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
NASA Astrophysics Data System (ADS)
Brischetto, Salvatore; Ciano, Alessandro; Ferro, Carlo Giovanni
2016-07-01
The present paper shows an innovative multirotor Unmanned Aerial Vehicle (UAV) which is able to easily and quickly change its configuration. In order to satisfy this feature, the principal structure is made of an universal plate, combined with a circular ring, to create a rail guide able to host the arms, in a variable number from 3 to 8, and the legs. The arms are adjustable and contain all the avionic and motor drivers to connect the main structure with each electric motor. The unique arm design, defined as all-in-one, allows classical single rotor configurations, double rotor configurations and amphibious configurations including inflatable elements positioned at the bottom of the arms. The proposed multi-rotor system is inexpensive because of the few universal pieces needed to compose the platform which allows the creation of a kit. This modular kit allows to have a modular drone with different configurations. Such configurations are distinguished among them for the number of arms, number of legs, number of rotors and motors, and landing capability. Another innovation feature is the introduction of the 3D printing technology to produce all the structural elements. In this manner, all the pieces are designed to be produced via the Fused Deposition Modelling (FDM) technology using desktop 3D printers. Therefore, an universal, dynamic and economic multi-rotor UAV has been developed.
Demonstration of a Small Modular BioPower System Using Poultry Litter
DOE Office of Scientific and Technical Information (OSTI.GOV)
John P. Reardon; Art Lilley; Jim Wimberly
2002-05-22
The purpose of this project was to assess poultry grower residue, or litter (manure plus absorbent biomass), as a fuel source for Community Power Corporation's small modular biopower system (SMB). A second objective was to assess the poultry industry to identify potential ''on-site'' applications of the SMB system using poultry litter residue as a fuel source, and to adapt CPC's existing SMB to generate electricity and heat from the poultry litter biomass fuel. Bench-scale testing and pilot testing were used to gain design information for the SMB retrofit. System design approach for the Phase II application of the SMB wasmore » the goal of Phase I testing. Cost estimates for an onsite poultry litter SMB were prepared. Finally, a market estimate was prepared for implementation of the on-farm SMB using poultry litter.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bibeault, Mark Leonide
This is a proposal to locate a combined Modular Pumped Hydro (MPH) Energy Storage plus PV solar facility at Rio Rancho High School, NM. The facility will functionally provide electricity at night derived from renewable solar energy. Additionally the facility will provide STEM related educational opportunities for students and staff of the school, public community outreach, and validation of an energy storage approach applicable for the Nation (up to 1,000,000 kWh per installation). The proposal will summarize the nature of electricity, why energy storage is useful, present the combined MPH and solar PV production design, present how the actual designmore » will be built and operated in a sustainable manner, how the project could be funded, and how the project could be used in STEM related activities.« less
Ezzell, Gary A.
2004-01-01
We have recently commissioned a temporary radiation therapy facility that is novel in two aspects: it was constructed using modular components, and the LINAC was installed in one of the modular sections before it was lifted into position. Additional steel and granular fill was added to the modular sections on‐site during construction. The building will be disassembled and removed when no longer needed. This paper describes the radiation shielding specifications and survey of the facility, as well as the ramifications for acceptance testing occasioned by the novel installation procedure. The LINAC is a Varian 21EX operating at 6 MV and 18 MV. The radiation levels outside the vault satisfied the design criteria, and no anomalous leakage was detected along the joints of the modular structure. At 18 MV and 600 monitor units (MU) per minute, the radiation level outside the primary barrier walls was 8.5μSv/h of photons; there were no detectable neutrons. Outside the direct‐shielded door, the levels were 0.4μSv/h of photons and 3.0μSv/h of neutrons. The isocentricity of the accelerator met the acceptance criteria and was not affected by its preinstallation into an integrated baseframe and subsequent transport to the building site. PACS numbers: 87.52.Df, 87.52.Ga PMID:15738926
Zuo, Yicong; Liu, Xiaolu; Wei, Dan; Sun, Jing; Xiao, Wenqian; Zhao, Huan; Guo, Likun; Wei, Qingrong; Fan, Hongsong; Zhang, Xingdong
2015-05-20
Modular tissue engineering holds great potential in regenerating natural complex tissues by engineering three-dimensional modular scaffolds with predefined geometry and biological characters. In modular tissue-like construction, a scaffold with an appropriate mechanical rigidity for assembling fabrication and high biocompatibility for cell survival is the key to the successful bioconstruction. In this work, a series of composite hydrogels (GH0, GH1, GH2, and GH3) based on a combination of methacrylated gelatin (GelMA) and hydroxyapatite (HA) was exploited to enhance hydrogel mechanical rigidity and promote cell functional expression for osteon biofabrication. These composite hydrogels presented a lower swelling ratio, higher mechanical moduli, and better biocompatibility when compared to the pure GelMA hydrogel. Furthermore, on the basis of the composite hydrogel and photolithograph technology, we successfully constructed an osteon-like concentric double-ring structure in which the inner ring encapsulating human umbilical vascular endothelial cells (HUVECs) was designed to imitate blood vessel tubule while the outer ring encapsulating human osteoblast-like cells (MG63s) acts as part of bone. During the coculture period, MG63s and HUVECs exhibited not only satisfying growth status but also the enhanced genic expression of osteogenesis-related and angiogenesis-related differentiations. These results demonstrate this GelMA-HA composite hydrogel system is promising for modular tissue engineering.
Re-emergence of modular brain networks in stroke recovery.
Siegel, Joshua S; Seitzman, Benjamin A; Ramsey, Lenny E; Ortega, Mario; Gordon, Evan M; Dosenbach, Nico U F; Petersen, Steven E; Shulman, Gordon L; Corbetta, Maurizio
2018-04-01
Studies of stroke have identified local reorganization in perilesional tissue. However, because the brain is highly networked, strokes also broadly alter the brain's global network organization. Here, we assess brain network structure longitudinally in adult stroke patients using resting state fMRI. The topology and boundaries of cortical regions remain grossly unchanged across recovery. In contrast, the modularity of brain systems i.e. the degree of integration within and segregation between networks, was significantly reduced sub-acutely (n = 107), but partially recovered by 3 months (n = 85), and 1 year (n = 67). Importantly, network recovery correlated with recovery from language, spatial memory, and attention deficits, but not motor or visual deficits. Finally, in-depth single subject analyses were conducted using tools for visualization of changes in brain networks over time. This exploration indicated that changes in modularity during successful recovery reflect specific alterations in the relationships between different networks. For example, in a patient with left temporo-parietal stroke and severe aphasia, sub-acute loss of modularity reflected loss of association between frontal and temporo-parietal regions bi-hemispherically across multiple modules. These long-distance connections then returned over time, paralleling aphasia recovery. This work establishes the potential importance of normalization of large-scale modular brain systems in stroke recovery. Copyright © 2017. Published by Elsevier Ltd.
Sehar, Ujala; Mehmood, Muhammad Aamer; Hussain, Khadim; Nawaz, Salman; Nadeem, Shahid; Siddique, Muhammad Hussnain; Nadeem, Habibullah; Gull, Munazza; Ahmad, Niaz; Sohail, Iqra; Gill, Saba Shahid; Majeed, Summera
2013-01-01
This paper presents an in silico characterization of the chitin binding protein CBP50 from B. thuringiensis serovar konkukian S4 through homology modeling and molecular docking. The CBP50 has shown a modular structure containing an N-terminal CBM33 domain, two consecutive fibronectin-III (Fn-III) like domains and a C-terminal CBM5 domain. The protein presented a unique modular structure which could not be modeled using ordinary procedures. So, domain wise modeling using MODELLER and docking analyses using Autodock Vina were performed. The best conformation for each domain was selected using standard procedure. It was revealed that four amino acid residues Glu-71, Ser-74, Glu-76 and Gln-90 from N-terminal domain are involved in protein-substrate interaction. Similarly, amino acid residues Trp-20, Asn-21, Ser-23 and Val-30 of Fn-III like domains and Glu-15, Ala-17, Ser-18 and Leu-35 of C-terminal domain were involved in substrate binding. Site-directed mutagenesis of these proposed amino acid residues in future will elucidate the key amino acids involved in chitin binding activity of CBP50 protein.
Using VCL as an Aspect-Oriented Approach to Requirements Modelling
NASA Astrophysics Data System (ADS)
Amálio, Nuno; Kelsen, Pierre; Ma, Qin; Glodt, Christian
Software systems are becoming larger and more complex. By tackling the modularisation of crosscutting concerns, aspect orientation draws attention to modularity as a means to address the problems of scalability, complexity and evolution in software systems development. Aspect-oriented modelling (AOM) applies aspect-orientation to the construction of models. Most existing AOM approaches are designed without a formal semantics, and use multi-view partial descriptions of behaviour. This paper presents an AOM approach based on the Visual Contract Language (VCL): a visual language for abstract and precise modelling, designed with a formal semantics, and comprising a novel approach to visual behavioural modelling based on design by contract where behavioural descriptions are total. By applying VCL to a large case study of a car-crash crisis management system, the paper demonstrates how modularity of VCL's constructs, at different levels of granularity, help to tackle complexity. In particular, it shows how VCL's package construct and its associated composition mechanisms are key in supporting separation of concerns, coarse-grained problem decomposition and aspect-orientation. The case study's modelling solution has a clear and well-defined modular structure; the backbone of this structure is a collection of packages encapsulating local solutions to concerns.
Solid oxide fuel cell generator with removable modular fuel cell stack configurations
Gillett, J.E.; Dederer, J.T.; Zafred, P.R.; Collie, J.C.
1998-04-21
A high temperature solid oxide fuel cell generator produces electrical power from oxidation of hydrocarbon fuel gases such as natural gas, or conditioned fuel gases, such as carbon monoxide or hydrogen, with oxidant gases, such as air or oxygen. This electrochemical reaction occurs in a plurality of electrically connected solid oxide fuel cells bundled and arrayed in a unitary modular fuel cell stack disposed in a compartment in the generator container. The use of a unitary modular fuel cell stack in a generator is similar in concept to that of a removable battery. The fuel cell stack is provided in a pre-assembled self-supporting configuration where the fuel cells are mounted to a common structural base having surrounding side walls defining a chamber. Associated generator equipment may also be mounted to the fuel cell stack configuration to be integral therewith, such as a fuel and oxidant supply and distribution systems, fuel reformation systems, fuel cell support systems, combustion, exhaust and spent fuel recirculation systems, and the like. The pre-assembled self-supporting fuel cell stack arrangement allows for easier assembly, installation, maintenance, better structural support and longer life of the fuel cells contained in the fuel cell stack. 8 figs.
Solid oxide fuel cell generator with removable modular fuel cell stack configurations
Gillett, James E.; Dederer, Jeffrey T.; Zafred, Paolo R.; Collie, Jeffrey C.
1998-01-01
A high temperature solid oxide fuel cell generator produces electrical power from oxidation of hydrocarbon fuel gases such as natural gas, or conditioned fuel gases, such as carbon monoxide or hydrogen, with oxidant gases, such as air or oxygen. This electrochemical reaction occurs in a plurality of electrically connected solid oxide fuel cells bundled and arrayed in a unitary modular fuel cell stack disposed in a compartment in the generator container. The use of a unitary modular fuel cell stack in a generator is similar in concept to that of a removable battery. The fuel cell stack is provided in a pre-assembled self-supporting configuration where the fuel cells are mounted to a common structural base having surrounding side walls defining a chamber. Associated generator equipment may also be mounted to the fuel cell stack configuration to be integral therewith, such as a fuel and oxidant supply and distribution systems, fuel reformation systems, fuel cell support systems, combustion, exhaust and spent fuel recirculation systems, and the like. The pre-assembled self-supporting fuel cell stack arrangement allows for easier assembly, installation, maintenance, better structural support and longer life of the fuel cells contained in the fuel cell stack.
Modular structural elements in the replication origin region of Tetrahymena rDNA.
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
Amp: A modular approach to machine learning in atomistic simulations
NASA Astrophysics Data System (ADS)
Khorshidi, Alireza; Peterson, Andrew A.
2016-10-01
Electronic structure calculations, such as those employing Kohn-Sham density functional theory or ab initio wavefunction theories, have allowed for atomistic-level understandings of a wide variety of phenomena and properties of matter at small scales. However, the computational cost of electronic structure methods drastically increases with length and time scales, which makes these methods difficult for long time-scale molecular dynamics simulations or large-sized systems. Machine-learning techniques can provide accurate potentials that can match the quality of electronic structure calculations, provided sufficient training data. These potentials can then be used to rapidly simulate large and long time-scale phenomena at similar quality to the parent electronic structure approach. Machine-learning potentials usually take a bias-free mathematical form and can be readily developed for a wide variety of systems. Electronic structure calculations have favorable properties-namely that they are noiseless and targeted training data can be produced on-demand-that make them particularly well-suited for machine learning. This paper discusses our modular approach to atomistic machine learning through the development of the open-source Atomistic Machine-learning Package (Amp), which allows for representations of both the total and atom-centered potential energy surface, in both periodic and non-periodic systems. Potentials developed through the atom-centered approach are simultaneously applicable for systems with various sizes. Interpolation can be enhanced by introducing custom descriptors of the local environment. We demonstrate this in the current work for Gaussian-type, bispectrum, and Zernike-type descriptors. Amp has an intuitive and modular structure with an interface through the python scripting language yet has parallelizable fortran components for demanding tasks; it is designed to integrate closely with the widely used Atomic Simulation Environment (ASE), which makes it compatible with a wide variety of commercial and open-source electronic structure codes. We finally demonstrate that the neural network model inside Amp can accurately interpolate electronic structure energies as well as forces of thousands of multi-species atomic systems.
Co-extinction in a host-parasite network: identifying key hosts for network stability.
Dallas, Tad; Cornelius, Emily
2015-08-17
Parasites comprise a substantial portion of total biodiversity. Ultimately, this means that host extinction could result in many secondary extinctions of obligate parasites and potentially alter host-parasite network structure. Here, we examined a highly resolved fish-parasite network to determine key hosts responsible for maintaining parasite diversity and network structure (quantified here as nestedness and modularity). We evaluated four possible host extinction orders and compared the resulting co-extinction dynamics to random extinction simulations; including host removal based on estimated extinction risk, parasite species richness and host level contributions to nestedness and modularity. We found that all extinction orders, except the one based on realistic extinction risk, resulted in faster declines in parasite diversity and network structure relative to random biodiversity loss. Further, we determined species-level contributions to network structure were best predicted by parasite species richness and host family. Taken together, we demonstrate that a small proportion of hosts contribute substantially to network structure and that removal of these hosts results in rapid declines in parasite diversity and network structure. As network stability can potentially be inferred through measures of network structure, our findings may provide insight into species traits that confer stability.
Image Intensifier Modules For Use With Commercially Available Solid State Cameras
NASA Astrophysics Data System (ADS)
Murphy, Howard; Tyler, Al; Lake, Donald W.
1989-04-01
A modular approach to design has contributed greatly to the success of the family of machine vision video equipment produced by EG&G Reticon during the past several years. Internal modularity allows high-performance area (matrix) and line scan cameras to be assembled with two or three electronic subassemblies with very low labor costs, and permits camera control and interface circuitry to be realized by assemblages of various modules suiting the needs of specific applications. Product modularity benefits equipment users in several ways. Modular matrix and line scan cameras are available in identical enclosures (Fig. 1), which allows enclosure components to be purchased in volume for economies of scale and allows field replacement or exchange of cameras within a customer-designed system to be easily accomplished. The cameras are optically aligned (boresighted) at final test; modularity permits optical adjustments to be made with the same precise test equipment for all camera varieties. The modular cameras contain two, or sometimes three, hybrid microelectronic packages (Fig. 2). These rugged and reliable "submodules" perform all of the electronic operations internal to the camera except for the job of image acquisition performed by the monolithic image sensor. Heat produced by electrical power dissipation in the electronic modules is conducted through low resistance paths to the camera case by the metal plates, which results in a thermally efficient and environmentally tolerant camera with low manufacturing costs. A modular approach has also been followed in design of the camera control, video processor, and computer interface accessory called the Formatter (Fig. 3). This unit can be attached directly onto either a line scan or matrix modular camera to form a self-contained units, or connected via a cable to retain the advantages inherent to a small, light weight, and rugged image sensing component. Available modules permit the bus-structured Formatter to be configured as required by a specific camera application. Modular line and matrix scan cameras incorporating sensors with fiber optic faceplates (Fig 4) are also available. These units retain the advantages of interchangeability, simple construction, ruggedness, and optical precision offered by the more common lens input units. Fiber optic faceplate cameras are used for a wide variety of applications. A common usage involves mating of the Reticon-supplied camera to a customer-supplied intensifier tube for low light level and/or short exposure time situations.
OpenStructure: a flexible software framework for computational structural biology.
Biasini, Marco; Mariani, Valerio; Haas, Jürgen; Scheuber, Stefan; Schenk, Andreas D; Schwede, Torsten; Philippsen, Ansgar
2010-10-15
Developers of new methods in computational structural biology are often hampered in their research by incompatible software tools and non-standardized data formats. To address this problem, we have developed OpenStructure as a modular open source platform to provide a powerful, yet flexible general working environment for structural bioinformatics. OpenStructure consists primarily of a set of libraries written in C++ with a cleanly designed application programmer interface. All functionality can be accessed directly in C++ or in a Python layer, meeting both the requirements for high efficiency and ease of use. Powerful selection queries and the notion of entity views to represent these selections greatly facilitate the development and implementation of algorithms on structural data. The modular integration of computational core methods with powerful visualization tools makes OpenStructure an ideal working and development environment. Several applications, such as the latest versions of IPLT and QMean, have been implemented based on OpenStructure-demonstrating its value for the development of next-generation structural biology algorithms. Source code licensed under the GNU lesser general public license and binaries for MacOS X, Linux and Windows are available for download at http://www.openstructure.org. torsten.schwede@unibas.ch Supplementary data are available at Bioinformatics online.
Low-cost modular array-field designs for flat-panel and concentrator photovoltaic systems
NASA Astrophysics Data System (ADS)
Post, H. N.; Carmichael, D. C.; Alexander, G.; Castle, J. A.
1982-09-01
Described are the design and development of low-cost, modular array fields for flat-panel and concentrator photovoltaic (PV) systems. The objective of the work was to reduce substantially the cost of the array-field Balance-of-System (BOS) subsystems and site-specific design costs as compared to previous PV installations. These subsystems include site preparation, foundations, support structures, electrical writing, grounding, lightning protection, electromagnetic interference considerations, and controls. To reduce these BOS and design costs, standardized modular (building-block) designs for flat-panel and concentrator array fields have been developed that are fully integrated and optimized for lowest life-cycle costs. Using drawings and specifications now available, these building-block designs can be used in multiples to install various size array fields. The developed designs are immediately applicable (1982) and reduce the array-field BOS costs to a fraction of previous costs.
Modular hybrid plasma reactor and related systems and methods
Kong, Peter C.; Grandy, Jon D.; Detering, Brent A.
2010-06-22
A device, method and system for generating a plasma is disclosed wherein an electrical arc is established and the movement of the electrical arc is selectively controlled. In one example, modular units are coupled to one another to collectively define a chamber. Each modular unit may include an electrode and a cathode spaced apart and configured to generate an arc therebetween. A device, such as a magnetic or electromagnetic device, may be used to selectively control the movement of the arc about a longitudinal axis of the chamber. The arcs of individual modules may be individually controlled so as to exhibit similar or dissimilar motions about the longitudinal axis of the chamber. In another embodiment, an inlet structure may be used to selectively define the flow path of matter introduced into the chamber such that it travels in a substantially circular or helical path within the chamber.
Shape Optimization and Modular Discretization for the Development of a Morphing Wingtip
NASA Astrophysics Data System (ADS)
Morley, Joshua
Better knowledge in the areas of aerodynamics and optimization has allowed designers to develop efficient wingtip structures in recent years. However, the requirements faced by wingtip devices can be considerably different amongst an aircraft's flight regimes. Traditional static wingtip devices are then a compromise between conflicting requirements, resulting in less than optimal performance within each regime. Alternatively, a morphing wingtip can reconfigure leading to improved performance over a range of dissimilar flight conditions. Developed within this thesis, is a modular morphing wingtip concept that centers on the use of variable geometry truss mechanisms to permit morphing. A conceptual design framework is established to aid in the development of the concept. The framework uses a metaheuristic optimization procedure to determine optimal continuous wingtip configurations. The configurations are then discretized for the modular concept. The functionality of the framework is demonstrated through a design study on a hypothetical wing/winglet within the thesis.
Ribo-attenuators: novel elements for reliable and modular riboswitch engineering.
Folliard, Thomas; Mertins, Barbara; Steel, Harrison; Prescott, Thomas P; Newport, Thomas; Jones, Christopher W; Wadhams, George; Bayer, Travis; Armitage, Judith P; Papachristodoulou, Antonis; Rothschild, Lynn J
2017-07-04
Riboswitches are structural genetic regulatory elements that directly couple the sensing of small molecules to gene expression. They have considerable potential for applications throughout synthetic biology and bio-manufacturing as they are able to sense a wide range of small molecules and regulate gene expression in response. Despite over a decade of research they have yet to reach this considerable potential as they cannot yet be treated as modular components. This is due to several limitations including sensitivity to changes in genetic context, low tunability, and variability in performance. To overcome the associated difficulties with riboswitches, we have designed and introduced a novel genetic element called a ribo-attenuator in Bacteria. This genetic element allows for predictable tuning, insulation from contextual changes, and a reduction in expression variation. Ribo-attenuators allow riboswitches to be treated as truly modular and tunable components, thus increasing their reliability for a wide range of applications.
Itoh, Takafumi; Hibi, Takao; Suzuki, Fumiko; Sugimoto, Ikumi; Fujiwara, Akihiro; Inaka, Koji; Tanaka, Hiroaki; Ohta, Kazunori; Fujii, Yutaka; Taketo, Akira; Kimoto, Hisashi
2016-01-01
The Gram-positive bacterium Paenibacillus sp. str. FPU-7 effectively hydrolyzes chitin by using a number of chitinases. A unique chitinase with two catalytic domains, ChiW, is expressed on the cell surface of this bacterium and has high activity towards various chitins, even crystalline chitin. Here, the crystal structure of ChiW at 2.1 Å resolution is presented and describes how the enzyme degrades chitin on the bacterial cell surface. The crystal structure revealed a unique multi-modular architecture composed of six domains to function efficiently on the cell surface: a right-handed β-helix domain (carbohydrate-binding module family 54, CBM-54), a Gly-Ser-rich loop, 1st immunoglobulin-like (Ig-like) fold domain, 1st β/α-barrel catalytic domain (glycoside hydrolase family 18, GH-18), 2nd Ig-like fold domain and 2nd β/α-barrel catalytic domain (GH-18). The structure of the CBM-54, flexibly linked to the catalytic region of ChiW, is described here for the first time. It is similar to those of carbohydrate lyases but displayed no detectable carbohydrate degradation activities. The CBM-54 of ChiW bound to cell wall polysaccharides, such as chin, chitosan, β-1,3-glucan, xylan and cellulose. The structural and biochemical data obtained here also indicated that the enzyme has deep and short active site clefts with endo-acting character. The affinity of CBM-54 towards cell wall polysaccharides and the degradation pattern of the catalytic domains may help to efficiently decompose the cell wall chitin through the contact surface. Furthermore, we clarify that other Gram-positive bacteria possess similar cell-surface-expressed multi-modular enzymes for cell wall polysaccharide degradation. PMID:27907169
The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability
Diehl, Alexander D.; Meehan, Terrence F.; Bradford, Yvonne M.; ...
2016-07-04
Background: The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies. Construction and content: Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologiesmore » in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning. Utility and discussion: The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs. Conclusions: The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the CL both among developers and within the user community.« less
L. Linsen; B.J. Karis; E.G. McPherson; B. Hamann
2005-01-01
In computer graphics, models describing the fractal branching structure of trees typically exploit the modularity of tree structures. The models are based on local production rules, which are applied iteratively and simultaneously to create a complex branching system. The objective is to generate three-dimensional scenes of often many realistic- looking and non-...
Quantitative tests of a reconstitution model for RNA folding thermodynamics and kinetics.
Bisaria, Namita; Greenfeld, Max; Limouse, Charles; Mabuchi, Hideo; Herschlag, Daniel
2017-09-12
Decades of study of the architecture and function of structured RNAs have led to the perspective that RNA tertiary structure is modular, made of locally stable domains that retain their structure across RNAs. We formalize a hypothesis inspired by this modularity-that RNA folding thermodynamics and kinetics can be quantitatively predicted from separable energetic contributions of the individual components of a complex RNA. This reconstitution hypothesis considers RNA tertiary folding in terms of ΔG align , the probability of aligning tertiary contact partners, and ΔG tert , the favorable energetic contribution from the formation of tertiary contacts in an aligned state. This hypothesis predicts that changes in the alignment of tertiary contacts from different connecting helices and junctions (ΔG HJH ) or from changes in the electrostatic environment (ΔG +/- ) will not affect the energetic perturbation from a mutation in a tertiary contact (ΔΔG tert ). Consistent with these predictions, single-molecule FRET measurements of folding of model RNAs revealed constant ΔΔG tert values for mutations in a tertiary contact embedded in different structural contexts and under different electrostatic conditions. The kinetic effects of these mutations provide further support for modular behavior of RNA elements and suggest that tertiary mutations may be used to identify rate-limiting steps and dissect folding and assembly pathways for complex RNAs. Overall, our model and results are foundational for a predictive understanding of RNA folding that will allow manipulation of RNA folding thermodynamics and kinetics. Conversely, the approaches herein can identify cases where an independent, additive model cannot be applied and so require additional investigation.
Triple products of Eisenstein series
NASA Astrophysics Data System (ADS)
Venkatesh, Anil
In this thesis, we construct a Massey triple product on the Deligne cohomology of the modular curve with coefficients in symmetric powers of the standard representation of the modular group. This result is obtained by constructing a Massey triple product on the extension groups in the category of admissible variations of mixed Hodge structure over the modular curve, which induces the desired construction on Deligne cohomology. The result extends Brown's construction of the cup product on Deligne cohomology to a higher cohomological product. Massey triple products on Deligne cohomology have been previously investigated by Deninger, who considered Deligne cohomology with trivial real coefficients. By working over the reals, Deninger was able to compute cohomology exclusively with differential forms. In this work, Deligne cohomology is studied over the rationals, which introduces an obstruction to applying Deninger's results. The obstruction arises from the fact that the integration map from the de Rham complex to the Eilenberg-MacLane complex of the modular group is not an algebra homomorphism. We compute the correction terms of the integration map as regularized iterated integrals of Eisenstein series, and show that these integrals arise in the cup product and Massey triple product on Deligne cohomology.
NASA Astrophysics Data System (ADS)
Fan, Liming; Zhang, Yujuan; Wang, Jiang; Zhao, Li; Wang, Xiaoqing; Hu, Tuoping; Zhang, Xiutang
2018-04-01
Two 3D modular designed coordination polymers, namely, {[H2N(CH3)2]2[Mn(TPT)]}n (1), and {[Cd(TPT)0.5(bib)]·0.5H2O}n (2) (H4TPT = p-terphenyl-2,2″,5″,5‴-tetracarboxylate acid, and bib = 1,3-bis((imidazol-1-yl) benzene) have been synthesized and structural characterized by EA, IR, TG, PXRD. Single-crystal X-ray diffraction analyses reveal that complex 1 is a 3D 4-connected {42.63.8}-sra net with the tiling modular being [42.62.82] = [4a.4b.62.8a.8b] (transitivity is 2451). While complex 2 is a 3D (4,4)-connected {64.82}{66}2-bbf net with tiling modular is [6.82]+[63.8] = [6 c.8a.8b]+[6a.6b.6 c.8a] (transitivity is 2352). The variable-temperature susceptibility of 1 has been investigated. Besides, complex 2 exhibits highly sensitive sensing of FeIII ions in DMF solution.
Deinterlacing using modular neural network
NASA Astrophysics Data System (ADS)
Woo, Dong H.; Eom, Il K.; Kim, Yoo S.
2004-05-01
Deinterlacing is the conversion process from the interlaced scan to progressive one. While many previous algorithms that are based on weighted-sum cause blurring in edge region, deinterlacing using neural network can reduce the blurring through recovering of high frequency component by learning process, and is found robust to noise. In proposed algorithm, input image is divided into edge and smooth region, and then, to each region, one neural network is assigned. Through this process, each neural network learns only patterns that are similar, therefore it makes learning more effective and estimation more accurate. But even within each region, there are various patterns such as long edge and texture in edge region. To solve this problem, modular neural network is proposed. In proposed modular neural network, two modules are combined in output node. One is for low frequency feature of local area of input image, and the other is for high frequency feature. With this structure, each modular neural network can learn different patterns with compensating for drawback of counterpart. Therefore it can adapt to various patterns within each region effectively. In simulation, the proposed algorithm shows better performance compared with conventional deinterlacing methods and single neural network method.
Existence and significance of communities in the World Trade Web
NASA Astrophysics Data System (ADS)
Piccardi, Carlo; Tajoli, Lucia
2012-06-01
The World Trade Web (WTW), which models the international transactions among countries, is a fundamental tool for studying the economics of trade flows, their evolution over time, and their implications for a number of phenomena, including the propagation of economic shocks among countries. In this respect, the possible existence of communities is a key point, because it would imply that countries are organized in groups of preferential partners. In this paper, we use four approaches to analyze communities in the WTW between 1962 and 2008, based, respectively, on modularity optimization, cluster analysis, stability functions, and persistence probabilities. Overall, the four methods agree in finding no evidence of significant partitions. A few weak communities emerge from the analysis, but they do not represent secluded groups of countries, as intercommunity linkages are also strong, supporting the view of a truly globalized trading system.
Erlandson, Sonya R; Savage, Jessica A; Cavender-Bares, Jeannine M; Peay, Kabir G
2016-01-01
Influences of soil environment and willow host species on ectomycorrhizal fungi communities was studied across an hydrologic gradient in temperate North America. Soil moisture, organic matter and pH strongly predicted changes in fungal community composition. In contrast, increased fungal richness strongly correlated with higher plant-available phosphorus. The 93 willow trees sampled for ectomycorrhizal fungi included seven willow species. Host identity did not influence fungal richness or community composition, nor was there strong evidence of willow host preference for fungal species. Network analysis suggests that these mutualist interaction networks are not significantly nested or modular. Across a strong environmental gradient, fungal abiotic niche determined the fungal species available to associate with host plants within a habitat. © FEMS 2015. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Existence and significance of communities in the World Trade Web.
Piccardi, Carlo; Tajoli, Lucia
2012-06-01
The World Trade Web (WTW), which models the international transactions among countries, is a fundamental tool for studying the economics of trade flows, their evolution over time, and their implications for a number of phenomena, including the propagation of economic shocks among countries. In this respect, the possible existence of communities is a key point, because it would imply that countries are organized in groups of preferential partners. In this paper, we use four approaches to analyze communities in the WTW between 1962 and 2008, based, respectively, on modularity optimization, cluster analysis, stability functions, and persistence probabilities. Overall, the four methods agree in finding no evidence of significant partitions. A few weak communities emerge from the analysis, but they do not represent secluded groups of countries, as intercommunity linkages are also strong, supporting the view of a truly globalized trading system.
Abnormalities in Structural Covariance of Cortical Gyrification in Parkinson's Disease.
Xu, Jinping; Zhang, Jiuquan; Zhang, Jinlei; Wang, Yue; Zhang, Yanling; Wang, Jian; Li, Guanglin; Hu, Qingmao; Zhang, Yuanchao
2017-01-01
Although abnormal cortical morphology and connectivity between brain regions (structural covariance) have been reported in Parkinson's disease (PD), the topological organizations of large-scale structural brain networks are still poorly understood. In this study, we investigated large-scale structural brain networks in a sample of 37 PD patients and 34 healthy controls (HC) by assessing the structural covariance of cortical gyrification with local gyrification index (lGI). We demonstrated prominent small-world properties of the structural brain networks for both groups. Compared with the HC group, PD patients showed significantly increased integrated characteristic path length and integrated clustering coefficient, as well as decreased integrated global efficiency in structural brain networks. Distinct distributions of hub regions were identified between the two groups, showing more hub regions in the frontal cortex in PD patients. Moreover, the modular analyses revealed significantly decreased integrated regional efficiency in lateral Fronto-Insula-Temporal module, and increased integrated regional efficiency in Parieto-Temporal module in the PD group as compared to the HC group. In summary, our study demonstrated altered topological properties of structural networks at a global, regional and modular level in PD patients. These findings suggests that the structural networks of PD patients have a suboptimal topological organization, resulting in less effective integration of information between brain regions.
Balasubramaniam, Krishna N; Beisner, Brianne A; Berman, Carol M; De Marco, Arianna; Duboscq, Julie; Koirala, Sabina; Majolo, Bonaventura; MacIntosh, Andrew J; McFarland, Richard; Molesti, Sandra; Ogawa, Hideshi; Petit, Odile; Schino, Gabriele; Sosa, Sebastian; Sueur, Cédric; Thierry, Bernard; de Waal, Frans B M; McCowan, Brenda
2018-01-01
Among nonhuman primates, the evolutionary underpinnings of variation in social structure remain debated, with both ancestral relationships and adaptation to current conditions hypothesized to play determining roles. Here we assess whether interspecific variation in higher-order aspects of female macaque (genus: Macaca) dominance and grooming social structure show phylogenetic signals, that is, greater similarity among more closely-related species. We use a social network approach to describe higher-order characteristics of social structure, based on both direct interactions and secondary pathways that connect group members. We also ask whether network traits covary with each other, with species-typical social style grades, and/or with sociodemographic characteristics, specifically group size, sex-ratio, and current living condition (captive vs. free-living). We assembled 34-38 datasets of female-female dyadic aggression and allogrooming among captive and free-living macaques representing 10 species. We calculated dominance (transitivity, certainty), and grooming (centrality coefficient, Newman's modularity, clustering coefficient) network traits as aspects of social structure. Computations of K statistics and randomization tests on multiple phylogenies revealed moderate-strong phylogenetic signals in dominance traits, but moderate-weak signals in grooming traits. GLMMs showed that grooming traits did not covary with dominance traits and/or social style grade. Rather, modularity and clustering coefficient, but not centrality coefficient, were strongly predicted by group size and current living condition. Specifically, larger groups showed more modular networks with sparsely-connected clusters than smaller groups. Further, this effect was independent of variation in living condition, and/or sampling effort. In summary, our results reveal that female dominance networks were more phylogenetically conserved across macaque species than grooming networks, which were more labile to sociodemographic factors. Such findings narrow down the processes that influence interspecific variation in two core aspects of macaque social structure. Future directions should include using phylogeographic approaches, and addressing challenges in examining the effects of socioecological factors on primate social structure. © 2017 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Kim, Sang-Yoon; Lim, Woochang
2015-11-01
We consider a clustered network with small-world subnetworks of inhibitory fast spiking interneurons and investigate the effect of intermodular connection on the emergence of fast sparsely synchronized rhythms by varying both the intermodular coupling strength Jinter and the average number of intermodular links per interneuron Msyn(inter ). In contrast to the case of nonclustered networks, two kinds of sparsely synchronized states such as modular and global synchronization are found. For the case of modular sparse synchronization, the population behavior reveals the modular structure, because the intramodular dynamics of subnetworks make some mismatching. On the other hand, in the case of global sparse synchronization, the population behavior is globally identical, independently of the cluster structure, because the intramodular dynamics of subnetworks make perfect matching. We introduce a realistic cross-correlation modularity measure, representing the matching degree between the instantaneous subpopulation spike rates of the subnetworks, and examine whether the sparse synchronization is global or modular. Depending on its magnitude, the intermodular coupling strength Jinter seems to play "dual" roles for the pacing between spikes in each subnetwork. For large Jinter, due to strong inhibition it plays a destructive role to "spoil" the pacing between spikes, while for small Jinter it plays a constructive role to "favor" the pacing between spikes. Through competition between the constructive and the destructive roles of Jinter, there exists an intermediate optimal Jinter at which the pacing degree between spikes becomes maximal. In contrast, the average number of intermodular links per interneuron Msyn(inter ) seems to play a role just to favor the pacing between spikes. With increasing Msyn(inter ), the pacing degree between spikes increases monotonically thanks to the increase in the degree of effectiveness of global communication between spikes. Furthermore, we employ the realistic sub- and whole-population order parameters, based on the instantaneous sub- and whole-population spike rates, to determine the threshold values for the synchronization-unsynchronization transition in the sub- and whole populations, and the degrees of global and modular sparse synchronization are also measured in terms of the realistic sub- and whole-population statistical-mechanical spiking measures defined by considering both the occupation and the pacing degrees of spikes. It is expected that our results could have implications for the role of the brain plasticity in some functional behaviors associated with population synchronization.
Theory for the Emergence of Modularity in Complex Systems
NASA Astrophysics Data System (ADS)
Deem, Michael; Park, Jeong-Man
2013-03-01
Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a theory for the dynamics of modularity in these systems. We find a principle of least action for the evolved modularity at long times. In addition, we find a fluctuation dissipation relation for the rate of change of modularity at short times. We discuss a number of biological and social systems that can be understood with this framework. The modularity of the protein-protein interaction network increases when yeast are exposed to heat shock, and the modularity of the protein-protein networks in both yeast and E. coli appears to have increased over evolutionary time. Food webs in low-energy, stressful environments are more modular than those in plentiful environments, arid ecologies are more modular during droughts, and foraging of sea otters is more modular when food is limiting. The modularity of social networks changes over time: stock brokers instant messaging networks are more modular under stressful market conditions, criminal networks are more modular under increased police pressure, and world trade network modularity has decreased
Wong, Edmond; Vaaje-Kolstad, Gustav; Ghosh, Avishek; Hurtado-Guerrero, Ramon; Konarev, Peter V.; Ibrahim, Adel F. M.; Svergun, Dmitri I.; Eijsink, Vincent G. H.; Chatterjee, Nabendu S.; van Aalten, Daan M. F.
2012-01-01
Vibrio cholerae is a bacterial pathogen that colonizes the chitinous exoskeleton of zooplankton as well as the human gastrointestinal tract. Colonization of these different niches involves an N-acetylglucosamine binding protein (GbpA) that has been reported to mediate bacterial attachment to both marine chitin and mammalian intestinal mucin through an unknown molecular mechanism. We report structural studies that reveal that GbpA possesses an unusual, elongated, four-domain structure, with domains 1 and 4 showing structural homology to chitin binding domains. A glycan screen revealed that GbpA binds to GlcNAc oligosaccharides. Structure-guided GbpA truncation mutants show that domains 1 and 4 of GbpA interact with chitin in vitro, whereas in vivo complementation studies reveal that domain 1 is also crucial for mucin binding and intestinal colonization. Bacterial binding studies show that domains 2 and 3 bind to the V. cholerae surface. Finally, mouse virulence assays show that only the first three domains of GbpA are required for colonization. These results explain how GbpA provides structural/functional modular interactions between V. cholerae, intestinal epithelium and chitinous exoskeletons. PMID:22253590
Technology Challenges and Opportunities for Very Large In-Space Structural Systems
NASA Technical Reports Server (NTRS)
Belvin, W. Keith; Dorsey, John T.; Watson, Judith J.
2009-01-01
Space solar power satellites and other large space systems will require creative and innovative concepts in order to achieve economically viable designs. The mass and volume constraints of current and planned launch vehicles necessitate highly efficient structural systems be developed. In addition, modularity and in-space deployment/construction will be enabling design attributes. While current space systems allocate nearly 20 percent of the mass to the primary structure, the very large space systems of the future must overcome subsystem mass allocations by achieving a level of functional integration not yet realized. A proposed building block approach with two phases is presented to achieve near-term solar power satellite risk reduction with accompanying long-term technology advances. This paper reviews the current challenges of launching and building very large space systems from a structures and materials perspective utilizing recent experience. Promising technology advances anticipated in the coming decades in modularity, material systems, structural concepts, and in-space operations are presented. It is shown that, together, the current challenges and future advances in very large in-space structural systems may provide the technology pull/push necessary to make solar power satellite systems more technically and economically feasible.
Küchenmeister, Jens
2014-04-21
The Fourier modal method (FMM) has advanced greatly by using adaptive coordinates and adaptive spatial resolution. The convergence characteristics were shown to be improved significantly, a construction principle for suitable meshes was demonstrated and a guideline for the optimal choice of the coordinate transformation parameters was found. However, the construction guidelines published so far rely on a certain restriction that is overcome with the formulation presented in this paper. Moreover, a modularization principle is formulated that significantly eases the construction of coordinate transformations in unit cells with reappearing shapes and complex sub-structures.
The type I fatty acid and polyketide synthases: a tale of two megasynthases
Tsai, Shiou-Chuan
2008-01-01
This review chronicles the synergistic growth of the fields of fatty acid and polyketide synthesis over the last century. In both animal fatty acid synthases and modular polyketide synthases, similar catalytic elements are covalently linked in the same order in megasynthases. Whereas in fatty acid synthases the basic elements of the design remain immutable, guaranteeing the faithful production of saturated fatty acids, in the modular polyketide synthases, the potential of the basic design has been exploited to the full for the elaboration of a wide range of secondary metabolites of extraordinary structural diversity. PMID:17898897
Experimental Demonstration of Technologies for Autonomous On-Orbit Robotic Assembly
NASA Technical Reports Server (NTRS)
LeMaster, Edward A.; Schaechter, David B.; Carrington, Connie K.
2006-01-01
The Modular Reconfigurable High Energy (MRHE) program aimed to develop technologies for the automated assembly and deployment of large-scale space structures and aggregate spacecraft. Part of the project involved creation of a terrestrial robotic testbed for validation and demonstration of these technologies and for the support of future development activities. This testbed was completed in 2005, and was thereafter used to demonstrate automated rendezvous, docking, and self-assembly tasks between a group of three modular robotic spacecraft emulators. This paper discusses the rationale for the MRHE project, describes the testbed capabilities, and presents the MRHE assembly demonstration sequence.
Modular power converter having fluid cooled support
Beihoff, Bruce C.; Radosevich, Lawrence D.; Meyer, Andreas A.; Gollhardt, Neil; Kannenberg, Daniel G.
2005-09-06
A support may receive one or more power electronic circuits. The support may aid in removing heat from the circuits through fluid circulating through the support. The support, in conjunction with other packaging features may form a shield from both external EMI/RFI and from interference generated by operation of the power electronic circuits. Features may be provided to permit and enhance connection of the circuitry to external circuitry, such as improved terminal configurations. Modular units may be assembled that may be coupled to electronic circuitry via plug-in arrangements or through interface with a backplane or similar mounting and interconnecting structures.
Modular power converter having fluid cooled support
Beihoff, Bruce C.; Radosevich, Lawrence D.; Meyer, Andreas A.; Gollhardt, Neil; Kannenberg, Daniel G.
2005-12-06
A support may receive one or more power electronic circuits. The support may aid in removing heat from the circuits through fluid circulating through the support. The support, in conjunction with other packaging features may form a shield from both external EMI/RFI and from interference generated by operation of the power electronic circuits. Features may be provided to permit and enhance connection of the circuitry to external circuitry, such as improved terminal configurations. Modular units may be assembled that may be coupled to electronic circuitry via plug-in arrangements or through interface with a backplane or similar mounting and interconnecting structures.
NVSIM: UNIX-based thermal imaging system simulator
NASA Astrophysics Data System (ADS)
Horger, John D.
1993-08-01
For several years the Night Vision and Electronic Sensors Directorate (NVESD) has been using an internally developed forward looking infrared (FLIR) simulation program. In response to interest in the simulation part of these projects by other organizations, NVESD has been working on a new version of the simulation, NVSIM, that will be made generally available to the FLIR using community. NVSIM uses basic FLIR specification data, high resolution thermal input imagery and spatial domain image processing techniques to produce simulated image outputs from a broad variety of FLIRs. It is being built around modular programming techniques to allow simpler addition of more sensor effects. The modularity also allows selective inclusion and exclusion of individual sensor effects at run time. The simulation has been written in the industry standard ANSI C programming language under the widely used UNIX operating system to make it easily portable to a wide variety of computer platforms.
Collaborative Modular Pumped Hydro Energy Storage Design Study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bibeault, Mark Leonide; Roybal, Adam; Bailey, Jr., Richard J.
In May of 2017, Los Alamos National Laboratory (LANL) through the Applied Engineering Technology Division, Jemez Mountain Electric Cooperative Inc. (JMEC), and Northern New Mexico College (NNMC) agreed to enter into a small, joint, non-binding Modular Pumped Hydro (MPH) design study related to grid level energy storage to begin a process of collaboration. Los Alamos National Laboratory's mission is to solve national security challenges through scientific excellence. The mission of Northern New Mexico College is to ensure student success by providing access to affordable, community-based learning opportunities that meet the educational, cultural, and economic needs of the region. Jemez Mountainmore » Electric Cooperative Inc. is the largest electric co-op in the State of New Mexico providing affordable and reliable electricity to customers in the five counties of Rio Arriba, Santa Fe, San Juan, McKinley and Sandoval.« less
LST and instrument considerations. [modular design
NASA Technical Reports Server (NTRS)
Levin, G. M.
1974-01-01
In order that the LST meet its scientific objectives and also be a National Astronomical Space Facility during the 1980's and 1990's, broad requirements have been levied by the scientific community. These scientific requirements can be directly translated into design requirements and specifications for the scientific instruments. The instrument ensemble design must be consistent with a 15-year operational lifetime. Downtime for major repair/refurbishment or instrument updating must be minimized. The overall efficiency and performance of the instruments should be maximized. Modularization of instruments and instrument subsystems, some degree of on-orbit servicing (both repair and replacement), on-axis location, minimizing the number of reflections within instruments, minimizing polarization effects, and simultaneous operation of the F/24 camera with other instruments, are just a few of the design guidelines and specifications which can and will be met in order that these broader scientific requirements be satisfied.-
NASA Astrophysics Data System (ADS)
Collier, Charles Patrick
2017-04-01
The Next Generation Space Interconnect Standard (NGSIS) effort is a Government-Industry collaboration effort to define a set of standards for interconnects between space system components with the goal of cost effectively removing bandwidth as a constraint for future space systems. The NGSIS team has selected the ANSI/VITA 65 OpenVPXTM standard family for the physical baseline. The RapidIO protocol has been selected as the basis for the digital data transport. The NGSIS standards are developed to provide sufficient flexibility to enable users to implement a variety of system configurations, while meeting goals for interoperability and robustness for space. The NGSIS approach and effort represents a radical departure from past approaches to achieve a Modular Open System Architecture (MOSA) for space systems and serves as an exemplar for the civil, commercial, and military Space communities as well as a broader high reliability terrestrial market.
Saavedra, Serguei; Cenci, Simone; Del-Val, Ek; Boege, Karina; Rohr, Rudolf P
2017-09-01
Ecological interaction networks constantly reorganize as interspecific interactions change across successional stages and environmental gradients. This reorganization can also be associated with the extent to which species change their preference for types of niches available in their local sites. Despite the pervasiveness of these interaction changes, previous studies have revealed that network reorganizations have a minimal or insignificant effect on global descriptors of network architecture, such as connectance, modularity and nestedness. However, little is known about whether these reorganizations may have an effect on community dynamics and composition. To answer the question above, we study the multi-year dynamics and reorganization of plant-herbivore interaction networks across secondary successional stages of a tropical dry forest. We develop new quantitative tools based on a structural stability approach to estimate the potential impact of network reorganization on species persistence. Then, we investigate whether this impact can explain the likelihood of persistence of herbivore species in the observed communities. We find that resident (early-arriving) herbivore species increase their likelihood of persistence across time and successional stages. Importantly, we demonstrate that, in late successional stages, the reorganization of interactions among resident species has a strong inhibitory effect on the likelihood of persistence of colonizing (late-arriving) herbivores. These findings support earlier predictions suggesting that, in mature communities, changes of species interactions can act as community-control mechanisms (also known as priority effects). Furthermore, our results illustrate that the dynamics and composition of ecological communities cannot be fully understood without attention to their reorganization processes, despite the invariability of global network properties. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
Rare-event statistics and modular invariance
NASA Astrophysics Data System (ADS)
Nechaev, S. K.; Polovnikov, K.
2018-01-01
Simple geometric arguments based on constructing the Euclid orchard are presented, which explain the equivalence of various types of distributions that result from rare-event statistics. In particular, the spectral density of the exponentially weighted ensemble of linear polymer chains is examined for its number-theoretic properties. It can be shown that the eigenvalue statistics of the corresponding adjacency matrices in the sparse regime show a peculiar hierarchical structure and are described by the popcorn (Thomae) function discontinuous in the dense set of rational numbers. Moreover, the spectral edge density distribution exhibits Lifshitz tails, reminiscent of 1D Anderson localization. Finally, a continuous approximation for the popcorn function is suggested based on the Dedekind η-function, and the hierarchical ultrametric structure of the popcorn-like distributions is demonstrated to be related to hidden SL(2,Z) modular symmetry.
SIRU development. Volume 1: System development
NASA Technical Reports Server (NTRS)
Gilmore, J. P.; Cooper, R. J.
1973-01-01
A complete description of the development and initial evaluation of the Strapdown Inertial Reference Unit (SIRU) system is reported. System development documents the system mechanization with the analytic formulation for fault detection and isolation processing structure; the hardware redundancy design and the individual modularity features; the computational structure and facilities; and the initial subsystem evaluation results.
Protein linguistics - a grammar for modular protein assembly?
Gimona, Mario
2006-01-01
The correspondence between biology and linguistics at the level of sequence and lexical inventories, and of structure and syntax, has fuelled attempts to describe genome structure by the rules of formal linguistics. But how can we define protein linguistic rules? And how could compositional semantics improve our understanding of protein organization and functional plasticity?
Assessing the Structure of a Concept Map
ERIC Educational Resources Information Center
Giouvanakis, Thanasis; Samaras, Haido; Kehris, Evangelos; Mpakavos, Asterios
2013-01-01
This paper presents a framework for the evaluation of concept maps. We focus on supporting the student in dealing with ill-structured and complex problems. We argue that these problems require the application of "the modularity approach." In view of this, the paper describes ways of providing student support for the implementation of…