Protein Structure Determination using Metagenome sequence data

PubMed Central

Ovchinnikov, Sergey; Park, Hahnbeom; Varghese, Neha; Huang, Po-Ssu; Pavlopoulos, Georgios A.; Kim, David E.; Kamisetty, Hetunandan; Kyrpides, Nikos C.; Baker, David

2017-01-01

Despite decades of work by structural biologists, there are still ~5200 protein families with unknown structure outside the range of comparative modeling. We show that Rosetta structure prediction guided by residue-residue contacts inferred from evolutionary information can accurately model proteins that belong to large families, and that metagenome sequence data more than triples the number of protein families with sufficient sequences for accurate modeling. We then integrate metagenome data, contact based structure matching and Rosetta structure calculations to generate models for 614 protein families with currently unknown structures; 206 are membrane proteins and 137 have folds not represented in the PDB. This approach provides the representative models for large protein families originally envisioned as the goal of the protein structure initiative at a fraction of the cost. PMID:28104891

Cryogenic propellant thermal control system design considerations, analyses, and concepts applied to a Mars human exploration mission

NASA Technical Reports Server (NTRS)

Plachta, David W.; Tucker, Stephen; Hoffman, David J.

1993-01-01

This paper analyzes, defines, and sizes cryogenic storage thermal control systems that meet the requirements of future NASA Mars human exploration missions. The design issues of this system include the projection of the existing Multilayer Insulation data base for cryogenic storage to much thicker (10 cm or more) insulation systems, the unknown heat leak from mechanical interfaces, and the thermal and structural performance effects of the large tank sizes required for a Mars mission. Acknowledging these unknown effects, heat loss projections are made based on extrapolation of the existing data base. The results indicate that hydrogen, methane, and oxygen are feasible propellants, and that the best suited thermal control sytems are 'thick' MLI, thermodynamic vent sytems, cryocoolers, and vacuum jackets.

Exploring the Self-Ownership Effect: Separating Stimulus and Response Biases

ERIC Educational Resources Information Center

Golubickis, Marius; Falben, Johanna K.; Cunningham, William A.; Macrae, C. Neil

2018-01-01

Although ownership is acknowledged to exert a potent influence on various aspects of information processing, the origin of these effects remains largely unknown. Based on the demonstration that self-relevance facilitates perceptual judgments (i.e., the self-prioritization effect), here we explored the possibility that ownership enhances object…

GROUNDWATER RECHARGE AND CHEMICAL CONTAMINANTS: CHALLENGES IN COMMUNICATING THE CONNECTIONS AND COLLISIONS OF TWO DISPARATE WORLDS

EPA Science Inventory

The existing knowledge base regarding the presence and significance of chemicals foreign to the subsurface environment is large and growing -the papers in this volume serving as recent testament. But complex questions with few answers surround the unknowns regarding the potenti...

61. Picking Floor, Large Pile of Waste Rock and Wood ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

61. Picking Floor, Large Pile of Waste Rock and Wood date unknown Historic Photograph, Photographer Unknown; Collection of William Everett, Jr. (Wilkes-Barre, PA), photocopy by Joseph E.B. Elliot - Huber Coal Breaker, 101 South Main Street, Ashley, Luzerne County, PA

Dynamic Domains in Data Production Planning

NASA Technical Reports Server (NTRS)

Golden, Keith; Pang, Wanlin

2005-01-01

This paper discusses a planner-based approach to automating data production tasks, such as producing fire forecasts from satellite imagery and weather station data. Since the set of available data products is large, dynamic and mostly unknown, planning techniques developed for closed worlds are unsuitable. We discuss a number of techniques we have developed to cope with data production domains, including a novel constraint propagation algorithm based on planning graphs and a constraint-based approach to interleaved planning, sensing and execution.

Gender Differences in Consequences of ADHD Symptoms in a Community-Based Organization for Youth

ERIC Educational Resources Information Center

Vitulano, Michael L.; Fite, Paula J.; Wimsatt, Amber R.; Rathert, Jamie L.; Hatmaker, Rebecca S.

2012-01-01

Attention-Deficit/Hyperactivity Disorder (ADHD) has been linked to disruptive behavior and disciplinary consequences; however, the variables involved in this process are largely unknown. The current study examined rule-breaking behavior as a mediator of the relation between ADHD symptoms and disciplinary actions 1 year later during after-school…

Computer-Based Assessment of Complex Problem Solving: Concept, Implementation, and Application

ERIC Educational Resources Information Center

Greiff, Samuel; Wustenberg, Sascha; Holt, Daniel V.; Goldhammer, Frank; Funke, Joachim

2013-01-01

Complex Problem Solving (CPS) skills are essential to successfully deal with environments that change dynamically and involve a large number of interconnected and partially unknown causal influences. The increasing importance of such skills in the 21st century requires appropriate assessment and intervention methods, which in turn rely on adequate…

Forest Service research natural areas in California

Treesearch

Sheauchi Cheng

2004-01-01

Ecological descriptions of 98 research natural areas (of various statuses) in the Pacific Southwest Region of the USDA Forest Service are summarized in this report. These descriptions, basically based on ecological surveys conducted from 1975 through 2000, provide important but largely unknown information on the ecology of California. For each area, descriptions of...

An improved methodology of asymmetric flow field flow fractionation hyphenated with inductively coupled mass spectrometry for the determination of size distribution of gold nanoparticles in dietary supplements.

PubMed

Mudalige, Thilak K; Qu, Haiou; Linder, Sean W

2015-11-13

Engineered nanoparticles are available in large numbers of commercial products claiming various health benefits. Nanoparticle absorption, distribution, metabolism, excretion, and toxicity in a biological system are dependent on particle size, thus the determination of size and size distribution is essential for full characterization. Number based average size and size distribution is a major parameter for full characterization of the nanoparticle. In the case of polydispersed samples, large numbers of particles are needed to obtain accurate size distribution data. Herein, we report a rapid methodology, demonstrating improved nanoparticle recovery and excellent size resolution, for the characterization of gold nanoparticles in dietary supplements using asymmetric flow field flow fractionation coupled with visible absorption spectrometry and inductively coupled plasma mass spectrometry. A linear relationship between gold nanoparticle size and retention times was observed, and used for characterization of unknown samples. The particle size results from unknown samples were compared to results from traditional size analysis by transmission electron microscopy, and found to have less than a 5% deviation in size for unknown product over the size range from 7 to 30 nm. Published by Elsevier B.V.

Nonlinear unbiased minimum-variance filter for Mars entry autonomous navigation under large uncertainties and unknown measurement bias.

PubMed

Xiao, Mengli; Zhang, Yongbo; Fu, Huimin; Wang, Zhihua

2018-05-01

High-precision navigation algorithm is essential for the future Mars pinpoint landing mission. The unknown inputs caused by large uncertainties of atmospheric density and aerodynamic coefficients as well as unknown measurement biases may cause large estimation errors of conventional Kalman filters. This paper proposes a derivative-free version of nonlinear unbiased minimum variance filter for Mars entry navigation. This filter has been designed to solve this problem by estimating the state and unknown measurement biases simultaneously with derivative-free character, leading to a high-precision algorithm for the Mars entry navigation. IMU/radio beacons integrated navigation is introduced in the simulation, and the result shows that with or without radio blackout, our proposed filter could achieve an accurate state estimation, much better than the conventional unscented Kalman filter, showing the ability of high-precision Mars entry navigation algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

T-BAS: Tree-Based Alignment Selector toolkit for phylogenetic-based placement, alignment downloads and metadata visualization: an example with the Pezizomycotina tree of life.

PubMed

Carbone, Ignazio; White, James B; Miadlikowska, Jolanta; Arnold, A Elizabeth; Miller, Mark A; Kauff, Frank; U'Ren, Jana M; May, Georgiana; Lutzoni, François

2017-04-15

High-quality phylogenetic placement of sequence data has the potential to greatly accelerate studies of the diversity, systematics, ecology and functional biology of diverse groups. We developed the Tree-Based Alignment Selector (T-BAS) toolkit to allow evolutionary placement and visualization of diverse DNA sequences representing unknown taxa within a robust phylogenetic context, and to permit the downloading of highly curated, single- and multi-locus alignments for specific clades. In its initial form, T-BAS v1.0 uses a core phylogeny of 979 taxa (including 23 outgroup taxa, as well as 61 orders, 175 families and 496 genera) representing all 13 classes of largest subphylum of Fungi-Pezizomycotina (Ascomycota)-based on sequence alignments for six loci (nr5.8S, nrLSU, nrSSU, mtSSU, RPB1, RPB2 ). T-BAS v1.0 has three main uses: (i) Users may download alignments and voucher tables for members of the Pezizomycotina directly from the reference tree, facilitating systematics studies of focal clades. (ii) Users may upload sequence files with reads representing unknown taxa and place these on the phylogeny using either BLAST or phylogeny-based approaches, and then use the displayed tree to select reference taxa to include when downloading alignments. The placement of unknowns can be performed for large numbers of Sanger sequences obtained from fungal cultures and for alignable, short reads of environmental amplicons. (iii) User-customizable metadata can be visualized on the tree. T-BAS Version 1.0 is available online at http://tbas.hpc.ncsu.edu . Registration is required to access the CIPRES Science Gateway and NSF XSEDE's large computational resources. icarbon@ncsu.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

[Advances in the management of cervical lymphadenopathies of unknown primary: advances in diagnostic imaging and surgical modalities and new international staging system].

PubMed

Troussier, Idriss; Klausner, Guillaume; Morinière, Sylvain; Blais, Eivind; Jean-Christophe Faivre; Champion, Ambroise; Geoffrois, Lionnel; Pflumio, Carole; Babin, Emmanuel; Maingon, Philippe; Thariat, Juliette

2018-02-01

Cervical lymphadenopathies of unknown primary represent 3 % of head and neck cancers. Their diagnostic work up has largely changed in recent years. This review provides an update on diagnostic developments and their potential therapeutic impact. This is a systematic review of the literature. In recent years, changes in epidemiology-based prognostic factors such as human papilloma virus (HPV) cancers, advances in imaging and minimally invasive surgery have been integrated in the management of cervical lymphadenopathies of unknown primary. In particular, systematic use of PET scanner and increasing practice of robotic or laser surgery have contributed to increasing detection rate of primary cancers. These allow more adapted and personalized treatments. The impact of changes in the eighth TNM staging system is discussed. The management of cervical lymphadenopathies of unknown primary cancer has changed significantly in the last 10 years. On the other hand, practice changes will have to be assessed. Copyright © 2017 Société Française du Cancer. Published by Elsevier Masson SAS. All rights reserved.

A Localization Method for Underwater Wireless Sensor Networks Based on Mobility Prediction and Particle Swarm Optimization Algorithms

PubMed Central

Zhang, Ying; Liang, Jixing; Jiang, Shengming; Chen, Wei

2016-01-01

Due to their special environment, Underwater Wireless Sensor Networks (UWSNs) are usually deployed over a large sea area and the nodes are usually floating. This results in a lower beacon node distribution density, a longer time for localization, and more energy consumption. Currently most of the localization algorithms in this field do not pay enough consideration on the mobility of the nodes. In this paper, by analyzing the mobility patterns of water near the seashore, a localization method for UWSNs based on a Mobility Prediction and a Particle Swarm Optimization algorithm (MP-PSO) is proposed. In this method, the range-based PSO algorithm is used to locate the beacon nodes, and their velocities can be calculated. The velocity of an unknown node is calculated by using the spatial correlation of underwater object’s mobility, and then their locations can be predicted. The range-based PSO algorithm may cause considerable energy consumption and its computation complexity is a little bit high, nevertheless the number of beacon nodes is relatively smaller, so the calculation for the large number of unknown nodes is succinct, and this method can obviously decrease the energy consumption and time cost of localizing these mobile nodes. The simulation results indicate that this method has higher localization accuracy and better localization coverage rate compared with some other widely used localization methods in this field. PMID:26861348

Big-leaf mahogany Swietenia macrophylla population dynamics and implications for sustainable management

Treesearch

James Grogan; R. Matthew Landis; Christopher M. Free; Mark D. Schulze; Marco Lentini; Mark S. Ashton

2014-01-01

Summary 1. The impacts of selective harvesting in tropical forests on population recovery and future timber yields by high-value species remain largely unknown for lack of demographic data spanning all phases of life history, from seed to senescence. In this study, we use an individual- based model parameterized using 15 years of annual census data to simulate...

Marek's disease in backyard chickens, a study of pathological findings and viral loads in tumorous and non-tumorous birds

USDA-ARS?s Scientific Manuscript database

Marek’s disease (MD) is a major cause of mortality in backyard chickens. The diagnosis of MD is complex, however, and knowledge on Marek’s disease virus (MDV) in spontaneous field cases such as in backyard chickens is largely unknown. Forty backyard chickens with presumptive MD diagnosis based on hi...

The Impact of Attention-Deficit/Hyperactivity Disorder on Preadolescent Adjustment May Be Greater for Girls than for Boys

ERIC Educational Resources Information Center

Elkins, Irene J.; Malone, Steve; Keyes, Margaret; Iacono, William G.; McGue, Matt

2011-01-01

Whether gender differences exist in the impairment associated with attention-deficit/hyperactivity disorder (ADHD) is still largely unknown, because most samples have few affected girls or include only one sex. The current study evaluated whether ADHD affects adjustment differently for girls than boys in a population-based cohort of 11-year-olds…

Adjustment technique without explicit formation of normal equations /conjugate gradient method/

NASA Technical Reports Server (NTRS)

Saxena, N. K.

1974-01-01

For a simultaneous adjustment of a large geodetic triangulation system, a semiiterative technique is modified and used successfully. In this semiiterative technique, known as the conjugate gradient (CG) method, original observation equations are used, and thus the explicit formation of normal equations is avoided, 'huge' computer storage space being saved in the case of triangulation systems. This method is suitable even for very poorly conditioned systems where solution is obtained only after more iterations. A detailed study of the CG method for its application to large geodetic triangulation systems was done that also considered constraint equations with observation equations. It was programmed and tested on systems as small as two unknowns and three equations up to those as large as 804 unknowns and 1397 equations. When real data (573 unknowns, 965 equations) from a 1858-km-long triangulation system were used, a solution vector accurate to four decimal places was obtained in 2.96 min after 1171 iterations (i.e., 2.0 times the number of unknowns).

A Collaborative Secure Localization Algorithm Based on Trust Model in Underwater Wireless Sensor Networks

PubMed Central

Han, Guangjie; Liu, Li; Jiang, Jinfang; Shu, Lei; Rodrigues, Joel J.P.C.

2016-01-01

Localization is one of the hottest research topics in Underwater Wireless Sensor Networks (UWSNs), since many important applications of UWSNs, e.g., event sensing, target tracking and monitoring, require location information of sensor nodes. Nowadays, a large number of localization algorithms have been proposed for UWSNs. How to improve location accuracy are well studied. However, few of them take location reliability or security into consideration. In this paper, we propose a Collaborative Secure Localization algorithm based on Trust model (CSLT) for UWSNs to ensure location security. Based on the trust model, the secure localization process can be divided into the following five sub-processes: trust evaluation of anchor nodes, initial localization of unknown nodes, trust evaluation of reference nodes, selection of reference node, and secondary localization of unknown node. Simulation results demonstrate that the proposed CSLT algorithm performs better than the compared related works in terms of location security, average localization accuracy and localization ratio. PMID:26891300

Hybridizable discontinuous Galerkin method for the 2-D frequency-domain elastic wave equations

NASA Astrophysics Data System (ADS)

Bonnasse-Gahot, Marie; Calandra, Henri; Diaz, Julien; Lanteri, Stéphane

2018-04-01

Discontinuous Galerkin (DG) methods are nowadays actively studied and increasingly exploited for the simulation of large-scale time-domain (i.e. unsteady) seismic wave propagation problems. Although theoretically applicable to frequency-domain problems as well, their use in this context has been hampered by the potentially large number of coupled unknowns they incur, especially in the 3-D case, as compared to classical continuous finite element methods. In this paper, we address this issue in the framework of the so-called hybridizable discontinuous Galerkin (HDG) formulations. As a first step, we study an HDG method for the resolution of the frequency-domain elastic wave equations in the 2-D case. We describe the weak formulation of the method and provide some implementation details. The proposed HDG method is assessed numerically including a comparison with a classical upwind flux-based DG method, showing better overall computational efficiency as a result of the drastic reduction of the number of globally coupled unknowns in the resulting discrete HDG system.

Sparse graph regularization for robust crop mapping using hyperspectral remotely sensed imagery with very few in situ data

NASA Astrophysics Data System (ADS)

Xue, Zhaohui; Du, Peijun; Li, Jun; Su, Hongjun

2017-02-01

The generally limited availability of training data relative to the usually high data dimension pose a great challenge to accurate classification of hyperspectral imagery, especially for identifying crops characterized with highly correlated spectra. However, traditional parametric classification models are problematic due to the need of non-singular class-specific covariance matrices. In this research, a novel sparse graph regularization (SGR) method is presented, aiming at robust crop mapping using hyperspectral imagery with very few in situ data. The core of SGR lies in propagating labels from known data to unknown, which is triggered by: (1) the fraction matrix generated for the large unknown data by using an effective sparse representation algorithm with respect to the few training data serving as the dictionary; (2) the prediction function estimated for the few training data by formulating a regularization model based on sparse graph. Then, the labels of large unknown data can be obtained by maximizing the posterior probability distribution based on the two ingredients. SGR is more discriminative, data-adaptive, robust to noise, and efficient, which is unique with regard to previously proposed approaches and has high potentials in discriminating crops, especially when facing insufficient training data and high-dimensional spectral space. The study area is located at Zhangye basin in the middle reaches of Heihe watershed, Gansu, China, where eight crop types were mapped with Compact Airborne Spectrographic Imager (CASI) and Shortwave Infrared Airborne Spectrogrpahic Imager (SASI) hyperspectral data. Experimental results demonstrate that the proposed method significantly outperforms other traditional and state-of-the-art methods.

[Increased occurrence of nuclear cataract in the calf after erection of a mobile phone base station].

PubMed

Hässig, M; Jud, F; Spiess, B

2012-02-01

We examined and monitored a dairy farm in which a large number of calves were born with nuclear cataracts after a mobile phone base station had been erected in the vicinity of the barn. Calves showed a 3.5 times higher risk for heavy cataract if born there compared to Swiss average. All usual causes such as infection or poisoning, common in Switzerland, could be excluded. The real cause of the increased incidence of cataracts remains unknown.

pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree

PubMed Central

2010-01-01

Background Likelihood-based phylogenetic inference is generally considered to be the most reliable classification method for unknown sequences. However, traditional likelihood-based phylogenetic methods cannot be applied to large volumes of short reads from next-generation sequencing due to computational complexity issues and lack of phylogenetic signal. "Phylogenetic placement," where a reference tree is fixed and the unknown query sequences are placed onto the tree via a reference alignment, is a way to bring the inferential power offered by likelihood-based approaches to large data sets. Results This paper introduces pplacer, a software package for phylogenetic placement and subsequent visualization. The algorithm can place twenty thousand short reads on a reference tree of one thousand taxa per hour per processor, has essentially linear time and memory complexity in the number of reference taxa, and is easy to run in parallel. Pplacer features calculation of the posterior probability of a placement on an edge, which is a statistically rigorous way of quantifying uncertainty on an edge-by-edge basis. It also can inform the user of the positional uncertainty for query sequences by calculating expected distance between placement locations, which is crucial in the estimation of uncertainty with a well-sampled reference tree. The software provides visualizations using branch thickness and color to represent number of placements and their uncertainty. A simulation study using reads generated from 631 COG alignments shows a high level of accuracy for phylogenetic placement over a wide range of alignment diversity, and the power of edge uncertainty estimates to measure placement confidence. Conclusions Pplacer enables efficient phylogenetic placement and subsequent visualization, making likelihood-based phylogenetics methodology practical for large collections of reads; it is freely available as source code, binaries, and a web service. PMID:21034504

State estimation of spatio-temporal phenomena

NASA Astrophysics Data System (ADS)

Yu, Dan

This dissertation addresses the state estimation problem of spatio-temporal phenomena which can be modeled by partial differential equations (PDEs), such as pollutant dispersion in the atmosphere. After discretizing the PDE, the dynamical system has a large number of degrees of freedom (DOF). State estimation using Kalman Filter (KF) is computationally intractable, and hence, a reduced order model (ROM) needs to be constructed first. Moreover, the nonlinear terms, external disturbances or unknown boundary conditions can be modeled as unknown inputs, which leads to an unknown input filtering problem. Furthermore, the performance of KF could be improved by placing sensors at feasible locations. Therefore, the sensor scheduling problem to place multiple mobile sensors is of interest. The first part of the dissertation focuses on model reduction for large scale systems with a large number of inputs/outputs. A commonly used model reduction algorithm, the balanced proper orthogonal decomposition (BPOD) algorithm, is not computationally tractable for large systems with a large number of inputs/outputs. Inspired by the BPOD and randomized algorithms, we propose a randomized proper orthogonal decomposition (RPOD) algorithm and a computationally optimal RPOD (RPOD*) algorithm, which construct an ROM to capture the input-output behaviour of the full order model, while reducing the computational cost of BPOD by orders of magnitude. It is demonstrated that the proposed RPOD* algorithm could construct the ROM in real-time, and the performance of the proposed algorithms on different advection-diffusion equations. Next, we consider the state estimation problem of linear discrete-time systems with unknown inputs which can be treated as a wide-sense stationary process with rational power spectral density, while no other prior information needs to be known. We propose an autoregressive (AR) model based unknown input realization technique which allows us to recover the input statistics from the output data by solving an appropriate least squares problem, then fit an AR model to the recovered input statistics and construct an innovations model of the unknown inputs using the eigensystem realization algorithm. The proposed algorithm outperforms the augmented two-stage Kalman Filter (ASKF) and the unbiased minimum-variance (UMV) algorithm are shown in several examples. Finally, we propose a framework to place multiple mobile sensors to optimize the long-term performance of KF in the estimation of the state of a PDE. The major challenges are that placing multiple sensors is an NP-hard problem, and the optimization problem is non-convex in general. In this dissertation, first, we construct an ROM using RPOD* algorithm, and then reduce the feasible sensor locations into a subset using the ROM. The Information Space Receding Horizon Control (I-RHC) approach and a modified Monte Carlo Tree Search (MCTS) approach are applied to solve the sensor scheduling problem using the subset. Various applications have been provided to demonstrate the performance of the proposed approach.

The major-effect quantitative trait locus CsARN6.1 encodes an AAA ATPase domain-containing protein that is associated with waterlogging stress tolerance by promoting adventitious root formation

USDA-ARS?s Scientific Manuscript database

In plants, the formation of hypocotyl-derived adventitious roots (AR) is an important morphological acclimation to waterlogging stress, but its genetic basis is largely unknown. In the present study, with combined use of bulked segregant analysis-based high throughput next-gen whole genome sequencin...

An event-based approach for examining the effects of wildland fire decisions on communities

Treesearch

Stephen F. McCool; James A. Burchfield; Daniel R. Williams; Matthew S. Carroll

2006-01-01

Public concern over the consequences of forest fire to wildland interface communities has led to increased resources devoted to fire suppression, fuel treatment, and management of fire events. The social consequences of the decisions involved in these and other fire-related actions are largely unknown, except in an anecdotal sense, but do occur at a variety of temporal...

An Exploratory Analysis of Economic Factors in the Navy Total Force Strength Model (NTFSM)

DTIC Science & Technology

2015-12-01

NTFSM is still in the testing phase and its overall behavior is largely unknown. In particular, the analysts that NTFSM was designed to help are...NTFSM is still in the testing phase and its overall behavior is largely unknown. In particular, the analysts that NTFSM was designed to help are...7 B. NTFSM VERIFICATION AND TESTING ......................................... 8 C

Minimal-Approximation-Based Decentralized Backstepping Control of Interconnected Time-Delay Systems.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2016-12-01

A decentralized adaptive backstepping control design using minimal function approximators is proposed for nonlinear large-scale systems with unknown unmatched time-varying delayed interactions and unknown backlash-like hysteresis nonlinearities. Compared with existing decentralized backstepping methods, the contribution of this paper is to design a simple local control law for each subsystem, consisting of an actual control with one adaptive function approximator, without requiring the use of multiple function approximators and regardless of the order of each subsystem. The virtual controllers for each subsystem are used as intermediate signals for designing a local actual control at the last step. For each subsystem, a lumped unknown function including the unknown nonlinear terms and the hysteresis nonlinearities is derived at the last step and is estimated by one function approximator. Thus, the proposed approach only uses one function approximator to implement each local controller, while existing decentralized backstepping control methods require the number of function approximators equal to the order of each subsystem and a calculation of virtual controllers to implement each local actual controller. The stability of the total controlled closed-loop system is analyzed using the Lyapunov stability theorem.

Solutions of large-scale electromagnetics problems involving dielectric objects with the parallel multilevel fast multipole algorithm.

PubMed

Ergül, Özgür

2011-11-01

Fast and accurate solutions of large-scale electromagnetics problems involving homogeneous dielectric objects are considered. Problems are formulated with the electric and magnetic current combined-field integral equation and discretized with the Rao-Wilton-Glisson functions. Solutions are performed iteratively by using the multilevel fast multipole algorithm (MLFMA). For the solution of large-scale problems discretized with millions of unknowns, MLFMA is parallelized on distributed-memory architectures using a rigorous technique, namely, the hierarchical partitioning strategy. Efficiency and accuracy of the developed implementation are demonstrated on very large problems involving as many as 100 million unknowns.

Elucidation of the ‘Honeycrisp’ pedigree through haplotype analysis with a multi-family integrated SNP linkage map and a large apple (Malus×domestica) pedigree-connected SNP data set

PubMed Central

Howard, Nicholas P; van de Weg, Eric; Bedford, David S; Peace, Cameron P; Vanderzande, Stijn; Clark, Matthew D; Teh, Soon Li; Cai, Lichun; Luby, James J

2017-01-01

The apple (Malus×domestica) cultivar Honeycrisp has become important economically and as a breeding parent. An earlier study with SSR markers indicated the original recorded pedigree of ‘Honeycrisp’ was incorrect and ‘Keepsake’ was identified as one putative parent, the other being unknown. The objective of this study was to verify ‘Keepsake’ as a parent and identify and genetically describe the unknown parent and its grandparents. A multi-family based dense and high-quality integrated SNP map was created using the apple 8 K Illumina Infinium SNP array. This map was used alongside a large pedigree-connected data set from the RosBREED project to build extended SNP haplotypes and to identify pedigree relationships. ‘Keepsake’ was verified as one parent of ‘Honeycrisp’ and ‘Duchess of Oldenburg’ and ‘Golden Delicious’ were identified as grandparents through the unknown parent. Following this finding, siblings of ‘Honeycrisp’ were identified using the SNP data. Breeding records from several of these siblings suggested that the previously unreported parent is a University of Minnesota selection, MN1627. This selection is no longer available, but now is genetically described through imputed SNP haplotypes. We also present the mosaic grandparental composition of ‘Honeycrisp’ for each of its 17 chromosome pairs. This new pedigree and genetic information will be useful in future pedigree-based genetic studies to connect ‘Honeycrisp’ with other cultivars used widely in apple breeding programs. The created SNP linkage map will benefit future research using the data from the Illumina apple 8 and 20 K and Affymetrix 480 K SNP arrays. PMID:28243452

Respiratory Acid-Base Disorders in the Critical Care Unit.

PubMed

Hopper, Kate

2017-03-01

The incidence of respiratory acid-base abnormalities in the critical care unit (CCU) is unknown, although respiratory alkalosis is suspected to be common in this population. Abnormal carbon dioxide tension can have many physiologic effects, and changes in Pco 2 may have a significant impact on outcome. Monitoring Pco 2 in CCU patients is an important aspect of critical patient assessment, and identification of respiratory acid-base abnormalities can be valuable as a diagnostic tool. Treatment of respiratory acid-base disorders is largely focused on resolution of the primary disease, although mechanical ventilation may be indicated in cases with severe respiratory acidosis. Published by Elsevier Inc.

Photocopy of photograph (from NBPPNSY) photographer unknown, c. 1950's view ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph (from NBP-PNSY) photographer unknown, c. 1950's view northwest from 350-ton crane of drydock no. 2 (Haer no. Pa-387-B), 1950's. Pump house for the drydock is the round building below center of the photograph. The large building at the left center is building 546, the Turret Shop where naval gun turrets were assembled at the center rear is the foundry/propeller shop (Haer No. Pa-387-O) built in 1919. The foundry/propeller shop (building no. 20), designed by Warren-Moore and Company, resembles the Contemporaneous Architecture of Albert Kahn, who designed similar buildings for Henry Ford and the Chrysler Corporation in the 1920's and 1930's. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

Label-assisted mass spectrometry for the acceleration of reaction discovery and optimization

NASA Astrophysics Data System (ADS)

Cabrera-Pardo, Jaime R.; Chai, David I.; Liu, Song; Mrksich, Milan; Kozmin, Sergey A.

2013-05-01

The identification of new reactions expands our knowledge of chemical reactivity and enables new synthetic applications. Accelerating the pace of this discovery process remains challenging. We describe a highly effective and simple platform for screening a large number of potential chemical reactions in order to discover and optimize previously unknown catalytic transformations, thereby revealing new chemical reactivity. Our strategy is based on labelling one of the reactants with a polyaromatic chemical tag, which selectively undergoes a photoionization/desorption process upon laser irradiation, without the assistance of an external matrix, and enables rapid mass spectrometric detection of any products originating from such labelled reactants in complex reaction mixtures without any chromatographic separation. This method was successfully used for high-throughput discovery and subsequent optimization of two previously unknown benzannulation reactions.

Perfect blind restoration of images blurred by multiple filters: theory and efficient algorithms.

PubMed

Harikumar, G; Bresler, Y

1999-01-01

We address the problem of restoring an image from its noisy convolutions with two or more unknown finite impulse response (FIR) filters. We develop theoretical results about the existence and uniqueness of solutions, and show that under some generically true assumptions, both the filters and the image can be determined exactly in the absence of noise, and stably estimated in its presence. We present efficient algorithms to estimate the blur functions and their sizes. These algorithms are of two types, subspace-based and likelihood-based, and are extensions of techniques proposed for the solution of the multichannel blind deconvolution problem in one dimension. We present memory and computation-efficient techniques to handle the very large matrices arising in the two-dimensional (2-D) case. Once the blur functions are determined, they are used in a multichannel deconvolution step to reconstruct the unknown image. The theoretical and practical implications of edge effects, and "weakly exciting" images are examined. Finally, the algorithms are demonstrated on synthetic and real data.

End-to-End Commitment

NASA Technical Reports Server (NTRS)

Newcomb, John

2004-01-01

The end-to-end test would verify the complex sequence of events from lander separation to landing. Due to the large distances involved and the significant delay time in sending a command and receiving verification, the lander needed to operate autonomously after it separated from the orbiter. It had to sense conditions, make decisions, and act accordingly. We were flying into a relatively unknown set of conditions-a Martian atmosphere of unknown pressure, density, and consistency to land on a surface of unknown altitude, and one which had an unknown bearing strength.

U.S. Nuclear Weapons Enterprise: A Strategic Past and Unknown Future

DTIC Science & Technology

2012-04-25

are left to base their planning assumptions, weapons designs and capabilities on outdated models . The likelihood of a large-scale nuclear war has...conduct any testing on nuclear weapons and must rely on computer modeling . While this may provide sufficient confidence in the current nuclear...unlikely the world will be free of nuclear weapons. 24 APPENDIX A – Acronyms ACC – Air Combat Command ACM – Advanced cruise missle CSAF

[Pilot study of domain-specific terminology adaptation for morphological analysis: research on unknown terms in national examination documents of radiological technologists].

PubMed

Tsuji, Shintarou; Nishimoto, Naoki; Ogasawara, Katsuhiko

2008-07-20

Although large medical texts are stored in electronic format, they are seldom reused because of the difficulty of processing narrative texts by computer. Morphological analysis is a key technology for extracting medical terms correctly and automatically. This process parses a sentence into its smallest unit, the morpheme. Phrases consisting of two or more technical terms, however, cause morphological analysis software to fail in parsing the sentence and output unprocessed terms as "unknown words." The purpose of this study was to reduce the number of unknown words in medical narrative text processing. The results of parsing the text with additional dictionaries were compared with the analysis of the number of unknown words in the national examination for radiologists. The ratio of unknown words was reduced 1.0% to 0.36% by adding terminologies of radiological technology, MeSH, and ICD-10 labels. The terminology of radiological technology was the most effective resource, being reduced by 0.62%. This result clearly showed the necessity of additional dictionary selection and trends in unknown words. The potential for this investigation is to make available a large body of clinical information that would otherwise be inaccessible for applications other than manual health care review by personnel.

Extended state observer-based motion synchronisation control for hybrid actuation system of large civil aircraft

NASA Astrophysics Data System (ADS)

Wang, Xingjian; Shi, Cun; Wang, Shaoping

2017-07-01

Hybrid actuation system with dissimilar redundant actuators, which is composed of a hydraulic actuator (HA) and an electro-hydrostatic actuator (EHA), has been applied on modern civil aircraft to improve the reliability. However, the force fighting problem arises due to different dynamic performances between HA and EHA. This paper proposes an extended state observer (ESO)-based motion synchronisation control method. To cope with the problem of unavailability of the state signals, the well-designed ESO is utilised to observe the HA and EHA state variables which are unmeasured. In particular, the extended state of ESO can estimate the lumped effect of the unknown external disturbances acting on the control surface, the nonlinear dynamics, uncertainties, and the coupling term between HA and EHA. Based on the observed states of ESO, motion synchronisation controllers are presented to make HA and EHA to simultaneously track the desired motion trajectories, which are generated by a trajectory generator. Additionally, the unknown disturbances and the coupling terms can be compensated by using the extended state of the proposed ESO. Finally, comparative simulation results indicate that the proposed ESO-based motion synchronisation controller can achieve great force fighting reduction between HA and EHA.

Biological considerations in the delineation of critical habitat

USGS Publications Warehouse

Knight, Richard R.

1980-01-01

Grizzly bears (Ursus arctos) require large areas to satisfy their needs for food, cover, and space. They thrive best where disturbance by man is minimal. It is not a coincidence that the two major grizzly bear populations in the lower 48 states exist in large wilderness systems closely associated with two large national parks and a relatively large game preserve. If management objectives for these areas do not change, and man-bear interactions can be kept low, viable grizzly bear populations can be maintained. Outside of parks and wilderness areas, the picture is less clear. Grizzly bears adapt to some habitat modifications. the extent of their adaptability to habitat modification or human interaction is largely unknown. Answers to many pertinent questions will be slow in coming. In the meantime, management policies based on common sense rather than on adversary reactions among agencies are the best insurance of the grizzlies' survival.

Architecture of a Diels-Alderase ribozyme with a preformed catalytic pocket.

PubMed

Keiper, Sonja; Bebenroth, Dirk; Seelig, Burckhard; Westhof, Eric; Jäschke, Andres

2004-09-01

Artificial ribozymes catalyze a variety of chemical reactions. Their structures and reaction mechanisms are largely unknown. We have analyzed a ribozyme catalyzing Diels-Alder cycloaddition reactions by comprehensive mutation analysis and a variety of probing techniques. New tertiary interactions involving base pairs between nucleotides of the 5' terminus and a large internal loop forming a pseudoknot fold were identified. The probing data indicate a preformed tertiary structure that shows no major changes on substrate or product binding. Based on these observations, a molecular architecture featuring a Y-shaped arrangement is proposed. The tertiary structure is formed in a rather unusual way; that is, the opposite sides of the asymmetric internal loop are clamped by the four 5'-terminal nucleotides, forming two adjacent two base-pair helices. It is proposed that the catalytic pocket is formed by a wedge within one of these helices.

Functional Genome Mining for Metabolites Encoded by Large Gene Clusters through Heterologous Expression of a Whole-Genome Bacterial Artificial Chromosome Library in Streptomyces spp.

PubMed Central

Xu, Min; Wang, Yemin; Zhao, Zhilong; Gao, Guixi; Huang, Sheng-Xiong; Kang, Qianjin; He, Xinyi; Lin, Shuangjun; Pang, Xiuhua; Deng, Zixin

2016-01-01

ABSTRACT Genome sequencing projects in the last decade revealed numerous cryptic biosynthetic pathways for unknown secondary metabolites in microbes, revitalizing drug discovery from microbial metabolites by approaches called genome mining. In this work, we developed a heterologous expression and functional screening approach for genome mining from genomic bacterial artificial chromosome (BAC) libraries in Streptomyces spp. We demonstrate mining from a strain of Streptomyces rochei, which is known to produce streptothricins and borrelidin, by expressing its BAC library in the surrogate host Streptomyces lividans SBT5, and screening for antimicrobial activity. In addition to the successful capture of the streptothricin and borrelidin biosynthetic gene clusters, we discovered two novel linear lipopeptides and their corresponding biosynthetic gene cluster, as well as a novel cryptic gene cluster for an unknown antibiotic from S. rochei. This high-throughput functional genome mining approach can be easily applied to other streptomycetes, and it is very suitable for the large-scale screening of genomic BAC libraries for bioactive natural products and the corresponding biosynthetic pathways. IMPORTANCE Microbial genomes encode numerous cryptic biosynthetic gene clusters for unknown small metabolites with potential biological activities. Several genome mining approaches have been developed to activate and bring these cryptic metabolites to biological tests for future drug discovery. Previous sequence-guided procedures relied on bioinformatic analysis to predict potentially interesting biosynthetic gene clusters. In this study, we describe an efficient approach based on heterologous expression and functional screening of a whole-genome library for the mining of bioactive metabolites from Streptomyces. The usefulness of this function-driven approach was demonstrated by the capture of four large biosynthetic gene clusters for metabolites of various chemical types, including streptothricins, borrelidin, two novel lipopeptides, and one unknown antibiotic from Streptomyces rochei Sal35. The transfer, expression, and screening of the library were all performed in a high-throughput way, so that this approach is scalable and adaptable to industrial automation for next-generation antibiotic discovery. PMID:27451447

On Space Exploration and Human Error: A Paper on Reliability and Safety

NASA Technical Reports Server (NTRS)

Bell, David G.; Maluf, David A.; Gawdiak, Yuri

2005-01-01

NASA space exploration should largely address a problem class in reliability and risk management stemming primarily from human error, system risk and multi-objective trade-off analysis, by conducting research into system complexity, risk characterization and modeling, and system reasoning. In general, in every mission we can distinguish risk in three possible ways: a) known-known, b) known-unknown, and c) unknown-unknown. It is probably almost certain that space exploration will partially experience similar known or unknown risks embedded in the Apollo missions, Shuttle or Station unless something alters how NASA will perceive and manage safety and reliability

Reconstructing high-dimensional two-photon entangled states via compressive sensing

PubMed Central

Tonolini, Francesco; Chan, Susan; Agnew, Megan; Lindsay, Alan; Leach, Jonathan

2014-01-01

Accurately establishing the state of large-scale quantum systems is an important tool in quantum information science; however, the large number of unknown parameters hinders the rapid characterisation of such states, and reconstruction procedures can become prohibitively time-consuming. Compressive sensing, a procedure for solving inverse problems by incorporating prior knowledge about the form of the solution, provides an attractive alternative to the problem of high-dimensional quantum state characterisation. Using a modified version of compressive sensing that incorporates the principles of singular value thresholding, we reconstruct the density matrix of a high-dimensional two-photon entangled system. The dimension of each photon is equal to d = 17, corresponding to a system of 83521 unknown real parameters. Accurate reconstruction is achieved with approximately 2500 measurements, only 3% of the total number of unknown parameters in the state. The algorithm we develop is fast, computationally inexpensive, and applicable to a wide range of quantum states, thus demonstrating compressive sensing as an effective technique for measuring the state of large-scale quantum systems. PMID:25306850

ACOG Practice Bulletin No. 194: Polycystic Ovary Syndrome.

PubMed

2018-06-01

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovaries. Its etiology remains unknown, and treatment is largely symptom based and empirical. PCOS has the potential to cause substantial metabolic sequelae, including an increased risk of diabetes and cardiovascular disease, and these factors should be considered when determining long-term treatment. The purpose of this document is to examine the best available evidence for the diagnosis and clinical management of PCOS.

ACOG Practice Bulletin No. 194 Summary: Polycystic Ovary Syndrome.

PubMed

2018-06-01

Polycystic ovary syndrome (PCOS) is a disorder characterized by hyperandrogenism, ovulatory dysfunction, and polycystic ovaries. Its etiology remains unknown, and treatment is largely symptom based and empirical. PCOS has the potential to cause substantial metabolic sequelae, including an increased risk of diabetes and cardiovascular disease, and these factors should be considered when determining long-term treatment. The purpose of this document is to examine the best available evidence for the diagnosis and clinical management of PCOS.

The Connection Between Art, Healing, and Public Health: A Review of Current Literature

PubMed Central

Nobel, Jeremy

2010-01-01

This review explores the relationship between engagement with the creative arts and health outcomes, specifically the health effects of music engagement, visual arts therapy, movement-based creative expression, and expressive writing. Although there is evidence that art-based interventions are effective in reducing adverse physiological and psychological outcomes, the extent to which these interventions enhance health status is largely unknown. Our hope is to establish a foundation for continued investigation into this subject and to generate further interest in researching the complexities of engagement with the arts and health. PMID:20019311

Inquiry-based experiments for large-scale introduction to PCR and restriction enzyme digests.

PubMed

Johanson, Kelly E; Watt, Terry J

2015-01-01

Polymerase chain reaction and restriction endonuclease digest are important techniques that should be included in all Biochemistry and Molecular Biology laboratory curriculums. These techniques are frequently taught at an advanced level, requiring many hours of student and faculty time. Here we present two inquiry-based experiments that are designed for introductory laboratory courses and combine both techniques. In both approaches, students must determine the identity of an unknown DNA sequence, either a gene sequence or a primer sequence, based on a combination of PCR product size and restriction digest pattern. The experimental design is flexible, and can be adapted based on available instructor preparation time and resources, and both approaches can accommodate large numbers of students. We implemented these experiments in our courses with a combined total of 584 students and have an 85% success rate. Overall, students demonstrated an increase in their understanding of the experimental topics, ability to interpret the resulting data, and proficiency in general laboratory skills. © 2015 The International Union of Biochemistry and Molecular Biology.

Detecting fission from special nuclear material sources

DOEpatents

Rowland, Mark S [Alamo, CA; Snyderman, Neal J [Berkeley, CA

2012-06-05

A neutron detector system for discriminating fissile material from non-fissile material wherein a digital data acquisition unit collects data at high rate, and in real-time processes large volumes of data directly into information that a first responder can use to discriminate materials. The system comprises counting neutrons from the unknown source and detecting excess grouped neutrons to identify fission in the unknown source. The system includes a graphing component that displays the plot of the neutron distribution from the unknown source over a Poisson distribution and a plot of neutrons due to background or environmental sources. The system further includes a known neutron source placed in proximity to the unknown source to actively interrogate the unknown source in order to accentuate differences in neutron emission from the unknown source from Poisson distributions and/or environmental sources.

Theropod courtship: large scale physical evidence of display arenas and avian-like scrape ceremony behaviour by Cretaceous dinosaurs.

PubMed

Lockley, Martin G; McCrea, Richard T; Buckley, Lisa G; Lim, Jong Deock; Matthews, Neffra A; Breithaupt, Brent H; Houck, Karen J; Gierliński, Gerard D; Surmik, Dawid; Kim, Kyung Soo; Xing, Lida; Kong, Dal Yong; Cart, Ken; Martin, Jason; Hadden, Glade

2016-01-07

Relationships between non-avian theropod dinosaurs and extant and fossil birds are a major focus of current paleobiological research. Despite extensive phylogenetic and morphological support, behavioural evidence is mostly ambiguous and does not usually fossilize. Thus, inferences that dinosaurs, especially theropods displayed behaviour analogous to modern birds are intriguing but speculative. Here we present extensive and geographically widespread physical evidence of substrate scraping behavior by large theropods considered as compelling evidence of "display arenas" or leks, and consistent with "nest scrape display" behaviour among many extant ground-nesting birds. Large scrapes, up to 2 m in diameter, occur abundantly at several Cretaceous sites in Colorado. They constitute a previously unknown category of large dinosaurian trace fossil, inferred to fill gaps in our understanding of early phases in the breeding cycle of theropods. The trace makers were probably lekking species that were seasonally active at large display arena sites. Such scrapes indicate stereotypical avian behaviour hitherto unknown among Cretaceous theropods, and most likely associated with terrirorial activity in the breeding season. The scrapes most probably occur near nesting colonies, as yet unknown or no longer preserved in the immediate study areas. Thus, they provide clues to paleoenvironments where such nesting sites occurred.

Early signs of recovery of Acropora palmata in St. John, US Virgin Islands

USGS Publications Warehouse

Muller, E.M.; Rogers, Caroline S.; van Woesik, R.

2014-01-01

Since the 1980s, diseases have caused significant declines in the population of the threatened Caribbean coral Acropora palmata. Yet it is largely unknown whether the population densities have recovered from these declines and whether there have been any recent shifts in size-frequency distributions toward large colonies. It is also unknown whether colony size influences the risk of disease infection, the most common stressor affecting this species. To address these unknowns, we examined A. palmata colonies at ten sites around St. John, US Virgin Islands, in 2004 and 2010. The prevalence of white-pox disease was highly variable among sites, ranging from 0 to 53 %, and this disease preferentially targeted large colonies. We found that colony density did not significantly change over the 6-year period, although six out of ten sites showed higher densities through time. The size-frequency distributions of coral colonies at all sites were positively skewed in both 2004 and 2010, however, most sites showed a temporal shift toward more large-sized colonies. This increase in large-sized colonies occurred despite the presence of white-pox disease, a severe bleaching event, and several storms. This study provides evidence of slow recovery of the A. palmata population around St. John despite the persistence of several stressors.

Theropod courtship: large scale physical evidence of display arenas and avian-like scrape ceremony behaviour by Cretaceous dinosaurs

NASA Astrophysics Data System (ADS)

Lockley, Martin G.; McCrea, Richard T.; Buckley, Lisa G.; Deock Lim, Jong; Matthews, Neffra A.; Breithaupt, Brent H.; Houck, Karen J.; Gierliński, Gerard D.; Surmik, Dawid; Soo Kim, Kyung; Xing, Lida; Yong Kong, Dal; Cart, Ken; Martin, Jason; Hadden, Glade

2016-01-01

Relationships between non-avian theropod dinosaurs and extant and fossil birds are a major focus of current paleobiological research. Despite extensive phylogenetic and morphological support, behavioural evidence is mostly ambiguous and does not usually fossilize. Thus, inferences that dinosaurs, especially theropods displayed behaviour analogous to modern birds are intriguing but speculative. Here we present extensive and geographically widespread physical evidence of substrate scraping behavior by large theropods considered as compelling evidence of “display arenas” or leks, and consistent with “nest scrape display” behaviour among many extant ground-nesting birds. Large scrapes, up to 2 m in diameter, occur abundantly at several Cretaceous sites in Colorado. They constitute a previously unknown category of large dinosaurian trace fossil, inferred to fill gaps in our understanding of early phases in the breeding cycle of theropods. The trace makers were probably lekking species that were seasonally active at large display arena sites. Such scrapes indicate stereotypical avian behaviour hitherto unknown among Cretaceous theropods, and most likely associated with terrirorial activity in the breeding season. The scrapes most probably occur near nesting colonies, as yet unknown or no longer preserved in the immediate study areas. Thus, they provide clues to paleoenvironments where such nesting sites occurred.

Theropod courtship: large scale physical evidence of display arenas and avian-like scrape ceremony behaviour by Cretaceous dinosaurs

PubMed Central

Lockley, Martin G.; McCrea, Richard T.; Buckley, Lisa G.; Deock Lim, Jong; Matthews, Neffra A.; Breithaupt, Brent H.; Houck, Karen J.; Gierliński, Gerard D.; Surmik, Dawid; Soo Kim, Kyung; Xing, Lida; Yong Kong, Dal; Cart, Ken; Martin, Jason; Hadden, Glade

2016-01-01

Relationships between non-avian theropod dinosaurs and extant and fossil birds are a major focus of current paleobiological research. Despite extensive phylogenetic and morphological support, behavioural evidence is mostly ambiguous and does not usually fossilize. Thus, inferences that dinosaurs, especially theropods displayed behaviour analogous to modern birds are intriguing but speculative. Here we present extensive and geographically widespread physical evidence of substrate scraping behavior by large theropods considered as compelling evidence of “display arenas” or leks, and consistent with “nest scrape display” behaviour among many extant ground-nesting birds. Large scrapes, up to 2 m in diameter, occur abundantly at several Cretaceous sites in Colorado. They constitute a previously unknown category of large dinosaurian trace fossil, inferred to fill gaps in our understanding of early phases in the breeding cycle of theropods. The trace makers were probably lekking species that were seasonally active at large display arena sites. Such scrapes indicate stereotypical avian behaviour hitherto unknown among Cretaceous theropods, and most likely associated with terrirorial activity in the breeding season. The scrapes most probably occur near nesting colonies, as yet unknown or no longer preserved in the immediate study areas. Thus, they provide clues to paleoenvironments where such nesting sites occurred. PMID:26741567

Chaotic Traversal (CHAT): Very Large Graphs Traversal Using Chaotic Dynamics

NASA Astrophysics Data System (ADS)

Changaival, Boonyarit; Rosalie, Martin; Danoy, Grégoire; Lavangnananda, Kittichai; Bouvry, Pascal

2017-12-01

Graph Traversal algorithms can find their applications in various fields such as routing problems, natural language processing or even database querying. The exploration can be considered as a first stepping stone into knowledge extraction from the graph which is now a popular topic. Classical solutions such as Breadth First Search (BFS) and Depth First Search (DFS) require huge amounts of memory for exploring very large graphs. In this research, we present a novel memoryless graph traversal algorithm, Chaotic Traversal (CHAT) which integrates chaotic dynamics to traverse large unknown graphs via the Lozi map and the Rössler system. To compare various dynamics effects on our algorithm, we present an original way to perform the exploration of a parameter space using a bifurcation diagram with respect to the topological structure of attractors. The resulting algorithm is an efficient and nonresource demanding algorithm, and is therefore very suitable for partial traversal of very large and/or unknown environment graphs. CHAT performance using Lozi map is proven superior than the, commonly known, Random Walk, in terms of number of nodes visited (coverage percentage) and computation time where the environment is unknown and memory usage is restricted.

Geological and hydrogeological investigations in west Malaysia

NASA Technical Reports Server (NTRS)

Ahmad, J. B. (Principal Investigator); Khoon, S. Y.

1977-01-01

The author has identified the following significant results. Large structures along the east coast of the peninsula were discovered. Of particular significance were the circular structures which were believed to be associated with mineralization and whose existence was unknown. The distribution of the younger sediments along the east coast appeared to be more widespread than previously indicated. Along the Pahang coast on the southern end, small traces of raised beach lines were noted up to six miles inland. The existence of these beach lines was unknown due to their isolation in large coastal swamps.

Protein function prediction using neighbor relativity in protein-protein interaction network.

PubMed

Moosavi, Sobhan; Rahgozar, Masoud; Rahimi, Amir

2013-04-01

There is a large gap between the number of discovered proteins and the number of functionally annotated ones. Due to the high cost of determining protein function by wet-lab research, function prediction has become a major task for computational biology and bioinformatics. Some researches utilize the proteins interaction information to predict function for un-annotated proteins. In this paper, we propose a novel approach called "Neighbor Relativity Coefficient" (NRC) based on interaction network topology which estimates the functional similarity between two proteins. NRC is calculated for each pair of proteins based on their graph-based features including distance, common neighbors and the number of paths between them. In order to ascribe function to an un-annotated protein, NRC estimates a weight for each neighbor to transfer its annotation to the unknown protein. Finally, the unknown protein will be annotated by the top score transferred functions. We also investigate the effect of using different coefficients for various types of functions. The proposed method has been evaluated on Saccharomyces cerevisiae and Homo sapiens interaction networks. The performance analysis demonstrates that NRC yields better results in comparison with previous protein function prediction approaches that utilize interaction network. Copyright © 2012 Elsevier Ltd. All rights reserved.

EFFECTS OF LARGE-SCALE POULTRY FARMS ON AQUATIC MICROBIAL COMMUNITIES: A MOLECULAR INVESTIGATION.

EPA Science Inventory

The effects of large-scale poultry production operations on water quality and human health are largely unknown. Poultry litter is frequently applied as fertilizer to agricultural lands adjacent to large poultry farms. Run-off from the land introduces a variety of stressors into t...

Novel immunotherapeutic strategies in chronic inflammatory demyelinating polyneuropathy.

PubMed

Mathis, Stéphane; Vallat, Jean-Michel; Magy, Laurent

2016-02-01

Chronic inflammatory demyelinating polyradiculoneuropathy (CIDP) is a chronic immune-mediated neuropathy: it is clinically heterogeneous (relapsing-remitting form, chronic progressive form, monophasic form or CIDP having a Guillain-Barré syndrome-like onset), but potentially treatable. Although its pathophysiology remains largely unknown, CIDP is considered an immune-mediated neuropathy. Therefore, many immunotherapies have been proposed in this peripheral nervous system disorder, the most known efficient treatments being intravenous immunoglobulin, corticosteroids and plasma exchange. However, these therapies remain unsatisfactory for many patients, so numerous other immunotherapeutic strategies have been evaluated, based on their immunosuppressant or immunomodulatory potency. We have performed a large review of the literature about treatment in CIDP, with a special emphasis on novel and alternative immunotherapeutic strategies.

Decentralized Adaptive Neural Output-Feedback DSC for Switched Large-Scale Nonlinear Systems.

PubMed

Lijun Long; Jun Zhao

2017-04-01

In this paper, for a class of switched large-scale uncertain nonlinear systems with unknown control coefficients and unmeasurable states, a switched-dynamic-surface-based decentralized adaptive neural output-feedback control approach is developed. The approach proposed extends the classical dynamic surface control (DSC) technique for nonswitched version to switched version by designing switched first-order filters, which overcomes the problem of multiple "explosion of complexity." Also, a dual common coordinates transformation of all subsystems is exploited to avoid individual coordinate transformations for subsystems that are required when applying the backstepping recursive design scheme. Nussbaum-type functions are utilized to handle the unknown control coefficients, and a switched neural network observer is constructed to estimate the unmeasurable states. Combining with the average dwell time method and backstepping and the DSC technique, decentralized adaptive neural controllers of subsystems are explicitly designed. It is proved that the approach provided can guarantee the semiglobal uniformly ultimately boundedness for all the signals in the closed-loop system under a class of switching signals with average dwell time, and the tracking errors to a small neighborhood of the origin. A two inverted pendulums system is provided to demonstrate the effectiveness of the method proposed.

Stroke With Unknown Time of Symptom Onset: Baseline Clinical and Magnetic Resonance Imaging Data of the First Thousand Patients in WAKE-UP (Efficacy and Safety of MRI-Based Thrombolysis in Wake-Up Stroke: A Randomized, Doubleblind, Placebo-Controlled Trial).

PubMed

Thomalla, Götz; Boutitie, Florent; Fiebach, Jochen B; Simonsen, Claus Z; Nighoghossian, Norbert; Pedraza, Salvador; Lemmens, Robin; Roy, Pascal; Muir, Keith W; Ebinger, Martin; Ford, Ian; Cheng, Bastian; Galinovic, Ivana; Cho, Tae-Hee; Puig, Josep; Thijs, Vincent; Endres, Matthias; Fiehler, Jens; Gerloff, Christian

2017-03-01

We describe clinical and magnetic resonance imaging (MRI) characteristics of stroke patients with unknown time of symptom onset potentially eligible for thrombolysis from a large prospective cohort. We analyzed baseline data from WAKE-UP (Efficacy and Safety of MRI-Based Thrombolysis in Wake-Up Stroke: A Randomized, Doubleblind, Placebo-Controlled Trial), an investigator-initiated, randomized, placebo-controlled trial of MRI-based thrombolysis in stroke patients with unknown time of symptom onset. MRI judgment included assessment of the mismatch between visibility of the acute ischemic lesion on diffusion-weighted imaging and fluid-attenuated inversion recovery. Of 1005 patients included, diffusion-weighted imaging and fluid-attenuated inversion recovery mismatch was present in 479 patients (48.0%). Patients with daytime-unwitnessed stroke (n=138, 13.7%) had a shorter delay between symptom recognition and hospital arrival (1.5 versus 1.8 hours; P =0.002), a higher National Institutes of Stroke Scale score on admission (8 versus 6; P <0.001), and more often aphasia (72.5% versus 34.0%; P <0.001) when compared with stroke patients waking up from nighttime sleep. Frequency of diffusion-weighted imaging and fluid-attenuated inversion recovery mismatch was comparable between both groups (43.7% versus 48.7%; P =0.30). Almost half of the patients with unknown time of symptom onset stroke otherwise eligible for thrombolysis had MRI findings making them likely to be within a time window for safe and effective thrombolysis. Patients with daytime onset unwitnessed stroke differ from wake-up stroke patients with regards to clinical characteristics but are comparable in terms of MRI characteristics of lesion age. URL: http://www.clinicaltrials.gov. Unique identifier: NCT01525290. URL: https://www.clinicaltrialsregister.eu. Unique identifier: 2011-005906-32. © 2017 American Heart Association, Inc.

Cotargeting VEGF and Neuropilins with Bevacizumab and Secreted Wnt Inhibitors in Prostate Cancer

DTIC Science & Technology

2012-09-18

18. NUMBER OF PAGES 19a. NAME OF RESPONSIBLE PERSON USAMRMC a. REPORT U b. ABSTRACT U c . THIS PAGE U UU 12 19b. TELEPHONE...largely unknown. Neuropilin-2 (NRP2) and c -Met are co-receptors with each other and with VEGF receptors [3, 4]. Accumulating studies have...implicated that both NRP2 and c -Met play important roles in tumor progression and metastasis and are involved in angiogenesis [3, 4]. Based on our

Proceedings of the Annual Environmental Systems Symposium (12th) Held on May 20-21 1982 at Langley Air Force Base, Virginia

DTIC Science & Technology

1982-01-01

have become highly sensitized to the potential long-term health and environmental effects of the so-called "toxic * and hazardous chemicals," which...their assumption of the Defense Disposal mission. The PCB collection and disposal exercise will be on-going for several years. PCB disposal is by...imposed with respect to the disposal of *. materials at a time when their effects were largely unknown (and in many cases still are). Moreover, the

Gpm Level 1 Science Requirements: Science and Performance Viewed from the Ground

NASA Technical Reports Server (NTRS)

Petersen, W.; Kirstetter, P.; Wolff, D.; Kidd, C.; Tokay, A.; Chandrasekar, V.; Grecu, M.; Huffman, G.; Jackson, G. S.

2016-01-01

GPM meets Level 1 science requirements for rain estimation based on the strong performance of its radar algorithms. Changes in the V5 GPROF algorithm should correct errors in V4 and will likely resolve GPROF performance issues relative to L1 requirements. L1 FOV Snow detection largely verified but at unknown SWE rate threshold (likely < 0.5 –1 mm/hr/liquid equivalent). Ongoing work to improve SWE rate estimation for both satellite and GV remote sensing.

The Planform Mobility of Large River Channel Confluences

NASA Astrophysics Data System (ADS)

Sambrook Smith, Greg; Dixon, Simon; Nicholas, Andrew; Bull, Jon; Vardy, Mark; Best, James; Goodbred, Steven; Sarker, Maminul

2017-04-01

Large river confluences are widely acknowledged as exerting a controlling influence upon both upstream and downstream morphology and thus channel planform evolution. Despite their importance, little is known concerning their longer-term evolution and planform morphodynamics, with much of the literature focusing on confluences as representing fixed, nodal points in the fluvial network. In contrast, some studies of large sand bed rivers in India and Bangladesh have shown large river confluences can be highly mobile, although the extent to which this is representative of large confluences around the world is unknown. Confluences have also been shown to generate substantial bed scours, and if the confluence location is mobile these scours could 'comb' across wide areas. This paper presents field data of large confluences morphologies in the Ganges-Brahmaputra-Meghna river basin, illustrating the spatial extent of large river bed scours and showing scour depth can extend below base level, enhancing long term preservation potential. Based on a global review of the planform of large river confluences using Landsat imagery from 1972 to 2014 this study demonstrates such scour features can be highly mobile and there is an array of confluence morphodynamic types: from freely migrating confluences, through confluences migrating on decadal timescales to fixed confluences. Based on this analysis, a conceptual model of large river confluence types is proposed, which shows large river confluences can be sites of extensive bank erosion and avulsion, creating substantial management challenges. We quantify the abundance of mobile confluence types by classifying all large confluences in both the Amazon and Ganges-Brahmaputra-Meghna basins, showing these two large rivers have contrasting confluence morphodynamics. We show large river confluences have multiple scales of planform adjustment with important implications for river management, infrastructure and interpretation of the rock record.

Do trust-based beliefs mediate the associations of frequency of private prayer with mental health? A cross-sectional study.

PubMed

Pössel, Patrick; Winkeljohn Black, Stephanie; Bjerg, Annie C; Jeppsen, Benjamin D; Wooldridge, Don T

2014-06-01

Significant associations of private prayer with mental health have been found, while mechanisms underlying these associations are largely unknown. This cross-sectional online study (N = 325, age 35.74, SD 18.50, 77.5 % females) used path modeling to test if trust-based beliefs (whether, when, and how prayers are answered) mediated the associations of prayer frequency with the Anxiety, Confusion, and Depression Profile of Mood States-Short Form scales. The association of prayer and depression was fully mediated by trust-based beliefs; associations with anxiety and confusion were partially mediated. Further, the interaction of prayer frequency by stress was associated with anxiety.

Lessons From Recruitment to an Internet-Based Survey for Degenerative Cervical Myelopathy: Comparison of Free and Fee-Based Methods.

PubMed

Davies, Benjamin; Kotter, Mark

2018-02-05

Degenerative Cervical Myelopathy (DCM) is a syndrome of subacute cervical spinal cord compression due to spinal degeneration. Although DCM is thought to be common, many fundamental questions such as the natural history and epidemiology of DCM remain unknown. In order to answer these, access to a large cohort of patients with DCM is required. With its unrivalled and efficient reach, the Internet has become an attractive tool for medical research and may overcome these limitations in DCM. The most effective recruitment strategy, however, is unknown. To compare the efficacy of fee-based advertisement with alternative free recruitment strategies to a DCM Internet health survey. An Internet health survey (SurveyMonkey) accessed by a new DCM Internet platform (myelopathy.org) was created. Using multiple survey collectors and the website's Google Analytics, the efficacy of fee-based recruitment strategies (Google AdWords) and free alternatives (including Facebook, Twitter, and myelopathy.org) were compared. Overall, 760 surveys (513 [68%] fully completed) were accessed, 305 (40%) from fee-based strategies and 455 (60%) from free alternatives. Accounting for researcher time, fee-based strategies were more expensive ($7.8 per response compared to $3.8 per response for free alternatives) and identified a less motivated audience (Click-Through-Rate of 5% compared to 57% using free alternatives) but were more time efficient for the researcher (2 minutes per response compared to 16 minutes per response for free methods). Facebook was the most effective free strategy, providing 239 (31%) responses, where a single message to 4 existing communities yielded 133 (18%) responses within 7 days. The Internet can efficiently reach large numbers of patients. Free and fee-based recruitment strategies both have merits. Facebook communities are a rich resource for Internet researchers. ©Benjamin Davies, Mark Kotter. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 05.02.2018.

Lessons From Recruitment to an Internet-Based Survey for Degenerative Cervical Myelopathy: Comparison of Free and Fee-Based Methods

PubMed Central

2018-01-01

Background Degenerative Cervical Myelopathy (DCM) is a syndrome of subacute cervical spinal cord compression due to spinal degeneration. Although DCM is thought to be common, many fundamental questions such as the natural history and epidemiology of DCM remain unknown. In order to answer these, access to a large cohort of patients with DCM is required. With its unrivalled and efficient reach, the Internet has become an attractive tool for medical research and may overcome these limitations in DCM. The most effective recruitment strategy, however, is unknown. Objective To compare the efficacy of fee-based advertisement with alternative free recruitment strategies to a DCM Internet health survey. Methods An Internet health survey (SurveyMonkey) accessed by a new DCM Internet platform (myelopathy.org) was created. Using multiple survey collectors and the website’s Google Analytics, the efficacy of fee-based recruitment strategies (Google AdWords) and free alternatives (including Facebook, Twitter, and myelopathy.org) were compared. Results Overall, 760 surveys (513 [68%] fully completed) were accessed, 305 (40%) from fee-based strategies and 455 (60%) from free alternatives. Accounting for researcher time, fee-based strategies were more expensive ($7.8 per response compared to $3.8 per response for free alternatives) and identified a less motivated audience (Click-Through-Rate of 5% compared to 57% using free alternatives) but were more time efficient for the researcher (2 minutes per response compared to 16 minutes per response for free methods). Facebook was the most effective free strategy, providing 239 (31%) responses, where a single message to 4 existing communities yielded 133 (18%) responses within 7 days. Conclusions The Internet can efficiently reach large numbers of patients. Free and fee-based recruitment strategies both have merits. Facebook communities are a rich resource for Internet researchers. PMID:29402760

Association between parental history of diabetes and type 2 diabetes genetic risk scores in the PPP-Botnia and Framingham Offspring Studies.

PubMed

Vassy, Jason L; Shrader, Peter; Jonsson, Anna; Fox, Caroline S; Lyssenko, Valeriya; Isomaa, Bo; Groop, Leif; Meigs, James B; Franks, Paul W

2011-08-01

Parental history of diabetes and specific gene variants are risk factors for type 2 diabetes, but the extent to which these factors are associated is unknown. We examined the association between parental history of diabetes and a type 2 diabetes genetic risk score (GRS) in two cohort studies from Finland (population-based PPP-Botnia study) and the US (family-based Framingham Offspring Study). Mean (95% CI) GRS increased from 16.8 (16.8-16.9) to 16.9 (16.8-17.1) to 17.1 (16.8-17.4) among PPP-Botnia participants with 0, 1, and 2 parents with diabetes, respectively (p(trend)=0.03). The trend was similar among Framingham Offspring but was not statistically significant (p=0.07). The meta-analyzed p value for trend from the two studies was 0.005. The very modest associations reported above suggest that the increased risk of diabetes in offspring of parents with diabetes is largely the result of shared environmental/lifestyle factors and/or hitherto unknown genetic factors. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Defining the Geographical Range of the Plasmodium knowlesi Reservoir

PubMed Central

Moyes, Catherine L.; Henry, Andrew J.; Golding, Nick; Huang, Zhi; Singh, Balbir; Baird, J. Kevin; Newton, Paul N.; Huffman, Michael; Duda, Kirsten A.; Drakeley, Chris J.; Elyazar, Iqbal R. F.; Anstey, Nicholas M.; Chen, Qijun; Zommers, Zinta; Bhatt, Samir; Gething, Peter W.; Hay, Simon I.

2014-01-01

Background The simian malaria parasite, Plasmodium knowlesi, can cause severe and fatal disease in humans yet it is rarely included in routine public health reporting systems for malaria and its geographical range is largely unknown. Because malaria caused by P. knowlesi is a truly neglected tropical disease, there are substantial obstacles to defining the geographical extent and risk of this disease. Information is required on the occurrence of human cases in different locations, on which non-human primates host this parasite and on which vectors are able to transmit it to humans. We undertook a systematic review and ranked the existing evidence, at a subnational spatial scale, to investigate the potential geographical range of the parasite reservoir capable of infecting humans. Methodology/Principal Findings After reviewing the published literature we identified potential host and vector species and ranked these based on how informative they are for the presence of an infectious parasite reservoir, based on current evidence. We collated spatial data on parasite occurrence and the ranges of the identified host and vector species. The ranked spatial data allowed us to assign an evidence score to 475 subnational areas in 19 countries and we present the results on a map of the Southeast and South Asia region. Conclusions/Significance We have ranked subnational areas within the potential disease range according to evidence for presence of a disease risk to humans, providing geographical evidence to support decisions on prevention, management and prophylaxis. This work also highlights the unknown risk status of large parts of the region. Within this unknown category, our map identifies which areas have most evidence for the potential to support an infectious reservoir and are therefore a priority for further investigation. Furthermore we identify geographical areas where further investigation of putative host and vector species would be highly informative for the region-wide assessment. PMID:24676231

Identification of unknown apple cultivars demonstrates the impact of local breeding program on cultivar diversity

USDA-ARS?s Scientific Manuscript database

Apple trees, either abandoned or cared for, are common on the North American landscape. These trees can live for decades, and therefore represent a record of large- and small-scale agricultural practices through time. Here, we assessed the genetic diversity and identity of 330 unknown apple trees in...

A Size Exclusion Chromatography Laboratory with Unknowns for Introductory Students

ERIC Educational Resources Information Center

McIntee, Edward J.; Graham, Kate J.; Colosky, Edward C.; Jakubowski, Henry V.

2015-01-01

Size exclusion chromatography is an important technique in the separation of biological and polymeric samples by molecular weight. While a number of laboratory experiments have been published that use this technique for the purification of large molecules, this is the first report of an experiment that focuses on purifying an unknown small…

Application of incremental unknowns to the Burgers equation

NASA Technical Reports Server (NTRS)

Choi, Haecheon; Temam, Roger

1993-01-01

In this article, we make a few remarks on the role that attractors and inertial manifolds play in fluid mechanics problems. We then describe the role of incremental unknowns for approximating attractors and inertial manifolds when finite difference multigrid discretizations are used. The relation with direct numerical simulation and large eddy simulation is also mentioned.

Characterizing unknown systematics in large scale structure surveys

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

Agarwal, Nishant; Ho, Shirley; Myers, Adam D.

Photometric large scale structure (LSS) surveys probe the largest volumes in the Universe, but are inevitably limited by systematic uncertainties. Imperfect photometric calibration leads to biases in our measurements of the density fields of LSS tracers such as galaxies and quasars, and as a result in cosmological parameter estimation. Earlier studies have proposed using cross-correlations between different redshift slices or cross-correlations between different surveys to reduce the effects of such systematics. In this paper we develop a method to characterize unknown systematics. We demonstrate that while we do not have sufficient information to correct for unknown systematics in the data,more » we can obtain an estimate of their magnitude. We define a parameter to estimate contamination from unknown systematics using cross-correlations between different redshift slices and propose discarding bins in the angular power spectrum that lie outside a certain contamination tolerance level. We show that this method improves estimates of the bias using simulated data and further apply it to photometric luminous red galaxies in the Sloan Digital Sky Survey as a case study.« less

Discontinuous Spectral Difference Method for Conservation Laws on Unstructured Grids

NASA Technical Reports Server (NTRS)

Liu, Yen; Vinokur, Marcel

2004-01-01

A new, high-order, conservative, and efficient discontinuous spectral finite difference (SD) method for conservation laws on unstructured grids is developed. The concept of discontinuous and high-order local representations to achieve conservation and high accuracy is utilized in a manner similar to the Discontinuous Galerkin (DG) and the Spectral Volume (SV) methods, but while these methods are based on the integrated forms of the equations, the new method is based on the differential form to attain a simpler formulation and higher efficiency. Conventional unstructured finite-difference and finite-volume methods require data reconstruction based on the least-squares formulation using neighboring point or cell data. Since each unknown employs a different stencil, one must repeat the least-squares inversion for every point or cell at each time step, or to store the inversion coefficients. In a high-order, three-dimensional computation, the former would involve impractically large CPU time, while for the latter the memory requirement becomes prohibitive. In addition, the finite-difference method does not satisfy the integral conservation in general. By contrast, the DG and SV methods employ a local, universal reconstruction of a given order of accuracy in each cell in terms of internally defined conservative unknowns. Since the solution is discontinuous across cell boundaries, a Riemann solver is necessary to evaluate boundary flux terms and maintain conservation. In the DG method, a Galerkin finite-element method is employed to update the nodal unknowns within each cell. This requires the inversion of a mass matrix, and the use of quadratures of twice the order of accuracy of the reconstruction to evaluate the surface integrals and additional volume integrals for nonlinear flux functions. In the SV method, the integral conservation law is used to update volume averages over subcells defined by a geometrically similar partition of each grid cell. As the order of accuracy increases, the partitioning for 3D requires the introduction of a large number of parameters, whose optimization to achieve convergence becomes increasingly more difficult. Also, the number of interior facets required to subdivide non-planar faces, and the additional increase in the number of quadrature points for each facet, increases the computational cost greatly.

Synchronization of coupled different chaotic FitzHugh-Nagumo neurons with unknown parameters under communication-direction-dependent coupling.

PubMed

Iqbal, Muhammad; Rehan, Muhammad; Khaliq, Abdul; Saeed-ur-Rehman; Hong, Keum-Shik

2014-01-01

This paper investigates the chaotic behavior and synchronization of two different coupled chaotic FitzHugh-Nagumo (FHN) neurons with unknown parameters under external electrical stimulation (EES). The coupled FHN neurons of different parameters admit unidirectional and bidirectional gap junctions in the medium between them. Dynamical properties, such as the increase in synchronization error as a consequence of the deviation of neuronal parameters for unlike neurons, the effect of difference in coupling strengths caused by the unidirectional gap junctions, and the impact of large time-delay due to separation of neurons, are studied in exploring the behavior of the coupled system. A novel integral-based nonlinear adaptive control scheme, to cope with the infeasibility of the recovery variable, for synchronization of two coupled delayed chaotic FHN neurons of different and unknown parameters under uncertain EES is derived. Further, to guarantee robust synchronization of different neurons against disturbances, the proposed control methodology is modified to achieve the uniformly ultimately bounded synchronization. The parametric estimation errors can be reduced by selecting suitable control parameters. The effectiveness of the proposed control scheme is illustrated via numerical simulations.

Adaptive Neural Networks Decentralized FTC Design for Nonstrict-Feedback Nonlinear Interconnected Large-Scale Systems Against Actuator Faults.

PubMed

Li, Yongming; Tong, Shaocheng

The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.The problem of active fault-tolerant control (FTC) is investigated for the large-scale nonlinear systems in nonstrict-feedback form. The nonstrict-feedback nonlinear systems considered in this paper consist of unstructured uncertainties, unmeasured states, unknown interconnected terms, and actuator faults (e.g., bias fault and gain fault). A state observer is designed to solve the unmeasurable state problem. Neural networks (NNs) are used to identify the unknown lumped nonlinear functions so that the problems of unstructured uncertainties and unknown interconnected terms can be solved. By combining the adaptive backstepping design principle with the combination Nussbaum gain function property, a novel NN adaptive output-feedback FTC approach is developed. The proposed FTC controller can guarantee that all signals in all subsystems are bounded, and the tracking errors for each subsystem converge to a small neighborhood of zero. Finally, numerical results of practical examples are presented to further demonstrate the effectiveness of the proposed control strategy.

On Borders: From Ancient to Postmodern Times

NASA Astrophysics Data System (ADS)

Bellezza, G.

2013-11-01

The article deals with the evolution of the concept of borders between human groups and with its slow evolution from the initial no men's land zones to the ideal single-dimension linear borders. In ancient times the first borders were natural, such as mountain ranges or large rivers until, with the development of Geodesy, astronomical borders based on meridians and parallels became a favourite natural base. Actually, Modern States adopted these to fix limits in unknown conquered territories. The postmodern thought led give more importance to cultural borders until, in the most recent times, is becoming rather impossible to fix borders in the virtual cyberspace.

Size-based trends and management implications of microhabitat utilization by Brown Treesnakes, with an emphasis on juvenile snakes

USGS Publications Warehouse

Rodda, Gordon H.; Reed, Robert N.

2007-01-01

The brown treesnake (Boiga irregularis, or BTS), a costly invasive species, has been the subject of intensive research on Guam over the past two decades. The behavior and habitat use of hatchling and juvenile snakes, however, remain largely unknown. We used a long-term dataset of BTS captures (N = 2,415) and a dataset resulting from intensive sampling within and immediately around a 5-ha fenced population (N = 2,541) to examine habitat use of BTS. Small snakes were almost exclusively arboreal and that they appeared to prefer tangantangan (Leucaena leucocephala) habitats. In contrast, large snakes used arboreal and terrestrial habitats in roughly equal proportion, and were less frequently found in tangantangan. Among snakes found in trees, there were no clear size-based preferences for certain heights above ground, nor for size-based choice of perch diameters. We discuss these results as they relate to management and interdiction implications for brown treesnakes on Guam and in potential incipient populations on other islands.

Combined magnetic vector-scalar potential finite element computation of 3D magnetic field and performance of modified Lundell alternators in Space Station applications. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Wang, Ren H.

1991-01-01

A method of combined use of magnetic vector potential (MVP) based finite element (FE) formulations and magnetic scalar potential (MSP) based FE formulations for computation of three-dimensional (3D) magnetostatic fields is developed. This combined MVP-MSP 3D-FE method leads to considerable reduction by nearly a factor of 3 in the number of unknowns in comparison to the number of unknowns which must be computed in global MVP based FE solutions. This method allows one to incorporate portions of iron cores sandwiched in between coils (conductors) in current-carrying regions. Thus, it greatly simplifies the geometries of current carrying regions (in comparison with the exclusive MSP based methods) in electric machinery applications. A unique feature of this approach is that the global MSP solution is single valued in nature, that is, no branch cut is needed. This is again a superiority over the exclusive MSP based methods. A Newton-Raphson procedure with a concept of an adaptive relaxation factor was developed and successfully used in solving the 3D-FE problem with magnetic material anisotropy and nonlinearity. Accordingly, this combined MVP-MSP 3D-FE method is most suited for solution of large scale global type magnetic field computations in rotating electric machinery with very complex magnetic circuit geometries, as well as nonlinear and anisotropic material properties.

Calibration strategies for a groundwater model in a highly dynamic alpine floodplain

USGS Publications Warehouse

Foglia, L.; Burlando, P.; Hill, Mary C.; Mehl, S.

2004-01-01

Most surface flows to the 20-km-long Maggia Valley in Southern Switzerland are impounded and the valley is being investigated to determine environmental flow requirements. The aim of the investigation is the devel-opment of a modelling framework that simulates the dynamics of the ground-water, hydrologic, and ecologic systems. Because of the multi-scale nature of the modelling framework, large-scale models are first developed to provide the boundary conditions for more detailed models of reaches that are of eco-logical importance. We describe here the initial (large-scale) groundwa-ter/surface water model and its calibration in relation to initial and boundary conditions. A MODFLOW-2000 model was constructed to simulate the inter-action of groundwater and surface water and was developed parsimoniously to avoid modelling artefacts and parameter inconsistencies. Model calibration includes two steady-state conditions, with and without recharge to the aquifer from the adjoining hillslopes. Parameters are defined to represent areal re-charge, hydraulic conductivity of the aquifer (up to 5 classes), and streambed hydraulic conductivity. Model performance was investigated following two system representation. The first representation assumed unknown flow input at the northern end of the groundwater domain and unknown lateral inflow. The second representation used simulations of the lateral flow obtained by means of a raster-based, physically oriented and continuous in time rainfall-runoff (R-R) model. Results based on these two representations are compared and discussed.

Advanced Computational Framework for Environmental Management ZEM, Version 1.x

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

Vesselinov, Velimir V.; O'Malley, Daniel; Pandey, Sachin

2016-11-04

Typically environmental management problems require analysis of large and complex data sets originating from concurrent data streams with different data collection frequencies and pedigree. These big data sets require on-the-fly integration into a series of models with different complexity for various types of model analyses where the data are applied as soft and hard model constraints. This is needed to provide fast iterative model analyses based on the latest available data to guide decision-making. Furthermore, the data and model are associated with uncertainties. The uncertainties are probabilistic (e.g. measurement errors) and non-probabilistic (unknowns, e.g. alternative conceptual models characterizing site conditions).more » To address all of these issues, we have developed an integrated framework for real-time data and model analyses for environmental decision-making called ZEM. The framework allows for seamless and on-the-fly integration of data and modeling results for robust and scientifically-defensible decision-making applying advanced decision analyses tools such as Bayesian- Information-Gap Decision Theory (BIG-DT). The framework also includes advanced methods for optimization that are capable of dealing with a large number of unknown model parameters, and surrogate (reduced order) modeling capabilities based on support vector regression techniques. The framework is coded in Julia, a state-of-the-art high-performance programing language (http://julialang.org). The ZEM framework is open-source and can be applied to any environmental management site. The framework will be open-source and released under GPL V3 license.« less

Adaptive Fuzzy Output-Constrained Fault-Tolerant Control of Nonlinear Stochastic Large-Scale Systems With Actuator Faults.

PubMed

Li, Yongming; Ma, Zhiyao; Tong, Shaocheng

2017-09-01

The problem of adaptive fuzzy output-constrained tracking fault-tolerant control (FTC) is investigated for the large-scale stochastic nonlinear systems of pure-feedback form. The nonlinear systems considered in this paper possess the unstructured uncertainties, unknown interconnected terms and unknown nonaffine nonlinear faults. The fuzzy logic systems are employed to identify the unknown lumped nonlinear functions so that the problems of structured uncertainties can be solved. An adaptive fuzzy state observer is designed to solve the nonmeasurable state problem. By combining the barrier Lyapunov function theory, adaptive decentralized and stochastic control principles, a novel fuzzy adaptive output-constrained FTC approach is constructed. All the signals in the closed-loop system are proved to be bounded in probability and the system outputs are constrained in a given compact set. Finally, the applicability of the proposed controller is well carried out by a simulation example.

Fission meter

DOEpatents

Rowland, Mark S [Alamo, CA; Snyderman, Neal J [Berkeley, CA

2012-04-10

A neutron detector system for discriminating fissile material from non-fissile material wherein a digital data acquisition unit collects data at high rate, and in real-time processes large volumes of data directly into information that a first responder can use to discriminate materials. The system comprises counting neutrons from the unknown source and detecting excess grouped neutrons to identify fission in the unknown source.

Customizing a rangefinder for community-based wildlife conservation initiatives

USGS Publications Warehouse

Ransom, Jason I.

2011-01-01

Population size of many threatened and endangered species is relatively unknown because estimating animal abundance in remote parts of the world, without access to aircraft for surveying vast areas, is a scientific challenge with few proposed solutions. One option is to enlist local community members and train them in data collection for large line transect or point count surveys, but financial and sometimes technological constraints prevent access to the necessary equipment and training for accurately quantifying distance measurements. Such measurements are paramount for generating reliable estimates of animal density. This problem was overcome in a survey of Asiatic wild ass (Equus hemionus) in the Great Gobi B Strictly Protected Area, Mongolia, by converting an inexpensive optical sporting rangefinder into a species-specific rangefinder with visual-based categorical labels. Accuracy trials concluded 96.86% of 350 distance measures matched those from a laser rangefinder. This simple customized optic subsequently allowed for a large group of minimally-trained observers to simultaneously record quantitative measures of distance, despite language, education, and skill differences among the diverse group. The large community-based effort actively engaged local residents in species conservation by including them as the foundation for collecting scientific data.

ERTS-1 data user investigation of wetlands ecology

NASA Technical Reports Server (NTRS)

Anderson, R. R. (Principal Investigator)

1973-01-01

The author has identified the following significant results. ERTS-1 imagery (enlarged to 1:250,000) is an excellent tool by which large area coastal marshland mapping may be undertaken. If states can sacrifice some accuracy (amount unknown at this time) in placing of boundary lines, the technique may be used to do the following: (1) estimate extent of man's impact on marshes by ditching and lagooning and accelerated successional trends; (2) place boundaries between wetland and upland and hence estimate amount of coastal marshland remaining in the state; (3) distinguish among relatively large zones of various plant species including high and low growth S. alterniflora, J. roemerianus, and S. cynosuroides; and (4) estimate marsh plant species productivity when ground based information is available.

Evidence Based Assessment of Public Health Planning: A Case Study of the 2014 Crisis in Ukraine

DTIC Science & Technology

2015-06-12

Unknowns, Unknown Unknowns and the Propagation of Scientific Enquiry,” Journal of Experimental Botany 60, no. 3 (March 2009): 712-714. Risk...David C. Logan, “Known Knowns, Known Unknowns, Unknown Unknowns and the Propagation of Scientific Enquiry,” Journal of Experimental Botany 60, no. 3...Experimental Botany 60, no. 3 (March 2009): 712-714. Markel, Howard. “Facing Tuberculosis,” When Germs Travel: Six Major Epidemics That Have Invaded America

Adaptive neural output-feedback control for nonstrict-feedback time-delay fractional-order systems with output constraints and actuator nonlinearities.

PubMed

Zouari, Farouk; Ibeas, Asier; Boulkroune, Abdesselem; Cao, Jinde; Mehdi Arefi, Mohammad

2018-06-01

This study addresses the issue of the adaptive output tracking control for a category of uncertain nonstrict-feedback delayed incommensurate fractional-order systems in the presence of nonaffine structures, unmeasured pseudo-states, unknown control directions, unknown actuator nonlinearities and output constraints. Firstly, the mean value theorem and the Gaussian error function are introduced to eliminate the difficulties that arise from the nonaffine structures and the unknown actuator nonlinearities, respectively. Secondly, the immeasurable tracking error variables are suitably estimated by constructing a fractional-order linear observer. Thirdly, the neural network, the Razumikhin Lemma, the variable separation approach, and the smooth Nussbaum-type function are used to deal with the uncertain nonlinear dynamics, the unknown time-varying delays, the nonstrict feedback and the unknown control directions, respectively. Fourthly, asymmetric barrier Lyapunov functions are employed to overcome the violation of the output constraints and to tune online the parameters of the adaptive neural controller. Through rigorous analysis, it is proved that the boundedness of all variables in the closed-loop system and the semi global asymptotic tracking are ensured without transgression of the constraints. The principal contributions of this study can be summarized as follows: (1) based on Caputo's definitions and new lemmas, methods concerning the controllability, observability and stability analysis of integer-order systems are extended to fractional-order ones, (2) the output tracking objective for a relatively large class of uncertain systems is achieved with a simple controller and less tuning parameters. Finally, computer-simulation studies from the robotic field are given to demonstrate the effectiveness of the proposed controller. Copyright © 2018 Elsevier Ltd. All rights reserved.

An Adaptive Moving Target Imaging Method for Bistatic Forward-Looking SAR Using Keystone Transform and Optimization NLCS.

PubMed

Li, Zhongyu; Wu, Junjie; Huang, Yulin; Yang, Haiguang; Yang, Jianyu

2017-01-23

Bistatic forward-looking SAR (BFSAR) is a kind of bistatic synthetic aperture radar (SAR) system that can image forward-looking terrain in the flight direction of an aircraft. Until now, BFSAR imaging theories and methods for a stationary scene have been researched thoroughly. However, for moving-target imaging with BFSAR, the non-cooperative movement of the moving target induces some new issues: (I) large and unknown range cell migration (RCM) (including range walk and high-order RCM); (II) the spatial-variances of the Doppler parameters (including the Doppler centroid and high-order Doppler) are not only unknown, but also nonlinear for different point-scatterers. In this paper, we put forward an adaptive moving-target imaging method for BFSAR. First, the large and unknown range walk is corrected by applying keystone transform over the whole received echo, and then, the relationships among the unknown high-order RCM, the nonlinear spatial-variances of the Doppler parameters, and the speed of the mover, are established. After that, using an optimization nonlinear chirp scaling (NLCS) technique, not only can the unknown high-order RCM be accurately corrected, but also the nonlinear spatial-variances of the Doppler parameters can be balanced. At last, a high-order polynomial filter is applied to compress the whole azimuth data of the moving target. Numerical simulations verify the effectiveness of the proposed method.

Epidemiology of neuroendocrine cancers in an Australian population.

PubMed

Luke, Colin; Price, Timothy; Townsend, Amanda; Karapetis, Christos; Kotasek, Dusan; Singhal, Nimit; Tracey, Elizabeth; Roder, David

2010-06-01

The aim was to explore incidence, mortality and case survivals for invasive neuroendocrine cancers in an Australian population and consider cancer control implications. Directly age-standardised incidence and mortality rates were investigated from 1980 to 2006, plus disease-specific survivals. Annual incidence per 100,000 increased from 1.7 in 1980-1989 to 3.3 in 2000-2006. A corresponding mortality increase was not observed, although numbers of deaths were low, reducing statistical power. Increases in incidence affected both sexes and were more evident for female lung, large bowel (excluding appendix), and unknown primary site. Common sites were lung (25.9%), large bowel (23.3%) (40.9% were appendix), small intestine (20.6%), unknown primary (15.0%), pancreas (6.5%), and stomach (3.7%). Site distribution did not vary by sex (p = 0.260). Younger ages at diagnosis applied for lung (p = 0.002) and appendix (p < 0.001) and older ages for small intestine (p < 0.001) and unknown primary site (p < 0.001). Five-year survival was 68.5% for all sites combined, with secular increases (p < 0.001). After adjusting for age and diagnostic period, survivals were higher for appendix and lower for unknown primary site, pancreas, and colon (excluding appendix). Incidence rates are increasing. Research is needed into possible aetiological factors for lung and large-bowel sites, including tobacco smoking, and excess body weight and lack of exercise, respectively; and Crohn's disease as a possible precursor condition.

Expert systems identify fossils and manage large paleontological databases

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

Beightol, D.S.; Conrad, M.A.

EXPAL is a computer program permitting creation and maintenance of comprehensive databases in marine paleontology. It is designed to assist specialists and non-specialists. EXPAL includes a powerful expert system based on the morphological descriptors specific to a given group of fossils. The expert system may be used, for example, to describe and automatically identify an unknown specimen. EXPAL was first applied to Dasycladales (Calcareous green algae). Projects are under way for corresponding expert systems and databases on planktonic foraminifers and calpionellids. EXPAL runs on an IBM XT or compatible microcomputer.

GNE-886: A Potent and Selective Inhibitor of the Cat Eye Syndrome Chromosome Region Candidate 2 Bromodomain (CECR2).

PubMed

Crawford, Terry D; Audia, James E; Bellon, Steve; Burdick, Daniel J; Bommi-Reddy, Archana; Côté, Alexandre; Cummings, Richard T; Duplessis, Martin; Flynn, E Megan; Hewitt, Michael; Huang, Hon-Ren; Jayaram, Hariharan; Jiang, Ying; Joshi, Shivangi; Kiefer, James R; Murray, Jeremy; Nasveschuk, Christopher G; Neiss, Arianne; Pardo, Eneida; Romero, F Anthony; Sandy, Peter; Sims, Robert J; Tang, Yong; Taylor, Alexander M; Tsui, Vickie; Wang, Jian; Wang, Shumei; Wang, Yongyun; Xu, Zhaowu; Zawadzke, Laura; Zhu, Xiaoqin; Albrecht, Brian K; Magnuson, Steven R; Cochran, Andrea G

2017-07-13

The biological function of bromodomains, epigenetic readers of acetylated lysine residues, remains largely unknown. Herein we report our efforts to discover a potent and selective inhibitor of the bromodomain of cat eye syndrome chromosome region candidate 2 (CECR2). Screening of our internal medicinal chemistry collection led to the identification of a pyrrolopyridone chemical lead, and subsequent structure-based drug design led to a potent and selective CECR2 bromodomain inhibitor (GNE-886) suitable for use as an in vitro tool compound.

The first case of Niikawa-Kuroki syndrome in Kazakhstan associated with café au lait spots.

PubMed

Al Mosawi, A J; Fewin, L

2009-10-01

Niikawa-Kuroki syndrome (Kabuki syndrome) is a multiple congenital anomaly syndrome of unknown etiology with a very wide spectrum of abnormalities and severity. The aim of this paper was to report the first case of the syndrome in Kazakhstan associated café au lait. Five year and half old boy from Kazakhstan (Uzbek-of Turk ethnicity) presented with dysmorphic facial features (long palpebral fissures, a broad and depressed nasal tip, large prominent earlobes, small head, epicanthic folds short stature, delayed language development, hypotonia, bilateral developmental dysplasia of the hip (DDH), large ears and triangular chin, café au lait spots. The clinical diagnosis was based on the triad of characteristic facial abnormalities (long palpebral fissures, a broad and depressed nasal tip, large prominent earlobes, small head), growth retardation, (DDH). In this paper the authors report the first case of Kabuki syndrome associated with café au lait spots.

Current understanding of dysbiosis in disease in human and animal models

PubMed Central

DeGruttola, Arianna K.; Low, Daren; Mizoguchi, Atsushi; Mizoguchi, Emiko

2016-01-01

Inflammatory bowel disease (IBD) is an intestinal inflammatory condition that affects over two million people in the United States. Although the etiology and pathogenesis of IBD are still largely unknown, dysregulated host/enteric microbial interactions are requisite for the development of IBD. So far, many researchers have tried to identify a precise relationship between IBD and an imbalance of the intestinal microbiota, termed “dysbiosis”. In spite of the extensive efforts, it is still largely unknown about the interplay among microbes, their hosts, and their environments, and whether dysbiosis is a causal factor or an effect of IBD. Recently, deep-sequencing analyses of the microbiota in IBD patients have been instrumental in characterizing the strong association between dysbiosis and IBD development, although it is still unable to identify specific-associated species level changes in most cases. Based on many recent reports, dysbiosis of the commensal microbiota is implicated in the pathogenesis of several diseases, including IBD, obesity, and allergic disorders, in both human and animal models. In this review article, we have focused on explaining the multiple types of dysbiosis, as well as dysbiosis-related diseases and potential treatments in order to apply this knowledge to understand a possible cause and potentially find therapeutic strategies for IBD as well as the other dysbiosis-related diseases. PMID:27070911

Effects of alternative styles of risk information on EMF risk perception.

PubMed

Nielsen, Jesper Bo; Elstein, Arthur; Gyrd-Hansen, Dorte; Kildemoes, Helle Wallach; Kristiansen, Ivar Sønbø; Støvring, Henrik

2010-10-01

Risk scenarios characterized by exposures to new technologies with unknown health effects, together with limited appreciation of benefits pose a challenge to risk communication. The present report illustrates this situation through a study of the perceived risk from mobile phones and mobile masts in residential areas. Good information should objectively convey the current state of knowledge. The research question is then how to inform lay people so that they trust and understand the information. We used an Internet-based survey with 1687 Danish participants randomized to three types of information about radiation from mobile phones and masts. The objective was to study whether different types of information were rated as equally useful, informative, comprehensible, and trustworthy. Moreover, an important issue was whether information would influence risk perception and intended behavior. The conclusion is that lay people rate information about risks associated with a new and largely unknown technology more useful and trustworthy when provided with brief statements about how to handle the risk, rather than more lengthy technical information about why the technology may or may not entail health hazards. Further, the results demonstrate that information may increase concern among a large proportion of the population, and that discrepancies exist between expressed concern and intended behavior.

Decentralized adaptive neural control for high-order interconnected stochastic nonlinear time-delay systems with unknown system dynamics.

PubMed

Si, Wenjie; Dong, Xunde; Yang, Feifei

2018-03-01

This paper is concerned with the problem of decentralized adaptive backstepping state-feedback control for uncertain high-order large-scale stochastic nonlinear time-delay systems. For the control design of high-order large-scale nonlinear systems, only one adaptive parameter is constructed to overcome the over-parameterization, and neural networks are employed to cope with the difficulties raised by completely unknown system dynamics and stochastic disturbances. And then, the appropriate Lyapunov-Krasovskii functional and the property of hyperbolic tangent functions are used to deal with the unknown unmatched time-delay interactions of high-order large-scale systems for the first time. At last, on the basis of Lyapunov stability theory, the decentralized adaptive neural controller was developed, and it decreases the number of learning parameters. The actual controller can be designed so as to ensure that all the signals in the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) and the tracking error converges in the small neighborhood of zero. The simulation example is used to further show the validity of the design method. Copyright © 2018 Elsevier Ltd. All rights reserved.

Identification of Breast Cancer-Associated Lipids in Scalp Hair

PubMed Central

Mistry, Dharmica A.H.; Haklani, Joseph; French, Peter W.

2012-01-01

A correlation between the presence of breast cancer and a change in the synchrotron-generated X-ray diffraction (XRD) pattern of hair has been reported in several publications by different groups, and on average XRD-based assays detect around 75% of breast cancer patients in blinded studies. To date, the molecular mechanisms leading to this alteration are largely unknown. We have determined that the alteration is likely to be due to the presence of one or more breast cancer-associated phospholipids. Further characterization of these lipids could be used to develop a novel, sensitive and specific screening test for breast cancer, based on hair initially, and potentially extendable to other biological samples. PMID:22872787

A Behavior-Based Strategy for Single and Multi-Robot Autonomous Exploration

PubMed Central

Cepeda, Jesus S.; Chaimowicz, Luiz; Soto, Rogelio; Gordillo, José L.; Alanís-Reyes, Edén A.; Carrillo-Arce, Luis C.

2012-01-01

In this paper, we consider the problem of autonomous exploration of unknown environments with single and multiple robots. This is a challenging task, with several potential applications. We propose a simple yet effective approach that combines a behavior-based navigation with an efficient data structure to store previously visited regions. This allows robots to safely navigate, disperse and efficiently explore the environment. A series of experiments performed using a realistic robotic simulator and a real testbed scenario demonstrate that our technique effectively distributes the robots over the environment and allows them to quickly accomplish their mission in large open spaces, narrow cluttered environments, dead-end corridors, as well as rooms with minimum exits.

Window-based method for approximating the Hausdorff in three-dimensional range imagery

DOEpatents

Koch, Mark W [Albuquerque, NM

2009-06-02

One approach to pattern recognition is to use a template from a database of objects and match it to a probe image containing the unknown. Accordingly, the Hausdorff distance can be used to measure the similarity of two sets of points. In particular, the Hausdorff can measure the goodness of a match in the presence of occlusion, clutter, and noise. However, existing 3D algorithms for calculating the Hausdorff are computationally intensive, making them impractical for pattern recognition that requires scanning of large databases. The present invention is directed to a new method that can efficiently, in time and memory, compute the Hausdorff for 3D range imagery. The method uses a window-based approach.

Realtime motion planning for a mobile robot in an unknown environment using a neurofuzzy based approach

NASA Astrophysics Data System (ADS)

Zheng, Taixiong

2005-12-01

A neuro-fuzzy network based approach for robot motion in an unknown environment was proposed. In order to control the robot motion in an unknown environment, the behavior of the robot was classified into moving to the goal and avoiding obstacles. Then, according to the dynamics of the robot and the behavior character of the robot in an unknown environment, fuzzy control rules were introduced to control the robot motion. At last, a 6-layer neuro-fuzzy network was designed to merge from what the robot sensed to robot motion control. After being trained, the network may be used for robot motion control. Simulation results show that the proposed approach is effective for robot motion control in unknown environment.

Novel fluorinated surfactants tentatively identified in firefighters using liquid chromatography quadrupole time-of-flight tandem mass spectrometry and a case-control approach.

PubMed

Rotander, Anna; Kärrman, Anna; Toms, Leisa-Maree L; Kay, Margaret; Mueller, Jochen F; Gómez Ramos, María José

2015-02-17

Fluorinated surfactant-based aqueous film-forming foams (AFFFs) are made up of per- and polyfluorinated alkyl substances (PFAS) and are used to extinguish fires involving highly flammable liquids. The use of perfluorooctanesulfonic acid (PFOS) and other perfluoroalkyl acids (PFAAs) in some AFFF formulations has been linked to substantial environmental contamination. Recent studies have identified a large number of novel and infrequently reported fluorinated surfactants in different AFFF formulations. In this study, a strategy based on a case-control approach using quadrupole time-of-flight tandem mass spectrometry (QTOF-MS/MS) and advanced statistical methods has been used to extract and identify known and unknown PFAS in human serum associated with AFFF-exposed firefighters. Two target sulfonic acids [PFOS and perfluorohexanesulfonic acid (PFHxS)], three non-target acids [perfluoropentanesulfonic acid (PFPeS), perfluoroheptanesulfonic acid (PFHpS), and perfluorononanesulfonic acid (PFNS)], and four unknown sulfonic acids (Cl-PFOS, ketone-PFOS, ether-PFHxS, and Cl-PFHxS) were exclusively or significantly more frequently detected at higher levels in firefighters compared to controls. The application of this strategy has allowed for identification of previously unreported fluorinated chemicals in a timely and cost-efficient way.

Hypothesis testing of a change point during cognitive decline among Alzheimer's disease patients.

PubMed

Ji, Ming; Xiong, Chengjie; Grundman, Michael

2003-10-01

In this paper, we present a statistical hypothesis test for detecting a change point over the course of cognitive decline among Alzheimer's disease patients. The model under the null hypothesis assumes a constant rate of cognitive decline over time and the model under the alternative hypothesis is a general bilinear model with an unknown change point. When the change point is unknown, however, the null distribution of the test statistics is not analytically tractable and has to be simulated by parametric bootstrap. When the alternative hypothesis that a change point exists is accepted, we propose an estimate of its location based on the Akaike's Information Criterion. We applied our method to a data set from the Neuropsychological Database Initiative by implementing our hypothesis testing method to analyze Mini Mental Status Exam scores based on a random-slope and random-intercept model with a bilinear fixed effect. Our result shows that despite large amount of missing data, accelerated decline did occur for MMSE among AD patients. Our finding supports the clinical belief of the existence of a change point during cognitive decline among AD patients and suggests the use of change point models for the longitudinal modeling of cognitive decline in AD research.

Discrete-time switching periodic adaptive control for time-varying parameters with unknown periodicity

NASA Astrophysics Data System (ADS)

Yu, Miao; Huang, Deqing; Yang, Wanqiu

2018-06-01

In this paper, we address the problem of unknown periodicity for a class of discrete-time nonlinear parametric systems without assuming any growth conditions on the nonlinearities. The unknown periodicity hides in the parametric uncertainties, which is difficult to estimate with existing techniques. By incorporating a logic-based switching mechanism, we identify the period and bound of unknown parameter simultaneously. Lyapunov-based analysis is given to demonstrate that a finite number of switchings can guarantee the asymptotic tracking for the nonlinear parametric systems. The simulation result also shows the efficacy of the proposed switching periodic adaptive control approach.

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

Drosophila transposon insertions as unknowns for structured inquiry recombination mapping exercises in an undergraduate genetics course.

PubMed

Marcus, Jeffrey M; Hughes, Tia M

2009-06-01

Structured inquiry approaches, in which students receive a Drosophila strain of unknown genotype to analyze and map the constituent mutations, are a common feature of many genetics teaching laboratories. The required crosses frustrate many students because they are aware that they are participating in a fundamentally trivial exercise, as the map locations of the genes are already established and have been recalculated thousands of times by generations of students. We modified the traditional structured inquiry approach to include a novel research experience for the students in our undergraduate genetics laboratories. Students conducted crosses with Drosophila strains carrying P[lacW] transposon insertions in genes without documented recombination map positions, representing a large number of unique, but equivalent genetic unknowns. Using the eye color phenotypes associated with the inserts as visible markers, it is straightforward to calculate recombination map positions for the interrupted loci. Collectively, our students mapped 95 genetic loci on chromosomes 2 and 3. In most cases, the calculated 95% confidence interval for meiotic map location overlapped with the predicted map position based on cytology. The research experience evoked positive student responses and helped students better understand the nature of scientific research for little additional cost or instructor effort.

15. Photographic copy of photograph dated ca. 1929; Photographer unknown; ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

15. Photographic copy of photograph dated ca. 1929; Photographer unknown; Original in Rath collection at Grout Museum, Waterloo, Iowa; Filed under: Rath Packing Company, Box 4; THE RATH COMPLEX IN THE LATE 1920S; LOOKING WEST FROM 18TH STREET; LARGE BUILDING AT CENTER IS HOG KILL (BUILDING 40) - Rath Packing Company, Sycamore Street between Elm & Eighteenth Streets, Waterloo, Black Hawk County, IA

The impact of simulation-based learning on students' English for Nursing Purposes (ENP) reading proficiency: a quasi-experimental study.

PubMed

Chang, Hsiao-Yun Annie; Chan, Luke; Siren, Betty

2013-06-01

This is a report of a study which evaluated simulation-based learning as a teaching strategy for improving participants' ENP reading proficiency in the senior college program of students whose first language is Chinese, not English. Simulation-based learning is known to be one of most effective teaching strategies in the healthcare professional curricula, which brings a clinical setting into the classroom. However, developing English reading skills for English written nursing journals through simulation-based learning in the nursing curricula, is largely unknown. We used a quasi-experimental approach with nonequivalent control group design to collect the causal connections between intervention and outcomes. 101 students were enrolled in this study (response rate 92.6%) of these 48 students volunteered for the intervention group, and 53 students for the control group. The findings indicated that the intervention group had significantly higher mean scores in ENP reading proficiency with unknown words in the article (p=.004), vocabulary (p<.001), and comprehension (p<.001) compared to the control group. Also, the intervention students showed more improvement in their English reading, both from quantitative and qualitative findings. Simulation-based learning may have some advantages in improving the English reading ability on English written nursing journals among nursing students. However, the benefits to the students of this study is still to be determined, and further exploration is needed with well designed research and a universal method of outcome measurement. Copyright © 2012 Elsevier Ltd. All rights reserved.

Directly patching high-level exchange-correlation potential based on fully determined optimized effective potentials

NASA Astrophysics Data System (ADS)

Huang, Chen; Chi, Yu-Chieh

2017-12-01

The key element in Kohn-Sham (KS) density functional theory is the exchange-correlation (XC) potential. We recently proposed the exchange-correlation potential patching (XCPP) method with the aim of directly constructing high-level XC potential in a large system by patching the locally computed, high-level XC potentials throughout the system. In this work, we investigate the patching of the exact exchange (EXX) and the random phase approximation (RPA) correlation potentials. A major challenge of XCPP is that a cluster's XC potential, obtained by solving the optimized effective potential equation, is only determined up to an unknown constant. Without fully determining the clusters' XC potentials, the patched system's XC potential is "uneven" in the real space and may cause non-physical results. Here, we developed a simple method to determine this unknown constant. The performance of XCPP-RPA is investigated on three one-dimensional systems: H20, H10Li8, and the stretching of the H19-H bond. We investigated two definitions of EXX: (i) the definition based on the adiabatic connection and fluctuation dissipation theorem (ACFDT) and (ii) the Hartree-Fock (HF) definition. With ACFDT-type EXX, effective error cancellations were observed between the patched EXX and the patched RPA correlation potentials. Such error cancellations were absent for the HF-type EXX, which was attributed to the fact that for systems with fractional occupation numbers, the integral of the HF-type EXX hole is not -1. The KS spectra and band gaps from XCPP agree reasonably well with the benchmarks as we make the clusters large.

An approach to the analysis of SDSS spectroscopic outliers based on self-organizing maps. Designing the outlier analysis software package for the next Gaia survey

NASA Astrophysics Data System (ADS)

Fustes, D.; Manteiga, M.; Dafonte, C.; Arcay, B.; Ulla, A.; Smith, K.; Borrachero, R.; Sordo, R.

2013-11-01

Aims: A new method applied to the segmentation and further analysis of the outliers resulting from the classification of astronomical objects in large databases is discussed. The method is being used in the framework of the Gaia satellite Data Processing and Analysis Consortium (DPAC) activities to prepare automated software tools that will be used to derive basic astrophysical information that is to be included in final Gaia archive. Methods: Our algorithm has been tested by means of simulated Gaia spectrophotometry, which is based on SDSS observations and theoretical spectral libraries covering a wide sample of astronomical objects. Self-organizing maps networks are used to organize the information in clusters of objects, as homogeneously as possible according to their spectral energy distributions, and to project them onto a 2D grid where the data structure can be visualized. Results: We demonstrate the usefulness of the method by analyzing the spectra that were rejected by the SDSS spectroscopic classification pipeline and thus classified as "UNKNOWN". First, our method can help distinguish between astrophysical objects and instrumental artifacts. Additionally, the application of our algorithm to SDSS objects of unknown nature has allowed us to identify classes of objects with similar astrophysical natures. In addition, the method allows for the potential discovery of hundreds of new objects, such as white dwarfs and quasars. Therefore, the proposed method is shown to be very promising for data exploration and knowledge discovery in very large astronomical databases, such as the archive from the upcoming Gaia mission.

Large mass affecting retroperitoneal great vessels: a rare presentation of a cancer of unknown primary with diagnostic dilemma and challenged surgical intervention.

PubMed

Stakia, Paraskevi; Lagos, Panagiotis; Gourgiotis, Stavros; Tzilalis, Vasilios D; Aloizos, Stavros; Salemis, Nikolaos S

2009-01-01

Cancers of unknown primary site (CUPs) consist of a clinical entity which accounts for 3-5% of all solid tumor patients. They are metastatic solid tumors whose fundamental characteristic is the absence of identifiable site of the primary tumor. We report the case of a completely asymptomatic 34-year-old man with a palpated huge mass found incidentally in the left abdomen. All the investigations were normal. During the operation, a large mass was identified 2 cm below the left renal artery which was displacing and encompassing the great retroperitoneal vessels and the left ureter. A complete resection of the mass was performed while the histological examination revealed a solitary retroperitoneal lymph node categorized as metastatic adenocarcinoma of unknown primary site. It is essential to assess the high incidence of patients with cancer who present with CUP. Early surgical excision of the metastatic lesion followed by adjuvant combination chemotherapy should be considered for patients with only a single site of malignancy.

A large-scale dataset of single and mixed-source short tandem repeat profiles to inform human identification strategies: PROVEDIt.

PubMed

Alfonse, Lauren E; Garrett, Amanda D; Lun, Desmond S; Duffy, Ken R; Grgicak, Catherine M

2018-01-01

DNA-based human identity testing is conducted by comparison of PCR-amplified polymorphic Short Tandem Repeat (STR) motifs from a known source with the STR profiles obtained from uncertain sources. Samples such as those found at crime scenes often result in signal that is a composite of incomplete STR profiles from an unknown number of unknown contributors, making interpretation an arduous task. To facilitate advancement in STR interpretation challenges we provide over 25,000 multiplex STR profiles produced from one to five known individuals at target levels ranging from one to 160 copies of DNA. The data, generated under 144 laboratory conditions, are classified by total copy number and contributor proportions. For the 70% of samples that were synthetically compromised, we report the level of DNA damage using quantitative and end-point PCR. In addition, we characterize the complexity of the signal by exploring the number of detected alleles in each profile. Copyright © 2017 Elsevier B.V. All rights reserved.

Crystal structure of the toxin Msmeg_6760, the structural homolog of Mycobacterium tuberculosis Rv2035, a novel type II toxin involved in the hypoxic response

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

Bajaj, R. Alexandra; Arbing, Mark A.; Shin, Annie

The structure of Msmeg_6760, a protein of unknown function, has been determined. Biochemical and bioinformatics analyses determined that Msmeg_6760 interacts with a protein encoded in the same operon, Msmeg_6762, and predicted that the operon is a toxin–antitoxin (TA) system. Structural comparison of Msmeg_6760 with proteins of known function suggests that Msmeg_6760 binds a hydrophobic ligand in a buried cavity lined by large hydrophobic residues. Access to this cavity could be controlled by a gate–latch mechanism. The function of the Msmeg_6760 toxin is unknown, but structure-based predictions revealed that Msmeg_6760 and Msmeg_6762 are homologous to Rv2034 and Rv2035, a predicted novelmore » TA system involved inMycobacterium tuberculosislatency during macrophage infection. The Msmeg_6760 toxin fold has not been previously described for bacterial toxins and its unique structural features suggest that toxin activation is likely to be mediated by a novel mechanism.« less

Simple scheme for encoding and decoding a qubit in unknown state for various topological codes

PubMed Central

Łodyga, Justyna; Mazurek, Paweł; Grudka, Andrzej; Horodecki, Michał

2015-01-01

We present a scheme for encoding and decoding an unknown state for CSS codes, based on syndrome measurements. We illustrate our method by means of Kitaev toric code, defected-lattice code, topological subsystem code and 3D Haah code. The protocol is local whenever in a given code the crossings between the logical operators consist of next neighbour pairs, which holds for the above codes. For subsystem code we also present scheme in a noisy case, where we allow for bit and phase-flip errors on qubits as well as state preparation and syndrome measurement errors. Similar scheme can be built for two other codes. We show that the fidelity of the protected qubit in the noisy scenario in a large code size limit is of , where p is a probability of error on a single qubit per time step. Regarding Haah code we provide noiseless scheme, leaving the noisy case as an open problem. PMID:25754905

Capture-recapture studies for multiple strata including non-markovian transitions

USGS Publications Warehouse

Brownie, C.; Hines, J.E.; Nichols, J.D.; Pollock, K.H.; Hestbeck, J.B.

1993-01-01

We consider capture-recapture studies where release and recapture data are available from each of a number of strata on every capture occasion. Strata may, for example, be geographic locations or physiological states. Movement of animals among strata occurs with unknown probabilities, and estimation of these unknown transition probabilities is the objective. We describe a computer routine for carrying out the analysis under a model that assumes Markovian transitions and under reduced parameter versions of this model. We also introduce models that relax the Markovian assumption and allow 'memory' to operate (i.e., allow dependence of the transition probabilities on the previous state). For these models, we sugg st an analysis based on a conditional likelihood approach. Methods are illustrated with data from a large study on Canada geese (Branta canadensis) banded in three geographic regions. The assumption of Markovian transitions is rejected convincingly for these data, emphasizing the importance of the more general models that allow memory.

Clustering redshift distributions for the Dark Energy Survey

NASA Astrophysics Data System (ADS)

Helsby, Jennifer

Accurate determination of photometric redshifts and their errors is critical for large scale structure and weak lensing studies for constraining cosmology from deep, wide imaging surveys. Current photometric redshift methods suffer from bias and scatter due to incomplete training sets. Exploiting the clustering between a sample of galaxies for which we have spectroscopic redshifts and a sample of galaxies for which the redshifts are unknown can allow us to reconstruct the true redshift distribution of the unknown sample. Here we use this method in both simulations and early data from the Dark Energy Survey (DES) to determine the true redshift distributions of galaxies in photometric redshift bins. We find that cross-correlating with the spectroscopic samples currently used for training provides a useful test of photometric redshifts and provides reliable estimates of the true redshift distribution in a photometric redshift bin. We discuss the use of the cross-correlation method in validating template- or learning-based approaches to redshift estimation and its future use in Stage IV surveys.

Robust control of the DC-DC boost converter based on the uncertainty and disturbance estimator

NASA Astrophysics Data System (ADS)

Oucheriah, Said

2017-11-01

In this paper, a robust non-linear controller based on the uncertainty and disturbance estimator (UDE) scheme is successfully developed and implemented for the output voltage regulation of the DC-DC boost converter. System uncertainties, external disturbances and unknown non-linear dynamics are lumped as a signal that is accurately estimated using a low-pass filter and their effects are cancelled by the controller. This methodology forms the basis of the UDE-based controller. A simple procedure is also developed that systematically determines the parameters of the controller to meet certain specifications. Using simulation, the effectiveness of the proposed controller is compared against the sliding-mode control (SMC). Experimental tests also show that the proposed controller is robust to system uncertainties, large input and load perturbations.

Bayesian nonlinear structural FE model and seismic input identification for damage assessment of civil structures

NASA Astrophysics Data System (ADS)

Astroza, Rodrigo; Ebrahimian, Hamed; Li, Yong; Conte, Joel P.

2017-09-01

A methodology is proposed to update mechanics-based nonlinear finite element (FE) models of civil structures subjected to unknown input excitation. The approach allows to jointly estimate unknown time-invariant model parameters of a nonlinear FE model of the structure and the unknown time histories of input excitations using spatially-sparse output response measurements recorded during an earthquake event. The unscented Kalman filter, which circumvents the computation of FE response sensitivities with respect to the unknown model parameters and unknown input excitations by using a deterministic sampling approach, is employed as the estimation tool. The use of measurement data obtained from arrays of heterogeneous sensors, including accelerometers, displacement sensors, and strain gauges is investigated. Based on the estimated FE model parameters and input excitations, the updated nonlinear FE model can be interrogated to detect, localize, classify, and assess damage in the structure. Numerically simulated response data of a three-dimensional 4-story 2-by-1 bay steel frame structure with six unknown model parameters subjected to unknown bi-directional horizontal seismic excitation, and a three-dimensional 5-story 2-by-1 bay reinforced concrete frame structure with nine unknown model parameters subjected to unknown bi-directional horizontal seismic excitation are used to illustrate and validate the proposed methodology. The results of the validation studies show the excellent performance and robustness of the proposed algorithm to jointly estimate unknown FE model parameters and unknown input excitations.

Online Cross-Validation-Based Ensemble Learning

PubMed Central

Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

2017-01-01

Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. PMID:28474419

A study on model fidelity for model predictive control-based obstacle avoidance in high-speed autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Liu, Jiechao; Jayakumar, Paramsothy; Stein, Jeffrey L.; Ersal, Tulga

2016-11-01

This paper investigates the level of model fidelity needed in order for a model predictive control (MPC)-based obstacle avoidance algorithm to be able to safely and quickly avoid obstacles even when the vehicle is close to its dynamic limits. The context of this work is large autonomous ground vehicles that manoeuvre at high speed within unknown, unstructured, flat environments and have significant vehicle dynamics-related constraints. Five different representations of vehicle dynamics models are considered: four variations of the two degrees-of-freedom (DoF) representation as lower fidelity models and a fourteen DoF representation with combined-slip Magic Formula tyre model as a higher fidelity model. It is concluded that the two DoF representation that accounts for tyre nonlinearities and longitudinal load transfer is necessary for the MPC-based obstacle avoidance algorithm in order to operate the vehicle at its limits within an environment that includes large obstacles. For less challenging environments, however, the two DoF representation with linear tyre model and constant axle loads is sufficient.

Mapping the Human Toxome by Systems Toxicology

PubMed Central

Bouhifd, Mounir; Hogberg, Helena T.; Kleensang, Andre; Maertens, Alexandra; Zhao, Liang; Hartung, Thomas

2014-01-01

Toxicity testing typically involves studying adverse health outcomes in animals subjected to high doses of toxicants with subsequent extrapolation to expected human responses at lower doses. The low-throughput of current toxicity testing approaches (which are largely the same for industrial chemicals, pesticides and drugs) has led to a backlog of more than 80,000 chemicals to which human beings are potentially exposed whose potential toxicity remains largely unknown. Employing new testing strategies that employ the use of predictive, high-throughput cell-based assays (of human origin) to evaluate perturbations in key pathways, referred as pathways of toxicity, and to conduct targeted testing against those pathways, we can begin to greatly accelerate our ability to test the vast “storehouses” of chemical compounds using a rational, risk-based approach to chemical prioritization, and provide test results that are more predictive of human toxicity than current methods. The NIH Transformative Research Grant project Mapping the Human Toxome by Systems Toxicology aims at developing the tools for pathway mapping, annotation and validation as well as the respective knowledge base to share this information. PMID:24443875

Comments on the Yule Marble Haines block: potential replacement, Tomb of the Unknown Soldier, Arlington National Cemetery

USGS Publications Warehouse

Mossotti, Victor G.

2014-01-01

Marble for the Tomb of the Unknown Soldier at Arlington National Cemetery was cut from the Colorado Yule Marble Quarry in 1931. Although anecdotal reports suggest that cracks were noticed in the main section of the monument shortly after its installation at the Arlington National Cemetery in Arlington, Virginia, detailed documentation of the extent of cracking did not appear until 1963. Although debate continues as to whether the main section of the Tomb of the Unknowns monument should be repaired or replaced, Mr. John S. Haines of Glenwood Springs, Colorado, in anticipation of the permanent closing of the Yule Quarry, donated a 58-ton block of Yule Marble, the so-called Haines block, as a potential backup. The brief study reported here was conducted during mid-summer 2009 at the behest of the superintendent of Arlington National Cemetery. The field team entered the subterranean Yule Marble Quarry with the Chief Extraction Engineer in order to contrast the method used for extraction of the Haines block with the method that was probably used to extract the marble block that is now cracked. Based on surficial inspection and shallow coring of the Haines block, and on the nature of crack propagation in Yule Marble as judged by close inspection of a large collection of surrogate Yule Marble blocks, the team found the block to be structurally sound and cosmetically equivalent to the marble used for the current monument. If the Haines block were needed, it would be an appropriate replacement for the existing cracked section of the Tomb of the Unknown Soldier Monument.

Multilevel fast multipole method based on a potential formulation for 3D electromagnetic scattering problems.

PubMed

Fall, Mandiaye; Boutami, Salim; Glière, Alain; Stout, Brian; Hazart, Jerome

2013-06-01

A combination of the multilevel fast multipole method (MLFMM) and boundary element method (BEM) can solve large scale photonics problems of arbitrary geometry. Here, MLFMM-BEM algorithm based on a scalar and vector potential formulation, instead of the more conventional electric and magnetic field formulations, is described. The method can deal with multiple lossy or lossless dielectric objects of arbitrary geometry, be they nested, in contact, or dispersed. Several examples are used to demonstrate that this method is able to efficiently handle 3D photonic scatterers involving large numbers of unknowns. Absorption, scattering, and extinction efficiencies of gold nanoparticle spheres, calculated by the MLFMM, are compared with Mie's theory. MLFMM calculations of the bistatic radar cross section (RCS) of a gold sphere near the plasmon resonance and of a silica coated gold sphere are also compared with Mie theory predictions. Finally, the bistatic RCS of a nanoparticle gold-silver heterodimer calculated with MLFMM is compared with unmodified BEM calculations.

Distributed Optimization Design of Continuous-Time Multiagent Systems With Unknown-Frequency Disturbances.

PubMed

Wang, Xinghu; Hong, Yiguang; Yi, Peng; Ji, Haibo; Kang, Yu

2017-05-24

In this paper, a distributed optimization problem is studied for continuous-time multiagent systems with unknown-frequency disturbances. A distributed gradient-based control is proposed for the agents to achieve the optimal consensus with estimating unknown frequencies and rejecting the bounded disturbance in the semi-global sense. Based on convex optimization analysis and adaptive internal model approach, the exact optimization solution can be obtained for the multiagent system disturbed by exogenous disturbances with uncertain parameters.

Direct Analysis in Real Time Mass Spectrometry for Characterization of Large Saccharides.

PubMed

Ma, Huiying; Jiang, Qing; Dai, Diya; Li, Hongli; Bi, Wentao; Da Yong Chen, David

2018-03-06

Polysaccharide characterization posts the most difficult challenge to available analytical technologies compared to other types of biomolecules. Plant polysaccharides are reported to have numerous medicinal values, but their effect can be different based on the types of plants, and even regions of productions and conditions of cultivation. However, the molecular basis of the differences of these polysaccharides is largely unknown. In this study, direct analysis in real time mass spectrometry (DART-MS) was used to generate polysaccharide fingerprints. Large saccharides can break down into characteristic small fragments in the DART source via pyrolysis, and the products are then detected by high resolution MS. Temperature was shown to be a crucial parameter for the decomposition of large polysaccharide. The general behavior of carbohydrates in DART-MS was also studied through the investigation of a number of mono- and oligosaccharide standards. The chemical formula and putative ionic forms of the fragments were proposed based on accurate mass with less than 10 ppm mass errors. Multivariate data analysis shows the clear differentiation of different plant species. Intensities of marker ions compared among samples also showed obvious differences. The combination of DART-MS analysis and mechanochemical extraction method used in this work demonstrates a simple, fast, and high throughput analytical protocol for the efficient evaluation of molecular features in plant polysaccharides.

DNA attachment to support structures

DOEpatents

Balhorn, Rodney L.; Barry, Christopher H.

2002-01-01

Microscopic beads or other structures are attached to nucleic acids (DNA) using a terminal transferase. The transferase adds labeled dideoxy nucleotide bases to the ends of linear strands of DNA. The labels, such as the antigens digoxigenin and biotin, bind to the antibody compounds or other appropriate complementary ligands, which are bound to the microscopic beads or other support structures. The method does not require the synthesis of a synthetic oligonucleotide probe. The method can be used to tag or label DNA even when the DNA has an unknown sequence, has blunt ends, or is a very large fragment (e.g., >500 kilobase pairs).

Associations between antimicrobial stewardship program elements and Clostridium difficile infection performance.

PubMed

Barlow, Giulia; Patterson, Julie; Stultz, Jeremy; Pakyz, Amy L

2017-12-01

Hospitals are categorized as better, no different, or worse at a national level based on their Clostridium difficile infection performance. Institutional antimicrobial stewardship programs seek to decrease the occurrence of C difficile by implementing strategies to address antibiotic usage; however, optimal structure and strategies for accomplishing this remain largely unknown. We found that a higher proportion of hospitals with either a worse or no different rank used a postprescription audit and feedback strategy than hospitals with a better rank. Copyright © 2017 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.

Epistemic and aleatory uncertainty in the study of dynamic human-water systems

NASA Astrophysics Data System (ADS)

Di Baldassarre, Giuliano; Brandimarte, Luigia; Beven, Keith

2016-04-01

Here we discuss epistemic and aleatory uncertainty in the study of dynamic human-water systems (e.g. socio-hydrology), which is one of the main topics of Panta Rhei, the current scientific decade of the International Association of Hydrological Sciences (IAHS). In particular, we identify three types of lack of understanding: (i) known unknowns, which are things we know we don't know; (ii) unknown unknowns, which are things we don't know we don't know; and (iii) wrong assumptions, things we think we know, but we actually don't know. We posit that a better understanding of human-water interactions and feedbacks can help coping with wrong assumptions and known unknowns. Moreover, being aware of the existence of unknown unknowns, and their potential capability to generate surprises or black swans, suggest the need to rely more on bottom-up approaches, based on social vulnerabilities and possibilities of failures, and less on top-down approaches, based on optimization and quantitative predictions.

Flagellum synchronization inhibits large-scale hydrodynamic instabilities in sperm suspensions

NASA Astrophysics Data System (ADS)

Schöller, Simon F.; Keaveny, Eric E.

2016-11-01

Sperm in suspension can exhibit large-scale collective motion and form coherent structures. Our picture of such coherent motion is largely based on reduced models that treat the swimmers as self-locomoting rigid bodies that interact via steady dipolar flow fields. Swimming sperm, however, have many more degrees of freedom due to elasticity, have a more exotic shape, and generate spatially-complex, time-dependent flow fields. While these complexities are known to lead to phenomena such as flagellum synchronization and attraction, how these effects impact the overall suspension behaviour and coherent structure formation is largely unknown. Using a computational model that captures both flagellum beating and elasticity, we simulate suspensions on the order of 103 individual swimming sperm cells whose motion is coupled through the surrounding Stokesian fluid. We find that the tendency for flagella to synchronize and sperm to aggregate inhibits the emergence of the large-scale hydrodynamic instabilities often associated with active suspensions. However, when synchronization is repressed by adding noise in the flagellum actuation mechanism, the picture changes and the structures that resemble large-scale vortices appear to re-emerge. Supported by an Imperial College PhD scholarship.

Microlens Masses from Astrometry and Parallax in Space-based Surveys: From Planets to Black Holes

NASA Astrophysics Data System (ADS)

Gould, Andrew; Yee, Jennifer C.

2014-03-01

We show that space-based microlensing experiments can recover lens masses and distances for a large fraction of all events (those with individual photometric errors <~ 0.01 mag) using a combination of one-dimensional microlens parallaxes and astrometric microlensing. This will provide a powerful probe of the mass distributions of planets, black holes, and neutron stars, the distribution of planets as a function of Galactic environment, and the velocity distributions of black holes and neutron stars. While systematics are in principle a significant concern, we show that it is possible to vet against all systematics (known and unknown) using single-epoch precursor observations with the Hubble Space Telescope roughly 10 years before the space mission.

Fluorometric imaging methods for palladium and platinum and the use of palladium for imaging biomolecules.

PubMed

Tracey, Matthew P; Pham, Dianne; Koide, Kazunori

2015-07-21

Neither palladium nor platinum is an endogenous biological metal. Imaging palladium in biological samples, however, is becoming increasingly important because bioorthogonal organometallic chemistry involves palladium catalysis. In addition to being an imaging target, palladium has been used to fluorometrically image biomolecules. In these cases, palladium species are used as imaging-enabling reagents. This review article discusses these fluorometric methods. Platinum-based drugs are widely used as anticancer drugs, yet their mechanism of action remains largely unknown. We discuss fluorometric methods for imaging or quantifying platinum in cells or biofluids. These methods include the use of chemosensors to directly detect platinum, fluorescently tagging platinum-based drugs, and utilizing post-labeling to elucidate distribution and mode of action.

Carcinoma of Unknown Primary—Health Professional Version

Cancer.gov

Carcinoma of unknown primary (CUP) is a rare disease in which malignant cells are found in the body but the site of the primary cancer is not known. Most CUPs are adenocarcinomas, or undifferentiated tumors. Find evidence-based information on the treatment for carcinoma of unknown primary.

Selection of core animals in the Algorithm for Proven and Young using a simulation model.

PubMed

Bradford, H L; Pocrnić, I; Fragomeni, B O; Lourenco, D A L; Misztal, I

2017-12-01

The Algorithm for Proven and Young (APY) enables the implementation of single-step genomic BLUP (ssGBLUP) in large, genotyped populations by separating genotyped animals into core and non-core subsets and creating a computationally efficient inverse for the genomic relationship matrix (G). As APY became the choice for large-scale genomic evaluations in BLUP-based methods, a common question is how to choose the animals in the core subset. We compared several core definitions to answer this question. Simulations comprised a moderately heritable trait for 95,010 animals and 50,000 genotypes for animals across five generations. Genotypes consisted of 25,500 SNP distributed across 15 chromosomes. Genotyping errors and missing pedigree were also mimicked. Core animals were defined based on individual generations, equal representation across generations, and at random. For a sufficiently large core size, core definitions had the same accuracies and biases, even if the core animals had imperfect genotypes. When genotyped animals had unknown parents, accuracy and bias were significantly better (p ≤ .05) for random and across generation core definitions. © 2017 The Authors. Journal of Animal Breeding and Genetics Published by Blackwell Verlag GmbH.

An eigenvalue approach for the automatic scaling of unknowns in model-based reconstructions: Application to real-time phase-contrast flow MRI.

PubMed

Tan, Zhengguo; Hohage, Thorsten; Kalentev, Oleksandr; Joseph, Arun A; Wang, Xiaoqing; Voit, Dirk; Merboldt, K Dietmar; Frahm, Jens

2017-12-01

The purpose of this work is to develop an automatic method for the scaling of unknowns in model-based nonlinear inverse reconstructions and to evaluate its application to real-time phase-contrast (RT-PC) flow magnetic resonance imaging (MRI). Model-based MRI reconstructions of parametric maps which describe a physical or physiological function require the solution of a nonlinear inverse problem, because the list of unknowns in the extended MRI signal equation comprises multiple functional parameters and all coil sensitivity profiles. Iterative solutions therefore rely on an appropriate scaling of unknowns to numerically balance partial derivatives and regularization terms. The scaling of unknowns emerges as a self-adjoint and positive-definite matrix which is expressible by its maximal eigenvalue and solved by power iterations. The proposed method is applied to RT-PC flow MRI based on highly undersampled acquisitions. Experimental validations include numerical phantoms providing ground truth and a wide range of human studies in the ascending aorta, carotid arteries, deep veins during muscular exercise and cerebrospinal fluid during deep respiration. For RT-PC flow MRI, model-based reconstructions with automatic scaling not only offer velocity maps with high spatiotemporal acuity and much reduced phase noise, but also ensure fast convergence as well as accurate and precise velocities for all conditions tested, i.e. for different velocity ranges, vessel sizes and the simultaneous presence of signals with velocity aliasing. In summary, the proposed automatic scaling of unknowns in model-based MRI reconstructions yields quantitatively reliable velocities for RT-PC flow MRI in various experimental scenarios. Copyright © 2017 John Wiley & Sons, Ltd.

Genome-wide computational prediction and analysis of core promoter elements across plant monocots and dicots

USDA-ARS?s Scientific Manuscript database

Transcription initiation, essential to gene expression regulation, involves recruitment of basal transcription factors to the core promoter elements (CPEs). The distribution of currently known CPEs across plant genomes is largely unknown. This is the first large scale genome-wide report on the compu...

Neurobiologically based interventions for autism spectrum disorders-rationale and new directions.

PubMed

Poustka, Luise; Brandeis, Daniel; Hohmann, Sarah; Holtmann, Martin; Bölte, Sven; Banaschewski, Tobias

2014-01-01

Autism spectrum disorders (ASD) are heterogeneous, neurodevelopmental disorders with early onset, characterized by a triad of impairments in reciprocal interaction and communication as well as repetitive and restricted interests and activities. Though underlying causes still remain largely unknown, there is now evidence for abnormal growth trajectories in the early brain development in ASD during vulnerable periods and subsequent impairment of neuronal organization and differentiation of neuronal networks. A growing number of studies over the last 10 years support the efficacy of behaviorally based interventions in ASD for the improvement of social communication and behavioral functioning. In contrast, research on neurobiologically based therapies for ASD is still at its beginnings. In this article, we will provide a selective overview of novel interventions and trainings based on neurobiological principles. Directions and options for future research on treatment aiming at restoration of normal plasticity in disrupted brain circuits in ASD are discussed.

Virus-Based MicroRNA Silencing in Plants1[C][W][OPEN

PubMed Central

Sha, Aihua; Zhao, Jinping; Yin, Kangquan; Tang, Yang; Wang, Yan; Wei, Xiang; Hong, Yiguo; Liu, Yule

2014-01-01

MicroRNAs (miRNAs) play pivotal roles in various biological processes across kingdoms. Many plant miRNAs have been experimentally identified or predicted by bioinformatics mining of small RNA databases. However, the functions of these miRNAs remain largely unknown due to the lack of effective genetic tools. Here, we report a virus-based microRNA silencing (VbMS) system that can be used for functional analysis of plant miRNAs. VbMS is performed through tobacco rattle virus-based expression of miRNA target mimics to silence endogenous miRNAs. VbMS of either miR172 or miR165/166 caused developmental defects in Nicotiana benthamiana. VbMS of miR319 reduced the complexity of tomato (Solanum lycopersicum) compound leaves. These results demonstrate that tobacco rattle virus-based VbMS is a powerful tool to silence endogenous miRNAs and to dissect their functions in different plant species. PMID:24296072

Observer-based robust finite time H∞ sliding mode control for Markovian switching systems with mode-dependent time-varying delay and incomplete transition rate.

PubMed

Gao, Lijun; Jiang, Xiaoxiao; Wang, Dandan

2016-03-01

This paper investigates the problem of robust finite time H∞ sliding mode control for a class of Markovian switching systems. The system is subjected to the mode-dependent time-varying delay, partly unknown transition rate and unmeasurable state. The main difficulty is that, a sliding mode surface cannot be designed based on the unknown transition rate and unmeasurable state directly. To overcome this obstacle, the set of modes is firstly divided into two subsets standing for known transition rate subset and unknown one, based on which a state observer is established. A component robust finite-time sliding mode controller is also designed to cope with the effect of partially unknown transition rate. It is illustrated that the reachability, finite-time stability, finite-time boundedness, finite-time H∞ state feedback stabilization of sliding mode dynamics can be ensured despite the unknown transition rate. Finally, the simulation results verify the effectiveness of robust finite time control problem. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Progressive forest canopy water loss during the 2012-2015 California drought.

PubMed

Asner, Gregory P; Brodrick, Philip G; Anderson, Christopher B; Vaughn, Nicholas; Knapp, David E; Martin, Roberta E

2016-01-12

The 2012-2015 drought has left California with severely reduced snowpack, soil moisture, ground water, and reservoir stocks, but the impact of this estimated millennial-scale event on forest health is unknown. We used airborne laser-guided spectroscopy and satellite-based models to assess losses in canopy water content of California's forests between 2011 and 2015. Approximately 10.6 million ha of forest containing up to 888 million large trees experienced measurable loss in canopy water content during this drought period. Severe canopy water losses of greater than 30% occurred over 1 million ha, affecting up to 58 million large trees. Our measurements exclude forests affected by fire between 2011 and 2015. If drought conditions continue or reoccur, even with temporary reprieves such as El Niño, we predict substantial future forest change.

An abundance of rare functional variants in 202 drug target genes sequenced in 14,002 people

PubMed Central

Nelson, Matthew R.; Wegmann, Daniel; Ehm, Margaret G.; Kessner, Darren; St. Jean, Pamela; Verzilli, Claudio; Shen, Judong; Tang, Zhengzheng; Bacanu, Silviu-Alin; Fraser, Dana; Warren, Liling; Aponte, Jennifer; Zawistowski, Matthew; Liu, Xiao; Zhang, Hao; Zhang, Yong; Li, Jun; Li, Yun; Li, Li; Woollard, Peter; Topp, Simon; Hall, Matthew D.; Nangle, Keith; Wang, Jun; Abecasis, Gonçalo; Cardon, Lon R.; Zöllner, Sebastian; Whittaker, John C.; Chissoe, Stephanie L.; Novembre, John; Mooser, Vincent

2015-01-01

Rare genetic variants contribute to complex disease risk; however, the abundance of rare variants in human populations remains unknown. We explored this spectrum of variation by sequencing 202 genes encoding drug targets in 14,002 individuals. We find rare variants are abundant (one every 17 bases) and geographically localized, such that even with large sample sizes, rare variant catalogs will be largely incomplete. We used the observed patterns of variation to estimate population growth parameters, the proportion of variants in a given frequency class that are putatively deleterious, and mutation rates for each gene. Overall we conclude that, due to rapid population growth and weak purifying selection, human populations harbor an abundance of rare variants, many of which are deleterious and have relevance to understanding disease risk. PMID:22604722

Place recognition using batlike sonar.

PubMed

Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

2016-08-02

Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map.

Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Kashima, Hisashi; Tanaka, Isao

2018-01-01

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine learning is a unique approach to search for currently unknown CRCs from vast candidates. Herein we propose matrix- and tensor-based recommender system approaches to predict currently unknown CRCs from database entries of CRCs. Firstly, the performance of the recommender system approaches to discover currently unknown CRCs is examined. A Tucker decomposition recommender system shows the best discovery rate of CRCs as the majority of the top 100 recommended ternary and quaternary compositions correspond to CRCs. Secondly, systematic density functional theory (DFT) calculations are performed to investigate the phase stability of the recommended compositions. The phase stability of the 27 compositions reveals that 23 currently unknown compounds are newly found to be stable. These results indicate that the recommender system has great potential to accelerate the discovery of new compounds.

Chitin-Like Molecules Associate with Cryptococcus neoformans Glucuronoxylomannan To Form a Glycan Complex with Previously Unknown Properties

PubMed Central

Ramos, Caroline L.; Fonseca, Fernanda L.; Rodrigues, Jessica; Guimarães, Allan J.; Cinelli, Leonardo P.; Miranda, Kildare; Nimrichter, Leonardo; Casadevall, Arturo; Travassos, Luiz R.

2012-01-01

In prior studies, we demonstrated that glucuronoxylomannan (GXM), the major capsular polysaccharide of the fungal pathogen Cryptococcus neoformans, interacts with chitin oligomers at the cell wall-capsule interface. The structural determinants regulating these carbohydrate-carbohydrate interactions, as well as the functions of these structures, have remained unknown. In this study, we demonstrate that glycan complexes composed of chitooligomers and GXM are formed during fungal growth and macrophage infection by C. neoformans. To investigate the required determinants for the assembly of chitin-GXM complexes, we developed a quantitative scanning electron microscopy-based method using different polysaccharide samples as inhibitors of the interaction of chitin with GXM. This assay revealed that chitin-GXM association involves noncovalent bonds and large GXM fibers and depends on the N-acetyl amino group of chitin. Carboxyl and O-acetyl groups of GXM are not required for polysaccharide-polysaccharide interactions. Glycan complex structures composed of cryptococcal GXM and chitin-derived oligomers were tested for their ability to induce pulmonary cytokines in mice. They were significantly more efficient than either GXM or chitin oligomers alone in inducing the production of lung interleukin 10 (IL-10), IL-17, and tumor necrosis factor alpha (TNF-α). These results indicate that association of chitin-derived structures with GXM through their N-acetyl amino groups generates glycan complexes with previously unknown properties. PMID:22562469

Epidemiology of Domestically Acquired Amebiasis in Japan, 2000–2013

PubMed Central

Ishikane, Masahiro; Arima, Yuzo; Kanayama, Atsuhiro; Takahashi, Takuri; Yamagishi, Takuya; Yahata, Yuichiro; Matsui, Tamano; Sunagawa, Tomimasa; Nozaki, Tomoyoshi; Oishi, Kazunori

2016-01-01

Notifications of amebiasis have been increasing in Japan. Using national surveillance data during 2000–2013, reported cases of amebiasis were analyzed. A case of amebiasis was defined as laboratory-confirmed Entamoeba histolytica infection, regardless of presence of symptoms. We described temporal trends and analyzed correlates of asymptomatic versus symptomatic cases based on odds ratios (ORs) and 95% confidence intervals (CIs) using logistic regression. Of 9,946 cases reported during 2000–2013, 7,403 were domestic cases. During this period, the proportion of domestic cases increased from 63% to 85%. Among male cases, majority were middle aged, and from 2008, the number of cases attributed to heterosexual contact surpassed that of homosexual contact. During 2010–2013, increase in notifications was associated with asymptomatic cases, colonoscopy diagnosis, and males with unknown or heterosexual route of infection. Among males, colonoscopy (OR = 31.5; 95% CI = 14.0–71.0) and cases with unknown route of infection, relative to homosexual contact (OR = 2.2; 95% CI = 1.3–3.9), were associated with asymptomatic infections in multivariate analysis. Although the recent rise may have been due to enhanced detection by colonoscopy or reporting, the large number of asymptomatic cases, with reportedly unknown or heterosexual route of infection, has led to a better understanding of amebiasis in Japan and highlights the potential public health concern. PMID:26976888

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras.

PubMed

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-08-30

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme.

Target Capturing Control for Space Robots with Unknown Mass Properties: A Self-Tuning Method Based on Gyros and Cameras

PubMed Central

Li, Zhenyu; Wang, Bin; Liu, Hong

2016-01-01

Satellite capturing with free-floating space robots is still a challenging task due to the non-fixed base and unknown mass property issues. In this paper gyro and eye-in-hand camera data are adopted as an alternative choice for solving this problem. For this improved system, a new modeling approach that reduces the complexity of system control and identification is proposed. With the newly developed model, the space robot is equivalent to a ground-fixed manipulator system. Accordingly, a self-tuning control scheme is applied to handle such a control problem including unknown parameters. To determine the controller parameters, an estimator is designed based on the least-squares technique for identifying the unknown mass properties in real time. The proposed method is tested with a credible 3-dimensional ground verification experimental system, and the experimental results confirm the effectiveness of the proposed control scheme. PMID:27589748

Three-dimensional cinematography with control object of unknown shape.

PubMed

Dapena, J; Harman, E A; Miller, J A

1982-01-01

A technique for reconstruction of three-dimensional (3D) motion which involves a simple filming procedure but allows the deduction of coordinates in large object volumes was developed. Internal camera parameters are calculated from measurements of the film images of two calibrated crosses while external camera parameters are calculated from the film images of points in a control object of unknown shape but at least one known length. The control object, which includes the volume in which the activity is to take place, is formed by a series of poles placed at unknown locations, each carrying two targets. From the internal and external camera parameters, and from locations of the images of point in the films of the two cameras, 3D coordinates of the point can be calculated. Root mean square errors of the three coordinates of points in a large object volume (5m x 5m x 1.5m) were 15 mm, 13 mm, 13 mm and 6 mm, and relative errors in lengths averaged 0.5%, 0.7% and 0.5%, respectively.

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

Kim, A.; Avakian, H.; Burkert, V.

The target and double spin asymmetries of the exclusive pseudoscalar channel e→p→→epπ0 were measured for the first time in the deep-inelastic regime using a longitudinally polarized 5.9 GeV electron beam and a longitudinally polarized proton target at Jefferson Lab with the CEBAF Large Acceptance Spectrometer (CLAS). The data were collected over a large kinematic phase space and divided into 110 four-dimensional bins of Q2, xB, -t and Φ. Large values of asymmetry moments clearly indicate a substantial contribution to the polarized structure functions from transverse virtual photon amplitudes. The interpretation of experimental data in terms of generalized parton distributions (GPDs)more » provides the first insight on the chiral-odd GPDs H˜T and ET, and complement previous measurements of unpolarized structure functions sensitive to the GPDs HT and E¯T. These data provide a crucial input for parametrizations of essentially unknown chiral-odd GPDs and will strongly influence existing theoretical calculations based on the handbag formalism.« less

Direct Solve of Electrically Large Integral Equations for Problem Sizes to 1M Unknowns

NASA Technical Reports Server (NTRS)

Shaeffer, John

2008-01-01

Matrix methods for solving integral equations via direct solve LU factorization are presently limited to weeks to months of very expensive supercomputer time for problems sizes of several hundred thousand unknowns. This report presents matrix LU factor solutions for electromagnetic scattering problems for problem sizes to one million unknowns with thousands of right hand sides that run in mere days on PC level hardware. This EM solution is accomplished by utilizing the numerical low rank nature of spatially blocked unknowns using the Adaptive Cross Approximation for compressing the rank deficient blocks of the system Z matrix, the L and U factors, the right hand side forcing function and the final current solution. This compressed matrix solution is applied to a frequency domain EM solution of Maxwell's equations using standard Method of Moments approach. Compressed matrix storage and operations count leads to orders of magnitude reduction in memory and run time.

A Personalized QoS Prediction Approach for CPS Service Recommendation Based on Reputation and Location-Aware Collaborative Filtering.

PubMed

Kuang, Li; Yu, Long; Huang, Lan; Wang, Yin; Ma, Pengju; Li, Chuanbin; Zhu, Yujia

2018-05-14

With the rapid development of cyber-physical systems (CPS), building cyber-physical systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedure of building Cyber-physical systems, it has been found that a large number of functionally equivalent services exist, so it becomes an urgent task to recommend suitable services from the large number of services available in CPS. However, since it is time-consuming, and even impractical, for a single user to invoke all of the services in CPS to experience their QoS, a robust QoS prediction method is needed to predict unknown QoS values. A commonly used method in QoS prediction is collaborative filtering, however, it is hard to deal with the data sparsity and cold start problem, and meanwhile most of the existing methods ignore the data credibility issue. Thence, in order to solve both of these challenging problems, in this paper, we design a framework of QoS prediction for CPS services, and propose a personalized QoS prediction approach based on reputation and location-aware collaborative filtering. Our approach first calculates the reputation of users by using the Dirichlet probability distribution, so as to identify untrusted users and process their unreliable data, and then it digs out the geographic neighborhood in three levels to improve the similarity calculation of users and services. Finally, the data from geographical neighbors of users and services are fused to predict the unknown QoS values. The experiments using real datasets show that our proposed approach outperforms other existing methods in terms of accuracy, efficiency, and robustness.

A Personalized QoS Prediction Approach for CPS Service Recommendation Based on Reputation and Location-Aware Collaborative Filtering

PubMed Central

Huang, Lan; Wang, Yin; Ma, Pengju; Li, Chuanbin; Zhu, Yujia

2018-01-01

With the rapid development of cyber-physical systems (CPS), building cyber-physical systems with high quality of service (QoS) has become an urgent requirement in both academia and industry. During the procedure of building Cyber-physical systems, it has been found that a large number of functionally equivalent services exist, so it becomes an urgent task to recommend suitable services from the large number of services available in CPS. However, since it is time-consuming, and even impractical, for a single user to invoke all of the services in CPS to experience their QoS, a robust QoS prediction method is needed to predict unknown QoS values. A commonly used method in QoS prediction is collaborative filtering, however, it is hard to deal with the data sparsity and cold start problem, and meanwhile most of the existing methods ignore the data credibility issue. Thence, in order to solve both of these challenging problems, in this paper, we design a framework of QoS prediction for CPS services, and propose a personalized QoS prediction approach based on reputation and location-aware collaborative filtering. Our approach first calculates the reputation of users by using the Dirichlet probability distribution, so as to identify untrusted users and process their unreliable data, and then it digs out the geographic neighborhood in three levels to improve the similarity calculation of users and services. Finally, the data from geographical neighbors of users and services are fused to predict the unknown QoS values. The experiments using real datasets show that our proposed approach outperforms other existing methods in terms of accuracy, efficiency, and robustness. PMID:29757995

Cultural Resources Investigations, Cross Basin Channel Realignments, Atchafalaya Basin, Louisiana

DTIC Science & Technology

1990-12-01

of the currently-planned Old Atchafalaya River Area. On Upper Grand River, opposite the mouth of Bayou Pigeon (Figure 13), Moore reported another mound...might have been buried by the large amount of recent sedimentation. To illustrate this point, Kniffen referred to the mound "opposite Bayou Pigeon " (16...Lake Natchez Ridge Shell Ridge Unknown Prelistoric * 16 IV 15 Mound at Bayou Pigeon Mound Unknown Prehistoric * 16 IV 156 Alabama-Bayou Des Ourses Mound

14. Photographic copy of photograph dated ca. 1925; Photographer unknown; ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Photographic copy of photograph dated ca. 1925; Photographer unknown; Original in Rath collection at Iowa State University Libraries, Department of Special Collection, Ames, Iowa; Filed under: Rath Packing Company, Public Relations, Symbol N, Box 106, File 6: THE RATH COMPLEX IN THE MID 1920; LARGE BUILDING TO LEFT OF SMOKESTACK IS HOG KILL (BUILDING 40); LOOKING NORTH FROM ACROSS CEDAR RIVER - Rath Packing Company, Sycamore Street between Elm & Eighteenth Streets, Waterloo, Black Hawk County, IA

A Reduced-Order Successive Linear Estimator for Geostatistical Inversion and its Application in Hydraulic Tomography

NASA Astrophysics Data System (ADS)

Zha, Yuanyuan; Yeh, Tian-Chyi J.; Illman, Walter A.; Zeng, Wenzhi; Zhang, Yonggen; Sun, Fangqiang; Shi, Liangsheng

2018-03-01

Hydraulic tomography (HT) is a recently developed technology for characterizing high-resolution, site-specific heterogeneity using hydraulic data (nd) from a series of cross-hole pumping tests. To properly account for the subsurface heterogeneity and to flexibly incorporate additional information, geostatistical inverse models, which permit a large number of spatially correlated unknowns (ny), are frequently used to interpret the collected data. However, the memory storage requirements for the covariance of the unknowns (ny × ny) in these models are prodigious for large-scale 3-D problems. Moreover, the sensitivity evaluation is often computationally intensive using traditional difference method (ny forward runs). Although employment of the adjoint method can reduce the cost to nd forward runs, the adjoint model requires intrusive coding effort. In order to resolve these issues, this paper presents a Reduced-Order Successive Linear Estimator (ROSLE) for analyzing HT data. This new estimator approximates the covariance of the unknowns using Karhunen-Loeve Expansion (KLE) truncated to nkl order, and it calculates the directional sensitivities (in the directions of nkl eigenvectors) to form the covariance and cross-covariance used in the Successive Linear Estimator (SLE). In addition, the covariance of unknowns is updated every iteration by updating the eigenvalues and eigenfunctions. The computational advantages of the proposed algorithm are demonstrated through numerical experiments and a 3-D transient HT analysis of data from a highly heterogeneous field site.

Off-Policy Actor-Critic Structure for Optimal Control of Unknown Systems With Disturbances.

PubMed

Song, Ruizhuo; Lewis, Frank L; Wei, Qinglai; Zhang, Huaguang

2016-05-01

An optimal control method is developed for unknown continuous-time systems with unknown disturbances in this paper. The integral reinforcement learning (IRL) algorithm is presented to obtain the iterative control. Off-policy learning is used to allow the dynamics to be completely unknown. Neural networks are used to construct critic and action networks. It is shown that if there are unknown disturbances, off-policy IRL may not converge or may be biased. For reducing the influence of unknown disturbances, a disturbances compensation controller is added. It is proven that the weight errors are uniformly ultimately bounded based on Lyapunov techniques. Convergence of the Hamiltonian function is also proven. The simulation study demonstrates the effectiveness of the proposed optimal control method for unknown systems with disturbances.

An integrated approach to piezoactuator positioning in high-speed atomic force microscope imaging

NASA Astrophysics Data System (ADS)

Yan, Yan; Wu, Ying; Zou, Qingze; Su, Chanmin

2008-07-01

In this paper, an integrated approach to achieve high-speed atomic force microscope (AFM) imaging of large-size samples is proposed, which combines the enhanced inversion-based iterative control technique to drive the piezotube actuator control for lateral x-y axis positioning with the use of a dual-stage piezoactuator for vertical z-axis positioning. High-speed, large-size AFM imaging is challenging because in high-speed lateral scanning of the AFM imaging at large size, large positioning error of the AFM probe relative to the sample can be generated due to the adverse effects—the nonlinear hysteresis and the vibrational dynamics of the piezotube actuator. In addition, vertical precision positioning of the AFM probe is even more challenging (than the lateral scanning) because the desired trajectory (i.e., the sample topography profile) is unknown in general, and the probe positioning is also effected by and sensitive to the probe-sample interaction. The main contribution of this article is the development of an integrated approach that combines advanced control algorithm with an advanced hardware platform. The proposed approach is demonstrated in experiments by imaging a large-size (50μm ) calibration sample at high-speed (50Hz scan rate).

Optimal Transport Destination for Ischemic Stroke Patients With Unknown Vessel Status: Use of Prehospital Triage Scores.

PubMed

Schlemm, Eckhard; Ebinger, Martin; Nolte, Christian H; Endres, Matthias; Schlemm, Ludwig

2017-08-01

Patients with acute ischemic stroke (AIS) and large vessel occlusion may benefit from direct transportation to an endovascular capable comprehensive stroke center (mothership approach) as opposed to direct transportation to the nearest stroke unit without endovascular therapy (drip and ship approach). The optimal transport strategy for patients with AIS and unknown vessel status is uncertain. The rapid arterial occlusion evaluation scale (RACE, scores ranging from 0 to 9, with higher scores indicating higher stroke severity) correlates with the National Institutes of Health Stroke Scale and was developed to identify patients with large vessel occlusion in a prehospital setting. We evaluate how the RACE scale can help to inform prehospital triage decisions for AIS patients. In a model-based approach, we estimate probabilities of good outcome (modified Rankin Scale score of ≤2 at 3 months) as a function of severity of stroke symptoms and transport times for the mothership approach and the drip and ship approach. We use these probabilities to obtain optimal RACE cutoff scores for different transfer time settings and combinations of treatment options (time-based eligibility for secondary transfer under the drip and ship approach, time-based eligibility for thrombolysis at the comprehensive stroke center under the mothership approach). In our model, patients with AIS are more likely to benefit from direct transportation to the comprehensive stroke center if they have more severe strokes. Values of the optimal RACE cutoff scores range from 0 (mothership for all patients) to >9 (drip and ship for all patients). Shorter transfer times and longer door-to-needle and needle-to-transfer (door out) times are associated with lower optimal RACE cutoff scores. Use of RACE cutoff scores that take into account transport times to triage AIS patients to the nearest appropriate hospital may lead to improved outcomes. Further studies should examine the feasibility of translation into clinical practice. © 2017 American Heart Association, Inc.

Fuzzy Adaptive Decentralized Optimal Control for Strict Feedback Nonlinear Large-Scale Systems.

PubMed

Sun, Kangkang; Sui, Shuai; Tong, Shaocheng

2018-04-01

This paper considers the optimal decentralized fuzzy adaptive control design problem for a class of interconnected large-scale nonlinear systems in strict feedback form and with unknown nonlinear functions. The fuzzy logic systems are introduced to learn the unknown dynamics and cost functions, respectively, and a state estimator is developed. By applying the state estimator and the backstepping recursive design algorithm, a decentralized feedforward controller is established. By using the backstepping decentralized feedforward control scheme, the considered interconnected large-scale nonlinear system in strict feedback form is changed into an equivalent affine large-scale nonlinear system. Subsequently, an optimal decentralized fuzzy adaptive control scheme is constructed. The whole optimal decentralized fuzzy adaptive controller is composed of a decentralized feedforward control and an optimal decentralized control. It is proved that the developed optimal decentralized controller can ensure that all the variables of the control system are uniformly ultimately bounded, and the cost functions are the smallest. Two simulation examples are provided to illustrate the validity of the developed optimal decentralized fuzzy adaptive control scheme.

Cost-effectiveness of using a gene expression profiling test to aid in identifying the primary tumour in patients with cancer of unknown primary.

PubMed

Hannouf, M B; Winquist, E; Mahmud, S M; Brackstone, M; Sarma, S; Rodrigues, G; Rogan, P; Hoch, J S; Zaric, G S

2017-06-01

We aimed to investigate the cost-effectiveness of a 2000-gene-expression profiling (GEP) test to help identify the primary tumor site when clinicopathological diagnostic evaluation was inconclusive in patients with cancer of unknown primary (CUP). We built a decision-analytic-model to project the lifetime clinical and economic consequences of different clinical management strategies for CUP. The model was parameterized using follow-up data from the Manitoba Cancer Registry, cost data from Manitoba Health administrative databases and secondary sources. The 2000-GEP-based strategy compared to current clinical practice resulted in an incremental cost-effectiveness ratio (ICER) of $44,151 per quality-adjusted life years (QALY) gained. The total annual-budget impact was $36.2 million per year. A value-of-information analysis revealed that the expected value of perfect information about the test's clinical impact was $4.2 million per year. The 2000-GEP test should be considered for adoption in CUP. Field evaluations of the test are associated with a large societal benefit.

A numerical method for measuring capacitive soft sensors through one channel

NASA Astrophysics Data System (ADS)

Tairych, Andreas; Anderson, Iain A.

2018-03-01

Soft capacitive stretch sensors are well suited for unobtrusive wearable body motion capture. Conventional sensing methods measure sensor capacitances through separate channels. In sensing garments with many sensors, this results in high wiring complexity, and a large footprint of rigid sensing circuit boards. We have developed a more efficient sensing method that detects multiple sensors through only one channel, and one set of wires. It is based on a R-C transmission line assembled from capacitive conductive fabric stretch sensors, and external resistors. The unknown capacitances are identified by solving a system of nonlinear equations. These equations are established by modelling and continuously measuring transmission line reactances at different frequencies. Solving these equations numerically with a Newton-Raphson solver for the unknown capacitances enables real time reading of all sensors. The method was verified with a prototype comprising three sensors that is capable of detecting both individually and simultaneously stretched sensors. Instead of using three channels and six wires to detect the sensors, the task was achieved with only one channel and two wires.

Underworld results as a triple (shopping list, posterior, priors)

NASA Astrophysics Data System (ADS)

Quenette, S. M.; Moresi, L. N.; Abramson, D.

2013-12-01

When studying long-term lithosphere deformation and other such large-scale, spatially distinct and behaviour rich problems, there is a natural trade-off between the meaning of a model, the observations used to validate the model and the ability to compute over this space. For example, many models of varying lithologies, rheological properties and underlying physics may reasonably match (or not match) observables. To compound this problem, each realisation is computationally intensive, requiring high resolution, algorithm tuning and code tuning to contemporary computer hardware. It is often intractable to use sampling based assimilation methods, but with better optimisation, the window of tractability becomes wider. The ultimate goal is to find a sweet-spot where a formal assimilation method is used, and where a model affines to observations. Its natural to think of this as an inverse problem, in which the underlying physics may be fixed and the rheological properties and possibly the lithologies themselves are unknown. What happens when we push this approach and treat some portion of the underlying physics as an unknown? At its extreme this is an intractable problem. However, there is an analogy here with how we develop software for these scientific problems. What happens when we treat the changing part of a largely complete code as an unknown, where the changes are working towards this sweet-spot? When posed as a Bayesian inverse problem the result is a triple - the model changes, the real priors and the real posterior. Not only does this give meaning to the process by which a code changes, it forms a mathematical bridge from an inverse problem to compiler optimisations given such changes. As a stepping stone example we show a regional scale heat flow model with constraining observations, and the inverse process including increasingly complexity in the software. The implementation uses Underworld-GT (Underworld plus research extras to import geology and export geothermic measures, etc). Underworld uses StGermain an early (partial) implementation of the theories described here.

Information loss method to measure node similarity in networks

NASA Astrophysics Data System (ADS)

Li, Yongli; Luo, Peng; Wu, Chong

2014-09-01

Similarity measurement for the network node has been paid increasing attention in the field of statistical physics. In this paper, we propose an entropy-based information loss method to measure the node similarity. The whole model is established based on this idea that less information loss is caused by seeing two more similar nodes as the same. The proposed new method has relatively low algorithm complexity, making it less time-consuming and more efficient to deal with the large scale real-world network. In order to clarify its availability and accuracy, this new approach was compared with some other selected approaches on two artificial examples and synthetic networks. Furthermore, the proposed method is also successfully applied to predict the network evolution and predict the unknown nodes' attributions in the two application examples.

Linear reduction method for predictive and informative tag SNP selection.

PubMed

He, Jingwu; Westbrooks, Kelly; Zelikovsky, Alexander

2005-01-01

Constructing a complete human haplotype map is helpful when associating complex diseases with their related SNPs. Unfortunately, the number of SNPs is very large and it is costly to sequence many individuals. Therefore, it is desirable to reduce the number of SNPs that should be sequenced to a small number of informative representatives called tag SNPs. In this paper, we propose a new linear algebra-based method for selecting and using tag SNPs. We measure the quality of our tag SNP selection algorithm by comparing actual SNPs with SNPs predicted from selected linearly independent tag SNPs. Our experiments show that for sufficiently long haplotypes, knowing only 0.4% of all SNPs the proposed linear reduction method predicts an unknown haplotype with the error rate below 2% based on 10% of the population.

Adaptive Control of a Transport Aircraft Using Differential Thrust

NASA Technical Reports Server (NTRS)

Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan

2009-01-01

The paper presents an adaptive control technique for a damaged large transport aircraft subject to unknown atmospheric disturbances such as wind gust or turbulence. It is assumed that the damage results in vertical tail loss with no rudder authority, which is replaced with a differential thrust input. The proposed technique uses the adaptive prediction based control design in conjunction with the time scale separation principle, based on the singular perturbation theory. The application of later is necessitated by the fact that the engine response to a throttle command is substantially slow that the angular rate dynamics of the aircraft. It is shown that this control technique guarantees the stability of the closed-loop system and the tracking of a given reference model. The simulation example shows the benefits of the approach.

Learning Rates and Known-to-Unknown Flash-Card Ratios: Comparing Effectiveness While Holding Instructional Time Constant

ERIC Educational Resources Information Center

Forbes, Bethany E.; Skinner, Christopher H.; Black, Michelle P.; Yaw, Jared; Booher, Joshua; Delisle, Jean

2013-01-01

Using alternating treatments designs, we compared learning rates across 2 computer-based flash-card interventions (3?min each): a traditional drill intervention with 15 unknown words and an interspersal intervention with 12 known words and 3 unknown words. Each student acquired more words under the traditional drill intervention. Discussion…

Online cross-validation-based ensemble learning.

PubMed

Benkeser, David; Ju, Cheng; Lendle, Sam; van der Laan, Mark

2018-01-30

Online estimators update a current estimate with a new incoming batch of data without having to revisit past data thereby providing streaming estimates that are scalable to big data. We develop flexible, ensemble-based online estimators of an infinite-dimensional target parameter, such as a regression function, in the setting where data are generated sequentially by a common conditional data distribution given summary measures of the past. This setting encompasses a wide range of time-series models and, as special case, models for independent and identically distributed data. Our estimator considers a large library of candidate online estimators and uses online cross-validation to identify the algorithm with the best performance. We show that by basing estimates on the cross-validation-selected algorithm, we are asymptotically guaranteed to perform as well as the true, unknown best-performing algorithm. We provide extensions of this approach including online estimation of the optimal ensemble of candidate online estimators. We illustrate excellent performance of our methods using simulations and a real data example where we make streaming predictions of infectious disease incidence using data from a large database. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

GIS modeling of archaeological site locations: A low-tech approach

NASA Technical Reports Server (NTRS)

Futato, Eugene M.

1991-01-01

A Geographic Information System (GIS)-type analysis of archaeological site locations using a dBase III plus program and a desk top computer is presented. A previously developed model of site locations in the Sequatchie Valley of northeastern Alabama is tested against known site locations in another large survey area there. The model fails to account for site locations in the test area. A model is developed for the test area and indicates the site locations are indeed different. Whether this is due to differences in site locations on a sub-regional level, or to sample error in the original model is unknown.

Why Atens Enjoy Enhanced Accessibility for Human Space Flight

NASA Technical Reports Server (NTRS)

Barbee, Brent W.; Adamo, Daniel R.

2011-01-01

Near-Earth objects can be grouped into multiple orbit classifications, among them being the Aten group, whose members have orbits crossing Earth's with semi-major axes less than 1 astronomical unit. Atens comprise well under 10% of known near-Earth objects. This is in dramatic contrast to results from recent human space flight near-Earth object accessibility studies, where the most favorable known destinations are typically almost 50% Atens. Geocentric dynamics explain this enhanced Aten accessibility and lead to an understanding of where the most accessible near-Earth objects reside. Without a comprehensive space-based survey, however, highly accessible Atens will remain largely unknown.

Environmental epigenetics in metal exposure

PubMed Central

Martinez-Zamudio, Ricardo

2011-01-01

Although it is widely accepted that chronic exposure to arsenite, nickel, chromium and cadmium increases cancer incidence in individuals, the molecular mechanisms underlying their ability to transform cells remain largely unknown. Carcinogenic metals are typically weak mutagens, suggesting that genetic-based mechanisms may not be primarily responsible for metal-induced carcinogenesis. Growing evidence shows that environmental metal exposure involves changes in epigenetic marks, which may lead to a possible link between heritable changes in gene expression and disease susceptibility and development. Here, we review recent advances in the understanding of metal exposure affecting epigenetic marks and discuss establishment of heritable gene expression in metal-induced carcinogenesis. PMID:21610324

Prevalent and persistent viral infection in cultures of the coral algal endosymbiont Symbiodinium

NASA Astrophysics Data System (ADS)

Weynberg, Karen D.; Neave, Matthew; Clode, Peta L.; Voolstra, Christian R.; Brownlee, Christopher; Laffy, Patrick; Webster, Nicole S.; Levin, Rachel A.; Wood-Charlson, Elisha M.; van Oppen, Madeleine J. H.

2017-09-01

Reef corals are under threat from bleaching and disease outbreaks that target both the host animal and the algal symbionts within the coral holobiont. A viral origin for coral bleaching has been hypothesized, but direct evidence has remained elusive. Using a multifaceted approach incorporating flow cytometry, transmission electron microscopy, DNA and RNA virome sequencing, we show that type C1 Symbiodinium cultures host a nucleocytoplasmic large double-stranded DNA virus (NCLDV) related to Phycodnaviridae and Mimiviridae, a novel filamentous virus of unknown phylogenetic affiliation, and a single-stranded RNA virus related to retroviruses. We discuss implications of these findings for laboratory-based experiments using Symbiodinium cultures.

Adding control to arbitrary unknown quantum operations

PubMed Central

Zhou, Xiao-Qi; Ralph, Timothy C.; Kalasuwan, Pruet; Zhang, Mian; Peruzzo, Alberto; Lanyon, Benjamin P.; O'Brien, Jeremy L.

2011-01-01

Although quantum computers promise significant advantages, the complexity of quantum algorithms remains a major technological obstacle. We have developed and demonstrated an architecture-independent technique that simplifies adding control qubits to arbitrary quantum operations—a requirement in many quantum algorithms, simulations and metrology. The technique, which is independent of how the operation is done, does not require knowledge of what the operation is, and largely separates the problems of how to implement a quantum operation in the laboratory and how to add a control. Here, we demonstrate an entanglement-based version in a photonic system, realizing a range of different two-qubit gates with high fidelity. PMID:21811242

Polymer separations by liquid interaction chromatography: principles - prospects - limitations.

PubMed

Radke, Wolfgang

2014-03-28

Most heterogeneities of polymers with respect to different structural features cannot be resolved by only size exclusion chromatography (SEC), the most frequently applied mode of polymer chromatography. Instead, methods of interaction chromatography became increasingly important. However, despite the increasing applications the principles and potential of polymer interaction chromatography are still often unknown to a large number of polymer scientists. The present review will explain the principles of the different modes of polymer chromatography. Based on selected examples it will be shown which separation techniques can be successfully applied for separations with respect to the different structural features of polymers. Copyright © 2013 Elsevier B.V. All rights reserved.

Risks of Plastic Debris: Unravelling Fact, Opinion, Perception, and Belief

PubMed Central

2017-01-01

Researcher and media alarms have caused plastic debris to be perceived as a major threat to humans and animals. However, although the waste of plastic in the environment is clearly undesirable for aesthetic and economic reasons, the actual environmental risks of different plastics and their associated chemicals remain largely unknown. Here we show how a systematic assessment of adverse outcome pathways based on ecologically relevant metrics for exposure and effect can bring risk assessment within reach. Results of such an assessment will help to respond to the current public worry in a balanced way and allow policy makers to take measures for scientifically sound reasons. PMID:28971682

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

Good, but Not Perfect: Parental Knowledge About Risk Factors for Skin Cancer and the Necessity of Sun Protection in Southern Germany.

PubMed

Gefeller, Olaf; Uter, Wolfgang; Pfahlberg, Annette B

2015-01-01

The level of knowledge and awareness of skin cancer risks in parents of young children is largely unknown. The Erlangen Kindergarten study, which enrolled 3,129 parents of 3- to 6-year-old children in southern Germany, addressed this. The population-based survey found an overall high level of knowledge about skin cancer risks and strong support for the necessity of sun protection but identified two areas (role of intermittent sun exposure, sun protection on cloudy summer days) offering a target for improvement in future public health campaigns. © 2015 Wiley Periodicals, Inc.

Evidence-Based Reptile Housing and Nutrition.

PubMed

Oonincx, Dennis; van Leeuwen, Jeroen

2017-09-01

The provision of a good light source is important for reptiles. For instance, ultraviolet light is used in social interactions and used for vitamin D synthesis. With respect to housing, most reptilians are best kept pairwise or individually. Environmental enrichment can be effective but depends on the form and the species to which it is applied. Temperature gradients around preferred body temperatures allow accurate thermoregulation, which is essential for reptiles. Natural distributions indicate suitable ambient temperatures, but microclimatic conditions are at least as important. Because the nutrient requirements of reptiles are largely unknown, facilitating self-selection from various dietary items is preferable. Copyright © 2017 Elsevier Inc. All rights reserved.

Global 3ν oscillation analysis: Status of unknown parameters and future systematic challenges for ORCA and PINGU

NASA Astrophysics Data System (ADS)

Capozzi, Francesco; Lisi, Eligio; Marrone, Antonio

2016-04-01

Within the standard 3ν oscillation framework, we illustrate the status of currently unknown oscillation parameters: the θ23 octant, the mass hierarchy (normal or inverted), and the possible CP-violating phase δ, as derived by a (preliminary) global analysis of oscillation data available in 2015. We then discuss some challenges that will be faced by future, high-statistics analyses of spectral data, starting with one-dimensional energy spectra in reactor experiments, and concluding with two-dimensional energy-angle spectra in large-volume atmospheric experiments. It is shown that systematic uncertainties in the spectral shapes can noticeably affect the prospective sensitivities to unknown oscillation parameters, in particular to the mass hierarchy.

A learning-based semi-autonomous controller for robotic exploration of unknown disaster scenes while searching for victims.

PubMed

Doroodgar, Barzin; Liu, Yugang; Nejat, Goldie

2014-12-01

Semi-autonomous control schemes can address the limitations of both teleoperation and fully autonomous robotic control of rescue robots in disaster environments by allowing a human operator to cooperate and share such tasks with a rescue robot as navigation, exploration, and victim identification. In this paper, we present a unique hierarchical reinforcement learning-based semi-autonomous control architecture for rescue robots operating in cluttered and unknown urban search and rescue (USAR) environments. The aim of the controller is to enable a rescue robot to continuously learn from its own experiences in an environment in order to improve its overall performance in exploration of unknown disaster scenes. A direction-based exploration technique is integrated in the controller to expand the search area of the robot via the classification of regions and the rubble piles within these regions. Both simulations and physical experiments in USAR-like environments verify the robustness of the proposed HRL-based semi-autonomous controller to unknown cluttered scenes with different sizes and varying types of configurations.

SVM and SVM Ensembles in Breast Cancer Prediction.

PubMed

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers.

SVM and SVM Ensembles in Breast Cancer Prediction

PubMed Central

Huang, Min-Wei; Chen, Chih-Wen; Lin, Wei-Chao; Ke, Shih-Wen; Tsai, Chih-Fong

2017-01-01

Breast cancer is an all too common disease in women, making how to effectively predict it an active research problem. A number of statistical and machine learning techniques have been employed to develop various breast cancer prediction models. Among them, support vector machines (SVM) have been shown to outperform many related techniques. To construct the SVM classifier, it is first necessary to decide the kernel function, and different kernel functions can result in different prediction performance. However, there have been very few studies focused on examining the prediction performances of SVM based on different kernel functions. Moreover, it is unknown whether SVM classifier ensembles which have been proposed to improve the performance of single classifiers can outperform single SVM classifiers in terms of breast cancer prediction. Therefore, the aim of this paper is to fully assess the prediction performance of SVM and SVM ensembles over small and large scale breast cancer datasets. The classification accuracy, ROC, F-measure, and computational times of training SVM and SVM ensembles are compared. The experimental results show that linear kernel based SVM ensembles based on the bagging method and RBF kernel based SVM ensembles with the boosting method can be the better choices for a small scale dataset, where feature selection should be performed in the data pre-processing stage. For a large scale dataset, RBF kernel based SVM ensembles based on boosting perform better than the other classifiers. PMID:28060807

A network property necessary for concentration robustness

NASA Astrophysics Data System (ADS)

Eloundou-Mbebi, Jeanne M. O.; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran

2016-10-01

Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications.

Performance testing of 3D point cloud software

NASA Astrophysics Data System (ADS)

Varela-González, M.; González-Jorge, H.; Riveiro, B.; Arias, P.

2013-10-01

LiDAR systems are being used widely in recent years for many applications in the engineering field: civil engineering, cultural heritage, mining, industry and environmental engineering. One of the most important limitations of this technology is the large computational requirements involved in data processing, especially for large mobile LiDAR datasets. Several software solutions for data managing are available in the market, including open source suites, however, users often unknown methodologies to verify their performance properly. In this work a methodology for LiDAR software performance testing is presented and four different suites are studied: QT Modeler, VR Mesh, AutoCAD 3D Civil and the Point Cloud Library running in software developed at the University of Vigo (SITEGI). The software based on the Point Cloud Library shows better results in the loading time of the point clouds and CPU usage. However, it is not as strong as commercial suites in working set and commit size tests.

Potential toxicity of graphene to cell functions via disrupting protein-protein interactions.

PubMed

Luan, Binquan; Huynh, Tien; Zhao, Lin; Zhou, Ruhong

2015-01-27

While carbon-based nanomaterials such as graphene and carbon nanotubes (CNTs) have become popular in state-of-the-art nanotechnology, their biological safety and underlying molecular mechanism is still largely unknown. Experimental studies have been focused at the cellular level and revealed good correlations between cell's death and the application of CNTs or graphene. Using large-scale all-atom molecular dynamics simulations, we theoretically investigate the potential toxicity of graphene to a biological cell at molecular level. Simulation results show that the hydrophobic protein-protein interaction (or recognition) that is essential to biological functions can be interrupted by a graphene nanosheet. Due to the hydrophobic nature of graphene, it is energetically favorable for a graphene nanosheet to enter the hydrophobic interface of two contacting proteins, such as a dimer. The forced separation of two functional proteins can disrupt the cell's metabolism and even lead to the cell's mortality.

Testing for the 'predictability' of dynamically triggered earthquakes in The Geysers geothermal field

NASA Astrophysics Data System (ADS)

Aiken, Chastity; Meng, Xiaofeng; Hardebeck, Jeanne

2018-03-01

The Geysers geothermal field is well known for being susceptible to dynamic triggering of earthquakes by large distant earthquakes, owing to the introduction of fluids for energy production. Yet, it is unknown if dynamic triggering of earthquakes is 'predictable' or whether dynamic triggering could lead to a potential hazard for energy production. In this paper, our goal is to investigate the characteristics of triggering and the physical conditions that promote triggering to determine whether or not triggering is in anyway foreseeable. We find that, at present, triggering in The Geysers is not easily 'predictable' in terms of when and where based on observable physical conditions. However, triggered earthquake magnitude positively correlates with peak imparted dynamic stress, and larger dynamic stresses tend to trigger sequences similar to mainshock-aftershock sequences. Thus, we may be able to 'predict' what size earthquakes to expect at The Geysers following a large distant earthquake.

Loss of Brain Aerobic Glycolysis in Normal Human Aging.

PubMed

Goyal, Manu S; Vlassenko, Andrei G; Blazey, Tyler M; Su, Yi; Couture, Lars E; Durbin, Tony J; Bateman, Randall J; Benzinger, Tammie L-S; Morris, John C; Raichle, Marcus E

2017-08-01

The normal aging human brain experiences global decreases in metabolism, but whether this affects the topography of brain metabolism is unknown. Here we describe PET-based measurements of brain glucose uptake, oxygen utilization, and blood flow in cognitively normal adults from 20 to 82 years of age. Age-related decreases in brain glucose uptake exceed that of oxygen use, resulting in loss of brain aerobic glycolysis (AG). Whereas the topographies of total brain glucose uptake, oxygen utilization, and blood flow remain largely stable with age, brain AG topography changes significantly. Brain regions with high AG in young adults show the greatest change, as do regions with prolonged developmental transcriptional features (i.e., neoteny). The normal aging human brain thus undergoes characteristic metabolic changes, largely driven by global loss and topographic changes in brain AG. Copyright © 2017 Elsevier Inc. All rights reserved.

Rainforest metropolis casts 1,000-km defaunation shadow.

PubMed

Tregidgo, Daniel J; Barlow, Jos; Pompeu, Paulo S; de Almeida Rocha, Mayana; Parry, Luke

2017-08-08

Tropical rainforest regions are urbanizing rapidly, yet the role of emerging metropolises in driving wildlife overharvesting in forests and inland waters is unknown. We present evidence of a large defaunation shadow around a rainforest metropolis. Using interviews with 392 rural fishers, we show that fishing has severely depleted a large-bodied keystone fish species, tambaqui ( Colossoma macropomum ), with an impact extending over 1,000 km from the rainforest city of Manaus (population 2.1 million). There was strong evidence of defaunation within this area, including a 50% reduction in body size and catch rate (catch per unit effort). Our findings link these declines to city-based boats that provide rural fishers with reliable access to fish buyers and ice and likely impact rural fisher livelihoods and flooded forest biodiversity. This empirical evidence that urban markets can defaunate deep into rainforest wilderness has implications for other urbanizing socioecological systems.

Endocytic reawakening of motility in jammed epithelia

NASA Astrophysics Data System (ADS)

Malinverno, Chiara; Corallino, Salvatore; Giavazzi, Fabio; Bergert, Martin; Li, Qingsen; Leoni, Marco; Disanza, Andrea; Frittoli, Emanuela; Oldani, Amanda; Martini, Emanuele; Lendenmann, Tobias; Deflorian, Gianluca; Beznoussenko, Galina V.; Poulikakos, Dimos; Ong, Kok Haur; Uroz, Marina; Trepat, Xavier; Parazzoli, Dario; Maiuri, Paolo; Yu, Weimiao; Ferrari, Aldo; Cerbino, Roberto; Scita, Giorgio

2017-05-01

Dynamics of epithelial monolayers has recently been interpreted in terms of a jamming or rigidity transition. How cells control such phase transitions is, however, unknown. Here we show that RAB5A, a key endocytic protein, is sufficient to induce large-scale, coordinated motility over tens of cells, and ballistic motion in otherwise kinetically arrested monolayers. This is linked to increased traction forces and to the extension of cell protrusions, which align with local velocity. Molecularly, impairing endocytosis, macropinocytosis or increasing fluid efflux abrogates RAB5A-induced collective motility. A simple model based on mechanical junctional tension and an active cell reorientation mechanism for the velocity of self-propelled cells identifies regimes of monolayer dynamics that explain endocytic reawakening of locomotion in terms of a combination of large-scale directed migration and local unjamming. These changes in multicellular dynamics enable collectives to migrate under physical constraints and may be exploited by tumours for interstitial dissemination.

A network property necessary for concentration robustness.

PubMed

Eloundou-Mbebi, Jeanne M O; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran

2016-10-19

Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications.

A network property necessary for concentration robustness

PubMed Central

Eloundou-Mbebi, Jeanne M. O.; Küken, Anika; Omranian, Nooshin; Kleessen, Sabrina; Neigenfind, Jost; Basler, Georg; Nikoloski, Zoran

2016-01-01

Maintenance of functionality of complex cellular networks and entire organisms exposed to environmental perturbations often depends on concentration robustness of the underlying components. Yet, the reasons and consequences of concentration robustness in large-scale cellular networks remain largely unknown. Here, we derive a necessary condition for concentration robustness based only on the structure of networks endowed with mass action kinetics. The structural condition can be used to design targeted experiments to study concentration robustness. We show that metabolites satisfying the necessary condition are present in metabolic networks from diverse species, suggesting prevalence of this property across kingdoms of life. We also demonstrate that our predictions about concentration robustness of energy-related metabolites are in line with experimental evidence from Escherichia coli. The necessary condition is applicable to mass action biological systems of arbitrary size, and will enable understanding the implications of concentration robustness in genetic engineering strategies and medical applications. PMID:27759015

Observational evidence for cloud cover enhancement over western European forests.

PubMed

Teuling, Adriaan J; Taylor, Christopher M; Meirink, Jan Fokke; Melsen, Lieke A; Miralles, Diego G; van Heerwaarden, Chiel C; Vautard, Robert; Stegehuis, Annemiek I; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-11

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas.

Observational evidence for cloud cover enhancement over western European forests

PubMed Central

Teuling, Adriaan J.; Taylor, Christopher M.; Meirink, Jan Fokke; Melsen, Lieke A.; Miralles, Diego G.; van Heerwaarden, Chiel C.; Vautard, Robert; Stegehuis, Annemiek I.; Nabuurs, Gert-Jan; de Arellano, Jordi Vilà-Guerau

2017-01-01

Forests impact regional hydrology and climate directly by regulating water and heat fluxes. Indirect effects through cloud formation and precipitation can be important in facilitating continental-scale moisture recycling but are poorly understood at regional scales. In particular, the impact of temperate forest on clouds is largely unknown. Here we provide observational evidence for a strong increase in cloud cover over large forest regions in western Europe based on analysis of 10 years of 15 min resolution data from geostationary satellites. In addition, we show that widespread windthrow by cyclone Klaus in the Landes forest led to a significant decrease in local cloud cover in subsequent years. Strong cloud development along the downwind edges of larger forest areas are consistent with a forest-breeze mesoscale circulation. Our results highlight the need to include impacts on cloud formation when evaluating the water and climate services of temperate forests, in particular around densely populated areas. PMID:28074840

Testing for the ‘predictability’ of dynamically triggered earthquakes in Geysers Geothermal Field

USGS Publications Warehouse

Aiken, Chastity; Meng, Xiaofeng; Hardebeck, Jeanne L.

2018-01-01

The Geysers geothermal field is well known for being susceptible to dynamic triggering of earthquakes by large distant earthquakes, owing to the introduction of fluids for energy production. Yet, it is unknown if dynamic triggering of earthquakes is ‘predictable’ or whether dynamic triggering could lead to a potential hazard for energy production. In this paper, our goal is to investigate the characteristics of triggering and the physical conditions that promote triggering to determine whether or not triggering is in anyway foreseeable. We find that, at present, triggering in The Geysers is not easily ‘predictable’ in terms of when and where based on observable physical conditions. However, triggered earthquake magnitude positively correlates with peak imparted dynamic stress, and larger dynamic stresses tend to trigger sequences similar to mainshock–aftershock sequences. Thus, we may be able to ‘predict’ what size earthquakes to expect at The Geysers following a large distant earthquake.

Construction and Screening of Marine Metagenomic Large Insert Libraries.

PubMed

Weiland-Bräuer, Nancy; Langfeldt, Daniela; Schmitz, Ruth A

2017-01-01

The marine environment covers more than 70 % of the world's surface. Marine microbial communities are highly diverse and have evolved during extended evolutionary processes of physiological adaptations under the influence of a variety of ecological conditions and selection pressures. They harbor an enormous diversity of microbes with still unknown and probably new physiological characteristics. In the past, marine microbes, mostly bacteria of microbial consortia attached to marine tissues of multicellular organisms, have proven to be a rich source of highly potent bioactive compounds, which represent a considerable number of drug candidates. However, to date, the biodiversity of marine microbes and the versatility of their bioactive compounds and metabolites have not been fully explored. This chapter describes sampling in the marine environment, construction of metagenomic large insert libraries from marine habitats, and exemplarily one function based screen of metagenomic clones for identification of quorum quenching activities.

Bending and buckling formulation of graphene sheets based on nonlocal simple first-order shear deformation theory

NASA Astrophysics Data System (ADS)

Golmakani, M. E.; Malikan, M.; Sadraee Far, M. N.; Majidi, H. R.

2018-06-01

This paper presents a formulation based on simple first-order shear deformation theory (S-FSDT) for large deflection and buckling of orthotropic single-layered graphene sheets (SLGSs). The S-FSDT has many advantages compared to the classical plate theory (CPT) and conventional FSDT such as needless of shear correction factor, containing less number of unknowns than the existing FSDT and strong similarities with the CPT. Governing equations and boundary conditions are derived based on Hamilton’s principle using the nonlocal differential constitutive relations of Eringen and von Kármán geometrical model. Numerical results are obtained using differential quadrature (DQ) method and the Newton–Raphson iterative scheme. Finally, some comparison studies are carried out to show the high accuracy and reliability of the present formulations compared to the nonlocal CPT and FSDT for different thicknesses, elastic foundations and nonlocal parameters.

Place recognition using batlike sonar

PubMed Central

Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

2016-01-01

Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map. DOI: http://dx.doi.org/10.7554/eLife.14188.001 PMID:27481189

Physician need. An alternative projection from a study of large, prepaid group practices.

PubMed

Mulhausen, R; McGee, J

1989-04-07

To model a base level of physician demand in a managed health care system, we examined in 1983 the ratios by specialty of full-time equivalent physicians to health maintenance organization members in seven large, closed-panel health maintenance organizations, each with more than 100,000 members. The medical director of each plan was surveyed by mailed questionnaire and telephone interview to determine the plan's number of full-time equivalent physicians by specialty and members served. Out-of-plan physicians contracted by the group were included within the specialty distribution wherever possible. We compared our findings (4779.4 full-time equivalent physicians serving 4,297,790 members) with Graduate Medical Education National Advisory Committee and others' projections of physician need and supply. Based on this model and unknowns that might affect utilization, our study suggests that at least 111 physicians per 100,000 population would be necessary in a system that emphasized reduced utilization of services and that more primary care physicians would be needed than the Graduate Medical Education National Advisory Committee predicted would be available.

Measuring Student Interactions Using Networks: Insights into the Learning Community of a Large Active Learning Course

ERIC Educational Resources Information Center

Buchenroth-Martin, Cynthia; DiMartino, Trevor; Martin, Andrew P.

2017-01-01

Collaborative learning in small groups is commonly implemented as a part of student-centered curricula. In large-enrollment courses, details of the interactions among students as a consequence of working in collaborative groups are often unknown but are important because how students interact influences the effectiveness of peer learning. We…

Dermacentor andersoni transmission of Francisella tularensis subsp. novicida reflects bacterial colonization, dissemination and replication coordinated with tick feeding.

USDA-ARS?s Scientific Manuscript database

Ticks serve as biological vectors for a wide variety of bacterial pathogens which must be able to efficiently colonize specific tick tissues prior to transmission. The bacterial determinants of tick colonization are largely unknown, a knowledge gap attributed in large part to the paucity of tools t...

Understanding Participation in E-Learning in Organizations: A Large-Scale Empirical Study of Employees

ERIC Educational Resources Information Center

Garavan, Thomas N.; Carbery, Ronan; O'Malley, Grace; O'Donnell, David

2010-01-01

Much remains unknown in the increasingly important field of e-learning in organizations. Drawing on a large-scale survey of employees (N = 557) who had opportunities to participate in voluntary e-learning activities, the factors influencing participation in e-learning are explored in this empirical paper. It is hypothesized that key variables…

A dynamic regularized gradient model of the subgrid-scale stress tensor for large-eddy simulation

NASA Astrophysics Data System (ADS)

Vollant, A.; Balarac, G.; Corre, C.

2016-02-01

Large-eddy simulation (LES) solves only the large scales part of turbulent flows by using a scales separation based on a filtering operation. The solution of the filtered Navier-Stokes equations requires then to model the subgrid-scale (SGS) stress tensor to take into account the effect of scales smaller than the filter size. In this work, a new model is proposed for the SGS stress model. The model formulation is based on a regularization procedure of the gradient model to correct its unstable behavior. The model is developed based on a priori tests to improve the accuracy of the modeling for both structural and functional performances, i.e., the model ability to locally approximate the SGS unknown term and to reproduce enough global SGS dissipation, respectively. LES is then performed for a posteriori validation. This work is an extension to the SGS stress tensor of the regularization procedure proposed by Balarac et al. ["A dynamic regularized gradient model of the subgrid-scale scalar flux for large eddy simulations," Phys. Fluids 25(7), 075107 (2013)] to model the SGS scalar flux. A set of dynamic regularized gradient (DRG) models is thus made available for both the momentum and the scalar equations. The second objective of this work is to compare this new set of DRG models with direct numerical simulations (DNS), filtered DNS in the case of classic flows simulated with a pseudo-spectral solver and with the standard set of models based on the dynamic Smagorinsky model. Various flow configurations are considered: decaying homogeneous isotropic turbulence, turbulent plane jet, and turbulent channel flows. These tests demonstrate the stable behavior provided by the regularization procedure, along with substantial improvement for velocity and scalar statistics predictions.

An Approach to Function Annotation for Proteins of Unknown Function (PUFs) in the Transcriptome of Indian Mulberry.

PubMed

Dhanyalakshmi, K H; Naika, Mahantesha B N; Sajeevan, R S; Mathew, Oommen K; Shafi, K Mohamed; Sowdhamini, Ramanathan; N Nataraja, Karaba

2016-01-01

The modern sequencing technologies are generating large volumes of information at the transcriptome and genome level. Translation of this information into a biological meaning is far behind the race due to which a significant portion of proteins discovered remain as proteins of unknown function (PUFs). Attempts to uncover the functional significance of PUFs are limited due to lack of easy and high throughput functional annotation tools. Here, we report an approach to assign putative functions to PUFs, identified in the transcriptome of mulberry, a perennial tree commonly cultivated as host of silkworm. We utilized the mulberry PUFs generated from leaf tissues exposed to drought stress at whole plant level. A sequence and structure based computational analysis predicted the probable function of the PUFs. For rapid and easy annotation of PUFs, we developed an automated pipeline by integrating diverse bioinformatics tools, designated as PUFs Annotation Server (PUFAS), which also provides a web service API (Application Programming Interface) for a large-scale analysis up to a genome. The expression analysis of three selected PUFs annotated by the pipeline revealed abiotic stress responsiveness of the genes, and hence their potential role in stress acclimation pathways. The automated pipeline developed here could be extended to assign functions to PUFs from any organism in general. PUFAS web server is available at http://caps.ncbs.res.in/pufas/ and the web service is accessible at http://capservices.ncbs.res.in/help/pufas.

Extended behavioural modelling of FET and lattice-mismatched HEMT devices

NASA Astrophysics Data System (ADS)

Khawam, Yahya; Albasha, Lutfi

2017-07-01

This study presents an improved large signal model that can be used for high electron mobility transistors (HEMTs) and field effect transistors using measurement-based behavioural modelling techniques. The steps for accurate large and small signal modelling for transistor are also discussed. The proposed DC model is based on the Fager model since it compensates between the number of model's parameters and accuracy. The objective is to increase the accuracy of the drain-source current model with respect to any change in gate or drain voltages. Also, the objective is to extend the improved DC model to account for soft breakdown and kink effect found in some variants of HEMT devices. A hybrid Newton's-Genetic algorithm is used in order to determine the unknown parameters in the developed model. In addition to accurate modelling of a transistor's DC characteristics, the complete large signal model is modelled using multi-bias s-parameter measurements. The way that the complete model is performed is by using a hybrid multi-objective optimisation technique (Non-dominated Sorting Genetic Algorithm II) and local minimum search (multivariable Newton's method) for parasitic elements extraction. Finally, the results of DC modelling and multi-bias s-parameters modelling are presented, and three-device modelling recommendations are discussed.

Marbles for the Imagination

NASA Technical Reports Server (NTRS)

Shue, Jack

2004-01-01

The end-to-end test would verify the complex sequence of events from lander separation to landing. Due to the large distances involved and the significant delay time in sending a command and receiving verification, the lander needed to operate autonomously after it separated from the orbiter. It had to sense conditions, make decisions, and act accordingly. We were flying into a relatively unknown set of conditions-a Martian atmosphere of unknown pressure, density, and consistency to land on a surface of unknown altitude, and one which had an unknown bearing strength. In order to touch down safely on Mars the lander had to orient itself for descent and entry, modulate itself to maintain proper lift, pop a parachute, jettison its aeroshell, deploy landing legs and radar, ignite a terminal descent engine, and fly a given trajectory to the surface. Once on the surface, it would determine its orientation, raise the high-gain antenna, perform a sweep to locate Earth, and begin transmitting information. It was this complicated, autonomous sequence that the end-to-end test was to simulate.

An iterative method for the localization of a neutron source in a large box (container)

NASA Astrophysics Data System (ADS)

Dubinski, S.; Presler, O.; Alfassi, Z. B.

2007-12-01

The localization of an unknown neutron source in a bulky box was studied. This can be used for the inspection of cargo, to prevent the smuggling of neutron and α emitters. It is important to localize the source from the outside for safety reasons. Source localization is necessary in order to determine its activity. A previous study showed that, by using six detectors, three on each parallel face of the box (460×420×200 mm 3), the location of the source can be found with an average distance of 4.73 cm between the real source position and the calculated one and a maximal distance of about 9 cm. Accuracy was improved in this work by applying an iteration method based on four fixed detectors and the successive iteration of positioning of an external calibrating source. The initial positioning of the calibrating source is the plane of detectors 1 and 2. This method finds the unknown source location with an average distance of 0.78 cm between the real source position and the calculated one and a maximum distance of 3.66 cm for the same box. For larger boxes, localization without iterations requires an increase in the number of detectors, while localization with iterations requires only an increase in the number of iteration steps. In addition to source localization, two methods for determining the activity of the unknown source were also studied.

Synthesis and Characterization of Aldol Condensation Products from Unknown Aldehydes and Ketones: An Inquiry-Based Experiment in the Undergraduate Laboratory

ERIC Educational Resources Information Center

Angelo, Nicholas G.; Henchey, Laura K.; Waxman, Adam J.; Canary, James W.; Arora, Paramjit S.; Wink, Donald

2007-01-01

An experiment for the undergraduate chemistry laboratory in which students perform the aldol condensation on an unknown aldehyde and an unknown ketone is described. The experiment involves the use of techniques such as TLC, column chromatography, and recrystallization, and compounds are characterized by [to the first power]H NMR, GC-MS, and FTIR.…

Comparative study of methods for recognition of an unknown person's action from a video sequence

NASA Astrophysics Data System (ADS)

Hori, Takayuki; Ohya, Jun; Kurumisawa, Jun

2009-02-01

This paper proposes a Tensor Decomposition Based method that can recognize an unknown person's action from a video sequence, where the unknown person is not included in the database (tensor) used for the recognition. The tensor consists of persons, actions and time-series image features. For the observed unknown person's action, one of the actions stored in the tensor is assumed. Using the motion signature obtained from the assumption, the unknown person's actions are synthesized. The actions of one of the persons in the tensor are replaced by the synthesized actions. Then, the core tensor for the replaced tensor is computed. This process is repeated for the actions and persons. For each iteration, the difference between the replaced and original core tensors is computed. The assumption that gives the minimal difference is the action recognition result. For the time-series image features to be stored in the tensor and to be extracted from the observed video sequence, the human body silhouette's contour shape based feature is used. To show the validity of our proposed method, our proposed method is experimentally compared with Nearest Neighbor rule and Principal Component analysis based method. Experiments using 33 persons' seven kinds of action show that our proposed method achieves better recognition accuracies for the seven actions than the other methods.

Sizing and Discovery of Nanosized Polyoxometalate Clusters by Mass Spectrometry

PubMed Central

2016-01-01

Ion mobility-mass spectrometry (IM-MS) is a powerful technique for structural characterization, e.g., sizing and conformation, particularly when combined with quantitative modeling and comparison to theoretical values. Traveling wave IM-MS (TW-IM-MS) has recently become commercially available to nonspecialist groups and has been exploited in the structural study of large biomolecules, however reliable calibrants for large anions have not been available. Polyoxometalate (POM) species—nanoscale inorganic anions—share many of the facets of large biomolecules, however, the full potential of IM-MS in their study has yet to be realized due to a lack of suitable calibration data or validated theoretical models. Herein we address these limitations by reporting DT-IM (drift tube) data for a set of POM clusters {M12} Keggin 1, {M18} Dawson 2, and two {M7} Anderson derivatives 3 and 4 which demonstrate their use as a TW-IM-MS calibrant set to facilitate characterization of very large (ca. 1–4 nm) anionic species. The data was also used to assess the validity of standard techniques to model the collision cross sections of large inorganic anions using the nanoscale family of compounds based upon the {Se2W29} unit including the trimer, {Se8W86O299} A, tetramer, {Se8W116O408} B, and hexamer {Se12W174O612} C, including their relative sizing in solution. Furthermore, using this data set, we demonstrated how IM-MS can be used to conveniently characterize and identify the synthesis of two new, i.e., previously unreported POM species, {P8W116}, unknown D, and {Te8W116}, unknown E, which are not amenable to analysis by other means with the approximate formulation of [H34W118X8M2O416]44–, where X = P and M = Co for D and X = Te and M = Mn for E. This work establishes a new type of inorganic calibrant for IM-MS allowing sizing, structural analysis, and discovery of molecular nanostructures directly from solution. PMID:26906879

Chapter 11 - Post-hurricane fuel dynamics and implications for fire behavior (Project SO-EM-F-12-01)

Treesearch

Shanyue Guan; G. Geoff. Wang

2018-01-01

Hurricanes have long been a powerful and recurring disturbance in many coastal forest ecosystems. Intense hurricanes often produce a large amount of dead fuels in their affected forests. How the post-hurricane fuel complex changes with time, due todecomposition and management such as salvage, and its implications for fire behavior remain largely unknown....

Transition into and out of Special Education Services by Young Australian School Children between 2006 and 2010

ERIC Educational Resources Information Center

Dempsey, Ian

2014-01-01

The extent to which school students continue to receive special education services over time is largely unknown because longitudinal studies are rare in this area. The present study examined a large Australian longitudinal database to track the status of children who received special education support in 2006 and whether they continued to access…

A vehicle stability control strategy with adaptive neural network sliding mode theory based on system uncertainty approximation

NASA Astrophysics Data System (ADS)

Ji, Xuewu; He, Xiangkun; Lv, Chen; Liu, Yahui; Wu, Jian

2018-06-01

Modelling uncertainty, parameter variation and unknown external disturbance are the major concerns in the development of an advanced controller for vehicle stability at the limits of handling. Sliding mode control (SMC) method has proved to be robust against parameter variation and unknown external disturbance with satisfactory tracking performance. But modelling uncertainty, such as errors caused in model simplification, is inevitable in model-based controller design, resulting in lowered control quality. The adaptive radial basis function network (ARBFN) can effectively improve the control performance against large system uncertainty by learning to approximate arbitrary nonlinear functions and ensure the global asymptotic stability of the closed-loop system. In this paper, a novel vehicle dynamics stability control strategy is proposed using the adaptive radial basis function network sliding mode control (ARBFN-SMC) to learn system uncertainty and eliminate its adverse effects. This strategy adopts a hierarchical control structure which consists of reference model layer, yaw moment control layer, braking torque allocation layer and executive layer. Co-simulation using MATLAB/Simulink and AMESim is conducted on a verified 15-DOF nonlinear vehicle system model with the integrated-electro-hydraulic brake system (I-EHB) actuator in a Sine With Dwell manoeuvre. The simulation results show that ARBFN-SMC scheme exhibits superior stability and tracking performance in different running conditions compared with SMC scheme.

Fission meter and neutron detection using poisson distribution comparison

DOEpatents

Rowland, Mark S; Snyderman, Neal J

2014-11-18

A neutron detector system and method for discriminating fissile material from non-fissile material wherein a digital data acquisition unit collects data at high rate, and in real-time processes large volumes of data directly into information that a first responder can use to discriminate materials. The system comprises counting neutrons from the unknown source and detecting excess grouped neutrons to identify fission in the unknown source. Comparison of the observed neutron count distribution with a Poisson distribution is performed to distinguish fissile material from non-fissile material.

Meta-Storms: efficient search for similar microbial communities based on a novel indexing scheme and similarity score for metagenomic data.

PubMed

Su, Xiaoquan; Xu, Jian; Ning, Kang

2012-10-01

It has long been intriguing scientists to effectively compare different microbial communities (also referred as 'metagenomic samples' here) in a large scale: given a set of unknown samples, find similar metagenomic samples from a large repository and examine how similar these samples are. With the current metagenomic samples accumulated, it is possible to build a database of metagenomic samples of interests. Any metagenomic samples could then be searched against this database to find the most similar metagenomic sample(s). However, on one hand, current databases with a large number of metagenomic samples mostly serve as data repositories that offer few functionalities for analysis; and on the other hand, methods to measure the similarity of metagenomic data work well only for small set of samples by pairwise comparison. It is not yet clear, how to efficiently search for metagenomic samples against a large metagenomic database. In this study, we have proposed a novel method, Meta-Storms, that could systematically and efficiently organize and search metagenomic data. It includes the following components: (i) creating a database of metagenomic samples based on their taxonomical annotations, (ii) efficient indexing of samples in the database based on a hierarchical taxonomy indexing strategy, (iii) searching for a metagenomic sample against the database by a fast scoring function based on quantitative phylogeny and (iv) managing database by index export, index import, data insertion, data deletion and database merging. We have collected more than 1300 metagenomic data from the public domain and in-house facilities, and tested the Meta-Storms method on these datasets. Our experimental results show that Meta-Storms is capable of database creation and effective searching for a large number of metagenomic samples, and it could achieve similar accuracies compared with the current popular significance testing-based methods. Meta-Storms method would serve as a suitable database management and search system to quickly identify similar metagenomic samples from a large pool of samples. ningkang@qibebt.ac.cn Supplementary data are available at Bioinformatics online.

Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System.

PubMed

Xie, Ruihong; Zhang, Tao; Li, Jiaquan; Dai, Ming

2017-05-09

This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight) motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration) control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square) error is 1.253 mrad when tracking 10° 0.2 Hz signal.

A load-based mechanism for inter-leg coordination in insects

PubMed Central

2017-01-01

Animals rely on an adaptive coordination of legs during walking. However, which specific mechanisms underlie coordination during natural locomotion remains largely unknown. One hypothesis is that legs can be coordinated mechanically based on a transfer of body load from one leg to another. To test this hypothesis, we simultaneously recorded leg kinematics, ground reaction forces and muscle activity in freely walking stick insects (Carausius morosus). Based on torque calculations, we show that load sensors (campaniform sensilla) at the proximal leg joints are well suited to encode the unloading of the leg in individual steps. The unloading coincides with a switch from stance to swing muscle activity, consistent with a load reflex promoting the stance-to-swing transition. Moreover, a mechanical simulation reveals that the unloading can be ascribed to the loading of a specific neighbouring leg, making it exploitable for inter-leg coordination. We propose that mechanically mediated load-based coordination is used across insects analogously to mammals. PMID:29187626

Robust interval-based regulation for anaerobic digestion processes.

PubMed

Alcaraz-González, V; Harmand, J; Rapaport, A; Steyer, J P; González-Alvarez, V; Pelayo-Ortiz, C

2005-01-01

A robust regulation law is applied to the stabilization of a class of biochemical reactors exhibiting partially known highly nonlinear dynamic behavior. An uncertain environment with the presence of unknown inputs is considered. Based on some structural and operational conditions, this regulation law is shown to exponentially stabilize the aforementioned bioreactors around a desired set-point. This approach is experimentally applied and validated on a pilot-scale (1 m3) anaerobic digestion process for the treatment of raw industrial wine distillery wastewater where the objective is the regulation of the chemical oxygen demand (COD) by using the dilution rate as the manipulated variable. Despite large disturbances on the input COD and state and parametric uncertainties, this regulation law gave excellent performances leading the output COD towards its set-point and keeping it inside a pre-specified interval.

A cautionary note on Bayesian estimation of population size by removal sampling with diffuse priors.

PubMed

Bord, Séverine; Bioche, Christèle; Druilhet, Pierre

2018-05-01

We consider the problem of estimating a population size by removal sampling when the sampling rate is unknown. Bayesian methods are now widespread and allow to include prior knowledge in the analysis. However, we show that Bayes estimates based on default improper priors lead to improper posteriors or infinite estimates. Similarly, weakly informative priors give unstable estimators that are sensitive to the choice of hyperparameters. By examining the likelihood, we show that population size estimates can be stabilized by penalizing small values of the sampling rate or large value of the population size. Based on theoretical results and simulation studies, we propose some recommendations on the choice of the prior. Then, we applied our results to real datasets. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Origin-based polyphenolic fingerprinting of Theobroma cacao in unfermented and fermented beans.

PubMed

D'Souza, Roy N; Grimbs, Sergio; Behrends, Britta; Bernaert, Herwig; Ullrich, Matthias S; Kuhnert, Nikolai

2017-09-01

A comprehensive analysis of cocoa polyphenols from unfermented and fermented cocoa beans from a wide range of geographic origins was carried out to catalogue systematic differences based on their origin as well as fermentation status. This study identifies previously unknown compounds with the goal to ascertain, which of these are responsible for the largest differences between bean types. UHPLC coupled with ultra-high resolution time-of-flight mass spectrometry was employed to identify and relatively quantify various oligomeric proanthocyanidins and their glycosides amongst several other unreported compounds. A series of biomarkers allowing a clear distinction between unfermented and fermented cocoa beans and for beans of different origins were identified. The large sample set employed allowed comparison of statistically significant variations of key cocoa constituents. Copyright © 2017 Elsevier Ltd. All rights reserved.

An examination of the impact of attention-deficit hyperactivity disorder on IQ: a large controlled family-based analysis.

PubMed

Biederman, Joseph; Fried, Ronna; Petty, Carter; Mahoney, Laura; Faraone, Stephen V

2012-10-01

Although children with attention-deficit hyperactivity disorder (ADHD) have, on average, lower intelligence quotient (IQ) scores than control subjects, the reasons for these deficits remain unknown. Because IQ is highly familial, we investigated whether children with ADHD have a decrement in IQ from expectations based on parental IQ. Subjects were 276 children with ADHD and 239 control subjects of similar age and sex. Expected IQ was calculated based on biological parents' estimated IQ. A significant discrepancy between observed and expected estimated IQ was defined by a child scoring 15 IQ points or more lower than expected, based on parental IQ. Compared with control subjects, children with ADHD were significantly more likely to have lower than expected estimated IQ scores based on parental IQ, though this finding was accounted for by a small subgroup of children with ADHD who had an IQ 15 points or more lower than expected, based on parental IQ. These children were more likely to be female, have higher psychopathological, neuropsychological, educational, and interpersonal deficits, as well as higher rates of perinatal complications. Group differences in IQ scores between children with and without ADHD reported in the literature may be accounted for by a subgroup of children with ADHD who have a large decrement in IQ from expectations based on parental IQ. Although perinatal complications may explain these findings, more work is needed to better understand the etiology of these IQ deficits.

Active vibration control for piezoelectricity cantilever beam: an adaptive feedforward control method

NASA Astrophysics Data System (ADS)

Zhu, Qiao; Yue, Jun-Zhou; Liu, Wei-Qun; Wang, Xu-Dong; Chen, Jun; Hu, Guang-Di

2017-04-01

This work is focused on the active vibration control of piezoelectric cantilever beam, where an adaptive feedforward controller (AFC) is utilized to reject the vibration with unknown multiple frequencies. First, the experiment setup and its mathematical model are introduced. Due to that the channel between the disturbance and the vibration output is unknown in practice, a concept of equivalent input disturbance (EID) is employed to put an equivalent disturbance into the input channel. In this situation, the vibration control can be achieved by setting the control input be the identified EID. Then, for the EID with known multiple frequencies, the AFC is introduced to perfectly reject the vibration but is sensitive to the frequencies. In order to accurately identify the unknown frequencies of EID in presence of the random disturbances and un-modeled nonlinear dynamics, the time-frequency-analysis (TFA) method is employed to precisely identify the unknown frequencies. Consequently, a TFA-based AFC algorithm is proposed to the active vibration control with unknown frequencies. Finally, four cases are given to illustrate the efficiency of the proposed TFA-based AFC algorithm by experiment.

A spline-based parameter estimation technique for static models of elastic structures

NASA Technical Reports Server (NTRS)

Dutt, P.; Taasan, S.

1986-01-01

The problem of identifying the spatially varying coefficient of elasticity using an observed solution to the forward problem is considered. Under appropriate conditions this problem can be treated as a first order hyperbolic equation in the unknown coefficient. Some continuous dependence results are developed for this problem and a spline-based technique is proposed for approximating the unknown coefficient, based on these results. The convergence of the numerical scheme is established and error estimates obtained.

Target and double spin asymmetries of deeply virtual π0 production with a longitudinally polarized proton target and CLAS

NASA Astrophysics Data System (ADS)

Kim, A.; Avakian, H.; Burkert, V.; Joo, K.; Kim, W.; Adhikari, K. P.; Akbar, Z.; Anefalos Pereira, S.; Badui, R. A.; Battaglieri, M.; Batourine, V.; Bedlinskiy, I.; Biselli, A. S.; Boiarinov, S.; Bosted, P.; Briscoe, W. J.; Brooks, W. K.; Bültmann, S.; Cao, T.; Carman, D. S.; Celentano, A.; Chandavar, S.; Charles, G.; Chetry, T.; Colaneri, L.; Cole, P. L.; Compton, N.; Contalbrigo, M.; Cortes, O.; Crede, V.; D'Angelo, A.; Dashyan, N.; De Vita, R.; De Sanctis, E.; Djalali, C.; Egiyan, H.; El Alaoui, A.; El Fassi, L.; Eugenio, P.; Fedotov, G.; Fersch, R.; Filippi, A.; Fleming, J. A.; Fradi, A.; Garc con, M.; Ghandilyan, Y.; Gilfoyle, G. P.; Giovanetti, K. L.; Girod, F. X.; Gohn, W.; Golovatch, E.; Gothe, R. W.; Griffioen, K. A.; Guo, L.; Hafidi, K.; Hanretty, C.; Hattawy, M.; Heddle, D.; Hicks, K.; Holtrop, M.; Ilieva, Y.; Ireland, D. G.; Ishkhanov, B. S.; Jenkins, D.; Jiang, H.; Jo, H. S.; Joosten, S.; Keller, D.; Khachatryan, G.; Khandaker, M.; Klein, A.; Klein, F. J.; Kubarovsky, V.; Kuhn, S. E.; Kuleshov, S. V.; Lanza, L.; Lenisa, P.; Lu, H. Y.; MacGregor, I. J. D.; Markov, N.; Mattione, P.; McCracken, M. E.; McKinnon, B.; Mokeev, V.; Movsisyan, A.; Munevar, E.; Nadel-Turonski, P.; Net, L. A.; Niccolai, S.; Osipenko, M.; Ostrovidov, A. I.; Paolone, M.; Park, K.; Pasyuk, E.; Phelps, W.; Pisano, S.; Pogorelko, O.; Price, J. W.; Prok, Y.; Ripani, M.; Rizzo, A.; Rosner, G.; Rossi, P.; Roy, P.; Salgado, C.; Schumacher, R. A.; Seder, E.; Sharabian, Y. G.; Skorodumina, Iu.; Smith, G. D.; Sokhan, D.; Sparveris, N.; Stepanyan, S.; Stoler, P.; Strakovsky, I. I.; Strauch, S.; Sytnik, V.; Taiuti, M.; Torayev, B.; Ungaro, M.; Voskanyan, H.; Voutier, E.; Watts, D. P.; Wei, X.; Weinstein, L. B.; Zachariou, N.; Zana, L.; Zhang, J.

2017-05-01

The target and double spin asymmetries of the exclusive pseudoscalar channel e → p → → epπ0 were measured for the first time in the deep-inelastic regime using a longitudinally polarized 5.9 GeV electron beam and a longitudinally polarized proton target at Jefferson Lab with the CEBAF Large Acceptance Spectrometer (CLAS). The data were collected over a large kinematic phase space and divided into 110 four-dimensional bins of Q2, xB, -t and ϕ. Large values of asymmetry moments clearly indicate a substantial contribution to the polarized structure functions from transverse virtual photon amplitudes. The interpretation of experimental data in terms of generalized parton distributions (GPDs) provides the first insight on the chiral-odd GPDs H˜T and ET, and complement previous measurements of unpolarized structure functions sensitive to the GPDs HT and EbarT. These data provide a crucial input for parametrizations of essentially unknown chiral-odd GPDs and will strongly influence existing theoretical calculations based on the handbag formalism.

Systematic Survey of Serine Hydrolase Activity in Mycobacterium tuberculosis Defines Changes Associated with Persistence

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

Ortega, Corrie; Anderson, Lindsey N.; Frando, Andrew

The transition between replication and non-replication underlies much of Mycobacterium tuberculosis (Mtb) pathogenicity, as non- or slowly replicating Mtb are responsible for persistence and poor treatment outcomes. Therapeutic targeting of non-replicating, persistent populations is a priority for tuberculosis treatment, but only few drug targets in non-replicating Mtb are currently known. Here, we directly measure the activity of the highly diverse and druggable serine hydrolases (SHs) during active replication and non-replication by activity-based proteomics. We predict serine hydrolase activity for 78 proteins, including 27 proteins with previously unknown function, and identify 37 SHs that remain active even in the absence ofmore » replication, providing a set of candidate persistence targets. Non-replication was associated with large shifts in the activity of the majority of SHs. These activity changes were largely independent of SH abundance, indicating extensive post-translational regulation. By probing a large cross-section of druggable Mtb enzyme space during replication and non-replication, we identify new SHs and suggest new persistence targets.« less

Examining gray matter structure associated with academic performance in a large sample of Chinese high school students.

PubMed

Wang, Song; Zhou, Ming; Chen, Taolin; Yang, Xun; Chen, Guangxiang; Wang, Meiyun; Gong, Qiyong

2017-04-18

Achievement in school is crucial for students to be able to pursue successful careers and lead happy lives in the future. Although many psychological attributes have been found to be associated with academic performance, the neural substrates of academic performance remain largely unknown. Here, we investigated the relationship between brain structure and academic performance in a large sample of high school students via structural magnetic resonance imaging (S-MRI) using voxel-based morphometry (VBM) approach. The whole-brain regression analyses showed that higher academic performance was related to greater regional gray matter density (rGMD) of the left dorsolateral prefrontal cortex (DLPFC), which is considered a neural center at the intersection of cognitive and non-cognitive functions. Furthermore, mediation analyses suggested that general intelligence partially mediated the impact of the left DLPFC density on academic performance. These results persisted even after adjusting for the effect of family socioeconomic status (SES). In short, our findings reveal a potential neuroanatomical marker for academic performance and highlight the role of general intelligence in explaining the relationship between brain structure and academic performance.

Ratbot automatic navigation by electrical reward stimulation based on distance measurement in unknown environments.

PubMed

Gao, Liqiang; Sun, Chao; Zhang, Chen; Zheng, Nenggan; Chen, Weidong; Zheng, Xiaoxiang

2013-01-01

Traditional automatic navigation methods for bio-robots are constrained to configured environments and thus can't be applied to tasks in unknown environments. With no consideration of bio-robot's own innate living ability and treating bio-robots in the same way as mechanical robots, those methods neglect the intelligence behavior of animals. This paper proposes a novel ratbot automatic navigation method in unknown environments using only reward stimulation and distance measurement. By utilizing rat's habit of thigmotaxis and its reward-seeking behavior, this method is able to incorporate rat's intrinsic intelligence of obstacle avoidance and path searching into navigation. Experiment results show that this method works robustly and can successfully navigate the ratbot to a target in the unknown environment. This work might put a solid base for application of ratbots and also has significant implication of automatic navigation for other bio-robots as well.

Adaptive control of Parkinson's state based on a nonlinear computational model with unknown parameters.

PubMed

Su, Fei; Wang, Jiang; Deng, Bin; Wei, Xi-Le; Chen, Ying-Yuan; Liu, Chen; Li, Hui-Yan

2015-02-01

The objective here is to explore the use of adaptive input-output feedback linearization method to achieve an improved deep brain stimulation (DBS) algorithm for closed-loop control of Parkinson's state. The control law is based on a highly nonlinear computational model of Parkinson's disease (PD) with unknown parameters. The restoration of thalamic relay reliability is formulated as the desired outcome of the adaptive control methodology, and the DBS waveform is the control input. The control input is adjusted in real time according to estimates of unknown parameters as well as the feedback signal. Simulation results show that the proposed adaptive control algorithm succeeds in restoring the relay reliability of the thalamus, and at the same time achieves accurate estimation of unknown parameters. Our findings point to the potential value of adaptive control approach that could be used to regulate DBS waveform in more effective treatment of PD.

Distributed Adaptive Neural Network Output Tracking of Leader-Following High-Order Stochastic Nonlinear Multiagent Systems With Unknown Dead-Zone Input.

PubMed

Hua, Changchun; Zhang, Liuliu; Guan, Xinping

2017-01-01

This paper studies the problem of distributed output tracking consensus control for a class of high-order stochastic nonlinear multiagent systems with unknown nonlinear dead-zone under a directed graph topology. The adaptive neural networks are used to approximate the unknown nonlinear functions and a new inequality is used to deal with the completely unknown dead-zone input. Then, we design the controllers based on backstepping method and the dynamic surface control technique. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of semiglobally uniform ultimate boundedness and the tracking errors between the leader and the followers approach to a small residual set based on Lyapunov stability theory. Finally, two simulation examples are presented to show the effectiveness and the advantages of the proposed techniques.

A continuous optimization approach for inferring parameters in mathematical models of regulatory networks.

PubMed

Deng, Zhimin; Tian, Tianhai

2014-07-29

The advances of systems biology have raised a large number of sophisticated mathematical models for describing the dynamic property of complex biological systems. One of the major steps in developing mathematical models is to estimate unknown parameters of the model based on experimentally measured quantities. However, experimental conditions limit the amount of data that is available for mathematical modelling. The number of unknown parameters in mathematical models may be larger than the number of observation data. The imbalance between the number of experimental data and number of unknown parameters makes reverse-engineering problems particularly challenging. To address the issue of inadequate experimental data, we propose a continuous optimization approach for making reliable inference of model parameters. This approach first uses a spline interpolation to generate continuous functions of system dynamics as well as the first and second order derivatives of continuous functions. The expanded dataset is the basis to infer unknown model parameters using various continuous optimization criteria, including the error of simulation only, error of both simulation and the first derivative, or error of simulation as well as the first and second derivatives. We use three case studies to demonstrate the accuracy and reliability of the proposed new approach. Compared with the corresponding discrete criteria using experimental data at the measurement time points only, numerical results of the ERK kinase activation module show that the continuous absolute-error criteria using both function and high order derivatives generate estimates with better accuracy. This result is also supported by the second and third case studies for the G1/S transition network and the MAP kinase pathway, respectively. This suggests that the continuous absolute-error criteria lead to more accurate estimates than the corresponding discrete criteria. We also study the robustness property of these three models to examine the reliability of estimates. Simulation results show that the models with estimated parameters using continuous fitness functions have better robustness properties than those using the corresponding discrete fitness functions. The inference studies and robustness analysis suggest that the proposed continuous optimization criteria are effective and robust for estimating unknown parameters in mathematical models.

Stem Cell Niche, the Microenvironment and Immunological Crosstalk

PubMed Central

Sujata, Law; Chaudhuri, S

2008-01-01

The concept of stem cells, their physiological existence, the intricate anatomical localization, the known and the unknown functions, and their exclusive utility for the purpose of regenerative medicine, are all now encompassed within an emergent question, ‘how compatible these cells are immunologically?' Indeed, the medical aspects of stem cells are dependent on a large number of queries based on the basic properties of the cells. It has greatly been emphasized to probe into the basic research on stem cells before any successful therapeutic attempts are made. One of the intricate aspects of the adult stem cells is its immunological behavior in relation to the microenvironmental associates, the stromal cells in the presence of a suitable target. PMID:18445340

Stem cell niche, the microenvironment and immunological crosstalk.

PubMed

Sujata, Law; Chaudhuri, S

2008-04-01

The concept of stem cells, their physiological existence, the intricate anatomical localization, the known and the unknown functions, and their exclusive utility for the purpose of regenerative medicine, are all now encompassed within an emergent question, 'how compatible these cells are immunologically?' Indeed, the medical aspects of stem cells are dependent on a large number of queries based on the basic properties of the cells. It has greatly been emphasized to probe into the basic research on stem cells before any successful therapeutic attempts are made. One of the intricate aspects of the adult stem cells is its immunological behavior in relation to the microenvironmental associates, the stromal cells in the presence of a suitable target.

E-Cigarettes and Potential Implications for Plastic Surgery.

PubMed

Taub, Peter J; Matarasso, Alan

2016-12-01

The use of tobacco-based products, most notably cigarettes, is related directly to wound healing problems and poorer outcomes in plastic surgery. Current abstracts have highlighted the potential complications from nicotine, specifically following plastic surgery in patients who choose to smoke. Recently, products that use electricity to vaporize liquid nitrogen have been gaining popularity. New rules were recently proposed that would give the federal government authority over electronic cigarettes. However, the health-related issues surrounding e-cigarettes are still largely unknown or misunderstood. These issues also extend to their impact on surgical procedures, notably their effect on plastic surgical procedures that rely heavily on the vascularity of either the host wound bed or the replacement tissue.

Imaging and Screening of Cancer of the Small Bowel.

PubMed

Kim, Jin Sil; Park, Seong Ho; Hansel, Stephanie; Fletcher, Joel G

2017-11-01

Delayed diagnosis of small bowel cancers frequently occurs and may arise because of many factors, including low incidence of disease, difficult endoscopic access, lack of mucosal mass or abnormality, subtle radiologic features, and low index of clinical suspicion. As small bowel cancers are rare and their causes are largely unknown, routine population-based screening of asymptomatic patients to find precursor lesions or early cancers is ineffective. However, targeted screening/surveillance strategies are used in specific at-risk and symptomatic patient populations. This article reviews issues regarding early diagnosis of small bowel cancers, with focus on state-of-the-art cross-sectional imaging techniques. Copyright © 2017 Elsevier Inc. All rights reserved.

Astrophysical data analysis with information field theory

NASA Astrophysics Data System (ADS)

Enßlin, Torsten

2014-12-01

Non-parametric imaging and data analysis in astrophysics and cosmology can be addressed by information field theory (IFT), a means of Bayesian, data based inference on spatially distributed signal fields. IFT is a statistical field theory, which permits the construction of optimal signal recovery algorithms. It exploits spatial correlations of the signal fields even for nonlinear and non-Gaussian signal inference problems. The alleviation of a perception threshold for recovering signals of unknown correlation structure by using IFT will be discussed in particular as well as a novel improvement on instrumental self-calibration schemes. IFT can be applied to many areas. Here, applications in in cosmology (cosmic microwave background, large-scale structure) and astrophysics (galactic magnetism, radio interferometry) are presented.

Geophysics and nutritional science: toward a novel, unified paradigm.

PubMed

Eshel, Gidon; Martin, Pamela A

2009-05-01

This article discusses a few basic geophysical processes, which collectively indicate that several nutritionally adverse elements of current Western diets also yield environmentally harmful food consumption patterns. We address oceanic dead zones, which are at the confluence of oceanography, aquatic chemistry, and agronomy and which are a clear environmental problem, and agriculture's effects on the surface heat budget. These exemplify the unknown, complex, and sometimes unexpected large-scale environmental effects of agriculture. We delineate the significant alignment in purpose between nutritional and environmental sciences. We identify red meat, and to a lesser extent the broader animal-based portion of the diet, as having the greatest environmental effect, with clear nutritional parallels.

Control of Complex Dynamic Systems by Neural Networks

NASA Technical Reports Server (NTRS)

Spall, James C.; Cristion, John A.

1993-01-01

This paper considers the use of neural networks (NN's) in controlling a nonlinear, stochastic system with unknown process equations. The NN is used to model the resulting unknown control law. The approach here is based on using the output error of the system to train the NN controller without the need to construct a separate model (NN or other type) for the unknown process dynamics. To implement such a direct adaptive control approach, it is required that connection weights in the NN be estimated while the system is being controlled. As a result of the feedback of the unknown process dynamics, however, it is not possible to determine the gradient of the loss function for use in standard (back-propagation-type) weight estimation algorithms. Therefore, this paper considers the use of a new stochastic approximation algorithm for this weight estimation, which is based on a 'simultaneous perturbation' gradient approximation that only requires the system output error. It is shown that this algorithm can greatly enhance the efficiency over more standard stochastic approximation algorithms based on finite-difference gradient approximations.

Electromagnetic spectrum management system

DOEpatents

Seastrand, Douglas R.

2017-01-31

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process the unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.

Using Project-Based Learning to Design, Build, and Test Student-Made Photometer by Measuring the Unknown Concentration of Colored Substances

ERIC Educational Resources Information Center

Diawati, Chansyanah; Liliasari; Setiabudi, Agus; Buchari

2018-01-01

Students learned the principles and practice of photometry through project-based learning. They addressed the challenge of measuring the unknown concentration of a colored substance using a photometer they were required to design, build, and test. Then, they used that instrument to carry out the experiment and fulfill the challenge. A photometer…

Minimal-Approximation-Based Distributed Consensus Tracking of a Class of Uncertain Nonlinear Multiagent Systems With Unknown Control Directions.

PubMed

Choi, Yun Ho; Yoo, Sung Jin

2017-03-28

A minimal-approximation-based distributed adaptive consensus tracking approach is presented for strict-feedback multiagent systems with unknown heterogeneous nonlinearities and control directions under a directed network. Existing approximation-based consensus results for uncertain nonlinear multiagent systems in lower-triangular form have used multiple function approximators in each local controller to approximate unmatched nonlinearities of each follower. Thus, as the follower's order increases, the number of the approximators used in its local controller increases. However, the proposed approach employs only one function approximator to construct the local controller of each follower regardless of the order of the follower. The recursive design methodology using a new error transformation is derived for the proposed minimal-approximation-based design. Furthermore, a bounding lemma on parameters of Nussbaum functions is presented to handle the unknown control direction problem in the minimal-approximation-based distributed consensus tracking framework and the stability of the overall closed-loop system is rigorously analyzed in the Lyapunov sense.

Hair Testing for Drugs of Abuse and New Psychoactive Substances in a High-Risk Population.

PubMed

Salomone, Alberto; Palamar, Joseph J; Gerace, Enrico; Di Corcia, Daniele; Vincenti, Marco

2017-06-01

Hundreds of new psychoactive substances (NPS) have emerged in the drug market over the last decade. Few drug surveys in the USA, however, ask about use of NPS, so prevalence and correlates of use are largely unknown. A large portion of NPS use is unintentional or unknown as NPS are common adulterants in drugs like ecstasy/Molly, and most NPS are rapidly eliminated from the body, limiting efficacy of urine, blood and saliva testing. We utilized a novel method of examining prevalence of NPS use in a high-risk population utilizing hair-testing. Hair samples from high-risk nightclub and dance music attendees were tested for 82 drugs and metabolites (including NPS) using ultra-high performance liquid chromatography-tandem mass spectrometry. Eighty samples collected from different parts of the body were analyzed, 57 of which detected positive for at least one substance-either a traditional or new drug. Among these, 26 samples tested positive for at least one NPS-the most common being butylone (25 samples). Other new drugs detected include methylone, methoxetamine, 5/6-APB, α-PVP and 4-FA. Hair analysis proved a powerful tool to gain objective biological drug-prevalence information, free from possible biases of unintentional or unknown intake and untruthful reporting of use. Such testing can be used actively or retrospectively to validate survey responses and inform research on consumption patterns, including intentional and unknown use, polydrug-use, occasional NPS intake and frequent or heavy use. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Inferring terrestrial photosynthetic light use efficiency of temperate ecosystems from space

Treesearch

Thomas Hilker; Nicholas C. Coops; Forest G. Hall; Caroline J. Nichol; Alexei Lyapustin; T. Andrew Black; Michael A. Wulder; Ray Leuning; Alan Barr; David Y. Hollinger; Bill Munger; Compton J. Tucker

2011-01-01

Terrestrial ecosystems absorb about 2.8 Gt C yr−1, which is estimated to be about a quarter of the carbon emitted from fossil fuel combustion. However, the uncertainties of this sink are large, on the order of ±40%, with spatial and temporal variations largely unknown. One of the largest factors contributing to the uncertainty is photosynthesis,...

A large source of dust missing in particulate matter emission inventories? Wind erosion of post-fire landscapes

Treesearch

N. S. Wagenbrenner; S. H. Chung; B. K. Lamb

2017-01-01

Wind erosion of soils burned by wildfire contributes substantial particulate matter (PM) in the form of dust to the atmosphere, but the magnitude of this dust source is largely unknown. It is important to accurately quantify dust emissions because they can impact human health, degrade visibility, exacerbate dust-on-snow issues (including snowmelt timing, snow chemistry...

Laterodorsal Nucleus of the Thalamus: A Processor of Somatosensory Inputs

PubMed Central

BEZDUDNAYA, TATIANA; KELLER, ASAF

2009-01-01

The laterodorsal (LD) nucleus of the thalamus has been considered a “higher order” nucleus that provides inputs to limbic cortical areas. Although its functions are largely unknown, it is often considered to be involved in spatial learning and memory. Here we provide evidence that LD is part of a hitherto unknown pathway for processing somatosensory information. Juxtacellular and extracellular recordings from LD neurons reveal that they respond to vibrissa stimulation with short latency (median = 7 ms) and large magnitude responses (median = 1.2 spikes/stimulus). Most neurons (62%) had large receptive fields, responding to six and more individual vibrissae. Electrical stimulation of the trigeminal nucleus interpolaris (SpVi) evoked short latency responses (median = 3.8 ms) in vibrissa-responsive LD neurons. Labeling produced by anterograde and retrograde neuroanatomical tracers confirmed that LD neurons receive direct inputs from SpVi. Electrophysiological and neuroanatomical analyses revealed also that LD projects upon the cingulate and retrosplenial cortex, but has only sparse projections to the barrel cortex. These findings suggest that LD is part of a novel processing stream involved in spatial orientation and learning related to somatosensory cues. PMID:18273888

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

Slater, Paul B.

Paralleling our recent computationally intensive (quasi-Monte Carlo) work for the case N=4 (e-print quant-ph/0308037), we undertake the task for N=6 of computing to high numerical accuracy, the formulas of Sommers and Zyczkowski (e-print quant-ph/0304041) for the (N{sup 2}-1)-dimensional volume and (N{sup 2}-2)-dimensional hyperarea of the (separable and nonseparable) NxN density matrices, based on the Bures (minimal monotone) metric--and also their analogous formulas (e-print quant-ph/0302197) for the (nonmonotone) flat Hilbert-Schmidt metric. With the same seven 10{sup 9} well-distributed ('low-discrepancy') sample points, we estimate the unknown volumes and hyperareas based on five additional (monotone) metrics of interest, including the Kubo-Mori and Wigner-Yanase.more » Further, we estimate all of these seven volume and seven hyperarea (unknown) quantities when restricted to the separable density matrices. The ratios of separable volumes (hyperareas) to separable plus nonseparable volumes (hyperareas) yield estimates of the separability probabilities of generically rank-6 (rank-5) density matrices. The (rank-6) separability probabilities obtained based on the 35-dimensional volumes appear to be--independently of the metric (each of the seven inducing Haar measure) employed--twice as large as those (rank-5 ones) based on the 34-dimensional hyperareas. (An additional estimate--33.9982--of the ratio of the rank-6 Hilbert-Schmidt separability probability to the rank-4 one is quite clearly close to integral too.) The doubling relationship also appears to hold for the N=4 case for the Hilbert-Schmidt metric, but not the others. We fit simple exact formulas to our estimates of the Hilbert-Schmidt separable volumes and hyperareas in both the N=4 and N=6 cases.« less

Industrialized timber structures.

DOT National Transportation Integrated Search

1974-01-01

It was recently learned that a number of innovations in structural timber components are available to the construction industry, but that they were largely unknown to bridge designers. The purpose of this study was to develop for the Department a fea...

Associations of endothelial function and air temperature in diabetic subjects

EPA Science Inventory

Background and Objective: Epidemiological studies consistently show that air temperature is associated with changes in cardiovascular morbidity and mortality. However, the biological mechanisms underlying the association remain largely unknown. As one index of endothelial functio...

Promoting Community Health Resources: Preferred Communication Strategies

USDA-ARS?s Scientific Manuscript database

Background: Community health promotion efforts involve communicating resource information to priority populations. Which communication strategies are most effective is largely unknown for specific populations. Objective: A random-dialed telephone survey was conducted to assess health resource comm...

Automated adaptive inference of phenomenological dynamical models.

PubMed

Daniels, Bryan C; Nemenman, Ilya

2015-08-21

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved.

Automated adaptive inference of phenomenological dynamical models

PubMed Central

Daniels, Bryan C.; Nemenman, Ilya

2015-01-01

Dynamics of complex systems is often driven by large and intricate networks of microscopic interactions, whose sheer size obfuscates understanding. With limited experimental data, many parameters of such dynamics are unknown, and thus detailed, mechanistic models risk overfitting and making faulty predictions. At the other extreme, simple ad hoc models often miss defining features of the underlying systems. Here we develop an approach that instead constructs phenomenological, coarse-grained models of network dynamics that automatically adapt their complexity to the available data. Such adaptive models produce accurate predictions even when microscopic details are unknown. The approach is computationally tractable, even for a relatively large number of dynamical variables. Using simulated data, it correctly infers the phase space structure for planetary motion, avoids overfitting in a biological signalling system and produces accurate predictions for yeast glycolysis with tens of data points and over half of the interacting species unobserved. PMID:26293508

Communicating with children and adolescents about the risk of natural disasters.

PubMed

Midtbust, Liv Gunvor Hove; Dyregrov, Atle; Djup, Heidi Wittrup

2018-01-01

A vast number of people annually are affected by natural disasters. Children are at risk of losing their lives and suffer mentally or physically after such events. The fostering of resilience and preparedness ahead of disasters can reduce untoward effects of disastrous events. Risk communication and disaster education are considered important aspects of disaster preparedness, but little is known about whether such strategies influence children's behaviour when natural disasters occur or how they cope in the aftermath. This paper presents and discusses various strategies that promote preparedness activities to save lives. To a minor extent, it also includes strategies that can promote coping in the aftermath. Strategies such as informational campaigns, educational activities, psychoeducation and parental guidance are addressed. The literature to date indicates that schools are a suitable arena for risk communication, and that adolescents themselves should be involved and engaged in the communication strategies. However, the relationship between knowledge of preparedness strategies and the resulting preparedness actions is largely unknown. It is unknown whether changes in awareness and attitudes have resulted in actual behaviour change. It is advocated that preparedness activities and parental involvement should supplement information-based strategies.

Microstructure and phase analyses of melt-spun Si-Ni base anode materials for Li-ion battery

NASA Astrophysics Data System (ADS)

Jeon, Sung Min; Song, Jong Jin; Kim, Sun-I.; Kwon, Hye Jin; Sohn, Keun Yong; Park, Won-Wook

2013-01-01

Si-based anode composite materials have been studied to improve the performance and the durability of Li-ion secondary batteries in this study. Si-Ni-Al, Si-Ni-Cu and Si-Ni-Cu-Al base alloys were designed and rapidly solidified at the cooling rate of about 106 °C/sec by optimizing the melt spinning. The ribbons were characterized using FE-SEM equipped with EDS, X-ray diffractometer and HR-TEM. The thin ribbons of Si-Ni-Al alloy consisted of nano-sized Si particles and amorphous matrix, which was regarded as an ideal microstructure for the anode material. At the wheel side of the ribbon, 20-30 nm of Si particles were formed (Zone A); whereas at the air side relatively large Si particles were distributed (Zone B). The Si-Ni-Cu alloy showed coarser Si particles than the Si-Ni-Al alloy, and its matrix consisted of NiSi2, Cu3Si and amorphous structures. Finally, the microstructure of the Si-Ni-Cu-Al alloy strips was composed of coarse Si particles, CuNi, Al4Cu9, NiSi2, and unknown phases, and the size of those Si particles were too large to be used for the anode materials.

On-Site Classification of Pansteatitis in Mozambique Tilapia (Oreochromis mossambicus) using a Portable Lipid-Based Analyzer

PubMed Central

Somerville, Stephen E.; Cantu, Theresa M.; Guillette, Matthew P.; Botha, Hannes; Boggs, Ashley S. P.; Luus-Powell, Wilmien; Guillette, Louis J.

2017-01-01

While no pansteatitis-related large-scale mortality events have occurred since 2008, the current status of pansteatitis (presence and pervasiveness) in the Olifants River system and other regions of South Africa remain largely unknown. In part, this is due to both a lack of known biological markers of pansteatitis and a lack of suitable non-invasive assays capable of rapidly classifying the disease. Here, we propose the application of a point-of-care (POC) device using lipid-based test strips (total cholesterol (TC) and total triglyceride (TG)), for classifying pansteatitis status in the whole blood of pre-spawning Mozambique tilapia (Oreochromis mossambicus). Using the TC strips, the POC device was able to non-lethally classify the tilapia as either healthy or pansteatitis-affected; the sexes were examined independently because sexual dimorphism was observed for TC (males p = 0.0364, females χ2 = 0.0007). No significant difference between diseased and pansteatitis-affected tilapia was observed using the TG strips. This is one of the first described applications of using POC devices for on-site environmental disease state testing. A discussion on the merits of using portable lipid-based analyzers as an in-field disease-state diagnostic tool is provided. PMID:28729886

Automatic Classification of Cellular Expression by Nonlinear Stochastic Embedding (ACCENSE).

PubMed

Shekhar, Karthik; Brodin, Petter; Davis, Mark M; Chakraborty, Arup K

2014-01-07

Mass cytometry enables an unprecedented number of parameters to be measured in individual cells at a high throughput, but the large dimensionality of the resulting data severely limits approaches relying on manual "gating." Clustering cells based on phenotypic similarity comes at a loss of single-cell resolution and often the number of subpopulations is unknown a priori. Here we describe ACCENSE, a tool that combines nonlinear dimensionality reduction with density-based partitioning, and displays multivariate cellular phenotypes on a 2D plot. We apply ACCENSE to 35-parameter mass cytometry data from CD8(+) T cells derived from specific pathogen-free and germ-free mice, and stratify cells into phenotypic subpopulations. Our results show significant heterogeneity within the known CD8(+) T-cell subpopulations, and of particular note is that we find a large novel subpopulation in both specific pathogen-free and germ-free mice that has not been described previously. This subpopulation possesses a phenotypic signature that is distinct from conventional naive and memory subpopulations when analyzed by ACCENSE, but is not distinguishable on a biaxial plot of standard markers. We are able to automatically identify cellular subpopulations based on all proteins analyzed, thus aiding the full utilization of powerful new single-cell technologies such as mass cytometry.

Modeling kinetic rate variation in third generation DNA sequencing data to detect putative modifications to DNA bases

PubMed Central

Schadt, Eric E.; Banerjee, Onureena; Fang, Gang; Feng, Zhixing; Wong, Wing H.; Zhang, Xuegong; Kislyuk, Andrey; Clark, Tyson A.; Luong, Khai; Keren-Paz, Alona; Chess, Andrew; Kumar, Vipin; Chen-Plotkin, Alice; Sondheimer, Neal; Korlach, Jonas; Kasarskis, Andrew

2013-01-01

Current generation DNA sequencing instruments are moving closer to seamlessly sequencing genomes of entire populations as a routine part of scientific investigation. However, while significant inroads have been made identifying small nucleotide variation and structural variations in DNA that impact phenotypes of interest, progress has not been as dramatic regarding epigenetic changes and base-level damage to DNA, largely due to technological limitations in assaying all known and unknown types of modifications at genome scale. Recently, single-molecule real time (SMRT) sequencing has been reported to identify kinetic variation (KV) events that have been demonstrated to reflect epigenetic changes of every known type, providing a path forward for detecting base modifications as a routine part of sequencing. However, to date no statistical framework has been proposed to enhance the power to detect these events while also controlling for false-positive events. By modeling enzyme kinetics in the neighborhood of an arbitrary location in a genomic region of interest as a conditional random field, we provide a statistical framework for incorporating kinetic information at a test position of interest as well as at neighboring sites that help enhance the power to detect KV events. The performance of this and related models is explored, with the best-performing model applied to plasmid DNA isolated from Escherichia coli and mitochondrial DNA isolated from human brain tissue. We highlight widespread kinetic variation events, some of which strongly associate with known modification events, while others represent putative chemically modified sites of unknown types. PMID:23093720

Modeling kinetic rate variation in third generation DNA sequencing data to detect putative modifications to DNA bases.

PubMed

Schadt, Eric E; Banerjee, Onureena; Fang, Gang; Feng, Zhixing; Wong, Wing H; Zhang, Xuegong; Kislyuk, Andrey; Clark, Tyson A; Luong, Khai; Keren-Paz, Alona; Chess, Andrew; Kumar, Vipin; Chen-Plotkin, Alice; Sondheimer, Neal; Korlach, Jonas; Kasarskis, Andrew

2013-01-01

Current generation DNA sequencing instruments are moving closer to seamlessly sequencing genomes of entire populations as a routine part of scientific investigation. However, while significant inroads have been made identifying small nucleotide variation and structural variations in DNA that impact phenotypes of interest, progress has not been as dramatic regarding epigenetic changes and base-level damage to DNA, largely due to technological limitations in assaying all known and unknown types of modifications at genome scale. Recently, single-molecule real time (SMRT) sequencing has been reported to identify kinetic variation (KV) events that have been demonstrated to reflect epigenetic changes of every known type, providing a path forward for detecting base modifications as a routine part of sequencing. However, to date no statistical framework has been proposed to enhance the power to detect these events while also controlling for false-positive events. By modeling enzyme kinetics in the neighborhood of an arbitrary location in a genomic region of interest as a conditional random field, we provide a statistical framework for incorporating kinetic information at a test position of interest as well as at neighboring sites that help enhance the power to detect KV events. The performance of this and related models is explored, with the best-performing model applied to plasmid DNA isolated from Escherichia coli and mitochondrial DNA isolated from human brain tissue. We highlight widespread kinetic variation events, some of which strongly associate with known modification events, while others represent putative chemically modified sites of unknown types.

A novel sensitivity-based method for damage detection of structures under unknown periodic excitations

NASA Astrophysics Data System (ADS)

Naseralavi, S. S.; Salajegheh, E.; Fadaee, M. J.; Salajegheh, J.

2014-06-01

This paper presents a technique for damage detection in structures under unknown periodic excitations using the transient displacement response. The method is capable of identifying the damage parameters without finding the input excitations. We first define the concept of displacement space as a linear space in which each point represents displacements of structure under an excitation and initial condition. Roughly speaking, the method is based on the fact that structural displacements under free and forced vibrations are associated with two parallel subspaces in the displacement space. Considering this novel geometrical viewpoint, an equation called kernel parallelization equation (KPE) is derived for damage detection under unknown periodic excitations and a sensitivity-based algorithm for solving KPE is proposed accordingly. The method is evaluated via three case studies under periodic excitations, which confirm the efficiency of the proposed method.

Distant Supervision with Transductive Learning for Adverse Drug Reaction Identification from Electronic Medical Records

PubMed Central

Ikeda, Mitsuru

2017-01-01

Information extraction and knowledge discovery regarding adverse drug reaction (ADR) from large-scale clinical texts are very useful and needy processes. Two major difficulties of this task are the lack of domain experts for labeling examples and intractable processing of unstructured clinical texts. Even though most previous works have been conducted on these issues by applying semisupervised learning for the former and a word-based approach for the latter, they face with complexity in an acquisition of initial labeled data and ignorance of structured sequence of natural language. In this study, we propose automatic data labeling by distant supervision where knowledge bases are exploited to assign an entity-level relation label for each drug-event pair in texts, and then, we use patterns for characterizing ADR relation. The multiple-instance learning with expectation-maximization method is employed to estimate model parameters. The method applies transductive learning to iteratively reassign a probability of unknown drug-event pair at the training time. By investigating experiments with 50,998 discharge summaries, we evaluate our method by varying large number of parameters, that is, pattern types, pattern-weighting models, and initial and iterative weightings of relations for unlabeled data. Based on evaluations, our proposed method outperforms the word-based feature for NB-EM (iEM), MILR, and TSVM with F1 score of 11.3%, 9.3%, and 6.5% improvement, respectively. PMID:29090077

Comprehensive analysis of organic ligands in whole root exudates using nuclear magnetic resonance and gas chromatography-mass spectrometry.

PubMed

Fan, T W; Lane, A N; Pedler, J; Crowley, D; Higashi, R M

1997-08-15

Root exudates in the rhizosphere are vital to the normal life cycle of plants. A key factor is phytometallophores, which function in the nutritional acquisition of iron and zinc and are likely to be important in the uptake of pollutant metals by plants. Unraveling the biochemistry of these compounds is tedious using traditional analyses, which also fall short in providing the overall chemical composition or in detecting unknown or unexpected organic ligands in the exudates. Here, we demonstrate a comprehensive analysis of the exudate composition directly by 1H and 13C multidimensional NMR and silylation GC-MS. The advantages are (a) minimal sample preparation, with no loss of unknown compounds, and reduced net analysis time; (b) structure-based analysis for universal detection and identification; and (c) simultaneous analysis of a large number of constituents in a complex mixture. Using barley root exudates, a large number of common organic and amino acids were identified. Three derivatives of mugineic acid phytosiderophores were also determined, the major one being 3-epihydroxymugineic acid, for which complete 1H and 13C NMR assignments were obtained. Quantification of all major components using these methods revealed a sevenfold increase in total exudation under moderate iron deficiency, with 3-epihydroxymugineic acid comprising approximately 22% of the exudate mixture. As iron deficiency increased, total quantities of exudate per gram of root remained unchanged, but the relative quantity of carbon allocated to phytosiderophore increased to approximately 50% of the total exudate in response to severe iron deficiency.

Computational-experimental approach to drug-target interaction mapping: A case study on kinase inhibitors

PubMed Central

Ravikumar, Balaguru; Parri, Elina; Timonen, Sanna; Airola, Antti; Wennerberg, Krister

2017-01-01

Due to relatively high costs and labor required for experimental profiling of the full target space of chemical compounds, various machine learning models have been proposed as cost-effective means to advance this process in terms of predicting the most potent compound-target interactions for subsequent verification. However, most of the model predictions lack direct experimental validation in the laboratory, making their practical benefits for drug discovery or repurposing applications largely unknown. Here, we therefore introduce and carefully test a systematic computational-experimental framework for the prediction and pre-clinical verification of drug-target interactions using a well-established kernel-based regression algorithm as the prediction model. To evaluate its performance, we first predicted unmeasured binding affinities in a large-scale kinase inhibitor profiling study, and then experimentally tested 100 compound-kinase pairs. The relatively high correlation of 0.77 (p < 0.0001) between the predicted and measured bioactivities supports the potential of the model for filling the experimental gaps in existing compound-target interaction maps. Further, we subjected the model to a more challenging task of predicting target interactions for such a new candidate drug compound that lacks prior binding profile information. As a specific case study, we used tivozanib, an investigational VEGF receptor inhibitor with currently unknown off-target profile. Among 7 kinases with high predicted affinity, we experimentally validated 4 new off-targets of tivozanib, namely the Src-family kinases FRK and FYN A, the non-receptor tyrosine kinase ABL1, and the serine/threonine kinase SLK. Our sub-sequent experimental validation protocol effectively avoids any possible information leakage between the training and validation data, and therefore enables rigorous model validation for practical applications. These results demonstrate that the kernel-based modeling approach offers practical benefits for probing novel insights into the mode of action of investigational compounds, and for the identification of new target selectivities for drug repurposing applications. PMID:28787438

Electromagnetic spectrum management system

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

Seastrand, Douglas R.

A system for transmitting a wireless countermeasure signal to disrupt third party communications is disclosed that include an antenna configured to receive wireless signals and transmit wireless counter measure signals such that the wireless countermeasure signals are responsive to the received wireless signals. A receiver processes the received wireless signals to create processed received signal data while a spectrum control module subtracts known source signal data from the processed received signal data to generate unknown source signal data. The unknown source signal data is based on unknown wireless signals, such as enemy signals. A transmitter is configured to process themore » unknown source signal data to create countermeasure signals and transmit a wireless countermeasure signal over the first antenna or a second antenna to thereby interfere with the unknown wireless signals.« less

Radiative flux and forcing parameterization error in aerosol-free clear skies.

PubMed

Pincus, Robert; Mlawer, Eli J; Oreopoulos, Lazaros; Ackerman, Andrew S; Baek, Sunghye; Brath, Manfred; Buehler, Stefan A; Cady-Pereira, Karen E; Cole, Jason N S; Dufresne, Jean-Louis; Kelley, Maxwell; Li, Jiangnan; Manners, James; Paynter, David J; Roehrig, Romain; Sekiguchi, Miho; Schwarzkopf, Daniel M

2015-07-16

Radiation parameterizations in GCMs are more accurate than their predecessorsErrors in estimates of 4 ×CO 2 forcing are large, especially for solar radiationErrors depend on atmospheric state, so global mean error is unknown.

Robust Fault Detection for Switched Fuzzy Systems With Unknown Input.

PubMed

Han, Jian; Zhang, Huaguang; Wang, Yingchun; Sun, Xun

2017-10-03

This paper investigates the fault detection problem for a class of switched nonlinear systems in the T-S fuzzy framework. The unknown input is considered in the systems. A novel fault detection unknown input observer design method is proposed. Based on the proposed observer, the unknown input can be removed from the fault detection residual. The weighted H∞ performance level is considered to ensure the robustness. In addition, the weighted H₋ performance level is introduced, which can increase the sensibility of the proposed detection method. To verify the proposed scheme, a numerical simulation example and an electromechanical system simulation example are provided at the end of this paper.

Photocopy of photograph (from NBPPNSY, CSF530663) photographer unknown, June 16, ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph (from NBP-PNSY, CSF-530-6-63) photographer unknown, June 16, 1963 view of a blade for a variable-pitch propeller positioned for finish machining. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

Neural Network Based Sensory Fusion for Landmark Detection

NASA Technical Reports Server (NTRS)

Kumbla, Kishan -K.; Akbarzadeh, Mohammad R.

1997-01-01

NASA is planning to send numerous unmanned planetary missions to explore the space. This requires autonomous robotic vehicles which can navigate in an unstructured, unknown, and uncertain environment. Landmark based navigation is a new area of research which differs from the traditional goal-oriented navigation, where a mobile robot starts from an initial point and reaches a destination in accordance with a pre-planned path. The landmark based navigation has the advantage of allowing the robot to find its way without communication with the mission control station and without exact knowledge of its coordinates. Current algorithms based on landmark navigation however pose several constraints. First, they require large memories to store the images. Second, the task of comparing the images using traditional methods is computationally intensive and consequently real-time implementation is difficult. The method proposed here consists of three stages, First stage utilizes a heuristic-based algorithm to identify significant objects. The second stage utilizes a neural network (NN) to efficiently classify images of the identified objects. The third stage combines distance information with the classification results of neural networks for efficient and intelligent navigation.

Structural damage identification using piezoelectric impedance measurement with sparse inverse analysis

NASA Astrophysics Data System (ADS)

Cao, Pei; Qi, Shuai; Tang, J.

2018-03-01

The impedance/admittance measurements of a piezoelectric transducer bonded to or embedded in a host structure can be used as damage indicator. When a credible model of the healthy structure, such as the finite element model, is available, using the impedance/admittance change information as input, it is possible to identify both the location and severity of damage. The inverse analysis, however, may be under-determined as the number of unknowns in high-frequency analysis is usually large while available input information is limited. The fundamental challenge thus is how to find a small set of solutions that cover the true damage scenario. In this research we cast the damage identification problem into a multi-objective optimization framework to tackle this challenge. With damage locations and severities as unknown variables, one of the objective functions is the difference between impedance-based model prediction in the parametric space and the actual measurements. Considering that damage occurrence generally affects only a small number of elements, we choose the sparsity of the unknown variables as another objective function, deliberately, the l 0 norm. Subsequently, a multi-objective Dividing RECTangles (DIRECT) algorithm is developed to facilitate the inverse analysis where the sparsity is further emphasized by sigmoid transformation. As a deterministic technique, this approach yields results that are repeatable and conclusive. In addition, only one algorithmic parameter, the number of function evaluations, is needed. Numerical and experimental case studies demonstrate that the proposed framework is capable of obtaining high-quality damage identification solutions with limited measurement information.

A reactive, scalable, and transferable model for molecular energies from a neural network approach based on local information

NASA Astrophysics Data System (ADS)

Unke, Oliver T.; Meuwly, Markus

2018-06-01

Despite the ever-increasing computer power, accurate ab initio calculations for large systems (thousands to millions of atoms) remain infeasible. Instead, approximate empirical energy functions are used. Most current approaches are either transferable between different chemical systems, but not particularly accurate, or they are fine-tuned to a specific application. In this work, a data-driven method to construct a potential energy surface based on neural networks is presented. Since the total energy is decomposed into local atomic contributions, the evaluation is easily parallelizable and scales linearly with system size. With prediction errors below 0.5 kcal mol-1 for both unknown molecules and configurations, the method is accurate across chemical and configurational space, which is demonstrated by applying it to datasets from nonreactive and reactive molecular dynamics simulations and a diverse database of equilibrium structures. The possibility to use small molecules as reference data to predict larger structures is also explored. Since the descriptor only uses local information, high-level ab initio methods, which are computationally too expensive for large molecules, become feasible for generating the necessary reference data used to train the neural network.

Decoupling a hole spin qubit from the nuclear spins.

PubMed

Prechtel, Jonathan H; Kuhlmann, Andreas V; Houel, Julien; Ludwig, Arne; Valentin, Sascha R; Wieck, Andreas D; Warburton, Richard J

2016-09-01

A huge effort is underway to develop semiconductor nanostructures as low-noise hosts for qubits. The main source of dephasing of an electron spin qubit in a GaAs-based system is the nuclear spin bath. A hole spin may circumvent the nuclear spin noise. In principle, the nuclear spins can be switched off for a pure heavy-hole spin. In practice, it is unknown to what extent this ideal limit can be achieved. A major hindrance is that p-type devices are often far too noisy. We investigate here a single hole spin in an InGaAs quantum dot embedded in a new generation of low-noise p-type device. We measure the hole Zeeman energy in a transverse magnetic field with 10 neV resolution by dark-state spectroscopy as we create a large transverse nuclear spin polarization. The hole hyperfine interaction is highly anisotropic: the transverse coupling is <1% of the longitudinal coupling. For unpolarized, randomly fluctuating nuclei, the ideal heavy-hole limit is achieved down to nanoelectronvolt energies; equivalently dephasing times up to a microsecond. The combination of large and strong optical dipole makes the single hole spin in a GaAs-based device an attractive quantum platform.

A robust sparse-modeling framework for estimating schizophrenia biomarkers from fMRI.

PubMed

Dillon, Keith; Calhoun, Vince; Wang, Yu-Ping

2017-01-30

Our goal is to identify the brain regions most relevant to mental illness using neuroimaging. State of the art machine learning methods commonly suffer from repeatability difficulties in this application, particularly when using large and heterogeneous populations for samples. We revisit both dimensionality reduction and sparse modeling, and recast them in a common optimization-based framework. This allows us to combine the benefits of both types of methods in an approach which we call unambiguous components. We use this to estimate the image component with a constrained variability, which is best correlated with the unknown disease mechanism. We apply the method to the estimation of neuroimaging biomarkers for schizophrenia, using task fMRI data from a large multi-site study. The proposed approach yields an improvement in both robustness of the estimate and classification accuracy. We find that unambiguous components incorporate roughly two thirds of the same brain regions as sparsity-based methods LASSO and elastic net, while roughly one third of the selected regions differ. Further, unambiguous components achieve superior classification accuracy in differentiating cases from controls. Unambiguous components provide a robust way to estimate important regions of imaging data. Copyright © 2016 Elsevier B.V. All rights reserved.

Deceleration-driven wetting transition of "gently" deposited drops on textured hydrophobic surfaces

NASA Astrophysics Data System (ADS)

Varanasi, Kripa; Kwon, Hyukmin; Paxson, Adam; Patankar, Neelesh

2010-11-01

Many applications of rough superhydrophobic surfaces rely on the presence of droplets in a Cassie state on the substrates. A well established understanding is that if sessile droplets are smaller than a critical size, then the large Laplace pressure induces wetting transition from a Cassie to a Wenzel state, i.e., the liquid impales the roughness grooves. Thus, larger droplets are expected to remain in the Cassie state. In this work we report a surprising wetting transition where even a "gentle" deposition of droplets on rough substrates lead to the transition of larger droplets to the Wenzel state. A hitherto unknown mechanism based on rapid deceleration is identified. It is found that modest amount of energy, during the deposition process, is channeled through rapid deceleration into high water hammer pressure which induces wetting transition. A new "phase" diagram is reported which shows that both large and small droplets can transition to Wenzel states due to the deceleration and Laplace mechanisms, respectively. This novel insight reveals for the first time that the attainment of a Cassie state is more restrictive than previous criteria based on the Laplace pressure transition mechanism.

The Landscape of long non-coding RNA classification

PubMed Central

St Laurent, Georges; Wahlestedt, Claes; Kapranov, Philipp

2015-01-01

Advances in the depth and quality of transcriptome sequencing have revealed many new classes of long non-coding RNAs (lncRNAs). lncRNA classification has mushroomed to accommodate these new findings, even though the real dimensions and complexity of the non-coding transcriptome remain unknown. Although evidence of functionality of specific lncRNAs continues to accumulate, conflicting, confusing, and overlapping terminology has fostered ambiguity and lack of clarity in the field in general. The lack of fundamental conceptual un-ambiguous classification framework results in a number of challenges in the annotation and interpretation of non-coding transcriptome data. It also might undermine integration of the new genomic methods and datasets in an effort to unravel function of lncRNA. Here, we review existing lncRNA classifications, nomenclature, and terminology. Then we describe the conceptual guidelines that have emerged for their classification and functional annotation based on expanding and more comprehensive use of large systems biology-based datasets. PMID:25869999

A unifying paradigm for naphthoquinone-based meroterpenoid (bio)synthesis

NASA Astrophysics Data System (ADS)

Miles, Zachary D.; Diethelm, Stefan; Pepper, Henry P.; Huang, David M.; George, Jonathan H.; Moore, Bradley S.

2017-12-01

Bacterial meroterpenoids constitute an important class of natural products with diverse biological properties and therapeutic potential. The biosynthetic logic for their production is unknown and defies explanation via classical biochemical paradigms. A large subgroup of naphthoquinone-based meroterpenoids exhibits a substitution pattern of the polyketide-derived aromatic core that seemingly contradicts the established reactivity pattern of polyketide phenol nucleophiles and terpene diphosphate electrophiles. We report the discovery of a hitherto unprecedented enzyme-promoted α-hydroxyketone rearrangement catalysed by vanadium-dependent haloperoxidases to account for these discrepancies in the merochlorin and napyradiomycin class of meroterpenoid antibiotics, and we demonstrate that the α-hydroxyketone rearrangement is potentially a conserved biosynthetic reaction in this molecular class. The biosynthetic α-hydroxyketone rearrangement was applied in a concise total synthesis of naphthomevalin, a prominent member of the napyradiomycin meroterpenes, and sheds further light on the mechanism of this unifying enzymatic transformation.

Calibration and analysis of genome-based models for microbial ecology.

PubMed

Louca, Stilianos; Doebeli, Michael

2015-10-16

Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

Neurexin and Neuroligin-based adhesion complexes drive axonal arborisation growth independent of synaptic activity

PubMed Central

Constance, William D; Mukherjee, Amrita; Fisher, Yvette E; Pop, Sinziana; Blanc, Eric; Toyama, Yusuke

2018-01-01

Building arborisations of the right size and shape is fundamental for neural network function. Live imaging in vertebrate brains strongly suggests that nascent synapses are critical for branch growth during development. The molecular mechanisms underlying this are largely unknown. Here we present a novel system in Drosophila for studying the development of complex arborisations live, in vivo during metamorphosis. In growing arborisations we see branch dynamics and localisations of presynaptic proteins very similar to the ‘synaptotropic growth’ described in fish/frogs. These accumulations of presynaptic proteins do not appear to be presynaptic release sites and are not paired with neurotransmitter receptors. Knockdowns of either evoked or spontaneous neurotransmission do not impact arbor growth. Instead, we find that axonal branch growth is regulated by dynamic, focal localisations of Neurexin and Neuroligin. These adhesion complexes provide stability for filopodia by a ‘stick-and-grow’ based mechanism wholly independent of synaptic activity. PMID:29504935

Accelerator-based Neutrino Physics at Fermilab

NASA Astrophysics Data System (ADS)

Dukes, Edmond

2008-10-01

The discovery of neutrino mass has excited great interest in elucidating the properties of neutrinos and their role in nature. Experiments around the world take advantage of solar, atmospheric, reactor, and accelerator sources of neutrinos. Accelerator-based sources are particularly convenient since their parameters can be tuned to optimize the measurement in question. At Fermilab an extensive neutrino program includes the MiniBooNE, SciBooNE, and MINOS experiments. Two major new experiments, MINERvA and NOvA, are being constructed, plans for a high-intensity neutrino source to DUSEL are underway, and an R&D effort towards a large liquid argon detector is being pursued. The NOvA experiment intends to search for electron neutrino appearance using a massive surface detector 811 km from Fermilab. In addition to measuring the last unknown mixing angle, theta(13), NOvA has the possibility of seeing matter-antimatter asymmetries in neutrinos and resolving the ordering of the neutrino mass states.

Real-Time Measurement of Machine Efficiency during Inertia Friction Welding.

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

Tung, Daniel Joseph; Mahaffey, David; Senkov, Oleg

Process efficiency is a crucial parameter for inertia friction welding (IFW) that is largely unknown at the present time. A new method has been developed to determine the transient profile of the IFW process efficiency by comparing the workpiece torque used to heat and deform the joint region to the total torque. Particularly, the former is measured by a torque load cell attached to the non-rotating workpiece while the latter is calculated from the deceleration rate of flywheel rotation. The experimentally-measured process efficiency for IFW of AISI 1018 steel rods is validated independently by the upset length estimated from anmore » analytical equation of heat balance and the flash profile calculated from a finite element based thermal stress model. The transient behaviors of torque and efficiency during IFW are discussed based on the energy loss to machine bearings and the bond formation at the joint interface.« less

An Enzyme-Catalyzed Multistep DNA Refolding Mechanism in Hairpin Telomere Formation

PubMed Central

Shi, Ke; Huang, Wai Mun; Aihara, Hideki

2013-01-01

Hairpin telomeres of bacterial linear chromosomes are generated by a DNA cutting–rejoining enzyme protelomerase. Protelomerase resolves a concatenated dimer of chromosomes as the last step of chromosome replication, converting a palindromic DNA sequence at the junctions between chromosomes into covalently closed hairpins. The mechanism by which protelomerase transforms a duplex DNA substrate into the hairpin telomeres remains largely unknown. We report here a series of crystal structures of the protelomerase TelA bound to DNA that represent distinct stages along the reaction pathway. The structures suggest that TelA converts a linear duplex substrate into hairpin turns via a transient strand-refolding intermediate that involves DNA-base flipping and wobble base-pairs. The extremely compact di-nucleotide hairpin structure of the product is fully stabilized by TelA prior to strand ligation, which drives the reaction to completion. The enzyme-catalyzed, multistep strand refolding is a novel mechanism in DNA rearrangement reactions. PMID:23382649

Glycogen synthase kinase 3 phosphorylates kinesin light chains and negatively regulates kinesin-based motility

NASA Technical Reports Server (NTRS)

Morfini, Gerardo; Szebenyi, Gyorgyi; Elluru, Ravindhra; Ratner, Nancy; Brady, Scott T.

2002-01-01

Membrane-bounded organelles (MBOs) are delivered to different domains in neurons by fast axonal transport. The importance of kinesin for fast antero grade transport is well established, but mechanisms for regulating kinesin-based motility are largely unknown. In this report, we provide biochemical and in vivo evidence that kinesin light chains (KLCs) interact with and are in vivo substrates for glycogen synthase kinase 3 (GSK3). Active GSK3 inhibited anterograde, but not retrograde, transport in squid axoplasm and reduced the amount of kinesin bound to MBOs. Kinesin microtubule binding and microtubule-stimulated ATPase activities were unaffected by GSK3 phosphorylation of KLCs. Active GSK3 was also localized preferentially to regions known to be sites of membrane delivery. These data suggest that GSK3 can regulate fast anterograde axonal transport and targeting of cargos to specific subcellular domains in neurons.

FBRDLR: Fast blind reconstruction approach with dictionary learning regularization for infrared microscopy spectra

NASA Astrophysics Data System (ADS)

Liu, Tingting; Liu, Hai; Chen, Zengzhao; Chen, Yingying; Wang, Shengming; Liu, Zhi; Zhang, Hao

2018-05-01

Infrared (IR) spectra are the fingerprints of the molecules, and the spectral band location closely relates to the structure of a molecule. Thus, specimen identification can be performed based on IR spectroscopy. However, spectrally overlapping components prevent the specific identification of hyperfine molecular information of different substances. In this paper, we propose a fast blind reconstruction approach for IR spectra, which is based on sparse and redundant representations over a dictionary. The proposed method recovers the spectrum with the discrete wavelet transform dictionary on its content. The experimental results demonstrate that the proposed method is superior because of the better performance when compared with other state-of-the-art methods. The method the authors used remove the instrument aging issue to a large extent, thus leading the reconstruction IR spectra a more convenient tool for extracting features of an unknown material and interpreting it.

Adventures in Ichthyology: Pacific Northwest Fishes of the Lewis and Clark Expedition

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

Dauble, Dennis D.

2005-09-01

Captains Meriwether Lewis and William Clark and other members of their expedition collected and identified nearly 400 species of plants and animals during the Voyage of Discovery. Of this total, 31 species of fish were included in Burrough’s summary of the natural history of the Expedition, including 12 fishes considered unknown to science at that time. While there is little doubt of the identity of fish for which Lewis and Clark provided detailed descriptions in their daily logs, other species designations were largely conjecture based on later scholars interpretation of the Lewis and Clarks account. Unlike other biological specimens encounteredmore » during the Expedition, no fishes were brought back for study. As a result, the identity of some fishes was never resolved. Many other fishes were reclassified during the past century based on updated scientific methods.« less

NAVIS-An UGV Indoor Positioning System Using Laser Scan Matching for Large-Area Real-Time Applications

PubMed Central

Tang, Jian.; Chen, Yuwei.; Jaakkola, Anttoni.; Liu, Jinbing.; Hyyppä, Juha.; Hyyppä, Hannu.

2014-01-01

Laser scan matching with grid-based maps is a promising tool for real-time indoor positioning of mobile Unmanned Ground Vehicles (UGVs). While there are critical implementation problems, such as the ability to estimate the position by sensing the unknown indoor environment with sufficient accuracy and low enough latency for stable vehicle control, further development work is necessary. Unfortunately, most of the existing methods employ heuristics for quick positioning in which numerous accumulated errors easily lead to loss of positioning accuracy. This severely restricts its applications in large areas and over lengthy periods of time. This paper introduces an efficient real-time mobile UGV indoor positioning system for large-area applications using laser scan matching with an improved probabilistically-motivated Maximum Likelihood Estimation (IMLE) algorithm, which is based on a multi-resolution patch-divided grid likelihood map. Compared with traditional methods, the improvements embodied in IMLE include: (a) Iterative Closed Point (ICP) preprocessing, which adaptively decreases the search scope; (b) a totally brute search matching method on multi-resolution map layers, based on the likelihood value between current laser scan and the grid map within refined search scope, adopted to obtain the global optimum position at each scan matching; and (c) a patch-divided likelihood map supporting a large indoor area. A UGV platform called NAVIS was designed, manufactured, and tested based on a low-cost robot integrating a LiDAR and an odometer sensor to verify the IMLE algorithm. A series of experiments based on simulated data and field tests with NAVIS proved that the proposed IMEL algorithm is a better way to perform local scan matching that can offer a quick and stable positioning solution with high accuracy so it can be part of a large area localization/mapping, application. The NAVIS platform can reach an updating rate of 12 Hz in a feature-rich environment and 2 Hz even in a feature-poor environment, respectively. Therefore, it can be utilized in a real-time application. PMID:24999715

NAVIS-An UGV indoor positioning system using laser scan matching for large-area real-time applications.

PubMed

Tang, Jian; Chen, Yuwei; Jaakkola, Anttoni; Liu, Jinbing; Hyyppä, Juha; Hyyppä, Hannu

2014-07-04

Laser scan matching with grid-based maps is a promising tool for real-time indoor positioning of mobile Unmanned Ground Vehicles (UGVs). While there are critical implementation problems, such as the ability to estimate the position by sensing the unknown indoor environment with sufficient accuracy and low enough latency for stable vehicle control, further development work is necessary. Unfortunately, most of the existing methods employ heuristics for quick positioning in which numerous accumulated errors easily lead to loss of positioning accuracy. This severely restricts its applications in large areas and over lengthy periods of time. This paper introduces an efficient real-time mobile UGV indoor positioning system for large-area applications using laser scan matching with an improved probabilistically-motivated Maximum Likelihood Estimation (IMLE) algorithm, which is based on a multi-resolution patch-divided grid likelihood map. Compared with traditional methods, the improvements embodied in IMLE include: (a) Iterative Closed Point (ICP) preprocessing, which adaptively decreases the search scope; (b) a totally brute search matching method on multi-resolution map layers, based on the likelihood value between current laser scan and the grid map within refined search scope, adopted to obtain the global optimum position at each scan matching; and (c) a patch-divided likelihood map supporting a large indoor area. A UGV platform called NAVIS was designed, manufactured, and tested based on a low-cost robot integrating a LiDAR and an odometer sensor to verify the IMLE algorithm. A series of experiments based on simulated data and field tests with NAVIS proved that the proposed IMEL algorithm is a better way to perform local scan matching that can offer a quick and stable positioning solution with high accuracy so it can be part of a large area localization/mapping, application. The NAVIS platform can reach an updating rate of 12 Hz in a feature-rich environment and 2 Hz even in a feature-poor environment, respectively. Therefore, it can be utilized in a real-time application.

A universal formula for the field enhancement factor

NASA Astrophysics Data System (ADS)

Biswas, Debabrata

2018-04-01

The field enhancement factor (FEF) is an important quantity in field emission calculations since the tunneling electron current depends very sensitively on its magnitude. The exact dependence of FEF on the emitter height h, the radius of curvature at the apex Ra, as well as the shape of the emitter base are still largely unknown. In this work, a universal formula for the field enhancement factor is derived for a single emitter. It depends on the ratio h/Ra and has the form γ a = ( 2 h / R a ) / [ α 1 ln ( 4 h / R a ) - α 2 ] , where α1 and α2 depend on the charge distribution on the emitter. Numerical results show that a simpler form γ a = ( 2 h / R a ) / [ ln ( 4 h / R a ) - α ] is equally valid with α depending on the emitter-base. Thus, for the hyperboloid, conical, and ellipsoid emitters, the value of α is 0, 0.88, and 2, while for the cylindrical base, α ≃ 2.6.

Inland-directed base surge generated by the explosive interaction of pyroclastic flows and seawater at Soufrière Hills volcano, Montserrat

USGS Publications Warehouse

Edmonds, Marie; Herd, Richard A.

2005-01-01

The largest and most intense lava-dome collapse during the eruption of Soufrière Hills volcano, Montserrat, 1995–2004, occurred 12–13 July 2003. The dome collapse involved around 200 × 106 m3 of material and was associated with a phenomenon previously unknown at this volcano. Large pyroclastic flows at the peak of the dome collapse interacted explosively with seawater at the mouth of the Tar River Valley and generated a hot, dry base surge that flowed 4 km inland and 300 m uphill. The surge was destructive to at least 25 m above the ground and it carbonized vegetation. The resulting two-layer deposits were as much as 0.9 m thick. Although the entire collapse lasted 18 h, the base surge greatly increased the land area affected by the dome collapse in a few minutes at the peak of the event, illustrating the complex nature of the interaction between pyroclastic flows and seawater.

Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

NASA Astrophysics Data System (ADS)

Chen, Xin; Liu, Li; Zhou, Sida; Yue, Zhenjiang

2016-09-01

Reduced order models(ROMs) based on the snapshots on the CFD high-fidelity simulations have been paid great attention recently due to their capability of capturing the features of the complex geometries and flow configurations. To improve the efficiency and precision of the ROMs, it is indispensable to add extra sampling points to the initial snapshots, since the number of sampling points to achieve an adequately accurate ROM is generally unknown in prior, but a large number of initial sampling points reduces the parsimony of the ROMs. A fuzzy-clustering-based adding-point strategy is proposed and the fuzzy clustering acts an indicator of the region in which the precision of ROMs is relatively low. The proposed method is applied to construct the ROMs for the benchmark mathematical examples and a numerical example of hypersonic aerothermodynamics prediction for a typical control surface. The proposed method can achieve a 34.5% improvement on the efficiency than the estimated mean squared error prediction algorithm and shows same-level prediction accuracy.

A Qualitative Investigation of Adolescents’ Perceived Mechanisms of Change from a Universal School-Based Depression Prevention Program

PubMed Central

Shochet, Ian; Montague, Roslyn; Smith, Coral; Dadds, Mark

2014-01-01

A recent meta-analysis provides evidence supporting the universal application of school-based prevention programs for adolescent depression. The mechanisms underlying such successful interventions, however, are largely unknown. We report on a qualitative analysis of 109 Grade 9 students’ beliefs about what they gained from an evidence-based depression prevention intervention, the Resourceful Adolescent Program (RAP-A). Fifty-four percent of interviewees articulated at least one specific example of program benefit. A thematic analysis of responses revealed two major themes, improved interpersonal relationships and improved self-regulation, both stronger than originally assumed. A more minor theme also emerged—more helpful cognitions. It is postulated that both improved interpersonal relationships and improved self-regulation are likely to enhance one another, and more helpful cognitions may express its contribution through enhanced self-regulation. These findings broaden our understanding of the impact of depression prevention programs, beginning to illuminate how such programs benefit participants. PMID:24859679

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System.

PubMed

Zhao, Kaihui; Li, Peng; Zhang, Changfan; Li, Xiangfei; He, Jing; Lin, Yuliang

2017-12-06

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system.

Visual Target Tracking in the Presence of Unknown Observer Motion

NASA Technical Reports Server (NTRS)

Williams, Stephen; Lu, Thomas

2009-01-01

Much attention has been given to the visual tracking problem due to its obvious uses in military surveillance. However, visual tracking is complicated by the presence of motion of the observer in addition to the target motion, especially when the image changes caused by the observer motion are large compared to those caused by the target motion. Techniques for estimating the motion of the observer based on image registration techniques and Kalman filtering are presented and simulated. With the effects of the observer motion removed, an additional phase is implemented to track individual targets. This tracking method is demonstrated on an image stream from a buoy-mounted or periscope-mounted camera, where large inter-frame displacements are present due to the wave action on the camera. This system has been shown to be effective at tracking and predicting the global position of a planar vehicle (boat) being observed from a single, out-of-plane camera. Finally, the tracking system has been extended to a multi-target scenario.

ChIP-seq reveals broad roles of SARD1 and CBP60g in regulating plant immunity.

PubMed

Sun, Tongjun; Zhang, Yaxi; Li, Yan; Zhang, Qian; Ding, Yuli; Zhang, Yuelin

2015-12-18

Recognition of pathogens by host plants leads to rapid transcriptional reprogramming and activation of defence responses. The expression of many defence regulators is induced in this process, but the mechanisms of how they are controlled transcriptionally are largely unknown. Here we use chromatin immunoprecipitation sequencing to show that the transcription factors SARD1 and CBP60g bind to the promoter regions of a large number of genes encoding key regulators of plant immunity. Among them are positive regulators of systemic immunity and signalling components for effector-triggered immunity and PAMP-triggered immunity, which is consistent with the critical roles of SARD1 and CBP60g in these processes. In addition, SARD1 and CBP60g target a number of genes encoding negative regulators of plant immunity, suggesting that they are also involved in negative feedback regulation of defence responses. Based on these findings we propose that SARD1 and CBP60g function as master regulators of plant immune responses.

The phylogenetic analysis of tetraspanins projects the evolution of cell-cell interactions from unicellular to multicellular organisms.

PubMed

Huang, Shengfeng; Yuan, Shaochun; Dong, Meiling; Su, Jing; Yu, Cuiling; Shen, Yang; Xie, Xiaojin; Yu, Yanhong; Yu, Xuesong; Chen, Shangwu; Zhang, Shicui; Pontarotti, Pierre; Xu, Anlong

2005-12-01

In animals, the tetraspanins are a large superfamily of membrane proteins that play important roles in organizing various cell-cell and matrix-cell interactions and signal pathways based on such interactions. However, their origin and evolution largely remain elusive and most of the family's members are functionally unknown or less known due to difficulties of study, such as functional redundancy. In this study, we rebuilt the family's phylogeny with sequences retrieved from online databases and our cDNA library of amphioxus. We reveal that, in addition to in metazoans, various tetraspanins are extensively expressed in protozoan amoebae, fungi, and plants. We also discuss the structural evolution of tetraspanin's major extracellular domain and the relation between tetraspanin's duplication and functional redundancy. Finally, we elucidate the coevolution of tetraspanins and eukaryotes and suggest that tetraspanins play important roles in the unicell-to-multicell transition. In short, the study of tetraspanin in a phylogenetic context helps us understand the evolution of intercellular interactions.

Identification of the miRNA targetome in hippocampal neurons using RIP-seq.

PubMed

Malmevik, Josephine; Petri, Rebecca; Klussendorf, Thies; Knauff, Pina; Åkerblom, Malin; Johansson, Jenny; Soneji, Shamit; Jakobsson, Johan

2015-07-28

MicroRNAs (miRNAs) are key players in the regulation of neuronal processes by targeting a large network of target messenger RNAs (mRNAs). However, the identity and function of mRNAs targeted by miRNAs in specific cells of the brain are largely unknown. Here, we established an adeno-associated viral vector (AAV)-based neuron-specific Argonaute2:GFP-RNA immunoprecipitation followed by high-throughput sequencing to analyse the regulatory role of miRNAs in mouse hippocampal neurons. Using this approach, we identified more than two thousand miRNA targets in hippocampal neurons, regulating essential neuronal features such as cell signalling, transcription and axon guidance. Furthermore, we found that stable inhibition of the highly expressed miR-124 and miR-125 in hippocampal neurons led to significant but distinct changes in the AGO2 binding of target mRNAs, resulting in subsequent upregulation of numerous miRNA target genes. These findings greatly enhance our understanding of the miRNA targetome in hippocampal neurons.

Formal Models of the Network Co-occurrence Underlying Mental Operations.

PubMed

Bzdok, Danilo; Varoquaux, Gaël; Grisel, Olivier; Eickenberg, Michael; Poupon, Cyril; Thirion, Bertrand

2016-06-01

Systems neuroscience has identified a set of canonical large-scale networks in humans. These have predominantly been characterized by resting-state analyses of the task-unconstrained, mind-wandering brain. Their explicit relationship to defined task performance is largely unknown and remains challenging. The present work contributes a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two extensive datasets (n = 500 and n = 81) by model-based generation of synthetic activity maps from recombination of shared network topographies. To study a use case, we formally revisited the poorly understood difference between neural activity underlying idling versus goal-directed behavior. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks. The possibility of decomposing a mental task into the relative contributions of major brain networks, the "network co-occurrence architecture" of a given task, opens an alternative access to the neural substrates of human cognition.

High-Performance Signal Detection for Adverse Drug Events using MapReduce Paradigm.

PubMed

Fan, Kai; Sun, Xingzhi; Tao, Ying; Xu, Linhao; Wang, Chen; Mao, Xianling; Peng, Bo; Pan, Yue

2010-11-13

Post-marketing pharmacovigilance is important for public health, as many Adverse Drug Events (ADEs) are unknown when those drugs were approved for marketing. However, due to the large number of reported drugs and drug combinations, detecting ADE signals by mining these reports is becoming a challenging task in terms of computational complexity. Recently, a parallel programming model, MapReduce has been introduced by Google to support large-scale data intensive applications. In this study, we proposed a MapReduce-based algorithm, for common ADE detection approach, Proportional Reporting Ratio (PRR), and tested it in mining spontaneous ADE reports from FDA. The purpose is to investigate the possibility of using MapReduce principle to speed up biomedical data mining tasks using this pharmacovigilance case as one specific example. The results demonstrated that MapReduce programming model could improve the performance of common signal detection algorithm for pharmacovigilance in a distributed computation environment at approximately liner speedup rates.

Formal Models of the Network Co-occurrence Underlying Mental Operations

PubMed Central

Bzdok, Danilo; Varoquaux, Gaël; Grisel, Olivier; Eickenberg, Michael; Poupon, Cyril; Thirion, Bertrand

2016-01-01

Systems neuroscience has identified a set of canonical large-scale networks in humans. These have predominantly been characterized by resting-state analyses of the task-unconstrained, mind-wandering brain. Their explicit relationship to defined task performance is largely unknown and remains challenging. The present work contributes a multivariate statistical learning approach that can extract the major brain networks and quantify their configuration during various psychological tasks. The method is validated in two extensive datasets (n = 500 and n = 81) by model-based generation of synthetic activity maps from recombination of shared network topographies. To study a use case, we formally revisited the poorly understood difference between neural activity underlying idling versus goal-directed behavior. We demonstrate that task-specific neural activity patterns can be explained by plausible combinations of resting-state networks. The possibility of decomposing a mental task into the relative contributions of major brain networks, the "network co-occurrence architecture" of a given task, opens an alternative access to the neural substrates of human cognition. PMID:27310288

Prioritizing Environmental Risk of Prescription Pharmaceuticals

PubMed Central

Dong, Zhao; Senn, David B.; Moran, Rebecca E.

2015-01-01

Low levels of pharmaceutical compounds have been detected in aquatic environments worldwide, but their human and ecological health risks associated with low dose environmental exposure is largely unknown due to the large number of these compounds and a lack of information. Therefore prioritization and ranking methods are needed for screening target compounds for research and risk assessment. Previous efforts to rank pharmaceutical compounds have often focused on occurrence data and have paid less attention to removal mechanisms such as human metabolism. This study proposes a simple prioritization approach based on number of prescriptions and toxicity information, accounting for metabolism and wastewater treatment removal, and can be applied to unmeasured compounds. The approach was performed on the 200 most-prescribed drugs in the U.S. in 2009. Our results showed that under-studied compounds such as levothyroxine and montelukast sodium received the highest scores, suggesting the importance of removal mechanisms in influencing the ranking, and the need for future environmental research to include other less-studied but potentially harmful pharmaceutical compounds. PMID:22813724

Accelerating forest growth enhancement due to climate and atmospheric changes in British Colombia, Canada over 1956-2001.

PubMed

Wu, Chaoyang; Hember, Robbie A; Chen, Jing M; Kurz, Werner A; Price, David T; Boisvenue, Céline; Gonsamo, Alemu; Ju, Weimin

2014-03-25

Changes in climate and atmospheric CO2 and nitrogen (N) over the last several decades have induced significant effects on forest carbon (C) cycling. However, contributions of individual factors are largely unknown because of the lack of long observational data and the undifferentiating between intrinsic factors and external forces in current ecosystem models. Using over four decades (1956-2001) of forest inventory data at 3432 permanent samples in maritime and boreal regions of British Columbia (B.C.), Canada, growth enhancements were reconstructed and partitioned into contributions of climate, CO2 and N after removal of age effects. We found that climate change contributed a particularly large amount (over 70%) of the accumulated growth enhancement, while the remaining was attributed to CO2 and N, respectively. We suggest that climate warming is contributing a widespread growth enhancement in B.C.'s forests, but ecosystem models should consider CO2 and N fertilization effects to fully explain inventory-based observations.

Georges Bank: a leaky incubator of Alexandrium fundyense blooms

PubMed Central

McGillicuddy, D.J.; Townsend, D.W.; Keafer, B.A.; Thomas, M.A.; Anderson, D.M.

2012-01-01

A series of oceanographic surveys on Georges Bank document variability of populations of the toxic dinoflagellate Alexandrium fundyense on time scales ranging from synoptic to seasonal to interannual. Blooms of A. fundyense on Georges Bank can reach concentrations on the order of 104 cells l−1, and are generally bank-wide in extent. Georges Bank populations of A. fundyense appear to be quasi-independent of those in the adjacent coastal Gulf of Maine, insofar as they occupy a hydrographic niche that is colder and saltier than their coastal counterparts. In contrast to coastal populations that rely on abundant resting cysts for bloom initiation, very few cysts are present in the sediments on Georges Bank. Bloom dynamics must therefore be largely controlled by the balance between growth and mortality processes, which are at present largely unknown for this population. Based on correlations between cell abundance and nutrient distributions, ammonium appears to be an important source of nitrogen for A. fundyense blooms on Georges Bank. PMID:24976691

Georges Bank: a leaky incubator of Alexandrium fundyense blooms.

PubMed

McGillicuddy, D J; Townsend, D W; Keafer, B A; Thomas, M A; Anderson, D M

2014-05-01

A series of oceanographic surveys on Georges Bank document variability of populations of the toxic dinoflagellate Alexandrium fundyense on time scales ranging from synoptic to seasonal to interannual. Blooms of A. fundyense on Georges Bank can reach concentrations on the order of 10 4 cells l -1 , and are generally bank-wide in extent. Georges Bank populations of A. fundyense appear to be quasi-independent of those in the adjacent coastal Gulf of Maine, insofar as they occupy a hydrographic niche that is colder and saltier than their coastal counterparts. In contrast to coastal populations that rely on abundant resting cysts for bloom initiation, very few cysts are present in the sediments on Georges Bank. Bloom dynamics must therefore be largely controlled by the balance between growth and mortality processes, which are at present largely unknown for this population. Based on correlations between cell abundance and nutrient distributions, ammonium appears to be an important source of nitrogen for A. fundyense blooms on Georges Bank.

Common Genetic Variant in VIT Is Associated with Human Brain Asymmetry.

PubMed

Tadayon, Sayed H; Vaziri-Pashkam, Maryam; Kahali, Pegah; Ansari Dezfouli, Mitra; Abbassian, Abdolhossein

2016-01-01

Brain asymmetry varies across individuals. However, genetic factors contributing to this normal variation are largely unknown. Here we studied variation of cortical surface area asymmetry in a large sample of subjects. We performed principal component analysis (PCA) to capture correlated asymmetry variation across cortical regions. We found that caudal and rostral anterior cingulate together account for a substantial part of asymmetry variation among individuals. To find SNPs associated with this subset of brain asymmetry variation we performed a genome-wide association study followed by replication in an independent cohort. We identified one SNP (rs11691187) that had genome-wide significant association (P Combined = 2.40e-08). The rs11691187 is in the first intron of VIT. In a follow-up analysis, we found that VIT gene expression is associated with brain asymmetry in six donors of the Allen Human Brain Atlas. Based on these findings we suggest that VIT contributes to normal brain asymmetry variation. Our results can shed light on disorders associated with altered brain asymmetry.

14. Photocopy of historic photograph (original photograph on file at ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

14. Photocopy of historic photograph (original photograph on file at Fairchild Air Force Museum, Spokane, WA) Photographer unknown, date unknown BOMBER ALERT FACILITY, INTERIOR, SLEEPING QUARTERS - Fairchild Air Force Base, Bomber Alert Facility, 803G South Taxi Way, Spokane, Spokane County, WA

Photocopy of photograph (from NBPPNSY) photographer unknown, 1988 view east ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Photocopy of photograph (from NBP-PNSY) photographer unknown, 1988 view east of marine railway (Haer no. Pa-387-W). The railway was being dismantled at the time this photograph was taken. - Naval Base Philadelphia-Philadelphia Naval Shipyard, League Island, Philadelphia, Philadelphia County, PA

[Fast discrimination of edible vegetable oil based on Raman spectroscopy].

PubMed

Zhou, Xiu-Jun; Dai, Lian-Kui; Li, Sheng

2012-07-01

A novel method to fast discriminate edible vegetable oils by Raman spectroscopy is presented. The training set is composed of different edible vegetable oils with known classes. Based on their original Raman spectra, baseline correction and normalization were applied to obtain standard spectra. Two characteristic peaks describing the unsaturated degree of vegetable oil were selected as feature vectors; then the centers of all classes were calculated. For an edible vegetable oil with unknown class, the same pretreatment and feature extraction methods were used. The Euclidian distances between the feature vector of the unknown sample and the center of each class were calculated, and the class of the unknown sample was finally determined by the minimum distance. For 43 edible vegetable oil samples from seven different classes, experimental results show that the clustering effect of each class was more obvious and the class distance was much larger with the new feature extraction method compared with PCA. The above classification model can be applied to discriminate unknown edible vegetable oils rapidly and accurately.

Quantum Standard Teleportation Based on the Generic Measurement Bases

NASA Astrophysics Data System (ADS)

Hao, San-Ru; Hou, Bo-Yu; Xi, Xiao-Qiang; Yue, Rui-Hong

2003-10-01

We study the quantum standard teleportation based on the generic measurement bases. It is shown that the quantum standard teleportation does not depend on the explicit expression of the measurement bases. We have given the correspondence relation between the measurement performed by Alice and the unitary transformation performed by Bob. We also prove that the single particle unknown states and the two-particle unknown cat-like states can be exactly transmitted by means of the generic measurement bases and the correspondence unitary transformations. The project supported in part by National Natural Science Foundation of China, the Hunan Provincial Natural Science Foundation of China, and the Scientific Research Fund of Hunan Provincial Education Department

Fast Markerless Tracking for Augmented Reality in Planar Environment

NASA Astrophysics Data System (ADS)

Basori, Ahmad Hoirul; Afif, Fadhil Noer; Almazyad, Abdulaziz S.; AbuJabal, Hamza Ali S.; Rehman, Amjad; Alkawaz, Mohammed Hazim

2015-12-01

Markerless tracking for augmented reality should not only be accurate but also fast enough to provide a seamless synchronization between real and virtual beings. Current reported methods showed that a vision-based tracking is accurate but requires high computational power. This paper proposes a real-time hybrid-based method for tracking unknown environments in markerless augmented reality. The proposed method provides collaboration of vision-based approach with accelerometers and gyroscopes sensors as camera pose predictor. To align the augmentation relative to camera motion, the tracking method is done by substituting feature-based camera estimation with combination of inertial sensors with complementary filter to provide more dynamic response. The proposed method managed to track unknown environment with faster processing time compared to available feature-based approaches. Moreover, the proposed method can sustain its estimation in a situation where feature-based tracking loses its track. The collaboration of sensor tracking managed to perform the task for about 22.97 FPS, up to five times faster than feature-based tracking method used as comparison. Therefore, the proposed method can be used to track unknown environments without depending on amount of features on scene, while requiring lower computational cost.

Antibiotic resistance genes and residual antimicrobials in cattle feedlot surface soil

USDA-ARS?s Scientific Manuscript database

Cattle feedlot soils receive manure containing both antibiotic residues and antibiotic resistant bacteria. The fates of these constituents are largely unknown with potentially serious consequences for increased antibiotic resistance in the environment. Determine if common antimicrobials (tetracycl...

Signaling hierarchy regulating human endothelial cell development

USDA-ARS?s Scientific Manuscript database

Our present knowledge of the regulation of mammalian endothelial cell differentiation has been largely derived from studies of mouse embryonic development. However, unique mechanisms and hierarchy of signals that govern human endothelial cell development are unknown and, thus, explored in these stud...

The caprine abomasal microbiome

USDA-ARS?s Scientific Manuscript database

Parasitism is considered the number one health problem in small ruminants. The barber's pole worm Haemonchus contortus infection in goats elicits a strong host immune response. However, the effect of the parasitic infection on the structure and function of the gut microbiome remains largely unknown....

Hybrid modeling of nitrate fate in large catchments using fuzzy-rules

NASA Astrophysics Data System (ADS)

van der Heijden, Sven; Haberlandt, Uwe

2010-05-01

Especially for nutrient balance simulations, physically based ecohydrological modeling needs an abundance of measured data and model parameters, which for large catchments all too often are not available in sufficient spatial or temporal resolution or are simply unknown. For efficient large-scale studies it is thus beneficial to have methods at one's disposal which are parsimonious concerning the number of model parameters and the necessary input data. One such method is fuzzy-rule based modeling, which compared to other machine-learning techniques has the advantages to produce models (the fuzzy-rules) which are physically interpretable to a certain extent, and to allow the explicit introduction of expert knowledge through pre-defined rules. The study focuses on the application of fuzzy-rule based modeling for nitrate simulation in large catchments, in particular concerning decision support. Fuzzy-rule based modeling enables the generation of simple, efficient, easily understandable models with nevertheless satisfactory accuracy for problems of decision support. The chosen approach encompasses a hybrid metamodeling, which includes the generation of fuzzy-rules with data originating from physically based models as well as a coupling with a physically based water balance model. For the generation of the needed training data and also as coupled water balance model the ecohydrological model SWAT is employed. The conceptual model divides the nitrate pathway into three parts. The first fuzzy-module calculates nitrate leaching with the percolating water from soil surface to groundwater, the second module simulates groundwater passage, and the final module replaces the in-stream processes. The aim of this modularization is to create flexibility for using each of the modules on its own, for changing or completely replacing it. For fuzzy-rule based modeling this can explicitly mean that the re-training of one of the modules with newly available data will be possible without problem, while the module assembly does not have to be modified. Apart from the concept of hybrid metamodeling first results are presented for the fuzzy-module for nitrate passage through the unsaturated zone.

The effects of task difficulty, novelty and the size of the search space on intrinsically motivated exploration.

PubMed

Baranes, Adrien F; Oudeyer, Pierre-Yves; Gottlieb, Jacqueline

2014-01-01

Devising efficient strategies for exploration in large open-ended spaces is one of the most difficult computational problems of intelligent organisms. Because the available rewards are ambiguous or unknown during the exploratory phase, subjects must act in intrinsically motivated fashion. However, a vast majority of behavioral and neural studies to date have focused on decision making in reward-based tasks, and the rules guiding intrinsically motivated exploration remain largely unknown. To examine this question we developed a paradigm for systematically testing the choices of human observers in a free play context. Adult subjects played a series of short computer games of variable difficulty, and freely choose which game they wished to sample without external guidance or physical rewards. Subjects performed the task in three distinct conditions where they sampled from a small or a large choice set (7 vs. 64 possible levels of difficulty), and where they did or did not have the possibility to sample new games at a constant level of difficulty. We show that despite the absence of external constraints, the subjects spontaneously adopted a structured exploration strategy whereby they (1) started with easier games and progressed to more difficult games, (2) sampled the entire choice set including extremely difficult games that could not be learnt, (3) repeated moderately and high difficulty games much more frequently than was predicted by chance, and (4) had higher repetition rates and chose higher speeds if they could generate new sequences at a constant level of difficulty. The results suggest that intrinsically motivated exploration is shaped by several factors including task difficulty, novelty and the size of the choice set, and these come into play to serve two internal goals-maximize the subjects' knowledge of the available tasks (exploring the limits of the task set), and maximize their competence (performance and skills) across the task set.

A genetic analysis of post-weaning feedlot performance and profitability in Bonsmara cattle.

PubMed

van der Westhuizen, R R; van der Westhuizen, J; Schoeman, S J

2009-02-25

The aim of this study was to identify factors influencing profitability in a feedlot environment and to estimate genetic parameters for and between a feedlot profit function and productive traits measured in growth tests. The heritability estimate of 0.36 for feedlot profitability shows that this trait is genetically inherited and that it can be selected for. The genetic correlations between feedlot profitability and production and efficiency varied from negligible to high. The genetic correlation estimate of -0.92 between feed conversion ratio and feedlot profitability is largely due to the part-whole relationship between these two traits. Consequently, a multiple regression equation was developed to estimate a feed intake value for all performance-tested Bonsmara bulls, which were group fed and whose feed intakes were unknown. These predicted feed intake values enabled the calculation of a post-weaning growth or feedlot profitability value for all tested bulls, even where individual feed intakes were unknown. Subsequently, a feedlot profitability value for each bull was calculated in a favorable economic environment, an average economic environment and in an unfavorable economic environment. The high Pearson and Spearman correlations between the estimate breeding values based on the average economic environment and the other two environments suggested that the average economic environment could be used to calculate estimate breeding values for feedlot profitability. It is therefore not necessary to change the carcass, weaned calf or feed price on a regular basis to allow for possible re-rankings based on estimate breeding values.

Adaptive Approximation-Based Regulation Control for a Class of Uncertain Nonlinear Systems Without Feedback Linearizability.

PubMed

Wang, Ning; Sun, Jing-Chao; Han, Min; Zheng, Zhongjiu; Er, Meng Joo

2017-09-06

In this paper, for a general class of uncertain nonlinear (cascade) systems, including unknown dynamics, which are not feedback linearizable and cannot be solved by existing approaches, an innovative adaptive approximation-based regulation control (AARC) scheme is developed. Within the framework of adding a power integrator (API), by deriving adaptive laws for output weights and prediction error compensation pertaining to single-hidden-layer feedforward network (SLFN) from the Lyapunov synthesis, a series of SLFN-based approximators are explicitly constructed to exactly dominate completely unknown dynamics. By the virtue of significant advancements on the API technique, an adaptive API methodology is eventually established in combination with SLFN-based adaptive approximators, and it contributes to a recursive mechanism for the AARC scheme. As a consequence, the output regulation error can asymptotically converge to the origin, and all other signals of the closed-loop system are uniformly ultimately bounded. Simulation studies and comprehensive comparisons with backstepping- and API-based approaches demonstrate that the proposed AARC scheme achieves remarkable performance and superiority in dealing with unknown dynamics.

Voting contagion: Modeling and analysis of a century of U.S. presidential elections

PubMed Central

de Aguiar, Marcus A. M.

2017-01-01

Social influence plays an important role in human behavior and decisions. Sources of influence can be divided as external, which are independent of social context, or as originating from peers, such as family and friends. An important question is how to disentangle the social contagion by peers from external influences. While a variety of experimental and observational studies provided insight into this problem, identifying the extent of contagion based on large-scale observational data with an unknown network structure remains largely unexplored. By bridging the gap between the large-scale complex systems perspective of collective human dynamics and the detailed approach of social sciences, we present a parsimonious model of social influence, and apply it to a central topic in political science—elections and voting behavior. We provide an analytical expression of the county vote-share distribution, which is in excellent agreement with almost a century of observed U.S. presidential election data. Analyzing the social influence topography over this period reveals an abrupt phase transition from low to high levels of social contagion, and robust differences among regions. These results suggest that social contagion effects are becoming more instrumental in shaping large-scale collective political behavior, with implications on democratic electoral processes and policies. PMID:28542409

Drought Rapidly Diminishes the Large Net CO2 Uptake in 2011 Over Semi-Arid Australia

NASA Technical Reports Server (NTRS)

Ma, Xuanlong; Huete, Alfredo; Cleverly, James; Eamus, Derek; Chevallier, Frederic; Joiner, Joanna; Poulter, Benjamin; Zhang, Yongguang; Guanter, Luis; Meyer, Wayne;

Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia

NASA Astrophysics Data System (ADS)

Ma, Xuanlong; Huete, Alfredo; Cleverly, James; Eamus, Derek; Chevallier, Frédéric; Joiner, Joanna; Poulter, Benjamin; Zhang, Yongguang; Guanter, Luis; Meyer, Wayne; Xie, Zunyi; Ponce-Campos, Guillermo

2016-11-01

Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO2 and photosynthesis and in-situ flux tower measures. We show the 2010-11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010-11 net CO2 uptake was highly transient with rapid dissipation through drought. The size of the 2010-11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011-12, and was nearly eliminated in 2012-13 (0.08 Pg). We further report evidence of an earlier 2000-01 large net CO2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle.

Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia.

PubMed

Ma, Xuanlong; Huete, Alfredo; Cleverly, James; Eamus, Derek; Chevallier, Frédéric; Joiner, Joanna; Poulter, Benjamin; Zhang, Yongguang; Guanter, Luis; Meyer, Wayne; Xie, Zunyi; Ponce-Campos, Guillermo

2016-11-25

Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO 2 and photosynthesis and in-situ flux tower measures. We show the 2010-11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010-11 net CO 2 uptake was highly transient with rapid dissipation through drought. The size of the 2010-11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011-12, and was nearly eliminated in 2012-13 (0.08 Pg). We further report evidence of an earlier 2000-01 large net CO 2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle.

Pathophysiology of gadolinium-associated systemic fibrosis

PubMed Central

Drel, Viktor; Gorin, Yves

2016-01-01

Systemic fibrosis from gadolinium-based magnetic resonance imaging contrast is a scourge for the afflicted. Although gadolinium-associated systemic fibrosis is a rare condition, the threat of litigation has vastly altered clinical practice. Most theories concerning the etiology of the fibrosis are grounded in case reports rather than experiment. This has led to the widely accepted conjecture that the relative affinity of certain contrast agents for the gadolinium ion inversely correlates with the risk of succumbing to the disease. How gadolinium-containing contrast agents trigger widespread and site-specific systemic fibrosis and how chronicity is maintained are largely unknown. This review highlights experimentally-derived information from our laboratory and others that pertain to our understanding of the pathophysiology of gadolinium-associated systemic fibrosis. PMID:27147669

The outcomes of complementary and alternative medicine use among pregnant and birthing women: current trends and future directions.

PubMed

Steel, Amie; Adams, Jon; Sibbritt, David; Broom, Alex

2015-06-01

Complementary and alternative medicine is used by a substantial number of pregnant women and maternity care providers are often faced with the task of ensuring women are using safe and effective treatments while respecting a woman's right to autonomous decision-making. In the era of evidence-based medicine maternity health professionals are expected to draw upon the best available evidence when making clinical decisions and providing health advice. This review will outline the current trends in research evidence associated with the outcomes of complementary and alternative medicine use amongst pregnant and birthing women as well as highlight some potential directions for future development in this important yet largely unknown topic in contemporary maternity care.

Autoimmune encephalitis associated with vitiligo?

PubMed

Haitao, Ren; Huiqin, Liu; Tao, Qu; Xunzhe, Yang; Xiaoqiu, Shao; Wei, Li; Jiewen, Zhang; Liying, Cui; Hongzhi, Guan

2017-09-15

The autoimmune encephalitis can develop with or without an underlying tumor. For tumor-negative autoimmune encephalitis, the causes are still largely unknown. Here we presented three patients with autoimmune encephalitis accompanied with vitiligo. Among them, two patients suffered from anti-leucine-rich glioma-inactivated 1 (LGI1) encephalitis and one patient suffered from anti-IgLON5 encephalopathy. All of them received intravenous immunoglobulin and steroids as immunotherapy. The two patients with anti-LGI1 encephalitis recovered and got a good prognosis. For the patient with anti-IgLON5 encephalopathy, he only got a moderate and transient improvement. Based on the above, we speculate that vitiligo may be a clue to an autoimmune cause for encephalitis. Copyright © 2017. Published by Elsevier B.V.

Toward an architecture of attachment disorganization: John Bowlby's published and unpublished reflections.

PubMed

Solomon, Judith; Duschinsky, Robbie; Bakkum, Lianne; Schuengel, Carlo

2017-10-01

This article examines the construct of disorganized attachment originally proposed by Main and Solomon, developing some new conjectures based on inspiration from a largely unknown source: John Bowlby's unpublished texts, housed at the Wellcome Trust Library Archive in London (with permission from the Bowlby family). We explore Bowlby's discussions of disorganized attachment, which he understood from the perspective of ethological theories of conflict behavior. Bowlby's reflections regarding differences among the behaviors used to code disorganized attachment will be used to explore distinctions that may underlie the structure of the current coding system. The article closes with an emphasis on the importance Bowlby placed on Popper's distinction between the context of discovery and the context of justification in developmental science.

Regulation of behavioral plasticity by systemic temperature signaling in Caenorhabditis elegans.

PubMed

Sugi, Takuma; Nishida, Yukuo; Mori, Ikue

2011-06-26

Animals cope with environmental changes by altering behavioral strategy. Environmental information is generally received by sensory neurons in the neural circuit that generates behavior. However, although environmental temperature inevitably influences an animal's entire body, the mechanism of systemic temperature perception remains largely unknown. We show here that systemic temperature signaling induces a change in a memory-based behavior in C. elegans. During behavioral conditioning, non-neuronal cells as well as neuronal cells respond to cultivation temperature through a heat-shock transcription factor that drives newly identified gene expression dynamics. This systemic temperature signaling regulates thermosensory neurons non-cell-autonomously through the estrogen signaling pathway, producing thermotactic behavior. We provide a link between systemic environmental recognition and behavioral plasticity in the nervous system.

The three-dimensional structure of "Lonely Guy" from Claviceps purpurea provides insights into the phosphoribohydrolase function of Rossmann fold-containing lysine decarboxylase-like proteins.

PubMed

Dzurová, Lenka; Forneris, Federico; Savino, Simone; Galuszka, Petr; Vrabka, Josef; Frébort, Ivo

2015-08-01

The recently discovered cytokinin (CK)-specific phosphoribohydrolase "Lonely Guy" (LOG) is a key enzyme of CK biosynthesis, converting inactive CK nucleotides into biologically active free bases. We have determined the crystal structures of LOG from Claviceps purpurea (cpLOG) and its complex with the enzymatic product phosphoribose. The structures reveal a dimeric arrangement of Rossmann folds, with the ligands bound to large pockets at the interface between cpLOG monomers. Structural comparisons highlight the homology of cpLOG to putative lysine decarboxylases. Extended sequence analysis enabled identification of a distinguishing LOG sequence signature. Taken together, our data suggest phosphoribohydrolase activity for several proteins of unknown function. © 2015 Wiley Periodicals, Inc.

Material Characterization for the Analysis of Skin/Stiffener Separation

NASA Technical Reports Server (NTRS)

Davila, Carlos G.; Leone, Frank A.; Song, Kyongchan; Ratcliffe, James G.; Rose, Cheryl A.

2017-01-01

Test results show that separation failure in co-cured skin/stiffener interfaces is characterized by dense networks of interacting cracks and crack path migrations that are not present in standard characterization tests for delamination. These crack networks result in measurable large-scale and sub-ply-scale R curve toughening mechanisms, such as fiber bridging, crack migration, and crack delving. Consequently, a number of unknown issues exist regarding the level of analysis detail that is required for sufficient predictive fidelity. The objective of the present paper is to examine some of the difficulties associated with modeling separation failure in stiffened composite structures. A procedure to characterize the interfacial material properties is proposed and the use of simplified models based on empirical interface properties is evaluated.

Combining gait optimization with passive system to increase the energy efficiency of a humanoid robot walking movement

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

Pereira, Ana I.; ALGORITMI,University of Minho; Lima, José

There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The energy consumption can also be reduced with elastic elements coupled to each joint. The presented paper addresses an optimization method, the Stretched Simulated Annealing, that runs in an accurate and stable simulation model to find the optimal gait combined with elastic elements. Finalmore » results demonstrate that optimization is a valid gait planning technique.« less

Genetic causes of male infertility.

PubMed

Stouffs, Katrien; Seneca, Sara; Lissens, Willy

2014-05-01

Male infertility, affecting around half of the couples with a problem to get pregnant, is a very heterogeneous condition. Part of patients are having a defect in spermatogenesis of which the underlying causes (including genetic ones) remain largely unknown. The only genetic tests routinely used in the diagnosis of male infertility are the analyses for the presence of Yq microdeletions and/or chromosomal abnormalities. Various other single gene or polygenic defects have been proposed to be involved in male fertility. Yet, their causative effect often remains to be proven. The recent evolution in the development of whole genome-based techniques may help in clarifying the role of genes and other genetic factors involved in spermatogenesis and spermatogenesis defects. Copyright © 2014 Elsevier Masson SAS. All rights reserved.

Construction and screening of marine metagenomic libraries.

PubMed

Weiland, Nancy; Löscher, Carolin; Metzger, Rebekka; Schmitz, Ruth

2010-01-01

Marine microbial communities are highly diverse and have evolved during extended evolutionary processes of physiological adaptations under the influence of a variety of ecological conditions and selection pressures. They harbor an enormous diversity of microbes with still unknown and probably new physiological characteristics. Besides, the surfaces of marine multicellular organisms are typically covered by a consortium of epibiotic bacteria and act as barriers, where diverse interactions between microorganisms and hosts take place. Thus, microbial diversity in the water column of the oceans and the microbial consortia on marine tissues of multicellular organisms are rich sources for isolating novel bioactive compounds and genes. Here we describe the sampling, construction of large-insert metagenomic libraries from marine habitats and exemplarily one function based screen of metagenomic clones.

US Intergroup Anal Carcinoma Trial: Tumor Diameter Predicts for Colostomy

PubMed Central

Ajani, Jaffer A.; Winter, Kathryn A.; Gunderson, Leonard L.; Pedersen, John; Benson, Al B.; Thomas, Charles R.; Mayer, Robert J.; Haddock, Michael G.; Rich, Tyvin A.; Willett, Christopher G.

2009-01-01

Purpose The US Gastrointestinal Intergroup Radiation Therapy Oncology Group 98-11 anal carcinoma trial showed that cisplatin-based concurrent chemoradiotherapy resulted in a significantly higher rate of colostomy compared with mitomycin-based therapy. Established prognostic variables for patients with anal carcinoma include tumor diameter, clinical nodal status, and sex, but pretreatment variables that would predict the likelihood of colostomy are unknown. Methods A secondary analysis was performed by combining patients in the two treatment arms to evaluate whether new predictive and prognostic variables would emerge. Univariate and multivariate analyses were carried out to correlate overall survival (OS), disease-free survival, and time to colostomy (TTC) with pretreatment and treatment variables. Results Of 682 patients enrolled, 644 patients were assessable and analyzed. In the multivariate analysis, tumor-related prognosticators for poorer OS included node-positive cancer (P ≤ .0001), large (> 5 cm) tumor diameter (P = .01), and male sex (P = .016). In the treatment-related categories, cisplatin-based therapy was statistically significantly associated with a higher rate of colostomy (P = .03) than was mitomycin-based therapy. In the pretreatment variables category, only large tumor diameter independently predicted for TTC (P = .008). Similarly, the cumulative 5-year colostomy rate was statistically significantly higher for large tumor diameter than for small tumor diameter (Gray's test; P = .0074). Clinical nodal status and sex were not predictive of TTC. Conclusion The combined analysis of the two arms of RTOG 98-11, representing the largest prospective database, reveals that tumor diameter (irrespective of the nodal status) is the only independent pretreatment variable that predicts TTC and 5-year colostomy rate in patients with anal carcinoma. PMID:19139424

An imperative need for global change research in tropical forests.

PubMed

Zhou, Xuhui; Fu, Yuling; Zhou, Lingyan; Li, Bo; Luo, Yiqi

2013-09-01

Tropical forests play a crucial role in regulating regional and global climate dynamics, and model projections suggest that rapid climate change may result in forest dieback or savannization. However, these predictions are largely based on results from leaf-level studies. How tropical forests respond and feedback to climate change is largely unknown at the ecosystem level. Several complementary approaches have been used to evaluate the effects of climate change on tropical forests, but the results are conflicting, largely due to confounding effects of multiple factors. Although altered precipitation and nitrogen deposition experiments have been conducted in tropical forests, large-scale warming and elevated carbon dioxide (CO2) manipulations are completely lacking, leaving many hypotheses and model predictions untested. Ecosystem-scale experiments to manipulate temperature and CO2 concentration individually or in combination are thus urgently needed to examine their main and interactive effects on tropical forests. Such experiments will provide indispensable data and help gain essential knowledge on biogeochemical, hydrological and biophysical responses and feedbacks of tropical forests to climate change. These datasets can also inform regional and global models for predicting future states of tropical forests and climate systems. The success of such large-scale experiments in natural tropical forests will require an international framework to coordinate collaboration so as to meet the challenges in cost, technological infrastructure and scientific endeavor.

Clinic Network Collaboration and Patient Tracing to Maximize Retention in HIV Care.

PubMed

McMahon, James H; Moore, Richard; Eu, Beng; Tee, Ban-Kiem; Chen, Marcus; El-Hayek, Carol; Street, Alan; Woolley, Ian; Buggie, Andrew; Collins, Danielle; Medland, Nicholas; Hoy, Jennifer

2015-01-01

Understanding retention and loss to follow up in HIV care, in particular the number of people with unknown outcomes, is critical to maximise the benefits of antiretroviral therapy. Individual-level data are not available for these outcomes in Australia, which has an HIV epidemic predominantly focused amongst men who have sex with men. A network of the 6 main HIV clinical care sites was established in the state of Victoria, Australia. Individuals who had accessed care at these sites between February 2011 and June 2013 as assessed by HIV viral load testing but not accessed care between June 2013 and February 2014 were considered individuals with potentially unknown outcomes. For this group an intervention combining cross-referencing of clinical data between sites and phone tracing individuals with unknown outcomes was performed. 4966 people were in care in the network and before the intervention estimates of retention ranged from 85.9%-95.8% and the proportion with unknown outcomes ranged from 1.3-5.5%. After the intervention retention increased to 91.4-98.8% and unknown outcomes decreased to 0.1-2.4% (p<.01 for all sites for both outcomes). Most common reasons for disengagement from care were being too busy to attend or feeling well. For those with unknown outcomes prior to the intervention documented active psychiatric illness at last visit was associated with not re-entering care (p = 0.04). The network demonstrated low numbers of people with unknown outcomes and high levels of retention in care. Increased levels of retention in care and reductions in unknown outcomes identified after the intervention largely reflected confirmation of clinic transfers while a smaller number were successfully re-engaged in care. Factors associated with disengagement from care were identified. Systems to monitor patient retention, care transfer and minimize disengagement will maximise individual and population-level outcomes for populations with HIV.

A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

PubMed

Tsai, Jason S-H; Hsu, Wen-Teng; Lin, Long-Guei; Guo, Shu-Mei; Tann, Joseph W

2014-01-01

A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states. Besides, an effective state space self-turner with fault tolerance scheme is presented for the unknown multivariable stochastic system. A quantitative criterion is suggested by comparing the innovation process error estimated by the Kalman filter estimation algorithm, so that a weighting matrix resetting technique by adjusting and resetting the covariance matrices of parameter estimate obtained by the Kalman filter estimation algorithm is utilized to achieve the parameter estimation for faulty system recovery. Consequently, the proposed method can effectively cope with partially abrupt and/or gradual system faults and input failures by the fault detection. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Transcriptome profiling analysis of cultivar-specific apple fruit ripening and texture attributes

USDA-ARS?s Scientific Manuscript database

Molecular events regulating cultivar-specific apple fruit ripening and sensory quality are largely unknown. Such knowledge is essential for genomic-assisted apple breeding and postharvest quality management. In this study, transcriptome profile analysis, scanning electron microscopic examination an...

Habitat filters in fungal endophyte community assembly

USDA-ARS?s Scientific Manuscript database

Fungal endophytes can influence host health, and more broadly, can instigate trophic cascades with effects scaling to the ecosystem level. Despite this, biotic mechanisms of endophyte community assembly are largely unknown. We used maize to investigate three potential habitat filters in endophyte co...

Suppression of NADPH oxidases prevents chronic ethanol-induced bone loss

USDA-ARS?s Scientific Manuscript database

Since the molecular mechanisms through which chronic excessive alcohol consumption induces osteopenia and osteoporosis are largely unknown, potential treatments for prevention of alcohol-induced bone loss remain unclear. We have previously demonstrated that, chronic ethanol (EtOH) treatment leads to...

Spatial Distribution of Small Water Body Types across Indiana Ecoregions

EPA Science Inventory

Due to their large numbers and biogeochemical activity, small water bodies (SWB), such as ponds and wetlands, can have substantial cumulative effects on hydrologic, biogeochemical, and biological processes; yet the spatial distributions of various SWB types are often unknown. Usi...

Control of Chrysanthemum flowering through integration with an aging pathway

USDA-ARS?s Scientific Manuscript database

Age, as a threshold of floral competence acquisition, prevents precocious flowering when there is insufficient biomass, and ensures flowering independent of environmental conditions; however, the underlying regulatory mechanisms are largely unknown. In this study, silencing the expression of a nucle...

Exploring links between greenspace and sudden unexpected death: a spatial analysis

EPA Science Inventory

Greenspace has been increasingly recognized as having numerous health benefits. However, its effects are unknown concerning sudden unexpected death (SUD), commonly referred to as sudden cardiac death, which constitutes a large proportion of mortality in the United States. Because...

Approach for establishing approximate load carrying capacity for bridges with unknown material and unknown design properties.

DOT National Transportation Integrated Search

2011-07-01

There are 16 small to medium simple span bridges in Larimer County, Colorado that are currently load rated solely based on visual inspections. Most of these bridges are prestressed concrete bridges. The objective of this project is to load rate these...

383. F.A.N., Delineator Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

383. F.A.N., Delineator Date Unknown STATE OF CALIFORNIA; DEPARTMENT OF PUBLIC WORKS; SAN FRANCISCO - OAKLAND BAY BRIDGE; WEST BAY CROSSING; TOWERS; TYPICAL BASE DETAILS; DRG. NO. 29 - San Francisco Oakland Bay Bridge, Spanning San Francisco Bay, San Francisco, San Francisco County, CA

Unique growth strategy in the Earth's first trees revealed in silicified fossil trunks from China.

PubMed

Xu, Hong-He; Berry, Christopher M; Stein, William E; Wang, Yi; Tang, Peng; Fu, Qiang

2017-11-07

Cladoxylopsida included the earliest large trees that formed critical components of globally transformative pioneering forest ecosystems in the Mid- and early Late Devonian (ca. 393-372 Ma). Well-known cladoxylopsid fossils include the up to ∼1-m-diameter sandstone casts known as Eospermatopteris from Middle Devonian strata of New York State. Cladoxylopsid trunk structure comprised a more-or-less distinct cylinder of numerous separate cauline xylem strands connected internally with a network of medullary xylem strands and, near the base, externally with downward-growing roots, all embedded within parenchyma. However, the means by which this complex vascular system was able to grow to a large diameter is unknown. We demonstrate-based on exceptional, up to ∼70-cm-diameter silicified fossil trunks with extensive preservation of cellular anatomy from the early Late Devonian (Frasnian, ca. 374 Ma) of Xinjiang, China-that trunk expansion is associated with a cylindrical zone of diffuse secondary growth within ground and cortical parenchyma and with production of a large amount of wood containing both rays and growth increments concentrically around individual xylem strands by normal cambia. The xylem system accommodates expansion by tearing of individual strand interconnections during secondary development. This mode of growth seems indeterminate, capable of producing trees of large size and, despite some unique features, invites comparison with secondary development in some living monocots. Understanding the structure and growth of cladoxylopsids informs analysis of canopy competition within early forests with the potential to drive global processes. Published under the PNAS license.

Transcriptional analysis of product-concentration driven changes in cellular programs of recombinant Clostridium acetobutylicumstrains.

PubMed

Tummala, Seshu B; Junne, Stefan G; Paredes, Carlos J; Papoutsakis, Eleftherios T

2003-12-30

Antisense RNA (asRNA) downregulation alters protein expression without changing the regulation of gene expression. Downregulation of primary metabolic enzymes possibly combined with overexpression of other metabolic enzymes may result in profound changes in product formation, and this may alter the large-scale transcriptional program of the cells. DNA-array based large-scale transcriptional analysis has the potential to elucidate factors that control cellular fluxes even in the absence of proteome data. These themes are explored in the study of large-scale transcriptional analysis programs and the in vivo primary-metabolism fluxes of several related recombinant C. acetobutylicum strains: C. acetobutylicum ATCC 824(pSOS95del) (plasmid control; produces high levels of butanol snd acetone), 824(pCTFB1AS) (expresses antisense RNA against CoA transferase (ctfb1-asRNA); produces very low levels of butanol and acetone), and 824(pAADB1) (expresses ctfb1-asRNA and the alcohol-aldehyde dahydrogenase gene (aad); produce high alcohol and low acetone levels). DNA-array based transcriptional analysis revealed that the large changes in product concentrations (snd notably butanol concentration) due to ctfb1-asRNA expression alone and in combination with aad overexpression resulted in dramatic changes of the cellular transcriptome. Cluster analysis and gene expression patterns of established and putative operons involved in stress response, motility, sporulation, and fatty-acid biosynthesis indicate that these simple genetic changes dramatically alter the cellular programs of C. acetobutylicum. Comparison of gene expression and flux analysis data may point to possible flux-controling steps and suggest unknown regulatory mechanisms. Copyright 2003; Wiley Periodicals, Inc.

Hybrid estimation of complex systems.

PubMed

Hofbaur, Michael W; Williams, Brian C

2004-10-01

Modern automated systems evolve both continuously and discretely, and hence require estimation techniques that go well beyond the capability of a typical Kalman Filter. Multiple model (MM) estimation schemes track these system evolutions by applying a bank of filters, one for each discrete system mode. Modern systems, however, are often composed of many interconnected components that exhibit rich behaviors, due to complex, system-wide interactions. Modeling these systems leads to complex stochastic hybrid models that capture the large number of operational and failure modes. This large number of modes makes a typical MM estimation approach infeasible for online estimation. This paper analyzes the shortcomings of MM estimation, and then introduces an alternative hybrid estimation scheme that can efficiently estimate complex systems with large number of modes. It utilizes search techniques from the toolkit of model-based reasoning in order to focus the estimation on the set of most likely modes, without missing symptoms that might be hidden amongst the system noise. In addition, we present a novel approach to hybrid estimation in the presence of unknown behavioral modes. This leads to an overall hybrid estimation scheme for complex systems that robustly copes with unforeseen situations in a degraded, but fail-safe manner.

Animal water balance drives top-down effects in a riparian forest—implications for terrestrial trophic cascades

PubMed Central

Sabo, John L.

2016-01-01

Despite the clear importance of water balance to the evolution of terrestrial life, much remains unknown about the effects of animal water balance on food webs. Based on recent research suggesting animal water imbalance can increase trophic interaction strengths in cages, we hypothesized that water availability could drive top-down effects in open environments, influencing the occurrence of trophic cascades. We manipulated large spider abundance and water availability in 20 × 20 m open-air plots in a streamside forest in Arizona, USA, and measured changes in cricket and small spider abundance and leaf damage. As expected, large spiders reduced both cricket abundance and herbivory under ambient, dry conditions, but not where free water was added. When water was added (free or within moist leaves), cricket abundance was unaffected by large spiders, but spiders still altered herbivory, suggesting behavioural effects. Moreover, we found threshold-type increases in herbivory at moderately low soil moisture (between 5.5% and 7% by volume), suggesting the possibility that water balance may commonly influence top-down effects. Overall, our results point towards animal water balance as an important driver of direct and indirect species interactions and food web dynamics in terrestrial ecosystems. PMID:27534953

Rate/state Coulomb stress transfer model for the CSEP Japan seismicity forecast

NASA Astrophysics Data System (ADS)

Toda, Shinji; Enescu, Bogdan

2011-03-01

Numerous studies retrospectively found that seismicity rate jumps (drops) by coseismic Coulomb stress increase (decrease). The Collaboratory for the Study of Earthquake Prediction (CSEP) instead provides us an opportunity for prospective testing of the Coulomb hypothesis. Here we adapt our stress transfer model incorporating rate and state dependent friction law to the CSEP Japan seismicity forecast. We demonstrate how to compute the forecast rates of large shocks in 2009 using the large earthquakes during the past 120 years. The time dependent impact of the coseismic stress perturbations explains qualitatively well the occurrence of the recent moderate size shocks. Such ability is partly similar to that of statistical earthquake clustering models. However, our model differs from them as follows: the off-fault aftershock zones can be simulated using finite fault sources; the regional areal patterns of triggered seismicity are modified by the dominant mechanisms of the potential sources; the imparted stresses due to large earthquakes produce stress shadows that lead to a reduction of the forecasted number of earthquakes. Although the model relies on several unknown parameters, it is the first physics based model submitted to the CSEP Japan test center and has the potential to be tuned for short-term earthquake forecasts.

Laterodorsal nucleus of the thalamus: A processor of somatosensory inputs.

PubMed

Bezdudnaya, Tatiana; Keller, Asaf

2008-04-20

The laterodorsal (LD) nucleus of the thalamus has been considered a "higher order" nucleus that provides inputs to limbic cortical areas. Although its functions are largely unknown, it is often considered to be involved in spatial learning and memory. Here we provide evidence that LD is part of a hitherto unknown pathway for processing somatosensory information. Juxtacellular and extracellular recordings from LD neurons reveal that they respond to vibrissa stimulation with short latency (median = 7 ms) and large magnitude responses (median = 1.2 spikes/stimulus). Most neurons (62%) had large receptive fields, responding to six and more individual vibrissae. Electrical stimulation of the trigeminal nucleus interpolaris (SpVi) evoked short latency responses (median = 3.8 ms) in vibrissa-responsive LD neurons. Labeling produced by anterograde and retrograde neuroanatomical tracers confirmed that LD neurons receive direct inputs from SpVi. Electrophysiological and neuroanatomical analyses revealed also that LD projects upon the cingulate and retrosplenial cortex, but has only sparse projections to the barrel cortex. These findings suggest that LD is part of a novel processing stream involved in spatial orientation and learning related to somatosensory cues. (c) 2008 Wiley-Liss, Inc.

Prioritizing Genes Related to Nicotine Addiction Via a Multi-source-Based Approach.

PubMed

Liu, Xinhua; Liu, Meng; Li, Xia; Zhang, Lihua; Fan, Rui; Wang, Ju

2015-08-01

Nicotine has a broad impact on both the central and peripheral nervous systems. Over the past decades, an increasing number of genes potentially involved in nicotine addiction have been identified by different technical approaches. However, the molecular mechanisms underlying nicotine addiction remain largely unknown. Under such situation, prioritizing the candidate genes for further investigation is becoming increasingly important. In this study, we presented a multi-source-based gene prioritization approach for nicotine addiction by utilizing the vast amounts of information generated from for nicotine addiction study during the past years. In this approach, we first collected and curated genes from studies in four categories, i.e., genetic association analysis, genetic linkage analysis, high-throughput gene/protein expression analysis, and literature search of single gene/protein-based studies. Based on these resources, the genes were scored and a weight value was determined for each category. Finally, the genes were ranked by their combined scores, and 220 genes were selected as the prioritized nicotine addiction-related genes. Evaluation suggested the prioritized genes were promising targets for further analysis and replication study.

Antiferroic electronic structure in the nonmagnetic superconducting state of the iron-based superconductors

PubMed Central

Shimojima, Takahiro; Malaeb, Walid; Nakamura, Asuka; Kondo, Takeshi; Kihou, Kunihiro; Lee, Chul-Ho; Iyo, Akira; Eisaki, Hiroshi; Ishida, Shigeyuki; Nakajima, Masamichi; Uchida, Shin-ichi; Ohgushi, Kenya; Ishizaka, Kyoko; Shin, Shik

2017-01-01

A major problem in the field of high-transition temperature (Tc) superconductivity is the identification of the electronic instabilities near superconductivity. It is known that the iron-based superconductors exhibit antiferromagnetic order, which competes with the superconductivity. However, in the nonmagnetic state, there are many aspects of the electronic instabilities that remain unclarified, as represented by the orbital instability and several in-plane anisotropic physical properties. We report a new aspect of the electronic state of the optimally doped iron-based superconductors by using high–energy resolution angle-resolved photoemission spectroscopy. We find spectral evidence for the folded electronic structure suggestive of an antiferroic electronic instability, coexisting with the superconductivity in the nonmagnetic state of Ba1−xKxFe2As2. We further establish a phase diagram showing that the antiferroic electronic structure persists in a large portion of the nonmagnetic phase covering the superconducting dome. These results motivate consideration of a key unknown electronic instability, which is necessary for the achievement of high-Tc superconductivity in the iron-based superconductors. PMID:28875162

Antiferroic electronic structure in the nonmagnetic superconducting state of the iron-based superconductors.

PubMed

Shimojima, Takahiro; Malaeb, Walid; Nakamura, Asuka; Kondo, Takeshi; Kihou, Kunihiro; Lee, Chul-Ho; Iyo, Akira; Eisaki, Hiroshi; Ishida, Shigeyuki; Nakajima, Masamichi; Uchida, Shin-Ichi; Ohgushi, Kenya; Ishizaka, Kyoko; Shin, Shik

2017-08-01

A major problem in the field of high-transition temperature ( T c ) superconductivity is the identification of the electronic instabilities near superconductivity. It is known that the iron-based superconductors exhibit antiferromagnetic order, which competes with the superconductivity. However, in the nonmagnetic state, there are many aspects of the electronic instabilities that remain unclarified, as represented by the orbital instability and several in-plane anisotropic physical properties. We report a new aspect of the electronic state of the optimally doped iron-based superconductors by using high-energy resolution angle-resolved photoemission spectroscopy. We find spectral evidence for the folded electronic structure suggestive of an antiferroic electronic instability, coexisting with the superconductivity in the nonmagnetic state of Ba 1- x K x Fe 2 As 2 . We further establish a phase diagram showing that the antiferroic electronic structure persists in a large portion of the nonmagnetic phase covering the superconducting dome. These results motivate consideration of a key unknown electronic instability, which is necessary for the achievement of high- T c superconductivity in the iron-based superconductors.

Opportunistic pathology-based screening for diabetes

PubMed Central

Simpson, Aaron J; Krowka, Renata; Kerrigan, Jennifer L; Southcott, Emma K; Wilson, J Dennis; Potter, Julia M; Nolan, Christopher J; Hickman, Peter E

2013-01-01

Objective To determine the potential of opportunistic glycated haemoglobin (HbA1c) testing of pathology samples to detect previously unknown diabetes. Design Pathology samples from participants collected for other reasons and suitable for HbA1c testing were utilised for opportunistic diabetes screening. HbA1c was measured with a Biorad Variant II turbo analyser and HbA1c levels of ≥6.5% (48 mmol/mol) were considered diagnostic for diabetes. Confirmation of previously unknown diabetes status was obtained by a review of hospital medical records and phone calls to general practitioners. Setting Hospital pathology laboratory receiving samples from hospital-based and community-based (CB) settings. Participants Participants were identified based on the blood sample collection location in the CB, emergency department (ED) and inpatient (IP) groups. Exclusions pretesting were made based on the electronic patient history of: age <18 years, previous diabetes diagnosis, query for diabetes status in the past 12 months, evidence of pregnancy and sample collected postsurgery or transfusion. Only one sample per individual participant was tested. Results Of the 22 396 blood samples collected, 4505 (1142 CB, 1113 ED, 2250 IP) were tested of which 327 (7.3%) had HbA1c levels ≥6.5% (48 mmol/mol). Of these 120 (2.7%) were determined to have previously unknown diabetes (11 (1%) CB, 21 (1.9%) ED, 88 (3.9%) IP). The prevalence of previously unknown diabetes was substantially higher (5.4%) in hospital-based (ED and IP) participants aged over 54 years. Conclusions Opportunistic testing of referred pathology samples can be an effective method of screening for diabetes, especially in hospital-based and older persons. PMID:24065696

A sting from an unknown jellyfish species associated with persistent symptoms and raised troponin I levels.

PubMed

McD Taylor, David; Pereira, Peter; Seymour, Jamie; Winkel, Kenneth D

2002-06-01

We describe a patient stung by an unknown jellyfish species offshore in Far North Queensland. The sting caused immediate and severe pain, multiple whip-like skin lesions and constitutional symptoms. The jellyfish tentacular nematocysyts were similar to, but distinct from, those of Carukia barnesi, a cause of the 'Irukandji' syndrome. The patients symptoms largely resolved over seven months and were associated with elevated cardiac troponin levels, in the absence of other evidence of cardiac disease. This case highlights the envenomation risks associated with marine recreation, and the need for critical evaluation of cardiac troponin assays and for further research in marine toxicology.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

Searching for ultra high energy neutrinos from space

NASA Astrophysics Data System (ADS)

Santangelo, A.

2006-07-01

Observations of neutrinos at Ultra High Energies (UHE), from a few 1018 eV to beyond the decade of 1020 eV, are an extraordinary opportunity to explore this still largely unknown Universe and present us a tremendous experimental challenge. It is indeed expected that observations of UHEνs (and cosmic rays) will provide entirely new information on the sources and on the physical mechanisms able to accelerate these extreme messengers to macroscopic energies. However, as extensively debated in the last few years, UHE particles might, also, carry evidence of unknown physics or of exotic particles, relics of the early Universe. To reach these goals, high statistics, high quality observations are required. This implies innovative experiments with larger acceptances and good understanding of systematic uncertainties. The ground-based Pierre Auger Observatory, whose southern site is expected to be completed in Malargue, Argentina by the end of 2006, will surely provide, in the near future, a more solid observational scenario for UHE Cosmic Rays (UHECR). However, only space-based observatories can reach the effective area necessary to systematically explore the UHE universe. Space-based observatories are likely to be essential for neutrino observations at UHE. In fact only a few UHE neutrinos will be detected by the current planned observatories and only if the most promising estimates for fluxes applies. In the present paper, after summarizing the science rationale behind UHEν studies, we review the status of current experimental efforts, with the main emphasis on the actual generation of space-based observatories. We also briefly discuss the scientific goals, the requirements and the R&D of a “next-generation” space-based mission for UHE observations. The opening of the ESA “Cosmic Vision 2015 2025” long term plan provides, in the very near future, an unique opportunity to develop such a challenging and innovative observatory for UHE.

Sliding Mode Observer-Based Current Sensor Fault Reconstruction and Unknown Load Disturbance Estimation for PMSM Driven System

PubMed Central

Li, Xiangfei; Lin, Yuliang

2017-01-01

This paper proposes a new scheme of reconstructing current sensor faults and estimating unknown load disturbance for a permanent magnet synchronous motor (PMSM)-driven system. First, the original PMSM system is transformed into two subsystems; the first subsystem has unknown system load disturbances, which are unrelated to sensor faults, and the second subsystem has sensor faults, but is free from unknown load disturbances. Introducing a new state variable, the augmented subsystem that has sensor faults can be transformed into having actuator faults. Second, two sliding mode observers (SMOs) are designed: the unknown load disturbance is estimated by the first SMO in the subsystem, which has unknown load disturbance, and the sensor faults can be reconstructed using the second SMO in the augmented subsystem, which has sensor faults. The gains of the proposed SMOs and their stability analysis are developed via the solution of linear matrix inequality (LMI). Finally, the effectiveness of the proposed scheme was verified by simulations and experiments. The results demonstrate that the proposed scheme can reconstruct current sensor faults and estimate unknown load disturbance for the PMSM-driven system. PMID:29211017

NABS RESPONSE OF A MULTI-METRIC FISH BIOTIC INDEX TO SPECIES DECLINES

EPA Science Inventory

Multi-metric indices of biotic integrity (IBI) are commonly used to compare fish communities among streams, but ability to monitor trends within streams is largely unknown. We assessed the IBI trend detection ability using simulations which progressively degraded the fish assembl...

Transcriptomic analysis of apple fruit ripening and texture attributes

USDA-ARS?s Scientific Manuscript database

Molecular events regulating cultivar-specific apple fruit ripening and sensory quality are largely unknown. Such knowledge is essential for genomic-assisted apple breeding and postharvest quality management. The ripening behavior and texture attributes of two apple cultivars, ‘Pink Lady’ and ‘Honey...

Potential biological activities and bioavailability of alfrutamide and caffedymine

USDA-ARS?s Scientific Manuscript database

Alfrutamide and caffedymine are clovamide-type phenolic amides whose analogues are found in numerous plants including garlic and cocoa. However, potential health effects of the amides are largely unknown. For last ten years, several amides have been synthesized and their potential biological activi...

Optimization of high-throughput nanomaterial developmental toxicity testing in zebrafish embryos

EPA Science Inventory

Nanomaterial (NM) developmental toxicities are largely unknown. With an extensive variety of NMs available, high-throughput screening methods may be of value for initial characterization of potential hazard. We optimized a zebrafish embryo test as an in vivo high-throughput assay...

Genome-wide association studies of obesity and metabolic syndrome.

PubMed

Fall, Tove; Ingelsson, Erik

2014-01-25

Until just a few years ago, the genetic determinants of obesity and metabolic syndrome were largely unknown, with the exception of a few forms of monogenic extreme obesity. Since genome-wide association studies (GWAS) became available, large advances have been made. The first single nucleotide polymorphism robustly associated with increased body mass index (BMI) was in 2007 mapped to a gene with for the time unknown function. This gene, now known as fat mass and obesity associated (FTO) has been repeatedly replicated in several ethnicities and is affecting obesity by regulating appetite. Since the first report from a GWAS of obesity, an increasing number of markers have been shown to be associated with BMI, other measures of obesity or fat distribution and metabolic syndrome. This systematic review of obesity GWAS will summarize genome-wide significant findings for obesity and metabolic syndrome and briefly give a few suggestions of what is to be expected in the next few years. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Distributed weighted least-squares estimation with fast convergence for large-scale systems.

PubMed

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods.

Distributed weighted least-squares estimation with fast convergence for large-scale systems☆

PubMed Central

Marelli, Damián Edgardo; Fu, Minyue

2015-01-01

In this paper we study a distributed weighted least-squares estimation problem for a large-scale system consisting of a network of interconnected sub-systems. Each sub-system is concerned with a subset of the unknown parameters and has a measurement linear in the unknown parameters with additive noise. The distributed estimation task is for each sub-system to compute the globally optimal estimate of its own parameters using its own measurement and information shared with the network through neighborhood communication. We first provide a fully distributed iterative algorithm to asymptotically compute the global optimal estimate. The convergence rate of the algorithm will be maximized using a scaling parameter and a preconditioning method. This algorithm works for a general network. For a network without loops, we also provide a different iterative algorithm to compute the global optimal estimate which converges in a finite number of steps. We include numerical experiments to illustrate the performances of the proposed methods. PMID:25641976

A family of dynamic models for large-eddy simulation

NASA Technical Reports Server (NTRS)

Carati, D.; Jansen, K.; Lund, T.

1995-01-01

Since its first application, the dynamic procedure has been recognized as an effective means to compute rather than prescribe the unknown coefficients that appear in a subgrid-scale model for Large-Eddy Simulation (LES). The dynamic procedure is usually used to determine the nondimensional coefficient in the Smagorinsky (1963) model. In reality the procedure is quite general and it is not limited to the Smagorinsky model by any theoretical or practical constraints. The purpose of this note is to consider a generalized family of dynamic eddy viscosity models that do not necessarily rely on the local equilibrium assumption built into the Smagorinsky model. By invoking an inertial range assumption, it will be shown that the coefficients in the new models need not be nondimensional. This additional degree of freedom allows the use of models that are scaled on traditionally unknown quantities such as the dissipation rate. In certain cases, the dynamic models with dimensional coefficients are simpler to implement, and allow for a 30% reduction in the number of required filtering operations.

Ontology-Based Search of Genomic Metadata.

PubMed

Fernandez, Javier D; Lenzerini, Maurizio; Masseroli, Marco; Venco, Francesco; Ceri, Stefano

2016-01-01

The Encyclopedia of DNA Elements (ENCODE) is a huge and still expanding public repository of more than 4,000 experiments and 25,000 data files, assembled by a large international consortium since 2007; unknown biological knowledge can be extracted from these huge and largely unexplored data, leading to data-driven genomic, transcriptomic, and epigenomic discoveries. Yet, search of relevant datasets for knowledge discovery is limitedly supported: metadata describing ENCODE datasets are quite simple and incomplete, and not described by a coherent underlying ontology. Here, we show how to overcome this limitation, by adopting an ENCODE metadata searching approach which uses high-quality ontological knowledge and state-of-the-art indexing technologies. Specifically, we developed S.O.S. GeM (http://www.bioinformatics.deib.polimi.it/SOSGeM/), a system supporting effective semantic search and retrieval of ENCODE datasets. First, we constructed a Semantic Knowledge Base by starting with concepts extracted from ENCODE metadata, matched to and expanded on biomedical ontologies integrated in the well-established Unified Medical Language System. We prove that this inference method is sound and complete. Then, we leveraged the Semantic Knowledge Base to semantically search ENCODE data from arbitrary biologists' queries. This allows correctly finding more datasets than those extracted by a purely syntactic search, as supported by the other available systems. We empirically show the relevance of found datasets to the biologists' queries.

Hybrid fully nonlinear BEM-LBM numerical wave tank with applications in naval hydrodynamics

NASA Astrophysics Data System (ADS)

Mivehchi, Amin; Grilli, Stephan T.; Dahl, Jason M.; O'Reilly, Chris M.; Harris, Jeffrey C.; Kuznetsov, Konstantin; Janssen, Christian F.

2017-11-01

simulation of the complex dynamics response of ships in waves is typically modeled by nonlinear potential flow theory, usually solved with a higher order BEM. In some cases, the viscous/turbulent effects around a structure and in its wake need to be accurately modeled to capture the salient physics of the problem. Here, we present a fully 3D model based on a hybrid perturbation method. In this method, the velocity and pressure are decomposed as the sum of an inviscid flow and viscous perturbation. The inviscid part is solved over the whole domain using a BEM based on cubic spline element. These inviscid results are then used to force a near-field perturbation solution on a smaller domain size, which is solved with a NS model based on LBM-LES, and implemented on GPUs. The BEM solution for large grids is greatly accelerated by using a parallelized FMM, which is efficiently implemented on large and small clusters, yielding an almost linear scaling with the number of unknowns. A new representation of corners and edges is implemented, which improves the global accuracy of the BEM solver, particularly for moving boundaries. We present model results and the recent improvements of the BEM, alongside results of the hybrid model, for applications to problems. Office of Naval Research Grants N000141310687 and N000141612970.

Opportunities and Challenges for Payment Reform: Observations from Massachusetts.

PubMed

Mechanic, Robert E

2016-08-01

Policy makers and private health plans are expanding their efforts to implement new payment models that will encourage providers to improve quality and deliver health care more efficiently. Over the past five years, payment reforms have progressed faster in Massachusetts than in any other state. The reasons include a major effort by Blue Cross Blue Shield of Massachusetts to implement global payment, the presence of large integrated systems willing to take on financial risk, and a supportive state policy environment. By 2014, thirty-seven percent of Massachusetts's residents enrolled in health plans were covered under risk-based payment models tied to global budgets. But the expansion of payment reform in Massachusetts slowed between 2012 and 2015 because some commercial enrollment shifted from risk-based health maintenance organization products to fee-for-service preferred provider organization (PPO) plans, and the state Medicaid program fell short of its payment reform goals. Provider groups will not fully commit to population-based clinical models if they believe it will result in large reductions in fee-for-service revenue. The use of alternative payment models will accelerate in 2016 when Blue Cross begins implementing PPO payment reforms, but it is unknown how quickly other payers will follow. Massachusetts's experience illustrates the complexity of payment reform in pluralistic health care markets and the need for complementary efforts by public and private stakeholders. Copyright © 2016 by Duke University Press.

Evaluation of respondent-driven sampling.

PubMed

McCreesh, Nicky; Frost, Simon D W; Seeley, Janet; Katongole, Joseph; Tarsh, Matilda N; Ndunguse, Richard; Jichi, Fatima; Lunel, Natasha L; Maher, Dermot; Johnston, Lisa G; Sonnenberg, Pam; Copas, Andrew J; Hayes, Richard J; White, Richard G

2012-01-01

Respondent-driven sampling is a novel variant of link-tracing sampling for estimating the characteristics of hard-to-reach groups, such as HIV prevalence in sex workers. Despite its use by leading health organizations, the performance of this method in realistic situations is still largely unknown. We evaluated respondent-driven sampling by comparing estimates from a respondent-driven sampling survey with total population data. Total population data on age, tribe, religion, socioeconomic status, sexual activity, and HIV status were available on a population of 2402 male household heads from an open cohort in rural Uganda. A respondent-driven sampling (RDS) survey was carried out in this population, using current methods of sampling (RDS sample) and statistical inference (RDS estimates). Analyses were carried out for the full RDS sample and then repeated for the first 250 recruits (small sample). We recruited 927 household heads. Full and small RDS samples were largely representative of the total population, but both samples underrepresented men who were younger, of higher socioeconomic status, and with unknown sexual activity and HIV status. Respondent-driven sampling statistical inference methods failed to reduce these biases. Only 31%-37% (depending on method and sample size) of RDS estimates were closer to the true population proportions than the RDS sample proportions. Only 50%-74% of respondent-driven sampling bootstrap 95% confidence intervals included the population proportion. Respondent-driven sampling produced a generally representative sample of this well-connected nonhidden population. However, current respondent-driven sampling inference methods failed to reduce bias when it occurred. Whether the data required to remove bias and measure precision can be collected in a respondent-driven sampling survey is unresolved. Respondent-driven sampling should be regarded as a (potentially superior) form of convenience sampling method, and caution is required when interpreting findings based on the sampling method.

Sex Chromosome Evolution, Heterochiasmy, and Physiological QTL in the Salmonid Brook Charr Salvelinus fontinalis

PubMed Central

Sutherland, Ben J.G.; Rico, Ciro; Audet, Céline; Bernatchez, Louis

2017-01-01

Whole-genome duplication (WGD) can have large impacts on genome evolution, and much remains unknown about these impacts. This includes the mechanisms of coping with a duplicated sex determination system and whether this has an impact on increasing the diversity of sex determination mechanisms. Other impacts include sexual conflict, where alleles having different optimums in each sex can result in sequestration of genes into nonrecombining sex chromosomes. Sex chromosome development itself may involve sex-specific recombination rate (i.e., heterochiasmy), which is also poorly understood. The family Salmonidae is a model system for these phenomena, having undergone autotetraploidization and subsequent rediploidization in most of the genome at the base of the lineage. The salmonid master sex determining gene is known, and many species have nonhomologous sex chromosomes, putatively due to transposition of this gene. In this study, we identify the sex chromosome of Brook Charr Salvelinus fontinalis and compare sex chromosome identities across the lineage (eight species and four genera). Although nonhomology is frequent, homologous sex chromosomes and other consistencies are present in distantly related species, indicating probable convergence on specific sex and neo-sex chromosomes. We also characterize strong heterochiasmy with 2.7-fold more crossovers in maternal than paternal haplotypes with paternal crossovers biased to chromosome ends. When considering only rediploidized chromosomes, the overall heterochiasmy trend remains, although with only 1.9-fold more recombination in the female than the male. Y chromosome crossovers are restricted to a single end of the chromosome, and this chromosome contains a large interspecific inversion, although its status between males and females remains unknown. Finally, we identify quantitative trait loci (QTL) for 21 unique growth, reproductive, and stress-related phenotypes to improve knowledge of the genetic architecture of these traits important to aquaculture and evolution. PMID:28626004

Comparisons of two moments‐based estimators that utilize historical and paleoflood data for the log Pearson type III distribution

USGS Publications Warehouse

England, John F.; Salas, José D.; Jarrett, Robert D.

2003-01-01

The expected moments algorithm (EMA) [Cohn et al., 1997] and the Bulletin 17B [Interagency Committee on Water Data, 1982] historical weighting procedure (B17H) for the log Pearson type III distribution are compared by Monte Carlo computer simulation for cases in which historical and/or paleoflood data are available. The relative performance of the estimators was explored for three cases: fixed‐threshold exceedances, a fixed number of large floods, and floods generated from a different parent distribution. EMA can effectively incorporate four types of historical and paleoflood data: floods where the discharge is explicitly known, unknown discharges below a single threshold, floods with unknown discharge that exceed some level, and floods with discharges described in a range. The B17H estimator can utilize only the first two types of historical information. Including historical/paleoflood data in the simulation experiments significantly improved the quantile estimates in terms of mean square error and bias relative to using gage data alone. EMA performed significantly better than B17H in nearly all cases considered. B17H performed as well as EMA for estimating X100 in some limited fixed‐threshold exceedance cases. EMA performed comparatively much better in other fixed‐threshold situations, for the single large flood case, and in cases when estimating extreme floods equal to or greater than X500. B17H did not fully utilize historical information when the historical period exceeded 200 years. Robustness studies using GEV‐simulated data confirmed that EMA performed better than B17H. Overall, EMA is preferred to B17H when historical and paleoflood data are available for flood frequency analysis.

Comparisons of two moments-based estimators that utilize historical and paleoflood data for the log Pearson type III distribution

NASA Astrophysics Data System (ADS)

England, John F.; Salas, José D.; Jarrett, Robert D.

2003-09-01

The expected moments algorithm (EMA) [, 1997] and the Bulletin 17B [, 1982] historical weighting procedure (B17H) for the log Pearson type III distribution are compared by Monte Carlo computer simulation for cases in which historical and/or paleoflood data are available. The relative performance of the estimators was explored for three cases: fixed-threshold exceedances, a fixed number of large floods, and floods generated from a different parent distribution. EMA can effectively incorporate four types of historical and paleoflood data: floods where the discharge is explicitly known, unknown discharges below a single threshold, floods with unknown discharge that exceed some level, and floods with discharges described in a range. The B17H estimator can utilize only the first two types of historical information. Including historical/paleoflood data in the simulation experiments significantly improved the quantile estimates in terms of mean square error and bias relative to using gage data alone. EMA performed significantly better than B17H in nearly all cases considered. B17H performed as well as EMA for estimating X100 in some limited fixed-threshold exceedance cases. EMA performed comparatively much better in other fixed-threshold situations, for the single large flood case, and in cases when estimating extreme floods equal to or greater than X500. B17H did not fully utilize historical information when the historical period exceeded 200 years. Robustness studies using GEV-simulated data confirmed that EMA performed better than B17H. Overall, EMA is preferred to B17H when historical and paleoflood data are available for flood frequency analysis.

Machine intelligence-based decision-making (MIND) for automatic anomaly detection

NASA Astrophysics Data System (ADS)

Prasad, Nadipuram R.; King, Jason C.; Lu, Thomas

2007-04-01

Any event deemed as being out-of-the-ordinary may be called an anomaly. Anomalies by virtue of their definition are events that occur spontaneously with no prior indication of their existence or appearance. Effects of anomalies are typically unknown until they actually occur, and their effects aggregate in time to show noticeable change from the original behavior. An evolved behavior would in general be very difficult to correct unless the anomalous event that caused such behavior can be detected early, and any consequence attributed to the specific anomaly. Substantial time and effort is required to back-track the cause for abnormal behavior and to recreate the event sequence leading to abnormal behavior. There is a critical need therefore to automatically detect anomalous behavior as and when they may occur, and to do so with the operator in the loop. Human-machine interaction results in better machine learning and a better decision-support mechanism. This is the fundamental concept of intelligent control where machine learning is enhanced by interaction with human operators, and vice versa. The paper discusses a revolutionary framework for the characterization, detection, identification, learning, and modeling of anomalous behavior in observed phenomena arising from a large class of unknown and uncertain dynamical systems.

A metagenomic-based survey of microbial (de)halogenation potential in a German forest soil

PubMed Central

Weigold, Pascal; El-Hadidi, Mohamed; Ruecker, Alexander; Huson, Daniel H.; Scholten, Thomas; Jochmann, Maik; Kappler, Andreas; Behrens, Sebastian

2016-01-01

In soils halogens (fluorine, chlorine, bromine, iodine) are cycled through the transformation of inorganic halides into organohalogen compounds and vice versa. There is evidence that these reactions are microbially driven but the key enzymes and groups of microorganisms involved are largely unknown. Our aim was to uncover the diversity, abundance and distribution of genes encoding for halogenating and dehalogenating enzymes in a German forest soil by shotgun metagenomic sequencing. Metagenomic libraries of three soil horizons revealed the presence of genera known to be involved in halogenation and dehalogenation processes such as Bradyrhizobium or Pseudomonas. We detected a so far unknown diversity of genes encoding for (de)halogenating enzymes in the soil metagenome including specific and unspecific halogenases as well as metabolic and cometabolic dehalogenases. Genes for non-heme, no-metal chloroperoxidases and haloalkane dehalogenases were the most abundant halogenase and dehalogenase genes, respectively. The high diversity and abundance of (de)halogenating enzymes suggests a strong microbial contribution to natural halogen cycling. This was also confirmed in microcosm experiments in which we quantified the biotic formation of chloroform and bromoform. Knowledge on microorganisms and genes that catalyze (de)halogenation reactions is critical because they are highly relevant to industrial biotechnologies and bioremediation applications. PMID:27353292

Analysis of suspicious powders following the post 9/11 anthrax scare.

PubMed

Wills, Brandon; Leikin, Jerrold; Rhee, James; Saeedi, Bijan

2008-06-01

Following the 9/11 terrorist attacks, SET Environmental, Inc., a Chicago-based environmental and hazardous materials management company received a large number of suspicious powders for analysis. Samples of powders were submitted to SET for anthrax screening and/or unknown identification (UI). Anthrax screening was performed on-site using a ruggedized analytical pathogen identification device (R.A.P.I.D.) (Idaho Technologies, Salt Lake City, UT). UI was performed at SET headquarters (Wheeling, IL) utilizing a combination of wet chemistry techniques, infrared spectroscopy, and gas chromatography/mass spectroscopy. Turnaround time was approximately 2-3 hours for either anthrax or UI. Between October 10, 2001 and October 11, 2002, 161 samples were analyzed. Of these, 57 were for anthrax screening only, 78 were for anthrax and UI, and 26 were for UI only. Sources of suspicious powders included industries (66%), U.S. Postal Service (19%), law enforcement (9%), and municipalities (7%). There were 0/135 anthrax screens that were positive. There were no positive anthrax screens performed by SET in the Chicago area following the post-9/11 anthrax scare. The only potential biological or chemical warfare agent identified (cyanide) was provided by law enforcement. Rapid anthrax screening and identification of unknown substances at the scene are useful to prevent costly interruption of services and potential referral for medical evaluation.

Statistically Optimized Inversion Algorithm for Enhanced Retrieval of Aerosol Properties from Spectral Multi-Angle Polarimetric Satellite Observations

NASA Technical Reports Server (NTRS)

Dubovik, O; Herman, M.; Holdak, A.; Lapyonok, T.; Taure, D.; Deuze, J. L.; Ducos, F.; Sinyuk, A.

2011-01-01

The proposed development is an attempt to enhance aerosol retrieval by emphasizing statistical optimization in inversion of advanced satellite observations. This optimization concept improves retrieval accuracy relying on the knowledge of measurement error distribution. Efficient application of such optimization requires pronounced data redundancy (excess of the measurements number over number of unknowns) that is not common in satellite observations. The POLDER imager on board the PARASOL microsatellite registers spectral polarimetric characteristics of the reflected atmospheric radiation at up to 16 viewing directions over each observed pixel. The completeness of such observations is notably higher than for most currently operating passive satellite aerosol sensors. This provides an opportunity for profound utilization of statistical optimization principles in satellite data inversion. The proposed retrieval scheme is designed as statistically optimized multi-variable fitting of all available angular observations obtained by the POLDER sensor in the window spectral channels where absorption by gas is minimal. The total number of such observations by PARASOL always exceeds a hundred over each pixel and the statistical optimization concept promises to be efficient even if the algorithm retrieves several tens of aerosol parameters. Based on this idea, the proposed algorithm uses a large number of unknowns and is aimed at retrieval of extended set of parameters affecting measured radiation.

An approximate solution for interlaminar stresses in laminated composites: Applied mechanics program

NASA Technical Reports Server (NTRS)

Rose, Cheryl A.; Herakovich, Carl T.

1992-01-01

An approximate solution for interlaminar stresses in finite width, laminated composites subjected to uniform extensional, and bending loads is presented. The solution is based upon the principle of minimum complementary energy and an assumed, statically admissible stress state, derived by considering local material mismatch effects and global equilibrium requirements. The stresses in each layer are approximated by polynomial functions of the thickness coordinate, multiplied by combinations of exponential functions of the in-plane coordinate, expressed in terms of fourteen unknown decay parameters. Imposing the stationary condition of the laminate complementary energy with respect to the unknown variables yields a system of fourteen non-linear algebraic equations for the parameters. Newton's method is implemented to solve this system. Once the parameters are known, the stresses can be easily determined at any point in the laminate. Results are presented for through-thickness and interlaminar stress distributions for angle-ply, cross-ply (symmetric and unsymmetric laminates), and quasi-isotropic laminates subjected to uniform extension and bending. It is shown that the solution compares well with existing finite element solutions and represents an improved approximate solution for interlaminar stresses, primarily at interfaces where global equilibrium is satisfied by the in-plane stresses, but large local mismatch in properties requires the presence of interlaminar stresses.

Method for genetic identification of unknown organisms

DOEpatents

Colston, Jr., Billy W.; Fitch, Joseph P.; Hindson, Benjamin J.; Carter, Chance J.; Beer, Neil Reginald

2016-08-23

A method of rapid, genome and proteome based identification of unknown pathogenic or non-pathogenic organisms in a complex sample. The entire sample is analyzed by creating millions of emulsion encapsulated microdroplets, each containing a single pathogenic or non-pathogenic organism sized particle and appropriate reagents for amplification. Following amplification, the amplified product is analyzed.

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints.

PubMed

Li, Da-Peng; Li, Dong-Juan; Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip

2017-10-01

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays. The barrier Lyapunov functions are employed to prevent the violation of the full state constraints. The singular problems are dealt with by introducing the signal function. Finally, it is proven that the proposed method can both guarantee the good tracking performance of the systems output, all states are remained in the constrained interval and all the closed-loop signals are bounded in the design process based on choosing appropriate design parameters. The practicability of the proposed control technique is demonstrated by a simulation study in this paper.

FLOURY ENDOSPERM7 encodes a regulator of starch synthesis and amyloplast development essential for peripheral endosperm development in rice

PubMed Central

Zhang, Long; Ren, Yulong; Lu, Bingyue; Yang, Chunyan; Feng, Zhiming; Liu, Zhou; Chen, Jun; Ma, Weiwei; Wang, Ying; Yu, Xiaowen; Wang, Yunlong; Zhang, Wenwei; Wang, Yihua; Liu, Shijia; Wu, Fuqing; Zhang, Xin; Guo, Xiuping; Bao, Yiqun; Jiang, Ling; Wan, Jianmin

2016-01-01

In cereal crops, starch synthesis and storage depend mainly on a specialized class of plastids, termed amyloplasts. Despite the importance of starch, the molecular machinery regulating starch synthesis and amyloplast development remains largely unknown. Here, we report the characterization of the rice (Oryza sativa) floury endosperm7 (flo7) mutant, which develops a floury-white endosperm only in the periphery and not in the inner portion. Consistent with the phenotypic alternation in flo7 endosperm, the flo7 mutant had reduced amylose content and seriously disrupted amylopectin structure only in the peripheral endosperm. Notably, flo7 peripheral endosperm cells showed obvious defects in compound starch grain development. Map-based cloning of FLO7 revealed that it encodes a protein of unknown function. FLO7 harbors an N-terminal transit peptide capable of targeting functional FLO7 fused to green fluorescent protein to amyloplast stroma in developing endosperm cells, and a domain of unknown function 1338 (DUF1338) that is highly conserved in green plants. Furthermore, our combined β-glucuronidase activity and RNA in situ hybridization assays showed that the FLO7 gene was expressed ubiquitously but exhibited a specific expression in the endosperm periphery. Moreover, a set of in vivo experiments demonstrated that the missing 32 aa in the flo7 mutant protein are essential for the stable accumulation of FLO7 in the endosperm. Together, our findings identify FLO7 as a unique plant regulator required for starch synthesis and amyloplast development within the peripheral endosperm and provide new insights into the spatial regulation of endosperm development in rice. PMID:26608643

Treatment Patterns for Cervical Carcinoma In Situ in Michigan, 1998-2003

PubMed Central

Patel, Divya A.; Saraiya, Mona; Copeland, Glenn; Cote, Michele L.; Datta, S. Deblina; Sawaya, George F.

2015-01-01

Objective To characterize population-level surgical treatment patterns for cervical carcinoma in situ (CIS) reported to the Michigan Cancer Surveillance Program (MCSP), and to inform data collection strategies. Methods All cases of cervical carcinoma in situ (CIS) (including cervical intraepithelial neoplasia grade 3 and adenocarcinoma in situ [AIS]) reported to the MCSP during 1998–2003 were identified. First course of treatment (ablative procedure, cone biopsy, loop electrosurgical excisional procedure [LEEP], hysterectomy, unspecified surgical treatment, no surgical treatment, unknown if surgically treated) was described by histology, race, and age at diagnosis. Results Of 17,022 cases of cervical CIS, 82.8% were squamous CIS, 3% AIS/adenosquamous CIS, and 14.2% unspecified/other CIS. Over half (54.7%) of cases were diagnosed in women under age 30. Excisional treatments (LEEP, 32.3% and cone biopsy, 17.3%) were most common, though substantial proportions had no reported treatment (17.8%) or unknown treatment (21.1%). Less common were hysterectomy (7.2%) and ablative procedures (2.6%). LEEP was the most common treatment for squamous cases, while hysterectomy was the most treatment for AIS/adenosquamous CIS cases. Across histologic types, a sizeable proportion of women diagnosed ≤30 years of age underwent excision, either LEEP (20%–38.7%) or cone biopsy (13.7%–44%). Conclusion Despite evidence suggesting it may be safer and equally effective as excision, ablation was rarely used for treating cervical squamous CIS. These population-based data indicate some notable differences in treatment by histology and age at diagnosis, with observed patterns appearing consistent with consensus guidelines in place at the time of study, but favoring more aggressive procedures. Future data collection strategies may need to validate treatment information, including the large proportion of no or unknown treatment. PMID:24002133

Critical Assessment of Small Molecule Identification 2016: automated methods.

PubMed

Schymanski, Emma L; Ruttkies, Christoph; Krauss, Martin; Brouard, Céline; Kind, Tobias; Dührkop, Kai; Allen, Felicity; Vaniya, Arpana; Verdegem, Dries; Böcker, Sebastian; Rousu, Juho; Shen, Huibin; Tsugawa, Hiroshi; Sajed, Tanvir; Fiehn, Oliver; Ghesquière, Bart; Neumann, Steffen

2017-03-27

The fourth round of the Critical Assessment of Small Molecule Identification (CASMI) Contest ( www.casmi-contest.org ) was held in 2016, with two new categories for automated methods. This article covers the 208 challenges in Categories 2 and 3, without and with metadata, from organization, participation, results and post-contest evaluation of CASMI 2016 through to perspectives for future contests and small molecule annotation/identification. The Input Output Kernel Regression (CSI:IOKR) machine learning approach performed best in "Category 2: Best Automatic Structural Identification-In Silico Fragmentation Only", won by Team Brouard with 41% challenge wins. The winner of "Category 3: Best Automatic Structural Identification-Full Information" was Team Kind (MS-FINDER), with 76% challenge wins. The best methods were able to achieve over 30% Top 1 ranks in Category 2, with all methods ranking the correct candidate in the Top 10 in around 50% of challenges. This success rate rose to 70% Top 1 ranks in Category 3, with candidates in the Top 10 in over 80% of the challenges. The machine learning and chemistry-based approaches are shown to perform in complementary ways. The improvement in (semi-)automated fragmentation methods for small molecule identification has been substantial. The achieved high rates of correct candidates in the Top 1 and Top 10, despite large candidate numbers, open up great possibilities for high-throughput annotation of untargeted analysis for "known unknowns". As more high quality training data becomes available, the improvements in machine learning methods will likely continue, but the alternative approaches still provide valuable complementary information. Improved integration of experimental context will also improve identification success further for "real life" annotations. The true "unknown unknowns" remain to be evaluated in future CASMI contests. Graphical abstract .

[Distortion of the anterior airway anatomy and cervical spine motion during laryngoscopy with GlideScope videolaryngoscope: a comparison of mid-size blade vs large blade].

PubMed

Otsuka, Yoji; Hirabayashi, Yoshihiro; Fujita, Akifumi; Sugimoto, Hideharu; Seo, Norimasa

2011-03-01

GlideScope videolaryngoscope (GVL) is a novel indirect laryngogoscope for tracheal intubation. Both mid-size and large blades of the GVL are available for adult patients. The distortion of the anterior airway anatomy and cervical spine motion using the mid-size GVL is unknown. We compare the degree of anterior airway distortion and cervical spine movement during the use of the mid-size GVL compared with the large GVL. Twenty patients requiring general anesthesia and tracheal intubation were studied. Each patient underwent laryngoscopy with both mid-size and large GVLs. During each laryngoscopy, a radiograph for the lateral view of the head and neck was taken when the best view of the larynx was obtained. Based on the radiographs, independent radiologists evaluated anterior airway movement and cervical spine movement. The tip of the mid-size GVL was anteriorly positioned during laryngoscopy, compared with large GVL. The distance between epiglottis and posterior laryngeal wall was longer with the mid-size GVL than with the large GVL. Both the mid-size and large GVL caused a significant anterior movement in the cervical spine during laryngoscope. The difference in the movement in the atlas and C2 was small, but statistically significant. No difference was found in the anterior movement with C3 and C4. During laryngoscopy, cervical spinal extension occurred with both GVLs, while there was no difference in the cervical spinal extension between the mid-size and large GVL. The tip of the mid-size GVL during laryngoscopy is anteriorly positioned and the distortion of the anterior airway was greater with the mid-size GVL than with the large GVL.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities.

PubMed

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

A combined Fisher and Laplacian score for feature selection in QSAR based drug design using compounds with known and unknown activities

NASA Astrophysics Data System (ADS)

Valizade Hasanloei, Mohammad Amin; Sheikhpour, Razieh; Sarram, Mehdi Agha; Sheikhpour, Elnaz; Sharifi, Hamdollah

2018-02-01

Quantitative structure-activity relationship (QSAR) is an effective computational technique for drug design that relates the chemical structures of compounds to their biological activities. Feature selection is an important step in QSAR based drug design to select the most relevant descriptors. One of the most popular feature selection methods for classification problems is Fisher score which aim is to minimize the within-class distance and maximize the between-class distance. In this study, the properties of Fisher criterion were extended for QSAR models to define the new distance metrics based on the continuous activity values of compounds with known activities. Then, a semi-supervised feature selection method was proposed based on the combination of Fisher and Laplacian criteria which exploits both compounds with known and unknown activities to select the relevant descriptors. To demonstrate the efficiency of the proposed semi-supervised feature selection method in selecting the relevant descriptors, we applied the method and other feature selection methods on three QSAR data sets such as serine/threonine-protein kinase PLK3 inhibitors, ROCK inhibitors and phenol compounds. The results demonstrated that the QSAR models built on the selected descriptors by the proposed semi-supervised method have better performance than other models. This indicates the efficiency of the proposed method in selecting the relevant descriptors using the compounds with known and unknown activities. The results of this study showed that the compounds with known and unknown activities can be helpful to improve the performance of the combined Fisher and Laplacian based feature selection methods.

Inquiry-Based Approach to a Carbohydrate Analysis Experiment

NASA Astrophysics Data System (ADS)

Senkbeil, Edward G.

1999-01-01

The analysis of an unknown carbohydrate in an inquiry-based learning format has proven to be a valuable and interesting undergraduate biochemistry laboratory experiment. Students are given a list of carbohydrates and a list of references for carbohydrate analysis. The references contain a variety of well-characterized wet chemistry and instrumental techniques for carbohydrate identification, but the students must develop an appropriate sequential protocol for unknown identification. The students are required to provide a list of chemicals and procedures and a flow chart for identification before the lab. During the 3-hour laboratory period, they utilize their accumulated information and knowledge to classify and identify their unknown. Advantages of the inquiry-based format are (i) students must be well prepared in advance to be successful in the laboratory, (ii) students feel a sense of accomplishment in both designing and carrying out a successful experiment, and (iii) the carbohydrate background information digested by the students significantly decreases the amount of lecture time required for this topic.

A generic standard additions based method to determine endogenous analyte concentrations by immunoassays to overcome complex biological matrix interference.

PubMed

Pang, Susan; Cowen, Simon

2017-12-13

We describe a novel generic method to derive the unknown endogenous concentrations of analyte within complex biological matrices (e.g. serum or plasma) based upon the relationship between the immunoassay signal response of a biological test sample spiked with known analyte concentrations and the log transformed estimated total concentration. If the estimated total analyte concentration is correct, a portion of the sigmoid on a log-log plot is very close to linear, allowing the unknown endogenous concentration to be estimated using a numerical method. This approach obviates conventional relative quantification using an internal standard curve and need for calibrant diluent, and takes into account the individual matrix interference on the immunoassay by spiking the test sample itself. This technique is based on standard additions for chemical analytes. Unknown endogenous analyte concentrations within even 2-fold diluted human plasma may be determined reliably using as few as four reaction wells.

SENSITIVITY OF INDICES OF BIOTIC INTEGRITY TO SIMULATED FISH ASSEMBLAGE CHANGES - 2

EPA Science Inventory

Multi-metric indices of biotic integrity (IBI) are commonly used to compare fish communities among streams, but their ability to monitor trends within streams is largely unknown. We assessed the IBI trend detection ability using simulations which progressively degraded the fish a...

SENSITIVITY OF INDICES OF BIOTIC INTEGRITY TO SIMULATED FISH ASSEMBLAGE CHANGES

EPA Science Inventory

Multi-metric indices of biotic integrity (IBI) are commonly used to assess condition of stream fish assemblages, but their ability to monitor trends within streams over time is largely unknown. We assessed the trend detection ability of two IBI formulations (one with traditional ...

Multiple plant hormones and cell wall metabolism regulate apple fruit maturation patterns and texture attributes

USDA-ARS?s Scientific Manuscript database

Molecular events regulating apple fruit ripening and sensory quality are largely unknown. Such knowledge is essential for genomic-assisted apple breeding and postharvest quality management. In this study, a parallel transcriptome profile analysis, scanning electron microscopic (SEM) examination and...

Stress-Induced Cortisol Hampers Memory Generalization

ERIC Educational Resources Information Center

Dandolo, Lisa C.; Schwabe, Lars

2016-01-01

Integrative encoding and generalization across past experiences depends largely on the hippocampus, an area known to be particularly sensitive to stress. Yet, whether stress influences the ability to generalize memories is unknown. We exposed volunteers to a stressor or a control manipulation before they completed an acquired equivalence task…

Alpha-lipoic acid protects mitochondrial enzymes and attenuates lipopolysaccharide-induced hypothermia in mice

EPA Science Inventory

Abstract: Hypothermia is a key symptom of sepsis and the mechanism(s) leading to hypothermia during sepsis is largely unknown. To investigate a potential mechanism and find an effective treatment for hypothermia in sepsis, we induced hypothermia in mice by lipopolysaccharide (LP...

Anxiety, Depression, Hostility and General Psychopathology: An Arabian Study.

ERIC Educational Resources Information Center

Ibrahim, Abdel-Sattar; Ibrahim, Radwa M.

In Arabian cultures, the psychosocial characteristics of psychopathological trends, including depression, anxiety, and hostility remain largely unknown. Scales measuring depression, anxiety, and hostility were administered to a voluntary sample of 989 Saudi Arabian men and 1,024 Saudi women coming from different social, economical, and educational…

Diesel particle-induced transcriptional expression of P21 involves activation of EGFR, SRC, and STAT3

EPA Science Inventory

Exposure to diesel exhaust particles (DEP) has been associated with adverse health outcomes such as inflammation, adjuvancy, and mutagenesis. However, the molecular mechanisms by which DEP inhalation exerts these effects are still largely unknown. We previously reported that expo...

Unknown genius

NASA Astrophysics Data System (ADS)

Weaire, Denis; Donegan, John F.; Florides, Petros S.

2012-12-01

A visionary who saw far ahead of his contemporaries, Edward Hutchinson Synge has been largely overlooked by the academic world, from which he worked in isolation before he was confined to a mental hospital at the age of 46. Denis Weaire, John F Donegan and Petros S Florides uncover his remarkable story.

Ecological Regional Analysis Applied to Campus Sustainability Performance

ERIC Educational Resources Information Center

Weber, Shana; Newman, Julie; Hill, Adam

2017-01-01

Purpose: Sustainability performance in higher education is often evaluated at a generalized large scale. It remains unknown to what extent campus efforts address regional sustainability needs. This study begins to address this gap by evaluating trends in performance through the lens of regional environmental characteristics.…

Small heterodimer partner (NROB2) coordinates nutrient signaling and the circadian clock in mice

USDA-ARS?s Scientific Manuscript database

Circadian rhythm regulates multiple metabolic processes and in turn is readily entrained by feeding-fasting cycles. However, the molecular mechanisms by which the peripheral clock senses nutrition availability remain largely unknown. Bile acids are under circadian control and also increase postprand...

Exposure of agricultural crops to nanoparticle CeO2 in biochar-amended soil

USDA-ARS?s Scientific Manuscript database

Biochar is seeing increased usage as an amendment in agricultural soils but the significance of nanoscale interactions between this additive and engineered nanoparticles (ENP) remains largely unknown. In the present study, corn (Zea mays), lettuce (Lactuca sativa), soybean (Glycine max) and zucchini...

Low-Density microarray technologies for rapid human norovirus genotyping

USDA-ARS?s Scientific Manuscript database

Human noroviruses (HuNoV) are the most common cause of food borne disease and viruses are likely responsible for a large proportion of foodborne diseases of unknown etiology. Recent advancements in molecular biology, bioinformatics, epidemiology, and risk analysis have aided the study of these agent...

HOx Observation and Model Comparison During INTEX-A 2004

NASA Technical Reports Server (NTRS)

Ren, Xinrong; Olson, Jennifer R.; Crawford, James H.; Brune, William H.; Mao, Jingqiu; Long, Robert B.; Chen, Zhong; Chen, Gao; Avery, Melody A.; Sachse, Glen W.;

Bioinformatic Identification of Potential MicroRNAs and Their Targets in the Lingzhi or Reishi Medicinal Mushroom Ganoderma lucidum (Higher Basidiomycetes).

PubMed

Mu, Da-Shuai; Li, Chenyang; Shi, Liang; Zhang, Xuchen; Ren, Ang; Zhao, Ming-Wen

2015-01-01

MicroRNAs (miRNAs) are a class of small, endogenous, noncoding RNA molecules that negatively regulate gene expression at the transcriptional or the post-transcriptional level. Although a large number of miRNAs have been identified in many species, especially model plants and animals, miRNAs in fungi remain largely unknown. In this study, based on a database of expressed sequence tags in Ganoderma lucidum, 89 potential miRNAs were identified using computational methods. Real-time polymerase chain reaction analysis of miRNA-like samples prepared from G. lucidum at different development stages revealed that miRNA-like RNAs were differentially expressed in different stages. Furthermore, a total of 28 potential targets were found based on near-perfect or perfect complementarity between the randomly selected 9 miRNA-like RNAs and the target sequences, and potential targets for G. lucidum miRNA-like RNAs were predicted. Finally, we studied the expression pattern of 4 target genes in 3 different development stages of G. lucidum to further understand the mechanism of interaction between miRNA-like RNAs and their target genes. Our analysis paves the way toward identifying fungal miRNA-like RNAs that might be involved in various physiological and cellular differentiation processes.

Performance of an MPI-only semiconductor device simulator on a quad socket/quad core InfiniBand platform.

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

Shadid, John Nicolas; Lin, Paul Tinphone

2009-01-01

This preliminary study considers the scaling and performance of a finite element (FE) semiconductor device simulator on a capacity cluster with 272 compute nodes based on a homogeneous multicore node architecture utilizing 16 cores. The inter-node communication backbone for this Tri-Lab Linux Capacity Cluster (TLCC) machine is comprised of an InfiniBand interconnect. The nonuniform memory access (NUMA) nodes consist of 2.2 GHz quad socket/quad core AMD Opteron processors. The performance results for this study are obtained with a FE semiconductor device simulation code (Charon) that is based on a fully-coupled Newton-Krylov solver with domain decomposition and multilevel preconditioners. Scaling andmore » multicore performance results are presented for large-scale problems of 100+ million unknowns on up to 4096 cores. A parallel scaling comparison is also presented with the Cray XT3/4 Red Storm capability platform. The results indicate that an MPI-only programming model for utilizing the multicore nodes is reasonably efficient on all 16 cores per compute node. However, the results also indicated that the multilevel preconditioner, which is critical for large-scale capability type simulations, scales better on the Red Storm machine than the TLCC machine.« less

Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

PubMed

Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

2017-09-21

Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

Orbital Circularization of Hot and Cool Kepler Eclipsing Binaries

NASA Astrophysics Data System (ADS)

Van Eylen, Vincent; Winn, Joshua N.; Albrecht, Simon

2016-06-01

The rate of tidal circularization is predicted to be faster for relatively cool stars with convective outer layers, compared to hotter stars with radiative outer layers. Observing this effect is challenging because it requires large and well-characterized samples that include both hot and cool stars. Here we seek evidence of the predicted dependence of circularization upon stellar type, using a sample of 945 eclipsing binaries observed by Kepler. This sample complements earlier studies of this effect, which employed smaller samples of better-characterized stars. For each Kepler binary we measure e cos ω based on the relative timing of the primary and secondary eclipses. We examine the distribution of e cos ω as a function of period for binaries composed of hot stars, cool stars, and mixtures of the two types. At the shortest periods, hot-hot binaries are most likely to be eccentric; for periods shorter than four days, significant eccentricities occur frequently for hot-hot binaries, but not for hot-cool or cool-cool binaries. This is in qualitative agreement with theoretical expectations based on the slower dissipation rates of hot stars. However, the interpretation of our results is complicated by the largely unknown ages and evolutionary states of the stars in our sample.

Genetic heterogeneity in primary and relapsed mantle cell lymphomas: Impact of recurrent CARD11 mutations.

PubMed

Wu, Chenglin; de Miranda, Noel Fcc; Chen, Longyun; Wasik, Agata M; Mansouri, Larry; Jurczak, Wojciech; Galazka, Krystyna; Dlugosz-Danecka, Monika; Machaczka, Maciej; Zhang, Huilai; Peng, Roujun; Morin, Ryan D; Rosenquist, Richard; Sander, Birgitta; Pan-Hammarström, Qiang

2016-06-21

The genetic mechanisms underlying disease progression, relapse and therapy resistance in mantle cell lymphoma (MCL) remain largely unknown. Whole-exome sequencing was performed in 27 MCL samples from 13 patients, representing the largest analyzed series of consecutive biopsies obtained at diagnosis and/or relapse for this type of lymphoma. Eighteen genes were found to be recurrently mutated in these samples, including known (ATM, MEF2B and MLL2) and novel mutation targets (S1PR1 and CARD11). CARD11, a scaffold protein required for B-cell receptor (BCR)-induced NF-κB activation, was subsequently screened in an additional 173 MCL samples and mutations were observed in 5.5% of cases. Based on in vitro cell line-based experiments, overexpression of CARD11 mutants were demonstrated to confer resistance to the BCR-inhibitor ibrutinib and NF-κB-inhibitor lenalidomide. Genetic alterations acquired in the relapse samples were found to be largely non-recurrent, in line with the branched evolutionary pattern of clonal evolution observed in most cases. In summary, this study highlights the genetic heterogeneity in MCL, in particular at relapse, and provides for the first time genetic evidence of BCR/NF-κB activation in a subset of MCL.

vConTACT: an iVirus tool to classify double-stranded DNA viruses that infect Archaea and Bacteria.

PubMed

Bolduc, Benjamin; Jang, Ho Bin; Doulcier, Guilhem; You, Zhi-Qiang; Roux, Simon; Sullivan, Matthew B

2017-01-01

Taxonomic classification of archaeal and bacterial viruses is challenging, yet also fundamental for developing a predictive understanding of microbial ecosystems. Recent identification of hundreds of thousands of new viral genomes and genome fragments, whose hosts remain unknown, requires a paradigm shift away from traditional classification approaches and towards the use of genomes for taxonomy. Here we revisited the use of genomes and their protein content as a means for developing a viral taxonomy for bacterial and archaeal viruses. A network-based analytic was evaluated and benchmarked against authority-accepted taxonomic assignments and found to be largely concordant. Exceptions were manually examined and found to represent areas of viral genome 'sequence space' that are under-sampled or prone to excessive genetic exchange. While both cases are poorly resolved by genome-based taxonomic approaches, the former will improve as viral sequence space is better sampled and the latter are uncommon. Finally, given the largely robust taxonomic capabilities of this approach, we sought to enable researchers to easily and systematically classify new viruses. Thus, we established a tool, vConTACT, as an app at iVirus, where it operates as a fast, highly scalable, user-friendly app within the free and powerful CyVerse cyberinfrastructure.

vConTACT: an iVirus tool to classify double-stranded DNA viruses that infect Archaea and Bacteria

PubMed Central

Doulcier, Guilhem; You, Zhi-Qiang; Roux, Simon

2017-01-01

Taxonomic classification of archaeal and bacterial viruses is challenging, yet also fundamental for developing a predictive understanding of microbial ecosystems. Recent identification of hundreds of thousands of new viral genomes and genome fragments, whose hosts remain unknown, requires a paradigm shift away from traditional classification approaches and towards the use of genomes for taxonomy. Here we revisited the use of genomes and their protein content as a means for developing a viral taxonomy for bacterial and archaeal viruses. A network-based analytic was evaluated and benchmarked against authority-accepted taxonomic assignments and found to be largely concordant. Exceptions were manually examined and found to represent areas of viral genome ‘sequence space’ that are under-sampled or prone to excessive genetic exchange. While both cases are poorly resolved by genome-based taxonomic approaches, the former will improve as viral sequence space is better sampled and the latter are uncommon. Finally, given the largely robust taxonomic capabilities of this approach, we sought to enable researchers to easily and systematically classify new viruses. Thus, we established a tool, vConTACT, as an app at iVirus, where it operates as a fast, highly scalable, user-friendly app within the free and powerful CyVerse cyberinfrastructure. PMID:28480138

Acute ethanol poisoning in a 6-year-old girl following ingestion of alcohol-based hand sanitizer at school.

PubMed

Joseph, Madeline Matar; Zeretzke, Cristina; Reader, Sara; Sollee, Dawn R

2011-01-01

Alcohol-based hand sanitizers (ABHSs) have been widely used in homes, workplaces and schools to prevent the spread of infectious diseases. We report a young child unintentionally ingested ABHS at a school, resulting in intoxication. The child was a 6-year-old girl who had been brought to the emergency department (ED) for hypothermia, altered mental status (AMS), periods of hypoventilation, hypothermia and vomiting. Computed tomography of her head revealed nothing abnormal in intracranial pathology. Urine drug screening was negative. Alcohol level was 205 mg/dL on admission. Other abnormal values included potassium of 2.8 mEq/L, osmolality of 340 mOsm/kg and no hypoglycemia. Further investigation revealed that the patient had gone frequently to the class restroom for ingestion of unknown quantities of ABHSs during the day. The patient was admitted for one day for intravenous fluid hydration and close observation of her mental status. The patient was discharged from the hospital the next day without any complications. Despite the large safety margin of ABHSs, emergency physicians need to be aware of the potential risk of ingestion of a large amount of such products in children and consider it in the assessment and management of school-age children with acute AMS.

vConTACT: an iVirus tool to classify double-stranded DNA viruses that infect Archaea and Bacteria

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

Bolduc, Benjamin; Jang, Ho Bin; Doulcier, Guilhem

Taxonomic classification of archaeal and bacterial viruses is challenging, yet also fundamental for developing a predictive understanding of microbial ecosystems. Recent identification of hundreds of thousands of new viral genomes and genome fragments, whose hosts remain unknown, requires a paradigm shift away from traditional classification approaches and towards the use of genomes for taxonomy. Here we revisited the use of genomes and their protein content as a means for developing a viral taxonomy for bacterial and archaeal viruses. A network-based analytic was evaluated and benchmarked against authority-accepted taxonomic assignments and found to be largely concordant. Exceptions were manually examined andmore » found to represent areas of viral genome ‘sequence space’ that are under-sampled or prone to excessive genetic exchange. While both cases are poorly resolved by genome-based taxonomic approaches, the former will improve as viral sequence space is better sampled and the latter are uncommon. Finally, given the largely robust taxonomic capabilities of this approach, we sought to enable researchers to easily and systematically classify new viruses. Thus, we established a tool, vConTACT, as an app at iVirus, where it operates as a fast, highly scalable, user-friendly app within the free and powerful CyVerse cyberinfrastructure.« less

ORBITAL CIRCULARIZATION OF HOT AND COOL KEPLER ECLIPSING BINARIES

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

Eylen, Vincent Van; Albrecht, Simon; Winn, Joshua N., E-mail: vincent@phys.au.dk

The rate of tidal circularization is predicted to be faster for relatively cool stars with convective outer layers, compared to hotter stars with radiative outer layers. Observing this effect is challenging because it requires large and well-characterized samples that include both hot and cool stars. Here we seek evidence of the predicted dependence of circularization upon stellar type, using a sample of 945 eclipsing binaries observed by Kepler . This sample complements earlier studies of this effect, which employed smaller samples of better-characterized stars. For each Kepler binary we measure e cos ω based on the relative timing of themore » primary and secondary eclipses. We examine the distribution of e cos ω as a function of period for binaries composed of hot stars, cool stars, and mixtures of the two types. At the shortest periods, hot–hot binaries are most likely to be eccentric; for periods shorter than four days, significant eccentricities occur frequently for hot–hot binaries, but not for hot–cool or cool–cool binaries. This is in qualitative agreement with theoretical expectations based on the slower dissipation rates of hot stars. However, the interpretation of our results is complicated by the largely unknown ages and evolutionary states of the stars in our sample.« less

vConTACT: an iVirus tool to classify double-stranded DNA viruses that infect Archaea and Bacteria

DOE PAGES

Bolduc, Benjamin; Jang, Ho Bin; Doulcier, Guilhem; ...

2017-05-03

Taxonomic classification of archaeal and bacterial viruses is challenging, yet also fundamental for developing a predictive understanding of microbial ecosystems. Recent identification of hundreds of thousands of new viral genomes and genome fragments, whose hosts remain unknown, requires a paradigm shift away from traditional classification approaches and towards the use of genomes for taxonomy. Here we revisited the use of genomes and their protein content as a means for developing a viral taxonomy for bacterial and archaeal viruses. A network-based analytic was evaluated and benchmarked against authority-accepted taxonomic assignments and found to be largely concordant. Exceptions were manually examined andmore » found to represent areas of viral genome ‘sequence space’ that are under-sampled or prone to excessive genetic exchange. While both cases are poorly resolved by genome-based taxonomic approaches, the former will improve as viral sequence space is better sampled and the latter are uncommon. Finally, given the largely robust taxonomic capabilities of this approach, we sought to enable researchers to easily and systematically classify new viruses. Thus, we established a tool, vConTACT, as an app at iVirus, where it operates as a fast, highly scalable, user-friendly app within the free and powerful CyVerse cyberinfrastructure.« less

The empirical status of the third-wave behaviour therapies for the treatment of eating disorders: A systematic review.

PubMed

Linardon, Jake; Fairburn, Christopher G; Fitzsimmons-Craft, Ellen E; Wilfley, Denise E; Brennan, Leah

2017-12-01

Although third-wave behaviour therapies are being increasingly used for the treatment of eating disorders, their efficacy is largely unknown. This systematic review and meta-analysis aimed to examine the empirical status of these therapies. Twenty-seven studies met full inclusion criteria. Only 13 randomized controlled trials (RCT) were identified, most on binge eating disorder (BED). Pooled within- (pre-post change) and between-groups effect sizes were calculated for the meta-analysis. Large pre-post symptom improvements were observed for all third-wave treatments, including dialectical behaviour therapy (DBT), schema therapy (ST), acceptance and commitment therapy (ACT), mindfulness-based interventions (MBI), and compassion-focused therapy (CFT). Third-wave therapies were not superior to active comparisons generally, or to cognitive-behaviour therapy (CBT) in RCTs. Based on our qualitative synthesis, none of the third-wave therapies meet established criteria for an empirically supported treatment for particular eating disorder subgroups. Until further RCTs demonstrate the efficacy of third-wave therapies for particular eating disorder subgroups, the available data suggest that CBT should retain its status as the recommended treatment approach for bulimia nervosa (BN) and BED, and the front running treatment for anorexia nervosa (AN) in adults, with interpersonal psychotherapy (IPT) considered a strong empirically-supported alternative. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effects of Surface-Engineered Nanoparticle-Based Dispersants for Marine Oil Spills on the Model Organism Artemia franciscana

PubMed Central

2015-01-01

Fine particles are under active consideration as alternatives to chemical dispersants for large-scale petroleum spills. Fine carbon particles with engineered surface chemistry have been shown to stabilize oil-in-water emulsions, but the environmental impacts of large-scale particle introduction to the marine environment are unknown. Here we study the impact of surface-engineered carbon-black materials on brine shrimp (Artemia franciscana) as a model marine microcrustacean. Mortality was characterized at 50–1000 mg/L, and levels of heat shock protein 70 (hsp70) were characterized at sublethal particle concentrations (25–50 mg/L). Functionalized carbon black (CB) nanoparticles were found to be nontoxic at all concentrations, while hydrophobic (annealed) and as-produced CB induced adverse effects at high concentrations. CB was also shown to adsorb benzene, a model hydrocarbon representing the more soluble and toxic low-molecular weight aromatic fraction of petroleum, but the extent of adsorption was insufficient to mitigate benzene toxicity to Artemia in coexposure experiments. At lower benzene concentrations (25–75 mg/L), coexposure with annealed and as-produced CB increased hsp70 protein levels. This study suggests that surface functionalization for increased hydrophilicity can not only improve the performance of CB-based dispersants but also reduce their adverse environmental impacts on marine organisms. PMID:24823274

Stem parasitic plant Cuscuta australis (dodder) transfers herbivory-induced signals among plants.

PubMed

Hettenhausen, Christian; Li, Juan; Zhuang, Huifu; Sun, Huanhuan; Xu, Yuxing; Qi, Jinfeng; Zhang, Jingxiong; Lei, Yunting; Qin, Yan; Sun, Guiling; Wang, Lei; Baldwin, Ian T; Wu, Jianqiang

2017-08-08

Cuscuta spp. (i.e., dodders) are stem parasites that naturally graft to their host plants to extract water and nutrients; multiple adjacent hosts are often parasitized by one or more Cuscuta plants simultaneously, forming connected plant clusters. Metabolites, proteins, and mRNAs are known to be transferred from hosts to Cuscuta , and Cuscuta bridges even facilitate host-to-host virus movement. Whether Cuscuta bridges transmit ecologically meaningful signals remains unknown. Here we show that, when host plants are connected by Cuscuta bridges, systemic herbivory signals are transmitted from attacked plants to unattacked plants, as revealed by the large transcriptomic changes in the attacked local leaves, undamaged systemic leaves of the attacked plants, and leaves of unattacked but connected hosts. The interplant signaling is largely dependent on the jasmonic acid pathway of the damaged local plants, and can be found among conspecific or heterospecific hosts of different families. Importantly, herbivore attack of one host plant elevates defensive metabolites in the other systemic Cuscuta bridge-connected hosts, resulting in enhanced resistance against insects even in several consecutively Cuscuta -connected host plants over long distances (> 100 cm). By facilitating plant-to-plant signaling, Cuscuta provides an information-based means of countering the resource-based fitness costs to their hosts.

Stem parasitic plant Cuscuta australis (dodder) transfers herbivory-induced signals among plants

PubMed Central

Hettenhausen, Christian; Li, Juan; Zhuang, Huifu; Sun, Huanhuan; Xu, Yuxing; Qi, Jinfeng; Zhang, Jingxiong; Lei, Yunting; Qin, Yan; Sun, Guiling; Wang, Lei; Baldwin, Ian T.

2017-01-01

Cuscuta spp. (i.e., dodders) are stem parasites that naturally graft to their host plants to extract water and nutrients; multiple adjacent hosts are often parasitized by one or more Cuscuta plants simultaneously, forming connected plant clusters. Metabolites, proteins, and mRNAs are known to be transferred from hosts to Cuscuta, and Cuscuta bridges even facilitate host-to-host virus movement. Whether Cuscuta bridges transmit ecologically meaningful signals remains unknown. Here we show that, when host plants are connected by Cuscuta bridges, systemic herbivory signals are transmitted from attacked plants to unattacked plants, as revealed by the large transcriptomic changes in the attacked local leaves, undamaged systemic leaves of the attacked plants, and leaves of unattacked but connected hosts. The interplant signaling is largely dependent on the jasmonic acid pathway of the damaged local plants, and can be found among conspecific or heterospecific hosts of different families. Importantly, herbivore attack of one host plant elevates defensive metabolites in the other systemic Cuscuta bridge-connected hosts, resulting in enhanced resistance against insects even in several consecutively Cuscuta-connected host plants over long distances (> 100 cm). By facilitating plant-to-plant signaling, Cuscuta provides an information-based means of countering the resource-based fitness costs to their hosts. PMID:28739895

Toward an architecture of attachment disorganization: John Bowlby’s published and unpublished reflections

PubMed Central

Solomon, Judith; Duschinsky, Robbie; Bakkum, Lianne; Schuengel, Carlo

2017-01-01

This article examines the construct of disorganized attachment originally proposed by Main and Solomon, developing some new conjectures based on inspiration from a largely unknown source: John Bowlby’s unpublished texts, housed at the Wellcome Trust Library Archive in London (with permission from the Bowlby family). We explore Bowlby’s discussions of disorganized attachment, which he understood from the perspective of ethological theories of conflict behavior. Bowlby’s reflections regarding differences among the behaviors used to code disorganized attachment will be used to explore distinctions that may underlie the structure of the current coding system. The article closes with an emphasis on the importance Bowlby placed on Popper’s distinction between the context of discovery and the context of justification in developmental science. PMID:28791871

Bioaerosol generation by raindrops on soil

NASA Astrophysics Data System (ADS)

Joung, Young Soo; Ge, Zhifei; Buie, Cullen R.

2017-03-01

Aerosolized microorganisms may play an important role in climate change, disease transmission, water and soil contaminants, and geographic migration of microbes. While it is known that bioaerosols are generated when bubbles break on the surface of water containing microbes, it is largely unclear how viable soil-based microbes are transferred to the atmosphere. Here we report a previously unknown mechanism by which rain disperses soil bacteria into the air. Bubbles, tens of micrometres in size, formed inside the raindrops disperse micro-droplets containing soil bacteria during raindrop impingement. A single raindrop can transfer 0.01% of bacteria on the soil surface and the bacteria can survive more than one hour after the aerosol generation process. This work further reveals that bacteria transfer by rain is highly dependent on the regional soil profile and climate conditions.

Hamiltonian models for topological phases of matter in three spatial dimensions

NASA Astrophysics Data System (ADS)

Williamson, Dominic J.; Wang, Zhenghan

2017-02-01

We present commuting projector Hamiltonian realizations of a large class of (3 + 1)D topological models based on mathematical objects called unitary G-crossed braided fusion categories. This construction comes with a wealth of examples from the literature of symmetry-enriched topological phases. The spacetime counterparts to our Hamiltonians are unitary state sum topological quantum fields theories (TQFTs) that appear to capture all known constructions in the literature, including the Crane-Yetter-Walker-Wang and 2-Group gauge theory models. We also present Hamiltonian realizations of a state sum TQFT recently constructed by Kashaev whose relation to existing models was previously unknown. We argue that this TQFT is captured as a special case of the Crane-Yetter-Walker-Wang model, with a premodular input category in some instances.

Verification of specific selection SNPs between broiler and layer chicken in Chinese indigenous chicken breeds.

PubMed

Lan, D; Hu, Y D; Zhu, Q; Li, D Y; Liu, Y P

2015-07-28

The direction of production for indigenous chicken breeds is currently unknown and this knowledge, combined with the development of chicken genome-wide association studies, led us to investigate differences in specific loci between broiler and layer chicken using bioinformatic methods. In addition, we analyzed the distribution of these seven identified loci in four Chinese indigenous chicken breeds, Caoke chicken, Jiuyuan chicken, Sichuan mountain chicken, and Tibetan chicken, using DNA direct sequencing methods, and analyzed the data using bioinformatic methods. Based on the results, we suggest that Caoke chicken could be developed for meat production, while Jiuyuan chicken could be developed for egg production. As Sichuan mountain chicken and Tibetan chicken exhibited large polymorphisms, these breeds could be improved by changing their living environment.

Boundary layer flow of air over water on a flat plate

NASA Technical Reports Server (NTRS)

Nelson, John; Alving, Amy E.; Joseph, Daniel D.

1993-01-01

A non-similar boundary layer theory for air blowing over a water layer on a flat plate is formulated and studied as a two-fluid problem in which the position of the interface is unknown. The problem is considered at large Reynolds number (based on x), away from the leading edge. A simple non-similar analytic solution of the problem is derived for which the interface height is proportional to x(sub 1/4) and the water and air flow satisfy the Blasius boundary layer equations, with a linear profile in the water and a Blasius profile in the air. Numerical studies of the initial value problem suggests that this asymptotic, non-similar air-water boundary layer solution is a global attractor for all initial conditions.

AI tools in computer based problem solving

NASA Technical Reports Server (NTRS)

Beane, Arthur J.

1988-01-01

The use of computers to solve value oriented, deterministic, algorithmic problems, has evolved a structured life cycle model of the software process. The symbolic processing techniques used, primarily in research, for solving nondeterministic problems, and those for which an algorithmic solution is unknown, have evolved a different model, much less structured. Traditionally, the two approaches have been used completely independently. With the advent of low cost, high performance 32 bit workstations executing identical software with large minicomputers and mainframes, it became possible to begin to merge both models into a single extended model of computer problem solving. The implementation of such an extended model on a VAX family of micro/mini/mainframe systems is described. Examples in both development and deployment of applications involving a blending of AI and traditional techniques are given.

Genomic analyses provide insights into the history of tomato breeding.

PubMed

Lin, Tao; Zhu, Guangtao; Zhang, Junhong; Xu, Xiangyang; Yu, Qinghui; Zheng, Zheng; Zhang, Zhonghua; Lun, Yaoyao; Li, Shuai; Wang, Xiaoxuan; Huang, Zejun; Li, Junming; Zhang, Chunzhi; Wang, Taotao; Zhang, Yuyang; Wang, Aoxue; Zhang, Yancong; Lin, Kui; Li, Chuanyou; Xiong, Guosheng; Xue, Yongbiao; Mazzucato, Andrea; Causse, Mathilde; Fei, Zhangjun; Giovannoni, James J; Chetelat, Roger T; Zamir, Dani; Städler, Thomas; Li, Jingfu; Ye, Zhibiao; Du, Yongchen; Huang, Sanwen

2014-11-01

The histories of crop domestication and breeding are recorded in genomes. Although tomato is a model species for plant biology and breeding, the nature of human selection that altered its genome remains largely unknown. Here we report a comprehensive analysis of tomato evolution based on the genome sequences of 360 accessions. We provide evidence that domestication and improvement focused on two independent sets of quantitative trait loci (QTLs), resulting in modern tomato fruit ∼100 times larger than its ancestor. Furthermore, we discovered a major genomic signature for modern processing tomatoes, identified the causative variants that confer pink fruit color and precisely visualized the linkage drag associated with wild introgressions. This study outlines the accomplishments as well as the costs of historical selection and provides molecular insights toward further improvement.

Bio-nano interactions detected by nanochannel electrophoresis.

PubMed

Luan, Binquan

2016-08-01

Engineered nanoparticles have been widely used in industry and are present in many consumer products. However, their bio-safeties especially in a long term are largely unknown. Here, a nanochannel-electrophoresis-based method is proposed for detecting the potential bio-nano interactions that may further lead to damages to human health and/or biological environment. Through proof-of-concept molecular dynamics simulations, it was demonstrated that the transport of a protein-nanoparticle complex is very different from that of a protein along. By monitoring the change of ionic currents induced by a transported analyte as well as the transport velocities of the analyte, the complex (with bio-nano interaction) can be clearly distinguished from the protein alone (with no interaction with tested nanoparticles). © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Predictive representations can link model-based reinforcement learning to model-free mechanisms.

PubMed

Russek, Evan M; Momennejad, Ida; Botvinick, Matthew M; Gershman, Samuel J; Daw, Nathaniel D

2017-09-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation.

Predictive representations can link model-based reinforcement learning to model-free mechanisms

PubMed Central

Botvinick, Matthew M.

2017-01-01

Humans and animals are capable of evaluating actions by considering their long-run future rewards through a process described using model-based reinforcement learning (RL) algorithms. The mechanisms by which neural circuits perform the computations prescribed by model-based RL remain largely unknown; however, multiple lines of evidence suggest that neural circuits supporting model-based behavior are structurally homologous to and overlapping with those thought to carry out model-free temporal difference (TD) learning. Here, we lay out a family of approaches by which model-based computation may be built upon a core of TD learning. The foundation of this framework is the successor representation, a predictive state representation that, when combined with TD learning of value predictions, can produce a subset of the behaviors associated with model-based learning, while requiring less decision-time computation than dynamic programming. Using simulations, we delineate the precise behavioral capabilities enabled by evaluating actions using this approach, and compare them to those demonstrated by biological organisms. We then introduce two new algorithms that build upon the successor representation while progressively mitigating its limitations. Because this framework can account for the full range of observed putatively model-based behaviors while still utilizing a core TD framework, we suggest that it represents a neurally plausible family of mechanisms for model-based evaluation. PMID:28945743

Teleportation of Unknown Superpositions of Collective Atomic Coherent States

NASA Astrophysics Data System (ADS)

Zheng, Shi-Biao

2001-06-01

We propose a scheme to teleport an unknown superposition of two atomic coherent states with different phases. Our scheme is based on resonant and dispersive atom-field interaction. Our scheme provides a possibility of teleporting macroscopic superposition states of many atoms first time. The project supported by National Natural Science Foundation of China under Grant No. 60008003

Learning Unknown Event Models

DTIC Science & Technology

2014-07-01

Intelligence (www.aaai.org). All rights reserved. knowledge engineering, but it is often impractical due to high environment variance, or unknown events...distribution unlimited 13. SUPPLEMENTARY NOTES In Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence , 27-31 July 2014...autonomy for responding to unexpected events in strategy simulations. Computational Intelligence , 29(2), 187-206. Leake, D. B. (1991), Goal-based

Using Conductivity Measurements to Determine the Identities and Concentrations of Unknown Acids: An Inquiry Laboratory Experiment

ERIC Educational Resources Information Center

Smith, K. Christopher; Garza, Ariana

2015-01-01

This paper describes a student designed experiment using titrations involving conductivity measurements to identify unknown acids as being either HCl or H[subscript 2]SO[subscript 4], and to determine the concentrations of the acids, thereby improving the utility of standard acid-base titrations. Using an inquiry context, students gain experience…

Differential emitter geolocation

DOEpatents

Mason, John J.; Romero, Louis A.

2015-08-18

An unknown location of a transmitter of interest is determined based on wireless signals transmitted by both the transmitter of interest and a reference transmitter positioned at a known location. The transmitted signals are received at a plurality of non-earthbound platforms each moving in a known manner, and phase measurements for each received signal are used to determine the unknown location.

Impaired glucose metabolism and type 2 diabetes in apparently healthy senior citizens.

PubMed

Medina Escobar, Pedro; Moser, Michel; Risch, Lorenz; Risch, Martin; Nydegger, Urs Ernst; Stanga, Zeno

2015-01-01

To estimate the prevalence of unknown impaired glucose metabolism, also referred to as prediabetes (PreD), and unknown type 2 diabetes mellitus (T2DM) among subjectively healthy Swiss senior citizens. The fasting plasma glucose (FPG) and glycated haemoglobin A(1c) (HbA(1c)) levels were used for screening. A total of 1 362 subjects were included (613 men and 749 women; age range 60-99 years). Subjects with known T2DM were excluded. The FPG was processed immediately for analysis under standardised preanalytical conditions in a cross-sectional cohort study; plasma glucose levels were measured by means of the hexokinase procedure, and HbA(1c) was measured chromatographically and classified using the current American Diabetes Association (ADA) criteria. The crude prevalence of individuals unaware of having prediabetic FPG or HbA(1c) levels, was 64.5% (n = 878). Analogously, unknown T2DM was found in 8.4% (n = 114) On the basis of HbA(1c) criteria alone, significantly more subjects with unknown fasting glucose impairment and laboratory T2DM could be identified than with the FPG. The prevalence of PreD as well as of T2DM increased with age. The mean HOMA indices (homeostasis model assessment) for the different age groups, between 2.12 and 2.59, are consistent with clinically hidden disease and are in agreement with the largely orderly Body Mass Indices found in the normal range. Laboratory evidence of impaired glucose metabolism and, to a lesser extent, unknown T2DM, has a high prevalence among subjectively healthy older Swiss individuals. Laboratory identification of people with unknown out-of-range glucose values and overt diabetic hyperglycaemia might improve the prognosis by delaying the emergence of overt disease.

The Future Russian Navy: Interests of the Military

DTIC Science & Technology

1993-05-01

plasma, pulse, membrane, biochemistry , and radiology.’𔃿 Soviet science had to discover and apply "as yet unknown properties of matter, natural laws...agree that large armored forces have become " dinosaurs " in modern warfare.1 Second, all parties agree that the Russian armed forces must be smaller

Infant iron status affects iron absorption in Peruvian breastfed infants at 2 and 5 mo of age

USDA-ARS?s Scientific Manuscript database

Effects of prenatal iron supplementation on maternal postpartum iron status and early infant iron homeostasis remain largely unknown. We examined iron absorption and growth in exclusively breastfed infants in relation to fetal iron exposure and iron status during early infancy. Longitudinal, paired ...

Application of a plasmid classification system to determine prevalence of replicon families among multidrug resistant enterococci

USDA-ARS?s Scientific Manuscript database

The presence and transfer of plasmids from commensal bacteria to more pathogenic bacteria may contribute to dissemination of antimicrobial resistance. However, prevalence of plasmids from commensal bacteria in food animals such as the enterococci remains largely unknown. In this study, the prevale...

Differential lysine acetylation profiles of Erwinia amylovora strains revealed by proteomics

USDA-ARS?s Scientific Manuscript database

Protein lysine acetylation (LysAc) in bacteria has recently been demonstrated to be widespread in E. coli and Salmonella and to broadly regulate bacterial physiology and metabolism. However, LysAc in plant pathogenic bacteria is largely unknown. Here we report the lysine acetylome of Erwinia amylovo...

Specifying the Links between Household Chaos and Preschool Children's Development

ERIC Educational Resources Information Center

Martin, Anne; Razza, Rachel A.; Brooks-Gunn, Jeanne

2012-01-01

Household chaos has been linked to poorer cognitive, behavioural, and self-regulatory outcomes in young children, but the mechanisms responsible remain largely unknown. Using a diverse sample of families in Chicago, the present study tests for the independent contributions made by five indicators of household chaos: noise, crowding, family…

Active taste compounds in juice from oranges symptomatic for Huanglongbing (HLB) citrus greening disease

USDA-ARS?s Scientific Manuscript database

Citrus greening disease, also known as Huanglongbing (HLB), compromises the quality of citrus fruit and juice, causing increased bitterness, metallic taste, astringency and a burning mouthfeel. The chemical basis responsible for these changes remains largely unknown other than the roles of the bitte...

Perchlorate exposure is associated with oxidative stress and indicators of serum iron homeostasis among NHANES 2005-2008 subjects

EPA Science Inventory

ABSTRACT Perchlorate (ClO4-), an oxidizing agent, is a ubiquitous environmental pollutant. Several studies have investigated its thyroid hormone disrupting properties. Its associations with other biological measures are largely unknown. This study, combining 2005-2008 National H...

Vitamin and Mineral Supplements Have a Nutritionally Significant Impact on Micronutrient Intakes of Older Adults Attending Senior Centers

USDA-ARS?s Scientific Manuscript database

Background: Older adults frequently report use of vitamin and mineral (VM) supplements, though the impact of supplements on dietary adequacy remains largely unknown. Despite possible improvements in dietary intake, concern remains over potential excessive nutrient consumption from VM supplement us...

Body shape, burst speed and escape behavior of larval anurans

Treesearch

Gage H. Dayton; Daniel Saenz; Kristen A. Baum; R. Brian Langerhans; Thomas J. DeWitt

2005-01-01

Variation in behavior, morphology and life history traits of larval anurans across predator gradients, and consequences of that variation, have been abundantly studied. Yet the functional link between morphology and burst-swimming speed is largely unknown. We conducted experiments with two divergent species of anurans, Scaphiopus holbrookii and

Industrial Manufacture and Use of Nanocomponents & Their Role in the Life Cycle Impact of Nanoproducts

EPA Science Inventory

The development of methods and processes to mass produce nanocomponents, materials with characteristic lengths less than 100 nm, has led to the emergence of a large number of consumer goods (nanoproducts) containing these materials. The unknown health effects and risks associate...

Spatial probability models of fire in the desert grasslands of the southwestern USA

USDA-ARS?s Scientific Manuscript database

Fire is an important driver of ecological processes in semiarid environments; however, the role of fire in desert grasslands of the Southwestern US is controversial and the regional fire distribution is largely unknown. We characterized the spatial distribution of fire in the desert grassland region...

Australian Adolescents' Extracurricular Activity Participation and Positive Development: Is the Relationship Mediated by Peer Attributes?

ERIC Educational Resources Information Center

Blomfield, Corey; Barber, Bonnie

2010-01-01

Adolescent participation in extracurricular activities is associated with numerous positive outcomes, yet the mechanisms underlying this relationship are largely unknown. This study had two goals: to investigate the association between participation in extracurricular activities and indicators of positive and negative development for Australian…

Intercultural Identity and Intercultural Experiences of American Students in China

ERIC Educational Resources Information Center

Tian, Mei; Lowe, John Anthony

2014-01-01

The number of international students in China is increasing rapidly, but their experiences in China remain largely unknown. This article reports an intensive longitudinal multiple case study that explores eight American students' intercultural experiences and the impacts of such experiences on individual identity during their study in a Chinese…

Vygotsky's Legacy: A Foundation for Research and Practice

ERIC Educational Resources Information Center

Gredler, Margaret E.; Shields, Carolyn Claytor

2007-01-01

Most educators are familiar with Lev Vygotsky's concept of the "zone of proximal development," yet the bulk of Vygotsky's pioneering theory of cognitive development largely remains unknown. This volume provides a systematic, authoritative overview of Vygotsky's work and its implications for educational research and practice. Major topics include…

Proteome Profiling of BEAS-2B Cells Treated with Titanium Dioxide Reveals Potential Toxicity of and Detoxification Pathways for Nanomaterial

EPA Science Inventory

Oxidative stress is known to play important roles in nanomaterial-induced toxicities. However, the proteins and signaling pathways associated with nanomaterial-mediated oxidative stress and toxicity are largely unknown. To identify oxidative stress-responding toxicity pathways an...

Proteome Profiling Reveals Potential Toxicity and Detoxification Pathways Following Exposure of BEAS-2B Cells to Engineered Titanium Dioxide Nanoparticles

EPA Science Inventory

Oxidative stress is known to play important roles in engineered nanomaterial induced cellular toxicity. However, the proteins and signaling pathways associated with the engineered nanomaterial mediated oxidative stress and toxicity are largely unknown. To identify these toxicity ...

Disruption of microRNA expression in human airway cells by diesel exhaust particles is linked to tumorigenesis-associated pathways

EPA Science Inventory

Background: Particulate matter is associated with adverse airway health effects; however, the underlying mechanism in disease initiation is still largely unknown. Recently, microRNAs (small noncoding RNAs) have been suggested as important in maintaining the lung in a disease free...

Why environmental scientists are becoming Bayesians

Treesearch

James S. Clark

2005-01-01

Advances in computational statistics provide a general framework for the high dimensional models typically needed for ecological inference and prediction. Hierarchical Bayes (HB) represents a modelling structure with capacity to exploit diverse sources of information, to accommodate influences that are unknown (or unknowable), and to draw inference on large numbers of...

The Essential Gene EMB1611 Maintains Shoot Apical Meristem Function During Arabidopsis Development

USDA-ARS?s Scientific Manuscript database

The Arabidopsis thaliana genome contains hundreds of genes essential for seed development. Because null mutations in these genes cause embryo lethality, their specific molecular and developmental functions are largely unknown. Here, we identify a role for EMB1611/MEE22, an essential gene in Arabidop...

Recent tree die-off has little effect on streamflow in contrast to expected increases from historical studies

USDA-ARS?s Scientific Manuscript database

Recent bark beetle epidemics have caused regional-scale tree mortality in many snowmelt-dominated headwater catchments of western North America. Initial expectations of increased streamflow have not been supported by observations, and the basin-scale response of annual streamflow is largely unknown....

Students' Perception of Homework Assignments and What Influences Their Ideas

ERIC Educational Resources Information Center

Letterman, Denise

2013-01-01

Authors have researched the effects of homework, but few studies have delved into the idea of students' attitude towards homework. Consequently, students' perception of homework, the principal participants, remains largely unknown. Students' experience in homework that started as early as elementary school has influenced their ideas of homework.…

The Development of Executive Functions and Early Mathematics: A Dynamic Relationship

ERIC Educational Resources Information Center

Van der Ven, Sanne H. G.; Kroesbergen, Evelyn H.; Boom, Jan; Leseman, Paul P. M.

2012-01-01

Background: The relationship between executive functions and mathematical skills has been studied extensively, but results are inconclusive, and how this relationship evolves longitudinally is largely unknown. Aim: The aim was to investigate the factor structure of executive functions in inhibition, shifting, and updating; the longitudinal…

A maize caffeoyl-CoA O-methyltransferase gene confers quantitative resistance to multiple pathogens

USDA-ARS?s Scientific Manuscript database

Alleles that confer multiple disease resistance (MDR) are valuable in crop improvement though molecular mechanisms underlying their functions remain largely unknown. A QTL, qMdr9.02, associated with resistance to three important foliar maize diseases, southern leaf blight (SLB), gray leaf spot (GLS)...

Seroprevalence of Toxoplasma gondii infection in domestic sheep in Durango State, Mexico

USDA-ARS?s Scientific Manuscript database

The seroprevalence of Toxoplasma gondii infection in sheep in northern Mexico is largely unknown. Antibodies to T. gondii were determined in serum samples from 511 sheep from 8 farms in Durango State, Mexico using the modified agglutination test (MAT). Sheep were raised in 3 geographical regions, i....

Crop rotations and poultry litter impact dynamic soil chemical properties and soil biota long-term

USDA-ARS?s Scientific Manuscript database

Dynamic soil physiochemical interactions with conservation agricultural practices and soil biota are largely unknown. Therefore, this study aims to quantify long-term (12-yr) impacts of cover crops, poultry litter, crop rotations, and conservation tillage and their interactions on soil physiochemica...

Soil classification and carbon storage in cacao agroforestry farming systems of Bahia, Brazil

USDA-ARS?s Scientific Manuscript database

Information concerning the classification of soils and their properties under cacao agroforestry systems of the Atlantic rain forest biome region in the Southeast of Bahia Brazil is largely unknown. Soil and climatic conditions in this region are favorable for high soil carbon storage. This study is...

Everyday Cognitive Failures and Memory Problems in Parkinson's Patients without Dementia

ERIC Educational Resources Information Center

Poliakoff, Ellen; Smith-Spark, James H.

2008-01-01

There is growing evidence that Parkinson's disease patients without dementia exhibit cognitive deficits in some executive, memory and selective attention tasks. However, the impact of these deficits on their everyday cognitive functioning remains largely unknown. This issue was explored using self-report questionnaires. Twenty-four Parkinson's…

ENVIRONMENTALLY STRATIFIED SAMPLING DESIGN FOR THE DEVELOPMENT OF THE GREAT LAKES ENVIRONMENTAL INDICATORS

EPA Science Inventory

Ecological indicators must be shown to be responsive to stress. For large-scale observational studies the best way to demonstrate responsiveness is by evaluating indicators along a gradient of stress, but such gradients are often unknown for a population of sites prior to site se...

Response to Comments by V. N. Manskikh: "Do External or Internal Factors Lead to Tumor Development? It Is Still Unknown".

PubMed

Lichtenstein, A V

2017-01-01

The opinion is presented according to which the "bad luck" hypothesis (Tomasetti, C., and Vogelstein, B. (2015) Science, 347, 78-81), which has recently received experimental confirmation, has the right to exist, and its criticisms are largely unfounded.

A Hierarchic System for Information Usage.

ERIC Educational Resources Information Center

Lu, John; Markham, David

This paper demonstrates an approach which enables one to reduce in a systematic way the immense complexity of a large body of knowledge. This approach provides considerable insight into what is known and unknown in a given academic field by systematically and pragmatically ordering the information. As a case study, the authors selected…

Digital Media and Emergent Literacy

ERIC Educational Resources Information Center

Hisrich, Katy; Blanchard, Jay

2009-01-01

This article discusses digital media and its potential effects on emergent literacy skills development for young children. While the impact of digital media exposure on children's emergent literacy development is largely unknown, it is becoming a significant issue, as more and more young children throughout the world observe and use various forms…

Adult Psychopathology and Intimate Partner Violence among Survivors of Childhood Maltreatment

ERIC Educational Resources Information Center

Lang, Ariel J.; Stein, Murray B.; Kennedy, Colleen M.; Foy, David W.

2004-01-01

Childhood maltreatment is associated with psychopathology and revictimization in adulthood. Whether different types of childhood maltreatment have different long-term consequences, however, is largely unknown. The participants in this study included 42 female victims of intimate partner violence and 30 women with no history of serious trauma.…

Arithmetic and Brain Connectivity: Mental Calculation in Adolescents with Periventricular Lesions

ERIC Educational Resources Information Center

Pavlova, Marina; Sokolov, Alexander N.; Krageloh-Mann, Ingeborg

2009-01-01

The ability for mental calculation represents a fundamental prerequisite for development of intelligence, which is predictive for educational and professional success in life. Many individuals with calculation difficulties are survivors of premature birth. The brain mechanisms of these deficits are, however, largely unknown. In this work, we…

77 FR 55091 - National Childhood Cancer Awareness Month, 2012

Federal Register 2010, 2011, 2012, 2013, 2014

2012-09-06

... Proclamation Every year, thousands of children across America are diagnosed with cancer--an often life-threatening illness that remains the leading cause of death by disease for children under the age of 15. The causes of pediatric cancer are still largely unknown, and though new discoveries are resulting in new...

Investigating crosstalk between heat tolerance and redox status through suppressor screening of EMS mutagenized Arabidopsis monothioglutaredoxin GRXS17 mutants

USDA-ARS?s Scientific Manuscript database

Global environmental temperature changes threaten innumerable plant species. While various signaling networks regulate plant responses to heat stress (HS), the mechanisms unifying these diverse processes are largely unknown. The thioredoxin (Trx) and glutaredoxin (Grx) systems help control cellular ...

The Resin and Carder bees of south India (Hymenoptera: Megachilidae: Anthidiini)

USDA-ARS?s Scientific Manuscript database

Little is known about the Anthidiini of southern India. A study focused on the state of Karnataka found a hitherto unknown diversity of thirteen species. Though the number of species is not large, the generic diversity is noteworthy (eight genera represented): Anthidiellum (2 species), Anthidium (2 ...

Gene expression profiling in chicken heterophils with Salmonella enteritidis stimulation using a chicken 44 K Agilent microarray

USDA-ARS?s Scientific Manuscript database

Salmonella enterica serovar Enteritidis (SE) is one of the most common food-borne pathogens that cause human salmonellosis and usually results from the consumption of contaminated poultry products. The mechanism of SE resistance in chickens remains largely unknown. Previously, heterophils isolated...

Cold temperature delays wound healing in postharvest sugarbeet roots

USDA-ARS?s Scientific Manuscript database

Storage temperature affects the rate and extent of wound-healing in a number of root and tuber crops. The effect of storage temperature on wound-healing in sugarbeet (Beta vulgaris L.) roots, however, is largely unknown. Wound-healing of sugarbeet roots was investigated using surface-abraded roots s...

Drosophila Kruppel homolog 1 represses lipolysis through interactions with dFOXO

USDA-ARS?s Scientific Manuscript database

Juvenile hormone (JH) is a key endocrine signal involved in insect molting and metamorphosis. Recent studies suggest that JH is involved in not only development programming, but also in metabolic control. However, how JH modulates metabolism remains largely unknown. It has been shown that JH induces...

Dyadic Processes in Early Marriage: Attributions, Behavior, and Marital Quality

ERIC Educational Resources Information Center

Durtschi, Jared A.; Fincham, Frank D.; Cui, Ming; Lorenz, Frederick O.; Conger, Rand D.

2011-01-01

Marital processes in early marriage are important for understanding couples' future marital quality. Spouses' attributions about a partner's behavior have been linked to marital quality, yet the mechanisms underlying this association remain largely unknown. When we used couple data from the Family Transitions Project (N = 280 couples) across the…

Population structure and molecular characterization of Nigerian field genebank collections of cacao, Theobroma cacao L

USDA-ARS?s Scientific Manuscript database

Over the last 130 years since cacao introduction into Nigeria, genetic variability in cacao cultivated which has increased as a result of further introduction and breeding activities, remain largely unknown. To determine the genetic diversity and population structure of cacao populations, 13 cacao ...

The Enzyme Function Initiative†

PubMed Central

Gerlt, John A.; Allen, Karen N.; Almo, Steven C.; Armstrong, Richard N.; Babbitt, Patricia C.; Cronan, John E.; Dunaway-Mariano, Debra; Imker, Heidi J.; Jacobson, Matthew P.; Minor, Wladek; Poulter, C. Dale; Raushel, Frank M.; Sali, Andrej; Shoichet, Brian K.; Sweedler, Jonathan V.

2011-01-01

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily-specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include: 1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation); 2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia; 3) computational and bioinformatic tools for using the strategy; 4) provision of experimental protocols and/or reagents for enzyme production and characterization; and 5) dissemination of data via the EFI’s website, enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal and pharmaceutical efforts. PMID:21999478

The Enzyme Function Initiative.

PubMed

Gerlt, John A; Allen, Karen N; Almo, Steven C; Armstrong, Richard N; Babbitt, Patricia C; Cronan, John E; Dunaway-Mariano, Debra; Imker, Heidi J; Jacobson, Matthew P; Minor, Wladek; Poulter, C Dale; Raushel, Frank M; Sali, Andrej; Shoichet, Brian K; Sweedler, Jonathan V

2011-11-22

The Enzyme Function Initiative (EFI) was recently established to address the challenge of assigning reliable functions to enzymes discovered in bacterial genome projects; in this Current Topic, we review the structure and operations of the EFI. The EFI includes the Superfamily/Genome, Protein, Structure, Computation, and Data/Dissemination Cores that provide the infrastructure for reliably predicting the in vitro functions of unknown enzymes. The initial targets for functional assignment are selected from five functionally diverse superfamilies (amidohydrolase, enolase, glutathione transferase, haloalkanoic acid dehalogenase, and isoprenoid synthase), with five superfamily specific Bridging Projects experimentally testing the predicted in vitro enzymatic activities. The EFI also includes the Microbiology Core that evaluates the in vivo context of in vitro enzymatic functions and confirms the functional predictions of the EFI. The deliverables of the EFI to the scientific community include (1) development of a large-scale, multidisciplinary sequence/structure-based strategy for functional assignment of unknown enzymes discovered in genome projects (target selection, protein production, structure determination, computation, experimental enzymology, microbiology, and structure-based annotation), (2) dissemination of the strategy to the community via publications, collaborations, workshops, and symposia, (3) computational and bioinformatic tools for using the strategy, (4) provision of experimental protocols and/or reagents for enzyme production and characterization, and (5) dissemination of data via the EFI's Website, http://enzymefunction.org. The realization of multidisciplinary strategies for functional assignment will begin to define the full metabolic diversity that exists in nature and will impact basic biochemical and evolutionary understanding, as well as a wide range of applications of central importance to industrial, medicinal, and pharmaceutical efforts. © 2011 American Chemical Society

Improving Bayesian credibility intervals for classifier error rates using maximum entropy empirical priors.

PubMed

Gustafsson, Mats G; Wallman, Mikael; Wickenberg Bolin, Ulrika; Göransson, Hanna; Fryknäs, M; Andersson, Claes R; Isaksson, Anders

2010-06-01

Successful use of classifiers that learn to make decisions from a set of patient examples require robust methods for performance estimation. Recently many promising approaches for determination of an upper bound for the error rate of a single classifier have been reported but the Bayesian credibility interval (CI) obtained from a conventional holdout test still delivers one of the tightest bounds. The conventional Bayesian CI becomes unacceptably large in real world applications where the test set sizes are less than a few hundred. The source of this problem is that fact that the CI is determined exclusively by the result on the test examples. In other words, there is no information at all provided by the uniform prior density distribution employed which reflects complete lack of prior knowledge about the unknown error rate. Therefore, the aim of the study reported here was to study a maximum entropy (ME) based approach to improved prior knowledge and Bayesian CIs, demonstrating its relevance for biomedical research and clinical practice. It is demonstrated how a refined non-uniform prior density distribution can be obtained by means of the ME principle using empirical results from a few designs and tests using non-overlapping sets of examples. Experimental results show that ME based priors improve the CIs when employed to four quite different simulated and two real world data sets. An empirically derived ME prior seems promising for improving the Bayesian CI for the unknown error rate of a designed classifier. Copyright 2010 Elsevier B.V. All rights reserved.

Childhood exposure to green space - A novel risk-decreasing mechanism for schizophrenia?

PubMed

Engemann, Kristine; Pedersen, Carsten Bøcker; Arge, Lars; Tsirogiannis, Constantinos; Mortensen, Preben Bo; Svenning, Jens-Christian

2018-03-21

Schizophrenia risk has been linked to urbanization, but the underlying mechanism remains unknown. Green space is hypothesized to positively influence mental health and might mediate risk of schizophrenia by mitigating noise and particle pollution exposure, stress relief, or other unknown mechanisms. The objectives for this study were to determine if green space are associated with schizophrenia risk, and if different measures of green space associate differently with risk. We used satellite data from the Landsat program to quantify green space in a new data set for Denmark at 30×30m resolution for the years 1985-2013. The effect of green space at different ages and within different distances from each person's place of residence on schizophrenia risk was estimated using Cox regression on a very large longitudinal population-based sample of the Danish population (943,027 persons). Living at the lowest amount of green space was associated with a 1.52-fold increased risk of developing schizophrenia compared to persons living at the highest level of green space. This association remained after adjusting for known risk factors for schizophrenia: urbanization, age, sex, and socioeconomic status. The strongest protective association was observed during the earliest childhood years and closest to place of residence. This is the first nationwide population-based study to demonstrate a protective association between green space during childhood and schizophrenia risk; suggesting limited green space as a novel environmental risk factor for schizophrenia. This study supports findings from other studies highlighting positive effects of exposure to natural environments for human health. Copyright © 2018 Elsevier B.V. All rights reserved.

Diversity and Habitat Preferences of Cultivated and Uncultivated Aerobic Methanotrophic Bacteria Evaluated Based on pmoA as Molecular Marker

PubMed Central

Knief, Claudia

2015-01-01

Methane-oxidizing bacteria are characterized by their capability to grow on methane as sole source of carbon and energy. Cultivation-dependent and -independent methods have revealed that this functional guild of bacteria comprises a substantial diversity of organisms. In particular the use of cultivation-independent methods targeting a subunit of the particulate methane monooxygenase (pmoA) as functional marker for the detection of aerobic methanotrophs has resulted in thousands of sequences representing “unknown methanotrophic bacteria.” This limits data interpretation due to restricted information about these uncultured methanotrophs. A few groups of uncultivated methanotrophs are assumed to play important roles in methane oxidation in specific habitats, while the biology behind other sequence clusters remains still largely unknown. The discovery of evolutionary related monooxygenases in non-methanotrophic bacteria and of pmoA paralogs in methanotrophs requires that sequence clusters of uncultivated organisms have to be interpreted with care. This review article describes the present diversity of cultivated and uncultivated aerobic methanotrophic bacteria based on pmoA gene sequence diversity. It summarizes current knowledge about cultivated and major clusters of uncultivated methanotrophic bacteria and evaluates habitat specificity of these bacteria at different levels of taxonomic resolution. Habitat specificity exists for diverse lineages and at different taxonomic levels. Methanotrophic genera such as Methylocystis and Methylocaldum are identified as generalists, but they harbor habitat specific methanotrophs at species level. This finding implies that future studies should consider these diverging preferences at different taxonomic levels when analyzing methanotrophic communities. PMID:26696968

Changes of the Electrical and Optical Character of Polyimide Films Due to Exposure to High Energy GEO-like Electrons and the Chemistry that Drives it

NASA Astrophysics Data System (ADS)

Hoffmann, R.; Cooper, R.; Ferguson, D.

As a result of the interaction between the spacecraft and its operational environment, the constituent materials begin to change. These changes are determined by a combination of: chemical reactions, contamination, and energy deposition. They can range in severity from negligible to total loss of the material. Virtually all properties of the material, the mechanical, optical/thermal, and electrical are altered in largely unknown ways from the pristine materials. This negatively impacts the ability of spacecraft operators to predict the behavior of a spacecraft as it ages its environment. For example, in the case of electrical conduction in polyimide, there is a three orders of magnitude decrease in the resistivity after only eight months of simulated GEO electron exposure. Optical changes in the material also dramatically impact the ability of ground based optical observations to identify and track both known and unknown spacecraft. We will be presenting work done within the Spacecraft Charging and Instrument Calibration Lab at AFRL/RVB to quantify the changes in total reflection, BRDF, and electrical conduction of aluminized polyimide film after simulated aging in a GEO-like electron environment. We correlate these data with the chemical structure of the film as determined by XPS and NMR. A deeper, predictive understanding of how materials change will not only increase the operational lifetime of space assets by providing more accurate data to operators, it will improve SSA by allowing ground based observers to more accurately deduce component materials and determine how long a spacecraft has been in orbit.

Contact allergy in patients with rosacea: a clinic-based, prospective epidemiological study.

PubMed

Jappe, U; Schäfer, T; Schnuch, A; Uter, W

2008-11-01

Rosacea is a relatively common inflammatory skin disease of unknown prevalence. The proportion of contact allergy complicating rosacea and its therapy, respectively, is largely unknown. To estimate the prevalence of specific contact allergy in rosacea patients and to compare this with the prevalence observed in the general population and in general patch test patients. In this prospective monocentre study, 78 patients with rosacea were investigated for contact sensitizations via patch testing the standard series, constituents of topical formulations, preservatives, fragrances, topically applied drugs and, if available, patient's own products. Positive reactions occurred to nickel (II) sulphate (12 of 78, 15.4%), fragrance mix I (4 of 77, 5.2%), balsam of Peru (8 of 77, 10.4%; significantly elevated prevalence compared to that observed in the population-based KORA study), potassium dichromate (4 of 78, 5.1%) and Lyral (3 of 78, 3.8%). Regarding topical antibiotics, only 1 of 78 (1.3%) patients was positive to neomycin sulphate, and none to metronidazole; however, 6 of 75 (8%) patients were positive to gentamicin sulphate, and 4 of 76 (5.3%) patients were positive to framycetin sulphate. No allergic but irritant patch test reactions, instead, were provoked by various patients' own products as well as by the irritant sodium lauryl sulphate (SLS) even in low concentrations. Despite the limited power of the study, a strikingly high prevalence of contact allergy to gentamicin sulphate was observed, which is probably due to antibiotic treatment of rosacea-associated eye symptoms. The reactions to the irritant SLS probably mirror the extreme skin sensitivity in rosacea.

Water cavities of sH clathrate hydrate stabilized by molecular hydrogen.

PubMed

Strobel, Timothy A; Koh, Carolyn A; Sloan, E Dendy

2008-02-21

X-ray diffraction and Raman spectroscopic measurements confirm that molecular hydrogen can be contained within the small water cavities of a binary sH clathrate hydrate using large guest molecules that stabilize the large cavity. The potential increase in hydrogen storage could be more than 40% when compared with binary sII hydrates. This work demonstrates the stabilization of hydrogen in a hydrate structure previously unknown for encapsulating molecular hydrogen, indicating the potential for other inclusion compound materials with even greater hydrogen storage capabilities.

Estimation of the Arrival Time and Duration of a Radio Signal with Unknown Amplitude and Initial Phase

NASA Astrophysics Data System (ADS)

Trifonov, A. P.; Korchagin, Yu. E.; Korol'kov, S. V.

2018-05-01

We synthesize the quasi-likelihood, maximum-likelihood, and quasioptimal algorithms for estimating the arrival time and duration of a radio signal with unknown amplitude and initial phase. The discrepancies between the hardware and software realizations of the estimation algorithm are shown. The characteristics of the synthesized-algorithm operation efficiency are obtained. Asymptotic expressions for the biases, variances, and the correlation coefficient of the arrival-time and duration estimates, which hold true for large signal-to-noise ratios, are derived. The accuracy losses of the estimates of the radio-signal arrival time and duration because of the a priori ignorance of the amplitude and initial phase are determined.

Tune-stabilized, non-scaling, fixed-field, alternating gradient accelerator

DOEpatents

Johnstone, Carol J [Warrenville, IL

2011-02-01

A FFAG is a particle accelerator having turning magnets with a linear field gradient for confinement and a large edge angle to compensate for acceleration. FODO cells contain focus magnets and defocus magnets that are specified by a number of parameters. A set of seven equations, called the FFAG equations relate the parameters to one another. A set of constraints, call the FFAG constraints, constrain the FFAG equations. Selecting a few parameters, such as injection momentum, extraction momentum, and drift distance reduces the number of unknown parameters to seven. Seven equations with seven unknowns can be solved to yield the values for all the parameters and to thereby fully specify a FFAG.

A definition of unknown parent groups based on bull usage patterns across herds.

PubMed

Bouquet, A; Renand, G; Phocas, F

2011-03-01

In genetic evaluations, the definition of unknown parent groups (UPG) is usually based on time periods, selection path and flows of foreign founders. The definition of UPG may be more complex for populations presenting genetic heterogeneity due to both, large national expansion and coexistence of artificial insemination (AI) and natural service (NS). A UPG definition method accounting for beef bull flows was proposed and applied to the French Charolais cattle population. It assumed that, at a given time period, unknown parents belonged to the same UPG when their progeny were bred in herds that used bulls with similar origins (birth region and reproduction way). Thus, the birth period, region and AI rate of a herd were pointed out to be the three criteria reflecting genetic disparities at the national level in a beef cattle population. To deal with regional genetic disparities, 14 regions were identified using a factorial approach combining principal component analysis and Ward clustering. The selection nucleus of the French cattle population was dispersed over three main breeding areas. Flows of NS bulls were mainly carried out within each breeding area. On the contrary, the use and the selection of AI bulls were based on a national pool of candidates. Within a time period, herds of different regions were clustered together when they used bulls coming from the same origin and with an estimated difference of genetic level lower than 20% of genetic standard deviation (σg) for calf muscle and skeleton scores (SS) at weaning. This led to the definition of 16 UPG of sires, which were validated as robust and relevant in a sire model, meaning numerically stable and corresponding to distinct genetic subpopulations. The UPG genetic levels were estimated for muscle and SS under sire and animal models. Whatever the trait, differences between bull UPG estimates within a time period could reach 0.5 σg across regions. For a given time period, bull UPG estimates for muscle and SS were generally larger by 0.30 to 0.75 σg than those of cows. Including genetic groups in the evaluation model increased the estimated genetic trends by 20% to 30%. It also provoked re-ranking in favor of bulls and cows without pedigree.

Investigation of Vapor Cooling Enhancements for Applications on Large Cryogenic Systems

NASA Technical Reports Server (NTRS)

Ameen, Lauren; Zoeckler, Joseph

2017-01-01

The need to demonstrate and evaluate the effectiveness of heat interception methods for use on a relevant cryogenic propulsion stage at a system level has been identified. Evolvable Cryogenics (eCryo) Structural Heat Intercept, Insulation and Vibration Evaluation Rig (SHIIVER) will be designed with vehicle specific geometries (SLS Exploration Upper Stage (EUS) as guidance) and will be subjected to simulated space environments. One method of reducing structure-born heat leak being investigated utilizes vapor-based heat interception. Vapor-based heat interception could potentially reduce heat leak into liquid hydrogen propulsion tanks, increasing potential mission length or payload capability. Due to the high number of unknowns associated with the heat transfer mechanism and integration of vapor-based heat interception on a realistic large-scale skirt design, a sub-scale investigation was developed. The sub-project effort is known as the Small-scale Laboratory Investigation of Cooling Enhancements (SLICE). The SLICE aims to study, design, and test sub-scale multiple attachments and flow configuration concepts for vapor-based heat interception of structural skirts. SLICE will focus on understanding the efficiency of the heat transfer mechanism to the boil-off hydrogen vapor by varying the fluid network designs and configurations. Various analyses were completed in MATLAB, Excel VBA, and COMSOL Multiphysics to understand the optimum flow pattern for heat transfer and fluid dynamics. Results from these analyses were used to design and fabricate test article subsections of a large forward skirt with vapor cooling applied. The SLICE testing is currently being performed to collect thermal mechanical performance data on multiple skirt heat removal designs while varying inlet vapor conditions necessary to intercept a specified amount of heat for a given system. Initial results suggest that applying vapor-cooling provides a 50 heat reduction in conductive heat transmission along the skirt to the tank. The information obtained by SLICE will be used by the SHIIVER engineering team to design and implement vapor-based heat removal technology into the SHIIVER forward skirt hardware design.

A Bayesian nonparametric approach to dynamical noise reduction

NASA Astrophysics Data System (ADS)

Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

2018-06-01

We propose a Bayesian nonparametric approach for the noise reduction of a given chaotic time series contaminated by dynamical noise, based on Markov Chain Monte Carlo methods. The underlying unknown noise process (possibly) exhibits heavy tailed behavior. We introduce the Dynamic Noise Reduction Replicator model with which we reconstruct the unknown dynamic equations and in parallel we replicate the dynamics under reduced noise level dynamical perturbations. The dynamic noise reduction procedure is demonstrated specifically in the case of polynomial maps. Simulations based on synthetic time series are presented.

Study of Cetane Properties of ATJ Blends Based on World Survey of Jet Fuels

DTIC Science & Technology

2016-01-28

49.84 N/A N/A N/A 46.92 N/A N/A N/A 12 (100% Syn.) 1 57.79 N/A N/A N/A 53.48 N/A N/A N/A a - Conventional petroleum based jet fuel; b - Oil Shale ...Australia (% Nitrogen content unknown) c - Oil Shale , Australia (Low Nitrogen); d - Oil Shale , Australia (High Nitrogen) U/A – Unavailable in PQIS...fuel b - Oil Shale , Australia (% Nitrogen content unknown) c - Oil Shale , Australia (Low Nitrogen) d - Oil Shale , Australia (High Nitrogen) U/A

Implications for plastic flow in the deep mantle from modelling dislocations in MgSiO3 minerals.

PubMed

Carrez, Philippe; Ferré, Denise; Cordier, Patrick

2007-03-01

The dynamics of the Earth's interior is largely controlled by mantle convection, which transports radiogenic and primordial heat towards the surface. Slow stirring of the deep mantle is achieved in the solid state through high-temperature creep of rocks, which are dominated by the mineral MgSiO3 perovskite. Transformation of MgSiO3 to a 'post-perovskite' phase may explain the peculiarities of the lowermost mantle, such as the observed seismic anisotropy, but the mechanical properties of these mineralogical phases are largely unknown. Plastic flow of solids involves the motion of a large number of crystal defects, named dislocations. A quantitative description of flow in the Earth's mantle requires information about dislocations in high-pressure minerals and their behaviour under stress. This property is currently out of reach of direct atomistic simulations using either empirical interatomic potentials or ab initio calculations. Here we report an alternative to direct atomistic simulations based on the framework of the Peierls-Nabarro model. Dislocation core models are proposed for MgSiO3 perovskite (at 100 GPa) and post-perovskite (at 120 GPa). We show that in perovskite, plastic deformation is strongly influenced by the orthorhombic distortions of the unit cell. In silicate post-perovskite, large dislocations are relaxed through core dissociation, with implications for the mechanical properties and seismic anisotropy of the lowermost mantle.

Drought rapidly diminishes the large net CO2 uptake in 2011 over semi-arid Australia

PubMed Central

Ma, Xuanlong; Huete, Alfredo; Cleverly, James; Eamus, Derek; Chevallier, Frédéric; Joiner, Joanna; Poulter, Benjamin; Zhang, Yongguang; Guanter, Luis; Meyer, Wayne; Xie, Zunyi; Ponce-Campos, Guillermo

2016-01-01

Each year, terrestrial ecosystems absorb more than a quarter of the anthropogenic carbon emissions, termed as land carbon sink. An exceptionally large land carbon sink anomaly was recorded in 2011, of which more than half was attributed to Australia. However, the persistence and spatially attribution of this carbon sink remain largely unknown. Here we conducted an observation-based study to characterize the Australian land carbon sink through the novel coupling of satellite retrievals of atmospheric CO2 and photosynthesis and in-situ flux tower measures. We show the 2010–11 carbon sink was primarily ascribed to savannas and grasslands. When all biomes were normalized by rainfall, shrublands however, were most efficient in absorbing carbon. We found the 2010–11 net CO2 uptake was highly transient with rapid dissipation through drought. The size of the 2010–11 carbon sink over Australia (0.97 Pg) was reduced to 0.48 Pg in 2011–12, and was nearly eliminated in 2012–13 (0.08 Pg). We further report evidence of an earlier 2000–01 large net CO2 uptake, demonstrating a repetitive nature of this land carbon sink. Given a significant increasing trend in extreme wet year precipitation over Australia, we suggest that carbon sink episodes will exert greater future impacts on global carbon cycle. PMID:27886216

Hierarchial mark-recapture models: a framework for inference about demographic processes

USGS Publications Warehouse

Link, W.A.; Barker, R.J.

2004-01-01

The development of sophisticated mark-recapture models over the last four decades has provided fundamental tools for the study of wildlife populations, allowing reliable inference about population sizes and demographic rates based on clearly formulated models for the sampling processes. Mark-recapture models are now routinely described by large numbers of parameters. These large models provide the next challenge to wildlife modelers: the extraction of signal from noise in large collections of parameters. Pattern among parameters can be described by strong, deterministic relations (as in ultrastructural models) but is more flexibly and credibly modeled using weaker, stochastic relations. Trend in survival rates is not likely to be manifest by a sequence of values falling precisely on a given parametric curve; rather, if we could somehow know the true values, we might anticipate a regression relation between parameters and explanatory variables, in which true value equals signal plus noise. Hierarchical models provide a useful framework for inference about collections of related parameters. Instead of regarding parameters as fixed but unknown quantities, we regard them as realizations of stochastic processes governed by hyperparameters. Inference about demographic processes is based on investigation of these hyperparameters. We advocate the Bayesian paradigm as a natural, mathematically and scientifically sound basis for inference about hierarchical models. We describe analysis of capture-recapture data from an open population based on hierarchical extensions of the Cormack-Jolly-Seber model. In addition to recaptures of marked animals, we model first captures of animals and losses on capture, and are thus able to estimate survival probabilities w (i.e., the complement of death or permanent emigration) and per capita growth rates f (i.e., the sum of recruitment and immigration rates). Covariation in these rates, a feature of demographic interest, is explicitly described in the model.

Proposed Confidence Scale and ID Score in the Identification of Known-Unknown Compounds Using High Resolution MS Data

NASA Astrophysics Data System (ADS)

Rochat, Bertrand

2017-04-01

High-resolution (HR) MS instruments recording HR-full scan allow analysts to go further beyond pre-acquisition choices. Untargeted acquisition can reveal unexpected compounds or concentrations and can be performed for preliminary diagnosis attempt. Then, revealed compounds will have to be identified for interpretations. Whereas the need of reference standards is mandatory to confirm identification, the diverse information collected from HRMS allows identifying unknown compounds with relatively high degree of confidence without reference standards injected in the same analytical sequence. However, there is a necessity to evaluate the degree of confidence in putative identifications, possibly before further targeted analyses. This is why a confidence scale and a score in the identification of (non-peptidic) known-unknown, defined as compounds with entries in database, is proposed for (LC-) HRMS data. The scale is based on two representative documents edited by the European Commission (2007/657/EC) and the Metabolomics Standard Initiative (MSI), in an attempt to build a bridge between the communities of metabolomics and screening labs. With this confidence scale, an identification (ID) score is determined as [a number, a letter, and a number] (e.g., 2D3), from the following three criteria: I, a General Identification Category (1, confirmed, 2, putatively identified, 3, annotated compounds/classes, and 4, unknown); II, a Chromatography Class based on the relative retention time (from the narrowest tolerance, A, to no chromatographic references, D); and III, an Identification Point Level (1, very high, 2, high, and 3, normal level) based on the number of identification points collected. Three putative identification examples of known-unknown will be presented.

Efficient Bayesian experimental design for contaminant source identification

NASA Astrophysics Data System (ADS)

Zhang, J.; Zeng, L.

2013-12-01

In this study, an efficient full Bayesian approach is developed for the optimal sampling well location design and source parameter identification of groundwater contaminants. An information measure, i.e., the relative entropy, is employed to quantify the information gain from indirect concentration measurements in identifying unknown source parameters such as the release time, strength and location. In this approach, the sampling location that gives the maximum relative entropy is selected as the optimal one. Once the sampling location is determined, a Bayesian approach based on Markov Chain Monte Carlo (MCMC) is used to estimate unknown source parameters. In both the design and estimation, the contaminant transport equation is required to be solved many times to evaluate the likelihood. To reduce the computational burden, an interpolation method based on the adaptive sparse grid is utilized to construct a surrogate for the contaminant transport. The approximated likelihood can be evaluated directly from the surrogate, which greatly accelerates the design and estimation process. The accuracy and efficiency of our approach are demonstrated through numerical case studies. Compared with the traditional optimal design, which is based on the Gaussian linear assumption, the method developed in this study can cope with arbitrary nonlinearity. It can be used to assist in groundwater monitor network design and identification of unknown contaminant sources. Contours of the expected information gain. The optimal observing location corresponds to the maximum value. Posterior marginal probability densities of unknown parameters, the thick solid black lines are for the designed location. For comparison, other 7 lines are for randomly chosen locations. The true values are denoted by vertical lines. It is obvious that the unknown parameters are estimated better with the desinged location.

Supervised Detection of Anomalous Light Curves in Massive Astronomical Catalogs

NASA Astrophysics Data System (ADS)

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos; Kim, Dae-Won

2014-09-01

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each of the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.

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

Nun, Isadora; Pichara, Karim; Protopapas, Pavlos

The development of synoptic sky surveys has led to a massive amount of data for which resources needed for analysis are beyond human capabilities. In order to process this information and to extract all possible knowledge, machine learning techniques become necessary. Here we present a new methodology to automatically discover unknown variable objects in large astronomical catalogs. With the aim of taking full advantage of all information we have about known objects, our method is based on a supervised algorithm. In particular, we train a random forest classifier using known variability classes of objects and obtain votes for each ofmore » the objects in the training set. We then model this voting distribution with a Bayesian network and obtain the joint voting distribution among the training objects. Consequently, an unknown object is considered as an outlier insofar it has a low joint probability. By leaving out one of the classes on the training set, we perform a validity test and show that when the random forest classifier attempts to classify unknown light curves (the class left out), it votes with an unusual distribution among the classes. This rare voting is detected by the Bayesian network and expressed as a low joint probability. Our method is suitable for exploring massive data sets given that the training process is performed offline. We tested our algorithm on 20 million light curves from the MACHO catalog and generated a list of anomalous candidates. After analysis, we divided the candidates into two main classes of outliers: artifacts and intrinsic outliers. Artifacts were principally due to air mass variation, seasonal variation, bad calibration, or instrumental errors and were consequently removed from our outlier list and added to the training set. After retraining, we selected about 4000 objects, which we passed to a post-analysis stage by performing a cross-match with all publicly available catalogs. Within these candidates we identified certain known but rare objects such as eclipsing Cepheids, blue variables, cataclysmic variables, and X-ray sources. For some outliers there was no additional information. Among them we identified three unknown variability types and a few individual outliers that will be followed up in order to perform a deeper analysis.« less