An adaptable architecture for patient cohort identification from diverse data sources.

PubMed

Bache, Richard; Miles, Simon; Taweel, Adel

2013-12-01

We define and validate an architecture for systems that identify patient cohorts for clinical trials from multiple heterogeneous data sources. This architecture has an explicit query model capable of supporting temporal reasoning and expressing eligibility criteria independently of the representation of the data used to evaluate them. The architecture has the key feature that queries defined according to the query model are both pre and post-processed and this is used to address both structural and semantic heterogeneity. The process of extracting the relevant clinical facts is separated from the process of reasoning about them. A specific instance of the query model is then defined and implemented. We show that the specific instance of the query model has wide applicability. We then describe how it is used to access three diverse data warehouses to determine patient counts. Although the proposed architecture requires greater effort to implement the query model than would be the case for using just SQL and accessing a data-based management system directly, this effort is justified because it supports both temporal reasoning and heterogeneous data sources. The query model only needs to be implemented once no matter how many data sources are accessed. Each additional source requires only the implementation of a lightweight adaptor. The architecture has been used to implement a specific query model that can express complex eligibility criteria and access three diverse data warehouses thus demonstrating the feasibility of this approach in dealing with temporal reasoning and data heterogeneity.

Articulation Management for Intelligent Integration of Information

NASA Technical Reports Server (NTRS)

Maluf, David A.; Tran, Peter B.; Clancy, Daniel (Technical Monitor)

2001-01-01

When combining data from distinct sources, there is a need to share meta-data and other knowledge about various source domains. Due to semantic inconsistencies and heterogeneity of representations, problems arise in combining multiple domains when the domains are merged. The knowledge that is irrelevant to the task of interoperation will be included, making the result unnecessarily complex. This heterogeneity problem can be eliminated by mediating the conflicts and managing the intersections of the domains. For interoperation and intelligent access to heterogeneous information, the focus is on the intersection of the knowledge, since intersection will define the required articulation rules. An algebra over domain has been proposed to use articulation rules to support disciplined manipulation of domain knowledge resources. The objective of a domain algebra is to provide the capability for interrogating many domain knowledge resources, which are largely semantically disjoint. The algebra supports formally the tasks of selecting, combining, extending, specializing, and modifying Components from a diverse set of domains. This paper presents a domain algebra and demonstrates the use of articulation rules to link declarative interfaces for Internet and enterprise applications. In particular, it discusses the articulation implementation as part of a production system capable of operating over the domain described by the IDL (interface description language) of objects registered in multiple CORBA servers.

Estimating Animal Abundance in Ground Beef Batches Assayed with Molecular Markers

PubMed Central

Hu, Xin-Sheng; Simila, Janika; Platz, Sindey Schueler; Moore, Stephen S.; Plastow, Graham; Meghen, Ciaran N.

2012-01-01

Estimating animal abundance in industrial scale batches of ground meat is important for mapping meat products through the manufacturing process and for effectively tracing the finished product during a food safety recall. The processing of ground beef involves a potentially large number of animals from diverse sources in a single product batch, which produces a high heterogeneity in capture probability. In order to estimate animal abundance through DNA profiling of ground beef constituents, two parameter-based statistical models were developed for incidence data. Simulations were applied to evaluate the maximum likelihood estimate (MLE) of a joint likelihood function from multiple surveys, showing superiority in the presence of high capture heterogeneity with small sample sizes, or comparable estimation in the presence of low capture heterogeneity with a large sample size when compared to other existing models. Our model employs the full information on the pattern of the capture-recapture frequencies from multiple samples. We applied the proposed models to estimate animal abundance in six manufacturing beef batches, genotyped using 30 single nucleotide polymorphism (SNP) markers, from a large scale beef grinding facility. Results show that between 411∼1367 animals were present in six manufacturing beef batches. These estimates are informative as a reference for improving recall processes and tracing finished meat products back to source. PMID:22479559

A framework for characterizing drug information sources.

PubMed

Sharp, Mark; Bodenreider, Olivier; Wacholder, Nina

2008-11-06

Drug information is complex, voluminous, heterogeneous, and dynamic. Multiple sources are available, each providing some elements of information about drugs (usually for a given purpose), but there exists no integrated view or directory that could be used to locate sources appropriate to a given purpose. We examined 23 sources that provide drug information in the pharmacy, chemistry, biology, and clinical medicine domains. Their drug information content could be categorized with 39 dimensions. We propose this list of dimensions as a framework for characterizing drug information sources. As an evaluation, we show that this framework is useful for comparing drug information sources and selecting sources most relevant to a given use case.

Joint Blind Source Separation by Multi-set Canonical Correlation Analysis

PubMed Central

Li, Yi-Ou; Adalı, Tülay; Wang, Wei; Calhoun, Vince D

2009-01-01

In this work, we introduce a simple and effective scheme to achieve joint blind source separation (BSS) of multiple datasets using multi-set canonical correlation analysis (M-CCA) [1]. We first propose a generative model of joint BSS based on the correlation of latent sources within and between datasets. We specify source separability conditions, and show that, when the conditions are satisfied, the group of corresponding sources from each dataset can be jointly extracted by M-CCA through maximization of correlation among the extracted sources. We compare source separation performance of the M-CCA scheme with other joint BSS methods and demonstrate the superior performance of the M-CCA scheme in achieving joint BSS for a large number of datasets, group of corresponding sources with heterogeneous correlation values, and complex-valued sources with circular and non-circular distributions. We apply M-CCA to analysis of functional magnetic resonance imaging (fMRI) data from multiple subjects and show its utility in estimating meaningful brain activations from a visuomotor task. PMID:20221319

Developing a Domain Ontology: the Case of Water Cycle and Hydrology

NASA Astrophysics Data System (ADS)

Gupta, H.; Pozzi, W.; Piasecki, M.; Imam, B.; Houser, P.; Raskin, R.; Ramachandran, R.; Martinez Baquero, G.

2008-12-01

A semantic web ontology enables semantic data integration and semantic smart searching. Several organizations have attempted to implement smart registration and integration or searching using ontologies. These are the NOESIS (NSF project: LEAD) and HydroSeek (NSF project: CUAHS HIS) data discovery engines and the NSF project GEON. All three applications use ontologies to discover data from multiple sources and projects. The NASA WaterNet project was established to identify creative, innovative ways to bridge NASA research results to real world applications, linking decision support needs to available data, observations, and modeling capability. WaterNet (NASA project) utilized the smart query tool Noesis as a testbed to test whether different ontologies (and different catalog searches) could be combined to match resources with user needs. NOESIS contains the upper level SWEET ontology that accepts plug in domain ontologies to refine user search queries, reducing the burden of multiple keyword searches. Another smart search interface was that developed for CUAHSI, HydroSeek, that uses a multi-layered concept search ontology, tagging variables names from any number of data sources to specific leaf and higher level concepts on which the search is executed. This approach has proven to be quite successful in mitigating semantic heterogeneity as the user does not need to know the semantic specifics of each data source system but just uses a set of common keywords to discover the data for a specific temporal and geospatial domain. This presentation will show tests with Noesis and Hydroseek lead to the conclusion that the construction of a complex, and highly heterogeneous water cycle ontology requires multiple ontology modules. To illustrate the complexity and heterogeneity of a water cycle ontology, Hydroseek successfully utilizes WaterOneFlow to integrate data across multiple different data collections, such as USGS NWIS. However,different methodologies are employed by the Earth Science, the Hydrological, and Hydraulic Engineering Communities, and each community employs models that require different input data. If a sub-domain ontology is created for each of these,describing water balance calculations, then the resulting structure of the semantic network describing these various terms can be rather complex, heterogeneous, and overlapping, and will require "mapping" between equivalent terms in the ontologies, along with the development of an upper level conceptual or domain ontology to utilize and link to those already in existence.

Linked data and provenance in biological data webs.

PubMed

Zhao, Jun; Miles, Alistair; Klyne, Graham; Shotton, David

2009-03-01

The Web is now being used as a platform for publishing and linking life science data. The Web's linking architecture can be exploited to join heterogeneous data from multiple sources. However, as data are frequently being updated in a decentralized environment, provenance information becomes critical to providing reliable and trustworthy services to scientists. This article presents design patterns for representing and querying provenance information relating to mapping links between heterogeneous data from sources in the domain of functional genomics. We illustrate the use of named resource description framework (RDF) graphs at different levels of granularity to make provenance assertions about linked data, and demonstrate that these assertions are sufficient to support requirements including data currency, integrity, evidential support and historical queries.

Clustering header categories extracted from web tables

NASA Astrophysics Data System (ADS)

Nagy, George; Embley, David W.; Krishnamoorthy, Mukkai; Seth, Sharad

2015-01-01

Revealing related content among heterogeneous web tables is part of our long term objective of formulating queries over multiple sources of information. Two hundred HTML tables from institutional web sites are segmented and each table cell is classified according to the fundamental indexing property of row and column headers. The categories that correspond to the multi-dimensional data cube view of a table are extracted by factoring the (often multi-row/column) headers. To reveal commonalities between tables from diverse sources, the Jaccard distances between pairs of category headers (and also table titles) are computed. We show how about one third of our heterogeneous collection can be clustered into a dozen groups that exhibit table-title and header similarities that can be exploited for queries.

Implementation Issues in Federal Reform Efforts in Education: The United States and Australia.

ERIC Educational Resources Information Center

Porter, Paige

Multiple data sources are used in this study of educational change in the United States and Australia. The author considers political issues that may affect the implementation of educational reform efforts at the federal level, such as homogeneity versus heterogeneity, centralization versus decentralization, constitutional responsibility for…

Family Matters: Gender, Networks, and Entrepreneurial Outcomes.

ERIC Educational Resources Information Center

Renzulli, Linda A.; Aldrich, Howard; Moody, James

2000-01-01

Examines the association between men's and women's social capital and their likelihood of starting a business. Suggests that heterogeneous social networks provide greater access to multiple sources of information. Women had a greater proportion of kin and greater homogeneity in their networks, but it was network characteristics rather than gender…

Heterogeneous data fusion for brain tumor classification.

PubMed

Metsis, Vangelis; Huang, Heng; Andronesi, Ovidiu C; Makedon, Fillia; Tzika, Aria

2012-10-01

Current research in biomedical informatics involves analysis of multiple heterogeneous data sets. This includes patient demographics, clinical and pathology data, treatment history, patient outcomes as well as gene expression, DNA sequences and other information sources such as gene ontology. Analysis of these data sets could lead to better disease diagnosis, prognosis, treatment and drug discovery. In this report, we present a novel machine learning framework for brain tumor classification based on heterogeneous data fusion of metabolic and molecular datasets, including state-of-the-art high-resolution magic angle spinning (HRMAS) proton (1H) magnetic resonance spectroscopy and gene transcriptome profiling, obtained from intact brain tumor biopsies. Our experimental results show that our novel framework outperforms any analysis using individual dataset.

Contaminant point source localization error estimates as functions of data quantity and model quality

NASA Astrophysics Data System (ADS)

Hansen, Scott K.; Vesselinov, Velimir V.

2016-10-01

We develop empirically-grounded error envelopes for localization of a point contamination release event in the saturated zone of a previously uncharacterized heterogeneous aquifer into which a number of plume-intercepting wells have been drilled. We assume that flow direction in the aquifer is known exactly and velocity is known to within a factor of two of our best guess from well observations prior to source identification. Other aquifer and source parameters must be estimated by interpretation of well breakthrough data via the advection-dispersion equation. We employ high performance computing to generate numerous random realizations of aquifer parameters and well locations, simulate well breakthrough data, and then employ unsupervised machine optimization techniques to estimate the most likely spatial (or space-time) location of the source. Tabulating the accuracy of these estimates from the multiple realizations, we relate the size of 90% and 95% confidence envelopes to the data quantity (number of wells) and model quality (fidelity of ADE interpretation model to actual concentrations in a heterogeneous aquifer with channelized flow). We find that for purely spatial localization of the contaminant source, increased data quantities can make up for reduced model quality. For space-time localization, we find similar qualitative behavior, but significantly degraded spatial localization reliability and less improvement from extra data collection. Since the space-time source localization problem is much more challenging, we also tried a multiple-initial-guess optimization strategy. This greatly enhanced performance, but gains from additional data collection remained limited.

Individual crypt genetic heterogeneity and the origin of metaplastic glandular epithelium in human Barrett’s oesophagus

PubMed Central

Leedham, S J; Preston, S L; McDonald, S A C; Elia, G; Bhandari, P; Poller, D; Harrison, R; Novelli, M R; Jankowski, J A; Wright, N A

2008-01-01

Objectives: Current models of clonal expansion in human Barrett’s oesophagus are based upon heterogenous, flow-purified biopsy analysis taken at multiple segment levels. Detection of identical mutation fingerprints from these biopsy samples led to the proposal that a mutated clone with a selective advantage can clonally expand to fill an entire Barrett’s segment at the expense of competing clones (selective sweep to fixation model). We aimed to assess clonality at a much higher resolution by microdissecting and genetically analysing individual crypts. The histogenesis of Barrett’s metaplasia and neo-squamous islands has never been demonstrated. We investigated the oesophageal gland squamous ducts as the source of both epithelial sub-types. Methods: Individual crypts across Barrett’s biopsy and oesophagectomy blocks were dissected. Determination of tumour suppressor gene loss of heterozygosity patterns, p16 and p53 point mutations were carried out on a crypt-by-crypt basis. Cases of contiguous neo-squamous islands and columnar metaplasia with oesophageal squamous ducts were identified. Tissues were isolated by laser capture microdissection and genetically analysed. Results: Individual crypt dissection revealed mutation patterns that were masked in whole biopsy analysis. Dissection across oesophagectomy specimens demonstrated marked clonal heterogeneity, with multiple independent clones present. We identified a p16 point mutation arising in the squamous epithelium of the oesophageal gland duct, which was also present in a contiguous metaplastic crypt, whereas neo-squamous islands arising from squamous ducts were wild-type with respect to surrounding Barrett’s dysplasia. Conclusions: By studying clonality at the crypt level we demonstrate that Barrett’s heterogeneity arises from multiple independent clones, in contrast to the selective sweep to fixation model of clonal expansion previously described. We suggest that the squamous gland ducts situated throughout the oesophagus are the source of a progenitor cell that may be susceptible to gene mutation resulting in conversion to Barrett’s metaplastic epithelium. Additionally, these data suggest that wild-type ducts may be the source of neo-squamous islands. PMID:18305067

Finding missing heritability in less significant Loci and allelic heterogeneity: genetic variation in human height.

PubMed

Zhang, Ge; Karns, Rebekah; Sun, Guangyun; Indugula, Subba Rao; Cheng, Hong; Havas-Augustin, Dubravka; Novokmet, Natalija; Durakovic, Zijad; Missoni, Sasa; Chakraborty, Ranajit; Rudan, Pavao; Deka, Ranjan

2012-01-01

Genome-wide association studies (GWAS) have identified many common variants associated with complex traits in human populations. Thus far, most reported variants have relatively small effects and explain only a small proportion of phenotypic variance, leading to the issues of 'missing' heritability and its explanation. Using height as an example, we examined two possible sources of missing heritability: first, variants with smaller effects whose associations with height failed to reach genome-wide significance and second, allelic heterogeneity due to the effects of multiple variants at a single locus. Using a novel analytical approach we examined allelic heterogeneity of height-associated loci selected from SNPs of different significance levels based on the summary data of the GIANT (stage 1) studies. In a sample of 1,304 individuals collected from an island population of the Adriatic coast of Croatia, we assessed the extent of height variance explained by incorporating the effects of less significant height loci and multiple effective SNPs at the same loci. Our results indicate that approximately half of the 118 loci that achieved stringent genome-wide significance (p-value<5×10(-8)) showed evidence of allelic heterogeneity. Additionally, including less significant loci (i.e., p-value<5×10(-4)) and accounting for effects of allelic heterogeneity substantially improved the variance explained in height.

An adaptable architecture for patient cohort identification from diverse data sources

PubMed Central

Bache, Richard; Miles, Simon; Taweel, Adel

2013-01-01

Objective We define and validate an architecture for systems that identify patient cohorts for clinical trials from multiple heterogeneous data sources. This architecture has an explicit query model capable of supporting temporal reasoning and expressing eligibility criteria independently of the representation of the data used to evaluate them. Method The architecture has the key feature that queries defined according to the query model are both pre and post-processed and this is used to address both structural and semantic heterogeneity. The process of extracting the relevant clinical facts is separated from the process of reasoning about them. A specific instance of the query model is then defined and implemented. Results We show that the specific instance of the query model has wide applicability. We then describe how it is used to access three diverse data warehouses to determine patient counts. Discussion Although the proposed architecture requires greater effort to implement the query model than would be the case for using just SQL and accessing a data-based management system directly, this effort is justified because it supports both temporal reasoning and heterogeneous data sources. The query model only needs to be implemented once no matter how many data sources are accessed. Each additional source requires only the implementation of a lightweight adaptor. Conclusions The architecture has been used to implement a specific query model that can express complex eligibility criteria and access three diverse data warehouses thus demonstrating the feasibility of this approach in dealing with temporal reasoning and data heterogeneity. PMID:24064442

The Chandra Source Catalog : Automated Source Correlation

NASA Astrophysics Data System (ADS)

Hain, Roger; Evans, I. N.; Evans, J. D.; Glotfelty, K. J.; Anderson, C. S.; Bonaventura, N. R.; Chen, J. C.; Davis, J. E.; Doe, S. M.; Fabbiano, G.; Galle, E.; Gibbs, D. G.; Grier, J. D.; Hall, D. M.; Harbo, P. N.; He, X.; Houck, J. C.; Karovska, M.; Lauer, J.; McCollough, M. L.; McDowell, J. C.; Miller, J. B.; Mitschang, A. W.; Morgan, D. L.; Nichols, J. S.; Nowak, M. A.; Plummer, D. A.; Primini, F. A.; Refsdal, B. L.; Rots, A. H.; Siemiginowska, A. L.; Sundheim, B. A.; Tibbetts, M. S.; Van Stone, D. W.; Winkelman, S. L.; Zografou, P.

2009-01-01

Chandra Source Catalog (CSC) master source pipeline processing seeks to automatically detect sources and compute their properties. Since Chandra is a pointed mission and not a sky survey, different sky regions are observed for a different number of times at varying orientations, resolutions, and other heterogeneous conditions. While this provides an opportunity to collect data from a potentially large number of observing passes, it also creates challenges in determining the best way to combine different detection results for the most accurate characterization of the detected sources. The CSC master source pipeline correlates data from multiple observations by updating existing cataloged source information with new data from the same sky region as they become available. This process sometimes leads to relatively straightforward conclusions, such as when single sources from two observations are similar in size and position. Other observation results require more logic to combine, such as one observation finding a single, large source and another identifying multiple, smaller sources at the same position. We present examples of different overlapping source detections processed in the current version of the CSC master source pipeline. We explain how they are resolved into entries in the master source database, and examine the challenges of computing source properties for the same source detected multiple times. Future enhancements are also discussed. This work is supported by NASA contract NAS8-03060 (CXC).

A service-oriented distributed semantic mediator: integrating multiscale biomedical information.

PubMed

Mora, Oscar; Engelbrecht, Gerhard; Bisbal, Jesus

2012-11-01

Biomedical research continuously generates large amounts of heterogeneous and multimodal data spread over multiple data sources. These data, if appropriately shared and exploited, could dramatically improve the research practice itself, and ultimately the quality of health care delivered. This paper presents DISMED (DIstributed Semantic MEDiator), an open source semantic mediator that provides a unified view of a federated environment of multiscale biomedical data sources. DISMED is a Web-based software application to query and retrieve information distributed over a set of registered data sources, using semantic technologies. It also offers a userfriendly interface specifically designed to simplify the usage of these technologies by non-expert users. Although the architecture of the software mediator is generic and domain independent, in the context of this paper, DISMED has been evaluated for managing biomedical environments and facilitating research with respect to the handling of scientific data distributed in multiple heterogeneous data sources. As part of this contribution, a quantitative evaluation framework has been developed. It consist of a benchmarking scenario and the definition of five realistic use-cases. This framework, created entirely with public datasets, has been used to compare the performance of DISMED against other available mediators. It is also available to the scientific community in order to evaluate progress in the domain of semantic mediation, in a systematic and comparable manner. The results show an average improvement in the execution time by DISMED of 55% compared to the second best alternative in four out of the five use-cases of the experimental evaluation.

Device Data Ingestion for Industrial Big Data Platforms with a Case Study †

PubMed Central

Ji, Cun; Shao, Qingshi; Sun, Jiao; Liu, Shijun; Pan, Li; Wu, Lei; Yang, Chenglei

2016-01-01

Despite having played a significant role in the Industry 4.0 era, the Internet of Things is currently faced with the challenge of how to ingest large-scale heterogeneous and multi-type device data. In response to this problem we present a heterogeneous device data ingestion model for an industrial big data platform. The model includes device templates and four strategies for data synchronization, data slicing, data splitting and data indexing, respectively. We can ingest device data from multiple sources with this heterogeneous device data ingestion model, which has been verified on our industrial big data platform. In addition, we present a case study on device data-based scenario analysis of industrial big data. PMID:26927121

AMS+ALS: Kinetic and Product Studies of the Heterogeneous Oxidation of Organic Aerosol at the Advanced Light Source

NASA Astrophysics Data System (ADS)

Kroll, J. H.; Wilson, K. R.; Kessler, S. H.; Browne, E. C.; Nah, T.; Smith, J.; Worsnop, D. R.

2014-12-01

The atmospheric oxidation of condensed-phase organic species can have a major influence on the composition, properties, and impacts of organic aerosol (OA); however the rates and products of such "aging" reactions are poorly constrained. Here we describe a series of laboratory experiments aimed at better understanding one class of aging reactions, the heterogeneous oxidation of OA by gas-phase oxidants. Central to these experiments is the availability of vacuum ultraviolet (VUV) light at the Chemical Dynamics Beamline of the Advanced Light Source at LBNL, which enables the implementation of VUV photoionization aerosol mass spectrometry. This technique allows for the real-time, speciated measurement of OA composition, yielding molecular information that is highly complementary to ensemble data from electron-impact ionization. OA composition is measured with both ionization schemes as a function of oxidant exposure within a flow reactor, providing detailed information on the kinetics and products of heterogeneous oxidation over multiple generations of oxidation. Specific topics investigated include the branching between functionalization and fragmentation of OA components, the formation of secondary organic aerosol from photolytically-generated radical species, and the heterogeneous aging of soot-associated organic species.

Application-Level Interoperability Across Grids and Clouds

NASA Astrophysics Data System (ADS)

Jha, Shantenu; Luckow, Andre; Merzky, Andre; Erdely, Miklos; Sehgal, Saurabh

Application-level interoperability is defined as the ability of an application to utilize multiple distributed heterogeneous resources. Such interoperability is becoming increasingly important with increasing volumes of data, multiple sources of data as well as resource types. The primary aim of this chapter is to understand different ways in which application-level interoperability can be provided across distributed infrastructure. We achieve this by (i) using the canonical wordcount application, based on an enhanced version of MapReduce that scales-out across clusters, clouds, and HPC resources, (ii) establishing how SAGA enables the execution of wordcount application using MapReduce and other programming models such as Sphere concurrently, and (iii) demonstrating the scale-out of ensemble-based biomolecular simulations across multiple resources. We show user-level control of the relative placement of compute and data and also provide simple performance measures and analysis of SAGA-MapReduce when using multiple, different, heterogeneous infrastructures concurrently for the same problem instance. Finally, we discuss Azure and some of the system-level abstractions that it provides and show how it is used to support ensemble-based biomolecular simulations.

Contaminant point source localization error estimates as functions of data quantity and model quality

DOE PAGES

Hansen, Scott K.; Vesselinov, Velimir Valentinov

2016-10-01

We develop empirically-grounded error envelopes for localization of a point contamination release event in the saturated zone of a previously uncharacterized heterogeneous aquifer into which a number of plume-intercepting wells have been drilled. We assume that flow direction in the aquifer is known exactly and velocity is known to within a factor of two of our best guess from well observations prior to source identification. Other aquifer and source parameters must be estimated by interpretation of well breakthrough data via the advection-dispersion equation. We employ high performance computing to generate numerous random realizations of aquifer parameters and well locations, simulatemore » well breakthrough data, and then employ unsupervised machine optimization techniques to estimate the most likely spatial (or space-time) location of the source. Tabulating the accuracy of these estimates from the multiple realizations, we relate the size of 90% and 95% confidence envelopes to the data quantity (number of wells) and model quality (fidelity of ADE interpretation model to actual concentrations in a heterogeneous aquifer with channelized flow). We find that for purely spatial localization of the contaminant source, increased data quantities can make up for reduced model quality. For space-time localization, we find similar qualitative behavior, but significantly degraded spatial localization reliability and less improvement from extra data collection. Since the space-time source localization problem is much more challenging, we also tried a multiple-initial-guess optimization strategy. Furthermore, this greatly enhanced performance, but gains from additional data collection remained limited.« less

Heterogeneous source components of intraplate basalts from NE China induced by the ongoing Pacific slab subduction

NASA Astrophysics Data System (ADS)

Chen, Huan; Xia, Qun-Ke; Ingrin, Jannick; Deloule, Etienne; Bi, Yao

2017-02-01

The subduction of oceanic slabs is widely accepted to be a main reason for chemical heterogeneities in the mantle. However, determining the contributions of slabs in areas that have experienced multiple subduction events is often difficult due to possible overlapping imprints. Understanding the temporal and spatial variations of source components for widespread intraplate small volume basalts in eastern China may be a basis for investigating the influence of the subducted Pacific slab, which has long been postulated but never confirmed. For this purpose, we investigated the Chaihe-aershan volcanic field (including more than 35 small-volume Quaternary basaltic volcanoes) in NE China and measured the oxygen isotopes and water content of clinopyroxene (cpx) phenocrysts using secondary ion mass spectrometry (SIMS) and Fourier transform infrared spectroscopy (FTIR), respectively. The water content of magma was then estimated based on the partition coefficient of H2O between cpx and the basaltic melt. The δ18O of cpx phenocrysts (4.28‰ to 8.57‰) and H2O content of magmas (0.19 wt.%-2.70 wt.%) show large variations, reflecting the compositional heterogeneity of the mantle source. The δ18O values and H2O content within individual samples also display considerable variation, suggesting the mixing of magmas and that the magma mixing occurred shortly before the eruption. The relation between the δ18O values of cpx phenocrysts and the H2O/Ce ratio, Ba/Th ratio and Eu anomaly of whole rocks demonstrates the contributions of three components to the mantle source (hydrothermally altered upper oceanic crust and marine sediments, altered lower gabbroic oceanic crust, and ambient mantle). The proportions of these three components have varied widely over time (∼1.37 Ma to ∼0.25 Ma). The Pacific slab is constantly subducted under eastern Asia and continuously transports recycled materials to the deep mantle. The temporal heterogeneity of the source components may be caused by ongoing Pacific slab subduction. Combined with other basalt localities in eastern China (Shuangliao basalts, Taihang basalts and Shangdong basalts), the contributions of recycled oceanic components in their mantle source are heterogeneous. This spatial heterogeneity of mantle sources may be induced by variable alterations and dehydration during the recycling process of the Pacific slab. Our results show that the source components of Cenozoic intraplate small-volume basalts in eastern China are temporally and spatially heterogeneous, which is likely induced by the ongoing subduction of the Pacific slab. This demonstrates that integrating the temporal variations in geochemical characteristics and tectonic history of a study region can identify the subducted oceanic plate that induced enriched components in the mantle source of intraplate basalts.

Combined virtual and real robotic test-bed for single operator control of multiple robots

NASA Astrophysics Data System (ADS)

Lee, Sam Y.-S.; Hunt, Shawn; Cao, Alex; Pandya, Abhilash

2010-04-01

Teams of heterogeneous robots with different dynamics or capabilities could perform a variety of tasks such as multipoint surveillance, cooperative transport and explorations in hazardous environments. In this study, we work with heterogeneous robots of semi-autonomous ground and aerial robots for contaminant localization. We developed a human interface system which linked every real robot to its virtual counterpart. A novel virtual interface has been integrated with Augmented Reality that can monitor the position and sensory information from video feed of ground and aerial robots in the 3D virtual environment, and improve user situational awareness. An operator can efficiently control the real multi-robots using the Drag-to-Move method on the virtual multi-robots. This enables an operator to control groups of heterogeneous robots in a collaborative way for allowing more contaminant sources to be pursued simultaneously. The advanced feature of the virtual interface system is guarded teleoperation. This can be used to prevent operators from accidently driving multiple robots into walls and other objects. Moreover, the feature of the image guidance and tracking is able to reduce operator workload.

A multiple-point geostatistical method for characterizing uncertainty of subsurface alluvial units and its effects on flow and transport

USGS Publications Warehouse

Cronkite-Ratcliff, C.; Phelps, G.A.; Boucher, A.

2012-01-01

This report provides a proof-of-concept to demonstrate the potential application of multiple-point geostatistics for characterizing geologic heterogeneity and its effect on flow and transport simulation. The study presented in this report is the result of collaboration between the U.S. Geological Survey (USGS) and Stanford University. This collaboration focused on improving the characterization of alluvial deposits by incorporating prior knowledge of geologic structure and estimating the uncertainty of the modeled geologic units. In this study, geologic heterogeneity of alluvial units is characterized as a set of stochastic realizations, and uncertainty is indicated by variability in the results of flow and transport simulations for this set of realizations. This approach is tested on a hypothetical geologic scenario developed using data from the alluvial deposits in Yucca Flat, Nevada. Yucca Flat was chosen as a data source for this test case because it includes both complex geologic and hydrologic characteristics and also contains a substantial amount of both surface and subsurface geologic data. Multiple-point geostatistics is used to model geologic heterogeneity in the subsurface. A three-dimensional (3D) model of spatial variability is developed by integrating alluvial units mapped at the surface with vertical drill-hole data. The SNESIM (Single Normal Equation Simulation) algorithm is used to represent geologic heterogeneity stochastically by generating 20 realizations, each of which represents an equally probable geologic scenario. A 3D numerical model is used to simulate groundwater flow and contaminant transport for each realization, producing a distribution of flow and transport responses to the geologic heterogeneity. From this distribution of flow and transport responses, the frequency of exceeding a given contaminant concentration threshold can be used as an indicator of uncertainty about the location of the contaminant plume boundary.

A three-source capture-recapture estimate of the number of new HIV diagnoses in children in France from 2003–2006 with multiple imputation of a variable of heterogeneous catchability

PubMed Central

2012-01-01

Background Nearly all HIV infections in children worldwide are acquired through mother-to-child transmission (MTCT) during pregnancy, labour, delivery or breastfeeding. The objective of our study was to estimate the number and rate of new HIV diagnoses in children less than 13 years of age in mainland France from 2003–2006. Methods We performed a capture-recapture analysis based on three sources of information: the mandatory HIV case reporting (DOVIH), the French Perinatal Cohort (ANRS-EPF) and a laboratory-based surveillance of HIV (LaboVIH). The missing values of a variable of heterogeneous catchability were estimated through multiple imputation. Log-linear modelling provided estimates of the number of new HIV infections in children, taking into account dependencies between sources and variables of heterogeneous catchability. Results The three sources observed 216 new HIV diagnoses after record-linkage. The number of new HIV diagnoses in children was estimated at 387 (95%CI [271–503]) from 2003–2006, among whom 60% were born abroad. The estimated rate of new HIV diagnoses in children in mainland France was 9.1 per million in 2006 and was 38 times higher in children born abroad than in those born in France. The estimated completeness of the three sources combined was 55.8% (95% CI [42.9 – 79.7]) and varied according to the source; the completeness of DOVIH (28.4%) and ANRS-EPF (26.1%) were lower than that of LaboVIH (33.3%). Conclusion Our study provided, for the first time, an estimated annual rate of new HIV diagnoses in children under 13 years old in mainland France. A more systematic HIV screening of pregnant women that is repeated during pregnancy among women likely to engage in risky behaviour is needed to optimise the prevention of MTCT. HIV screening for children who migrate from countries with high HIV prevalence to France could be recommended to facilitate early diagnosis and treatment. PMID:23050554

VAUD: A Visual Analysis Approach for Exploring Spatio-Temporal Urban Data.

PubMed

Chen, Wei; Huang, Zhaosong; Wu, Feiran; Zhu, Minfeng; Guan, Huihua; Maciejewski, Ross

2017-10-02

Urban data is massive, heterogeneous, and spatio-temporal, posing a substantial challenge for visualization and analysis. In this paper, we design and implement a novel visual analytics approach, Visual Analyzer for Urban Data (VAUD), that supports the visualization, querying, and exploration of urban data. Our approach allows for cross-domain correlation from multiple data sources by leveraging spatial-temporal and social inter-connectedness features. Through our approach, the analyst is able to select, filter, aggregate across multiple data sources and extract information that would be hidden to a single data subset. To illustrate the effectiveness of our approach, we provide case studies on a real urban dataset that contains the cyber-, physical-, and socialinformation of 14 million citizens over 22 days.

The localization of focal heart activity via body surface potential measurements: tests in a heterogeneous torso phantom

NASA Astrophysics Data System (ADS)

Wetterling, F.; Liehr, M.; Schimpf, P.; Liu, H.; Haueisen, J.

2009-09-01

The non-invasive localization of focal heart activity via body surface potential measurements (BSPM) could greatly benefit the understanding and treatment of arrhythmic heart diseases. However, the in vivo validation of source localization algorithms is rather difficult with currently available measurement techniques. In this study, we used a physical torso phantom composed of different conductive compartments and seven dipoles, which were placed in the anatomical position of the human heart in order to assess the performance of the Recursively Applied and Projected Multiple Signal Classification (RAP-MUSIC) algorithm. Electric potentials were measured on the torso surface for single dipoles with and without further uncorrelated or correlated dipole activity. The localization error averaged 11 ± 5 mm over 22 dipoles, which shows the ability of RAP-MUSIC to distinguish an uncorrelated dipole from surrounding sources activity. For the first time, real computational modelling errors could be included within the validation procedure due to the physically modelled heterogeneities. In conclusion, the introduced heterogeneous torso phantom can be used to validate state-of-the-art algorithms under nearly realistic measurement conditions.

Mitochondrial phylogenomics of Hemiptera reveals adaptive innovations driving the diversification of true bugs

PubMed Central

Li, Hu; Leavengood, John M.; Chapman, Eric G.; Burkhardt, Daniel; Song, Fan; Jiang, Pei; Liu, Jinpeng; Cai, Wanzhi

2017-01-01

Hemiptera, the largest non-holometabolous order of insects, represents approximately 7% of metazoan diversity. With extraordinary life histories and highly specialized morphological adaptations, hemipterans have exploited diverse habitats and food sources through approximately 300 Myr of evolution. To elucidate the phylogeny and evolutionary history of Hemiptera, we carried out the most comprehensive mitogenomics analysis on the richest taxon sampling to date covering all the suborders and infraorders, including 34 newly sequenced and 94 published mitogenomes. With optimized branch length and sequence heterogeneity, Bayesian analyses using a site-heterogeneous mixture model resolved the higher-level hemipteran phylogeny as (Sternorrhyncha, (Auchenorrhyncha, (Coleorrhyncha, Heteroptera))). Ancestral character state reconstruction and divergence time estimation suggest that the success of true bugs (Heteroptera) is probably due to angiosperm coevolution, but key adaptive innovations (e.g. prognathous mouthpart, predatory behaviour, and haemelytron) facilitated multiple independent shifts among diverse feeding habits and multiple independent colonizations of aquatic habitats. PMID:28878063

Integrated photoacoustic, ultrasound and fluorescence platform for diagnostic medical imaging-proof of concept study with a tissue mimicking phantom.

PubMed

James, Joseph; Murukeshan, Vadakke Matham; Woh, Lye Sun

2014-07-01

The structural and molecular heterogeneities of biological tissues demand the interrogation of the samples with multiple energy sources and provide visualization capabilities at varying spatial resolution and depth scales for obtaining complementary diagnostic information. A novel multi-modal imaging approach that uses optical and acoustic energies to perform photoacoustic, ultrasound and fluorescence imaging at multiple resolution scales from the tissue surface and depth is proposed in this paper. The system comprises of two distinct forms of hardware level integration so as to have an integrated imaging system under a single instrumentation set-up. The experimental studies show that the system is capable of mapping high resolution fluorescence signatures from the surface, optical absorption and acoustic heterogeneities along the depth (>2cm) of the tissue at multi-scale resolution (<1µm to <0.5mm).

Decision Aids Using Heterogeneous Intelligence Analysis

DTIC Science & Technology

2010-08-20

developing a Geocultural service, a software framework and inferencing engine for the Transparent Urban Structures program. The scope of the effort...has evolved as the program has matured and is including multiple data sources, as well as interfaces out to the ONR architectural framework . Tasks...Interface; Application Program Interface; Application Programmer Interface CAF Common Application Framework EDA Event Driven Architecture a 16. SECURITY

Custom E-Learning Experiences: Working with Profiles for Multiple Content Sources Access and Adaptation

ERIC Educational Resources Information Center

Ferretti, Stefano; Roccetti, Marco; Salomoni, Paola; Mirri, Silvia

2009-01-01

It is a common belief that the problem of extracting learners' profiles to be used for delivering custom learning experiences is a closed case. Yet, practical solutions do not completely cope with the complex issue of capturing all the features of users, especially those of heterogeneous learners, who may have special needs or characteristics…

Surgeon and Hospital Volume as Quality Indicators for CABG in Taiwan: Examining Hazard to Mortality and Accounting for Unobserved Heterogeneity

PubMed Central

Hockenberry, Jason M; Lien, Hsien-Ming; Chou, Shin-Yi

2010-01-01

Objective To investigate whether provider volume has an impact on the hazard of mortality for coronary artery bypass grafting (CABG) patients in Taiwan. Data Sources/Study Setting Multiple sources of linked data from the National Health Insurance Program in Taiwan. Study Design The linked data were used to identify 27,463 patients who underwent CABG without concomitant angioplasty or valve procedures and the surgeon and hospital volumes. Generalized estimating equations and hazard models were estimated to assess the impact of volume on mortality. The hazard modeling technique used accounts for bias stemming from unobserved heterogeneity. Principal Findings Both surgeon and hospital volume quartiles are inversely related to the hazard of mortality after CABG. Patients whose surgeon is in the three higher volume quartiles have lower 1-, 3-, 6-, and 12-month mortality after CABG, while only those having their procedure performed at the highest quartile of volume hospitals have lower mortality outcomes. Conclusions Mortality outcomes are related to provider CABG volume in Taiwan. Unobserved heterogeneity is a concern in the volume–outcome relationship; after accounting for it, surgeon volume effects on short-term mortality are large. Using models controlling for unobserved heterogeneity and examining longer term mortality may still differentiate provider quality by volume. PMID:20662948

Gene flow in environmental Legionella pneumophila leads to genetic and pathogenic heterogeneity within a Legionnaires' disease outbreak.

PubMed

McAdam, Paul R; Vander Broek, Charles W; Lindsay, Diane S J; Ward, Melissa J; Hanson, Mary F; Gillies, Michael; Watson, Mick; Stevens, Joanne M; Edwards, Giles F; Fitzgerald, J Ross

2014-01-01

Legionnaires' disease is a severe form of pneumonia caused by the environmental bacterium Legionella pneumophila. Outbreaks commonly affect people with known risk factors, but the genetic and pathogenic complexity of L. pneumophila within an outbreak is not well understood. Here, we investigate the etiology of the major Legionnaires' disease outbreak that occurred in Edinburgh, UK, in 2012, by examining the evolutionary history, genome content, and virulence of L. pneumophila clinical isolates. Our high resolution genomic approach reveals that the outbreak was caused by multiple genetic subtypes of L. pneumophila, the majority of which had diversified from a single progenitor through mutation, recombination, and horizontal gene transfer within an environmental reservoir prior to release. In addition, we discover that some patients were infected with multiple L. pneumophila subtypes, a finding which can affect the certainty of source attribution. Importantly, variation in the complement of type IV secretion systems encoded by different genetic subtypes correlates with virulence in a Galleria mellonella model of infection, revealing variation in pathogenic potential among the outbreak source population of L. pneumophila. Taken together, our study indicates previously cryptic levels of pathogen heterogeneity within a Legionnaires' disease outbreak, a discovery that impacts on source attribution for future outbreak investigations. Furthermore, our data suggest that in addition to host immune status, pathogen diversity may be an important influence on the clinical outcome of individual outbreak infections.

One size does not fit all: investigating doctors' stated preference heterogeneity for job incentives to inform policy in Thailand.

PubMed

Lagarde, Mylene; Pagaiya, Nonglak; Tangcharoensathian, Viroj; Blaauw, Duane

2013-12-01

This study investigates heterogeneity in Thai doctors' job preferences at the beginning of their career, with a view to inform the design of effective policies to retain them in rural areas. A discrete choice experiment was designed and administered to 198 young doctors. We analysed the data using several specifications of a random parameter model to account for various sources of preference heterogeneity. By modelling preference heterogeneity, we showed how sensitivity to different incentives varied in different sections of the population. In particular, doctors from rural backgrounds were more sensitive than others to a 45% salary increase and having a post near their home province, but they were less sensitive to a reduction in the number of on-call nights. On the basis of the model results, the effects of two types of interventions were simulated: introducing various incentives and modifying the population structure. The results of the simulations provide multiple elements for consideration for policy-makers interested in designing effective interventions. They also underline the interest of modelling preference heterogeneity carefully. Copyright © 2013 John Wiley & Sons, Ltd.

Maintenance of ventricular fibrillation in heterogeneous ventricle.

PubMed

Arevalo, Hamenegild J; Trayanova, Natalia A

2006-01-01

Although ventricular fibrillation (VF) is the prevalent cause of sudden cardiac death, the mechanisms that underlie VF remain elusive. One possible explanation is that VF is driven by a single robust rotor that is the source of wavefronts that break-up due to functional heterogeneities. Previous 2D computer simulations have proposed that a heterogeneity in background potassium current (IK1) can serve as the substrate for the formation of mother rotor activity. This study incorporates IK1 heterogeneity between the left and right ventricle in a realistic 3D rabbit ventricle model to examine its effects on the organization of VF. Computer simulations show that the IK1 heterogeneity contributes to the initiation and maintenance of VF by providing regions of different refractoriness which serves as sites of wave break and rotor formation. A single rotor that drives the fibrillatory activity in the ventricle is not found in this study. Instead, multiple sites of reentry are recorded throughout the ventricle. Calculation of dominant frequencies for each myocardial node yields no significant difference between the dominant frequency of the LV and the RV. The 3D computer simulations suggest that IK1 spatial heterogeneity alone can not lead to the formation of a stable rotor.

Dual-color single-mode lasing in axially coupled organic nanowire resonators

PubMed Central

Zhang, Chunhuan; Zou, Chang-Ling; Dong, Haiyun; Yan, Yongli; Yao, Jiannian; Zhao, Yong Sheng

2017-01-01

Miniaturized lasers with multicolor output and high spectral purity are of crucial importance for yielding more compact and more versatile photonic devices. However, multicolor lasers usually operate in multimode, which largely restricts their practical applications due to the lack of an effective mode selection mechanism that is simultaneously applicable to multiple wavebands. We propose a mutual mode selection strategy to realize dual-color single-mode lasing in axially coupled cavities constructed from two distinct organic self-assembled single-crystal nanowires. The unique mode selection mechanism in the heterogeneously coupled nanowires was elucidated experimentally and theoretically. With each individual nanowire functioning as both the laser source and the mode filter for the other nanowire, dual-color single-mode lasing was successfully achieved in the axially coupled heterogeneous nanowire resonators. Furthermore, the heterogeneously coupled resonators provided multiple nanoscale output ports for delivering coherent signals with different colors, which could greatly contribute to increasing the integration level of functional photonic devices. These results advance the fundamental understanding of the lasing modulation in coupled cavity systems and offer a promising route to building multifunctional nanoscale lasers for high-level practical photonic integrations. PMID:28785731

Rupture Dynamics and Ground Motion from Earthquakes on Rough Faults in Heterogeneous Media

NASA Astrophysics Data System (ADS)

Bydlon, S. A.; Kozdon, J. E.; Duru, K.; Dunham, E. M.

2013-12-01

Heterogeneities in the material properties of Earth's crust scatter propagating seismic waves. The effects of scattered waves are reflected in the seismic coda and depend on the amplitude of the heterogeneities, spatial arrangement, and distance from source to receiver. In the vicinity of the fault, scattered waves influence the rupture process by introducing fluctuations in the stresses driving propagating ruptures. Further variability in the rupture process is introduced by naturally occurring geometric complexity of fault surfaces, and the stress changes that accompany slip on rough surfaces. Our goal is to better understand the origin of complexity in the earthquake source process, and to quantify the relative importance of source complexity and scattering along the propagation path in causing incoherence of high frequency ground motion. Using a 2D high order finite difference rupture dynamics code, we nucleate ruptures on either flat or rough faults that obey strongly rate-weakening friction laws. These faults are embedded in domains with spatially varying material properties characterized by Von Karman autocorrelation functions and their associated power spectral density functions, with variations in wave speed of approximately 5 to 10%. Flat fault simulations demonstrate that off-fault material heterogeneity, at least with this particular form and amplitude, has only a minor influence on the rupture process (i.e., fluctuations in slip and rupture velocity). In contrast, ruptures histories on rough faults in both homogeneous and heterogeneous media include much larger short-wavelength fluctuations in slip and rupture velocity. We therefore conclude that source complexity is dominantly influenced by fault geometric complexity. To examine contributions of scattering versus fault geometry on ground motions, we compute spatially averaged root-mean-square (RMS) acceleration values as a function of fault perpendicular distance for a homogeneous medium and several heterogeneous media characterized by different statistical properties. We find that at distances less than ~6 km from the fault, RMS acceleration values from simulations with homogeneous and heterogeneous media are similar, but at greater distances the RMS values associated with heterogeneous media are larger than those associated with homogeneous media. The magnitude of this divergence increases with the amplitude of the heterogeneities. For instance, for a heterogeneous medium with a 10% standard deviation in material property values relative to mean values, RMS accelerations are ~50% larger than for a homogeneous medium at distances greater than 6 km. This finding is attributed to the scattering of coherent pulses into multiple pulses of decreased amplitude that subsequently arrive at later times. In order to understand the robustness of these results, an extension of our dynamic rupture and wave propagation code to 3D is underway.

Hydrogeophysical imaging of deposit heterogeneity and groundwater chemistry changes during DNAPL source zone bioremediation.

PubMed

Chambers, J E; Wilkinson, P B; Wealthall, G P; Loke, M H; Dearden, R; Wilson, R; Allen, D; Ogilvy, R D

2010-10-21

Robust characterization and monitoring of dense nonaqueous phase liquid (DNAPL) source zones is essential for designing effective remediation strategies, and for assessing the efficacy of treatment. In this study high-resolution cross-hole electrical resistivity tomography (ERT) was evaluated as a means of monitoring a field-scale in-situ bioremediation experiment, in which emulsified vegetable oil (EVO) electron donor was injected into a trichloroethene source zone. Baseline ERT scans delineated the geometry of the interface between the contaminated alluvial aquifer and the underlying mudstone bedrock, and also the extent of drilling-induced physical heterogeneity. Time-lapse ERT images revealed major preferential flow pathways in the source and plume zones, which were corroborated by multiple lines of evidence, including geochemical monitoring and hydraulic testing using high density multilevel sampler arrays within the geophysical imaging planes. These pathways were shown to control the spatial distribution of the injected EVO, and a bicarbonate buffer introduced into the cell for pH control. Resistivity signatures were observed within the preferential flow pathways that were consistent with elevated chloride levels, providing tentative evidence from ERT of the biodegradation of chlorinated solvents. Copyright © 2010 S. Yamamoto. Published by Elsevier B.V. All rights reserved.

Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.

PubMed

Argelaguet, Ricard; Velten, Britta; Arnol, Damien; Dietrich, Sascha; Zenz, Thorsten; Marioni, John C; Buettner, Florian; Huber, Wolfgang; Stegle, Oliver

2018-06-20

Multi-omics studies promise the improved characterization of biological processes across molecular layers. However, methods for the unsupervised integration of the resulting heterogeneous data sets are lacking. We present Multi-Omics Factor Analysis (MOFA), a computational method for discovering the principal sources of variation in multi-omics data sets. MOFA infers a set of (hidden) factors that capture biological and technical sources of variability. It disentangles axes of heterogeneity that are shared across multiple modalities and those specific to individual data modalities. The learnt factors enable a variety of downstream analyses, including identification of sample subgroups, data imputation and the detection of outlier samples. We applied MOFA to a cohort of 200 patient samples of chronic lymphocytic leukaemia, profiled for somatic mutations, RNA expression, DNA methylation and ex vivo drug responses. MOFA identified major dimensions of disease heterogeneity, including immunoglobulin heavy-chain variable region status, trisomy of chromosome 12 and previously underappreciated drivers, such as response to oxidative stress. In a second application, we used MOFA to analyse single-cell multi-omics data, identifying coordinated transcriptional and epigenetic changes along cell differentiation. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Low-energy Control of Electrical Turbulence in the Heart

PubMed Central

Luther, Stefan; Fenton, Flavio H.; Kornreich, Bruce G.; Squires, Amgad; Bittihn, Philip; Hornung, Daniel; Zabel, Markus; Flanders, James; Gladuli, Andrea; Campoy, Luis; Cherry, Elizabeth M.; Luther, Gisa; Hasenfuss, Gerd; Krinsky, Valentin I.; Pumir, Alain; Gilmour, Robert F.; Bodenschatz, Eberhard

2011-01-01

Controlling the complex spatio-temporal dynamics underlying life-threatening cardiac arrhythmias such as fibrillation is extremely difficult due to the nonlinear interaction of excitation waves within a heterogeneous anatomical substrate1–4. Lacking a better strategy, strong, globally resetting electrical shocks remain the only reliable treatment for cardiac fibrillation5–7. Here, we establish the relation between the response of the tissue to an electric field and the spatial distribution of heterogeneities of the scale-free coronary vascular structure. We show that in response to a pulsed electric field E, these heterogeneities serve as nucleation sites for the generation of intramural electrical waves with a source density ρ(E), and a characteristic time τ for tissue depolarization that obeys a power law τ∝Eα. These intramural wave sources permit targeting of electrical turbulence near the cores of the vortices of electrical activity that drive complex fibrillatory dynamics. We show in vitro that simultaneous and direct access to multiple vortex cores results in rapid synchronization of cardiac tissue and therefore efficient termination of fibrillation. Using this novel control strategy, we demonstrate, for the first time, low-energy termination of fibrillation in vivo. Our results give new insights into the mechanisms and dynamics underlying the control of spatio-temporal chaos in heterogeneous excitable media and at the same time provide new research perspectives towards alternative, life-saving low-energy defibrillation techniques. PMID:21753855

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices

PubMed Central

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B.

2018-01-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support. PMID:29629431

RSTensorFlow: GPU Enabled TensorFlow for Deep Learning on Commodity Android Devices.

PubMed

Alzantot, Moustafa; Wang, Yingnan; Ren, Zhengshuang; Srivastava, Mani B

2017-06-01

Mobile devices have become an essential part of our daily lives. By virtue of both their increasing computing power and the recent progress made in AI, mobile devices evolved to act as intelligent assistants in many tasks rather than a mere way of making phone calls. However, popular and commonly used tools and frameworks for machine intelligence are still lacking the ability to make proper use of the available heterogeneous computing resources on mobile devices. In this paper, we study the benefits of utilizing the heterogeneous (CPU and GPU) computing resources available on commodity android devices while running deep learning models. We leveraged the heterogeneous computing framework RenderScript to accelerate the execution of deep learning models on commodity Android devices. Our system is implemented as an extension to the popular open-source framework TensorFlow. By integrating our acceleration framework tightly into TensorFlow, machine learning engineers can now easily make benefit of the heterogeneous computing resources on mobile devices without the need of any extra tools. We evaluate our system on different android phones models to study the trade-offs of running different neural network operations on the GPU. We also compare the performance of running different models architectures such as convolutional and recurrent neural networks on CPU only vs using heterogeneous computing resources. Our result shows that although GPUs on the phones are capable of offering substantial performance gain in matrix multiplication on mobile devices. Therefore, models that involve multiplication of large matrices can run much faster (approx. 3 times faster in our experiments) due to GPU support.

PopHR: a knowledge-based platform to support integration, analysis, and visualization of population health data.

PubMed

Shaban-Nejad, Arash; Lavigne, Maxime; Okhmatovskaia, Anya; Buckeridge, David L

2017-01-01

Population health decision makers must consider complex relationships between multiple concepts measured with differential accuracy from heterogeneous data sources. Population health information systems are currently limited in their ability to integrate data and present a coherent portrait of population health. Consequentially, these systems can provide only basic support for decision makers. The Population Health Record (PopHR) is a semantic web application that automates the integration and extraction of massive amounts of heterogeneous data from multiple distributed sources (e.g., administrative data, clinical records, and survey responses) to support the measurement and monitoring of population health and health system performance for a defined population. The design of the PopHR draws on the theories of the determinants of health and evidence-based public health to harmonize and explicitly link information about a population with evidence about the epidemiology and control of chronic diseases. Organizing information in this manner and linking it explicitly to evidence is expected to improve decision making related to the planning, implementation, and evaluation of population health and health system interventions. In this paper, we describe the PopHR platform and discuss the architecture, design, key modules, and its implementation and use. © 2016 New York Academy of Sciences.

Identifying Genetic Sources of Phenotypic Heterogeneity in Orofacial Clefts by Targeted Sequencing.

PubMed

Carlson, Jenna C; Taub, Margaret A; Feingold, Eleanor; Beaty, Terri H; Murray, Jeffrey C; Marazita, Mary L; Leslie, Elizabeth J

2017-07-17

Orofacial clefts (OFCs), including nonsyndromic cleft lip with or without cleft palate (NSCL/P), are common birth defects. NSCL/P is highly heterogeneous with multiple phenotypic presentations. Two common subtypes of NSCL/P are cleft lip (CL) and cleft lip with cleft palate (CLP) which have different population prevalence. Similarly, NSCL/P can be divided into bilateral and unilateral clefts, with unilateral being the most common. Individuals with unilateral NSCL/P are more likely to be affected on the left side of the upper lip, but right side affection also occurs. Moreover, NSCL/P is twice as common in males as in females. The goal of this study is to discover genetic variants that have different effects in case subgroups. We conducted both common variant and rare variant analyses in 1034 individuals of Asian ancestry with NSCL/P, examining four sources of heterogeneity within CL/P: cleft type, sex, laterality, and side. We identified several regions associated with subtype differentiation: cleft type differences in 8q24 (p = 1.00 × 10 -4 ), laterality differences in IRF6, a gene previously implicated with wound healing (p = 2.166 × 10 -4 ), sex differences and side of unilateral CL differences in FGFR2 (p = 3.00 × 10 -4 ; p = 6.00 × 10 -4 ), and sex differences in VAX1 (p < 1.00 × 10 -4 ) among others. Many of the regions associated with phenotypic modification were either adjacent to or overlapping functional elements based on ENCODE chromatin marks and published craniofacial enhancers. We have identified multiple common and rare variants as potential phenotypic modifiers of NSCL/P, and suggest plausible elements responsible for phenotypic heterogeneity, further elucidating the complex genetic architecture of OFCs. Birth Defects Research 109:1030-1038, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Use of Graph Database for the Integration of Heterogeneous Biological Data.

PubMed

Yoon, Byoung-Ha; Kim, Seon-Kyu; Kim, Seon-Young

2017-03-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data.

Use of Graph Database for the Integration of Heterogeneous Biological Data

PubMed Central

Yoon, Byoung-Ha; Kim, Seon-Kyu

2017-01-01

Understanding complex relationships among heterogeneous biological data is one of the fundamental goals in biology. In most cases, diverse biological data are stored in relational databases, such as MySQL and Oracle, which store data in multiple tables and then infer relationships by multiple-join statements. Recently, a new type of database, called the graph-based database, was developed to natively represent various kinds of complex relationships, and it is widely used among computer science communities and IT industries. Here, we demonstrate the feasibility of using a graph-based database for complex biological relationships by comparing the performance between MySQL and Neo4j, one of the most widely used graph databases. We collected various biological data (protein-protein interaction, drug-target, gene-disease, etc.) from several existing sources, removed duplicate and redundant data, and finally constructed a graph database containing 114,550 nodes and 82,674,321 relationships. When we tested the query execution performance of MySQL versus Neo4j, we found that Neo4j outperformed MySQL in all cases. While Neo4j exhibited a very fast response for various queries, MySQL exhibited latent or unfinished responses for complex queries with multiple-join statements. These results show that using graph-based databases, such as Neo4j, is an efficient way to store complex biological relationships. Moreover, querying a graph database in diverse ways has the potential to reveal novel relationships among heterogeneous biological data. PMID:28416946

A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm.

PubMed

Ethier, Jean-François; Dameron, Olivier; Curcin, Vasa; McGilchrist, Mark M; Verheij, Robert A; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C; Burgun, Anita

2013-01-01

Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration.

A unified structural/terminological interoperability framework based on LexEVS: application to TRANSFoRm

PubMed Central

Ethier, Jean-François; Dameron, Olivier; Curcin, Vasa; McGilchrist, Mark M; Verheij, Robert A; Arvanitis, Theodoros N; Taweel, Adel; Delaney, Brendan C; Burgun, Anita

2013-01-01

Objective Biomedical research increasingly relies on the integration of information from multiple heterogeneous data sources. Despite the fact that structural and terminological aspects of interoperability are interdependent and rely on a common set of requirements, current efforts typically address them in isolation. We propose a unified ontology-based knowledge framework to facilitate interoperability between heterogeneous sources, and investigate if using the LexEVS terminology server is a viable implementation method. Materials and methods We developed a framework based on an ontology, the general information model (GIM), to unify structural models and terminologies, together with relevant mapping sets. This allowed a uniform access to these resources within LexEVS to facilitate interoperability by various components and data sources from implementing architectures. Results Our unified framework has been tested in the context of the EU Framework Program 7 TRANSFoRm project, where it was used to achieve data integration in a retrospective diabetes cohort study. The GIM was successfully instantiated in TRANSFoRm as the clinical data integration model, and necessary mappings were created to support effective information retrieval for software tools in the project. Conclusions We present a novel, unifying approach to address interoperability challenges in heterogeneous data sources, by representing structural and semantic models in one framework. Systems using this architecture can rely solely on the GIM that abstracts over both the structure and coding. Information models, terminologies and mappings are all stored in LexEVS and can be accessed in a uniform manner (implementing the HL7 CTS2 service functional model). The system is flexible and should reduce the effort needed from data sources personnel for implementing and managing the integration. PMID:23571850

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-02-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes simultaneously, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modelling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous lower limit for expression variability. A second source, which is modelled as originating from a common upstream transcription factor, exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-03-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes in concert, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modeling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous noise floor in expression variability. A second source which is modeled as originating from a common upstream transcription factor exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Federated querying architecture with clinical & translational health IT application.

PubMed

Livne, Oren E; Schultz, N Dustin; Narus, Scott P

2011-10-01

We present a software architecture that federates data from multiple heterogeneous health informatics data sources owned by multiple organizations. The architecture builds upon state-of-the-art open-source Java and XML frameworks in innovative ways. It consists of (a) federated query engine, which manages federated queries and result set aggregation via a patient identification service; and (b) data source facades, which translate the physical data models into a common model on-the-fly and handle large result set streaming. System modules are connected via reusable Apache Camel integration routes and deployed to an OSGi enterprise service bus. We present an application of our architecture that allows users to construct queries via the i2b2 web front-end, and federates patient data from the University of Utah Enterprise Data Warehouse and the Utah Population database. Our system can be easily adopted, extended and integrated with existing SOA Healthcare and HL7 frameworks such as i2b2 and caGrid.

A Virtual Science Data Environment for Carbon Dioxide Observations

NASA Astrophysics Data System (ADS)

Verma, R.; Goodale, C. E.; Hart, A. F.; Law, E.; Crichton, D. J.; Mattmann, C. A.; Gunson, M. R.; Braverman, A. J.; Nguyen, H. M.; Eldering, A.; Castano, R.; Osterman, G. B.

2011-12-01

Climate science data are often distributed cross-institutionally and made available using heterogeneous interfaces. With respect to observational carbon-dioxide (CO2) records, these data span across national as well as international institutions and are typically distributed using a variety of data standards. Such an arrangement can yield challenges from a research perspective, as users often need to independently aggregate datasets as well as address the issue of data quality. To tackle this dispersion and heterogeneity of data, we have developed the CO2 Virtual Science Data Environment - a comprehensive approach to virtually integrating CO2 data and metadata from multiple missions and providing a suite of computational services that facilitate analysis, comparison, and transformation of that data. The Virtual Science Environment provides climate scientists with a unified web-based destination for discovering relevant observational data in context, and supports a growing range of online tools and services for analyzing and transforming the available data to suit individual research needs. It includes web-based tools to geographically and interactively search for CO2 observations collected from multiple airborne, space, as well as terrestrial platforms. Moreover, the data analysis services it provides over the Internet, including offering techniques such as bias estimation and spatial re-gridding, move computation closer to the data and reduce the complexity of performing these operations repeatedly and at scale. The key to enabling these services, as well as consolidating the disparate data into a unified resource, has been to focus on leveraging metadata descriptors as the foundation of our data environment. This metadata-centric architecture, which leverages the Dublin Core standard, forgoes the need to replicate remote datasets locally. Instead, the system relies upon an extensive, metadata-rich virtual data catalog allowing on-demand browsing and retrieval of CO2 records from multiple missions. In other words, key metadata information about remote CO2 records is stored locally while the data itself is preserved at its respective archive of origin. This strategy has been made possible by our method of encapsulating the heterogeneous sources of data using a common set of web-based services, including services provided by Jet Propulsion Laboratory's Climate Data Exchange (CDX). Furthermore, this strategy has enabled us to scale across missions, and to provide access to a broad array of CO2 observational data. Coupled with on-demand computational services and an intuitive web-portal interface, the CO2 Virtual Science Data Environment effectively transforms heterogeneous CO2 records from multiple sources into a unified resource for scientific discovery.

Semantic integration of data on transcriptional regulation

PubMed Central

Baitaluk, Michael; Ponomarenko, Julia

2010-01-01

Motivation: Experimental and predicted data concerning gene transcriptional regulation are distributed among many heterogeneous sources. However, there are no resources to integrate these data automatically or to provide a ‘one-stop shop’ experience for users seeking information essential for deciphering and modeling gene regulatory networks. Results: IntegromeDB, a semantic graph-based ‘deep-web’ data integration system that automatically captures, integrates and manages publicly available data concerning transcriptional regulation, as well as other relevant biological information, is proposed in this article. The problems associated with data integration are addressed by ontology-driven data mapping, multiple data annotation and heterogeneous data querying, also enabling integration of the user's data. IntegromeDB integrates over 100 experimental and computational data sources relating to genomics, transcriptomics, genetics, and functional and interaction data concerning gene transcriptional regulation in eukaryotes and prokaryotes. Availability: IntegromeDB is accessible through the integrated research environment BiologicalNetworks at http://www.BiologicalNetworks.org Contact: baitaluk@sdsc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:20427517

Semantic integration of data on transcriptional regulation.

PubMed

Baitaluk, Michael; Ponomarenko, Julia

2010-07-01

Experimental and predicted data concerning gene transcriptional regulation are distributed among many heterogeneous sources. However, there are no resources to integrate these data automatically or to provide a 'one-stop shop' experience for users seeking information essential for deciphering and modeling gene regulatory networks. IntegromeDB, a semantic graph-based 'deep-web' data integration system that automatically captures, integrates and manages publicly available data concerning transcriptional regulation, as well as other relevant biological information, is proposed in this article. The problems associated with data integration are addressed by ontology-driven data mapping, multiple data annotation and heterogeneous data querying, also enabling integration of the user's data. IntegromeDB integrates over 100 experimental and computational data sources relating to genomics, transcriptomics, genetics, and functional and interaction data concerning gene transcriptional regulation in eukaryotes and prokaryotes. IntegromeDB is accessible through the integrated research environment BiologicalNetworks at http://www.BiologicalNetworks.org baitaluk@sdsc.edu Supplementary data are available at Bioinformatics online.

Full Waveform Inversion for Seismic Velocity And Anelastic Losses in Heterogeneous Structures

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

Askan, A.; /Carnegie Mellon U.; Akcelik, V.

2009-04-30

We present a least-squares optimization method for solving the nonlinear full waveform inverse problem of determining the crustal velocity and intrinsic attenuation properties of sedimentary valleys in earthquake-prone regions. Given a known earthquake source and a set of seismograms generated by the source, the inverse problem is to reconstruct the anelastic properties of a heterogeneous medium with possibly discontinuous wave velocities. The inverse problem is formulated as a constrained optimization problem, where the constraints are the partial and ordinary differential equations governing the anelastic wave propagation from the source to the receivers in the time domain. This leads to amore » variational formulation in terms of the material model plus the state variables and their adjoints. We employ a wave propagation model in which the intrinsic energy-dissipating nature of the soil medium is modeled by a set of standard linear solids. The least-squares optimization approach to inverse wave propagation presents the well-known difficulties of ill posedness and multiple minima. To overcome ill posedness, we include a total variation regularization functional in the objective function, which annihilates highly oscillatory material property components while preserving discontinuities in the medium. To treat multiple minima, we use a multilevel algorithm that solves a sequence of subproblems on increasingly finer grids with increasingly higher frequency source components to remain within the basin of attraction of the global minimum. We illustrate the methodology with high-resolution inversions for two-dimensional sedimentary models of the San Fernando Valley, under SH-wave excitation. We perform inversions for both the seismic velocity and the intrinsic attenuation using synthetic waveforms at the observer locations as pseudoobserved data.« less

Geochemistry of lavas from Taal volcano, southwestern Luzon, Philippines: evidence for multiple magma supply systems and mantle source heterogeneity

USGS Publications Warehouse

Miklius, Asta; Flower, M.F.J.; Huijsmans, J.P.P.; Mukasa, S.B.; Castillo, P.

1991-01-01

Taal lava series can be distinguished from each other by differences in major and trace element trends and trace element ratios, indicating multiple magmatic systems associated with discrete centers in time and space. On Volcano Island, contemporaneous lava series range from typically calc-alkaline to iron-enriched. Major and trace element variation in these series can be modelled by fractionation of similar assemblages, with early fractionation of titano-magnetite in less iron-enriched series. However, phase compositional and petrographic evidence of mineral-liquid disequilibrium suggests that magma mixing played an important role in the evolution of these series. -from Authors

Generation of open biomedical datasets through ontology-driven transformation and integration processes.

PubMed

Carmen Legaz-García, María Del; Miñarro-Giménez, José Antonio; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2016-06-03

Biomedical research usually requires combining large volumes of data from multiple heterogeneous sources, which makes difficult the integrated exploitation of such data. The Semantic Web paradigm offers a natural technological space for data integration and exploitation by generating content readable by machines. Linked Open Data is a Semantic Web initiative that promotes the publication and sharing of data in machine readable semantic formats. We present an approach for the transformation and integration of heterogeneous biomedical data with the objective of generating open biomedical datasets in Semantic Web formats. The transformation of the data is based on the mappings between the entities of the data schema and the ontological infrastructure that provides the meaning to the content. Our approach permits different types of mappings and includes the possibility of defining complex transformation patterns. Once the mappings are defined, they can be automatically applied to datasets to generate logically consistent content and the mappings can be reused in further transformation processes. The results of our research are (1) a common transformation and integration process for heterogeneous biomedical data; (2) the application of Linked Open Data principles to generate interoperable, open, biomedical datasets; (3) a software tool, called SWIT, that implements the approach. In this paper we also describe how we have applied SWIT in different biomedical scenarios and some lessons learned. We have presented an approach that is able to generate open biomedical repositories in Semantic Web formats. SWIT is able to apply the Linked Open Data principles in the generation of the datasets, so allowing for linking their content to external repositories and creating linked open datasets. SWIT datasets may contain data from multiple sources and schemas, thus becoming integrated datasets.

Evidence of intermetastatic heterogeneity for pathological response and genetic mutations within colorectal liver metastases following preoperative chemotherapy.

PubMed

Sebagh, Mylène; Allard, Marc-Antoine; Bosselut, Nelly; Dao, Myriam; Vibert, Eric; Lewin, Maïté; Lemoine, Antoinette; Cherqui, Daniel; Adam, René; Sa Cunha, Antonio

2016-04-19

In patients receiving preoperative chemotherapy, colorectal liver metastases (CLM) are expected to demonstrate a similar behaviour because of similar organ microenvironment and tumour cell chemosensitivity. We focused on the occurrence of pathological and genetic heterogeneity within CLM. Patients resected for multiple CLM between 2004 and 2011 after > three cycles of chemotherapy were included. Pathological heterogeneity was arbitrarily defined as a > 50% difference in the percentage of remaining tumour cells between individual CLM. In patients with pathological heterogeneity, the mutational genotyping (KRAS, NRAS, BRAF and PIK3CA) was determined from the most heterogeneous CLM. Pathological heterogeneity was observed in 31 of 157 patients with multiple CLM (median = 4, range, 2-32) (19.7%). In 72.4% of them, we found a concordance of the mutation status between the paired CLM: both wild-type in 55%, and both mutated in 17.2%. We observed a discordance of the mutation status of 27.6% between CLM: one mutated and the other wild-type. The mutated CLM was the less florid one in 75% of patients with genetic heterogeneity. Pathological heterogeneity is present in 19.7% of patients with multiple CLM. Genetic heterogeneity is present in 27.6% of patients with pathological heterogeneity. Heterogeneity could refine guide management for tissue sampling.

Organelles – understanding noise and heterogeneity in cell biology at an intermediate scale

PubMed Central

Chang, Amy Y.

2017-01-01

ABSTRACT Many studies over the years have shown that non-genetic mechanisms for producing cell-to-cell variation can lead to highly variable behaviors across genetically identical populations of cells. Most work to date has focused on gene expression noise as the primary source of phenotypic heterogeneity, yet other sources may also contribute. In this Commentary, we explore organelle-level heterogeneity as a potential secondary source of cellular ‘noise’ that contributes to phenotypic heterogeneity. We explore mechanisms for generating organelle heterogeneity and present evidence of functional links between organelle morphology and cellular behavior. Given the many instances in which molecular-level heterogeneity has been linked to phenotypic heterogeneity, we posit that organelle heterogeneity may similarly contribute to overall phenotypic heterogeneity and underline the importance of studying organelle heterogeneity to develop a more comprehensive understanding of phenotypic heterogeneity. Finally, we conclude with a discussion of the medical challenges associated with phenotypic heterogeneity and outline how improved methods for characterizing and controlling this heterogeneity may lead to improved therapeutic strategies and outcomes for patients. PMID:28183729

Determining heterogeneous slip activity on multiple slip systems from single crystal orientation pole figures

DOE PAGES

Pagan, Darren C.; Miller, Matthew P.

2016-09-01

A new experimental method to determine heterogeneity of shear strains associated with crystallographic slip in the bulk of ductile, crystalline materials is outlined. The method quantifies the time resolved evolution of misorientation within plastically deforming crystals using single crystal orientation pole figures (SCPFs) measured in-situ with X-ray diffraction. A multiplicative decomposition of the crystal kinematics is used to interpret the distributions of lattice plane orientation observed on the SCPFs in terms of heterogeneous slip activity (shear strains) on multiple slip systems. Here, to show the method’s utility, the evolution of heterogeneous slip is quantified in a silicon single crystal plasticallymore » deformed at high temperature at multiple load steps, with slip activity in sub-volumes of the crystal analyzed simultaneously.« less

Mining large heterogeneous data sets in drug discovery.

PubMed

Wild, David J

2009-10-01

Increasingly, effective drug discovery involves the searching and data mining of large volumes of information from many sources covering the domains of chemistry, biology and pharmacology amongst others. This has led to a proliferation of databases and data sources relevant to drug discovery. This paper provides a review of the publicly-available large-scale databases relevant to drug discovery, describes the kinds of data mining approaches that can be applied to them and discusses recent work in integrative data mining that looks for associations that pan multiple sources, including the use of Semantic Web techniques. The future of mining large data sets for drug discovery requires intelligent, semantic aggregation of information from all of the data sources described in this review, along with the application of advanced methods such as intelligent agents and inference engines in client applications.

Phagocytosis imprints heterogeneity in tissue-resident macrophages

PubMed Central

A-Gonzalez, Noelia; Quintana, Juan A.; Mazariegos, Marina; González de la Aleja, Arturo; Nicolás-Ávila, José A.; Crainiciuc, Georgiana; Rothlin, Carla V.; Peinado, Héctor; Castrillo, Antonio

2017-01-01

Tissue-resident macrophages display varying phenotypic and functional properties that are largely specified by their local environment. One of these functions, phagocytosis, mediates the natural disposal of billions of cells, but its mechanisms and consequences within living tissues are poorly defined. Using a parabiosis-based strategy, we identified and isolated macrophages from multiple tissues as they phagocytosed blood-borne cellular material. Phagocytosis was circadianally regulated and mediated by distinct repertoires of receptors, opsonins, and transcription factors in macrophages from each tissue. Although the tissue of residence defined the core signature of macrophages, phagocytosis imprinted a distinct antiinflammatory profile. Phagocytic macrophages expressed CD206, displayed blunted expression of Il1b, and supported tissue homeostasis. Thus, phagocytosis is a source of macrophage heterogeneity that acts together with tissue-derived factors to preserve homeostasis. PMID:28432199

Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons.

PubMed

Nicola, Wilten; Campbell, Sue Ann

2013-01-01

We analytically derive mean-field models for all-to-all coupled networks of heterogeneous, adapting, two-dimensional integrate and fire neurons. The class of models we consider includes the Izhikevich, adaptive exponential and quartic integrate and fire models. The heterogeneity in the parameters leads to different moment closure assumptions that can be made in the derivation of the mean-field model from the population density equation for the large network. Three different moment closure assumptions lead to three different mean-field systems. These systems can be used for distinct purposes such as bifurcation analysis of the large networks, prediction of steady state firing rate distributions, parameter estimation for actual neurons and faster exploration of the parameter space. We use the mean-field systems to analyze adaptation induced bursting under realistic sources of heterogeneity in multiple parameters. Our analysis demonstrates that the presence of heterogeneity causes the Hopf bifurcation associated with the emergence of bursting to change from sub-critical to super-critical. This is confirmed with numerical simulations of the full network for biologically reasonable parameter values. This change decreases the plausibility of adaptation being the cause of bursting in hippocampal area CA3, an area with a sizable population of heavily coupled, strongly adapting neurons.

Mean-field models for heterogeneous networks of two-dimensional integrate and fire neurons

PubMed Central

Nicola, Wilten; Campbell, Sue Ann

2013-01-01

We analytically derive mean-field models for all-to-all coupled networks of heterogeneous, adapting, two-dimensional integrate and fire neurons. The class of models we consider includes the Izhikevich, adaptive exponential and quartic integrate and fire models. The heterogeneity in the parameters leads to different moment closure assumptions that can be made in the derivation of the mean-field model from the population density equation for the large network. Three different moment closure assumptions lead to three different mean-field systems. These systems can be used for distinct purposes such as bifurcation analysis of the large networks, prediction of steady state firing rate distributions, parameter estimation for actual neurons and faster exploration of the parameter space. We use the mean-field systems to analyze adaptation induced bursting under realistic sources of heterogeneity in multiple parameters. Our analysis demonstrates that the presence of heterogeneity causes the Hopf bifurcation associated with the emergence of bursting to change from sub-critical to super-critical. This is confirmed with numerical simulations of the full network for biologically reasonable parameter values. This change decreases the plausibility of adaptation being the cause of bursting in hippocampal area CA3, an area with a sizable population of heavily coupled, strongly adapting neurons. PMID:24416013

Micro-heterogeneity of corn hulls cellulosic fiber biopolymer studied by multiple-particle tracking (MPT)

USDA-ARS?s Scientific Manuscript database

A novel technique named multiple-particle tracking (MPT) was used to investigate the micro-structural heterogeneities of Z-trim, a zero calorie cellulosic fiber biopolymer produced from corn hulls. The Multiple-Particle Tracking (MPT) method was used in this study, which was originally described by ...

An Extension of Multiple Correspondence Analysis for Identifying Heterogeneous Subgroups of Respondents

ERIC Educational Resources Information Center

Hwang, Heungsun; Montreal, Hec; Dillon, William R.; Takane, Yoshio

2006-01-01

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

Stochastic Cell Fate Progression in Embryonic Stem Cells

NASA Astrophysics Data System (ADS)

Zou, Ling-Nan; Doyle, Adele; Jang, Sumin; Ramanathan, Sharad

2013-03-01

Studies on the directed differentiation of embryonic stem (ES) cells suggest that some early developmental decisions may be stochastic in nature. To identify the sources of this stochasticity, we analyzed the heterogeneous expression of key transcription factors in single ES cells as they adopt distinct germ layer fates. We find that under sufficiently stringent signaling conditions, the choice of lineage is unambiguous. ES cells flow into differentiated fates via diverging paths, defined by sequences of transitional states that exhibit characteristic co-expression of multiple transcription factors. These transitional states have distinct responses to morphogenic stimuli; by sequential exposure to multiple signaling conditions, ES cells are steered towards specific fates. However, the rate at which cells travel down a developmental path is stochastic: cells exposed to the same signaling condition for the same amount of time can populate different states along the same path. The heterogeneity of cell states seen in our experiments therefore does not reflect the stochastic selection of germ layer fates, but the stochastic rate of progression along a chosen developmental path. Supported in part by the Jane Coffin Childs Fund

Effect of the heterogeneous neuron and information transmission delay on stochastic resonance of neuronal networks

NASA Astrophysics Data System (ADS)

Wang, Qingyun; Zhang, Honghui; Chen, Guanrong

2012-12-01

We study the effect of heterogeneous neuron and information transmission delay on stochastic resonance of scale-free neuronal networks. For this purpose, we introduce the heterogeneity to the specified neuron with the highest degree. It is shown that in the absence of delay, an intermediate noise level can optimally assist spike firings of collective neurons so as to achieve stochastic resonance on scale-free neuronal networks for small and intermediate αh, which plays a heterogeneous role. Maxima of stochastic resonance measure are enhanced as αh increases, which implies that the heterogeneity can improve stochastic resonance. However, as αh is beyond a certain large value, no obvious stochastic resonance can be observed. If the information transmission delay is introduced to neuronal networks, stochastic resonance is dramatically affected. In particular, the tuned information transmission delay can induce multiple stochastic resonance, which can be manifested as well-expressed maximum in the measure for stochastic resonance, appearing every multiple of one half of the subthreshold stimulus period. Furthermore, we can observe that stochastic resonance at odd multiple of one half of the subthreshold stimulus period is subharmonic, as opposed to the case of even multiple of one half of the subthreshold stimulus period. More interestingly, multiple stochastic resonance can also be improved by the suitable heterogeneous neuron. Presented results can provide good insights into the understanding of the heterogeneous neuron and information transmission delay on realistic neuronal networks.

Predictive Big Data Analytics: A Study of Parkinson's Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations.

PubMed

Dinov, Ivo D; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W; Price, Nathan D; Van Horn, John D; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M; Dauer, William; Toga, Arthur W

2016-01-01

A unique archive of Big Data on Parkinson's Disease is collected, managed and disseminated by the Parkinson's Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson's disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data-large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources-all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson's disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson's disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer's, Huntington's, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications.

Rapid heterogeneous assembly of multiple magma reservoirs prior to Yellowstone supereruptions.

PubMed

Wotzlaw, Jörn-Frederik; Bindeman, Ilya N; Stern, Richard A; D'Abzac, Francois-Xavier; Schaltegger, Urs

2015-09-10

Large-volume caldera-forming eruptions of silicic magmas are an important feature of continental volcanism. The timescales and mechanisms of assembly of the magma reservoirs that feed such eruptions as well as the durations and physical conditions of upper-crustal storage remain highly debated topics in volcanology. Here we explore a comprehensive data set of isotopic (O, Hf) and chemical proxies in precisely U-Pb dated zircon crystals from all caldera-forming eruptions of Yellowstone supervolcano. Analysed zircons record rapid assembly of multiple magma reservoirs by repeated injections of isotopically heterogeneous magma batches and short pre-eruption storage times of 10(3) to 10(4) years. Decoupled oxygen-hafnium isotope systematics suggest a complex source for these magmas involving variable amounts of differentiated mantle-derived melt, Archean crust and hydrothermally altered shallow-crustal rocks. These data demonstrate that complex magma reservoirs with multiple sub-chambers are a common feature of rift- and hotspot related supervolcanoes. The short duration of reservoir assembly documents rapid crustal remelting and two to three orders of magnitude higher magma production rates beneath Yellowstone compared to continental arc volcanoes. The short pre-eruption storage times further suggest that the detection of voluminous reservoirs of eruptible magma beneath active supervolcanoes may only be possible prior to an impending eruption.

Rapid heterogeneous assembly of multiple magma reservoirs prior to Yellowstone supereruptions

PubMed Central

Wotzlaw, Jörn-Frederik; Bindeman, Ilya N.; Stern, Richard A.; D’Abzac, Francois-Xavier; Schaltegger, Urs

2015-01-01

Large-volume caldera-forming eruptions of silicic magmas are an important feature of continental volcanism. The timescales and mechanisms of assembly of the magma reservoirs that feed such eruptions as well as the durations and physical conditions of upper-crustal storage remain highly debated topics in volcanology. Here we explore a comprehensive data set of isotopic (O, Hf) and chemical proxies in precisely U-Pb dated zircon crystals from all caldera-forming eruptions of Yellowstone supervolcano. Analysed zircons record rapid assembly of multiple magma reservoirs by repeated injections of isotopically heterogeneous magma batches and short pre-eruption storage times of 103 to 104 years. Decoupled oxygen-hafnium isotope systematics suggest a complex source for these magmas involving variable amounts of differentiated mantle-derived melt, Archean crust and hydrothermally altered shallow-crustal rocks. These data demonstrate that complex magma reservoirs with multiple sub-chambers are a common feature of rift- and hotspot related supervolcanoes. The short duration of reservoir assembly documents rapid crustal remelting and two to three orders of magnitude higher magma production rates beneath Yellowstone compared to continental arc volcanoes. The short pre-eruption storage times further suggest that the detection of voluminous reservoirs of eruptible magma beneath active supervolcanoes may only be possible prior to an impending eruption. PMID:26356304

Evidence for nucleosynthetic enrichment of the protosolar molecular cloud core by multiple supernova events.

PubMed

Schiller, Martin; Paton, Chad; Bizzarro, Martin

2015-01-15

The presence of isotope heterogeneity of nucleosynthetic origin amongst meteorites and their components provides a record of the diverse stars that contributed matter to the protosolar molecular cloud core. Understanding how and when the solar system's nucleosynthetic heterogeneity was established and preserved within the solar protoplanetary disk is critical for unraveling the earliest formative stages of the solar system. Here, we report calcium and magnesium isotope measurements of primitive and differentiated meteorites as well as various types of refractory inclusions, including refractory inclusions (CAIs) formed with the canonical 26 Al/ 27 Al of ~5 × 10 -5 ( 26 Al decays to 26 Mg with a half-life of ~0.73 Ma) and CAIs that show fractionated and unidentified nuclear effects (FUN-CAIs) to understand the origin of the solar system's nucleosynthetic heterogeneity. Bulk analyses of primitive and differentiated meteorites along with canonical and FUN-CAIs define correlated, mass-independent variations in 43 Ca, 46 Ca and 48 Ca. Moreover, sequential dissolution experiments of the Ivuna carbonaceous chondrite aimed at identifying the nature and number of presolar carriers of isotope anomalies within primitive meteorites have detected the presence of multiple carriers of the short-lived 26 Al nuclide as well as carriers of anomalous and uncorrelated 43 Ca, 46 Ca and 48 Ca compositions, which requires input from multiple and recent supernovae sources. We infer that the solar system's correlated nucleosynthetic variability reflects unmixing of old, galactically-inherited homogeneous dust from a new, supernovae-derived dust component formed shortly prior to or during the evolution of the giant molecular cloud parental to the protosolar molecular cloud core. This implies that similarly to 43 Ca, 46 Ca and 48 Ca, the short-lived 26 Al nuclide was heterogeneously distributed in the inner solar system at the time of CAI formation.

Competitive-Cooperative Automated Reasoning from Distributed and Multiple Source of Data

NASA Astrophysics Data System (ADS)

Fard, Amin Milani

Knowledge extraction from distributed database systems, have been investigated during past decade in order to analyze billions of information records. In this work a competitive deduction approach in a heterogeneous data grid environment is proposed using classic data mining and statistical methods. By applying a game theory concept in a multi-agent model, we tried to design a policy for hierarchical knowledge discovery and inference fusion. To show the system run, a sample multi-expert system has also been developed.

Transparent mediation-based access to multiple yeast data sources using an ontology driven interface.

PubMed

Briache, Abdelaali; Marrakchi, Kamar; Kerzazi, Amine; Navas-Delgado, Ismael; Rossi Hassani, Badr D; Lairini, Khalid; Aldana-Montes, José F

2012-01-25

Saccharomyces cerevisiae is recognized as a model system representing a simple eukaryote whose genome can be easily manipulated. Information solicited by scientists on its biological entities (Proteins, Genes, RNAs...) is scattered within several data sources like SGD, Yeastract, CYGD-MIPS, BioGrid, PhosphoGrid, etc. Because of the heterogeneity of these sources, querying them separately and then manually combining the returned results is a complex and time-consuming task for biologists most of whom are not bioinformatics expert. It also reduces and limits the use that can be made on the available data. To provide transparent and simultaneous access to yeast sources, we have developed YeastMed: an XML and mediator-based system. In this paper, we present our approach in developing this system which takes advantage of SB-KOM to perform the query transformation needed and a set of Data Services to reach the integrated data sources. The system is composed of a set of modules that depend heavily on XML and Semantic Web technologies. User queries are expressed in terms of a domain ontology through a simple form-based web interface. YeastMed is the first mediation-based system specific for integrating yeast data sources. It was conceived mainly to help biologists to find simultaneously relevant data from multiple data sources. It has a biologist-friendly interface easy to use. The system is available at http://www.khaos.uma.es/yeastmed/.

K-Rich Basaltic Sources beneath Ultraslow Spreading Central Lena Trough in the Arctic Ocean

NASA Astrophysics Data System (ADS)

Ling, X.; Snow, J. E.; Li, Y.

2016-12-01

Magma sources fundamentally influence accretion processes at ultraslow spreading ridges. Potassium enriched Mid-Ocean Ridge Basalt (K-MORB) was dredged from the central Lena Trough (CLT) in the Arctic Ocean (Nauret et al., 2011). Its geochemical signatures indicate a heterogeneous mantle source with probable garnet present under low pressure. To explore the basaltic mantle sources beneath the study area, multiple models are carried out predicting melting sources and melting P-T conditions in this study. P-T conditions are estimated by the experimental derived thermobarometer from Hoang and Flower (1998). Batch melting model and major element model (AlphaMELTs) are used to calculate the heterogeneous mantle sources. The modeling suggests phlogopite is the dominant H2O-K bearing mineral in the magma source. 5% partial melting of phlogopite and amphibole mixing with depleted mantle (DM) melt is consistent with the incompatible element pattern of CLT basalt. P-T estimation shows 1198-1212oC/4-7kbar as the possible melting condition for CLT basalt. Whereas the chemical composition of north Lena Trough (NLT) basalt is similar to N-MORB, and the P-T estimation corresponds to 1300oC normal mantle adiabat. The CLT basalt bulk composition is of mixture of 40% of the K-MORB endmember and an N-MORB-like endmember similar to NLT basalt. Therefore the binary mixing of the two endmembers exists in the CLT region. This kind of mixing infers to the tectonic evolution of the region, which is simultaneous to the Arctic Ocean opening.

A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems

DOE PAGES

Song, Fengguang; Dongarra, Jack

2014-10-01

Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less

A scalable approach to solving dense linear algebra problems on hybrid CPU-GPU systems

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

Song, Fengguang; Dongarra, Jack

Aiming to fully exploit the computing power of all CPUs and all graphics processing units (GPUs) on hybrid CPU-GPU systems to solve dense linear algebra problems, in this paper we design a class of heterogeneous tile algorithms to maximize the degree of parallelism, to minimize the communication volume, and to accommodate the heterogeneity between CPUs and GPUs. The new heterogeneous tile algorithms are executed upon our decentralized dynamic scheduling runtime system, which schedules a task graph dynamically and transfers data between compute nodes automatically. The runtime system uses a new distributed task assignment protocol to solve data dependencies between tasksmore » without any coordination between processing units. By overlapping computation and communication through dynamic scheduling, we are able to attain scalable performance for the double-precision Cholesky factorization and QR factorization. Finally, our approach demonstrates a performance comparable to Intel MKL on shared-memory multicore systems and better performance than both vendor (e.g., Intel MKL) and open source libraries (e.g., StarPU) in the following three environments: heterogeneous clusters with GPUs, conventional clusters without GPUs, and shared-memory systems with multiple GPUs.« less

SIMS: addressing the problem of heterogeneity in databases

NASA Astrophysics Data System (ADS)

Arens, Yigal

1997-02-01

The heterogeneity of remotely accessible databases -- with respect to contents, query language, semantics, organization, etc. -- presents serious obstacles to convenient querying. The SIMS (single interface to multiple sources) system addresses this global integration problem. It does so by defining a single language for describing the domain about which information is stored in the databases and using this language as the query language. Each database to which SIMS is to provide access is modeled using this language. The model describes a database's contents, organization, and other relevant features. SIMS uses these models, together with a planning system drawing on techniques from artificial intelligence, to decompose a given user's high-level query into a series of queries against the databases and other data manipulation steps. The retrieval plan is constructed so as to minimize data movement over the network and maximize parallelism to increase execution speed. SIMS can recover from network failures during plan execution by obtaining data from alternate sources, when possible. SIMS has been demonstrated in the domains of medical informatics and logistics, using real databases.

Heterogeneous classifier fusion for ligand-based virtual screening: or, how decision making by committee can be a good thing.

PubMed

Riniker, Sereina; Fechner, Nikolas; Landrum, Gregory A

2013-11-25

The concept of data fusion - the combination of information from different sources describing the same object with the expectation to generate a more accurate representation - has found application in a very broad range of disciplines. In the context of ligand-based virtual screening (VS), data fusion has been applied to combine knowledge from either different active molecules or different fingerprints to improve similarity search performance. Machine-learning (ML) methods based on fusion of multiple homogeneous classifiers, in particular random forests, have also been widely applied in the ML literature. The heterogeneous version of classifier fusion - fusing the predictions from different model types - has been less explored. Here, we investigate heterogeneous classifier fusion for ligand-based VS using three different ML methods, RF, naïve Bayes (NB), and logistic regression (LR), with four 2D fingerprints, atom pairs, topological torsions, RDKit fingerprint, and circular fingerprint. The methods are compared using a previously developed benchmarking platform for 2D fingerprints which is extended to ML methods in this article. The original data sets are filtered for difficulty, and a new set of challenging data sets from ChEMBL is added. Data sets were also generated for a second use case: starting from a small set of related actives instead of diverse actives. The final fused model consistently outperforms the other approaches across the broad variety of targets studied, indicating that heterogeneous classifier fusion is a very promising approach for ligand-based VS. The new data sets together with the adapted source code for ML methods are provided in the Supporting Information .

Effect of distance-related heterogeneity on population size estimates from point counts

USGS Publications Warehouse

Efford, Murray G.; Dawson, Deanna K.

2009-01-01

Point counts are used widely to index bird populations. Variation in the proportion of birds counted is a known source of error, and for robust inference it has been advocated that counts be converted to estimates of absolute population size. We used simulation to assess nine methods for the conduct and analysis of point counts when the data included distance-related heterogeneity of individual detection probability. Distance from the observer is a ubiquitous source of heterogeneity, because nearby birds are more easily detected than distant ones. Several recent methods (dependent double-observer, time of first detection, time of detection, independent multiple-observer, and repeated counts) do not account for distance-related heterogeneity, at least in their simpler forms. We assessed bias in estimates of population size by simulating counts with fixed radius w over four time intervals (occasions). Detection probability per occasion was modeled as a half-normal function of distance with scale parameter sigma and intercept g(0) = 1.0. Bias varied with sigma/w; values of sigma inferred from published studies were often 50% for a 100-m fixed-radius count. More critically, the bias of adjusted counts sometimes varied more than that of unadjusted counts, and inference from adjusted counts would be less robust. The problem was not solved by using mixture models or including distance as a covariate. Conventional distance sampling performed well in simulations, but its assumptions are difficult to meet in the field. We conclude that no existing method allows effective estimation of population size from point counts.

ProphTools: general prioritization tools for heterogeneous biological networks.

PubMed

Navarro, Carmen; Martínez, Victor; Blanco, Armando; Cano, Carlos

2017-12-01

Networks have been proven effective representations for the analysis of biological data. As such, there exist multiple methods to extract knowledge from biological networks. However, these approaches usually limit their scope to a single biological entity type of interest or they lack the flexibility to analyze user-defined data. We developed ProphTools, a flexible open-source command-line tool that performs prioritization on a heterogeneous network. ProphTools prioritization combines a Flow Propagation algorithm similar to a Random Walk with Restarts and a weighted propagation method. A flexible model for the representation of a heterogeneous network allows the user to define a prioritization problem involving an arbitrary number of entity types and their interconnections. Furthermore, ProphTools provides functionality to perform cross-validation tests, allowing users to select the best network configuration for a given problem. ProphTools core prioritization methodology has already been proven effective in gene-disease prioritization and drug repositioning. Here we make ProphTools available to the scientific community as flexible, open-source software and perform a new proof-of-concept case study on long noncoding RNAs (lncRNAs) to disease prioritization. ProphTools is robust prioritization software that provides the flexibility not present in other state-of-the-art network analysis approaches, enabling researchers to perform prioritization tasks on any user-defined heterogeneous network. Furthermore, the application to lncRNA-disease prioritization shows that ProphTools can reach the performance levels of ad hoc prioritization tools without losing its generality. © The Authors 2017. Published by Oxford University Press.

Multiple Spatial Coherence Resonances and Spatial Patterns in a Noise-Driven Heterogeneous Neuronal Network

NASA Astrophysics Data System (ADS)

Li, Yu-Ye; Ding, Xue-Li

2014-12-01

Heterogeneity of the neurons and noise are inevitable in the real neuronal network. In this paper, Gaussian white noise induced spatial patterns including spiral waves and multiple spatial coherence resonances are studied in a network composed of Morris—Lecar neurons with heterogeneity characterized by parameter diversity. The relationship between the resonances and the transitions between ordered spiral waves and disordered spatial patterns are achieved. When parameter diversity is introduced, the maxima of multiple resonances increases first, and then decreases as diversity strength increases, which implies that the coherence degrees induced by noise are enhanced at an intermediate diversity strength. The synchronization degree of spatial patterns including ordered spiral waves and disordered patterns is identified to be a very low level. The results suggest that the nervous system can profit from both heterogeneity and noise, and the multiple spatial coherence resonances are achieved via the emergency of spiral waves instead of synchronization patterns.

Hurricane Harvey Riverine Flooding: Part 2: Integration of Heterogeneous Earth Observation Data for Comparative Analysis with High-Resolution Inundation Boundaries Reconstructed from Flood2D-GPU Model

NASA Astrophysics Data System (ADS)

Jackson, C.; Sava, E.; Cervone, G.

2017-12-01

Hurricane Harvey has been noted as the wettest cyclone on record for the US as well as the most destructive (so far) for the 2017 hurricane season. An entire year worth of rainfall occurred over the course of a few days. The city of Houston was greatly impacted as the storm lingered over the city for five days, causing a record-breaking 50+ inches of rain as well as severe damage from flooding. Flood model simulations were performed to reconstruct the event in order to better understand, assess, and predict flooding dynamics for the future. Additionally, number of remote sensing platforms, and on ground instruments that provide near real-time data have also been used for flood identification, monitoring, and damage assessment. Although both flood models and remote sensing techniques are able to identify inundated areas, rapid and accurate flood prediction at a high spatio-temporal resolution remains a challenge. Thus a methodological approach which fuses the two techniques can help to better validate what is being modeled and observed. Recent advancements in data fusion techniques of remote sensing with near real time heterogeneous datasets have allowed emergency responders to more efficiently extract increasingly precise and relevant knowledge from the available information. In this work the use of multiple sources of contributed data, coupled with remotely sensed and open source geospatial datasets is demonstrated to generate an understanding of potential damage assessment for the floods after Hurricane Harvey in Harris County, Texas. The feasibility of integrating multiple sources at different temporal and spatial resolutions into hydrodynamic models for flood inundation simulations is assessed. Furthermore the contributed datasets are compared against a reconstructed flood extent generated from the Flood2D-GPU model.

Integrating heterogeneous earth observation data for assessment of high-resolution inundation boundaries generated during flood emergencies.

NASA Astrophysics Data System (ADS)

Sava, E.; Cervone, G.; Kalyanapu, A. J.; Sampson, K. M.

2017-12-01

The increasing trend in flooding events, paired with rapid urbanization and an aging infrastructure is projected to enhance the risk of catastrophic losses and increase the frequency of both flash and large area floods. During such events, it is critical for decision makers and emergency responders to have access to timely actionable knowledge regarding preparedness, emergency response, and recovery before, during and after a disaster. Large volumes of data sets derived from sophisticated sensors, mobile phones, and social media feeds are increasingly being used to improve citizen services and provide clues to the best way to respond to emergencies through the use of visualization and GIS mapping. Such data, coupled with recent advancements in data fusion techniques of remote sensing with near real time heterogeneous datasets have allowed decision makers to more efficiently extract precise and relevant knowledge and better understand how damage caused by disasters have real time effects on urban population. This research assesses the feasibility of integrating multiple sources of contributed data into hydrodynamic models for flood inundation simulation and estimating damage assessment. It integrates multiple sources of high-resolution physiographic data such as satellite remote sensing imagery coupled with non-authoritative data such as Civil Air Patrol (CAP) and `during-event' social media observations of flood inundation in order to improve the identification of flood mapping. The goal is to augment remote sensing imagery with new open-source datasets to generate flood extend maps at higher temporal and spatial resolution. The proposed methodology is applied on two test cases, relative to the 2013 Boulder Colorado flood and the 2015 floods in Texas.

Lessons learned in the generation of biomedical research datasets using Semantic Open Data technologies.

PubMed

Legaz-García, María del Carmen; Miñarro-Giménez, José Antonio; Menárguez-Tortosa, Marcos; Fernández-Breis, Jesualdo Tomás

2015-01-01

Biomedical research usually requires combining large volumes of data from multiple heterogeneous sources. Such heterogeneity makes difficult not only the generation of research-oriented dataset but also its exploitation. In recent years, the Open Data paradigm has proposed new ways for making data available in ways that sharing and integration are facilitated. Open Data approaches may pursue the generation of content readable only by humans and by both humans and machines, which are the ones of interest in our work. The Semantic Web provides a natural technological space for data integration and exploitation and offers a range of technologies for generating not only Open Datasets but also Linked Datasets, that is, open datasets linked to other open datasets. According to the Berners-Lee's classification, each open dataset can be given a rating between one and five stars attending to can be given to each dataset. In the last years, we have developed and applied our SWIT tool, which automates the generation of semantic datasets from heterogeneous data sources. SWIT produces four stars datasets, given that fifth one can be obtained by being the dataset linked from external ones. In this paper, we describe how we have applied the tool in two projects related to health care records and orthology data, as well as the major lessons learned from such efforts.

Predicting Lg Coda Using Synthetic Seismograms and Media With Stochastic Heterogeneity

NASA Astrophysics Data System (ADS)

Tibuleac, I. M.; Stroujkova, A.; Bonner, J. L.; Mayeda, K.

2005-12-01

Recent examinations of the characteristics of coda-derived Sn and Lg spectra for yield estimation have shown that the spectral peak of Nevada Test Site (NTS) explosion spectra is depth-of-burial dependent, and that this peak is shifted to higher frequencies for Lop Nor explosions at the same depths. To confidently use coda-based yield formulas, we need to understand and predict coda spectral shape variations with depth, source media, velocity structure, topography, and geological heterogeneity. We present results of a coda modeling study to predict Lg coda. During the initial stages of this research, we have acquired and parameterized a deterministic 6 deg. x 6 deg. velocity and attenuation model centered on the Nevada Test Site. Near-source data are used to constrain density and attenuation profiles for the upper five km. The upper crust velocity profiles are quilted into a background velocity profile at depths greater than five km. The model is parameterized for use in a modified version of the Generalized Fourier Method in two dimensions (GFM2D). We modify this model to include stochastic heterogeneities of varying correlation lengths within the crust. Correlation length, Hurst number and fractional velocity perturbation of the heterogeneities are used to construct different realizations of the random media. We use nuclear explosion and earthquake cluster waveform analysis, as well as well log and geological information to constrain the stochastic parameters for a path between the NTS and the seismic stations near Mina, Nevada. Using multiple runs, we quantify the effects of variations in the stochastic parameters, of heterogeneity location in the crust and attenuation on coda amplitude and spectral characteristics. We calibrate these parameters by matching synthetic earthquake Lg coda envelopes to coda envelopes of local earthquakes with well-defined moments and mechanisms. We generate explosion synthetics for these calibrated deterministic and stochastic models. Secondary effects, including a compensated linear vector dipole source, are superposed on the synthetics in order to adequately characterize the Lg generation. We use this technique to characterize the effects of depth of burial on the coda spectral shapes.

Mach wave properties in the presence of source and medium heterogeneity

NASA Astrophysics Data System (ADS)

Vyas, J. C.; Mai, P. M.; Galis, M.; Dunham, Eric M.; Imperatori, W.

2018-06-01

We investigate Mach wave coherence for kinematic supershear ruptures with spatially heterogeneous source parameters, embedded in 3D scattering media. We assess Mach wave coherence considering: 1) source heterogeneities in terms of variations in slip, rise time and rupture speed; 2) small-scale heterogeneities in Earth structure, parameterized from combinations of three correlation lengths and two standard deviations (assuming von Karman power spectral density with fixed Hurst exponent); and 3) joint effects of source and medium heterogeneities. Ground-motion simulations are conducted using a generalized finite-difference method, choosing a parameterization such that the highest resolved frequency is ˜5 Hz. We discover that Mach wave coherence is slightly diminished at near fault distances (< 10 km) due to spatially variable slip and rise time; beyond this distance the Mach wave coherence is more strongly reduced by wavefield scattering due to small-scale heterogeneities in Earth structure. Based on our numerical simulations and theoretical considerations we demonstrate that the standard deviation of medium heterogeneities controls the wavefield scattering, rather than the correlation length. In addition, we find that peak ground accelerations in the case of combined source and medium heterogeneities are consistent with empirical ground motion prediction equations for all distances, suggesting that in nature ground shaking amplitudes for supershear ruptures may not be elevated due to complexities in the rupture process and seismic wave-scattering.

Modeling and interoperability of heterogeneous genomic big data for integrative processing and querying.

PubMed

Masseroli, Marco; Kaitoua, Abdulrahman; Pinoli, Pietro; Ceri, Stefano

2016-12-01

While a huge amount of (epi)genomic data of multiple types is becoming available by using Next Generation Sequencing (NGS) technologies, the most important emerging problem is the so-called tertiary analysis, concerned with sense making, e.g., discovering how different (epi)genomic regions and their products interact and cooperate with each other. We propose a paradigm shift in tertiary analysis, based on the use of the Genomic Data Model (GDM), a simple data model which links genomic feature data to their associated experimental, biological and clinical metadata. GDM encompasses all the data formats which have been produced for feature extraction from (epi)genomic datasets. We specifically describe the mapping to GDM of SAM (Sequence Alignment/Map), VCF (Variant Call Format), NARROWPEAK (for called peaks produced by NGS ChIP-seq or DNase-seq methods), and BED (Browser Extensible Data) formats, but GDM supports as well all the formats describing experimental datasets (e.g., including copy number variations, DNA somatic mutations, or gene expressions) and annotations (e.g., regarding transcription start sites, genes, enhancers or CpG islands). We downloaded and integrated samples of all the above-mentioned data types and formats from multiple sources. The GDM is able to homogeneously describe semantically heterogeneous data and makes the ground for providing data interoperability, e.g., achieved through the GenoMetric Query Language (GMQL), a high-level, declarative query language for genomic big data. The combined use of the data model and the query language allows comprehensive processing of multiple heterogeneous data, and supports the development of domain-specific data-driven computations and bio-molecular knowledge discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Application of multiple tracers (SF6 and chloride) to identify the transport by characteristics of contaminant at two separate contaminated sites

NASA Astrophysics Data System (ADS)

Lee, K. K.; Lee, S. S.; Kim, H. H.; Koh, E. H.; Kim, M. O.; Lee, K.; Kim, H. J.

2016-12-01

Multiple tracers were applied for source and pathway detection at two different sites. CO2 gas injected in the subsurface for a shallow-depth CO2 injection and leak test can be regarded as a potential contaminant source. Therefore, it is necessary to identify the migration pattern of CO2 gas. Also, at a DNAPL contaminated site, it is important to figure out the characteristics of plume evolution from the source zone. In this study, multiple tracers (SF6 and chloride) were used to evaluate the applicability of volatile and non-volatile tracers and to identify the characteristics of contaminant transport at each CO2 injection and leak test site and DNAPL contaminated site. Firstly, at the CO2 test site, multiple tracers were used to perform the single well push-drift-pull tracer test at total 3 specific depth zones. As results of tests, volatile and non-volatile tracers showed different mass recovery percentage. Most of chloride mass was recovered but less than half of SF6 mass was recovered due to volatile property. This means that only gaseous SF6 leak out to unsaturated zone. However, breakthrough curves of both tracers indicated similar peak time, effective porosity, and regional groundwater velocity. Also, at both contaminated sites, natural gradient tracer tests were performed with multiple tracers. With the results of natural gradient tracer test, it was possible to confirm the applicability of multiple tracers and to understand the contaminant transport in highly heterogeneous aquifer systems through the long-term monitoring of tracers. Acknowledgement: financial support was provided by the R&D Project on Environmental Management of Geologic CO2 Storage)" from the KEITI (Project Number: 2014001810003) and Korea Ministry of Environment as "The GAIA project (2014000540010)".

Linking transcriptional and genetic tumor heterogeneity through allele analysis of single-cell RNA-seq data.

PubMed

Fan, Jean; Lee, Hae-Ock; Lee, Soohyun; Ryu, Da-Eun; Lee, Semin; Xue, Catherine; Kim, Seok Jin; Kim, Kihyun; Barkas, Nikolas; Park, Peter J; Park, Woong-Yang; Kharchenko, Peter V

2018-06-13

Characterization of intratumoral heterogeneity is critical to cancer therapy, as presence of phenotypically diverse cell populations commonly fuels relapse and resistance to treatment. Although genetic variation is a well-studied source of intratumoral heterogeneity, the functional impact of most genetic alterations remains unclear. Even less understood is the relative importance of other factors influencing heterogeneity, such as epigenetic state or tumor microenvironment. To investigate the relationship between genetic and transcriptional heterogeneity in a context of cancer progression, we devised a computational approach called HoneyBADGER to identify copy number variation and loss-of-heterozygosity in individual cells from single-cell RNA-sequencing data. By integrating allele and normalized expression information, HoneyBADGER is able to identify and infer the presence of subclone-specific alterations in individual cells and reconstruct underlying subclonal architecture. Examining several tumor types, we show that HoneyBADGER is effective at identifying deletion, amplifications, and copy-neutral loss-of-heterozygosity events, and is capable of robustly identifying subclonal focal alterations as small as 10 megabases. We further apply HoneyBADGER to analyze single cells from a progressive multiple myeloma patient to identify major genetic subclones that exhibit distinct transcriptional signatures relevant to cancer progression. Surprisingly, other prominent transcriptional subpopulations within these tumors did not line up with the genetic subclonal structure, and were likely driven by alternative, non-clonal mechanisms. These results highlight the need for integrative analysis to understand the molecular and phenotypic heterogeneity in cancer. Published by Cold Spring Harbor Laboratory Press.

Effects of pore-scale dispersion, degree of heterogeneity, sampling size, and source volume on the concentration moments of conservative solutes in heterogeneous formations

Treesearch

Daniele Tonina; Alberto Bellin

2008-01-01

Pore-scale dispersion (PSD), aquifer heterogeneity, sampling volume, and source size influence solute concentrations of conservative tracers transported in heterogeneous porous formations. In this work, we developed a new set of analytical solutions for the concentration ensemble mean, variance, and coefficient of variation (CV), which consider the effects of all these...

Quantifying geological uncertainty for flow and transport modeling in multi-modal heterogeneous formations

NASA Astrophysics Data System (ADS)

Feyen, Luc; Caers, Jef

2006-06-01

In this work, we address the problem of characterizing the heterogeneity and uncertainty of hydraulic properties for complex geological settings. Hereby, we distinguish between two scales of heterogeneity, namely the hydrofacies structure and the intrafacies variability of the hydraulic properties. We employ multiple-point geostatistics to characterize the hydrofacies architecture. The multiple-point statistics are borrowed from a training image that is designed to reflect the prior geological conceptualization. The intrafacies variability of the hydraulic properties is represented using conventional two-point correlation methods, more precisely, spatial covariance models under a multi-Gaussian spatial law. We address the different levels and sources of uncertainty in characterizing the subsurface heterogeneity, and explore their effect on groundwater flow and transport predictions. Typically, uncertainty is assessed by way of many images, termed realizations, of a fixed statistical model. However, in many cases, sampling from a fixed stochastic model does not adequately represent the space of uncertainty. It neglects the uncertainty related to the selection of the stochastic model and the estimation of its input parameters. We acknowledge the uncertainty inherent in the definition of the prior conceptual model of aquifer architecture and in the estimation of global statistics, anisotropy, and correlation scales. Spatial bootstrap is used to assess the uncertainty of the unknown statistical parameters. As an illustrative example, we employ a synthetic field that represents a fluvial setting consisting of an interconnected network of channel sands embedded within finer-grained floodplain material. For this highly non-stationary setting we quantify the groundwater flow and transport model prediction uncertainty for various levels of hydrogeological uncertainty. Results indicate the importance of accurately describing the facies geometry, especially for transport predictions.

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories

PubMed Central

Neu, Scott C.; Crawford, Karen L.; Toga, Arthur W.

2012-01-01

Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead. PMID:22470336

Metainference: A Bayesian inference method for heterogeneous systems.

PubMed

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called "metainference," that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors.

Practical management of heterogeneous neuroimaging metadata by global neuroimaging data repositories.

PubMed

Neu, Scott C; Crawford, Karen L; Toga, Arthur W

2012-01-01

Rapidly evolving neuroimaging techniques are producing unprecedented quantities of digital data at the same time that many research studies are evolving into global, multi-disciplinary collaborations between geographically distributed scientists. While networked computers have made it almost trivial to transmit data across long distances, collecting and analyzing this data requires extensive metadata if the data is to be maximally shared. Though it is typically straightforward to encode text and numerical values into files and send content between different locations, it is often difficult to attach context and implicit assumptions to the content. As the number of and geographic separation between data contributors grows to national and global scales, the heterogeneity of the collected metadata increases and conformance to a single standardization becomes implausible. Neuroimaging data repositories must then not only accumulate data but must also consolidate disparate metadata into an integrated view. In this article, using specific examples from our experiences, we demonstrate how standardization alone cannot achieve full integration of neuroimaging data from multiple heterogeneous sources and why a fundamental change in the architecture of neuroimaging data repositories is needed instead.

Markov logic network based complex event detection under uncertainty

NASA Astrophysics Data System (ADS)

Lu, Jingyang; Jia, Bin; Chen, Genshe; Chen, Hua-mei; Sullivan, Nichole; Pham, Khanh; Blasch, Erik

2018-05-01

In a cognitive reasoning system, the four-stage Observe-Orient-Decision-Act (OODA) reasoning loop is of interest. The OODA loop is essential for the situational awareness especially in heterogeneous data fusion. Cognitive reasoning for making decisions can take advantage of different formats of information such as symbolic observations, various real-world sensor readings, or the relationship between intelligent modalities. Markov Logic Network (MLN) provides mathematically sound technique in presenting and fusing data at multiple levels of abstraction, and across multiple intelligent sensors to conduct complex decision-making tasks. In this paper, a scenario about vehicle interaction is investigated, in which uncertainty is taken into consideration as no systematic approaches can perfectly characterize the complex event scenario. MLNs are applied to the terrestrial domain where the dynamic features and relationships among vehicles are captured through multiple sensors and information sources regarding the data uncertainty.

Accounting for heterogeneity in meta-analysis using a multiplicative model-an empirical study.

PubMed

Mawdsley, David; Higgins, Julian P T; Sutton, Alex J; Abrams, Keith R

2017-03-01

In meta-analysis, the random-effects model is often used to account for heterogeneity. The model assumes that heterogeneity has an additive effect on the variance of effect sizes. An alternative model, which assumes multiplicative heterogeneity, has been little used in the medical statistics community, but is widely used by particle physicists. In this paper, we compare the two models using a random sample of 448 meta-analyses drawn from the Cochrane Database of Systematic Reviews. In general, differences in goodness of fit are modest. The multiplicative model tends to give results that are closer to the null, with a narrower confidence interval. Both approaches make different assumptions about the outcome of the meta-analysis. In our opinion, the selection of the more appropriate model will often be guided by whether the multiplicative model's assumption of a single effect size is plausible. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Saada: A Generator of Astronomical Database

NASA Astrophysics Data System (ADS)

Michel, L.

2011-11-01

Saada transforms a set of heterogeneous FITS files or VOtables of various categories (images, tables, spectra, etc.) in a powerful database deployed on the Web. Databases are located on your host and stay independent of any external server. This job doesn’t require writing code. Saada can mix data of various categories in multiple collections. Data collections can be linked each to others making relevant browsing paths and allowing data-mining oriented queries. Saada supports 4 VO services (Spectra, images, sources and TAP) . Data collections can be published immediately after the deployment of the Web interface.

Structured Multi-level Data Fusion and Modelling of Heterogeneous Environmental Data for Future Internet Applications

NASA Astrophysics Data System (ADS)

Sabeur, Zoheir; Chakravarthy, Ajay; Bashevoy, Maxim; Modafferi, Stefano

2013-04-01

The rapid increase in environmental observations which are conducted by Small to Medium Enterprise communities and volunteers using affordable in situ sensors at various scales, in addition to the more established observatories set up by environmental and space agencies using airborne and space-borne sensing technologies is generating serious amounts of BIG data at ever increasing speeds. Furthermore, the emergence of Future Internet technologies and the urgent requirements for the deployment of specific enablers for the delivery of processed environmental knowledge in real-time with advanced situation awareness to citizens has reached paramount importance. Specifically, it has become highly critical now to build and provide services which automate the aggregation of data from various sources, while surmounting the semantic gaps, conflicts and heterogeneity in data sources. The early stage aggregation of data will enable the pre-processing of data from multiple sources while reconciling the temporal gaps in measurement time series, and aligning their respective a-synchronicities. This low level type of data fusion process needs to be automated and chained to more advanced level of data fusion services specialising in observation forecasts at spaces where sensing is not deployed; or at time slices where sensing has not taken place yet. As a result, multi-level fusion services are required among the families of specific enablers for monitoring environments and spaces in the Future Internet. These have been intially deployed and piloted in the ongoing ENVIROFI project of the FI-PPP programme [1]. Automated fusion and modelling of in situ and remote sensing data has been set up and the experimentation successfully conducted using RBF networks for the spatial fusion of water quality parameters measurements from satellite and stationary buoys in the Irish Sea. The RBF networks method scales for the spatial data fusion of multiple types of observation sources. This important approach provides a strong basis for the delivery of environmental observations at desired spatial and temporal scales to multiple users with various needs of spatial and temporal resolutions. It has also led to building robust future internet specific enablers on data fusion, which can indeed be used for multiple usage areas above and beyond the environmental domains of the Future Internet. In this paper, data and processing workflow scenarios shall be described. The fucntionalities of the multi-level fusion services shall be demonstrated and made accessible to the wider communities of the Fututre Internet. [1] The Environmental Observation Web and its Service Applications within the Future Internet. ENVIROFI IP. FP7-2011-ICT-IF Pr.No: 284898 http://www.envirofi.eu/

CMSA: a heterogeneous CPU/GPU computing system for multiple similar RNA/DNA sequence alignment.

PubMed

Chen, Xi; Wang, Chen; Tang, Shanjiang; Yu, Ce; Zou, Quan

2017-06-24

The multiple sequence alignment (MSA) is a classic and powerful technique for sequence analysis in bioinformatics. With the rapid growth of biological datasets, MSA parallelization becomes necessary to keep its running time in an acceptable level. Although there are a lot of work on MSA problems, their approaches are either insufficient or contain some implicit assumptions that limit the generality of usage. First, the information of users' sequences, including the sizes of datasets and the lengths of sequences, can be of arbitrary values and are generally unknown before submitted, which are unfortunately ignored by previous work. Second, the center star strategy is suited for aligning similar sequences. But its first stage, center sequence selection, is highly time-consuming and requires further optimization. Moreover, given the heterogeneous CPU/GPU platform, prior studies consider the MSA parallelization on GPU devices only, making the CPUs idle during the computation. Co-run computation, however, can maximize the utilization of the computing resources by enabling the workload computation on both CPU and GPU simultaneously. This paper presents CMSA, a robust and efficient MSA system for large-scale datasets on the heterogeneous CPU/GPU platform. It performs and optimizes multiple sequence alignment automatically for users' submitted sequences without any assumptions. CMSA adopts the co-run computation model so that both CPU and GPU devices are fully utilized. Moreover, CMSA proposes an improved center star strategy that reduces the time complexity of its center sequence selection process from O(mn 2 ) to O(mn). The experimental results show that CMSA achieves an up to 11× speedup and outperforms the state-of-the-art software. CMSA focuses on the multiple similar RNA/DNA sequence alignment and proposes a novel bitmap based algorithm to improve the center star strategy. We can conclude that harvesting the high performance of modern GPU is a promising approach to accelerate multiple sequence alignment. Besides, adopting the co-run computation model can maximize the entire system utilization significantly. The source code is available at https://github.com/wangvsa/CMSA .

Optimization of light source parameters in the photodynamic therapy of heterogeneous prostate

NASA Astrophysics Data System (ADS)

Li, Jun; Altschuler, Martin D.; Hahn, Stephen M.; Zhu, Timothy C.

2008-08-01

The three-dimensional (3D) heterogeneous distributions of optical properties in a patient prostate can now be measured in vivo. Such data can be used to obtain a more accurate light-fluence kernel. (For specified sources and points, the kernel gives the fluence delivered to a point by a source of unit strength.) In turn, the kernel can be used to solve the inverse problem that determines the source strengths needed to deliver a prescribed photodynamic therapy (PDT) dose (or light-fluence) distribution within the prostate (assuming uniform drug concentration). We have developed and tested computational procedures to use the new heterogeneous data to optimize delivered light-fluence. New problems arise, however, in quickly obtaining an accurate kernel following the insertion of interstitial light sources and data acquisition. (1) The light-fluence kernel must be calculated in 3D and separately for each light source, which increases kernel size. (2) An accurate kernel for light scattering in a heterogeneous medium requires ray tracing and volume partitioning, thus significant calculation time. To address these problems, two different kernels were examined and compared for speed of creation and accuracy of dose. Kernels derived more quickly involve simpler algorithms. Our goal is to achieve optimal dose planning with patient-specific heterogeneous optical data applied through accurate kernels, all within clinical times. The optimization process is restricted to accepting the given (interstitially inserted) sources, and determining the best source strengths with which to obtain a prescribed dose. The Cimmino feasibility algorithm is used for this purpose. The dose distribution and source weights obtained for each kernel are analyzed. In clinical use, optimization will also be performed prior to source insertion to obtain initial source positions, source lengths and source weights, but with the assumption of homogeneous optical properties. For this reason, we compare the results from heterogeneous optical data with those obtained from average homogeneous optical properties. The optimized treatment plans are also compared with the reference clinical plan, defined as the plan with sources of equal strength, distributed regularly in space, which delivers a mean value of prescribed fluence at detector locations within the treatment region. The study suggests that comprehensive optimization of source parameters (i.e. strengths, lengths and locations) is feasible, thus allowing acceptable dose coverage in a heterogeneous prostate PDT within the time constraints of the PDT procedure.

Spatiotemporal Heterogeneity of Dissolved Organic Carbon in Waters and Soils in a Snow-dominated Headwater Catchment: Investigations at Reynolds Creek Critical Zone Observatory, Owyhee County, Idaho

NASA Astrophysics Data System (ADS)

Radke, A. G.; Godsey, S.; Lohse, K. A.; Huber, D. P.; Patton, N. R.; Holbrook, S.

2017-12-01

The non-uniform distribution of precipitation in snowmelt-driven systems—the result of blowing and drifting snow—is a primary driver of spatial heterogeneity in vegetative communities and soil development. Snowdrifts may increase bedrock weathering below them, creating deeper soils and the potential for greater fracture flow. These snowdrift areas are also commonly more productive than the snow-starved, scoured areas where wind has removed snow. Warming-induced changes in the fraction of precipitation falling as snow, and therefore subject to drifting, may significantly affect carbon dynamics on multiple timescales. The focus of this study is to understand the coupled hydrological and carbon dynamics in a heterogeneous, drift-dominated watershed. We seek to determine the paths of soil water and groundwater in a small headwater catchment (Reynolds Mountain East, Reynolds Creek Critical Zone Observatory, Idaho, USA). Additionally, we anticipate quantifying the flux of dissolved organic carbon through these paths, and relate this to zones of greater vegetative productivity. We deduce likely flowpaths through a combination of soil water, groundwater, and precipitation characterization. Along a transect running from a snowdrift to the stream, we measure hydrometric and hydrochemical signatures of flow throughout the snowmelt period and summer. We then use end-member-mixing analysis to interpret flowpaths in light of inferred subsurface structure derived from drilling and electrical resistance tomography transects. Preliminary results from soil moisture sensors suggest that increased bedrock weathering creates pathways by which snowmelt bypasses portions of the soil, further increasing landscape heterogeneity. Further analysis will identify seasonal changes in carbon sourcing for this watershed, but initial indications are that spring streamwater is sourced primarily from soil water, with close associations between soil carbon and DOC.

Human Rights Event Detection from Heterogeneous Social Media Graphs.

PubMed

Chen, Feng; Neill, Daniel B

2015-03-01

Human rights organizations are increasingly monitoring social media for identification, verification, and documentation of human rights violations. Since manual extraction of events from the massive amount of online social network data is difficult and time-consuming, we propose an approach for automated, large-scale discovery and analysis of human rights-related events. We apply our recently developed Non-Parametric Heterogeneous Graph Scan (NPHGS), which models social media data such as Twitter as a heterogeneous network (with multiple different node types, features, and relationships) and detects emerging patterns in the network, to identify and characterize human rights events. NPHGS efficiently maximizes a nonparametric scan statistic (an aggregate measure of anomalousness) over connected subgraphs of the heterogeneous network to identify the most anomalous network clusters. It summarizes each event with information such as type of event, geographical locations, time, and participants, and provides documentation such as links to videos and news reports. Building on our previous work that demonstrates the utility of NPHGS for civil unrest prediction and rare disease outbreak detection, we present an analysis of human rights events detected by NPHGS using two years of Twitter data from Mexico. NPHGS was able to accurately detect relevant clusters of human rights-related tweets prior to international news sources, and in some cases, prior to local news reports. Analysis of social media using NPHGS could enhance the information-gathering missions of human rights organizations by pinpointing specific abuses, revealing events and details that may be blocked from traditional media sources, and providing evidence of emerging patterns of human rights violations. This could lead to more timely, targeted, and effective advocacy, as well as other potential interventions.

Surgeon and hospital volume as quality indicators for CABG in Taiwan: examining hazard to mortality and accounting for unobserved heterogeneity.

PubMed

Hockenberry, Jason M; Lien, Hsien-Ming; Chou, Shin-Yi

2010-10-01

To investigate whether provider volume has an impact on the hazard of mortality for coronary artery bypass grafting (CABG) patients in Taiwan. Multiple sources of linked data from the National Health Insurance Program in Taiwan. The linked data were used to identify 27,463 patients who underwent CABG without concomitant angioplasty or valve procedures and the surgeon and hospital volumes. Generalized estimating equations and hazard models were estimated to assess the impact of volume on mortality. The hazard modeling technique used accounts for bias stemming from unobserved heterogeneity. Both surgeon and hospital volume quartiles are inversely related to the hazard of mortality after CABG. Patients whose surgeon is in the three higher volume quartiles have lower 1-, 3-, 6-, and 12-month mortality after CABG, while only those having their procedure performed at the highest quartile of volume hospitals have lower mortality outcomes. Mortality outcomes are related to provider CABG volume in Taiwan. Unobserved heterogeneity is a concern in the volume-outcome relationship; after accounting for it, surgeon volume effects on short-term mortality are large. Using models controlling for unobserved heterogeneity and examining longer term mortality may still differentiate provider quality by volume. Copyright © Health Research and Educational Trust.

Stable carbon isotope ratios of intact GDGTs indicate heterogeneous sources to marine sediments

NASA Astrophysics Data System (ADS)

Pearson, Ann; Hurley, Sarah J.; Walter, Sunita R. Shah; Kusch, Stephanie; Lichtin, Samantha; Zhang, Yi Ge

2016-05-01

Thaumarchaeota, the major sources of marine glycerol dibiphytanyl glycerol tetraether lipids (GDGTs), are believed to fix the majority of their carbon directly from dissolved inorganic carbon (DIC). The δ13C values of GDGTs (δ13CGDGT) may be powerful tools for reconstructing variations in the ocean carbon cycle, including paleoproductivity and water mass circulation, if they can be related to values of δ13CDIC. To date, isotope measurements primarily are made on the C40 biphytane skeletons of GDGTs, rather than on complete tetraether structures. This approach erases information revealed by the isotopic heterogeneity of GDGTs within a sample and may impart an isotopic fractionation associated with the ether cleavage. To circumvent these issues, we present δ13C values for GDGTs from twelve recent sediments representing ten continental margin locations. Samples are purified by orthogonal dimensions of HPLC, followed by measurement of δ13C values by Spooling Wire Microcombustion (SWiM)-isotope ratio mass spectrometry (IRMS) with 1σ precision and accuracy of ±0.25‰. Using this approach, we confirm that GDGTs, generally around -19‰, are isotopically ;heavy; compared to other marine lipids. However, measured δ13CGDGT values are inconsistent with predicted values based on the 13C content of DIC in the overlying water column and the previously-published biosynthetic isotope fractionation for a pure culture of an autotrophic marine thaumarchaeon. In some sediments, the isotopic composition of individual GDGTs differs, indicating multiple source inputs. The data appear to confirm that crenarchaeol primarily is a biomarker for Thaumarchaeota, but its δ13C values still cannot be explained solely by autotrophic carbon fixation. Overall the complexity of the results suggests that both organic carbon assimilation (ca. 25% of total carbon) and multiple source(s) of exogenous GDGTs (contributing generally <30% of input to sediments) are necessary to explain the observed δ13CGDGT values. The results suggest caution when interpreting the total inputs of GDGTs to sedimentary records. Biogenic or open-slope sediments, rather than clastic basinal or shallow shelf sediments, are preferred locations for generating minimally-biased GDGT proxy records.

Quantifying site-specific physical heterogeneity within an estuarine seascape

USGS Publications Warehouse

Kennedy, Cristina G.; Mather, Martha E.; Smith, Joseph M.

2017-01-01

Quantifying physical heterogeneity is essential for meaningful ecological research and effective resource management. Spatial patterns of multiple, co-occurring physical features are rarely quantified across a seascape because of methodological challenges. Here, we identified approaches that measured total site-specific heterogeneity, an often overlooked aspect of estuarine ecosystems. Specifically, we examined 23 metrics that quantified four types of common physical features: (1) river and creek confluences, (2) bathymetric variation including underwater drop-offs, (3) land features such as islands/sandbars, and (4) major underwater channel networks. Our research at 40 sites throughout Plum Island Estuary (PIE) provided solutions to two problems. The first problem was that individual metrics that measured heterogeneity of a single physical feature showed different regional patterns. We solved this first problem by combining multiple metrics for a single feature using a within-physical feature cluster analysis. With this approach, we identified sites with four different types of confluences and three different types of underwater drop-offs. The second problem was that when multiple physical features co-occurred, new patterns of total site-specific heterogeneity were created across the seascape. This pattern of total heterogeneity has potential ecological relevance to structure-oriented predators. To address this second problem, we identified sites with similar types of total physical heterogeneity using an across-physical feature cluster analysis. Then, we calculated an additive heterogeneity index, which integrated all physical features at a site. Finally, we tested if site-specific additive heterogeneity index values differed for across-physical feature clusters. In PIE, the sites with the highest additive heterogeneity index values were clustered together and corresponded to sites where a fish predator, adult striped bass (Morone saxatilis), aggregated in a related acoustic tracking study. In summary, we have shown general approaches to quantifying site-specific heterogeneity.

Risk Profiles of Children Entering Residential Care: A Cluster Analysis

ERIC Educational Resources Information Center

Hagaman, Jessica L.; Trout, Alexandra L.; Chmelka, M. Beth; Thompson, Ronald W.; Reid, Robert

2010-01-01

Children in residential care are a heterogeneous population, presenting various combinations of risks. Existing studies on these children suggest high variability across multiple domains (e.g., academics, behavior). Given this heterogeneity, it is important to begin to identify the combinations and patterns of multiple risks, or risk profiles,…

A simplified analytical dose calculation algorithm accounting for tissue heterogeneity for low-energy brachytherapy sources.

PubMed

Mashouf, Shahram; Lechtman, Eli; Beaulieu, Luc; Verhaegen, Frank; Keller, Brian M; Ravi, Ananth; Pignol, Jean-Philippe

2013-09-21

The American Association of Physicists in Medicine Task Group No. 43 (AAPM TG-43) formalism is the standard for seeds brachytherapy dose calculation. But for breast seed implants, Monte Carlo simulations reveal large errors due to tissue heterogeneity. Since TG-43 includes several factors to account for source geometry, anisotropy and strength, we propose an additional correction factor, called the inhomogeneity correction factor (ICF), accounting for tissue heterogeneity for Pd-103 brachytherapy. This correction factor is calculated as a function of the media linear attenuation coefficient and mass energy absorption coefficient, and it is independent of the source internal structure. Ultimately the dose in heterogeneous media can be calculated as a product of dose in water as calculated by TG-43 protocol times the ICF. To validate the ICF methodology, dose absorbed in spherical phantoms with large tissue heterogeneities was compared using the TG-43 formalism corrected for heterogeneity versus Monte Carlo simulations. The agreement between Monte Carlo simulations and the ICF method remained within 5% in soft tissues up to several centimeters from a Pd-103 source. Compared to Monte Carlo, the ICF methods can easily be integrated into a clinical treatment planning system and it does not require the detailed internal structure of the source or the photon phase-space.

Multiple Kernel Learning with Random Effects for Predicting Longitudinal Outcomes and Data Integration

PubMed Central

Chen, Tianle; Zeng, Donglin

2015-01-01

Summary Predicting disease risk and progression is one of the main goals in many clinical research studies. Cohort studies on the natural history and etiology of chronic diseases span years and data are collected at multiple visits. Although kernel-based statistical learning methods are proven to be powerful for a wide range of disease prediction problems, these methods are only well studied for independent data but not for longitudinal data. It is thus important to develop time-sensitive prediction rules that make use of the longitudinal nature of the data. In this paper, we develop a novel statistical learning method for longitudinal data by introducing subject-specific short-term and long-term latent effects through a designed kernel to account for within-subject correlation of longitudinal measurements. Since the presence of multiple sources of data is increasingly common, we embed our method in a multiple kernel learning framework and propose a regularized multiple kernel statistical learning with random effects to construct effective nonparametric prediction rules. Our method allows easy integration of various heterogeneous data sources and takes advantage of correlation among longitudinal measures to increase prediction power. We use different kernels for each data source taking advantage of the distinctive feature of each data modality, and then optimally combine data across modalities. We apply the developed methods to two large epidemiological studies, one on Huntington's disease and the other on Alzheimer's Disease (Alzheimer's Disease Neuroimaging Initiative, ADNI) where we explore a unique opportunity to combine imaging and genetic data to study prediction of mild cognitive impairment, and show a substantial gain in performance while accounting for the longitudinal aspect of the data. PMID:26177419

Scuba: scalable kernel-based gene prioritization.

PubMed

Zampieri, Guido; Tran, Dinh Van; Donini, Michele; Navarin, Nicolò; Aiolli, Fabio; Sperduti, Alessandro; Valle, Giorgio

2018-01-25

The uncovering of genes linked to human diseases is a pressing challenge in molecular biology and precision medicine. This task is often hindered by the large number of candidate genes and by the heterogeneity of the available information. Computational methods for the prioritization of candidate genes can help to cope with these problems. In particular, kernel-based methods are a powerful resource for the integration of heterogeneous biological knowledge, however, their practical implementation is often precluded by their limited scalability. We propose Scuba, a scalable kernel-based method for gene prioritization. It implements a novel multiple kernel learning approach, based on a semi-supervised perspective and on the optimization of the margin distribution. Scuba is optimized to cope with strongly unbalanced settings where known disease genes are few and large scale predictions are required. Importantly, it is able to efficiently deal both with a large amount of candidate genes and with an arbitrary number of data sources. As a direct consequence of scalability, Scuba integrates also a new efficient strategy to select optimal kernel parameters for each data source. We performed cross-validation experiments and simulated a realistic usage setting, showing that Scuba outperforms a wide range of state-of-the-art methods. Scuba achieves state-of-the-art performance and has enhanced scalability compared to existing kernel-based approaches for genomic data. This method can be useful to prioritize candidate genes, particularly when their number is large or when input data is highly heterogeneous. The code is freely available at https://github.com/gzampieri/Scuba .

Utilized Resources of Hope, Orientation, and Inspiration in Life of Persons with Multiple Sclerosis and Their Association with Life Satisfaction, Adaptive Coping Strategies, and Spirituality.

PubMed

Wirth, Anne-Gritli; Büssing, Arndt

2016-08-01

In a cross-sectional survey among 213 patients with multiple sclerosis, we intended to analyze their resources of hope, orientation, and inspiration in life, and how these resources are related to health-associated variables, adaptive coping strategies, and life satisfaction. Resources were categorized as Faith (10 %), Family (22 %), Other sources (16 %), and No answer (53 %). These non-respondents were predominantly neither religious nor spiritual (70 % R-S-). Although R-S- persons are a heterogeneous group with varying existential interest, they did not significantly differ from their spiritual/religious counterparts with respect to physical and mental health or life satisfaction, but for an adaptive Reappraisal strategy and Gratitude/Awe.

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection

PubMed Central

Dang, Yaoguo; Mao, Wenxin

2018-01-01

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method. PMID:29510521

A Decision-Making Method with Grey Multi-Source Heterogeneous Data and Its Application in Green Supplier Selection.

PubMed

Sun, Huifang; Dang, Yaoguo; Mao, Wenxin

2018-03-03

In view of the multi-attribute decision-making problem that the attribute values are grey multi-source heterogeneous data, a decision-making method based on kernel and greyness degree is proposed. The definitions of kernel and greyness degree of an extended grey number in a grey multi-source heterogeneous data sequence are given. On this basis, we construct the kernel vector and greyness degree vector of the sequence to whiten the multi-source heterogeneous information, then a grey relational bi-directional projection ranking method is presented. Considering the multi-attribute multi-level decision structure and the causalities between attributes in decision-making problem, the HG-DEMATEL method is proposed to determine the hierarchical attribute weights. A green supplier selection example is provided to demonstrate the rationality and validity of the proposed method.

Micro-heterogeneity of corn hulls cellulosic fiber biopolymer studied by multiple-particle tracking (MPT)

USDA-ARS?s Scientific Manuscript database

A novel technique named multiple-particle tracking (MPT) was used to investigate the micro-structural heterogeneities of Z-trim, a zero calorie cellulosic fiber biopolymer produced from corn hulls. The principle of MPT technique is to monitor the thermally driven motion of inert micro-spheres, which...

Counting on β-Diversity to Safeguard the Resilience of Estuaries

PubMed Central

de Juan, Silvia; Thrush, Simon F.; Hewitt, Judi E.

2013-01-01

Coastal ecosystems are often stressed by non-point source and cumulative effects that can lead to local-scale community homogenisation and a concomitant loss of large-scale ecological connectivity. Here we investigate the use of β-diversity as a measure of both community heterogeneity and ecological connectivity. To understand the consequences of different environmental scenarios on heterogeneity and connectivity, it is necessary to understand the scale at which different environmental factors affect β-diversity. We sampled macrofauna from intertidal sites in nine estuaries from New Zealand’s North Island that represented different degrees of stress derived from land-use. We used multiple regression models to identify relationships between β-diversity and local sediment variables, factors related to the estuarine and catchment hydrodynamics and morphology and land-based stressors. At local scales, we found higher β-diversity at sites with a relatively high total richness. At larger scales, β-diversity was positively related to γ-diversity, suggesting that a large regional species pool was linked with large-scale heterogeneity in these systems. Local environmental heterogeneity influenced β-diversity at both local and regional scales, although variables at the estuarine and catchment scales were both needed to explain large scale connectivity. The estuaries expected a priori to be the most stressed exhibited higher variance in community dissimilarity between sites and connectivity to the estuary species pool. This suggests that connectivity and heterogeneity metrics could be used to generate early warning signals of cumulative stress. PMID:23755252

Unexpected Nongenetic Individual Heterogeneity and Trait Covariance in Daphnia and Its Consequences for Ecological and Evolutionary Dynamics.

PubMed

Cressler, Clayton E; Bengtson, Stefan; Nelson, William A

2017-07-01

Individual differences in genetics, age, or environment can cause tremendous differences in individual life-history traits. This individual heterogeneity generates demographic heterogeneity at the population level, which is predicted to have a strong impact on both ecological and evolutionary dynamics. However, we know surprisingly little about the sources of individual heterogeneity for particular taxa or how different sources scale up to impact ecological and evolutionary dynamics. Here we experimentally study the individual heterogeneity that emerges from both genetic and nongenetic sources in a species of freshwater zooplankton across a large gradient of food quality. Despite the tight control of environment, we still find that the variation from nongenetic sources is greater than that from genetic sources over a wide range of food quality and that this variation has strong positive covariance between growth and reproduction. We evaluate the general consequences of genetic and nongenetic covariance for ecological and evolutionary dynamics theoretically and find that increasing nongenetic variation slows evolution independent of the correlation in heritable life-history traits but that the impact on ecological dynamics depends on both nongenetic and genetic covariance. Our results demonstrate that variation in the relative magnitude of nongenetic versus genetic sources of variation impacts the predicted ecological and evolutionary dynamics.

Integration of Schemas on the Pre-Design Level Using the KCPM-Approach

NASA Astrophysics Data System (ADS)

Vöhringer, Jürgen; Mayr, Heinrich C.

Integration is a central research and operational issue in information system design and development. It can be conducted on the system, schema, and view or data level. On the system level, integration deals with the progressive linking and testing of system components to merge their functional and technical characteristics and behavior into a comprehensive, interoperable system. Schema integration comprises the comparison and merging of two or more schemas, usually conceptual database schemas. The integration of data deals with merging the contents of multiple sources of related data. View integration is similar to schema integration, however focuses on views and queries on these instead of schemas. All these types of integration have in common, that two or more sources are merged and previously compared, in order to identify matches and mismatches as well as conflicts and inconsistencies. The sources may stem from heterogeneous companies, organizational units or projects. Integration enables the reuse and combined use of source components.

Combined mining: discovering informative knowledge in complex data.

PubMed

Cao, Longbing; Zhang, Huaifeng; Zhao, Yanchang; Luo, Dan; Zhang, Chengqi

2011-06-01

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.

The big data-big model (BDBM) challenges in ecological research

NASA Astrophysics Data System (ADS)

Luo, Y.

2015-12-01

The field of ecology has become a big-data science in the past decades due to development of new sensors used in numerous studies in the ecological community. Many sensor networks have been established to collect data. For example, satellites, such as Terra and OCO-2 among others, have collected data relevant on global carbon cycle. Thousands of field manipulative experiments have been conducted to examine feedback of terrestrial carbon cycle to global changes. Networks of observations, such as FLUXNET, have measured land processes. In particular, the implementation of the National Ecological Observatory Network (NEON), which is designed to network different kinds of sensors at many locations over the nation, will generate large volumes of ecological data every day. The raw data from sensors from those networks offer an unprecedented opportunity for accelerating advances in our knowledge of ecological processes, educating teachers and students, supporting decision-making, testing ecological theory, and forecasting changes in ecosystem services. Currently, ecologists do not have the infrastructure in place to synthesize massive yet heterogeneous data into resources for decision support. It is urgent to develop an ecological forecasting system that can make the best use of multiple sources of data to assess long-term biosphere change and anticipate future states of ecosystem services at regional and continental scales. Forecasting relies on big models that describe major processes that underlie complex system dynamics. Ecological system models, despite great simplification of the real systems, are still complex in order to address real-world problems. For example, Community Land Model (CLM) incorporates thousands of processes related to energy balance, hydrology, and biogeochemistry. Integration of massive data from multiple big data sources with complex models has to tackle Big Data-Big Model (BDBM) challenges. Those challenges include interoperability of multiple, heterogeneous data sets; intractability of structural complexity of big models; equifinality of model structure selection and parameter estimation; and computational demand of global optimization with Big Models.

Propagation of Gaussian wave packets in complex media and application to fracture characterization

NASA Astrophysics Data System (ADS)

Ding, Yinshuai; Zheng, Yingcai; Zhou, Hua-Wei; Howell, Michael; Hu, Hao; Zhang, Yu

2017-08-01

Knowledge of the subsurface fracture networks is critical in probing the tectonic stress states and flow of fluids in reservoirs containing fractures. We propose to characterize fractures using scattered seismic data, based on the theory of local plane-wave multiple scattering in a fractured medium. We construct a localized directional wave packet using point sources on the surface and propagate it toward the targeted subsurface fractures. The wave packet behaves as a local plane wave when interacting with the fractures. The interaction produces multiple scattering of the wave packet that eventually travels up to the surface receivers. The propagation direction and amplitude of the multiply scattered wave can be used to characterize fracture density, orientation and compliance. Two key aspects in this characterization process are the spatial localization and directionality of the wave packet. Here we first show the physical behaviour of a new localized wave, known as the Gaussian Wave Packet (GWP), by examining its analytical solution originally formulated for a homogenous medium. We then use a numerical finite-difference time-domain (FDTD) method to study its propagation behaviour in heterogeneous media. We find that a GWP can still be localized and directional in space even over a large propagation distance in heterogeneous media. We then propose a method to decompose the recorded seismic wavefield into GWPs based on the reverse-time concept. This method enables us to create a virtually recorded seismic data using field shot gathers, as if the source were an incident GWP. Finally, we demonstrate the feasibility of using GWPs for fracture characterization using three numerical examples. For a medium containing fractures, we can reliably invert for the local parameters of multiple fracture sets. Differing from conventional seismic imaging such as migration methods, our fracture characterization method is less sensitive to errors in the background velocity model. For a layered medium containing fractures, our method can correctly recover the fracture density even with an inaccurate velocity model.

Algorithmic Foundation of Spectral Rarefaction for Measuring Satellite Imagery Heterogeneity at Multiple Spatial Scales

PubMed Central

Rocchini, Duccio

2009-01-01

Measuring heterogeneity in satellite imagery is an important task to deal with. Most measures of spectral diversity have been based on Shannon Information theory. However, this approach does not inherently address different scales, ranging from local (hereafter referred to alpha diversity) to global scales (gamma diversity). The aim of this paper is to propose a method for measuring spectral heterogeneity at multiple scales based on rarefaction curves. An algorithmic solution of rarefaction applied to image pixel values (Digital Numbers, DNs) is provided and discussed. PMID:22389600

Using conceptual spaces to fuse knowledge from heterogeneous robot platforms

NASA Astrophysics Data System (ADS)

Kira, Zsolt

2010-04-01

As robots become more common, it becomes increasingly useful for many applications to use them in teams that sense the world in a distributed manner. In such situations, the robots or a central control center must communicate and fuse information received from multiple sources. A key challenge for this problem is perceptual heterogeneity, where the sensors, perceptual representations, and training instances used by the robots differ dramatically. In this paper, we use Gärdenfors' conceptual spaces, a geometric representation with strong roots in cognitive science and psychology, in order to represent the appearance of objects and show how the problem of heterogeneity can be intuitively explored by looking at the situation where multiple robots differ in their conceptual spaces at different levels. To bridge low-level sensory differences, we abstract raw sensory data into properties (such as color or texture categories), represented as Gaussian Mixture Models, and demonstrate that this facilitates both individual learning and the fusion of concepts between robots. Concepts (e.g. objects) are represented as a fuzzy mixture of these properties. We then treat the problem where the conceptual spaces of two robots differ and they only share a subset of these properties. In this case, we use joint interaction and statistical metrics to determine which properties are shared. Finally, we show how conceptual spaces can handle the combination of such missing properties when fusing concepts received from different robots. We demonstrate the fusion of information in real-robot experiments with a Mobile Robots Amigobot and Pioneer 2DX with significantly different cameras and (on one robot) a SICK lidar.ÿÿÿÿ

Conceptual Model Formalization in a Semantic Interoperability Service Framework: Transforming Relational Database Schemas to OWL.

PubMed

Bravo, Carlos; Suarez, Carlos; González, Carolina; López, Diego; Blobel, Bernd

2014-01-01

Healthcare information is distributed through multiple heterogeneous and autonomous systems. Access to, and sharing of, distributed information sources are a challenging task. To contribute to meeting this challenge, this paper presents a formal, complete and semi-automatic transformation service from Relational Databases to Web Ontology Language. The proposed service makes use of an algorithm that allows to transform several data models of different domains by deploying mainly inheritance rules. The paper emphasizes the relevance of integrating the proposed approach into an ontology-based interoperability service to achieve semantic interoperability.

Shared Decision Making Among Clinicians and Asian American and Pacific Islander Sexual and Gender Minorities: An Intersectional Approach to Address a Critical Care Gap.

PubMed

Tan, Judy Y; Xu, Lucy J; Lopez, Fanny Y; Jia, Justin L; Pho, Mai T; Kim, Karen E; Chin, Marshall H

2016-10-01

Shared decision making (SDM) is a model of patient-provider communication. Little is known about the role of SDM in health disparities among Asian American and Pacific Islander (AAPI) sexual and gender minorities (SGM). We illustrate how issues at the intersection of AAPI and SGM identities affect SDM processes and health outcomes. We discuss experiences of AAPI SGM that are affected by AAPI heterogeneity, SGM stigma, multiple minority group identities, and sources of discrimination. Recommendations for clinical practice, research, policy, community development, and education are offered.

On the multiple depots vehicle routing problem with heterogeneous fleet capacity and velocity

NASA Astrophysics Data System (ADS)

Hanum, F.; Hartono, A. P.; Bakhtiar, T.

2018-03-01

This current manuscript concerns with the optimization problem arising in a route determination of products distribution. The problem is formulated in the form of multiple depots and time windowed vehicle routing problem with heterogeneous capacity and velocity of fleet. Model includes a number of constraints such as route continuity, multiple depots availability and serving time in addition to generic constraints. In dealing with the unique feature of heterogeneous velocity, we generate a number of velocity profiles along the road segments, which then converted into traveling-time tables. An illustrative example of rice distribution among villages by bureau of logistics is provided. Exact approach is utilized to determine the optimal solution in term of vehicle routes and starting time of service.

Evaluation of groundwater residence time in a high mountain aquifer system (Sacramento Mountains, USA): insights gained from use of multiple environmental tracers

NASA Astrophysics Data System (ADS)

Land, Lewis; Timmons, Stacy

2016-06-01

The New Mexico Bureau of Geology and Mineral Resources (USA) has conducted a regional investigation of groundwater residence time within the southern Sacramento Mountains aquifer system using multiple environmental tracers. Results of the tracer surveys indicate that groundwater in the southern Sacramento Mountains ranges in age from less than 1 year to greater than 50 years, although the calculated ages contain uncertainties and vary significantly depending on which tracer is used. A distinctive feature of the results is discordance among the methods used to date groundwater in the study area. This apparent ambiguity results from the effects of a thick unsaturated zone, which produces non-conservative behavior among the dissolved gas tracers, and the heterogeneous character and semi-karstic nature of the aquifer system, which may yield water from matrix porosity, fractures, solution-enlarged conduits, or a combination of the three. The data also indicate mixing of groundwater from two or more sources, including recent recharge originating from precipitation at high elevations, old groundwater stored in the matrix, and pre-modern groundwater upwelling along fault zones. The tracer data have also been influenced by surface-water/groundwater exchange via losing streams and lower elevation springs (groundwater recycling). This study highlights the importance of using multiple tracers when conducting large-scale investigations of a heterogeneous aquifer system, and sheds light on characteristics of groundwater flow systems that can produce discrepancies in calculations of groundwater age.

Metainference: A Bayesian inference method for heterogeneous systems

PubMed Central

Bonomi, Massimiliano; Camilloni, Carlo; Cavalli, Andrea; Vendruscolo, Michele

2016-01-01

Modeling a complex system is almost invariably a challenging task. The incorporation of experimental observations can be used to improve the quality of a model and thus to obtain better predictions about the behavior of the corresponding system. This approach, however, is affected by a variety of different errors, especially when a system simultaneously populates an ensemble of different states and experimental data are measured as averages over such states. To address this problem, we present a Bayesian inference method, called “metainference,” that is able to deal with errors in experimental measurements and with experimental measurements averaged over multiple states. To achieve this goal, metainference models a finite sample of the distribution of models using a replica approach, in the spirit of the replica-averaging modeling based on the maximum entropy principle. To illustrate the method, we present its application to a heterogeneous model system and to the determination of an ensemble of structures corresponding to the thermal fluctuations of a protein molecule. Metainference thus provides an approach to modeling complex systems with heterogeneous components and interconverting between different states by taking into account all possible sources of errors. PMID:26844300

A Semantic Big Data Platform for Integrating Heterogeneous Wearable Data in Healthcare.

PubMed

Mezghani, Emna; Exposito, Ernesto; Drira, Khalil; Da Silveira, Marcos; Pruski, Cédric

2015-12-01

Advances supported by emerging wearable technologies in healthcare promise patients a provision of high quality of care. Wearable computing systems represent one of the most thrust areas used to transform traditional healthcare systems into active systems able to continuously monitor and control the patients' health in order to manage their care at an early stage. However, their proliferation creates challenges related to data management and integration. The diversity and variety of wearable data related to healthcare, their huge volume and their distribution make data processing and analytics more difficult. In this paper, we propose a generic semantic big data architecture based on the "Knowledge as a Service" approach to cope with heterogeneity and scalability challenges. Our main contribution focuses on enriching the NIST Big Data model with semantics in order to smartly understand the collected data, and generate more accurate and valuable information by correlating scattered medical data stemming from multiple wearable devices or/and from other distributed data sources. We have implemented and evaluated a Wearable KaaS platform to smartly manage heterogeneous data coming from wearable devices in order to assist the physicians in supervising the patient health evolution and keep the patient up-to-date about his/her status.

NoSQL data model for semi-automatic integration of ethnomedicinal plant data from multiple sources.

PubMed

Ningthoujam, Sanjoy Singh; Choudhury, Manabendra Dutta; Potsangbam, Kumar Singh; Chetia, Pankaj; Nahar, Lutfun; Sarker, Satyajit D; Basar, Norazah; Das Talukdar, Anupam

2014-01-01

Sharing traditional knowledge with the scientific community could refine scientific approaches to phytochemical investigation and conservation of ethnomedicinal plants. As such, integration of traditional knowledge with scientific data using a single platform for sharing is greatly needed. However, ethnomedicinal data are available in heterogeneous formats, which depend on cultural aspects, survey methodology and focus of the study. Phytochemical and bioassay data are also available from many open sources in various standards and customised formats. To design a flexible data model that could integrate both primary and curated ethnomedicinal plant data from multiple sources. The current model is based on MongoDB, one of the Not only Structured Query Language (NoSQL) databases. Although it does not contain schema, modifications were made so that the model could incorporate both standard and customised ethnomedicinal plant data format from different sources. The model presented can integrate both primary and secondary data related to ethnomedicinal plants. Accommodation of disparate data was accomplished by a feature of this database that supported a different set of fields for each document. It also allowed storage of similar data having different properties. The model presented is scalable to a highly complex level with continuing maturation of the database, and is applicable for storing, retrieving and sharing ethnomedicinal plant data. It can also serve as a flexible alternative to a relational and normalised database. Copyright © 2014 John Wiley & Sons, Ltd.

Homogenized moment tensor and the effect of near-field heterogeneities on nonisotropic radiation in nuclear explosion

NASA Astrophysics Data System (ADS)

Burgos, Gaël.; Capdeville, Yann; Guillot, Laurent

2016-06-01

We investigate the effect of small-scale heterogeneities close to a seismic explosive source, at intermediate periods (20-50 s), with an emphasis on the resulting nonisotropic far-field radiation. First, using a direct numerical approach, we show that small-scale elastic heterogeneities located in the near-field of an explosive source, generate unexpected phases (i.e., long period S waves). We then demonstrate that the nonperiodic homogenization theory applied to 2-D and 3-D elastic models, with various pattern of small-scale heterogeneities near the source, leads to accurate waveforms at a reduced computational cost compared to direct modeling. Further, it gives an interpretation of how nearby small-scale features interact with the source at low frequencies, through an explicit correction to the seismic moment tensor. In 2-D simulations, we find a deviatoric contribution to the moment tensor, as high as 21% for near-source heterogeneities showing a 25% contrast of elastic values (relative to a homogeneous background medium). In 3-D this nonisotropic contribution reaches 27%. Second, we analyze intermediate-periods regional seismic waveforms associated with some underground nuclear explosions conducted at the Nevada National Security Site and invert for the full moment tensor, in order to quantify the relative contribution of the isotropic and deviatoric components of the tensor. The average value of the deviatoric part is about 35%. We conclude that the interactions between an explosive source and small-scale local heterogeneities of moderate amplitude may lead to a deviatoric contribution to the seismic moment, close to what is observed using regional data from nuclear test explosions.

Automated deconvolution of structured mixtures from heterogeneous tumor genomic data

PubMed Central

Roman, Theodore; Xie, Lu

2017-01-01

With increasing appreciation for the extent and importance of intratumor heterogeneity, much attention in cancer research has focused on profiling heterogeneity on a single patient level. Although true single-cell genomic technologies are rapidly improving, they remain too noisy and costly at present for population-level studies. Bulk sequencing remains the standard for population-scale tumor genomics, creating a need for computational tools to separate contributions of multiple tumor clones and assorted stromal and infiltrating cell populations to pooled genomic data. All such methods are limited to coarse approximations of only a few cell subpopulations, however. In prior work, we demonstrated the feasibility of improving cell type deconvolution by taking advantage of substructure in genomic mixtures via a strategy called simplicial complex unmixing. We improve on past work by introducing enhancements to automate learning of substructured genomic mixtures, with specific emphasis on genome-wide copy number variation (CNV) data, as well as the ability to process quantitative RNA expression data, and heterogeneous combinations of RNA and CNV data. We introduce methods for dimensionality estimation to better decompose mixture model substructure; fuzzy clustering to better identify substructure in sparse, noisy data; and automated model inference methods for other key model parameters. We further demonstrate their effectiveness in identifying mixture substructure in true breast cancer CNV data from the Cancer Genome Atlas (TCGA). Source code is available at https://github.com/tedroman/WSCUnmix PMID:29059177

Comparing Students With and Without Reading Difficulties on Reading Comprehension Assessments: A Meta-Analysis.

PubMed

Collins, Alyson A; Lindström, Esther R; Compton, Donald L

Researchers have increasingly investigated sources of variance in reading comprehension test scores, particularly with students with reading difficulties (RD). The purpose of this meta-analysis was to determine if the achievement gap between students with RD and typically developing (TD) students varies as a function of different reading comprehension response formats (e.g., multiple choice, cloze). A systematic literature review identified 82 eligible studies. All studies administered reading comprehension assessments to students with RD and TD students in Grades K-12. Hedge's g standardized mean difference effect sizes were calculated, and random effects robust variance estimation techniques were used to aggregate average weighted effect sizes for each response format. Results indicated that the achievement gap between students with RD and TD students was larger for some response formats (e.g., picture selection ES g = -1.80) than others (e.g., retell ES g = -0.60). Moreover, for multiple-choice, cloze, and open-ended question response formats, single-predictor metaregression models explored potential moderators of heterogeneity in effect sizes. No clear patterns, however, emerged in regard to moderators of heterogeneity in effect sizes across response formats. Findings suggest that the use of different response formats may lead to variability in the achievement gap between students with RD and TD students.

Organic contaminant transport and fate in the subsurface: Evolution of knowledge and understanding

NASA Astrophysics Data System (ADS)

Essaid, Hedeff I.; Bekins, Barbara A.; Cozzarelli, Isabelle M.

2015-07-01

Toxic organic contaminants may enter the subsurface as slightly soluble and volatile nonaqueous phase liquids (NAPLs) or as dissolved solutes resulting in contaminant plumes emanating from the source zone. A large body of research published in Water Resources Research has been devoted to characterizing and understanding processes controlling the transport and fate of these organic contaminants and the effectiveness of natural attenuation, bioremediation, and other remedial technologies. These contributions include studies of NAPL flow, entrapment, and interphase mass transfer that have advanced from the analysis of simple systems with uniform properties and equilibrium contaminant phase partitioning to complex systems with pore-scale and macroscale heterogeneity and rate-limited interphase mass transfer. Understanding of the fate of dissolved organic plumes has advanced from when biodegradation was thought to require oxygen to recognition of the importance of anaerobic biodegradation, multiple redox zones, microbial enzyme kinetics, and mixing of organic contaminants and electron acceptors at plume fringes. Challenges remain in understanding the impacts of physical, chemical, biological, and hydrogeological heterogeneity, pore-scale interactions, and mixing on the fate of organic contaminants. Further effort is needed to successfully incorporate these processes into field-scale predictions of transport and fate. Regulations have greatly reduced the frequency of new point-source contamination problems; however, remediation at many legacy plumes remains challenging. A number of fields of current relevance are benefiting from research advances from point-source contaminant research. These include geologic carbon sequestration, nonpoint-source contamination, aquifer storage and recovery, the fate of contaminants from oil and gas development, and enhanced bioremediation.

Organic contaminant transport and fate in the subsurface: evolution of knowledge and understanding

USGS Publications Warehouse

Essaid, Hedeff I.; Bekins, Barbara A.; Cozzarelli, Isabelle M.

2015-01-01

Toxic organic contaminants may enter the subsurface as slightly soluble and volatile nonaqueous phase liquids (NAPLs) or as dissolved solutes resulting in contaminant plumes emanating from the source zone. A large body of research published in Water Resources Research has been devoted to characterizing and understanding processes controlling the transport and fate of these organic contaminants and the effectiveness of natural attenuation, bioremediation, and other remedial technologies. These contributions include studies of NAPL flow, entrapment, and interphase mass transfer that have advanced from the analysis of simple systems with uniform properties and equilibrium contaminant phase partitioning to complex systems with pore-scale and macroscale heterogeneity and rate-limited interphase mass transfer. Understanding of the fate of dissolved organic plumes has advanced from when biodegradation was thought to require oxygen to recognition of the importance of anaerobic biodegradation, multiple redox zones, microbial enzyme kinetics, and mixing of organic contaminants and electron acceptors at plume fringes. Challenges remain in understanding the impacts of physical, chemical, biological, and hydrogeological heterogeneity, pore-scale interactions, and mixing on the fate of organic contaminants. Further effort is needed to successfully incorporate these processes into field-scale predictions of transport and fate. Regulations have greatly reduced the frequency of new point-source contamination problems; however, remediation at many legacy plumes remains challenging. A number of fields of current relevance are benefiting from research advances from point-source contaminant research. These include geologic carbon sequestration, nonpoint-source contamination, aquifer storage and recovery, the fate of contaminants from oil and gas development, and enhanced bioremediation.

Analysis of the Coupled Influence of Hydraulic Conductivity and Porosity Heterogeneity on Probabilistic Risk Analysis

NASA Astrophysics Data System (ADS)

Libera, A.; Henri, C.; de Barros, F.

2017-12-01

Heterogeneities in natural porous formations, mainly manifested through the hydraulic conductivity (K) and, to a lesser degree, the porosity (Φ), largely control subsurface flow and solute transport. The influence of the heterogeneous structure of K on flow and solute transport processes has been widely studied, whereas less attention is dedicated to the joint heterogeneity of conductivity and porosity fields. Our study employs computational tools to investigate the joint effect of the spatial variabilities of K and Φ on the transport behavior of a solute plume. We explore multiple scenarios, characterized by different levels of heterogeneity of the geological system, and compare the computational results from the joint K and Φ heterogeneous system with the results originating from the generally adopted constant porosity case. In our work, we assume that the heterogeneous porosity is positively correlated to hydraulic conductivity. We perform numerical Monte Carlo simulations of conservative and reactive contaminant transport in a 3D aquifer. Contaminant mass and plume arrival times at multiple control planes and/or pumping wells operating under different extraction rates are analyzed. We employ different probabilistic metrics to quantify the risk at the monitoring locations, e.g., increased lifetime cancer risk and exceedance of Maximum Contaminant Levels (MCLs), under multiple transport scenarios (i.e., different levels of heterogeneity, conservative or reactive solutes and different contaminant species). Results show that early and late arrival times of the solute mass at the selected sensitive locations (i.e. control planes/pumping wells) as well as risk metrics are strongly influenced by the spatial variability of the Φ field.

Automated Historical and Real-Time Cyclone Discovery With Multimodal Remote Satellite Measurements

NASA Astrophysics Data System (ADS)

Ho, S.; Talukder, A.; Liu, T.; Tang, W.; Bingham, A.

2008-12-01

Existing cyclone detection and tracking solutions involve extensive manual analysis of modeled-data and field campaign data by teams of experts. We have developed a novel automated global cyclone detection and tracking system by assimilating and sharing information from multiple remote satellites. This unprecedented solution of combining multiple remote satellite measurements in an autonomous manner allows leveraging off the strengths of each individual satellite. Use of multiple satellite data sources also results in significantly improved temporal tracking accuracy for cyclones. Our solution involves an automated feature extraction and machine learning technique based on an ensemble classifier and Kalman filter for cyclone detection and tracking from multiple heterogeneous satellite data sources. Our feature-based methodology that focuses on automated cyclone discovery is fundamentally different from, and actually complements, the well-known Dvorak technique for cyclone intensity estimation (that often relies on manual detection of cyclonic regions) from field and remote data. Our solution currently employs the QuikSCAT wind measurement and the merged level 3 TRMM precipitation data for automated cyclone discovery. Assimilation of other types of remote measurements is ongoing and planned in the near future. Experimental results of our automated solution on historical cyclone datasets demonstrate the superior performance of our automated approach compared to previous work. Performance of our detection solution compares favorably against the list of cyclones occurring in North Atlantic Ocean for the 2005 calendar year reported by the National Hurricane Center (NHC) in our initial analysis. We have also demonstrated the robustness of our cyclone tracking methodology in other regions over the world by using multiple heterogeneous satellite data for detection and tracking of three arbitrary historical cyclones in other regions. Our cyclone detection and tracking methodology can be applied to (i) historical data to support Earth scientists in climate modeling, cyclonic-climate interactions, and obtain a better understanding of the cause and effects of cyclone (e.g. cyclo-genesis), and (ii) automatic cyclone discovery in near real-time using streaming satellite to support and improve the planning of global cyclone field campaigns. Additional satellite data from GOES and other orbiting satellites can be easily assimilated and integrated into our automated cyclone detection and tracking module to improve the temporal tracking accuracy of cyclones down to ½ hr and reduce the incidence of false alarms.

Ground Layer Plant Species Turnover and Beta Diversity in Southern-European Old-Growth Forests

PubMed Central

Sabatini, Francesco Maria; Burrascano, Sabina; Tuomisto, Hanna; Blasi, Carlo

2014-01-01

Different assembly processes may simultaneously affect local-scale variation of species composition in temperate old-growth forests. Ground layer species diversity reflects chance colonization and persistence of low-dispersal species, as well as fine-scale environmental heterogeneity. The latter depends on both purely abiotic factors, such as soil properties and topography, and factors primarily determined by overstorey structure, such as light availability. Understanding the degree to which plant diversity in old-growth forests is associated with structural heterogeneity and/or to dispersal limitation will help assessing the effectiveness of silvicultural practices that recreate old-growth patterns and structures for the conservation or restoration of plant diversity. We used a nested sampling design to assess fine-scale species turnover, i.e. the proportion of species composition that changes among sampling units, across 11 beech-dominated old-growth forests in Southern Europe. For each stand, we also measured a wide range of environmental and structural variables that might explain ground layer species turnover. Our aim was to quantify the relative importance of dispersal limitation in comparison to that of stand structural heterogeneity while controlling for other sources of environmental heterogeneity. For this purpose, we used multiple regression on distance matrices at the within-stand extent, and mixed effect models at the extent of the whole dataset. Species turnover was best predicted by structural and environmental heterogeneity, especially by differences in light availability and in topsoil nutrient concentration and texture. Spatial distances were significant only in four out of eleven stands with a relatively low explanatory power. This suggests that structural heterogeneity is a more important driver of local-scale ground layer species turnover than dispersal limitation in southern European old-growth beech forests. PMID:24748155

On the importance of considering heterogeneity in witnesses' competence levels when reconstructing crimes from multiple witness testimonies.

PubMed

Waubert de Puiseau, Berenike; Greving, Sven; Aßfalg, André; Musch, Jochen

2017-09-01

Aggregating information across multiple testimonies may improve crime reconstructions. However, different aggregation methods are available, and research on which method is best suited for aggregating multiple observations is lacking. Furthermore, little is known about how variance in the accuracy of individual testimonies impacts the performance of competing aggregation procedures. We investigated the superiority of aggregation-based crime reconstructions involving multiple individual testimonies and whether this superiority varied as a function of the number of witnesses and the degree of heterogeneity in witnesses' ability to accurately report their observations. Moreover, we examined whether heterogeneity in competence levels differentially affected the relative accuracy of two aggregation procedures: a simple majority rule, which ignores individual differences, and the more complex general Condorcet model (Romney et al., Am Anthropol 88(2):313-338, 1986; Batchelder and Romney, Psychometrika 53(1):71-92, 1988), which takes into account differences in competence between individuals. 121 participants viewed a simulated crime and subsequently answered 128 true/false questions about the crime. We experimentally generated groups of witnesses with homogeneous or heterogeneous competences. Both the majority rule and the general Condorcet model provided more accurate reconstructions of the observed crime than individual testimonies. The superiority of aggregated crime reconstructions involving multiple individual testimonies increased with an increasing number of witnesses. Crime reconstructions were most accurate when competences were heterogeneous and aggregation was based on the general Condorcet model. We argue that a formal aggregation should be considered more often when eyewitness testimonies have to be assessed and that the general Condorcet model provides a good framework for such aggregations.

System for Performing Single Query Searches of Heterogeneous and Dispersed Databases

NASA Technical Reports Server (NTRS)

Maluf, David A. (Inventor); Okimura, Takeshi (Inventor); Gurram, Mohana M. (Inventor); Tran, Vu Hoang (Inventor); Knight, Christopher D. (Inventor); Trinh, Anh Ngoc (Inventor)

2017-01-01

The present invention is a distributed computer system of heterogeneous databases joined in an information grid and configured with an Application Programming Interface hardware which includes a search engine component for performing user-structured queries on multiple heterogeneous databases in real time. This invention reduces overhead associated with the impedance mismatch that commonly occurs in heterogeneous database queries.

HETEROGENEOUS SOOT NANOSTRUCTURE IN ATMOSPHERIC AND COMBUSTION SOURCE AEROSOLS

EPA Science Inventory

Microscopic images of soot emissions from wildfire and a wide range of anthropogenic combustion sources show that the nanostructures of individual particles in these emissions are predominantly heterogeneous, decidedly influenced by the fuel composition and by the particular comb...

Heterogeneity in lunar anorthosite meteorites: implications for the lunar magma ocean model.

PubMed

Russell, Sara S; Joy, Katherine H; Jeffries, Teresa E; Consolmagno, Guy J; Kearsley, Anton

2014-09-13

The lunar magma ocean model is a well-established theory of the early evolution of the Moon. By this model, the Moon was initially largely molten and the anorthositic crust that now covers much of the lunar surface directly crystallized from this enormous magma source. We are undertaking a study of the geochemical characteristics of anorthosites from lunar meteorites to test this model. Rare earth and other element abundances have been measured in situ in relict anorthosite clasts from two feldspathic lunar meteorites: Dhofar 908 and Dhofar 081. The rare earth elements were present in abundances of approximately 0.1 to approximately 10× chondritic (CI) abundance. Every plagioclase exhibited a positive Eu-anomaly, with Eu abundances of up to approximately 20×CI. Calculations of the melt in equilibrium with anorthite show that it apparently crystallized from a magma that was unfractionated with respect to rare earth elements and ranged in abundance from 8 to 80×CI. Comparisons of our data with other lunar meteorites and Apollo samples suggest that there is notable heterogeneity in the trace element abundances of lunar anorthosites, suggesting these samples did not all crystallize from a common magma source. Compositional and isotopic data from other authors also suggest that lunar anorthosites are chemically heterogeneous and have a wide range of ages. These observations may support other models of crust formation on the Moon or suggest that there are complexities in the lunar magma ocean scenario to allow for multiple generations of anorthosite formation. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Modernized Approach for Generating Reproducible Heterogeneity Using Transmitted-Light for Flow Visualization Experiments

NASA Astrophysics Data System (ADS)

Jones, A. A.; Holt, R. M.

2017-12-01

Image capturing in flow experiments has been used for fluid mechanics research since the early 1970s. Interactions of fluid flow between the vadose zone and permanent water table are of great interest because this zone is responsible for all recharge waters, pollutant transport and irrigation efficiency for agriculture. Griffith, et al. (2011) developed an approach where constructed reproducible "geologically realistic" sand configurations are deposited in sandfilled experimental chambers for light-transmitted flow visualization experiments. This method creates reproducible, reverse graded, layered (stratified) thin-slab sand chambers for point source experiments visualizing multiphase flow through porous media. Reverse-graded stratification of sand chambers mimic many naturally occurring sedimentary deposits. Sandfilled chambers use light as nonintrusive tools for measuring water saturation in two-dimensions (2-D). Homogeneous and heterogeneous sand configurations can be produced to visualize the complex physics of the unsaturated zone. The experimental procedure developed by Griffith, et al. (2011) was designed using now outdated and obsolete equipment. We have modernized this approach with new Parker Deadel linear actuator and programed projects/code for multiple configurations. We have also updated the Roper CCD software and image processing software with the latest in industry standards. Modernization of transmitted-light source, robotic equipment, redesigned experimental chambers, and newly developed analytical procedures have greatly reduced time and cost per experiment. We have verified the ability of the new equipment to generate reproducible heterogeneous sand-filled chambers and demonstrated the functionality of the new equipment and procedures by reproducing several gravity-driven fingering experiments conducted by Griffith (2008).

Heterogeneity in lunar anorthosite meteorites: implications for the lunar magma ocean model

PubMed Central

Russell, Sara S.; Joy, Katherine H.; Jeffries, Teresa E.; Consolmagno, Guy J.; Kearsley, Anton

2014-01-01

The lunar magma ocean model is a well-established theory of the early evolution of the Moon. By this model, the Moon was initially largely molten and the anorthositic crust that now covers much of the lunar surface directly crystallized from this enormous magma source. We are undertaking a study of the geochemical characteristics of anorthosites from lunar meteorites to test this model. Rare earth and other element abundances have been measured in situ in relict anorthosite clasts from two feldspathic lunar meteorites: Dhofar 908 and Dhofar 081. The rare earth elements were present in abundances of approximately 0.1 to approximately 10× chondritic (CI) abundance. Every plagioclase exhibited a positive Eu-anomaly, with Eu abundances of up to approximately 20×CI. Calculations of the melt in equilibrium with anorthite show that it apparently crystallized from a magma that was unfractionated with respect to rare earth elements and ranged in abundance from 8 to 80×CI. Comparisons of our data with other lunar meteorites and Apollo samples suggest that there is notable heterogeneity in the trace element abundances of lunar anorthosites, suggesting these samples did not all crystallize from a common magma source. Compositional and isotopic data from other authors also suggest that lunar anorthosites are chemically heterogeneous and have a wide range of ages. These observations may support other models of crust formation on the Moon or suggest that there are complexities in the lunar magma ocean scenario to allow for multiple generations of anorthosite formation. PMID:25114312

Acknowledging patient heterogeneity in economic evaluation : a systematic literature review.

PubMed

Grutters, Janneke P C; Sculpher, Mark; Briggs, Andrew H; Severens, Johan L; Candel, Math J; Stahl, James E; De Ruysscher, Dirk; Boer, Albert; Ramaekers, Bram L T; Joore, Manuela A

2013-02-01

Patient heterogeneity is the part of variability that can be explained by certain patient characteristics (e.g. age, disease stage). Population reimbursement decisions that acknowledge patient heterogeneity could potentially save money and increase population health. To date, however, economic evaluations pay only limited attention to patient heterogeneity. The objective of the present paper is to provide a comprehensive overview of the current knowledge regarding patient heterogeneity within economic evaluation of healthcare programmes. A systematic literature review was performed to identify methodological papers on the topic of patient heterogeneity in economic evaluation. Data were obtained using a keyword search of the PubMed database and manual searches. Handbooks were also included. Relevant data were extracted regarding potential sources of patient heterogeneity, in which of the input parameters of an economic evaluation these occur, methods to acknowledge patient heterogeneity and specific concerns associated with this acknowledgement. A total of 20 articles and five handbooks were included. The relevant sources of patient heterogeneity (demographics, preferences and clinical characteristics) and the input parameters where they occurred (baseline risk, treatment effect, health state utility and resource utilization) were combined in a framework. Methods were derived for the design, analysis and presentation phases of an economic evaluation. Concerns related mainly to the danger of false-positive results and equity issues. By systematically reviewing current knowledge regarding patient heterogeneity within economic evaluations of healthcare programmes, we provide guidance for future economic evaluations. Guidance is provided on which sources of patient heterogeneity to consider, how to acknowledge them in economic evaluation and potential concerns. The improved acknowledgement of patient heterogeneity in future economic evaluations may well improve the efficiency of healthcare.

Dynamic equilibrium of heterogeneous and interconvertible multipotent hematopoietic cell subsets

PubMed Central

Weston, Wendy; Zayas, Jennifer; Perez, Ruben; George, John; Jurecic, Roland

2014-01-01

Populations of hematopoietic stem cells and progenitors are quite heterogeneous and consist of multiple cell subsets with distinct phenotypic and functional characteristics. Some of these subsets also appear to be interconvertible and oscillate between functionally distinct states. The multipotent hematopoietic cell line EML has emerged as a unique model to study the heterogeneity and interconvertibility of multipotent hematopoietic cells. Here we describe extensive phenotypic and functional heterogeneity of EML cells which stems from the coexistence of multiple cell subsets. Each of these subsets is phenotypically and functionally heterogeneous, and displays distinct multilineage differentiation potential, cell cycle profile, proliferation kinetics, and expression pattern of HSC markers and some of the key lineage-associated transcription factors. Analysis of their maintenance revealed that on a population level all EML cell subsets exhibit cell-autonomous interconvertible properties, with the capacity to generate all other subsets and re-establish complete parental EML cell population. Moreover, all EML cell subsets generated during multiple cell generations maintain their distinct phenotypic and functional signatures and interconvertible properties. The model of EML cell line suggests that interconvertible multipotent hematopoietic cell subsets coexist in a homeostatically maintained dynamic equilibrium which is regulated by currently unknown cell-intrinsic mechanisms. PMID:24903657

Dynamic equilibrium of heterogeneous and interconvertible multipotent hematopoietic cell subsets.

PubMed

Weston, Wendy; Zayas, Jennifer; Perez, Ruben; George, John; Jurecic, Roland

2014-06-06

Populations of hematopoietic stem cells and progenitors are quite heterogeneous and consist of multiple cell subsets with distinct phenotypic and functional characteristics. Some of these subsets also appear to be interconvertible and oscillate between functionally distinct states. The multipotent hematopoietic cell line EML has emerged as a unique model to study the heterogeneity and interconvertibility of multipotent hematopoietic cells. Here we describe extensive phenotypic and functional heterogeneity of EML cells which stems from the coexistence of multiple cell subsets. Each of these subsets is phenotypically and functionally heterogeneous, and displays distinct multilineage differentiation potential, cell cycle profile, proliferation kinetics, and expression pattern of HSC markers and some of the key lineage-associated transcription factors. Analysis of their maintenance revealed that on a population level all EML cell subsets exhibit cell-autonomous interconvertible properties, with the capacity to generate all other subsets and re-establish complete parental EML cell population. Moreover, all EML cell subsets generated during multiple cell generations maintain their distinct phenotypic and functional signatures and interconvertible properties. The model of EML cell line suggests that interconvertible multipotent hematopoietic cell subsets coexist in a homeostatically maintained dynamic equilibrium which is regulated by currently unknown cell-intrinsic mechanisms.

Examination of the suitability of an implementation of the Jette localized heterogeneities fluence term L(1)(x,y,z) in an electron beam treatment planning algorithm

NASA Astrophysics Data System (ADS)

Rodebaugh, Raymond Francis, Jr.

2000-11-01

In this project we applied modifications of the Fermi- Eyges multiple scattering theory to attempt to achieve the goals of a fast, accurate electron dose calculation algorithm. The dose was first calculated for an ``average configuration'' based on the patient's anatomy using a modification of the Hogstrom algorithm. It was split into a measured central axis depth dose component based on the material between the source and the dose calculation point, and an off-axis component based on the physics of multiple coulomb scattering for the average configuration. The former provided the general depth dose characteristics along the beam fan lines, while the latter provided the effects of collimation. The Gaussian localized heterogeneities theory of Jette provided the lateral redistribution of the electron fluence by heterogeneities. Here we terminated Jette's infinite series of fluence redistribution terms after the second term. Experimental comparison data were collected for 1 cm thick x 1 cm diameter air and aluminum pillboxes using the Varian 2100C linear accelerator at Rush-Presbyterian- St. Luke's Medical Center. For an air pillbox, the algorithm results were in reasonable agreement with measured data at both 9 and 20 MeV. For the Aluminum pill box, there were significant discrepancies between the results of this algorithm and experiment. This was particularly apparent for the 9 MeV beam. Of course a one cm thick Aluminum heterogeneity is unlikely to be encountered in a clinical situation; the thickness, linear stopping power, and linear scattering power of Aluminum are all well above what would normally be encountered. We found that the algorithm is highly sensitive to the choice of the average configuration. This is an indication that the series of fluence redistribution terms does not converge fast enough to terminate after the second term. It also makes it difficult to apply the algorithm to cases where there are no a priori means of choosing the best average configuration or where there is a complex geometry containing both lowly and highly scattering heterogeneities. There is some hope of decreasing the sensitivity to the average configuration by including portions of the next term of the localized heterogeneities series.

An open, object-based modeling approach for simulating subsurface heterogeneity

NASA Astrophysics Data System (ADS)

Bennett, J.; Ross, M.; Haslauer, C. P.; Cirpka, O. A.

2017-12-01

Characterization of subsurface heterogeneity with respect to hydraulic and geochemical properties is critical in hydrogeology as their spatial distribution controls groundwater flow and solute transport. Many approaches of characterizing subsurface heterogeneity do not account for well-established geological concepts about the deposition of the aquifer materials; those that do (i.e. process-based methods) often require forcing parameters that are difficult to derive from site observations. We have developed a new method for simulating subsurface heterogeneity that honors concepts of sequence stratigraphy, resolves fine-scale heterogeneity and anisotropy of distributed parameters, and resembles observed sedimentary deposits. The method implements a multi-scale hierarchical facies modeling framework based on architectural element analysis, with larger features composed of smaller sub-units. The Hydrogeological Virtual Reality simulator (HYVR) simulates distributed parameter models using an object-based approach. Input parameters are derived from observations of stratigraphic morphology in sequence type-sections. Simulation outputs can be used for generic simulations of groundwater flow and solute transport, and for the generation of three-dimensional training images needed in applications of multiple-point geostatistics. The HYVR algorithm is flexible and easy to customize. The algorithm was written in the open-source programming language Python, and is intended to form a code base for hydrogeological researchers, as well as a platform that can be further developed to suit investigators' individual needs. This presentation will encompass the conceptual background and computational methods of the HYVR algorithm, the derivation of input parameters from site characterization, and the results of groundwater flow and solute transport simulations in different depositional settings.

Automatic analysis of online image data for law enforcement agencies by concept detection and instance search

NASA Astrophysics Data System (ADS)

de Boer, Maaike H. T.; Bouma, Henri; Kruithof, Maarten C.; ter Haar, Frank B.; Fischer, Noëlle M.; Hagendoorn, Laurens K.; Joosten, Bart; Raaijmakers, Stephan

2017-10-01

The information available on-line and off-line, from open as well as from private sources, is growing at an exponential rate and places an increasing demand on the limited resources of Law Enforcement Agencies (LEAs). The absence of appropriate tools and techniques to collect, process, and analyze the volumes of complex and heterogeneous data has created a severe information overload. If a solution is not found, the impact on law enforcement will be dramatic, e.g. because important evidence is missed or the investigation time is too long. Furthermore, there is an uneven level of capabilities to deal with the large volumes of complex and heterogeneous data that come from multiple open and private sources at national level across the EU, which hinders cooperation and information sharing. Consequently, there is a pertinent need to develop tools, systems and processes which expedite online investigations. In this paper, we describe a suite of analysis tools to identify and localize generic concepts, instances of objects and logos in images, which constitutes a significant portion of everyday law enforcement data. We describe how incremental learning based on only a few examples and large-scale indexing are addressed in both concept detection and instance search. Our search technology allows querying of the database by visual examples and by keywords. Our tools are packaged in a Docker container to guarantee easy deployment on a system and our tools exploit possibilities provided by open source toolboxes, contributing to the technical autonomy of LEAs.

Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

PubMed Central

Dinov, Ivo D.; Heavner, Ben; Tang, Ming; Glusman, Gustavo; Chard, Kyle; Darcy, Mike; Madduri, Ravi; Pa, Judy; Spino, Cathie; Kesselman, Carl; Foster, Ian; Deutsch, Eric W.; Price, Nathan D.; Van Horn, John D.; Ames, Joseph; Clark, Kristi; Hood, Leroy; Hampstead, Benjamin M.; Dauer, William; Toga, Arthur W.

2016-01-01

Background A unique archive of Big Data on Parkinson’s Disease is collected, managed and disseminated by the Parkinson’s Progression Markers Initiative (PPMI). The integration of such complex and heterogeneous Big Data from multiple sources offers unparalleled opportunities to study the early stages of prevalent neurodegenerative processes, track their progression and quickly identify the efficacies of alternative treatments. Many previous human and animal studies have examined the relationship of Parkinson’s disease (PD) risk to trauma, genetics, environment, co-morbidities, or life style. The defining characteristics of Big Data–large size, incongruency, incompleteness, complexity, multiplicity of scales, and heterogeneity of information-generating sources–all pose challenges to the classical techniques for data management, processing, visualization and interpretation. We propose, implement, test and validate complementary model-based and model-free approaches for PD classification and prediction. To explore PD risk using Big Data methodology, we jointly processed complex PPMI imaging, genetics, clinical and demographic data. Methods and Findings Collective representation of the multi-source data facilitates the aggregation and harmonization of complex data elements. This enables joint modeling of the complete data, leading to the development of Big Data analytics, predictive synthesis, and statistical validation. Using heterogeneous PPMI data, we developed a comprehensive protocol for end-to-end data characterization, manipulation, processing, cleaning, analysis and validation. Specifically, we (i) introduce methods for rebalancing imbalanced cohorts, (ii) utilize a wide spectrum of classification methods to generate consistent and powerful phenotypic predictions, and (iii) generate reproducible machine-learning based classification that enables the reporting of model parameters and diagnostic forecasting based on new data. We evaluated several complementary model-based predictive approaches, which failed to generate accurate and reliable diagnostic predictions. However, the results of several machine-learning based classification methods indicated significant power to predict Parkinson’s disease in the PPMI subjects (consistent accuracy, sensitivity, and specificity exceeding 96%, confirmed using statistical n-fold cross-validation). Clinical (e.g., Unified Parkinson's Disease Rating Scale (UPDRS) scores), demographic (e.g., age), genetics (e.g., rs34637584, chr12), and derived neuroimaging biomarker (e.g., cerebellum shape index) data all contributed to the predictive analytics and diagnostic forecasting. Conclusions Model-free Big Data machine learning-based classification methods (e.g., adaptive boosting, support vector machines) can outperform model-based techniques in terms of predictive precision and reliability (e.g., forecasting patient diagnosis). We observed that statistical rebalancing of cohort sizes yields better discrimination of group differences, specifically for predictive analytics based on heterogeneous and incomplete PPMI data. UPDRS scores play a critical role in predicting diagnosis, which is expected based on the clinical definition of Parkinson’s disease. Even without longitudinal UPDRS data, however, the accuracy of model-free machine learning based classification is over 80%. The methods, software and protocols developed here are openly shared and can be employed to study other neurodegenerative disorders (e.g., Alzheimer’s, Huntington’s, amyotrophic lateral sclerosis), as well as for other predictive Big Data analytics applications. PMID:27494614

Characterizing Tumor Heterogeneity With Functional Imaging and Quantifying High-Risk Tumor Volume for Early Prediction of Treatment Outcome: Cervical Cancer as a Model

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

Mayr, Nina A., E-mail: Nina.Mayr@osumc.edu; Huang Zhibin; Wang, Jian Z.

2012-07-01

Purpose: Treatment response in cancer has been monitored by measuring anatomic tumor volume (ATV) at various times without considering the inherent functional tumor heterogeneity known to critically influence ultimate treatment outcome: primary tumor control and survival. This study applied dynamic contrast-enhanced (DCE) functional MRI to characterize tumors' heterogeneous subregions with low DCE values, at risk for treatment failure, and to quantify the functional risk volume (FRV) for personalized early prediction of treatment outcome. Methods and Materials: DCE-MRI was performed in 102 stage IB{sub 2}-IVA cervical cancer patients to assess tumor perfusion heterogeneity before and during radiation/chemotherapy. FRV represents the totalmore » volume of tumor voxels with critically low DCE signal intensity (<2.1 compared with precontrast image, determined by previous receiver operator characteristic analysis). FRVs were correlated with treatment outcome (follow-up: 0.2-9.4, mean 6.8 years) and compared with ATVs (Mann-Whitney, Kaplan-Meier, and multivariate analyses). Results: Before and during therapy at 2-2.5 and 4-5 weeks of RT, FRVs >20, >13, and >5 cm{sup 3}, respectively, significantly predicted unfavorable 6-year primary tumor control (p = 0.003, 7.3 Multiplication-Sign 10{sup -8}, 2.0 Multiplication-Sign 10{sup -8}) and disease-specific survival (p = 1.9 Multiplication-Sign 10{sup -4}, 2.1 Multiplication-Sign 10{sup -6}, 2.5 Multiplication-Sign 10{sup -7}, respectively). The FRVs were superior to the ATVs as early predictors of outcome, and the differentiating power of FRVs increased during treatment. Discussion: Our preliminary results suggest that functional tumor heterogeneity can be characterized by DCE-MRI to quantify FRV for predicting ultimate long-term treatment outcome. FRV is a novel functional imaging heterogeneity parameter, superior to ATV, and can be clinically translated for personalized early outcome prediction before or as early as 2-5 weeks into treatment.« less

A pragmatic decision model for inventory management with heterogeneous suppliers

NASA Astrophysics Data System (ADS)

Nakandala, Dilupa; Lau, Henry; Zhang, Jingjing; Gunasekaran, Angappa

2018-05-01

For enterprises, it is imperative that the trade-off between the cost of inventory and risk implications is managed in the most efficient manner. To explore this, we use the common example of a wholesaler operating in an environment where suppliers demonstrate heterogeneous reliability. The wholesaler has partial orders with dual suppliers and uses lateral transshipments. While supplier reliability is a key concern in inventory management, reliable suppliers are more expensive and investment in strategic approaches that improve supplier performance carries a high cost. Here we consider the operational strategy of dual sourcing with reliable and unreliable suppliers and model the total inventory cost where the likely scenario lead-time of the unreliable suppliers extends beyond the scheduling period. We then develop a Customized Integer Programming Optimization Model to determine the optimum size of partial orders with multiple suppliers. In addition to the objective of total cost optimization, this study takes into account the volatility of the cost associated with the uncertainty of an inventory system.

Challenge Paper: Validation of Forensic Techniques for Criminal Prosecution

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

Erbacher, Robert F.; Endicott-Popovsky, Barbara E.; Frincke, Deborah A.

2007-04-10

Abstract: As in many domains, there is increasing agreement in the user and research community that digital forensics analysts would benefit from the extension, development and application of advanced techniques in performing large scale and heterogeneous data analysis. Modern digital forensics analysis of cyber-crimes and cyber-enabled crimes often requires scrutiny of massive amounts of data. For example, a case involving network compromise across multiple enterprises might require forensic analysis of numerous sets of network logs and computer hard drives, potentially involving 100?s of gigabytes of heterogeneous data, or even terabytes or petabytes of data. Also, the goal for forensic analysismore » is to not only determine whether the illicit activity being considered is taking place, but also to identify the source of the activity and the full extent of the compromise or impact on the local network. Even after this analysis, there remains the challenge of using the results in subsequent criminal and civil processes.« less

The Impact of Heterogeneity and Awareness in Modeling Epidemic Spreading on Multiplex Networks

PubMed Central

Scatà, Marialisa; Di Stefano, Alessandro; Liò, Pietro; La Corte, Aurelio

2016-01-01

In the real world, dynamic processes involving human beings are not disjoint. To capture the real complexity of such dynamics, we propose a novel model of the coevolution of epidemic and awareness spreading processes on a multiplex network, also introducing a preventive isolation strategy. Our aim is to evaluate and quantify the joint impact of heterogeneity and awareness, under different socioeconomic conditions. Considering, as case study, an emerging public health threat, Zika virus, we introduce a data-driven analysis by exploiting multiple sources and different types of data, ranging from Big Five personality traits to Google Trends, related to different world countries where there is an ongoing epidemic outbreak. Our findings demonstrate how the proposed model allows delaying the epidemic outbreak and increasing the resilience of nodes, especially under critical economic conditions. Simulation results, using data-driven approach on Zika virus, which has a growing scientific research interest, are coherent with the proposed analytic model. PMID:27848978

Speckle contrast diffuse correlation tomography of complex turbid medium flow

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

Huang, Chong; Irwin, Daniel; Lin, Yu

2015-07-15

Purpose: Developed herein is a three-dimensional (3D) flow contrast imaging system leveraging advancements in the extension of laser speckle contrast imaging theories to deep tissues along with our recently developed finite-element diffuse correlation tomography (DCT) reconstruction scheme. This technique, termed speckle contrast diffuse correlation tomography (scDCT), enables incorporation of complex optical property heterogeneities and sample boundaries. When combined with a reflectance-based design, this system facilitates a rapid segue into flow contrast imaging of larger, in vivo applications such as humans. Methods: A highly sensitive CCD camera was integrated into a reflectance-based optical system. Four long-coherence laser source positions were coupledmore » to an optical switch for sequencing of tomographic data acquisition providing multiple projections through the sample. This system was investigated through incorporation of liquid and solid tissue-like phantoms exhibiting optical properties and flow characteristics typical of human tissues. Computer simulations were also performed for comparisons. A uniquely encountered smear correction algorithm was employed to correct point-source illumination contributions during image capture with the frame-transfer CCD and reflectance setup. Results: Measurements with scDCT on a homogeneous liquid phantom showed that speckle contrast-based deep flow indices were within 12% of those from standard DCT. Inclusion of a solid phantom submerged below the liquid phantom surface allowed for heterogeneity detection and validation. The heterogeneity was identified successfully by reconstructed 3D flow contrast tomography with scDCT. The heterogeneity center and dimensions and averaged relative flow (within 3%) and localization were in agreement with actuality and computer simulations, respectively. Conclusions: A custom cost-effective CCD-based reflectance 3D flow imaging system demonstrated rapid acquisition of dense boundary data and, with further studies, a high potential for translatability to real tissues with arbitrary boundaries. A requisite correction was also found for measurements in the fashion of scDCT to recover accurate speckle contrast of deep tissues.« less

A multiple-point geostatistical approach to quantifying uncertainty for flow and transport simulation in geologically complex environments

NASA Astrophysics Data System (ADS)

Cronkite-Ratcliff, C.; Phelps, G. A.; Boucher, A.

2011-12-01

In many geologic settings, the pathways of groundwater flow are controlled by geologic heterogeneities which have complex geometries. Models of these geologic heterogeneities, and consequently, their effects on the simulated pathways of groundwater flow, are characterized by uncertainty. Multiple-point geostatistics, which uses a training image to represent complex geometric descriptions of geologic heterogeneity, provides a stochastic approach to the analysis of geologic uncertainty. Incorporating multiple-point geostatistics into numerical models provides a way to extend this analysis to the effects of geologic uncertainty on the results of flow simulations. We present two case studies to demonstrate the application of multiple-point geostatistics to numerical flow simulation in complex geologic settings with both static and dynamic conditioning data. Both cases involve the development of a training image from a complex geometric description of the geologic environment. Geologic heterogeneity is modeled stochastically by generating multiple equally-probable realizations, all consistent with the training image. Numerical flow simulation for each stochastic realization provides the basis for analyzing the effects of geologic uncertainty on simulated hydraulic response. The first case study is a hypothetical geologic scenario developed using data from the alluvial deposits in Yucca Flat, Nevada. The SNESIM algorithm is used to stochastically model geologic heterogeneity conditioned to the mapped surface geology as well as vertical drill-hole data. Numerical simulation of groundwater flow and contaminant transport through geologic models produces a distribution of hydraulic responses and contaminant concentration results. From this distribution of results, the probability of exceeding a given contaminant concentration threshold can be used as an indicator of uncertainty about the location of the contaminant plume boundary. The second case study considers a characteristic lava-flow aquifer system in Pahute Mesa, Nevada. A 3D training image is developed by using object-based simulation of parametric shapes to represent the key morphologic features of rhyolite lava flows embedded within ash-flow tuffs. In addition to vertical drill-hole data, transient pressure head data from aquifer tests can be used to constrain the stochastic model outcomes. The use of both static and dynamic conditioning data allows the identification of potential geologic structures that control hydraulic response. These case studies demonstrate the flexibility of the multiple-point geostatistics approach for considering multiple types of data and for developing sophisticated models of geologic heterogeneities that can be incorporated into numerical flow simulations.

Molecular profiling of multiple myeloma: from gene expression analysis to next-generation sequencing.

PubMed

Agnelli, Luca; Tassone, Pierfrancesco; Neri, Antonino

2013-06-01

Multiple myeloma is a fatal malignant proliferation of clonal bone marrow Ig-secreting plasma cells, characterized by wide clinical, biological, and molecular heterogeneity. Herein, global gene and microRNA expression, genome-wide DNA profilings, and next-generation sequencing technology used to investigate the genomic alterations underlying the bio-clinical heterogeneity in multiple myeloma are discussed. High-throughput technologies have undoubtedly allowed a better comprehension of the molecular basis of the disease, a fine stratification, and early identification of high-risk patients, and have provided insights toward targeted therapy studies. However, such technologies are at risk of being affected by laboratory- or cohort-specific biases, and are moreover influenced by high number of expected false positives. This aspect has a major weight in myeloma, which is characterized by large molecular heterogeneity. Therefore, meta-analysis as well as multiple approaches are desirable if not mandatory to validate the results obtained, in line with commonly accepted recommendation for tumor diagnostic/prognostic biomarker studies.

Using Eddy Covariance to Quantify Methane Emissions from a Dynamic Heterogeneous Area

EPA Science Inventory

Measuring emissions of CH4, CO2, H2O, and other greenhouse gases from heterogeneous land area sources is challenging. Dynamic changes within the source area as well as changing environmental conditions make individual point measurements less informative than desired, especially w...

Using Eddy Covariance to Quantify Methane Emission from a Dynamic Heterogeneous Area

EPA Science Inventory

Measuring emissions of CH4, CO2, H2O, and other greenhouse gases from heterogeneous land area sources is challenging. Dynamic changes within the source area as well as changing environmental conditions make individual point measurements less informative than desired, especially w...

A Dashboard for the Italian Computing in ALICE

NASA Astrophysics Data System (ADS)

Elia, D.; Vino, G.; Bagnasco, S.; Crescente, A.; Donvito, G.; Franco, A.; Lusso, S.; Mura, D.; Piano, S.; Platania, G.; ALICE Collaboration

2017-10-01

A dashboard devoted to the computing in the Italian sites for the ALICE experiment at the LHC has been deployed. A combination of different complementary monitoring tools is typically used in most of the Tier-2 sites: this makes somewhat difficult to figure out at a glance the status of the site and to compare information extracted from different sources for debugging purposes. To overcome these limitations a dedicated ALICE dashboard has been designed and implemented in each of the ALICE Tier-2 sites in Italy: in particular, it provides a single, interactive and easily customizable graphical interface where heterogeneous data are presented. The dashboard is based on two main ingredients: an open source time-series database and a dashboard builder tool for visualizing time-series metrics. Various sensors, able to collect data from the multiple data sources, have been also written. A first version of a national computing dashboard has been implemented using a specific instance of the builder to gather data from all the local databases.

GO2OGS 1.0: a versatile workflow to integrate complex geological information with fault data into numerical simulation models

NASA Astrophysics Data System (ADS)

Fischer, T.; Naumov, D.; Sattler, S.; Kolditz, O.; Walther, M.

2015-11-01

We offer a versatile workflow to convert geological models built with the ParadigmTM GOCAD© (Geological Object Computer Aided Design) software into the open-source VTU (Visualization Toolkit unstructured grid) format for usage in numerical simulation models. Tackling relevant scientific questions or engineering tasks often involves multidisciplinary approaches. Conversion workflows are needed as a way of communication between the diverse tools of the various disciplines. Our approach offers an open-source, platform-independent, robust, and comprehensible method that is potentially useful for a multitude of environmental studies. With two application examples in the Thuringian Syncline, we show how a heterogeneous geological GOCAD model including multiple layers and faults can be used for numerical groundwater flow modeling, in our case employing the OpenGeoSys open-source numerical toolbox for groundwater flow simulations. The presented workflow offers the chance to incorporate increasingly detailed data, utilizing the growing availability of computational power to simulate numerical models.

Genomic Analysis of Salmonella enterica Serovar Typhimurium DT160 Associated with a 14-Year Outbreak, New Zealand, 1998–2012

PubMed Central

Benschop, Jackie; Biggs, Patrick J.; Marshall, Jonathan C.; Hayman, David T.S.; Carter, Philip E.; Midwinter, Anne C.; Mather, Alison E.; French, Nigel P.

2017-01-01

During 1998–2012, an extended outbreak of Salmonella enterica serovar Typhimurium definitive type 160 (DT160) affected >3,000 humans and killed wild birds in New Zealand. However, the relationship between DT160 within these 2 host groups and the origin of the outbreak are unknown. Whole-genome sequencing was used to compare 109 Salmonella Typhimurium DT160 isolates from sources throughout New Zealand. We provide evidence that DT160 was introduced into New Zealand around 1997 and rapidly propagated throughout the country, becoming more genetically diverse over time. The genetic heterogeneity was evenly distributed across multiple predicted functional protein groups, and we found no evidence of host group differentiation between isolates collected from human, poultry, bovid, and wild bird sources, indicating ongoing transmission between these host groups. Our findings demonstrate how a comparative genomic approach can be used to gain insight into outbreaks, disease transmission, and the evolution of a multihost pathogen after a probable point-source introduction. PMID:28516864

Intra-tumor heterogeneity: lessons from microbial evolution and clinical implications

PubMed Central

2013-01-01

Multiple subclonal populations of tumor cells can coexist within the same tumor. This intra-tumor heterogeneity will have clinical implications and it is therefore important to identify factors that drive or suppress such heterogeneous tumor progression. Evolutionary biology can provide important insights into this process. In particular, experimental evolution studies of microbial populations, which exist as clonal populations that can diversify into multiple subclones, have revealed important evolutionary processes driving heterogeneity within a population. There are transferrable lessons that can be learnt from these studies that will help us to understand the process of intra-tumor heterogeneity in the clinical setting. In this review, we summarize drivers of microbial diversity that have been identified, such as mutation rate and environmental influences, and discuss how knowledge gained from microbial experimental evolution studies may guide us to identify and understand important selective factors that promote intra-tumor heterogeneity. Furthermore, we discuss how these factors could be used to direct and optimize research efforts to improve patient care, focusing on therapeutic resistance. Finally, we emphasize the need for longitudinal studies to address the impact of these potential tumor heterogeneity-promoting factors on drug resistance, metastatic potential and clinical outcome. PMID:24267946

Intratumoral heterogeneity identified at the epigenetic, genetic and transcriptional level in glioblastoma.

PubMed

Parker, Nicole R; Hudson, Amanda L; Khong, Peter; Parkinson, Jonathon F; Dwight, Trisha; Ikin, Rowan J; Zhu, Ying; Cheng, Zhangkai Jason; Vafaee, Fatemeh; Chen, Jason; Wheeler, Helen R; Howell, Viive M

2016-03-04

Heterogeneity is a hallmark of glioblastoma with intratumoral heterogeneity contributing to variability in responses and resistance to standard treatments. Promoter methylation status of the DNA repair enzyme O(6)-methylguanine DNA methyltransferase (MGMT) is the most important clinical biomarker in glioblastoma, predicting for therapeutic response. However, it does not always correlate with response. This may be due to intratumoral heterogeneity, with a single biopsy unlikely to represent the entire lesion. Aberrations in other DNA repair mechanisms may also contribute. This study investigated intratumoral heterogeneity in multiple glioblastoma tumors with a particular focus on the DNA repair pathways. Transcriptional intratumoral heterogeneity was identified in 40% of cases with variability in MGMT methylation status found in 14% of cases. As well as identifying intratumoral heterogeneity at the transcriptional and epigenetic levels, targeted next generation sequencing identified between 1 and 37 unique sequence variants per specimen. In-silico tools were then able to identify deleterious variants in both the base excision repair and the mismatch repair pathways that may contribute to therapeutic response. As these pathways have roles in temozolomide response, these findings may confound patient management and highlight the importance of assessing multiple tumor biopsies.

A 3D object-based model to simulate highly-heterogeneous, coarse, braided river deposits

NASA Astrophysics Data System (ADS)

Huber, E.; Huggenberger, P.; Caers, J.

2016-12-01

There is a critical need in hydrogeological modeling for geologically more realistic representation of the subsurface. Indeed, widely-used representations of the subsurface heterogeneity based on smooth basis functions such as cokriging or the pilot-point approach fail at reproducing the connectivity of high permeable geological structures that control subsurface solute transport. To realistically model the connectivity of high permeable structures of coarse, braided river deposits, multiple-point statistics and object-based models are promising alternatives. We therefore propose a new object-based model that, according to a sedimentological model, mimics the dominant processes of floodplain dynamics. Contrarily to existing models, this object-based model possesses the following properties: (1) it is consistent with field observations (outcrops, ground-penetrating radar data, etc.), (2) it allows different sedimentological dynamics to be modeled that result in different subsurface heterogeneity patterns, (3) it is light in memory and computationally fast, and (4) it can be conditioned to geophysical data. In this model, the main sedimentological elements (scour fills with open-framework-bimodal gravel cross-beds, gravel sheet deposits, open-framework and sand lenses) and their internal structures are described by geometrical objects. Several spatial distributions are proposed that allow to simulate the horizontal position of the objects on the floodplain as well as the net rate of sediment deposition. The model is grid-independent and any vertical section can be computed algebraically. Furthermore, model realizations can serve as training images for multiple-point statistics. The significance of this model is shown by its impact on the subsurface flow distribution that strongly depends on the sedimentological dynamics modeled. The code will be provided as a free and open-source R-package.

Shared Decision Making Among Clinicians and Asian American and Pacific Islander Sexual and Gender Minorities: An Intersectional Approach to Address a Critical Care Gap

PubMed Central

Xu, Lucy J.; Lopez, Fanny Y.; Jia, Justin L.; Pho, Mai T.; Kim, Karen E.; Chin, Marshall H.

2016-01-01

Abstract Shared decision making (SDM) is a model of patient-provider communication. Little is known about the role of SDM in health disparities among Asian American and Pacific Islander (AAPI) sexual and gender minorities (SGM). We illustrate how issues at the intersection of AAPI and SGM identities affect SDM processes and health outcomes. We discuss experiences of AAPI SGM that are affected by AAPI heterogeneity, SGM stigma, multiple minority group identities, and sources of discrimination. Recommendations for clinical practice, research, policy, community development, and education are offered. PMID:27158858

XaNSoNS: GPU-accelerated simulator of diffraction patterns of nanoparticles

NASA Astrophysics Data System (ADS)

Neverov, V. S.

XaNSoNS is an open source software with GPU support, which simulates X-ray and neutron 1D (or 2D) diffraction patterns and pair-distribution functions (PDF) for amorphous or crystalline nanoparticles (up to ∼107 atoms) of heterogeneous structural content. Among the multiple parameters of the structure the user may specify atomic displacements, site occupancies, molecular displacements and molecular rotations. The software uses general equations nonspecific to crystalline structures to calculate the scattering intensity. It supports four major standards of parallel computing: MPI, OpenMP, Nvidia CUDA and OpenCL, enabling it to run on various architectures, from CPU-based HPCs to consumer-level GPUs.

Information Fusion Issues in the UK Environmental Science Community

NASA Astrophysics Data System (ADS)

Giles, J. R.

2010-12-01

The Earth is a complex, interacting system which cannot be neatly divided by discipline boundaries. To gain an holistic understanding of even a component of an Earth System requires researchers to draw information from multiple disciplines and integrate these to develop a broader understanding. But the barriers to achieving this are formidable. Research funders attempting to encourage the integration of information across disciplines need to take into account culture issues, the impact of intrusion of projects on existing information systems, ontologies and semantics, scale issues, heterogeneity and the uncertainties associated with combining information from diverse sources. Culture - There is a cultural dualism in the environmental sciences were information sharing is both rewarded and discouraged. Researchers who share information both gain new opportunities and risk reducing their chances of being first author in an high-impact journal. The culture of the environmental science community has to be managed to ensure that information fusion activities are encouraged. Intrusion - Existing information systems have an inertia of there own because of the intellectual and financial capital invested within them. Information fusion activities must recognise and seek to minimise the potential impact of their projects on existing systems. Low intrusion information fusions systems such as OGC web-service and the OpenMI Standard are to be preferred to whole-sale replacement of existing systems. Ontology and Semantics - Linking information across disciplines requires a clear understanding of the concepts deployed in the vocabulary used to describe them. Such work is a critical first step to creating routine information fusion. It is essential that national bodies, such as geological surveys organisations, document and publish their ontologies, semantics, etc. Scale - Environmental processes operate at scales ranging from microns to the scale of the Solar System and potentially beyond. The many different scales involved provide serious challenges to information fusion which need to be researched. Heterogeneity - Natural systems are heterogeneous, that is a system consisting of multiple components each of which may have considerable internal variation. Modelling Earth Systems requires recognition of the inherent complexity. Uncertainty - Understanding the uncertainties within a single information source can be difficult. Understanding the uncertainties across a system of linked models, each drawn from multiple information resources, represents a considerable challenge that must be addressed. The challenges to overcome appear insurmountable to individual research groups; but the potential rewards, in terms of a fuller scientific understanding of Earth Systems, are significant. A major international effort must be mounted to tackle these barriers and enable routine information fusion.

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

PubMed

Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

2017-08-10

Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

Scalable and massively parallel Monte Carlo photon transport simulations for heterogeneous computing platforms

NASA Astrophysics Data System (ADS)

Yu, Leiming; Nina-Paravecino, Fanny; Kaeli, David; Fang, Qianqian

2018-01-01

We present a highly scalable Monte Carlo (MC) three-dimensional photon transport simulation platform designed for heterogeneous computing systems. Through the development of a massively parallel MC algorithm using the Open Computing Language framework, this research extends our existing graphics processing unit (GPU)-accelerated MC technique to a highly scalable vendor-independent heterogeneous computing environment, achieving significantly improved performance and software portability. A number of parallel computing techniques are investigated to achieve portable performance over a wide range of computing hardware. Furthermore, multiple thread-level and device-level load-balancing strategies are developed to obtain efficient simulations using multiple central processing units and GPUs.

Modeling the heterogeneous catalytic activity of a single nanoparticle using a first passage time distribution formalism

NASA Astrophysics Data System (ADS)

Das, Anusheela; Chaudhury, Srabanti

2015-11-01

Metal nanoparticles are heterogeneous catalysts and have a multitude of non-equivalent, catalytic sites on the nanoparticle surface. The product dissociation step in such reaction schemes can follow multiple pathways. Proposed here for the first time is a completely analytical theoretical framework, based on the first passage time distribution, that incorporates the effect of heterogeneity in nanoparticle catalysis explicitly by considering multiple, non-equivalent catalytic sites on the nanoparticle surface. Our results show that in nanoparticle catalysis, the effect of dynamic disorder is manifested even at limiting substrate concentrations in contrast to an enzyme that has only one well-defined active site.

Unsupervised multiple kernel learning for heterogeneous data integration.

PubMed

Mariette, Jérôme; Villa-Vialaneix, Nathalie

2018-03-15

Recent high-throughput sequencing advances have expanded the breadth of available omics datasets and the integrated analysis of multiple datasets obtained on the same samples has allowed to gain important insights in a wide range of applications. However, the integration of various sources of information remains a challenge for systems biology since produced datasets are often of heterogeneous types, with the need of developing generic methods to take their different specificities into account. We propose a multiple kernel framework that allows to integrate multiple datasets of various types into a single exploratory analysis. Several solutions are provided to learn either a consensus meta-kernel or a meta-kernel that preserves the original topology of the datasets. We applied our framework to analyse two public multi-omics datasets. First, the multiple metagenomic datasets, collected during the TARA Oceans expedition, was explored to demonstrate that our method is able to retrieve previous findings in a single kernel PCA as well as to provide a new image of the sample structures when a larger number of datasets are included in the analysis. To perform this analysis, a generic procedure is also proposed to improve the interpretability of the kernel PCA in regards with the original data. Second, the multi-omics breast cancer datasets, provided by The Cancer Genome Atlas, is analysed using a kernel Self-Organizing Maps with both single and multi-omics strategies. The comparison of these two approaches demonstrates the benefit of our integration method to improve the representation of the studied biological system. Proposed methods are available in the R package mixKernel, released on CRAN. It is fully compatible with the mixOmics package and a tutorial describing the approach can be found on mixOmics web site http://mixomics.org/mixkernel/. jerome.mariette@inra.fr or nathalie.villa-vialaneix@inra.fr. Supplementary data are available at Bioinformatics online.

Identification of Chiari Type I Malformation subtypes using whole genome expression profiles and cranial base morphometrics

PubMed Central

2014-01-01

Background Chiari Type I Malformation (CMI) is characterized by herniation of the cerebellar tonsils through the foramen magnum at the base of the skull, resulting in significant neurologic morbidity. As CMI patients display a high degree of clinical variability and multiple mechanisms have been proposed for tonsillar herniation, it is hypothesized that this heterogeneous disorder is due to multiple genetic and environmental factors. The purpose of the present study was to gain a better understanding of what factors contribute to this heterogeneity by using an unsupervised statistical approach to define disease subtypes within a case-only pediatric population. Methods A collection of forty-four pediatric CMI patients were ascertained to identify disease subtypes using whole genome expression profiles generated from patient blood and dura mater tissue samples, and radiological data consisting of posterior fossa (PF) morphometrics. Sparse k-means clustering and an extension to accommodate multiple data sources were used to cluster patients into more homogeneous groups using biological and radiological data both individually and collectively. Results All clustering analyses resulted in the significant identification of patient classes, with the pure biological classes derived from patient blood and dura mater samples demonstrating the strongest evidence. Those patient classes were further characterized by identifying enriched biological pathways, as well as correlated cranial base morphological and clinical traits. Conclusions Our results implicate several strong biological candidates warranting further investigation from the dura expression analysis and also identified a blood gene expression profile corresponding to a global down-regulation in protein synthesis. PMID:24962150

Integrative data analysis in clinical psychology research.

PubMed

Hussong, Andrea M; Curran, Patrick J; Bauer, Daniel J

2013-01-01

Integrative data analysis (IDA), a novel framework for conducting the simultaneous analysis of raw data pooled from multiple studies, offers many advantages including economy (i.e., reuse of extant data), power (i.e., large combined sample sizes), the potential to address new questions not answerable by a single contributing study (e.g., combining longitudinal studies to cover a broader swath of the lifespan), and the opportunity to build a more cumulative science (i.e., examining the similarity of effects across studies and potential reasons for dissimilarities). There are also methodological challenges associated with IDA, including the need to account for sampling heterogeneity across studies, to develop commensurate measures across studies, and to account for multiple sources of study differences as they impact hypothesis testing. In this review, we outline potential solutions to these challenges and describe future avenues for developing IDA as a framework for studies in clinical psychology.

Integrative Data Analysis in Clinical Psychology Research

PubMed Central

Hussong, Andrea M.; Curran, Patrick J.; Bauer, Daniel J.

2013-01-01

Integrative Data Analysis (IDA), a novel framework for conducting the simultaneous analysis of raw data pooled from multiple studies, offers many advantages including economy (i.e., reuse of extant data), power (i.e., large combined sample sizes), the potential to address new questions not answerable by a single contributing study (e.g., combining longitudinal studies to cover a broader swath of the lifespan), and the opportunity to build a more cumulative science (i.e., examining the similarity of effects across studies and potential reasons for dissimilarities). There are also methodological challenges associated with IDA, including the need to account for sampling heterogeneity across studies, to develop commensurate measures across studies, and to account for multiple sources of study differences as they impact hypothesis testing. In this review, we outline potential solutions to these challenges and describe future avenues for developing IDA as a framework for studies in clinical psychology. PMID:23394226

Heterogeneous Clustering: Operational and User Impacts

NASA Technical Reports Server (NTRS)

Salm, Saita Wood

1999-01-01

Heterogeneous clustering can improve overall utilization of multiple hosts and can provide better turnaround to users by balancing workloads across hosts. Building a cluster requires both operational changes and revisions in user scripts.

In Silico Gene Prioritization by Integrating Multiple Data Sources

PubMed Central

Zhou, Yingyao; Shields, Robert; Chanda, Sumit K.; Elston, Robert C.; Li, Jing

2011-01-01

Identifying disease genes is crucial to the understanding of disease pathogenesis, and to the improvement of disease diagnosis and treatment. In recent years, many researchers have proposed approaches to prioritize candidate genes by considering the relationship of candidate genes and existing known disease genes, reflected in other data sources. In this paper, we propose an expandable framework for gene prioritization that can integrate multiple heterogeneous data sources by taking advantage of a unified graphic representation. Gene-gene relationships and gene-disease relationships are then defined based on the overall topology of each network using a diffusion kernel measure. These relationship measures are in turn normalized to derive an overall measure across all networks, which is utilized to rank all candidate genes. Based on the informativeness of available data sources with respect to each specific disease, we also propose an adaptive threshold score to select a small subset of candidate genes for further validation studies. We performed large scale cross-validation analysis on 110 disease families using three data sources. Results have shown that our approach consistently outperforms other two state of the art programs. A case study using Parkinson disease (PD) has identified four candidate genes (UBB, SEPT5, GPR37 and TH) that ranked higher than our adaptive threshold, all of which are involved in the PD pathway. In particular, a very recent study has observed a deletion of TH in a patient with PD, which supports the importance of the TH gene in PD pathogenesis. A web tool has been implemented to assist scientists in their genetic studies. PMID:21731658

Resolution analysis of finite fault source inversion using one- and three-dimensional Green's functions 2. Combining seismic and geodetic data

USGS Publications Warehouse

Wald, D.J.; Graves, R.W.

2001-01-01

Using numerical tests for a prescribed heterogeneous earthquake slip distribution, we examine the importance of accurate Green's functions (GF) for finite fault source inversions which rely on coseismic GPS displacements and leveling line uplift alone and in combination with near-source strong ground motions. The static displacements, while sensitive to the three-dimensional (3-D) structure, are less so than seismic waveforms and thus are an important contribution, particularly when used in conjunction with waveform inversions. For numerical tests of an earthquake source and data distribution modeled after the 1994 Northridge earthquake, a joint geodetic and seismic inversion allows for reasonable recovery of the heterogeneous slip distribution on the fault. In contrast, inaccurate 3-D GFs or multiple 1-D GFs allow only partial recovery of the slip distribution given strong motion data alone. Likewise, using just the GPS and leveling line data requires significant smoothing for inversion stability, and hence, only a blurred vision of the prescribed slip is recovered. Although the half-space approximation for computing the surface static deformation field is no longer justifiable based on the high level of accuracy for current GPS data acquisition and the computed differences between 3-D and half-space surface displacements, a layered 1-D approximation to 3-D Earth structure provides adequate representation of the surface displacement field. However, even with the half-space approximation, geodetic data can provide additional slip resolution in the joint seismic and geodetic inversion provided a priori fault location and geometry are correct. Nevertheless, the sensitivity of the static displacements to the Earth structure begs caution for interpretation of surface displacements, particularly those recorded at monuments located in or near basin environments. Copyright 2001 by the American Geophysical Union.

Consecutive five-year analysis of paternal and maternal gene flow and contributions of gametic heterogeneities to overall genetic composition of dispersed seeds of Pinus densiflora (Pinaceae).

PubMed

Iwaizumi, Masakazu G; Takahashi, Makoto; Isoda, Keiya; Austerlitz, Frédéric

2013-09-01

Genetic variability in monoecious woody plant populations results from the assemblage of individuals issued from asymmetrical male and female reproductive functions, produced during spatially and temporarily heterogeneous reproductive and dispersal events. Here we investigated the dispersal patterns and levels of genetic diversity and differentiation of both paternal and maternal gametes in a natural population of Pinus densiflora at the multiple-year scale as long as five consecutive years. • We analyzed the paternity and maternity for 1576 seeds and 454 candidate adult trees using nuclear DNA polymorphisms of diploid biparental embryos and haploid maternal megagametophytes at eight microsatellite loci. • Despite the low levels of genetic differentiation among gamete groups, a two-way AMOVA analysis showed that the parental origin (paternal vs. maternal gametes), the year of gamete production and their interaction had significant effects on the genetic composition of the seeds. While maternal gamete groups showed a significant FST value across the 5 years, this was not true for their paternal counterparts. Within the population, we found that the relative reproductive contributions of the paternal vs. the maternal parent differed among adult trees, the maternal contributions showing a larger year-to-year fluctuation. • The overall genetic variability of dispersed seeds appeared to result from two sources of heterogeneity: the difference between paternal and maternal patterns of reproduction and gamete dispersal and year-to-year heterogeneity of reproduction of adult trees, especially in their maternal reproduction.

Application of data fusion modeling (DFM) to site characterization

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

Porter, D.W.; Gibbs, B.P.; Jones, W.F.

1996-01-01

Subsurface characterization is faced with substantial uncertainties because the earth is very heterogeneous, and typical data sets are fragmented and disparate. DFM removes many of the data limitations of current methods to quantify and reduce uncertainty for a variety of data types and models. DFM is a methodology to compute hydrogeological state estimates and their uncertainties from three sources of information: measured data, physical laws, and statistical models for spatial heterogeneities. The benefits of DFM are savings in time and cost through the following: the ability to update models in real time to help guide site assessment, improved quantification ofmore » uncertainty for risk assessment, and improved remedial design by quantifying the uncertainty in safety margins. A Bayesian inverse modeling approach is implemented with a Gauss Newton method where spatial heterogeneities are viewed as Markov random fields. Information from data, physical laws, and Markov models is combined in a Square Root Information Smoother (SRIS). Estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. An application of DFM to the Old Burial Ground at the DOE Savannah River Site will be presented. DFM estimates and quantifies uncertainty in hydrogeological parameters using variably saturated flow numerical modeling to constrain the estimation. Then uncertainties are propagated through the transport modeling to quantify the uncertainty in tritium breakthrough curves at compliance points.« less

Application of data fusion modeling (DFM) to site characterization

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

Porter, D.W.; Gibbs, B.P.; Jones, W.F.

1996-12-31

Subsurface characterization is faced with substantial uncertainties because the earth is very heterogeneous, and typical data sets are fragmented and disparate. DFM removes many of the data limitations of current methods to quantify and reduce uncertainty for a variety of data types and models. DFM is a methodology to compute hydrogeological state estimates and their uncertainties from three sources of information: measured data, physical laws, and statistical models for spatial heterogeneities. The benefits of DFM are savings in time and cost through the following: the ability to update models in real time to help guide site assessment, improved quantification ofmore » uncertainty for risk assessment, and improved remedial design by quantifying the uncertainty in safety margins. A Bayesian inverse modeling approach is implemented with a Gauss Newton method where spatial heterogeneities are viewed as Markov random fields. Information from data, physical laws, and Markov models is combined in a Square Root Information Smoother (SRIS). Estimates and uncertainties can be computed for heterogeneous hydraulic conductivity fields in multiple geological layers from the usually sparse hydraulic conductivity data and the often more plentiful head data. An application of DFM to the Old Burial Ground at the DOE Savannah River Site will be presented. DFM estimates and quantifies uncertainty in hydrogeological parameters using variably saturated flow numerical modeling to constrain the estimation. Then uncertainties are propagated through the transport modeling to quantify the uncertainty in tritium breakthrough curves at compliance points.« less

Three-Dimensional Magnetic Levitation Culture System Simulating White Adipose Tissue.

PubMed

Tseng, Hubert; Daquinag, Alexes C; Souza, Glauco R; Kolonin, Mikhail G

2018-01-01

White adipose tissue (WAT) has attracted interest for tissue engineering and cell-based therapies as an abundant source of adipose stem/stromal cells (ASC). However, technical challenges in WAT cell culture have limited its applications in regenerative medicine. Traditional two-dimensional (2D) cell culture models, which are essentially monolayers of cells on glass or plastic substrates, inadequately represent tissue architecture, biochemical concentration gradients, substrate stiffness, and most importantly for WAT research, cell phenotypic heterogeneity. Physiological cell culture platforms for WAT modeling must recapitulate the native diversity of cell types and their coordination within the organ. For this purpose, we developed a three-dimensional (3D) model using magnetic levitation. Here, we describe our protocol that we successfully employed to build adipose tissue organoids (adipospheres) that preserve the heterogeneity of the constituent cell types in vitro. We demonstrate the capacity of assembling adipospheres from multiple cell types, including ASCs, endohtelial cells, and leukocytes that recreate tissue organization. These adipospheres mimicked WAT organogenesis in that they enabled the formation of vessel-like endothelial structures with lumens and differentiation of unilocular adipocytes. Altogether, magnetic levitation is a cell culture platform that recreates tissue structure, function, and heterogeneity in vitro, and serves as a foundation for high-throughput WAT tissue culture and analysis.

XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets.

PubMed

Yu, Yao; Hu, Hao; Bohlender, Ryan J; Hu, Fulan; Chen, Jiun-Sheng; Holt, Carson; Fowler, Jerry; Guthery, Stephen L; Scheet, Paul; Hildebrandt, Michelle A T; Yandell, Mark; Huff, Chad D

2018-04-06

High-throughput sequencing data are increasingly being made available to the research community for secondary analyses, providing new opportunities for large-scale association studies. However, heterogeneity in target capture and sequencing technologies often introduce strong technological stratification biases that overwhelm subtle signals of association in studies of complex traits. Here, we introduce the Cross-Platform Association Toolkit, XPAT, which provides a suite of tools designed to support and conduct large-scale association studies with heterogeneous sequencing datasets. XPAT includes tools to support cross-platform aware variant calling, quality control filtering, gene-based association testing and rare variant effect size estimation. To evaluate the performance of XPAT, we conducted case-control association studies for three diseases, including 783 breast cancer cases, 272 ovarian cancer cases, 205 Crohn disease cases and 3507 shared controls (including 1722 females) using sequencing data from multiple sources. XPAT greatly reduced Type I error inflation in the case-control analyses, while replicating many previously identified disease-gene associations. We also show that association tests conducted with XPAT using cross-platform data have comparable performance to tests using matched platform data. XPAT enables new association studies that combine existing sequencing datasets to identify genetic loci associated with common diseases and other complex traits.

Synaptic heterogeneity and stimulus-induced modulation of depression in central synapses.

PubMed

Hunter, J D; Milton, J G

2001-08-01

Short-term plasticity is a pervasive feature of synapses. Synapses exhibit many forms of plasticity operating over a range of time scales. We develop an optimization method that allows rapid characterization of synapses with multiple time scales of facilitation and depression. Investigation of paired neurons that are postsynaptic to the same identified interneuron in the buccal ganglion of Aplysia reveals that the responses of the two neurons differ in the magnitude of synaptic depression. Also, for single neurons, prolonged stimulation of the presynaptic neuron causes stimulus-induced increases in the early phase of synaptic depression. These observations can be described by a model that incorporates two availability factors, e.g., depletable vesicle pools or desensitizing receptor populations, with different time courses of recovery, and a single facilitation component. This model accurately predicts the responses to novel stimuli. The source of synaptic heterogeneity is identified with variations in the relative sizes of the two availability factors, and the stimulus-induced decrement in the early synaptic response is explained by a slowing of the recovery rate of one of the availability factors. The synaptic heterogeneity and stimulus-induced modifications in synaptic depression observed here emphasize that synaptic efficacy depends on both the individual properties of synapses and their past history.

Magma mixing and the generation of isotopically juvenile silicic magma at Yellowstone caldera inferred from coupling 238U–230Th ages with trace elements and Hf and O isotopes in zircon and Pb isotopes in sanidine

USGS Publications Warehouse

Stelten, Mark E.; Cooper, Kari M.; Vazquez, Jorge A.; Reid, Mary R.; Barfod, Gry H.; Wimpenny, Josh; Yin, Qing-Zhu

2013-01-01

The nature of compositional heterogeneity within large silicic magma bodies has important implications for how silicic reservoirs are assembled and evolve through time. We examine compositional heterogeneity in the youngest (~170 to 70 ka) post-caldera volcanism at Yellowstone caldera, the Central Plateau Member (CPM) rhyolites, as a case study. We compare 238U–230Th age, trace-element, and Hf isotopic data from zircons, and major-element, Ba, and Pb isotopic data from sanidines hosted in two CPM rhyolites (Hayden Valley and Solfatara Plateau flows) and one extracaldera rhyolite (Gibbon River flow), all of which erupted near the caldera margin ca. 100 ka. The Hayden Valley flow hosts two zircon populations and one sanidine population that are consistent with residence in the CPM reservoir. The Gibbon River flow hosts one zircon population that is compositionally distinct from Hayden Valley flow zircons. The Solfatara Plateau flow contains multiple sanidine populations and all three zircon populations found in the Hayden Valley and Gibbon River flows, demonstrating that the Solfatara Plateau flow formed by mixing extracaldera magma with the margin of the CPM reservoir. This process highlights the dynamic nature of magmatic interactions at the margins of large silicic reservoirs. More generally, Hf isotopic data from the CPM zircons provide the first direct evidence for isotopically juvenile magmas contributing mass to the youngest post-caldera magmatic system and demonstrate that the sources contributing magma to the CPM reservoir were heterogeneous in 176Hf/177Hf at ca. 100 ka. Thus, the limited compositional variability of CPM glasses reflects homogenization occurring within the CPM reservoir, not a homogeneous source.

Explorative search of distributed bio-data to answer complex biomedical questions

PubMed Central

2014-01-01

Background The huge amount of biomedical-molecular data increasingly produced is providing scientists with potentially valuable information. Yet, such data quantity makes difficult to find and extract those data that are most reliable and most related to the biomedical questions to be answered, which are increasingly complex and often involve many different biomedical-molecular aspects. Such questions can be addressed only by comprehensively searching and exploring different types of data, which frequently are ordered and provided by different data sources. Search Computing has been proposed for the management and integration of ranked results from heterogeneous search services. Here, we present its novel application to the explorative search of distributed biomedical-molecular data and the integration of the search results to answer complex biomedical questions. Results A set of available bioinformatics search services has been modelled and registered in the Search Computing framework, and a Bioinformatics Search Computing application (Bio-SeCo) using such services has been created and made publicly available at http://www.bioinformatics.deib.polimi.it/bio-seco/seco/. It offers an integrated environment which eases search, exploration and ranking-aware combination of heterogeneous data provided by the available registered services, and supplies global results that can support answering complex multi-topic biomedical questions. Conclusions By using Bio-SeCo, scientists can explore the very large and very heterogeneous biomedical-molecular data available. They can easily make different explorative search attempts, inspect obtained results, select the most appropriate, expand or refine them and move forward and backward in the construction of a global complex biomedical query on multiple distributed sources that could eventually find the most relevant results. Thus, it provides an extremely useful automated support for exploratory integrated bio search, which is fundamental for Life Science data driven knowledge discovery. PMID:24564278

Distributed Earth observation data integration and on-demand services based on a collaborative framework of geospatial data service gateway

NASA Astrophysics Data System (ADS)

Xie, Jibo; Li, Guoqing

2015-04-01

Earth observation (EO) data obtained by air-borne or space-borne sensors has the characteristics of heterogeneity and geographical distribution of storage. These data sources belong to different organizations or agencies whose data management and storage methods are quite different and geographically distributed. Different data sources provide different data publish platforms or portals. With more Remote sensing sensors used for Earth Observation (EO) missions, different space agencies have distributed archived massive EO data. The distribution of EO data archives and system heterogeneity makes it difficult to efficiently use geospatial data for many EO applications, such as hazard mitigation. To solve the interoperable problems of different EO data systems, an advanced architecture of distributed geospatial data infrastructure is introduced to solve the complexity of distributed and heterogeneous EO data integration and on-demand processing in this paper. The concept and architecture of geospatial data service gateway (GDSG) is proposed to build connection with heterogeneous EO data sources by which EO data can be retrieved and accessed with unified interfaces. The GDSG consists of a set of tools and service to encapsulate heterogeneous geospatial data sources into homogenous service modules. The GDSG modules includes EO metadata harvesters and translators, adaptors to different type of data system, unified data query and access interfaces, EO data cache management, and gateway GUI, etc. The GDSG framework is used to implement interoperability and synchronization between distributed EO data sources with heterogeneous architecture. An on-demand distributed EO data platform is developed to validate the GDSG architecture and implementation techniques. Several distributed EO data achieves are used for test. Flood and earthquake serves as two scenarios for the use cases of distributed EO data integration and interoperability.

Nonparametric estimation of the heterogeneity of a random medium using compound Poisson process modeling of wave multiple scattering.

PubMed

Le Bihan, Nicolas; Margerin, Ludovic

2009-07-01

In this paper, we present a nonparametric method to estimate the heterogeneity of a random medium from the angular distribution of intensity of waves transmitted through a slab of random material. Our approach is based on the modeling of forward multiple scattering using compound Poisson processes on compact Lie groups. The estimation technique is validated through numerical simulations based on radiative transfer theory.

Helioviewer.org: Enhanced Solar & Heliospheric Data Visualization

NASA Astrophysics Data System (ADS)

Stys, J. E.; Ireland, J.; Hughitt, V. K.; Mueller, D.

2013-12-01

Helioviewer.org enables the simultaneous exploration of multiple heterogeneous solar data sets. In the latest iteration of this open-source web application, Hinode XRT and Yohkoh SXT join SDO, SOHO, STEREO, and PROBA2 as supported data sources. A newly enhanced user-interface expands the utility of Helioviewer.org by adding annotations backed by data from the Heliospheric Events Knowledgebase (HEK). Helioviewer.org can now overlay solar feature and event data via interactive marker pins, extended regions, data labels, and information panels. An interactive time-line provides enhanced browsing and visualization to image data set coverage and solar events. The addition of a size-of-the-Earth indicator provides a sense of the scale to solar and heliospheric features for education and public outreach purposes. Tight integration with the Virtual Solar Observatory and SDO AIA cutout service enable solar physicists to seamlessly import science data into their SSW/IDL or SunPy/Python data analysis environments.

Conducting requirements analyses for research using routinely collected health data: a model driven approach.

PubMed

de Lusignan, Simon; Cashman, Josephine; Poh, Norman; Michalakidis, Georgios; Mason, Aaron; Desombre, Terry; Krause, Paul

2012-01-01

Medical research increasingly requires the linkage of data from different sources. Conducting a requirements analysis for a new application is an established part of software engineering, but rarely reported in the biomedical literature; and no generic approaches have been published as to how to link heterogeneous health data. Literature review, followed by a consensus process to define how requirements for research, using, multiple data sources might be modeled. We have developed a requirements analysis: i-ScheDULEs - The first components of the modeling process are indexing and create a rich picture of the research study. Secondly, we developed a series of reference models of progressive complexity: Data flow diagrams (DFD) to define data requirements; unified modeling language (UML) use case diagrams to capture study specific and governance requirements; and finally, business process models, using business process modeling notation (BPMN). These requirements and their associated models should become part of research study protocols.

Medium change based image estimation from application of inverse algorithms to coda wave measurements

NASA Astrophysics Data System (ADS)

Zhan, Hanyu; Jiang, Hanwan; Jiang, Ruinian

2018-03-01

Perturbations worked as extra scatters will cause coda waveform distortions; thus, coda wave with long propagation time and traveling path are sensitive to micro-defects in strongly heterogeneous media such as concretes. In this paper, we conduct varied external loads on a life-size concrete slab which contains multiple existing micro-cracks, and a couple of sources and receivers are installed to collect coda wave signals. The waveform decorrelation coefficients (DC) at different loads are calculated for all available source-receiver pair measurements. Then inversions of the DC results are applied to estimate the associated distribution density values in three-dimensional regions through kernel sensitivity model and least-square algorithms, which leads to the images indicating the micro-cracks positions. This work provides an efficiently non-destructive approach to detect internal defects and damages of large-size concrete structures.

Catchment heterogeneity controls emergent archetype concentration-discharge relationships

NASA Astrophysics Data System (ADS)

Musolff, A.; Fleckenstein, J. H.; Rao, P. S.; Jawitz, J. W.

2017-12-01

Relationships between in-stream dissolved solute concentrations (C) and discharge (Q) are often-used indicators of catchment-scale processes and their interference with human activities. Here we analyze observational C-Q relationships from 61 catchments and 8 different solutes across a wide range of land-uses and discharge regimes. This analysis is combined with a parsimonious stochastic modeling approach to test how C-Q relationships arise from spatial heterogeneity in catchment solute sources coupled with different timescales of biogeochemical reactions. The observational data exhibit archetypical dilution, enrichment, and constant C-Q patterns. Moreover, with land-use intensification we find decreasing C variability relative to Q variability (chemostatic export regime). Our model indicates that the dominant driver of emergent C-Q patterns was structured heterogeneity of solute sources implemented as correlation of source concentration to travel time. Regardless of the C-Q pattern, with decreasing source heterogeneity we consistently find lower variability in C than in Q and a dominance of chemostatic export regimes. Here, the variance in exported loads is determined primarily by variance of Q. We conclude that efforts to improve stream water quality and ecological integrity in intensely managed catchments should lead away from landscape homogenization by introducing structured source heterogeneity. References: Musolff, A., J. H. Fleckenstein, P. S. C. Rao, and J. W. Jawitz (2017), Emergent archetype patterns of coupled hydrologic and biogeochemical responses in catchments, Geophys. Res. Lett., 44(9), 4143-4151, doi: 10.1002/2017GL072630.

Explosion localization and characterization via infrasound using numerical modeling

NASA Astrophysics Data System (ADS)

Fee, D.; Kim, K.; Iezzi, A. M.; Matoza, R. S.; Jolly, A. D.; De Angelis, S.; Diaz Moreno, A.; Szuberla, C.

2017-12-01

Numerous methods have been applied to locate, detect, and characterize volcanic and anthropogenic explosions using infrasound. Far-field localization techniques typically use back-azimuths from multiple arrays (triangulation) or Reverse Time Migration (RTM, or back-projection). At closer ranges, networks surrounding a source may use Time Difference of Arrival (TDOA), semblance, station-pair double difference, etc. However, at volcanoes and regions with topography or obstructions that block the direct path of sound, recent studies have shown that numerical modeling is necessary to provide an accurate source location. A heterogeneous and moving atmosphere (winds) may also affect the location. The time reversal mirror (TRM) application of Kim et al. (2015) back-propagates the wavefield using a Finite Difference Time Domain (FDTD) algorithm, with the source corresponding to the location of peak convergence. Although it provides high-resolution source localization and can account for complex wave propagation, TRM is computationally expensive and limited to individual events. Here we present a new technique, termed RTM-FDTD, which integrates TRM and FDTD. Travel time and transmission loss information is computed from each station to the entire potential source grid from 3-D Green's functions derived via FDTD. The wave energy is then back-projected and stacked at each grid point, with the maximum corresponding to the likely source. We apply our method to detect and characterize thousands of explosions from Yasur Volcano, Vanuatu and Etna Volcano, Italy, which both provide complex wave propagation and multiple source locations. We compare our results with those from more traditional methods (e.g. semblance), and suggest our method is preferred as it is computationally less expensive than TRM but still integrates numerical modeling. RTM-FDTD could be applied to volcanic other anthropogenic sources at a wide variety of ranges and scenarios. Kim, K., Lees, J.M., 2015. Imaging volcanic infrasound sources using time reversal mirror algorithm. Geophysical Journal International 202, 1663-1676.

Transcription elongation. Heterogeneous tracking of RNA polymerase and its biological implications.

PubMed

Imashimizu, Masahiko; Shimamoto, Nobuo; Oshima, Taku; Kashlev, Mikhail

2014-01-01

Regulation of transcription elongation via pausing of RNA polymerase has multiple physiological roles. The pausing mechanism depends on the sequence heterogeneity of the DNA being transcribed, as well as on certain interactions of polymerase with specific DNA sequences. In order to describe the mechanism of regulation, we introduce the concept of heterogeneity into the previously proposed alternative models of elongation, power stroke and Brownian ratchet. We also discuss molecular origins and physiological significances of the heterogeneity.

Research on detecting heterogeneous fibre from cotton based on linear CCD camera

NASA Astrophysics Data System (ADS)

Zhang, Xian-bin; Cao, Bing; Zhang, Xin-peng; Shi, Wei

2009-07-01

The heterogeneous fibre in cotton make a great impact on production of cotton textile, it will have a bad effect on the quality of product, thereby affect economic benefits and market competitive ability of corporation. So the detecting and eliminating of heterogeneous fibre is particular important to improve machining technics of cotton, advance the quality of cotton textile and reduce production cost. There are favorable market value and future development for this technology. An optical detecting system obtains the widespread application. In this system, we use a linear CCD camera to scan the running cotton, then the video signals are put into computer and processed according to the difference of grayscale, if there is heterogeneous fibre in cotton, the computer will send an order to drive the gas nozzle to eliminate the heterogeneous fibre. In the paper, we adopt monochrome LED array as the new detecting light source, it's lamp flicker, stability of luminous intensity, lumens depreciation and useful life are all superior to fluorescence light. We analyse the reflection spectrum of cotton and various heterogeneous fibre first, then select appropriate frequency of the light source, we finally adopt violet LED array as the new detecting light source. The whole hardware structure and software design are introduced in this paper.

Boosting probabilistic graphical model inference by incorporating prior knowledge from multiple sources.

PubMed

Praveen, Paurush; Fröhlich, Holger

2013-01-01

Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available.

Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

USGS Publications Warehouse

Weisberg, Peter J.; Dilts, Thomas E.; Becker, Miles E.; Young, Jock S.; Wong-Kone, Diane C.; Newton, Wesley E.; Ammon, Elisabeth M.

2014-01-01

Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R2 range: 0.03–0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.

Guild-specific responses of avian species richness to LiDAR-derived habitat heterogeneity

NASA Astrophysics Data System (ADS)

Weisberg, Peter J.; Dilts, Thomas E.; Becker, Miles E.; Young, Jock S.; Wong-Kone, Diane C.; Newton, Wesley E.; Ammon, Elisabeth M.

2014-08-01

Ecological niche theory implies that more heterogeneous habitats have the potential to support greater biodiversity. Positive heterogeneity-diversity relationships have been found for most studies investigating animal taxa, although negative relationships also occur and the scale dependence of heterogeneity-diversity relationships is little known. We investigated multi-scale, heterogeneity-diversity relationships for bird communities in a semi-arid riparian landscape, using airborne LiDAR data to derive key measures of structural habitat complexity. Habitat heterogeneity-diversity relationships were generally positive, although the overall strength of relationships varied across avian life history guilds (R2 range: 0.03-0.41). Best predicted were the species richness indices of cavity nesters, habitat generalists, woodland specialists, and foliage foragers. Heterogeneity-diversity relationships were also strongly scale-dependent, with strongest associations at the 200-m scale (4 ha) and weakest associations at the 50-m scale (0.25 ha). Our results underscore the value of LiDAR data for fine-grained quantification of habitat structure, as well as the need for biodiversity studies to incorporate variation among life-history guilds and to simultaneously consider multiple guild functional types (e.g. nesting, foraging, habitat). Results suggest that certain life-history guilds (foliage foragers, cavity nesters, woodland specialists) are more susceptible than others (ground foragers, ground nesters, low nesters) to experiencing declines in local species richness if functional elements of habitat heterogeneity are lost. Positive heterogeneity-diversity relationships imply that riparian conservation efforts need to not only provide high-quality riparian habitat locally, but also to provide habitat heterogeneity across multiple scales.

Accounting for aquifer heterogeneity from geological data to management tools.

PubMed

Blouin, Martin; Martel, Richard; Gloaguen, Erwan

2013-01-01

A nested workflow of multiple-point geostatistics (MPG) and sequential Gaussian simulation (SGS) was tested on a study area of 6 km(2) located about 20 km northwest of Quebec City, Canada. In order to assess its geological and hydrogeological parameter heterogeneity and to provide tools to evaluate uncertainties in aquifer management, direct and indirect field measurements are used as inputs in the geostatistical simulations to reproduce large and small-scale heterogeneities. To do so, the lithological information is first associated to equivalent hydrogeological facies (hydrofacies) according to hydraulic properties measured at several wells. Then, heterogeneous hydrofacies (HF) realizations are generated using a prior geological model as training image (TI) with the MPG algorithm. The hydraulic conductivity (K) heterogeneity modeling within each HF is finally computed using SGS algorithm. Different K models are integrated in a finite-element hydrogeological model to calculate multiple transport simulations. Different scenarios exhibit variations in mass transport path and dispersion associated with the large- and small-scale heterogeneity respectively. Three-dimensional maps showing the probability of overpassing different thresholds are presented as examples of management tools. © 2012, The Author(s). Groundwater © 2012, National Ground Water Association.

Estimating and validating surface energy fluxes at field scale over a heterogeneous land surfaces based on two-source energy balance model (TSEB)

USDA-ARS?s Scientific Manuscript database

Accurate estimation of surface energy fluxes at field scale over large areas has the potential to improve agricultural water management in arid and semiarid watersheds. Remote sensing may be the only viable approach for mapping fluxes over heterogeneous landscapes. The Two-Source Energy Balance mode...

Hapl-o-Mat: open-source software for HLA haplotype frequency estimation from ambiguous and heterogeneous data.

PubMed

Schäfer, Christian; Schmidt, Alexander H; Sauter, Jürgen

2017-05-30

Knowledge of HLA haplotypes is helpful in many settings as disease association studies, population genetics, or hematopoietic stem cell transplantation. Regarding the recruitment of unrelated hematopoietic stem cell donors, HLA haplotype frequencies of specific populations are used to optimize both donor searches for individual patients and strategic donor registry planning. However, the estimation of haplotype frequencies from HLA genotyping data is challenged by the large amount of genotype data, the complex HLA nomenclature, and the heterogeneous and ambiguous nature of typing records. To meet these challenges, we have developed the open-source software Hapl-o-Mat. It estimates haplotype frequencies from population data including an arbitrary number of loci using an expectation-maximization algorithm. Its key features are the processing of different HLA typing resolutions within a given population sample and the handling of ambiguities recorded via multiple allele codes or genotype list strings. Implemented in C++, Hapl-o-Mat facilitates efficient haplotype frequency estimation from large amounts of genotype data. We demonstrate its accuracy and performance on the basis of artificial and real genotype data. Hapl-o-Mat is a versatile and efficient software for HLA haplotype frequency estimation. Its capability of processing various forms of HLA genotype data allows for a straightforward haplotype frequency estimation from typing records usually found in stem cell donor registries.

Expression of cholinesterase gene(s) in human brain tissues: translational evidence for multiple mRNA species.

PubMed Central

Soreq, H; Zevin-Sonkin, D; Razon, N

1984-01-01

To resolve the origin(s) of the molecular heterogeneity of human nervous system cholinesterases (ChEs), we used Xenopus oocytes, which produce biologically active ChE when microinjected with unfractionated brain mRNA. The RNA was prepared from primary gliomas, meningiomas and embryonic brain, each of which expresses ChE activity with distinct substrate specificities and molecular forms. Sucrose gradient fractionation of DMSO-denatured mRNA from these sources revealed three size classes of ChE-inducing mRNAs, sedimenting at approximately 32S, 20S and 9S. The amounts of these different classes of ChE-inducing mRNAs varied between the three tissue sources examined. To distinguish between ChEs produced in oocytes and having different substrate specificities, their activity was determined in the presence of selective inhibitors. Both 'true' (acetylcholine hydrolase, EC 3.1.1.7) and 'pseudo' (acylcholine acylhydrolase, EC 3.1.1.8) multimeric cholinesterase activities were found in the mRNA-injected oocytes. Moreover, human brain mRNAs inducing 'true' and 'pseudo' ChE activities had different size distribution, indicating that different mRNAs might be translated into various types of ChEs. These findings imply that the heterogeneity of ChEs in the human nervous system is not limited to the post-translational level, but extends to the level of mRNA. PMID:6745236

Clinical results of HIS, RIS, PACS integration using data integration CASE tools

NASA Astrophysics Data System (ADS)

Taira, Ricky K.; Chan, Hing-Ming; Breant, Claudine M.; Huang, Lu J.; Valentino, Daniel J.

1995-05-01

Current infrastructure research in PACS is dominated by the development of communication networks (local area networks, teleradiology, ATM networks, etc.), multimedia display workstations, and hierarchical image storage architectures. However, limited work has been performed on developing flexible, expansible, and intelligent information processing architectures for the vast decentralized image and text data repositories prevalent in healthcare environments. Patient information is often distributed among multiple data management systems. Current large-scale efforts to integrate medical information and knowledge sources have been costly with limited retrieval functionality. Software integration strategies to unify distributed data and knowledge sources is still lacking commercially. Systems heterogeneity (i.e., differences in hardware platforms, communication protocols, database management software, nomenclature, etc.) is at the heart of the problem and is unlikely to be standardized in the near future. In this paper, we demonstrate the use of newly available CASE (computer- aided software engineering) tools to rapidly integrate HIS, RIS, and PACS information systems. The advantages of these tools include fast development time (low-level code is generated from graphical specifications), and easy system maintenance (excellent documentation, easy to perform changes, and centralized code repository in an object-oriented database). The CASE tools are used to develop and manage the `middle-ware' in our client- mediator-serve architecture for systems integration. Our architecture is scalable and can accommodate heterogeneous database and communication protocols.

Origin and Role of Recycled Crust in Flood Basalt Magmatism: Case Study of the Central East Greenland Rifted Margin

NASA Astrophysics Data System (ADS)

Brown, E.; Lesher, C. E.

2015-12-01

Continental flood basalts (CFB) are extreme manifestations of mantle melting derived from chemically/isotopically heterogeneous mantle. Much of this heterogeneity comes from lithospheric material recycled into the convecting mantle by a range of mechanisms (e.g. subduction, delamination). The abundance and petrogenetic origins of these lithologies thus provide important constraints on the geodynamical origins of CFB magmatism, and the timescales of lithospheric recycling in the mantle. Basalt geochemistry has long been used to constrain the compositions and mean ages of recycled lithologies in the mantle. Typically, this work assumes the isotopic compositions of the basalts are the same as their mantle source(s). However, because basalts are mixtures of melts derived from different sources (having different fusibilities) generated over ranges of P and T, their isotopic compositions only indirectly represent the isotopic compositions of their mantle sources[1]. Thus, relating basalts compositions to mantle source compositions requires information about the melting process itself. To investigate the nature of lithologic source heterogeneity while accounting for the effects of melting during CFB magmatism, we utilize the REEBOX PRO forward melting model[2], which simulates adiabatic decompression melting in lithologically heterogeneous mantle. We apply the model to constrain the origins and abundance of mantle heterogeneity associated with Paleogene flood basalts erupted during the rift-to-drift transition of Pangea breakup along the Central East Greenland rifted margin of the North Atlantic igneous province. We show that these basalts were derived by melting of a hot, lithologically heterogeneous source containing depleted, subduction-modified lithospheric mantle, and <10% recycled oceanic crust. The Paleozoic mean age we calculate for this recycled crust is consistent with an origin in the region's prior subduction history, and with estimates for the mean age of recycled crust in the modern Iceland plume[3]. These results suggest that this lithospheric material was not recycled into the lower mantle before becoming entrained in the Iceland plume. [1] Rudge et al. (2013). GCA, 114, p112-143; [2] Brown & Lesher (2014). Nat. Geo., 7, p820-824; [3] Thirlwall et al. (2004). GCA, 68, p361-386

Growth advantage of Escherichia coli O104:H4 strains on 5-N-acetyl-9-O-acetyl neuraminic acid as a carbon source is dependent on heterogeneous phage-Borne nanS-p esterases.

PubMed

Saile, Nadja; Schwarz, Lisa; Eißenberger, Kristina; Klumpp, Jochen; Fricke, Florian W; Schmidt, Herbert

2018-06-01

Enterohemorrhagic E. coli (EHEC) are serious bacterial pathogens which are able to cause a hemorrhagic colitis or the life-threatening hemolytic-uremic syndrome (HUS) in humans. EHEC strains can carry different numbers of phage-borne nanS-p alleles that are responsible for acetic acid release from mucin from bovine submaxillary gland and 5-N-acetyl-9-O-acetyl neuraminic acid (Neu5,9Ac 2 ), a carbohydrate present in mucin. Thus, Neu5,9Ac 2 can be transformed to 5-N-acetyl neuraminic acid, an energy source used by E. coli strains. We hypothesize that these NanS-p proteins are involved in competitive growth of EHEC in the gastrointestinal tract of humans and animals. The aim of the current study was to demonstrate and characterize the nanS-p alleles of the 2011 E. coli O104:H4 outbreak strain LB226692 and analyze whether the presence of multiple nanS-p alleles in the LB226692 genome causes a competitive growth advantage over a commensal E. coli strain. We detected and characterized five heterogeneous phage-borne nanS-p alleles in the genome of E. coli O104:H4 outbreak strain LB226692 by in silico analysis of its genome. Furthermore, successive deletion of all nanS-p alleles, subsequent complementation with recombinant NanS-p13-His, and in vitro co-culturing experiments with the commensal E. coli strain AMC 198 were conducted. We could show that nanS-p genes of E. coli O104:H4 are responsible for growth inhibition of strain AMC 198, when Neu5,9Ac 2 was used as sole carbon source in co-culture. The results of this study let us suggest that multiple nanS-p alleles may confer a growth advantage by outcompeting other E. coli strains in Neu5,9Ac 2 rich environments, such as mucus in animal and human gut. Copyright © 2018 Elsevier GmbH. All rights reserved.

Modelling, Design, Growth and Characterization of Strain Balanced Quantum Cascade Lasers (3-11mum), grown by Gas Source Molecular Beam Epitaxy

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Neelanjan

Quantum Cascade Laser (QCL) is a compact room temperature (RT) source of mid-infrared radiation, which can be used for spectroscopic detection of trace amount of chemicals. The mid-infrared spectral range between (3-11 microm), has a dense array of absorption lines of numerous molecules, due to the presence of fundamental vibrational modes. The goal of this thesis can be subdivided into two parts. Firstly, short wavelength QCLs, emitting below 4microm, perform poorly at RT, due to inter-valley Gamma --- L carrier scattering, carrier escape to the continuum, heat removal from the core region at high power density corresponding to short wavelength operation, and large interface scattering due to highly strained materials. Secondly, it is desirable to have a single QCL based source emitting between 6-10microm, which be used to detect multiple molecules having their peak absorptions far apart, inside this spectral range. However, gain bandwidth of a single core QCL is relatively small, so laser emission cannot be tuned over a wide spectral range. This thesis describes the working principle of a QCL based on superlattice transport, rate equations, scattering mechanism, and waveguide design. The choice of the material system for this work and the fundamentals of band structure engineering has been derived. Gas source molecular beam epitaxy - growth optimization and characterization is one of the most important features of this work, especially for short wavelength QCLs, and has been explained in depth. Different strategies for design of active region design of short wavelength QCL and heterogeneous broadband QCL has been explored. The major milestones, of this research was the world's first watt level continuous wave (CW), RT demonstration at 3.76 microm, which was followed by another milestone of the first CW, RT demonstration at 3.39microm and 3.55microm, and finally the elusive result of QCL emitting at CW, RT at a wavelength as short as lambda ~3microm, a record. In the longer wavelength side a novel approach to design of strain balanced QCLs based on the same material composition was demonstrated. Finally a gapless heterogeneous broadband QCL, incorporating multiple QCL cores in a single active region, with record tunability between 6.1-10.2 microm, was demonstrated.

Cascaded discrimination of normal, abnormal, and confounder classes in histopathology: Gleason grading of prostate cancer

PubMed Central

2012-01-01

Background Automated classification of histopathology involves identification of multiple classes, including benign, cancerous, and confounder categories. The confounder tissue classes can often mimic and share attributes with both the diseased and normal tissue classes, and can be particularly difficult to identify, both manually and by automated classifiers. In the case of prostate cancer, they may be several confounding tissue types present in a biopsy sample, posing as major sources of diagnostic error for pathologists. Two common multi-class approaches are one-shot classification (OSC), where all classes are identified simultaneously, and one-versus-all (OVA), where a “target” class is distinguished from all “non-target” classes. OSC is typically unable to handle discrimination of classes of varying similarity (e.g. with images of prostate atrophy and high grade cancer), while OVA forces several heterogeneous classes into a single “non-target” class. In this work, we present a cascaded (CAS) approach to classifying prostate biopsy tissue samples, where images from different classes are grouped to maximize intra-group homogeneity while maximizing inter-group heterogeneity. Results We apply the CAS approach to categorize 2000 tissue samples taken from 214 patient studies into seven classes: epithelium, stroma, atrophy, prostatic intraepithelial neoplasia (PIN), and prostate cancer Gleason grades 3, 4, and 5. A series of increasingly granular binary classifiers are used to split the different tissue classes until the images have been categorized into a single unique class. Our automatically-extracted image feature set includes architectural features based on location of the nuclei within the tissue sample as well as texture features extracted on a per-pixel level. The CAS strategy yields a positive predictive value (PPV) of 0.86 in classifying the 2000 tissue images into one of 7 classes, compared with the OVA (0.77 PPV) and OSC approaches (0.76 PPV). Conclusions Use of the CAS strategy increases the PPV for a multi-category classification system over two common alternative strategies. In classification problems such as histopathology, where multiple class groups exist with varying degrees of heterogeneity, the CAS system can intelligently assign class labels to objects by performing multiple binary classifications according to domain knowledge. PMID:23110677

Genetic heterogeneity of hepatitis E virus in Darfur, Sudan, and neighboring Chad.

PubMed

Nicand, Elisabeth; Armstrong, Gregory L; Enouf, Vincent; Guthmann, Jean Paul; Guerin, Jean-Philippe; Caron, Mélanie; Nizou, Jacques Yves; Andraghetti, Roberta

2005-12-01

The within-outbreak diversity of hepatitis E virus (HEV) was studied during the outbreak of hepatitis E that occurred in Sudan in 2004. Specimens were collected from internally displaced persons living in a Sudanese refugee camp and two camps implanted in Chad. A comparison of the sequences in the ORF2 region of 23 Sudanese isolates and five HEV samples from the two Chadian camps displayed a high similarity (>99.7%) to strains belonging to Genotype 1. But four isolates collected in one of the Chadian camps were close to Genotype 2. Circulation of divergent strains argues for possible multiple sources of infection. Copyright (c) 2005 Wiley-Liss, inc.

Design and Implementation of a Distributed Version of the NASA Engine Performance Program

NASA Technical Reports Server (NTRS)

Cours, Jeffrey T.

1994-01-01

Distributed NEPP is a new version of the NASA Engine Performance Program that runs in parallel on a collection of Unix workstations connected through a network. The program is fault-tolerant, efficient, and shows significant speed-up in a multi-user, heterogeneous environment. This report describes the issues involved in designing distributed NEPP, the algorithms the program uses, and the performance distributed NEPP achieves. It develops an analytical model to predict and measure the performance of the simple distribution, multiple distribution, and fault-tolerant distribution algorithms that distributed NEPP incorporates. Finally, the appendices explain how to use distributed NEPP and document the organization of the program's source code.

Characterization of continuously distributed cortical water diffusion rates with a stretched-exponential model.

PubMed

Bennett, Kevin M; Schmainda, Kathleen M; Bennett, Raoqiong Tong; Rowe, Daniel B; Lu, Hanbing; Hyde, James S

2003-10-01

Experience with diffusion-weighted imaging (DWI) shows that signal attenuation is consistent with a multicompartmental theory of water diffusion in the brain. The source of this so-called nonexponential behavior is a topic of debate, because the cerebral cortex contains considerable microscopic heterogeneity and is therefore difficult to model. To account for this heterogeneity and understand its implications for current models of diffusion, a stretched-exponential function was developed to describe diffusion-related signal decay as a continuous distribution of sources decaying at different rates, with no assumptions made about the number of participating sources. DWI experiments were performed using a spin-echo diffusion-weighted pulse sequence with b-values of 500-6500 s/mm(2) in six rats. Signal attenuation curves were fit to a stretched-exponential function, and 20% of the voxels were better fit to the stretched-exponential model than to a biexponential model, even though the latter model had one more adjustable parameter. Based on the calculated intravoxel heterogeneity measure, the cerebral cortex contains considerable heterogeneity in diffusion. The use of a distributed diffusion coefficient (DDC) is suggested to measure mean intravoxel diffusion rates in the presence of such heterogeneity. Copyright 2003 Wiley-Liss, Inc.

Stretching and smearing of chemical heterogeneity by melting and melt migration beneath mid-ocean ridges

NASA Astrophysics Data System (ADS)

Liu, B.; Liang, Y.

2017-12-01

The size of mantle source heterogeneity is important to the interpretation of isotopic signals observed in residual peridotites and basalts. During concurrent melting and melt migration beneath a mid-ocean ridge, both porosity and melt velocity increase upward, resulting in an upward increase in the effective transport velocity for a trace element. Hence a chemical heterogeneity of finite size will be stretched during its transport in the upwelling mantle. This melt migration induced chemical deformation can be quantified by a simple stretching factor. During equilibrium melting, the isotope signals of Sr, Nd and Hf in a 1 km size enriched mantle will be stretched to 2 6 km at the top of the melting column, depending on the style of melt migration. A finite rate of diffusive exchange between residual minerals and partial melt will result in smearing of chemical heterogeneity during its transport in the upwelling melting column. A Gaussian-shaped enriched source in depleted background mantle would be gradually deformed its transit through the melting column. The width of the enriched signal spreads out between the fronts of melt and solid while its amplitude decreases. This melt migration induced smearing also cause mixing of nearby heterogeneities or absorption of enriched heterogeneity by the ambient mantle. Smaller heterogeneities in the solid is more efficiently mixed or aborted by the background mantle than larger ones. Mixing of heterogeneities in the melt depends on the size in the same sense although the erupted melt is more homogenized due to melt accumulation and magma chamber process. The mapping of chemical heterogeneities observed in residual peridotites and basalts into their source region is therefore highly nonlinear. We will show that the observed variations in Nd and Hf isotopes in the global MORB and abyssal peridotites are consistent with kilometer-scale enriched heterogeneities embedded in depleted MORB mantle.

L1 Retrotransposon Heterogeneity in Ovarian Tumor Cell Evolution.

PubMed

Nguyen, Thu H M; Carreira, Patricia E; Sanchez-Luque, Francisco J; Schauer, Stephanie N; Fagg, Allister C; Richardson, Sandra R; Davies, Claire M; Jesuadian, J Samuel; Kempen, Marie-Jeanne H C; Troskie, Robin-Lee; James, Cini; Beaven, Elizabeth A; Wallis, Tristan P; Coward, Jermaine I G; Chetty, Naven P; Crandon, Alexander J; Venter, Deon J; Armes, Jane E; Perrin, Lewis C; Hooper, John D; Ewing, Adam D; Upton, Kyle R; Faulkner, Geoffrey J

2018-06-26

LINE-1 (L1) retrotransposons are a source of insertional mutagenesis in tumor cells. However, the clinical significance of L1 mobilization during tumorigenesis remains unclear. Here, we applied retrotransposon capture sequencing (RC-seq) to multiple single-cell clones isolated from five ovarian cancer cell lines and HeLa cells and detected endogenous L1 retrotransposition in vitro. We then applied RC-seq to ovarian tumor and matched blood samples from 19 patients and identified 88 tumor-specific L1 insertions. In one tumor, an intronic de novo L1 insertion supplied a novel cis-enhancer to the putative chemoresistance gene STC1. Notably, the tumor subclone carrying the STC1 L1 mutation increased in prevalence after chemotherapy, further increasing STC1 expression. We also identified hypomethylated donor L1s responsible for new L1 insertions in tumors and cultivated cancer cells. These congruent in vitro and in vivo results highlight L1 insertional mutagenesis as a common component of ovarian tumorigenesis and cancer genome heterogeneity. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

The Fireball integrated code package

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

Dobranich, D.; Powers, D.A.; Harper, F.T.

1997-07-01

Many deep-space satellites contain a plutonium heat source. An explosion, during launch, of a rocket carrying such a satellite offers the potential for the release of some of the plutonium. The fireball following such an explosion exposes any released plutonium to a high-temperature chemically-reactive environment. Vaporization, condensation, and agglomeration processes can alter the distribution of plutonium-bearing particles. The Fireball code package simulates the integrated response of the physical and chemical processes occurring in a fireball and the effect these processes have on the plutonium-bearing particle distribution. This integrated treatment of multiple phenomena represents a significant improvement in the state ofmore » the art for fireball simulations. Preliminary simulations of launch-second scenarios indicate: (1) most plutonium vaporization occurs within the first second of the fireball; (2) large non-aerosol-sized particles contribute very little to plutonium vapor production; (3) vaporization and both homogeneous and heterogeneous condensation occur simultaneously; (4) homogeneous condensation transports plutonium down to the smallest-particle sizes; (5) heterogeneous condensation precludes homogeneous condensation if sufficient condensation sites are available; and (6) agglomeration produces larger-sized particles but slows rapidly as the fireball grows.« less

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks

PubMed Central

Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic. PMID:28245222

Generic, network schema agnostic sparse tensor factorization for single-pass clustering of heterogeneous information networks.

PubMed

Wu, Jibing; Meng, Qinggang; Deng, Su; Huang, Hongbin; Wu, Yahui; Badii, Atta

2017-01-01

Heterogeneous information networks (e.g. bibliographic networks and social media networks) that consist of multiple interconnected objects are ubiquitous. Clustering analysis is an effective method to understand the semantic information and interpretable structure of the heterogeneous information networks, and it has attracted the attention of many researchers in recent years. However, most studies assume that heterogeneous information networks usually follow some simple schemas, such as bi-typed networks or star network schema, and they can only cluster one type of object in the network each time. In this paper, a novel clustering framework is proposed based on sparse tensor factorization for heterogeneous information networks, which can cluster multiple types of objects simultaneously in a single pass without any network schema information. The types of objects and the relations between them in the heterogeneous information networks are modeled as a sparse tensor. The clustering issue is modeled as an optimization problem, which is similar to the well-known Tucker decomposition. Then, an Alternating Least Squares (ALS) algorithm and a feasible initialization method are proposed to solve the optimization problem. Based on the tensor factorization, we simultaneously partition different types of objects into different clusters. The experimental results on both synthetic and real-world datasets have demonstrated that our proposed clustering framework, STFClus, can model heterogeneous information networks efficiently and can outperform state-of-the-art clustering algorithms as a generally applicable single-pass clustering method for heterogeneous network which is network schema agnostic.

Glucose uptake heterogeneity of the leg muscles is similar between patients with multiple sclerosis and healthy controls during walking.

PubMed

Kindred, John H; Ketelhut, Nathaniel B; Rudroff, Thorsten

2015-02-01

Difficulties in ambulation are one of the main problems reported by patients with multiple sclerosis. A previous study by our research group showed increased recruitment of muscle groups during walking, but the influence of skeletal muscle properties, such as muscle fiber activity, has not been fully elucidated. The purpose of this investigation was to use the novel method of calculating glucose uptake heterogeneity in the leg muscles of patients with multiple sclerosis and compare these results to healthy controls. Eight patients with multiple sclerosis (4 men) and 8 healthy controls (4 men) performed 15 min of treadmill walking at a comfortable self-selected speed following muscle strength tests. Participants were injected with ≈ 8 mCi of [(18)F]-fluorodeoxyglucose during walking after which positron emission tomography/computed tomography imaging was performed. No differences in muscle strength were detected between multiple sclerosis and control groups (P>0.27). Within the multiple sclerosis, group differences in muscle volume existed between the stronger and weaker legs in the vastus lateralis, semitendinosus, and semimembranosus (P<0.03). Glucose uptake heterogeneity between the groups was not different for any muscle group or individual muscle of the legs (P>0.16, P≥0.05). Patients with multiple sclerosis and healthy controls showed similar muscle fiber activity during walking. Interpretations of these results, with respect to our previous study, suggest that walking difficulties in patients with multiple sclerosis may be more associated with altered central nervous system motor patterns rather than alterations in skeletal muscle properties. Published by Elsevier Ltd.

Homogeneous spectral spanning of terahertz semiconductor lasers with radio frequency modulation.

PubMed

Wan, W J; Li, H; Zhou, T; Cao, J C

2017-03-08

Homogeneous broadband and electrically pumped semiconductor radiation sources emitting in the terahertz regime are highly desirable for various applications, including spectroscopy, chemical sensing, and gas identification. In the frequency range between 1 and 5 THz, unipolar quantum cascade lasers employing electron inter-subband transitions in multiple-quantum-well structures are the most powerful semiconductor light sources. However, these devices are normally characterized by either a narrow emission spectrum due to the narrow gain bandwidth of the inter-subband optical transitions or an inhomogeneous broad terahertz spectrum from lasers with heterogeneous stacks of active regions. Here, we report the demonstration of homogeneous spectral spanning of long-cavity terahertz semiconductor quantum cascade lasers based on a bound-to-continuum and resonant phonon design under radio frequency modulation. At a single drive current, the terahertz spectrum under radio frequency modulation continuously spans 330 GHz (~8% of the central frequency), which is the record for single plasmon waveguide terahertz lasers with a bound-to-continuum design. The homogeneous broadband terahertz sources can be used for spectroscopic applications, i.e., GaAs etalon transmission measurement and ammonia gas identification.

Homogeneous spectral spanning of terahertz semiconductor lasers with radio frequency modulation

PubMed Central

Wan, W. J.; Li, H.; Zhou, T.; Cao, J. C.

2017-01-01

Homogeneous broadband and electrically pumped semiconductor radiation sources emitting in the terahertz regime are highly desirable for various applications, including spectroscopy, chemical sensing, and gas identification. In the frequency range between 1 and 5 THz, unipolar quantum cascade lasers employing electron inter-subband transitions in multiple-quantum-well structures are the most powerful semiconductor light sources. However, these devices are normally characterized by either a narrow emission spectrum due to the narrow gain bandwidth of the inter-subband optical transitions or an inhomogeneous broad terahertz spectrum from lasers with heterogeneous stacks of active regions. Here, we report the demonstration of homogeneous spectral spanning of long-cavity terahertz semiconductor quantum cascade lasers based on a bound-to-continuum and resonant phonon design under radio frequency modulation. At a single drive current, the terahertz spectrum under radio frequency modulation continuously spans 330 GHz (~8% of the central frequency), which is the record for single plasmon waveguide terahertz lasers with a bound-to-continuum design. The homogeneous broadband terahertz sources can be used for spectroscopic applications, i.e., GaAs etalon transmission measurement and ammonia gas identification. PMID:28272492

Applications of tissue heterogeneity corrections and biologically effective dose volume histograms in assessing the doses for accelerated partial breast irradiation using an electronic brachytherapy source.

PubMed

Shi, Chengyu; Guo, Bingqi; Cheng, Chih-Yao; Eng, Tony; Papanikolaou, Nikos

2010-09-21

A low-energy electronic brachytherapy source (EBS), the model S700 Axxent x-ray device developed by Xoft Inc., has been used in high dose rate (HDR) intracavitary accelerated partial breast irradiation (APBI) as an alternative to an Ir-192 source. The prescription dose and delivery schema of the electronic brachytherapy APBI plan are the same as the Ir-192 plan. However, due to its lower mean energy than the Ir-192 source, an EBS plan has dosimetric and biological features different from an Ir-192 source plan. Current brachytherapy treatment planning methods may have large errors in treatment outcome prediction for an EBS plan. Two main factors contribute to the errors: the dosimetric influence of tissue heterogeneities and the enhancement of relative biological effectiveness (RBE) of electronic brachytherapy. This study quantified the effects of these two factors and revisited the plan quality of electronic brachytherapy APBI. The influence of tissue heterogeneities is studied by a Monte Carlo method and heterogeneous 'virtual patient' phantoms created from CT images and structure contours; the effect of RBE enhancement in the treatment outcome was estimated by biologically effective dose (BED) distribution. Ten electronic brachytherapy APBI cases were studied. The results showed that, for electronic brachytherapy cases, tissue heterogeneities and patient boundary effect decreased dose to the target and skin but increased dose to the bones. On average, the target dose coverage PTV V(100) reduced from 95.0% in water phantoms (planned) to only 66.7% in virtual patient phantoms (actual). The actual maximum dose to the ribs is 3.3 times higher than the planned dose; the actual mean dose to the ipsilateral breast and maximum dose to the skin were reduced by 22% and 17%, respectively. Combining the effect of tissue heterogeneities and RBE enhancement, BED coverage of the target was 89.9% in virtual patient phantoms with RBE enhancement (actual BED) as compared to 95.2% in water phantoms without RBE enhancement (planned BED). About 10% increase in the source output is required to raise BED PTV V(100) to 95%. As a conclusion, the composite effect of dose reduction in the target due to heterogeneities and RBE enhancement results in a net effect of 5.3% target BED coverage loss for electronic brachytherapy. Therefore, it is suggested that about 10% increase in the source output may be necessary to achieve sufficient target coverage higher than 95%.

Applications of tissue heterogeneity corrections and biologically effective dose volume histograms in assessing the doses for accelerated partial breast irradiation using an electronic brachytherapy source

NASA Astrophysics Data System (ADS)

Shi, Chengyu; Guo, Bingqi; Cheng, Chih-Yao; Eng, Tony; Papanikolaou, Nikos

2010-09-01

A low-energy electronic brachytherapy source (EBS), the model S700 Axxent™ x-ray device developed by Xoft Inc., has been used in high dose rate (HDR) intracavitary accelerated partial breast irradiation (APBI) as an alternative to an Ir-192 source. The prescription dose and delivery schema of the electronic brachytherapy APBI plan are the same as the Ir-192 plan. However, due to its lower mean energy than the Ir-192 source, an EBS plan has dosimetric and biological features different from an Ir-192 source plan. Current brachytherapy treatment planning methods may have large errors in treatment outcome prediction for an EBS plan. Two main factors contribute to the errors: the dosimetric influence of tissue heterogeneities and the enhancement of relative biological effectiveness (RBE) of electronic brachytherapy. This study quantified the effects of these two factors and revisited the plan quality of electronic brachytherapy APBI. The influence of tissue heterogeneities is studied by a Monte Carlo method and heterogeneous 'virtual patient' phantoms created from CT images and structure contours; the effect of RBE enhancement in the treatment outcome was estimated by biologically effective dose (BED) distribution. Ten electronic brachytherapy APBI cases were studied. The results showed that, for electronic brachytherapy cases, tissue heterogeneities and patient boundary effect decreased dose to the target and skin but increased dose to the bones. On average, the target dose coverage PTV V100 reduced from 95.0% in water phantoms (planned) to only 66.7% in virtual patient phantoms (actual). The actual maximum dose to the ribs is 3.3 times higher than the planned dose; the actual mean dose to the ipsilateral breast and maximum dose to the skin were reduced by 22% and 17%, respectively. Combining the effect of tissue heterogeneities and RBE enhancement, BED coverage of the target was 89.9% in virtual patient phantoms with RBE enhancement (actual BED) as compared to 95.2% in water phantoms without RBE enhancement (planned BED). About 10% increase in the source output is required to raise BED PTV V100 to 95%. As a conclusion, the composite effect of dose reduction in the target due to heterogeneities and RBE enhancement results in a net effect of 5.3% target BED coverage loss for electronic brachytherapy. Therefore, it is suggested that about 10% increase in the source output may be necessary to achieve sufficient target coverage higher than 95%.

Development of a flattening filter free multiple source model for use as an independent, Monte Carlo, dose calculation, quality assurance tool for clinical trials.

PubMed

Faught, Austin M; Davidson, Scott E; Popple, Richard; Kry, Stephen F; Etzel, Carol; Ibbott, Geoffrey S; Followill, David S

2017-09-01

The Imaging and Radiation Oncology Core-Houston (IROC-H) Quality Assurance Center (formerly the Radiological Physics Center) has reported varying levels of compliance from their anthropomorphic phantom auditing program. IROC-H studies have suggested that one source of disagreement between institution submitted calculated doses and measurement is the accuracy of the institution's treatment planning system dose calculations and heterogeneity corrections used. In order to audit this step of the radiation therapy treatment process, an independent dose calculation tool is needed. Monte Carlo multiple source models for Varian flattening filter free (FFF) 6 MV and FFF 10 MV therapeutic x-ray beams were commissioned based on central axis depth dose data from a 10 × 10 cm 2 field size and dose profiles for a 40 × 40 cm 2 field size. The models were validated against open-field measurements in a water tank for field sizes ranging from 3 × 3 cm 2 to 40 × 40 cm 2 . The models were then benchmarked against IROC-H's anthropomorphic head and neck phantom and lung phantom measurements. Validation results, assessed with a ±2%/2 mm gamma criterion, showed average agreement of 99.9% and 99.0% for central axis depth dose data for FFF 6 MV and FFF 10 MV models, respectively. Dose profile agreement using the same evaluation technique averaged 97.8% and 97.9% for the respective models. Phantom benchmarking comparisons were evaluated with a ±3%/2 mm gamma criterion, and agreement averaged 90.1% and 90.8% for the respective models. Multiple source models for Varian FFF 6 MV and FFF 10 MV beams have been developed, validated, and benchmarked for inclusion in an independent dose calculation quality assurance tool for use in clinical trial audits. © 2017 American Association of Physicists in Medicine.

Development of a Monte Carlo multiple source model for inclusion in a dose calculation auditing tool.

PubMed

Faught, Austin M; Davidson, Scott E; Fontenot, Jonas; Kry, Stephen F; Etzel, Carol; Ibbott, Geoffrey S; Followill, David S

2017-09-01

The Imaging and Radiation Oncology Core Houston (IROC-H) (formerly the Radiological Physics Center) has reported varying levels of agreement in their anthropomorphic phantom audits. There is reason to believe one source of error in this observed disagreement is the accuracy of the dose calculation algorithms and heterogeneity corrections used. To audit this component of the radiotherapy treatment process, an independent dose calculation tool is needed. Monte Carlo multiple source models for Elekta 6 MV and 10 MV therapeutic x-ray beams were commissioned based on measurement of central axis depth dose data for a 10 × 10 cm 2 field size and dose profiles for a 40 × 40 cm 2 field size. The models were validated against open field measurements consisting of depth dose data and dose profiles for field sizes ranging from 3 × 3 cm 2 to 30 × 30 cm 2 . The models were then benchmarked against measurements in IROC-H's anthropomorphic head and neck and lung phantoms. Validation results showed 97.9% and 96.8% of depth dose data passed a ±2% Van Dyk criterion for 6 MV and 10 MV models respectively. Dose profile comparisons showed an average agreement using a ±2%/2 mm criterion of 98.0% and 99.0% for 6 MV and 10 MV models respectively. Phantom plan comparisons were evaluated using ±3%/2 mm gamma criterion, and averaged passing rates between Monte Carlo and measurements were 87.4% and 89.9% for 6 MV and 10 MV models respectively. Accurate multiple source models for Elekta 6 MV and 10 MV x-ray beams have been developed for inclusion in an independent dose calculation tool for use in clinical trial audits. © 2017 American Association of Physicists in Medicine.

Improving the interoperability of biomedical ontologies with compound alignments.

PubMed

Oliveira, Daniela; Pesquita, Catia

2018-01-09

Ontologies are commonly used to annotate and help process life sciences data. Although their original goal is to facilitate integration and interoperability among heterogeneous data sources, when these sources are annotated with distinct ontologies, bridging this gap can be challenging. In the last decade, ontology matching systems have been evolving and are now capable of producing high-quality mappings for life sciences ontologies, usually limited to the equivalence between two ontologies. However, life sciences research is becoming increasingly transdisciplinary and integrative, fostering the need to develop matching strategies that are able to handle multiple ontologies and more complex relations between their concepts. We have developed ontology matching algorithms that are able to find compound mappings between multiple biomedical ontologies, in the form of ternary mappings, finding for instance that "aortic valve stenosis"(HP:0001650) is equivalent to the intersection between "aortic valve"(FMA:7236) and "constricted" (PATO:0001847). The algorithms take advantage of search space filtering based on partial mappings between ontology pairs, to be able to handle the increased computational demands. The evaluation of the algorithms has shown that they are able to produce meaningful results, with precision in the range of 60-92% for new mappings. The algorithms were also applied to the potential extension of logical definitions of the OBO and the matching of several plant-related ontologies. This work is a first step towards finding more complex relations between multiple ontologies. The evaluation shows that the results produced are significant and that the algorithms could satisfy specific integration needs.

A novel multi-segment path analysis based on a heterogeneous velocity model for the localization of acoustic emission sources in complex propagation media.

PubMed

Gollob, Stephan; Kocur, Georg Karl; Schumacher, Thomas; Mhamdi, Lassaad; Vogel, Thomas

2017-02-01

In acoustic emission analysis, common source location algorithms assume, independently of the nature of the propagation medium, a straight (shortest) wave path between the source and the sensors. For heterogeneous media such as concrete, the wave travels in complex paths due to the interaction with the dissimilar material contents and with the possible geometrical and material irregularities present in these media. For instance, cracks and large air voids present in concrete influence significantly the way the wave travels, by causing wave path deviations. Neglecting these deviations by assuming straight paths can introduce significant errors to the source location results. In this paper, a novel source localization method called FastWay is proposed. It accounts, contrary to most available shortest path-based methods, for the different effects of material discontinuities (cracks and voids). FastWay, based on a heterogeneous velocity model, uses the fastest rather than the shortest travel paths between the source and each sensor. The method was evaluated both numerically and experimentally and the results from both evaluation tests show that, in general, FastWay was able to locate sources of acoustic emissions more accurately and reliably than the traditional source localization methods. Copyright © 2016 Elsevier B.V. All rights reserved.

Evaluating the combined effects of source zone mass release rates and aquifer heterogeneity on solute discharge uncertainty

NASA Astrophysics Data System (ADS)

de Barros, Felipe P. J.

2018-07-01

Quantifying the uncertainty in solute mass discharge at an environmentally sensitive location is key to assess the risks due to groundwater contamination. Solute mass fluxes are strongly affected by the spatial variability of hydrogeological properties as well as release conditions at the source zone. This paper provides a methodological framework to investigate the interaction between the ubiquitous heterogeneity of the hydraulic conductivity and the mass release rate at the source zone on the uncertainty of mass discharge. Through the use of perturbation theory, we derive analytical and semi-analytical expressions for the statistics of the solute mass discharge at a control plane in a three-dimensional aquifer while accounting for the solute mass release rates at the source. The derived solutions are limited to aquifers displaying low-to-mild heterogeneity. Results illustrate the significance of the source zone mass release rate in controlling the mass discharge uncertainty. The relative importance of the mass release rate on the mean solute discharge depends on the distance between the source and the control plane. On the other hand, we find that the solute release rate at the source zone has a strong impact on the variance of the mass discharge. Within a risk context, we also compute the peak mean discharge as a function of the parameters governing the spatial heterogeneity of the hydraulic conductivity field and mass release rates at the source zone. The proposed physically-based framework is application-oriented, computationally efficient and capable of propagating uncertainty from different parameters onto risk metrics. Furthermore, it can be used for preliminary screening purposes to guide site managers to perform system-level sensitivity analysis and better allocate resources.

A regulation probability model-based meta-analysis of multiple transcriptomics data sets for cancer biomarker identification.

PubMed

Xie, Xin-Ping; Xie, Yu-Feng; Wang, Hong-Qiang

2017-08-23

Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent but subtle gene activity patterns across studies. Study heterogeneity needs to be addressed carefully for this goal. This paper proposes a regulation probability model-based meta-analysis, jGRP, for identifying differentially expressed genes (DEGs). The method integrates multiple transcriptomics data sets in a gene regulatory space instead of in a gene expression space, which makes it easy to capture and manage data heterogeneity across studies from different laboratories or platforms. Specifically, we transform gene expression profiles into a united gene regulation profile across studies by mathematically defining two gene regulation events between two conditions and estimating their occurring probabilities in a sample. Finally, a novel differential expression statistic is established based on the gene regulation profiles, realizing accurate and flexible identification of DEGs in gene regulation space. We evaluated the proposed method on simulation data and real-world cancer datasets and showed the effectiveness and efficiency of jGRP in identifying DEGs identification in the context of meta-analysis. Data heterogeneity largely influences the performance of meta-analysis of DEGs identification. Existing different meta-analysis methods were revealed to exhibit very different degrees of sensitivity to study heterogeneity. The proposed method, jGRP, can be a standalone tool due to its united framework and controllable way to deal with study heterogeneity.

Issues and Solutions for Bringing Heterogeneous Water Cycle Data Sets Together

NASA Technical Reports Server (NTRS)

Acker, James; Kempler, Steven; Teng, William; Belvedere, Deborah; Liu, Zhong; Leptoukh, Gregory

2010-01-01

The water cycle research community has generated many regional to global scale products using data from individual NASA missions or sensors (e.g., TRMM, AMSR-E); multiple ground- and space-based data sources (e.g., Global Precipitation Climatology Project [GPCP] products); and sophisticated data assimilation systems (e.g., Land Data Assimilation Systems [LDAS]). However, it is often difficult to access, explore, merge, analyze, and inter-compare these data in a coherent manner due to issues of data resolution, format, and structure. These difficulties were substantiated at the recent Collaborative Energy and Water Cycle Information Services (CEWIS) Workshop, where members of the NASA Energy and Water cycle Study (NEWS) community gave presentations, provided feedback, and developed scenarios which illustrated the difficulties and techniques for bringing together heterogeneous datasets. This presentation reports on the findings of the workshop, thus defining the problems and challenges of multi-dataset research. In addition, the CEWIS prototype shown at the workshop will be presented to illustrate new technologies that can mitigate data access roadblocks encountered in multi-dataset research, including: (1) Quick and easy search and access of selected NEWS data sets. (2) Multi-parameter data subsetting, manipulation, analysis, and display tools. (3) Access to input and derived water cycle data (data lineage). It is hoped that this presentation will encourage community discussion and feedback on heterogeneous data analysis scenarios, issues, and remedies.

Computer-aided multiple-head 3D printing system for printing of heterogeneous organ/tissue constructs

NASA Astrophysics Data System (ADS)

Jung, Jin Woo; Lee, Jung-Seob; Cho, Dong-Woo

2016-02-01

Recently, much attention has focused on replacement or/and enhancement of biological tissues via the use of cell-laden hydrogel scaffolds with an architecture that mimics the tissue matrix, and with the desired three-dimensional (3D) external geometry. However, mimicking the heterogeneous tissues that most organs and tissues are formed of is challenging. Although multiple-head 3D printing systems have been proposed for fabricating heterogeneous cell-laden hydrogel scaffolds, to date only the simple exterior form has been realized. Here we describe a computer-aided design and manufacturing (CAD/CAM) system for this application. We aim to develop an algorithm to enable easy, intuitive design and fabrication of a heterogeneous cell-laden hydrogel scaffolds with a free-form 3D geometry. The printing paths of the scaffold are automatically generated from the 3D CAD model, and the scaffold is then printed by dispensing four materials; i.e., a frame, two kinds of cell-laden hydrogel and a support. We demonstrated printing of heterogeneous tissue models formed of hydrogel scaffolds using this approach, including the outer ear, kidney and tooth tissue. These results indicate that this approach is particularly promising for tissue engineering and 3D printing applications to regenerate heterogeneous organs and tissues with tailored geometries to treat specific defects or injuries.

Computer-aided multiple-head 3D printing system for printing of heterogeneous organ/tissue constructs.

PubMed

Jung, Jin Woo; Lee, Jung-Seob; Cho, Dong-Woo

2016-02-22

Recently, much attention has focused on replacement or/and enhancement of biological tissues via the use of cell-laden hydrogel scaffolds with an architecture that mimics the tissue matrix, and with the desired three-dimensional (3D) external geometry. However, mimicking the heterogeneous tissues that most organs and tissues are formed of is challenging. Although multiple-head 3D printing systems have been proposed for fabricating heterogeneous cell-laden hydrogel scaffolds, to date only the simple exterior form has been realized. Here we describe a computer-aided design and manufacturing (CAD/CAM) system for this application. We aim to develop an algorithm to enable easy, intuitive design and fabrication of a heterogeneous cell-laden hydrogel scaffolds with a free-form 3D geometry. The printing paths of the scaffold are automatically generated from the 3D CAD model, and the scaffold is then printed by dispensing four materials; i.e., a frame, two kinds of cell-laden hydrogel and a support. We demonstrated printing of heterogeneous tissue models formed of hydrogel scaffolds using this approach, including the outer ear, kidney and tooth tissue. These results indicate that this approach is particularly promising for tissue engineering and 3D printing applications to regenerate heterogeneous organs and tissues with tailored geometries to treat specific defects or injuries.

Length Scales and Types of Heterogeneities Along the Deep Subduction Interface: Insights From an Exhumed Subduction Complex on Syros Island, Greece

NASA Astrophysics Data System (ADS)

Kotowski, A. J.; Behr, W. M.; Tong, X.; Lavier, L.

2017-12-01

The rheology of the deep subduction interface strongly influences the occurrence, recurrence, and migration of episodic tremor and slow slip (ETS) events. To better understand the environment of deep ETS, we characterize the length scales and types of rheological heterogeneities that decorate the deep interface using an exhumed subduction complex. The Cycladic Blueschist Unit on Syros, Greece, records Eocene subduction to 60 km, partial exhumation along the top of the slab, and final exhumation along Miocene detachment faults. The CBU reached 450-580˚C and 14-16 kbar, PT conditions similar to where ETS occurs in several modern subduction zones. Rheological heterogeneity is preserved in a range of rock types on Syros, with the most prominent type being brittle pods embedded within a viscous matrix. Prograde, blueschist-facies metabasalts show strong deformation fabrics characteristic of viscous flow; cm- to m-scale eclogitic lenses are embedded within them as massive, veined pods, foliated pods rotated with respect to the blueschist fabric, and attenuated, foliation-parallel lenses. Similar relationships are observed in blueschist-facies metasediments interpreted to have deformed during early exhumation. In these rocks, metabasalts form lenses ranging in size from m- to 10s of m and are distributed at the m-scale throughout the metasedimentary matrix. Several of the metamafic lenses, and the matrix rocks immediately adjacent to them, preserve multiple generations of dilational veins and shear fractures filled with quartz and high pressure minerals. These observations suggest that coupled brittle-viscous deformation under high fluid pressures may characterize the subduction interface in the deep tremor source region. To test this further, we modeled the behavior of an elasto-plastic pod in a viscous shear zone under high fluid pressures. Our models show that local stress concentrations around the pod are large enough to generate transient dilational shear at seismic strain rates. Scaling the model up to a typical source area for deep tremor suggests these heterogeneities may yield a seismic moment similar to those calculated for tremor bursts in modern subduction zones.

PICKLE 2.0: A human protein-protein interaction meta-database employing data integration via genetic information ontology

PubMed Central

Gioutlakis, Aris; Klapa, Maria I.

2017-01-01

It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes. PMID:29023571

Bridging Social Capital in Online Communities: Heterogeneity and Social Tolerance of Online Game Players in Japan

ERIC Educational Resources Information Center

Kobayashi, Tetsuro

2010-01-01

This article examines the democratic potential of online communities by investigating the influence of network heterogeneity on social tolerance in an online gaming environment. Online game communities are potential sources of bridging social capital because they tend to be relatively heterogeneous. Causal analyses are conducted using structural…

Micro-heterogeneity of Cellulosic Fiber Biopolymer Prepared from Corn Hulls

USDA-ARS?s Scientific Manuscript database

Z-trim is a zero calorie cellulosic fiber biopolymer produced from corn hulls. The micro-structural heterogeneities of Z-trim biopolymer were investigated by monitoring the thermally driven displacements of well-dispersed micro-spheres via video fluorescence microscopy named multiple-particle track...

Micro-Heterogeneity of Cellulosic Fiber Biopolymer Prepared from Corn Hulls

USDA-ARS?s Scientific Manuscript database

Z-trim is a zero calorie cellulosic fiber biopolymer produced from corn hulls. The micro-structural heterogeneities of Z-trim biopolymer were investigated by monitoring the thermally driven displacements of well-dispersed micro-spheres via video fluorescence microscopy named multiple-particle track...

Effects of Contaminated Site Age on Dissolution Dynamics

NASA Astrophysics Data System (ADS)

Jawitz, J. W.

2004-12-01

This work presents a streamtube-based analytical approach to evaluate reduction in groundwater contaminant flux resulting from partial mass reduction in a nonaqueous phase liquid (NAPL) source zone. The reduction in contaminant flux, Rj, discharged from the source zone is a remediation performance metric that has a direct effect on the fundamental drivers of remediation: protection of human health risks and the environment. Spatial variability is described within a Lagrangian framework where aquifer hydrodynamic heterogeneities are characterized using nonreactive travel time distributions, while NAPL spatial distribution heterogeneity can be similarly described using reactive travel time distributions. The combined statistics of these distributions are used to evaluate the relationship between reduction in contaminant mass, Rm, and Rj. A portion of the contaminant mass in the source zone is assumed to be removed via in-situ flushing remediation, with the initial and final conditions defined as steady-state natural-gradient groundwater flow through the contaminant source zone. The combined effect of aquifer and NAPL heterogeneities are shown to be captured in a single parameter, reactive travel time variability, that was determined to be the most important factor controlling the relationship between Rm and Rj. Increased values of the following parameters are shown to result in more favorable contaminant elution dynamics (i.e., greater flux reduction for a given reduction in mass): aquifer hydrodynamic heterogeneity, NAPL source zone heterogeneity, positive correlation between travel time and NAPL content, and time since the contamination event. Less favorable elution behavior is shown to result from negative correlations between travel time and NAPL content and rate-limited dissolution. The specific emphasis of this presentation is on the effects of the length of time that has elapsed since the contamination event (site age) on the dissolution dynamics.

A scrutiny of heterogeneity at the TCE Source Area BioREmediation (SABRE) test site

NASA Astrophysics Data System (ADS)

Rivett, M.; Wealthall, G. P.; Mcmillan, L. A.; Zeeb, P.

2015-12-01

A scrutiny of heterogeneity at the UK's Source Area BioREmediation (SABRE) test site is presented to better understand how spatial heterogeneity in subsurface properties and process occurrence may constrain performance of enhanced in-situ bioremediation (EISB). The industrial site contained a 25 to 45 year old trichloroethene (TCE) dense non-aqueous phase liquid (DNAPL) that was exceptionally well monitored via a network of multilevel samplers and high resolution core sampling. Moreover, monitoring was conducted within a 3-sided sheet-pile cell that allowed a controlled streamtube of flow to be drawn through the source zone by an extraction well. We primarily focus on the longitudinal transect of monitoring along the length of the cell that provides a 200 groundwater point sample slice along the streamtube of flow through the DNAPL source zone. TCE dechlorination is shown to be significant throughout the cell domain, but spatially heterogeneous in occurrence and progress of dechlorination to lesser chlorinated ethenes - it is this heterogeneity in dechlorination that we primarily scrutinise. We illustrate the diagnostic use of the relative occurrence of TCE parent and daughter compounds to confirm: dechlorination in close proximity to DNAPL and enhanced during the bioremediation; persistent layers of DNAPL into which gradients of dechlorination products are evident; fast flowpaths through the source zone where dechlorination is less evident; and, the importance of underpinning flow regime understanding on EISB performance. Still, even with such spatial detail, there remains uncertainty over the dataset interpretation. These includes poor closure of mass balance along the cell length for the multilevel sampler based monitoring and points to needs to still understand lateral flows (even in the constrained cell), even greater spatial resolution of point monitoring and potentially, not easily proven, ethene degradation loss.

Online Heterogeneous Transfer by Hedge Ensemble of Offline and Online Decisions.

PubMed

Yan, Yuguang; Wu, Qingyao; Tan, Mingkui; Ng, Michael K; Min, Huaqing; Tsang, Ivor W

2017-10-10

In this paper, we study the online heterogeneous transfer (OHT) learning problem, where the target data of interest arrive in an online manner, while the source data and auxiliary co-occurrence data are from offline sources and can be easily annotated. OHT is very challenging, since the feature spaces of the source and target domains are different. To address this, we propose a novel technique called OHT by hedge ensemble by exploiting both offline knowledge and online knowledge of different domains. To this end, we build an offline decision function based on a heterogeneous similarity that is constructed using labeled source data and unlabeled auxiliary co-occurrence data. After that, an online decision function is learned from the target data. Last, we employ a hedge weighting strategy to combine the offline and online decision functions to exploit knowledge from the source and target domains of different feature spaces. We also provide a theoretical analysis regarding the mistake bounds of the proposed approach. Comprehensive experiments on three real-world data sets demonstrate the effectiveness of the proposed technique.

Boosting Probabilistic Graphical Model Inference by Incorporating Prior Knowledge from Multiple Sources

PubMed Central

Praveen, Paurush; Fröhlich, Holger

2013-01-01

Inferring regulatory networks from experimental data via probabilistic graphical models is a popular framework to gain insights into biological systems. However, the inherent noise in experimental data coupled with a limited sample size reduces the performance of network reverse engineering. Prior knowledge from existing sources of biological information can address this low signal to noise problem by biasing the network inference towards biologically plausible network structures. Although integrating various sources of information is desirable, their heterogeneous nature makes this task challenging. We propose two computational methods to incorporate various information sources into a probabilistic consensus structure prior to be used in graphical model inference. Our first model, called Latent Factor Model (LFM), assumes a high degree of correlation among external information sources and reconstructs a hidden variable as a common source in a Bayesian manner. The second model, a Noisy-OR, picks up the strongest support for an interaction among information sources in a probabilistic fashion. Our extensive computational studies on KEGG signaling pathways as well as on gene expression data from breast cancer and yeast heat shock response reveal that both approaches can significantly enhance the reconstruction accuracy of Bayesian Networks compared to other competing methods as well as to the situation without any prior. Our framework allows for using diverse information sources, like pathway databases, GO terms and protein domain data, etc. and is flexible enough to integrate new sources, if available. PMID:23826291

Resting-state fMRI correlations: From link-wise unreliability to whole brain stability.

PubMed

Pannunzi, Mario; Hindriks, Rikkert; Bettinardi, Ruggero G; Wenger, Elisabeth; Lisofsky, Nina; Martensson, Johan; Butler, Oisin; Filevich, Elisa; Becker, Maxi; Lochstet, Martyna; Kühn, Simone; Deco, Gustavo

2017-08-15

The functional architecture of spontaneous BOLD fluctuations has been characterized in detail by numerous studies, demonstrating its potential relevance as a biomarker. However, the systematic investigation of its consistency is still in its infancy. Here, we analyze within- and between-subject variability and test-retest reliability of resting-state functional connectivity (FC) in a unique data set comprising multiple fMRI scans (42) from 5 subjects, and 50 single scans from 50 subjects. We adopt a statistical framework that enables us to identify different sources of variability in FC. We show that the low reliability of single links can be significantly improved by using multiple scans per subject. Moreover, in contrast to earlier studies, we show that spatial heterogeneity in FC reliability is not significant. Finally, we demonstrate that despite the low reliability of individual links, the information carried by the whole-brain FC matrix is robust and can be used as a functional fingerprint to identify individual subjects from the population. Copyright © 2017 Elsevier Inc. All rights reserved.

Study on distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng

2017-06-01

Integration of distributed heterogeneous data sources is the key issues under the big data applications. In this paper the strategy of variable precision is introduced to the concept lattice, and the one-to-one mapping mode of variable precision concept lattice and ontology concept lattice is constructed to produce the local ontology by constructing the variable precision concept lattice for each subsystem, and the distributed generation algorithm of variable precision concept lattice based on ontology heterogeneous database is proposed to draw support from the special relationship between concept lattice and ontology construction. Finally, based on the standard of main concept lattice of the existing heterogeneous database generated, a case study has been carried out in order to testify the feasibility and validity of this algorithm, and the differences between the main concept lattice and the standard concept lattice are compared. Analysis results show that this algorithm above-mentioned can automatically process the construction process of distributed concept lattice under the heterogeneous data sources.

From Purgatory to Paradise: The Volatile Life of Hawaiian Magma

NASA Astrophysics Data System (ADS)

Marske, J. P.; Hauri, E. H.; Trusdell, F.; Garcia, M. O.; Pietruszka, A. J.

2014-12-01

Variations in radiogenic isotope ratios and magmatic volatile abundances (e.g., CO2 or H2O) in Hawaiian lavas reveal key processes within a deep-seated mantle plume (e.g., mantle heterogeneity, source lithology, partial melting, and magma degassing). Shield-stage Hawaiian lavas likely originate from a mixed plume source containing peridotite and recycled oceanic crust (pyroxenite) based on variations of radiogenic isotopes (e.g., 206Pb/204Pb). The mantle source region may also be heterogeneous with respect to volatile contents, yet the link between pre-eruptive volatile budgets and mantle source lithology in the Hawaiian plume is poorly constrained due to shallow magmatic degassing and mixing. Here, we use a novel approach to investigate this link using Os isotopic ratios, and major, trace, and volatile elements in olivines and mineral-hosted melt inclusions (MIs) from 34 samples from Koolau, Mauna Loa, Hualalai, Kilauea, and Loihi. These samples reveal a strong correlation between volatile contents in olivine-hosted MIs and Os isotopes of the same olivines, in which lavas that originated from greater proportions of recycled oceanic crust/pyroxenite (i.e. 'Loa' chain volcanoes: Koolau, Mauna Loa, Loihi) have MIs with the lower H2O, F, and Cl contents than 'Kea' chain volcanoes (i.e. Kilauea) that contain greater amounts of peridotite in the source region. No correlation is observed with CO2 or S. The depletion of fluid-mobile elements (H2O, F, and Cl) in 'Loa' chain volcanoes indicates ancient dehydrated oceanic crust is a plume component that controls much of the compositional variation of Hawaiian Volcanoes. The presence of dehydrated recycled mafic material in the plume source suggests that subduction effectively devolatilizes the mafic part of the oceanic crust. These results are similar to the observed shifts in H2O/Ce ratios near the Easter and Samoan hotspots [1,2]. Thus, it appears that multiple hotspots may record relative H2O depletions and possibly other volatiles. [1] Dixon et al. 2002, Nature 420:385-89 [2] Workman et al. 2006, EPSL 241:932-51

Towards a consistent framework to oversample multi-sensors, multi-species satellite data into a common grid

NASA Astrophysics Data System (ADS)

Sun, K.; Zhu, L.; Gonzalez Abad, G.; Nowlan, C. R.; Miller, C. E.; Huang, G.; Liu, X.; Chance, K.; Yang, K.

2017-12-01

It has been well demonstrated that regridding Level 2 products (satellite observations from individual footprints, or pixels) from multiple sensors/species onto regular spatial and temporal grids makes the data more accessible for scientific studies and can even lead to additional discoveries. However, synergizing multiple species retrieved from multiple satellite sensors faces many challenges, including differences in spatial coverage, viewing geometry, and data filtering criteria. These differences will lead to errors and biases if not treated carefully. Operational gridded products are often at 0.25°×0.25° resolution with a global scale, which is too coarse for local heterogeneous emission sources (e.g., urban areas), and at fixed temporal intervals (e.g., daily or monthly). We propose a consistent framework to fully use and properly weight the information of all possible individual satellite observations. A key aspect of this work is an accurate knowledge of the spatial response function (SRF) of the satellite Level 2 pixels. We found that the conventional overlap-area-weighting method (tessellation) is accurate only when the SRF is homogeneous within the parameterized pixel boundary and zero outside the boundary. There will be a tessellation error if the SRF is a smooth distribution, and if this distribution is not properly considered. On the other hand, discretizing the SRF at the destination grid will also induce errors. By balancing these error sources, we found that the SRF should be used in gridding OMI data to 0.2° for fine resolutions. Case studies by merging multiple species and wind data into 0.01° grid will be shown in the presentation.

Cross-Country Heterogeneity in Students' Reporting Behavior: The Use of the Anchoring Vignette Method

ERIC Educational Resources Information Center

Vonkova, Hana; Zamarro, Gema; Hitt, Collin

2018-01-01

Self-reports are an indispensable source of information in education research but they are often affected by heterogeneity in reporting behavior. Failing to correct for this heterogeneity can lead to invalid comparisons across groups. The researchers use the parametric anchoring vignette method to correct for cross-country incomparability of…

Methods for Synthesizing Findings on Moderation Effects Across Multiple Randomized Trials

PubMed Central

Brown, C Hendricks; Sloboda, Zili; Faggiano, Fabrizio; Teasdale, Brent; Keller, Ferdinand; Burkhart, Gregor; Vigna-Taglianti, Federica; Howe, George; Masyn, Katherine; Wang, Wei; Muthén, Bengt; Stephens, Peggy; Grey, Scott; Perrino, Tatiana

2011-01-01

This paper presents new methods for synthesizing results from subgroup and moderation analyses across different randomized trials. We demonstrate that such a synthesis generally results in additional power to detect significant moderation findings above what one would find in a single trial. Three general methods for conducting synthesis analyses are discussed, with two methods, integrative data analysis, and parallel analyses, sharing a large advantage over traditional methods available in meta-analysis. We present a broad class of analytic models to examine moderation effects across trials that can be used to assess their overall effect and explain sources of heterogeneity, and present ways to disentangle differences across trials due to individual differences, contextual level differences, intervention, and trial design. PMID:21360061

Methods for synthesizing findings on moderation effects across multiple randomized trials.

PubMed

Brown, C Hendricks; Sloboda, Zili; Faggiano, Fabrizio; Teasdale, Brent; Keller, Ferdinand; Burkhart, Gregor; Vigna-Taglianti, Federica; Howe, George; Masyn, Katherine; Wang, Wei; Muthén, Bengt; Stephens, Peggy; Grey, Scott; Perrino, Tatiana

2013-04-01

This paper presents new methods for synthesizing results from subgroup and moderation analyses across different randomized trials. We demonstrate that such a synthesis generally results in additional power to detect significant moderation findings above what one would find in a single trial. Three general methods for conducting synthesis analyses are discussed, with two methods, integrative data analysis and parallel analyses, sharing a large advantage over traditional methods available in meta-analysis. We present a broad class of analytic models to examine moderation effects across trials that can be used to assess their overall effect and explain sources of heterogeneity, and present ways to disentangle differences across trials due to individual differences, contextual level differences, intervention, and trial design.

Coding of time-dependent stimuli in homogeneous and heterogeneous neural populations.

PubMed

Beiran, Manuel; Kruscha, Alexandra; Benda, Jan; Lindner, Benjamin

2018-04-01

We compare the information transmission of a time-dependent signal by two types of uncoupled neuron populations that differ in their sources of variability: i) a homogeneous population whose units receive independent noise and ii) a deterministic heterogeneous population, where each unit exhibits a different baseline firing rate ('disorder'). Our criterion for making both sources of variability quantitatively comparable is that the interspike-interval distributions are identical for both systems. Numerical simulations using leaky integrate-and-fire neurons unveil that a non-zero amount of both noise or disorder maximizes the encoding efficiency of the homogeneous and heterogeneous system, respectively, as a particular case of suprathreshold stochastic resonance. Our findings thus illustrate that heterogeneity can render similarly profitable effects for neuronal populations as dynamic noise. The optimal noise/disorder depends on the system size and the properties of the stimulus such as its intensity or cutoff frequency. We find that weak stimuli are better encoded by a noiseless heterogeneous population, whereas for strong stimuli a homogeneous population outperforms an equivalent heterogeneous system up to a moderate noise level. Furthermore, we derive analytical expressions of the coherence function for the cases of very strong noise and of vanishing intrinsic noise or heterogeneity, which predict the existence of an optimal noise intensity. Our results show that, depending on the type of signal, noise as well as heterogeneity can enhance the encoding performance of neuronal populations.

Simultaneous Two-Way Clustering of Multiple Correspondence Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun; Dillon, William R.

2010-01-01

A 2-way clustering approach to multiple correspondence analysis is proposed to account for cluster-level heterogeneity of both respondents and variable categories in multivariate categorical data. Specifically, in the proposed method, multiple correspondence analysis is combined with k-means in a unified framework in which "k"-means is…

Rupture Dynamics and Ground Motion from Earthquakes in Heterogeneous Media

NASA Astrophysics Data System (ADS)

Bydlon, S.; Dunham, E. M.; Kozdon, J. E.

2012-12-01

Heterogeneities in the material properties of Earth's crust scatter propagating seismic waves. The effects of scattered waves are reflected in the seismic coda and depend on the relative strength of the heterogeneities, spatial arrangement, and distance from source to receiver. In the vicinity of the fault, scattered waves influence the rupture process by introducing fluctuations in the stresses driving propagating ruptures. Further variability in the rupture process is introduced by naturally occurring geometric complexity of fault surfaces, and the stress changes that accompany slip on rough surfaces. We have begun a modeling effort to better understand the origin of complexity in the earthquake source process, and to quantify the relative importance of source complexity and scattering along the propagation path in causing incoherence of high frequency ground motion. To do this we extended our two-dimensional high order finite difference rupture dynamics code to accommodate material heterogeneities. We generate synthetic heterogeneous media using Von Karman correlation functions and their associated power spectral density functions. We then nucleate ruptures on either flat or rough faults, which obey strongly rate-weakening friction laws. Preliminary results for flat faults with uniform frictional properties and initial stresses indicate that off-fault material heterogeneity alone can lead to a complex rupture process. Our simulations reveal the excitation of high frequency bursts of waves, which radiate energy away from the propagating rupture. The average rupture velocity is thus reduced relative to its value in simulations employing homogeneous material properties. In the coming months, we aim to more fully explore parameter space by varying the correlation length, Hurst exponent, and amplitude of medium heterogeneities, as well as the statistical properties characterizing fault roughness.

Heterogeneity of long-history migration predicts emotion recognition accuracy.

PubMed

Wood, Adrienne; Rychlowska, Magdalena; Niedenthal, Paula M

2016-06-01

Recent work (Rychlowska et al., 2015) demonstrated the power of a relatively new cultural dimension, historical heterogeneity, in predicting cultural differences in the endorsement of emotion expression norms. Historical heterogeneity describes the number of source countries that have contributed to a country's present-day population over the last 500 years. People in cultures originating from a large number of source countries may have historically benefited from greater and clearer emotional expressivity, because they lacked a common language and well-established social norms. We therefore hypothesized that in addition to endorsing more expressive display rules, individuals from heterogeneous cultures will also produce facial expressions that are easier to recognize by people from other cultures. By reanalyzing cross-cultural emotion recognition data from 92 papers and 82 cultures, we show that emotion expressions of people from heterogeneous cultures are more easily recognized by observers from other cultures than are the expressions produced in homogeneous cultures. Heterogeneity influences expression recognition rates alongside the individualism-collectivism of the perceivers' culture, as more individualistic cultures were more accurate in emotion judgments than collectivistic cultures. This work reveals the present-day behavioral consequences of long-term historical migration patterns and demonstrates the predictive power of historical heterogeneity. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Visualizing the Heterogeneity of Effects in the Analysis of Associations of Multiple Myeloma with Glyphosate Use. Comments on Sorahan, T. Multiple Myeloma and Glyphosate Use: A Re-Analysis of US Agricultural Health Study (AHS) Data. Int. J. Environ. Res. Public Health 2015, 12, 1548-1559.

PubMed

Burstyn, Igor; De Roos, Anneclaire J

2016-12-22

We address a methodological issue of the evaluation of the difference in effects in epidemiological studies that may arise, for example, from stratum-specific analyses or differences in analytical decisions during data analysis. We propose a new simulation-based method to quantify the plausible extent of such heterogeneity, rather than testing a hypothesis about its existence. We examine the contribution of the method to the debate surrounding risk of multiple myeloma and glyphosate use and propose that its application contributes to a more balanced weighting of evidence.

Visualizing the Heterogeneity of Effects in the Analysis of Associations of Multiple Myeloma with Glyphosate Use. Comments on Sorahan, T. Multiple Myeloma and Glyphosate Use: A Re-Analysis of US Agricultural Health Study (AHS) Data. Int. J. Environ. Res. Public Health 2015, 12, 1548–1559

PubMed Central

Burstyn, Igor; De Roos, Anneclaire J.

2016-01-01

We address a methodological issue of the evaluation of the difference in effects in epidemiological studies that may arise, for example, from stratum-specific analyses or differences in analytical decisions during data analysis. We propose a new simulation-based method to quantify the plausible extent of such heterogeneity, rather than testing a hypothesis about its existence. We examine the contribution of the method to the debate surrounding risk of multiple myeloma and glyphosate use and propose that its application contributes to a more balanced weighting of evidence. PMID:28025514

Ontologies to improve chronic disease management research and quality improvement studies - a conceptual framework.

PubMed

Liyanage, Harshana; Liaw, Siaw-Teng; Kuziemsky, Craig; de Lusignan, Simon

2013-01-01

There is a growing burden of chronic non-communicable disease (CNCD). Managing CNCDs requires use of multiple sources of health and social care data, and information about coordination and outcomes. Many people with CNCDs have multimorbidity. Problems with data quality exacerbate challenges in measuring quality and health outcomes especially where there is multimorbidity. We have developed an ontological toolkit to support research and quality improvement studies in CNCDs using heterogeneous data, with diabetes mellitus as an exemplar. International experts held a workshop meeting, with follow up discussions and consensus building exercise. We generated conceptual statements about problems with a CNCD that ontologies might support, and a generic reference model. There were varying degrees of consensus. We propose a set of tools, and a four step method: (1) Identification and specification of data sources; (2) Conceptualisation of semantic meaning; (3) How available routine data can be used as a measure of the process or outcome of care; (4) Formalisation and validation of the final ontology.

A knowledge discovery object model API for Java

PubMed Central

Zuyderduyn, Scott D; Jones, Steven JM

2003-01-01

Background Biological data resources have become heterogeneous and derive from multiple sources. This introduces challenges in the management and utilization of this data in software development. Although efforts are underway to create a standard format for the transmission and storage of biological data, this objective has yet to be fully realized. Results This work describes an application programming interface (API) that provides a framework for developing an effective biological knowledge ontology for Java-based software projects. The API provides a robust framework for the data acquisition and management needs of an ontology implementation. In addition, the API contains classes to assist in creating GUIs to represent this data visually. Conclusions The Knowledge Discovery Object Model (KDOM) API is particularly useful for medium to large applications, or for a number of smaller software projects with common characteristics or objectives. KDOM can be coupled effectively with other biologically relevant APIs and classes. Source code, libraries, documentation and examples are available at . PMID:14583100

Discovering spatio-temporal models of the spread of West Nile virus.

PubMed

Orme-Zavaleta, Jennifer; Jorgensen, Jane; D'Ambrosio, Bruce; Altendorf, Eric; Rossignol, Philippe A

2006-04-01

Emerging infectious diseases are characterized by complex interactions among disease agents, vectors, wildlife, humans, and the environment. Since the appearance of West Nile virus (WNV) in New York City in 1999, it has infected over 8,000 people in the United States, resulting in several hundred deaths in 46 contiguous states. The virus is transmitted by mosquitoes and maintained in various bird reservoir hosts. Its unexpected introduction, high morbidity, and rapid spread have left public health agencies facing severe time constraints in a theory-poor environment, dependent largely on observational data collected by independent survey efforts and much uncertainty. Current knowledge may be expressed as a priori constraints on models learned from data. Accordingly, we applied a Bayesian probabilistic relational approach to generate spatially and temporally linked models from heterogeneous data sources. Using data collected from multiple independent sources in Maryland, we discovered the integrated context in which infected birds are plausible indicators for positive mosquito pools and human cases for 2001 and 2002.

Combining non selective gas sensors on a mobile robot for identification and mapping of multiple chemical compounds.

PubMed

Bennetts, Victor Hernandez; Schaffernicht, Erik; Pomareda, Victor; Lilienthal, Achim J; Marco, Santiago; Trincavelli, Marco

2014-09-17

In this paper, we address the task of gas distribution modeling in scenarios where multiple heterogeneous compounds are present. Gas distribution modeling is particularly useful in emission monitoring applications where spatial representations of the gaseous patches can be used to identify emission hot spots. In realistic environments, the presence of multiple chemicals is expected and therefore, gas discrimination has to be incorporated in the modeling process. The approach presented in this work addresses the task of gas distribution modeling by combining different non selective gas sensors. Gas discrimination is addressed with an open sampling system, composed by an array of metal oxide sensors and a probabilistic algorithm tailored to uncontrolled environments. For each of the identified compounds, the mapping algorithm generates a calibrated gas distribution model using the classification uncertainty and the concentration readings acquired with a photo ionization detector. The meta parameters of the proposed modeling algorithm are automatically learned from the data. The approach was validated with a gas sensitive robot patrolling outdoor and indoor scenarios, where two different chemicals were released simultaneously. The experimental results show that the generated multi compound maps can be used to accurately predict the location of emitting gas sources.

Identifying sources of heterogeneity in capture probabilities: An example using the Great Tit Parus major

USGS Publications Warehouse

Senar, J.C.; Conroy, M.J.; Carrascal, L.M.; Domenech, J.; Mozetich, I.; Uribe, F.

1999-01-01

Heterogeneous capture probabilities are a common problem in many capture-recapture studies. Several methods of detecting the presence of such heterogeneity are currently available, and stratification of data has been suggested as the standard method to avoid its effects. However, few studies have tried to identify sources of heterogeneity, or whether there are interactions among sources. The aim of this paper is to suggest an analytical procedure to identify sources of capture heterogeneity. We use data on the sex and age of Great Tits captured in baited funnel traps, at two localities differing in average temperature. We additionally use 'recapture' data obtained by videotaping at feeder (with no associated trap), where the tits ringed with different colours were recorded. This allowed us to test whether individuals in different classes (age, sex and condition) are not trapped because of trap shyness or because o a reduced use of the bait. We used logistic regression analysis of the capture probabilities to test for the effects of age, sex, condition, location and 'recapture method. The results showed a higher recapture probability in the colder locality. Yearling birds (either males or females) had the highest recapture prob abilities, followed by adult males, while adult females had the lowest recapture probabilities. There was no effect of the method of 'recapture' (trap or video tape), which suggests that adult females are less often captured in traps no because of trap-shyness but because of less dependence on supplementary food. The potential use of this methodological approach in other studies is discussed.

Computer-aided multiple-head 3D printing system for printing of heterogeneous organ/tissue constructs

PubMed Central

Jung, Jin Woo; Lee, Jung-Seob; Cho, Dong-Woo

2016-01-01

Recently, much attention has focused on replacement or/and enhancement of biological tissues via the use of cell-laden hydrogel scaffolds with an architecture that mimics the tissue matrix, and with the desired three-dimensional (3D) external geometry. However, mimicking the heterogeneous tissues that most organs and tissues are formed of is challenging. Although multiple-head 3D printing systems have been proposed for fabricating heterogeneous cell-laden hydrogel scaffolds, to date only the simple exterior form has been realized. Here we describe a computer-aided design and manufacturing (CAD/CAM) system for this application. We aim to develop an algorithm to enable easy, intuitive design and fabrication of a heterogeneous cell-laden hydrogel scaffolds with a free-form 3D geometry. The printing paths of the scaffold are automatically generated from the 3D CAD model, and the scaffold is then printed by dispensing four materials; i.e., a frame, two kinds of cell-laden hydrogel and a support. We demonstrated printing of heterogeneous tissue models formed of hydrogel scaffolds using this approach, including the outer ear, kidney and tooth tissue. These results indicate that this approach is particularly promising for tissue engineering and 3D printing applications to regenerate heterogeneous organs and tissues with tailored geometries to treat specific defects or injuries. PMID:26899876

A loosely coupled framework for terminology controlled distributed EHR search for patient cohort identification in clinical research.

PubMed

Zhao, Lei; Lim Choi Keung, Sarah N; Taweel, Adel; Tyler, Edward; Ogunsina, Ire; Rossiter, James; Delaney, Brendan C; Peterson, Kevin A; Hobbs, F D Richard; Arvanitis, Theodoros N

2012-01-01

Heterogeneous data models and coding schemes for electronic health records present challenges for automated search across distributed data sources. This paper describes a loosely coupled software framework based on the terminology controlled approach to enable the interoperation between the search interface and heterogeneous data sources. Software components interoperate via common terminology service and abstract criteria model so as to promote component reuse and incremental system evolution.

Erratum: Sources of Image Degradation in Fundamental and Harmonic Ultrasound Imaging: A Nonlinear, Full-Wave, Simulation Study

PubMed Central

Pinton, Gianmarco F.; Trahey, Gregg E.; Dahl, Jeremy J.

2015-01-01

A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain. This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-and-sum beamforming is used to generate point spread functions (PSFs) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is due to reverberation from near-field structures. Compared with fundamental imaging, reverberation clutter in harmonic imaging is 27.1 dB lower. Simulated tissue with uniform velocity but unchanged impedance characteristics indicates that for harmonic imaging, the primary source of degradation is phase aberration. PMID:21693410

Understanding Interdependencies between Heterogeneous Earth Observation Systems When Applied to Federal Objectives

NASA Astrophysics Data System (ADS)

Gallo, J.; Sylak-Glassman, E.

2017-12-01

We will present a method for assessing interdependencies between heterogeneous Earth observation (EO) systems when applied to key Federal objectives. Using data from the National Earth Observation Assessment (EOA), we present a case study that examines the frequency that measurements from each of the Landsat 8 sensors are used in conjunction with heterogeneous measurements from other Earth observation sensors to develop data and information products. This EOA data allows us to map the most frequent interactions between Landsat measurements and measurements from other sensors, identify high-impact data and information products where these interdependencies occur, and identify where these combined measurements contribute most to meeting a key Federal objective within one of the 13 Societal Benefit Areas used in the EOA study. Using a value-tree framework to trace the application of data from EO systems to weighted key Federal objectives within the EOA study, we are able to estimate relative contribution of individual EO systems to meeting those objectives, as well as the interdependencies between measurements from all EO systems within the EOA study. The analysis relies on a modified Delphi method to elicit relative levels of reliance on individual measurements from EO systems, including combinations of measurements, from subject matter experts. This results in the identification of a representative portfolio of all EO systems used to meet key Federal objectives. Understanding the interdependencies among a heterogeneous set of measurements that modify the impact of any one individual measurement on meeting a key Federal objective, especially if the measurements originate from multiple agencies or state/local/tribal, international, academic, and commercial sources, can impact agency decision-making regarding mission requirements and inform understanding of user needs.

Social relationships and cognitive decline: a systematic review and meta-analysis of longitudinal cohort studies.

PubMed

Kuiper, Jisca S; Zuidersma, Marij; Zuidema, Sytse U; Burgerhof, Johannes Gm; Stolk, Ronald P; Oude Voshaar, Richard C; Smidt, Nynke

2016-08-01

Although poor social relationships are assumed to contribute to cognitive decline, meta-analytic approaches have not been applied. Individual study results are mixed and difficult to interpret due to heterogeneity in measures of social relationships. We conducted a systematic review and meta-analysis to investigate the relation between poor social relationships and cognitive decline. MEDLINE, Embase and PsycINFO were searched for longitudinal cohort studies examining various aspects of social relationships and cognitive decline in the general population. Odds ratios (ORs) with 95% confidence intervals (CIs) were pooled using random effects meta-analysis. Sources of heterogeneity were explored and likelihood of publication bias was assessed. We stratified analyses according to three aspects of social relationships: structural, functional and a combination of these. We identified 43 articles. Poor social relationships predicted cognitive decline; for structural (19 studies): pooled OR: 1.08 (95% CI: 1.05-1.11); functional (8 studies): pooled OR: 1.15 (95% CI: 1.00-1.32); and combined measures (7 studies): pooled OR: 1.12 (95% CI: 1.01-1.24). Meta-regression and subgroup analyses showed that the heterogeneity could be explained by the type of social relationship measurement and methodological quality of included studies. Despite heterogeneity in study design and measures, our meta-analyses show that multiple aspects of social relationships are associated with cognitive decline. As evidence for publication bias was found, the association might be overestimated and should therefore be interpreted with caution. Future studies are needed to better define the mechanisms underlying these associations. Potential causality of this prognostic association should be examined in future randomized controlled studies. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.

A Nth-order linear algorithm for extracting diffuse correlation spectroscopy blood flow indices in heterogeneous tissues.

PubMed

Shang, Yu; Yu, Guoqiang

2014-09-29

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a N th-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD B ). The purpose of this study is to extend the capability of the N th-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different types of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD B in the brain layer with a step decrement of 10% while maintaining αD B values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order ( N  ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The N th-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.

Albumin heterogeneity in low-abundance fluids. The case of urine and cerebro-spinal fluid.

PubMed

Bruschi, Maurizio; Santucci, Laura; Candiano, Giovanni; Ghiggeri, Gian Marco

2013-12-01

Serum albumin is a micro-heterogeneous protein composed of at least 40 isoforms. Its heterogeneity is even more pronounced in biological fluids other than serum, the major being urine and cerebrospinal fluid. Modification 'in situ' and/or selectivity of biological barriers, such as in the kidney, determines the final composition of albumin and may help in definition of inflammatory states. This review focuses on various aspects of albumin heterogeneity in low 'abundance fluids' and highlights the potential source of information in diseases. The electrical charge of the protein in urine and CSF is modified but with an opposite change and depending on clinical conditions. In normal urine, the bulk of albumin is more anionic than in serum for the presence of ten times more fatty acids that introduce equivalent anionic charges and modify hydrophobicity of the protein. At the same time, urinary albumin is more glycosylated compared to the serum homolog. Finally, albumin fragments can be detected in urine in patients with proteinuria. For albumin in CSF, we lack information relative to normal conditions since ethical problems do not allow normal CSF to be studied. In multiple sclerosis, the albumin charge in CSF is more cationic than in serum, this change possibly involving structural anomalies or small molecules bindings. Massively fatty albumin could be toxic for tubular cells and be eliminated on this basis. Renal handling of glycosylated albumin can alter the normal equilibrium of filtration/reabsorption and trigger mechanisms leading to glomerulosclerosis and tubulo-interstitial fibrosis. This article is part of a Special Issue entitled Serum Albumin. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Specific ultra-violet absorbance as an indicator measurement of merucry sources in an Adirondack River basin

USGS Publications Warehouse

Burns, Douglas A.; Aiken, George R.; Bradley, Paul M.; Journey, Celeste A.; Schelker, Jakob

2013-01-01

The Adirondack region of New York has been identified as a hot spot where high methylmercury concentrations are found in surface waters and biota, yet mercury (Hg) concentrations vary widely in this region. We collected stream and groundwater samples for Hg and organic carbon analyses across the upper Hudson River, a 493 km2 basin in the central Adirondacks to evaluate and model the sources of variation in filtered total Hg (FTHg) concentrations. Variability in FTHg concentrations during the growing seasons (May-Oct) of 2007-2009 in Fishing Brook, a 66-km2 sub-basin, was better explained by specific ultra-violet absorbance at 254 nm (SUVA254), a measure of organic carbon aromaticity, than by dissolved organic carbon (DOC) concentrations, a commonly used Hg indicator. SUVA254 was a stronger predictor of FTHg concentrations during the growing season than during the dormant season. Multiple linear regression models that included SUVA254 values and DOC concentrations could explain 75 % of the variation in FTHg concentrations on an annual basis and 84 % during the growing season. A multiple linear regression landscape modeling approach applied to 27 synoptic sites across the upper Hudson basin found that higher SUVA254 values are associated with gentler slopes, and greater riparian area, and lower SUVA254 values are associated with an increasing influence of open water. We hypothesize that the strong Hg?SUVA254 relation in this basin reflects distinct patterns of FTHg and SUVA254 that are characteristic of source areas that control the mobilization of Hg to surface waters, and that the seasonal influence of these source areas varies in this heterogeneous basin landscape.

TLM-Quant: an open-source pipeline for visualization and quantification of gene expression heterogeneity in growing microbial cells.

PubMed

Piersma, Sjouke; Denham, Emma L; Drulhe, Samuel; Tonk, Rudi H J; Schwikowski, Benno; van Dijl, Jan Maarten

2013-01-01

Gene expression heterogeneity is a key driver for microbial adaptation to fluctuating environmental conditions, cell differentiation and the evolution of species. This phenomenon has therefore enormous implications, not only for life in general, but also for biotechnological applications where unwanted subpopulations of non-producing cells can emerge in large-scale fermentations. Only time-lapse fluorescence microscopy allows real-time measurements of gene expression heterogeneity. A major limitation in the analysis of time-lapse microscopy data is the lack of fast, cost-effective, open, simple and adaptable protocols. Here we describe TLM-Quant, a semi-automatic pipeline for the analysis of time-lapse fluorescence microscopy data that enables the user to visualize and quantify gene expression heterogeneity. Importantly, our pipeline builds on the open-source packages ImageJ and R. To validate TLM-Quant, we selected three possible scenarios, namely homogeneous expression, highly 'noisy' heterogeneous expression, and bistable heterogeneous expression in the Gram-positive bacterium Bacillus subtilis. This bacterium is both a paradigm for systems-level studies on gene expression and a highly appreciated biotechnological 'cell factory'. We conclude that the temporal resolution of such analyses with TLM-Quant is only limited by the numbers of recorded images.

Clinical Significance of Accounting for Tissue Heterogeneity in Permanent Breast Seed Implant Brachytherapy Planning

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

Mashouf, Shahram; Department of Radiation Oncology, Sunnybrook Odette Cancer Centre, Toronto, Ontario; Fleury, Emmanuelle

Purpose: The inhomogeneity correction factor (ICF) method provides heterogeneity correction for the fast calculation TG43 formalism in seed brachytherapy. This study compared ICF-corrected plans to their standard TG43 counterparts, looking at their capacity to assess inadequate coverage and/or risk of any skin toxicities for patients who received permanent breast seed implant (PBSI). Methods and Materials: Two-month postimplant computed tomography scans and plans of 140 PBSI patients were used to calculate dose distributions by using the TG43 and the ICF methods. Multiple dose-volume histogram (DVH) parameters of clinical target volume (CTV) and skin were extracted and compared for both ICF and TG43more » dose distributions. Short-term (desquamation and erythema) and long-term (telangiectasia) skin toxicity data were available on 125 and 110 of the patients, respectively, at the time of the study. The predictive value of each DVH parameter of skin was evaluated using the area under the receiver operating characteristic (ROC) curve for each toxicity endpoint. Results: Dose-volume histogram parameters of CTV, calculated using the ICF method, showed an overall decrease compared to TG43, whereas those of skin showed an increase, confirming previously reported findings of the impact of heterogeneity with low-energy sources. The ICF methodology enabled us to distinguish patients for whom the CTV V{sub 100} and V{sub 90} are up to 19% lower compared to TG43, which could present a risk of recurrence not detected when heterogeneity are not accounted for. The ICF method also led to an increase in the prediction of desquamation, erythema, and telangiectasia for 91% of skin DVH parameters studied. Conclusions: The ICF methodology has the advantage of distinguishing any inadequate dose coverage of CTV due to breast heterogeneity, which can be missed by TG43. Use of ICF correction also led to an increase in prediction accuracy of skin toxicities in most cases.« less

Clinical Significance of Accounting for Tissue Heterogeneity in Permanent Breast Seed Implant Brachytherapy Planning.

PubMed

Mashouf, Shahram; Fleury, Emmanuelle; Lai, Priscilla; Merino, Tomas; Lechtman, Eli; Kiss, Alex; McCann, Claire; Pignol, Jean-Philippe

2016-03-15

The inhomogeneity correction factor (ICF) method provides heterogeneity correction for the fast calculation TG43 formalism in seed brachytherapy. This study compared ICF-corrected plans to their standard TG43 counterparts, looking at their capacity to assess inadequate coverage and/or risk of any skin toxicities for patients who received permanent breast seed implant (PBSI). Two-month postimplant computed tomography scans and plans of 140 PBSI patients were used to calculate dose distributions by using the TG43 and the ICF methods. Multiple dose-volume histogram (DVH) parameters of clinical target volume (CTV) and skin were extracted and compared for both ICF and TG43 dose distributions. Short-term (desquamation and erythema) and long-term (telangiectasia) skin toxicity data were available on 125 and 110 of the patients, respectively, at the time of the study. The predictive value of each DVH parameter of skin was evaluated using the area under the receiver operating characteristic (ROC) curve for each toxicity endpoint. Dose-volume histogram parameters of CTV, calculated using the ICF method, showed an overall decrease compared to TG43, whereas those of skin showed an increase, confirming previously reported findings of the impact of heterogeneity with low-energy sources. The ICF methodology enabled us to distinguish patients for whom the CTV V100 and V90 are up to 19% lower compared to TG43, which could present a risk of recurrence not detected when heterogeneity are not accounted for. The ICF method also led to an increase in the prediction of desquamation, erythema, and telangiectasia for 91% of skin DVH parameters studied. The ICF methodology has the advantage of distinguishing any inadequate dose coverage of CTV due to breast heterogeneity, which can be missed by TG43. Use of ICF correction also led to an increase in prediction accuracy of skin toxicities in most cases. Copyright © 2016 Elsevier Inc. All rights reserved.

Sources and Sinks: A Stochastic Model of Evolution in Heterogeneous Environments

NASA Astrophysics Data System (ADS)

Hermsen, Rutger; Hwa, Terence

2010-12-01

We study evolution driven by spatial heterogeneity in a stochastic model of source-sink ecologies. A sink is a habitat where mortality exceeds reproduction so that a local population persists only due to immigration from a source. Immigrants can, however, adapt to conditions in the sink by mutation. To characterize the adaptation rate, we derive expressions for the first arrival time of adapted mutants. The joint effects of migration, mutation, birth, and death result in two distinct parameter regimes. These results may pertain to the rapid evolution of drug-resistant pathogens and insects.

A novel algorithm for fully automated mapping of geospatial ontologies

NASA Astrophysics Data System (ADS)

Chaabane, Sana; Jaziri, Wassim

2018-01-01

Geospatial information is collected from different sources thus making spatial ontologies, built for the same geographic domain, heterogeneous; therefore, different and heterogeneous conceptualizations may coexist. Ontology integrating helps creating a common repository of the geospatial ontology and allows removing the heterogeneities between the existing ontologies. Ontology mapping is a process used in ontologies integrating and consists in finding correspondences between the source ontologies. This paper deals with the "mapping" process of geospatial ontologies which consist in applying an automated algorithm in finding the correspondences between concepts referring to the definitions of matching relationships. The proposed algorithm called "geographic ontologies mapping algorithm" defines three types of mapping: semantic, topological and spatial.

Analysis of Genome-Wide Association Studies with Multiple Outcomes Using Penalization

PubMed Central

Liu, Jin; Huang, Jian; Ma, Shuangge

2012-01-01

Genome-wide association studies have been extensively conducted, searching for markers for biologically meaningful outcomes and phenotypes. Penalization methods have been adopted in the analysis of the joint effects of a large number of SNPs (single nucleotide polymorphisms) and marker identification. This study is partly motivated by the analysis of heterogeneous stock mice dataset, in which multiple correlated phenotypes and a large number of SNPs are available. Existing penalization methods designed to analyze a single response variable cannot accommodate the correlation among multiple response variables. With multiple response variables sharing the same set of markers, joint modeling is first employed to accommodate the correlation. The group Lasso approach is adopted to select markers associated with all the outcome variables. An efficient computational algorithm is developed. Simulation study and analysis of the heterogeneous stock mice dataset show that the proposed method can outperform existing penalization methods. PMID:23272092

Investigation of detonation velocity in heterogeneous explosive system using the reactive Burgers' analog

NASA Astrophysics Data System (ADS)

Di Labbio, G.; Kiyanda, C. B.; Mi, X.; Higgins, A. J.; Nikiforakis, N.; Ng, H. D.

2016-06-01

In this study, the applicability of the Chapman-Jouguet (CJ) criterion is tested numerically for heterogeneous explosive media using a simple detonation analog. The analog system consists of a reactive Burgers' equation coupled with an Arrhenius type reaction wave, and the heterogeneity of the explosive media is mimicked using a discrete energy source approach. The governing equation is solved using a second order, finite-volume approach and the average propagation velocity of the discrete detonation is determined by tracking the leading shock front. Consistent with previous studies, the averaged velocity of the leading shock front from the unsteady numerical simulations is also found to be in good agreement with the velocity of a CJ detonation in a uniform medium wherein the energy source is spatially homogenized. These simulations have thus implications for whether the CJ criterion is valid to predict the detonation velocity in heterogeneous explosive media.

Calibration of Cosmic Ray Neutron Probes in complex systems: open research issues

NASA Astrophysics Data System (ADS)

Piussi, Laura; Tomelleri, Enrico; Bertoldi, Giacomo; Zebisch, Marc; Niedrist, Georg; Tonon, Giustino

2017-04-01

Soil moisture is a key variable for environmental monitoring, hydrological and climate change research as it controls mass and energy fluxes in the soil-plant-atmosphere continuum. Actual soil moisture monitoring methods are capable of providing observations either at a very big spatial scale and timely spotty satellite observations or at a very small scale and timely continuous point measurements. In this framework, meso-scale timely continuous measurements appear of key relevance, thus, recently, Cosmic Ray Neutron Sensing (CRNS) is gaining more and more importance, because of its capacity to deliver long time-series of observations within a footprint of 500m of diameter. Even if during the last years a remarkable number of papers have been published, the calibration of Cosmic Ray Neutron Probes (CRPs) in heterogeneous ecosystems is still an open issue. The CRP is sensitive to all the Hydrogen species and their distribution within the footprint, thus in environments that can be assumed as homogeneous a good accordance between the CRNS data and observed soil moisture can be reached, but, where Hydrogen distributions are complex, different calibration campaigns lead to different results. In order to improve the efficiency of the method, a better understanding of the effects of combined spatial and temporal variability has to be reached. The aim of the actual work is to better understand the effects of multiple Hydrogen sources that vary in time and space and evaluate different approaches in calibration over complex terrain in a mountain area. We present different calibration approaches used for an alpine pasture, which is a research site of the LTER network in South-Tyrol (Italy). In the study site long-term soil moisture observations are present and are used for remote-sensing data validation. For this specific and highly heterogeneous site, the effects of heterogeneous land-cover and topography on CRP calibration are evaluated and some hypotheses on the major sources of uncertainty are formulated.

Variation in worldwide incidence of amyotrophic lateral sclerosis: a meta-analysis.

PubMed

Marin, Benoît; Boumédiene, Farid; Logroscino, Giancarlo; Couratier, Philippe; Babron, Marie-Claude; Leutenegger, Anne Louise; Copetti, Massimilano; Preux, Pierre-Marie; Beghi, Ettore

2017-02-01

To assess the worldwide variation of amyotrophic lateral sclerosis (ALS) incidence, we performed a systematic review and meta-analysis of population-based data published to date. We reviewed Medline and Embase up to June 2015 and included all population-based studies of newly diagnosed ALS cases, using multiple sources for case ascertainment. ALS crude and standardized incidence (on age and sex using the US 2010 population) were calculated. Random effect meta-analysis and meta-regression were performed using the subcontinent as the main study level covariate. Sources of heterogeneity related to the characteristics of the study population and the study methodology were investigated. Among 3216 records, 44 studies were selected, covering 45 geographical areas in 11 sub-continents. A total of 13 146 ALS cases and 825 million person-years of follow-up (PYFU) were co-nsidered. The overall pooled worldwide crude ALS incidence was at 1.75 (1.55-1.96)/100 000 PYFU; 1.68 (1.50-1.85)/100 000 PYFU after standardization. Heterogeneity was identified in ALS standardized incidence between North Europe [1.89 (1.46-2.32)/100 000 PYFU] and East Asia [0.83 (0.42-1.24)/100 000 PYFU, China and Japan P = 0.001] or South Asia [0.73 (0.58-0.89)/100 000/PYFU Iran, P = 0.02]. Conversely, homogeneous rates have been reported in populations from Europe, North America and New Zealand [pooled ALS standardized incidence of 1.81 (1.66-1.97)/100 000 PYFU for those areas]. This review confirms a heterogeneous distribution worldwide of ALS, and sets the scene to sustain a collaborative study involving a wide international consortium to investigate the link between ancestry, environment and ALS incidence. © The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association

Finding Groups Using Model-Based Cluster Analysis: Heterogeneous Emotional Self-Regulatory Processes and Heavy Alcohol Use Risk

ERIC Educational Resources Information Center

Mun, Eun Young; von Eye, Alexander; Bates, Marsha E.; Vaschillo, Evgeny G.

2008-01-01

Model-based cluster analysis is a new clustering procedure to investigate population heterogeneity utilizing finite mixture multivariate normal densities. It is an inferentially based, statistically principled procedure that allows comparison of nonnested models using the Bayesian information criterion to compare multiple models and identify the…

Identification, Attribution, and Quantification of Highly Heterogeneous Methane Sources Using a Mobile Stable Isotope Analyzer

NASA Astrophysics Data System (ADS)

Crosson, E.; Rella, C.; Cunningham, K.

2012-04-01

Despite methane's importance as a potent greenhouse gas second only to carbon dioxide in the magnitude of its contribution to global warming, natural contributions to the overall methane budget are only poorly understood. A big contributor to this gap in knowledge is the highly spatially and temporally heterogeneous nature of most natural (and for that matter anthropogenic) methane sources. This high degree of heterogeneity, where the methane emission rates can vary over many orders of magnitude on a spatial scale of meters or even centimeters, and over a temporal scale of minutes or even seconds, means that traditional methods of emissions flux estimation, such as flux chambers or eddy-covariance, are difficult or impossible to apply. In this paper we present new measurement methods that are capable of detecting, attributing, and quantifying emissions from highly heterogeneous sources. These methods take full advantage of the new class of methane concentration and stable isotope analyzers that are capable of laboratory-quality analysis from a mobile field platform in real time. In this paper we present field measurements demonstrating the real-time detection of methane 'hot spots,' attribution of the methane to a source process via real-time stable isotope analysis, and quantification of the emissions flux using mobile concentration measurements of the horizontal and vertical atmospheric dispersion, combined with atmospheric transport calculations. Although these techniques are applicable to both anthropogenic and natural methane sources, in this initial work we focus primarily on landfills and fugitive emissions from natural gas distribution, as these sources are better characterized, and because they provide a more reliable and stable source of methane for quantifying the measurement uncertainty inherent in the different methods. Implications of these new technologies and techniques are explored for the quantification of natural methane sources in a variety of environments, including wetlands, peatlands, and the arctic.

Topographic heterogeneity influences fish use of an experimentally restored tidal marsh.

PubMed

Larkin, Daniel J; Madon, Sharook P; West, Janelle M; Zedler, Joy B

2008-03-01

Ecological theory predicts that incorporating habitat heterogeneity into restoration sites should enhance diversity and key functions, yet research is limited on how topographic heterogeneity affects higher trophic levels. Our large (8-ha) southern California restoration experiment tested effects of tidal creek networks and pools on trophic structure of salt marsh habitat and high-tide use by two regionally dominant fish species, California killifish (Fundulus parvipinnis) and longjaw mudsucker (Gillichthys mirabilis). We expected tidal creeks to function as "conduits" that would enhance connectivity between subtidal and intertidal habitat and pools to serve as microhabitat "oases" for fishes. Pools did provide abundant invertebrate prey and were a preferred microhabitat for F. parvipinnis, even when the entire marsh was inundated (catch rates were 61% higher in pools). However, G. mirabilis showed no preference for pools. At a larger scale, effects of tidal creek networks were also mixed. Areas containing creeks had 12% higher catch rates of G. mirabilis, but lower catch rates and feeding rates of F. parvipinnis. Collectively, the results indicate that restoring multiple forms of heterogeneity is required to provide opportunities for multiple target consumers.

Screening Models of Aquifer Heterogeneity Using the Flow Dimension

NASA Astrophysics Data System (ADS)

Walker, D. D.; Cello, P. A.; Roberts, R. M.; Valocchi, A. J.

2007-12-01

Despite advances in test interpretation and modeling, typical groundwater modeling studies only indirectly use the parameters and information inferred from hydraulic tests. In particular, the Generalized Radial Flow approach to test interpretation infers the flow dimension, a parameter describing the geometry of the flow field during a hydraulic test. Noninteger values of the flow dimension often are inferred for tests in highly heterogeneous aquifers, yet subsequent modeling studies typically ignore the flow dimension. Monte Carlo analyses of detailed numerical models of aquifer tests examine the flow dimension for several stochastic models of heterogeneous transmissivity, T(x). These include multivariate lognormal, fractional Brownian motion, a site percolation network, and discrete linear features with lengths distributed as power-law. The behavior of the simulated flow dimensions are compared to the flow dimensions observed for multiple aquifer tests in a fractured dolomite aquifer in the Great Lakes region of North America. The combination of multiple hydraulic tests, observed fracture patterns, and the Monte Carlo results are used to screen models of heterogeneity and their parameters for subsequent groundwater flow modeling.

The Flow Dimension and Aquifer Heterogeneity: Field evidence and Numerical Analyses

NASA Astrophysics Data System (ADS)

Walker, D. D.; Cello, P. A.; Valocchi, A. J.; Roberts, R. M.; Loftis, B.

2008-12-01

The Generalized Radial Flow approach to hydraulic test interpretation infers the flow dimension to describe the geometry of the flow field during a hydraulic test. Noninteger values of the flow dimension often are inferred for tests in highly heterogeneous aquifers, yet subsequent modeling studies typically ignore the flow dimension. Monte Carlo analyses of detailed numerical models of aquifer tests examine the flow dimension for several stochastic models of heterogeneous transmissivity, T(x). These include multivariate lognormal, fractional Brownian motion, a site percolation network, and discrete linear features with lengths distributed as power-law. The behavior of the simulated flow dimensions are compared to the flow dimensions observed for multiple aquifer tests in a fractured dolomite aquifer in the Great Lakes region of North America. The combination of multiple hydraulic tests, observed fracture patterns, and the Monte Carlo results are used to screen models of heterogeneity and their parameters for subsequent groundwater flow modeling. The comparison shows that discrete linear features with lengths distributed as a power-law appear to be the most consistent with observations of the flow dimension in fractured dolomite aquifers.

Circulating tumour DNA profiling reveals heterogeneity of EGFR inhibitor resistance mechanisms in lung cancer patients

PubMed Central

Chabon, Jacob J.; Simmons, Andrew D.; Lovejoy, Alexander F.; Esfahani, Mohammad S.; Newman, Aaron M.; Haringsma, Henry J.; Kurtz, David M.; Stehr, Henning; Scherer, Florian; Karlovich, Chris A.; Harding, Thomas C.; Durkin, Kathleen A.; Otterson, Gregory A.; Purcell, W. Thomas; Camidge, D. Ross; Goldman, Jonathan W.; Sequist, Lecia V.; Piotrowska, Zofia; Wakelee, Heather A.; Neal, Joel W.; Alizadeh, Ash A.; Diehn, Maximilian

2016-01-01

Circulating tumour DNA (ctDNA) analysis facilitates studies of tumour heterogeneity. Here we employ CAPP-Seq ctDNA analysis to study resistance mechanisms in 43 non-small cell lung cancer (NSCLC) patients treated with the third-generation epidermal growth factor receptor (EGFR) inhibitor rociletinib. We observe multiple resistance mechanisms in 46% of patients after treatment with first-line inhibitors, indicating frequent intra-patient heterogeneity. Rociletinib resistance recurrently involves MET, EGFR, PIK3CA, ERRB2, KRAS and RB1. We describe a novel EGFR L798I mutation and find that EGFR C797S, which arises in ∼33% of patients after osimertinib treatment, occurs in <3% after rociletinib. Increased MET copy number is the most frequent rociletinib resistance mechanism in this cohort and patients with multiple pre-existing mechanisms (T790M and MET) experience inferior responses. Similarly, rociletinib-resistant xenografts develop MET amplification that can be overcome with the MET inhibitor crizotinib. These results underscore the importance of tumour heterogeneity in NSCLC and the utility of ctDNA-based resistance mechanism assessment. PMID:27283993

Multiple Food-Animal-Borne Route in Transmission of Antibiotic-Resistant Salmonella Newport to Humans

PubMed Central

Pan, Hang; Paudyal, Narayan; Li, Xiaoliang; Fang, Weihuan; Yue, Min

2018-01-01

Characterization of transmission routes of Salmonella among various food-animal reservoirs and their antibiogram is crucial for appropriate intervention and medical treatment. Here, we analyzed 3728 Salmonella enterica serovar Newport (S. Newport) isolates collected from various food-animals, retail meats and humans in the United States between 1996 and 2015, based on their minimum inhibitory concentration (MIC) toward 27 antibiotics. Random Forest and Hierarchical Clustering statistic was used to group the isolates according to their MICs. Classification and Regression Tree (CART) analysis was used to identify the appropriate antibiotic and its cut-off value between human- and animal-population. Two distinct populations were revealed based on the MICs of individual strain by both methods, with the animal population having significantly higher MICs which correlates to antibiotic-resistance (AR) phenotype. Only ∼9.7% (267/2763) human isolates could be attributed to food–animal origins. Furthermore, the isolates of animal origin had less diverse antibiogram than human isolates (P < 0.001), suggesting multiple sources involved in human infections. CART identified trimethoprim-sulfamethoxazole to be the best classifier for differentiating the animal and human isolates. Additionally, two typical AR patterns, MDR-Amp and Tet-SDR dominant in bovine- or turkey-population, were identified, indicating that distinct food-animal sources could be involved in human infections. The AR analysis suggested fluoroquinolones (i.e., ciprofloxacin), but not extended-spectrum cephalosporins (i.e., ceftriaxone, cefoxitin), is the adaptive choice for empirical therapy. Antibiotic-resistant S. Newport from humans has multiple origins, with distinct food-animal-borne route contributing to a significant proportion of heterogeneous isolates. PMID:29410657

Fourier mode analysis of slab-geometry transport iterations in spatially periodic media

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

Larsen, E; Zika, M

1999-04-01

We describe a Fourier analysis of the diffusion-synthetic acceleration (DSA) and transport-synthetic acceleration (TSA) iteration schemes for a spatially periodic, but otherwise arbitrarily heterogeneous, medium. Both DSA and TSA converge more slowly in a heterogeneous medium than in a homogeneous medium composed of the volume-averaged scattering ratio. In the limit of a homogeneous medium, our heterogeneous analysis contains eigenvalues of multiplicity two at ''resonant'' wave numbers. In the presence of material heterogeneities, error modes corresponding to these resonant wave numbers are ''excited'' more than other error modes. For DSA and TSA, the iteration spectral radius may occur at these resonantmore » wave numbers, in which case the material heterogeneities most strongly affect iterative performance.« less

Whole-body voxel-based personalized dosimetry: Multiple voxel S-value approach for heterogeneous media with non-uniform activity distributions.

PubMed

Lee, Min Sun; Kim, Joong Hyun; Paeng, Jin Chul; Kang, Keon Wook; Jeong, Jae Min; Lee, Dong Soo; Lee, Jae Sung

2017-12-14

Personalized dosimetry with high accuracy is becoming more important because of the growing interests in personalized medicine and targeted radionuclide therapy. Voxel-based dosimetry using dose point kernel or voxel S-value (VSV) convolution is available. However, these approaches do not consider medium heterogeneity. Here, we propose a new method for whole-body voxel-based personalized dosimetry for heterogeneous media with non-uniform activity distributions, which is referred to as the multiple VSV approach. Methods: The multiple numbers (N) of VSVs for media with different densities covering the whole-body density ranges were used instead of using only a single VSV for water. The VSVs were pre-calculated using GATE Monte Carlo simulation; those were convoluted with the time-integrated activity to generate density-specific dose maps. Computed tomography-based segmentation was conducted to generate binary maps for each density region. The final dose map was acquired by the summation of N segmented density-specific dose maps. We tested several sets of VSVs with different densities: N = 1 (single water VSV), 4, 6, 8, 10, and 20. To validate the proposed method, phantom and patient studies were conducted and compared with direct Monte Carlo, which was considered the ground truth. Finally, patient dosimetry (10 subjects) was conducted using the multiple VSV approach and compared with the single VSV and organ-based dosimetry approaches. Errors at the voxel- and organ-levels were reported for eight organs. Results: In the phantom and patient studies, the multiple VSV approach showed significant improvements regarding voxel-level errors, especially for the lung and bone regions. As N increased, voxel-level errors decreased, although some overestimations were observed at lung boundaries. In the case of multiple VSVs ( N = 8), we achieved voxel-level errors of 2.06%. In the dosimetry study, our proposed method showed much improved results compared to the single VSV and organ-based dosimetry. Errors at the organ-level were -6.71%, 2.17%, and 227.46% for the single VSV, multiple VSV, and organ-based dosimetry, respectively. Conclusion: The multiple VSV approach for heterogeneous media with non-uniform activity distributions offers fast personalized dosimetry at whole-body level, yielding results comparable to those of the direct Monte Carlo approach. Copyright © 2017 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

@neurIST: infrastructure for advanced disease management through integration of heterogeneous data, computing, and complex processing services.

PubMed

Benkner, Siegfried; Arbona, Antonio; Berti, Guntram; Chiarini, Alessandro; Dunlop, Robert; Engelbrecht, Gerhard; Frangi, Alejandro F; Friedrich, Christoph M; Hanser, Susanne; Hasselmeyer, Peer; Hose, Rod D; Iavindrasana, Jimison; Köhler, Martin; Iacono, Luigi Lo; Lonsdale, Guy; Meyer, Rodolphe; Moore, Bob; Rajasekaran, Hariharan; Summers, Paul E; Wöhrer, Alexander; Wood, Steven

2010-11-01

The increasing volume of data describing human disease processes and the growing complexity of understanding, managing, and sharing such data presents a huge challenge for clinicians and medical researchers. This paper presents the @neurIST system, which provides an infrastructure for biomedical research while aiding clinical care, by bringing together heterogeneous data and complex processing and computing services. Although @neurIST targets the investigation and treatment of cerebral aneurysms, the system's architecture is generic enough that it could be adapted to the treatment of other diseases. Innovations in @neurIST include confining the patient data pertaining to aneurysms inside a single environment that offers clinicians the tools to analyze and interpret patient data and make use of knowledge-based guidance in planning their treatment. Medical researchers gain access to a critical mass of aneurysm related data due to the system's ability to federate distributed information sources. A semantically mediated grid infrastructure ensures that both clinicians and researchers are able to seamlessly access and work on data that is distributed across multiple sites in a secure way in addition to providing computing resources on demand for performing computationally intensive simulations for treatment planning and research.

Simulation results for a multirate mass transfer modell for immiscible displacement of two fluids in highly heterogeneous porous media

NASA Astrophysics Data System (ADS)

Tecklenburg, Jan; Neuweiler, Insa; Dentz, Marco; Carrera, Jesus; Geiger, Sebastian

2013-04-01

Flow processes in geotechnical applications do often take place in highly heterogeneous porous media, such as fractured rock. Since, in this type of media, classical modelling approaches are problematic, flow and transport is often modelled using multi-continua approaches. From such approaches, multirate mass transfer models (mrmt) can be derived to describe the flow and transport in the "fast" or mobile zone of the medium. The porous media is then modeled with one mobile zone and multiple immobile zones, where the immobile zones are connected to the mobile zone by single rate mass transfer. We proceed from a mrmt model for immiscible displacement of two fluids, where the Buckley-Leverett equation is expanded by a sink-source-term which is nonlocal in time. This sink-source-term models exchange with an immobile zone with mass transfer driven by capillary diffusion. This nonlinear diffusive mass transfer can be approximated for particular imbibition or drainage cases by a linear process. We present a numerical scheme for this model together with simulation results for a single fracture test case. We solve the mrmt model with the finite volume method and explicit time integration. The sink-source-term is transformed to multiple single rate mass transfer processes, as shown by Carrera et. al. (1998), to make it local in time. With numerical simulations we studied immiscible displacement in a single fracture test case. To do this we calculated the flow parameters using information about the geometry and the integral solution for two phase flow by McWorther and Sunnada (1990). Comparision to the results of the full two dimensional two phase flow model by Flemisch et. al. (2011) show good similarities of the saturation breakthrough curves. Carrera, J., Sanchez-Vila, X., Benet, I., Medina, A., Galarza, G., and Guimera, J.: On matrix diffusion: formulations, solution methods and qualitative effects, Hydrogeology Journal, 6, 178-190, 1998. Flemisch, B., Darcis, M., Erbertseder, K., Faigle, B., Lauser, A. et al.: Dumux: Dune for multi-{Phase, Component, Scale, Physics, ...} flow and transport in porous media, Advances in Water Resources, 34, 1102-1112, 2011. McWhorter, D. B., and Sunada, D. K.: Exact integral solutions for two-phase flow, Water Resources Research, 26(3), 399-413, 1990.

Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy

PubMed Central

Lohr, Jens G.; Stojanov, Petar; Carter, Scott L.; Cruz-Gordillo, Peter; Lawrence, Michael S.; Auclair, Daniel; Sougnez, Carrie; Knoechel, Birgit; Gould, Joshua; Saksena, Gordon; Cibulskis, Kristian; McKenna, Aaron; Chapman, Michael A.; Straussman, Ravid; Levy, Joan; Perkins, Louise M.; Keats, Jonathan J.; Schumacher, Steven E.; Rosenberg, Mara; Getz, Gad

2014-01-01

SUMMARY We performed massively parallel sequencing of paired tumor/normal samples from 203 multiple myeloma (MM) patients and identified significantly mutated genes and copy number alterations, and discovered putative tumor suppressor genes by determining homozygous deletions and loss-of-heterozygosity. We observed frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53 and DIS3 (particularly in non-hyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g. KRAS, NRAS and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of non-mutated subclones in some cases. These results emphasize the importance of heterogeneity analysis for treatment decisions. PMID:24434212

Widespread genetic heterogeneity in multiple myeloma: implications for targeted therapy.

PubMed

Lohr, Jens G; Stojanov, Petar; Carter, Scott L; Cruz-Gordillo, Peter; Lawrence, Michael S; Auclair, Daniel; Sougnez, Carrie; Knoechel, Birgit; Gould, Joshua; Saksena, Gordon; Cibulskis, Kristian; McKenna, Aaron; Chapman, Michael A; Straussman, Ravid; Levy, Joan; Perkins, Louise M; Keats, Jonathan J; Schumacher, Steven E; Rosenberg, Mara; Getz, Gad; Golub, Todd R

2014-01-13

We performed massively parallel sequencing of paired tumor/normal samples from 203 multiple myeloma (MM) patients and identified significantly mutated genes and copy number alterations and discovered putative tumor suppressor genes by determining homozygous deletions and loss of heterozygosity. We observed frequent mutations in KRAS (particularly in previously treated patients), NRAS, BRAF, FAM46C, TP53, and DIS3 (particularly in nonhyperdiploid MM). Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g., KRAS, NRAS, and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of nonmutated subclones in some cases. These results emphasize the importance of heterogeneity analysis for treatment decisions. Copyright © 2014 Elsevier Inc. All rights reserved.

Imaging metabolic heterogeneity in cancer.

PubMed

Sengupta, Debanti; Pratx, Guillem

2016-01-06

As our knowledge of cancer metabolism has increased, it has become apparent that cancer metabolic processes are extremely heterogeneous. The reasons behind this heterogeneity include genetic diversity, the existence of multiple and redundant metabolic pathways, altered microenvironmental conditions, and so on. As a result, methods in the clinic and beyond have been developed in order to image and study tumor metabolism in the in vivo and in vitro regimes. Both regimes provide unique advantages and challenges, and may be used to provide a picture of tumor metabolic heterogeneity that is spatially and temporally comprehensive. Taken together, these methods may hold the key to appropriate cancer diagnoses and treatments in the future.

DDR: efficient computational method to predict drug-target interactions using graph mining and machine learning approaches.

PubMed

Olayan, Rawan S; Ashoor, Haitham; Bajic, Vladimir B

2018-04-01

Finding computationally drug-target interactions (DTIs) is a convenient strategy to identify new DTIs at low cost with reasonable accuracy. However, the current DTI prediction methods suffer the high false positive prediction rate. We developed DDR, a novel method that improves the DTI prediction accuracy. DDR is based on the use of a heterogeneous graph that contains known DTIs with multiple similarities between drugs and multiple similarities between target proteins. DDR applies non-linear similarity fusion method to combine different similarities. Before fusion, DDR performs a pre-processing step where a subset of similarities is selected in a heuristic process to obtain an optimized combination of similarities. Then, DDR applies a random forest model using different graph-based features extracted from the DTI heterogeneous graph. Using 5-repeats of 10-fold cross-validation, three testing setups, and the weighted average of area under the precision-recall curve (AUPR) scores, we show that DDR significantly reduces the AUPR score error relative to the next best start-of-the-art method for predicting DTIs by 34% when the drugs are new, by 23% when targets are new and by 34% when the drugs and the targets are known but not all DTIs between them are not known. Using independent sources of evidence, we verify as correct 22 out of the top 25 DDR novel predictions. This suggests that DDR can be used as an efficient method to identify correct DTIs. The data and code are provided at https://bitbucket.org/RSO24/ddr/. vladimir.bajic@kaust.edu.sa. Supplementary data are available at Bioinformatics online.

A multilayer concentric filter device to diminish clogging for separation of particles and microalgae based on size.

PubMed

Chen, Chih-Chung; Chen, Yu-An; Liu, Yi-Ju; Yao, Da-Jeng

2014-04-21

Microalgae species have great economic importance; they are a source of medicines, health foods, animal feeds, industrial pigments, cosmetic additives and biodiesel. Specific microalgae species collected from the environment must be isolated for examination and further application, but their varied size and culture conditions make their isolation using conventional methods, such as filtration, streaking plate and flow cytometric sorting, labour-intensive and costly. A separation device based on size is one of the most rapid, simple and inexpensive methods to separate microalgae, but this approach encounters major disadvantages of clogging and multiple filtration steps when the size of microalgae varies over a wide range. In this work, we propose a multilayer concentric filter device with varied pore size and is driven by a centrifugation force. The device, which includes multiple filter layers, was employed to separate a heterogeneous population of microparticles into several subpopulations by filtration in one step. A cross-flow to attenuate prospective clogging was generated by altering the rate of rotation instantly through the relative motion between the fluid and the filter according to the structural design of the device. Mixed microparticles of varied size were tested to demonstrate that clogging was significantly suppressed due to a highly efficient separation. Microalgae in a heterogeneous population collected from an environmental soil collection were separated and enriched into four subpopulations according to size in a one step filtration process. A microalgae sample contaminated with bacteria and insect eggs was also tested to prove the decontamination capability of the device.

PA-GFP: a window into the subcellular adventures of the individual mitochondrion.

PubMed

Haigh, Sarah E; Twig, Gilad; Molina, Anthony A J; Wikstrom, Jakob D; Deutsch, Motti; Shirihai, Orian S

2007-01-01

Mitochondrial connectivity is characterized by matrix lumen continuity and by dynamic rewiring through fusion and fission events. While these mechanisms homogenize the mitochondrial population, a number of studies looking at mitochondrial membrane potential have demonstrated that mitochondria exist as a heterogeneous population within individual cells. To address the relationship between mitochondrial dynamics and heterogeneity, we tagged and tracked individual mitochondria over time while monitoring their mitochondrial membrane potential (deltapsi(m)). By utilizing photoactivatible-GFP (PA-GFP), targeted to the mitochondrial matrix, we determined the boundaries of the individual mitochondrion. A single mitochondrion is defined by the continuity of its matrix lumen. The boundaries set by luminal continuity matched those set by electrical coupling, indicating that the individual mitochondrion is equipotential throughout the entire organelle. Similar results were obtained with PA-GFP targeted to the inner membrane indicating that matrix continuity parallels inner membrane continuity. Sequential photoconversion of matrix PA-GFP in multiple locations within the mitochondrial web reveals that each ramified mitochondrial structure is composed of juxtaposed but discontinuous units. Moreover, as many as half of the events in which mitochondria come into contact, do not result in fusion. While all fission events generated two electrically uncoupled discontinuous matrices, the two daughter mitochondria frequently remained juxtaposed, keeping the tubular appearance unchanged. These morphologically invisible fission events illustrate the difference between mitochondrial fission and fragmentation; the latter representing the movement and separation of disconnected units. Simultaneous monitoring of deltapsi(m) of up to four individual mitochondria within the same cell revealed that subcellular heterogeneity in deltapsi(m) does not represent multiple unstable mitochondria that appear 'heterogeneous' at any given point, but rather multiple stable, but heterogeneous units.

Legacy of contaminant N sources to the NO3- signature in rivers: a combined isotopic (δ15N-NO3-, δ18O-NO3-, δ11B) and microbiological investigation

NASA Astrophysics Data System (ADS)

Briand, Cyrielle; Sebilo, Mathieu; Louvat, Pascale; Chesnot, Thierry; Vaury, Véronique; Schneider, Maude; Plagnes, Valérie

2017-02-01

Nitrate content of surface waters results from complex mixing of multiple sources, whose signatures can be modified through N reactions occurring within the different compartments of the whole catchment. Despite this complexity, the determination of nitrate origin is the first and crucial step for water resource preservation. Here, for the first time, we combined at the catchment scale stable isotopic tracers (δ15N and δ18O of nitrate and δ11B) and fecal indicators to trace nitrate sources and pathways to the stream. We tested this approach on two rivers in an agricultural region of SW France. Boron isotopic ratios evidenced inflow from anthropogenic waters, microbiological markers revealed organic contaminations from both human and animal wastes. Nitrate δ15N and δ18O traced inputs from the surface leaching during high flow events and from the subsurface drainage in base flow regime. They also showed that denitrification occurred within the soils before reaching the rivers. Furthermore, this study highlighted the determinant role of the soil compartment in nitrate formation and recycling with important spatial heterogeneity and temporal variability.

Global high-frequency source imaging accounting for complexity in Green's functions

NASA Astrophysics Data System (ADS)

Lambert, V.; Zhan, Z.

2017-12-01

The general characterization of earthquake source processes at long periods has seen great success via seismic finite fault inversion/modeling. Complementary techniques, such as seismic back-projection, extend the capabilities of source imaging to higher frequencies and reveal finer details of the rupture process. However, such high frequency methods are limited by the implicit assumption of simple Green's functions, which restricts the use of global arrays and introduces artifacts (e.g., sweeping effects, depth/water phases) that require careful attention. This motivates the implementation of an imaging technique that considers the potential complexity of Green's functions at high frequencies. We propose an alternative inversion approach based on the modest assumption that the path effects contributing to signals within high-coherency subarrays share a similar form. Under this assumption, we develop a method that can combine multiple high-coherency subarrays to invert for a sparse set of subevents. By accounting for potential variability in the Green's functions among subarrays, our method allows for the utilization of heterogeneous global networks for robust high resolution imaging of the complex rupture process. The approach also provides a consistent framework for examining frequency-dependent radiation across a broad frequency spectrum.

The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Discovering, Exploring, and Mapping Spatiotemporal Patterns Across Heterogenous Space-Time Data

NASA Astrophysics Data System (ADS)

Morton, A.; Stewart, R.; Held, E.; Piburn, J.; Allen, M. R.; McManamay, R.; Sanyal, J.; Sorokine, A.; Bhaduri, B. L.

2017-12-01

Spatiotemporal (ST) analytics applied to major spatio-temporal data sources from major vendors such as USGS, NOAA, World Bank and World Health Organization have tremendous value in shedding light on the evolution of physical, cultural, and geopolitical landscapes on a local and global level. Especially powerful is the integration of these physical and cultural datasets across multiple and disparate formats, facilitating new interdisciplinary analytics and insights. Realizing this potential first requires an ST data model that addresses challenges in properly merging data from multiple authors, with evolving ontological perspectives, semantical differences, changing attributes, and content that is textual, numeric, categorical, and hierarchical. Equally challenging is the development of analytical and visualization approaches that provide a serious exploration of this integrated data while remaining accessible to practitioners with varied backgrounds. The WSTAMP project at the Oak Ridge National Laboratory has yielded two major results in addressing these challenges: 1) development of the WSTAMP database, a significant advance in ST data modeling that integrates 16000+ attributes covering 200+ countries for over 50 years from over 30 major sources and 2) a novel online ST exploratory and analysis tool providing an array of modern statistical and visualization techniques for analyzing these data temporally, spatially, and spatiotemporally under a standard analytic workflow. We report on these advances, provide an illustrative case study, and inform how others may freely access the tool.

Precise segmentation of multiple organs in CT volumes using learning-based approach and information theory.

PubMed

Lu, Chao; Zheng, Yefeng; Birkbeck, Neil; Zhang, Jingdan; Kohlberger, Timo; Tietjen, Christian; Boettger, Thomas; Duncan, James S; Zhou, S Kevin

2012-01-01

In this paper, we present a novel method by incorporating information theory into the learning-based approach for automatic and accurate pelvic organ segmentation (including the prostate, bladder and rectum). We target 3D CT volumes that are generated using different scanning protocols (e.g., contrast and non-contrast, with and without implant in the prostate, various resolution and position), and the volumes come from largely diverse sources (e.g., diseased in different organs). Three key ingredients are combined to solve this challenging segmentation problem. First, marginal space learning (MSL) is applied to efficiently and effectively localize the multiple organs in the largely diverse CT volumes. Second, learning techniques, steerable features, are applied for robust boundary detection. This enables handling of highly heterogeneous texture pattern. Third, a novel information theoretic scheme is incorporated into the boundary inference process. The incorporation of the Jensen-Shannon divergence further drives the mesh to the best fit of the image, thus improves the segmentation performance. The proposed approach is tested on a challenging dataset containing 188 volumes from diverse sources. Our approach not only produces excellent segmentation accuracy, but also runs about eighty times faster than previous state-of-the-art solutions. The proposed method can be applied to CT images to provide visual guidance to physicians during the computer-aided diagnosis, treatment planning and image-guided radiotherapy to treat cancers in pelvic region.

Automated Traffic Management System and Method

NASA Technical Reports Server (NTRS)

Glass, Brian J. (Inventor); Spirkovska, Liljana (Inventor); McDermott, William J. (Inventor); Reisman, Ronald J. (Inventor); Gibson, James (Inventor); Iverson, David L. (Inventor)

2000-01-01

A data management system and method that enables acquisition, integration, and management of real-time data generated at different rates, by multiple heterogeneous incompatible data sources. The system achieves this functionality by using an expert system to fuse data from a variety of airline, airport operations, ramp control, and air traffic control tower sources, to establish and update reference data values for every aircraft surface operation. The system may be configured as a real-time airport surface traffic management system (TMS) that electronically interconnects air traffic control, airline data, and airport operations data to facilitate information sharing and improve taxi queuing. In the TMS operational mode, empirical data shows substantial benefits in ramp operations for airlines, reducing departure taxi times by about one minute per aircraft in operational use, translating as $12 to $15 million per year savings to airlines at the Atlanta, Georgia airport. The data management system and method may also be used for scheduling the movement of multiple vehicles in other applications, such as marine vessels in harbors and ports, trucks or railroad cars in ports or shipping yards, and railroad cars in switching yards. Finally, the data management system and method may be used for managing containers at a shipping dock, stock on a factory floor or in a warehouse, or as a training tool for improving situational awareness of FAA tower controllers, ramp and airport operators, or commercial airline personnel in airfield surface operations.

Simultaneous Quantification of Temperature, Pyroxenite Abundance, and Upwelling Rates in the Iceland Mantle Source

NASA Astrophysics Data System (ADS)

Brown, E.; Lesher, C. E.

2014-12-01

The compositions and volumes of basalts erupted at the earth's surface are a function of mantle temperature, mantle composition, and the rate at which the mantle upwells through the melting zone. Thus, basaltic magmatism has long been used to probe the thermal and physiochemical state of the earth's mantle. Great insight has been gained into the mantle beneath the global spreading ridge system, where the mantle source is assumed to be homogeneous peridotite that upwells passively [1]. However, it is now recognized that many basalt source regions are lithologically heterogeneous (i.e. containing recycled lithospheric material ranging from harzburgite to pyroxenite) and upwell at rates in excess of those governed by plate separation. To account for these complexities, we have developed a forward melting model for lithologically heterogeneous mantle that incorporates thermodynamically and experimentally constrained melting functions for a range of peridotite and pyroxenite lithologies. The model is unique because it quantifies mantle upwelling rates based on the net buoyancy of the source, thus providing a means for linking basalt compositions/volumes to mantle flow while accounting for source heterogeneity. We apply the model to investigate the mantle properties governing magmatism along different rift segments in Iceland, where lithologic heterogeneity and variable upwelling rates have been inferred through geochemical means [2,3]. Using constraints from seismically determined crustal thicknesses and recent estimates of the proportion of pyroxenite-derived melt contributing to Icelandic basalt compositions [4,5], we show that mantle sources beneath Iceland have excess potential temperatures >85 °C, contain <7% pyroxenite, and maximum upwelling rates ~14 times the passive rate. Our modeling highlights the dominant role of elevated mantle temperature and enhanced upwelling for high productivity magmatism in Iceland, and a subordinate role for mantle heterogeneity, which is required to account for much of the observed chemical and isotopic diversity. [1] Langmuir et al, 1992, AGU Geophys. Mono. Ser. 71 [2] Chauvel & Hemond, 2000, G-cubed, v 1 [3] Kokfelt et al, 2003, EPSL, v 214 [4] Sobolev et al, 2007, Science, v 316 [5] Shorttle et al, 2014, EPSL, v 395

Rg-Lg coupling as a Lg-wave excitation mechanism

NASA Astrophysics Data System (ADS)

Ge, Z.; Xie, X.

2003-12-01

Regional phase Lg is predominantly comprised of shear wave energy trapped in the crust. Explosion sources are expected to be less efficient for excitation of Lg phases than earthquakes to the extent that the source can be approximated as isotropic. Shallow explosions generate relatively large surface wave Rg compared to deeper earthquakes, and Rg is readily disrupted by crustal heterogeneity. Rg energy may thus scatter into trapped crustal S-waves near the source region and contribute to low-frequency Lg wave. In this study, a finite-difference modeling plus the slowness analysis are used for investigating the above mentioned Lg-wave excitation mechanism. The method allows us to investigate near source energy partitioning in multiple domains including frequency, slowness and time. The main advantage of this method is that it can be applied at close range, before Lg is actually formed, which allows us to use very fine near source velocity model to simulate the energy partitioning process. We use a layered velocity structure as the background model and add small near source random velocity patches to the model to generate the Rg to Lg coupling. Two types of simulations are conducted, (1) a fixed shallow explosion source vs. randomness at different depths and (2) a fixed shallow randomness vs. explosion sources at different depths. The results show apparent couplings between the Rg and Lg waves at lower frequencies (0.3-1.5 Hz). A shallow source combined with shallow randomness generates the maximum Lg-wave, which is consistent with the Rg energy distribution of a shallow explosion source. The Rg energy and excited Lg energy show a near linear relationship. The numerical simulation and slowness analysis suggest that the Rg to Lg coupling is an effective excitation mechanism for low frequency Lg-waves from a shallow explosion source.

A new approach to flow simulation in highly heterogeneous porous media

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

Rame, M.; Killough, J.E.

In this paper, applications are presented for a new numerical method - operator splittings on multiple grids (OSMG) - devised for simulations in heterogeneous porous media. A coarse-grid, finite-element pressure solver is interfaced with a fine-grid timestepping scheme. The CPU time for the pressure solver is greatly reduced and concentration fronts have minimal numerical dispersion.

TLM-Quant: An Open-Source Pipeline for Visualization and Quantification of Gene Expression Heterogeneity in Growing Microbial Cells

PubMed Central

Piersma, Sjouke; Denham, Emma L.; Drulhe, Samuel; Tonk, Rudi H. J.; Schwikowski, Benno; van Dijl, Jan Maarten

2013-01-01

Gene expression heterogeneity is a key driver for microbial adaptation to fluctuating environmental conditions, cell differentiation and the evolution of species. This phenomenon has therefore enormous implications, not only for life in general, but also for biotechnological applications where unwanted subpopulations of non-producing cells can emerge in large-scale fermentations. Only time-lapse fluorescence microscopy allows real-time measurements of gene expression heterogeneity. A major limitation in the analysis of time-lapse microscopy data is the lack of fast, cost-effective, open, simple and adaptable protocols. Here we describe TLM-Quant, a semi-automatic pipeline for the analysis of time-lapse fluorescence microscopy data that enables the user to visualize and quantify gene expression heterogeneity. Importantly, our pipeline builds on the open-source packages ImageJ and R. To validate TLM-Quant, we selected three possible scenarios, namely homogeneous expression, highly ‘noisy’ heterogeneous expression, and bistable heterogeneous expression in the Gram-positive bacterium Bacillus subtilis. This bacterium is both a paradigm for systems-level studies on gene expression and a highly appreciated biotechnological ‘cell factory’. We conclude that the temporal resolution of such analyses with TLM-Quant is only limited by the numbers of recorded images. PMID:23874729

Stochastic simulation in systems biology

PubMed Central

Székely, Tamás; Burrage, Kevin

2014-01-01

Natural systems are, almost by definition, heterogeneous: this can be either a boon or an obstacle to be overcome, depending on the situation. Traditionally, when constructing mathematical models of these systems, heterogeneity has typically been ignored, despite its critical role. However, in recent years, stochastic computational methods have become commonplace in science. They are able to appropriately account for heterogeneity; indeed, they are based around the premise that systems inherently contain at least one source of heterogeneity (namely, intrinsic heterogeneity). In this mini-review, we give a brief introduction to theoretical modelling and simulation in systems biology and discuss the three different sources of heterogeneity in natural systems. Our main topic is an overview of stochastic simulation methods in systems biology. There are many different types of stochastic methods. We focus on one group that has become especially popular in systems biology, biochemistry, chemistry and physics. These discrete-state stochastic methods do not follow individuals over time; rather they track only total populations. They also assume that the volume of interest is spatially homogeneous. We give an overview of these methods, with a discussion of the advantages and disadvantages of each, and suggest when each is more appropriate to use. We also include references to software implementations of them, so that beginners can quickly start using stochastic methods for practical problems of interest. PMID:25505503

Finite-fault source inversion using adjoint methods in 3D heterogeneous media

NASA Astrophysics Data System (ADS)

Somala, Surendra Nadh; Ampuero, Jean-Paul; Lapusta, Nadia

2018-04-01

Accounting for lateral heterogeneities in the 3D velocity structure of the crust is known to improve earthquake source inversion, compared to results based on 1D velocity models which are routinely assumed to derive finite-fault slip models. The conventional approach to include known 3D heterogeneity in source inversion involves pre-computing 3D Green's functions, which requires a number of 3D wave propagation simulations proportional to the number of stations or to the number of fault cells. The computational cost of such an approach is prohibitive for the dense datasets that could be provided by future earthquake observation systems. Here, we propose an adjoint-based optimization technique to invert for the spatio-temporal evolution of slip velocity. The approach does not require pre-computed Green's functions. The adjoint method provides the gradient of the cost function, which is used to improve the model iteratively employing an iterative gradient-based minimization method. The adjoint approach is shown to be computationally more efficient than the conventional approach based on pre-computed Green's functions in a broad range of situations. We consider data up to 1 Hz from a Haskell source scenario (a steady pulse-like rupture) on a vertical strike-slip fault embedded in an elastic 3D heterogeneous velocity model. The velocity model comprises a uniform background and a 3D stochastic perturbation with the von Karman correlation function. Source inversions based on the 3D velocity model are performed for two different station configurations, a dense and a sparse network with 1 km and 20 km station spacing, respectively. These reference inversions show that our inversion scheme adequately retrieves the rise time when the velocity model is exactly known, and illustrates how dense coverage improves the inference of peak slip velocities. We investigate the effects of uncertainties in the velocity model by performing source inversions based on an incorrect, homogeneous velocity model. We find that, for velocity uncertainties that have standard deviation and correlation length typical of available 3D crustal models, the inverted sources can be severely contaminated by spurious features even if the station density is high. When data from thousand or more receivers is used in source inversions in 3D heterogeneous media, the computational cost of the method proposed in this work is at least two orders of magnitude lower than source inversion based on pre-computed Green's functions.

Finite-fault source inversion using adjoint methods in 3-D heterogeneous media

NASA Astrophysics Data System (ADS)

Somala, Surendra Nadh; Ampuero, Jean-Paul; Lapusta, Nadia

2018-07-01

Accounting for lateral heterogeneities in the 3-D velocity structure of the crust is known to improve earthquake source inversion, compared to results based on 1-D velocity models which are routinely assumed to derive finite-fault slip models. The conventional approach to include known 3-D heterogeneity in source inversion involves pre-computing 3-D Green's functions, which requires a number of 3-D wave propagation simulations proportional to the number of stations or to the number of fault cells. The computational cost of such an approach is prohibitive for the dense data sets that could be provided by future earthquake observation systems. Here, we propose an adjoint-based optimization technique to invert for the spatio-temporal evolution of slip velocity. The approach does not require pre-computed Green's functions. The adjoint method provides the gradient of the cost function, which is used to improve the model iteratively employing an iterative gradient-based minimization method. The adjoint approach is shown to be computationally more efficient than the conventional approach based on pre-computed Green's functions in a broad range of situations. We consider data up to 1 Hz from a Haskell source scenario (a steady pulse-like rupture) on a vertical strike-slip fault embedded in an elastic 3-D heterogeneous velocity model. The velocity model comprises a uniform background and a 3-D stochastic perturbation with the von Karman correlation function. Source inversions based on the 3-D velocity model are performed for two different station configurations, a dense and a sparse network with 1 and 20 km station spacing, respectively. These reference inversions show that our inversion scheme adequately retrieves the rise time when the velocity model is exactly known, and illustrates how dense coverage improves the inference of peak-slip velocities. We investigate the effects of uncertainties in the velocity model by performing source inversions based on an incorrect, homogeneous velocity model. We find that, for velocity uncertainties that have standard deviation and correlation length typical of available 3-D crustal models, the inverted sources can be severely contaminated by spurious features even if the station density is high. When data from thousand or more receivers is used in source inversions in 3-D heterogeneous media, the computational cost of the method proposed in this work is at least two orders of magnitude lower than source inversion based on pre-computed Green's functions.

Mono-static GPR without transmitting anything for pavement damage inspection: interferometry by auto-correlation applied to mobile phone signals

NASA Astrophysics Data System (ADS)

Feld, R.; Slob, E. C.; Thorbecke, J.

2015-12-01

Creating virtual sources at locations where physical receivers have measured a response is known as seismic interferometry. A much appreciated benefit of interferometry is its independence of the actual source locations. The use of ambient noise as actual source is therefore not uncommon in this field. Ambient noise can be commercial noise, like for example mobile phone signals. For GPR this can be useful in cases where it is not possible to place a source, for instance when it is prohibited by laws and regulations. A mono-static GPR antenna can measure ambient noise. Interferometry by auto-correlation (AC) places a virtual source on this antenna's position, without actually transmitting anything. This can be used for pavement damage inspection. Earlier work showed very promising results with 2D numerical models of damaged pavement. 1D and 2D heterogeneities were compared, both modelled in a 2D pavement world. In a 1D heterogeneous model energy leaks away to the sides, whereas in a 2D heterogeneous model rays can reflect and therefore still add to the signal reconstruction (see illustration). In the first case the amount of stationary points is strictly limited, while in the other case the amount of stationary points is very large. We extend these models to a 3D world and optimise an experimental configuration. The illustration originates from the journal article under submission 'Non-destructive pavement damage inspection by mono-static GPR without transmitting anything' by R. Feld, E.C. Slob, and J.W. Thorbecke. (a) 2D heterogeneous pavement model with three irregular-shaped misalignments between the base and subbase layer (marked by arrows). Mono-antenna B-scan positions are shown schematically. (b) Ideal output: a real source at the receiver's position. The difference w.r.t. the trace found in the middle is shown. (c) AC output: a virtual source at the receiver's position. There is a clear overlap with the ideal output.

Heterogeneity, histological features and DNA ploidy in oral carcinoma by image-based analysis.

PubMed

Diwakar, N; Sperandio, M; Sherriff, M; Brown, A; Odell, E W

2005-04-01

Oral squamous carcinomas appear heterogeneous on DNA ploidy analysis. However, this may be partly a result of sample dilution or the detection limit of techniques. The aim of this study was to determine whether oral squamous carcinomas are heterogeneous for ploidy status using image-based ploidy analysis and to determine whether ploidy status correlates with histological parameters. Multiple samples from 42 oral squamous carcinomas were analysed for DNA ploidy using an image-based system and scored for histological parameters. 22 were uniformly aneuploid, 1 uniformly tetraploid and 3 uniformly diploid. 16 appeared heterogeneous but only 8 appeared to be genuinely heterogeneous when minor ploidy histogram peaks were taken into account. Ploidy was closely related to nuclear pleomorphism but not differentiation. Sample variation, detection limits and diagnostic criteria account for much of the ploidy heterogeneity observed. Confident diagnosis of diploid status in an oral squamous cell carcinoma requires a minimum of 5 samples.

Kalman approach to accuracy management for interoperable heterogeneous model abstraction within an HLA-compliant simulation

NASA Astrophysics Data System (ADS)

Leskiw, Donald M.; Zhau, Junmei

2000-06-01

This paper reports on results from an ongoing project to develop methodologies for representing and managing multiple, concurrent levels of detail and enabling high performance computing using parallel arrays within distributed object-based simulation frameworks. At this time we present the methodology for representing and managing multiple, concurrent levels of detail and modeling accuracy by using a representation based on the Kalman approach for estimation. The Kalman System Model equations are used to represent model accuracy, Kalman Measurement Model equations provide transformations between heterogeneous levels of detail, and interoperability among disparate abstractions is provided using a form of the Kalman Update equations.

Analytical framework for reconstructing heterogeneous environmental variables from mammal community structure.

PubMed

Louys, Julien; Meloro, Carlo; Elton, Sarah; Ditchfield, Peter; Bishop, Laura C

2015-01-01

We test the performance of two models that use mammalian communities to reconstruct multivariate palaeoenvironments. While both models exploit the correlation between mammal communities (defined in terms of functional groups) and arboreal heterogeneity, the first uses a multiple multivariate regression of community structure and arboreal heterogeneity, while the second uses a linear regression of the principal components of each ecospace. The success of these methods means the palaeoenvironment of a particular locality can be reconstructed in terms of the proportions of heavy, moderate, light, and absent tree canopy cover. The linear regression is less biased, and more precisely and accurately reconstructs heavy tree canopy cover than the multiple multivariate model. However, the multiple multivariate model performs better than the linear regression for all other canopy cover categories. Both models consistently perform better than randomly generated reconstructions. We apply both models to the palaeocommunity of the Upper Laetolil Beds, Tanzania. Our reconstructions indicate that there was very little heavy tree cover at this site (likely less than 10%), with the palaeo-landscape instead comprising a mixture of light and absent tree cover. These reconstructions help resolve the previous conflicting palaeoecological reconstructions made for this site. Copyright © 2014 Elsevier Ltd. All rights reserved.

Statistical and sampling issues when using multiple particle tracking

NASA Astrophysics Data System (ADS)

Savin, Thierry; Doyle, Patrick S.

2007-08-01

Video microscopy can be used to simultaneously track several microparticles embedded in a complex material. The trajectories are used to extract a sample of displacements at random locations in the material. From this sample, averaged quantities characterizing the dynamics of the probes are calculated to evaluate structural and/or mechanical properties of the assessed material. However, the sampling of measured displacements in heterogeneous systems is singular because the volume of observation with video microscopy is finite. By carefully characterizing the sampling design in the experimental output of the multiple particle tracking technique, we derive estimators for the mean and variance of the probes’ dynamics that are independent of the peculiar statistical characteristics. We expose stringent tests of these estimators using simulated and experimental complex systems with a known heterogeneous structure. Up to a certain fundamental limitation, which we characterize through a material degree of sampling by the embedded probe tracking, these estimators can be applied to quantify the heterogeneity of a material, providing an original and intelligible kind of information on complex fluid properties. More generally, we show that the precise assessment of the statistics in the multiple particle tracking output sample of observations is essential in order to provide accurate unbiased measurements.

Application of normal mode theory to seismic source and structure problems: Seismic investigations of upper mantle lateral heterogeneity. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Okal, E. A.

1978-01-01

The theory of the normal modes of the earth is investigated and used to build synthetic seismograms in order to solve source and structural problems. A study is made of the physical properties of spheroidal modes leading to a rational classification. Two problems addressed are the observability of deep isotropic seismic sources and the investigation of the physical properties of the earth in the neighborhood of the Core-Mantle boundary, using SH waves diffracted at the core's surface. Data sets of seismic body and surface waves are used in a search for possible deep lateral heterogeneities in the mantle. In both cases, it is found that seismic data do not require structural differences between oceans and continents to extend deeper than 250 km. In general, differences between oceans and continents are found to be on the same order of magnitude as the intrinsic lateral heterogeneity in the oceanic plate brought about by the aging of the oceanic lithosphere.

Prediction of Down-Gradient Impacts of DNAPL Source Depletion Using Tracer Techniques

NASA Astrophysics Data System (ADS)

Basu, N. B.; Fure, A. D.; Jawitz, J. W.

2006-12-01

Four simplified DNAPL source depletion models that have been discussed in the literature recently are evaluated for the prediction of long-term effects of source depletion under natural gradient flow. These models are simple in form (a power function equation is an example) but are shown here to serve as mathematical analogs to complex multiphase flow and transport simulators. One of the source depletion models, the equilibrium streamtube model, is shown to be relatively easily parameterized using non-reactive and reactive tracers. Non-reactive tracers are used to characterize the aquifer heterogeneity while reactive tracers are used to describe the mean DNAPL mass and its distribution. This information is then used in a Lagrangian framework to predict source remediation performance. In a Lagrangian approach the source zone is conceptualized as a collection of non-interacting streamtubes with hydrodynamic and DNAPL heterogeneity represented by the variation of the travel time and DNAPL saturation among the streamtubes. The travel time statistics are estimated from the non-reactive tracer data while the DNAPL distribution statistics are estimated from the reactive tracer data. The combined statistics are used to define an analytical solution for contaminant dissolution under natural gradient flow. The tracer prediction technique compared favorably with results from a multiphase flow and transport simulator UTCHEM in domains with different hydrodynamic heterogeneity (variance of the log conductivity field = 0.2, 1 and 3).

ODMSummary: A Tool for Automatic Structured Comparison of Multiple Medical Forms Based on Semantic Annotation with the Unified Medical Language System.

PubMed

Storck, Michael; Krumm, Rainer; Dugas, Martin

2016-01-01

Medical documentation is applied in various settings including patient care and clinical research. Since procedures of medical documentation are heterogeneous and developed further, secondary use of medical data is complicated. Development of medical forms, merging of data from different sources and meta-analyses of different data sets are currently a predominantly manual process and therefore difficult and cumbersome. Available applications to automate these processes are limited. In particular, tools to compare multiple documentation forms are missing. The objective of this work is to design, implement and evaluate the new system ODMSummary for comparison of multiple forms with a high number of semantically annotated data elements and a high level of usability. System requirements are the capability to summarize and compare a set of forms, enable to estimate the documentation effort, track changes in different versions of forms and find comparable items in different forms. Forms are provided in Operational Data Model format with semantic annotations from the Unified Medical Language System. 12 medical experts were invited to participate in a 3-phase evaluation of the tool regarding usability. ODMSummary (available at https://odmtoolbox.uni-muenster.de/summary/summary.html) provides a structured overview of multiple forms and their documentation fields. This comparison enables medical experts to assess multiple forms or whole datasets for secondary use. System usability was optimized based on expert feedback. The evaluation demonstrates that feedback from domain experts is needed to identify usability issues. In conclusion, this work shows that automatic comparison of multiple forms is feasible and the results are usable for medical experts.

Sedimentation equilibrium analysis of protein interactions with global implicit mass conservation constraints and systematic noise decomposition.

PubMed

Vistica, Jennifer; Dam, Julie; Balbo, Andrea; Yikilmaz, Emine; Mariuzza, Roy A; Rouault, Tracey A; Schuck, Peter

2004-03-15

Sedimentation equilibrium is a powerful tool for the characterization of protein self-association and heterogeneous protein interactions. Frequently, it is applied in a configuration with relatively long solution columns and with equilibrium profiles being acquired sequentially at several rotor speeds. The present study proposes computational tools, implemented in the software SEDPHAT, for the global analysis of equilibrium data at multiple rotor speeds with multiple concentrations and multiple optical detection methods. The detailed global modeling of such equilibrium data can be a nontrivial computational problem. It was shown previously that mass conservation constraints can significantly improve and extend the analysis of heterogeneous protein interactions. Here, a method for using conservation of mass constraints for the macromolecular redistribution is proposed in which the effective loading concentrations are calculated from the sedimentation equilibrium profiles. The approach is similar to that described by Roark (Biophys. Chem. 5 (1976) 185-196), but its utility is extended by determining the bottom position of the solution columns from the macromolecular redistribution. For analyzing heterogeneous associations at multiple protein concentrations, additional constraints that relate the effective loading concentrations of the different components or their molar ratio in the global analysis are introduced. Equilibrium profiles at multiple rotor speeds also permit the algebraic determination of radial-dependent baseline profiles, which can govern interference optical ultracentrifugation data, but usually also occur, to a smaller extent, in absorbance optical data. Finally, the global analysis of equilibrium profiles at multiple rotor speeds with implicit mass conservation and computation of the bottom of the solution column provides an unbiased scale for determining molar mass distributions of noninteracting species. The properties of these tools are studied with theoretical and experimental data sets.

CROPPER: a metagene creator resource for cross-platform and cross-species compendium studies.

PubMed

Paananen, Jussi; Storvik, Markus; Wong, Garry

2006-09-22

Current genomic research methods provide researchers with enormous amounts of data. Combining data from different high-throughput research technologies commonly available in biological databases can lead to novel findings and increase research efficiency. However, combining data from different heterogeneous sources is often a very arduous task. These sources can be different microarray technology platforms, genomic databases, or experiments performed on various species. Our aim was to develop a software program that could facilitate the combining of data from heterogeneous sources, and thus allow researchers to perform genomic cross-platform/cross-species studies and to use existing experimental data for compendium studies. We have developed a web-based software resource, called CROPPER that uses the latest genomic information concerning different data identifiers and orthologous genes from the Ensembl database. CROPPER can be used to combine genomic data from different heterogeneous sources, allowing researchers to perform cross-platform/cross-species compendium studies without the need for complex computational tools or the requirement of setting up one's own in-house database. We also present an example of a simple cross-platform/cross-species compendium study based on publicly available Parkinson's disease data derived from different sources. CROPPER is a user-friendly and freely available web-based software resource that can be successfully used for cross-species/cross-platform compendium studies.

In vivo quantitative bioluminescence tomography using heterogeneous and homogeneous mouse models.

PubMed

Liu, Junting; Wang, Yabin; Qu, Xiaochao; Li, Xiangsi; Ma, Xiaopeng; Han, Runqiang; Hu, Zhenhua; Chen, Xueli; Sun, Dongdong; Zhang, Rongqing; Chen, Duofang; Chen, Dan; Chen, Xiaoyuan; Liang, Jimin; Cao, Feng; Tian, Jie

2010-06-07

Bioluminescence tomography (BLT) is a new optical molecular imaging modality, which can monitor both physiological and pathological processes by using bioluminescent light-emitting probes in small living animal. Especially, this technology possesses great potential in drug development, early detection, and therapy monitoring in preclinical settings. In the present study, we developed a dual modality BLT prototype system with Micro-computed tomography (MicroCT) registration approach, and improved the quantitative reconstruction algorithm based on adaptive hp finite element method (hp-FEM). Detailed comparisons of source reconstruction between the heterogeneous and homogeneous mouse models were performed. The models include mice with implanted luminescence source and tumor-bearing mice with firefly luciferase report gene. Our data suggest that the reconstruction based on heterogeneous mouse model is more accurate in localization and quantification than the homogeneous mouse model with appropriate optical parameters and that BLT allows super-early tumor detection in vivo based on tomographic reconstruction of heterogeneous mouse model signal.

Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images.

PubMed

Spagnolo, Daniel M; Al-Kofahi, Yousef; Zhu, Peihong; Lezon, Timothy R; Gough, Albert; Stern, Andrew M; Lee, Adrian V; Ginty, Fiona; Sarachan, Brion; Taylor, D Lansing; Chennubhotla, S Chakra

2017-11-01

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and noncellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole-slide immunofluorescence images and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research. Cancer Res; 77(21); e71-74. ©2017 AACR . ©2017 American Association for Cancer Research.

Numerical simulation of two-dimensional flow over a heated carbon surface with coupled heterogeneous and homogeneous reactions

NASA Astrophysics Data System (ADS)

Johnson, Ryan Federick; Chelliah, Harsha Kumar

2017-01-01

For a range of flow and chemical timescales, numerical simulations of two-dimensional laminar flow over a reacting carbon surface were performed to understand further the complex coupling between heterogeneous and homogeneous reactions. An open-source computational package (OpenFOAM®) was used with previously developed lumped heterogeneous reaction models for carbon surfaces and a detailed homogeneous reaction model for CO oxidation. The influence of finite-rate chemical kinetics was explored by varying the surface temperatures from 1800 to 2600 K, while flow residence time effects were explored by varying the free-stream velocity up to 50 m/s. The reacting boundary layer structure dependence on the residence time was analysed by extracting the ratio of chemical source and species diffusion terms. The important contributions of radical species reactions on overall carbon removal rate, which is often neglected in multi-dimensional simulations, are highlighted. The results provide a framework for future development and validation of lumped heterogeneous reaction models based on multi-dimensional reacting flow configurations.

Coupled lasers: phase versus chaos synchronization.

PubMed

Reidler, I; Nixon, M; Aviad, Y; Guberman, S; Friesem, A A; Rosenbluh, M; Davidson, N; Kanter, I

2013-10-15

The synchronization of chaotic lasers and the optical phase synchronization of light originating in multiple coupled lasers have both been extensively studied. However, the interplay between these two phenomena, especially at the network level, is unexplored. Here, we experimentally compare these phenomena by controlling the heterogeneity of the coupling delay times of two lasers. While chaotic lasers exhibit deterioration in synchronization as the time delay heterogeneity increases, phase synchronization is found to be independent of heterogeneity. The experimental results are found to be in agreement with numerical simulations for semiconductor lasers.

The Effects of Realistic Geological Heterogeneity on Seismic Modeling: Applications in Shear Wave Generation and Near-Surface Tunnel Detection

NASA Astrophysics Data System (ADS)

Sherman, Christopher Scott

Naturally occurring geologic heterogeneity is an important, but often overlooked, aspect of seismic wave propagation. This dissertation presents a strategy for modeling the effects of heterogeneity using a combination of geostatistics and Finite Difference simulation. In the first chapter, I discuss my motivations for studying geologic heterogeneity and seis- mic wave propagation. Models based upon fractal statistics are powerful tools in geophysics for modeling heterogeneity. The important features of these fractal models are illustrated using borehole log data from an oil well and geomorphological observations from a site in Death Valley, California. A large part of the computational work presented in this disserta- tion was completed using the Finite Difference Code E3D. I discuss the Python-based user interface for E3D and the computational strategies for working with heterogeneous models developed over the course of this research. The second chapter explores a phenomenon observed for wave propagation in heteroge- neous media - the generation of unexpected shear wave phases in the near-source region. In spite of their popularity amongst seismic researchers, approximate methods for modeling wave propagation in these media, such as the Born and Rytov methods or Radiative Trans- fer Theory, are incapable of explaining these shear waves. This is primarily due to these method's assumptions regarding the coupling of near-source terms with the heterogeneities and mode conversion. To determine the source of these shear waves, I generate a suite of 3D synthetic heterogeneous fractal geologic models and use E3D to simulate the wave propaga- tion for a vertical point force on the surface of the models. I also present a methodology for calculating the effective source radiation patterns from the models. The numerical results show that, due to a combination of mode conversion and coupling with near-source hetero- geneity, shear wave energy on the order of 10% of the compressional wave energy may be generated within the shear radiation node of the source. Interestingly, in some cases this shear wave may arise as a coherent pulse, which may be used to improve seismic imaging efforts. In the third and fourth chapters, I discuss the results of a numerical analysis and field study of seismic near-surface tunnel detection methods. Detecting unknown tunnels and voids, such as old mine workings or solution cavities in karst terrain, is a challenging prob- lem in geophysics and has implications for geotechnical design, public safety, and domestic security. Over the years, a number of different geophysical methods have been developed to locate these objects (microgravity, resistivity, seismic diffraction, etc.), each with varying results. One of the major challenges facing these methods is understanding the influence of geologic heterogeneity on their results, which makes this problem a natural extension of the modeling work discussed in previous chapters. In the third chapter, I present the results of a numerical study of surface-wave based tunnel detection methods. The results of this analysis show that these methods are capable of detecting a void buried within one wavelength of the surface, with size potentially much less than one wavelength. In addition, seismic surface- wave based detection methods are effective in media with moderate heterogeneity (epsilon < 5 %), and in fact, this heterogeneity may serve to increase the resolution of these methods. In the fourth chapter, I discuss the results of a field study of tunnel detection methods at a site within the Black Diamond Mines Regional Preserve, near Antioch California. I use a com- bination of surface wave backscattering, 1D surface wave attenuation, and 2D attenuation tomography to locate and determine the condition of two tunnels at this site. These results compliment the numerical study in chapter 3 and highlight their usefulness for detecting tunnels at other sites.

Geochemical Analysis of Parasequences within the Productive Middle Member of the Eagle Ford Formation at Lozier Canyon near Del Rio, Texas

NASA Astrophysics Data System (ADS)

Shane, Timothy E.

The middle member of the Eagle Ford formation is a heterogeneous, carbonate-shale unit that is a focus of unconventional oil and gas exploration in southern Texas. Exploration results have been mixed because of the apparent heterogeneity of the member. In this study, the extent of heterogeneities in the Eagle Ford on the "bedding-scale" were examined by evaluating changes in organic and inorganic geochemistry. Samples were collected vertically in outcrop covering four non-consecutive parasequences. These samples were analyzed using a Rock Eval 6 Analyzer(TM) to determine source rock generative potential and a Niton(TM) XRF to evaluate inorganic geochemistry to identify changes in paleoredox conditions, paleoproductivity, and clastic influx. From pyrolysis data, it is determined that Parasequence 1 potentially displays an increase in source rock potential, Parasequence 2 potentially displays a constant source rock potential, and Parasequences 3 and 4 potentially display overall decreases in source rock potential during deposition. From the inferred paleoredox conditions, paleoproductivity, and clastic influx, it is determined that Parasequence 1 experienced a potential increase in oxygen abundance, Parasequence 2 experienced a potential decrease in oxygen abundance, and Parasequences 3 and 4 potentially experienced increases in oxygen abundance during deposition. It is concluded that geochemical heterogeneities do exist on a bedding scale within the parasequences of the middle member of the Eagle Ford. Additional comprehensive sampling and analysis is recommended in the future in order to tie these data to subsurface data for economic application.

Dry season limnological conditions and basin geology exhibit complex relationships with δ13C and δ15N of carbon sources in four Neotropical floodplains.

PubMed

Zaia Alves, Gustavo H; Hoeinghaus, David J; Manetta, Gislaine I; Benedito, Evanilde

2017-01-01

Studies in freshwater ecosystems are seeking to improve understanding of carbon flow in food webs and stable isotopes have been influential in this work. However, variation in isotopic values of basal production sources could either be an asset or a hindrance depending on study objectives. We assessed the potential for basin geology and local limnological conditions to predict stable carbon and nitrogen isotope values of six carbon sources at multiple locations in four Neotropical floodplain ecosystems (Paraná, Pantanal, Araguaia, and Amazon). Limnological conditions exhibited greater variation within than among systems. δ15N differed among basins for most carbon sources, but δ13C did not (though high within-basin variability for periphyton, phytoplankton and particulate organic carbon was observed). Although δ13C and δ15N values exhibited significant correlations with some limnological factors within and among basins, those relationships differed among carbon sources. Regression trees for both carbon and nitrogen isotopes for all sources depicted complex and in some cases nested relationships, and only very limited similarity was observed among trees for different carbon sources. Although limnological conditions predicted variation in isotope values of carbon sources, we suggest the resulting models were too complex to enable mathematical corrections of source isotope values among sites based on these parameters. The importance of local conditions in determining variation in source isotope values suggest that isotopes may be useful for examining habitat use, dispersal and patch dynamics within heterogeneous floodplain ecosystems, but spatial variability in isotope values needs to be explicitly considered when testing ecosystem models of carbon flow in these systems.

Dry season limnological conditions and basin geology exhibit complex relationships with δ13C and δ15N of carbon sources in four Neotropical floodplains

PubMed Central

Hoeinghaus, David J.; Manetta, Gislaine I.; Benedito, Evanilde

2017-01-01

Studies in freshwater ecosystems are seeking to improve understanding of carbon flow in food webs and stable isotopes have been influential in this work. However, variation in isotopic values of basal production sources could either be an asset or a hindrance depending on study objectives. We assessed the potential for basin geology and local limnological conditions to predict stable carbon and nitrogen isotope values of six carbon sources at multiple locations in four Neotropical floodplain ecosystems (Paraná, Pantanal, Araguaia, and Amazon). Limnological conditions exhibited greater variation within than among systems. δ15N differed among basins for most carbon sources, but δ13C did not (though high within-basin variability for periphyton, phytoplankton and particulate organic carbon was observed). Although δ13C and δ15N values exhibited significant correlations with some limnological factors within and among basins, those relationships differed among carbon sources. Regression trees for both carbon and nitrogen isotopes for all sources depicted complex and in some cases nested relationships, and only very limited similarity was observed among trees for different carbon sources. Although limnological conditions predicted variation in isotope values of carbon sources, we suggest the resulting models were too complex to enable mathematical corrections of source isotope values among sites based on these parameters. The importance of local conditions in determining variation in source isotope values suggest that isotopes may be useful for examining habitat use, dispersal and patch dynamics within heterogeneous floodplain ecosystems, but spatial variability in isotope values needs to be explicitly considered when testing ecosystem models of carbon flow in these systems. PMID:28358822

ALFA: The new ALICE-FAIR software framework

NASA Astrophysics Data System (ADS)

Al-Turany, M.; Buncic, P.; Hristov, P.; Kollegger, T.; Kouzinopoulos, C.; Lebedev, A.; Lindenstruth, V.; Manafov, A.; Richter, M.; Rybalchenko, A.; Vande Vyvre, P.; Winckler, N.

2015-12-01

The commonalities between the ALICE and FAIR experiments and their computing requirements led to the development of large parts of a common software framework in an experiment independent way. The FairRoot project has already shown the feasibility of such an approach for the FAIR experiments and extending it beyond FAIR to experiments at other facilities[1, 2]. The ALFA framework is a joint development between ALICE Online- Offline (O2) and FairRoot teams. ALFA is designed as a flexible, elastic system, which balances reliability and ease of development with performance using multi-processing and multithreading. A message- based approach has been adopted; such an approach will support the use of the software on different hardware platforms, including heterogeneous systems. Each process in ALFA assumes limited communication and reliance on other processes. Such a design will add horizontal scaling (multiple processes) to vertical scaling provided by multiple threads to meet computing and throughput demands. ALFA does not dictate any application protocols. Potentially, any content-based processor or any source can change the application protocol. The framework supports different serialization standards for data exchange between different hardware and software languages.

Multiple Reaction Equilibria--With Pencil and Paper: A Class Problem on Coal Methanation.

ERIC Educational Resources Information Center

Helfferich, Friedrich G.

1989-01-01

Points out a different and much simpler approach for the study of equilibria of multiple and heterogeneous chemical reactions. A simulation on coal methanation is used to teach the technique. An example and the methodology used are provided. (MVL)

Origin of Multiple Peaks in the Potentiodynamic Oxidation of CO Adlayers on Pt and Ru-Modified Pt Electrodes

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

Wang, Hongsen; Abruña, Héctor D.

2015-05-21

The study of the electrooxidation mechanism of COad on Pt based catalysts is very important for designing more effective CO-tolerant electrocatalysts for fuel cells. We have studied the origin of multiple peaks in the cyclic voltammograms of CO stripping from polycrystalline Pt and Ru modified polycrystalline Pt (Pt/Ru) surfaces in both acidic and alkaline media by differential electrochemical mass spectrometry (DEMS), DFT calculations, and kinetic Monte Carlo (KMC) simulations. A new COad electrooxidation kinetic model on heterogeneous Pt and Pt/Ru catalysts is proposed to account for the multiple peaks experimentally observed. In this model, OH species prefer to adsorb atmore » low-coordination sites or Ru sites and, thus, suppress CO repopulation from high-coordination sites onto these sites. Therefore, COad oxidation occurs on different facets or regions, leading to multiplicity of CO stripping peaks. This work provides a new insight into the CO electrooxidation mechanism and kinetics on heterogeneous catalysts.« less

Integration of heterogeneous features for remote sensing scene classification

NASA Astrophysics Data System (ADS)

Wang, Xin; Xiong, Xingnan; Ning, Chen; Shi, Aiye; Lv, Guofang

2018-01-01

Scene classification is one of the most important issues in remote sensing (RS) image processing. We find that features from different channels (shape, spectral, texture, etc.), levels (low-level and middle-level), or perspectives (local and global) could provide various properties for RS images, and then propose a heterogeneous feature framework to extract and integrate heterogeneous features with different types for RS scene classification. The proposed method is composed of three modules (1) heterogeneous features extraction, where three heterogeneous feature types, called DS-SURF-LLC, mean-Std-LLC, and MS-CLBP, are calculated, (2) heterogeneous features fusion, where the multiple kernel learning (MKL) is utilized to integrate the heterogeneous features, and (3) an MKL support vector machine classifier for RS scene classification. The proposed method is extensively evaluated on three challenging benchmark datasets (a 6-class dataset, a 12-class dataset, and a 21-class dataset), and the experimental results show that the proposed method leads to good classification performance. It produces good informative features to describe the RS image scenes. Moreover, the integration of heterogeneous features outperforms some state-of-the-art features on RS scene classification tasks.

Spatial variation in anthropogenic mortality induces a source-sink system in a hunted mesopredator.

PubMed

Minnie, Liaan; Zalewski, Andrzej; Zalewska, Hanna; Kerley, Graham I H

2018-04-01

Lethal carnivore management is a prevailing strategy to reduce livestock predation. Intensity of lethal management varies according to land-use, where carnivores are more intensively hunted on farms relative to reserves. Variations in hunting intensity may result in the formation of a source-sink system where carnivores disperse from high-density to low-density areas. Few studies quantify dispersal between supposed sources and sinks-a fundamental requirement for source-sink systems. We used the black-backed jackal (Canis mesomelas) as a model to determine if heterogeneous anthropogenic mortality induces a source-sink system. We analysed 12 microsatellite loci from 554 individuals from lightly hunted and previously unhunted reserves, as well as heavily hunted livestock- and game farms. Bayesian genotype assignment showed that jackal populations displayed a hierarchical population structure. We identified two genetically distinct populations at the regional level and nine distinct subpopulations at the local level, with each cluster corresponding to distinct land-use types separated by various dispersal barriers. Migration, estimated using Bayesian multilocus genotyping, between reserves and farms was asymmetric and heterogeneous anthropogenic mortality induced source-sink dynamics via compensatory immigration. Additionally some heavily hunted populations also acted as source populations, exporting individuals to other heavily hunted populations. This indicates that heterogeneous anthropogenic mortality results in the formation of a complex series of interconnected sources and sinks. Thus, lethal management of mesopredators may not be an effective long-term strategy in reducing livestock predation, as dispersal and, more importantly, compensatory immigration may continue to affect population reduction efforts as long as dispersal from other areas persists.

Ambiguity in measuring matrix diffusion with single-well injection/recovery tracer tests

USGS Publications Warehouse

Lessoff, S.C.; Konikow, Leonard F.

1997-01-01

Single-well injection/recovery tracer tests are considered for use in characterizing and quantifying matrix diffusion in dual-porosity aquifers. Numerical modeling indicates that neither regional drift in homogeneous aquifers, nor heterogeneity in aquifers having no regional drift, nor hydrodynamic dispersion significantly affects these tests. However, when drift is coupled simultaneously with heterogeneity, they can have significant confounding effects on tracer return. This synergistic effect of drift and heterogeneity may help explain irreversible flow and inconsistent results sometimes encountered in previous single-well injection/recovery tracer tests. Numerical results indicate that in a hypothetical single-well injection/recovery tracer test designed to demonstrate and measure dual-porosity characteristics in a fractured dolomite, the simultaneous effects of drift and heterogeneity sometimes yields responses similar to those anticipated in a homogeneous dual-porosity formation. In these cases, tracer recovery could provide a false indication of the occurrence of matrix diffusion. Shortening the shut-in period between injection and recovery periods may make the test less sensitive to drift. Using multiple tracers having different diffusion characteristics, multiple tests having different pumping schedules, and testing the formation at more than one location would decrease the ambiguity in the interpretation of test data.

Hot spots and hot moments in riparian zones: potential for improved water quality management

USDA-ARS?s Scientific Manuscript database

Despite considerable heterogeneity over space and time, biogeochemical and hydrological processes in riparian zones regulate contaminant movement to receiving waters and often mitigate the impact of upland sources of contaminants on water quality. Recently, these heterogeneous processes have been co...

Heterogeneous Teams of Autonomous Vehicles: Advanced Sensing & Control

DTIC Science & Technology

2009-03-01

Final Technical 3. DATES COVERED (From To) 7/1/05-12/31708 4. TITLE AND SUBTITLE Heterogeneous Teams of Autonomous Vehicles Advanced Sensing...assimilating data from underwater and surface autonomous vehicles in addition to the usual sources of Eulerian and Lagrangian systems into a small scale

The Phillips pluton, Maine, USA: evidence of heterogeneous crustal sources and implications for granite ascent and emplacement mechanisms in convergent orogens

NASA Astrophysics Data System (ADS)

Pressley, Rachel A.; Brown, Michael

1999-03-01

The Phillips pluton (age of 403.8±1.3 Ma) was assembled at a crustal level below the contemporary brittle-plastic transition during regional dextral-reverse transpressive deformation. The pluton is composed dominantly of medium- to coarse-grained leucogranite sensu lato (s.l.), but within its bounds includes decametric massive outcrop of fine- to medium-grained granodiorite (s.l.). In places, the leucogranite contains centimetric enclaves apparently of the granodiorite. Granodiorite is host to more biotite than muscovite, and more calcic, oscillatory-zoned plagioclase, compared to the leucogranite. Pegmatitic granite and composite pegmatite-aplite occur as metric sheets within the pluton and as larger bodies outside the pluton to the SW. Magmatic fabrics, defined by biotite schlieren, occur locally in the leucogranite; the attitude of these fabrics and layering within the leucogranite are concordant with the NE-striking, steeply-dipping country rock foliation. K 2O contents, Rb/Sr ratios, Rb, Sr and Ba covariations, and chondrite-normalized rare earth element (REE) patterns of leucogranite are consistent with high-to-moderate a(H 2O) muscovite dehydration equilibrium eutectic melting of a predominantly pelite source similar to metasedimentary rocks of the surrounding central Maine belt (CMB). The REE patterns and Rb/Sr ratios of granodiorite also suggest derivation from a metasedimentary source, but more likely by moderate-to-low a(H 2O) (muscovite-) biotite dehydration equilibrium eutectic to non-eutectic (minimum) melting of a protolith dominated by greywacke in which garnet and plagioclase were residual phases. Both granite (s.l.) types have heterogeneous initial Nd isotope compositions. Samples of granodiorite define a range in ɛNd (404 Ma) of -1.8 to +0.1 (±0.3 2 σ uncertainty), and samples of leucogranite define a range in ɛNd (404 Ma) of -8.0 to -5.3 (±0.3 2 σ uncertainty). This bimodal distribution suggests that melts were derived from a minimum of two sources. The data are consistent with these sources being CMB metasedimentary rocks ( ɛNd (404 Ma)<-4) for the leucogranite, and Avalon-like (peri-Gondwanan) metasedimentary crust ( ɛNd (404 Ma)>-4) for the granodiorite. The range of Nd isotope compositions within each granite type most likely reflects isotopic heterogeneity inherited from the source. These data imply that the integrity of individual melt batches was maintained during ascent, and that extensive mixing of melt batches during emplacement at this level in the pluton did not occur, although centimetric enclaves have intermediate Nd isotope compositions consistent with small-scale interactions between magmas. We infer that the Phillips pluton represents the root of a larger pluton, and that what remains of this larger pluton is the feeder constructed from multiple melt batches arrested during waning flow of granite magma through a crustal-scale shear zone system.

Data integration of structured and unstructured sources for assigning clinical codes to patient stays

PubMed Central

Luyckx, Kim; Luyten, Léon; Daelemans, Walter; Van den Bulcke, Tim

2016-01-01

Objective Enormous amounts of healthcare data are becoming increasingly accessible through the large-scale adoption of electronic health records. In this work, structured and unstructured (textual) data are combined to assign clinical diagnostic and procedural codes (specifically ICD-9-CM) to patient stays. We investigate whether integrating these heterogeneous data types improves prediction strength compared to using the data types in isolation. Methods Two separate data integration approaches were evaluated. Early data integration combines features of several sources within a single model, and late data integration learns a separate model per data source and combines these predictions with a meta-learner. This is evaluated on data sources and clinical codes from a broad set of medical specialties. Results When compared with the best individual prediction source, late data integration leads to improvements in predictive power (eg, overall F-measure increased from 30.6% to 38.3% for International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) diagnostic codes), while early data integration is less consistent. The predictive strength strongly differs between medical specialties, both for ICD-9-CM diagnostic and procedural codes. Discussion Structured data provides complementary information to unstructured data (and vice versa) for predicting ICD-9-CM codes. This can be captured most effectively by the proposed late data integration approach. Conclusions We demonstrated that models using multiple electronic health record data sources systematically outperform models using data sources in isolation in the task of predicting ICD-9-CM codes over a broad range of medical specialties. PMID:26316458

Mean Comparison: Manifest Variable versus Latent Variable

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Bentler, Peter M.

2006-01-01

An extension of multiple correspondence analysis is proposed that takes into account cluster-level heterogeneity in respondents' preferences/choices. The method involves combining multiple correspondence analysis and k-means in a unified framework. The former is used for uncovering a low-dimensional space of multivariate categorical variables…

Formation of Moon-Type Rocks by Multiple Impacts with Porous, Crystals and Glassy Soils

NASA Astrophysics Data System (ADS)

Miura, Yas.

2012-03-01

Lunar rocks are checked by two data of (a) density, porosity, and age; and (b) FeO, Ni, Co, and C contents and age. The results indicate that primordial FAN anorthosites are relatively brecciated on heterogeneous surface with multiple impact process.

The lunar crust - A product of heterogeneous accretion or differentiation of a homogeneous moon

NASA Technical Reports Server (NTRS)

Brett, R.

1973-01-01

The outer portion of the moon (including the aluminum-rich crust and the source regions of mare basalts) was either accreted heterogeneously or was the product of widespread differentiation of an originally homogeneous source. Existing evidence for and against each of these two models is reviewed. It is concluded that the accretionary model presents more problems than it solves, and the model involving differentiation of an originally homogeneous moon is considered to be more plausible. A hypothesis for the formation of mare basalts is advanced.

Genome-wide detection of intervals of genetic heterogeneity associated with complex traits

PubMed Central

Llinares-López, Felipe; Grimm, Dominik G.; Bodenham, Dean A.; Gieraths, Udo; Sugiyama, Mahito; Rowan, Beth; Borgwardt, Karsten

2015-01-01

Motivation: Genetic heterogeneity, the fact that several sequence variants give rise to the same phenotype, is a phenomenon that is of the utmost interest in the analysis of complex phenotypes. Current approaches for finding regions in the genome that exhibit genetic heterogeneity suffer from at least one of two shortcomings: (i) they require the definition of an exact interval in the genome that is to be tested for genetic heterogeneity, potentially missing intervals of high relevance, or (ii) they suffer from an enormous multiple hypothesis testing problem due to the large number of potential candidate intervals being tested, which results in either many false positives or a lack of power to detect true intervals. Results: Here, we present an approach that overcomes both problems: it allows one to automatically find all contiguous sequences of single nucleotide polymorphisms in the genome that are jointly associated with the phenotype. It also solves both the inherent computational efficiency problem and the statistical problem of multiple hypothesis testing, which are both caused by the huge number of candidate intervals. We demonstrate on Arabidopsis thaliana genome-wide association study data that our approach can discover regions that exhibit genetic heterogeneity and would be missed by single-locus mapping. Conclusions: Our novel approach can contribute to the genome-wide discovery of intervals that are involved in the genetic heterogeneity underlying complex phenotypes. Availability and implementation: The code can be obtained at: http://www.bsse.ethz.ch/mlcb/research/bioinformatics-and-computational-biology/sis.html. Contact: felipe.llinares@bsse.ethz.ch Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26072488

A model for cancer tissue heterogeneity.

PubMed

Mohanty, Anwoy Kumar; Datta, Aniruddha; Venkatraj, Vijayanagaram

2014-03-01

An important problem in the study of cancer is the understanding of the heterogeneous nature of the cell population. The clonal evolution of the tumor cells results in the tumors being composed of multiple subpopulations. Each subpopulation reacts differently to any given therapy. This calls for the development of novel (regulatory network) models, which can accommodate heterogeneity in cancerous tissues. In this paper, we present a new approach to model heterogeneity in cancer. We model heterogeneity as an ensemble of deterministic Boolean networks based on prior pathway knowledge. We develop the model considering the use of qPCR data. By observing gene expressions when the tissue is subjected to various stimuli, the compositional breakup of the tissue under study can be determined. We demonstrate the viability of this approach by using our model on synthetic data, and real-world data collected from fibroblasts.

[Application of Stata software to test heterogeneity in meta-analysis method].

PubMed

Wang, Dan; Mou, Zhen-yun; Zhai, Jun-xia; Zong, Hong-xia; Zhao, Xiao-dong

2008-07-01

To introduce the application of Stata software to heterogeneity test in meta-analysis. A data set was set up according to the example in the study, and the corresponding commands of the methods in Stata 9 software were applied to test the example. The methods used were Q-test and I2 statistic attached to the fixed effect model forest plot, H statistic and Galbraith plot. The existence of the heterogeneity among studies could be detected by Q-test and H statistic and the degree of the heterogeneity could be detected by I2 statistic. The outliers which were the sources of the heterogeneity could be spotted from the Galbraith plot. Heterogeneity test in meta-analysis can be completed by the four methods in Stata software simply and quickly. H and I2 statistics are more robust, and the outliers of the heterogeneity can be clearly seen in the Galbraith plot among the four methods.

Ecosystem services capacity across heterogeneous forest types: understanding the interactions and suggesting pathways for sustaining multiple ecosystem services.

PubMed

Alamgir, Mohammed; Turton, Stephen M; Macgregor, Colin J; Pert, Petina L

2016-10-01

As ecosystem services supply from tropical forests is declining due to deforestation and forest degradation, much effort is essential to sustain ecosystem services supply from tropical forested landscapes, because tropical forests provide the largest flow of multiple ecosystem services among the terrestrial ecosystems. In order to sustain multiple ecosystem services, understanding ecosystem services capacity across heterogeneous forest types and identifying certain ecosystem services that could be managed to leverage positive effects across the wider bundle of ecosystem services are required. We sampled three forest types, tropical rainforests, sclerophyll forests, and rehabilitated plantation forests, over an area of 32,000m(2) from Wet Tropics bioregion, Australia, aiming to compare supply and evaluate interactions and patterns of eight ecosystem services (global climate regulation, air quality regulation, erosion regulation, nutrient regulation, cyclone protection, habitat provision, energy provision, and timber provision). On average, multiple ecosystem services were highest in the rainforests, lowest in sclerophyll forests, and intermediate in rehabilitated plantation forests. However, a wide variation was apparent among the plots across the three forest types. Global climate regulation service had a synergistic impact on the supply of multiple ecosystem services, while nutrient regulation service was found to have a trade-off impact. Considering multiple ecosystem services, most of the rehabilitated plantation forest plots shared the same ordination space with rainforest plots in the ordination analysis, indicating that rehabilitated plantation forests may supply certain ecosystem services nearly equivalent to rainforests. Two synergy groups and one trade-off group were identified. Apart from conserving rainforests and sclerophyll forests, our findings suggest two additional integrated pathways to sustain the supply of multiple ecosystem services from a heterogeneous tropical forest landscape: (i) rehabilitation of degraded forests aiming to provide global climate regulation and habitat provision ecosystem services and (ii) management intervention to sustain global climate regulation and habitat provision ecosystem services. Copyright © 2016 Elsevier B.V. All rights reserved.

On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance-weighted principal component analysis.

PubMed

Martinez-Murcia, Francisco Jesús; Lai, Meng-Chuan; Górriz, Juan Manuel; Ramírez, Javier; Young, Adam M H; Deoni, Sean C L; Ecker, Christine; Lombardo, Michael V; Baron-Cohen, Simon; Murphy, Declan G M; Bullmore, Edward T; Suckling, John

2017-03-01

Neuroimaging studies have reported structural and physiological differences that could help understand the causes and development of Autism Spectrum Disorder (ASD). Many of them rely on multisite designs, with the recruitment of larger samples increasing statistical power. However, recent large-scale studies have put some findings into question, considering the results to be strongly dependent on the database used, and demonstrating the substantial heterogeneity within this clinically defined category. One major source of variance may be the acquisition of the data in multiple centres. In this work we analysed the differences found in the multisite, multi-modal neuroimaging database from the UK Medical Research Council Autism Imaging Multicentre Study (MRC AIMS) in terms of both diagnosis and acquisition sites. Since the dissimilarities between sites were higher than between diagnostic groups, we developed a technique called Significance Weighted Principal Component Analysis (SWPCA) to reduce the undesired intensity variance due to acquisition site and to increase the statistical power in detecting group differences. After eliminating site-related variance, statistically significant group differences were found, including Broca's area and the temporo-parietal junction. However, discriminative power was not sufficient to classify diagnostic groups, yielding accuracies results close to random. Our work supports recent claims that ASD is a highly heterogeneous condition that is difficult to globally characterize by neuroimaging, and therefore different (and more homogenous) subgroups should be defined to obtain a deeper understanding of ASD. Hum Brain Mapp 38:1208-1223, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Patient-specific Monte Carlo-based dose-kernel approach for inverse planning in afterloading brachytherapy.

PubMed

D'Amours, Michel; Pouliot, Jean; Dagnault, Anne; Verhaegen, Frank; Beaulieu, Luc

2011-12-01

Brachytherapy planning software relies on the Task Group report 43 dosimetry formalism. This formalism, based on a water approximation, neglects various heterogeneous materials present during treatment. Various studies have suggested that these heterogeneities should be taken into account to improve the treatment quality. The present study sought to demonstrate the feasibility of incorporating Monte Carlo (MC) dosimetry within an inverse planning algorithm to improve the dose conformity and increase the treatment quality. The method was based on precalculated dose kernels in full patient geometries, representing the dose distribution of a brachytherapy source at a single dwell position using MC simulations and the Geant4 toolkit. These dose kernels are used by the inverse planning by simulated annealing tool to produce a fast MC-based plan. A test was performed for an interstitial brachytherapy breast treatment using two different high-dose-rate brachytherapy sources: the microSelectron iridium-192 source and the electronic brachytherapy source Axxent operating at 50 kVp. A research version of the inverse planning by simulated annealing algorithm was combined with MC to provide a method to fully account for the heterogeneities in dose optimization, using the MC method. The effect of the water approximation was found to depend on photon energy, with greater dose attenuation for the lower energies of the Axxent source compared with iridium-192. For the latter, an underdosage of 5.1% for the dose received by 90% of the clinical target volume was found. A new method to optimize afterloading brachytherapy plans that uses MC dosimetric information was developed. Including computed tomography-based information in MC dosimetry in the inverse planning process was shown to take into account the full range of scatter and heterogeneity conditions. This led to significant dose differences compared with the Task Group report 43 approach for the Axxent source. Copyright © 2011 Elsevier Inc. All rights reserved.

Surface induced molecular dynamics of thin lipid films confined to submicron cavities: A 1H multiple-quantum NMR study

NASA Astrophysics Data System (ADS)

Jagadeesh, B.; Prabhakar, A.; Demco, D. E.; Buda, A.; Blümich, B.

2005-03-01

The dynamics and molecular order of thin lipid (lecithin) films confined to 200, 100 and 20 nm cylindrical pores with varying surface coverage, were investigated by 1H multiple-quantum NMR. The results show that the molecular dynamics in the surface controlled layers are less hindered compared to those in the bulk. Dynamic heterogeneity among terminal CH 3 groups is evident. Enhanced dynamic freedom is observed for films with area per molecule, ˜ 128 Å 2. The results are discussed in terms of changes in the lipid molecular organization with respect to surface concentration, its plausible motional modes and dynamic heterogeneity.

Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

PubMed

Yuan, Chengzhi; Licht, Stephen; He, Haibo

2017-09-26

In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

Bioanalysis of antibody-drug conjugates: American Association of Pharmaceutical Scientists Antibody-Drug Conjugate Working Group position paper.

PubMed

Gorovits, Boris; Alley, Stephen C; Bilic, Sanela; Booth, Brian; Kaur, Surinder; Oldfield, Phillip; Purushothama, Shobha; Rao, Chetana; Shord, Stacy; Siguenza, Patricia

2013-05-01

Antibody-drug conjugates (ADCs) typically consist of a cytotoxic drug covalently bound to an antibody by a linker. These conjugates have the potential to substantially improve efficacy and reduce toxicity compared with cytotoxic small-molecule drugs. Since ADCs are generally complex heterogeneous mixtures of multiple species, these novel therapeutic products present unique bioanalytical challenges. The growing number of ADCs being developed across the industry suggests the need for alignment of the bioanalytical methods or approaches used to assess the multiple species and facilitate consistent interpretation of the bioanalytical data. With limited clinical data, the current strategies that can be used to provide insight into the relationship between the multiple species and the observed clinical safety and efficacy are still evolving. Considerations of the bioanalytical strategies for ADCs based on the current industry practices that take into account the complexity and heterogeneity of ADCs are discussed.

Shifts in controls on the temporal coherence of throughfall chemical flux in Acadia National Park, Maine, USA

USGS Publications Warehouse

Nelson, Sarah J.; Webster, Katherine E.; Loftin, Cynthia S.; Weathers, Kathleen C.

2013-01-01

Major ion and mercury (Hg) inputs to terrestrial ecosystems include both wet and dry deposition (total deposition). Estimating total deposition to sensitive receptor sites is hampered by limited information regarding its spatial heterogeneity and seasonality. We used measurements of throughfall flux, which includes atmospheric inputs to forests and the net effects of canopy leaching or uptake, for ten major ions and Hg collected during 35 time periods in 1999–2005 at over 70 sites within Acadia National Park, Maine to (1) quantify coherence in temporal dynamics of seasonal throughfall deposition and (2) examine controls on these patterns at multiple scales. We quantified temporal coherence as the correlation between all possible site pairs for each solute on a seasonal basis. In the summer growing season and autumn, coherence among pairs of sites with similar vegetation was stronger than for site-pairs that differed in vegetation suggesting that interaction with the canopy and leaching of solutes differed in coniferous, deciduous, mixed, and shrub or open canopy sites. The spatial pattern in throughfall hydrologic inputs across Acadia National Park was more variable during the winter snow season, suggesting that snow re-distribution affects net hydrologic input, which consequently affects chemical flux. Sea-salt corrected calcium concentrations identified a shift in air mass sources from maritime in winter to the continental industrial corridor in summer. Our results suggest that the spatial pattern of throughfall hydrologic flux, dominant seasonal air mass source, and relationship with vegetation in winter differ from the spatial pattern of throughfall flux in these solutes in summer and autumn. The coherence approach applied here made clear the strong influence of spatial heterogeneity in throughfall hydrologic inputs and a maritime air mass source on winter patterns of throughfall flux. By contrast, vegetation type was the most important influence on throughfall chemical flux in summer and autumn.

A semantic problem solving environment for integrative parasite research: identification of intervention targets for Trypanosoma cruzi.

PubMed

Parikh, Priti P; Minning, Todd A; Nguyen, Vinh; Lalithsena, Sarasi; Asiaee, Amir H; Sahoo, Satya S; Doshi, Prashant; Tarleton, Rick; Sheth, Amit P

2012-01-01

Research on the biology of parasites requires a sophisticated and integrated computational platform to query and analyze large volumes of data, representing both unpublished (internal) and public (external) data sources. Effective analysis of an integrated data resource using knowledge discovery tools would significantly aid biologists in conducting their research, for example, through identifying various intervention targets in parasites and in deciding the future direction of ongoing as well as planned projects. A key challenge in achieving this objective is the heterogeneity between the internal lab data, usually stored as flat files, Excel spreadsheets or custom-built databases, and the external databases. Reconciling the different forms of heterogeneity and effectively integrating data from disparate sources is a nontrivial task for biologists and requires a dedicated informatics infrastructure. Thus, we developed an integrated environment using Semantic Web technologies that may provide biologists the tools for managing and analyzing their data, without the need for acquiring in-depth computer science knowledge. We developed a semantic problem-solving environment (SPSE) that uses ontologies to integrate internal lab data with external resources in a Parasite Knowledge Base (PKB), which has the ability to query across these resources in a unified manner. The SPSE includes Web Ontology Language (OWL)-based ontologies, experimental data with its provenance information represented using the Resource Description Format (RDF), and a visual querying tool, Cuebee, that features integrated use of Web services. We demonstrate the use and benefit of SPSE using example queries for identifying gene knockout targets of Trypanosoma cruzi for vaccine development. Answers to these queries involve looking up multiple sources of data, linking them together and presenting the results. The SPSE facilitates parasitologists in leveraging the growing, but disparate, parasite data resources by offering an integrative platform that utilizes Semantic Web techniques, while keeping their workload increase minimal.

Gifts of the Spirit: Multiple Intelligences in Religious Education.

ERIC Educational Resources Information Center

Nuzzi, Ronald

This book provides practical direction for religious educators in teaching heterogeneous groups of learners by employing a broad range of teaching and learning approaches. The booklet explains the attributes of multiple intelligence theory, including the seven types of intelligence, and provides suggestions for engaging students in each…

Different initiatives across Europe to enhance losartan utilization post generics: impact and implications.

PubMed

Moon, James C; Godman, Brian; Petzold, Max; Alvarez-Madrazo, Samantha; Bennett, Kathleen; Bishop, Iain; Bucsics, Anna; Hesse, Ulrik; Martin, Andrew; Simoens, Steven; Zara, Corinne; Malmström, Rickard E

2014-01-01

There is an urgent need for health authorities across Europe to fully realize potential savings from increased use of generics to sustain their healthcare systems. A variety of strategies were used across Europe following the availability of generic losartan, the first angiotensin receptor blocker (ARB) to be approved and marketed, to enhance its prescribing vs. single-sourced drugs in the class. Demand-side strategies ranged from 100% co-payment for single-sourced ARBs in Denmark to no specific measures. We hypothesized this heterogeneity of approaches would provide opportunities to explore prescribing in a class following patent expiry. Contrast the impact of the different approaches among European countries and regions to the availability of generic losartan to provide future guidance. Retrospective segmented regression analyses applying linear random coefficient models with country specific intercepts and slopes were used to assess the impact of the various initiatives across Europe following the availability of generic losartan. Utilization measured in defined daily doses (DDDs). Price reductions for generic losartan were also measured. Utilization of losartan was over 90% of all ARBs in Denmark by the study end. Multiple measures in Sweden and one English primary care group also appreciably enhanced losartan utilization. Losartan utilization actually fell in some countries with no specific demand-side measures. Considerable differences were seen in the prices of generic losartan. Delisting single-sourced ARBs produced the greatest increase in losartan utilization. Overall, multiple demand-side measures are needed to change physician prescribing habits to fully realize savings from generics. There is no apparent "spill over" effect from one class to another to influence future prescribing patterns even if these are closely related.

Different initiatives across Europe to enhance losartan utilization post generics: impact and implications

PubMed Central

Moon, James C.; Godman, Brian; Petzold, Max; Alvarez-Madrazo, Samantha; Bennett, Kathleen; Bishop, Iain; Bucsics, Anna; Hesse, Ulrik; Martin, Andrew; Simoens, Steven; Zara, Corinne; Malmström, Rickard E.

2014-01-01

Introduction: There is an urgent need for health authorities across Europe to fully realize potential savings from increased use of generics to sustain their healthcare systems. A variety of strategies were used across Europe following the availability of generic losartan, the first angiotensin receptor blocker (ARB) to be approved and marketed, to enhance its prescribing vs. single-sourced drugs in the class. Demand-side strategies ranged from 100% co-payment for single-sourced ARBs in Denmark to no specific measures. We hypothesized this heterogeneity of approaches would provide opportunities to explore prescribing in a class following patent expiry. Objective: Contrast the impact of the different approaches among European countries and regions to the availability of generic losartan to provide future guidance. Methodology: Retrospective segmented regression analyses applying linear random coefficient models with country specific intercepts and slopes were used to assess the impact of the various initiatives across Europe following the availability of generic losartan. Utilization measured in defined daily doses (DDDs). Price reductions for generic losartan were also measured. Results: Utilization of losartan was over 90% of all ARBs in Denmark by the study end. Multiple measures in Sweden and one English primary care group also appreciably enhanced losartan utilization. Losartan utilization actually fell in some countries with no specific demand-side measures. Considerable differences were seen in the prices of generic losartan. Conclusion: Delisting single-sourced ARBs produced the greatest increase in losartan utilization. Overall, multiple demand-side measures are needed to change physician prescribing habits to fully realize savings from generics. There is no apparent “spill over” effect from one class to another to influence future prescribing patterns even if these are closely related. PMID:25339902

PropBase Query Layer: a single portal to UK subsurface physical property databases

NASA Astrophysics Data System (ADS)

Kingdon, Andrew; Nayembil, Martin L.; Richardson, Anne E.; Smith, A. Graham

2013-04-01

Until recently, the delivery of geological information for industry and public was achieved by geological mapping. Now pervasively available computers mean that 3D geological models can deliver realistic representations of the geometric location of geological units, represented as shells or volumes. The next phase of this process is to populate these with physical properties data that describe subsurface heterogeneity and its associated uncertainty. Achieving this requires capture and serving of physical, hydrological and other property information from diverse sources to populate these models. The British Geological Survey (BGS) holds large volumes of subsurface property data, derived both from their own research data collection and also other, often commercially derived data sources. This can be voxelated to incorporate this data into the models to demonstrate property variation within the subsurface geometry. All property data held by BGS has for many years been stored in relational databases to ensure their long-term continuity. However these have, by necessity, complex structures; each database contains positional reference data and model information, and also metadata such as sample identification information and attributes that define the source and processing. Whilst this is critical to assessing these analyses, it also hugely complicates the understanding of variability of the property under assessment and requires multiple queries to study related datasets making extracting physical properties from these databases difficult. Therefore the PropBase Query Layer has been created to allow simplified aggregation and extraction of all related data and its presentation of complex data in simple, mostly denormalized, tables which combine information from multiple databases into a single system. The structure from each relational database is denormalized in a generalised structure, so that each dataset can be viewed together in a common format using a simple interface. Data are re-engineered to facilitate easy loading. The query layer structure comprises tables, procedures, functions, triggers, views and materialised views. The structure contains a main table PRB_DATA which contains all of the data with the following attribution: • a unique identifier • the data source • the unique identifier from the parent database for traceability • the 3D location • the property type • the property value • the units • necessary qualifiers • precision information and an audit trail Data sources, property type and units are constrained by dictionaries, a key component of the structure which defines what properties and inheritance hierarchies are to be coded and also guides the process as to what and how these are extracted from the structure. Data types served by the Query Layer include site investigation derived geotechnical data, hydrogeology datasets, regional geochemistry, geophysical logs as well as lithological and borehole metadata. The size and complexity of the data sets with multiple parent structures requires a technically robust approach to keep the layer synchronised. This is achieved through Oracle procedures written in PL/SQL containing the logic required to carry out the data manipulation (inserts, updates, deletes) to keep the layer synchronised with the underlying databases either as regular scheduled jobs (weekly, monthly etc) or invoked on demand. The PropBase Query Layer's implementation has enabled rapid data discovery, visualisation and interpretation of geological data with greater ease, simplifying the parametrisation of 3D model volumes and facilitating the study of intra-unit heterogeneity.

An improved recommendation algorithm via weakening indirect linkage effect

NASA Astrophysics Data System (ADS)

Chen, Guang; Qiu, Tian; Shen, Xiao-Quan

2015-07-01

We propose an indirect-link-weakened mass diffusion method (IMD), by considering the indirect linkage and the source object heterogeneity effect in the mass diffusion (MD) recommendation method. Experimental results on the MovieLens, Netflix, and RYM datasets show that, the IMD method greatly improves both the recommendation accuracy and diversity, compared with a heterogeneity-weakened MD method (HMD), which only considers the source object heterogeneity. Moreover, the recommendation accuracy of the cold objects is also better elevated in the IMD than the HMD method. It suggests that eliminating the redundancy induced by the indirect linkages could have a prominent effect on the recommendation efficiency in the MD method. Project supported by the National Natural Science Foundation of China (Grant No. 11175079) and the Young Scientist Training Project of Jiangxi Province, China (Grant No. 20133BCB23017).

Effects of Heterogeneity and Uncertainties in Sources and Initial and Boundary Conditions on Spatiotemporal Variations of Groundwater Levels

NASA Astrophysics Data System (ADS)

Zhang, Y. K.; Liang, X.

2014-12-01

Effects of aquifer heterogeneity and uncertainties in source/sink, and initial and boundary conditions in a groundwater flow model on the spatiotemporal variations of groundwater level, h(x,t), were investigated. Analytical solutions for the variance and covariance of h(x, t) in an unconfined aquifer described by a linearized Boussinesq equation with a white noise source/sink and a random transmissivity field were derived. It was found that in a typical aquifer the error in h(x,t) in early time is mainly caused by the random initial condition and the error reduces as time goes to reach a constant error in later time. The duration during which the effect of the random initial condition is significant may last a few hundred days in most aquifers. The constant error in groundwater in later time is due to the combined effects of the uncertain source/sink and flux boundary: the closer to the flux boundary, the larger the error. The error caused by the uncertain head boundary is limited in a narrow zone near the boundary but it remains more or less constant over time. The effect of the heterogeneity is to increase the variation of groundwater level and the maximum effect occurs close to the constant head boundary because of the linear mean hydraulic gradient. The correlation of groundwater level decreases with temporal interval and spatial distance. In addition, the heterogeneity enhances the correlation of groundwater level, especially at larger time intervals and small spatial distances.

Repeat immigration: A previously unobserved source of heterogeneity?

PubMed

Aradhya, Siddartha; Scott, Kirk; Smith, Christopher D

2017-07-01

Register data allow for nuanced analyses of heterogeneities between sub-groups which are not observable in other data sources. One heterogeneity for which register data is particularly useful is in identifying unique migration histories of immigrant populations, a group of interest across disciplines. Years since migration is a commonly used measure of integration in studies seeking to understand the outcomes of immigrants. This study constructs detailed migration histories to test whether misclassified migrations may mask important heterogeneities. In doing so, we identify a previously understudied group of migrants called repeat immigrants, and show that they differ systematically from permanent immigrants. In addition, we quantify the degree to which migration information is misreported in the registers. The analysis is carried out in two steps. First, we estimate income trajectories for repeat immigrants and permanent immigrants to understand the degree to which they differ. Second, we test data validity by cross-referencing migration information with changes in income to determine whether there are inconsistencies indicating misreporting. From the first part of the analysis, the results indicate that repeat immigrants systematically differ from permanent immigrants in terms of income trajectories. Furthermore, income trajectories differ based on the way in which years since migration is calculated. The second part of the analysis suggests that misreported migration events, while present, are negligible. Repeat immigrants differ in terms of income trajectories, and may differ in terms of other outcomes as well. Furthermore, this study underlines that Swedish registers provide a reliable data source to analyze groups which are unidentifiable in other data sources.

Matching Alternative Addresses: a Semantic Web Approach

NASA Astrophysics Data System (ADS)

Ariannamazi, S.; Karimipour, F.; Hakimpour, F.

2015-12-01

Rapid development of crowd-sourcing or volunteered geographic information (VGI) provides opportunities for authoritatives that deal with geospatial information. Heterogeneity of multiple data sources and inconsistency of data types is a key characteristics of VGI datasets. The expansion of cities resulted in the growing number of POIs in the OpenStreetMap, a well-known VGI source, which causes the datasets to outdate in short periods of time. These changes made to spatial and aspatial attributes of features such as names and addresses might cause confusion or ambiguity in the processes that require feature's literal information like addressing and geocoding. VGI sources neither will conform specific vocabularies nor will remain in a specific schema for a long period of time. As a result, the integration of VGI sources is crucial and inevitable in order to avoid duplication and the waste of resources. Information integration can be used to match features and qualify different annotation alternatives for disambiguation. This study enhances the search capabilities of geospatial tools with applications able to understand user terminology to pursuit an efficient way for finding desired results. Semantic web is a capable tool for developing technologies that deal with lexical and numerical calculations and estimations. There are a vast amount of literal-spatial data representing the capability of linguistic information in knowledge modeling, but these resources need to be harmonized based on Semantic Web standards. The process of making addresses homogenous generates a helpful tool based on spatial data integration and lexical annotation matching and disambiguating.

Conflicting health information: a critical research need.

PubMed

Carpenter, Delesha M; Geryk, Lorie L; Chen, Annie T; Nagler, Rebekah H; Dieckmann, Nathan F; Han, Paul K J

2016-12-01

Conflicting health information is increasing in amount and visibility, as evidenced most recently by the controversy surrounding the risks and benefits of childhood vaccinations. The mechanisms through which conflicting information affects individuals are poorly understood; thus, we are unprepared to help people process conflicting information when making important health decisions. In this viewpoint article, we describe this problem, summarize insights from the existing literature on the prevalence and effects of conflicting health information, and identify important knowledge gaps. We propose a working definition of conflicting health information and describe a conceptual typology to guide future research in this area. The typology classifies conflicting information according to four fundamental dimensions: the substantive issue under conflict, the number of conflicting sources (multiplicity), the degree of evidence heterogeneity and the degree of temporal inconsistency. © 2015 The Authors. Health Expectations Published by John Wiley & Sons Ltd.

Health and work in the family: Evidence from spouses' cancer diagnoses.

PubMed

Jeon, Sung-Hee; Pohl, R Vincent

2017-03-01

Using Canadian administrative data from multiple sources, we provide the first nationally representative estimates for the effect of spouses' cancer diagnoses on individuals' employment and earnings and on family income. Our identification strategy exploits unexpected health shocks and combines matching with individual fixed effects in a generalized difference-in-differences framework to control for observable and unobservable heterogeneity. While the effect of spousal health shocks on labor supply is theoretically ambiguous, we find strong evidence for a decline in employment and earnings of individuals whose spouses are diagnosed with cancer. We interpret this result as individuals reducing their labor supply to provide care to their sick spouses and to enjoy joint leisure. Family income substantially declines after spouses' cancer diagnoses, suggesting that the financial consequences of such health shocks are considerable. Copyright © 2017 Elsevier B.V. All rights reserved.

Reassessing the Link Between Premarital Cohabitation and Marital Instability

PubMed Central

REINHOLD, STEFFEN

2010-01-01

Premarital cohabitation has been found to be positively correlated with the likelihood of marital dissolution in the United States. To reassess this link, I estimate proportional hazard models of marital dissolution for first marriages by using pooled data from the 1988, 1995, and 2002 surveys of the National Survey of Family Growth (NSFG). These results suggest that the positive relationship between premarital cohabitation and marital instability has weakened for more recent birth and marriage cohorts. Using multiple marital outcomes for a person to account for one source of unobserved heterogeneity, panel models suggest that cohabitation is not selective of individuals with higher risk of marital dissolution and may be a stabilizing factor for higher-order marriages. Further research with more recent data is needed to assess whether these results are statistical artifacts caused by data weaknesses in the NSFG. PMID:20879685

Federated ontology-based queries over cancer data

PubMed Central

2012-01-01

Background Personalised medicine provides patients with treatments that are specific to their genetic profiles. It requires efficient data sharing of disparate data types across a variety of scientific disciplines, such as molecular biology, pathology, radiology and clinical practice. Personalised medicine aims to offer the safest and most effective therapeutic strategy based on the gene variations of each subject. In particular, this is valid in oncology, where knowledge about genetic mutations has already led to new therapies. Current molecular biology techniques (microarrays, proteomics, epigenetic technology and improved DNA sequencing technology) enable better characterisation of cancer tumours. The vast amounts of data, however, coupled with the use of different terms - or semantic heterogeneity - in each discipline makes the retrieval and integration of information difficult. Results Existing software infrastructures for data-sharing in the cancer domain, such as caGrid, support access to distributed information. caGrid follows a service-oriented model-driven architecture. Each data source in caGrid is associated with metadata at increasing levels of abstraction, including syntactic, structural, reference and domain metadata. The domain metadata consists of ontology-based annotations associated with the structural information of each data source. However, caGrid's current querying functionality is given at the structural metadata level, without capitalising on the ontology-based annotations. This paper presents the design of and theoretical foundations for distributed ontology-based queries over cancer research data. Concept-based queries are reformulated to the target query language, where join conditions between multiple data sources are found by exploiting the semantic annotations. The system has been implemented, as a proof of concept, over the caGrid infrastructure. The approach is applicable to other model-driven architectures. A graphical user interface has been developed, supporting ontology-based queries over caGrid data sources. An extensive evaluation of the query reformulation technique is included. Conclusions To support personalised medicine in oncology, it is crucial to retrieve and integrate molecular, pathology, radiology and clinical data in an efficient manner. The semantic heterogeneity of the data makes this a challenging task. Ontologies provide a formal framework to support querying and integration. This paper provides an ontology-based solution for querying distributed databases over service-oriented, model-driven infrastructures. PMID:22373043

Dynamic Pore-Scale Imaging of Reactive Transport in Heterogeneous Carbonates at Reservoir Conditions Across Multiple Dissolution Regimes

NASA Astrophysics Data System (ADS)

Menke, H. P.; Bijeljic, B.; Andrew, M. G.; Blunt, M. J.

2014-12-01

Sequestering carbon in deep geologic formations is one way of reducing anthropogenic CO2 emissions. When supercritical CO2 mixes with brine in a reservoir, the acid generated has the potential to dissolve the surrounding pore structure. However, the magnitude and type of dissolution are condition dependent. Understanding how small changes in the pore structure, chemistry, and flow properties affect dissolution is paramount for successful predictive modelling. Both 'Pink Beam' synchrotron radiation and a Micro-CT lab source are used in dynamic X-ray microtomography to investigate the pore structure changes during supercritical CO2 injection in carbonate rocks of varying heterogeneity at high temperatures and pressures and various flow-rates. Three carbonate rock types were studied, one with a homogeneous pore structure and two heterogeneous carbonates. All samples are practically pure calcium carbonate, but have widely varying rock structures. Flow-rate was varied in three successive experiments by over an order of magnitude whlie keeping all other experimental conditions constant. A 4-mm carbonate core was injected with CO2-saturated brine at 10 MPa and 50oC. Tomographic images were taken at 30-second to 20-minute time-resolutions during a 2 to 4-hour injection period. A pore network was extracted using a topological analysis of the pore space and pore-scale flow modelling was performed directly on the binarized images with connected pathways and used to track the altering velocity distributions. Significant differences in dissolution type and magnitude were found for each rock type and flowrate. At the highest flow-rates, the homogeneous carbonate was seen to have predominately uniform dissolution with minor dissolution rate differences between the pores and pore throats. Alternatively, the heterogeneous carbonates which formed wormholes at high flow rates. At low flow rates the homogeneous rock developed wormholes, while the heterogeneous samples showed evidence of compact dissolution. This study serves as a unique benchmark for pore-scale reactive transport modelling directly on the binarized Micro-CT images. Dynamic pore-scale imaging methods offer advantages in helping explain the dominant processes at the pore scale so that they may be up-scaled for accurate model prediction.

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium.

PubMed

Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

2017-09-01

Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

Emergent dynamics of spatio-temporal chaos in a heterogeneous excitable medium

NASA Astrophysics Data System (ADS)

Bittihn, Philip; Berg, Sebastian; Parlitz, Ulrich; Luther, Stefan

2017-09-01

Self-organized activation patterns in excitable media such as spiral waves and spatio-temporal chaos underlie dangerous cardiac arrhythmias. While the interaction of single spiral waves with different types of heterogeneity has been studied extensively, the effect of heterogeneity on fully developed spatio-temporal chaos remains poorly understood. We investigate how the complexity and stability properties of spatio-temporal chaos in the Bär-Eiswirth model of excitable media depend on the heterogeneity of the underlying medium. We employ different measures characterizing the chaoticity of the system and find that the spatial arrangement of multiple discrete lower excitability regions has a strong impact on the complexity of the dynamics. Varying the number, shape, and spatial arrangement of the heterogeneities, we observe strong emergent effects ranging from increases in chaoticity to the complete cessation of chaos, contrasting the expectation from the homogeneous behavior. The implications of our findings for the development and treatment of arrhythmias in the heterogeneous cardiac muscle are discussed.

Long-range Ising model for credit portfolios with heterogeneous credit exposures

NASA Astrophysics Data System (ADS)

Kato, Kensuke

2016-11-01

We propose the finite-size long-range Ising model as a model for heterogeneous credit portfolios held by a financial institution in the view of econophysics. The model expresses the heterogeneity of the default probability and the default correlation by dividing a credit portfolio into multiple sectors characterized by credit rating and industry. The model also expresses the heterogeneity of the credit exposure, which is difficult to evaluate analytically, by applying the replica exchange Monte Carlo method to numerically calculate the loss distribution. To analyze the characteristics of the loss distribution for credit portfolios with heterogeneous credit exposures, we apply this model to various credit portfolios and evaluate credit risk. As a result, we show that the tail of the loss distribution calculated by this model has characteristics that are different from the tail of the loss distribution of the standard models used in credit risk modeling. We also show that there is a possibility of different evaluations of credit risk according to the pattern of heterogeneity.

Towards enhanced and interpretable clustering/classification in integrative genomics

PubMed Central

Lu, Yang Young; Lv, Jinchi; Fuhrman, Jed A.

2017-01-01

Abstract High-throughput technologies have led to large collections of different types of biological data that provide unprecedented opportunities to unravel molecular heterogeneity of biological processes. Nevertheless, how to jointly explore data from multiple sources into a holistic, biologically meaningful interpretation remains challenging. In this work, we propose a scalable and tuning-free preprocessing framework, Heterogeneity Rescaling Pursuit (Hetero-RP), which weighs important features more highly than less important ones in accord with implicitly existing auxiliary knowledge. Finally, we demonstrate effectiveness of Hetero-RP in diverse clustering and classification applications. More importantly, Hetero-RP offers an interpretation of feature importance, shedding light on the driving forces of the underlying biology. In metagenomic contig binning, Hetero-RP automatically weighs abundance and composition profiles according to the varying number of samples, resulting in markedly improved performance of contig binning. In RNA-binding protein (RBP) binding site prediction, Hetero-RP not only improves the prediction performance measured by the area under the receiver operating characteristic curves (AUC), but also uncovers the evidence supported by independent studies, including the distribution of the binding sites of IGF2BP and PUM2, the binding competition between hnRNPC and U2AF2, and the intron–exon boundary of U2AF2 [availability: https://github.com/younglululu/Hetero-RP]. PMID:28977511

BioTCM-SE: a semantic search engine for the information retrieval of modern biology and traditional Chinese medicine.

PubMed

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM.

BioTCM-SE: A Semantic Search Engine for the Information Retrieval of Modern Biology and Traditional Chinese Medicine

PubMed Central

Chen, Xi; Chen, Huajun; Bi, Xuan; Gu, Peiqin; Chen, Jiaoyan; Wu, Zhaohui

2014-01-01

Understanding the functional mechanisms of the complex biological system as a whole is drawing more and more attention in global health care management. Traditional Chinese Medicine (TCM), essentially different from Western Medicine (WM), is gaining increasing attention due to its emphasis on individual wellness and natural herbal medicine, which satisfies the goal of integrative medicine. However, with the explosive growth of biomedical data on the Web, biomedical researchers are now confronted with the problem of large-scale data analysis and data query. Besides that, biomedical data also has a wide coverage which usually comes from multiple heterogeneous data sources and has different taxonomies, making it hard to integrate and query the big biomedical data. Embedded with domain knowledge from different disciplines all regarding human biological systems, the heterogeneous data repositories are implicitly connected by human expert knowledge. Traditional search engines cannot provide accurate and comprehensive search results for the semantically associated knowledge since they only support keywords-based searches. In this paper, we present BioTCM-SE, a semantic search engine for the information retrieval of modern biology and TCM, which provides biologists with a comprehensive and accurate associated knowledge query platform to greatly facilitate the implicit knowledge discovery between WM and TCM. PMID:24772189

“Epidemic Clones” of Listeria monocytogenes Are Widespread and Ancient Clonal Groups

PubMed Central

Cantinelli, Thomas; Chenal-Francisque, Viviane; Diancourt, Laure; Frezal, Lise; Leclercq, Alexandre; Wirth, Thierry

2013-01-01

The food-borne pathogen Listeria monocytogenes is genetically heterogeneous. Although some clonal groups have been implicated in multiple outbreaks, there is currently no consensus on how “epidemic clones” should be defined. The objectives of this work were to compare the patterns of sequence diversity on two sets of genes that have been widely used to define L. monocytogenes clonal groups: multilocus sequence typing (MLST) and multi-virulence-locus sequence typing (MvLST). Further, we evaluated the diversity within clonal groups by pulsed-field gel electrophoresis (PFGE). Based on 125 isolates of diverse temporal, geographical, and source origins, MLST and MvLST genes (i) had similar patterns of sequence polymorphisms, recombination, and selection, (ii) provided concordant phylogenetic clustering, and (iii) had similar discriminatory power, which was not improved when we combined both data sets. Inclusion of representative strains of previous outbreaks demonstrated the correspondence of epidemic clones with previously recognized MLST clonal complexes. PFGE analysis demonstrated heterogeneity within major clones, most of which were isolated decades before their involvement in outbreaks. We conclude that the “epidemic clone” denominations represent a redundant but largely incomplete nomenclature system for MLST-defined clones, which must be regarded as successful genetic groups that are widely distributed across time and space. PMID:24006010

A review on machine learning principles for multi-view biological data integration.

PubMed

Li, Yifeng; Wu, Fang-Xiang; Ngom, Alioune

2018-03-01

Driven by high-throughput sequencing techniques, modern genomic and clinical studies are in a strong need of integrative machine learning models for better use of vast volumes of heterogeneous information in the deep understanding of biological systems and the development of predictive models. How data from multiple sources (called multi-view data) are incorporated in a learning system is a key step for successful analysis. In this article, we provide a comprehensive review on omics and clinical data integration techniques, from a machine learning perspective, for various analyses such as prediction, clustering, dimension reduction and association. We shall show that Bayesian models are able to use prior information and model measurements with various distributions; tree-based methods can either build a tree with all features or collectively make a final decision based on trees learned from each view; kernel methods fuse the similarity matrices learned from individual views together for a final similarity matrix or learning model; network-based fusion methods are capable of inferring direct and indirect associations in a heterogeneous network; matrix factorization models have potential to learn interactions among features from different views; and a range of deep neural networks can be integrated in multi-modal learning for capturing the complex mechanism of biological systems.

Molecular Epidemiology of Leptospira Serogroup Pomona Infections Among Wild and Domestic Animals in Spain.

PubMed

Arent, Z J; Gilmore, C; San-Miguel Ayanz, J M; Neyra, L Quevedo; García-Peña, F J

2017-03-01

Strains of Leptospira serogroup Pomona are known to cause widespread animal infections in many parts of the world. Forty-three isolates retrieved from domestic animals and wild small mammals suggest that serogroup Pomona is epidemiologically relevant in Spain. This is supported by the high prevalence of serovar Pomona antibodies in livestock and wild animals. In this study, the strains were serologically and genetically characterized in an attempt to elucidate their epidemiology. Serological typing was based on the microscopic agglutination test but molecular typing involved species-specific polymerase chain reaction, restriction endonuclease analysis, and multiple-locus variable-number tandem repeat analysis. The study revealed that the infections are caused by two serovars, namely Pomona and Mozdok. Serovar Pomona was derived only from farm animals and may be adapted to pigs, which are recognized as the maintenance host. The results demonstrated that serovar Pomona is genetically heterogeneous and three different types were recognized. This heterogeneity was correlated with different geographical distributions of the isolates. All strains derived from small wild mammals were identified as serovar Mozdok. Some isolates of this serovar retrieved from cattle confirm that this serovar may also be the cause of infections in food-producing animals for which these wild species may be source of infection.

Semantic Web technologies for the big data in life sciences.

PubMed

Wu, Hongyan; Yamaguchi, Atsuko

2014-08-01

The life sciences field is entering an era of big data with the breakthroughs of science and technology. More and more big data-related projects and activities are being performed in the world. Life sciences data generated by new technologies are continuing to grow in not only size but also variety and complexity, with great speed. To ensure that big data has a major influence in the life sciences, comprehensive data analysis across multiple data sources and even across disciplines is indispensable. The increasing volume of data and the heterogeneous, complex varieties of data are two principal issues mainly discussed in life science informatics. The ever-evolving next-generation Web, characterized as the Semantic Web, is an extension of the current Web, aiming to provide information for not only humans but also computers to semantically process large-scale data. The paper presents a survey of big data in life sciences, big data related projects and Semantic Web technologies. The paper introduces the main Semantic Web technologies and their current situation, and provides a detailed analysis of how Semantic Web technologies address the heterogeneous variety of life sciences big data. The paper helps to understand the role of Semantic Web technologies in the big data era and how they provide a promising solution for the big data in life sciences.

Effect of subsurface heterogeneity on free-product recovery from unconfined aquifers

NASA Astrophysics Data System (ADS)

Kaluarachchi, Jagath J.

1996-03-01

Free-product record system designs for light-hydrocarbon-contaminated sites were investigated to evaluate the effects of subsurface heterogeneity using a vertically integrated three-phase flow model. The input stochastic variable of the areal flow analysis was the log-intrinsic permeability and it was generated using the Turning Band method. The results of a series of hypothetical field-scale simulations showed that subsurface heterogeneity has a substantial effect on free-product recovery predictions. As the heterogeneity increased, the recoverable oil volume decreased and the residual trapped oil volume increased. As the subsurface anisotropy increased, these effects together with free- and total-oil contaminated areas were further enhanced. The use of multiple-stage water pumping was found to be insignificant compared to steady uniform pumping due to reduced recovery efficiency and increased residual oil volume. This observation was opposite to that produced under homogeneous scenarios. The effect of subsurface heterogeneity was enhanced at relatively low water pumping rates. The difference in results produced by homogeneous and heterogeneous simulations was substantial, indicating greater attention should be paid in modeling free-product recovery systems with appropriate subsurface heterogeneity.

Single versus successive pop-in modes in nanoindentation tests of single crystals

DOE PAGES

Xia, Yuzhi; Gao, Yanfei; Pharr, George M.; ...

2016-05-24

From recent nanoindentation experiments, two types of pop-in modes have been identified: a single pop-in with a large displacement excursion, or a number of pop-ins with comparable and small displacement excursions. Theoretical analyses are developed here to study the roles played by indenter tip radius, pre-existing defect density, heterogeneous nucleation source type, and lattice resistance on the pop-in modes. The evolution of dislocation structures in earlier pop-ins provides input to modeling a stochastic, heterogeneous mechanism that may be responsible for the subsequent pop-ins. It is found that when the first pop-in occurs near theoretical shear stress, the pop-in mode ismore » determined by the lattice resistance and tip radius. When the first pop-in occurs at low shear stress, whether the successive pop-in mode occurs depends on how the heterogeneous dislocation nucleation source density increases as compared to the increase of the total dislocation density. Lastly, the above transitions are found to correlate well with the ratio of indenter tip radius to the mean spacing of dislocation nucleation sources.« less

3D numerical simulation of the long range propagation of acoustical shock waves through a heterogeneous and moving medium

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

Luquet, David; Marchiano, Régis; Coulouvrat, François, E-mail: francois.coulouvrat@upmc.fr

2015-10-28

Many situations involve the propagation of acoustical shock waves through flows. Natural sources such as lightning, volcano explosions, or meteoroid atmospheric entries, emit loud, low frequency, and impulsive sound that is influenced by atmospheric wind and turbulence. The sonic boom produced by a supersonic aircraft and explosion noises are examples of intense anthropogenic sources in the atmosphere. The Buzz-Saw-Noise produced by turbo-engine fan blades rotating at supersonic speed also propagates in a fast flow within the engine nacelle. Simulating these situations is challenging, given the 3D nature of the problem, the long range propagation distances relative to the central wavelength,more » the strongly nonlinear behavior of shocks associated to a wide-band spectrum, and finally the key role of the flow motion. With this in view, the so-called FLHOWARD (acronym for FLow and Heterogeneous One-Way Approximation for Resolution of Diffraction) method is presented with three-dimensional applications. A scalar nonlinear wave equation is established in the framework of atmospheric applications, assuming weak heterogeneities and a slow wind. It takes into account diffraction, absorption and relaxation properties of the atmosphere, quadratic nonlinearities including weak shock waves, heterogeneities of the medium in sound speed and density, and presence of a flow (assuming a mean stratified wind and 3D turbulent ? flow fluctuations of smaller amplitude). This equation is solved in the framework of the one-way method. A split-step technique allows the splitting of the non-linear wave equation into simpler equations, each corresponding to a physical effect. Each sub-equation is solved using an analytical method if possible, and finite-differences otherwise. Nonlinear effects are solved in the time domain, and others in the frequency domain. Homogeneous diffraction is handled by means of the angular spectrum method. Ground is assumed perfectly flat and rigid. Due to the 3D aspect, the code was massively parallelized using the single program, multiple data paradigm with the Message Passing Interfaces (MPI) for distributed memory architectures. This allows us to handle problems in the order of a thousand billion mesh points in the four dimensions (3 dimensions of space plus time). The validity of the method has been thoroughly evaluated on many cases with known solutions: linear piston, scattering of plane wave by a heterogeneous sphere, propagation in a waveguide with a shear flow, scattering by a finite amplitude vortex and nonlinear propagation in a thermoviscous medium. This validation process allows for a detailed assessment of the advantages and limitations of the method. Finally, applications to atmospheric propagation of shock waves will be presented.« less

3D numerical simulation of the long range propagation of acoustical shock waves through a heterogeneous and moving medium

NASA Astrophysics Data System (ADS)

Luquet, David; Marchiano, Régis; Coulouvrat, François

2015-10-01

Many situations involve the propagation of acoustical shock waves through flows. Natural sources such as lightning, volcano explosions, or meteoroid atmospheric entries, emit loud, low frequency, and impulsive sound that is influenced by atmospheric wind and turbulence. The sonic boom produced by a supersonic aircraft and explosion noises are examples of intense anthropogenic sources in the atmosphere. The Buzz-Saw-Noise produced by turbo-engine fan blades rotating at supersonic speed also propagates in a fast flow within the engine nacelle. Simulating these situations is challenging, given the 3D nature of the problem, the long range propagation distances relative to the central wavelength, the strongly nonlinear behavior of shocks associated to a wide-band spectrum, and finally the key role of the flow motion. With this in view, the so-called FLHOWARD (acronym for FLow and Heterogeneous One-Way Approximation for Resolution of Diffraction) method is presented with three-dimensional applications. A scalar nonlinear wave equation is established in the framework of atmospheric applications, assuming weak heterogeneities and a slow wind. It takes into account diffraction, absorption and relaxation properties of the atmosphere, quadratic nonlinearities including weak shock waves, heterogeneities of the medium in sound speed and density, and presence of a flow (assuming a mean stratified wind and 3D turbulent ? flow fluctuations of smaller amplitude). This equation is solved in the framework of the one-way method. A split-step technique allows the splitting of the non-linear wave equation into simpler equations, each corresponding to a physical effect. Each sub-equation is solved using an analytical method if possible, and finite-differences otherwise. Nonlinear effects are solved in the time domain, and others in the frequency domain. Homogeneous diffraction is handled by means of the angular spectrum method. Ground is assumed perfectly flat and rigid. Due to the 3D aspect, the code was massively parallelized using the single program, multiple data paradigm with the Message Passing Interfaces (MPI) for distributed memory architectures. This allows us to handle problems in the order of a thousand billion mesh points in the four dimensions (3 dimensions of space plus time). The validity of the method has been thoroughly evaluated on many cases with known solutions: linear piston, scattering of plane wave by a heterogeneous sphere, propagation in a waveguide with a shear flow, scattering by a finite amplitude vortex and nonlinear propagation in a thermoviscous medium. This validation process allows for a detailed assessment of the advantages and limitations of the method. Finally, applications to atmospheric propagation of shock waves will be presented.

Heterogeneous Monolithic Integration of Single-Crystal Organic Materials.

PubMed

Park, Kyung Sun; Baek, Jangmi; Park, Yoonkyung; Lee, Lynn; Hyon, Jinho; Koo Lee, Yong-Eun; Shrestha, Nabeen K; Kang, Youngjong; Sung, Myung Mo

2017-02-01

Manufacturing high-performance organic electronic circuits requires the effective heterogeneous integration of different nanoscale organic materials with uniform morphology and high crystallinity in a desired arrangement. In particular, the development of high-performance organic electronic and optoelectronic devices relies on high-quality single crystals that show optimal intrinsic charge-transport properties and electrical performance. Moreover, the heterogeneous integration of organic materials on a single substrate in a monolithic way is highly demanded for the production of fundamental organic electronic components as well as complex integrated circuits. Many of the various methods that have been designed to pattern multiple heterogeneous organic materials on a substrate and the heterogeneous integration of organic single crystals with their crystal growth are described here. Critical issues that have been encountered in the development of high-performance organic integrated electronics are also addressed. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Effectively Identifying eQTLs from Multiple Tissues by Combining Mixed Model and Meta-analytic Approaches

PubMed Central

Choi, Ted; Eskin, Eleazar

2013-01-01

Gene expression data, in conjunction with information on genetic variants, have enabled studies to identify expression quantitative trait loci (eQTLs) or polymorphic locations in the genome that are associated with expression levels. Moreover, recent technological developments and cost decreases have further enabled studies to collect expression data in multiple tissues. One advantage of multiple tissue datasets is that studies can combine results from different tissues to identify eQTLs more accurately than examining each tissue separately. The idea of aggregating results of multiple tissues is closely related to the idea of meta-analysis which aggregates results of multiple genome-wide association studies to improve the power to detect associations. In principle, meta-analysis methods can be used to combine results from multiple tissues. However, eQTLs may have effects in only a single tissue, in all tissues, or in a subset of tissues with possibly different effect sizes. This heterogeneity in terms of effects across multiple tissues presents a key challenge to detect eQTLs. In this paper, we develop a framework that leverages two popular meta-analysis methods that address effect size heterogeneity to detect eQTLs across multiple tissues. We show by using simulations and multiple tissue data from mouse that our approach detects many eQTLs undetected by traditional eQTL methods. Additionally, our method provides an interpretation framework that accurately predicts whether an eQTL has an effect in a particular tissue. PMID:23785294

Sources of image degradation in fundamental and harmonic ultrasound imaging using nonlinear, full-wave simulations.

PubMed

Pinton, Gianmarco F; Trahey, Gregg E; Dahl, Jeremy J

2011-04-01

A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain (FDTD). This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-andsum beamforming is used to generate point spread functions (PSF) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is reverberation from near-field structures. Reverberation clutter in the harmonic PSF is 26 dB higher than the fundamental PSF. An artificial medium with uniform velocity but unchanged impedance characteristics indicates that for the fundamental PSF, the primary source of degradation is phase aberration. An ultrasound image is created in silico using the same physical and algorithmic process used in an ultrasound scanner: a series of pulses are transmitted through heterogeneous scattering tissue and the received echoes are used in a delay-and-sum beamforming algorithm to generate images. These beamformed images are compared with images obtained from convolution of the PSF with a scatterer field to demonstrate that a very large portion of the PSF must be used to accurately represent the clutter observed in conventional imaging. © 2011 IEEE

Do factors related to combustion-based sources explain heterogeneity in PM-mortality associations across the United States?

EPA Science Inventory

Introduction: Spatial heterogeneity of effect estimates in associations between PM2.5 and total non-accidental mortality (TNA) in the United States (US), is an issue in epidemiology. This study uses rate ratios generated from the Multi-City/Multi-Pollutant study (1999-2005) for 3...

Evaluating source area contributions from aircraft flux measurements over heterogeneous land cover by large eddy simulation

USDA-ARS?s Scientific Manuscript database

The estimation of spatial patterns in surface fluxes from aircraft observations poses several challenges in presence of heterogeneous land cover. In particular, the effects of turbulence on scalar transport and the different behavior of passive (e.g. moisture) versus active (e.g. temperature) scalar...

SQL is Dead; Long-live SQL: Relational Database Technology in Science Contexts

NASA Astrophysics Data System (ADS)

Howe, B.; Halperin, D.

2014-12-01

Relational databases are often perceived as a poor fit in science contexts: Rigid schemas, poor support for complex analytics, unpredictable performance, significant maintenance and tuning requirements --- these idiosyncrasies often make databases unattractive in science contexts characterized by heterogeneous data sources, complex analysis tasks, rapidly changing requirements, and limited IT budgets. In this talk, I'll argue that although the value proposition of typical relational database systems are weak in science, the core ideas that power relational databases have become incredibly prolific in open source science software, and are emerging as a universal abstraction for both big data and small data. In addition, I'll talk about two open source systems we are building to "jailbreak" the core technology of relational databases and adapt them for use in science. The first is SQLShare, a Database-as-a-Service system supporting collaborative data analysis and exchange by reducing database use to an Upload-Query-Share workflow with no installation, schema design, or configuration required. The second is Myria, a service that supports much larger scale data, complex analytics, and supports multiple back end systems. Finally, I'll describe some of the ways our collaborators in oceanography, astronomy, biology, fisheries science, and more are using these systems to replace script-based workflows for reasons of performance, flexibility, and convenience.

Legacy of contaminant N sources to the NO3− signature in rivers: a combined isotopic (δ15N-NO3−, δ18O-NO3−, δ11B) and microbiological investigation

PubMed Central

Briand, Cyrielle; Sebilo, Mathieu; Louvat, Pascale; Chesnot, Thierry; Vaury, Véronique; Schneider, Maude; Plagnes, Valérie

2017-01-01

Nitrate content of surface waters results from complex mixing of multiple sources, whose signatures can be modified through N reactions occurring within the different compartments of the whole catchment. Despite this complexity, the determination of nitrate origin is the first and crucial step for water resource preservation. Here, for the first time, we combined at the catchment scale stable isotopic tracers (δ15N and δ18O of nitrate and δ11B) and fecal indicators to trace nitrate sources and pathways to the stream. We tested this approach on two rivers in an agricultural region of SW France. Boron isotopic ratios evidenced inflow from anthropogenic waters, microbiological markers revealed organic contaminations from both human and animal wastes. Nitrate δ15N and δ18O traced inputs from the surface leaching during high flow events and from the subsurface drainage in base flow regime. They also showed that denitrification occurred within the soils before reaching the rivers. Furthermore, this study highlighted the determinant role of the soil compartment in nitrate formation and recycling with important spatial heterogeneity and temporal variability. PMID:28150819

Development and human factors analysis of an augmented reality interface for multi-robot tele-operation and control

NASA Astrophysics Data System (ADS)

Lee, Sam; Lucas, Nathan P.; Ellis, R. Darin; Pandya, Abhilash

2012-06-01

This paper presents a seamlessly controlled human multi-robot system comprised of ground and aerial robots of semiautonomous nature for source localization tasks. The system combines augmented reality interfaces capabilities with human supervisor's ability to control multiple robots. The role of this human multi-robot interface is to allow an operator to control groups of heterogeneous robots in real time in a collaborative manner. It used advanced path planning algorithms to ensure obstacles are avoided and that the operators are free for higher-level tasks. Each robot knows the environment and obstacles and can automatically generate a collision-free path to any user-selected target. It displayed sensor information from each individual robot directly on the robot in the video view. In addition, a sensor data fused AR view is displayed which helped the users pin point source information or help the operator with the goals of the mission. The paper studies a preliminary Human Factors evaluation of this system in which several interface conditions are tested for source detection tasks. Results show that the novel Augmented Reality multi-robot control (Point-and-Go and Path Planning) reduced mission completion times compared to the traditional joystick control for target detection missions. Usability tests and operator workload analysis are also investigated.

ODMSummary: A Tool for Automatic Structured Comparison of Multiple Medical Forms Based on Semantic Annotation with the Unified Medical Language System

PubMed Central

Krumm, Rainer; Dugas, Martin

2016-01-01

Introduction Medical documentation is applied in various settings including patient care and clinical research. Since procedures of medical documentation are heterogeneous and developed further, secondary use of medical data is complicated. Development of medical forms, merging of data from different sources and meta-analyses of different data sets are currently a predominantly manual process and therefore difficult and cumbersome. Available applications to automate these processes are limited. In particular, tools to compare multiple documentation forms are missing. The objective of this work is to design, implement and evaluate the new system ODMSummary for comparison of multiple forms with a high number of semantically annotated data elements and a high level of usability. Methods System requirements are the capability to summarize and compare a set of forms, enable to estimate the documentation effort, track changes in different versions of forms and find comparable items in different forms. Forms are provided in Operational Data Model format with semantic annotations from the Unified Medical Language System. 12 medical experts were invited to participate in a 3-phase evaluation of the tool regarding usability. Results ODMSummary (available at https://odmtoolbox.uni-muenster.de/summary/summary.html) provides a structured overview of multiple forms and their documentation fields. This comparison enables medical experts to assess multiple forms or whole datasets for secondary use. System usability was optimized based on expert feedback. Discussion The evaluation demonstrates that feedback from domain experts is needed to identify usability issues. In conclusion, this work shows that automatic comparison of multiple forms is feasible and the results are usable for medical experts. PMID:27736972

Development of Mobile Tracer Correlation Strategies for Quantification of Emissions from Landfills and Other Large Area Sources

EPA Science Inventory

Emission measurements from large area sources such as landfills are complicated by their spatial extent and heterogeneous nature. In recent years, an on-site optical remote sensing (ORS) technique for characterizing emissions from area sources was described in an EPA-published p...

Integrated Forensics Approach To Fingerprint PCB Sources In Sediments Using Immunoassays And GC/MS Congener Analyses

EPA Science Inventory

Determining the original source of contamination to a heterogeneous matrix such as sediments is a requirement for both clean-up and compliance programs within the military. Understanding the source of contaminants to sediment in industrial settings is a prerequisite to implement...

An Integrated Forensics Approach To Fingerprint PCB Sources In Sediments Using RSC And ACF

EPA Science Inventory

Determing the original source of contamination to a heterogeneous matrix matrix such as sediment is a requirement for both clean-up and compliance programs. Identifying the source of sediment contaminants in industrial settings is a pre-requisite to implementing any proposed se...

Lessons learned from a pilot implementation of the UMLS information sources map.

PubMed

Miller, P L; Frawley, S J; Wright, L; Roderer, N K; Powsner, S M

1995-01-01

To explore the software design issues involved in implementing an operational information sources map (ISM) knowledge base (KB) and system of navigational tools that can help medical users access network-based information sources relevant to a biomedical question. A pilot biomedical ISM KB and associated client-server software (ISM/Explorer) have been developed to help students, clinicians, researchers, and staff access network-based information sources, as part of the National Library of Medicine's (NLM) multi-institutional Unified Medical Language System (UMLS) project. The system allows the user to specify and constrain a search for a biomedical question of interest. The system then returns a list of sources matching the search. At this point the user may request 1) further information about a source, 2) that the list of sources be regrouped by different criteria to allow the user to get a better overall appreciation of the set of retrieved sources as a whole, or 3) automatic connection to a source. The pilot system operates in client-server mode and currently contains coded information for 121 sources. It is in routine use from approximately 40 workstations at the Yale School of Medicine. The lessons that have been learned are that: 1) it is important to make access to different versions of a source as seamless as possible, 2) achieving seamless, cross-platform access to heterogeneous sources is difficult, 3) significant differences exist between coding the subject content of an electronic information resource versus that of an article or a book, 4) customizing the ISM to multiple institutions entails significant complexities, and 5) there are many design trade-offs between specifying searches and viewing sets of retrieved sources that must be taken into consideration. An ISM KB and navigational tools have been constructed. In the process, much has been learned about the complexities of development and evaluation in this new environment, which are different from those for Gopher, wide area information servers (WAIS), World-Wide-Web (WWW), and MOSAIC resources.

Asterism: an integrated, complete, and open-source approach for running seismologist continuous data-intensive analysis on heterogeneous systems

NASA Astrophysics Data System (ADS)

Ferreira da Silva, R.; Filgueira, R.; Deelman, E.; Atkinson, M.

2016-12-01

We present Asterism, an open source data-intensive framework, which combines the Pegasus and dispel4py workflow systems. Asterism aims to simplify the effort required to develop data-intensive applications that run across multiple heterogeneous resources, without users having to: re-formulate their methods according to different enactment systems; manage the data distribution across systems; parallelize their methods; co-place and schedule their methods with computing resources; and store and transfer large/small volumes of data. Asterism's key element is to leverage the strengths of each workflow system: dispel4py allows developing scientific applications locally and then automatically parallelize and scale them on a wide range of HPC infrastructures with no changes to the application's code; Pegasus orchestrates the distributed execution of applications while providing portability, automated data management, recovery, debugging, and monitoring, without users needing to worry about the particulars of the target execution systems. Asterism leverages the level of abstractions provided by each workflow system to describe hybrid workflows where no information about the underlying infrastructure is required beforehand. The feasibility of Asterism has been evaluated using the seismic ambient noise cross-correlation application, a common data-intensive analysis pattern used by many seismologists. The application preprocesses (Phase1) and cross-correlates (Phase2) traces from several seismic stations. The Asterism workflow is implemented as a Pegasus workflow composed of two tasks (Phase1 and Phase2), where each phase represents a dispel4py workflow. Pegasus tasks describe the in/output data at a logical level, the data dependency between tasks, and the e-Infrastructures and the execution engine to run each dispel4py workflow. We have instantiated the workflow using data from 1000 stations from the IRIS services, and run it across two heterogeneous resources described as Docker containers: MPI (Container2) and Storm (Container3) clusters (Figure 1). Each dispel4py workflow is mapped to a particular execution engine, and data transfers between resources are automatically handled by Pegasus. Asterism is freely available online at http://github.com/dispel4py/pegasus_dispel4py.

Ultra-wideband WDM VCSEL arrays by lateral heterogeneous integration

NASA Astrophysics Data System (ADS)

Geske, Jon

Advancements in heterogeneous integration are a driving factor in the development of evermore sophisticated and functional electronic and photonic devices. Such advancements will merge the optical and electronic capabilities of different material systems onto a common integrated device platform. This thesis presents a new lateral heterogeneous integration technology called nonplanar wafer bonding. The technique is capable of integrating multiple dissimilar semiconductor device structures on the surface of a substrate in a single wafer bond step, leaving different integrated device structures adjacent to each other on the wafer surface. Material characterization and numerical simulations confirm that the material quality is not compromised during the process. Nonplanar wafer bonding is used to fabricate ultra-wideband wavelength division multiplexed (WDM) vertical-cavity surface-emitting laser (VCSEL) arrays. The optically-pumped VCSEL arrays span 140 nm from 1470 to 1610 nm, a record wavelength span for devices operating in this wavelength range. The array uses eight wavelength channels to span the 140 nm with all channels separated by precisely 20 nm. All channels in the array operate single mode to at least 65°C with output power uniformity of +/- 1 dB. The ultra-wideband WDM VCSEL arrays are a significant first step toward the development of a single-chip source for optical networks based on coarse WDM (CWDM), a low-cost alternative to traditional dense WDM. The CWDM VCSEL arrays make use of fully-oxidized distributed Bragg reflectors (DBRs) to provide the wideband reflectivity required for optical feedback and lasing across 140 rim. In addition, a novel optically-pumped active region design is presented. It is demonstrated, with an analytical model and experimental results, that the new active-region design significantly improves the carrier uniformity in the quantum wells and results in a 50% lasing threshold reduction and a 20°C improvement in the peak operating temperature of the devices. This thesis investigates the integration and fabrication technologies required to fabricate ultra-wideband WDM VCSEL arrays. The complete device design and fabrication process is presented along with actual device results from completed CWDM VCSEL arrays. Future recommendations for improvements are presented, along with a roadmap toward a final electrically-pumped single-chip source for CWDM applications.

Intra-tumor genetic heterogeneity and mortality in head and neck cancer: analysis of data from the Cancer Genome Atlas.

PubMed

Mroz, Edmund A; Tward, Aaron D; Tward, Aaron M; Hammon, Rebecca J; Ren, Yin; Rocco, James W

2015-02-01

Although the involvement of intra-tumor genetic heterogeneity in tumor progression, treatment resistance, and metastasis is established, genetic heterogeneity is seldom examined in clinical trials or practice. Many studies of heterogeneity have had prespecified markers for tumor subpopulations, limiting their generalizability, or have involved massive efforts such as separate analysis of hundreds of individual cells, limiting their clinical use. We recently developed a general measure of intra-tumor genetic heterogeneity based on whole-exome sequencing (WES) of bulk tumor DNA, called mutant-allele tumor heterogeneity (MATH). Here, we examine data collected as part of a large, multi-institutional study to validate this measure and determine whether intra-tumor heterogeneity is itself related to mortality. Clinical and WES data were obtained from The Cancer Genome Atlas in October 2013 for 305 patients with head and neck squamous cell carcinoma (HNSCC), from 14 institutions. Initial pathologic diagnoses were between 1992 and 2011 (median, 2008). Median time to death for 131 deceased patients was 14 mo; median follow-up of living patients was 22 mo. Tumor MATH values were calculated from WES results. Despite the multiple head and neck tumor subsites and the variety of treatments, we found in this retrospective analysis a substantial relation of high MATH values to decreased overall survival (Cox proportional hazards analysis: hazard ratio for high/low heterogeneity, 2.2; 95% CI 1.4 to 3.3). This relation of intra-tumor heterogeneity to survival was not due to intra-tumor heterogeneity's associations with other clinical or molecular characteristics, including age, human papillomavirus status, tumor grade and TP53 mutation, and N classification. MATH improved prognostication over that provided by traditional clinical and molecular characteristics, maintained a significant relation to survival in multivariate analyses, and distinguished outcomes among patients having oral-cavity or laryngeal cancers even when standard disease staging was taken into account. Prospective studies, however, will be required before MATH can be used prognostically in clinical trials or practice. Such studies will need to examine homogeneously treated HNSCC at specific head and neck subsites, and determine the influence of cancer therapy on MATH values. Analysis of MATH and outcome in human-papillomavirus-positive oropharyngeal squamous cell carcinoma is particularly needed. To our knowledge this study is the first to combine data from hundreds of patients, treated at multiple institutions, to document a relation between intra-tumor heterogeneity and overall survival in any type of cancer. We suggest applying the simply calculated MATH metric of heterogeneity to prospective studies of HNSCC and other tumor types.

Bio-inspired UAV routing, source localization, and acoustic signature classification for persistent surveillance

NASA Astrophysics Data System (ADS)

Burman, Jerry; Hespanha, Joao; Madhow, Upamanyu; Pham, Tien

2011-06-01

A team consisting of Teledyne Scientific Company, the University of California at Santa Barbara and the Army Research Laboratory* is developing technologies in support of automated data exfiltration from heterogeneous battlefield sensor networks to enhance situational awareness for dismounts and command echelons. Unmanned aerial vehicles (UAV) provide an effective means to autonomously collect data from a sparse network of unattended ground sensors (UGSs) that cannot communicate with each other. UAVs are used to reduce the system reaction time by generating autonomous collection routes that are data-driven. Bio-inspired techniques for search provide a novel strategy to detect, capture and fuse data. A fast and accurate method has been developed to localize an event by fusing data from a sparse number of UGSs. This technique uses a bio-inspired algorithm based on chemotaxis or the motion of bacteria seeking nutrients in their environment. A unique acoustic event classification algorithm was also developed based on using swarm optimization. Additional studies addressed the problem of routing multiple UAVs, optimally placing sensors in the field and locating the source of gunfire at helicopters. A field test was conducted in November of 2009 at Camp Roberts, CA. The field test results showed that a system controlled by bio-inspired software algorithms can autonomously detect and locate the source of an acoustic event with very high accuracy and visually verify the event. In nine independent test runs of a UAV, the system autonomously located the position of an explosion nine times with an average accuracy of 3 meters. The time required to perform source localization using the UAV was on the order of a few minutes based on UAV flight times. In June 2011, additional field tests of the system will be performed and will include multiple acoustic events, optimal sensor placement based on acoustic phenomenology and the use of the International Technology Alliance (ITA) Sensor Network Fabric (IBM).

Single-cell multimodal profiling reveals cellular epigenetic heterogeneity.

PubMed

Cheow, Lih Feng; Courtois, Elise T; Tan, Yuliana; Viswanathan, Ramya; Xing, Qiaorui; Tan, Rui Zhen; Tan, Daniel S W; Robson, Paul; Loh, Yuin-Han; Quake, Stephen R; Burkholder, William F

2016-10-01

Sample heterogeneity often masks DNA methylation signatures in subpopulations of cells. Here, we present a method to genotype single cells while simultaneously interrogating gene expression and DNA methylation at multiple loci. We used this targeted multimodal approach, implemented on an automated, high-throughput microfluidic platform, to assess primary lung adenocarcinomas and human fibroblasts undergoing reprogramming by profiling epigenetic variation among cell types identified through genotyping and transcriptional analysis.

Education to Thrive in a Heterogeneous and Democratic Society--A Task for Citizenship and Character Education? Results of Case Studies in Three Berlin Schools

ERIC Educational Resources Information Center

Bacia, Ewa; Ittel, Angela

2017-01-01

Purpose: The main goal of this paper is to analyze how the schools and teachers in three high schools dealt with the challenges of heterogeneity in the classroom using methods of citizenship and character education (CCE). Approach: To achieve this goal we conducted case studies in three high schools in Berlin, using multiple Methodological…

LNAPL source zone delineation using soil gases in a heterogeneous silty-sand aquifer.

PubMed

Cohen, Grégory J V; Jousse, Florie; Luze, Nicolas; Höhener, Patrick; Atteia, Olivier

2016-09-01

Source delineation of hydrocarbon contaminated sites is of high importance for remediation work. However, traditional methods like soil core extraction and analysis or recent Membrane Interface Probe methods are time consuming and costly. Therefore, the development of an in situ method based on soil gas analysis can be interesting. This includes the direct measurement of volatile organic compounds (VOCs) in soil gas taken from gas probes using a PID (Photo Ionization Detector) and the analysis of other soil gases related to VOC degradation distribution (CH4, O2, CO2) or related to presence of Light Non-Aqueous Phase Liquid (LNAPL) as (222)Rn. However, in widespread heterogeneous formations, delineation by gas measurements becomes more challenging. The objective of this study is twofold: (i) to analyse the potential of several in situ gas measurement techniques in comparison to soil coring for LNAPL source delineation at a heterogeneous contaminated site where the techniques might be limited by a low diffusion potential linked to the presence of fine sands and silts, and (ii) to analyse the effect of vertical sediment heterogeneities on the performance of these gas measurement methods. Thus, five types of gases were analysed: VOCs, their three related degradation products O2, CO2 and CH4 and (222)Rn. Gas measurements were compared to independent LNAPL analysis by coring. This work was conducted at an old industrial site frequently contaminated by a Diesel-Fuel mixture located in a heterogeneous fine-grained aquifer. Results show that in such heterogeneous media migration of reactive gases like VOCs occurs only across small distances and the VOC concentrations sampled with gas probes are mainly related to local conditions rather than the presence of LNAPL below the gas probe. (222)Rn is not well correlated with LNAPL because of sediment heterogeneity. Oxygen, CO2, and especially CH4, have larger lengths of diffusion and give the clearest picture for LNAPL presence at this site even when the gas probe is somewhat distant. Copyright © 2016 Elsevier B.V. All rights reserved.

Evidence-Based Assessment of Conduct Problems in Children and Adolescents

ERIC Educational Resources Information Center

McMahon, Robert J.; Frick, Paul J.

2005-01-01

This article provides a summary of research in 4 areas that have direct and important implications for evidence-based assessment of children and adolescents with conduct problems (CP): (a) the heterogeneity in types and severity of CP, (b) common comorbid conditions, (c) multiple risk factors associated with CP, and (d) multiple developmental…

Occupational exposure to methylene chloride and risk of cancer: a meta-analysis.

PubMed

Liu, Tao; Xu, Qin-er; Zhang, Chuan-hui; Zhang, Peng

2013-12-01

We searched MEDLINE and EMBASE for epidemiologic studies on occupational exposure to methylene chloride and risk of cancer. Estimates of study-specific odds ratios (ORs) were calculated using inverse-variance-weighted fixed-effects models and random-effects models. Statistical tests for heterogeneity were applied. We summarized data from five cohort studies and 13 case-control studies. The pooled OR for multiple myeloma was (OR 2.04; 95 % CI 1.31-3.17) in relation to occupational exposure to methylene chloride but not for non-Hodgkin's lymphoma, leukemia, breast, bronchus, trachea and lung, brain and other CNS, biliary passages and liver, prostate, pancreas, and rectum. Furthermore, we focused on specific outcomes for non-Hodgkin's lymphoma and multiple myeloma because of exposure misclassification. The pooling OR for non-Hodgkin's lymphoma and multiple myeloma was 1.42 (95 % CI 1.10-1.83) with moderate degree of heterogeneity among the studies (I (2) = 26.9 %, p = 0.205). We found an excess risk of multiple myeloma. The non-Hodgkin's lymphoma and leukemia that have shown weak effects should be investigated further.

A model for assessing water quality risk in catchments prone to wildfire

NASA Astrophysics Data System (ADS)

Langhans, Christoph; Smith, Hugh; Chong, Derek; Nyman, Petter; Lane, Patrick; Sheridan, Gary

2017-04-01

Post-fire debris flows can have erosion rates up to three orders of magnitude higher than background rates. They are major sources of fine suspended sediment, which is critical to the safety of water supply from forested catchments. Fire can cover parts or all of these large catchments and burn severity is often heterogeneous. The probability of spatial and temporal overlap of fire disturbance and rainfall events, and the susceptibility of hillslopes to severe erosion determine the risk to water quality. Here we present a model to calculate recurrence intervals of high magnitude sediment delivery from runoff-generated debris flows to a reservoir in a large catchment (>100 km2) accounting for heterogeneous burn conditions. Debris flow initiation was modelled with indicators of surface runoff and soil surface erodibility. Debris flow volume was calculated with an empirical model, and fine sediment delivery was calculated using simple, expert-based assumptions. In a Monte-Carlo simulation, wildfire was modelled with a fire spread model using historic data on weather and ignition probabilities for a forested catchment in central Victoria, Australia. Multiple high intensity storms covering the study catchment were simulated using Intensity-Frequency-Duration relationships, and the runoff indicator calculated with a runoff model for hillslopes. A sensitivity analysis showed that fine sediment is most sensitive to variables related to the texture of the source material, debris flow volume estimation, and the proportion of fine sediment transported to the reservoir. As a measure of indirect validation, denudation rates of 4.6 - 28.5 mm ka-1 were estimated and compared well to other studies in the region. From the results it was extrapolated that in the absence of fire management intervention the critical sediment concentrations in the studied reservoir could be exceeded in intervals of 18 - 124 years.

The dynamics of methane emissions in Alaskan peatlands at different trophic levels

NASA Astrophysics Data System (ADS)

Zhang, L.; Liu, X.; Langford, L.; Chanton, J.; Hines, M. E.

2016-12-01

One major uncertainty in estimating methane (CH4) emission from wetlands is extrapolating from highly heterogeneous and inadequately studied local sites to larger scales. The heterogeneity of peatlands comes from contrasting surface vegetation compositions within short distances that are usually associated with different nutrient sources and trophic status. Different microbial communities and metabolic pathways occur at different trophic levels. Stable isotope C ratios (δ13C) have been used as a robust tool to distinguish methanogenic pathways, but different sources of parent compounds (acetate and CO2) with unique δ13C signatures, and unresolved fractionation factors associated with different methanogens, add complexity. To better understand the relationships between trophic status, surface vegetation compositions and methanogenic pathways, 28 peatland sites were studied in Fairbanks and Anchorage, Alaska in the summer of 2015. These sites were ordinated using multiple factor analysis into 3 clusters based on pH, temp, CH4 and volatile fatty acids production rates, δ13C values, and surface vegetation composition. In the low-pH trophic cluster (pH 4.2), Sphagnum fuscum was the dominant species with specific sedges (Ledum decumbens), and primary fermentation rates was slow with no CH4 detected. In the intermediate trophic level (pH 5.3), in which Sphagnum magellanicum was largely present, both hydrogenotrophic (HM) and acetoclastic methanogenesis (AM) were very active. Syntrophy was present at certain sites, which may provide CO2 and acetate with unique δ13C for CH4 production. At the highest pH trophic cluster examined in this study (pH 5.8), Carex tenuiflora, Carex aquatilis, and Sphagnum Squarrosum dominated. CH4 production rates were higher than those in the intermediate cluster and the apparent fractionation factor a was lower.

Comparison of TG-43 and TG-186 in breast irradiation using a low energy electronic brachytherapy source.

PubMed

White, Shane A; Landry, Guillaume; Fonseca, Gabriel Paiva; Holt, Randy; Rusch, Thomas; Beaulieu, Luc; Verhaegen, Frank; Reniers, Brigitte

2014-06-01

The recently updated guidelines for dosimetry in brachytherapy in TG-186 have recommended the use of model-based dosimetry calculations as a replacement for TG-43. TG-186 highlights shortcomings in the water-based approach in TG-43, particularly for low energy brachytherapy sources. The Xoft Axxent is a low energy (<50 kV) brachytherapy system used in accelerated partial breast irradiation (APBI). Breast tissue is a heterogeneous tissue in terms of density and composition. Dosimetric calculations of seven APBI patients treated with Axxent were made using a model-based Monte Carlo platform for a number of tissue models and dose reporting methods and compared to TG-43 based plans. A model of the Axxent source, the S700, was created and validated against experimental data. CT scans of the patients were used to create realistic multi-tissue/heterogeneous models with breast tissue segmented using a published technique. Alternative water models were used to isolate the influence of tissue heterogeneity and backscatter on the dose distribution. Dose calculations were performed using Geant4 according to the original treatment parameters. The effect of the Axxent balloon applicator used in APBI which could not be modeled in the CT-based model, was modeled using a novel technique that utilizes CAD-based geometries. These techniques were validated experimentally. Results were calculated using two dose reporting methods, dose to water (Dw,m) and dose to medium (Dm,m), for the heterogeneous simulations. All results were compared against TG-43-based dose distributions and evaluated using dose ratio maps and DVH metrics. Changes in skin and PTV dose were highlighted. All simulated heterogeneous models showed a reduced dose to the DVH metrics that is dependent on the method of dose reporting and patient geometry. Based on a prescription dose of 34 Gy, the average D90 to PTV was reduced by between ~4% and ~40%, depending on the scoring method, compared to the TG-43 result. Peak skin dose is also reduced by 10%-15% due to the absence of backscatter not accounted for in TG-43. The balloon applicator also contributed to the reduced dose. Other ROIs showed a difference depending on the method of dose reporting. TG-186-based calculations produce results that are different from TG-43 for the Axxent source. The differences depend strongly on the method of dose reporting. This study highlights the importance of backscatter to peak skin dose. Tissue heterogeneities, applicator, and patient geometries demonstrate the need for a more robust dose calculation method for low energy brachytherapy sources.

Modeling the influence of coupled mass transfer processes on mass flux downgradient of heterogeneous DNAPL source zones

NASA Astrophysics Data System (ADS)

Yang, Lurong; Wang, Xinyu; Mendoza-Sanchez, Itza; Abriola, Linda M.

2018-04-01

Sequestered mass in low permeability zones has been increasingly recognized as an important source of organic chemical contamination that acts to sustain downgradient plume concentrations above regulated levels. However, few modeling studies have investigated the influence of this sequestered mass and associated (coupled) mass transfer processes on plume persistence in complex dense nonaqueous phase liquid (DNAPL) source zones. This paper employs a multiphase flow and transport simulator (a modified version of the modular transport simulator MT3DMS) to explore the two- and three-dimensional evolution of source zone mass distribution and near-source plume persistence for two ensembles of highly heterogeneous DNAPL source zone realizations. Simulations reveal the strong influence of subsurface heterogeneity on the complexity of DNAPL and sequestered (immobile/sorbed) mass distribution. Small zones of entrapped DNAPL are shown to serve as a persistent source of low concentration plumes, difficult to distinguish from other (sorbed and immobile dissolved) sequestered mass sources. Results suggest that the presence of DNAPL tends to control plume longevity in the near-source area; for the examined scenarios, a substantial fraction (43.3-99.2%) of plume life was sustained by DNAPL dissolution processes. The presence of sorptive media and the extent of sorption non-ideality are shown to greatly affect predictions of near-source plume persistence following DNAPL depletion, with plume persistence varying one to two orders of magnitude with the selected sorption model. Results demonstrate the importance of sorption-controlled back diffusion from low permeability zones and reveal the importance of selecting the appropriate sorption model for accurate prediction of plume longevity. Large discrepancies for both DNAPL depletion time and plume longevity were observed between 2-D and 3-D model simulations. Differences between 2- and 3-D predictions increased in the presence of sorption, especially for the case of non-ideal sorption, demonstrating the limitations of employing 2-D predictions for field-scale modeling.

Algorithms for differentiating between images of heterogeneous tissue across fluorescence microscopes.

PubMed

Chitalia, Rhea; Mueller, Jenna; Fu, Henry L; Whitley, Melodi Javid; Kirsch, David G; Brown, J Quincy; Willett, Rebecca; Ramanujam, Nimmi

2016-09-01

Fluorescence microscopy can be used to acquire real-time images of tissue morphology and with appropriate algorithms can rapidly quantify features associated with disease. The objective of this study was to assess the ability of various segmentation algorithms to isolate fluorescent positive features (FPFs) in heterogeneous images and identify an approach that can be used across multiple fluorescence microscopes with minimal tuning between systems. Specifically, we show a variety of image segmentation algorithms applied to images of stained tumor and muscle tissue acquired with 3 different fluorescence microscopes. Results indicate that a technique called maximally stable extremal regions followed by thresholding (MSER + Binary) yielded the greatest contrast in FPF density between tumor and muscle images across multiple microscopy systems.

Pacemakers in large arrays of oscillators with nonlocal coupling

NASA Astrophysics Data System (ADS)

Jaramillo, Gabriela; Scheel, Arnd

2016-02-01

We model pacemaker effects of an algebraically localized heterogeneity in a 1 dimensional array of oscillators with nonlocal coupling. We assume the oscillators obey simple phase dynamics and that the array is large enough so that it can be approximated by a continuous nonlocal evolution equation. We concentrate on the case of heterogeneities with positive average and show that steady solutions to the nonlocal problem exist. In particular, we show that these heterogeneities act as a wave source. This effect is not possible in 3 dimensional systems, such as the complex Ginzburg-Landau equation, where the wavenumber of weak sources decays at infinity. To obtain our results we use a series of isomorphisms to relate the nonlocal problem to the viscous eikonal equation. We then use Fredholm properties of the Laplace operator in Kondratiev spaces to obtain solutions to the eikonal equation, and by extension to the nonlocal problem.

Evaluating Spatial Heterogeneity and Environmental Variability Inferred from Branched Glycerol Dialkyl Glycerol Tetraethers (GDGTs) Distribution in Soils from Valles Caldera, New Mexic

NASA Astrophysics Data System (ADS)

Contreras Quintana, S. H.; Werne, J. P.; Brown, E. T.; Halbur, J.; Sinninghe Damsté, , J.; Schouten, S.; Correa-Metrio, A.; Fawcett, P. J.

2014-12-01

Branched glycerol dialkyl glycerol tetraethers (GDGTs) are recently discovered bacterial membrane lipids, ubiquitously present in peat bogs and soils, as well as in rivers, lakes and lake sediments. Their distribution appears to be controlled mainly by soil pH and annual mean air temperature (MAT) and they have been increasingly used as paleoclimate proxies in sedimentary records. In order to validate their application as paleoclimate proxies, it is essential evaluate the influence of small scale environmental variability on their distribution. Initial application of the original soil-based branched GDGT distribution proxy to lacustrine sediments from Valles Caldera, New Mexico (NM) was promising, producing a viable temperature record spanning two glacial/interglacial cycles. In this study, we assess the influence of analytical and spatial soil heterogeneity on the concentration and distribution of 9 branched GDGTs in soils from Valles Caldera, and show how this variability is propagated to MAT and pH estimates using multiple soil-based branched GDGT transfer functions. Our results show that significant differences in the abundance and distribution of branched GDGTs in soil can be observed even within a small area such as Valles Caldera. Although the original MBT-CBT calibration appears to give robust MAT estimates and the newest calibration provides pH estimates in better agreement with modern local soils in Valles Caldera, the environmental heterogeneity (e.g. vegetation type and soil moisture) appears to affect the precision of MAT and pH estimates. Furthermore, the heterogeneity of soils leads to significant variability among samples taken even from within a square meter. While such soil heterogeneity is not unknown (and is typically controlled for by combining multiple samples), this study quantifies heterogeneity relative to branched GDGT-based proxies for the first time, indicating that care must be taken with samples from heterogeneous soils in MAT and pH reconstructions.

Heterogeneity of direct aftershock productivity of the main shock rupture

NASA Astrophysics Data System (ADS)

Guo, Yicun; Zhuang, Jiancang; Hirata, Naoshi; Zhou, Shiyong

2017-07-01

The epidemic type aftershock sequence (ETAS) model is widely used to describe and analyze the clustering behavior of seismicity. Instead of regarding large earthquakes as point sources, the finite-source ETAS model treats them as ruptures that extend in space. Each earthquake rupture consists of many patches, and each patch triggers its own aftershocks isotropically. We design an iterative algorithm to invert the unobserved fault geometry based on the stochastic reconstruction method. This model is applied to analyze the Japan Meteorological Agency (JMA) catalog during 1964-2014. We take six great earthquakes with magnitudes >7.5 after 1980 as finite sources and reconstruct the aftershock productivity patterns on each rupture surface. Comparing results from the point-source ETAS model, we find the following: (1) the finite-source model improves the data fitting; (2) direct aftershock productivity is heterogeneous on the rupture plane; (3) the triggering abilities of M5.4+ events are enhanced; (4) the background rate is higher in the off-fault region and lower in the on-fault region for the Tohoku earthquake, while high probabilities of direct aftershocks distribute all over the source region in the modified model; (5) the triggering abilities of five main shocks become 2-6 times higher after taking the rupture geometries into consideration; and (6) the trends of the cumulative background rate are similar in both models, indicating the same levels of detection ability for seismicity anomalies. Moreover, correlations between aftershock productivity and slip distributions imply that aftershocks within rupture faults are adjustments to coseismic stress changes due to slip heterogeneity.

KaBOB: ontology-based semantic integration of biomedical databases.

PubMed

Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

2015-04-23

The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for formal reasoning over a wealth of integrated biomedical data.

Ownership and ecosystem as sources of spatial heterogeneity in a forested landscape, Wisconsin, USA

Treesearch

Thomas R. Crow; George E. Host; David J. Mladenoff

1999-01-01

The interaction between physical environment and land ownership in creating spatial heterogeneity was studied in largely forested landscapes of northern Wisconsin, USA. A stratified random approach was used in which 2500-ha plots representing two ownerships (National Forest and private non-industrial) were located within two regional ecosystems (extremely well-drained...

Moderating Effects of Aggression on the Associations between Social Withdrawal Subtypes and Peer Difficulties during Early Adolescence

ERIC Educational Resources Information Center

Bowker, Julie C.; Markovic, Andrea; Cogswell, Alex; Raja, Radhi

2012-01-01

Recent research has revealed significant heterogeneity in the peer difficulties associated with social withdrawal subtypes during early adolescence, but little is known about possible sources of that heterogeneity. This study of 194 Indian young adolescents (48% female; 90% Hindu; M age = 13.35 years) evaluated whether the peer adversity related…

Genetic Advances in Autism: Heterogeneity and Convergence on Shared Pathways

PubMed Central

Bill, Brent R.; Geschwind, Daniel H.

2009-01-01

The autism spectrum disorders (ASD) are a heterogeneous set of developmental disorders characterized at their core by deficits in social interaction and communication. Current psychiatric nosology groups this broad set of disorders with strong genetic liability and multiple etiologies into the same diagnostic category. This heterogeneity has challenged genetic analyses. But shared patient resources, genomic technologies, more refined phenotypes, and novel computational approaches have begun to yield dividends in defining the genetic mechanisms at work. Over the last five years, a large number of autism susceptibility loci have emerged, redefining our notion of autism’s etiologies, and reframing how we think about ASD. PMID:19477629

Formation and propagation of Love waves in a surface layer with a P-wave source. Technical report

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

Florence, A.L.; Miller, S.A.

The objective of this research is to investigate experimentally, and support with theoretical calculations, the formation and propagation of Love waves from a P-wave source due to scattering at material heterogeneities. The P-wave source is a spherical piezoelectric crystal cast in a surface layer of rock simulant overlaying a higher impedance granite substrate. Excitation of the piezoelectric crystal with a known voltage applies a spherical compressional pulse of known amplitude to the surrounding medium. Lateral heterogeneities cast in the surface layer convert incident P-wave energy into shear waves. The horizontally polarized shear waves (SH waves) trapped in the surface layermore » wave guide are the Love waves we will measure at the surface.« less

Meta-analysis of the effectiveness of chronic care management for diabetes: investigating heterogeneity in outcomes.

PubMed

Elissen, Arianne M J; Steuten, Lotte M G; Lemmens, Lidwien C; Drewes, Hanneke W; Lemmens, Karin M M; Meeuwissen, Jolanda A C; Baan, Caroline A; Vrijhoef, Hubertus J M

2013-10-01

The study aims to support decision making on how best to redesign diabetes care by investigating three potential sources of heterogeneity in effectiveness across trials of diabetes care management. Medline, CINAHL and PsycInfo were searched for systematic reviews and empirical studies focusing on: (1) diabetes mellitus; (2) adult patients; and (3) interventions consisting of at least two components of the chronic care model (CCM). Systematic reviews were analysed descriptively; empirical studies were meta-analysed. Pooled effect measures were estimated using a meta-regression model that incorporated study quality, length of follow-up and number of intervention components as potential predictors of heterogeneity in effects. Overall, reviews (n = 15) of diabetes care programmes report modest improvements in glycaemic control. Empirical studies (n = 61) show wide-ranging results on HbA1c, systolic blood pressure and guideline adherence. Differences between studies in methodological quality cannot explain this heterogeneity in effects. Variety in length of follow-up can explain (part of) the variability, yet not across all outcomes. Diversity in the number of included intervention components can explain 8-12% of the heterogeneity in effects on HbA1c and systolic blood pressure. The outcomes of chronic care management for diabetes are generally positive, yet differ considerably across trials. The most promising results are attained in studies with limited follow-up (<1 year) and by programmes including more than two CCM components. These factors can, however, explain only part of the heterogeneity in effectiveness between studies. Other potential sources of heterogeneity should be investigated to ensure implementation of evidence-based improvements in diabetes care. © 2012 John Wiley & Sons Ltd.

Isotopic Recorders of Pollution in Heterogeneous Urban Areas

NASA Astrophysics Data System (ADS)

Pataki, D. E.; Cobley, L.; Smith, R. M.; Ehleringer, J. R.; Chritz, K.

2017-12-01

A significant difficulty in quantifying urban pollution lies in the extreme spatial and temporal heterogeneity of cities. Dense sources of both point and non-point source pollution as well as the dynamic role of human activities, which vary over very short time scales and small spatial scales, complicate efforts to establish long-term urban monitoring networks that are relevant at neighborhood, municipal, and regional scales. Fortunately, the natural abundance of isotopes of carbon, nitrogen, and other elements provides a wealth of information about the sources and fate of urban atmospheric pollution. In particular, soils and plant material integrate pollution sources and cycling over space and time, and have the potential to provide long-term records of pollution dynamics that extend back before atmospheric monitoring data are available. Similarly, sampling organic material at high spatial resolution can provide "isoscapes" that shed light on the spatial heterogeneity of pollutants in different urban parcels and neighborhoods, along roads of varying traffic density, and across neighborhoods of varying affluence and sociodemographic composition. We have compiled numerous datasets of the isotopic composition of urban organic matter that illustrate the potential for isotopic monitoring of urban areas as a means of understanding hot spots and hot moments in urban atmospheric biogeochemistry. Findings to date already reveal the critical role of affluence, economic activity, demographic change, and land management practices in influencing urban pollution sources and sinks, and suggest an important role of stable isotope and radioisotope measurements in urban atmospheric and biogeochemical monitoring.

Sources of secondary organic aerosols over North China Plain in winter

NASA Astrophysics Data System (ADS)

Xing, L.; Li, G.; Tie, X.; Junji, C.; Long, X.

2017-12-01

Organic aerosol (OA) concentrations are simulated over the North China Plain (NCP) from 10th to 26th January, 2014 using the Weather Research and Forecasting model coupled to chemistry (WRF-CHEM), with the goal of examining the impact of heterogeneous HONO sources on atmospheric oxidation capacity and consequently on SOA formation and SOA formation from different pathways in winter. Generally, the model well reproduced the spatial and temporal distribution of PM2.5, SO2, NO2, and O3 concentrations. The heterogeneous HONO formation contributed a major part of atmospheric HONO concentrations in Beijing. The heterogeneous HONO sources significantly increased the daily maximum OH concentrations by 260% on average in Beijing, which enhanced the atmospheric oxidation capacity and consequently SOA concentrations by 80% in Beijing on average. Under severe haze pollution on January 16th 2014, the regional average HONO concentration over NCP was 0.86 ppb, which increased SOA concentration by 68% on average. The average mass fractions of ASOA (SOA from oxidation of anthropogenic VOCs), BSOA (SOA from oxidation of biogenic VOCs), PSOA (SOA from oxidation of evaporated POA), and GSOA (SOA from irreversible uptake of glyoxal and methylglyoxal) during the simulation period over NCP were 24%, 5%, 26% and 45%, respectively. GSOA contributed most to the total SOA mass over NCP in winter. The model sensitivity simulation revealed that GSOA in winter was mainly from primary residential sources. The regional average of GSOA from primary residential sources constituted 87% of total GSOA mass.

Monitoring well utility in a heterogeneous DNAPL source zone area: Insights from proximal multilevel sampler wells and sampling capture-zone modelling

NASA Astrophysics Data System (ADS)

McMillan, Lindsay A.; Rivett, Michael O.; Wealthall, Gary P.; Zeeb, Peter; Dumble, Peter

2018-03-01

Groundwater-quality assessment at contaminated sites often involves the use of short-screen (1.5 to 3 m) monitoring wells. However, even over these intervals considerable variation may occur in contaminant concentrations in groundwater adjacent to the well screen. This is especially true in heterogeneous dense non-aqueous phase liquid (DNAPL) source zones, where cm-scale contamination variability may call into question the effectiveness of monitoring wells to deliver representative data. The utility of monitoring wells in such settings is evaluated by reference to high-resolution multilevel sampler (MLS) wells located proximally to short-screen wells, together with sampling capture-zone modelling to explore controls upon well sample provenance and sensitivity to monitoring protocols. Field data are analysed from the highly instrumented SABRE research site that contained an old trichloroethene source zone within a shallow alluvial aquifer at a UK industrial facility. With increased purging, monitoring-well samples tend to a flow-weighted average concentration but may exhibit sensitivity to the implemented protocol and degree of purging. Formation heterogeneity adjacent to the well-screen particularly, alongside pump-intake position and water level, influence this sensitivity. Purging of low volumes is vulnerable to poor reproducibility arising from concentration variability predicted over the initial 1 to 2 screen volumes purged. Marked heterogeneity may also result in limited long-term sample concentration stabilization. Development of bespoke monitoring protocols, that consider screen volumes purged, alongside water-quality indicator parameter stabilization, is recommended to validate and reduce uncertainty when interpreting monitoring-well data within source zone areas. Generalised recommendations on monitoring well based protocols are also developed. A key monitoring well utility is their proportionately greater sample draw from permeable horizons constituting a significant contaminant flux pathway and hence representative fraction of source mass flux. Acquisition of complementary, high-resolution, site monitoring data, however, vitally underpins optimal interpretation of monitoring-well datasets and appropriate advancement of a site conceptual model and remedial implementation.

Effect of multiple-source entry on price competition after patent expiration in the pharmaceutical industry.

PubMed Central

Suh, D C; Manning, W G; Schondelmeyer, S; Hadsall, R S

2000-01-01

OBJECTIVE: To analyze the effect of multiple-source drug entry on price competition after patent expiration in the pharmaceutical industry. DATA SOURCES: Originators and their multiple-source drugs selected from the 35 chemical entities whose patents expired from 1984 through 1987. Data were obtained from various primary and secondary sources for the patents' expiration dates, sales volume and units sold, and characteristics of drugs in the sample markets. STUDY DESIGN: The study was designed to determine significant factors using the study model developed under the assumption that the off-patented market is an imperfectly segmented market. PRINCIPAL FINDINGS: After patent expiration, the originators' prices continued to increase, while the price of multiple-source drugs decreased significantly over time. By the fourth year after patent expiration, originators' sales had decreased 12 percent in dollars and 30 percent in quantity. Multiple-source drugs increased their sales twofold in dollars and threefold in quantity, and possessed about one-fourth (in dollars) and half (in quantity) of the total market three years after entry. CONCLUSION: After patent expiration, multiple-source drugs compete largely with other multiple-source drugs in the price-sensitive sector, but indirectly with the originator in the price-insensitive sector. Originators have first-mover advantages, and therefore have a market that is less price sensitive after multiple-source drugs enter. On the other hand, multiple-source drugs target the price-sensitive sector, using their lower-priced drugs. This trend may indicate that the off-patented market is imperfectly segmented between the price-sensitive and insensitive sector. Consumers as a whole can gain from the entry of multiple-source drugs because the average price of the market continually declines after patent expiration. PMID:10857475

Orchestrating Distributed Resource Ensembles for Petascale Science

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

Baldin, Ilya; Mandal, Anirban; Ruth, Paul

2014-04-24

Distributed, data-intensive computational science applications of interest to DOE scientific com- munities move large amounts of data for experiment data management, distributed analysis steps, remote visualization, and accessing scientific instruments. These applications need to orchestrate ensembles of resources from multiple resource pools and interconnect them with high-capacity multi- layered networks across multiple domains. It is highly desirable that mechanisms are designed that provide this type of resource provisioning capability to a broad class of applications. It is also important to have coherent monitoring capabilities for such complex distributed environments. In this project, we addressed these problems by designing an abstractmore » API, enabled by novel semantic resource descriptions, for provisioning complex and heterogeneous resources from multiple providers using their native provisioning mechanisms and control planes: computational, storage, and multi-layered high-speed network domains. We used an extensible resource representation based on semantic web technologies to afford maximum flexibility to applications in specifying their needs. We evaluated the effectiveness of provisioning using representative data-intensive ap- plications. We also developed mechanisms for providing feedback about resource performance to the application, to enable closed-loop feedback control and dynamic adjustments to resource allo- cations (elasticity). This was enabled through development of a novel persistent query framework that consumes disparate sources of monitoring data, including perfSONAR, and provides scalable distribution of asynchronous notifications.« less

Legacies of Lead in Charm City’s Soil: Lessons from the Baltimore Ecosystem Study

PubMed Central

Schwarz, Kirsten; Pouyat, Richard V.; Yesilonis, Ian

2016-01-01

Understanding the spatial distribution of soil lead has been a focus of the Baltimore Ecosystem Study since its inception in 1997. Through multiple research projects that span spatial scales and use different methodologies, three overarching patterns have been identified: (1) soil lead concentrations often exceed state and federal regulatory limits; (2) the variability of soil lead concentrations is high; and (3) despite multiple sources and the highly heterogeneous and patchy nature of soil lead, discernable patterns do exist. Specifically, housing age, the distance to built structures, and the distance to a major roadway are strong predictors of soil lead concentrations. Understanding what drives the spatial distribution of soil lead can inform the transition of underutilized urban space into gardens and other desirable land uses while protecting human health. A framework for management is proposed that considers three factors: (1) the level of contamination; (2) the desired land use; and (3) the community’s preference in implementing the desired land use. The goal of the framework is to promote dialogue and resultant policy changes that support consistent and clear regulatory guidelines for soil lead, without which urban communities will continue to be subject to the potential for lead exposure. PMID:26861371

What contributes to disparities in the preterm birth rate in European countries?

PubMed Central

Delnord, Marie; Blondel, Béatrice; Zeitlin, Jennifer

2015-01-01

Purpose of review In countries with comparable levels of development and healthcare systems, preterm birth rates vary markedly – a range from 5 to 10% among live births in Europe. This review seeks to identify the most likely sources of heterogeneity in preterm birth rates, which could explain differences between European countries. Recent findings Multiple risk factors impact on preterm birth. Recent studies reported on measurement issues, population characteristics, reproductive health policies as well as medical practices, including those related to subfertility treatments and indicated deliveries, which affect preterm birth rates and trends in high-income countries. We showed wide variation in population characteristics, including multiple pregnancies, maternal age, BMI, smoking, and percentage of migrants in European countries. Summary Many potentially modifiable population factors (BMI, smoking, and environmental exposures) as well as health system factors (practices related to indicated preterm deliveries) play a role in determining preterm birth risk. More knowledge about how these factors contribute to low and stable preterm birth rates in some countries is needed for shaping future policy. It is also important to clarify the potential contribution of artifactual differences owing to measurement. PMID:25692506

A reproducible approach to high-throughput biological data acquisition and integration

PubMed Central

Rahnavard, Gholamali; Waldron, Levi; McIver, Lauren; Shafquat, Afrah; Franzosa, Eric A.; Miropolsky, Larissa; Sweeney, Christopher

2015-01-01

Modern biological research requires rapid, complex, and reproducible integration of multiple experimental results generated both internally and externally (e.g., from public repositories). Although large systematic meta-analyses are among the most effective approaches both for clinical biomarker discovery and for computational inference of biomolecular mechanisms, identifying, acquiring, and integrating relevant experimental results from multiple sources for a given study can be time-consuming and error-prone. To enable efficient and reproducible integration of diverse experimental results, we developed a novel approach for standardized acquisition and analysis of high-throughput and heterogeneous biological data. This allowed, first, novel biomolecular network reconstruction in human prostate cancer, which correctly recovered and extended the NFκB signaling pathway. Next, we investigated host-microbiome interactions. In less than an hour of analysis time, the system retrieved data and integrated six germ-free murine intestinal gene expression datasets to identify the genes most influenced by the gut microbiota, which comprised a set of immune-response and carbohydrate metabolism processes. Finally, we constructed integrated functional interaction networks to compare connectivity of peptide secretion pathways in the model organisms Escherichia coli, Bacillus subtilis, and Pseudomonas aeruginosa. PMID:26157642

Measurements and simulations of the optical gain and anti-reflection coating modal reflectivity in quantum cascade lasers with multiple active region stacks

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

Bidaux, Y., E-mail: yves.bidaux@alpeslasers.ch; Alpes Lasers SA, 1-3 Maximilien-de-Meuron, CH-2000 Neuchatel; Terazzi, R.

2015-09-07

We report spectrally resolved gain measurements and simulations for quantum cascade lasers (QCLs) composed of multiple heterogeneous stacks designed for broadband emission in the mid-infrared. The measurement method is first demonstrated on a reference single active region QCL based on a double-phonon resonance design emitting at 7.8 μm. It is then extended to a three-stack active region based on bound-to-continuum designs with a broadband emission range from 7.5 to 10.5 μm. A tight agreement is found with simulations based on a density matrix model. The latter implements exhaustive microscopic scattering and dephasing sources with virtually no fitting parameters. The quantitative agreement ismore » furthermore assessed by measuring gain coefficients obtained by studying the threshold current dependence with the cavity length. These results are particularly relevant to understand fundamental gain mechanisms in complex semiconductor heterostructure QCLs and to move towards efficient gain engineering. Finally, the method is extended to the measurement of the modal reflectivity of an anti-reflection coating deposited on the front facet of the broadband QCL.« less

Top 10 Research Questions Related to Physical Activity and Multiple Sclerosis

ERIC Educational Resources Information Center

Motl, Robert W.; Learmonth, Yvonne C.; Pilutti, Lara A.; Gappmaier, Eduard; Coote, Susan

2015-01-01

An estimated 2.5 million people worldwide are living with multiple sclerosis (MS), and this disease may be increasing in prevalence. MS is a disease of the central nervous system that is associated with heterogeneous symptoms and functional consequences, and the current first-line disease-modifying therapies often become ineffective later in the…

A distributed data base management facility for the CAD/CAM environment

NASA Technical Reports Server (NTRS)

Balza, R. M.; Beaudet, R. W.; Johnson, H. R.

1984-01-01

Current/PAD research in the area of distributed data base management considers facilities for supporting CAD/CAM data management in a heterogeneous network of computers encompassing multiple data base managers supporting a variety of data models. These facilities include coordinated execution of multiple DBMSs to provide for administration of and access to data distributed across them.

DServO: A Peer-to-Peer-based Approach to Biomedical Ontology Repositories.

PubMed

Mambone, Zakaria; Savadogo, Mahamadi; Some, Borlli Michel Jonas; Diallo, Gayo

2015-01-01

We present in this poster an extension of the ServO ontology server system, which adopts a decentralized Peer-To-Peer approach for managing multiple heterogeneous knowledge organization systems. It relies on the use of the JXTA protocol coupled with information retrieval techniques to provide a decentralized infrastructure for managing multiples instances of Ontology Repositories.

A Strategy for Detection of Inconsistency in Evaluation of Essay Type Answers

ERIC Educational Resources Information Center

Shukla, Archana; Chaudhary, Banshi D.

2014-01-01

The quality of evaluation of essay type answer books involving multiple evaluators for courses with large number of enrollments is likely to be affected due to heterogeneity in experience, expertise and maturity of evaluators. In this paper, we present a strategy to detect anomalies in evaluation of essay type answers by multiple evaluators based…

A Revised Version of the Norwegian Adaptation of the Test Anxiety Inventory in a Heterogeneous Population

ERIC Educational Resources Information Center

Oktedalen, Tuva; Hagtvet, Knut A.

2011-01-01

Confirmatory factor analysis and Multiple Indicators, Multiple Causes (MIMIC) modeling were employed to investigate psychometric properties of a revised adaptation of the Norwegian version of the Test Anxiety Inventory (RTAIN) in a sample of 456 students. The study supported the Norwegian version as a useful inventory for measuring the components…

Effects of Heterogeneous Diffuse Fibrosis on Arrhythmia Dynamics and Mechanism

PubMed Central

Kazbanov, Ivan V.; ten Tusscher, Kirsten H. W. J.; Panfilov, Alexander V.

2016-01-01

Myocardial fibrosis is an important risk factor for cardiac arrhythmias. Previous experimental and numerical studies have shown that the texture and spatial distribution of fibrosis may play an important role in arrhythmia onset. Here, we investigate how spatial heterogeneity of fibrosis affects arrhythmia onset using numerical methods. We generate various tissue textures that differ by the mean amount of fibrosis, the degree of heterogeneity and the characteristic size of heterogeneity. We study the onset of arrhythmias using a burst pacing protocol. We confirm that spatial heterogeneity of fibrosis increases the probability of arrhythmia induction. This effect is more pronounced with the increase of both the spatial size and the degree of heterogeneity. The induced arrhythmias have a regular structure with the period being mostly determined by the maximal local fibrosis level. We perform ablations of the induced fibrillatory patterns to classify their type. We show that in fibrotic tissue fibrillation is usually of the mother rotor type but becomes of the multiple wavelet type with increase in tissue size. Overall, we conclude that the most important factor determining the formation and dynamics of arrhythmia in heterogeneous fibrotic tissue is the value of maximal local fibrosis. PMID:26861111

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

Shang, Yu; Yu, Guoqiang, E-mail: guoqiang.yu@uky.edu

Conventional semi-infinite analytical solutions of correlation diffusion equation may lead to errors when calculating blood flow index (BFI) from diffuse correlation spectroscopy (DCS) measurements in tissues with irregular geometries. Very recently, we created an algorithm integrating a Nth-order linear model of autocorrelation function with the Monte Carlo simulation of photon migrations in homogenous tissues with arbitrary geometries for extraction of BFI (i.e., αD{sub B}). The purpose of this study is to extend the capability of the Nth-order linear algorithm for extracting BFI in heterogeneous tissues with arbitrary geometries. The previous linear algorithm was modified to extract BFIs in different typesmore » of tissues simultaneously through utilizing DCS data at multiple source-detector separations. We compared the proposed linear algorithm with the semi-infinite homogenous solution in a computer model of adult head with heterogeneous tissue layers of scalp, skull, cerebrospinal fluid, and brain. To test the capability of the linear algorithm for extracting relative changes of cerebral blood flow (rCBF) in deep brain, we assigned ten levels of αD{sub B} in the brain layer with a step decrement of 10% while maintaining αD{sub B} values constant in other layers. Simulation results demonstrate the accuracy (errors < 3%) of high-order (N ≥ 5) linear algorithm in extracting BFIs in different tissue layers and rCBF in deep brain. By contrast, the semi-infinite homogenous solution resulted in substantial errors in rCBF (34.5% ≤ errors ≤ 60.2%) and BFIs in different layers. The Nth-order linear model simplifies data analysis, thus allowing for online data processing and displaying. Future study will test this linear algorithm in heterogeneous tissues with different levels of blood flow variations and noises.« less

3D heterogeneous islet organoid generation from human embryonic stem cells using a novel engineered hydrogel platform.

PubMed

Candiello, Joseph; Grandhi, Taraka Sai Pavan; Goh, Saik Kia; Vaidya, Vimal; Lemmon-Kishi, Maya; Eliato, Kiarash Rahmani; Ros, Robert; Kumta, Prashant N; Rege, Kaushal; Banerjee, Ipsita

2018-05-25

Organoids, which exhibit spontaneous organ specific organization, function, and multi-cellular complexity, are in essence the in vitro reproduction of specific in vivo organ systems. Recent work has demonstrated human pluripotent stem cells (hPSCs) as a viable regenerative cell source for tissue-specific organoid engineering. This is especially relevant for engineering islet organoids, due to the recent advances in generating functional beta-like cells from human pluripotent stem cells. In this study, we report specific engineering of regenerative islet organoids of precise size and cellular heterogeneity, using a novel hydrogel system, Amikagel. Amikagel facilitated controlled and spontaneous aggregation of human embryonic stem cell derived pancreatic progenitor cells (hESC-PP) into robust homogeneous spheroids. This platform further allowed fine control over the integration of multiple cell populations to produce heterogeneous spheroids, which is a necessity for complex organoid engineering. Amikagel induced hESC-PP spheroid formation enhanced pancreatic islet-specific Pdx-1 and NKX6.1 gene and protein expression, while also increasing the percentage of committed population. hESC-PP spheroids were further induced towards mature beta-like cells which demonstrated increased Beta-cell specific INS1 gene and C-peptide protein expression along with functional insulin production in response to in vitro glucose challenge. Further integration of hESC-PP with biologically relevant supporting endothelial cells resulted in multicellular organoids which demonstrated spontaneous maturation towards islet-specific INS1 gene and C-peptide protein expression along with a significantly developed extracellular matrix support system. These findings establish Amikagel -facilitated platform ideal for islet organoid engineering. Copyright © 2018. Published by Elsevier Ltd.

The Stanford Data Miner: a novel approach for integrating and exploring heterogeneous immunological data.

PubMed

Siebert, Janet C; Munsil, Wes; Rosenberg-Hasson, Yael; Davis, Mark M; Maecker, Holden T

2012-03-28

Systems-level approaches are increasingly common in both murine and human translational studies. These approaches employ multiple high information content assays. As a result, there is a need for tools to integrate heterogeneous types of laboratory and clinical/demographic data, and to allow the exploration of that data by aggregating and/or segregating results based on particular variables (e.g., mean cytokine levels by age and gender). Here we describe the application of standard data warehousing tools to create a novel environment for user-driven upload, integration, and exploration of heterogeneous data. The system presented here currently supports flow cytometry and immunoassays performed in the Stanford Human Immune Monitoring Center, but could be applied more generally. Users upload assay results contained in platform-specific spreadsheets of a defined format, and clinical and demographic data in spreadsheets of flexible format. Users then map sample IDs to connect the assay results with the metadata. An OLAP (on-line analytical processing) data exploration interface allows filtering and display of various dimensions (e.g., Luminex analytes in rows, treatment group in columns, filtered on a particular study). Statistics such as mean, median, and N can be displayed. The views can be expanded or contracted to aggregate or segregate data at various levels. Individual-level data is accessible with a single click. The result is a user-driven system that permits data integration and exploration in a variety of settings. We show how the system can be used to find gender-specific differences in serum cytokine levels, and compare them across experiments and assay types. We have used the tools and techniques of data warehousing, including open-source business intelligence software, to support investigator-driven data integration and mining of diverse immunological data.

HIV promoter integration site primarily modulates transcriptional burst size rather than frequency.

PubMed

Skupsky, Ron; Burnett, John C; Foley, Jonathan E; Schaffer, David V; Arkin, Adam P

2010-09-30

Mammalian gene expression patterns, and their variability across populations of cells, are regulated by factors specific to each gene in concert with its surrounding cellular and genomic environment. Lentiviruses such as HIV integrate their genomes into semi-random genomic locations in the cells they infect, and the resulting viral gene expression provides a natural system to dissect the contributions of genomic environment to transcriptional regulation. Previously, we showed that expression heterogeneity and its modulation by specific host factors at HIV integration sites are key determinants of infected-cell fate and a possible source of latent infections. Here, we assess the integration context dependence of expression heterogeneity from diverse single integrations of a HIV-promoter/GFP-reporter cassette in Jurkat T-cells. Systematically fitting a stochastic model of gene expression to our data reveals an underlying transcriptional dynamic, by which multiple transcripts are produced during short, infrequent bursts, that quantitatively accounts for the wide, highly skewed protein expression distributions observed in each of our clonal cell populations. Interestingly, we find that the size of transcriptional bursts is the primary systematic covariate over integration sites, varying from a few to tens of transcripts across integration sites, and correlating well with mean expression. In contrast, burst frequencies are scattered about a typical value of several per cell-division time and demonstrate little correlation with the clonal means. This pattern of modulation generates consistently noisy distributions over the sampled integration positions, with large expression variability relative to the mean maintained even for the most productive integrations, and could contribute to specifying heterogeneous, integration-site-dependent viral production patterns in HIV-infected cells. Genomic environment thus emerges as a significant control parameter for gene expression variation that may contribute to structuring mammalian genomes, as well as be exploited for survival by integrating viruses.

Mixing-dependent Reactions in the Hyporheic Zone: Laboratory and Numerical Experiments

NASA Astrophysics Data System (ADS)

Santizo, K. Y.; Eastes, L. A.; Hester, E. T.; Widdowson, M.

2017-12-01

The hyporheic zone is the surface water-groundwater interface surrounding the river's perimeter. Prior research demonstrates the ability of the hyporheic zone to attenuate pollutants when surface water cycles through reactive sediments (non-mixing-dependent reactions). However, the colocation of both surface and ground water within hyporheic sediments also allows mixing-dependent reactions that require mixing of reactants from these two water sources. Recent modeling studies show these mixing zones can be small under steady state homogeneous conditions, but do not validate those results in the laboratory or explore the range of hydrological characteristics that control the extent of mixing. Our objective was to simulate the mixing zone, quantify its thickness, and probe its hydrological controls using a "mix" of laboratory and numerical experiments. For the lab experiments, a hyporheic zone was simulated in a sand mesocosm, and a mixing-dependent abiotic reaction of sodium sulfite and dissolved oxygen was induced. Oxygen concentration response and oxygen consumption were visualized via planar optodes. Sulfate production by the mixing-dependent reaction was measured by fluid samples and a spectrophometer. Key hydrologic controls varied in the mesocosm included head gradient driving hyporheic exchange and hydraulic conductivity/heterogeneity. Results show a clear mixing area, sulfate production, and oxygen gradient. Mixing zone length (hyporheic flow cell size) and thickness both increase with the driving head gradient. For the numerical experiments, transient surface water boundary conditions were implemented together with heterogeneity of hydraulic conductivity. Results indicate that both fluctuating boundary conditions and heterogeneity increase mixing-dependent reaction. The hyporheic zone is deemed an attenuation hotspot by multiple studies, but here we demonstrate its potential for mixing-dependent reactions and the influence of important hydrological parameters.

The Stanford Data Miner: a novel approach for integrating and exploring heterogeneous immunological data

PubMed Central

2012-01-01

Background Systems-level approaches are increasingly common in both murine and human translational studies. These approaches employ multiple high information content assays. As a result, there is a need for tools to integrate heterogeneous types of laboratory and clinical/demographic data, and to allow the exploration of that data by aggregating and/or segregating results based on particular variables (e.g., mean cytokine levels by age and gender). Methods Here we describe the application of standard data warehousing tools to create a novel environment for user-driven upload, integration, and exploration of heterogeneous data. The system presented here currently supports flow cytometry and immunoassays performed in the Stanford Human Immune Monitoring Center, but could be applied more generally. Results Users upload assay results contained in platform-specific spreadsheets of a defined format, and clinical and demographic data in spreadsheets of flexible format. Users then map sample IDs to connect the assay results with the metadata. An OLAP (on-line analytical processing) data exploration interface allows filtering and display of various dimensions (e.g., Luminex analytes in rows, treatment group in columns, filtered on a particular study). Statistics such as mean, median, and N can be displayed. The views can be expanded or contracted to aggregate or segregate data at various levels. Individual-level data is accessible with a single click. The result is a user-driven system that permits data integration and exploration in a variety of settings. We show how the system can be used to find gender-specific differences in serum cytokine levels, and compare them across experiments and assay types. Conclusions We have used the tools and techniques of data warehousing, including open-source business intelligence software, to support investigator-driven data integration and mining of diverse immunological data. PMID:22452993

Multiple imputation for IPD meta-analysis: allowing for heterogeneity and studies with missing covariates.

PubMed

Quartagno, M; Carpenter, J R

2016-07-30

Recently, multiple imputation has been proposed as a tool for individual patient data meta-analysis with sporadically missing observations, and it has been suggested that within-study imputation is usually preferable. However, such within study imputation cannot handle variables that are completely missing within studies. Further, if some of the contributing studies are relatively small, it may be appropriate to share information across studies when imputing. In this paper, we develop and evaluate a joint modelling approach to multiple imputation of individual patient data in meta-analysis, with an across-study probability distribution for the study specific covariance matrices. This retains the flexibility to allow for between-study heterogeneity when imputing while allowing (i) sharing information on the covariance matrix across studies when this is appropriate, and (ii) imputing variables that are wholly missing from studies. Simulation results show both equivalent performance to the within-study imputation approach where this is valid, and good results in more general, practically relevant, scenarios with studies of very different sizes, non-negligible between-study heterogeneity and wholly missing variables. We illustrate our approach using data from an individual patient data meta-analysis of hypertension trials. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd. © 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Sparse Group Penalized Integrative Analysis of Multiple Cancer Prognosis Datasets

PubMed Central

Liu, Jin; Huang, Jian; Xie, Yang; Ma, Shuangge

2014-01-01

SUMMARY In cancer research, high-throughput profiling studies have been extensively conducted, searching for markers associated with prognosis. Because of the “large d, small n” characteristic, results generated from the analysis of a single dataset can be unsatisfactory. Recent studies have shown that integrative analysis, which simultaneously analyzes multiple datasets, can be more effective than single-dataset analysis and classic meta-analysis. In most of existing integrative analysis, the homogeneity model has been assumed, which postulates that different datasets share the same set of markers. Several approaches have been designed to reinforce this assumption. In practice, different datasets may differ in terms of patient selection criteria, profiling techniques, and many other aspects. Such differences may make the homogeneity model too restricted. In this study, we assume the heterogeneity model, under which different datasets are allowed to have different sets of markers. With multiple cancer prognosis datasets, we adopt the AFT (accelerated failure time) model to describe survival. This model may have the lowest computational cost among popular semiparametric survival models. For marker selection, we adopt a sparse group MCP (minimax concave penalty) approach. This approach has an intuitive formulation and can be computed using an effective group coordinate descent algorithm. Simulation study shows that it outperforms the existing approaches under both the homogeneity and heterogeneity models. Data analysis further demonstrates the merit of heterogeneity model and proposed approach. PMID:23938111

Criticality and Induction Time of Hot Spots in Detonating Heterogeneous Explosives

NASA Astrophysics Data System (ADS)

Hill, Larry

2017-06-01

Detonation reaction in physically heterogeneous explosives is-to an extent that depends on multiple material attributes-likewise heterogeneous. Like all heterogeneous reaction, detonation heterogeneous reaction begins at nucleation sites, which, in this case, comprise localized regions of higher-than-average temperature-so-called hot spots. Burning grows at, and then spreads from these nucleation sites, via reactive-thermal (R-T) waves, to consume the interstitial material. Not all hot spots are consequential, but only those that are 1) supercritical, and 2) sufficiently so as to form R-T waves before being consumed by those already emanating from neighboring sites. I explore aspects of these two effects by deriving simple formulae for hot spot criticality and the induction time of supercritical hot spots. These results serve to illustrate the non-intuitive, yet mathematically simplifying, effects of extreme dependence of reaction rate upon temperature. They can play a role in the development of better reactive burn models, for which we seek to homogenize the essentials of heterogeneous detonation reaction without introducing spurious complexity. Work supported by the US Dept. of Energy.

Amniotic-Fluid Stem Cells: Growth Dynamics and Differentiation Potential after a CD-117-Based Selection Procedure

PubMed Central

Arnhold, S.; Glüer, S.; Hartmann, K.; Raabe, O.; Addicks, K.; Wenisch, S.; Hoopmann, M.

2011-01-01

Amniotic fluid (AF) has become an interesting source of fetal stem cells. However, AF contains heterogeneous and multiple, partially differentiated cell types. After isolation from the amniotic fluid, cells were characterized regarding their morphology and growth dynamics. They were sorted by magnetic associated cell sorting using the surface marker CD 117. In order to show stem cell characteristics such as pluripotency and to evaluate a possible therapeutic application of these cells, AF fluid-derived stem cells were differentiated along the adipogenic, osteogenic, and chondrogenic as well as the neuronal lineage under hypoxic conditions. Our findings reveal that magnetic associated cell sorting (MACS) does not markedly influence growth characteristics as demonstrated by the generation doubling time. There was, however, an effect regarding an altered adipogenic, osteogenic, and chondrogenic differentiation capacity in the selected cell fraction. In contrast, in the unselected cell population neuronal differentiation is enhanced. PMID:21437196

The Evolution of the Stem Cell Theory for Heart Failure.

PubMed

Silvestre, Jean-Sébastien; Menasché, Philippe

2015-12-01

Various stem cell-based approaches for cardiac repair have achieved encouraging results in animal experiments, often leading to their rapid proceeding to clinical testing. However, freewheeling evolutionary developments of the stem cell theory might lead to dystopian scenarios where heterogeneous sources of therapeutic cells could promote mixed clinical outcomes in un-stratified patient populations. This review focuses on the lessons that should be learnt from the first generation of stem cell-based strategies and emphasizes the absolute requirement to better understand the basic mechanisms of stem cell biology and cardiogenesis. We will also discuss about the unexpected "big bang" in the stem cell theory, "blasting" the therapeutic cells to their unchallenged ability to release paracrine factors such as extracellular membrane vesicles. Paradoxically, the natural evolution of the stem cell theory for cardiac regeneration may end with the development of cell-free strategies with multiple cellular targets including cardiomyocytes but also other infiltrating or resident cardiac cells.

Querying and Extracting Timeline Information from Road Traffic Sensor Data

PubMed Central

Imawan, Ardi; Indikawati, Fitri Indra; Kwon, Joonho; Rao, Praveen

2016-01-01

The escalation of traffic congestion in urban cities has urged many countries to use intelligent transportation system (ITS) centers to collect historical traffic sensor data from multiple heterogeneous sources. By analyzing historical traffic data, we can obtain valuable insights into traffic behavior. Many existing applications have been proposed with limited analysis results because of the inability to cope with several types of analytical queries. In this paper, we propose the QET (querying and extracting timeline information) system—a novel analytical query processing method based on a timeline model for road traffic sensor data. To address query performance, we build a TQ-index (timeline query-index) that exploits spatio-temporal features of timeline modeling. We also propose an intuitive timeline visualization method to display congestion events obtained from specified query parameters. In addition, we demonstrate the benefit of our system through a performance evaluation using a Busan ITS dataset and a Seattle freeway dataset. PMID:27563900

Biological data warehousing system for identifying transcriptional regulatory sites from gene expressions of microarray data.

PubMed

Tsou, Ann-Ping; Sun, Yi-Ming; Liu, Chia-Lin; Huang, Hsien-Da; Horng, Jorng-Tzong; Tsai, Meng-Feng; Liu, Baw-Juine

2006-07-01

Identification of transcriptional regulatory sites plays an important role in the investigation of gene regulation. For this propose, we designed and implemented a data warehouse to integrate multiple heterogeneous biological data sources with data types such as text-file, XML, image, MySQL database model, and Oracle database model. The utility of the biological data warehouse in predicting transcriptional regulatory sites of coregulated genes was explored using a synexpression group derived from a microarray study. Both of the binding sites of known transcription factors and predicted over-represented (OR) oligonucleotides were demonstrated for the gene group. The potential biological roles of both known nucleotides and one OR nucleotide were demonstrated using bioassays. Therefore, the results from the wet-lab experiments reinforce the power and utility of the data warehouse as an approach to the genome-wide search for important transcription regulatory elements that are the key to many complex biological systems.

Influence of Silver and Gold Nanoparticles and Thin Layers on Charge Carrier Generation in InGaN/GaN Multiple Quantum Well Structures and Crystalline Zinc Oxide Films

NASA Astrophysics Data System (ADS)

Mezdrogina, M. M.; Vinogradov, A. Ya.; Kozhanova, Yu. V.; Levitskii, V. S.

2018-04-01

It has been shown that Ag and Au nanoparticles and thin layers influence charge carrier generation in InGaN/GaN multiple quantum well structures and crystalline ZnO films owing to the surface morphology heterogeneity of the semiconductors. When nanoparticles 10 < d < 20 nm in size are applied on InGaN/GaN multiple quantum well structures with surface morphology less nonuniform than that of ZnO films, the radiation intensity has turned out to grow considerably because of a plasmon resonance with the participation of localized plasmons. The application of Ag or Au layers on the surface of the structures strongly attenuates the radiation. When Ag and Au nanoparticles are applied on crystalline ZnO films obtained by rf magnetron sputtering, the radiation intensity in the short-wavelength part of the spectrum increases insignificantly because of their highly heterogeneous surface morphology.

High-risk multiple myeloma: a multifaceted entity, multiple therapeutic challenges.

PubMed

Muchtar, Eli; Magen, Hila; Gertz, Morie A

2017-06-01

The term high-risk multiple myeloma is aimed to identify a heterogeneous group of patients who are more likely to progress and die early of their disease. Therefore, recognition of these patients is crucial. With the increase in the number of treatment options, the outcome for high-risk patients has probably improved, although the true extent of this improvement remains unknown, due to both the heterogeneous components of high-risk disease and its under-representation in clinical trials. In this article, we review the definitions of high-risk disease, emphasizing the fact that no single definition can represent the entire high-risk population. In the second part, we review the treatment options available for the management of high-risk myeloma as well as our general approach for high-risk disease. In light of the poor prognosis associated with high-risk myeloma, even in the current era, new approaches for the management of this subset of patients are needed.

Multiscale Modelling of Cancer Progression and Treatment Control: The Role of Intracellular Heterogeneities in Chemotherapy Treatment

NASA Astrophysics Data System (ADS)

Chaplain, Mark A. J.; Powathil, Gibin G.

Cancer is a complex, multiscale process involving interactions at intracellular, intercellular and tissue scales that are in turn susceptible to microenvironmental changes. Each individual cancer cell within a cancer cell mass is unique, with its own internal cellular pathways and biochemical interactions. These interactions contribute to the functional changes at the cellular and tissue scale, creating a heterogenous cancer cell population. Anticancer drugs are effective in controlling cancer growth by inflicting damage to various target molecules and thereby triggering multiple cellular and intracellular pathways, leading to cell death or cell-cycle arrest. One of the major impediments in the chemotherapy treatment of cancer is drug resistance driven by multiple mechanisms, including multi-drug and cell-cycle mediated resistance to chemotherapy drugs. In this article, we discuss two hybrid multiscale modelling approaches, incorporating multiple interactions involved in the sub-cellular, cellular and microenvironmental levels to study the effects of cell-cycle, phase-specific chemotherapy on the growth and progression of cancer cells.

Multiscale Modelling of Cancer Progression and Treatment Control: The Role of Intracellular Heterogeneities in Chemotherapy Treatment

NASA Astrophysics Data System (ADS)

Chaplain, Mark A. J.; Powathil, Gibin G.

2015-04-01

Cancer is a complex, multiscale process involving interactions at intracellular, intercellular and tissue scales that are in turn susceptible to microenvironmental changes. Each individual cancer cell within a cancer cell mass is unique, with its own internal cellular pathways and biochemical interactions. These interactions contribute to the functional changes at the cellular and tissue scale, creating a heterogenous cancer cell population. Anticancer drugs are effective in controlling cancer growth by inflicting damage to various target molecules and thereby triggering multiple cellular and intracellular pathways, leading to cell death or cell-cycle arrest. One of the major impediments in the chemotherapy treatment of cancer is drug resistance driven by multiple mechanisms, including multi-drug and cell-cycle mediated resistance to chemotherapy drugs. In this article, we discuss two hybrid multiscale modelling approaches, incorporating multiple interactions involved in the sub-cellular, cellular and microenvironmental levels to study the effects of cell-cycle, phase-specific chemotherapy on the growth and progression of cancer cells.

Heterogeneity of the Caribbean plateau mantle source: Sr, O and He isotopic compositions of olivine and clinopyroxene from Gorgona Island

NASA Astrophysics Data System (ADS)

Révillon, S.; Chauvel, C.; Arndt, N. T.; Pik, R.; Martineau, F.; Fourcade, S.; Marty, B.

2002-12-01

The composition of the mantle plumes that created large oceanic plateaus such as Ontong Java or the Caribbean is still poorly known. Geochemical and isotopic studies on accreted portions of the Caribbean plateau have shown that the plume source was heterogeneous and contained isotopically depleted and relatively enriched portions. A distinctive feature of samples from the Caribbean plateau is their unusual Sr isotopic compositions, which, at a given Nd isotopic ratio, are far higher than in samples from other oceanic plateaus. Sr, O and He isotopic compositions of whole rocks and magmatic minerals (clinopyroxene or olivine) separated from komatiites, gabbros and peridotites from Gorgona Island in Colombia were determined to investigate the origin of these anomalously radiogenic compositions. Sequentially leached clinopyroxenes have Sr isotopic compositions in the range 87Sr/ 86Sr=0.70271-0.70352, systematically lower than those of leached and unleached whole rocks. Oxygen isotopic ratios of clinopyroxene vary within the range δ 18O=5.18-5.35‰, similar to that recorded in oceanic island basalts. He isotopic ratios are high ( R/ Ra=8-19). The lower 87Sr/ 86Sr ratios of most of the clinopyroxenes shift the field of the Caribbean plateau in Nd-Sr isotope diagrams toward more 'normal' values, i.e. a position closer to the field defined by mid-ocean ridge basalts and oceanic-island basalts. Three clinopyroxenes have slightly higher 87Sr/ 86Sr ratios that cannot be explained by an assimilation model. The high 87Sr/ 86Sr and variations of 143Nd/ 144Nd are interpreted as a source characteristic. Trace-element ratios, however, are controlled mainly by fractionation during partial melting. We combine these isotopic data in a heterogeneous plume source model that accounts for the diversity of isotopic signatures recorded on Gorgona Island and throughout the Caribbean plateau. The heterogeneities are related to old recycled oceanic lithosphere in the plume source; the high 3He/ 4He ratios may indicate that the source material once resided in the lower mantle.

The Role of Microglial Subsets in Regulating Traumatic Brain Injury

DTIC Science & Technology

2013-07-01

CCR)2. J. Exp. Med. 2000. 192: 1075–1080. 9 Mahad, D. J. and Ransohoff, R. M., The role of MCP-1 (CCL2) and CCR2 in multiple sclerosis and...at multiple timepoints in vivo and establish the function of these microglial subtypes ex vivo. 2. Skew the microglial response to TBI towards... multiple aspects, most notably in their chemokine repertoires. Thus, the macrophage response to TBI ini- tially involves heterogeneous polarization

The Gender Pay Gap Beyond Human Capital: Heterogeneity in Noncognitive Skills and in Labor Market Tastes

ERIC Educational Resources Information Center

Grove, Wayne A.; Hussey, Andrew; Jetter, Michael

2011-01-01

Focused on human capital, economists typically explain about half of the gender earnings gap. For a national sample of MBAs, we account for 82 percent of the gap by incorporating noncognitive skills (for example, confidence and assertiveness) and preferences regarding family, career, and jobs. Those two sources of gender heterogeneity account for…

Distributed containment control of heterogeneous fractional-order multi-agent systems with communication delays

NASA Astrophysics Data System (ADS)

Yang, Hongyong; Han, Fujun; Zhao, Mei; Zhang, Shuning; Yue, Jun

2017-08-01

Because many networked systems can only be characterized with fractional-order dynamics in complex environments, fractional-order calculus has been studied deeply recently. When diverse individual features are shown in different agents of networked systems, heterogeneous fractional-order dynamics will be used to describe the complex systems. Based on the distinguishing properties of agents, heterogeneous fractional-order multi-agent systems (FOMAS) are presented. With the supposition of multiple leader agents in FOMAS, distributed containment control of FOMAS is studied in directed weighted topologies. By applying Laplace transformation and frequency domain theory of the fractional-order operator, an upper bound of delays is obtained to ensure containment consensus of delayed heterogenous FOMAS. Consensus results of delayed FOMAS in this paper can be extended to systems with integer-order models. Finally, numerical examples are used to verify our results.

Zebrafish as a model to assess cancer heterogeneity, progression and relapse

PubMed Central

Blackburn, Jessica S.; Langenau, David M.

2014-01-01

Clonal evolution is the process by which genetic and epigenetic diversity is created within malignant tumor cells. This process culminates in a heterogeneous tumor, consisting of multiple subpopulations of cancer cells that often do not contain the same underlying mutations. Continuous selective pressure permits outgrowth of clones that harbor lesions that are capable of enhancing disease progression, including those that contribute to therapy resistance, metastasis and relapse. Clonal evolution and the resulting intratumoral heterogeneity pose a substantial challenge to biomarker identification, personalized cancer therapies and the discovery of underlying driver mutations in cancer. The purpose of this Review is to highlight the unique strengths of zebrafish cancer models in assessing the roles that intratumoral heterogeneity and clonal evolution play in cancer, including transgenesis, imaging technologies, high-throughput cell transplantation approaches and in vivo single-cell functional assays. PMID:24973745

BiP clustering facilitates protein folding in the endoplasmic reticulum.

PubMed

Griesemer, Marc; Young, Carissa; Robinson, Anne S; Petzold, Linda

2014-07-01

The chaperone BiP participates in several regulatory processes within the endoplasmic reticulum (ER): translocation, protein folding, and ER-associated degradation. To facilitate protein folding, a cooperative mechanism known as entropic pulling has been proposed to demonstrate the molecular-level understanding of how multiple BiP molecules bind to nascent and unfolded proteins. Recently, experimental evidence revealed the spatial heterogeneity of BiP within the nuclear and peripheral ER of S. cerevisiae (commonly referred to as 'clusters'). Here, we developed a model to evaluate the potential advantages of accounting for multiple BiP molecules binding to peptides, while proposing that BiP's spatial heterogeneity may enhance protein folding and maturation. Scenarios were simulated to gauge the effectiveness of binding multiple chaperone molecules to peptides. Using two metrics: folding efficiency and chaperone cost, we determined that the single binding site model achieves a higher efficiency than models characterized by multiple binding sites, in the absence of cooperativity. Due to entropic pulling, however, multiple chaperones perform in concert to facilitate the resolubilization and ultimate yield of folded proteins. As a result of cooperativity, multiple binding site models used fewer BiP molecules and maintained a higher folding efficiency than the single binding site model. These insilico investigations reveal that clusters of BiP molecules bound to unfolded proteins may enhance folding efficiency through cooperative action via entropic pulling.

Modeling unobserved sources of heterogeneity in animal abundance using a Dirichlet process prior

USGS Publications Warehouse

Dorazio, R.M.; Mukherjee, B.; Zhang, L.; Ghosh, M.; Jelks, H.L.; Jordan, F.

2008-01-01

In surveys of natural populations of animals, a sampling protocol is often spatially replicated to collect a representative sample of the population. In these surveys, differences in abundance of animals among sample locations may induce spatial heterogeneity in the counts associated with a particular sampling protocol. For some species, the sources of heterogeneity in abundance may be unknown or unmeasurable, leading one to specify the variation in abundance among sample locations stochastically. However, choosing a parametric model for the distribution of unmeasured heterogeneity is potentially subject to error and can have profound effects on predictions of abundance at unsampled locations. In this article, we develop an alternative approach wherein a Dirichlet process prior is assumed for the distribution of latent abundances. This approach allows for uncertainty in model specification and for natural clustering in the distribution of abundances in a data-adaptive way. We apply this approach in an analysis of counts based on removal samples of an endangered fish species, the Okaloosa darter. Results of our data analysis and simulation studies suggest that our implementation of the Dirichlet process prior has several attractive features not shared by conventional, fully parametric alternatives. ?? 2008, The International Biometric Society.

A flexible model of foraging by a honey bee colony: the effects of individual behaviour on foraging success.

PubMed

Cox, Melissa D; Myerscough, Mary R

2003-07-21

This paper develops and explores a model of foraging in honey bee colonies. The model may be applied to forage sources with various properties, and to colonies with different foraging-related parameters. In particular, we examine the effect of five foraging-related parameters on the foraging response and consequent nectar intake of a homogeneous colony. The parameters investigated affect different quantities critical to the foraging cycle--visit rate (affected by g), probability of dancing (mpd and bpd), duration of dancing (mcirc), or probability of abandonment (A). We show that one parameter, A, affects nectar intake in a nonlinear way. Further, we show that colonies with a midrange value of any foraging parameter perform better than the average of colonies with high- and low-range values, when profitable sources are available. Together these observations suggest that a heterogeneous colony, in which a range of parameter values are present, may perform better than a homogeneous colony. We modify the model to represent heterogeneous colonies and use it to show that the most important effect of heterogeneous foraging behaviour within the colony is to reduce the variance in the average quantity of nectar collected by heterogeneous colonies.

Multiresource allocation and scheduling for periodic soft real-time applications

NASA Astrophysics Data System (ADS)

Gopalan, Kartik; Chiueh, Tzi-cker

2001-12-01

Real-time applications that utilize multiple system resources, such as CPU, disks, and network links, require coordinated scheduling of these resources in order to meet their end-to-end performance requirements. Most state-of-the-art operating systems support independent resource allocation and deadline-driven scheduling but lack coordination among multiple heterogeneous resources. This paper describes the design and implementation of an Integrated Real-time Resource Scheduler (IRS) that performs coordinated allocation and scheduling of multiple heterogeneous resources on the same machine for periodic soft real-time application. The principal feature of IRS is a heuristic multi-resource allocation algorithm that reserves multiple resources for real-time applications in a manner that can maximize the number of applications admitted into the system in the long run. At run-time, a global scheduler dispatches the tasks of the soft real-time application to individual resource schedulers according to the precedence constraints between tasks. The individual resource schedulers, which could be any deadline based schedulers, can make scheduling decisions locally and yet collectively satisfy a real-time application's performance requirements. The tightness of overall timing guarantees is ultimately determined by the properties of individual resource schedulers. However, IRS maximizes overall system resource utilization efficiency by coordinating deadline assignment across multiple tasks in a soft real-time application.

Quantifying postfire aeolian sediment transport using rare earth element tracers

USGS Publications Warehouse

Dukes, David; Gonzales, Howell B.; Ravi, Sujith; Grandstaff, David E.; Van Pelt, R. Scott; Li, Junran; Wang, Guan; Sankey, Joel B.

2018-01-01

Grasslands, which provide fundamental ecosystem services in many arid and semiarid regions of the world, are undergoing rapid increases in fire activity and are highly susceptible to postfire-accelerated soil erosion by wind. A quantitative assessment of physical processes that integrates fire-wind erosion feedbacks is therefore needed relative to vegetation change, soil biogeochemical cycling, air quality, and landscape evolution. We investigated the applicability of a novel tracer technique—the use of multiple rare earth elements (REE)—to quantify soil transport by wind and to identify sources and sinks of wind-blown sediments in both burned and unburned shrub-grass transition zone in the Chihuahuan Desert, NM, USA. Results indicate that the horizontal mass flux of wind-borne sediment increased approximately threefold following the fire. The REE tracer analysis of wind-borne sediments shows that the source of the horizontal mass flux in the unburned site was derived from bare microsites (88.5%), while in the burned site it was primarily sourced from shrub (42.3%) and bare (39.1%) microsites. Vegetated microsites which were predominantly sinks of aeolian sediments in the unburned areas became sediment sources following the fire. The burned areas showed a spatial homogenization of sediment tracers, highlighting a potential negative feedback on landscape heterogeneity induced by shrub encroachment into grasslands. Though fires are known to increase aeolian sediment transport, accompanying changes in the sources and sinks of wind-borne sediments may influence biogeochemical cycling and land degradation dynamics. Furthermore, our experiment demonstrated that REEs can be used as reliable tracers for field-scale aeolian studies.

Temporal and spatial heterogeneity of rupture process application in shakemaps of Yushu Ms7.1 earthquake, China

NASA Astrophysics Data System (ADS)

Kun, C.

2015-12-01

Studies have shown that estimates of ground motion parameter from ground motion attenuation relationship often greater than the observed value, mainly because multiple ruptures of the big earthquake reduce the source pulse height of source time function. In the absence of real-time data of the station after the earthquake, this paper attempts to make some constraints from the source, to improve the accuracy of shakemaps. Causative fault of Yushu Ms 7.1 earthquake is vertical approximately (dip 83 °), and source process in time and space was dispersive distinctly. Main shock of Yushu Ms7.1 earthquake can be divided into several sub-events based on source process of this earthquake. Magnitude of each sub-events depended on each area under the curve of source pulse of source time function, and location derived from source process of each sub-event. We use ShakeMap method with considering the site effect to generate shakeMap for each sub-event, respectively. Finally, ShakeMaps of mainshock can be aquired from superposition of shakemaps for all the sub-events in space. Shakemaps based on surface rupture of causative Fault from field survey can also be derived for mainshock with only one magnitude. We compare ShakeMaps of both the above methods with Intensity of investigation. Comparisons show that decomposition method of main shock more accurately reflect the shake of earthquake in near-field, but for far field the shake is controlled by the weakening influence of the source, the estimated Ⅵ area was smaller than the intensity of the actual investigation. Perhaps seismic intensity in far-field may be related to the increasing seismic duration for the two events. In general, decomposition method of main shock based on source process, considering shakemap of each sub-event, is feasible for disaster emergency response, decision-making and rapid Disaster Assessment after the earthquake.

Fractal density modeling of crustal heterogeneity from the KTB deep hole

NASA Astrophysics Data System (ADS)

Chen, Guoxiong; Cheng, Qiuming

2017-03-01

Fractal or multifractal concepts have significantly enlightened our understanding of crustal heterogeneity. Much attention has focused on 1/f scaling natures of physicochemical heterogeneity of Earth crust from fractal increment perspective. In this study, fractal density model from fractal clustering point of view is used to characterize the scaling behaviors of heterogeneous sources recorded at German Continental Deep Drilling Program (KTB) main hole, and of special contribution is the local and global multifractal analysis revisited by using Haar wavelet transform (HWT). Fractal density modeling of mass accumulation generalizes the unit of rock density from integer (e.g., g/cm3) to real numbers (e.g., g/cmα), so that crustal heterogeneities with respect to source accumulation are quantified by singularity strength of fractal density in α-dimensional space. From that perspective, we found that the bulk densities of metamorphic rocks exhibit fractal properties but have a weak multifractality, decreasing with the depth. The multiscaling natures of chemical logs also have been evidenced, and the observed distinct fractal laws for mineral contents are related to their different geochemical behaviors within complex lithological context. Accordingly, scaling distributions of mineral contents have been recognized as a main contributor to the multifractal natures of heterogeneous density for low-porosity crystalline rocks. This finally allows us to use de Wijs cascade process to explain the mechanism of fractal density. In practice, the proposed local singularity analysis based on HWT is suggested as an attractive high-pass filtering to amplify weak signatures of well logs as well as to delineate microlithological changes.

Relative importance of multiple scattering by air molecules and aerosols in forming the atmospheric path radiance in the visible and near-infrared parts of the spectrum.

PubMed

Antoine, D; Morel, A

1998-04-20

Single and multiple scattering by molecules or by atmospheric aerosols only (homogeneous scattering), and heterogeneous scattering by aerosols and molecules, are recorded in Monte Carlo simulations. It is shown that heterogeneous scattering (1) always contributes significantly to the path reflectance (rho(path)), (2) is realized at the expense of homogeneous scattering, (3) decreases when aerosols are absorbing, and (4) introduces deviations in the spectral dependencies of reflectances compared with the Rayleigh exponent and the aerosol angstrom exponent. The ratio of rho(path) to the Rayleigh reflectance for an aerosol-free atmosphere is linearly related to the aerosol optical thickness. This result provides a basis for a new scheme for atmospheric correction of remotely sensed ocean color observations.

Can we still learn something from the relationship between fertility and mother's employment? Evidence from developing countries.

PubMed

Cáceres-Delpiano, Julio

2012-02-01

In this work, I study the impact of fertility on mothers' employment for a sample of developing countries. Using the event of multiple births as an instrumental variable (IV) for fertility, I find that having children has a negative impact on female employment. In addition, three types of heterogeneity are found. First, the magnitude of the impact depends on the birth at which the increase in fertility takes place. Second, the types of jobs affected by a fertility shock (multiple births) are jobs identified with a higher degree of informality, such as self-employment or unpaid jobs. Finally, the heterogeneity analysis reveals that an unexpected change in fertility is stronger at a higher education level of the mother and in urban areas.

Detection of admittivity anomaly on high-contrast heterogeneous backgrounds using frequency difference EIT.

PubMed

Jang, J; Seo, J K

2015-06-01

This paper describes a multiple background subtraction method in frequency difference electrical impedance tomography (fdEIT) to detect an admittivity anomaly from a high-contrast background conductivity distribution. The proposed method expands the use of the conventional weighted frequency difference EIT method, which has been used limitedly to detect admittivity anomalies in a roughly homogeneous background. The proposed method can be viewed as multiple weighted difference imaging in fdEIT. Although the spatial resolutions of the output images by fdEIT are very low due to the inherent ill-posedness, numerical simulations and phantom experiments of the proposed method demonstrate its feasibility to detect anomalies. It has potential application in stroke detection in a head model, which is highly heterogeneous due to the skull.

Multiple Household Water Sources and Their Use in Remote Communities With Evidence From Pacific Island Countries

NASA Astrophysics Data System (ADS)

Elliott, Mark; MacDonald, Morgan C.; Chan, Terence; Kearton, Annika; Shields, Katherine F.; Bartram, Jamie K.; Hadwen, Wade L.

2017-11-01

Global water research and monitoring typically focus on the household's "main source of drinking-water." Use of multiple water sources to meet daily household needs has been noted in many developing countries but rarely quantified or reported in detail. We gathered self-reported data using a cross-sectional survey of 405 households in eight communities of the Republic of the Marshall Islands (RMI) and five Solomon Islands (SI) communities. Over 90% of households used multiple sources, with differences in sources and uses between wet and dry seasons. Most RMI households had large rainwater tanks and rationed stored rainwater for drinking throughout the dry season, whereas most SI households collected rainwater in small pots, precluding storage across seasons. Use of a source for cooking was strongly positively correlated with use for drinking, whereas use for cooking was negatively correlated or uncorrelated with nonconsumptive uses (e.g., bathing). Dry season water uses implied greater risk of water-borne disease, with fewer (frequently zero) handwashing sources reported and more unimproved sources consumed. Use of multiple sources is fundamental to household water management and feasible to monitor using electronic survey tools. We contend that recognizing multiple water sources can greatly improve understanding of household-level and community-level climate change resilience, that use of multiple sources confounds health impact studies of water interventions, and that incorporating multiple sources into water supply interventions can yield heretofore-unrealized benefits. We propose that failure to consider multiple sources undermines the design and effectiveness of global water monitoring, data interpretation, implementation, policy, and research.

[Digital media as laypeople's source of information about the environment and health].

PubMed

Sassenberg, Kai

2017-06-01

Over the last two decades, the Internet has become the primary source of information. Thanks to the Internet, laypeople have access to information from the health and the environmental sector, which was for a long time available only to experts (e. g. scientific publications, statistics). Information on the Internet varies in quality, as generally anybody can publish online, without any quality control. At the same time, Internet use comes with specific situational characteristics. Given that the amount of information is nearly unlimited and that this information is easily available via search engines, users are not restricted to one or just a few texts, but can choose between multiple sources depending on their motivation and interest. Together with the heterogeneity of the sources, this provides the basis for a strong impact of motivation on the process and the outcomes of information acquisition online. Based on empirical research in the domain of Internet searching in the health sector, the current article discusses the impact of the use of digital media in the context of environmental medicine. Research has led to four conclusions: (1) Users are not sufficiently sensitive to the quality of information. (2) Information supporting their own opinion is preferably processed. (3) Users who feel threatened focus on positive information. (4) Vigilant users focus on negative information, which might result in cyberchrondria. The implications of these effects for the use of digital media in the sector of environmental medicine are discussed.

Anomalous Stars and Where to Find Them

NASA Astrophysics Data System (ADS)

Muna, Demitri; Huff, Eric

2018-01-01

The sky is now extensively mapped by imaging surveys in wavelengths that span the electromagnetic spectrum, ranging from Fermi and GALEX down to WISE, Planck, and radio surveys like FIRST and VLSS. Individual public catalogs now contain on order hundreds of millions of distinct sources. Recent progress in image analysis techniques makes possible great increases in the efficiency, sensitivity, and reliability of measurements that combine imaging data from multiple probes with heterogeneous properties. This is especially true for the identification of anomalous sources: traditional methods for finding ‘outliers’ typically rely on making hard cuts on noisy catalog properties, greatly restricting the potential discovery space. Cross-catalog matches confine investigation to objects that occur at signal-to-noise ratios sufficient to be independently detectable in a subset of all the available multi-wavelength coverage. The process of merging the latest analyses with existing data is severely hampered, however, by the fractured way in which these data are processed and stored, limitations of data access, the data volume involved, and the computation power required. This has left archive data far from fully exploited. Stellar anomalies present the best place to start: joint distributions of stellar colors and magnitudes have finer structures than extended sources, and modelling of point sources is computationally cheaper than for galaxies. We present a framework to solve the problem of applying new algorithms to old data while overcoming the limitations described above, in the search for the undiscovered anomalous.

The effects of acupuncture on rates of clinical pregnancy among women undergoing in vitro fertilization: a systematic review and meta-analysis

PubMed Central

Manheimer, Eric; van der Windt, Daniëlle; Cheng, Ke; Stafford, Kristen; Liu, Jianping; Tierney, Jayne; Lao, Lixing; Berman, Brian M.; Langenberg, Patricia; Bouter, Lex M.

2013-01-01

BACKGROUND Recent systematic reviews of adjuvant acupuncture for IVF have pooled heterogeneous trials, without examining variables that might explain the heterogeneity. The aims of our meta-analysis were to quantify the overall pooled effects of adjuvant acupuncture on IVF clinical pregnancy success rates, and evaluate whether study design-, treatment- and population-related factors influence effect estimates. METHODS We included randomized controlled trials that compared needle acupuncture administered within 1 day of embryo transfer, versus sham acupuncture or no adjuvant treatment. Our primary outcome was clinical pregnancy rates. We obtained from all investigators additional methodological details and outcome data not included in their original publications. We analysed sham-controlled and no adjuvant treatment-controlled trials separately, but since there were no large or significant differences between these two subsets, we pooled all trials for subgroup analyses. We prespecified 11 subgroup variables (5 clinical and 6 methodological) to investigate sources of heterogeneity, using single covariate meta-regressions. RESULTS Sixteen trials (4021 participants) were included in the meta-analyses. There was no statistically significant difference between acupuncture and controls when combining all trials [risk ratio (RR) 1.12, 95% confidence interval (CI), 0.96–1.31; I2 = 68%; 16 trials; 4021 participants], or when restricting to sham-controlled (RR 1.02, 0.83–1.26; I2 = 66%; 7 trials; 2044 participants) or no adjuvant treatment-controlled trials (RR 1.22, 0.97–1.52; I2 = 67%; 9 trials; 1977 participants). The type of control used did not significantly explain the statistical heterogeneity (interaction P = 0.27). Baseline pregnancy rate, measured as the observed rate of clinical pregnancy in the control group of each trial, was a statistically significant effect modifier (interaction P < 0.001), and this covariate explained most of the heterogeneity of the effects of adjuvant acupuncture across all trials (adjusted R2 = 93%; I2 residual = 9%). Trials with lower control group rates of clinical pregnancy showed larger effects of adjuvant acupuncture (RR 1.53, 1.28–1.84; 7 trials; 1732 participants) than trials with higher control group rates of clinical pregnancy (RR 0.90, 0.80–1.01; 9 trials; 2289 participants). The asymmetric funnel plot showed a tendency for the intervention effects to be more beneficial in smaller trials. CONCLUSIONS We found no pooled benefit of adjuvant acupuncture for IVF. The subgroup finding of a benefit in trials with lower, but not higher, baseline pregnancy rates (the only statistically significant subgroup finding in our earlier review) has been confirmed in this update, and was not explained by any confounding variables evaluated. However, this baseline pregnancy rate subgroup finding among published trials requires further confirmation and exploration in additional studies because of the multiple subgroup tests conducted, the risk of unidentified confounders, the multiple different factors that determine baseline rates, and the possibility of publication bias. PMID:23814102

Heterogeneity and changes in inequality of malaria risk after introduction of insecticide-treated bed nets in Macha, Zambia.

PubMed

Norris, Laura C; Norris, Douglas E

2013-04-01

In 2007, the first free mass distribution of insecticide-treated bed nets (ITNs) occurred in southern Zambia. To determine the effect of ITNs on heterogeneity in biting rates, human DNA from Anopheles arabiensis blood meals was genotyped to determine the number of hosts that had contributed to the blood meals. The multiple feeding rate decreased from 18.9% pre-ITN to 9.1% post-ITN, suggesting that mosquito biting had focused onto a smaller fraction of the population. Pre-ITN, 20% of persons in a household provided 40% of blood meals, which increased to 59% post-ITN. To measure heterogeneity over a larger scale, mosquitoes were collected in 90 households in two village areas. Of these households, 25% contributed 78.1% of An. arabiensis, and households with high frequencies of An. arabiensis were significantly spatially clustered. The results indicate that substantial heterogeneity in malaria risk exists at local and household levels, and household-level heterogeneity may be influenced by interventions, such as ITNs.

Intratumor DNA methylation heterogeneity reflects clonal evolution in aggressive prostate cancer.

PubMed

Brocks, David; Assenov, Yassen; Minner, Sarah; Bogatyrova, Olga; Simon, Ronald; Koop, Christina; Oakes, Christopher; Zucknick, Manuela; Lipka, Daniel Bernhard; Weischenfeldt, Joachim; Feuerbach, Lars; Cowper-Sal Lari, Richard; Lupien, Mathieu; Brors, Benedikt; Korbel, Jan; Schlomm, Thorsten; Tanay, Amos; Sauter, Guido; Gerhäuser, Clarissa; Plass, Christoph

2014-08-07

Despite much evidence on epigenetic abnormalities in cancer, it is currently unclear to what extent epigenetic alterations can be associated with tumors' clonal genetic origins. Here, we show that the prostate intratumor heterogeneity in DNA methylation and copy-number patterns can be explained by a unified evolutionary process. By assaying multiple topographically distinct tumor sites, premalignant lesions, and lymph node metastases within five cases of prostate cancer, we demonstrate that both DNA methylation and copy-number heterogeneity consistently reflect the life history of the tumors. Furthermore, we show cases of genetic or epigenetic convergent evolution and highlight the diversity in the evolutionary origins and aberration spectrum between tumor and metastatic subclones. Importantly, DNA methylation can complement genetic data by serving as a proxy for activity at regulatory domains, as we show through identification of high epigenetic heterogeneity at androgen-receptor-bound enhancers. Epigenome variation thereby expands on the current genome-centric view on tumor heterogeneity. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Single Cell Proteolytic Assays to Investigate Cancer Clonal Heterogeneity and Cell Dynamics Using an Efficient Cell Loading Scheme

NASA Astrophysics Data System (ADS)

Chen, Yu-Chih; Cheng, Yu-Heng; Ingram, Patrick; Yoon, Euisik

2016-06-01

Proteolytic degradation of the extracellular matrix (ECM) is critical in cancer invasion, and recent work suggests that heterogeneous cancer populations cooperate in this process. Despite the importance of cell heterogeneity, conventional proteolytic assays measure average activity, requiring thousands of cells and providing limited information about heterogeneity and dynamics. Here, we developed a microfluidic platform that provides high-efficiency cell loading and simple valveless isolation, so the proteolytic activity of a small sample (10-100 cells) can be easily characterized. Combined with a single cell derived (clonal) sphere formation platform, we have successfully demonstrated the importance of microenvironmental cues for proteolytic activity and also investigated the difference between clones. Furthermore, the platform allows monitoring single cells at multiple time points, unveiling different cancer cell line dynamics in proteolytic activity. The presented tool facilitates single cell proteolytic analysis using small samples, and our findings illuminate the heterogeneous and dynamic nature of proteolytic activity.

Two-dimensional gel analysis of protein expression in ovarian tumors shows a low degree of intratumoral heterogeneity.

PubMed

Alaiya, A A; Franzén, B; Moberger, B; Silfverswärd, C; Linder, S; Auer, G

1999-01-01

The process of tumor progression leads to the emergence of multiple clones, and to the development of tumor heterogeneity. One approach to the study of the extent of such heterogeneity is to examine the expression of marker proteins in different tumor areas. Two-dimensional gel electrophoresis (2-DE) is a powerful tool for such studies, since the expression of a large number of polypeptide markers can be evaluated. In the present study, tumor cells were prepared from human ovarian tumors and analyzed by 2-DE and PDQUEST. As judged from the analysis of two different areas in each of nine ovarian tumors, the intratumoral variation in protein expression was low. In contrast, large differences were observed when the protein profiles of different tumors were compared. The differences in gene expression between pairs of malignant carcinomas were slightly larger than the differences observed between pairs of benign tumors. We conclude that 2-DE analysis of intratumoral heterogeneity in ovarian cancer tissue indicates a low degree of heterogeneity.

Genomic profiling of multiple sequentially acquired tumor metastatic sites from an “exceptional responder” lung adenocarcinoma patient reveals extensive genomic heterogeneity and novel somatic variants driving treatment response. | Center for Cancer Research

Cancer.gov

Biswas et al. describe an “exceptional responder” lung adenocarcinoma patient who survived with metastatic lung adenocarcinoma for 7 years while undergoing single or combination ERBB2-directed therapies. Whole-genome, whole-exome, and high-coverage ion-torrent targeted sequencing were used to demonstrate extreme genomic heterogeneity between the lung and lymph node metastatic

Biological and Clinical Implications of Clonal Heterogeneity and Clonal Evolution in Multiple Myeloma.

PubMed

Bianchi, Giada; Ghobrial, Irene M

Clonal heterogeneity and clonal evolution have emerged as critical concepts in the field of oncology over the past four decades, largely thanks to the implementation of novel technologies such as comparative genomic hybridization, whole genome/exome sequencing and epigenetic analysis. Along with the identification of cancer stem cells in the majority of neoplasia, the recognition of intertumor and intratumor variability has provided a novel perspective to understand the mechanisms behind tumor evolution and its implication in terms of treatment failure and cancer relapse or recurrence. First hypothesized over two decades ago, clonal heterogeneity and clonal evolution have been confirmed in multiple myeloma (MM), an incurable cancer of plasma cells, almost universally preceded by a pre-malignant conditioned named monoclonal gammopathy of undetermined significance (MGUS). The genetic events and molecular mechanisms underlying such evolution have been difficult to dissect. Moreover, while a role for the bone marrow microenvironment in supporting MM cell survival, proliferation and drug-resistance has been well established, whether it is directly involved in driving evolution from MGUS to MM is at present unclear. We present in this review a historical excursus on the concepts of clonal heterogeneity and clonal evolution in MM with a special emphasis on their role in the progression from MGUS to MM; the contribution of the microenvironment; and the clinical implications in terms of resistance to treatment and disease relapse/recurrence.

Biological and Clinical Implications of Clonal Heterogeneity and Clonal Evolution in Multiple Myeloma

PubMed Central

Bianchi, Giada; Ghobrial, Irene M.

2015-01-01

Clonal heterogeneity and clonal evolution have emerged as critical concepts in the field of oncology over the past four decades, largely thanks to the implementation of novel technologies such as comparative genomic hybridization, whole genome/exome sequencing and epigenetic analysis. Along with the identification of cancer stem cells in the majority of neoplasia, the recognition of intertumor and intratumor variability has provided a novel perspective to understand the mechanisms behind tumor evolution and its implication in terms of treatment failure and cancer relapse or recurrence. First hypothesized over two decades ago, clonal heterogeneity and clonal evolution have been confirmed in multiple myeloma (MM), an incurable cancer of plasma cells, almost universally preceded by a pre-malignant conditioned named monoclonal gammopathy of undetermined significance (MGUS). The genetic events and molecular mechanisms underlying such evolution have been difficult to dissect. Moreover, while a role for the bone marrow microenvironment in supporting MM cell survival, proliferation and drug-resistance has been well established, whether it is directly involved in driving evolution from MGUS to MM is at present unclear. We present in this review a historical excursus on the concepts of clonal heterogeneity and clonal evolution in MM with a special emphasis on their role in the progression from MGUS to MM; the contribution of the microenvironment; and the clinical implications in terms of resistance to treatment and disease relapse/recurrence. PMID:25705146

Circulating tumor DNA functions as an alternative for tissue to overcome tumor heterogeneity in advanced gastric cancer.

PubMed

Gao, Jing; Wang, Haixing; Zang, Wanchun; Li, Beifang; Rao, Guanhua; Li, Lei; Yu, Yang; Li, Zhongwu; Dong, Bin; Lu, Zhihao; Jiang, Zhi; Shen, Lin

2017-09-01

Overcoming tumor heterogeneity is a major challenge for personalized treatment of gastric cancer, especially for human epidermal growth factor receptor-2 targeted therapy. Analysis of circulating tumor DNA allows a more comprehensive analysis of tumor heterogeneity than traditional biopsies in lung cancer and breast cancer, but little is known in gastric cancer. We assessed mutation profiles of ctDNA and primary tumors from 30 patients with advanced gastric cancer, then performed a comprehensive analysis of tumor mutations by multiple biopsies from five patients, and finally analyzed the concordance of HER2 amplification in ctDNA and paired tumor tissues in 70 patients. By comparing with a single tumor sample, ctDNA displayed a low concordance of mutation profile, only approximately 50% (138/275) somatic mutations were found in paired tissue samples, however, when compared with multiple biopsies, most DNA mutations in ctDNA were also shown in paired tumor tissues. ctDNA had a high concordance (91.4%, Kappa index = 0.784, P < 0.001) of HER2 amplification with tumor tissues, suggesting it might be an alternative for tissue. It implied that ctDNA-based assessment could partially overcome the tumor heterogeneity, and might serve as a potential surrogate for HER2 analysis in gastric cancer. © 2017 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.

Drivers of age-specific survival in a long-lived seabird: contributions of observed and hidden sources of heterogeneity.

PubMed

Aubry, Lise M; Cam, Emmanuelle; Koons, David N; Monnat, Jean-Yves; Pavard, Samuel

2011-03-01

1. We assessed the relative influence of variability in recruitment age, dynamic reproductive investment (time-specific reproductive states) and frailty (unobserved differences in survival abilities across individuals) on survival in the black-legged kittiwake. Furthermore, we examined whether observed variability in survival trajectories was best explained by immediate reproductive investment, cumulative investment, or both. 2. Individuals that delayed recruitment (≥ age 7) suffered a higher mortality risk than early recruits (age 3), especially later in life, suggesting that recruitment age may be an indicator of individual quality. Although recruitment age helped explain variation in survival, time-varying reproductive investment had a more substantial influence. 3. The dichotomy of attempting to breed or not explained variability in survival across life better than other parameterizations of reproductive states such as clutch size, brood size or breeding success. In the kittiwake, the sinequanon condition to initiate reproduction is to hold a nest site, which is considered a very competitive activity. This might explain why attempting to breed is the key level of investment that affects survival, independent of the outcome (failure or success). 4. Interestingly, the more individuals cumulate reproductive attempts over life, the lower their mortality risk, indicating that breeding experience may be a good indicator of parental quality as well. In contrast, attempting to breed at time t increased the risk of mortality between t and t + 1. We thus detected an immediate trade-off between attempting to breed and survival in this population; however, the earlier individuals recruited, and the more breeding experience they accumulated, the smaller the cost. 5. Lastly, unobserved heterogeneity across individuals improved model fit more (1·3 times) than fixed and dynamic sources of observed heterogeneity in reproductive investment, demonstrating that it is critical to account for both sources of individual heterogeneity when studying survival trajectories. Only after simultaneously accounting for both sources of heterogeneity were we able to detect the 'cost' of immediate reproductive investment on survival and the 'benefit' of cumulative breeding attempts (experience), a proxy to individual quality. © 2010 The Authors. Journal of Animal Ecology © 2010 British Ecological Society.

Regression Models for the Analysis of Longitudinal Gaussian Data from Multiple Sources

PubMed Central

O’Brien, Liam M.; Fitzmaurice, Garrett M.

2006-01-01

We present a regression model for the joint analysis of longitudinal multiple source Gaussian data. Longitudinal multiple source data arise when repeated measurements are taken from two or more sources, and each source provides a measure of the same underlying variable and on the same scale. This type of data generally produces a relatively large number of observations per subject; thus estimation of an unstructured covariance matrix often may not be possible. We consider two methods by which parsimonious models for the covariance can be obtained for longitudinal multiple source data. The methods are illustrated with an example of multiple informant data arising from a longitudinal interventional trial in psychiatry. PMID:15726666

Consistent Simulation Framework for Efficient Mass Discharge and Source Depletion Time Predictions of DNAPL Contaminants in Heterogeneous Aquifers Under Uncertainty

NASA Astrophysics Data System (ADS)

Nowak, W.; Koch, J.

2014-12-01

Predicting DNAPL fate and transport in heterogeneous aquifers is challenging and subject to an uncertainty that needs to be quantified. Models for this task needs to be equipped with an accurate source zone description, i.e., the distribution of mass of all partitioning phases (DNAPL, water, and soil) in all possible states ((im)mobile, dissolved, and sorbed), mass-transfer algorithms, and the simulation of transport processes in the groundwater. Such detailed models tend to be computationally cumbersome when used for uncertainty quantification. Therefore, a selective choice of the relevant model states, processes, and scales are both sensitive and indispensable. We investigate the questions: what is a meaningful level of model complexity and how to obtain an efficient model framework that is still physically and statistically consistent. In our proposed model, aquifer parameters and the contaminant source architecture are conceptualized jointly as random space functions. The governing processes are simulated in a three-dimensional, highly-resolved, stochastic, and coupled model that can predict probability density functions of mass discharge and source depletion times. We apply a stochastic percolation approach as an emulator to simulate the contaminant source formation, a random walk particle tracking method to simulate DNAPL dissolution and solute transport within the aqueous phase, and a quasi-steady-state approach to solve for DNAPL depletion times. Using this novel model framework, we test whether and to which degree the desired model predictions are sensitive to simplifications often found in the literature. With this we identify that aquifer heterogeneity, groundwater flow irregularity, uncertain and physically-based contaminant source zones, and their mutual interlinkages are indispensable components of a sound model framework.

Visualizing medium and biodistribution in complex cell culture bioreactors using in vivo imaging.

PubMed

Ratcliffe, E; Thomas, R J; Stacey, A J

2014-01-01

There is a dearth of technology and methods to aid process characterization, control and scale-up of complex culture platforms that provide niche micro-environments for some stem cell-based products. We have demonstrated a novel use of 3d in vivo imaging systems to visualize medium flow and cell distribution within a complex culture platform (hollow fiber bioreactor) to aid characterization of potential spatial heterogeneity and identify potential routes of bioreactor failure or sources of variability. This can then aid process characterization and control of such systems with a view to scale-up. Two potential sources of variation were observed with multiple bioreactors repeatedly imaged using two different imaging systems: shortcutting of medium between adjacent inlet and outlet ports with the potential to create medium gradients within the bioreactor, and localization of bioluminescent murine 4T1-luc2 cells upon inoculation with the potential to create variable seeding densities at different points within the cell growth chamber. The ability of the imaging technique to identify these key operational bioreactor characteristics demonstrates an emerging technique in troubleshooting and engineering optimization of bioreactor performance. © 2013 American Institute of Chemical Engineers.

Metadata management for high content screening in OMERO

PubMed Central

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K.; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J.; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R.

2016-01-01

High content screening (HCS) experiments create a classic data management challenge—multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of “final” results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. PMID:26476368

Metadata management for high content screening in OMERO.

PubMed

Li, Simon; Besson, Sébastien; Blackburn, Colin; Carroll, Mark; Ferguson, Richard K; Flynn, Helen; Gillen, Kenneth; Leigh, Roger; Lindner, Dominik; Linkert, Melissa; Moore, William J; Ramalingam, Balaji; Rozbicki, Emil; Rustici, Gabriella; Tarkowska, Aleksandra; Walczysko, Petr; Williams, Eleanor; Allan, Chris; Burel, Jean-Marie; Moore, Josh; Swedlow, Jason R

2016-03-01

High content screening (HCS) experiments create a classic data management challenge-multiple, large sets of heterogeneous structured and unstructured data, that must be integrated and linked to produce a set of "final" results. These different data include images, reagents, protocols, analytic output, and phenotypes, all of which must be stored, linked and made accessible for users, scientists, collaborators and where appropriate the wider community. The OME Consortium has built several open source tools for managing, linking and sharing these different types of data. The OME Data Model is a metadata specification that supports the image data and metadata recorded in HCS experiments. Bio-Formats is a Java library that reads recorded image data and metadata and includes support for several HCS screening systems. OMERO is an enterprise data management application that integrates image data, experimental and analytic metadata and makes them accessible for visualization, mining, sharing and downstream analysis. We discuss how Bio-Formats and OMERO handle these different data types, and how they can be used to integrate, link and share HCS experiments in facilities and public data repositories. OME specifications and software are open source and are available at https://www.openmicroscopy.org. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

A method and software framework for enriching private biomedical sources with data from public online repositories.

PubMed

Anguita, Alberto; García-Remesal, Miguel; Graf, Norbert; Maojo, Victor

2016-04-01

Modern biomedical research relies on the semantic integration of heterogeneous data sources to find data correlations. Researchers access multiple datasets of disparate origin, and identify elements-e.g. genes, compounds, pathways-that lead to interesting correlations. Normally, they must refer to additional public databases in order to enrich the information about the identified entities-e.g. scientific literature, published clinical trial results, etc. While semantic integration techniques have traditionally focused on providing homogeneous access to private datasets-thus helping automate the first part of the research, and there exist different solutions for browsing public data, there is still a need for tools that facilitate merging public repositories with private datasets. This paper presents a framework that automatically locates public data of interest to the researcher and semantically integrates it with existing private datasets. The framework has been designed as an extension of traditional data integration systems, and has been validated with an existing data integration platform from a European research project by integrating a private biological dataset with data from the National Center for Biotechnology Information (NCBI). Copyright © 2016 Elsevier Inc. All rights reserved.

Oscillatory magnetic brain activity is related to dissociative symptoms and childhood adversities - A study in women with multiple trauma.

PubMed

Schalinski, I; Moran, J K; Elbert, T; Reindl, V; Wienbruch, C

2017-08-15

Individuals with trauma-related disorders are complex and heterogeneous; part of this complexity derives from additional psychopathology like dissociation as well as environmental adversities such as traumatic stress, experienced throughout the lifespan. Understanding the neurophysiological abnormalities in Post-traumatic stress disorder (PTSD) requires a simultaneous consideration of these factors. Resting state magnetoencephalography (MEG) recordings were obtained from 41 women with PTSD and comorbid depressive symptoms, and 16 healthy women. Oscillatory brain activity was extracted for five frequency bands and 11 source locations, and analyzed in relation to shutdown dissociation and adversity-related measures. Dissociative symptoms were related to increased delta and lowered beta power. Adversity-related measures modulated theta and alpha oscillatory power (in particular childhood sexual abuse) and differed between patients and controls. Findings are based on women with comorbid depressive symptoms and therefore may not be applicable for men or groups with other clinical profiles. In respect to childhood adversities, we had no reliable source for the early infancy. Trauma-related abnormalities in neural organization vary with both exposure to adversities as well as their potential to evoke ongoing shutdown responses. Copyright © 2017 Elsevier B.V. All rights reserved.

Impacts of Heterogeneous Recycle in Fast Reactors on Overall Fuel Cycle

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

Temitope A. Taiwo; Samuel E. Bays; Abdullatif M. Yacout

2011-03-01

A study in the United States has evaluated the attributes of the heterogeneous recycle approach for plutonium and minor actinide transmutation in fast reactor fuel cycles, with comparison to the homogeneous recycle approach, where pertinent. The work investigated the characteristics, advantages, and disadvantages of the approach in the overall fuel cycle, including reactor transmutation, systems and safety impacts, fuel separation and fabrication issues, and proliferation risk and transportation impacts. For this evaluation, data from previous and ongoing national studies on heterogeneous recycle were reviewed and synthesized. Where useful, information from international sources was included in the findings. The intent ofmore » the work was to provide a comprehensive assessment of the heterogeneous recycle approach at the current time.« less

Investigation Gender/Ethnicity Heterogeneity in Course Management System Use in Higher Education by Utilizing the MIMIC Model

ERIC Educational Resources Information Center

Li, Yi

2012-01-01

This study focuses on the issue of learning equity in colleges and universities where teaching and learning have come to depend heavily on computer technologies. The study uses the Multiple Indicators Multiple Causes (MIMIC) latent variable model to quantitatively investigate whether there is a gender /ethnicity difference in using computer based…

Sources of heterogeneity in studies of the BMI-mortality association.

PubMed

Peter, Raphael Simon; Nagel, Gabriele

2017-06-01

To date, the amount of heterogeneity among studies of the body mass index-mortality association attributable to differences in the age distribution and length of follow-up has not been quantified. Therefore, we wanted to quantify the amount of heterogeneity attributable to age and follow-up in results of studies on the body mass index-mortality relation. We used optima of the body mass index mortality association reported for 30 populations and performed meta-regression to estimate the amount of heterogeneity attributable to sex, ethnicity, mean age at baseline, percentage smokers, and length of follow-up. Ethnicity as single factor accounted for 36% (95% CI, 11-56%) of heterogeneity. Mean age and length of follow-up had an interactive effect and together accounted for 56% (95% CI, 24-74%) of the remaining heterogeneity. Sex did not significantly contribute to the heterogeneity, after controlling for ethnicity, age, and length of follow-up. A considerable amount of heterogeneity in studies of the body mass index-mortality association is attributable to ethnicity, age, and length of follow-up. Copyright © 2017 The Authors. Production and hosting by Elsevier B.V. All rights reserved.

Analysing the impact of multiple stressors in aquatic biomonitoring data: A 'cookbook' with applications in R.

PubMed

Feld, Christian K; Segurado, Pedro; Gutiérrez-Cánovas, Cayetano

2016-12-15

Multiple stressors threaten biodiversity and ecosystem integrity, imposing new challenges to ecosystem management and restoration. Ecosystem managers are required to address and mitigate the impact of multiple stressors, yet the knowledge required to disentangle multiple-stressor effects is still incomplete. Experimental studies have advanced the understanding of single and combined stressor effects, but there is a lack of a robust analytical framework, to address the impact of multiple stressors based on monitoring data. Since 2000, the monitoring of Europe's waters has resulted in a vast amount of biological and environmental (stressor) data of about 120,000 water bodies. For many reasons, this data is rarely exploited in the multiple-stressor context, probably because of its rather heterogeneous nature: stressors vary and are mixed with broad-scale proxies of environmental stress (e.g. land cover), missing values and zero-inflated data limit the application of statistical methods and biological indicators are often aggregated (e.g. taxon richness) and do not respond stressor-specific. Here, we present a 'cookbook' to analyse the biological response to multiple stressors using data from biomonitoring schemes. Our 'cookbook' includes guidance for the analytical process and the interpretation of results. The 'cookbook' is accompanied by scripts, which allow the user to run a stepwise analysis based on his/her own data in R, an open-source language and environment for statistical computing and graphics. Using simulated and real data, we show that the recommended procedure is capable of identifying stressor hierarchy (importance) and interaction in large datasets. We recommend a minimum number of 150 independent observations and a minimum stressor gradient length of 75% (of the most relevant stressor's gradient in nature), to be able to reliably rank the stressor's importance, detect relevant interactions and estimate their standardised effect size. We conclude with a brief discussion of the advantages and limitations of this protocol. Copyright © 2016 Elsevier B.V. All rights reserved.

Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks.

PubMed

Wang, Chenguang; Song, Yangqiu; El-Kishky, Ahmed; Roth, Dan; Zhang, Ming; Han, Jiawei

2015-08-01

One of the key obstacles in making learning protocols realistic in applications is the need to supervise them, a costly process that often requires hiring domain experts. We consider the framework to use the world knowledge as indirect supervision. World knowledge is general-purpose knowledge, which is not designed for any specific domain. Then the key challenges are how to adapt the world knowledge to domains and how to represent it for learning. In this paper, we provide an example of using world knowledge for domain dependent document clustering. We provide three ways to specify the world knowledge to domains by resolving the ambiguity of the entities and their types, and represent the data with world knowledge as a heterogeneous information network. Then we propose a clustering algorithm that can cluster multiple types and incorporate the sub-type information as constraints. In the experiments, we use two existing knowledge bases as our sources of world knowledge. One is Freebase, which is collaboratively collected knowledge about entities and their organizations. The other is YAGO2, a knowledge base automatically extracted from Wikipedia and maps knowledge to the linguistic knowledge base, Word-Net. Experimental results on two text benchmark datasets (20newsgroups and RCV1) show that incorporating world knowledge as indirect supervision can significantly outperform the state-of-the-art clustering algorithms as well as clustering algorithms enhanced with world knowledge features.

Building an Ontology for Identity Resolution in Healthcare and Public Health.

PubMed

Duncan, Jeffrey; Eilbeck, Karen; Narus, Scott P; Clyde, Stephen; Thornton, Sidney; Staes, Catherine

2015-01-01

Integration of disparate information from electronic health records, clinical data warehouses, birth certificate registries and other public health information systems offers great potential for clinical care, public health practice, and research. Such integration, however, depends on correctly matching patient-specific records using demographic identifiers. Without standards for these identifiers, record linkage is complicated by issues of structural and semantic heterogeneity. Our objectives were to develop and validate an ontology to: 1) identify components of identity and events subsequent to birth that result in creation, change, or sharing of identity information; 2) develop an ontology to facilitate data integration from multiple healthcare and public health sources; and 3) validate the ontology's ability to model identity-changing events over time. We interviewed domain experts in area hospitals and public health programs and developed process models describing the creation and transmission of identity information among various organizations for activities subsequent to a birth event. We searched for existing relevant ontologies. We validated the content of our ontology with simulated identity information conforming to scenarios identified in our process models. We chose the Simple Event Model (SEM) to describe events in early childhood and integrated the Clinical Element Model (CEM) for demographic information. We demonstrated the ability of the combined SEM-CEM ontology to model identity events over time. The use of an ontology can overcome issues of semantic and syntactic heterogeneity to facilitate record linkage.