29 CFR 4022.3 - Guaranteed benefits.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 9 2014-07-01 2014-07-01 false Guaranteed benefits. 4022.3 Section 4022.3 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS General Provisions; Guaranteed Benefits § 4022.3 Guaranteed...

29 CFR 4022.3 - Guaranteed benefits.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 9 2013-07-01 2013-07-01 false Guaranteed benefits. 4022.3 Section 4022.3 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS General Provisions; Guaranteed Benefits § 4022.3 Guaranteed...

45 CFR 148.120 - Guaranteed availability of individual health insurance coverage to certain individuals with prior...

Code of Federal Regulations, 2011 CFR

2011-10-01

... DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS REQUIREMENTS FOR THE INDIVIDUAL HEALTH INSURANCE MARKET Requirements Relating to Access and Renewability of Coverage § 148.120... 45 Public Welfare 1 2011-10-01 2011-10-01 false Guaranteed availability of individual health...

45 CFR 148.120 - Guaranteed availability of individual health insurance coverage to certain individuals with prior...

Code of Federal Regulations, 2012 CFR

2012-10-01

... DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS REQUIREMENTS FOR THE INDIVIDUAL HEALTH INSURANCE MARKET Requirements Relating to Access and Renewability of Coverage § 148.120... 45 Public Welfare 1 2012-10-01 2012-10-01 false Guaranteed availability of individual health...

7 CFR 1493.40 - Application for payment guarantee.

Code of Federal Regulations, 2011 CFR

2011-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Export Credit Guarantee Program (GSM-102) and CCC Intermediate Export Credit Guarantee Program..., contract loading tolerance and, if necessary, a request for CCC to reserve coverage up to the maximum...

7 CFR 1493.40 - Application for payment guarantee.

Code of Federal Regulations, 2010 CFR

2010-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Export Credit Guarantee Program (GSM-102) and CCC Intermediate Export Credit Guarantee Program..., contract loading tolerance and, if necessary, a request for CCC to reserve coverage up to the maximum...

7 CFR 1493.430 - Application for a payment guarantee.

Code of Federal Regulations, 2010 CFR

2010-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier Credit Guarantee Program Operations § 1493.430 Application for a payment guarantee... request for CCC to reserve coverage up to the maximum quantity permitted by the contract loading tolerance...

7 CFR 1493.40 - Application for payment guarantee.

Code of Federal Regulations, 2012 CFR

2012-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Export Credit Guarantee Program (GSM-102) and CCC Intermediate Export Credit Guarantee Program (GSM-103) Operations § 1493..., if necessary, a request for CCC to reserve coverage up to the maximum quantity permitted by the...

7 CFR 1493.40 - Application for payment guarantee.

Code of Federal Regulations, 2014 CFR

2014-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Export Credit Guarantee Program (GSM-102) and CCC Intermediate Export Credit Guarantee Program (GSM-103) Operations § 1493..., if necessary, a request for CCC to reserve coverage up to the maximum quantity permitted by the...

7 CFR 1493.430 - Application for a payment guarantee.

Code of Federal Regulations, 2011 CFR

2011-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier Credit Guarantee Program Operations § 1493.430 Application for a payment guarantee... request for CCC to reserve coverage up to the maximum quantity permitted by the contract loading tolerance...

7 CFR 1493.40 - Application for payment guarantee.

Code of Federal Regulations, 2013 CFR

2013-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Export Credit Guarantee Program (GSM-102) and CCC Intermediate Export Credit Guarantee Program (GSM-103) Operations § 1493..., if necessary, a request for CCC to reserve coverage up to the maximum quantity permitted by the...

Removal of nuisance signals from limited and sparse 1H MRSI data using a union-of-subspaces model.

PubMed

Ma, Chao; Lam, Fan; Johnson, Curtis L; Liang, Zhi-Pei

2016-02-01

To remove nuisance signals (e.g., water and lipid signals) for (1) H MRSI data collected from the brain with limited and/or sparse (k, t)-space coverage. A union-of-subspace model is proposed for removing nuisance signals. The model exploits the partial separability of both the nuisance signals and the metabolite signal, and decomposes an MRSI dataset into several sets of generalized voxels that share the same spectral distributions. This model enables the estimation of the nuisance signals from an MRSI dataset that has limited and/or sparse (k, t)-space coverage. The proposed method has been evaluated using in vivo MRSI data. For conventional chemical shift imaging data with limited k-space coverage, the proposed method produced "lipid-free" spectra without lipid suppression during data acquisition at 130 ms echo time. For sparse (k, t)-space data acquired with conventional pulses for water and lipid suppression, the proposed method was also able to remove the remaining water and lipid signals with negligible residuals. Nuisance signals in (1) H MRSI data reside in low-dimensional subspaces. This property can be utilized for estimation and removal of nuisance signals from (1) H MRSI data even when they have limited and/or sparse coverage of (k, t)-space. The proposed method should prove useful especially for accelerated high-resolution (1) H MRSI of the brain. © 2015 Wiley Periodicals, Inc.

Uniform Recovery Bounds for Structured Random Matrices in Corrupted Compressed Sensing

NASA Astrophysics Data System (ADS)

Zhang, Peng; Gan, Lu; Ling, Cong; Sun, Sumei

2018-04-01

We study the problem of recovering an $s$-sparse signal $\\mathbf{x}^{\\star}\\in\\mathbb{C}^n$ from corrupted measurements $\\mathbf{y} = \\mathbf{A}\\mathbf{x}^{\\star}+\\mathbf{z}^{\\star}+\\mathbf{w}$, where $\\mathbf{z}^{\\star}\\in\\mathbb{C}^m$ is a $k$-sparse corruption vector whose nonzero entries may be arbitrarily large and $\\mathbf{w}\\in\\mathbb{C}^m$ is a dense noise with bounded energy. The aim is to exactly and stably recover the sparse signal with tractable optimization programs. In this paper, we prove the uniform recovery guarantee of this problem for two classes of structured sensing matrices. The first class can be expressed as the product of a unit-norm tight frame (UTF), a random diagonal matrix and a bounded columnwise orthonormal matrix (e.g., partial random circulant matrix). When the UTF is bounded (i.e. $\\mu(\\mathbf{U})\\sim1/\\sqrt{m}$), we prove that with high probability, one can recover an $s$-sparse signal exactly and stably by $l_1$ minimization programs even if the measurements are corrupted by a sparse vector, provided $m = \\mathcal{O}(s \\log^2 s \\log^2 n)$ and the sparsity level $k$ of the corruption is a constant fraction of the total number of measurements. The second class considers randomly sub-sampled orthogonal matrix (e.g., random Fourier matrix). We prove the uniform recovery guarantee provided that the corruption is sparse on certain sparsifying domain. Numerous simulation results are also presented to verify and complement the theoretical results.

Evaluation of fast highly undersampled contrast-enhanced MR angiography (sparse CE-MRA) in intracranial applications - initial study.

PubMed

Gratz, Marcel; Schlamann, Marc; Goericke, Sophia; Maderwald, Stefan; Quick, Harald H

2017-03-01

To assess the image quality of sparsely sampled contrast-enhanced MR angiography (sparse CE-MRA) providing high spatial resolution and whole-head coverage. Twenty-three patients scheduled for contrast-enhanced MR imaging of the head, (N = 19 with intracranial pathologies, N = 9 with vascular diseases), were included. Sparse CE-MRA at 3 Tesla was conducted using a single dose of contrast agent. Two neuroradiologists independently evaluated the data regarding vascular visibility and diagnostic value of overall 24 parameters and vascular segments on a 5-point ordinary scale (5 = very good, 1 = insufficient vascular visibility). Contrast bolus timing and the resulting arterio-venous overlap was also evaluated. Where available (N = 9), sparse CE-MRA was compared to intracranial Time-of-Flight MRA. The overall rating across all patients for sparse CE-MRA was 3.50 ± 1.07. Direct influence of the contrast bolus timing on the resulting image quality was observed. Overall mean vascular visibility and image quality across different features was rated good to intermediate (3.56 ± 0.95). The average performance of intracranial Time-of-Flight was rated 3.84 ± 0.87 across all patients and 3.54 ± 0.62 across all features. Sparse CE-MRA provides high-quality 3D MRA with high spatial resolution and whole-head coverage within short acquisition time. Accurate contrast bolus timing is mandatory. • Sparse CE-MRA enables fast vascular imaging with full brain coverage. • Volumes with sub-millimetre resolution can be acquired within 10 seconds. • Reader's ratings are good to intermediate and dependent on contrast bolus timing. • The method provides an excellent overview and allows screening for vascular pathologies.

Is It More Important to Address the Issue of Patient Mobility or to Guarantee Universal Health Coverage in Europe?

PubMed Central

Legido-Quigley, Helena

2016-01-01

This paper discusses whether European institutions should devote so much attention and funding to cross-border healthcare or they should instead prioritise guaranteeing universal health coverage (UHC), “addressing inequalities” and tackling the effects of austerity measures. The paper argues through providing the evidence in both areas of research, that the priority at European level from a public health and social justice perspective should be to guarantee UHC for all the population living in Europe and prioritise protective action for those who are most in need. PMID:26673649

45 CFR 148.122 - Guaranteed renewability of individual health insurance coverage.

Code of Federal Regulations, 2010 CFR

2010-10-01

... insurance coverage. 148.122 Section 148.122 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS REQUIREMENTS FOR THE INDIVIDUAL HEALTH INSURANCE MARKET... health insurance coverage. (a) Applicability. This section applies to all health insurance coverage in...

29 CFR 4022.22 - Maximum guaranteeable benefit.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 9 2010-07-01 2010-07-01 false Maximum guaranteeable benefit. 4022.22 Section 4022.22 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND... Maximum guaranteeable benefit. Subject to section 4022B of ERISA and part 4022B of this chapter, benefits...

Matrix Recipes for Hard Thresholding Methods

DTIC Science & Technology

2012-11-07

have been proposed to approximate the solution. In [11], Donoho et al . demonstrate that, in the sparse approximation problem, under basic incoherence...inducing convex surrogate ‖ · ‖1 with provable guarantees for unique signal recovery. In the ARM problem, Fazel et al . [12] identified the nuclear norm...sparse recovery for all. Technical report, EPFL, 2011 . [25] N. Halko , P. G. Martinsson, and J. A. Tropp. Finding structure with randomness: Probabilistic

Network Data: Statistical Theory and New Models

DTIC Science & Technology

2016-02-17

SECURITY CLASSIFICATION OF: During this period of review, Bin Yu worked on many thrusts of high-dimensional statistical theory and methodologies. Her...research covered a wide range of topics in statistics including analysis and methods for spectral clustering for sparse and structured networks...2,7,8,21], sparse modeling (e.g. Lasso) [4,10,11,17,18,19], statistical guarantees for the EM algorithm [3], statistical analysis of algorithm leveraging

7 CFR 457.3 - Premium rates, production guarantees or amounts of insurance, coverage levels, and prices at...

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 6 2010-01-01 2010-01-01 false Premium rates, production guarantees or amounts of... Agriculture Regulations of the Department of Agriculture (Continued) FEDERAL CROP INSURANCE CORPORATION, DEPARTMENT OF AGRICULTURE COMMON CROP INSURANCE REGULATIONS § 457.3 Premium rates, production guarantees or...

Is It More Important to Address the Issue of Patient Mobility or to Guarantee Universal Health Coverage in Europe?: Comment on "Regional Incentives and Patient Cross-Border Mobility: Evidence From the Italian Experience".

PubMed

Legido-Quigley, Helena

2015-09-02

This paper discusses whether European institutions should devote so much attention and funding to cross-border healthcare or they should instead prioritise guaranteeing universal health coverage (UHC), "addressing inequalities" and tackling the effects of austerity measures. The paper argues through providing the evidence in both areas of research, that the priority at European level from a public health and social justice perspective should be to guarantee UHC for all the population living in Europe and prioritise protective action for those who are most in need. © 2016 by Kerman University of Medical Sciences.

75 FR 4707 - Continuous Construction-Permanent Loan Guarantees Under the Section 538 Guaranteed Rural Rental...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-01-29

... for construction and permanent loans. Only projects that have low loan-to-cost ratios, as specified by... 538 program's debt service coverage ratio requirement of at least 1.15, based on the lender's analysis... CFR Part 3565 RIN-0575-AC80 Continuous Construction-Permanent Loan Guarantees Under the Section 538...

45 CFR 146.101 - Basis and scope.

Code of Federal Regulations, 2010 CFR

2010-10-01

... FOR THE GROUP HEALTH INSURANCE MARKET General Provisions § 146.101 Basis and scope. (a) Statutory... access to group health insurance coverage, to guarantee the renewability of all coverage in the group... group health plan or health insurance issuer offering group health insurance coverage may provide...

Convergence Speed of a Dynamical System for Sparse Recovery

NASA Astrophysics Data System (ADS)

Balavoine, Aurele; Rozell, Christopher J.; Romberg, Justin

2013-09-01

This paper studies the convergence rate of a continuous-time dynamical system for L1-minimization, known as the Locally Competitive Algorithm (LCA). Solving L1-minimization} problems efficiently and rapidly is of great interest to the signal processing community, as these programs have been shown to recover sparse solutions to underdetermined systems of linear equations and come with strong performance guarantees. The LCA under study differs from the typical L1 solver in that it operates in continuous time: instead of being specified by discrete iterations, it evolves according to a system of nonlinear ordinary differential equations. The LCA is constructed from simple components, giving it the potential to be implemented as a large-scale analog circuit. The goal of this paper is to give guarantees on the convergence time of the LCA system. To do so, we analyze how the LCA evolves as it is recovering a sparse signal from underdetermined measurements. We show that under appropriate conditions on the measurement matrix and the problem parameters, the path the LCA follows can be described as a sequence of linear differential equations, each with a small number of active variables. This allows us to relate the convergence time of the system to the restricted isometry constant of the matrix. Interesting parallels to sparse-recovery digital solvers emerge from this study. Our analysis covers both the noisy and noiseless settings and is supported by simulation results.

Sparse nonnegative matrix factorization with ℓ0-constraints

PubMed Central

Peharz, Robert; Pernkopf, Franz

2012-01-01

Although nonnegative matrix factorization (NMF) favors a sparse and part-based representation of nonnegative data, there is no guarantee for this behavior. Several authors proposed NMF methods which enforce sparseness by constraining or penalizing the ℓ1-norm of the factor matrices. On the other hand, little work has been done using a more natural sparseness measure, the ℓ0-pseudo-norm. In this paper, we propose a framework for approximate NMF which constrains the ℓ0-norm of the basis matrix, or the coefficient matrix, respectively. For this purpose, techniques for unconstrained NMF can be easily incorporated, such as multiplicative update rules, or the alternating nonnegative least-squares scheme. In experiments we demonstrate the benefits of our methods, which compare to, or outperform existing approaches. PMID:22505792

Extracting Vegetation Coverage in Dry-hot Valley Regions Based on Alternating Angle Minimum Algorithm

NASA Astrophysics Data System (ADS)

Y Yang, M.; Wang, J.; Zhang, Q.

2017-07-01

Vegetation coverage is one of the most important indicators for ecological environment change, and is also an effective index for the assessment of land degradation and desertification. The dry-hot valley regions have sparse surface vegetation, and the spectral information about the vegetation in such regions usually has a weak representation in remote sensing, so there are considerable limitations for applying the commonly-used vegetation index method to calculate the vegetation coverage in the dry-hot valley regions. Therefore, in this paper, Alternating Angle Minimum (AAM) algorithm of deterministic model is adopted for selective endmember for pixel unmixing of MODIS image in order to extract the vegetation coverage, and accuracy test is carried out by the use of the Landsat TM image over the same period. As shown by the results, in the dry-hot valley regions with sparse vegetation, AAM model has a high unmixing accuracy, and the extracted vegetation coverage is close to the actual situation, so it is promising to apply the AAM model to the extraction of vegetation coverage in the dry-hot valley regions.

Node Scheduling Strategies for Achieving Full-View Area Coverage in Camera Sensor Networks.

PubMed

Wu, Peng-Fei; Xiao, Fu; Sha, Chao; Huang, Hai-Ping; Wang, Ru-Chuan; Xiong, Nai-Xue

2017-06-06

Unlike conventional scalar sensors, camera sensors at different positions can capture a variety of views of an object. Based on this intrinsic property, a novel model called full-view coverage was proposed. We study the problem that how to select the minimum number of sensors to guarantee the full-view coverage for the given region of interest (ROI). To tackle this issue, we derive the constraint condition of the sensor positions for full-view neighborhood coverage with the minimum number of nodes around the point. Next, we prove that the full-view area coverage can be approximately guaranteed, as long as the regular hexagons decided by the virtual grid are seamlessly stitched. Then we present two solutions for camera sensor networks in two different deployment strategies. By computing the theoretically optimal length of the virtual grids, we put forward the deployment pattern algorithm (DPA) in the deterministic implementation. To reduce the redundancy in random deployment, we come up with a local neighboring-optimal selection algorithm (LNSA) for achieving the full-view coverage. Finally, extensive simulation results show the feasibility of our proposed solutions.

Node Scheduling Strategies for Achieving Full-View Area Coverage in Camera Sensor Networks

PubMed Central

Wu, Peng-Fei; Xiao, Fu; Sha, Chao; Huang, Hai-Ping; Wang, Ru-Chuan; Xiong, Nai-Xue

2017-01-01

Unlike conventional scalar sensors, camera sensors at different positions can capture a variety of views of an object. Based on this intrinsic property, a novel model called full-view coverage was proposed. We study the problem that how to select the minimum number of sensors to guarantee the full-view coverage for the given region of interest (ROI). To tackle this issue, we derive the constraint condition of the sensor positions for full-view neighborhood coverage with the minimum number of nodes around the point. Next, we prove that the full-view area coverage can be approximately guaranteed, as long as the regular hexagons decided by the virtual grid are seamlessly stitched. Then we present two solutions for camera sensor networks in two different deployment strategies. By computing the theoretically optimal length of the virtual grids, we put forward the deployment pattern algorithm (DPA) in the deterministic implementation. To reduce the redundancy in random deployment, we come up with a local neighboring-optimal selection algorithm (LNSA) for achieving the full-view coverage. Finally, extensive simulation results show the feasibility of our proposed solutions. PMID:28587304

House committees refuse to limit health plan abortion coverage.

PubMed

1994-06-24

Anti-choice efforts to eliminate and/or restrict abortion coverage in US health care reform proposals were overwhelmingly rejected by Congressional committees on June 22 and 23, 1994. The committees rejected Kentucky Republican Representative Jim Bunning's amendment to remove abortion services except in cases of life endangerment, rape, or incest; Wisconsin Democrat Gerald Kleczka's attempt to let health plans opt out of providing abortion coverage; Pennsylvania Republican Rick Santorum's attempt to prevent the health plan from preempting state constitutional laws and regulations on abortion; amendments by Pennsylvania Democrat Ron Klink to drop abortion coverage except in cases of life endangerment, rape, or incest, and to guarantee against the plan overturning state regulations on abortion; and an amendment by Wisconsin Republican Steve Gunderson to allow plans to single out abortion from the guaranteed benefits package and offer plans without that coverage as well as to allow self-insured businesses to opt out of abortion coverage. Moreover, a final proposal to move abortion services into an optional benefit category was withdrawn and the House Education and Labor Committee refused to endorse abortion restrictions in its version of Clinton's HR 3600 health care proposal. The Senate Labor and Human Resources Committee previously defeated restrictions on abortion coverage.

7 CFR 1493.280 - Evidence of export report.

Code of Federal Regulations, 2013 CFR

2013-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Facility Guarantee Program... to provide CCC an evidence of export report for each shipment of goods or provision of services... provided were included in the final application for a final commitment as approved by CCC for coverage...

7 CFR 1493.280 - Evidence of export report.

Code of Federal Regulations, 2012 CFR

2012-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Facility Guarantee Program... to provide CCC an evidence of export report for each shipment of goods or provision of services... provided were included in the final application for a final commitment as approved by CCC for coverage...

7 CFR 1493.280 - Evidence of export report.

Code of Federal Regulations, 2014 CFR

2014-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Facility Guarantee Program... to provide CCC an evidence of export report for each shipment of goods or provision of services... provided were included in the final application for a final commitment as approved by CCC for coverage...

7 CFR 1493.280 - Evidence of export report.

Code of Federal Regulations, 2011 CFR

2011-01-01

... OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC... exporter is required to provide CCC an evidence of export report for each shipment of goods or provision of... CCC for coverage under the facility payment guarantee and this subpart; (ii) The specifications and...

Sparse representation-based image restoration via nonlocal supervised coding

NASA Astrophysics Data System (ADS)

Li, Ao; Chen, Deyun; Sun, Guanglu; Lin, Kezheng

2016-10-01

Sparse representation (SR) and nonlocal technique (NLT) have shown great potential in low-level image processing. However, due to the degradation of the observed image, SR and NLT may not be accurate enough to obtain a faithful restoration results when they are used independently. To improve the performance, in this paper, a nonlocal supervised coding strategy-based NLT for image restoration is proposed. The novel method has three main contributions. First, to exploit the useful nonlocal patches, a nonnegative sparse representation is introduced, whose coefficients can be utilized as the supervised weights among patches. Second, a novel objective function is proposed, which integrated the supervised weights learning and the nonlocal sparse coding to guarantee a more promising solution. Finally, to make the minimization tractable and convergence, a numerical scheme based on iterative shrinkage thresholding is developed to solve the above underdetermined inverse problem. The extensive experiments validate the effectiveness of the proposed method.

Improved analysis of SP and CoSaMP under total perturbations

NASA Astrophysics Data System (ADS)

Li, Haifeng

2016-12-01

Practically, in the underdetermined model y= A x, where x is a K sparse vector (i.e., it has no more than K nonzero entries), both y and A could be totally perturbed. A more relaxed condition means less number of measurements are needed to ensure the sparse recovery from theoretical aspect. In this paper, based on restricted isometry property (RIP), for subspace pursuit (SP) and compressed sampling matching pursuit (CoSaMP), two relaxed sufficient conditions are presented under total perturbations to guarantee that the sparse vector x is recovered. Taking random matrix as measurement matrix, we also discuss the advantage of our condition. Numerical experiments validate that SP and CoSaMP can provide oracle-order recovery performance.

7 CFR 1493.430 - Application for a payment guarantee.

Code of Federal Regulations, 2013 CFR

2013-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier... quantity, contract loading tolerance and, if the exporter chooses, a request for CCC to reserve coverage up... is also being used as the basis for an application for participation in any of the following CCC or...

7 CFR 1493.430 - Application for a payment guarantee.

Code of Federal Regulations, 2014 CFR

2014-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier... quantity, contract loading tolerance and, if the exporter chooses, a request for CCC to reserve coverage up... is also being used as the basis for an application for participation in any of the following CCC or...

7 CFR 1493.430 - Application for a payment guarantee.

Code of Federal Regulations, 2012 CFR

2012-01-01

... CORPORATION, DEPARTMENT OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier... quantity, contract loading tolerance and, if the exporter chooses, a request for CCC to reserve coverage up... is also being used as the basis for an application for participation in any of the following CCC or...

Short-term memory capacity in networks via the restricted isometry property.

PubMed

Charles, Adam S; Yap, Han Lun; Rozell, Christopher J

2014-06-01

Cortical networks are hypothesized to rely on transient network activity to support short-term memory (STM). In this letter, we study the capacity of randomly connected recurrent linear networks for performing STM when the input signals are approximately sparse in some basis. We leverage results from compressed sensing to provide rigorous nonasymptotic recovery guarantees, quantifying the impact of the input sparsity level, the input sparsity basis, and the network characteristics on the system capacity. Our analysis demonstrates that network memory capacities can scale superlinearly with the number of nodes and in some situations can achieve STM capacities that are much larger than the network size. We provide perfect recovery guarantees for finite sequences and recovery bounds for infinite sequences. The latter analysis predicts that network STM systems may have an optimal recovery length that balances errors due to omission and recall mistakes. Furthermore, we show that the conditions yielding optimal STM capacity can be embodied in several network topologies, including networks with sparse or dense connectivities.

A QoS-guaranteed coverage precedence routing algorithm for wireless sensor networks.

PubMed

Jiang, Joe-Air; Lin, Tzu-Shiang; Chuang, Cheng-Long; Chen, Chia-Pang; Sun, Chin-Hong; Juang, Jehn-Yih; Lin, Jiun-Chuan; Liang, Wei-Wen

2011-01-01

For mission-critical applications of wireless sensor networks (WSNs) involving extensive battlefield surveillance, medical healthcare, etc., it is crucial to have low-power, new protocols, methodologies and structures for transferring data and information in a network with full sensing coverage capability for an extended working period. The upmost mission is to ensure that the network is fully functional providing reliable transmission of the sensed data without the risk of data loss. WSNs have been applied to various types of mission-critical applications. Coverage preservation is one of the most essential functions to guarantee quality of service (QoS) in WSNs. However, a tradeoff exists between sensing coverage and network lifetime due to the limited energy supplies of sensor nodes. In this study, we propose a routing protocol to accommodate both energy-balance and coverage-preservation for sensor nodes in WSNs. The energy consumption for radio transmissions and the residual energy over the network are taken into account when the proposed protocol determines an energy-efficient route for a packet. The simulation results demonstrate that the proposed protocol is able to increase the duration of the on-duty network and provide up to 98.3% and 85.7% of extra service time with 100% sensing coverage ratio comparing with LEACH and the LEACH-Coverage-U protocols, respectively.

7 CFR 760.633 - 2008 SURE guarantee calculation.

Code of Federal Regulations, 2010 CFR

2010-01-01

... percent of the NAP established price for the crop; (2) Coverage level in § 760.631(a)(1)(iv) is 70 percent... the NAP established price for the crop; and (ii) Coverage level in §§ 760.631(a)(1)(iv) and 760.634(a...

45 CFR 147.106 - Guaranteed renewability of coverage.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Section 147.106 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS HEALTH INSURANCE REFORM REQUIREMENTS FOR THE GROUP AND INDIVIDUAL HEALTH INSURANCE MARKETS...) of this section, a health insurance issuer offering health insurance coverage in the individual or...

7 CFR 4279.229 - Guaranteed loan funding.

Code of Federal Regulations, 2014 CFR

2014-01-01

.... For example, an eligible borrower is applying for a loan guarantee on a $1 million project. The... (d)(1) through (d)(4) of this section. (1) If the loan amount is equal to or less than $125 million... at least 1 year in duration; and (iii) Collateral coverage ratio, total discounted collateral value...

7 CFR 4279.229 - Guaranteed loan funding.

Code of Federal Regulations, 2012 CFR

2012-01-01

.... For example, an eligible borrower is applying for a loan guarantee on a $1 million project. The... (d)(1) through (d)(4) of this section. (1) If the loan amount is equal to or less than $125 million... at least 1 year in duration; and (iii) Collateral coverage ratio, total discounted collateral value...

7 CFR 4279.229 - Guaranteed loan funding.

Code of Federal Regulations, 2013 CFR

2013-01-01

.... For example, an eligible borrower is applying for a loan guarantee on a $1 million project. The... (d)(1) through (d)(4) of this section. (1) If the loan amount is equal to or less than $125 million... at least 1 year in duration; and (iii) Collateral coverage ratio, total discounted collateral value...

Objective sea level pressure analysis for sparse data areas

NASA Technical Reports Server (NTRS)

Druyan, L. M.

1972-01-01

A computer procedure was used to analyze the pressure distribution over the North Pacific Ocean for eleven synoptic times in February, 1967. Independent knowledge of the central pressures of lows is shown to reduce the analysis errors for very sparse data coverage. The application of planned remote sensing of sea-level wind speeds is shown to make a significant contribution to the quality of the analysis especially in the high gradient mid-latitudes and for sparse coverage of conventional observations (such as over Southern Hemisphere oceans). Uniform distribution of the available observations of sea-level pressure and wind velocity yields results far superior to those derived from a random distribution. A generalization of the results indicates that the average lower limit for analysis errors is between 2 and 2.5 mb based on the perfect specification of the magnitude of the sea-level pressure gradient from a known verification analysis. A less than perfect specification will derive from wind-pressure relationships applied to satellite observed wind speeds.

Estimation for sparse vegetation information in desertification region based on Tiangong-1 hyperspectral image.

PubMed

Wu, Jun-Jun; Gao, Zhi-Hai; Li, Zeng-Yuan; Wang, Hong-Yan; Pang, Yong; Sun, Bin; Li, Chang-Long; Li, Xu-Zhi; Zhang, Jiu-Xing

2014-03-01

In order to estimate the sparse vegetation information accurately in desertification region, taking southeast of Sunite Right Banner, Inner Mongolia, as the test site and Tiangong-1 hyperspectral image as the main data, sparse vegetation coverage and biomass were retrieved based on normalized difference vegetation index (NDVI) and soil adjusted vegetation index (SAVI), combined with the field investigation data. Then the advantages and disadvantages between them were compared. Firstly, the correlation between vegetation indexes and vegetation coverage under different bands combination was analyzed, as well as the biomass. Secondly, the best bands combination was determined when the maximum correlation coefficient turned up between vegetation indexes (VI) and vegetation parameters. It showed that the maximum correlation coefficient between vegetation parameters and NDVI could reach as high as 0.7, while that of SAVI could nearly reach 0.8. The center wavelength of red band in the best bands combination for NDVI was 630nm, and that of the near infrared (NIR) band was 910 nm. Whereas, when the center wavelength was 620 and 920 nm respectively, they were the best combination for SAVI. Finally, the linear regression models were established to retrieve vegetation coverage and biomass based on Tiangong-1 VIs. R2 of all models was more than 0.5, while that of the model based on SAVI was higher than that based on NDVI, especially, the R2 of vegetation coverage retrieve model based on SAVI was as high as 0.59. By intersection validation, the standard errors RMSE based on SAVI models were lower than that of the model based on NDVI. The results showed that the abundant spectral information of Tiangong-1 hyperspectral image can reflect the actual vegetaion condition effectively, and SAVI can estimate the sparse vegetation information more accurately than NDVI in desertification region.

12 CFR 324.134 - Guarantees and credit derivatives: PD substitution and LGD adjustment approaches.

Code of Federal Regulations, 2014 CFR

2014-01-01

... credit derivative covering an exposure described in paragraph (a)(1) of this section by using the PD... hedged exposures—(1) PD substitution approach—(i) Full coverage. If an eligible guarantee or eligible..., where PD is the protection provider's PD, LGD is determined under paragraph (c)(1)(iii) of this section...

12 CFR 217.134 - Guarantees and credit derivatives: PD substitution and LGD adjustment approaches.

Code of Federal Regulations, 2014 CFR

2014-01-01

... credit derivative covering an exposure described in paragraph (a)(1) of this section by using the PD... hedged exposures—(1) PD substitution approach—(i) Full coverage. If an eligible guarantee or eligible..., where PD is the protection provider's PD, LGD is determined under paragraph (c)(1)(iii) of this section...

Cerebellar Functional Parcellation Using Sparse Dictionary Learning Clustering.

PubMed

Wang, Changqing; Kipping, Judy; Bao, Chenglong; Ji, Hui; Qiu, Anqi

2016-01-01

The human cerebellum has recently been discovered to contribute to cognition and emotion beyond the planning and execution of movement, suggesting its functional heterogeneity. We aimed to identify the functional parcellation of the cerebellum using information from resting-state functional magnetic resonance imaging (rs-fMRI). For this, we introduced a new data-driven decomposition-based functional parcellation algorithm, called Sparse Dictionary Learning Clustering (SDLC). SDLC integrates dictionary learning, sparse representation of rs-fMRI, and k-means clustering into one optimization problem. The dictionary is comprised of an over-complete set of time course signals, with which a sparse representation of rs-fMRI signals can be constructed. Cerebellar functional regions were then identified using k-means clustering based on the sparse representation of rs-fMRI signals. We solved SDLC using a multi-block hybrid proximal alternating method that guarantees strong convergence. We evaluated the reliability of SDLC and benchmarked its classification accuracy against other clustering techniques using simulated data. We then demonstrated that SDLC can identify biologically reasonable functional regions of the cerebellum as estimated by their cerebello-cortical functional connectivity. We further provided new insights into the cerebello-cortical functional organization in children.

Accelerated Path-following Iterative Shrinkage Thresholding Algorithm with Application to Semiparametric Graph Estimation

PubMed Central

Zhao, Tuo; Liu, Han

2016-01-01

We propose an accelerated path-following iterative shrinkage thresholding algorithm (APISTA) for solving high dimensional sparse nonconvex learning problems. The main difference between APISTA and the path-following iterative shrinkage thresholding algorithm (PISTA) is that APISTA exploits an additional coordinate descent subroutine to boost the computational performance. Such a modification, though simple, has profound impact: APISTA not only enjoys the same theoretical guarantee as that of PISTA, i.e., APISTA attains a linear rate of convergence to a unique sparse local optimum with good statistical properties, but also significantly outperforms PISTA in empirical benchmarks. As an application, we apply APISTA to solve a family of nonconvex optimization problems motivated by estimating sparse semiparametric graphical models. APISTA allows us to obtain new statistical recovery results which do not exist in the existing literature. Thorough numerical results are provided to back up our theory. PMID:28133430

Regional media coverage influences the public's negative attitudes to policy implementation success in Sweden.

PubMed

Fredriksson, Mio; Tiainen, Anne; Hanning, Marianne

2015-12-01

One central aspect of health literacy is knowledge of patients' rights. Being an important source of information about health and health care, the media may influence health literacy and act as a policy implementer. To investigate whether regional news media coverage in Sweden is linked to (i) the public's awareness and knowledge of a patient's rights policy, the waiting-time guarantee and (ii) the public's attitudes to how the guarantee's time limits are met, that is, implementation success. Three types of data are used. First, a national telephone survey of the public's awareness, knowledge and attitudes; second, media coverage information from digital media monitoring; and third, official waiting-time statistics. Bivariate and multivariate regression analyses are performed with the 21 Swedish county councils/regions as a base. In the county councils/regions, non-awareness ranged from 1 to 15% and knowledge from 47 to 67%. There are relatively large differences between population groups. The amount of regional media coverage shows no significant correlation to the level of awareness and knowledge. There is, however, a significant correlation to both positive and negative attitudes; the latter remains after controlling for actual waiting times. At the national level, the media function as a policy implementer, being the primary source of information. At the regional level, the media are part of the political communication, reporting more extensively in county councils/regions where the population holds negative views towards the achievement in implementing the guarantee. We conclude that Swedish authorities should develop its communication strategies to bridge health literacy inequalities. © 2014 John Wiley & Sons Ltd.

Multi-objective based spectral unmixing for hyperspectral images

NASA Astrophysics Data System (ADS)

Xu, Xia; Shi, Zhenwei

2017-02-01

Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

Coverage-guaranteed sensor node deployment strategies for wireless sensor networks.

PubMed

Fan, Gaojuan; Wang, Ruchuan; Huang, Haiping; Sun, Lijuan; Sha, Chao

2010-01-01

Deployment quality and cost are two conflicting aspects in wireless sensor networks. Random deployment, where the monitored field is covered by randomly and uniformly deployed sensor nodes, is an appropriate approach for large-scale network applications. However, their successful applications depend considerably on the deployment quality that uses the minimum number of sensors to achieve a desired coverage. Currently, the number of sensors required to meet the desired coverage is based on asymptotic analysis, which cannot meet deployment quality due to coverage overestimation in real applications. In this paper, we first investigate the coverage overestimation and address the challenge of designing coverage-guaranteed deployment strategies. To overcome this problem, we propose two deployment strategies, namely, the Expected-area Coverage Deployment (ECD) and BOundary Assistant Deployment (BOAD). The deployment quality of the two strategies is analyzed mathematically. Under the analysis, a lower bound on the number of deployed sensor nodes is given to satisfy the desired deployment quality. We justify the correctness of our analysis through rigorous proof, and validate the effectiveness of the two strategies through extensive simulation experiments. The simulation results show that both strategies alleviate the coverage overestimation significantly. In addition, we also evaluate two proposed strategies in the context of target detection application. The comparison results demonstrate that if the target appears at the boundary of monitored region in a given random deployment, the average intrusion distance of BOAD is considerably shorter than that of ECD with the same desired deployment quality. In contrast, ECD has better performance in terms of the average intrusion distance when the invasion of intruder is from the inside of monitored region.

Improving M-SBL for Joint Sparse Recovery Using a Subspace Penalty

NASA Astrophysics Data System (ADS)

Ye, Jong Chul; Kim, Jong Min; Bresler, Yoram

2015-12-01

The multiple measurement vector problem (MMV) is a generalization of the compressed sensing problem that addresses the recovery of a set of jointly sparse signal vectors. One of the important contributions of this paper is to reveal that the seemingly least related state-of-art MMV joint sparse recovery algorithms - M-SBL (multiple sparse Bayesian learning) and subspace-based hybrid greedy algorithms - have a very important link. More specifically, we show that replacing the $\\log\\det(\\cdot)$ term in M-SBL by a rank proxy that exploits the spark reduction property discovered in subspace-based joint sparse recovery algorithms, provides significant improvements. In particular, if we use the Schatten-$p$ quasi-norm as the corresponding rank proxy, the global minimiser of the proposed algorithm becomes identical to the true solution as $p \\rightarrow 0$. Furthermore, under the same regularity conditions, we show that the convergence to a local minimiser is guaranteed using an alternating minimization algorithm that has closed form expressions for each of the minimization steps, which are convex. Numerical simulations under a variety of scenarios in terms of SNR, and condition number of the signal amplitude matrix demonstrate that the proposed algorithm consistently outperforms M-SBL and other state-of-the art algorithms.

7 CFR 457.116 - Sugarcane crop insurance provisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

.... The grass, Saccharum officinarum, that is grown to produce sugar. 2. Insurance Guarantees, Coverage... measures; (e) Wildlife; (f) Earthquake; (g) Volcanic eruption; or (h) Failure of the irrigation water...

Sparse RNA folding revisited: space-efficient minimum free energy structure prediction.

PubMed

Will, Sebastian; Jabbari, Hosna

2016-01-01

RNA secondary structure prediction by energy minimization is the central computational tool for the analysis of structural non-coding RNAs and their interactions. Sparsification has been successfully applied to improve the time efficiency of various structure prediction algorithms while guaranteeing the same result; however, for many such folding problems, space efficiency is of even greater concern, particularly for long RNA sequences. So far, space-efficient sparsified RNA folding with fold reconstruction was solved only for simple base-pair-based pseudo-energy models. Here, we revisit the problem of space-efficient free energy minimization. Whereas the space-efficient minimization of the free energy has been sketched before, the reconstruction of the optimum structure has not even been discussed. We show that this reconstruction is not possible in trivial extension of the method for simple energy models. Then, we present the time- and space-efficient sparsified free energy minimization algorithm SparseMFEFold that guarantees MFE structure prediction. In particular, this novel algorithm provides efficient fold reconstruction based on dynamically garbage-collected trace arrows. The complexity of our algorithm depends on two parameters, the number of candidates Z and the number of trace arrows T; both are bounded by [Formula: see text], but are typically much smaller. The time complexity of RNA folding is reduced from [Formula: see text] to [Formula: see text]; the space complexity, from [Formula: see text] to [Formula: see text]. Our empirical results show more than 80 % space savings over RNAfold [Vienna RNA package] on the long RNAs from the RNA STRAND database (≥2500 bases). The presented technique is intentionally generalizable to complex prediction algorithms; due to their high space demands, algorithms like pseudoknot prediction and RNA-RNA-interaction prediction are expected to profit even stronger than "standard" MFE folding. SparseMFEFold is free software, available at http://www.bioinf.uni-leipzig.de/~will/Software/SparseMFEFold.

Leveraging EAP-Sparsity for Compressed Sensing of MS-HARDI in (k, q)-Space.

PubMed

Sun, Jiaqi; Sakhaee, Elham; Entezari, Alireza; Vemuri, Baba C

2015-01-01

Compressed Sensing (CS) for the acceleration of MR scans has been widely investigated in the past decade. Lately, considerable progress has been made in achieving similar speed ups in acquiring multi-shell high angular resolution diffusion imaging (MS-HARDI) scans. Existing approaches in this context were primarily concerned with sparse reconstruction of the diffusion MR signal S(q) in the q-space. More recently, methods have been developed to apply the compressed sensing framework to the 6-dimensional joint (k, q)-space, thereby exploiting the redundancy in this 6D space. To guarantee accurate reconstruction from partial MS-HARDI data, the key ingredients of compressed sensing that need to be brought together are: (1) the function to be reconstructed needs to have a sparse representation, and (2) the data for reconstruction ought to be acquired in the dual domain (i.e., incoherent sensing) and (3) the reconstruction process involves a (convex) optimization. In this paper, we present a novel approach that uses partial Fourier sensing in the 6D space of (k, q) for the reconstruction of P(x, r). The distinct feature of our approach is a sparsity model that leverages surfacelets in conjunction with total variation for the joint sparse representation of P(x, r). Thus, our method stands to benefit from the practical guarantees for accurate reconstruction from partial (k, q)-space data. Further, we demonstrate significant savings in acquisition time over diffusion spectral imaging (DSI) which is commonly used as the benchmark for comparisons in reported literature. To demonstrate the benefits of this approach,.we present several synthetic and real data examples.

Real-time incident detection using social media data.

DOT National Transportation Integrated Search

2016-05-09

The effectiveness of traditional incident detection is often limited by sparse sensor coverage, and reporting incidents to emergency response systems : is labor-intensive. This research project mines tweet texts to extract incident information on bot...

Learning Collaborative Sparse Representation for Grayscale-Thermal Tracking.

PubMed

Li, Chenglong; Cheng, Hui; Hu, Shiyi; Liu, Xiaobai; Tang, Jin; Lin, Liang

2016-09-27

Integrating multiple different yet complementary feature representations has been proved to be an effective way for boosting tracking performance. This paper investigates how to perform robust object tracking in challenging scenarios by adaptively incorporating information from grayscale and thermal videos, and proposes a novel collaborative algorithm for online tracking. In particular, an adaptive fusion scheme is proposed based on collaborative sparse representation in Bayesian filtering framework. We jointly optimize sparse codes and the reliable weights of different modalities in an online way. In addition, this work contributes a comprehensive video benchmark, which includes 50 grayscale-thermal sequences and their ground truth annotations for tracking purpose. The videos are with high diversity and the annotations were finished by one single person to guarantee consistency. Extensive experiments against other stateof- the-art trackers with both grayscale and grayscale-thermal inputs demonstrate the effectiveness of the proposed tracking approach. Through analyzing quantitative results, we also provide basic insights and potential future research directions in grayscale-thermal tracking.

Inference for High-dimensional Differential Correlation Matrices.

PubMed

Cai, T Tony; Zhang, Anru

2016-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed.

A linear recurrent kernel online learning algorithm with sparse updates.

PubMed

Fan, Haijin; Song, Qing

2014-02-01

In this paper, we propose a recurrent kernel algorithm with selectively sparse updates for online learning. The algorithm introduces a linear recurrent term in the estimation of the current output. This makes the past information reusable for updating of the algorithm in the form of a recurrent gradient term. To ensure that the reuse of this recurrent gradient indeed accelerates the convergence speed, a novel hybrid recurrent training is proposed to switch on or off learning the recurrent information according to the magnitude of the current training error. Furthermore, the algorithm includes a data-dependent adaptive learning rate which can provide guaranteed system weight convergence at each training iteration. The learning rate is set as zero when the training violates the derived convergence conditions, which makes the algorithm updating process sparse. Theoretical analyses of the weight convergence are presented and experimental results show the good performance of the proposed algorithm in terms of convergence speed and estimation accuracy. Copyright © 2013 Elsevier Ltd. All rights reserved.

75 FR 48525 - Pennsylvania Regulatory Program

Federal Register 2010, 2011, 2012, 2013, 2014

2010-08-10

...OSM is announcing its partial approval of a program amendment submitted by the Commonwealth of Pennsylvania for the purpose of addressing the need for financial guarantees to cover the costs of treatment of post-mining pollutional discharges and land reclamation for those surface coal mining sites that were originally bonded under the Commonwealth's now defunct alternative bonding system (ABS). OSM is requiring that Pennsylvania ensure that its program provides suitable, enforceable funding mechanisms sufficient to guarantee coverage of land reclamation at all original ABS sites.

Compressive Information Extraction: A Dynamical Systems Approach

DTIC Science & Technology

2016-01-24

sparsely encoded in very large data streams. (a) Target tracking in an urban canyon; (b) and (c) sample frames showing contextually abnormal events: onset...extraction to identify contextually abnormal se- quences (see section 2.2.3). Formally, the problem of interest can be stated as establishing whether a noisy...relaxations with optimality guarantees can be obtained using tools from semi-algebraic geometry. 2.2 Application: Detecting Contextually Abnormal Events

Insurance status of urban detained adolescents.

PubMed

Aalsma, Matthew C; Blythe, Margaret J; Tong, Yan; Harezlak, Jaroslaw; Rosenman, Marc B

2012-10-01

The primary goal was to describe the health care coverage of detained youth. An exploratory second goal was to describe the possible relationship between redetention and coverage. Health care coverage status was abstracted from electronic detention center records for 1,614 adolescents in an urban detention center (October 2006 to December 2007). The majority of detained youth reported having Medicaid coverage (66%); 18% had private insurance and 17% had no insurance. Lack of insurance was more prevalent among older, male, and Hispanic youth. A substantial minority of detained youth were uninsured or had inconsistent coverage over time. While having insurance does not guarantee appropriate health care, lack of insurance is a barrier that should be addressed to facilitate coordination of medical and mental health care once the youth is released into the community.

A weighted ℓ{sub 1}-minimization approach for sparse polynomial chaos expansions

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

Peng, Ji; Hampton, Jerrad; Doostan, Alireza, E-mail: alireza.doostan@colorado.edu

2014-06-15

This work proposes a method for sparse polynomial chaos (PC) approximation of high-dimensional stochastic functions based on non-adapted random sampling. We modify the standard ℓ{sub 1}-minimization algorithm, originally proposed in the context of compressive sampling, using a priori information about the decay of the PC coefficients, when available, and refer to the resulting algorithm as weightedℓ{sub 1}-minimization. We provide conditions under which we may guarantee recovery using this weighted scheme. Numerical tests are used to compare the weighted and non-weighted methods for the recovery of solutions to two differential equations with high-dimensional random inputs: a boundary value problem with amore » random elliptic operator and a 2-D thermally driven cavity flow with random boundary condition.« less

On Connected Target k-Coverage in Heterogeneous Wireless Sensor Networks.

PubMed

Yu, Jiguo; Chen, Ying; Ma, Liran; Huang, Baogui; Cheng, Xiuzhen

2016-01-15

Coverage and connectivity are two important performance evaluation indices for wireless sensor networks (WSNs). In this paper, we focus on the connected target k-coverage (CTC k) problem in heterogeneous wireless sensor networks (HWSNs). A centralized connected target k-coverage algorithm (CCTC k) and a distributed connected target k-coverage algorithm (DCTC k) are proposed so as to generate connected cover sets for energy-efficient connectivity and coverage maintenance. To be specific, our proposed algorithms aim at achieving minimum connected target k-coverage, where each target in the monitored region is covered by at least k active sensor nodes. In addition, these two algorithms strive to minimize the total number of active sensor nodes and guarantee that each sensor node is connected to a sink, such that the sensed data can be forwarded to the sink. Our theoretical analysis and simulation results show that our proposed algorithms outperform a state-of-art connected k-coverage protocol for HWSNs.

ToxCast Data Expands Universe of Chemical-Gene Interactions (SOT)

EPA Science Inventory

Characterizing the effects of chemicals in biological systems is often summarized by chemical-gene interactions, which have sparse coverage in literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets. Thi...

State contraceptive coverage laws: creative responses to questions of "conscience".

PubMed

Dailard, C

1999-08-01

The Federal Employees Health Benefits Program (FEHBP) guaranteed contraceptive coverage for employees of the federal government. However, opponents of the FEHBP contraceptive coverage questioned the viability of the conscience clause. Supporters of the contraceptive coverage pressed for the narrowest exemption, one that only permit religious plans that clearly states religious objection to contraception. There are six of the nine states that have enacted contraceptive coverage laws aimed at the private sector. The statutes included a provision of conscience clause. The private sector disagrees to the plan since almost all of the employees¿ work for employers who only offer one plan. The scope of exemption for employers was an issue in five states that have enacted the contraceptive coverage. In Hawaii and California, it was exemplified that if employers are exempted from the contraceptive coverage based on religious grounds, an employee will be entitled to purchase coverage directly from the plan. There are still questions on how an insurer, who objects based on religious grounds to a plan with contraceptive coverage, can function in a marketplace where such coverage is provided by most private sector employers.

Sparse Representation Based Frequency Detection and Uncertainty Reduction in Blade Tip Timing Measurement for Multi-Mode Blade Vibration Monitoring

PubMed Central

Pan, Minghao; Yang, Yongmin; Guan, Fengjiao; Hu, Haifeng; Xu, Hailong

2017-01-01

The accurate monitoring of blade vibration under operating conditions is essential in turbo-machinery testing. Blade tip timing (BTT) is a promising non-contact technique for the measurement of blade vibrations. However, the BTT sampling data are inherently under-sampled and contaminated with several measurement uncertainties. How to recover frequency spectra of blade vibrations though processing these under-sampled biased signals is a bottleneck problem. A novel method of BTT signal processing for alleviating measurement uncertainties in recovery of multi-mode blade vibration frequency spectrum is proposed in this paper. The method can be divided into four phases. First, a single measurement vector model is built by exploiting that the blade vibration signals are sparse in frequency spectra. Secondly, the uniqueness of the nonnegative sparse solution is studied to achieve the vibration frequency spectrum. Thirdly, typical sources of BTT measurement uncertainties are quantitatively analyzed. Finally, an improved vibration frequency spectra recovery method is proposed to get a guaranteed level of sparse solution when measurement results are biased. Simulations and experiments are performed to prove the feasibility of the proposed method. The most outstanding advantage is that this method can prevent the recovered multi-mode vibration spectra from being affected by BTT measurement uncertainties without increasing the probe number. PMID:28758952

Southern Ocean Seasonal Net Production from Satellite, Atmosphere, and Ocean Data Sets

NASA Technical Reports Server (NTRS)

Keeling, Ralph F.; Campbell, J. (Technical Monitor)

2002-01-01

A new climatology of monthly air-sea O2 flux was developed using the net air-sea heat flux as a template for spatial and temporal interpolation of sparse hydrographic data. The climatology improves upon the previous climatology of Najjar and Keeling in the Southern Hemisphere, where the heat-based approach helps to overcome limitations due to sparse data coverage. The climatology is used to make comparisons with productivity derived from CZCS images. The climatology is also used in support of an investigation of the plausible impact of recent global warming an oceanic O2 inventories.

Inference for High-dimensional Differential Correlation Matrices *

PubMed Central

Cai, T. Tony; Zhang, Anru

2015-01-01

Motivated by differential co-expression analysis in genomics, we consider in this paper estimation and testing of high-dimensional differential correlation matrices. An adaptive thresholding procedure is introduced and theoretical guarantees are given. Minimax rate of convergence is established and the proposed estimator is shown to be adaptively rate-optimal over collections of paired correlation matrices with approximately sparse differences. Simulation results show that the procedure significantly outperforms two other natural methods that are based on separate estimation of the individual correlation matrices. The procedure is also illustrated through an analysis of a breast cancer dataset, which provides evidence at the gene co-expression level that several genes, of which a subset has been previously verified, are associated with the breast cancer. Hypothesis testing on the differential correlation matrices is also considered. A test, which is particularly well suited for testing against sparse alternatives, is introduced. In addition, other related problems, including estimation of a single sparse correlation matrix, estimation of the differential covariance matrices, and estimation of the differential cross-correlation matrices, are also discussed. PMID:26500380

Efficient Computation of Anharmonic Force Constants via q-space, with Application to Graphene

NASA Astrophysics Data System (ADS)

Kornbluth, Mordechai; Marianetti, Chris

We present a new approach for extracting anharmonic force constants from a sparse sampling of the anharmonic dynamical tensor. We calculate the derivative of the energy with respect to q-space displacements (phonons) and strain, which guarantees the absence of supercell image errors. Central finite differences provide a well-converged quadratic error tail for each derivative, separating the contribution of each anharmonic order. These derivatives populate the anharmonic dynamical tensor in a sparse mesh that bounds the Brillouin Zone, which ensures comprehensive sampling of q-space while exploiting small-cell calculations for efficient, high-throughput computation. This produces a well-converged and precisely-defined dataset, suitable for big-data approaches. We transform this sparsely-sampled anharmonic dynamical tensor to real-space anharmonic force constants that obey full space-group symmetries by construction. Machine-learning techniques identify the range of real-space interactions. We show the entire process executed for graphene, up to and including the fifth-order anharmonic force constants. This method successfully calculates strain-based phonon renormalization in graphene, even under large strains, which solves a major shortcoming of previous potentials.

Does medicaid coverage matter?: A qualitative multi-state study of abortion affordability for low-income women.

PubMed

Dennis, Amanda; Manski, Ruth; Blanchard, Kelly

2014-11-01

Medicaid is designed to ensure low-income populations can afford health care. However, not all health services are covered by the program. Most state Medicaid programs restrict abortion coverage, though a small number of state programs offer such coverage. Little is known about how low-income women are affected by differing Medicaid coverage policies regarding abortion. We conducted in depth interviews with 98 low-income women who had abortions. We found that women's impressions about abortion costs and the availability of Medicaid coverage are generally accurate and that women rely predominantly on abortion facilities for confirmatory cost and coverage information. Additionally, when abortion is out of financial reach, women and the people in their lives experience numerous emotional and financial harms. Policies that aim to ensure abortion is affordable largely prevent these harms, though the availability of Medicaid coverage does not always guarantee access to affordable care. Findings can help advance evidence-based policies

ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative–quantitative modeling

PubMed Central

Streif, Stefan; Savchenko, Anton; Rumschinski, Philipp; Borchers, Steffen; Findeisen, Rolf

2012-01-01

Summary: Often competing hypotheses for biochemical networks exist in the form of different mathematical models with unknown parameters. Considering available experimental data, it is then desired to reject model hypotheses that are inconsistent with the data, or to estimate the unknown parameters. However, these tasks are complicated because experimental data are typically sparse, uncertain, and are frequently only available in form of qualitative if–then observations. ADMIT (Analysis, Design and Model Invalidation Toolbox) is a MatLabTM-based tool for guaranteed model invalidation, state and parameter estimation. The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior. A constraint satisfaction problem is automatically generated and algorithms are implemented for solving the desired estimation, invalidation or analysis tasks. The implemented methods built on convex relaxation and optimization and therefore provide guaranteed estimation results and certificates for invalidity. Availability: ADMIT, tutorials and illustrative examples are available free of charge for non-commercial use at http://ifatwww.et.uni-magdeburg.de/syst/ADMIT/ Contact: stefan.streif@ovgu.de PMID:22451270

ADMIT: a toolbox for guaranteed model invalidation, estimation and qualitative-quantitative modeling.

PubMed

Streif, Stefan; Savchenko, Anton; Rumschinski, Philipp; Borchers, Steffen; Findeisen, Rolf

2012-05-01

Often competing hypotheses for biochemical networks exist in the form of different mathematical models with unknown parameters. Considering available experimental data, it is then desired to reject model hypotheses that are inconsistent with the data, or to estimate the unknown parameters. However, these tasks are complicated because experimental data are typically sparse, uncertain, and are frequently only available in form of qualitative if-then observations. ADMIT (Analysis, Design and Model Invalidation Toolbox) is a MatLab(TM)-based tool for guaranteed model invalidation, state and parameter estimation. The toolbox allows the integration of quantitative measurement data, a priori knowledge of parameters and states, and qualitative information on the dynamic or steady-state behavior. A constraint satisfaction problem is automatically generated and algorithms are implemented for solving the desired estimation, invalidation or analysis tasks. The implemented methods built on convex relaxation and optimization and therefore provide guaranteed estimation results and certificates for invalidity. ADMIT, tutorials and illustrative examples are available free of charge for non-commercial use at http://ifatwww.et.uni-magdeburg.de/syst/ADMIT/

High-frame-rate full-vocal-tract 3D dynamic speech imaging.

PubMed

Fu, Maojing; Barlaz, Marissa S; Holtrop, Joseph L; Perry, Jamie L; Kuehn, David P; Shosted, Ryan K; Liang, Zhi-Pei; Sutton, Bradley P

2017-04-01

To achieve high temporal frame rate, high spatial resolution and full-vocal-tract coverage for three-dimensional dynamic speech MRI by using low-rank modeling and sparse sampling. Three-dimensional dynamic speech MRI is enabled by integrating a novel data acquisition strategy and an image reconstruction method with the partial separability model: (a) a self-navigated sparse sampling strategy that accelerates data acquisition by collecting high-nominal-frame-rate cone navigator sand imaging data within a single repetition time, and (b) are construction method that recovers high-quality speech dynamics from sparse (k,t)-space data by enforcing joint low-rank and spatiotemporal total variation constraints. The proposed method has been evaluated through in vivo experiments. A nominal temporal frame rate of 166 frames per second (defined based on a repetition time of 5.99 ms) was achieved for an imaging volume covering the entire vocal tract with a spatial resolution of 2.2 × 2.2 × 5.0 mm 3 . Practical utility of the proposed method was demonstrated via both validation experiments and a phonetics investigation. Three-dimensional dynamic speech imaging is possible with full-vocal-tract coverage, high spatial resolution and high nominal frame rate to provide dynamic speech data useful for phonetic studies. Magn Reson Med 77:1619-1629, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

Chemical-Gene Interactions from ToxCast Bioactivity Data Expands Universe of Literature Network-Based Associations (SOT)

EPA Science Inventory

Characterizing the effects of chemicals in biological systems is often summarized by chemical-gene interactions, which have sparse coverage in the literature. The ToxCast chemical screening program has produced bioactivity data for nearly 2000 chemicals and over 450 gene targets....

Using classification and NDVI differencing methods for monitoring sparse vegetation coverage: a case study of saltcedar in Nevada, USA.

USDA-ARS?s Scientific Manuscript database

A change detection experiment for an invasive species, saltcedar, near Lovelock, Nevada, was conducted with multi-date Compact Airborne Spectrographic Imager (CASI) hyperspectral datasets. Classification and NDVI differencing change detection methods were tested, In the classification strategy, a p...

Selecting informative subsets of sparse supermatrices increases the chance to find correct trees.

PubMed

Misof, Bernhard; Meyer, Benjamin; von Reumont, Björn Marcus; Kück, Patrick; Misof, Katharina; Meusemann, Karen

2013-12-03

Character matrices with extensive missing data are frequently used in phylogenomics with potentially detrimental effects on the accuracy and robustness of tree inference. Therefore, many investigators select taxa and genes with high data coverage. Drawbacks of these selections are their exclusive reliance on data coverage without consideration of actual signal in the data which might, thus, not deliver optimal data matrices in terms of potential phylogenetic signal. In order to circumvent this problem, we have developed a heuristics implemented in a software called mare which (1) assesses information content of genes in supermatrices using a measure of potential signal combined with data coverage and (2) reduces supermatrices with a simple hill climbing procedure to submatrices with high total information content. We conducted simulation studies using matrices of 50 taxa × 50 genes with heterogeneous phylogenetic signal among genes and data coverage between 10-30%. With matrices of 50 taxa × 50 genes with heterogeneous phylogenetic signal among genes and data coverage between 10-30% Maximum Likelihood (ML) tree reconstructions failed to recover correct trees. A selection of a data subset with the herein proposed approach increased the chance to recover correct partial trees more than 10-fold. The selection of data subsets with the herein proposed simple hill climbing procedure performed well either considering the information content or just a simple presence/absence information of genes. We also applied our approach on an empirical data set, addressing questions of vertebrate systematics. With this empirical dataset selecting a data subset with high information content and supporting a tree with high average boostrap support was most successful if information content of genes was considered. Our analyses of simulated and empirical data demonstrate that sparse supermatrices can be reduced on a formal basis outperforming the usually used simple selections of taxa and genes with high data coverage.

45 CFR 147.104 - Guaranteed availability of coverage.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Section 147.104 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS HEALTH INSURANCE REFORM REQUIREMENTS FOR THE GROUP AND INDIVIDUAL HEALTH INSURANCE MARKETS... and group market. Subject to paragraphs (b) through (d) of this section, a health insurance issuer...

45 CFR 147.104 - Guaranteed availability of coverage.

Code of Federal Regulations, 2013 CFR

2013-10-01

... Section 147.104 Public Welfare DEPARTMENT OF HEALTH AND HUMAN SERVICES REQUIREMENTS RELATING TO HEALTH CARE ACCESS HEALTH INSURANCE REFORM REQUIREMENTS FOR THE GROUP AND INDIVIDUAL HEALTH INSURANCE MARKETS... and group market. Subject to paragraphs (b) through (d) of this section, a health insurance issuer...

29 CFR 4022.24 - Benefit increases.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 9 2010-07-01 2010-07-01 false Benefit increases. 4022.24 Section 4022.24 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS Limitations on Guaranteed Benefits § 4022.24 Benefit increases...

29 CFR 4022.24 - Benefit increases.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 9 2011-07-01 2011-07-01 false Benefit increases. 4022.24 Section 4022.24 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS Limitations on Guaranteed Benefits § 4022.24 Benefit increases...

29 CFR 4022.24 - Benefit increases.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 9 2014-07-01 2014-07-01 false Benefit increases. 4022.24 Section 4022.24 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS Limitations on Guaranteed Benefits § 4022.24 Benefit increases...

29 CFR 4022.24 - Benefit increases.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 9 2012-07-01 2012-07-01 false Benefit increases. 4022.24 Section 4022.24 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS Limitations on Guaranteed Benefits § 4022.24 Benefit increases...

29 CFR 4022.24 - Benefit increases.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 9 2013-07-01 2013-07-01 false Benefit increases. 4022.24 Section 4022.24 Labor Regulations Relating to Labor (Continued) PENSION BENEFIT GUARANTY CORPORATION COVERAGE AND BENEFITS BENEFITS PAYABLE IN TERMINATED SINGLE-EMPLOYER PLANS Limitations on Guaranteed Benefits § 4022.24 Benefit increases...

45 CFR 147.106 - Guaranteed renewability of coverage.

Code of Federal Regulations, 2014 CFR

2014-10-01

... Section 147.106 Public Welfare Department of Health and Human Services REQUIREMENTS RELATING TO HEALTH CARE ACCESS HEALTH INSURANCE REFORM REQUIREMENTS FOR THE GROUP AND INDIVIDUAL HEALTH INSURANCE MARKETS..., 2014. (a) General rule. Subject to paragraphs (b) through (d) of this section, a health insurance...

Patient Protection and Affordable Care Act; HHS notice of benefit and payment parameters for 2016. Final rule.

PubMed

2015-02-27

This final rule sets forth payment parameters and provisions related to the risk adjustment, reinsurance, and risk corridors programs; cost sharing parameters and cost-sharing reductions; and user fees for Federally-facilitated Exchanges. It also finalizes additional standards for the individual market annual open enrollment period for the 2016 benefit year, essential health benefits, qualified health plans, network adequacy, quality improvement strategies, the Small Business Health Options Program, guaranteed availability, guaranteed renewability, minimum essential coverage, the rate review program, the medical loss ratio program, and other related topics.

Signal processing using sparse derivatives with applications to chromatograms and ECG

NASA Astrophysics Data System (ADS)

Ning, Xiaoran

In this thesis, we investigate the sparsity exist in the derivative domain. Particularly, we focus on the type of signals which posses up to Mth (M > 0) order sparse derivatives. Efforts are put on formulating proper penalty functions and optimization problems to capture properties related to sparse derivatives, searching for fast, computationally efficient solvers. Also the effectiveness of these algorithms are applied to two real world applications. In the first application, we provide an algorithm which jointly addresses the problems of chromatogram baseline correction and noise reduction. The series of chromatogram peaks are modeled as sparse with sparse derivatives, and the baseline is modeled as a low-pass signal. A convex optimization problem is formulated so as to encapsulate these non-parametric models. To account for the positivity of chromatogram peaks, an asymmetric penalty function is also utilized with symmetric penalty functions. A robust, computationally efficient, iterative algorithm is developed that is guaranteed to converge to the unique optimal solution. The approach, termed Baseline Estimation And Denoising with Sparsity (BEADS), is evaluated and compared with two state-of-the-art methods using both simulated and real chromatogram data. Promising result is obtained. In the second application, a novel Electrocardiography (ECG) enhancement algorithm is designed also based on sparse derivatives. In the real medical environment, ECG signals are often contaminated by various kinds of noise or artifacts, for example, morphological changes due to motion artifact, non-stationary noise due to muscular contraction (EMG), etc. Some of these contaminations severely affect the usefulness of ECG signals, especially when computer aided algorithms are utilized. By solving the proposed convex l1 optimization problem, artifacts are reduced by modeling the clean ECG signal as a sum of two signals whose second and third-order derivatives (differences) are sparse respectively. At the end, the algorithm is applied to a QRS detection system and validated using the MIT-BIH Arrhythmia database (109452 anotations), resulting a sensitivity of Se = 99.87%$ and a positive prediction of +P = 99.88%.

75 FR 60341 - Deposit Insurance Regulations; Unlimited Coverage for Noninterest-bearing Transaction Accounts

Federal Register 2010, 2011, 2012, 2013, 2014

2010-09-30

... mail for depositors who ordinarily receive account information in this manner. The notice may be in the... existing information collection, OMB No. 3064-0168, currently entitled SWEEP Accounts: Disclosure of... discontinue its existing ``Transaction Account Guarantee Program Extension'' information collection, OMB No...

Sparse Coding and Counting for Robust Visual Tracking

PubMed Central

Liu, Risheng; Wang, Jing; Shang, Xiaoke; Wang, Yiyang; Su, Zhixun; Cai, Yu

2016-01-01

In this paper, we propose a novel sparse coding and counting method under Bayesian framework for visual tracking. In contrast to existing methods, the proposed method employs the combination of L0 and L1 norm to regularize the linear coefficients of incrementally updated linear basis. The sparsity constraint enables the tracker to effectively handle difficult challenges, such as occlusion or image corruption. To achieve real-time processing, we propose a fast and efficient numerical algorithm for solving the proposed model. Although it is an NP-hard problem, the proposed accelerated proximal gradient (APG) approach is guaranteed to converge to a solution quickly. Besides, we provide a closed solution of combining L0 and L1 regularized representation to obtain better sparsity. Experimental results on challenging video sequences demonstrate that the proposed method achieves state-of-the-art results both in accuracy and speed. PMID:27992474

Constellation analysis of an integrated AIS/remote sensing spaceborne system for ship detection

NASA Astrophysics Data System (ADS)

Graziano, Maria Daniela; D'Errico, Marco; Razzano, Elena

2012-08-01

A future system integrating data from remote sensing and upcoming AIS satellites is analyzed through the development of a novel design method for global, discontinuous coverage constellations. It is shown that 8 AIS satellites suffice to guarantee global coverage and a ship location update of 50 min if the spaceborne AIS receiver has a swath of 2800 nm. Furthermore, synergic utilization of COSMO/SkyMed and Radarsat-C data would provide a mean revisit time of 7 h, with AIS information available within 25 min from SAR data acquisition.

Effect of Atmospheric Conditions on Coverage of Fogger Applications in a Desert Surface Boundary Layer

DTIC Science & Technology

2012-01-01

2007) in pecan orchards, among others. In this sparse shrub desert environment, Nappo et al. (2010) showed that, during sta- ble conditions, the...measuring water use in flood-irrigated pecans (Carya illinoinensis). Agric. Water Mgmt. 88(1-3): 181-191. Solanelles, F., E. Gregorio, R. Sanz, J. R

Coverage maximization under resource constraints using a nonuniform proliferating random walk.

PubMed

Saha, Sudipta; Ganguly, Niloy

2013-02-01

Information management services on networks, such as search and dissemination, play a key role in any large-scale distributed system. One of the most desirable features of these services is the maximization of the coverage, i.e., the number of distinctly visited nodes under constraints of network resources as well as time. However, redundant visits of nodes by different message packets (modeled, e.g., as walkers) initiated by the underlying algorithms for these services cause wastage of network resources. In this work, using results from analytical studies done in the past on a K-random-walk-based algorithm, we identify that redundancy quickly increases with an increase in the density of the walkers. Based on this postulate, we design a very simple distributed algorithm which dynamically estimates the density of the walkers and thereby carefully proliferates walkers in sparse regions. We use extensive computer simulations to test our algorithm in various kinds of network topologies whereby we find it to be performing particularly well in networks that are highly clustered as well as sparse.

7 CFR 457.133 - Prune crop insurance provisions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Provisions that allow optional units by irrigated and non-irrigated practices are not applicable. Instead of establishing optional units by section, section equivalent, or FSA farm serial number optional units may be established if each optional unit is located on non-contiguous land. 3. Insurance Guarantees, Coverage Levels...

7 CFR 457.133 - Prune crop insurance provisions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Provisions that allow optional units by irrigated and non-irrigated practices are not applicable. Instead of establishing optional units by section, section equivalent, or FSA farm serial number optional units may be established if each optional unit is located on non-contiguous land. 3. Insurance Guarantees, Coverage Levels...

7 CFR 457.110 - Fig crop insurance provisions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... ground by hand or machine for the purpose of removal from the orchard. Interplanted—Acreage on which two... defined in section 1 of the Basic Provisions, will be divided into additional basic units by each fig type...-contiguous land, unless otherwise allowed by written agreement. 3. Insurance Guarantees, Coverage Levels, and...

7 CFR 457.125 - Safflower crop insurance provisions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Harvest. Collecting the safflower seed by combining or threshing. Local market price. The cash price per pound for undamaged safflower (test weight of 35 pounds per bushel or higher and seed damage less than..., seed damage in excess of 25 percent, or both). 2. Insurance Guarantees, Coverage Levels, and Prices for...

Conversations with your actuary: getting to the right number.

PubMed

Frese, Richard C

2013-05-01

A healthcare finance leader can guarantee recognition of his or her organization's insurance program and better manage the program's liability by discussing changes in the following areas with an actuary: Claims management. Exposure. Coverage or retention Financial reporting of losses. Management goals. Other insurance and operational matters.

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors

PubMed Central

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-01-01

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ-connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm. PMID:28587084

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors.

PubMed

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-05-25

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ -connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm.

[The relationship between the State and workers' unions and its impacts in the union-based health coverage regime in Argentina: an historical and political analysis].

PubMed

De Fazio, Federico Leandro

2013-12-01

This paper aims at developing a political and historical reconstruction of the period spanning from the late nineteenth century to the present. In particular, this work investigates the relationship between the Argentine State and workers' unions and the impacts of that relationship in the establishment, consolidation and potential decline of the health coverage system administrated by unions, in Argentina called obras sociales. This work will also support the hypothesis that the financing obtained by union leaders through this health coverage system has been an efficient instrument for sustaining a centralized union model and has in some cases guaranteed the continued governance of both union leaders and different national governments.

Pre-Scheduled and Self Organized Sleep-Scheduling Algorithms for Efficient K-Coverage in Wireless Sensor Networks

PubMed Central

Hwang, I-Shyan

2017-01-01

The K-coverage configuration that guarantees coverage of each location by at least K sensors is highly popular and is extensively used to monitor diversified applications in wireless sensor networks. Long network lifetime and high detection quality are the essentials of such K-covered sleep-scheduling algorithms. However, the existing sleep-scheduling algorithms either cause high cost or cannot preserve the detection quality effectively. In this paper, the Pre-Scheduling-based K-coverage Group Scheduling (PSKGS) and Self-Organized K-coverage Scheduling (SKS) algorithms are proposed to settle the problems in the existing sleep-scheduling algorithms. Simulation results show that our pre-scheduled-based KGS approach enhances the detection quality and network lifetime, whereas the self-organized-based SKS algorithm minimizes the computation and communication cost of the nodes and thereby is energy efficient. Besides, SKS outperforms PSKGS in terms of network lifetime and detection quality as it is self-organized. PMID:29257078

Node Self-Deployment Algorithm Based on Pigeon Swarm Optimization for Underwater Wireless Sensor Networks

PubMed Central

Yu, Shanen; Xu, Yiming; Jiang, Peng; Wu, Feng; Xu, Huan

2017-01-01

At present, free-to-move node self-deployment algorithms aim at event coverage and cannot improve network coverage under the premise of considering network connectivity, network reliability and network deployment energy consumption. Thus, this study proposes pigeon-based self-deployment algorithm (PSA) for underwater wireless sensor networks to overcome the limitations of these existing algorithms. In PSA, the sink node first finds its one-hop nodes and maximizes the network coverage in its one-hop region. The one-hop nodes subsequently divide the network into layers and cluster in each layer. Each cluster head node constructs a connected path to the sink node to guarantee network connectivity. Finally, the cluster head node regards the ratio of the movement distance of the node to the change in the coverage redundancy ratio as the target function and employs pigeon swarm optimization to determine the positions of the nodes. Simulation results show that PSA improves both network connectivity and network reliability, decreases network deployment energy consumption, and increases network coverage. PMID:28338615

7 CFR 1710.114 - TIER, DSC, OTIER and ODSC requirements.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false TIER, DSC, OTIER and ODSC requirements. 1710.114... AND GUARANTEES Loan Purposes and Basic Policies § 1710.114 TIER, DSC, OTIER and ODSC requirements. (a) General. Requirements for coverage ratios are set forth in the borrower's mortgage, loan contract, or...

A first attempt at few coils and low-coverage resistive wall mode stabilization of EXTRAP T2R

NASA Astrophysics Data System (ADS)

Olofsson, K. Erik J.; Brunsell, Per R.; Drake, James R.; Frassinetti, Lorenzo

2012-09-01

The reversed-field pinch features resistive-shell-type instabilities at any (vanishing and finite) plasma pressure. An attempt to stabilize the full spectrum of these modes using both (i) incomplete coverage and (ii) few coils is presented. Two empirically derived model-based control algorithms are compared with a baseline guaranteed suboptimal intelligent-shell-type (IS) feedback. Experimental stabilization could not be achieved for the coil array subset sizes considered by this first study. But the model-based controllers appear to significantly outperform the decentralized IS method.

Text Summarization Model based on Maximum Coverage Problem and its Variant

NASA Astrophysics Data System (ADS)

Takamura, Hiroya; Okumura, Manabu

We discuss text summarization in terms of maximum coverage problem and its variant. To solve the optimization problem, we applied some decoding algorithms including the ones never used in this summarization formulation, such as a greedy algorithm with performance guarantee, a randomized algorithm, and a branch-and-bound method. We conduct comparative experiments. On the basis of the experimental results, we also augment the summarization model so that it takes into account the relevance to the document cluster. Through experiments, we showed that the augmented model is at least comparable to the best-performing method of DUC'04.

Using an Android application to assess registration strategies in open hepatic procedures: a planning and simulation tool

NASA Astrophysics Data System (ADS)

Doss, Derek J.; Heiselman, Jon S.; Collins, Jarrod A.; Weis, Jared A.; Clements, Logan W.; Geevarghese, Sunil K.; Miga, Michael I.

2017-03-01

Sparse surface digitization with an optically tracked stylus for use in an organ surface-based image-to-physical registration is an established approach for image-guided open liver surgery procedures. However, variability in sparse data collections during open hepatic procedures can produce disparity in registration alignments. In part, this variability arises from inconsistencies with the patterns and fidelity of collected intraoperative data. The liver lacks distinct landmarks and experiences considerable soft tissue deformation. Furthermore, data coverage of the organ is often incomplete or unevenly distributed. While more robust feature-based registration methodologies have been developed for image-guided liver surgery, it is still unclear how variation in sparse intraoperative data affects registration. In this work, we have developed an application to allow surgeons to study the performance of surface digitization patterns on registration. Given the intrinsic nature of soft-tissue, we incorporate realistic organ deformation when assessing fidelity of a rigid registration methodology. We report the construction of our application and preliminary registration results using four participants. Our preliminary results indicate that registration quality improves as users acquire more experience selecting patterns of sparse intraoperative surface data.

The Free Press/Fair Trial Debate: Balancing First and Sixth Amendment Rights 1951-1986.

ERIC Educational Resources Information Center

Creech, Kenneth

Although the First Amendment guarantees the rights of freedom of speech and press, these rights are not absolute. With freedom comes the knowledge that irresponsible action can lead to the regulation of that freedom by others. The courts must balance conflicting rights in cases, such as press coverage of criminal trials, where irresponsible…

Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies

PubMed Central

Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

2016-01-01

Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K-means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups. PMID:27330233

Securing image information using double random phase encoding and parallel compressive sensing with updated sampling processes

NASA Astrophysics Data System (ADS)

Hu, Guiqiang; Xiao, Di; Wang, Yong; Xiang, Tao; Zhou, Qing

2017-11-01

Recently, a new kind of image encryption approach using compressive sensing (CS) and double random phase encoding has received much attention due to the advantages such as compressibility and robustness. However, this approach is found to be vulnerable to chosen plaintext attack (CPA) if the CS measurement matrix is re-used. Therefore, designing an efficient measurement matrix updating mechanism that ensures resistance to CPA is of practical significance. In this paper, we provide a novel solution to update the CS measurement matrix by altering the secret sparse basis with the help of counter mode operation. Particularly, the secret sparse basis is implemented by a reality-preserving fractional cosine transform matrix. Compared with the conventional CS-based cryptosystem that totally generates all the random entries of measurement matrix, our scheme owns efficiency superiority while guaranteeing resistance to CPA. Experimental and analysis results show that the proposed scheme has a good security performance and has robustness against noise and occlusion.

Detection of faults in rotating machinery using periodic time-frequency sparsity

NASA Astrophysics Data System (ADS)

Ding, Yin; He, Wangpeng; Chen, Binqiang; Zi, Yanyang; Selesnick, Ivan W.

2016-11-01

This paper addresses the problem of extracting periodic oscillatory features in vibration signals for detecting faults in rotating machinery. To extract the feature, we propose an approach in the short-time Fourier transform (STFT) domain where the periodic oscillatory feature manifests itself as a relatively sparse grid. To estimate the sparse grid, we formulate an optimization problem using customized binary weights in the regularizer, where the weights are formulated to promote periodicity. In order to solve the proposed optimization problem, we develop an algorithm called augmented Lagrangian majorization-minimization algorithm, which combines the split augmented Lagrangian shrinkage algorithm (SALSA) with majorization-minimization (MM), and is guaranteed to converge for both convex and non-convex formulation. As examples, the proposed approach is applied to simulated data, and used as a tool for diagnosing faults in bearings and gearboxes for real data, and compared to some state-of-the-art methods. The results show that the proposed approach can effectively detect and extract the periodical oscillatory features.

Meta-analytic framework for sparse K-means to identify disease subtypes in multiple transcriptomic studies.

PubMed

Huo, Zhiguang; Ding, Ying; Liu, Silvia; Oesterreich, Steffi; Tseng, George

Disease phenotyping by omics data has become a popular approach that potentially can lead to better personalized treatment. Identifying disease subtypes via unsupervised machine learning is the first step towards this goal. In this paper, we extend a sparse K -means method towards a meta-analytic framework to identify novel disease subtypes when expression profiles of multiple cohorts are available. The lasso regularization and meta-analysis identify a unique set of gene features for subtype characterization. An additional pattern matching reward function guarantees consistent subtype signatures across studies. The method was evaluated by simulations and leukemia and breast cancer data sets. The identified disease subtypes from meta-analysis were characterized with improved accuracy and stability compared to single study analysis. The breast cancer model was applied to an independent METABRIC dataset and generated improved survival difference between subtypes. These results provide a basis for diagnosis and development of targeted treatments for disease subgroups.

Community rating and sustainable individual health insurance markets in New Jersey.

PubMed

Monheit, Alan C; Cantor, Joel C; Koller, Margaret; Fox, Kimberley S

2004-01-01

The New Jersey Individual Health Coverage Program (IHCP) was implemented in 1993; key provisions included pure community rating and guaranteed issue/renewal of coverage. Despite positive early evaluations, the IHCP appears to be heading for collapse. Using unique administrative and survey data, we examined trends in IHCP enrollment and premiums. We found the stability of the IHCP to be fragile in light of improving opportunities for job-related health insurance. We also found that it is retaining high-risk enrollees. Institutional realities and the difficulty of identifying a control group preclude attributing causality to the plan's pure community rating and open enrollment provisions.

Where does the insurance industry stand on health reform today?

PubMed

Bodaken, Bruce G

2008-01-01

With another national health care debate on the horizon, many assume that health plans will present a major source of opposition to universal coverage and other reforms. But a closer look reveals signs of change. Some plans continue their reflexive opposition to increasing government's role in health care; other plans have stepped forward to advocate meaningful reform. Experience in Massachusetts, California, Minnesota, and elsewhere suggests a clear lesson for policymakers. Sensible proposals and a genuine commitment to cooperation can not only neutralize opposition from a potentially powerful opponent, but can actually bring health plans on board to support coverage mandates, guaranteed issue, and other reforms.

How temporary insurance for high-risk individuals may play out under health reform.

PubMed

Chollet, Deborah J

2010-06-01

The Patient Protection and Affordable Care Act guarantees that people with health problems will be able to buy private health insurance as of 2014. In the interim, a new federal high-risk program will accept those who are denied private insurance and have not found coverage from any other source. Such sources include a state high-risk pool or, in a handful of states, a designated carrier of last resort. However, restricted eligibility for the federal program suggests that state high-risk pools, in particular, will continue to be critical yet problematic sources of coverage for the next few years.

Guaranteed epsilon-optimal treatment plans with the minimum number of beams for stereotactic body radiation therapy

NASA Astrophysics Data System (ADS)

Yarmand, Hamed; Winey, Brian; Craft, David

2013-09-01

Stereotactic body radiation therapy (SBRT) is characterized by delivering a high amount of dose in a short period of time. In SBRT the dose is delivered using open fields (e.g., beam’s-eye-view) known as ‘apertures’. Mathematical methods can be used for optimizing treatment planning for delivery of sufficient dose to the cancerous cells while keeping the dose to surrounding organs at risk (OARs) minimal. Two important elements of a treatment plan are quality and delivery time. Quality of a plan is measured based on the target coverage and dose to OARs. Delivery time heavily depends on the number of beams used in the plan as the setup times for different beam directions constitute a large portion of the delivery time. Therefore the ideal plan, in which all potential beams can be used, will be associated with a long impractical delivery time. We use the dose to OARs in the ideal plan to find the plan with the minimum number of beams which is guaranteed to be epsilon-optimal (i.e., a predetermined maximum deviation from the ideal plan is guaranteed). Since the treatment plan optimization is inherently a multi-criteria-optimization problem, the planner can navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing epsilon-optimality. We use mixed integer programming (MIP) for optimization. To reduce the computation time for the resultant MIP, we use two heuristics: a beam elimination scheme and a family of heuristic cuts, known as ‘neighbor cuts’, based on the concept of ‘adjacent beams’. We show the effectiveness of the proposed technique on two clinical cases, a liver and a lung case. Based on our technique we propose an algorithm for fast generation of epsilon-optimal plans.

Guaranteed renewability and the problem of risk variation in individual health insurance markets.

PubMed

Patel, Vip; Pauly, Mark V

2002-01-01

Consumers should be protected against fluctuations in premiums for private individual health insurance associated with the onset of high-cost chronic conditions. The most commonly discussed way to do so is through community rating, which provides protection but can require a heavy regulatory burden and can create incentives for adverse selection and cream skimming. This paper describes an alternative method of providing the same type of protection: insurance contract provisions that guarantee renewability for the next coverage period at class-average rates. Drawing on recent work in insurance theory, the paper shows that such protection is feasible in competitive insurance markets. Guaranteed renewability, which is required of all individual health insurance by the Health Insurance Portability and Accountability Act (HIPAA) of 1996, is incomplete because the law fails to require that premiums be the same for all insured persons in a rating class. However, the paper reports the results of a recent survey of state insurance regulation, which indicates that all but three state insurance departments report having such a requirement. The paper concludes with a discussion of possible threats to the protection guaranteed renewability provides against risk segmentation.

Results of time-domain electromagnetic soundings in Everglades National Park, Florida

USGS Publications Warehouse

Fitterman, D.V.; Deszcz-Pan, Maria; Stoddard, C.E.

1999-01-01

This report describes the collection, processing, and interpretation of time-domain electromagnetic soundings from Everglades National Park. The results are used to locate the extent of seawater intrusion in the Biscayne aquifer and to map the base of the Biscayne aquifer in regions where well coverage is sparse. The data show no evidence of fresh, ground-water flows at depth into Florida Bay.

Sparsistency and Rates of Convergence in Large Covariance Matrix Estimation.

PubMed

Lam, Clifford; Fan, Jianqing

2009-01-01

This paper studies the sparsistency and rates of convergence for estimating sparse covariance and precision matrices based on penalized likelihood with nonconvex penalty functions. Here, sparsistency refers to the property that all parameters that are zero are actually estimated as zero with probability tending to one. Depending on the case of applications, sparsity priori may occur on the covariance matrix, its inverse or its Cholesky decomposition. We study these three sparsity exploration problems under a unified framework with a general penalty function. We show that the rates of convergence for these problems under the Frobenius norm are of order (s(n) log p(n)/n)(1/2), where s(n) is the number of nonzero elements, p(n) is the size of the covariance matrix and n is the sample size. This explicitly spells out the contribution of high-dimensionality is merely of a logarithmic factor. The conditions on the rate with which the tuning parameter λ(n) goes to 0 have been made explicit and compared under different penalties. As a result, for the L(1)-penalty, to guarantee the sparsistency and optimal rate of convergence, the number of nonzero elements should be small: sn'=O(pn) at most, among O(pn2) parameters, for estimating sparse covariance or correlation matrix, sparse precision or inverse correlation matrix or sparse Cholesky factor, where sn' is the number of the nonzero elements on the off-diagonal entries. On the other hand, using the SCAD or hard-thresholding penalty functions, there is no such a restriction.

Bilinear Inverse Problems: Theory, Algorithms, and Applications

NASA Astrophysics Data System (ADS)

Ling, Shuyang

We will discuss how several important real-world signal processing problems, such as self-calibration and blind deconvolution, can be modeled as bilinear inverse problems and solved by convex and nonconvex optimization approaches. In Chapter 2, we bring together three seemingly unrelated concepts, self-calibration, compressive sensing and biconvex optimization. We show how several self-calibration problems can be treated efficiently within the framework of biconvex compressive sensing via a new method called SparseLift. More specifically, we consider a linear system of equations y = DAx, where the diagonal matrix D (which models the calibration error) is unknown and x is an unknown sparse signal. By "lifting" this biconvex inverse problem and exploiting sparsity in this model, we derive explicit theoretical guarantees under which both x and D can be recovered exactly, robustly, and numerically efficiently. In Chapter 3, we study the question of the joint blind deconvolution and blind demixing, i.e., extracting a sequence of functions [special characters omitted] from observing only the sum of their convolutions [special characters omitted]. In particular, for the special case s = 1, it becomes the well-known blind deconvolution problem. We present a non-convex algorithm which guarantees exact recovery under conditions that are competitive with convex optimization methods, with the additional advantage of being computationally much more efficient. We discuss several applications of the proposed framework in image processing and wireless communications in connection with the Internet-of-Things. In Chapter 4, we consider three different self-calibration models of practical relevance. We show how their corresponding bilinear inverse problems can be solved by both the simple linear least squares approach and the SVD-based approach. As a consequence, the proposed algorithms are numerically extremely efficient, thus allowing for real-time deployment. Explicit theoretical guarantees and stability theory are derived and the number of sampling complexity is nearly optimal (up to a poly-log factor). Applications in imaging sciences and signal processing are discussed and numerical simulations are presented to demonstrate the effectiveness and efficiency of our approach.

"More Closeted Than Gayness Itself": The Depiction of Same-Sex Couple Violence in Newspaper Media.

PubMed

Estes, Michelle L; Webber, Gretchen R

2017-10-01

Same-sex intimate partner violence (IPV) lacks mainstream news media coverage. News media report on those stories that are most prominent, and these stories are often shaped and presented within a White, heterosexual, upper-class, male framework. This framework largely ignores or misrepresents those that do not fit these characteristics, resulting in a gap in research and coverage of same-sex IPV. This article explores whether U.S. newspapers cover same-sex IPV, how often, and how same-sex couple violence is portrayed in newspapers when covered. Twenty-five newspaper articles published from 2005 to 2015, 10 years prior to the U.S. Supreme Court decision that legalized same-sex marriage, were located and analyzed. Findings indicate sparse newspaper coverage of IPV in same-sex couples. Ten articles highlight the lack of coverage and knowledge related to same-sex couple IPV. Eighteen articles address same-sex IPV as a social issue and highlight resource concerns, police involvement, and heteronormativity and heterosexism. Sixteen articles depict specific instances of IPV in same-sex couples. The overall lack of coverage and how same-sex IPV is covered remains problematic and limited. More mainstream and accurate coverage is needed to effectively address this social issue. Limitations and directions for future research are also discussed.

Factors associated with dental health care coverage in Mexico: Findings from the National Performance Evaluation Survey 2002-2003.

PubMed

Pérez-Núñez, Ricardo; Medina-Solis, Carlo Eduardo; Maupomé, Gerardo; Vargas-Palacios, Armando

2006-10-01

To determine the level of dental health care coverage in people aged > or =18 years across the country, and to identify the factors associated with coverage. Using the instruments and sampling strategies developed by the World Health Organization for the World Health Survey, a cross-sectional national survey was carried out at the household and individual (adult) levels. Dental data were collected in 20 of Mexico's 32 states. The relationship between coverage and environmental and individual characteristics was examined through logistic regression models. Only 6098 of 24 159 individual respondents reported having oral problems during the preceding 12 months (accounting for 14 284 621 inhabitants of the country if weighted). Only 48% of respondents reporting problems were covered, although details of the appropriateness, timeliness and effectiveness of the intervention(s) were not assessed. The multivariate regression model showed that higher level of education, better socioeconomic status, having at least one chronic disease and having medical insurance were positively associated with better dental care coverage. Age and sex were also associated. Overall dental health care coverage could be improved, assuming that ideal coverage is 100%. Some equality of access issues are apparent because there are differences in coverage across populations in terms of wealth and social status. Identifying the factors associated with sparse coverage is a step in the right direction allowing policymakers to establish strategies aimed at increasing this coverage, focusing on more vulnerable groups and on individuals in greater need of preventive and rehabilitative interventions.

A Hidden Markov Model for Urban-Scale Traffic Estimation Using Floating Car Data.

PubMed

Wang, Xiaomeng; Peng, Ling; Chi, Tianhe; Li, Mengzhu; Yao, Xiaojing; Shao, Jing

2015-01-01

Urban-scale traffic monitoring plays a vital role in reducing traffic congestion. Owing to its low cost and wide coverage, floating car data (FCD) serves as a novel approach to collecting traffic data. However, sparse probe data represents the vast majority of the data available on arterial roads in most urban environments. In order to overcome the problem of data sparseness, this paper proposes a hidden Markov model (HMM)-based traffic estimation model, in which the traffic condition on a road segment is considered as a hidden state that can be estimated according to the conditions of road segments having similar traffic characteristics. An algorithm based on clustering and pattern mining rather than on adjacency relationships is proposed to find clusters with road segments having similar traffic characteristics. A multi-clustering strategy is adopted to achieve a trade-off between clustering accuracy and coverage. Finally, the proposed model is designed and implemented on the basis of a real-time algorithm. Results of experiments based on real FCD confirm the applicability, accuracy, and efficiency of the model. In addition, the results indicate that the model is practicable for traffic estimation on urban arterials and works well even when more than 70% of the probe data are missing.

Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus: SPATIAL COVERAGE AND BIAS IN TREND

DOE PAGES

Wang, Kang; Zhang, Tingjun; Zhang, Xiangdong; ...

2017-09-13

Historically, in-situ measurements have been notoriously sparse over the Arctic. As a consequence, the existing gridded data of Surface Air Temperature (SAT) may have large biases in estimating the warming trend in this region. Using data from an expanded monitoring network with 31 stations in the Alaskan Arctic, we demonstrate that the SAT has increased by 2.19 °C in this region, or at a rate of 0.23 °C/decade during 1921-2015. Mean- while, we found that the SAT warmed at 0.71 °C/decade over 1998-2015, which is two to three times faster than the rate established from the gridded datasets. Focusing onmore » the "hiatus" period 1998-2012 as identied by the Intergovernmental Panel on Climate Change (IPCC) report, the SAT has increased at 0.45 °C/decade, which captures more than 90% of the regional trend for 1951- 2012. We suggest that sparse in-situ measurements are responsible for underestimation of the SAT change in the gridded datasets. It is likely that enhanced climate warming may also have happened in the other regions of the Arctic since the late 1990s but left undetected because of incomplete observational coverage.« less

Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus: SPATIAL COVERAGE AND BIAS IN TREND

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

Wang, Kang; Zhang, Tingjun; Zhang, Xiangdong

Historically, in-situ measurements have been notoriously sparse over the Arctic. As a consequence, the existing gridded data of Surface Air Temperature (SAT) may have large biases in estimating the warming trend in this region. Using data from an expanded monitoring network with 31 stations in the Alaskan Arctic, we demonstrate that the SAT has increased by 2.19 °C in this region, or at a rate of 0.23 °C/decade during 1921-2015. Mean- while, we found that the SAT warmed at 0.71 °C/decade over 1998-2015, which is two to three times faster than the rate established from the gridded datasets. Focusing onmore » the "hiatus" period 1998-2012 as identied by the Intergovernmental Panel on Climate Change (IPCC) report, the SAT has increased at 0.45 °C/decade, which captures more than 90% of the regional trend for 1951- 2012. We suggest that sparse in-situ measurements are responsible for underestimation of the SAT change in the gridded datasets. It is likely that enhanced climate warming may also have happened in the other regions of the Arctic since the late 1990s but left undetected because of incomplete observational coverage.« less

Information-optimal genome assembly via sparse read-overlap graphs.

PubMed

Shomorony, Ilan; Kim, Samuel H; Courtade, Thomas A; Tse, David N C

2016-09-01

In the context of third-generation long-read sequencing technologies, read-overlap-based approaches are expected to play a central role in the assembly step. A fundamental challenge in assembling from a read-overlap graph is that the true sequence corresponds to a Hamiltonian path on the graph, and, under most formulations, the assembly problem becomes NP-hard, restricting practical approaches to heuristics. In this work, we avoid this seemingly fundamental barrier by first setting the computational complexity issue aside, and seeking an algorithm that targets information limits In particular, we consider a basic feasibility question: when does the set of reads contain enough information to allow unambiguous reconstruction of the true sequence? Based on insights from this information feasibility question, we present an algorithm-the Not-So-Greedy algorithm-to construct a sparse read-overlap graph. Unlike most other assembly algorithms, Not-So-Greedy comes with a performance guarantee: whenever information feasibility conditions are satisfied, the algorithm reduces the assembly problem to an Eulerian path problem on the resulting graph, and can thus be solved in linear time. In practice, this theoretical guarantee translates into assemblies of higher quality. Evaluations on both simulated reads from real genomes and a PacBio Escherichia coli K12 dataset demonstrate that Not-So-Greedy compares favorably with standard string graph approaches in terms of accuracy of the resulting read-overlap graph and contig N50. Available at github.com/samhykim/nsg courtade@eecs.berkeley.edu or dntse@stanford.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.

Folded concave penalized sparse linear regression: sparsity, statistical performance, and algorithmic theory for local solutions.

PubMed

Liu, Hongcheng; Yao, Tao; Li, Runze; Ye, Yinyu

2017-11-01

This paper concerns the folded concave penalized sparse linear regression (FCPSLR), a class of popular sparse recovery methods. Although FCPSLR yields desirable recovery performance when solved globally, computing a global solution is NP-complete. Despite some existing statistical performance analyses on local minimizers or on specific FCPSLR-based learning algorithms, it still remains open questions whether local solutions that are known to admit fully polynomial-time approximation schemes (FPTAS) may already be sufficient to ensure the statistical performance, and whether that statistical performance can be non-contingent on the specific designs of computing procedures. To address the questions, this paper presents the following threefold results: (i) Any local solution (stationary point) is a sparse estimator, under some conditions on the parameters of the folded concave penalties. (ii) Perhaps more importantly, any local solution satisfying a significant subspace second-order necessary condition (S 3 ONC), which is weaker than the second-order KKT condition, yields a bounded error in approximating the true parameter with high probability. In addition, if the minimal signal strength is sufficient, the S 3 ONC solution likely recovers the oracle solution. This result also explicates that the goal of improving the statistical performance is consistent with the optimization criteria of minimizing the suboptimality gap in solving the non-convex programming formulation of FCPSLR. (iii) We apply (ii) to the special case of FCPSLR with minimax concave penalty (MCP) and show that under the restricted eigenvalue condition, any S 3 ONC solution with a better objective value than the Lasso solution entails the strong oracle property. In addition, such a solution generates a model error (ME) comparable to the optimal but exponential-time sparse estimator given a sufficient sample size, while the worst-case ME is comparable to the Lasso in general. Furthermore, to guarantee the S 3 ONC admits FPTAS.

Structure-preserving and rank-revealing QR-factorizations

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

Bischof, C.H.; Hansen, P.C.

1991-11-01

The rank-revealing QR-factorization (RRQR-factorization) is a special QR-factorization that is guaranteed to reveal the numerical rank of the matrix under consideration. This makes the RRQR-factorization a useful tool in the numerical treatment of many rank-deficient problems in numerical linear algebra. In this paper, a framework is presented for the efficient implementation of RRQR algorithms, in particular, for sparse matrices. A sparse RRQR-algorithm should seek to preserve the structure and sparsity of the matrix as much as possible while retaining the ability to capture safely the numerical rank. To this end, the paper proposes to compute an initial QR-factorization using amore » restricted pivoting strategy guarded by incremental condition estimation (ICE), and then applies the algorithm suggested by Chan and Foster to this QR-factorization. The column exchange strategy used in the initial QR factorization will exploit the fact that certain column exchanges do not change the sparsity structure, and compute a sparse QR-factorization that is a good approximation of the sought-after RRQR-factorization. Due to quantities produced by ICE, the Chan/Foster RRQR algorithm can be implemented very cheaply, thus verifying that the sought-after RRQR-factorization has indeed been computed. Experimental results on a model problem show that the initial QR-factorization is indeed very likely to produce RRQR-factorization.« less

Affordable Care Act and Diabetes Mellitus.

PubMed

Shi, Qian; Nellans, Frank P; Shi, Lizheng

2015-12-01

The Affordable Care Act (ACA) has the potential for great impact on U.S. health care, especially for chronic disease patients requiring long-term care and management. The act was designed to improve insurance coverage, health care access, and quality of care for all Americans, which will assist patients with diabetes mellitus in acquiring routine monitoring and diabetes-related complication screening for better health management and outcomes. There is great potential for patients with diabetes to benefit from the new policy mandating health insurance coverage and plan improvement, Medicaid expansion, minimum coverage guarantees, and free preventative care. However, policy variability among states and ACA implementation present challenges to people with diabetes in understanding and optimizing ACA impact. This paper aims to select the most influential components of the ACA as relates to people with diabetes and discuss how the ACA may improve health care for this vulnerable population.

Coverage-based constraints for IMRT optimization

NASA Astrophysics Data System (ADS)

Mescher, H.; Ulrich, S.; Bangert, M.

2017-09-01

Radiation therapy treatment planning requires an incorporation of uncertainties in order to guarantee an adequate irradiation of the tumor volumes. In current clinical practice, uncertainties are accounted for implicitly with an expansion of the target volume according to generic margin recipes. Alternatively, it is possible to account for uncertainties by explicit minimization of objectives that describe worst-case treatment scenarios, the expectation value of the treatment or the coverage probability of the target volumes during treatment planning. In this note we show that approaches relying on objectives to induce a specific coverage of the clinical target volumes are inevitably sensitive to variation of the relative weighting of the objectives. To address this issue, we introduce coverage-based constraints for intensity-modulated radiation therapy (IMRT) treatment planning. Our implementation follows the concept of coverage-optimized planning that considers explicit error scenarios to calculate and optimize patient-specific probabilities q(\\hat{d}, \\hat{v}) of covering a specific target volume fraction \\hat{v} with a certain dose \\hat{d} . Using a constraint-based reformulation of coverage-based objectives we eliminate the trade-off between coverage and competing objectives during treatment planning. In-depth convergence tests including 324 treatment plan optimizations demonstrate the reliability of coverage-based constraints for varying levels of probability, dose and volume. General clinical applicability of coverage-based constraints is demonstrated for two cases. A sensitivity analysis regarding penalty variations within this planing study based on IMRT treatment planning using (1) coverage-based constraints, (2) coverage-based objectives, (3) probabilistic optimization, (4) robust optimization and (5) conventional margins illustrates the potential benefit of coverage-based constraints that do not require tedious adjustment of target volume objectives.

How Did the Media Report on the Great East Japan Earthquake? Objectivity and Emotionality Seeking in Japanese Media Coverage

PubMed Central

2015-01-01

The Great East Japan Earthquake was a tragic event requiring critical media involvement. Since the media played an important role in conveying factual information, journalists expressed feeling that it was difficult to guarantee the objectivity of their coverage. As media coverage constructs a socio-culturally shared reality among its audience, an examination of the objectivity and emotionality of the contents of the news coverage is needed. In Study 1, we conducted an exploratory content analysis of TV and newspaper coverage from the six month period following the March 11, 2011 disaster, finding that the news media generally reported neutral and objective factual information about the event, with emotionality shown only in the commentary. In order to examine how media coverage was constructed and evaluated by journalists, in Study 2 we conducted an online survey of 115 journalists working for mass media organizations. We found that that the journalists’ orientations tended to be more objective than emotional, which is consistent with the findings of Study 1. However, their evaluations of the objectivity of the published articles were low, especially for the coverage of the nuclear power plant accident, which was an accident of an unprecedented nature. The negative emotions that journalists experienced during their investigations negatively affected subsequent evaluations of the objectivity of their reporting. PMID:25985193

How did the media report on the Great East Japan Earthquake? Objectivity and emotionality seeking in Japanese media coverage.

PubMed

Uchida, Yukiko; Kanagawa, Chie; Takenishi, Ako; Harada, Akira; Okawa, Kiyotake; Yabuno, Hiromi

2015-01-01

The Great East Japan Earthquake was a tragic event requiring critical media involvement. Since the media played an important role in conveying factual information, journalists expressed feeling that it was difficult to guarantee the objectivity of their coverage. As media coverage constructs a socio-culturally shared reality among its audience, an examination of the objectivity and emotionality of the contents of the news coverage is needed. In Study 1, we conducted an exploratory content analysis of TV and newspaper coverage from the six month period following the March 11, 2011 disaster, finding that the news media generally reported neutral and objective factual information about the event, with emotionality shown only in the commentary. In order to examine how media coverage was constructed and evaluated by journalists, in Study 2 we conducted an online survey of 115 journalists working for mass media organizations. We found that that the journalists' orientations tended to be more objective than emotional, which is consistent with the findings of Study 1. However, their evaluations of the objectivity of the published articles were low, especially for the coverage of the nuclear power plant accident, which was an accident of an unprecedented nature. The negative emotions that journalists experienced during their investigations negatively affected subsequent evaluations of the objectivity of their reporting.

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Recording Fathometer Techniques for Determining Distribution and Biomass of Hydrilla verticillata Royle.

DTIC Science & Technology

1980-10-01

infestation or extent of open water was measured following the same procedures described for deter- fmination of transect percent cover. This value was...procedure where the last vegetation type ended along the transect (i.e. hydrilla, eelgrass, open water ), vegetation coverage was determined for the entire...ated open water , no measurements were made. Approximately 150 to 200 prediction stations were used per monthly sample. 61. For sparse and thick

Mismatch and resolution in compressive imaging

NASA Astrophysics Data System (ADS)

Fannjiang, Albert; Liao, Wenjing

2011-09-01

Highly coherent sensing matrices arise in discretization of continuum problems such as radar and medical imaging when the grid spacing is below the Rayleigh threshold as well as in using highly coherent, redundant dictionaries as sparsifying operators. Algorithms (BOMP, BLOOMP) based on techniques of band exclusion and local optimization are proposed to enhance Orthogonal Matching Pursuit (OMP) and deal with such coherent sensing matrices. BOMP and BLOOMP have provably performance guarantee of reconstructing sparse, widely separated objects independent of the redundancy and have a sparsity constraint and computational cost similar to OMP's. Numerical study demonstrates the effectiveness of BLOOMP for compressed sensing with highly coherent, redundant sensing matrices.

Clarifying the scope of Italian NHS coverage. Is it feasible? Is it desirable?

PubMed

Fattore, G

1999-12-01

The reduction in National Health Service (NHS) expenditure as a share of total health care expenditure, the fragmentation of the NHS into 21 regional systems and the implementation of a 'quasi-market' on the provider side of the system has pressed the government to define and specify, in detail, the set of services that are to be guaranteed by the public sector. To understand whether rationing can be more rational and explicit in the Italian NHS, the following are analysed: (i) the new positive list of drugs, as a major example of limiting and making more rational NHS pharmaceutical coverage; (ii) the Di Bella case, as an example of the difficulties of rational policy-making on sensitive issues; (iii) what Italian people think about health care rationing and priority setting (using the 1998 Eurobarometer Survey);( iv) the criteria defining the set of 'essential services' to be guaranteed to all Italian citizens, which are contained in the recently released National Health Plan. The 'revolution' that has taken place in the pharmaceutical sector shows it is feasible to limit, in an explicit and rational way, the extent of NHS coverage. However, the re-classification of the positive list should be regarded as an exceptional event in the history of Italian social policy. The 'Di Bella' case, on the contrary, shows that limiting NHS coverage can be very unpopular, and that the Italian cultural and social context can be unfavourable for the implementation of hard choices. Public attitude toward rationing seems to confirm that Italians are not familiar with rationing issues. Thus, it is very difficult to predict whether the national government will really go ahead with the implementation of a 'list of essential services' and whether this attempt will be successful. Rationing and priority setting should be discussed in the context of a general debate concerning the future of the Italian NHS.

34 CFR Appendix D to Part 682 - Policy for Waiving the Secretary's Right To Recover or Refuse To Pay Interest Benefits, Special...

Code of Federal Regulations, 2010 CFR

2010-07-01

... agency to do so, the Secretary will permit an agency to take either of the following approaches to its... documented, a case-by-case exercise of reasonable discretion allowing for guarantee coverage to be continued... repayment schedule or agreement.) In the case of a payment made by cash, money order, or other means that do...

Universalization of Primary Education in Colombia: The New School Programme. Notes, Comments... No. 191 = Colombie: L'enseignement primaire pour tous le programme "Ecole nouvelle."

ERIC Educational Resources Information Center

Colbert, Vicky; Arboleda, Jairo

For the first time, Colombia is in a position to comply with the article of her constitution which guarantees a primary education to all citizens. The country now has the technical, political and financial conditions necessary to universalize primary education, particularly in rural areas where low coverage and inefficiency of the system have…

High-dimensional statistical inference: From vector to matrix

NASA Astrophysics Data System (ADS)

Zhang, Anru

Statistical inference for sparse signals or low-rank matrices in high-dimensional settings is of significant interest in a range of contemporary applications. It has attracted significant recent attention in many fields including statistics, applied mathematics and electrical engineering. In this thesis, we consider several problems in including sparse signal recovery (compressed sensing under restricted isometry) and low-rank matrix recovery (matrix recovery via rank-one projections and structured matrix completion). The first part of the thesis discusses compressed sensing and affine rank minimization in both noiseless and noisy cases and establishes sharp restricted isometry conditions for sparse signal and low-rank matrix recovery. The analysis relies on a key technical tool which represents points in a polytope by convex combinations of sparse vectors. The technique is elementary while leads to sharp results. It is shown that, in compressed sensing, delta kA < 1/3, deltak A+ thetak,kA < 1, or deltatkA < √( t - 1)/t for any given constant t ≥ 4/3 guarantee the exact recovery of all k sparse signals in the noiseless case through the constrained ℓ1 minimization, and similarly in affine rank minimization delta rM < 1/3, deltar M + thetar, rM < 1, or deltatrM< √( t - 1)/t ensure the exact reconstruction of all matrices with rank at most r in the noiseless case via the constrained nuclear norm minimization. Moreover, for any epsilon > 0, delta kA < 1/3 + epsilon, deltak A + thetak,kA < 1 + epsilon, or deltatkA< √(t - 1) / t + epsilon are not sufficient to guarantee the exact recovery of all k-sparse signals for large k. Similar result also holds for matrix recovery. In addition, the conditions delta kA<1/3, deltak A+ thetak,kA<1, delta tkA < √(t - 1)/t and deltarM<1/3, delta rM+ thetar,rM<1, delta trM< √(t - 1)/ t are also shown to be sufficient respectively for stable recovery of approximately sparse signals and low-rank matrices in the noisy case. For the second part of the thesis, we introduce a rank-one projection model for low-rank matrix recovery and propose a constrained nuclear norm minimization method for stable recovery of low-rank matrices in the noisy case. The procedure is adaptive to the rank and robust against small perturbations. Both upper and lower bounds for the estimation accuracy under the Frobenius norm loss are obtained. The proposed estimator is shown to be rate-optimal under certain conditions. The estimator is easy to implement via convex programming and performs well numerically. The techniques and main results developed in the chapter also have implications to other related statistical problems. An application to estimation of spiked covariance matrices from one-dimensional random projections is considered. The results demonstrate that it is still possible to accurately estimate the covariance matrix of a high-dimensional distribution based only on one-dimensional projections. For the third part of the thesis, we consider another setting of low-rank matrix completion. Current literature on matrix completion focuses primarily on independent sampling models under which the individual observed entries are sampled independently. Motivated by applications in genomic data integration, we propose a new framework of structured matrix completion (SMC) to treat structured missingness by design. Specifically, our proposed method aims at efficient matrix recovery when a subset of the rows and columns of an approximately low-rank matrix are observed. We provide theoretical justification for the proposed SMC method and derive lower bound for the estimation errors, which together establish the optimal rate of recovery over certain classes of approximately low-rank matrices. Simulation studies show that the method performs well in finite sample under a variety of configurations. The method is applied to integrate several ovarian cancer genomic studies with different extent of genomic measurements, which enables us to construct more accurate prediction rules for ovarian cancer survival.

Dose-shaping using targeted sparse optimization

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

Sayre, George A.; Ruan, Dan

2013-07-15

Purpose: Dose volume histograms (DVHs) are common tools in radiation therapy treatment planning to characterize plan quality. As statistical metrics, DVHs provide a compact summary of the underlying plan at the cost of losing spatial information: the same or similar dose-volume histograms can arise from substantially different spatial dose maps. This is exactly the reason why physicians and physicists scrutinize dose maps even after they satisfy all DVH endpoints numerically. However, up to this point, little has been done to control spatial phenomena, such as the spatial distribution of hot spots, which has significant clinical implications. To this end, themore » authors propose a novel objective function that enables a more direct tradeoff between target coverage, organ-sparing, and planning target volume (PTV) homogeneity, and presents our findings from four prostate cases, a pancreas case, and a head-and-neck case to illustrate the advantages and general applicability of our method.Methods: In designing the energy minimization objective (E{sub tot}{sup sparse}), the authors utilized the following robust cost functions: (1) an asymmetric linear well function to allow differential penalties for underdose, relaxation of prescription dose, and overdose in the PTV; (2) a two-piece linear function to heavily penalize high dose and mildly penalize low and intermediate dose in organs-at risk (OARs); and (3) a total variation energy, i.e., the L{sub 1} norm applied to the first-order approximation of the dose gradient in the PTV. By minimizing a weighted sum of these robust costs, general conformity to dose prescription and dose-gradient prescription is achieved while encouraging prescription violations to follow a Laplace distribution. In contrast, conventional quadratic objectives are associated with a Gaussian distribution of violations, which is less forgiving to large violations of prescription than the Laplace distribution. As a result, the proposed objective E{sub tot}{sup sparse} improves tradeoff between planning goals by 'sacrificing' voxels that have already been violated to improve PTV coverage, PTV homogeneity, and/or OAR-sparing. In doing so, overall plan quality is increased since these large violations only arise if a net reduction in E{sub tot}{sup sparse} occurs as a result. For example, large violations to dose prescription in the PTV in E{sub tot}{sup sparse}-optimized plans will naturally localize to voxels in and around PTV-OAR overlaps where OAR-sparing may be increased without compromising target coverage. The authors compared the results of our method and the corresponding clinical plans using analyses of DVH plots, dose maps, and two quantitative metrics that quantify PTV homogeneity and overdose. These metrics do not penalize underdose since E{sub tot}{sup sparse}-optimized plans were planned such that their target coverage was similar or better than that of the clinical plans. Finally, plan deliverability was assessed with the 2D modulation index.Results: The proposed method was implemented using IBM's CPLEX optimization package (ILOG CPLEX, Sunnyvale, CA) and required 1-4 min to solve with a 12-core Intel i7 processor. In the testing procedure, the authors optimized for several points on the Pareto surface of four 7-field 6MV prostate cases that were optimized for different levels of PTV homogeneity and OAR-sparing. The generated results were compared against each other and the clinical plan by analyzing their DVH plots and dose maps. After developing intuition by planning the four prostate cases, which had relatively few tradeoffs, the authors applied our method to a 7-field 6 MV pancreas case and a 9-field 6MV head-and-neck case to test the potential impact of our method on more challenging cases. The authors found that our formulation: (1) provided excellent flexibility for balancing OAR-sparing with PTV homogeneity; and (2) permitted the dose planner more control over the evolution of the PTV's spatial dose distribution than conventional objective functions. In particular, E{sub tot}{sup sparse}-optimized plans for the pancreas case and head-and-neck case exhibited substantially improved sparing of the spinal cord and parotid glands, respectively, while maintaining or improving sparing for other OARs and markedly improving PTV homogeneity. Plan deliverability for E{sub tot}{sup sparse}-optimized plans was shown to be better than their associated clinical plans, according to the two-dimensional modulation index.Conclusions: These results suggest that our formulation may be used to improve dose-shaping and OAR-sparing for complicated disease sites, such as the pancreas or head and neck. Furthermore, our objective function and constraints are linear and constitute a linear program, which converges to the global minimum quickly, and can be easily implemented in treatment planning software. Thus, the authors expect fast translation of our method to the clinic where it may have a positive impact on plan quality for challenging disease sites.« less

Expanding the catalog of binary black-hole simulations: aligned-spin configurations

NASA Astrophysics Data System (ADS)

Chu, Tony; Pfeiffer, Harald; Scheel, Mark; Szilagyi, Bela; SXS Collaboration

2015-04-01

A major goal of numerical relativity is to model the inspiral and merger of binary black holes through sufficiently accurate and long simulations, to enable the successful detection of gravitational waves. However, covering the full parameter space of binary configurations is a computationally daunting task. The SXS Collaboration has made important progress in this direction recently, with a catalog of 174 publicly available binary black-hole simulations [black-holes.org/waveforms]. Nevertheless, the parameter-space coverage remains sparse, even for non-precessing binaries. In this talk, I will describe an addition to the SXS catalog to improve its coverage, consisting of 95 new simulations of aligned-spin binaries with moderate mass ratios and dimensionless spins as high as 0.9. Some applications of these new simulations will also be mentioned.

Sparse Representation with Spatio-Temporal Online Dictionary Learning for Efficient Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Tang, Xin; Zou, Junni; Xiong, Hongkai; Chen, Chang Wen

2016-07-27

Classical dictionary learning methods for video coding suer from high computational complexity and interfered coding eciency by disregarding its underlying distribution. This paper proposes a spatio-temporal online dictionary learning (STOL) algorithm to speed up the convergence rate of dictionary learning with a guarantee of approximation error. The proposed algorithm incorporates stochastic gradient descents to form a dictionary of pairs of 3-D low-frequency and highfrequency spatio-temporal volumes. In each iteration of the learning process, it randomly selects one sample volume and updates the atoms of dictionary by minimizing the expected cost, rather than optimizes empirical cost over the complete training data like batch learning methods, e.g. K-SVD. Since the selected volumes are supposed to be i.i.d. samples from the underlying distribution, decomposition coecients attained from the trained dictionary are desirable for sparse representation. Theoretically, it is proved that the proposed STOL could achieve better approximation for sparse representation than K-SVD and maintain both structured sparsity and hierarchical sparsity. It is shown to outperform batch gradient descent methods (K-SVD) in the sense of convergence speed and computational complexity, and its upper bound for prediction error is asymptotically equal to the training error. With lower computational complexity, extensive experiments validate that the STOL based coding scheme achieves performance improvements than H.264/AVC or HEVC as well as existing super-resolution based methods in ratedistortion performance and visual quality.

Analysis of Your Professional Liability Insurance Policy

PubMed Central

Sadusk, Joseph F.; Hassard, Howard; Waterson, Rollen

1958-01-01

The most important lessons for the physician to learn in regard to his professional liability insurance coverage are the following: 1. The physician should carefully read his professional liability policy and should secure the educated aid of his attorney and his insurance broker, if they are conversant with this field. 2. He should particularly read the definition of coverage and carefully survey the exclusion clauses which may deny him coverage under certain circumstances. 3. If the physician is in partnership or in a group, he should be certain that he has contingent partnership coverage. 4. The physician should accept coverage only from an insurance carrier of sufficient size and stability that he can be sure his coverage will be guaranteed for “latent liability” claims as the years go along—certainly for his lifetime. 5. The insurance carrier offering the professional liability policy should be prepared to offer coverages up to at least $100,000/$300,000. 6. The physician should be assured that the insurance carrier has claims-handling personnel and legal counsel who are experienced and expert in the professional liability field and who are locally available for service. 7. The physician is best protected by a local or state group program, next best by a national group program, and last, by individual coverage. 8. The physician should look with suspicion on a cancellation clause in which his policy may be summarily cancelled on brief notice. 9. The physician should not buy professional liability insurance on the basis of price alone; adequacy of coverage and service and a good insurance company for his protection should be the deciding factors. PMID:13489519

Analyzing the Impacts of Increased Wind Power on Generation Revenue Sufficiency: Preprint

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

Wang, Qin; Wu, Hongyu; Tan, Jin

2016-08-01

The Revenue Sufficiency Guarantee (RSG), as part of make-whole (or uplift) payments in electricity markets, is designed to recover the generation resources' offer-based production costs that are not otherwise covered by their market revenues. Increased penetrations of wind power will bring significant impacts to the RSG payments in the markets. However, literature related to this topic is sparse. This paper first reviews the industrial practices of implementing RSG in major U.S. independent system operators (ISOs) and regional transmission operators (RTOs) and then develops a general RSG calculation method. Finally, an 18-bus test system is adopted to demonstrate the impacts ofmore » increased wind power on RSG payments.« less

Analyzing the Impacts of Increased Wind Power on Generation Revenue Sufficiency

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

Wang, Qin; Wu, Hongyu; Tan, Jin

2016-11-14

The Revenue Sufficiency Guarantee (RSG), as part of make-whole (or uplift) payments in electricity markets, is designed to recover the generation resources' offer-based production costs that are not otherwise covered by their market revenues. Increased penetrations of wind power will bring significant impacts to the RSG payments in the markets. However, literature related to this topic is sparse. This paper first reviews the industrial practices of implementing RSG in major U.S. independent system operators (ISOs) and regional transmission operators (RTOs) and then develops a general RSG calculation method. Finally, an 18-bus test system is adopted to demonstrate the impacts ofmore » increased wind power on RSG payments.« less

JESTR: Jupiter Exploration Science in the Time Regime

NASA Technical Reports Server (NTRS)

Noll, Keith S.; Simon-Miller, A. A.; Wong, M. H.; Choi, D. S.

2012-01-01

Solar system objects are inherently time-varying with changes that occur on timescales ranging from seconds to years. For all planets other than the Earth, temporal coverage of atmospheric phenomena is limited and sparse. Many important atmospheric phenomena, especially those related to atmospheric dynamics, can be studied in only very limited ways with current data. JESTR is a mission concept that would remedy this gap in our exploration of the solar system by ncar-continuous imaging and spectral monitoring of Jupiter over a multi-year mission lifetime.

Workers' Compensation Insurance and Occupational Injuries

PubMed Central

Oh, Jun-Byoung; Yi, Hyung Kwan

2011-01-01

Objectives Although compensation for occupational injuries and diseases is guaranteed in almost all nations, countries vary greatly with respect to how they organize workers' compensation systems. In this paper, we focus on three aspects of workers' compensation insurance in Organization for Economic Cooperation and Development (OECD) countries - types of systems, employers' funding mechanisms, and coverage for injured workers - and their impacts on the actual frequencies of occupational injuries and diseases. Methods We estimated a panel data fixed effect model with cross-country OECD and International Labor Organization data. We controlled for country fixed effects, relevant aggregate variables, and dummy variables representing the occupational accidents data source. Results First, the use of a private insurance system is found to lower the occupational accidents. Second, the use of risk-based pricing for the payment of employer raises the occupational injuries and diseases. Finally, the wider the coverage of injured workers is, the less frequent the workplace accidents are. Conclusion Private insurance system, fixed flat rate employers' funding mechanism, and higher coverage of compensation scheme are significantly and positively correlated with lower level of occupational accidents compared with the public insurance system, risk-based funding system, and lower coverage of compensation scheme. PMID:22953197

Nutritional Treatment for Inborn Errors of Metabolism: Indications, Regulations, and Availability of Medical Foods and Dietary Supplements Using Phenylketonuria as an Example

PubMed Central

Camp, Kathryn M.; Lloyd-Puryear, Michele A.; Huntington, Kathleen L.

2012-01-01

Medical foods and dietary supplements are used to treat rare inborn errors of metabolism (IEM) identified through state-based universal newborn screening. These products are regulated under Food and Drug Administration (FDA) food and dietary supplement statutes. The lack of harmony in terminology used to refer to medical foods and dietary supplements and the misuse of words that imply that FDA regulates these products as drugs have led to confusion. These products are expensive and, although they are used for medical treatment of IEM, third-party payer coverage of these products is inconsistent across the United States. Clinicians and families report termination of coverage in late adolescence, failure to cover treatment during pregnancy, coverage for select conditions only, or no coverage. We describe the indications for specific nutritional treatment products for IEM and their regulation, availability, and categorization. We conclude with a discussion of the problems that have contributed to the paradox of identifying individuals with IEM through newborn screening but not guaranteeing that they receive optimal treatment. Throughout the paper, we use the nutritional treatment of phenylketonuria as an example of IEM treatment. PMID:22854513

Achieving Crossed Strong Barrier Coverage in Wireless Sensor Network.

PubMed

Han, Ruisong; Yang, Wei; Zhang, Li

2018-02-10

Barrier coverage has been widely used to detect intrusions in wireless sensor networks (WSNs). It can fulfill the monitoring task while extending the lifetime of the network. Though barrier coverage in WSNs has been intensively studied in recent years, previous research failed to consider the problem of intrusion in transversal directions. If an intruder knows the deployment configuration of sensor nodes, then there is a high probability that it may traverse the whole target region from particular directions, without being detected. In this paper, we introduce the concept of crossed barrier coverage that can overcome this defect. We prove that the problem of finding the maximum number of crossed barriers is NP-hard and integer linear programming (ILP) is used to formulate the optimization problem. The branch-and-bound algorithm is adopted to determine the maximum number of crossed barriers. In addition, we also propose a multi-round shortest path algorithm (MSPA) to solve the optimization problem, which works heuristically to guarantee efficiency while maintaining near-optimal solutions. Several conventional algorithms for finding the maximum number of disjoint strong barriers are also modified to solve the crossed barrier problem and for the purpose of comparison. Extensive simulation studies demonstrate the effectiveness of MSPA.

Lalinet status - station expansion and lidar ratio systematic measurements

NASA Astrophysics Data System (ADS)

Landulfo, Eduardo; Lopes, Fabio; Moreira, Gregori Arruda; da Silva, Jonatan; Ristori, Pablo; Quel, Eduardo; Otero, Lidia; Pallota, Juan Vicente; Herrera, Milagros; Salvador, Jacobo; Bali, Juan Lucas; Wolfram, Eliam; Etala, Paula; Barbero, Albane; Forno, Ricardo; Sanchez, Maria Fernanda; Barbosa, Henrique; Gouveia, Diego; Santos, Amanda Vieira; Hoelzemann, Judith; Fernandez, Jose Henrique; Guedes, Anderson; Silva, Antonieta; Barja, Boris; Zamorano, Felix; Legue, Raul Perez; Bastidas, Alvaro; Zabala, Maribel Vellejo; Velez, Juan; Nisperuza, Daniel; Montilla, Elena; Arredondo, Rene Estevam; Marrero, Juan Carlos Antuña; Vega, Alberth Rodriguez; Alados-Arboledas, Lucas; Guerrero-Rascado, Juan Luis; Sugimoto, Nobuo; Yoshitaka, Jin

2018-04-01

LALINET is expanding regionally to guarantee spatial coverage over South and Central Americas. One of the network goals is to obtain a set of regional representative aerosol optical properties such as particle backscatter, extinction and lidar ratio. Given the North-South extension and influence of distinct airmass circulation patterns it is paramount to distinguish these optical parameters in order to gain better perfomance in radiation transfer models. A set of lidar ratio data is presented.

Combining GOES-16 Geostationary Lightning Mapper with the ground based Earth Networks Total Lightning Network

NASA Astrophysics Data System (ADS)

Stock, M.; Lapierre, J. L.; Zhu, Y.

2017-12-01

Recently, the Geostationary Lightning Mapper (GLM) began collecting optical data to locate lightning events and flashes over the North and South American continents. This new instrument promises uniformly high detection efficiency (DE) over its entire field of view, with location accuracy on the order of 10 km. In comparison, Earth Networks Total Lightning Networks (ENTLN) has a less uniform coverage, with higher DE in regions with dense sensor coverage, and lower DE with sparse sensor coverage. ENTLN also offers better location accuracy, lightning classification, and peak current estimation for their lightning locations. It is desirable to produce an integrated dataset, combining the strong points of GLM and ENTLN. The easiest way to achieve this is to simply match located lightning processes from each system using time and distance criteria. This simple method will be limited in scope by the uneven coverage of the ground based network. Instead, we will use GLM group locations to look up the electric field change data recorded by ground sensors near each GLM group, vastly increasing the coverage of the ground network. The ground waveforms can then be used for: improvements to differentiation between glint and lightning for GLM, higher precision lighting location, current estimation, and lightning process classification. Presented is an initial implementation of this type of integration using preliminary GLM data, and waveforms from ENTLN.

Subspace aware recovery of low rank and jointly sparse signals

PubMed Central

Biswas, Sampurna; Dasgupta, Soura; Mudumbai, Raghuraman; Jacob, Mathews

2017-01-01

We consider the recovery of a matrix X, which is simultaneously low rank and joint sparse, from few measurements of its columns using a two-step algorithm. Each column of X is measured using a combination of two measurement matrices; one which is the same for every column, while the the second measurement matrix varies from column to column. The recovery proceeds by first estimating the row subspace vectors from the measurements corresponding to the common matrix. The estimated row subspace vectors are then used to recover X from all the measurements using a convex program of joint sparsity minimization. Our main contribution is to provide sufficient conditions on the measurement matrices that guarantee the recovery of such a matrix using the above two-step algorithm. The results demonstrate quite significant savings in number of measurements when compared to the standard multiple measurement vector (MMV) scheme, which assumes same time invariant measurement pattern for all the time frames. We illustrate the impact of the sampling pattern on reconstruction quality using breath held cardiac cine MRI and cardiac perfusion MRI data, while the utility of the algorithm to accelerate the acquisition is demonstrated on MR parameter mapping. PMID:28630889

Progressive Dictionary Learning with Hierarchical Predictive Structure for Scalable Video Coding.

PubMed

Dai, Wenrui; Shen, Yangmei; Xiong, Hongkai; Jiang, Xiaoqian; Zou, Junni; Taubman, David

2017-04-12

Dictionary learning has emerged as a promising alternative to the conventional hybrid coding framework. However, the rigid structure of sequential training and prediction degrades its performance in scalable video coding. This paper proposes a progressive dictionary learning framework with hierarchical predictive structure for scalable video coding, especially in low bitrate region. For pyramidal layers, sparse representation based on spatio-temporal dictionary is adopted to improve the coding efficiency of enhancement layers (ELs) with a guarantee of reconstruction performance. The overcomplete dictionary is trained to adaptively capture local structures along motion trajectories as well as exploit the correlations between neighboring layers of resolutions. Furthermore, progressive dictionary learning is developed to enable the scalability in temporal domain and restrict the error propagation in a close-loop predictor. Under the hierarchical predictive structure, online learning is leveraged to guarantee the training and prediction performance with an improved convergence rate. To accommodate with the stateof- the-art scalable extension of H.264/AVC and latest HEVC, standardized codec cores are utilized to encode the base and enhancement layers. Experimental results show that the proposed method outperforms the latest SHVC and HEVC simulcast over extensive test sequences with various resolutions.

Kriging and local polynomial methods for blending satellite-derived and gauge precipitation estimates to support hydrologic early warning systems

USGS Publications Warehouse

Verdin, Andrew; Funk, Christopher C.; Rajagopalan, Balaji; Kleiber, William

2016-01-01

Robust estimates of precipitation in space and time are important for efficient natural resource management and for mitigating natural hazards. This is particularly true in regions with developing infrastructure and regions that are frequently exposed to extreme events. Gauge observations of rainfall are sparse but capture the precipitation process with high fidelity. Due to its high resolution and complete spatial coverage, satellite-derived rainfall data are an attractive alternative in data-sparse regions and are often used to support hydrometeorological early warning systems. Satellite-derived precipitation data, however, tend to underrepresent extreme precipitation events. Thus, it is often desirable to blend spatially extensive satellite-derived rainfall estimates with high-fidelity rain gauge observations to obtain more accurate precipitation estimates. In this research, we use two different methods, namely, ordinary kriging and κ-nearest neighbor local polynomials, to blend rain gauge observations with the Climate Hazards Group Infrared Precipitation satellite-derived precipitation estimates in data-sparse Central America and Colombia. The utility of these methods in producing blended precipitation estimates at pentadal (five-day) and monthly time scales is demonstrated. We find that these blending methods significantly improve the satellite-derived estimates and are competitive in their ability to capture extreme precipitation.

Symbolic PathFinder: Symbolic Execution of Java Bytecode

NASA Technical Reports Server (NTRS)

Pasareanu, Corina S.; Rungta, Neha

2010-01-01

Symbolic Pathfinder (SPF) combines symbolic execution with model checking and constraint solving for automated test case generation and error detection in Java programs with unspecified inputs. In this tool, programs are executed on symbolic inputs representing multiple concrete inputs. Values of variables are represented as constraints generated from the analysis of Java bytecode. The constraints are solved using off-the shelf solvers to generate test inputs guaranteed to achieve complex coverage criteria. SPF has been used successfully at NASA, in academia, and in industry.

The Joker: A Custom Monte Carlo Sampler for Binary-star and Exoplanet Radial Velocity Data

NASA Astrophysics Data System (ADS)

Price-Whelan, Adrian M.; Hogg, David W.; Foreman-Mackey, Daniel; Rix, Hans-Walter

2017-03-01

Given sparse or low-quality radial velocity measurements of a star, there are often many qualitatively different stellar or exoplanet companion orbit models that are consistent with the data. The consequent multimodality of the likelihood function leads to extremely challenging search, optimization, and Markov chain Monte Carlo (MCMC) posterior sampling over the orbital parameters. Here we create a custom Monte Carlo sampler for sparse or noisy radial velocity measurements of two-body systems that can produce posterior samples for orbital parameters even when the likelihood function is poorly behaved. The six standard orbital parameters for a binary system can be split into four nonlinear parameters (period, eccentricity, argument of pericenter, phase) and two linear parameters (velocity amplitude, barycenter velocity). We capitalize on this by building a sampling method in which we densely sample the prior probability density function (pdf) in the nonlinear parameters and perform rejection sampling using a likelihood function marginalized over the linear parameters. With sparse or uninformative data, the sampling obtained by this rejection sampling is generally multimodal and dense. With informative data, the sampling becomes effectively unimodal but too sparse: in these cases we follow the rejection sampling with standard MCMC. The method produces correct samplings in orbital parameters for data that include as few as three epochs. The Joker can therefore be used to produce proper samplings of multimodal pdfs, which are still informative and can be used in hierarchical (population) modeling. We give some examples that show how the posterior pdf depends sensitively on the number and time coverage of the observations and their uncertainties.

SMURC: High-Dimension Small-Sample Multivariate Regression With Covariance Estimation.

PubMed

Bayar, Belhassen; Bouaynaya, Nidhal; Shterenberg, Roman

2017-03-01

We consider a high-dimension low sample-size multivariate regression problem that accounts for correlation of the response variables. The system is underdetermined as there are more parameters than samples. We show that the maximum likelihood approach with covariance estimation is senseless because the likelihood diverges. We subsequently propose a normalization of the likelihood function that guarantees convergence. We call this method small-sample multivariate regression with covariance (SMURC) estimation. We derive an optimization problem and its convex approximation to compute SMURC. Simulation results show that the proposed algorithm outperforms the regularized likelihood estimator with known covariance matrix and the sparse conditional Gaussian graphical model. We also apply SMURC to the inference of the wing-muscle gene network of the Drosophila melanogaster (fruit fly).

Measuring suspended sediment: Chapter 10

USGS Publications Warehouse

Gray, J.R.; Landers, M.N.

2013-01-01

Suspended sediment in streams and rivers can be measured using traditional instruments and techniques and (or) surrogate technologies. The former, as described herein, consists primarily of both manually deployed isokinetic samplers and their deployment protocols developed by the Federal Interagency Sedimentation Project. They are used on all continents other than Antarctica. The reliability of the typically spatially rich but temporally sparse data produced by traditional means is supported by a broad base of scientific literature since 1940. However, the suspended sediment surrogate technologies described herein – based on hydroacoustic, nephelometric, laser, and pressure difference principles – tend to produce temporally rich but in some cases spatially sparse datasets. The value of temporally rich data in the accuracy of continuous sediment-discharge records is hard to overstate, in part because such data can often overcome the shortcomings of poor spatial coverage. Coupled with calibration data produced by traditional means, surrogate technologies show considerable promise toward providing the fluvial sediment data needed to increase and bring more consistency to sediment-discharge measurements worldwide.

A "Cap" on Medicaid: How Block Grants, Per Capita Caps, and Capped Allotments Might Fundamentally Change the Safety Net.

PubMed

Mager-Mardeusz, Haleigh; Lenz, Cosima; Kominski, Gerald F

2017-04-01

Changing the Medicaid program is a top priority for the Republican party. Common themes from GOP proposals include converting Medicaid from a jointly financed entitlement benefit to a form of capped federal financing. While proponents of this reform argue that it would provide greater flexibility and a more predictable budget for state governments, serious consequences would likely result for Medicaid enrollees and state governments. Under all three scenarios promoted by Republicans--block grants, capped allotments, and per capita caps—most states would face increased costs. For all three scenarios, the capped nature of the funding guarantees that the real value of funds would decrease in future years relative to what would be expected from growth under the current program. Although the federal government would undoubtedly realize savings from all three scenarios, the impact might lead states to reduce benefits and services, create waiting lists, impose cost-sharing on a traditionally low-income enrollee population, or impose other obstacles to coverage. Nationally, as many as 20.5 million Americans stand to lose coverage under the proposed Medicaid changes. In California, up to 6 million people could lose coverage if changes to the Medicaid program were coupled with the repeal of coverage for the expansion population.

University-Based Teleradiology in the United States.

PubMed

Hunter, Tim B; Krupinski, Elizabeth A

2014-04-15

This article reviews the University of Arizona's more than 15 years of experience with teleradiology and provides an overview of university-based teleradiology practice in the United States (U.S.). In the U.S., teleradiology is a major economic enterprise with many private for-profit companies offering national teleradiology services (i.e., professional interpretation of radiologic studies of all types by American Board of Radiology certified radiologists). The initial thrust for teleradiology was for after-hours coverage of radiologic studies, but teleradiology has expanded its venue to include routine full-time or partial coverage for small hospitals, clinics, specialty medical practices, and urgent care centers. It also provides subspecialty radiologic coverage not available at smaller medical centers and clinics. Many U.S. university-based academic departments of radiology provide teleradiology services usually as an additional for-profit business to supplement departmental income. Since academic-based teleradiology providers have to compete in a very demanding marketplace, their success is not guaranteed. They must provide timely, high-quality professional services for a competitive price. Academic practices have the advantage of house officers and fellows who can help with the coverage, and they have excellent subspecialty expertise. The marketplace is constantly shifting, and university-based teleradiology practices have to be nimble and adjust to ever-changing situations.

Application of global datasets for hydrological modelling of a remote, snowmelt driven catchment in the Canadian Sub-Arctic

NASA Astrophysics Data System (ADS)

Casson, David; Werner, Micha; Weerts, Albrecht; Schellekens, Jaap; Solomatine, Dimitri

2017-04-01

Hydrological modelling in the Canadian Sub-Arctic is hindered by the limited spatial and temporal coverage of local meteorological data. Local watershed modelling often relies on data from a sparse network of meteorological stations with a rough density of 3 active stations per 100,000 km2. Global datasets hold great promise for application due to more comprehensive spatial and extended temporal coverage. A key objective of this study is to demonstrate the application of global datasets and data assimilation techniques for hydrological modelling of a data sparse, Sub-Arctic watershed. Application of available datasets and modelling techniques is currently limited in practice due to a lack of local capacity and understanding of available tools. Due to the importance of snow processes in the region, this study also aims to evaluate the performance of global SWE products for snowpack modelling. The Snare Watershed is a 13,300 km2 snowmelt driven sub-basin of the Mackenzie River Basin, Northwest Territories, Canada. The Snare watershed is data sparse in terms of meteorological data, but is well gauged with consistent discharge records since the late 1970s. End of winter snowpack surveys have been conducted every year from 1978-present. The application of global re-analysis datasets from the EU FP7 eartH2Observe project are investigated in this study. Precipitation data are taken from Multi-Source Weighted-Ensemble Precipitation (MSWEP) and temperature data from Watch Forcing Data applied to European Reanalysis (ERA)-Interim data (WFDEI). GlobSnow-2 is a global Snow Water Equivalent (SWE) measurement product funded by the European Space Agency (ESA) and is also evaluated over the local watershed. Downscaled precipitation, temperature and potential evaporation datasets are used as forcing data in a distributed version of the HBV model implemented in the WFLOW framework. Results demonstrate the successful application of global datasets in local watershed modelling, but that validation of actual frozen precipitation and snowpack conditions is very difficult. The distributed hydrological model shows good streamflow simulation performance based on statistical model evaluation techniques. Results are also promising for inter-annual variability, spring snowmelt onset and time to peak flows. It is expected that data assimilation of stream flow using an Ensemble Kalman Filter will further improve model performance. This study shows that global re-analysis datasets hold great potential for understanding the hydrology and snowpack dynamics of the expansive and data sparse sub-Arctic. However, global SWE products will require further validation and algorithm improvements, particularly over boreal forest and lake-rich regions.

A Performance Comparison of the Parallel Preconditioners for Iterative Methods for Large Sparse Linear Systems Arising from Partial Differential Equations on Structured Grids

NASA Astrophysics Data System (ADS)

Ma, Sangback

In this paper we compare various parallel preconditioners such as Point-SSOR (Symmetric Successive OverRelaxation), ILU(0) (Incomplete LU) in the Wavefront ordering, ILU(0) in the Multi-color ordering, Multi-Color Block SOR (Successive OverRelaxation), SPAI (SParse Approximate Inverse) and pARMS (Parallel Algebraic Recursive Multilevel Solver) for solving large sparse linear systems arising from two-dimensional PDE (Partial Differential Equation)s on structured grids. Point-SSOR is well-known, and ILU(0) is one of the most popular preconditioner, but it is inherently serial. ILU(0) in the Wavefront ordering maximizes the parallelism in the natural order, but the lengths of the wave-fronts are often nonuniform. ILU(0) in the Multi-color ordering is a simple way of achieving a parallelism of the order N, where N is the order of the matrix, but its convergence rate often deteriorates as compared to that of natural ordering. We have chosen the Multi-Color Block SOR preconditioner combined with direct sparse matrix solver, since for the Laplacian matrix the SOR method is known to have a nondeteriorating rate of convergence when used with the Multi-Color ordering. By using block version we expect to minimize the interprocessor communications. SPAI computes the sparse approximate inverse directly by least squares method. Finally, ARMS is a preconditioner recursively exploiting the concept of independent sets and pARMS is the parallel version of ARMS. Experiments were conducted for the Finite Difference and Finite Element discretizations of five two-dimensional PDEs with large meshsizes up to a million on an IBM p595 machine with distributed memory. Our matrices are real positive, i. e., their real parts of the eigenvalues are positive. We have used GMRES(m) as our outer iterative method, so that the convergence of GMRES(m) for our test matrices are mathematically guaranteed. Interprocessor communications were done using MPI (Message Passing Interface) primitives. The results show that in general ILU(0) in the Multi-Color ordering ahd ILU(0) in the Wavefront ordering outperform the other methods but for symmetric and nearly symmetric 5-point matrices Multi-Color Block SOR gives the best performance, except for a few cases with a small number of processors.

Quantitative Damage Detection and Sparse Sensor Array Optimization of Carbon Fiber Reinforced Resin Composite Laminates for Wind Turbine Blade Structural Health Monitoring

PubMed Central

Li, Xiang; Yang, Zhibo; Chen, Xuefeng

2014-01-01

The active structural health monitoring (SHM) approach for the complex composite laminate structures of wind turbine blades (WTBs), addresses the important and complicated problem of signal noise. After illustrating the wind energy industry's development perspectives and its crucial requirement for SHM, an improved redundant second generation wavelet transform (IRSGWT) pre-processing algorithm based on neighboring coefficients is introduced for feeble signal denoising. The method can avoid the drawbacks of conventional wavelet methods that lose information in transforms and the shortcomings of redundant second generation wavelet (RSGWT) denoising that can lead to error propagation. For large scale WTB composites, how to minimize the number of sensors while ensuring accuracy is also a key issue. A sparse sensor array optimization of composites for WTB applications is proposed that can reduce the number of transducers that must be used. Compared to a full sixteen transducer array, the optimized eight transducer configuration displays better accuracy in identifying the correct position of simulated damage (mass of load) on composite laminates with anisotropic characteristics than a non-optimized array. It can help to guarantee more flexible and qualified monitoring of the areas that more frequently suffer damage. The proposed methods are verified experimentally on specimens of carbon fiber reinforced resin composite laminates. PMID:24763210

Single-breath-hold abdominal [Formula: see text]  mapping using 3D Cartesian Look-Locker with spatiotemporal sparsity constraints.

PubMed

Lugauer, Felix; Wetzl, Jens; Forman, Christoph; Schneider, Manuel; Kiefer, Berthold; Hornegger, Joachim; Nickel, Dominik; Maier, Andreas

2018-06-01

Our aim was to develop and validate a 3D Cartesian Look-Locker [Formula: see text] mapping technique that achieves high accuracy and whole-liver coverage within a single breath-hold. The proposed method combines sparse Cartesian sampling based on a spatiotemporally incoherent Poisson pattern and k-space segmentation, dedicated for high-temporal-resolution imaging. This combination allows capturing tissue with short relaxation times with volumetric coverage. A joint reconstruction of the 3D + inversion time (TI) data via compressed sensing exploits the spatiotemporal sparsity and ensures consistent quality for the subsequent multistep [Formula: see text] mapping. Data from the National Institute of Standards and Technology (NIST) phantom and 11 volunteers, along with reference 2D Look-Locker acquisitions, are used for validation. 2D and 3D methods are compared based on [Formula: see text] values in different abdominal tissues at 1.5 and 3 T. [Formula: see text] maps obtained from the proposed 3D method compare favorably with those from the 2D reference and additionally allow for reformatting or volumetric analysis. Excellent agreement is shown in phantom [bias[Formula: see text] < 2%, bias[Formula: see text] < 5% for (120; 2000) ms] and volunteer data (3D and 2D deviation < 4% for liver, muscle, and spleen) for clinically acceptable scan (20 s) and reconstruction times (< 4 min). Whole-liver [Formula: see text] mapping with high accuracy and precision is feasible in one breath-hold using spatiotemporally incoherent, sparse 3D Cartesian sampling.

Superiorized algorithm for reconstruction of CT images from sparse-view and limited-angle polyenergetic data

NASA Astrophysics Data System (ADS)

Humphries, T.; Winn, J.; Faridani, A.

2017-08-01

Recent work in CT image reconstruction has seen increasing interest in the use of total variation (TV) and related penalties to regularize problems involving reconstruction from undersampled or incomplete data. Superiorization is a recently proposed heuristic which provides an automatic procedure to ‘superiorize’ an iterative image reconstruction algorithm with respect to a chosen objective function, such as TV. Under certain conditions, the superiorized algorithm is guaranteed to find a solution that is as satisfactory as any found by the original algorithm with respect to satisfying the constraints of the problem; this solution is also expected to be superior with respect to the chosen objective. Most work on superiorization has used reconstruction algorithms which assume a linear measurement model, which in the case of CT corresponds to data generated from a monoenergetic x-ray beam. Many CT systems generate x-rays from a polyenergetic spectrum, however, in which the measured data represent an integral of object attenuation over all energies in the spectrum. This inconsistency with the linear model produces the well-known beam hardening artifacts, which impair analysis of CT images. In this work we superiorize an iterative algorithm for reconstruction from polyenergetic data, using both TV and an anisotropic TV (ATV) penalty. We apply the superiorized algorithm in numerical phantom experiments modeling both sparse-view and limited-angle scenarios. In our experiments, the superiorized algorithm successfully finds solutions which are as constraints-compatible as those found by the original algorithm, with significantly reduced TV and ATV values. The superiorized algorithm thus produces images with greatly reduced sparse-view and limited angle artifacts, which are also largely free of the beam hardening artifacts that would be present if a superiorized version of a monoenergetic algorithm were used.

Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids.

PubMed

Hashemi, Abolfazl; Zhu, Banghua; Vikalo, Haris

2018-03-21

Haplotype assembly is the task of reconstructing haplotypes of an individual from a mixture of sequenced chromosome fragments. Haplotype information enables studies of the effects of genetic variations on an organism's phenotype. Most of the mathematical formulations of haplotype assembly are known to be NP-hard and haplotype assembly becomes even more challenging as the sequencing technology advances and the length of the paired-end reads and inserts increases. Assembly of haplotypes polyploid organisms is considerably more difficult than in the case of diploids. Hence, scalable and accurate schemes with provable performance are desired for haplotype assembly of both diploid and polyploid organisms. We propose a framework that formulates haplotype assembly from sequencing data as a sparse tensor decomposition. We cast the problem as that of decomposing a tensor having special structural constraints and missing a large fraction of its entries into a product of two factors, U and [Formula: see text]; tensor [Formula: see text] reveals haplotype information while U is a sparse matrix encoding the origin of erroneous sequencing reads. An algorithm, AltHap, which reconstructs haplotypes of either diploid or polyploid organisms by iteratively solving this decomposition problem is proposed. The performance and convergence properties of AltHap are theoretically analyzed and, in doing so, guarantees on the achievable minimum error correction scores and correct phasing rate are established. The developed framework is applicable to diploid, biallelic and polyallelic polyploid species. The code for AltHap is freely available from https://github.com/realabolfazl/AltHap . AltHap was tested in a number of different scenarios and was shown to compare favorably to state-of-the-art methods in applications to haplotype assembly of diploids, and significantly outperforms existing techniques when applied to haplotype assembly of polyploids.

BWM*: A Novel, Provable, Ensemble-based Dynamic Programming Algorithm for Sparse Approximations of Computational Protein Design.

PubMed

Jou, Jonathan D; Jain, Swati; Georgiev, Ivelin S; Donald, Bruce R

2016-06-01

Sparse energy functions that ignore long range interactions between residue pairs are frequently used by protein design algorithms to reduce computational cost. Current dynamic programming algorithms that fully exploit the optimal substructure produced by these energy functions only compute the GMEC. This disproportionately favors the sequence of a single, static conformation and overlooks better binding sequences with multiple low-energy conformations. Provable, ensemble-based algorithms such as A* avoid this problem, but A* cannot guarantee better performance than exhaustive enumeration. We propose a novel, provable, dynamic programming algorithm called Branch-Width Minimization* (BWM*) to enumerate a gap-free ensemble of conformations in order of increasing energy. Given a branch-decomposition of branch-width w for an n-residue protein design with at most q discrete side-chain conformations per residue, BWM* returns the sparse GMEC in O([Formula: see text]) time and enumerates each additional conformation in merely O([Formula: see text]) time. We define a new measure, Total Effective Search Space (TESS), which can be computed efficiently a priori before BWM* or A* is run. We ran BWM* on 67 protein design problems and found that TESS discriminated between BWM*-efficient and A*-efficient cases with 100% accuracy. As predicted by TESS and validated experimentally, BWM* outperforms A* in 73% of the cases and computes the full ensemble or a close approximation faster than A*, enumerating each additional conformation in milliseconds. Unlike A*, the performance of BWM* can be predicted in polynomial time before running the algorithm, which gives protein designers the power to choose the most efficient algorithm for their particular design problem.

Distance descending ordering method: An O(n) algorithm for inverting the mass matrix in simulation of macromolecules with long branches

NASA Astrophysics Data System (ADS)

Xu, Xiankun; Li, Peiwen

2017-11-01

Fixman's work in 1974 and the follow-up studies have developed a method that can factorize the inverse of mass matrix into an arithmetic combination of three sparse matrices-one of them is positive definite and needs to be further factorized by using the Cholesky decomposition or similar methods. When the molecule subjected to study is of serial chain structure, this method can achieve O (n) time complexity. However, for molecules with long branches, Cholesky decomposition about the corresponding positive definite matrix will introduce massive fill-in due to its nonzero structure. Although there are several methods can be used to reduce the number of fill-in, none of them could strictly guarantee for zero fill-in for all molecules according to our test, and thus cannot obtain O (n) time complexity by using these traditional methods. In this paper we present a new method that can guarantee for no fill-in in doing the Cholesky decomposition, which was developed based on the correlations between the mass matrix and the geometrical structure of molecules. As a result, the inverting of mass matrix will remain the O (n) time complexity, no matter the molecule structure has long branches or not.

77 FR 73117 - Patient Protection and Affordable Care Act; HHS Notice of Benefit and Payment Parameters for 2014

Federal Register 2010, 2011, 2012, 2013, 2014

2012-12-07

...This proposed rule provides further detail and parameters related to: the risk adjustment, reinsurance, and risk corridors programs; cost-sharing reductions; user fees for a Federally- facilitated Exchange; advance payments of the premium tax credit; a Federally-facilitated Small Business Health Option Program; and the medical loss ratio program. The cost-sharing reductions and advanced payments of the premium tax credit, combined with new insurance market reforms, will significantly increase the number of individuals with health insurance coverage, particularly in the individual market. The premium stabilization programs--risk adjustment, reinsurance, and risk corridors--will protect against adverse selection in the newly enrolled population. These programs, in combination with the medical loss ratio program and market reforms extending guaranteed availability (also known as guaranteed issue) protections and prohibiting the use of factors such as health status, medical history, gender, and industry of employment to set premium rates, will help to ensure that every American has access to high-quality, affordable health insurance.

78 FR 15409 - Patient Protection and Affordable Care Act; HHS Notice of Benefit and Payment Parameters for 2014

Federal Register 2010, 2011, 2012, 2013, 2014

2013-03-11

...This final rule provides detail and parameters related to: the risk adjustment, reinsurance, and risk corridors programs; cost-sharing reductions; user fees for Federally-facilitated Exchanges; advance payments of the premium tax credit; the Federally-facilitated Small Business Health Option Program; and the medical loss ratio program. Cost-sharing reductions and advance payments of the premium tax credit, combined with new insurance market reforms, are expected to significantly increase the number of individuals with health insurance coverage, particularly in the individual market. In addition, we expect the premium stabilization programs--risk adjustment, reinsurance, and risk corridors--to protect against the effects of adverse selection. These programs, in combination with the medical loss ratio program and market reforms extending guaranteed availability (also known as guaranteed issue) and prohibiting the use of factors such as health status, medical history, gender, and industry of employment to set premium rates, will help to ensure that every American has access to high-quality, affordable health insurance.

Competing health policies: insurance against universal public systems

PubMed Central

Laurell, Asa Ebba Cristina

2016-01-01

Objectives: This article analyzes the content and outcome of ongoing health reforms in Latin America: Universal Health Coverage with Health Insurance, and the Universal and Public Health Systems. It aims to compare and contrast the conceptual framework and practice of each and verify their concrete results regarding the guarantee of the right to health and access to required services. It identifies a direct relationship between the development model and the type of reform. The neoclassical-neoliberal model has succeeded in converting health into a field of privatized profits, but has failed to guarantee the right to health and access to services, which has discredited the governments. The reform of the progressive governments has succeeded in expanding access to services and ensuring the right to health, but faces difficulties and tensions related to the permanence of a powerful, private, industrial-insurance medical complex and persistence of the ideologies about medicalized 'good medicine'. Based on these findings, some strategies to strengthen unique and supportive public health systems are proposed. PMID:26959328

Identification of Successive ``Unobservable'' Cyber Data Attacks in Power Systems Through Matrix Decomposition

NASA Astrophysics Data System (ADS)

Gao, Pengzhi; Wang, Meng; Chow, Joe H.; Ghiocel, Scott G.; Fardanesh, Bruce; Stefopoulos, George; Razanousky, Michael P.

2016-11-01

This paper presents a new framework of identifying a series of cyber data attacks on power system synchrophasor measurements. We focus on detecting "unobservable" cyber data attacks that cannot be detected by any existing method that purely relies on measurements received at one time instant. Leveraging the approximate low-rank property of phasor measurement unit (PMU) data, we formulate the identification problem of successive unobservable cyber attacks as a matrix decomposition problem of a low-rank matrix plus a transformed column-sparse matrix. We propose a convex-optimization-based method and provide its theoretical guarantee in the data identification. Numerical experiments on actual PMU data from the Central New York power system and synthetic data are conducted to verify the effectiveness of the proposed method.

[Coverage for birth care in Mexico and its interpretation within the context of maternal mortality].

PubMed

Lazcano-Ponce, Eduardo; Schiavon, Raffaela; Uribe-Zúñiga, Patricia; Walker, Dilys; Suárez-López, Leticia; Luna-Gordillo, Rufino; Ulloa-Aguirre, Alfredo

2013-01-01

To evaluate health coverage for birth care in Mexico within the frame of maternal mortality reduction. Two information sources were used: 1) The comparison between the results yield by the Mexican National Health and Nutrition Surveys 2006 and 2012 (ENSANUT 2006 and 2012), and 2) the databases monitoring maternal deaths during 2012 (up to December 26), and live births (LB) in Mexico as estimated by the Mexican National Population Council (Conapo). The national coverage for birth care by medical units is nearly 94.4% at the national level, but in some federal entities such as Chiapas (60.5%), Nayarit (87.8%), Guerrero (91.2%), Durango (92.5%), Oaxaca (92.6%), and Puebla (93.4%), coverage remains below the national average. In women belonging to any social security system (eg. IMSS, IMSS Oportunidades, ISSSTE), coverage is almost 99%, whereas in those affiliated to the Mexican Popular Health Insurance (which depends directly from the Federal Ministry of Health), coverage reached 92.9%. In terms of Maternal Mortality Ratio (MMR), there are still large disparities among federal states in Mexico, with a national average of 47.0 per 100 000 LB (preliminary data for 2012, up to December 26). The MMR estimation has been updated using the most recent population projections. There is no correlation between the level of institutional birth care and the MMR in Mexico. It is thus necessary not only to guarantee universal birth care by health professionals, but also to provide obstetric care by qualified personnel in functional health services networks, to strengthen the quality of obstetric care, family planning programs, and to promote the implementation of new and innovative health policies that include intersectoral actions and human rights-based approaches targeted to reduce the enormous social inequity still prevailing in Mexico.

Funding, coverage, and access under Thailand's universal health insurance program: an update after ten years.

PubMed

Damrongplasit, Kannika; Melnick, Glenn

2015-04-01

In 2001, Thailand implemented a universal coverage program by expanding government-funded health coverage to uninsured citizens and limited their out-of-pocket payments to 30 Baht per encounter and, in 2006, eliminated out-of-pocket payments entirely. Prior research covering the early years of the program showed that the program effectively expanded coverage while a more recent paper of the early effects of the program found that improved access from the program led to a reduction in infant mortality. We expand and update previous analyses of the effects of the 30 Baht program on access and out-of-pocket payments. We analyze national survey and governmental budgeting data through 2011 to examine trends in health care financing, coverage and access, including out-of-pocket payments. By 2011, only 1.64 % of the population remained uninsured in Thailand (down from 2.61 % in 2009). While government funding increased 75 % between 2005 and 2010, budgetary requests by health care providers exceeded approved amounts in many years. The 30 Baht program beneficiaries paid zero out-of-pocket payments for both outpatient and inpatient care. Inpatient and outpatient contact rates across all insurance categories fell slightly over time. Overall, the statistical results suggest that the program is continuing to achieve its goals after 10 years of operation. Insurance coverage is now virtually universal, access has been more or less maintained, government funding has continued to grow, though at rates below requested levels and 30 Baht patients are still guaranteed access to care with limited or no out-of-pocket costs. Important issues going forward are the ability of the government to sustain continued funding increases while minimizing cost sharing.

Evaluation of pneumococcal and influenza vaccination coverage in rheumatology patients receiving biological therapy in a regional referral hospital.

PubMed

Fernández-Prada, María; Brandy-García, Anahy María; Rodríguez-Fonseca, Omar Darío; Huerta-González, Ismael; Fernández-Noval, Federico; Martínez-Ortega, Carmen

2018-05-08

Vaccination coverage for seasonal influenza and pneumococcus in rheumatology patients receiving biological treatment. To identify variables that predict vaccination adherence. Descriptive cross-sectional study. The study involved rheumatology patients who initiated biological therapy between 01/01/2016 and 12/31/2016 in a regional referral hospital. Variables included sociodemographic information, diagnostic data, treating physician, referral to the vaccine unit and vaccination against pneumococcus with 13-valent pneumococcal conjugate vaccine (PCV13) and 23-valent pneumococcal polysaccharide vaccine (PPSV23), as well as seasonal influenza (2016/17). Univariate, bivariate (Chi-square) and multivariate analysis (logistic regression) were performed. The differences were considered significant (P<.05) and the PASW v.18 software package was used. In all, 222 patients were included. Vaccination coverage was: PCV13, 80.2%; PPSV23, 77.9%; influenza 2016/17, 78.8%; PCV13+PPSV23, 75.2%; PCV13+PPSV23+influenza 2016/17, 68.9%. Axial spondylitis had the highest coverage (>80%) for pneumococcal vaccination and combination of pneumococcal with influenza. Overall, 27% of the patients were not referred to the unit. The treating physician was associated with statistical significance in each vaccine alone or combined, but referral to the vaccine unit was independently associated with the highest vaccination coverage (P<.001) in all cases. Compared to the scientific literature, we consider that the coverage of our patients against pneumococcus and influenza is high. Referral of these patients to the vaccine unit is the key to guarantee a correct immunization and to minimize some of the possible infectious adverse effects of biological therapies. Copyright © 2018 Sociedad Española de Reumatología y Colegio Mexicano de Reumatología. Publicado por Elsevier España, S.L.U. All rights reserved.

The path towards universal health coverage in the Arab uprising countries Tunisia, Egypt, Libya, and Yemen.

PubMed

Saleh, Shadi S; Alameddine, Mohamad S; Natafgi, Nabil M; Mataria, Awad; Sabri, Belgacem; Nasher, Jamal; Zeiton, Moez; Ahmad, Shaimaa; Siddiqi, Sameen

2014-01-25

The constitutions of many countries in the Arab world clearly highlight the role of governments in guaranteeing provision of health care as a right for all citizens. However, citizens still have inequitable health-care systems. One component of such inequity relates to restricted financial access to health-care services. The recent uprisings in the Arab world, commonly referred to as the Arab spring, created a sociopolitical momentum that should be used to achieve universal health coverage (UHC). At present, many countries of the Arab spring are considering health coverage as a priority in dialogues for new constitutions and national policy agendas. UHC is also the focus of advocacy campaigns of a number of non-governmental organisations and media outlets. As part of the health in the Arab world Series in The Lancet, this report has three overarching objectives. First, we present selected experiences of other countries that had similar social and political changes, and how these events affected their path towards UHC. Second, we present a brief overview of the development of health-care systems in the Arab world with regard to health-care coverage and financing, with a focus on Egypt, Libya, Tunisia, and Yemen. Third, we aim to integrate historical lessons with present contexts in a roadmap for action that addresses the challenges and opportunities for progression towards UHC. Copyright © 2014 Elsevier Ltd. All rights reserved.

Weighted low-rank sparse model via nuclear norm minimization for bearing fault detection

NASA Astrophysics Data System (ADS)

Du, Zhaohui; Chen, Xuefeng; Zhang, Han; Yang, Boyuan; Zhai, Zhi; Yan, Ruqiang

2017-07-01

It is a fundamental task in the machine fault diagnosis community to detect impulsive signatures generated by the localized faults of bearings. The main goal of this paper is to exploit the low-rank physical structure of periodic impulsive features and further establish a weighted low-rank sparse model for bearing fault detection. The proposed model mainly consists of three basic components: an adaptive partition window, a nuclear norm regularization and a weighted sequence. Firstly, due to the periodic repetition mechanism of impulsive feature, an adaptive partition window could be designed to transform the impulsive feature into a data matrix. The highlight of partition window is to accumulate all local feature information and align them. Then, all columns of the data matrix share similar waveforms and a core physical phenomenon arises, i.e., these singular values of the data matrix demonstrates a sparse distribution pattern. Therefore, a nuclear norm regularization is enforced to capture that sparse prior. However, the nuclear norm regularization treats all singular values equally and thus ignores one basic fact that larger singular values have more information volume of impulsive features and should be preserved as much as possible. Therefore, a weighted sequence with adaptively tuning weights inversely proportional to singular amplitude is adopted to guarantee the distribution consistence of large singular values. On the other hand, the proposed model is difficult to solve due to its non-convexity and thus a new algorithm is developed to search one satisfying stationary solution through alternatively implementing one proximal operator operation and least-square fitting. Moreover, the sensitivity analysis and selection principles of algorithmic parameters are comprehensively investigated through a set of numerical experiments, which shows that the proposed method is robust and only has a few adjustable parameters. Lastly, the proposed model is applied to the wind turbine (WT) bearing fault detection and its effectiveness is sufficiently verified. Compared with the current popular bearing fault diagnosis techniques, wavelet analysis and spectral kurtosis, our model achieves a higher diagnostic accuracy.

On the robust optimization to the uncertain vaccination strategy problem

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

Chaerani, D., E-mail: d.chaerani@unpad.ac.id; Anggriani, N., E-mail: d.chaerani@unpad.ac.id; Firdaniza, E-mail: d.chaerani@unpad.ac.id

2014-02-21

In order to prevent an epidemic of infectious diseases, the vaccination coverage needs to be minimized and also the basic reproduction number needs to be maintained below 1. This means that as we get the vaccination coverage as minimum as possible, thus we need to prevent the epidemic to a small number of people who already get infected. In this paper, we discuss the case of vaccination strategy in term of minimizing vaccination coverage, when the basic reproduction number is assumed as an uncertain parameter that lies between 0 and 1. We refer to the linear optimization model for vaccinationmore » strategy that propose by Becker and Starrzak (see [2]). Assuming that there is parameter uncertainty involved, we can see Tanner et al (see [9]) who propose the optimal solution of the problem using stochastic programming. In this paper we discuss an alternative way of optimizing the uncertain vaccination strategy using Robust Optimization (see [3]). In this approach we assume that the parameter uncertainty lies within an ellipsoidal uncertainty set such that we can claim that the obtained result will be achieved in a polynomial time algorithm (as it is guaranteed by the RO methodology). The robust counterpart model is presented.« less

Autonomous path-planning navigation system for site characterization

NASA Astrophysics Data System (ADS)

Rankin, Arturo L.; Crane, Carl D., III; Armstrong, David G., II; Nease, Allen D.; Brown, H. Edward

1996-05-01

The location and removal of buried munitions is an important yet hazardous task. Current development is aimed at performing both the ordnance location and removal tasks autonomously. An autonomous survey vehicle (ASV) named the Gator has been developed at the Center for Intelligent Machines and Robotics, under the direction of Wright Laboratory, Tyndall Air Force Base, Florida, and the Navy Explosive Ordnance Disposal Technology Division, Indian Head, Maryland. The primary task of the survey vehicle is to autonomously traverse an off-road site, towing behind it a trailer containing a sensor package capable of characterizing the sub-surface contents. Achieving 00 percent coverage of the site is critical to fully characterizing the site. This paper presents a strategy for planning efficient paths for the survey vehicle that guarantees near-complete coverage of a site. A small library of three in-house developed path planners are reviewed. A strategy is also presented to keep the trailer on-path and to calculate the percent of coverage of a site with a resolution of 0.01 m2. All of the algorithms discussed in this paper were initially developed in simulation on a Silicon Graphics computer and subsequently implemented on the survey vehicle.

How frequently will the Surface Water and Ocean Topography (SWOT) observe floods?

NASA Astrophysics Data System (ADS)

Frasson, R. P. M.; Schumann, G.

2017-12-01

The SWOT mission will measure river width and water surface elevations of rivers wider than 100 m. As the data gathered by this mission will be freely available, it can be of great use for flood modeling, especially in areas where streamgage networks are exceedingly sparse, or when data sharing barriers prevent the timely access to information. Despite having world-wide coverage, SWOT's temporal sampling is limited, with most locations being revisited once or twice every 21 days. Our objective is to evaluate which fraction of world-wide floods SWOT will observe and how many observations per event the satellite will likely obtain. We take advantage of the extensive database of floods constructed by the Dartmouth Flood Observatory, who, since 1985, searches through news sources and governmental agencies, and more recently remote sensing imagery for flood information, including flood duration, location and affected area. We cross-referenced the flood locations in the DFO archive with the SWOT prototype prior database of river centerlines and the anticipated satellite's orbit to identify how many of the SWOT swaths were located within 10 km, 20 km, and 50 km from a flood centroid. Subsequently, we estimated the probability that SWOT would have at least one observation of a flood event per distance bin by multiplying the number of swaths in the distance bin by the flood duration divided by the SWOT orbit repeat period. Our analysis contemplated 132 world-wide floods recorded between May 2016 and May 2017. From these, 29, 52, and 86 floods had at least a 50% probability of having one overpass within 10 km, 20 km, and 50 km respectively. Moreover, after excluding flood events with no river centerlines within 10 km of its centroid, the average number of swaths within 10 km of a flood centroid was 1.79, indicating that in the 37 flood events that were likely caused by river flooding, at least one measurement was guaranteed to happen during the event.

Regulating energy transfer of excited carriers and the case for excitation-induced hydrogen dissociation on hydrogenated graphene

PubMed Central

Bang, Junhyeok; Meng, Sheng; Sun, Yi-Yang; West, Damien; Wang, Zhiguo; Gao, Fei; Zhang, S. B.

2013-01-01

Understanding and controlling of excited carrier dynamics is of fundamental and practical importance, particularly in photochemistry and solar energy applications. However, theory of energy relaxation of excited carriers is still in its early stage. Here, using ab initio molecular dynamics (MD) coupled with time-dependent density functional theory, we show a coverage-dependent energy transfer of photoexcited carriers in hydrogenated graphene, giving rise to distinctively different ion dynamics. Graphene with sparsely populated H is difficult to dissociate due to inefficient transfer of the excitation energy into kinetic energy of the H. In contrast, H can easily desorb from fully hydrogenated graphane. The key is to bring down the H antibonding state to the conduction band minimum as the band gap increases. These results can be contrasted to those of standard ground-state MD that predict H in the sparse case should be much less stable than that in fully hydrogenated graphane. Our findings thus signify the importance of carrying out explicit electronic dynamics in excited-state simulations. PMID:23277576

The association between landscape and climate and reported tick paralysis cases in dogs and cats in Australia.

PubMed

Brazier, Isabel; Kelman, Mark; Ward, Michael P

2014-08-29

The aim of this study was to describe the association between landscape and climate factors and the occurrence of tick paralysis cases in dogs and cats reported by veterinarians in Australia. Data were collated based on postcode of residence of the animal and the corresponding landscape (landcover and elevation) and climate (precipitation, temperature) information was derived. During the study period (October 2010-December 2012), a total of 5560 cases (4235 [76%] canine and 1325 [24%] feline cases) were reported from 341 postcodes, mostly along the eastern seaboard of Australia and from the states of New South Wales and Queensland. Significantly more cases were reported from postcodes which contained areas of broadleaved, evergreen tree coverage (P=0.0019); broadleaved, deciduous open tree coverage (P=0.0416); and water bodies (P=0.0394). Significantly fewer tick paralysis cases were reported from postcodes which contained areas of sparse herbaceous or sparse shrub coverage (P=0.0297) and areas that were cultivated and managed (P=0.0005). No significant (P=0.6998) correlation between number of tick paralysis cases reported per postcode and elevation was found. Strong positive correlations were found between number of cases reported per postcode and the annual minimum (rSP=0.9552, P<0.0001) and maximum (rSP=0.9075; P=0.0001) precipitation. Correlations between reported tick paralysis cases and temperature variables were much weaker than for precipitation, rSP<0.23. For maximum temperature, the strongest correlation between cases was found in winter (rSP=0.1877; P=0.0005) and for minimum temperature in autumn (rSP=0.2289: P<0.0001). Study findings suggest that tick paralysis cases are more likely to occur and be reported in certain eco-climatic zones, such as those with higher rainfall and containing tree cover and areas of water. Veterinarians and pet owners in these zones should be particularly alert for tick paralysis cases to maximize the benefits of early treatment, and to be vigilant to use chemical prophylaxis to reduce the risk of tick parasitism. Copyright © 2014 Elsevier B.V. All rights reserved.

Gravity Data from Newark Valley, White Pine County, Nevada

USGS Publications Warehouse

Mankinen, Edward A.; McKee, Edwin H.

2007-01-01

The Newark Valley area, eastern Nevada is one of thirteen major ground-water basins investigated by the BARCAS (Basin and Range Carbonate Aquifer Study) Project. Gravity data are being used to help characterize the geophysical framework of the region. Although gravity coverage was extensive over parts of the BARCAS study area, data were sparse for a number of the valleys, including the northern part of Newark Valley. We addressed this lack of data by establishing seventy new gravity stations in and around Newark Valley. All available gravity data were then evaluated to determine their reliability, prior to calculating an isostatic residual gravity map to be used for subsequent analyses. A gravity inversion method was used to calculate depths to pre-Cenozoic basement rock and estimates of maximum alluvial/volcanic fill. The enhanced gravity coverage and the incorporation of lithologic information from several deep oil and gas wells yields a view of subsurface shape of the basin and will provide information useful for the development of hydrogeologic models for the region.

A quantitative assessment of Arctic shipping in 2010–2014

PubMed Central

Eguíluz, Victor M.; Fernández-Gracia, Juan; Irigoien, Xabier; Duarte, Carlos M.

2016-01-01

Rapid loss of sea ice is opening up the Arctic Ocean to shipping, a practice that is forecasted to increase rapidly by 2050 when many models predict that the Arctic Ocean will largely be free of ice toward the end of summer. These forecasts carry considerable uncertainty because Arctic shipping was previously considered too sparse to allow for adequate validation. Here, we provide quantitative evidence that the extent of Arctic shipping in the period 2011–2014 is already significant and that it is concentrated (i) in the Norwegian and Barents Seas, and (ii) predominantly accessed via the Northeast and Northwest Passages. Thick ice along the forecasted direct trans-Arctic route was still present in 2014, preventing transit. Although Arctic shipping remains constrained by the extent of ice coverage, during every September, this coverage is at a minimum, allowing the highest levels of shipping activity. Access to Arctic resources, particularly fisheries, is the most important driver of Arctic shipping thus far. PMID:27477878

Role of submerged vegetation in the retention processes of three plant protection products in flow-through stream mesocosms.

PubMed

Stang, Christoph; Wieczorek, Matthias Valentin; Noss, Christian; Lorke, Andreas; Scherr, Frank; Goerlitz, Gerhard; Schulz, Ralf

2014-07-01

Quantitative information on the processes leading to the retention of plant protection products (PPPs) in surface waters is not available, particularly for flow-through systems. The influence of aquatic vegetation on the hydraulic- and sorption-mediated mitigation processes of three PPPs (triflumuron, pencycuron, and penflufen; logKOW 3.3-4.9) in 45-m slow-flowing stream mesocosms was investigated. Peak reductions were 35-38% in an unvegetated stream mesocosm, 60-62% in a sparsely vegetated stream mesocosm (13% coverage with Elodea nuttallii), and in a similar range of 57-69% in a densely vegetated stream mesocosm (100% coverage). Between 89% and 93% of the measured total peak reductions in the sparsely vegetated stream can be explained by an increase of vegetation-induced dispersion (estimated with the one-dimensional solute transport model OTIS), while 7-11% of the peak reduction can be attributed to sorption processes. However, dispersion contributed only 59-71% of the peak reductions in the densely vegetated stream mesocosm, where 29% to 41% of the total peak reductions can be attributed to sorption processes. In the densely vegetated stream, 8-27% of the applied PPPs, depending on the logKOW values of the compounds, were temporarily retained by macrophytes. Increasing PPP recoveries in the aqueous phase were accompanied by a decrease of PPP concentrations in macrophytes indicating kinetic desorption over time. This is the first study to provide quantitative data on how the interaction of dispersion and sorption, driven by aquatic macrophytes, influences the mitigation of PPP concentrations in flowing vegetated stream systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

The right to health in Brazil: A Constitutional guarantee threatened by fiscal austerity.

PubMed

de Souza, Luis Eugenio Portela Fernandes

2017-11-01

After 25 years of expanding coverage and improving the quality of preventive public health measures and publicly financed medical care associated with positive outcomes for the health of Brazil's population, our country suffers from deterioration of social policies. Among the areas of policy affected by new economic austerity measures is health-with potential to damage lives. These threats stem mainly from the 2016 approval of a Constitutional amendment that limits, for the next 20 years, public investments in health, education, social assistance, and social security. This viewpoint addresses how the changes have come about and the possible consequences.

Fast Component Pursuit for Large-Scale Inverse Covariance Estimation.

PubMed

Han, Lei; Zhang, Yu; Zhang, Tong

2016-08-01

The maximum likelihood estimation (MLE) for the Gaussian graphical model, which is also known as the inverse covariance estimation problem, has gained increasing interest recently. Most existing works assume that inverse covariance estimators contain sparse structure and then construct models with the ℓ 1 regularization. In this paper, different from existing works, we study the inverse covariance estimation problem from another perspective by efficiently modeling the low-rank structure in the inverse covariance, which is assumed to be a combination of a low-rank part and a diagonal matrix. One motivation for this assumption is that the low-rank structure is common in many applications including the climate and financial analysis, and another one is that such assumption can reduce the computational complexity when computing its inverse. Specifically, we propose an efficient COmponent Pursuit (COP) method to obtain the low-rank part, where each component can be sparse. For optimization, the COP method greedily learns a rank-one component in each iteration by maximizing the log-likelihood. Moreover, the COP algorithm enjoys several appealing properties including the existence of an efficient solution in each iteration and the theoretical guarantee on the convergence of this greedy approach. Experiments on large-scale synthetic and real-world datasets including thousands of millions variables show that the COP method is faster than the state-of-the-art techniques for the inverse covariance estimation problem when achieving comparable log-likelihood on test data.

Unsupervised Learning for Monaural Source Separation Using Maximization–Minimization Algorithm with Time–Frequency Deconvolution †

PubMed Central

Bouridane, Ahmed; Ling, Bingo Wing-Kuen

2018-01-01

This paper presents an unsupervised learning algorithm for sparse nonnegative matrix factor time–frequency deconvolution with optimized fractional β-divergence. The β-divergence is a group of cost functions parametrized by a single parameter β. The Itakura–Saito divergence, Kullback–Leibler divergence and Least Square distance are special cases that correspond to β=0, 1, 2, respectively. This paper presents a generalized algorithm that uses a flexible range of β that includes fractional values. It describes a maximization–minimization (MM) algorithm leading to the development of a fast convergence multiplicative update algorithm with guaranteed convergence. The proposed model operates in the time–frequency domain and decomposes an information-bearing matrix into two-dimensional deconvolution of factor matrices that represent the spectral dictionary and temporal codes. The deconvolution process has been optimized to yield sparse temporal codes through maximizing the likelihood of the observations. The paper also presents a method to estimate the fractional β value. The method is demonstrated on separating audio mixtures recorded from a single channel. The paper shows that the extraction of the spectral dictionary and temporal codes is significantly more efficient by using the proposed algorithm and subsequently leads to better source separation performance. Experimental tests and comparisons with other factorization methods have been conducted to verify its efficacy. PMID:29702629

Accounting for biases in riboprofiling data indicates a major role for proline in stalling translation.

PubMed

Artieri, Carlo G; Fraser, Hunter B

2014-12-01

The recent advent of ribosome profiling-sequencing of short ribosome-bound fragments of mRNA-has offered an unprecedented opportunity to interrogate the sequence features responsible for modulating translational rates. Nevertheless, numerous analyses of the first riboprofiling data set have produced equivocal and often incompatible results. Here we analyze three independent yeast riboprofiling data sets, including two with much higher coverage than previously available, and find that all three show substantial technical sequence biases that confound interpretations of ribosomal occupancy. After accounting for these biases, we find no effect of previously implicated factors on ribosomal pausing. Rather, we find that incorporation of proline, whose unique side-chain stalls peptide synthesis in vitro, also slows the ribosome in vivo. We also reanalyze a method that implicated positively charged amino acids as the major determinant of ribosomal stalling and demonstrate that it produces false signals of stalling in low-coverage data. Our results suggest that any analysis of riboprofiling data should account for sequencing biases and sparse coverage. To this end, we establish a robust methodology that enables analysis of ribosome profiling data without prior assumptions regarding which positions spanned by the ribosome cause stalling. © 2014 Artieri and Fraser; Published by Cold Spring Harbor Laboratory Press.

Cataract surgical coverage and outcome in the Tibet Autonomous Region of China

PubMed Central

Bassett, K L; Noertjojo, K; Liu, L; Wang, F S; Tenzing, C; Wilkie, A; Santangelo, M; Courtright, P

2005-01-01

Background: A recently published, population based survey of the Tibet Autonomous Region (TAR) of China reported on low vision, blindness, and blinding conditions. This paper presents detailed findings from that survey regarding cataract, including prevalence, cataract surgical coverage, surgical outcome, and barriers to use of services. Methods: The Tibet Eye Care Assessment (TECA) was a prevalence survey of people from randomly selected households from three of the seven provinces of the TAR (Lhoka, Nakchu, and Lingzhr), representing its three main environmental regions. The survey, conducted in 1999 and 2000, assessed visual acuity, cause of vision loss, and eye care services. Results: Among the 15 900 people enumerated, 12 644 were examined (79.6%). Cataract prevalence was 5.2% and 13.8%, for the total population, and those over age 50, respectively. Cataract surgical coverage (vision <6/60) for people age 50 and older (85–90% of cataract blind) was 56% overall, 70% for men and 47% for women. The most common barriers to use of cataract surgical services were distance and cost. In the 216 eyes with cataract surgery, 60% were aphakic and 40% were pseudophakic. Pseudophakic surgery left 19% of eyes blind (<6/60) and an additional 20% of eyes with poor vision (6/24–6/60). Aphakic surgery left 24% of eyes blind and an additional 21% of eyes with poor vision. Even though more women remained blind than men, 28% versus 18% respectively, the different was not statistically significant (p = 0.25). Conclusions: Cataract surgical coverage was remarkably high despite the difficulty of providing services to such an isolated and sparse population. Cataract surgical outcome was poor for both aphakic and pseudophakic surgery. Two main priorities are improving cataract surgical quality and cataract surgical coverage, particularly for women. PMID:15615736

Non-rigid Reconstruction of Casting Process with Temperature Feature

NASA Astrophysics Data System (ADS)

Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Ying; Wang, Lu

2017-09-01

Off-line reconstruction of rigid scene has made a great progress in the past decade. However, the on-line reconstruction of non-rigid scene is still a very challenging task. The casting process is a non-rigid reconstruction problem, it is a high-dynamic molding process lacking of geometric features. In order to reconstruct the casting process robustly, an on-line fusion strategy is proposed for dynamic reconstruction of casting process. Firstly, the geometric and flowing feature of casting are parameterized in manner of TSDF (truncated signed distance field) which is a volumetric block, parameterized casting guarantees real-time tracking and optimal deformation of casting process. Secondly, data structure of the volume grid is extended to have temperature value, the temperature interpolation function is build to generate the temperature of each voxel. This data structure allows for dynamic tracking of temperature of casting during deformation stages. Then, the sparse RGB features is extracted from casting scene to search correspondence between geometric representation and depth constraint. The extracted color data guarantees robust tracking of flowing motion of casting. Finally, the optimal deformation of the target space is transformed into a nonlinear regular variational optimization problem. This optimization step achieves smooth and optimal deformation of casting process. The experimental results show that the proposed method can reconstruct the casting process robustly and reduce drift in the process of non-rigid reconstruction of casting.

Prior-Based Quantization Bin Matching for Cloud Storage of JPEG Images.

PubMed

Liu, Xianming; Cheung, Gene; Lin, Chia-Wen; Zhao, Debin; Gao, Wen

2018-07-01

Millions of user-generated images are uploaded to social media sites like Facebook daily, which translate to a large storage cost. However, there exists an asymmetry in upload and download data: only a fraction of the uploaded images are subsequently retrieved for viewing. In this paper, we propose a cloud storage system that reduces the storage cost of all uploaded JPEG photos, at the expense of a controlled increase in computation mainly during download of requested image subset. Specifically, the system first selectively re-encodes code blocks of uploaded JPEG images using coarser quantization parameters for smaller storage sizes. Then during download, the system exploits known signal priors-sparsity prior and graph-signal smoothness prior-for reverse mapping to recover original fine quantization bin indices, with either deterministic guarantee (lossless mode) or statistical guarantee (near-lossless mode). For fast reverse mapping, we use small dictionaries and sparse graphs that are tailored for specific clusters of similar blocks, which are classified via tree-structured vector quantizer. During image upload, cluster indices identifying the appropriate dictionaries and graphs for the re-quantized blocks are encoded as side information using a differential distributed source coding scheme to facilitate reverse mapping during image download. Experimental results show that our system can reap significant storage savings (up to 12.05%) at roughly the same image PSNR (within 0.18 dB).

Health care reform and people with disabilities.

PubMed

Batavia, A I

1993-01-01

As a group, people with disabilities or chronic conditions experience higher-than-average health care costs and have difficulty gaining access to affordable private health insurance coverage. While the Americans with Disabilities Act will enhance access by prohibiting differential treatment without sound actuarial justification, it will not guarantee equal access for people in impairment groups with high utilization rates. Health care reform is needed to subsidize the coverage of such individuals. Such subsidization can be achieved under either a casualty insurance model, in which premiums based on expected costs are subsidized directly, or a social insurance model, in which low-cost enrollees cross-subsidize high-cost enrollees. Cost containment provisions that focus on the provider, such as global budgeting and managed competition, will adversely affect disabled people if providers do not have adequate incentives to meet these people's needs. Provisions focusing on the consumer, such as cost sharing, case management, and benefit reductions, will adversely affect disabled people if they unduly limit needed services or impose a disproportionate financial burden on disabled people.

Fertility -- A new trend for a global business.

PubMed

Farley, J U

1969-01-01

Cooperation between the public and private sectors in helping control population is possible. The usual public outlet for contraceptives, the clinic, is unsatisfactory for 3 reasons: coverage is sparse; there is no simple, repetitive supply activity; and more immediate medical problems take precedence. The public sector is not conversant with advertising and merchandising techniques and research which aid dissemination of both information and the product. Common marketing notions, e.g., 'trading up' may be relevant, i.e., many new aspects of oral contraceptives, IUDs, had already used conventional methods of contraception. The private sector is less sensitive to the political and religious aspects of contraception than the public sector.

Ethical issues in the translation of social neuroscience: a policy analysis of current guidelines for public dialogue in human research.

PubMed

Zimmerman, Emma; Racine, Eric

2012-01-01

Social neuroscience and its potential implications create an interesting case study for examining human research ethics policies on the topic of public communication of research. We reviewed mainstream national and international human research ethics guidelines and policies on issues of public communication of research. Our analysis relied on five thematic nets to capture the interactions between research and the public: public understanding, knowledge translation, public participation, social outcomes, and dual use. Coverage of these topics is sparse and inconsistent in mainstream policies and guidelines. We identify three options to address these gaps and analyze their strengths and weaknesses.

Geosynchronous inclined orbits for high-latitude communications

NASA Astrophysics Data System (ADS)

Fantino, E.; Flores, R. M.; Di Carlo, M.; Di Salvo, A.; Cabot, E.

2017-11-01

We present and discuss a solution to the growing demand for satellite telecommunication coverage in the high-latitude geographical regions (beyond 55°N), where the signal from geostationary satellites is limited or unavailable. We focus on the dynamical issues associated to the design, the coverage, the maintenance and the disposal of a set of orbits selected for the purpose. Specifically, we identify a group of highly inclined, moderately eccentric geosynchronous orbits derived from the Tundra orbit (geosynchronous, eccentric and critically inclined). Continuous coverage can be guaranteed by a constellation of three satellites in equally spaced planes and suitably phased. By means of a high-precision model of the terrestrial gravity field and the relevant environmental perturbations, we study the evolution of these orbits. The effects of the different perturbations on the ground track (which is more important for coverage than the orbital elements themselves) are isolated and analyzed. The physical model and the numerical setup are optimized with respect to computing time and accuracy. We show that, in order to maintain the ground track unchanged, the key parameters are the orbital period and the argument of perigee. Furthermore, corrections to the right ascension of the ascending node are needed in order to preserve the relative orientation of the orbital planes. A station-keeping strategy that minimizes propellant consumption is then devised, and comparisons are made between the cost of a solution based on impulsive maneuvers and one with continuous thrust. Finally, the issue of end-of-life disposal is discussed.

The democratization of health in Mexico: financial innovations for universal coverage

PubMed Central

Frenk, Julio; Knaul, Felicia Marie

2009-01-01

Abstract In 2003, the Mexican Congress approved a reform establishing the Sistema de Protección Social en Salud [System of Social Protection in Health], whereby public funding for health is being increased by one percent of the 2003 gross domestic product over seven years to guarantee universal health insurance. Poor families that had been excluded from traditional social security can now enrol in a new public insurance scheme known as Seguro Popular [People’s Insurance], which assures legislated access to a comprehensive set of health-care entitlements. This paper describes the financial innovations behind the expansion of health-care coverage in Mexico to everyone and their effects. Evidence shows improvements in mobilization of additional public resources; availability of health infrastructure and drugs; service utilization; effective coverage; and financial protection. Future challenges are discussed, among them the need for additional public funding to extend access to costly interventions for non-communicable diseases not yet covered by the new insurance scheme, and to improve the technical quality of care and the responsiveness of the health system. Eventually, the progress achieved so far will have to be reflected in health outcomes, which will continue to be evaluated so that Mexico can meet the ultimate criterion of reform success: better health through equity, quality and fair financing. PMID:19649369

The democratization of health in Mexico: financial innovations for universal coverage.

PubMed

Frenk, Julio; Gómez-Dantés, Octavio; Knaul, Felicia Marie

2009-07-01

In 2003, the Mexican Congress approved a reform establishing the Sistema de Protección Social en Salud [System of Social Protection in Health], whereby public funding for health is being increased by one percent of the 2003 gross domestic product over seven years to guarantee universal health insurance. Poor families that had been excluded from traditional social security can now enrol in a new public insurance scheme known as Seguro Popular [People's Insurance], which assures legislated access to a comprehensive set of health-care entitlements. This paper describes the financial innovations behind the expansion of health-care coverage in Mexico to everyone and their effects. Evidence shows improvements in mobilization of additional public resources; availability of health infrastructure and drugs; service utilization; effective coverage; and financial protection. Future challenges are discussed, among them the need for additional public funding to extend access to costly interventions for non-communicable diseases not yet covered by the new insurance scheme, and to improve the technical quality of care and the responsiveness of the health system. Eventually, the progress achieved so far will have to be reflected in health outcomes, which will continue to be evaluated so that Mexico can meet the ultimate criterion of reform success: better health through equity, quality and fair financing.

Approximate equiangular tight frames for compressed sensing and CDMA applications

NASA Astrophysics Data System (ADS)

Tsiligianni, Evaggelia; Kondi, Lisimachos P.; Katsaggelos, Aggelos K.

2017-12-01

Performance guarantees for recovery algorithms employed in sparse representations, and compressed sensing highlights the importance of incoherence. Optimal bounds of incoherence are attained by equiangular unit norm tight frames (ETFs). Although ETFs are important in many applications, they do not exist for all dimensions, while their construction has been proven extremely difficult. In this paper, we construct frames that are close to ETFs. According to results from frame and graph theory, the existence of an ETF depends on the existence of its signature matrix, that is, a symmetric matrix with certain structure and spectrum consisting of two distinct eigenvalues. We view the construction of a signature matrix as an inverse eigenvalue problem and propose a method that produces frames of any dimensions that are close to ETFs. Due to the achieved equiangularity property, the so obtained frames can be employed as spreading sequences in synchronous code-division multiple access (s-CDMA) systems, besides compressed sensing.

A Galerkin discretisation-based identification for parameters in nonlinear mechanical systems

NASA Astrophysics Data System (ADS)

Liu, Zuolin; Xu, Jian

2018-04-01

In the paper, a new parameter identification method is proposed for mechanical systems. Based on the idea of Galerkin finite-element method, the displacement over time history is approximated by piecewise linear functions, and the second-order terms in model equation are eliminated by integrating by parts. In this way, the lost function of integration form is derived. Being different with the existing methods, the lost function actually is a quadratic sum of integration over the whole time history. Then for linear or nonlinear systems, the optimisation of the lost function can be applied with traditional least-squares algorithm or the iterative one, respectively. Such method could be used to effectively identify parameters in linear and arbitrary nonlinear mechanical systems. Simulation results show that even under the condition of sparse data or low sampling frequency, this method could still guarantee high accuracy in identifying linear and nonlinear parameters.

Designing and Testing Broadly-Protective Filoviral Vaccines Optimized for Cytotoxic T-Lymphocyte Epitope Coverage

PubMed Central

Fenimore, Paul W.; Foley, Brian T.; Bakken, Russell R.; Thurmond, James R.; Yusim, Karina; Yoon, Hyejin; Parker, Michael; Hart, Mary Kate; Dye, John M.; Korber, Bette; Kuiken, Carla

2012-01-01

We report the rational design and in vivo testing of mosaic proteins for a polyvalent pan-filoviral vaccine using a computational strategy designed for the Human Immunodeficiency Virus type 1 (HIV-1) but also appropriate for Hepatitis C virus (HCV) and potentially other diverse viruses. Mosaics are sets of artificial recombinant proteins that are based on natural proteins. The recombinants are computationally selected using a genetic algorithm to optimize the coverage of potential cytotoxic T lymphocyte (CTL) epitopes. Because evolutionary history differs markedly between HIV-1 and filoviruses, we devised an adapted computational technique that is effective for sparsely sampled taxa; our first significant result is that the mosaic technique is effective in creating high-quality mosaic filovirus proteins. The resulting coverage of potential epitopes across filovirus species is superior to coverage by any natural variants, including current vaccine strains with demonstrated cross-reactivity. The mosaic cocktails are also robust: mosaics substantially outperformed natural strains when computationally tested against poorly sampled species and more variable genes. Furthermore, in a computational comparison of cross-reactive potential a design constructed prior to the Bundibugyo outbreak performed nearly as well against all species as an updated design that included Bundibugyo. These points suggest that the mosaic designs would be more resilient than natural-variant vaccines against future Ebola outbreaks dominated by novel viral variants. We demonstrate in vivo immunogenicity and protection against a heterologous challenge in a mouse model. This design work delineates the likely requirements and limitations on broadly-protective filoviral CTL vaccines. PMID:23056184

Uncertainty in regional temperatures inferred from sparse global observations: Application to a probabilistic classification of El Niño

NASA Astrophysics Data System (ADS)

Ilyas, Maryam; Brierley, Christopher M.; Guillas, Serge

2017-09-01

Instrumental records showing increases in surface temperature are some of the robust and iconic evidence of climate change. But how much should we trust regional temperature estimates interpolated from sparse observations? Here we quantify the uncertainty in the instrumental record by applying multiresolution lattice kriging, a recently developed interpolation technique that leverages the multiple spatial scales of temperature anomalies. The probability of monthly anomalies across the globe is represented by an ensemble, based on HadCRUT4 and accounting for observational and coverage uncertainties. To demonstrate the potential of these new data, we investigate the area-averaged temperature anomalies over the Niño 3.4 region in the equatorial Pacific. Having developed a definition of the El Niño-Southern Oscillation (ENSO) able to cope with probability distribution functions, we classify the ENSO state for each year since 1851. We find that for many years it is ambiguous as to whether there was an El Niño or not from the Niño 3.4 region alone. These years are mainly before 1920, but also just after World War II.

Estimating Highway Volumes Using Vehicle Probe Data - Proof of Concept: Preprint

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

Hou, Yi; Young, Stanley E; Sadabadi, Kaveh

This paper examines the feasibility of using sampled commercial probe data in combination with validated continuous counter data to accurately estimate vehicle volume across the entire roadway network, for any hour during the year. Currently either real time or archived volume data for roadways at specific times are extremely sparse. Most volume data are average annual daily traffic (AADT) measures derived from the Highway Performance Monitoring System (HPMS). Although methods to factor the AADT to hourly averages for typical day of week exist, actual volume data is limited to a sparse collection of locations in which volumes are continuously recorded.more » This paper explores the use of commercial probe data to generate accurate volume measures that span the highway network providing ubiquitous coverage in space, and specific point-in-time measures for a specific date and time. The paper examines the need for the data, fundamental accuracy limitations based on a basic statistical model that take into account the sampling nature of probe data, and early results from a proof of concept exercise revealing the potential of probe type data calibrated with public continuous count data to meet end user expectations in terms of accuracy of volume estimates.« less

Energetics in a model of prebiotic evolution

NASA Astrophysics Data System (ADS)

Intoy, B. F.; Halley, J. W.

2017-12-01

Previously we reported [A. Wynveen et al., Phys. Rev. E 89, 022725 (2014), 10.1103/PhysRevE.89.022725] that requiring that the systems regarded as lifelike be out of chemical equilibrium in a model of abstracted polymers undergoing ligation and scission first introduced by Kauffman [S. A. Kauffman, The Origins of Order (Oxford University Press, New York, 1993), Chap. 7] implied that lifelike systems were most probable when the reaction network was sparse. The model was entirely statistical and took no account of the bond energies or other energetic constraints. Here we report results of an extension of the model to include effects of a finite bonding energy in the model. We studied two conditions: (1) A food set is continuously replenished and the total polymer population is constrained but the system is otherwise isolated and (2) in addition to the constraints in (1) the system is in contact with a finite-temperature heat bath. In each case, detailed balance in the dynamics is guaranteed during the computations by continuous recomputation of a temperature [in case (1)] and of the chemical potential (in both cases) toward which the system is driven by the dynamics. In the isolated case, the probability of reaching a metastable nonequilibrium state in this model depends significantly on the composition of the food set, and the nonequilibrium states satisfying lifelike condition turn out to be at energies and particle numbers consistent with an equilibrium state at high negative temperature. As a function of the sparseness of the reaction network, the lifelike probability is nonmonotonic, as in our previous model, but the maximum probability occurs when the network is less sparse. In the case of contact with a thermal bath at a positive ambient temperature, we identify two types of metastable nonequilibrium states, termed locally and thermally alive, and locally dead and thermally alive, and evaluate their likelihood of appearance, finding maxima at an optimal temperature and an optimal degree of sparseness in the network. We use a Euclidean metric in the space of polymer populations to distinguish these states from one another and from fully equilibrated states. The metric can be used to characterize the degree and type of chemical equilibrium in observed systems, as we illustrate for the proteome of the ribosome.

Disk Density Tuning of a Maximal Random Packing

PubMed Central

Ebeida, Mohamed S.; Rushdi, Ahmad A.; Awad, Muhammad A.; Mahmoud, Ahmed H.; Yan, Dong-Ming; English, Shawn A.; Owens, John D.; Bajaj, Chandrajit L.; Mitchell, Scott A.

2016-01-01

We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations. PMID:27563162

Disk Density Tuning of a Maximal Random Packing.

PubMed

Ebeida, Mohamed S; Rushdi, Ahmad A; Awad, Muhammad A; Mahmoud, Ahmed H; Yan, Dong-Ming; English, Shawn A; Owens, John D; Bajaj, Chandrajit L; Mitchell, Scott A

2016-08-01

We introduce an algorithmic framework for tuning the spatial density of disks in a maximal random packing, without changing the sizing function or radii of disks. Starting from any maximal random packing such as a Maximal Poisson-disk Sampling (MPS), we iteratively relocate, inject (add), or eject (remove) disks, using a set of three successively more-aggressive local operations. We may achieve a user-defined density, either more dense or more sparse, almost up to the theoretical structured limits. The tuned samples are conflict-free, retain coverage maximality, and, except in the extremes, retain the blue noise randomness properties of the input. We change the density of the packing one disk at a time, maintaining the minimum disk separation distance and the maximum domain coverage distance required of any maximal packing. These properties are local, and we can handle spatially-varying sizing functions. Using fewer points to satisfy a sizing function improves the efficiency of some applications. We apply the framework to improve the quality of meshes, removing non-obtuse angles; and to more accurately model fiber reinforced polymers for elastic and failure simulations.

Pesticides in U.S. streams and groundwater

USGS Publications Warehouse

Gilliom, Robert J.

2007-01-01

A 10­-year study by the U.S. Geological Survey’s (USGS’s) National Water-­Quality Assessment (NAWQA) Program provides a national-­scale view of pesticide occurrence in streams and groundwater. The 1992-2001 study builds upon a preliminary analysis from NAWQA’s first phase of studies during 1992-1996 (1, 2). Pesticide data available from various studies prior to 1992 did not allow national assessment because of limited and variable geographic coverage (usually focusing on individual states or regions), sparse and inconsistent inclusion of pesticides in use, and variable sampling designs (3-5). The expanded geographic coverage and improved data following 10 years of study (Figure 1) confirm and reinforce previously reported findings and enable more detailed analyses of each topic. This article summarizes selected findings from a comprehensive report (6), with a focus on the nature of pesticide occurrence and potential significance to human health and stream ecosystems. Information on study design and methods as well as additional analysis of geographic patterns and trends in relation to use and management practices are available in the full report (6).

SDN-enabled hybrid emergency message transmission architecture in internet-of-vehicles

NASA Astrophysics Data System (ADS)

Zhu, Wanting; Gao, Deyun; Zhao, Weicheng; Zhang, Hongke; Chiang, Hua-Pei

2018-04-01

With the increasing number of vehicles connected to the Internet-of-Things (IoT), Internet-of-Vehicles (IoV) is becoming a hot research topic. It can improve traffic safety and efficiency and promote the development of the intelligent transportation that is a very important element in Smart Cities. As an important part of the safety application in IoV, the emergency message transmission is designed to inform all the vehicles in the relevant area timely of the accident information through the multi-hop broadcast communication. In this paper, we propose a hybrid emergency message transmission (HEMT), which introduces the SDN technology into the vehicular network environment and utilizes the flexibility of inter-vehicle communication. By deploying SDN-enabled central controller and RSU switches, we can obtain reliable and fast emergency message dissemination. Moreover, considering the space between the coverages of RSUs caused by the sparse deployment, we also use inter-vehicle multi-hop broadcast communication to improve the message coverage ratio by adding the packet modification module on the RSU switch. Simulation results show the feasibility and effectiveness of our proposed scheme.

Geophysical Data from Spring Valley to Delamar Valley, East-Central Nevada

USGS Publications Warehouse

Mankinen, Edward A.; Roberts, Carter W.; McKee, Edwin H.; Chuchel, Bruce A.; Morin, Robert L.

2007-01-01

Cenozoic basins in eastern Nevada and western Utah constitute major ground-water recharge areas in the eastern part of the Great Basin and these were investigated to characterize the geologic framework of the region. Prior to these investigations, regional gravity coverage was variable over the region, adequate in some areas and very sparse in others. Cooperative studies described herein have established 1,447 new gravity stations in the region, providing a detailed description of density variations in the middle to upper crust. All previously available gravity data for the study area were evaluated to determine their reliability, prior to combining with our recent results and calculating an up-to-date isostatic residual gravity map of the area. A gravity inversion method was used to calculate depths to pre-Cenozoic basement rock and estimates of maximum alluvial/volcanic fill in the major valleys of the study area. The enhanced gravity coverage and the incorporation of lithologic information from several deep oil and gas wells yields a much improved view of subsurface shapes of these basins and provides insights useful for the development of hydrogeologic models for the region.

Hierarchical spatial models of abundance and occurrence from imperfect survey data

USGS Publications Warehouse

Royle, J. Andrew; Kery, M.; Gautier, R.; Schmid, Hans

2007-01-01

Many estimation and inference problems arising from large-scale animal surveys are focused on developing an understanding of patterns in abundance or occurrence of a species based on spatially referenced count data. One fundamental challenge, then, is that it is generally not feasible to completely enumerate ('census') all individuals present in each sample unit. This observation bias may consist of several components, including spatial coverage bias (not all individuals in the Population are exposed to sampling) and detection bias (exposed individuals may go undetected). Thus, observations are biased for the state variable (abundance, occupancy) that is the object of inference. Moreover, data are often sparse for most observation locations, requiring consideration of methods for spatially aggregating or otherwise combining sparse data among sample units. The development of methods that unify spatial statistical models with models accommodating non-detection is necessary to resolve important spatial inference problems based on animal survey data. In this paper, we develop a novel hierarchical spatial model for estimation of abundance and occurrence from survey data wherein detection is imperfect. Our application is focused on spatial inference problems in the Swiss Survey of Common Breeding Birds. The observation model for the survey data is specified conditional on the unknown quadrat population size, N(s). We augment the observation model with a spatial process model for N(s), describing the spatial variation in abundance of the species. The model includes explicit sources of variation in habitat structure (forest, elevation) and latent variation in the form of a correlated spatial process. This provides a model-based framework for combining the spatially referenced samples while at the same time yielding a unified treatment of estimation problems involving both abundance and occurrence. We provide a Bayesian framework for analysis and prediction based on the integrated likelihood, and we use the model to obtain estimates of abundance and occurrence maps for the European Jay (Garrulus glandarius), a widespread, elusive, forest bird. The naive national abundance estimate ignoring imperfect detection and incomplete quadrat coverage was 77 766 territories. Accounting for imperfect detection added approximately 18 000 territories, and adjusting for coverage bias added another 131 000 territories to yield a fully corrected estimate of the national total of about 227 000 territories. This is approximately three times as high as previous estimates that assume every territory is detected in each quadrat.

A two-step super-Gaussian independent component analysis approach for fMRI data.

PubMed

Ge, Ruiyang; Yao, Li; Zhang, Hang; Long, Zhiying

2015-09-01

Independent component analysis (ICA) has been widely applied to functional magnetic resonance imaging (fMRI) data analysis. Although ICA assumes that the sources underlying data are statistically independent, it usually ignores sources' additional properties, such as sparsity. In this study, we propose a two-step super-GaussianICA (2SGICA) method that incorporates the sparse prior of the sources into the ICA model. 2SGICA uses the super-Gaussian ICA (SGICA) algorithm that is based on a simplified Lewicki-Sejnowski's model to obtain the initial source estimate in the first step. Using a kernel estimator technique, the source density is acquired and fitted to the Laplacian function based on the initial source estimates. The fitted Laplacian prior is used for each source at the second SGICA step. Moreover, the automatic target generation process for initial value generation is used in 2SGICA to guarantee the stability of the algorithm. An adaptive step size selection criterion is also implemented in the proposed algorithm. We performed experimental tests on both simulated data and real fMRI data to investigate the feasibility and robustness of 2SGICA and made a performance comparison between InfomaxICA, FastICA, mean field ICA (MFICA) with Laplacian prior, sparse online dictionary learning (ODL), SGICA and 2SGICA. Both simulated and real fMRI experiments showed that the 2SGICA was most robust to noises, and had the best spatial detection power and the time course estimation among the six methods. Copyright © 2015. Published by Elsevier Inc.

Improving recovery of ECG signal with deterministic guarantees using split signal for multiple supports of matching pursuit (SS-MSMP) algorithm.

PubMed

Tawfic, Israa Shaker; Kayhan, Sema Koc

2017-02-01

Compressed sensing (CS) is a new field used for signal acquisition and design of sensor that made a large drooping in the cost of acquiring sparse signals. In this paper, new algorithms are developed to improve the performance of the greedy algorithms. In this paper, a new greedy pursuit algorithm, SS-MSMP (Split Signal for Multiple Support of Matching Pursuit), is introduced and theoretical analyses are given. The SS-MSMP is suggested for sparse data acquisition, in order to reconstruct analog and efficient signals via a small set of general measurements. This paper proposes a new fast method which depends on a study of the behavior of the support indices through picking the best estimation of the corrosion between residual and measurement matrix. The term multiple supports originates from an algorithm; in each iteration, the best support indices are picked based on maximum quality created by discovering correlation for a particular length of support. We depend on this new algorithm upon our previous derivative of halting condition that we produce for Least Support Orthogonal Matching Pursuit (LS-OMP) for clear and noisy signal. For better reconstructed results, SS-MSMP algorithm provides the recovery of support set for long signals such as signals used in WBAN. Numerical experiments demonstrate that the new suggested algorithm performs well compared to existing algorithms in terms of many factors used for reconstruction performance. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Low dose CT reconstruction via L1 norm dictionary learning using alternating minimization algorithm and balancing principle.

PubMed

Wu, Junfeng; Dai, Fang; Hu, Gang; Mou, Xuanqin

2018-04-18

Excessive radiation exposure in computed tomography (CT) scans increases the chance of developing cancer and has become a major clinical concern. Recently, statistical iterative reconstruction (SIR) with l0-norm dictionary learning regularization has been developed to reconstruct CT images from the low dose and few-view dataset in order to reduce radiation dose. Nonetheless, the sparse regularization term adopted in this approach is l0-norm, which cannot guarantee the global convergence of the proposed algorithm. To address this problem, in this study we introduced the l1-norm dictionary learning penalty into SIR framework for low dose CT image reconstruction, and developed an alternating minimization algorithm to minimize the associated objective function, which transforms CT image reconstruction problem into a sparse coding subproblem and an image updating subproblem. During the image updating process, an efficient model function approach based on balancing principle is applied to choose the regularization parameters. The proposed alternating minimization algorithm was evaluated first using real projection data of a sheep lung CT perfusion and then using numerical simulation based on sheep lung CT image and chest image. Both visual assessment and quantitative comparison using terms of root mean square error (RMSE) and structural similarity (SSIM) index demonstrated that the new image reconstruction algorithm yielded similar performance with l0-norm dictionary learning penalty and outperformed the conventional filtered backprojection (FBP) and total variation (TV) minimization algorithms.

Extended ellipse-line-ellipse trajectory for long-object cone-beam imaging with a mounted C-arm system

NASA Astrophysics Data System (ADS)

Yu, Zhicong; Lauritsch, Günter; Dennerlein, Frank; Mao, Yanfei; Hornegger, Joachim; Noo, Frédéric

2016-02-01

Recent reports show that three-dimensional cone-beam (CB) imaging with a floor-mounted (or ceiling-mounted) C-arm system has become a valuable tool in interventional radiology. Currently, a circular short scan is used for data acquisition, which inevitably yields CB artifacts and a short coverage in the direction of the patient table. To overcome these two limitations, a more sophisticated data acquisition geometry is needed. This geometry should be complete in terms of Tuy’s condition and should allow continuous scanning, while being compatible with the mechanical constraints of mounted C-arm systems. Additionally, the geometry should allow accurate image reconstruction from truncated data. One way to ensure such a feature is to adopt a trajectory that provides full R-line coverage within the field-of-view (FOV). An R-line is any segment of line that connects two points on a source trajectory, and the R-line coverage is the set of points that belong to an R-line. In this work, we propose a novel geometry called the extended ellipse-line-ellipse (ELE) for long-object imaging with a mounted C-arm system. This trajectory is built from modules consisting of two elliptical arcs connected by a line. We demonstrate that the extended ELE can be configured in many ways so that full R-line coverage is guaranteed. Both tight and relaxed parametric settings are presented. All results are supported by extensive mathematical proofs provided in appendices. Our findings make the extended ELE trajectory attractive for axially-extended FOV imaging in interventional radiology.

Bypassing the Limits of Ll Regularization: Convex Sparse Signal Processing Using Non-Convex Regularization

NASA Astrophysics Data System (ADS)

Parekh, Ankit

Sparsity has become the basis of some important signal processing methods over the last ten years. Many signal processing problems (e.g., denoising, deconvolution, non-linear component analysis) can be expressed as inverse problems. Sparsity is invoked through the formulation of an inverse problem with suitably designed regularization terms. The regularization terms alone encode sparsity into the problem formulation. Often, the ℓ1 norm is used to induce sparsity, so much so that ℓ1 regularization is considered to be `modern least-squares'. The use of ℓ1 norm, as a sparsity-inducing regularizer, leads to a convex optimization problem, which has several benefits: the absence of extraneous local minima, well developed theory of globally convergent algorithms, even for large-scale problems. Convex regularization via the ℓ1 norm, however, tends to under-estimate the non-zero values of sparse signals. In order to estimate the non-zero values more accurately, non-convex regularization is often favored over convex regularization. However, non-convex regularization generally leads to non-convex optimization, which suffers from numerous issues: convergence may be guaranteed to only a stationary point, problem specific parameters may be difficult to set, and the solution is sensitive to the initialization of the algorithm. The first part of this thesis is aimed toward combining the benefits of non-convex regularization and convex optimization to estimate sparse signals more effectively. To this end, we propose to use parameterized non-convex regularizers with designated non-convexity and provide a range for the non-convex parameter so as to ensure that the objective function is strictly convex. By ensuring convexity of the objective function (sum of data-fidelity and non-convex regularizer), we can make use of a wide variety of convex optimization algorithms to obtain the unique global minimum reliably. The second part of this thesis proposes a non-linear signal decomposition technique for an important biomedical signal processing problem: the detection of sleep spindles and K-complexes in human sleep electroencephalography (EEG). We propose a non-linear model for the EEG consisting of three components: (1) a transient (sparse piecewise constant) component, (2) a low-frequency component, and (3) an oscillatory component. The oscillatory component admits a sparse time-frequency representation. Using a convex objective function, we propose a fast non-linear optimization algorithm to estimate the three components in the proposed signal model. The low-frequency and oscillatory components are then used to estimate the K-complexes and sleep spindles respectively. The proposed detection method is shown to outperform several state-of-the-art automated sleep spindles detection methods.

The AGN fraction of submm-selected galaxies and contributions to the submm/mm-wave extragalactic background light

NASA Astrophysics Data System (ADS)

Serjeant, S.; Negrello, M.; Pearson, C.; Mortier, A.; Austermann, J.; Aretxaga, I.; Clements, D.; Chapman, S.; Dye, S.; Dunlop, J.; Dunne, L.; Farrah, D.; Hughes, D.; Lee, H.-M.; Matsuhara, H.; Ibar, E.; Im, M.; Jeong, W.-S.; Kim, S.; Oyabu, S.; Takagi, T.; Wada, T.; Wilson, G.; Vaccari, M.; Yun, M.

2010-05-01

We present a comparison of the SCUBA half degree extragalactic survey (SHADES) at 450 μm, 850 μm and 1100 μm with deep guaranteed time 15 μm AKARI FU-HYU survey data and Spitzer guaranteed time data at 3.6-24 μm in the Lockman hole east. The AKARI data was analysed using bespoke software based in part on the drizzling and minimum-variance matched filtering developed for SHADES, and was cross-calibrated against ISO fluxes. Our stacking analyses find AKARI 15 μm galaxies with ⪆200 μJy contribute >10% of the 450 μm background, but only <4% of the 1100 μm background, suggesting that different populations contribute at mm-wavelengths. We confirm our earlier result that the ultra-deep 450 μm SCUBA-2 cosmology survey will be dominated by populations already detected by AKARI and Spitzer mid-infrared surveys. The superb mid-infrared wavelength coverage afforded by combining Spitzer and AKARI photometry is an excellent diagnostic of AGN contributions, and we find that (23-52)% of submm-selected galaxies have AGN bolometric fractions fAGN > 0.3.

Equity in health care utilization in Chile.

PubMed

Núñez, Alicia; Chi, Chunhuei

2013-08-12

One of the most extensive Chilean health care reforms occurred in July 2005, when the Regime of Explicit Health Guarantees (AUGE) became effective. This reform guarantees coverage for a specific set of health conditions. Thus, the purpose of this study is to provide timely evidence for policy makers to understand the current distribution and equity of health care utilization in Chile.The authors analyzed secondary data from the National Socioeconomic Survey (CASEN) for the years 1992-2009 and the 2006 Satisfaction and Out-of-Pocket Payment Survey to assess equity in health care utilization using two different approaches. First, we used a two-part model to estimate factors associated with the utilization of health care. Second, we decomposed income-related inequalities in medical care use into contributions of need and non-need factors and estimated a horizontal inequity index.Findings of this empirical study include evidence of inequities in the Chilean health care system that are beneficial to the better-off. We also identified some key factors, including education and health care payment, which affect the utilization of health care services. Results of this study could help researchers and policy makers identify targets for improving equity in health care utilization and strengthening availability of health care services accordingly.

Money-back guarantees.

PubMed

Levens, Eric D; Richter, Kevin S; Levy, Michael J

2013-05-01

As fertility rates among women of advanced reproductive age have steadily increased, so has the utilization of fertility services. National health policies provide infertility treatment coverage in several developed countries; however, in the United States infertility treatment is largely privately funded, resulting in limited access to care. In response to the lack of insurance coverage, many practices offer fertility treatment on a risk-sharing or contingency fee basis. The ethical delivery of care under the auspices of these programs requires adherence to core principles including transparency, patient autonomy, and the delivery of appropriate medical care. Moreover, concerns regarding patient understanding and decision making have also been of foremost concern. Patients must be able to fully appreciate the financial and clinical implications of contingency fee programs. To further explore patient comprehension and satisfaction, we surveyed participants in our shared risk assisted reproductive technology program. The overwhelming majority of respondents felt adequately informed of and fairly charged for their treatment. Our results demonstrate that shared risk programs can receive strong endorsement from participants, which may lead to improved utilization of and perseverance with fertility treatment. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Rarity-weighted richness: a simple and reliable alternative to integer programming and heuristic algorithms for minimum set and maximum coverage problems in conservation planning.

PubMed

Albuquerque, Fabio; Beier, Paul

2015-01-01

Here we report that prioritizing sites in order of rarity-weighted richness (RWR) is a simple, reliable way to identify sites that represent all species in the fewest number of sites (minimum set problem) or to identify sites that represent the largest number of species within a given number of sites (maximum coverage problem). We compared the number of species represented in sites prioritized by RWR to numbers of species represented in sites prioritized by the Zonation software package for 11 datasets in which the size of individual planning units (sites) ranged from <1 ha to 2,500 km2. On average, RWR solutions were more efficient than Zonation solutions. Integer programming remains the only guaranteed way find an optimal solution, and heuristic algorithms remain superior for conservation prioritizations that consider compactness and multiple near-optimal solutions in addition to species representation. But because RWR can be implemented easily and quickly in R or a spreadsheet, it is an attractive alternative to integer programming or heuristic algorithms in some conservation prioritization contexts.

Michelson-type Radio Interferometer for University Education

NASA Astrophysics Data System (ADS)

Koda, Jin; Barrett, J. W.; Hasegawa, T.; Hayashi, M.; Shafto, G.; Slechta, J.

2013-01-01

Despite the increasing importance of interferometry in astronomy, the lack of educational interferometers is an obstacle to training the futue generation of astronomers. Students need hands-on experiments to fully understand the basic concepts of interferometry. Professional interferometers are often too complicated for education, and it is difficult to guarantee access for classes in a university course. We have built a simple and affordable radio interferometer for education and used it for an undergraduate and graduate laboratory project. This interferometer's design is based on the Michelson & Peace's stellar optical interferometer, but operates at a radio wavelength using a commercial broadcast satellite dish and receiver. Two side mirrors are surfaced with kitchen aluminum foil and slide on a ladder, providing baseline coverage. This interferometer can resolve and measure the diameter of the Sun, a nice daytime experiment which can be carried out even under a marginal weather (i.e., partial cloud coverage). Commercial broadcast satellites provide convenient point sources. By comparing the Sun and satellites, students can learn how an interferometer works and resolves structures in the sky.

Affordable health benefits for workers without employer coverage.

PubMed

Etheredge, L; Jones, S B

1998-02-01

With 42 million individuals lacking health insurance in 1996, an increase of 1.1 million uninsured from the previous year, new initiatives to deal with health insurance problems merit a high priority among domestic policy initiatives. This paper examines the opportunities for assisting full-time workers (and their families) who do not receive employer-paid health insurance-a group that now includes 49 million individuals-by using three policy tools that Congress and President Clinton have already agreed to use in recent healthcare legislation: (a) equitable tax assistance; (b) market reforms; and (c) competition among health plans that offer economical benefits. Estimates for a model plan illustrate that such strategies could make decent private health insurance more affordable and more accessible for workers and their families who want to purchase it; family insurance protection, with guaranteed issue of insurance and large-group-rated premiums, could be offered at potential savings of 42% (or more). Premiums for worker's coverage, after tax assistance, would be below $1,200 per year, i.e., less than 60 cents per hour. These market-oriented reforms can be accomplished with a limited government role, and, after start-up costs, ongoing federal expenses would be modest, predictable, and controllable. When combined with the new $24 billion child health initiative to assist low-income families, the proposed plan would provide considerable progress toward universal access to affordable insurance coverage.

Node Self-Deployment Algorithm Based on an Uneven Cluster with Radius Adjusting for Underwater Sensor Networks

PubMed Central

Jiang, Peng; Xu, Yiming; Wu, Feng

2016-01-01

Existing move-restricted node self-deployment algorithms are based on a fixed node communication radius, evaluate the performance based on network coverage or the connectivity rate and do not consider the number of nodes near the sink node and the energy consumption distribution of the network topology, thereby degrading network reliability and the energy consumption balance. Therefore, we propose a distributed underwater node self-deployment algorithm. First, each node begins the uneven clustering based on the distance on the water surface. Each cluster head node selects its next-hop node to synchronously construct a connected path to the sink node. Second, the cluster head node adjusts its depth while maintaining the layout formed by the uneven clustering and then adjusts the positions of in-cluster nodes. The algorithm originally considers the network reliability and energy consumption balance during node deployment and considers the coverage redundancy rate of all positions that a node may reach during the node position adjustment. Simulation results show, compared to the connected dominating set (CDS) based depth computation algorithm, that the proposed algorithm can increase the number of the nodes near the sink node and improve network reliability while guaranteeing the network connectivity rate. Moreover, it can balance energy consumption during network operation, further improve network coverage rate and reduce energy consumption. PMID:26784193

An Examination of Coarse Sun Sensor Contingencies in Attitude Determination and the Sun Vector Calculation

NASA Technical Reports Server (NTRS)

Coffey, Brenman; Welch, Ray; Burt, Brad

2012-01-01

Satellite pointing is vital to the success of a mission. One element of that entails describing the position of the sun relative to the frame of the satellite. Coarse Sun Sensors (CSS) are typically used to provide the information to calculate the sun's position in Safe Modes or contingency operations. In the OCO-2 configuration there are 13 CSS total, which provide redundant 4 celestial coverage. Failures of the individual CSS elements can introduce holes in the celestial coverage resulting in potential loss of sun knowledge. These failures must be analyzed to determine if the contingency plan is sufficient to assure mission success. First the static case was looked at and determined that at a maximum, 3 CSS failures can be sustained on the body and 1 on the array without causing coverage holes. Also array sensors are more important to mission success. The Sun Vector calculation has been transcribed to MATLAB code and failure scenarios are being examined to determine the maximum error given a set of failure scenarios. This activity indicated that if there is a loss of the sun, the sun-searching algorithm could be modified to use XZ rotation as that is guaranteed to find it whereas the design using the YZ rotation misses the sun if it is at the + or - Y orientation.

Role of block copolymer adsorption versus bimodal grafting on nanoparticle self-assembly in polymer nanocomposites.

PubMed

Zhao, Dan; Di Nicola, Matteo; Khani, Mohammad M; Jestin, Jacques; Benicewicz, Brian C; Kumar, Sanat K

2016-09-14

We compare the self-assembly of silica nanoparticles (NPs) with physically adsorbed polystyrene-block-poly(2-vinylpyridine) (PS-b-P2VP) copolymers (BCP) against NPs with grafted bimodal (BM) brushes comprised of long, sparsely grafted PS chains and a short dense carpet of P2VP chains. As with grafted NPs, the dispersion state of the BCP NPs can be facilely tuned in PS matrices by varying the PS coverage on the NP surface or by changes in the ratio of the PS graft to matrix chain lengths. Surprisingly, the BCP NPs are remarkably better dispersed than the NPs tethered with bimodal brushes at comparable PS grafting densities. We postulate that this difference arises because of two factors inherent in the synthesis of the NPs: In the case of the BCP NPs the adsorption process is analogous to the chains being "grafted to" the NP surface, while the BM case corresponds to "grafting from" the surface. We have shown that the "grafted from" protocol yields patchy NPs even if the graft points are uniformly placed on each particle. This phenomenon, which is caused by chain conformation fluctuations, is exacerbated by the distribution function associated with the (small) number of grafts per particle. In contrast, in the case of BCP adsorption, each NP is more uniformly coated by a P2VP monolayer driven by the strongly favorable P2VP-silica interactions. Since each P2VP block is connected to a PS chain we conjecture that these adsorbed systems are closer to the limit of spatially uniform sparse brush coverage than the chemically grafted case. We finally show that the better NP dispersion resulting from BCP adsorption leads to larger mechanical reinforcement than those achieved with BM particles. These results emphasize that physical adsorption of BCPs is a simple, effective and practically promising strategy to direct NP dispersion in a chemically unfavorable polymer matrix.

Improved Detection of Local Earthquakes in the Vienna Basin (Austria), using Subspace Detectors

NASA Astrophysics Data System (ADS)

Apoloner, Maria-Theresia; Caffagni, Enrico; Bokelmann, Götz

2016-04-01

The Vienna Basin in Eastern Austria is densely populated and highly-developed; it is also a region of low to moderate seismicity, yet the seismological network coverage is relatively sparse. This demands improving our capability of earthquake detection by testing new methods, enlarging the existing local earthquake catalogue. This contributes to imaging tectonic fault zones for better understanding seismic hazard, also through improved earthquake statistics (b-value, magnitude of completeness). Detection of low-magnitude earthquakes or events for which the highest amplitudes slightly exceed the signal-to-noise-ratio (SNR), may be possible by using standard methods like the short-term over long-term average (STA/LTA). However, due to sparse network coverage and high background noise, such a technique may not detect all potentially recoverable events. Yet, earthquakes originating from the same source region and relatively close to each other, should be characterized by similarity in seismic waveforms, at a given station. Therefore, waveform similarity can be exploited by using specific techniques such as correlation-template based (also known as matched filtering) or subspace detection methods (based on the subspace theory). Matching techniques basically require a reference or template event, usually characterized by high waveform coherence in the array receivers, and high SNR, which is cross-correlated with the continuous data. Instead, subspace detection methods overcome in principle the necessity of defining template events as single events, but use a subspace extracted from multiple events. This approach theoretically should be more robust in detecting signals that exhibit a strong variability (e.g. because of source or magnitude). In this study we scan the continuous data recorded in the Vienna Basin with a subspace detector to identify additional events. This will allow us to estimate the increase of the seismicity rate in the local earthquake catalogue, therefore providing an evaluation of network performance and efficiency of the method.

National-scale aboveground biomass geostatistical mapping with FIA inventory and GLAS data: Preparation for sparsely sampled lidar assisted forest inventory

NASA Astrophysics Data System (ADS)

Babcock, C. R.; Finley, A. O.; Andersen, H. E.; Moskal, L. M.; Morton, D. C.; Cook, B.; Nelson, R.

2017-12-01

Upcoming satellite lidar missions, such as GEDI and IceSat-2, are designed to collect laser altimetry data from space for narrow bands along orbital tracts. As a result lidar metric sets derived from these sources will not be of complete spatial coverage. This lack of complete coverage, or sparsity, means traditional regression approaches that consider lidar metrics as explanatory variables (without error) cannot be used to generate wall-to-wall maps of forest inventory variables. We implement a coregionalization framework to jointly model sparsely sampled lidar information and point-referenced forest variable measurements to create wall-to-wall maps with full probabilistic uncertainty quantification of all inputs. We inform the model with USFS Forest Inventory and Analysis (FIA) in-situ forest measurements and GLAS lidar data to spatially predict aboveground forest biomass (AGB) across the contiguous US. We cast our model within a Bayesian hierarchical framework to better model complex space-varying correlation structures among the lidar metrics and FIA data, which yields improved prediction and uncertainty assessment. To circumvent computational difficulties that arise when fitting complex geostatistical models to massive datasets, we use a Nearest Neighbor Gaussian process (NNGP) prior. Results indicate that a coregionalization modeling approach to leveraging sampled lidar data to improve AGB estimation is effective. Further, fitting the coregionalization model within a Bayesian mode of inference allows for AGB quantification across scales ranging from individual pixel estimates of AGB density to total AGB for the continental US with uncertainty. The coregionalization framework examined here is directly applicable to future spaceborne lidar acquisitions from GEDI and IceSat-2. Pairing these lidar sources with the extensive FIA forest monitoring plot network using a joint prediction framework, such as the coregionalization model explored here, offers the potential to improve forest AGB accounting certainty and provide maps for post-model fitting analysis of the spatial distribution of AGB.

Employer-employee relations.

PubMed

Copeland, J D

1993-09-01

As an employer, a veterinarian must be vigilant to protect the rights of both job applicants and employees. Federal and state statutes guarantee that applicants and employees will not be subjected to discrimination in any aspect of employment, including recruitment, hiring, promotion, compensation, and termination of employment. An employer may not discriminate on the basis of sex, race, color, national origin, religion, age, or physical disability. In addition, common law tort actions give employees powerful causes of action be against those employers who injure employees. More than ever, employers must be diligent in obeying the law. Employers must also take measures to protect themselves from employee claims by instituting risk management plans and purchasing adequate insurance coverage.

Aging in Canada: state of the art and science.

PubMed

Sheets, Debra J; Gallagher, Elaine M

2013-02-01

Canada shares many similarities with other industrialized countries around the world, including a rapidly aging population. What sets Canada uniquely apart is the collaborative approach that has been enacted in the health care system and the aging research initiatives. Canada has tremendous pride in its publicly funded health care system that guarantees universal coverage for health care services on the basis of need, rather than ability to pay. It is also distinguished as a multicultural society that is officially bilingual. Aging research has developed rapidly over the past decade. In particular, the Canadian Longitudinal Study on Aging is one of the most comprehensive research platforms of its kind and is expected to change the landscape of aging research.

Self-calibrating models for dynamic monitoring and diagnosis

NASA Technical Reports Server (NTRS)

Kuipers, Benjamin

1994-01-01

The present goal in qualitative reasoning is to develop methods for automatically building qualitative and semiquantitative models of dynamic systems and to use them for monitoring and fault diagnosis. The qualitative approach to modeling provides a guarantee of coverage while our semiquantitative methods support convergence toward a numerical model as observations are accumulated. We have developed and applied methods for automatic creation of qualitative models, developed two methods for obtaining tractable results on problems that were previously intractable for qualitative simulation, and developed more powerful methods for learning semiquantitative models from observations and deriving semiquantitative predictions from them. With these advances, qualitative reasoning comes significantly closer to realizing its aims as a practical engineering method.

Microseismic Monitoring Using Sparse Surface Network of Broadband Instruments: Western Canada Shale Play Case Study

NASA Astrophysics Data System (ADS)

Yenier, E.; Baturan, D.; Karimi, S.

2016-12-01

Monitoring of seismicity related to oil and gas operations is routinely performed nowadays using a number of different surface and downhole seismic array configurations and technologies. Here, we provide a hydraulic fracture (HF) monitoring case study that compares the data set generated by a sparse local surface network of broadband seismometers to a data set generated by a single downhole geophone string. Our data was collected during a 5-day single-well HF operation, by a temporary surface network consisting of 10 stations deployed within 5 km of the production well. The downhole data was recorded by a 20 geophone string deployed in an observation well located 15 m from the production well. Surface network data processing included standard STA/LTA event triggering enhanced by template-matching subspace detection, grid search locations which was improved using the double-differencing re-location technique, as well as Richter (ML) and moment (Mw) magnitude computations for all detected events. In addition, moment tensors were computed from first motion polarities and amplitudes for the subset of highest SNR events. The resulting surface event catalog shows a very weak spatio-temporal correlation to HF operations with only 43% of recorded seismicity occurring during HF stages times. This along with source mechanisms shows that the surface-recorded seismicity delineates the activation of several pre-existing structures striking NNE-SSW and consistent with regional stress conditions as indicated by the orientation of SHmax. Comparison of the sparse-surface and single downhole string datasets allows us to perform a cost-benefit analysis of the two monitoring methods. Our findings show that although the downhole array recorded ten times as many events, the surface network provides a more coherent delineation of the underlying structure and more accurate magnitudes for larger magnitude events. We attribute this to the enhanced focal coverage provided by the surface network and the use of broadband instrumentation. The results indicate that sparse surface networks of high quality instruments can provide rich and reliable datasets for evaluation of the impact and effectiveness of hydraulic fracture operations in regions with favorable surface noise, local stress and attenuation characteristics.

Continuously amplified warming in the Alaskan Arctic: Implications for estimating global warming hiatus

USGS Publications Warehouse

Wang, Kang; Zhang, Tingjun; Zhang, Xiangdong; Clow, Gary D.; Jafarov, Elchin E.; Overeem, Irina; Romanovsky, Vladimir; Peng, Xiaoqing; Cao, Bin

2017-01-01

Historically, in situ measurements have been notoriously sparse over the Arctic. As a consequence, the existing gridded data of surface air temperature (SAT) may have large biases in estimating the warming trend in this region. Using data from an expanded monitoring network with 31 stations in the Alaskan Arctic, we demonstrate that the SAT has increased by 2.19°C in this region, or at a rate of 0.23°C/decade during 1921–2015. Meanwhile, we found that the SAT warmed at 0.71°C/decade over 1998–2015, which is 2 to 3 times faster than the rate established from the gridded data sets. Focusing on the “hiatus” period 1998–2012 as identified by the Intergovernmental Panel on Climate Change (IPCC) report, the SAT has increased at 0.45°C/decade, which captures more than 90% of the regional trend for 1951–2012. We suggest that sparse in situ measurements are responsible for underestimation of the SAT change in the gridded data sets. It is likely that enhanced climate warming may also have happened in the other regions of the Arctic since the late 1990s but left undetected because of incomplete observational coverage.

Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.

PubMed

Basu, Sumanta; Duren, William; Evans, Charles R; Burant, Charles F; Michailidis, George; Karnovsky, Alla

2017-05-15

Recent technological advances in mass spectrometry, development of richer mass spectral libraries and data processing tools have enabled large scale metabolic profiling. Biological interpretation of metabolomics studies heavily relies on knowledge-based tools that contain information about metabolic pathways. Incomplete coverage of different areas of metabolism and lack of information about non-canonical connections between metabolites limits the scope of applications of such tools. Furthermore, the presence of a large number of unknown features, which cannot be readily identified, but nonetheless can represent bona fide compounds, also considerably complicates biological interpretation of the data. Leveraging recent developments in the statistical analysis of high-dimensional data, we developed a new Debiased Sparse Partial Correlation algorithm (DSPC) for estimating partial correlation networks and implemented it as a Java-based CorrelationCalculator program. We also introduce a new version of our previously developed tool Metscape that enables building and visualization of correlation networks. We demonstrate the utility of these tools by constructing biologically relevant networks and in aiding identification of unknown compounds. http://metscape.med.umich.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

A Cooperative Search and Coverage Algorithm with Controllable Revisit and Connectivity Maintenance for Multiple Unmanned Aerial Vehicles.

PubMed

Liu, Zhong; Gao, Xiaoguang; Fu, Xiaowei

2018-05-08

In this paper, we mainly study a cooperative search and coverage algorithm for a given bounded rectangle region, which contains several unknown stationary targets, by a team of unmanned aerial vehicles (UAVs) with non-ideal sensors and limited communication ranges. Our goal is to minimize the search time, while gathering more information about the environment and finding more targets. For this purpose, a novel cooperative search and coverage algorithm with controllable revisit mechanism is presented. Firstly, as the representation of the environment, the cognitive maps that included the target probability map (TPM), the uncertain map (UM), and the digital pheromone map (DPM) are constituted. We also design a distributed update and fusion scheme for the cognitive map. This update and fusion scheme can guarantee that each one of the cognitive maps converges to the same one, which reflects the targets’ true existence or absence in each cell of the search region. Secondly, we develop a controllable revisit mechanism based on the DPM. This mechanism can concentrate the UAVs to revisit sub-areas that have a large target probability or high uncertainty. Thirdly, in the frame of distributed receding horizon optimizing, a path planning algorithm for the multi-UAVs cooperative search and coverage is designed. In the path planning algorithm, the movement of the UAVs is restricted by the potential fields to meet the requirements of avoiding collision and maintaining connectivity constraints. Moreover, using the minimum spanning tree (MST) topology optimization strategy, we can obtain a tradeoff between the search coverage enhancement and the connectivity maintenance. The feasibility of the proposed algorithm is demonstrated by comparison simulations by way of analyzing the effects of the controllable revisit mechanism and the connectivity maintenance scheme. The Monte Carlo method is employed to validate the influence of the number of UAVs, the sensing radius, the detection and false alarm probabilities, and the communication range on the proposed algorithm.

GEO/SAMS - The Geostationary Synthetic Aperture Microwave Sounder

NASA Technical Reports Server (NTRS)

Lambrigtsen, Bjorn H.

2008-01-01

The National Oceanic and Atmospheric Administration (NOAA) has for many years operated two weather satellite systems, the Polar-orbiting Operational Environmental Satellite system (POES), using low-earth orbiting (LEO) satellites, and the Geostationary Operational Environmental Satellite system (GOES), using geostationary earth orbiting (GEO) satellites. (Similar systems are also operated by other nations.) The POES satellites have been equipped with both infrared (IR) and microwave (MW) atmospheric sounders, which makes it possible to determine the vertical distribution of temperature and humidity in the troposphere even under cloudy conditions. Such satellite observations have had a significant impact on weather forecasting accuracy, especially in regions where in situ observations are sparse. In contrast, the GOES satellites have only been equipped with IR sounders, since it has not been feasible to build a large enough antenna to achieve sufficient spatial resolution for a MW sounder in GEO. As a result, GOES soundings can only be obtained in cloud free areas and in the less important upper atmosphere, above the cloud tops. This has hindered the effective use of GOES data in numerical weather prediction. Full sounding capabilities with the GOES system is highly desirable because of the advantageous spatial and temporal coverage that is possible from GEO. While POES satellites provide coverage in relatively narrow swaths, and with a revisit time of 12-24 hours or more, GOES satellites can provide continuous hemispheric coverage, making it possible to monitor highly dynamic phenomena such as hurricanes.

Improve EPA's AIRNow Air Quality Index Maps with NASA/NOAA Satellite Data

NASA Astrophysics Data System (ADS)

Pasch, A.; Zahn, P. H.; DeWinter, J. L.; Haderman, M. D.; White, J. E.; Dickerson, P.; Dye, T. S.; Martin, R. V.

2011-12-01

The U.S. Environmental Protection Agency's (EPA) AIRNow program provides maps of real-time hourly Air Quality Index (AQI) conditions and daily AQI forecasts nationwide (http://www.airnow.gov). The public uses these maps to make decisions concerning their respiratory health. The usefulness of the AIRNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA and Sonoma Technology, Inc. are working in collaboration with the National Aeronautics and Space Administration (NASA), the National Oceanic and Atmospheric Administration (NOAA), and university researchers on a project to incorporate additional measurements into the maps via the AIRNow Satellite Data Processor (ASDP). These measurements include estimated surface PM

Achieving effective universal health coverage with equity: evidence from Chile.

PubMed

Frenz, Patricia; Delgado, Iris; Kaufman, Jay S; Harper, Sam

2014-09-01

Chile's 'health guarantees' approach to providing universal and equitable coverage for quality healthcare in a dual public-private health system has generated global interest. The programme, called AUGE, defines legally enforceable rights to explicit healthcare benefits for priority health conditions, which incrementally covered 56 problems representing 75% of the disease burden between 2005 and 2009. It was accompanied by other health reform measures to increase public financing and public sector planning to secure the guarantees nationwide, as well as the state's stewardship role. We analysed data from household surveys conducted before and after the AUGE reform to estimate changes in levels of unmet health need, defined as the lack of a healthcare visit for a health problem occurring in the last 30 days, by age, sex, income, education, health insurance, residence and ethnicity; fitting logistic regression models and using predictive margins. The overall prevalence of unmet health need was much lower in 2009 (17.6%, 95% CI: 16.5%, 18.6%) than in 2000 (30.0%, 95% CI: 28.3%, 31.7%). Differences by income and education extremes and rural-urban residence disappeared. In 2009, people who had been in treatment for a condition covered by AUGE in the past year had a lower adjusted prevalence of unmet need for their recent problem (11.7%, 95% CI: 10.5%, 13.2%) than who had not (21.0%, 95% CI: 19.6%, 22.4%). Despite limitations including cross-sectional and self-reported data, our findings suggest that the Chilean health system has become more equitable and responsive to need. While these changes cannot be directly attributed to AUGE, they were coincident with the AUGE reforms. However, healthcare equity concerns are still present, relating to quality of care, health system barriers and differential access for health conditions that are not covered by AUGE. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2013; all rights reserved.

Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring.

PubMed

Xiong, Naixue; Liu, Ryan Wen; Liang, Maohan; Wu, Di; Liu, Zhao; Wu, Huisi

2017-01-18

Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L 1 -norm of kernel intensity and the squared L 2 -norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L 1 -norm data-fidelity term and the total generalized variation (TGV) regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM)-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations.

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

Carpenter, J.A.

This report is a sequel to ORNL/CSD-96 in the ongoing supplements to Professor A.S. Householder's KWIC Index for Numerical Algebra. With this supplement, the coverage has been restricted to Numerical Linear Algebra and is now roughly characterized by the American Mathematical Society's classification section 15 and 65F but with little coverage of inifinite matrices, matrices over fields of characteristics other than zero, operator theory, optimization and those parts of matrix theory primarily combinatorial in nature. Some recognition is made of the uses of graph theory in Numerical Linear Algebra, particularly as regards their use in algorithms for sparse matrix computations.more » The period covered by this report is roughly the calendar year 1981 as measured by the appearance of the articles in the American Mathematical Society's Contents of Mathematical Publications. The review citations are limited to the Mathematical Reviews (MR) and Das Zentralblatt fur Mathematik und Ihre Grenzgebiete (ZBL). Future reports will be made more timely by closer ovservation of the few journals which supply the bulk of the listings rather than what appears to be too much reliance on secondary sources. Some thought is being given to the physical appearance of these reports and the author welcomes comments concerning both their appearance and contents.« less

Global assimilation of X Project Loon stratospheric balloon observations

NASA Astrophysics Data System (ADS)

Coy, L.; Schoeberl, M. R.; Pawson, S.; Candido, S.; Carver, R. W.

2017-12-01

Project Loon has an overall goal of providing worldwide internet coverage using a network of long-duration super-pressure balloons. Beginning in 2013, Loon has launched over 1600 balloons from multiple tropical and middle latitude locations. These GPS tracked balloon trajectories provide lower stratospheric wind information over the oceans and remote land areas where traditional radiosonde soundings are sparse, thus providing unique coverage of lower stratospheric winds. To fully investigate these Loon winds we: 1) compare the Loon winds to winds produced by a global data assimilation system (DAS: NASA GEOS) and 2) assimilate the Loon winds into the same comprehensive DAS. Results show that in middle latitudes the Loon winds and DAS winds agree well and assimilating the Loon winds have only a small impact on short-term forecasting of the Loon winds, however, in the tropics the loon winds and DAS winds often disagree substantially (8 m/s or more in magnitude) and in these cases assimilating the loon winds significantly improves the forecast of the loon winds. By highlighting cases where the Loon and DAS winds differ, these results can lead to improved understanding of stratospheric winds, especially in the tropics.

Global Assimilation of X Project Loon Stratospheric Balloon Observations

NASA Technical Reports Server (NTRS)

Coy, Lawrence; Schoeberl, Mark R.; Pawson, Steven; Candido, Salvatore; Carver, Robert W.

2017-01-01

Project Loon has an overall goal of providing worldwide internet coverage using a network of long-duration super-pressure balloons. Beginning in 2013, Loon has launched over 1600 balloons from multiple tropical and middle latitude locations. These GPS tracked balloon trajectories provide lower stratospheric wind information over the oceans and remote land areas where traditional radiosonde soundings are sparse, thus providing unique coverage of lower stratospheric winds. To fully investigate these Loon winds we: 1) compare the Loon winds to winds produced by a global data assimilation system (DAS: NASA GEOS) and 2) assimilate the Loon winds into the same comprehensive DAS. Results show that in middle latitudes the Loon winds and DAS winds agree well and assimilating the Loon winds have only a small impact on short-term forecasting of the Loon winds, however, in the tropics the loon winds and DAS winds often disagree substantially (8 m/s or more in magnitude) and in these cases assimilating the loon winds significantly improves the forecast of the loon winds. By highlighting cases where the Loon and DAS winds differ, these results can lead to improved understanding of stratospheric winds, especially in the tropics.

A distributed predictive control approach for periodic flow-based networks: application to drinking water systems

NASA Astrophysics Data System (ADS)

Grosso, Juan M.; Ocampo-Martinez, Carlos; Puig, Vicenç

2017-10-01

This paper proposes a distributed model predictive control approach designed to work in a cooperative manner for controlling flow-based networks showing periodic behaviours. Under this distributed approach, local controllers cooperate in order to enhance the performance of the whole flow network avoiding the use of a coordination layer. Alternatively, controllers use both the monolithic model of the network and the given global cost function to optimise the control inputs of the local controllers but taking into account the effect of their decisions over the remainder subsystems conforming the entire network. In this sense, a global (all-to-all) communication strategy is considered. Although the Pareto optimality cannot be reached due to the existence of non-sparse coupling constraints, the asymptotic convergence to a Nash equilibrium is guaranteed. The resultant strategy is tested and its effectiveness is shown when applied to a large-scale complex flow-based network: the Barcelona drinking water supply system.

How Does the Low-Rank Matrix Decomposition Help Internal and External Learnings for Super-Resolution.

PubMed

Wang, Shuang; Yue, Bo; Liang, Xuefeng; Jiao, Licheng

2018-03-01

Wisely utilizing the internal and external learning methods is a new challenge in super-resolution problem. To address this issue, we analyze the attributes of two methodologies and find two observations of their recovered details: 1) they are complementary in both feature space and image plane and 2) they distribute sparsely in the spatial space. These inspire us to propose a low-rank solution which effectively integrates two learning methods and then achieves a superior result. To fit this solution, the internal learning method and the external learning method are tailored to produce multiple preliminary results. Our theoretical analysis and experiment prove that the proposed low-rank solution does not require massive inputs to guarantee the performance, and thereby simplifying the design of two learning methods for the solution. Intensive experiments show the proposed solution improves the single learning method in both qualitative and quantitative assessments. Surprisingly, it shows more superior capability on noisy images and outperforms state-of-the-art methods.

Discriminative Structured Dictionary Learning on Grassmann Manifolds and Its Application on Image Restoration.

PubMed

Pan, Han; Jing, Zhongliang; Qiao, Lingfeng; Li, Minzhe

2017-09-25

Image restoration is a difficult and challenging problem in various imaging applications. However, despite of the benefits of a single overcomplete dictionary, there are still several challenges for capturing the geometric structure of image of interest. To more accurately represent the local structures of the underlying signals, we propose a new problem formulation for sparse representation with block-orthogonal constraint. There are three contributions. First, a framework for discriminative structured dictionary learning is proposed, which leads to a smooth manifold structure and quotient search spaces. Second, an alternating minimization scheme is proposed after taking both the cost function and the constraints into account. This is achieved by iteratively alternating between updating the block structure of the dictionary defined on Grassmann manifold and sparsifying the dictionary atoms automatically. Third, Riemannian conjugate gradient is considered to track local subspaces efficiently with a convergence guarantee. Extensive experiments on various datasets demonstrate that the proposed method outperforms the state-of-the-art methods on the removal of mixed Gaussian-impulse noise.

Impact of the federal contraceptive coverage guarantee on out-of-pocket payments for contraceptives: 2014 update.

PubMed

Sonfield, Adam; Tapales, Athena; Jones, Rachel K; Finer, Lawrence B

2015-01-01

The Affordable Care Act requires most private health plans to cover contraceptive methods, services and counseling, without any out-of-pocket costs to patients; that requirement took effect for millions of Americans in January 2013. Data for this study come from a subset of the 1842 women aged 18-39 years who responded to all four waves of a national longitudinal survey. This analysis focuses on the 892 women who had private health insurance and who used a prescription contraceptive method during any of the four study periods. Women were asked about the amount they paid out of pocket in an average month for their method of choice. Between fall 2012 and spring 2014, the proportion of privately insured women paying zero dollars out of pocket for oral contraceptives increased substantially, from 15% to 67%. Similar changes occurred among privately insured women using injectable contraception, the vaginal ring and the intrauterine device. The implementation of the federal contraceptive coverage requirement appears to have had a notable impact on the out-of-pocket costs paid by privately insured women, and that impact has increased over time. This study measures the out-of-pocket costs for women with private insurance prior to the federal contraceptive coverage requirement and after it took effect; in doing so, it highlights areas of progress in eliminating these costs. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Policy without politics: the limits of social engineering.

PubMed

Navarro, Vicente

2003-01-01

The extent of coverage provided by a country's health services is directly related to the level of development of that country's democratic process (and its power relations). The United States is the only developed country whose government does not guarantee access to health care for its citizens. It is also the developed country with the least representative and most insufficient democratic institutions, owing to the constitutional framework of the political system, the privatization of the electoral process, and the enormous power of corporate interests in both the media and the political process. As international experience shows, without a strong labor-based movement willing to be radical in its protests, a universal health care program will never be accepted by the US establishment.

Policy Without Politics: The Limits of Social Engineering

PubMed Central

Navarro, Vicente

2003-01-01

The extent of coverage provided by a country’s health services is directly related to the level of development of that country’s democratic process (and its power relations). The United States is the only developed country whose government does not guarantee access to health care for its citizens. It is also the developed country with the least representative and most insufficient democratic institutions, owing to the constitutional framework of the political system, the privatization of the electoral process, and the enormous power of corporate interests in both the media and the political process. As international experience shows, without a strong labor-based movement willing to be radical in its protests, a universal health care program will never be accepted by the US establishment. PMID:12511388

[The problems of pharmaceutical support of patients with diabetes mellitus type II].

PubMed

Khabriev, R U; Malichenko, V S; Malichenko, S B

2016-01-01

The diabetes mellitus acquires a character of sheer spreading global epidemic. Nowadays, in the Russian Federation number of patients with diabetes mellitus reaches 10 million. The accessibility of pharmaceuticals is one of main elements of support of effective treatment of disease. The analysis of federal and regional normative legal acts, territorial programs of state guarantees and data of portal of state purchases demonstrated inefficiency of actual regional system of medicinal support especially in modern economic situation. The necessity of optimization of state costs and also broadening of medicinal coverage of population, including pharmaceuticals for treatment of diabetes mellitus type II, requires development and implementation of step-by-step plan of reforming of regional system of preferential medicinal support.

Leveraging private and public exchanges in an employee benefits strategy.

PubMed

Margolis, Susan; Thompson, Michael

2013-01-01

Health reform is helping to transform the health insurance marketplace and facilitate new opportunities to reevaluate and restructure the underlying framework of employer-sponsored benefits. Central to these opportunities is the emergence of public health exchanges at the state and federal levels offering a coordinated platform of diverse designs and health plans available on a guaranteed issue basis and often with government-provided subsidies. Parallel and complementary to this trend is the emergence of private health exchanges that similarly offer a diversity of plans on a variety of bases. This article shows why, together, these offerings provide potential streamlined solutions for employers as they reevaluate how they facilitate and support access to affordable coverage for their employees (and retirees).

Equity in health care utilization in Chile

PubMed Central

2013-01-01

One of the most extensive Chilean health care reforms occurred in July 2005, when the Regime of Explicit Health Guarantees (AUGE) became effective. This reform guarantees coverage for a specific set of health conditions. Thus, the purpose of this study is to provide timely evidence for policy makers to understand the current distribution and equity of health care utilization in Chile. The authors analyzed secondary data from the National Socioeconomic Survey (CASEN) for the years 1992–2009 and the 2006 Satisfaction and Out-of-Pocket Payment Survey to assess equity in health care utilization using two different approaches. First, we used a two-part model to estimate factors associated with the utilization of health care. Second, we decomposed income-related inequalities in medical care use into contributions of need and non-need factors and estimated a horizontal inequity index. Findings of this empirical study include evidence of inequities in the Chilean health care system that are beneficial to the better-off. We also identified some key factors, including education and health care payment, which affect the utilization of health care services. Results of this study could help researchers and policy makers identify targets for improving equity in health care utilization and strengthening availability of health care services accordingly. PMID:23937894

Airborne SAR systems for infrastructures monitoring

NASA Astrophysics Data System (ADS)

Perna, Stefano; Berardino, Paolo; Esposito, Carmen; Natale, Antonio

2017-04-01

The present contribution is aimed at showing the capabilities of Synthetic Aperture Radar (SAR) systems mounted onboard airborne platforms for the monitoring of infrastructures. As well known, airborne SAR systems guarantee narrower spatial coverage than satellite sensors [1]. On the other side, airborne SAR products are characterized by geometric resolution typically higher than that achievable in the satellite case, where larger antennas must be necessarily exploited. More important, airborne SAR platforms guarantee operational flexibility significantly higher than that achievable with satellite systems. Indeed, the revisit time between repeated SAR acquisitions in the satellite case cannot be freely decided, whereas in the airborne case it can be kept very short. This renders the airborne platforms of key interest for the monitoring of infrastructures, especially in case of emergencies. However, due to the platform deviations from a rectilinear, reference flight track, the generation of airborne SAR products is not a turn of the crank procedure as in the satellite case. Notwithstanding proper algorithms exist in order to circumvent this kind of limitations. In this work, we show how the exploitation of airborne SAR sensors, coupled to the use of such algorithms, allows obtaining high resolution monitoring of infrastructures in urban areas. [1] G. Franceschetti, and R.Lanari, Synthetic Aperture Radar Processing, CRC PRESS, New York, 1999.

Subjective control and health among Mexican-origin elders in Mexico and the United States: structural considerations in comparative research.

PubMed

Angel, Ronald J; Angel, Jacqueline L; Hill, Terrence D

2009-05-01

This study examines the joint impact of psychological and structural factors on Mexican and Mexican American elders' sense of personal control over important aspects of their lives and health in Mexico and the United States. We employ the Mexican Health and Aging Study (MHAS) and the Hispanic Established Populations for Epidemiologic Studies of the Elderly (H-EPESE) to explore patterns of association among structural factors, personal characteristics, indicators of material and physical vulnerability, and expressed locus of control. The results suggest that an older individual's sense of personal control over important aspects of his or her life, including health, reflects real material and social resources in addition to individual predispositions. In Mexico, only the most privileged segment of the population has health insurance, and coverage increases one's sense of personal control. In the United States, on the other hand, Medicare guarantees basic coverage to the vast majority of Mexican Americans over 65, reducing its impact on one's sense of control. Psychological characteristics affect older individuals' sense of personal control over aspects of their health, but the effects are mediated by the economic and health services context in which they are expressed.

Organization of an optimal adaptive immune system

NASA Astrophysics Data System (ADS)

Walczak, Aleksandra; Mayer, Andreas; Balasubramanian, Vijay; Mora, Thierry

The repertoire of lymphocyte receptors in the adaptive immune system protects organisms from a diverse set of pathogens. A well-adapted repertoire should be tuned to the pathogenic environment to reduce the cost of infections. I will discuss a general framework for predicting the optimal repertoire that minimizes the cost of infections contracted from a given distribution of pathogens. The theory predicts that the immune system will have more receptors for rare antigens than expected from the frequency of encounters and individuals exposed to the same infections will have sparse repertoires that are largely different, but nevertheless exploit cross-reactivity to provide the same coverage of antigens. I will show that the optimal repertoires can be reached by dynamics that describes the competitive binding of antigens by receptors, and selective amplification of stimulated receptors.

A Novel Tool Improves Existing Estimates of Recent Tuberculosis Transmission in Settings of Sparse Data Collection.

PubMed

Kasaie, Parastu; Mathema, Barun; Kelton, W David; Azman, Andrew S; Pennington, Jeff; Dowdy, David W

2015-01-01

In any setting, a proportion of incident active tuberculosis (TB) reflects recent transmission ("recent transmission proportion"), whereas the remainder represents reactivation. Appropriately estimating the recent transmission proportion has important implications for local TB control, but existing approaches have known biases, especially where data are incomplete. We constructed a stochastic individual-based model of a TB epidemic and designed a set of simulations (derivation set) to develop two regression-based tools for estimating the recent transmission proportion from five inputs: underlying TB incidence, sampling coverage, study duration, clustered proportion of observed cases, and proportion of observed clusters in the sample. We tested these tools on a set of unrelated simulations (validation set), and compared their performance against that of the traditional 'n-1' approach. In the validation set, the regression tools reduced the absolute estimation bias (difference between estimated and true recent transmission proportion) in the 'n-1' technique by a median [interquartile range] of 60% [9%, 82%] and 69% [30%, 87%]. The bias in the 'n-1' model was highly sensitive to underlying levels of study coverage and duration, and substantially underestimated the recent transmission proportion in settings of incomplete data coverage. By contrast, the regression models' performance was more consistent across different epidemiological settings and study characteristics. We provide one of these regression models as a user-friendly, web-based tool. Novel tools can improve our ability to estimate the recent TB transmission proportion from data that are observable (or estimable) by public health practitioners with limited available molecular data.

A Novel Tool Improves Existing Estimates of Recent Tuberculosis Transmission in Settings of Sparse Data Collection

PubMed Central

Kasaie, Parastu; Mathema, Barun; Kelton, W. David; Azman, Andrew S.; Pennington, Jeff; Dowdy, David W.

2015-01-01

In any setting, a proportion of incident active tuberculosis (TB) reflects recent transmission (“recent transmission proportion”), whereas the remainder represents reactivation. Appropriately estimating the recent transmission proportion has important implications for local TB control, but existing approaches have known biases, especially where data are incomplete. We constructed a stochastic individual-based model of a TB epidemic and designed a set of simulations (derivation set) to develop two regression-based tools for estimating the recent transmission proportion from five inputs: underlying TB incidence, sampling coverage, study duration, clustered proportion of observed cases, and proportion of observed clusters in the sample. We tested these tools on a set of unrelated simulations (validation set), and compared their performance against that of the traditional ‘n-1’ approach. In the validation set, the regression tools reduced the absolute estimation bias (difference between estimated and true recent transmission proportion) in the ‘n-1’ technique by a median [interquartile range] of 60% [9%, 82%] and 69% [30%, 87%]. The bias in the ‘n-1’ model was highly sensitive to underlying levels of study coverage and duration, and substantially underestimated the recent transmission proportion in settings of incomplete data coverage. By contrast, the regression models’ performance was more consistent across different epidemiological settings and study characteristics. We provide one of these regression models as a user-friendly, web-based tool. Novel tools can improve our ability to estimate the recent TB transmission proportion from data that are observable (or estimable) by public health practitioners with limited available molecular data. PMID:26679499

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data

PubMed Central

Ran, Bin; Song, Li; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%. PMID:27448326

Using Tensor Completion Method to Achieving Better Coverage of Traffic State Estimation from Sparse Floating Car Data.

PubMed

Ran, Bin; Song, Li; Zhang, Jian; Cheng, Yang; Tan, Huachun

2016-01-01

Traffic state estimation from the floating car system is a challenging problem. The low penetration rate and random distribution make available floating car samples usually cover part space and time points of the road networks. To obtain a wide range of traffic state from the floating car system, many methods have been proposed to estimate the traffic state for the uncovered links. However, these methods cannot provide traffic state of the entire road networks. In this paper, the traffic state estimation is transformed to solve a missing data imputation problem, and the tensor completion framework is proposed to estimate missing traffic state. A tensor is constructed to model traffic state in which observed entries are directly derived from floating car system and unobserved traffic states are modeled as missing entries of constructed tensor. The constructed traffic state tensor can represent spatial and temporal correlations of traffic data and encode the multi-way properties of traffic state. The advantage of the proposed approach is that it can fully mine and utilize the multi-dimensional inherent correlations of traffic state. We tested the proposed approach on a well calibrated simulation network. Experimental results demonstrated that the proposed approach yield reliable traffic state estimation from very sparse floating car data, particularly when dealing with the floating car penetration rate is below 1%.

N-mixture models for estimating population size from spatially replicated counts

USGS Publications Warehouse

Royle, J. Andrew

2004-01-01

Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, i describe a class of models (n-mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, n, as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for n. Carroll and lombard (1985, journal of american statistical association 80, 423-426) proposed a class of estimators based on mixing over a prior distribution for detection probability. Their estimator can be applied in limited settings, but is sensitive to prior parameter values that are fixed a priori. Spatial replication provides additional information regarding the parameters of the prior distribution on n that is exploited by the n-mixture models and which leads to reasonable estimates of abundance from sparse data. A simulation study demonstrates superior operating characteristics (bias, confidence interval coverage) of the n-mixture estimator compared to the caroll and lombard estimator. Both estimators are applied to point count data on six species of birds illustrating the sensitivity to choice of prior on p and substantially different estimates of abundance as a consequence.

Sparsity-aware tight frame learning with adaptive subspace recognition for multiple fault diagnosis

NASA Astrophysics Data System (ADS)

Zhang, Han; Chen, Xuefeng; Du, Zhaohui; Yang, Boyuan

2017-09-01

It is a challenging problem to design excellent dictionaries to sparsely represent diverse fault information and simultaneously discriminate different fault sources. Therefore, this paper describes and analyzes a novel multiple feature recognition framework which incorporates the tight frame learning technique with an adaptive subspace recognition strategy. The proposed framework consists of four stages. Firstly, by introducing the tight frame constraint into the popular dictionary learning model, the proposed tight frame learning model could be formulated as a nonconvex optimization problem which can be solved by alternatively implementing hard thresholding operation and singular value decomposition. Secondly, the noises are effectively eliminated through transform sparse coding techniques. Thirdly, the denoised signal is decoupled into discriminative feature subspaces by each tight frame filter. Finally, in guidance of elaborately designed fault related sensitive indexes, latent fault feature subspaces can be adaptively recognized and multiple faults are diagnosed simultaneously. Extensive numerical experiments are sequently implemented to investigate the sparsifying capability of the learned tight frame as well as its comprehensive denoising performance. Most importantly, the feasibility and superiority of the proposed framework is verified through performing multiple fault diagnosis of motor bearings. Compared with the state-of-the-art fault detection techniques, some important advantages have been observed: firstly, the proposed framework incorporates the physical prior with the data-driven strategy and naturally multiple fault feature with similar oscillation morphology can be adaptively decoupled. Secondly, the tight frame dictionary directly learned from the noisy observation can significantly promote the sparsity of fault features compared to analytical tight frames. Thirdly, a satisfactory complete signal space description property is guaranteed and thus weak feature leakage problem is avoided compared to typical learning methods.

Piece-wise quadratic approximations of arbitrary error functions for fast and robust machine learning.

PubMed

Gorban, A N; Mirkes, E M; Zinovyev, A

2016-12-01

Most of machine learning approaches have stemmed from the application of minimizing the mean squared distance principle, based on the computationally efficient quadratic optimization methods. However, when faced with high-dimensional and noisy data, the quadratic error functionals demonstrated many weaknesses including high sensitivity to contaminating factors and dimensionality curse. Therefore, a lot of recent applications in machine learning exploited properties of non-quadratic error functionals based on L 1 norm or even sub-linear potentials corresponding to quasinorms L p (0

Implications of Surface Morphologies for the Distribution of Shallow Subsurface Ice in Arcadia Planitia, Mars

NASA Astrophysics Data System (ADS)

Williams, N. R.; Hibbard, S. M.; Golombek, M. P.

2017-12-01

The plains of Arcadia Planitia on Mars at 40°N and 200°E straddle the southern boundary of a latitude-dependent mantle (LDM) of shallow water-ice that holds key records for the planet's climate. Ice is not stable at mid-latitude surfaces today, but is expected to have precipitated in the past during different obliquities and climatic conditions with remnant excess ice preserved in the subsurface under a veneer of soil partially isolating it from the atmosphere. Previous work has documented evidence for substantial ice in Arcadia using gamma ray spectrometry; ground-penetrating radar reflections and dielectric constants; and surface morphologies of lobate debris aprons, expanded secondary craters, terraced craters, and surface polygons. New high-resolution orbital images have been acquired that resolve meter-scale ice-related morphologies. In particular, Arcadia exhibits widespread polygonal patterned ground created by cryoturbation, and large areas of crenulated "brain coral" terrain for which the sinuous troughs have already undergone sublimation while the sinuous ridges are still ice-rich. We examined over 200 High Resolution Imaging Science Experiment (HiRISE) 25 cm/pixel images that resolve these morphologies indicating a complex transition of progressive ice loss at the edge of the LDM. HiRISE coverage is sparse across Arcadia; however, 6 m/pixel Context Camera (CTX) image coverage is nearly complete and fills in the gaps for terrain units with distinct textures. We find that crenulated terrain is restricted to a narrow latitude band at 38°N-43°N. Isolated shallow pits also occur northward of 40°N, and in many cases interconnect to form crenulations as part of a transitional morphologic continuum. Polygonal surface morphologies are ubiquitous farther north, but become increasingly sparse and more degraded farther south. These pits, crenulations, and polygons are sensitive to ice at depths of centimeters to a few meters, which could be easily accessible for future in-situ resource utilization. The latitude band of 38°N-43°N where these fine-scale morphologies occur represents the southern edge of the LDM where significant remnant ice is stored in the shallow subsurface.

Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.

PubMed

Petrov, Andrii Y; Herbst, Michael; Andrew Stenger, V

2017-08-15

Rapid whole-brain dynamic Magnetic Resonance Imaging (MRI) is of particular interest in Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). Faster acquisitions with higher temporal sampling of the BOLD time-course provide several advantages including increased sensitivity in detecting functional activation, the possibility of filtering out physiological noise for improving temporal SNR, and freezing out head motion. Generally, faster acquisitions require undersampling of the data which results in aliasing artifacts in the object domain. A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data. The L+S approach assumes that the dynamic MRI data, represented as a space-time matrix M, is a linear superposition of L and S components, where L represents highly spatially and temporally correlated elements, such as the image background, while S captures dynamic information that is sparse in an appropriate transform domain. This suggests that L+S might be suited for undersampled task or slow event-related fMRI acquisitions because the periodic nature of the BOLD signal is sparse in the temporal Fourier transform domain and slowly varying low-rank brain background signals, such as physiological noise and drift, will be predominantly low-rank. In this work, as a proof of concept, we exploit the L+S method for accelerating block-design fMRI using a 3D stack of spirals (SoS) acquisition where undersampling is performed in the k z -t domain. We examined the feasibility of the L+S method to accurately separate temporally correlated brain background information in the L component while capturing periodic BOLD signals in the S component. We present results acquired in control human volunteers at 3T for both retrospective and prospectively acquired fMRI data for a visual activation block-design task. We show that a SoS fMRI acquisition with an acceleration of four and L+S reconstruction can achieve a brain coverage of 40 slices at 2mm isotropic resolution and 64 x 64 matrix size every 500ms. Copyright © 2017 Elsevier Inc. All rights reserved.

Variational Assimilation of Sparse and Uncertain Satellite Data For 1D Saint-Venant River Models

NASA Astrophysics Data System (ADS)

Garambois, P. A.; Brisset, P.; Monnier, J.; Roux, H.

2016-12-01

Profusion of satellites are providing increasingly accurate measurements of continental water cyle, and water bodies variations while in situ observability is declining. The future Surface Water and Ocean Topography (SWOT) mission will provide maps of river surface elevations widths and slopes with an almost global coverage and temporal revisits. This will offer the possibility to address a larger variety of inverse problems in surface hydrology. Data assimilation techniques, that are broadly used in several scientific fields, aim to optimally combine models, system observations and prior information. Variational assimilation consists in iterative minimization of a discrepency measure between model outputs and observations, here for retrieving boundary conditions and parameters of a 1D Saint Venant model. Nevertheless, inferring river discharge and hydraulic parameters thanks to the observation of river surface is not straightforward. This is particularly true in the case of sparse and uncertain observations of flow state variables since they are governed by nonlinear physical processes. This paper investigates the identifiability of hydraulic controls given sparse and uncertain satellite observations of a river. The identifiability of river discharge alone and with roughness is tested for several spatio temporal patterns of river observations, including SWOT like observations. A new 1D Shallow water model with variational data assimilation, within the DassFlow chain is presented as well as postprocessing and observation operator dedicated to the future SWOT and SWOT simulator data. In view to decrease inverse problem dimensionality discharge is represented in a reduced basis. Moreover we introduce an original and reduced parametrization of the flow resistance that can account for various flow regimes along with a cross section design dedicated to remote sensing. We show which discharge temporal frequencies can be identified w.r.t observation ones and at which accuracy. Eventually the important question of the discharge identifiability potential between observation times and depending on the spatio-temporal sampling is adressed with respect to the wave lengths of the hydrological signals.

Odyssey personal communications satellite system

NASA Technical Reports Server (NTRS)

Spitzer, Christopher J.

1993-01-01

The spectacular growth of cellular telephone networks has proved the demand for personal communications. Large regions of the world are too sparsely populated to be economically served by terrestrial cellular communications. Since satellites are well suited to this application, TRW filed with the FCC on May 31, 1993 for the Odyssey construction permit. Odyssey will provide high quality wireless communication services worldwide from satellites. These services will include: voice, data, paging, and messaging. Odyssey will be an economical approach to providing communications. A constellation of 12 satellites will be orbited in three, 55 deg. inclined planes at an altitude of 10,354 km to provide continuous coverage of designated regions. Two satellites will be visible anywhere in the world at all times. This dual visibility leads to high line-of-sight elevation angles, minimizing obstructions by terrain, trees and buildings. Each satellite generates a multibeam antenna pattern that divides its coverage area into a set of contiguous cells. The communications system employs spread spectrum CDMA on both the uplinks and downlinks. This signaling method permits band sharing with other systems and applications. Signal processing is accomplished on the ground at the satellite's 'Gateway' stations. The 'bent pipe' transponders accommodates different regional standards, as well as signaling changes over time. The low power Odyssey handset will be cellular compatible. Multipath fade protection is provided in the handset.

Global Ocean Evaporation Increases Since 1960 in Climate Reanalyses: How Accurate Are They?

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Roberts, Jason B.; Bosilovich, Michael G.

2016-01-01

AGCMs w/ Specified SSTs (AMIPs) GEOS-5, ERA-20CM Ensembles Incorporate best historical estimates of SST, sea ice, radiative forcing Atmospheric "weather noise" is inconsistent with specified SST. Instantaneous Sfc fluxes can be wrong sign (e.g. Indian Ocean Monsoon, high latitude oceans). Averaging over ensemble members helps isolate SST-forced signal. Reduced Observational Reanalyses: NOAA 20CR V2C, ERA-20C, JRA-55C Incorporate observed Sfc Press (20CR), Marine Winds (ERA-20C) and rawinsondes (JRA-55C) to recover much of true synoptic or weather w/o shock of new sat obs. Comprehensive Reanalyses (MERRA-2) Full suite of observational constraints- both conventional and remote sensing. But... substantial uncertainties owing to evolving satellite observing system. Multi-source Statistically Blended OAFlux, LargeYeager Blend reanalysis, satellite, and ocean buoy information. While climatological biases are removed, non-physical trends or variations in components remain. Satellite Retrievals GSSTF3, SeaFlux, HOAPS3... Global coverage. Retrieved near sfc wind speed, & humidity used with SST to drive accurate bulk aerodynamic flux estimates. Satellite inter-calibration, spacecraft pointing variations crucial. Short record ( late 1987-present). In situ Measurements ICOADS, IVAD, Res Cruises VOS and buoys offer direct measurements. Sparse data coverage (esp south of 30S. Changes in measurement techniques (e.g. shipboard anemometer height).

GIS management system of power plant staff based on wireless fidelity indoor location technology

NASA Astrophysics Data System (ADS)

Zhang, Ting

2017-05-01

The labor conditions and environment of electric power production are quite complicated. It is very difficult to realize the real-time supervision of the employees' working conditions and safety. Using the existing base stations in the power plant, the wireless fidelity network is established to realize the wireless coverage of the work site. We can use mobile phone to communicate and achieve positioning. The main content of this project is based on the special environment of the power plant, designed a suitable for ordinary Android mobile phone indoor wireless fidelity positioning system, real-time positioning and record the scene of each employee's movement trajectory, has achieved real-time staff check Gang, Staff in place, and for the safety of employees to provide a guarantee.

A new augmentation based algorithm for extracting maximal chordal subgraphs

DOE PAGES

Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh

2014-10-18

If every cycle of a graph is chordal length greater than three then it contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms’more » parallelizability. In our paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. Finally, we experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.« less

A New Augmentation Based Algorithm for Extracting Maximal Chordal Subgraphs.

PubMed

Bhowmick, Sanjukta; Chen, Tzu-Yi; Halappanavar, Mahantesh

2015-02-01

A graph is chordal if every cycle of length greater than three contains an edge between non-adjacent vertices. Chordal graphs are of interest both theoretically, since they admit polynomial time solutions to a range of NP-hard graph problems, and practically, since they arise in many applications including sparse linear algebra, computer vision, and computational biology. A maximal chordal subgraph is a chordal subgraph that is not a proper subgraph of any other chordal subgraph. Existing algorithms for computing maximal chordal subgraphs depend on dynamically ordering the vertices, which is an inherently sequential process and therefore limits the algorithms' parallelizability. In this paper we explore techniques to develop a scalable parallel algorithm for extracting a maximal chordal subgraph. We demonstrate that an earlier attempt at developing a parallel algorithm may induce a non-optimal vertex ordering and is therefore not guaranteed to terminate with a maximal chordal subgraph. We then give a new algorithm that first computes and then repeatedly augments a spanning chordal subgraph. After proving that the algorithm terminates with a maximal chordal subgraph, we then demonstrate that this algorithm is more amenable to parallelization and that the parallel version also terminates with a maximal chordal subgraph. That said, the complexity of the new algorithm is higher than that of the previous parallel algorithm, although the earlier algorithm computes a chordal subgraph which is not guaranteed to be maximal. We experimented with our augmentation-based algorithm on both synthetic and real-world graphs. We provide scalability results and also explore the effect of different choices for the initial spanning chordal subgraph on both the running time and on the number of edges in the maximal chordal subgraph.

Health reform: setting the agenda for long term care.

PubMed

Hatch, O G; Wofford, H; Willging, P R; Pomeroy, E

1993-06-01

The White House Task Force on National Health Care Reform, headed by First Lady Hillary Rodham Clinton, is expected to release its prescription for health care reform this month. From the outset, Clinton's mandate was clear: to provide universal coverage while reining in costs for delivering quality health care. Before President Clinton was even sworn into office, he had outlined the major principles that would shape the health reform debate. Global budgeting would establish limits on all health care expenditures, thereby containing health costs. Under a system of managed competition, employers would form health alliances for consumers to negotiate for cost-effective health care at the community level. So far, a basic approach to health care reform has emerged. A key element is universal coverage--with an emphasis on acute, preventive, and mental health care. Other likely pieces are employer-employee contributions to health care plans, laws that guarantee continued coverage if an individual changes jobs or becomes ill, and health insurance alliances that would help assure individual access to low-cost health care. What still is not clear is the extent to which long term care will be included in the basic benefits package. A confidential report circulated by the task force last month includes four options for long term care: incremental Medicaid reform; a new federal/state program to replace Medicaid; a social insurance program for home and community-based services; or full social insurance for long term care. Some work group members have identified an additional option: prefunded long term care insurance.(ABSTRACT TRUNCATED AT 250 WORDS)

Convective Radio Occultations Final Campaign Summary

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

Biondi, R.

2016-03-01

Deep convective systems are destructive weather phenomena that annually cause many deaths and injuries as well as much damage, thereby accounting for major economic losses in several countries. The number and intensity of such phenomena have increased over the last decades in some areas of the globe. Damage is mostly caused by strong winds and heavy rain parameters that are strongly connected to the structure of the particular storm. Convection over land is usually stronger and deeper than over the ocean and some convective systems, known as supercells, also develop tornadoes through processes that remain mostly unclear. The intensity forecastmore » and monitoring of convective systems is one of the major challenges for meteorology because in situ measurements during extreme events are too sparse or unreliable and most ongoing satellite missions do not provide suitable time/space coverage.« less

Investigation of aquifer-estuary interaction using wavelet analysis of fiber-optic temperature data

USGS Publications Warehouse

Henderson, R.D.; Day-Lewis, Frederick D.; Harvey, Charles F.

2009-01-01

Fiber-optic distributed temperature sensing (FODTS) provides sub-minute temporal and meter-scale spatial resolution over kilometer-long cables. Compared to conventional thermistor or thermocouple-based technologies, which measure temperature at discrete (and commonly sparse) locations, FODTS offers nearly continuous spatial coverage, thus providing hydrologic information at spatiotemporal scales previously impossible. Large and information-rich FODTS datasets, however, pose challenges for data exploration and analysis. To date, FODTS analyses have focused on time-series variance as the means to discriminate between hydrologic phenomena. Here, we demonstrate the continuous wavelet transform (CWT) and cross-wavelet transform (XWT) to analyze FODTS in the context of related hydrologic time series. We apply the CWT and XWT to data from Waquoit Bay, Massachusetts to identify the location and timing of tidal pumping of submarine groundwater.

Practical Formal Verification of MPI and Thread Programs

NASA Astrophysics Data System (ADS)

Gopalakrishnan, Ganesh; Kirby, Robert M.

Large-scale simulation codes in science and engineering are written using the Message Passing Interface (MPI). Shared memory threads are widely used directly, or to implement higher level programming abstractions. Traditional debugging methods for MPI or thread programs are incapable of providing useful formal guarantees about coverage. They get bogged down in the sheer number of interleavings (schedules), often missing shallow bugs. In this tutorial we will introduce two practical formal verification tools: ISP (for MPI C programs) and Inspect (for Pthread C programs). Unlike other formal verification tools, ISP and Inspect run directly on user source codes (much like a debugger). They pursue only the relevant set of process interleavings, using our own customized Dynamic Partial Order Reduction algorithms. For a given test harness, DPOR allows these tools to guarantee the absence of deadlocks, instrumented MPI object leaks and communication races (using ISP), and shared memory races (using Inspect). ISP and Inspect have been used to verify large pieces of code: in excess of 10,000 lines of MPI/C for ISP in under 5 seconds, and about 5,000 lines of Pthread/C code in a few hours (and much faster with the use of a cluster or by exploiting special cases such as symmetry) for Inspect. We will also demonstrate the Microsoft Visual Studio and Eclipse Parallel Tools Platform integrations of ISP (these will be available on the LiveCD).

A distributed geo-routing algorithm for wireless sensor networks.

PubMed

Joshi, Gyanendra Prasad; Kim, Sung Won

2009-01-01

Geographic wireless sensor networks use position information for greedy routing. Greedy routing works well in dense networks, whereas in sparse networks it may fail and require a recovery algorithm. Recovery algorithms help the packet to get out of the communication void. However, these algorithms are generally costly for resource constrained position-based wireless sensor networks (WSNs). In this paper, we propose a void avoidance algorithm (VAA), a novel idea based on upgrading virtual distance. VAA allows wireless sensor nodes to remove all stuck nodes by transforming the routing graph and forwarding packets using only greedy routing. In VAA, the stuck node upgrades distance unless it finds a next hop node that is closer to the destination than it is. VAA guarantees packet delivery if there is a topologically valid path. Further, it is completely distributed, immediately responds to node failure or topology changes and does not require planarization of the network. NS-2 is used to evaluate the performance and correctness of VAA and we compare its performance to other protocols. Simulations show our proposed algorithm consumes less energy, has an efficient path and substantially less control overheads.

Identification of spatially-localized initial conditions via sparse PCA

NASA Astrophysics Data System (ADS)

Dwivedi, Anubhav; Jovanovic, Mihailo

2017-11-01

Principal Component Analysis involves maximization of a quadratic form subject to a quadratic constraint on the initial flow perturbations and it is routinely used to identify the most energetic flow structures. For general flow configurations, principal components can be efficiently computed via power iteration of the forward and adjoint governing equations. However, the resulting flow structures typically have a large spatial support leading to a question of physical realizability. To obtain spatially-localized structures, we modify the quadratic constraint on the initial condition to include a convex combination with an additional regularization term which promotes sparsity in the physical domain. We formulate this constrained optimization problem as a nonlinear eigenvalue problem and employ an inverse power-iteration-based method to solve it. The resulting solution is guaranteed to converge to a nonlinear eigenvector which becomes increasingly localized as our emphasis on sparsity increases. We use several fluids examples to demonstrate that our method indeed identifies the most energetic initial perturbations that are spatially compact. This work was supported by Office of Naval Research through Grant Number N00014-15-1-2522.

Daubechies wavelets for linear scaling density functional theory.

PubMed

Mohr, Stephan; Ratcliff, Laura E; Boulanger, Paul; Genovese, Luigi; Caliste, Damien; Deutsch, Thierry; Goedecker, Stefan

2014-05-28

We demonstrate that Daubechies wavelets can be used to construct a minimal set of optimized localized adaptively contracted basis functions in which the Kohn-Sham orbitals can be represented with an arbitrarily high, controllable precision. Ground state energies and the forces acting on the ions can be calculated in this basis with the same accuracy as if they were calculated directly in a Daubechies wavelets basis, provided that the amplitude of these adaptively contracted basis functions is sufficiently small on the surface of the localization region, which is guaranteed by the optimization procedure described in this work. This approach reduces the computational costs of density functional theory calculations, and can be combined with sparse matrix algebra to obtain linear scaling with respect to the number of electrons in the system. Calculations on systems of 10,000 atoms or more thus become feasible in a systematic basis set with moderate computational resources. Further computational savings can be achieved by exploiting the similarity of the adaptively contracted basis functions for closely related environments, e.g., in geometry optimizations or combined calculations of neutral and charged systems.

Unified synchronization criteria in an array of coupled neural networks with hybrid impulses.

PubMed

Wang, Nan; Li, Xuechen; Lu, Jianquan; Alsaadi, Fuad E

2018-05-01

This paper investigates the problem of globally exponential synchronization of coupled neural networks with hybrid impulses. Two new concepts on average impulsive interval and average impulsive gain are proposed to deal with the difficulties coming from hybrid impulses. By employing the Lyapunov method combined with some mathematical analysis, some efficient unified criteria are obtained to guarantee the globally exponential synchronization of impulsive networks. Our method and criteria are proved to be effective for impulsively coupled neural networks simultaneously with synchronizing impulses and desynchronizing impulses, and we do not need to discuss these two kinds of impulses separately. Moreover, by using our average impulsive interval method, we can obtain an interesting and valuable result for the case of average impulsive interval T a =∞. For some sparse impulsive sequences with T a =∞, the impulses can happen for infinite number of times, but they do not have essential influence on the synchronization property of networks. Finally, numerical examples including scale-free networks are exploited to illustrate our theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.

Spatial Bayesian Latent Factor Regression Modeling of Coordinate-based Meta-analysis Data

PubMed Central

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D.; Nichols, Thomas E.

2017-01-01

Summary Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the paper are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to 1) identify areas of consistent activation; and 2) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterised as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. PMID:28498564

Subspace Clustering via Learning an Adaptive Low-Rank Graph.

PubMed

Yin, Ming; Xie, Shengli; Wu, Zongze; Zhang, Yun; Gao, Junbin

2018-08-01

By using a sparse representation or low-rank representation of data, the graph-based subspace clustering has recently attracted considerable attention in computer vision, given its capability and efficiency in clustering data. However, the graph weights built using the representation coefficients are not the exact ones as the traditional definition is in a deterministic way. The two steps of representation and clustering are conducted in an independent manner, thus an overall optimal result cannot be guaranteed. Furthermore, it is unclear how the clustering performance will be affected by using this graph. For example, the graph parameters, i.e., the weights on edges, have to be artificially pre-specified while it is very difficult to choose the optimum. To this end, in this paper, a novel subspace clustering via learning an adaptive low-rank graph affinity matrix is proposed, where the affinity matrix and the representation coefficients are learned in a unified framework. As such, the pre-computed graph regularizer is effectively obviated and better performance can be achieved. Experimental results on several famous databases demonstrate that the proposed method performs better against the state-of-the-art approaches, in clustering.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

NASA Astrophysics Data System (ADS)

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network.

PubMed

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-07-28

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes.

High Volume Pulsed EPC for T/R Modules in Satellite Constellation

NASA Astrophysics Data System (ADS)

Notarianni, Michael; Maynadier, Paul; Marin, Marc

2014-08-01

In the frame of Iridium Next business, a mobile satellite service, Thales Alenia Space (TAS) has to produce more than 2400 x 65W and 162 x 250W pulsed Electronic Power Conditioners (EPC) to supply the RF transmit/receive modules that compose the active antenna of the satellites.The company has to deal with mass production constraints where cost, volume and performances are crucial factors. Compared to previous constellations realized by TAS, the overall challenge is to make further improvements in a short time:- Predictable electrical models- Deeper design-to-cost approach- Streamlining improvements and test coverageAs the active antenna drives the consumption of the payload, accurate performances have been evaluated early owing to the use of simulation (based on average model) and breadboard tests at the same time.The necessary cost reduction has been done owing to large use of COTS (Components Off The Shelf). In order to secure cost and schedule, each manufacturing step has been optimized to maximize test coverage in order to guarantee high reliability.At this time, more than 200 flight models have already been manufactured, validating this approach.This paper is focused on the 65W EPC but the same activities have been led on the 250W EPC.

UST Financial Assurance Information

EPA Pesticide Factsheets

Subtitle I of the Resource Conservation and Recovery Act, as amended by the Hazardous Waste Disposal Act of 1984, brought underground storage tanks (USTs) under federal regulation. As part of that regulation, Congress directed EPA to develop financial responsibility regulations for UST owners and operators. Congress wanted owners and operators of underground storage tanks (USTs) to show that they have the financial resources to clean up a site if a release occurs, correct environmental damage, and compensate third parties for injury to their property or themselves.Owners and operators have several options: obtain insurance coverage from an insurer or a risk retention group; demonstrate self-insurance using a financial test; obtain corporate guarantees, surety bonds, or letters of credit; place the required amount into a trust fund administered by a third party; or rely on coverage provided by a state financial assurance fund.Information in this data asset includes state documentation to support this requirement. Many states have developed financial assurance funds to help owners and operators meet financial responsibility requirements and to help cover the costs of cleanups. State financial assurance fund programs, which supplement or are a substitute for private insurance, have been especially useful for small-to-medium sized petroleum marketers.EPA requires its Regional Offices to conduct annual reviews of state financial assurance funds. Data is provided by s

Subjective Control and Health Among Mexican-Origin Elders in Mexico and the United States: Structural Considerations in Comparative Research

PubMed Central

Hill, Terrence D.

2009-01-01

Objectives This study examines the joint impact of psychological and structural factors on Mexican and Mexican American elders' sense of personal control over important aspects of their lives and health in Mexico and the United States. Methods We employ the Mexican Health and Aging Study (MHAS) and the Hispanic Established Populations for Epidemiologic Studies of the Elderly (H-EPESE) to explore patterns of association among structural factors, personal characteristics, indicators of material and physical vulnerability, and expressed locus of control. Results The results suggest that an older individual's sense of personal control over important aspects of his or her life, including health, reflects real material and social resources in addition to individual predispositions. In Mexico, only the most privileged segment of the population has health insurance, and coverage increases one's sense of personal control. In the United States, on the other hand, Medicare guarantees basic coverage to the vast majority of Mexican Americans over 65, reducing its impact on one's sense of control. Discussion Psychological characteristics affect older individuals' sense of personal control over aspects of their health, but the effects are mediated by the economic and health services context in which they are expressed. PMID:19332436

Experimental demonstration of multi-dimensional resources integration for service provisioning in cloud radio over fiber network

PubMed Central

Yang, Hui; Zhang, Jie; Ji, Yuefeng; He, Yongqi; Lee, Young

2016-01-01

Cloud radio access network (C-RAN) becomes a promising scenario to accommodate high-performance services with ubiquitous user coverage and real-time cloud computing in 5G area. However, the radio network, optical network and processing unit cloud have been decoupled from each other, so that their resources are controlled independently. Traditional architecture cannot implement the resource optimization and scheduling for the high-level service guarantee due to the communication obstacle among them with the growing number of mobile internet users. In this paper, we report a study on multi-dimensional resources integration (MDRI) for service provisioning in cloud radio over fiber network (C-RoFN). A resources integrated provisioning (RIP) scheme using an auxiliary graph is introduced based on the proposed architecture. The MDRI can enhance the responsiveness to dynamic end-to-end user demands and globally optimize radio frequency, optical network and processing resources effectively to maximize radio coverage. The feasibility of the proposed architecture is experimentally verified on OpenFlow-based enhanced SDN testbed. The performance of RIP scheme under heavy traffic load scenario is also quantitatively evaluated to demonstrate the efficiency of the proposal based on MDRI architecture in terms of resource utilization, path blocking probability, network cost and path provisioning latency, compared with other provisioning schemes. PMID:27465296

Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures.

PubMed

Cañete, Eduardo; Chen, Jaime; Díaz, Manuel; Llopis, Luis; Reyna, Ana; Rubio, Bartolomé

2015-06-26

Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency.

Using Wireless Sensor Networks and Trains as Data Mules to Monitor Slab Track Infrastructures

PubMed Central

Cañete, Eduardo; Chen, Jaime; Díaz, Manuel; Llopis, Luis; Reyna, Ana; Rubio, Bartolomé

2015-01-01

Recently, slab track systems have arisen as a safer and more sustainable option for high speed railway infrastructures, compared to traditional ballasted tracks. Integrating Wireless Sensor Networks within these infrastructures can provide structural health related data that can be used to evaluate their degradation and to not only detect failures but also to predict them. The design of such systems has to deal with a scenario of large areas with inaccessible zones, where neither Internet coverage nor electricity supply is guaranteed. In this paper we propose a monitoring system for slab track systems that measures vibrations and displacements in the track. Collected data is transmitted to passing trains, which are used as data mules to upload the information to a remote control center. On arrival at the station, the data is stored in a database, which is queried by an application in order to detect and predict failures. In this paper, different communication architectures are designed and tested to select the most suitable system meeting such requirements as efficiency, low cost and data accuracy. In addition, to ensure communication between the sensing devices and the train, the communication system must take into account parameters such as train speed, antenna coverage, band and frequency. PMID:26131668

2010-2011 Performance of the AirNow Satellite Data Processor

NASA Astrophysics Data System (ADS)

Pasch, A. N.; DeWinter, J. L.; Haderman, M. D.; van Donkelaar, A.; Martin, R. V.; Szykman, J.; White, J. E.; Dickerson, P.; Zahn, P. H.; Dye, T. S.

2012-12-01

The U.S. Environmental Protection Agency's (EPA) AirNow program provides maps of real time hourly Air Quality Index (AQI) conditions and daily AQI forecasts nationwide (http://www.airnow.gov). The public uses these maps to make health-based decisions. The usefulness of the AirNow air quality maps depends on the accuracy and spatial coverage of air quality measurements. Currently, the maps use only ground-based measurements, which have significant gaps in coverage in some parts of the United States. As a result, contoured AQI levels have high uncertainty in regions far from monitors. To improve the usefulness of air quality maps, scientists at EPA, Dalhousie University, and Sonoma Technology, Inc. have been working in collaboration with the National Aeronautics and Space Administration (NASA) and the National Oceanic and Atmospheric Administration (NOAA) to incorporate satellite-estimated surface PM2.5 concentrations into the maps via the AirNow Satellite Data Processor (ASDP). These satellite estimates are derived using NASA/NOAA satellite aerosol optical depth (AOD) retrievals and GEOS-Chem modeled ratios of surface PM2.5 concentrations to AOD. GEOS-Chem is a three-dimensional chemical transport model for atmospheric composition driven by meteorological input from the Goddard Earth Observing System (GOES). The ASDP can fuse multiple PM2.5 concentration data sets to generate AQI maps with improved spatial coverage. The goal of ASDP is to provide more detailed AQI information in monitor-sparse locations and augment monitor-dense locations with more information. We will present a statistical analysis for 2010-2011 of the ASDP predictions of PM2.5 focusing on performance at validation sites. In addition, we will present several case studies evaluating the ASDP's performance for multiple regions and seasons, focusing specifically on days when large spatial gradients in AQI and wildfire smoke impact were observed.

A New Unified Approach to Determine Geocenter Motion Using Space Geodesy and GRACE Gravity Data

NASA Astrophysics Data System (ADS)

Wu, X.; Kusche, J.; Landerer, F. W.

2016-12-01

Spherical harmonic expansions of Earth's surface mass variations start from three degree-1 terms. These longest-wavelength terms induce geocenter motion between the center-of-mass of the total Earth system (CM) and the center-of-figure of the solid Earth surface (CF), and a degree-1 surface deformation field. For complete spectral coverage and robust assessment of geographic mass budget using GRACE data, very accurate knowledge of geocenter motion between CM and CF is required with precision goals of 0.2 mm in annual amplitude and 0.2 mm/yr leading to equivalent degree-1 coefficients. However, GRACE's K-band ranging data system is not sensitive to these variation modes. Although satellite laser ranging (SLR) system is thought to have the most reliable sensitivity to CM, its surface network is very sparse and can only deliver motion between CM and the center of a changing network (CN) of roughly 20 unevenly distributed stations. Recently, the network has been extended to include 82 stations with their geocentric displacements derived by transferring SLR's CM sensitivity to other technique networks through local tie and co-motion constraints. The CM-CN motion of this network has a better agreement with the geocenter motion result from a global inversion of relative GPS, GRACE, and the ECCO ocean bottom pressure (OBP) model. Still, there is no guarantee that such a CM-CN motion is the same as the CM-CF motion. Also, the global inversion result is subject to the impact of unknown errors in the OBP model. To improve reliability of geocenter motion determination, we use a new unified approach to geocenter motion determination by combining geocentric displacements of ground stations with GRACE gravity data. Both translational and deformational signatures will be exploited for retrieval of the degree-1 surface mass variation coefficients. Higher degree terms are estimated simultaneously using GRACE gravity data, which further improves CF knowledge and reduces aliasing effects. Such a data combination also uses full covariance matrices of all data types to facilitate a reliable variance component estimation. High-precision results for non-linear geocenter motion have been achieved and will be reported. We will also discuss challenges and strategies for improving geocenter velocity determination.

Impacts of distinct observations during the 2009 Prince William Sound field experiment: A data assimilation study

NASA Astrophysics Data System (ADS)

Li, Z.; Chao, Y.; Farrara, J.; McWilliams, J. C.

2012-12-01

A set of data assimilation experiments, known as Observing System Experiments (OSEs), are performed to assess the relative impacts of different types of observations acquired during the 2009 Prince William Sound Field Experiment. The observations assimilated consist primarily of three types: High Frequency (HF) radar surface velocities, vertical profiles of temperature/salinity (T/S) measured by ships, moorings, Autonomous Underwater Vehicles and gliders, and satellite sea surface temperatures (SSTs). The impact of all the observations, HF radar surface velocities, and T/S profiles is assessed. Without data assimilation, a frequently occurring cyclonic eddy in the central Sound is overly persistent and intense. The assimilation of the HF radar velocities effectively reduces these biases and improves the representation of the velocities as well as the T/S fields in the Sound. The assimilation of the T/S profiles improves the large scale representation of the temperature/salinity and also the velocity field in the central Sound. The combination of the HF radar surface velocities and sparse T/S profiles results in an observing system capable of representing the circulation in the Sound reliably and thus producing analyses and forecasts with useful skill. It is suggested that a potentially promising observing network could be based on satellite SSHs and SSTs along with sparse T/S profiles, and future satellite SSHs with wide swath coverage and higher resolution may offer excellent data that will be of great use for predicting the circulation in the Sound.

13 CFR 400.215 - Supplemental Guarantees.

Code of Federal Regulations, 2012 CFR

2012-01-01

... Section 400.215 Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM Steel Guarantee Loans § 400.215 Supplemental Guarantees. The Board will allow the structure of a guaranteed loan to include one or more Supplemental Guarantees that cover the Unguaranteed...

13 CFR 400.215 - Supplemental Guarantees.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Section 400.215 Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM Steel Guarantee Loans § 400.215 Supplemental Guarantees. The Board will allow the structure of a guaranteed loan to include one or more Supplemental Guarantees that cover the Unguaranteed...

13 CFR 400.215 - Supplemental Guarantees.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Section 400.215 Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM Steel Guarantee Loans § 400.215 Supplemental Guarantees. The Board will allow the structure of a guaranteed loan to include one or more Supplemental Guarantees that cover the Unguaranteed...

13 CFR 400.215 - Supplemental Guarantees.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Section 400.215 Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM Steel Guarantee Loans § 400.215 Supplemental Guarantees. The Board will allow the structure of a guaranteed loan to include one or more Supplemental Guarantees that cover the Unguaranteed...

13 CFR 400.215 - Supplemental Guarantees.

Code of Federal Regulations, 2013 CFR

2013-01-01

... Section 400.215 Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM Steel Guarantee Loans § 400.215 Supplemental Guarantees. The Board will allow the structure of a guaranteed loan to include one or more Supplemental Guarantees that cover the Unguaranteed...

A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems.

PubMed

Silva, Lenardo C; Almeida, Hyggo O; Perkusich, Angelo; Perkusich, Mirko

2015-10-30

Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different contexts. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage.

The data model for social welfare in Finland.

PubMed

Kärki, Jarmo; Ailio, Erja

2014-01-01

A client data model for social welfare was gradually developed in the National Project of IT in Social Services in Finland. The client data model describes the nationally uniformed data structures and relationships between the data elements needed in production of social services. It contains the structures of social care client records, unique core components and distinct classifications. The modeling method guaranteed the coverage, integrity, flexibility and device independency of the model. The model is maintained and developed by the National Institute for Health and Welfare (THL) together with the social workers and other experts of social welfare. It forms the basis of the electronic information management of the social services. Implementation of the data model in information systems enables the availability of the client data where and when ever a client has to be helped.

A Model-Based Approach to Support Validation of Medical Cyber-Physical Systems

PubMed Central

Silva, Lenardo C.; Almeida, Hyggo O.; Perkusich, Angelo; Perkusich, Mirko

2015-01-01

Medical Cyber-Physical Systems (MCPS) are context-aware, life-critical systems with patient safety as the main concern, demanding rigorous processes for validation to guarantee user requirement compliance and specification-oriented correctness. In this article, we propose a model-based approach for early validation of MCPS, focusing on promoting reusability and productivity. It enables system developers to build MCPS formal models based on a library of patient and medical device models, and simulate the MCPS to identify undesirable behaviors at design time. Our approach has been applied to three different clinical scenarios to evaluate its reusability potential for different contexts. We have also validated our approach through an empirical evaluation with developers to assess productivity and reusability. Finally, our models have been formally verified considering functional and safety requirements and model coverage. PMID:26528982

Interplay between cost and benefits triggers nontrivial vaccination uptake

NASA Astrophysics Data System (ADS)

Steinegger, Benjamin; Cardillo, Alessio; Rios, Paolo De Los; Gómez-Gardeñes, Jesús; Arenas, Alex

2018-03-01

The containment of epidemic spreading is a major challenge in science. Vaccination, whenever available, is the best way to prevent the spreading, because it eventually immunizes individuals. However, vaccines are not perfect, and total immunization is not guaranteed. Imperfect immunization has driven the emergence of antivaccine movements that totally alter the predictions about the epidemic incidence. Here, we propose a mathematically solvable mean-field vaccination model to mimic the spontaneous adoption of vaccines against influenzalike diseases and the expected epidemic incidence. The results are in agreement with extensive Monte Carlo simulations of the epidemics and vaccination coevolutionary processes. Interestingly, the results reveal a nonmonotonic behavior on the vaccination coverage that increases with the imperfection of the vaccine and after decreases. This apparent counterintuitive behavior is analyzed and understood from stability principles of the proposed mathematical model.

Public financing of the Medicare program will make its uniform structure increasingly costly to sustain.

PubMed

Baicker, Katherine; Shepard, Mark; Skinner, Jonathan

2013-05-01

The US Medicare program consumes an ever-rising share of the federal budget. Although this public spending can produce health and social benefits, raising taxes to finance it comes at the cost of slower economic growth. In this article we describe a model incorporating the benefits of public programs and the cost of tax financing. The model implies that the "one-size-fits-all" Medicare program, with everyone covered by the same insurance policy, will be increasingly difficult to sustain. We show that a Medicare program with guaranteed basic benefits and the option to purchase additional coverage could lead to more unequal health spending but slower growth in taxation, greater overall well-being, and more rapid growth of gross domestic product. Our framework highlights the key trade-offs between Medicare spending and economic prosperity.

A comparative study of CO adsorption on tetrahexahedral Pt nanocrystals and interrelated Pt single crystal electrodes by using cyclic voltammetry and in situ FTIR spectroscopy.

PubMed

Liu, Hai-Xia; Tian, Na; Ye, Jin-Yu; Lu, Bang-An; Ren, Jie; Huangfu, Zhi-Chao; Zhou, Zhi-You; Sun, Shi-Gang

2014-01-01

This study focuses on CO adsorption at tetrahexahedral Pt nanocrystals (THH Pt NCs) by using cyclic voltammetry and in situ FTIR spectroscopy. Since the electrochemically prepared THH Pt NCs in this study are enclosed by {730} facets which could be considered by a subfacet configuration of 2{210} + {310}, we have also studied CO adsorption on the interrelated Pt(310) and Pt(210) single crystal electrodes as a comparison. Cyclic voltammetry results demonstrated that CO adsorbs dominantly on the (100) sites of THH Pt NCs at low CO coverage (θ(CO)≤ 0.135), while on both (100) and (110) sites at higher CO coverage. On ordered Pt(310) and Pt(210), i.e. they were flame annealed and then cooled in H(2) + Ar, CO adsorption also illustrates relative priority on (100) sites at low CO coverage; while at high CO coverage or on oxygen-disordered Pt(310) and Pt(210) when they were cooled in air after flame annealing, the adsorption of CO presents a weak preference on (100) sites of Pt(310) and even no preference at all on (100) sites of Pt(210). In situ FTIR spectroscopic studies illustrated that CO adsorption on THH Pt NCs yields anomalous infrared effects (AIREs), which are depicted by the Fano-like IR feature on a dense distribution (60 μm(-2)) and the enhancement of abnormal IR absorption on a sparse distribution (22 μm(-2)) of THH Pt NCs on glassy carbon substrate. Systematic investigation of CO coverage dependence of IR features revealed that, on THH Pt NCs, the IR band center (ν(COL)) of linearly bonded CO (COL) is rapidly shifted to higher wavenumbers along with the increase of CO coverage to 0.184, yielding a fast linear increase rate with a high slope (dν(COL)/dθ(IR)(CO) = 219 cm(-1)); when θ > 0.184, the increase of ν(COL) with θCO slows down and deviates drastically from linearity. In contrast, the ν(COL) on the ordered Pt(310) electrode maintains a linear increase with θ(IR)(CO) for the whole range of θ(IR)(CO) variation, and gives a much smaller increase rate of slope 74.3 cm(-1). The significant differences in CO adsorption behavior on THH Pt NCs and on interrelated Pt single crystal planes demonstrated clearly the unique properties of nanoparticles enclosed by high-index facets.

7 CFR 1720.14 - Nature of guarantee; acceleration of guaranteed bonds.

Code of Federal Regulations, 2012 CFR

2012-01-01

... 7 Agriculture 11 2012-01-01 2012-01-01 false Nature of guarantee; acceleration of guaranteed bonds. 1720.14 Section 1720.14 Agriculture Regulations of the Department of Agriculture (Continued) RURAL... TELEPHONE PURPOSES § 1720.14 Nature of guarantee; acceleration of guaranteed bonds. (a) Any guarantee...

7 CFR 1720.14 - Nature of guarantee; acceleration of guaranteed bonds.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 11 2010-01-01 2010-01-01 false Nature of guarantee; acceleration of guaranteed bonds. 1720.14 Section 1720.14 Agriculture Regulations of the Department of Agriculture (Continued) RURAL... TELEPHONE PURPOSES § 1720.14 Nature of guarantee; acceleration of guaranteed bonds. (a) Any guarantee...

7 CFR 1720.14 - Nature of guarantee; acceleration of guaranteed bonds.

Code of Federal Regulations, 2011 CFR

2011-01-01

... 7 Agriculture 11 2011-01-01 2011-01-01 false Nature of guarantee; acceleration of guaranteed bonds. 1720.14 Section 1720.14 Agriculture Regulations of the Department of Agriculture (Continued) RURAL... TELEPHONE PURPOSES § 1720.14 Nature of guarantee; acceleration of guaranteed bonds. (a) Any guarantee...

7 CFR 1720.14 - Nature of guarantee; acceleration of guaranteed bonds.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Nature of guarantee; acceleration of guaranteed bonds. 1720.14 Section 1720.14 Agriculture Regulations of the Department of Agriculture (Continued) RURAL... TELEPHONE PURPOSES § 1720.14 Nature of guarantee; acceleration of guaranteed bonds. (a) Any guarantee...

7 CFR 1720.14 - Nature of guarantee; acceleration of guaranteed bonds.

Code of Federal Regulations, 2013 CFR

2013-01-01

... 7 Agriculture 11 2013-01-01 2013-01-01 false Nature of guarantee; acceleration of guaranteed bonds. 1720.14 Section 1720.14 Agriculture Regulations of the Department of Agriculture (Continued) RURAL... TELEPHONE PURPOSES § 1720.14 Nature of guarantee; acceleration of guaranteed bonds. (a) Any guarantee...

Optimization of parameters for coverage of low molecular weight proteins

PubMed Central

Müller, Stephan A.; Kohajda, Tibor; Findeiß, Sven; Stadler, Peter F.; Washietl, Stefan; Kellis, Manolis; von Bergen, Martin

2010-01-01

Proteins with molecular weights of <25 kDa are involved in major biological processes such as ribosome formation, stress adaption (e.g., temperature reduction) and cell cycle control. Despite their importance, the coverage of smaller proteins in standard proteome studies is rather sparse. Here we investigated biochemical and mass spectrometric parameters that influence coverage and validity of identification. The underrepresentation of low molecular weight (LMW) proteins may be attributed to the low numbers of proteolytic peptides formed by tryptic digestion as well as their tendency to be lost in protein separation and concentration/desalting procedures. In a systematic investigation of the LMW proteome of Escherichia coli, a total of 455 LMW proteins (27% of the 1672 listed in the SwissProt protein database) were identified, corresponding to a coverage of 62% of the known cytosolic LMW proteins. Of these proteins, 93 had not yet been functionally classified, and five had not previously been confirmed at the protein level. In this study, the influences of protein extraction (either urea or TFA), proteolytic digestion (solely, and the combined usage of trypsin and AspN as endoproteases) and protein separation (gel- or non-gel-based) were investigated. Compared to the standard procedure based solely on the use of urea lysis buffer, in-gel separation and tryptic digestion, the complementary use of TFA for extraction or endoprotease AspN for proteolysis permits the identification of an extra 72 (32%) and 51 proteins (23%), respectively. Regarding mass spectrometry analysis with an LTQ Orbitrap mass spectrometer, collision-induced fragmentation (CID and HCD) and electron transfer dissociation using the linear ion trap (IT) or the Orbitrap as the analyzer were compared. IT-CID was found to yield the best identification rate, whereas IT-ETD provided almost comparable results in terms of LMW proteome coverage. The high overlap between the proteins identified with IT-CID and IT-ETD allowed the validation of 75% of the identified proteins using this orthogonal fragmentation technique. Furthermore, a new approach to evaluating and improving the completeness of protein databases that utilizes the program RNAcode was introduced and examined. Electronic supplementary material The online version of this article (doi:10.1007/s00216-010-4093-x) contains supplementary material, which is available to authorized users. PMID:20803007

Comparing Types of Health Insurance for Children

PubMed Central

DeVoe, Jennifer E.; Tillotson, Carrie J.; Wallace, Lorraine S.; Selph, Shelley; Graham, Alan; Angier, Heather

2015-01-01

Background Many states have expanded public health insurance programs for children, and further expansions were proposed in recent national reform initiatives; yet the expansion of public insurance plans and the inclusion of a public option in state insurance exchange programs sparked controversies and raised new questions with regard to the quality and adequacy of various insurance types. Objectives We aimed to examine the comparative effectiveness of public versus private coverage on parental-reported children’s access to health care in low-income and middle-income families. Methods/Participants/Measures We conducted secondary data analyses of the nationally representative Medical Expenditure Panel Survey, pooling years 2002 to 2006. We assessed univariate and multivariate associations between child’s full-year insurance type and parental-reported unmet health care and preventive counseling needs among children in low-income (n =28,338) and middle-income families (n = 13,160). Results Among children in families earning <200% of the federal poverty level, those with public insurance were significantly less likely to have no usual source of care compared with privately insured children (adjusted relative risk, 0.79; 95% confidence interval, 0.63–0.99). This was the only significant difference in 50 logistic regression models comparing unmet health care and preventive counseling needs among low-income and middle-income children with public versus private coverage. Conclusions The striking similarities in reported rates of unmet needs among children with public versus private coverage in both low-income and middle-income groups suggest that a public children’s insurance option may be equivalent to a private option in guaranteeing access to necessary health care services for all children. PMID:21478781

Relationships Between Long-Range Lightning Networks and TRMM/LIS Observations

NASA Technical Reports Server (NTRS)

Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cummins, Kenneth L.; Cummins, Kenneth L.; Blakeslee, Richard J.; Goodman, Steven J.

2012-01-01

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. The present study intercompares long-range lightning data with observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study examines network detection efficiency and location accuracy relative to LIS observations, describes spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by the long-range networks. Improved knowledge of relationships between these datasets will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

Evaluation of Long-Range Lightning Detection Networks Using TRMM/LIS Observations

NASA Technical Reports Server (NTRS)

Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cecil, Daniel J.; Cummins, Kenneth L.; Petersen, Walter A.; Blakeslee, Richard J.; Goodman, Steven J.

2011-01-01

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. Toward this end, the present study evaluates data from the World Wide Lightning Location Network (WWLLN) using observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study documents the WWLLN detection efficiency and location accuracy relative to LIS observations, describes the spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by WWLLN. Improved knowledge of the WWLLN detection capabilities will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

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

Carpenter, J.A.

This report is a sequel to ORNL/CSD-106 in the ongoing supplements to Professor A.S. Householder's KWIC Index for Numerical Algebra. Beginning with the previous supplement, the subject has been restricted to Numerical Linear Algebra, roughly characterized by the American Mathematical Society's classification sections 15 and 65F but with little coverage of infinite matrices, matrices over fields of characteristics other than zero, operator theory, optimization and those parts of matrix theory primarily combinatorial in nature. Some consideration is given to the uses of graph theory in Numerical Linear Algebra, particularly with respect to algorithms for sparse matrix computations. The period coveredmore » by this report is roughly the calendar year 1982 as measured by the appearance of the articles in the American Mathematical Society's Contents of Mathematical Publications lagging actual appearance dates by up to nearly half a year. The review citations are limited to the Mathematical Reviews (MR).« less

Enclosure Transform for Interest Point Detection From Speckle Imagery.

PubMed

Yongjian Yu; Jue Wang

2017-03-01

We present a fast enclosure transform (ET) to localize complex objects of interest from speckle imagery. This approach explores the spatial confinement on regional features from a sparse image feature representation. Unrelated, broken ridge features surrounding an object are organized collaboratively, giving rise to the enclosureness of the object. Three enclosure likelihood measures are constructed, consisting of the enclosure force, potential energy, and encloser count. In the transform domain, the local maxima manifest the locations of objects of interest, for which only the intrinsic dimension is known a priori. The discrete ET algorithm is computationally efficient, being on the order of O(MN) using N measuring distances across an image of M ridge pixels. It involves easy and few parameter settings. We demonstrate and assess the performance of ET on the automatic detection of the prostate locations from supra-pubic ultrasound images. ET yields superior results in terms of positive detection rate, accuracy and coverage.

q-Space Upsampling Using x-q Space Regularization.

PubMed

Chen, Geng; Dong, Bin; Zhang, Yong; Shen, Dinggang; Yap, Pew-Thian

2017-09-01

Acquisition time in diffusion MRI increases with the number of diffusion-weighted images that need to be acquired. Particularly in clinical settings, scan time is limited and only a sparse coverage of the vast q -space is possible. In this paper, we show how non-local self-similar information in the x - q space of diffusion MRI data can be harnessed for q -space upsampling. More specifically, we establish the relationships between signal measurements in x - q space using a patch matching mechanism that caters to unstructured data. We then encode these relationships in a graph and use it to regularize an inverse problem associated with recovering a high q -space resolution dataset from its low-resolution counterpart. Experimental results indicate that the high-resolution datasets reconstructed using the proposed method exhibit greater quality, both quantitatively and qualitatively, than those obtained using conventional methods, such as interpolation using spherical radial basis functions (SRBFs).

Market opportunities in Canada for multimedia residential services in rural and small urban areas

NASA Technical Reports Server (NTRS)

Shariatmadar, Mehran; Narasimhan, Vasantha

1995-01-01

This paper reviews the studies which were undertaken jointly by Telesat and Industry Canada to provide an estimate of the market opportunities for residential multi-media services in the rural and small urban areas of Canada. This study is part of the Advanced Satcom program, a Ka-band satellite system proposal which is currently in the implementation proposal phase by the government and the Canadian space industry of which Telesat is an active member. Advanced Satcom extends the reach of terrestrial information highways to the remote and sparsely populated parts of the country in a cost-effective manner and thus provides a ubiquitous coverage of the information highways to all Canadians. Therefore, the rural and small urban markets are believed to be good opportunities for the Advanced Satcom. Although the results are primarily intended for fixed residential applications, they can also be used as input to market opportunity studies for wideband mobile applications.

Different Operating Modes of the Rosetta's Ion Composition Analyzer and Its Virtual Counterpart

NASA Astrophysics Data System (ADS)

Pospieszyński, R.

2009-12-01

The Ion Composition Analyzer (ICA) is a part of the Rosetta Plasma Consortium (RPC) which is on board the Rosetta space probe heading for the comet 67/P Churyumov-Gerasimenko. It is scheduled to reach the comet in year 2014. In order to reduce telemetry the ICA instrument has a number of data reduction modes (sampling modes). The effects of these different modes are investigated and a plan on how to best operate the instrument when in orbit around the comet will be prepared. In order to investigate all of the cases a virtual instrument is being prepared. The virtual instrument can be operated in different modes just as the ``real'' one. The work with sampling will be to calculate what particles are coming from each direction we are looking in, based on the ISSI Comet Model, and then see how much information we loose by too sparse sampling and incomplete spatial coverage.

Identifying Stratospheric Air Intrusions and Associated Hurricane-Force Wind Events over the North Pacific Ocean

NASA Technical Reports Server (NTRS)

Malloy, Kelsey; Folmer, Michael J.; Phillips, Joseph; Sienkiewicz, Joseph M.; Berndt, Emily

2017-01-01

Motivation: Ocean data is sparse: reliance on satellite imagery for marine forecasting; Ocean Prediction Center (OPC) –“mariner’s weather lifeline”. Responsible for: Pacific, Atlantic, Pacific Alaska surface analyses –24, 48, 96 hrs.; Wind & wave analyses –24, 48, 96 hrs.; Issue warnings, make decisions, Geostationary Operational Environmental Satellite –R Series (now GOES-16), Compared to the old GOES: 3 times spectral resolution, 4 times spatial resolution, 5 times faster coverage; Comparable to Japanese Meteorological Agency’s Himawari-8, used a lot throughout this research. Research Question: How can integrating satellite data imagery and derived products help forecasters improve prognosis of rapid cyclogenesis and hurricane-force wind events? Phase I –Identifying stratospheric air intrusions: Water Vapor –6.2, 6.9, 7.3 micron channels; Airmass RGB Product; AIRS, IASI, NUCAPS total column ozone and ozone anomaly; ASCAT (A/B) and AMSR-2 wind data.

The investigation of identifying method on grass fire by FY-3 VIRR images

NASA Astrophysics Data System (ADS)

Jiang, Youyan; Han, Tao; Wang, Dawei

2018-03-01

Grassland fire has the characteristics of fierce fire and rapid spreading, and many fires occur in sparsely populated places. Satellite remote sensing has the characteristics of fast imaging period and wide coverage, and plays an important role in the rapid monitoring and evaluation of grassland fire. FY-3 satellite has been widely used since its launch in September 2008, and this paper uses the fire information of Gansu grassland from 2011 to 2016, based on the more mature MODIS and NOAA-AVHRR fire identification method. The results show that the accuracy of FY-3/VIRR satellite data fire detection are higher than that of NOAA-AVHRR satellite, and the accuracy of FY-3/VIRR satellite data is described. There is a greater improvement, the ability to identify slightly worse than the MODIS satellite, the region is relatively large fire detection accuracy is higher.

Study on Data Clustering and Intelligent Decision Algorithm of Indoor Localization

NASA Astrophysics Data System (ADS)

Liu, Zexi

2018-01-01

Indoor positioning technology enables the human beings to have the ability of positional perception in architectural space, and there is a shortage of single network coverage and the problem of location data redundancy. So this article puts forward the indoor positioning data clustering algorithm and intelligent decision-making research, design the basic ideas of multi-source indoor positioning technology, analyzes the fingerprint localization algorithm based on distance measurement, position and orientation of inertial device integration. By optimizing the clustering processing of massive indoor location data, the data normalization pretreatment, multi-dimensional controllable clustering center and multi-factor clustering are realized, and the redundancy of locating data is reduced. In addition, the path is proposed based on neural network inference and decision, design the sparse data input layer, the dynamic feedback hidden layer and output layer, low dimensional results improve the intelligent navigation path planning.

Vegetation mapping of the Mond Protected Area of Bushehr Province (south-west Iran).

PubMed

Mehrabian, Ahmadreza; Naqinezhad, Alireza; Mahiny, Abdolrassoul Salman; Mostafavi, Hossein; Liaghati, Homan; Kouchekzadeh, Mohsen

2009-03-01

Arid regions of the world occupy up to 35% of the earth's surface, the basis of various definitions of climatic conditions, vegetation types or potential for food production. Due to their high ecological value, monitoring of arid regions is necessary and modern vegetation studies can help in the conservation and management of these areas. The use of remote sensing for mapping of desert vegetation is difficult due to mixing of the spectral reflectance of bright desert soils with the weak spectral response of sparse vegetation. We studied the vegetation types in the semiarid to arid region of Mond Protected Area, south-west Iran, based on unsupervised classification of the Spot XS bands and then produced updated maps. Sixteen map units covering 12 vegetation types were recognized in the area based on both field works and satellite mapping. Halocnemum strobilaceum and Suaeda fruticosa vegetation types were the dominant types and Ephedra foliata, Salicornia europaea-Suaeda heterophylla vegetation types were the smallest. Vegetation coverage decreased sharply with the increase in salinity towards the coastal areas of the Persian Gulf. The highest vegetation coverage belonged to the riparian vegetation along the Mond River, which represents the northern boundary of the protected area. The location of vegetation types was studied on the separate soil and habitat diversity maps of the study area, which helped in final refinements of the vegetation map produced.

Dynamics of the Antarctic Circumpolar Current as seen by GRACE (Invited)

NASA Astrophysics Data System (ADS)

Thomas, M.; Dobslaw, H.; Bergmann, I.

2010-12-01

The Antarctic Circumpolar Current, being the strongest and longest ocean current on Earth, connects the three great ocean basins and contributes substantially to the global re-distribution of water masses, with a significant impact on global climate. Observational coverage from in-situ measurements is sparse due to the harsh environmental conditions, and satellite altimetry does not capture the full extent of the current due to seasonal sea-ice coverage. Ocean bottom pressure variations as sensed with the satellite gravity mission GRACE provide a promising way to broaden our observational basis. Besides monthly mean gravity fields that provide ocean bottom pressure variations averaged over 30 days, several alternative GRACE products with higher temporal resolution have been developed during the most recent years. These include 10-day solutions from GRGS Toulouse, weekly solutions from the GFZ Potsdam as well as constrained daily solutions from the University of Bonn which have been obtained by means of a Kalman filtering approach. In this presentation, ocean bottom pressure derived from these alternative GRACE releases will be contrasted against both in-situ observations and output from a numerical ocean model, highlighting the additional information contained in these GRACE solutions with respect to the standard monthly fields. By means of statistical analyses of ocean bottom pressure variations and barotropic transports it will be demonstrated how these new GRACE releases are contributing to our understanding of this highly dynamic great ocean conveyor.

LGBT health and vaccinations: Findings from a community health survey of Lexington-Fayette County, Kentucky, USA.

PubMed

Jones, Jeff; Poole, Asheley; Lasley-Bibbs, Vivian; Johnson, Mark

2016-04-07

Data on adult immunization coverage at the state level and for LGBT Americans in particular are sparse. This study reports the results of a 2012 Lexington-Fayette County, Kentucky, community health assessment's results asking about eight adult vaccinations among 218 lesbian, gay, bisexual, and transgendered (LGBT) respondents. Researchers collected data using an online survey distributed through LGBT social media, posters, and LGBT print media. The LGBT sample largely matches the demographics of the county as a whole except this group reports higher level of education and fewer uninsured individuals. Among LGBT respondents, immunization prevalence reaches 68.0% (annual Influenza), 65.7% (Hepatitis B), 58.8% (Chickenpox/Varicella), 55.9% (Hepatitis A), 41.2% (Smallpox), and 25.8% (Pneumonia). Among respondents who are currently within the recommended 19-26 years age range for the Human Papillomavirus (HPV) vaccine, the LGBT females are less likely to report receiving the vaccine (15.4%) compared to the national coverage percentage of 34.5%. Males, however, are more likely to have received the vaccine (10.3%) than the national percentage of 2.3%. The small number of LGBT seniors in the study report a much higher prevalence of the Shingles (Herpes Zoster) vaccines than for U.S. seniors 60 and older (71.4% compared to 20.1% nationally). LGBT respondents report higher percentages of adult vaccination. Copyright © 2016 Elsevier Ltd. All rights reserved.

Global Seabed Materials and Habitats Mapped: The Computational Methods

NASA Astrophysics Data System (ADS)

Jenkins, C. J.

2016-02-01

What the seabed is made of has proven difficult to map on the scale of whole ocean-basins. Direct sampling and observation can be augmented with proxy-parameter methods such as acoustics. Both avenues are essential to obtain enough detail and coverage, and also to validate the mapping methods. We focus on the direct observations such as samplings, photo and video, probes, diver and sub reports, and surveyed features. These are often in word-descriptive form: over 85% of the records for site materials are in this form, whether as sample/view descriptions or classifications, or described parameters such as consolidation, color, odor, structures and components. Descriptions are absolutely necessary for unusual materials and for processes - in other words, for research. This project dbSEABED not only has the largest collection of seafloor materials data worldwide, but it uses advanced computing math to obtain the best possible coverages and detail. Included in those techniques are linguistic text analysis (e.g., Natural Language Processing, NLP), fuzzy set theory (FST), and machine learning (ML, e.g., Random Forest). These techniques allow efficient and accurate import of huge datasets, thereby optimizing the data that exists. They merge quantitative and qualitative types of data for rich parameter sets, and extrapolate where the data are sparse for best map production. The dbSEABED data resources are now very widely used worldwide in oceanographic research, environmental management, the geosciences, engineering and survey.

Sparse and optimal acquisition design for diffusion MRI and beyond

PubMed Central

Koay, Cheng Guan; Özarslan, Evren; Johnson, Kevin M.; Meyerand, M. Elizabeth

2012-01-01

Purpose: Diffusion magnetic resonance imaging (MRI) in combination with functional MRI promises a whole new vista for scientists to investigate noninvasively the structural and functional connectivity of the human brain—the human connectome, which had heretofore been out of reach. As with other imaging modalities, diffusion MRI data are inherently noisy and its acquisition time-consuming. Further, a faithful representation of the human connectome that can serve as a predictive model requires a robust and accurate data-analytic pipeline. The focus of this paper is on one of the key segments of this pipeline—in particular, the development of a sparse and optimal acquisition (SOA) design for diffusion MRI multiple-shell acquisition and beyond. Methods: The authors propose a novel optimality criterion for sparse multiple-shell acquisition and quasimultiple-shell designs in diffusion MRI and a novel and effective semistochastic and moderately greedy combinatorial search strategy with simulated annealing to locate the optimum design or configuration. The goal of the optimality criteria is threefold: first, to maximize uniformity of the diffusion measurements in each shell, which is equivalent to maximal incoherence in angular measurements; second, to maximize coverage of the diffusion measurements around each radial line to achieve maximal incoherence in radial measurements for multiple-shell acquisition; and finally, to ensure maximum uniformity of diffusion measurement directions in the limiting case when all the shells are coincidental as in the case of a single-shell acquisition. The approach taken in evaluating the stability of various acquisition designs is based on the condition number and the A-optimal measure of the design matrix. Results: Even though the number of distinct configurations for a given set of diffusion gradient directions is very large in general—e.g., in the order of 10232 for a set of 144 diffusion gradient directions, the proposed search strategy was found to be effective in finding the optimum configuration. It was found that the square design is the most robust (i.e., with stable condition numbers and A-optimal measures under varying experimental conditions) among many other possible designs of the same sample size. Under the same performance evaluation, the square design was found to be more robust than the widely used sampling schemes similar to that of 3D radial MRI and of diffusion spectrum imaging (DSI). Conclusions: A novel optimality criterion for sparse multiple-shell acquisition and quasimultiple-shell designs in diffusion MRI and an effective search strategy for finding the best configuration have been developed. The results are very promising, interesting, and practical for diffusion MRI acquisitions. PMID:22559620

7 CFR 1493.60 - Payment guarantee.

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2013-01-01

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7 CFR 1493.60 - Payment guarantee.

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... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier Credit Guarantee Program Operations § 1493.450 Payment guarantee. (a) CCC's obligation. The payment guarantee will provide that CCC agrees to pay the exporter or the exporter's assignee an amount not to exceed the guaranteed...

Quality maternity care for every woman, everywhere: a call to action.

PubMed

Koblinsky, Marjorie; Moyer, Cheryl A; Calvert, Clara; Campbell, James; Campbell, Oona M R; Feigl, Andrea B; Graham, Wendy J; Hatt, Laurel; Hodgins, Steve; Matthews, Zoe; McDougall, Lori; Moran, Allisyn C; Nandakumar, Allyala K; Langer, Ana

2016-11-05

To improve maternal health requires action to ensure quality maternal health care for all women and girls, and to guarantee access to care for those outside the system. In this paper, we highlight some of the most pressing issues in maternal health and ask: what steps can be taken in the next 5 years to catalyse action toward achieving the Sustainable Development Goal target of less than 70 maternal deaths per 100 000 livebirths by 2030, with no single country exceeding 140? What steps can be taken to ensure that high-quality maternal health care is prioritised for every woman and girl everywhere? We call on all stakeholders to work together in securing a healthy, prosperous future for all women. National and local governments must be supported by development partners, civil society, and the private sector in leading efforts to improve maternal-perinatal health. This effort means dedicating needed policies and resources, and sustaining implementation to address the many factors influencing maternal health-care provision and use. Five priority actions emerge for all partners: prioritise quality maternal health services that respond to the local specificities of need, and meet emerging challenges; promote equity through universal coverage of quality maternal health services, including for the most vulnerable women; increase the resilience and strength of health systems by optimising the health workforce, and improve facility capability; guarantee sustainable finances for maternal-perinatal health; and accelerate progress through evidence, advocacy, and accountability. Copyright © 2016 Elsevier Ltd. All rights reserved.

Pan-Arctic sea ice-algal chl a biomass and suitable habitat are largely underestimated for multiyear ice.

PubMed

Lange, Benjamin A; Flores, Hauke; Michel, Christine; Beckers, Justin F; Bublitz, Anne; Casey, John Alec; Castellani, Giulia; Hatam, Ido; Reppchen, Anke; Rudolph, Svenja A; Haas, Christian

2017-11-01

There is mounting evidence that multiyear ice (MYI) is a unique component of the Arctic Ocean and may play a more important ecological role than previously assumed. This study improves our understanding of the potential of MYI as a suitable habitat for sea ice algae on a pan-Arctic scale. We sampled sea ice cores from MYI and first-year sea ice (FYI) within the Lincoln Sea during four consecutive spring seasons. This included four MYI hummocks with a mean chl a biomass of 2.0 mg/m 2 , a value significantly higher than FYI and MYI refrozen ponds. Our results support the hypothesis that MYI hummocks can host substantial ice-algal biomass and represent a reliable ice-algal habitat due to the (quasi-) permanent low-snow surface of these features. We identified an ice-algal habitat threshold value for calculated light transmittance of 0.014%. Ice classes and coverage of suitable ice-algal habitat were determined from snow and ice surveys. These ice classes and associated coverage of suitable habitat were applied to pan-Arctic CryoSat-2 snow and ice thickness data products. This habitat classification accounted for the variability of the snow and ice properties and showed an areal coverage of suitable ice-algal habitat within the MYI-covered region of 0.54 million km 2 (8.5% of total ice area). This is 27 times greater than the areal coverage of 0.02 million km 2 (0.3% of total ice area) determined using the conventional block-model classification, which assigns single-parameter values to each grid cell and does not account for subgrid cell variability. This emphasizes the importance of accounting for variable snow and ice conditions in all sea ice studies. Furthermore, our results indicate the loss of MYI will also mean the loss of reliable ice-algal habitat during spring when food is sparse and many organisms depend on ice-algae. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Full-Coverage High-Resolution Daily PM(sub 2.5) Estimation using MAIAC AOD in the Yangtze River Delta of China

NASA Technical Reports Server (NTRS)

Xiao, Qingyang; Wang, Yujie; Chang, Howard H.; Meng, Xia; Geng, Guannan; Lyapustin, Alexei Ivanovich; Liu, Yang

2017-01-01

Satellite aerosol optical depth (AOD) has been used to assess population exposure to fine particulate matter (PM (sub 2.5)). The emerging high-resolution satellite aerosol product, Multi-Angle Implementation of Atmospheric Correction(MAIAC), provides a valuable opportunity to characterize local-scale PM(sub 2.5) at 1-km resolution. However, non-random missing AOD due to cloud snow cover or high surface reflectance makes this task challenging. Previous studies filled the data gap by spatially interpolating neighboring PM(sub 2.5) measurements or predictions. This strategy ignored the effect of cloud cover on aerosol loadings and has been shown to exhibit poor performance when monitoring stations are sparse or when there is seasonal large-scale missngness. Using the Yangtze River Delta of China as an example, we present a Multiple Imputation (MI) method that combines the MAIAC high-resolution satellite retrievals with chemical transport model (CTM) simulations to fill missing AOD. A two-stage statistical model driven by gap-filled AOD, meteorology and land use information was then fitted to estimate daily ground PM(sub 2.5) concentrations in 2013 and 2014 at 1 km resolution with complete coverage in space and time. The daily MI models have an average R(exp 2) of 0.77, with an inter-quartile range of 0.71 to 0.82 across days. The overall Ml model 10-fold cross-validation R(exp 2) (root mean square error) were 0.81 (25 gm(exp 3)) and 0.73 (18 gm(exp 3)) for year 2013 and 2014, respectively. Predictions with only observational AOD or only imputed AOD showed similar accuracy.Comparing with previous gap-filling methods, our MI method presented in this study performed bette rwith higher coverage, higher accuracy, and the ability to fill missing PM(sub 2.5) predictions without ground PM(sub 2.5) measurements. This method can provide reliable PM(sub 2.5)predictions with complete coverage that can reduce biasin exposure assessment in air pollution and health studies.

Water-resources data network evaluation for Monterey County, California; Phase 2, northern and coastal areas of Monterey County

USGS Publications Warehouse

Templin, W.E.; Smith, P.E.; DeBortoli, M.L.; Schluter, R.C.

1995-01-01

This report presents an evaluation of water- resources data-collection networks in the northern and coastal areas of Monterey County, California. This evaluation was done by the U.S. Geological Survey in cooperation with the Monterey County Flood Control and Water Conservation District to evaluate precipitation, surface water, and ground water monitoring networks. This report describes existing monitoring networks in the study areas and areas where possible additional data-collection is needed. During this study, 106 precipitation-quantity gages were identified, of which 84 were active; however, no precipitation-quality gages were identified in the study areas. The precipitaion-quantity gages were concentrated in the Monterey Peninsula and the northern part of the county. If the number of gages in these areas were reduced, coverage would still be adequate to meet most objectives; however, additional gages could improve coverage in the Tularcitos Creek basin and in the coastal areas south of Carmel to the county boundary. If collection of precipitation data were expanded to include monitoring precipitation quality, this expanded monitoring also could include monitoring precipitation for acid rain and pesticides. Eleven continuous streamflow-gaging stations were identified during this study, of which seven were active. To meet the objectives of the streamflow networks outlined in this report, the seven active stations would need to be continued, four stations would need to be reactivated, and an additional six streamflow-gaging stations would need to be added. Eleven stations that routinely were sampled for chemical constituents were identified in the study areas. Surface water in the lower Big Sur River basin was sampled annually for total coli- form and fecal coliform bacteria, and the Big Sur River was sampled monthly at 16 stations for these bacteria. Routine sampling for chemical constituents also was done in the Big Sur River basin. The Monterey County Flood Control and Water Conservation District maintained three networks in the study areas to measure ground-water levels: (1) the summer network, (2) the monthly network, and (3) the annual autumn network. The California American Water Company also did some ground-water-level monitoring in these areas. Well coverage for ground-water monitoring was dense in the seawater-intrusion area north of Moss Landing (possibly because of multiple overlying aquifers), but sparse in other parts of the study areas. During the study, 44 sections were identified as not monitored for ground-water levels. In an ideal ground-water-level network, wells would be evenly spaced, except where local conditions or correlations of wells make monitoring unnecessary. A total of 384 wells that monitor ground-water levels and/or ground-water quality were identified during this study. The Monterey County Flood Control and Water Conservation District sampled ground-water quality monthly during the irrigation season to monitor seawater intrusion. Once each year (during the summer), the wells in this network were monitored for chlorides, specific conductance, and nitrates. Additional samples were collected from each well once every 5 years for complete mineral analysis. The California Department of Health Services, the California American Water Company, the U.S. Army Health Service at Ford Ord, and the Monterey Peninsula Water Management District also monitored ground-water quality in wells in the study areas. Well coverage for the ground-water- quality networks was dense in the seawater- intrusion area north of Moss Landing, but sparse in the rest of the study areas. During this study, 54 sections were identified as not monitored for water quality.

Developing a regional retrospective ensemble precipitation dataset for watershed hydrology modeling, Idaho, USA

NASA Astrophysics Data System (ADS)

Flores, A. N.; Smith, K.; LaPorte, P.

2011-12-01

Applications like flood forecasting, military trafficability assessment, and slope stability analysis necessitate the use of models capable of resolving hydrologic states and fluxes at spatial scales of hillslopes (e.g., 10s to 100s m). These models typically require precipitation forcings at spatial scales of kilometers or better and time intervals of hours. Yet in especially rugged terrain that typifies much of the Western US and throughout much of the developing world, precipitation data at these spatiotemporal resolutions is difficult to come by. Ground-based weather radars have significant problems in high-relief settings and are sparsely located, leaving significant gaps in coverage and high uncertainties. Precipitation gages provide accurate data at points but are very sparsely located and their placement is often not representative, yielding significant coverage gaps in a spatial and physiographic sense. Numerical weather prediction efforts have made precipitation data, including critically important information on precipitation phase, available globally and in near real-time. However, these datasets present watershed modelers with two problems: (1) spatial scales of many of these datasets are tens of kilometers or coarser, (2) numerical weather models used to generate these datasets include a land surface parameterization that in some circumstances can significantly affect precipitation predictions. We report on the development of a regional precipitation dataset for Idaho that leverages: (1) a dataset derived from a numerical weather prediction model, (2) gages within Idaho that report hourly precipitation data, and (3) a long-term precipitation climatology dataset. Hourly precipitation estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA) are stochastically downscaled using a hybrid orographic and statistical model from their native resolution (1/2 x 2/3 degrees) to a resolution of approximately 1 km. Downscaled precipitation realizations are conditioned on hourly observations from reporting gages and then conditioned again on the Parameter-elevation Regressions on Independent Slopes Model (PRISM) at the monthly timescale to reflect orographic precipitation trends common to watersheds of the Western US. While this methodology potentially introduces cross-pollination of errors due to the re-use of precipitation gage data, it nevertheless achieves an ensemble-based precipitation estimate and appropriate measures of uncertainty at a spatiotemporal resolution appropriate for watershed modeling.

7 CFR 1720.9 - Guarantee Agreement.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 11 2014-01-01 2014-01-01 false Guarantee Agreement. 1720.9 Section 1720.9... Agreement. (a) The guaranteed lender will be required to sign a guarantee agreement with the Secretary... bonds. (b) The guaranteed bonds shall refer to the guarantee agreement as controlling the terms of the...

7 CFR 1710.52 - Loan guarantees.

Code of Federal Regulations, 2010 CFR

2010-01-01

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13 CFR 400.203 - Guarantee percentage.

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2012-01-01

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13 CFR 400.208 - Issuance of the Guarantee.

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2014-01-01

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13 CFR 400.208 - Issuance of the Guarantee.

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2010-01-01

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13 CFR 400.208 - Issuance of the Guarantee.

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2013-01-01

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13 CFR 400.208 - Issuance of the Guarantee.

Code of Federal Regulations, 2011 CFR

2011-01-01

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13 CFR 400.203 - Guarantee percentage.

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2010-01-01

... Section 400.203 Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM Steel Guarantee Loans § 400.203 Guarantee percentage. A guarantee issued by the Board may not exceed 85 percent of the amount of the principal of a loan to a Qualified Steel Company...

13 CFR 400.203 - Guarantee percentage.

Code of Federal Regulations, 2014 CFR

2014-01-01

... Section 400.203 Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM Steel Guarantee Loans § 400.203 Guarantee percentage. A guarantee issued by the Board may not exceed 85 percent of the amount of the principal of a loan to a Qualified Steel Company...

13 CFR 400.208 - Issuance of the Guarantee.

Code of Federal Regulations, 2012 CFR

2012-01-01

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13 CFR 400.203 - Guarantee percentage.

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2011-01-01

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A note on the blind deconvolution of multiple sparse signals from unknown subspaces

NASA Astrophysics Data System (ADS)

Cosse, Augustin

2017-08-01

This note studies the recovery of multiple sparse signals, xn ∈ ℝL, n = 1, . . . , N, from the knowledge of their convolution with an unknown point spread function h ∈ ℝL. When the point spread function is known to be nonzero, |h[k]| > 0, this blind deconvolution problem can be relaxed into a linear, ill-posed inverse problem in the vector concatenating the unknown inputs xn together with the inverse of the filter, d ∈ ℝL where d[k] := 1/h[k]. When prior information is given on the input subspaces, the resulting overdetermined linear system can be solved efficiently via least squares (see Ling et al. 20161). When no information is given on those subspaces, and the inputs are only known to be sparse, it still remains possible to recover these inputs along with the filter by considering an additional l1 penalty. This note certifies exact recovery of both the unknown PSF and unknown sparse inputs, from the knowledge of their convolutions, as soon as the number of inputs N and the dimension of each input, L , satisfy L ≳ N and N ≳ T2max, up to log factors. Here Tmax = maxn{Tn} and Tn, n = 1, . . . , N denote the supports of the inputs xn. Our proof system combines the recent results on blind deconvolution via least squares to certify invertibility of the linear map encoding the convolutions, with the construction of a dual certificate following the structure first suggested in Candés et al. 2007.2 Unlike in these papers, however, it is not possible to rely on the norm ||(A*TAT)-1|| to certify recovery. We instead use a combination of the Schur Complement and Neumann series to compute an expression for the inverse (A*TAT)-1. Given this expression, it is possible to show that the poorly scaled blocks in (A*TAT)-1 are multiplied by the better scaled ones or vanish in the construction of the certificate. Recovery is certified with high probablility on the choice of the supports and distribution of the signs of each input xn on the support. The paper follows the line of previous work by Wang et al. 20163 where the authors guarantee recovery for subgaussian × Bernoulli inputs satisfying 𝔼xn|k| ∈ [1/10, 1] as soon as N ≳ L. Examples of applications include seismic imaging with unknown source or marine seismic data deghosting, magnetic resonance autocalibration or multiple channel estimation in communication. Numerical experiments are provided along with a discussion on the sample complexity tightness.

Investigation of Unsteady Pressure-Sensitive Paint (uPSP) and a Dynamic Loads Balance to Predict Launch Vehicle Buffet Environments

NASA Technical Reports Server (NTRS)

Schuster, David M.; Panda, Jayanta; Ross, James C.; Roozeboom, Nettie H.; Burnside, Nathan J.; Ngo, Christina L.; Kumagai, Hiro; Sellers, Marvin; Powell, Jessica M.; Sekula, Martin K.;

Validation Of TRMM For Hazard Assessment In The Remote Context Of Tropical Africa

NASA Astrophysics Data System (ADS)

Monsieurs, E.; Kirschbaum, D.; Tan, J.; Jacobs, L.; Kervyn, M.; Demoulin, A.; Dewitte, O.

2017-12-01

Accurate rainfall data is fundamental for understanding and mitigating the disastrous effects of many rainfall-triggered hazards, especially when one considers the challenges arising from climate change and rainfall variability. In tropical Africa in particular, the sparse operational rainfall gauging network hampers the ability to understand these hazards. Satellite rainfall estimates (SRE) can therefore be of great value. Yet, rigorous validation is required to identify the uncertainties when using SRE for hazard applications. We evaluated the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) 3B42 Research Derived Daily Product from 1998 to 2017, at 0.25° x 0.25° spatial and 24 h temporal resolution. The validation was done over the western branch of the East African Rift, with the perspective of regional landslide hazard assessment in mind. Even though we collected an unprecedented dataset of 47 gauges with a minimum temporal resolution of 24 h, the sparse and heterogeneous temporal coverage in a region with high rainfall variability poses challenges for validation. In addition, the discrepancy between local-scale gauge data and spatially averaged ( 775 km²) TMPA data in the context of local convective storms and orographic rainfall is a crucial source of uncertainty. We adopted a flexible framework for SRE validation that fosters explorative research in a remote context. Results show that TMPA performs reasonably well during the rainy seasons for rainfall intensities <20 mm/day. TMPA systematically underestimates rainfall, but most problematic is the decreasing probability of detection of high intensity rainfalls. We suggest that landslide hazard might be efficiently assessed if we take account of the systematic biases in TMPA data and determine rainfall thresholds modulated by controls on, and uncertainties of, TMPA revealed in this study. Moreover, it is found relevant in mapping regional-scale rainfall-triggered hazards that are in any case poorly covered by the sparse available gauges. We anticipate validation of TMPA's successor (Integrated Multi-satellitE Retrievals for Global Precipitation Measurement; 10 km × 10 km, half-hourly) using the proposed framework, as soon as this product will be available in early 2018 for the 1998-present period.

Sparse Matrices in MATLAB: Design and Implementation

NASA Technical Reports Server (NTRS)

Gilbert, John R.; Moler, Cleve; Schreiber, Robert

1992-01-01

The matrix computation language and environment MATLAB is extended to include sparse matrix storage and operations. The only change to the outward appearance of the MATLAB language is a pair of commands to create full or sparse matrices. Nearly all the operations of MATLAB now apply equally to full or sparse matrices, without any explicit action by the user. The sparse data structure represents a matrix in space proportional to the number of nonzero entries, and most of the operations compute sparse results in time proportional to the number of arithmetic operations on nonzeros.

Short report: assessing field vaccine efficacy for measles in famine-affected rural Ethiopia.

PubMed

Talley, Leisel; Salama, Peter

2003-05-01

Measles is a major cause of mortality in complex emergencies. Both high vaccination coverage and vaccine efficacy are required to prevent major epidemics of measles in such situations. Evaluation of field vaccine efficacy is a critical but underutilized component of program monitoring in emergencies, and is particularly important in rural areas where the integrity of the cold chain is difficult to guarantee. In July 2000, we evaluated the field vaccine efficacy for measles vaccination by comparing the incidence of cases in vaccinated and unvaccinated groups during a two-stage cluster survey of 563 children in Ethiopia. Approximately 30% of the measles cases occurred in vaccinated children. Estimated field vaccine efficacy for measles was 66.9% in children 9-36 months old. The finding of a field vaccine efficacy for measles less than 80% warrants formal assessment of measles vaccine efficacy, particularly in famine emergencies where measles is associated with a high case fatality rate.

Impact of government regulation on health care technology

NASA Astrophysics Data System (ADS)

Berkowitz, Robert D.

1994-12-01

Increased government regulation of the medical device industry produces higher expenses, a longer time to return investment capital, and greater uncertainty. As a result there are fewer new ventures and reduced efforts to develop new technology in established companies. The current federal regulatory framework has shifted from monitoring the product to monitoring the process. The inability to reach perfect performance in such a regulated environment subject to continuous and fluid interpretation guarantees non-compliance and growing ethical tension. Without new medical technology, we may be unable to maintain quality medical coverage in the face of rising demand. The author proposes risk assessment to set regulatory priorities; the conversion of a national weapons lab to a national device testing lab; the establishment of device standards and the monitoring of in-use performance against these standards; and the education of patients and users as to the results of these examinations.

Dental Care Presents The Highest Level Of Financial Barriers, Compared To Other Types Of Health Care Services.

PubMed

Vujicic, Marko; Buchmueller, Thomas; Klein, Rachel

2016-12-01

The Affordable Care Act is improving access to and the affordability of a wide range of health care services. While dental care for children is part of the law's essential health benefits and state Medicaid programs must cover it, coverage of dental care for adults is not guaranteed. As a result, even with the recent health insurance expansion, many Americans face financial barriers to receiving dental care that lead to unmet oral health needs. Using data from the 2014 National Health Interview Survey, we analyzed financial barriers to a wide range of health care services. We found that irrespective of age, income level, and type of insurance, more people reported financial barriers to receiving dental care, compared to any other type of health care. We discuss policy options to address financial barriers to dental care, particularly for adults. Project HOPE—The People-to-People Health Foundation, Inc.

Development of U.S. Government General Technical Requirements for UAS Flight Safety Systems Utilizing the Iridium Satellite Constellation

NASA Technical Reports Server (NTRS)

Murray, Jennifer; Birr, Richard

2010-01-01

This slide presentation reviews the development of technical requirements for Unmanned Aircraft Systems (UAS) utilization of the Iridium Satellite Constellation to provide flight safety. The Federal Aviation Authority (FAA) required an over-the-horizon communication standard to guarantee flight safety before permitting widespread UAS flights in the National Air Space (NAS). This is important to ensure reliable control of UASs during loss-link and over-the-horizon scenarios. The core requirement was to utilize a satellite system to send GPS tracking data and other telemetry from a flight vehicle down to the ground. Iridium was chosen as the system because it is one of the only true satellite systems that has world wide coverage, and the service has a highly reliable link margin. The Iridium system, the flight modems, and the test flight are described.

Constraining Both the Star-Formation History and Metal-Enrichment History of Galaxies

NASA Astrophysics Data System (ADS)

Heap, Sara

2005-07-01

Using 380 stellar spectra from Hubble's Next Generation Spectral Library {NGSL; PI=Michael Gregg; GO 9088, 9786} incorporated in our stellar population synthesis code {Bruzual & Charlot 2003}, we propose to constrain simultaneously the star-formation history and mean age, stellar metallicity and mass of galaxies over a wide redshift interval {z= 0 -2}. The main advantages of the NGSL are the high-quality spectrophotometry {S/N >50} and broad wavelength coverage {2000-10, 000 Ang} of the STIS spectra. The NGSL enables mid-UV as well as optical spectral indices to be used, thereby increasing the redshift interval of their application. It also guarantees consistency in treating low- and high-redshift galaxies, since the same stars are used as spectral templates. To realize the full potential of the NGSL, however, will require significant custom data-processing, calibration, and evaluation of the STIS data.

EEOC sues freight company for inducing worker with HIV to quit. Equal Employment Opportunity Commission.

PubMed

1998-04-17

The Equal Employment Opportunity Commission (EEOC) sued a Japanese freight company, Nippon Express USA, for putting [name removed] into a do-nothing job and forcing him to quit. [Name removed] revealed his HIV status to a supervisor in 1990 while working as a trainer and customer troubleshooter. When his management changed shortly afterwards, he was transferred from Chicago to Indianapolis, presumably for a promotion. However, his responsibilities were reduced, his telephone and computer were taken away from him, and co-workers were ordered not to speak to him. Following surgery, a supervisor told [name removed] that his appearance was causing problems. The lawsuit was filed under the Americans with Disabilities Act (ADA) and seeks unspecified damages, training programs for managers and staff in dealing with HIV-positive employees, and guaranteed health care coverage for the rest of [name removed]'s life.

Model Checking Artificial Intelligence Based Planners: Even the Best Laid Plans Must Be Verified

NASA Technical Reports Server (NTRS)

Smith, Margaret H.; Holzmann, Gerard J.; Cucullu, Gordon C., III; Smith, Benjamin D.

2005-01-01

Automated planning systems (APS) are gaining acceptance for use on NASA missions as evidenced by APS flown On missions such as Orbiter and Deep Space 1 both of which were commanded by onboard planning systems. The planning system takes high level goals and expands them onboard into a detailed of action fiat the spacecraft executes. The system must be verified to ensure that the automatically generated plans achieve the goals as expected and do not generate actions that would harm the spacecraft or mission. These systems are typically tested using empirical methods. Formal methods, such as model checking, offer exhaustive or measurable test coverage which leads to much greater confidence in correctness. This paper describes a formal method based on the SPIN model checker. This method guarantees that possible plans meet certain desirable properties. We express the input model in Promela, the language of SPIN and express the properties of desirable plans formally.

Public Financing Of The Medicare Program Will Make Its Uniform Structure Increasingly Costly To Sustain

PubMed Central

Baicker, Katherine; Shepard, Mark; Skinner, Jonathan

2013-01-01

The US Medicare program consumes an ever-rising share of the federal budget. Although this public spending can produce health and social benefits, raising taxes to finance it comes at the cost of slower economic growth. In this article we describe a model incorporating the benefits of public programs and the cost of tax financing. The model implies that the “one-size-fits-all” Medicare program, with everyone covered by the same insurance policy, will be increasingly difficult to sustain. We show that a Medicare program with guaranteed basic benefits and the option to purchase additional coverage could lead to more unequal health spending but slower growth in taxation, greater overall well-being, and more rapid growth of gross domestic product. Our framework highlights the key trade-offs between Medicare spending and economic prosperity. PMID:23650321

Storage of sparse files using parallel log-structured file system

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

Bent, John M.; Faibish, Sorin; Grider, Gary

A sparse file is stored without holes by storing a data portion of the sparse file using a parallel log-structured file system; and generating an index entry for the data portion, the index entry comprising a logical offset, physical offset and length of the data portion. The holes can be restored to the sparse file upon a reading of the sparse file. The data portion can be stored at a logical end of the sparse file. Additional storage efficiency can optionally be achieved by (i) detecting a write pattern for a plurality of the data portions and generating a singlemore » patterned index entry for the plurality of the patterned data portions; and/or (ii) storing the patterned index entries for a plurality of the sparse files in a single directory, wherein each entry in the single directory comprises an identifier of a corresponding sparse file.« less

Idaho judge rebuffs abortion funding rule.

PubMed

1994-07-22

In a 3-page ruling on July 11, Ada County District Court Judge Duff McKee chastised Idaho officials for issuing new Medicaid regulations limiting abortion coverage to the same extent as an earlier rule found unconstitutional by the court. Judge McKee opened his order by calling the new rule "a blatant and ill-concealed attempt to maintain the status quo." Invalidating the prohibition on Medicaid coverage for low-income women's abortions except when two physicians certify that continued pregnancy will result in "grave, long-lasting physical damage," Judge McKee reiterated his holding that such a measure violates the Idaho Constitution. On February 1, Judge McKee held that the state Constitution provides broader protection for the right of privacy than the federal Constitution. The court indicated that the initial Medicaid regulation conflicted with a constitutional guarantee of neutrality, which requires Idaho to be evenhanded when subsidizing the exercise of a constitutionally protected right. Plaintiffs in Roe v. Harris--represented by ACLU Reproductive Freedom Project's Louise Melling, Planned Parenthood Federation's Carole Chervin, and cooperating attorney Newal Squyres--challenged the new regulation in early July. The lawsuit was originally filed in August of 1993. An Idaho statute, which was challenged but upheld, provides Medicaid funding when two physicians certify that it is necessary to save the woman's life or health, or when a court determines the pregnancy resulted from rape or incest. full text

Learning Sparse Feature Representations using Probabilistic Quadtrees and Deep Belief Nets

DTIC Science & Technology

2015-04-24

Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Learning sparse feature representations is a useful instru- ment for solving an...novel framework for the classifi cation of handwritten digits that learns sparse representations using probabilistic quadtrees and Deep Belief Nets... Learning Sparse Feature Representations usingProbabilistic Quadtrees and Deep Belief Nets Report Title Learning sparse feature representations is a useful

User's Manual for PCSMS (Parallel Complex Sparse Matrix Solver). Version 1.

NASA Technical Reports Server (NTRS)

Reddy, C. J.

2000-01-01

PCSMS (Parallel Complex Sparse Matrix Solver) is a computer code written to make use of the existing real sparse direct solvers to solve complex, sparse matrix linear equations. PCSMS converts complex matrices into real matrices and use real, sparse direct matrix solvers to factor and solve the real matrices. The solution vector is reconverted to complex numbers. Though, this utility is written for Silicon Graphics (SGI) real sparse matrix solution routines, it is general in nature and can be easily modified to work with any real sparse matrix solver. The User's Manual is written to make the user acquainted with the installation and operation of the code. Driver routines are given to aid the users to integrate PCSMS routines in their own codes.

13 CFR 400.212 - Guarantee.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Steel Guarantee Loans § 400.212 Guarantee. The Board shall adopt a form of Guarantee to be used by the... of the form of Guarantee must be approved and adopted by the Board. [65 FR 70294, Nov. 22, 2000] ...

Local structure preserving sparse coding for infrared target recognition

PubMed Central

Han, Jing; Yue, Jiang; Zhang, Yi; Bai, Lianfa

2017-01-01

Sparse coding performs well in image classification. However, robust target recognition requires a lot of comprehensive template images and the sparse learning process is complex. We incorporate sparsity into a template matching concept to construct a local sparse structure matching (LSSM) model for general infrared target recognition. A local structure preserving sparse coding (LSPSc) formulation is proposed to simultaneously preserve the local sparse and structural information of objects. By adding a spatial local structure constraint into the classical sparse coding algorithm, LSPSc can improve the stability of sparse representation for targets and inhibit background interference in infrared images. Furthermore, a kernel LSPSc (K-LSPSc) formulation is proposed, which extends LSPSc to the kernel space to weaken the influence of the linear structure constraint in nonlinear natural data. Because of the anti-interference and fault-tolerant capabilities, both LSPSc- and K-LSPSc-based LSSM can implement target identification based on a simple template set, which just needs several images containing enough local sparse structures to learn a sufficient sparse structure dictionary of a target class. Specifically, this LSSM approach has stable performance in the target detection with scene, shape and occlusions variations. High performance is demonstrated on several datasets, indicating robust infrared target recognition in diverse environments and imaging conditions. PMID:28323824

Variable is better than invariable: sparse VSS-NLMS algorithms with application to adaptive MIMO channel estimation.

PubMed

Gui, Guan; Chen, Zhang-xin; Xu, Li; Wan, Qun; Huang, Jiyan; Adachi, Fumiyuki

2014-01-01

Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparse invariable step-size normalized least mean square (ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stable sparse variable step-size NLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics.

Variable Is Better Than Invariable: Sparse VSS-NLMS Algorithms with Application to Adaptive MIMO Channel Estimation

PubMed Central

Gui, Guan; Chen, Zhang-xin; Xu, Li; Wan, Qun; Huang, Jiyan; Adachi, Fumiyuki

2014-01-01

Channel estimation problem is one of the key technical issues in sparse frequency-selective fading multiple-input multiple-output (MIMO) communication systems using orthogonal frequency division multiplexing (OFDM) scheme. To estimate sparse MIMO channels, sparse invariable step-size normalized least mean square (ISS-NLMS) algorithms were applied to adaptive sparse channel estimation (ACSE). It is well known that step-size is a critical parameter which controls three aspects: algorithm stability, estimation performance, and computational cost. However, traditional methods are vulnerable to cause estimation performance loss because ISS cannot balance the three aspects simultaneously. In this paper, we propose two stable sparse variable step-size NLMS (VSS-NLMS) algorithms to improve the accuracy of MIMO channel estimators. First, ASCE is formulated in MIMO-OFDM systems. Second, different sparse penalties are introduced to VSS-NLMS algorithm for ASCE. In addition, difference between sparse ISS-NLMS algorithms and sparse VSS-NLMS ones is explained and their lower bounds are also derived. At last, to verify the effectiveness of the proposed algorithms for ASCE, several selected simulation results are shown to prove that the proposed sparse VSS-NLMS algorithms can achieve better estimation performance than the conventional methods via mean square error (MSE) and bit error rate (BER) metrics. PMID:25089286

Universal health coverage from multiple perspectives: a synthesis of conceptual literature and global debates.

PubMed

Abiiro, Gilbert Abotisem; De Allegri, Manuela

2015-07-04

There is an emerging global consensus on the importance of universal health coverage (UHC), but no unanimity on the conceptual definition and scope of UHC, whether UHC is achievable or not, how to move towards it, common indicators for measuring its progress, and its long-term sustainability. This has resulted in various interpretations of the concept, emanating from different disciplinary perspectives. This paper discusses the various dimensions of UHC emerging from these interpretations and argues for the need to pay attention to the complex interactions across the various components of a health system in the pursuit of UHC as a legal human rights issue. The literature presents UHC as a multi-dimensional concept, operationalized in terms of universal population coverage, universal financial protection, and universal access to quality health care, anchored on the basis of health care as an international legal obligation grounded in international human rights laws. As a legal concept, UHC implies the existence of a legal framework that mandates national governments to provide health care to all residents while compelling the international community to support poor nations in implementing this right. As a humanitarian social concept, UHC aims at achieving universal population coverage by enrolling all residents into health-related social security systems and securing equitable entitlements to the benefits from the health system for all. As a health economics concept, UHC guarantees financial protection by providing a shield against the catastrophic and impoverishing consequences of out-of-pocket expenditure, through the implementation of pooled prepaid financing systems. As a public health concept, UHC has attracted several controversies regarding which services should be covered: comprehensive services vs. minimum basic package, and priority disease-specific interventions vs. primary health care. As a multi-dimensional concept, grounded in international human rights laws, the move towards UHC in LMICs requires all states to effectively recognize the right to health in their national constitutions. It also requires a human rights-focused integrated approach to health service delivery that recognizes the health system as a complex phenomenon with interlinked functional units whose effective interaction are essential to reach the equilibrium called UHC.

The Use of Sparse Direct Solver in Vector Finite Element Modeling for Calculating Two Dimensional (2-D) Magnetotelluric Responses in Transverse Electric (TE) Mode

NASA Astrophysics Data System (ADS)

Yihaa Roodhiyah, Lisa’; Tjong, Tiffany; Nurhasan; Sutarno, D.

2018-04-01

The late research, linear matrices of vector finite element in two dimensional(2-D) magnetotelluric (MT) responses modeling was solved by non-sparse direct solver in TE mode. Nevertheless, there is some weakness which have to be improved especially accuracy in the low frequency (10-3 Hz-10-5 Hz) which is not achieved yet and high cost computation in dense mesh. In this work, the solver which is used is sparse direct solver instead of non-sparse direct solverto overcome the weaknesses of solving linear matrices of vector finite element metod using non-sparse direct solver. Sparse direct solver will be advantageous in solving linear matrices of vector finite element method because of the matrix properties which is symmetrical and sparse. The validation of sparse direct solver in solving linear matrices of vector finite element has been done for a homogen half-space model and vertical contact model by analytical solution. Thevalidation result of sparse direct solver in solving linear matrices of vector finite element shows that sparse direct solver is more stable than non-sparse direct solver in computing linear problem of vector finite element method especially in low frequency. In the end, the accuracy of 2D MT responses modelling in low frequency (10-3 Hz-10-5 Hz) has been reached out under the efficient allocation memory of array and less computational time consuming.

7 CFR 2201.29 - Supplemental guarantees.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false Supplemental guarantees. 2201.29 Section 2201.29 Agriculture Regulations of the Department of Agriculture (Continued) LOCAL TELEVISION LOAN GUARANTEE BOARD LOCAL TELEVISION LOAN GUARANTEE PROGRAM-PROGRAM REGULATIONS Loan Guarantees § 2201.29 Supplemental...

7 CFR 1493.200 - General statement.

Code of Federal Regulations, 2013 CFR

2013-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Facility Guarantee Program... (CCC) Facility Guarantee Program (FGP). CCC will issue facility payment guarantees for project... so, will be incorporated by reference on the face of the facility payment guarantee issued by CCC. ...

7 CFR 1493.200 - General statement.

Code of Federal Regulations, 2012 CFR

2012-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Facility Guarantee Program... (CCC) Facility Guarantee Program (FGP). CCC will issue facility payment guarantees for project... so, will be incorporated by reference on the face of the facility payment guarantee issued by CCC. ...

7 CFR 1493.200 - General statement.

Code of Federal Regulations, 2014 CFR

2014-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Facility Guarantee Program... (CCC) Facility Guarantee Program (FGP). CCC will issue facility payment guarantees for project... so, will be incorporated by reference on the face of the facility payment guarantee issued by CCC. ...

Spatial Bayesian latent factor regression modeling of coordinate-based meta-analysis data.

PubMed

Montagna, Silvia; Wager, Tor; Barrett, Lisa Feldman; Johnson, Timothy D; Nichols, Thomas E

2018-03-01

Now over 20 years old, functional MRI (fMRI) has a large and growing literature that is best synthesised with meta-analytic tools. As most authors do not share image data, only the peak activation coordinates (foci) reported in the article are available for Coordinate-Based Meta-Analysis (CBMA). Neuroimaging meta-analysis is used to (i) identify areas of consistent activation; and (ii) build a predictive model of task type or cognitive process for new studies (reverse inference). To simultaneously address these aims, we propose a Bayesian point process hierarchical model for CBMA. We model the foci from each study as a doubly stochastic Poisson process, where the study-specific log intensity function is characterized as a linear combination of a high-dimensional basis set. A sparse representation of the intensities is guaranteed through latent factor modeling of the basis coefficients. Within our framework, it is also possible to account for the effect of study-level covariates (meta-regression), significantly expanding the capabilities of the current neuroimaging meta-analysis methods available. We apply our methodology to synthetic data and neuroimaging meta-analysis datasets. © 2017, The International Biometric Society.

7 CFR 1493.450 - Payment guarantee.

Code of Federal Regulations, 2010 CFR

2010-01-01

... OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier Credit Guarantee Program Operations § 1493.450 Payment guarantee. (a) CCC's obligation. The payment guarantee will provide that CCC agrees to pay the exporter or the exporter's assignee an amount...

7 CFR 1493.450 - Payment guarantee.

Code of Federal Regulations, 2011 CFR

2011-01-01

... OF AGRICULTURE LOANS, PURCHASES, AND OTHER OPERATIONS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier Credit Guarantee Program Operations § 1493.450 Payment guarantee. (a) CCC's obligation. The payment guarantee will provide that CCC agrees to pay the exporter or the exporter's assignee an amount...

Sparse Reconstruction Techniques in MRI: Methods, Applications, and Challenges to Clinical Adoption

PubMed Central

Yang, Alice Chieh-Yu; Kretzler, Madison; Sudarski, Sonja; Gulani, Vikas; Seiberlich, Nicole

2016-01-01

The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in Magnetic Resonance Imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be employed to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MR imaging, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold-standards, are discussed. PMID:27003227

7 CFR 2201.22 - Issuance of Guarantees.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false Issuance of Guarantees. 2201.22 Section 2201.22 Agriculture Regulations of the Department of Agriculture (Continued) LOCAL TELEVISION LOAN GUARANTEE BOARD LOCAL TELEVISION LOAN GUARANTEE PROGRAM-PROGRAM REGULATIONS Loan Guarantees § 2201.22 Issuance of...

7 CFR 2201.28 - Participation in guaranteed Loans.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false Participation in guaranteed Loans. 2201.28 Section 2201.28 Agriculture Regulations of the Department of Agriculture (Continued) LOCAL TELEVISION LOAN GUARANTEE BOARD LOCAL TELEVISION LOAN GUARANTEE PROGRAM-PROGRAM REGULATIONS Loan Guarantees § 2201.28...

26 CFR 1.817A-0 - Table of contents.

Code of Federal Regulations, 2010 CFR

2010-04-01

.... (5) Examples. (c) Applicable interest rates for equity-indexed modified guaranteed contracts... appear in section § 1.817A-1: § 1.817A-1Certain modified guaranteed contracts. (a) Definitions. (1) Modified guaranteed contract. (2) Temporary guarantee period. (3) Equity-indexed modified guaranteed...

78 FR 63158 - Information Collection; Guaranteed Farm Loan Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-23

... DEPARTMENT OF AGRICULTURE Farm Service Agency Information Collection; Guaranteed Farm Loan Program... collection associated with the Guaranteed Farm Loan Program. The amended estimate adds the merger of the information collection for the Land Contract Guarantee Program (0560-0279) into the Guaranteed Farm Loan...

Sparse gammatone signal model optimized for English speech does not match the human auditory filters.

PubMed

Strahl, Stefan; Mertins, Alfred

2008-07-18

Evidence that neurosensory systems use sparse signal representations as well as improved performance of signal processing algorithms using sparse signal models raised interest in sparse signal coding in the last years. For natural audio signals like speech and environmental sounds, gammatone atoms have been derived as expansion functions that generate a nearly optimal sparse signal model (Smith, E., Lewicki, M., 2006. Efficient auditory coding. Nature 439, 978-982). Furthermore, gammatone functions are established models for the human auditory filters. Thus far, a practical application of a sparse gammatone signal model has been prevented by the fact that deriving the sparsest representation is, in general, computationally intractable. In this paper, we applied an accelerated version of the matching pursuit algorithm for gammatone dictionaries allowing real-time and large data set applications. We show that a sparse signal model in general has advantages in audio coding and that a sparse gammatone signal model encodes speech more efficiently in terms of sparseness than a sparse modified discrete cosine transform (MDCT) signal model. We also show that the optimal gammatone parameters derived for English speech do not match the human auditory filters, suggesting for signal processing applications to derive the parameters individually for each applied signal class instead of using psychometrically derived parameters. For brain research, it means that care should be taken with directly transferring findings of optimality for technical to biological systems.

7 CFR 2201.10 - Loan amount and Guarantee percentage.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false Loan amount and Guarantee percentage. 2201.10 Section 2201.10 Agriculture Regulations of the Department of Agriculture (Continued) LOCAL TELEVISION LOAN GUARANTEE BOARD LOCAL TELEVISION LOAN GUARANTEE PROGRAM-PROGRAM REGULATIONS Loan Guarantees § 2201.10 Loan...

13 CFR 400.2 - Definitions.

Code of Federal Regulations, 2010 CFR

2010-01-01

... Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM General § 400.2 Definitions. (a) Act means the Emergency Steel Loan Guarantee Act of 1999, Chapter 1 of... institution applying for a loan guarantee under this part. (e) Board means the Emergency Steel Guarantee Loan...

13 CFR 400.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... Business Credit and Assistance EMERGENCY STEEL GUARANTEE LOAN BOARD EMERGENCY STEEL GUARANTEE LOAN PROGRAM General § 400.2 Definitions. (a) Act means the Emergency Steel Loan Guarantee Act of 1999, Chapter 1 of... institution applying for a loan guarantee under this part. (e) Board means the Emergency Steel Guarantee Loan...

22 CFR 221.11 - The Guarantee.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false The Guarantee. 221.11 Section 221.11 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.11 The Guarantee. Subject to these terms and conditions, the United States of America...

22 CFR 221.11 - The Guarantee.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false The Guarantee. 221.11 Section 221.11 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.11 The Guarantee. Subject to these terms and conditions, the United States of America...

22 CFR 221.14 - Transferability of Guarantee; Note Register.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Transferability of Guarantee; Note Register. 221.14 Section 221.14 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.14 Transferability of Guarantee; Note Register. A...

22 CFR 221.11 - The Guarantee.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false The Guarantee. 221.11 Section 221.11 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.11 The Guarantee. Subject to these terms and conditions, the United States of America...

22 CFR 221.11 - The Guarantee.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false The Guarantee. 221.11 Section 221.11 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.11 The Guarantee. Subject to these terms and conditions, the United States of America...

22 CFR 221.14 - Transferability of Guarantee; Note Register.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 22 Foreign Relations 1 2011-04-01 2011-04-01 false Transferability of Guarantee; Note Register. 221.14 Section 221.14 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.14 Transferability of Guarantee; Note Register. A...

22 CFR 221.14 - Transferability of Guarantee; Note Register.

Code of Federal Regulations, 2013 CFR

2013-04-01

... 22 Foreign Relations 1 2013-04-01 2013-04-01 false Transferability of Guarantee; Note Register. 221.14 Section 221.14 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.14 Transferability of Guarantee; Note Register. A...

22 CFR 221.14 - Transferability of Guarantee; Note Register.

Code of Federal Regulations, 2012 CFR

2012-04-01

... 22 Foreign Relations 1 2012-04-01 2012-04-01 false Transferability of Guarantee; Note Register. 221.14 Section 221.14 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.14 Transferability of Guarantee; Note Register. A...

22 CFR 221.14 - Transferability of Guarantee; Note Register.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Transferability of Guarantee; Note Register. 221.14 Section 221.14 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.14 Transferability of Guarantee; Note Register. A...

22 CFR 221.11 - The Guarantee.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false The Guarantee. 221.11 Section 221.11 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.11 The Guarantee. Subject to these terms and conditions, the United States of America...

Classification of multispectral or hyperspectral satellite imagery using clustering of sparse approximations on sparse representations in learned dictionaries obtained using efficient convolutional sparse coding

DOEpatents

Moody, Daniela; Wohlberg, Brendt

2018-01-02

An approach for land cover classification, seasonal and yearly change detection and monitoring, and identification of changes in man-made features may use a clustering of sparse approximations (CoSA) on sparse representations in learned dictionaries. The learned dictionaries may be derived using efficient convolutional sparse coding to build multispectral or hyperspectral, multiresolution dictionaries that are adapted to regional satellite image data. Sparse image representations of images over the learned dictionaries may be used to perform unsupervised k-means clustering into land cover categories. The clustering process behaves as a classifier in detecting real variability. This approach may combine spectral and spatial textural characteristics to detect geologic, vegetative, hydrologic, and man-made features, as well as changes in these features over time.

Guaranteed Student Loan Program 1981. State Agency Survey.

ERIC Educational Resources Information Center

New York State Higher Education Services Corp., Albany.

Responses to a questionnaire circulated in March 1981 are summarized. Data were gathered from all states regarding the federal Guaranteed Student Loan Program (GSL) and the state guarantee agencies on: guarantee agency organizational types; dates of GSL agreements with the Department of Education; states that guaranteed loans before GSL;…

7 CFR 1493.460 - Guarantee rates and fees.

Code of Federal Regulations, 2013 CFR

2013-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier Credit Guarantee... not be approved until the guarantee fee has been received by CCC. The exporter's check for the guarantee fee shall be made payable to CCC and mailed or delivered by courier to the office specified in the...

7 CFR 1493.460 - Guarantee rates and fees.

Code of Federal Regulations, 2010 CFR

2010-01-01

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7 CFR 1493.460 - Guarantee rates and fees.

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2011-01-01

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7 CFR 1493.460 - Guarantee rates and fees.

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2014-01-01

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7 CFR 1493.460 - Guarantee rates and fees.

Code of Federal Regulations, 2012 CFR

2012-01-01

... OF AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS CCC Supplier Credit Guarantee... not be approved until the guarantee fee has been received by CCC. The exporter's check for the guarantee fee shall be made payable to CCC and mailed or delivered by courier to the office specified in the...

Combined Targeted DNA Sequencing in Non-Small Cell Lung Cancer (NSCLC) Using UNCseq and NGScopy, and RNA Sequencing Using UNCqeR for the Detection of Genetic Aberrations in NSCLC

PubMed Central

Walter, Vonn; Patel, Nirali M.; Eberhard, David A.; Hayward, Michele C.; Salazar, Ashley H.; Jo, Heejoon; Soloway, Matthew G.; Wilkerson, Matthew D.; Parker, Joel S.; Yin, Xiaoying; Zhang, Guosheng; Siegel, Marni B.; Rosson, Gary B.; Earp, H. Shelton; Sharpless, Norman E.; Gulley, Margaret L.; Weck, Karen E.

2015-01-01

The recent FDA approval of the MiSeqDx platform provides a unique opportunity to develop targeted next generation sequencing (NGS) panels for human disease, including cancer. We have developed a scalable, targeted panel-based assay termed UNCseq, which involves a NGS panel of over 200 cancer-associated genes and a standardized downstream bioinformatics pipeline for detection of single nucleotide variations (SNV) as well as small insertions and deletions (indel). In addition, we developed a novel algorithm, NGScopy, designed for samples with sparse sequencing coverage to detect large-scale copy number variations (CNV), similar to human SNP Array 6.0 as well as small-scale intragenic CNV. Overall, we applied this assay to 100 snap-frozen lung cancer specimens lacking same-patient germline DNA (07–0120 tissue cohort) and validated our results against Sanger sequencing, SNP Array, and our recently published integrated DNA-seq/RNA-seq assay, UNCqeR, where RNA-seq of same-patient tumor specimens confirmed SNV detected by DNA-seq, if RNA-seq coverage depth was adequate. In addition, we applied the UNCseq assay on an independent lung cancer tumor tissue collection with available same-patient germline DNA (11–1115 tissue cohort) and confirmed mutations using assays performed in a CLIA-certified laboratory. We conclude that UNCseq can identify SNV, indel, and CNV in tumor specimens lacking germline DNA in a cost-efficient fashion. PMID:26076459

Southern Hemisphere Upper Thermospheric Wind Climatology

NASA Astrophysics Data System (ADS)

Dhadly, M. S.; Emmert, J. T.; Drob, D. P.

2017-12-01

This study is focused on the poorly understood large-scale upper thermospheric wind dynamics in the southern polar cap, auroral, and mid latitudes. The gaps in our understanding of the dynamic high-latitude thermosphere are largely due to the sparseness of thermospheric wind measurements. Using data from current observational facilities, it is unfeasible to construct a synoptic picture of the Southern Hemisphere upper thermospheric winds. However, enough data with wide spatial and temporal coverage have accumulated to construct a meaningful statistical analysis of winds as function of season, magnetic latitude, and magnetic local time. We use long-term data from nine ground-based stations located at different southern high latitudes and three space-based instruments. These diverse data sets possess different geometries and different spatial and solar coverage. The major challenge of the effort is to combine these disparate sources of data into a coherent picture while overcoming the sampling limitations and biases among the datasets. Our preliminary analyses show mutual biases present among some of them. We first address the biases among various data sets and then combine them in a coherent way to construct maps of neutral winds for various seasons. We then validate the fitted climatology against the observational data and compare with corresponding fits of 25 years of simulated winds from the National Center for Atmospheric Research Thermosphere-Ionosphere-Electrodynamics General Circulation Model. This study provides critical insight into magnetosphere-ionosphere-thermosphere coupling and sets a necessary benchmark for validating new observations and tuning first-principles models.

Understanding the links between humans, climate change, water and carbon and in a Corn Belt Watershed

NASA Astrophysics Data System (ADS)

Secchi, S.; Perez Lapena, B.; Teshager, A. D.; Bhattarai, M. D.; Schoof, J. T.

2014-12-01

As part of the High Latitude Proving Ground, the Geographic Information Network of Alaska (GINA) at the University of Alaska Fairbanks (UAF) receives data from the Suomi National Polar-orbiting Partnership (SNPP) satellite via direct broadcast antennas in Fairbanks, including data from the SNPP's Visible Infrared Imaging Radiometer Suite (VIIRS) instrument. These data are processed by GINA, and the resulting imagery is delivered in near real-time to the National Weather Service (NWS) in Alaska for use in weather analysis and forecasting. The VIIRS' Day-Night Band (DNB) produces what is functionally visible imagery at night and has been used extensively by operational meteorologists in Alaska, especially during the prolonged darkness of the arctic winter. The DNB has proven to be a powerful tool when combined with other observational and model data sets and has offered NWS meteorologists a more complete picture of weather processes in a region where coverage from surface-based observations is generally poor. Thanks to its high latitude, Alaska benefits from much more frequent coverage in time by polar orbiting satellites such as SNPP and its DNB channel. Also, the sparse population of Alaska and the vast stretches of ocean that surround Alaska on three sides allow meteorological and topographical signatures to be detected by the DNB with minimal interference from anthropogenic sources of light. Examples of how the DNB contributes to the NWS' forecast process in Alaska will be presented and discussed.

Kanerva's sparse distributed memory: An associative memory algorithm well-suited to the Connection Machine

NASA Technical Reports Server (NTRS)

Rogers, David

1988-01-01

The advent of the Connection Machine profoundly changes the world of supercomputers. The highly nontraditional architecture makes possible the exploration of algorithms that were impractical for standard Von Neumann architectures. Sparse distributed memory (SDM) is an example of such an algorithm. Sparse distributed memory is a particularly simple and elegant formulation for an associative memory. The foundations for sparse distributed memory are described, and some simple examples of using the memory are presented. The relationship of sparse distributed memory to three important computational systems is shown: random-access memory, neural networks, and the cerebellum of the brain. Finally, the implementation of the algorithm for sparse distributed memory on the Connection Machine is discussed.

SU-F-BRD-08: Guaranteed Epsilon-Optimal Treatment Plans with Minimum Number of Beams for SBRT Using RayStation

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

Yarmand, H; Winey, B; Craft, D

2014-06-15

Purpose: To efficiently find quality-guaranteed treatment plans with the minimum number of beams for stereotactic body radiation therapy using RayStation. Methods: For a pre-specified pool of candidate beams we use RayStation (a treatment planning software for clinical use) to identify the deliverable plan which uses all the beams with the minimum dose to organs at risk (OARs) and dose to the tumor and other structures in specified ranges. Then use the dose matrix information for the generated apertures from RayStation to solve a linear program to find the ideal plan with the same objective and constraints allowing use of allmore » beams. Finally we solve a mixed integer programming formulation of the beam angle optimization problem (BAO) with the objective of minimizing the number of beams while remaining in a predetermined epsilon-optimality of the ideal plan with respect to the dose to OARs. Since the treatment plan optimization is a multicriteria optimization problem, the planner can exploit the multicriteria optimization capability of RayStation to navigate the ideal dose distribution Pareto surface and select a plan of desired target coverage versus OARs sparing, and then use the proposed technique to reduce the number of beams while guaranteeing quality. For the numerical experiments two liver cases and one lung case with 33 non-coplanar beams are considered. Results: The ideal plan uses an impractically large number of beams. The proposed technique reduces the number of beams to the range of practical application (5 to 9 beams) while remaining in the epsilon-optimal range of 1% to 5% optimality gap. Conclusion: The proposed method can be integrated into a general algorithm for fast navigation of the ideal dose distribution Pareto surface and finding the treatment plan with the minimum number of beams, which corresponds to the delivery time, in epsilon-optimality range of the desired ideal plan. The project was supported by the Federal Share of program income earned by Massachusetts General Hospital on C06 CA059267, Proton Therapy Research and Treatment Center and partially by RaySearch Laboratories.« less

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

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

Jakeman, J.D., E-mail: jdjakem@sandia.gov; Wildey, T.

2015-01-01

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the physical discretization error and the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity of the sparse grid. Utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchicalmore » surplus based strategies. Throughout this paper we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.« less

Precession missile feature extraction using sparse component analysis of radar measurements

NASA Astrophysics Data System (ADS)

Liu, Lihua; Du, Xiaoyong; Ghogho, Mounir; Hu, Weidong; McLernon, Des

2012-12-01

According to the working mode of the ballistic missile warning radar (BMWR), the radar return from the BMWR is usually sparse. To recognize and identify the warhead, it is necessary to extract the precession frequency and the locations of the scattering centers of the missile. This article first analyzes the radar signal model of the precessing conical missile during flight and develops the sparse dictionary which is parameterized by the unknown precession frequency. Based on the sparse dictionary, the sparse signal model is then established. A nonlinear least square estimation is first applied to roughly extract the precession frequency in the sparse dictionary. Based on the time segmented radar signal, a sparse component analysis method using the orthogonal matching pursuit algorithm is then proposed to jointly estimate the precession frequency and the scattering centers of the missile. Simulation results illustrate the validity of the proposed method.

Sparse non-negative matrix factorizations via alternating non-negativity-constrained least squares for microarray data analysis.

PubMed

Kim, Hyunsoo; Park, Haesun

2007-06-15

Many practical pattern recognition problems require non-negativity constraints. For example, pixels in digital images and chemical concentrations in bioinformatics are non-negative. Sparse non-negative matrix factorizations (NMFs) are useful when the degree of sparseness in the non-negative basis matrix or the non-negative coefficient matrix in an NMF needs to be controlled in approximating high-dimensional data in a lower dimensional space. In this article, we introduce a novel formulation of sparse NMF and show how the new formulation leads to a convergent sparse NMF algorithm via alternating non-negativity-constrained least squares. We apply our sparse NMF algorithm to cancer-class discovery and gene expression data analysis and offer biological analysis of the results obtained. Our experimental results illustrate that the proposed sparse NMF algorithm often achieves better clustering performance with shorter computing time compared to other existing NMF algorithms. The software is available as supplementary material.

7 CFR 1779.73 - Replacement of loss, theft, destruction, mutilation, or defacement of Loan Note Guarantee or...

Code of Federal Regulations, 2010 CFR

2010-01-01

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78 FR 64175 - Hashemite Kingdom of Jordan Loan Guarantees Issued Under the Further Continuing Appropriations...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-28

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26 CFR 1.817A-1 - Certain modified guaranteed contracts.

Code of Federal Regulations, 2011 CFR

2011-04-01

... 26 Internal Revenue 8 2011-04-01 2011-04-01 false Certain modified guaranteed contracts. 1.817A-1... guaranteed contracts. (a) Definitions—(1) Modified guaranteed contract. The term modified guaranteed contract (MGC) is defined in section 817A(d) as an annuity, life insurance, or pension plan contract (other than...

22 CFR 221.13 - Non-impairment of the Guarantee.

Code of Federal Regulations, 2014 CFR

2014-04-01

... 22 Foreign Relations 1 2014-04-01 2014-04-01 false Non-impairment of the Guarantee. 221.13 Section 221.13 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.13 Non-impairment of the Guarantee. The full faith and credit of the United...

22 CFR 221.13 - Non-impairment of the Guarantee.

Code of Federal Regulations, 2013 CFR

2013-04-01

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22 CFR 221.13 - Non-impairment of the Guarantee.

Code of Federal Regulations, 2012 CFR

2012-04-01

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22 CFR 221.13 - Non-impairment of the Guarantee.

Code of Federal Regulations, 2011 CFR

2011-04-01

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22 CFR 221.13 - Non-impairment of the Guarantee.

Code of Federal Regulations, 2010 CFR

2010-04-01

... 22 Foreign Relations 1 2010-04-01 2010-04-01 false Non-impairment of the Guarantee. 221.13 Section 221.13 Foreign Relations AGENCY FOR INTERNATIONAL DEVELOPMENT ISRAEL LOAN GUARANTEE STANDARD TERMS AND CONDITIONS The Guarantee § 221.13 Non-impairment of the Guarantee. The full faith and credit of the United...

Urbanization Reduces Transfer of Diverse Environmental Microbiota Indoors

PubMed Central

Parajuli, Anirudra; Grönroos, Mira; Siter, Nathan; Puhakka, Riikka; Vari, Heli K.; Roslund, Marja I.; Jumpponen, Ari; Nurminen, Noora; Laitinen, Olli H.; Hyöty, Heikki; Rajaniemi, Juho; Sinkkonen, Aki

2018-01-01

Expanding urbanization is a major factor behind rapidly declining biodiversity. It has been proposed that in urbanized societies, the rarity of contact with diverse environmental microbiota negatively impacts immune function and ultimately increases the risk for allergies and other immune-mediated disorders. Surprisingly, the basic assumption that urbanization reduces exposure to environmental microbiota and its transfer indoors has rarely been examined. We investigated if the land use type around Finnish homes affects the diversity, richness, and abundance of bacterial communities indoors. Debris deposited on standardized doormats was collected in 30 rural and 26 urban households in and near the city of Lahti, Finland, in August 2015. Debris was weighed, bacterial community composition determined by high throughput sequencing of bacterial 16S ribosomal RNA (rRNA) gene on the Illumina MiSeq platform, and the percentage of four different land use types (i.e., built area, forest, transitional, and open area) within 200 m and 2000 m radiuses from each household was characterized. The quantity of doormat debris was inversely correlated with coverage of built area. The diversity of total bacterial, Proteobacterial, Actinobacterial, Bacteroidetes, and Firmicutes communities decreased as the percentage of built area increased. Their richness followed the same pattern except for Firmicutes for which no association was observed. The relative abundance of Proteobacteria and particularly Gammaproteobacteria increased, whereas that of Actinobacteria decreased with increasing built area. Neither Phylum Firmicutes nor Bacteroidetes varied with coverage of built area. Additionally, the relative abundance of potentially pathogenic bacterial families and genera increased as the percentage of built area increased. Interestingly, having domestic animals (including pets) only altered the association between the richness of Gammaproteobacteria and diversity of Firmicutes with the built area coverage suggesting that animal ownership minimally affects transfer of environmental microbiota indoors from the living environment. These results support the hypothesis that people living in densely built areas are less exposed to diverse environmental microbiota than people living in more sparsely built areas. PMID:29467728

A comprehensive review of available epidemiologic and HIV service data for female sex workers, men who have sex with men, and people who inject drugs in select West and Central African countries.

PubMed

MacAllister, Jack; Sherwood, Jennifer; Galjour, Joshua; Robbins, Sarah; Zhao, Jinkou; Dam, Kim; Grosso, Ashley; Baral, Stefan D

2015-03-01

To identify gaps in epidemiologic and HIV service coverage data for key populations (KP), including men who have sex with men (MSM), female sex workers (FSW), people who inject drugs (PWID), and transgender persons, in 8 West and Central Africa countries: Cameroon, Chad, Cote d'Ivoire, Democratic Republic of Congo, Ghana, Guinea-Bissau, Niger, and Nigeria. A comprehensive search of peer-reviewed literature was conducted using PubMed and MEDLINE. This search was supplemented by an additional search of relevant non-peer-reviewed, or gray, literature. Available data on HIV prevalence, KP size estimates, HIV prevention service targets, and HIV prevention service coverage, including the availability of population-specific minimum packages of services, were included in the review. No data for transgender persons were found. HIV prevalence data and size estimates were more frequently available for FSW, followed by MSM. Only 2 countries (Ghana and Nigeria) had both KP size estimates and HIV prevalence data for PWID. The degree to which HIV prevention service targets were adopted was highly variable across the selected countries, and the collection of relevant HIV prevention service coverage data for those targets that were identified was inconsistent. Population-specific minimum packages of services were identified in 3 countries (Cote d'Ivoire, Ghana, and Nigeria), although only Ghana and Nigeria included services for PWID. Epidemiologic and HIV prevention service data for FSW, MSM, PWID, and transgender persons remain sparse, and these KP are inconsistently accounted for in-service delivery and nationally endorsed minimum packages of HIV services in West and Central Africa. The strengthening of data collection and reporting to consistently include KP and the inclusion of that data in national planning is imperative for effectively addressing the HIV epidemic.

Satellite-based PM concentrations and their application to COPD in Cleveland, OH

PubMed Central

Kumar, Naresh; Liang, Dong; Comellas, Alejandro; Chu, Allen D.; Abrams, Thad

2014-01-01

A hybrid approach is proposed to estimate exposure to fine particulate matter (PM2.5) at a given location and time. This approach builds on satellite-based aerosol optical depth (AOD), air pollution data from sparsely distributed Environmental Protection Agency (EPA) sites and local time–space Kriging, an optimal interpolation technique. Given the daily global coverage of AOD data, we can develop daily estimate of air quality at any given location and time. This can assure unprecedented spatial coverage, needed for air quality surveillance and management and epidemiological studies. In this paper, we developed an empirical relationship between the 2 km AOD and PM2.5 data from EPA sites. Extrapolating this relationship to the study domain resulted in 2.3 million predictions of PM2.5 between 2000 and 2009 in Cleveland Metropolitan Statistical Area (MSA). We have developed local time–space Kriging to compute exposure at a given location and time using the predicted PM2.5. Daily estimates of PM2.5 were developed for Cleveland MSA between 2000 and 2009 at 2.5 km spatial resolution; 1.7 million (~79.8%) of 2.13 million predictions required for multiyear and geographic domain were robust. In the epidemiological application of the hybrid approach, admissions for an acute exacerbation of chronic obstructive pulmonary disease (AECOPD) was examined with respect to time–space lagged PM2.5 exposure. Our analysis suggests that the risk of AECOPD increases 2.3% with a unit increase in PM2.5 exposure within 9 days and 0.05° (~5 km) distance lags. In the aggregated analysis, the exposed groups (who experienced exposure to PM2.5 >15.4 μg/m3) were 54% more likely to be admitted for AECOPD than the reference group. The hybrid approach offers greater spatiotemporal coverage and reliable characterization of ambient concentration than conventional in situ monitoring-based approaches. Thus, this approach can potentially reduce exposure misclassification errors in the conventional air pollution epidemiology studies. PMID:24045428

High-Resolution Geomorphometry of Seamounts of the Young Walvis Ridge Guyot Province

NASA Astrophysics Data System (ADS)

Schnur, S. R.; Koppers, A. A.

2012-12-01

In February and March 2012, cruise MV1203 surveyed and dredged seamounts at the young end of the Walvis Ridge hotspot trail in the South Atlantic. The scientific goals were to better understand the hotspot origins of the Walvis Ridge by collecting rock samples for high-precision 40Ar/39Ar geochronology and by investigating the relationship between seamount morphology and different mechanisms of intra-plate volcanism. The area had until now been only sparsely-sampled, and most of the seamounts had never been mapped with multibeam. Here we present a geomorphometric analysis of edifice size and shape parameters from 74 seamounts of the young Walvis Ridge guyot province. The base data for each seamount consists of Simrad EM122 multibeam bathymetry combined with bathymetry from the SRTM30 PLUS compilation (V7.0: Becker et al., 2009; Sandwell and Smith, 2009), gridded at 180 m resolution. Multibeam coverage of individual seamounts ranges from 100% for small seamounts to 15% for large seamounts, with most seamounts having at least 50% coverage. Most of this data focuses on seamount flanks rather than flat guyot tops, covering the areas of greatest topographic variability even for seamounts with relatively low multibeam coverage. For each seamount we quantify edifice height, perimeter, volume, elongation, azimuth, irregularity and distance to nearest neighbor. These variables are compared to the age of the underlying crust, distance to the Mid-Atlantic Ridge and distance from the Etendeka flood basalts of Namibia, which are thought to signal the initial stages of hotspot volcanism at the old end of the chain. Additionally we assess how the addition of high resolution data affects these geomorphologic parameters. We will present an overview of the cruise outcomes as well as highlight unusual features observed in the new bathymetry and backscatter data. The cruise data suggest that the young Walvis Ridge guyot province holds great potential for further exploration and multidisciplinary research.

Feasibility of Very Large Sparse Aperture Deployable Antennas

DTIC Science & Technology

2014-03-27

FEASIBILITY OF VERY LARGE SPARSE APERTURE DEPLOYABLE ANTENNAS THESIS Jason C. Heller, Captain...States. AFIT-ENY-14-M-24 FEASIBILITY OF VERY LARGE SPARSE APERTURE DEPLOYABLE ANTENNAS THESIS Presented to the Faculty...UNLIMITED AFIT-ENY-14-M-24 FEASIBILITY OF VERY LARGE SPARSE APERTURE DEPLOYABLE ANTENNAS Jason C. Heller, B.S., Aerospace

Efficient sparse matrix-matrix multiplication for computing periodic responses by shooting method on Intel Xeon Phi

NASA Astrophysics Data System (ADS)

Stoykov, S.; Atanassov, E.; Margenov, S.

2016-10-01

Many of the scientific applications involve sparse or dense matrix operations, such as solving linear systems, matrix-matrix products, eigensolvers, etc. In what concerns structural nonlinear dynamics, the computations of periodic responses and the determination of stability of the solution are of primary interest. Shooting method iswidely used for obtaining periodic responses of nonlinear systems. The method involves simultaneously operations with sparse and dense matrices. One of the computationally expensive operations in the method is multiplication of sparse by dense matrices. In the current work, a new algorithm for sparse matrix by dense matrix products is presented. The algorithm takes into account the structure of the sparse matrix, which is obtained by space discretization of the nonlinear Mindlin's plate equation of motion by the finite element method. The algorithm is developed to use the vector engine of Intel Xeon Phi coprocessors. It is compared with the standard sparse matrix by dense matrix algorithm and the one developed by Intel MKL and it is shown that by considering the properties of the sparse matrix better algorithms can be developed.

17 CFR 240.15c2-7 - Identification of quotations.

Code of Federal Regulations, 2010 CFR

2010-04-01

..., guarantee of profit, guarantee against loss, commission, markup, markdown, indication of interest and... account, guarantee of profit, guarantee against loss, commission, markup, markdown, indication of interest...

Liver segmentation from CT images using a sparse priori statistical shape model (SP-SSM).

PubMed

Wang, Xuehu; Zheng, Yongchang; Gan, Lan; Wang, Xuan; Sang, Xinting; Kong, Xiangfeng; Zhao, Jie

2017-01-01

This study proposes a new liver segmentation method based on a sparse a priori statistical shape model (SP-SSM). First, mark points are selected in the liver a priori model and the original image. Then, the a priori shape and its mark points are used to obtain a dictionary for the liver boundary information. Second, the sparse coefficient is calculated based on the correspondence between mark points in the original image and those in the a priori model, and then the sparse statistical model is established by combining the sparse coefficients and the dictionary. Finally, the intensity energy and boundary energy models are built based on the intensity information and the specific boundary information of the original image. Then, the sparse matching constraint model is established based on the sparse coding theory. These models jointly drive the iterative deformation of the sparse statistical model to approximate and accurately extract the liver boundaries. This method can solve the problems of deformation model initialization and a priori method accuracy using the sparse dictionary. The SP-SSM can achieve a mean overlap error of 4.8% and a mean volume difference of 1.8%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 0.8 mm and 1.4 mm, respectively.

Feature Selection and Pedestrian Detection Based on Sparse Representation.

PubMed

Yao, Shihong; Wang, Tao; Shen, Weiming; Pan, Shaoming; Chong, Yanwen; Ding, Fei

2015-01-01

Pedestrian detection have been currently devoted to the extraction of effective pedestrian features, which has become one of the obstacles in pedestrian detection application according to the variety of pedestrian features and their large dimension. Based on the theoretical analysis of six frequently-used features, SIFT, SURF, Haar, HOG, LBP and LSS, and their comparison with experimental results, this paper screens out the sparse feature subsets via sparse representation to investigate whether the sparse subsets have the same description abilities and the most stable features. When any two of the six features are fused, the fusion feature is sparsely represented to obtain its important components. Sparse subsets of the fusion features can be rapidly generated by avoiding calculation of the corresponding index of dimension numbers of these feature descriptors; thus, the calculation speed of the feature dimension reduction is improved and the pedestrian detection time is reduced. Experimental results show that sparse feature subsets are capable of keeping the important components of these six feature descriptors. The sparse features of HOG and LSS possess the same description ability and consume less time compared with their full features. The ratios of the sparse feature subsets of HOG and LSS to their full sets are the highest among the six, and thus these two features can be used to best describe the characteristics of the pedestrian and the sparse feature subsets of the combination of HOG-LSS show better distinguishing ability and parsimony.

Introducing the National Institute for Sports Medicine in Hungary: a complex sports medical healthcare and screening system.

PubMed

Laki, Judit; Soós, Ágnes; Jákó, Péter; Tállay, András; Perjés, Ábel; Szabó, Anita Megyeriné

2017-01-01

The Hungarian National Institute for Sports Medicine (NISM) was founded in 1952 to provide medical coverage for national teams, screening and periodic health evaluation (PHE) for all Hungarian athletes. The system of 'all in one and ASAP' evolved by now to a specific state-funded healthcare provider with complex sports medical and sport-related services available for athletes. The NISM created a countrywide network to make health clearance available for all athletes close to their place of residency. This centralised system guarantees the uniformity and financial independence of the network, as it is directly financed by the government and free for every competitive athlete. Thus, it leaves no chance for conflict of interest in evaluating athletes' eligibility. In 2013, NISM established an online registry for preparticipation screening and PHE. This made the registry available for sports physicians and certain data for both sports physicians and athletes themselves. Furthermore, NISM created a nationwide, centrally coordinated, out of turn care with central coordination for elite athletes nationwide. Outpatient and inpatient clinics of NISM provide sports-specific care. Most of the minimally invasive techniques used at the Department of Sports Surgery are applied only here in the country. The medical staff of NISM has special experience in Sports Medicine and sport-related conditions. All tasks are managed within the same system, within institutional frames by professionals at Sports Medicine, which guarantees institutional expertise, competence and responsibility. Our aim is to introduce the complex system, the services and the recent achievements of the Hungarian NISM.

Introducing the National Institute for Sports Medicine in Hungary: a complex sports medical healthcare and screening system

PubMed Central

Laki, Judit; Soós, Ágnes; Jákó, Péter; Tállay, András; Perjés, Ábel; Szabó, Anita Megyeriné

2017-01-01

The Hungarian National Institute for Sports Medicine (NISM) was founded in 1952 to provide medical coverage for national teams, screening and periodic health evaluation (PHE) for all Hungarian athletes. The system of ‘all in one and ASAP’ evolved by now to a specific state-funded healthcare provider with complex sports medical and sport-related services available for athletes. The NISM created a countrywide network to make health clearance available for all athletes close to their place of residency. This centralised system guarantees the uniformity and financial independence of the network, as it is directly financed by the government and free for every competitive athlete. Thus, it leaves no chance for conflict of interest in evaluating athletes’ eligibility. In 2013, NISM established an online registry for preparticipation screening and PHE. This made the registry available for sports physicians and certain data for both sports physicians and athletes themselves. Furthermore, NISM created a nationwide, centrally coordinated, out of turn care with central coordination for elite athletes nationwide. Outpatient and inpatient clinics of NISM provide sports-specific care. Most of the minimally invasive techniques used at the Department of Sports Surgery are applied only here in the country. The medical staff of NISM has special experience in Sports Medicine and sport-related conditions. All tasks are managed within the same system, within institutional frames by professionals at Sports Medicine, which guarantees institutional expertise, competence and responsibility. Our aim is to introduce the complex system, the services and the recent achievements of the Hungarian NISM. PMID:29071113

76 FR 39068 - Guarantee Fee Rates for Guaranteed Loans for Fiscal Year 2011; Maximum Portion of Guarantee...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-05

... fundamental structural changes in its economic base. For guaranteed loans exceeding 80 percent, such projects...'s ability to focus guarantee assistance on projects which the Agency has found particularly... farmers benefiting financially, or such projects are high impact as defined in 7 CFR 4279.155(b)(5), and...

Artic and subarctic environmental analyses utilizing ERTS-1 imagery. Cold regions environmental analysis based on ERTS-1 imagery (preprint)

NASA Technical Reports Server (NTRS)

Anderson, D. M. (Principal Investigator); Haugen, R. K.; Gatto, L. W.; Slaughter, C. W.; Marlar, T. L.; Mckim, H. L.

1972-01-01

There are no author-identified significant results in this report. An overriding problem in arctic and subarctic environmental research has been the absence of long-term observational data and the sparseness of geographical coverage of existing data. A first look report is presented on the use of ERTS-1 imagery as a major tool in two large area environmental studies: (1) investigation of sedimentation and other nearshore marine processes in Cook Inlet, Alaska; and (2) a regional study of permafrost regimes in the discontinuous permafrost zone of Alaska. These studies incorporate ground truth acquisition techniques that are probably similar to most ERTS investigations. Studies of oceanographic processes in Cook Inlet will be focused on seasonal changes in nearshore bathymetry, tidal and major current circulation patterns, and coastal sedimentation processes, applicable to navigation, construction, and maintenance of harbors. Analyses will be made of the regional permafrost distribution and regimes in the Upper Koyukuk-Kobuk River area located in NW Alaska.

Remote sensing of surface currents with single shipborne high-frequency surface wave radar

NASA Astrophysics Data System (ADS)

Wang, Zhongbao; Xie, Junhao; Ji, Zhenyuan; Quan, Taifan

2016-01-01

High-frequency surface wave radar (HFSWR) is a useful technology for remote sensing of surface currents. It usually requires two (or more) stations spaced apart to create a two-dimensional (2D) current vector field. However, this method can only obtain the measurements within the overlapping coverage, which wastes most of the data from only one radar observation. Furthermore, it increases observation's costs significantly. To reduce the number of required radars and increase the ocean area that can be measured, this paper proposes an economical methodology for remote sensing of the 2D surface current vector field using single shipborne HFSWR. The methodology contains two parts: (1) a real space-time multiple signal classification (MUSIC) based on sparse representation and unitary transformation techniques is developed for measuring the radial currents from the spreading first-order spectra, and (2) the stream function method is introduced to obtain the 2D surface current vector field. Some important conclusions are drawn, and simulations are included to validate the correctness of them.

On the sensitivity of numerical weather prediction to remotely sensed marine surface wind data - A simulation study

NASA Technical Reports Server (NTRS)

Cane, M. A.; Cardone, V. J.; Halem, M.; Halberstam, I.

1981-01-01

The reported investigation has the objective to assess the potential impact on numerical weather prediction (NWP) of remotely sensed surface wind data. Other investigations conducted with similar objectives have not been satisfactory in connection with a use of procedures providing an unrealistic distribution of initial errors. In the current study, care has been taken to duplicate the actual distribution of information in the conventional observing system, thus shifting the emphasis from accuracy of the data to the data coverage. It is pointed out that this is an important consideration in assessing satellite observing systems since experience with sounder data has shown that improvements in forecasts due to satellite-derived information is due less to a general error reduction than to the ability to fill data-sparse regions. The reported study concentrates on the evaluation of the observing system simulation experimental design and on the assessment of the potential of remotely sensed marine surface wind data.

Sparse whole genome sequencing identifies two loci for major depressive disorder

PubMed Central

2015-01-01

Major depressive disorder (MDD), one of the most frequently encountered forms of mental illness and a leading cause of disability worldwide1, poses a major challenge to genetic analysis. To date no robustly replicated genetic loci have been identified 2, despite analysis of more than 9,000 cases3. Using low coverage genome sequence of 5,303 Chinese women with recurrent MDD selected to reduce phenotypic heterogeneity, and 5,337 controls screened to exclude MDD, we identified and replicated two genome-wide significant loci contributing to risk of MDD on chromosome 10: one near the SIRT1 gene (P-value = 2.53×10−10) the other in an intron of the LHPP gene (P = 6.45×10−12). Analysis of 4,509 cases with a severe subtype of MDD, melancholia, yielded an increased genetic signal at the SIRT1 locus. We attribute our success to the recruitment of relatively homogeneous cases with severe illness. PMID:26176920

The Biogeography of Putative Microbial Antibiotic Production

PubMed Central

Bryant, Jessica A.; Charkoudian, Louise K.; Docherty, Kathryn M.; Jones, Evan; Kembel, Steven W.; Green, Jessica L.; Bohannan, Brendan J. M.

2015-01-01

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. PMID:26102275

Current state and projection of the probable original vegetation of the São Carlos region of São Paulo State, Brazil.

PubMed

Soares, J J; da Silva, D W; Lima, M I

2003-08-01

A map of the native vegetation remaining in São Carlos County was built based on aerial images, satellite images, and field observations, and a projection of the probable original vegetation was made by checking it against soil and relief surveys. The existing vegetation is very fragmented and improverished, consisting predominantly of cerrados (savanna vegetation of various physiognomies), semideciduous and riparian forest, and regeneration areas. Araucaria angustifolia (Bertol.) Kuntze, found in patches inside the semideciduous forest beginning at a minimum altitude of 850 m, has practically disappeared. By evaluating areas on the map for different forms of vegetation, we obtained the following results for original coverage: 27% cerrado (sparsely arboreal and short-shrub savanna, and wet meadows); 16% cerradão (arboreal savanna); 55% semideciduous and riparian forests; and 2% forest with A. angustifolia. There are now 2% cerrados; 2.5% cerradão; 1% semideciduous forest and riparian forests; 1.5% regeneration areas; and 0% forest with A. angustifolia.

Input-Guarantee Versus Performance-Guarantee Approaches to School Accountability: Cross-State Comparisons of Policies, Resources, and Outcomes

ERIC Educational Resources Information Center

Lee, Jaekyung

2006-01-01

States' policy approaches to accountability tend to divide between a primary emphasis on input guarantees and a primary emphasis on performance guarantees. In the midst of keen controversies about the impact of high-stakes testing under the No Child Left Behind Act, this article examines separate and joint effects of input-guarantee versus…

7 CFR 1779.64 - Issuance of Lender's Agreement, Loan Note Guarantee, and Assignment Guarantee Agreement.

Code of Federal Regulations, 2010 CFR

2010-01-01

... of Agriculture (Continued) RURAL UTILITIES SERVICE, DEPARTMENT OF AGRICULTURE (CONTINUED) WATER AND WASTE DISPOSAL PROGRAMS GUARANTEED LOANS § 1779.64 Issuance of Lender's Agreement, Loan Note Guarantee...

Sparse Regression as a Sparse Eigenvalue Problem

NASA Technical Reports Server (NTRS)

Moghaddam, Baback; Gruber, Amit; Weiss, Yair; Avidan, Shai

2008-01-01

We extend the l0-norm "subspectral" algorithms for sparse-LDA [5] and sparse-PCA [6] to general quadratic costs such as MSE in linear (kernel) regression. The resulting "Sparse Least Squares" (SLS) problem is also NP-hard, by way of its equivalence to a rank-1 sparse eigenvalue problem (e.g., binary sparse-LDA [7]). Specifically, for a general quadratic cost we use a highly-efficient technique for direct eigenvalue computation using partitioned matrix inverses which leads to dramatic x103 speed-ups over standard eigenvalue decomposition. This increased efficiency mitigates the O(n4) scaling behaviour that up to now has limited the previous algorithms' utility for high-dimensional learning problems. Moreover, the new computation prioritizes the role of the less-myopic backward elimination stage which becomes more efficient than forward selection. Similarly, branch-and-bound search for Exact Sparse Least Squares (ESLS) also benefits from partitioned matrix inverse techniques. Our Greedy Sparse Least Squares (GSLS) generalizes Natarajan's algorithm [9] also known as Order-Recursive Matching Pursuit (ORMP). Specifically, the forward half of GSLS is exactly equivalent to ORMP but more efficient. By including the backward pass, which only doubles the computation, we can achieve lower MSE than ORMP. Experimental comparisons to the state-of-the-art LARS algorithm [3] show forward-GSLS is faster, more accurate and more flexible in terms of choice of regularization

Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA) for Lp-Regularization Using the Multiple Sub-Dictionary Representation

PubMed Central

Zhang, Jie; Fan, Shangang; Xiong, Jian; Cheng, Xiefeng; Sari, Hikmet; Adachi, Fumiyuki

2017-01-01

Both L1/2 and L2/3 are two typical non-convex regularizations of Lp (0

Sparse Adaptive Iteratively-Weighted Thresholding Algorithm (SAITA) for Lp-Regularization Using the Multiple Sub-Dictionary Representation.

PubMed

Li, Yunyi; Zhang, Jie; Fan, Shangang; Yang, Jie; Xiong, Jian; Cheng, Xiefeng; Sari, Hikmet; Adachi, Fumiyuki; Gui, Guan

2017-12-15

Both L 1/2 and L 2/3 are two typical non-convex regularizations of L p (0

Sparse, decorrelated odor coding in the mushroom body enhances learned odor discrimination.

PubMed

Lin, Andrew C; Bygrave, Alexei M; de Calignon, Alix; Lee, Tzumin; Miesenböck, Gero

2014-04-01

Sparse coding may be a general strategy of neural systems for augmenting memory capacity. In Drosophila melanogaster, sparse odor coding by the Kenyon cells of the mushroom body is thought to generate a large number of precisely addressable locations for the storage of odor-specific memories. However, it remains untested how sparse coding relates to behavioral performance. Here we demonstrate that sparseness is controlled by a negative feedback circuit between Kenyon cells and the GABAergic anterior paired lateral (APL) neuron. Systematic activation and blockade of each leg of this feedback circuit showed that Kenyon cells activated APL and APL inhibited Kenyon cells. Disrupting the Kenyon cell-APL feedback loop decreased the sparseness of Kenyon cell odor responses, increased inter-odor correlations and prevented flies from learning to discriminate similar, but not dissimilar, odors. These results suggest that feedback inhibition suppresses Kenyon cell activity to maintain sparse, decorrelated odor coding and thus the odor specificity of memories.

Sparse decomposition of seismic data and migration using Gaussian beams with nonzero initial curvature

NASA Astrophysics Data System (ADS)

Liu, Peng; Wang, Yanfei

2018-04-01

We study problems associated with seismic data decomposition and migration imaging. We first represent the seismic data utilizing Gaussian beam basis functions, which have nonzero curvature, and then consider the sparse decomposition technique. The sparse decomposition problem is an l0-norm constrained minimization problem. In solving the l0-norm minimization, a polynomial Radon transform is performed to achieve sparsity, and a fast gradient descent method is used to calculate the waveform functions. The waveform functions can subsequently be used for sparse Gaussian beam migration. Compared with traditional sparse Gaussian beam methods, the seismic data can be properly reconstructed employing fewer Gaussian beams with nonzero initial curvature. The migration approach described in this paper is more efficient than the traditional sparse Gaussian beam migration.

A performance study of sparse Cholesky factorization on INTEL iPSC/860

NASA Technical Reports Server (NTRS)

Zubair, M.; Ghose, M.

1992-01-01

The problem of Cholesky factorization of a sparse matrix has been very well investigated on sequential machines. A number of efficient codes exist for factorizing large unstructured sparse matrices. However, there is a lack of such efficient codes on parallel machines in general, and distributed machines in particular. Some of the issues that are critical to the implementation of sparse Cholesky factorization on a distributed memory parallel machine are ordering, partitioning and mapping, load balancing, and ordering of various tasks within a processor. Here, we focus on the effect of various partitioning schemes on the performance of sparse Cholesky factorization on the Intel iPSC/860. Also, a new partitioning heuristic for structured as well as unstructured sparse matrices is proposed, and its performance is compared with other schemes.

A new entity for the negotiation of public procurement prices for patented medicines in Mexico.

PubMed

Gómez-Dantés, Octavio; Wirtz, Veronika J; Reich, Michael R; Terrazas, Paulina; Ortiz, Maki

2012-10-01

As countries expand health insurance coverage, their expenditures on medicines increase. To address this problem, WHO has recommended that every country draw up a list of essential medicines. Although most medicines on the list are generics, in many countries patented medicines represent a substantial portion of pharmaceutical expenditure. To help control expenditure on patented medicines, in 2008 the Mexican Government created the Coordinating Commission for Negotiating the Price of Medicines and other Health Inputs (CCPNM), whose role, as the name suggests, is to enter into price negotiations with drug manufacturers for patented drugs on Mexico's list of essential medicines. Mexico's public expenditure on pharmaceuticals has increased substantially in the past decade owing to government efforts to achieve universal health-care coverage through Seguro Popular, an insurance programme introduced in 2004 that guarantees access to a comprehensive package of health services and medicines. Since 2008, the CCPNM has improved procurement practices in Mexico's public health institutions and has achieved significant price reductions resulting in substantial savings in public pharmaceutical expenditure. The CCPNM has successfully changed the landscape of price negotiation for patented medicines in Mexico. However, it is also facing challenges, including a lack of explicit indicators to assess CCPNM performance; a shortage of permanent staff with sufficient technical expertise; poor coordination among institutions in preparing background materials for the annual negotiation process in a timely manner; insufficient communication among committees and institutions; and a lack of political support to ensure the sustainability of the CCPNM.

An automatic markerless registration method for neurosurgical robotics based on an optical camera.

PubMed

Meng, Fanle; Zhai, Fangwen; Zeng, Bowei; Ding, Hui; Wang, Guangzhi

2018-02-01

Current markerless registration methods for neurosurgical robotics use the facial surface to match the robot space with the image space, and acquisition of the facial surface usually requires manual interaction and constrains the patient to a supine position. To overcome these drawbacks, we propose a registration method that is automatic and does not constrain patient position. An optical camera attached to the robot end effector captures images around the patient's head from multiple views. Then, high coverage of the head surface is reconstructed from the images through multi-view stereo vision. Since the acquired head surface point cloud contains color information, a specific mark that is manually drawn on the patient's head prior to the capture procedure can be extracted to automatically accomplish coarse registration rather than using facial anatomic landmarks. Then, fine registration is achieved by registering the high coverage of the head surface without relying solely on the facial region, thus eliminating patient position constraints. The head surface was acquired by the camera with a good repeatability accuracy. The average target registration error of 8 different patient positions measured with targets inside a head phantom was [Formula: see text], while the mean surface registration error was [Formula: see text]. The method proposed in this paper achieves automatic markerless registration in multiple patient positions and guarantees registration accuracy inside the head. This method provides a new approach for establishing the spatial relationship between the image space and the robot space.

Using Geostatistical Data Fusion Techniques and MODIS Data to Upscale Simulated Wheat Yield

NASA Astrophysics Data System (ADS)

Castrignano, A.; Buttafuoco, G.; Matese, A.; Toscano, P.

2014-12-01

Population growth increases food request. Assessing food demand and predicting the actual supply for a given location are critical components of strategic food security planning at regional scale. Crop yield can be simulated using crop models because is site-specific and determined by weather, management, length of growing season and soil properties. Crop models require reliable location-specific data that are not generally available. Obtaining these data at a large number of locations is time-consuming, costly and sometimes simply not feasible. An upscaling method to extend coverage of sparse estimates of crop yield to an appropriate extrapolation domain is required. This work is aimed to investigate the applicability of a geostatistical data fusion approach for merging remote sensing data with the predictions of a simulation model of wheat growth and production using ground-based data. The study area is Capitanata plain (4000 km2) located in Apulia Region, mostly cropped with durum wheat. The MODIS EVI/NDVI data products for Capitanata plain were downloaded from the Land Processes Distributed Active Archive Center (LPDAAC) remote for the whole crop cycle of durum wheat. Phenological development, biomass growth and grain quantity of durum wheat were simulated by the Delphi system, based on a crop simulation model linked to a database including soil properties, agronomical and meteorological data. Multicollocated cokriging was used to integrate secondary exhaustive information (multi-spectral MODIS data) with primary variable (sparsely distributed biomass/yield model predictions of durum wheat). The model estimates looked strongly spatially correlated with the radiance data (red and NIR bands) and the fusion data approach proved to be quite suitable and flexible to integrate data of different type and support.

The impact of the resolution of meteorological datasets on catchment-scale drought studies

NASA Astrophysics Data System (ADS)

Hellwig, Jost; Stahl, Kerstin

2017-04-01

Gridded meteorological datasets provide the basis to study drought at a range of scales, including catchment scale drought studies in hydrology. They are readily available to study past weather conditions and often serve real time monitoring as well. As these datasets differ in spatial/temporal coverage and spatial/temporal resolution, for most studies there is a tradeoff between these features. Our investigation examines whether biases occur when studying drought on catchment scale with low resolution input data. For that, a comparison among the datasets HYRAS (covering Central Europe, 1x1 km grid, daily data, 1951 - 2005), E-OBS (Europe, 0.25° grid, daily data, 1950-2015) and GPCC (whole world, 0.5° grid, monthly data, 1901 - 2013) is carried out. Generally, biases in precipitation increase with decreasing resolution. Most important variations are found during summer. In low mountain range of Central Europe the datasets of sparse resolution (E-OBS, GPCC) overestimate dry days and underestimate total precipitation since they are not able to describe high spatial variability. However, relative measures like the correlation coefficient reveal good consistencies of dry and wet periods, both for absolute precipitation values and standardized indices like the Standardized Precipitation Index (SPI) or Standardized Precipitation Evaporation Index (SPEI). Particularly the most severe droughts derived from the different datasets match very well. These results indicate that absolute values of sparse resolution datasets applied to catchment scale might be critical to use for an assessment of the hydrological drought at catchment scale, whereas relative measures for determining periods of drought are more trustworthy. Therefore, studies on drought, that downscale meteorological data, should carefully consider their data needs and focus on relative measures for dry periods if sufficient for the task.

High-resolution dynamic 31 P-MRSI using a low-rank tensor model.

PubMed

Ma, Chao; Clifford, Bryan; Liu, Yuchi; Gu, Yuning; Lam, Fan; Yu, Xin; Liang, Zhi-Pei

2017-08-01

To develop a rapid 31 P-MRSI method with high spatiospectral resolution using low-rank tensor-based data acquisition and image reconstruction. The multidimensional image function of 31 P-MRSI is represented by a low-rank tensor to capture the spatial-spectral-temporal correlations of data. A hybrid data acquisition scheme is used for sparse sampling, which consists of a set of "training" data with limited k-space coverage to capture the subspace structure of the image function, and a set of sparsely sampled "imaging" data for high-resolution image reconstruction. An explicit subspace pursuit approach is used for image reconstruction, which estimates the bases of the subspace from the "training" data and then reconstructs a high-resolution image function from the "imaging" data. We have validated the feasibility of the proposed method using phantom and in vivo studies on a 3T whole-body scanner and a 9.4T preclinical scanner. The proposed method produced high-resolution static 31 P-MRSI images (i.e., 6.9 × 6.9 × 10 mm 3 nominal resolution in a 15-min acquisition at 3T) and high-resolution, high-frame-rate dynamic 31 P-MRSI images (i.e., 1.5 × 1.5 × 1.6 mm 3 nominal resolution, 30 s/frame at 9.4T). Dynamic spatiospectral variations of 31 P-MRSI signals can be efficiently represented by a low-rank tensor. Exploiting this mathematical structure for data acquisition and image reconstruction can lead to fast 31 P-MRSI with high resolution, frame-rate, and SNR. Magn Reson Med 78:419-428, 2017. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Image fusion using sparse overcomplete feature dictionaries

DOEpatents

Brumby, Steven P.; Bettencourt, Luis; Kenyon, Garrett T.; Chartrand, Rick; Wohlberg, Brendt

2015-10-06

Approaches for deciding what individuals in a population of visual system "neurons" are looking for using sparse overcomplete feature dictionaries are provided. A sparse overcomplete feature dictionary may be learned for an image dataset and a local sparse representation of the image dataset may be built using the learned feature dictionary. A local maximum pooling operation may be applied on the local sparse representation to produce a translation-tolerant representation of the image dataset. An object may then be classified and/or clustered within the translation-tolerant representation of the image dataset using a supervised classification algorithm and/or an unsupervised clustering algorithm.

Institute for the Study of Sparsely Populated Areas. A Centre for Interdisciplinary Research into Sparsely Populated and Peripheral Regions.

ERIC Educational Resources Information Center

Sadler, Peter G.

The Institute for the Study of Sparsely Populated Areas is a multidisciplinary research unit which acts to coordinate, further, and initiate studies of the economic and social conditions of sparsely populated areas. Short summaries of the eight studies completed in the session of 1977-78 indicate work in such areas as the study of political life…

Disentangling giant component and finite cluster contributions in sparse random matrix spectra.

PubMed

Kühn, Reimer

2016-04-01

We describe a method for disentangling giant component and finite cluster contributions to sparse random matrix spectra, using sparse symmetric random matrices defined on Erdős-Rényi graphs as an example and test bed. Our methods apply to sparse matrices defined in terms of arbitrary graphs in the configuration model class, as long as they have finite mean degree.

Source-Type Identification Analysis Using Regional Seismic Moment Tensors

NASA Astrophysics Data System (ADS)

Chiang, A.; Dreger, D. S.; Ford, S. R.; Walter, W. R.

2012-12-01

Waveform inversion to determine the seismic moment tensor is a standard approach in determining the source mechanism of natural and manmade seismicity, and may be used to identify, or discriminate different types of seismic sources. The successful applications of the regional moment tensor method at the Nevada Test Site (NTS) and the 2006 and 2009 North Korean nuclear tests (Ford et al., 2009a, 2009b, 2010) show that the method is robust and capable for source-type discrimination at regional distances. The well-separated populations of explosions, earthquakes and collapses on a Hudson et al., (1989) source-type diagram enables source-type discrimination; however the question remains whether or not the separation of events is universal in other regions, where we have limited station coverage and knowledge of Earth structure. Ford et al., (2012) have shown that combining regional waveform data and P-wave first motions removes the CLVD-isotropic tradeoff and uniquely discriminating the 2009 North Korean test as an explosion. Therefore, including additional constraints from regional and teleseismic P-wave first motions enables source-type discrimination at regions with limited station coverage. We present moment tensor analysis of earthquakes and explosions (M6) from Lop Nor and Semipalatinsk test sites for station paths crossing Kazakhstan and Western China. We also present analyses of smaller events from industrial sites. In these sparse coverage situations we combine regional long-period waveforms, and high-frequency P-wave polarity from the same stations, as well as from teleseismic arrays to constrain the source type. Discrimination capability with respect to velocity model and station coverage is examined, and additionally we investigate the velocity model dependence of vanishing free-surface traction effects on seismic moment tensor inversion of shallow sources and recovery of explosive scalar moment. Our synthetic data tests indicate that biases in scalar seismic moment and discrimination for shallow sources are small and can be understood in a systematic manner. We are presently investigating the frequency dependence of vanishing traction of a very shallow (10m depth) M2+ chemical explosion recorded at several kilometer distances, and preliminary results indicate at the typical frequency passband we employ the bias does not affect our ability to retrieve the correct source mechanism but may affect the retrieval of the correct scalar seismic moment. Finally, we assess discrimination capability in a composite P-value statistical framework.

Optimized Design and Analysis of Sparse-Sampling fMRI Experiments

PubMed Central

Perrachione, Tyler K.; Ghosh, Satrajit S.

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power. PMID:23616742

Optimized design and analysis of sparse-sampling FMRI experiments.

PubMed

Perrachione, Tyler K; Ghosh, Satrajit S

2013-01-01

Sparse-sampling is an important methodological advance in functional magnetic resonance imaging (fMRI), in which silent delays are introduced between MR volume acquisitions, allowing for the presentation of auditory stimuli without contamination by acoustic scanner noise and for overt vocal responses without motion-induced artifacts in the functional time series. As such, the sparse-sampling technique has become a mainstay of principled fMRI research into the cognitive and systems neuroscience of speech, language, hearing, and music. Despite being in use for over a decade, there has been little systematic investigation of the acquisition parameters, experimental design considerations, and statistical analysis approaches that bear on the results and interpretation of sparse-sampling fMRI experiments. In this report, we examined how design and analysis choices related to the duration of repetition time (TR) delay (an acquisition parameter), stimulation rate (an experimental design parameter), and model basis function (an analysis parameter) act independently and interactively to affect the neural activation profiles observed in fMRI. First, we conducted a series of computational simulations to explore the parameter space of sparse design and analysis with respect to these variables; second, we validated the results of these simulations in a series of sparse-sampling fMRI experiments. Overall, these experiments suggest the employment of three methodological approaches that can, in many situations, substantially improve the detection of neurophysiological response in sparse fMRI: (1) Sparse analyses should utilize a physiologically informed model that incorporates hemodynamic response convolution to reduce model error. (2) The design of sparse fMRI experiments should maintain a high rate of stimulus presentation to maximize effect size. (3) TR delays of short to intermediate length can be used between acquisitions of sparse-sampled functional image volumes to increase the number of samples and improve statistical power.

Ontology Sparse Vector Learning Algorithm for Ontology Similarity Measuring and Ontology Mapping via ADAL Technology

NASA Astrophysics Data System (ADS)

Gao, Wei; Zhu, Linli; Wang, Kaiyun

2015-12-01

Ontology, a model of knowledge representation and storage, has had extensive applications in pharmaceutics, social science, chemistry and biology. In the age of “big data”, the constructed concepts are often represented as higher-dimensional data by scholars, and thus the sparse learning techniques are introduced into ontology algorithms. In this paper, based on the alternating direction augmented Lagrangian method, we present an ontology optimization algorithm for ontological sparse vector learning, and a fast version of such ontology technologies. The optimal sparse vector is obtained by an iterative procedure, and the ontology function is then obtained from the sparse vector. Four simulation experiments show that our ontological sparse vector learning model has a higher precision ratio on plant ontology, humanoid robotics ontology, biology ontology and physics education ontology data for similarity measuring and ontology mapping applications.

Enhancing adaptive sparse grid approximations and improving refinement strategies using adjoint-based a posteriori error estimates

DOE PAGES

Jakeman, J. D.; Wildey, T.

2015-01-01

In this paper we present an algorithm for adaptive sparse grid approximations of quantities of interest computed from discretized partial differential equations. We use adjoint-based a posteriori error estimates of the interpolation error in the sparse grid to enhance the sparse grid approximation and to drive adaptivity. We show that utilizing these error estimates provides significantly more accurate functional values for random samples of the sparse grid approximation. We also demonstrate that alternative refinement strategies based upon a posteriori error estimates can lead to further increases in accuracy in the approximation over traditional hierarchical surplus based strategies. Throughout this papermore » we also provide and test a framework for balancing the physical discretization error with the stochastic interpolation error of the enhanced sparse grid approximation.« less

7 CFR 762.145 - Restructuring guaranteed loans.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 7 2014-01-01 2014-01-01 false Restructuring guaranteed loans. 762.145 Section 762.145 Agriculture Regulations of the Department of Agriculture (Continued) FARM SERVICE AGENCY, DEPARTMENT OF AGRICULTURE SPECIAL PROGRAMS GUARANTEED FARM LOANS § 762.145 Restructuring guaranteed loans. (a...

7 CFR 1493.1 - General statement.

Code of Federal Regulations, 2012 CFR

2012-01-01

... AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS Restrictions and Criteria for Export Credit... use of credit guarantees under the Commodity Credit Corporation (CCC) Export Credit Guarantee Program (GSM-102) and the Intermediate Credit Guarantee Program (GSM-103) and the criteria considered by CCC in...

7 CFR 1493.1 - General statement.

Code of Federal Regulations, 2013 CFR

2013-01-01

... AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS Restrictions and Criteria for Export Credit... use of credit guarantees under the Commodity Credit Corporation (CCC) Export Credit Guarantee Program (GSM-102) and the Intermediate Credit Guarantee Program (GSM-103) and the criteria considered by CCC in...

7 CFR 1493.1 - General statement.

Code of Federal Regulations, 2014 CFR

2014-01-01

... AGRICULTURE EXPORT PROGRAMS CCC EXPORT CREDIT GUARANTEE PROGRAMS Restrictions and Criteria for Export Credit... use of credit guarantees under the Commodity Credit Corporation (CCC) Export Credit Guarantee Program (GSM-102) and the Intermediate Credit Guarantee Program (GSM-103) and the criteria considered by CCC in...

Practical Sub-Nyquist Sampling via Array-Based Compressed Sensing Receiver Architecture

DTIC Science & Technology

2016-07-10

different array ele- ments at different sub-Nyquist sampling rates. Signal processing inspired by the sparse fast Fourier transform allows for signal...reconstruction algorithms can be computationally demanding (REF). The related sparse Fourier transform algorithms aim to reduce the processing time nec- essary to...compute the DFT of frequency-sparse signals [7]. In particular, the sparse fast Fourier transform (sFFT) achieves processing time better than the

Evidence for sparse synergies in grasping actions.

PubMed

Prevete, Roberto; Donnarumma, Francesco; d'Avella, Andrea; Pezzulo, Giovanni

2018-01-12

Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) - sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) - sparsity in synergy representation - i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) - a novel view combining both SC and SE - i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks.

Turbulent flows over sparse canopies

NASA Astrophysics Data System (ADS)

Sharma, Akshath; García-Mayoral, Ricardo

2018-04-01

Turbulent flows over sparse and dense canopies exerting a similar drag force on the flow are investigated using Direct Numerical Simulations. The dense canopies are modelled using a homogeneous drag force, while for the sparse canopy, the geometry of the canopy elements is represented. It is found that on using the friction velocity based on the local shear at each height, the streamwise velocity fluctuations and the Reynolds stress within the sparse canopy are similar to those from a comparable smooth-wall case. In addition, when scaled with the local friction velocity, the intensity of the off-wall peak in the streamwise vorticity for sparse canopies also recovers a value similar to a smooth-wall. This indicates that the sparse canopy does not significantly disturb the near-wall turbulence cycle, but causes its rescaling to an intensity consistent with a lower friction velocity within the canopy. In comparison, the dense canopy is found to have a higher damping effect on the turbulent fluctuations. For the case of the sparse canopy, a peak in the spectral energy density of the wall-normal velocity, and Reynolds stress is observed, which may indicate the formation of Kelvin-Helmholtz-like instabilities. It is also found that a sparse canopy is better modelled by a homogeneous drag applied on the mean flow alone, and not the turbulent fluctuations.

Optical coherence tomography retinal image reconstruction via nonlocal weighted sparse representation

NASA Astrophysics Data System (ADS)

Abbasi, Ashkan; Monadjemi, Amirhassan; Fang, Leyuan; Rabbani, Hossein

2018-03-01

We present a nonlocal weighted sparse representation (NWSR) method for reconstruction of retinal optical coherence tomography (OCT) images. To reconstruct a high signal-to-noise ratio and high-resolution OCT images, utilization of efficient denoising and interpolation algorithms are necessary, especially when the original data were subsampled during acquisition. However, the OCT images suffer from the presence of a high level of noise, which makes the estimation of sparse representations a difficult task. Thus, the proposed NWSR method merges sparse representations of multiple similar noisy and denoised patches to better estimate a sparse representation for each patch. First, the sparse representation of each patch is independently computed over an overcomplete dictionary, and then a nonlocal weighted sparse coefficient is computed by averaging representations of similar patches. Since the sparsity can reveal relevant information from noisy patches, combining noisy and denoised patches' representations is beneficial to obtain a more robust estimate of the unknown sparse representation. The denoised patches are obtained by applying an off-the-shelf image denoising method and our method provides an efficient way to exploit information from noisy and denoised patches' representations. The experimental results on denoising and interpolation of spectral domain OCT images demonstrated the effectiveness of the proposed NWSR method over existing state-of-the-art methods.

Adaptive regulation of sparseness by feedforward inhibition

PubMed Central

Assisi, Collins; Stopfer, Mark; Laurent, Gilles; Bazhenov, Maxim

2014-01-01

In the mushroom body of insects, odors are represented by very few spikes in a small number of neurons, a highly efficient strategy known as sparse coding. Physiological studies of these neurons have shown that sparseness is maintained across thousand-fold changes in odor concentration. Using a realistic computational model, we propose that sparseness in the olfactory system is regulated by adaptive feedforward inhibition. When odor concentration changes, feedforward inhibition modulates the duration of the temporal window over which the mushroom body neurons may integrate excitatory presynaptic input. This simple adaptive mechanism could maintain the sparseness of sensory representations across wide ranges of stimulus conditions. PMID:17660812

7 CFR 762.160 - Assignment of guarantee.

Code of Federal Regulations, 2014 CFR

2014-01-01

... 7 Agriculture 7 2014-01-01 2014-01-01 false Assignment of guarantee. 762.160 Section 762.160 Agriculture Regulations of the Department of Agriculture (Continued) FARM SERVICE AGENCY, DEPARTMENT OF AGRICULTURE SPECIAL PROGRAMS GUARANTEED FARM LOANS § 762.160 Assignment of guarantee. (a) The following...

7 CFR 1779.30 - Loan guarantee limitations.

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2010-01-01

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7 CFR 4279.149 - Personal and corporate guarantee.

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2014-01-01

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7 CFR 4279.149 - Personal and corporate guarantee.

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2013-01-01

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7 CFR 4279.149 - Personal and corporate guarantee.

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2012-01-01

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7 CFR 4279.149 - Personal and corporate guarantee.

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2011-01-01

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7 CFR 4279.149 - Personal and corporate guarantee.

Code of Federal Regulations, 2010 CFR

2010-01-01

... 7 Agriculture 15 2010-01-01 2010-01-01 false Personal and corporate guarantee. 4279.149 Section... Industry Loans § 4279.149 Personal and corporate guarantee. (a) Unconditional personal and corporate... adequately secured for loanmaking purposes. Agency approved personal and corporate guarantees for the full...

78 FR 48135 - Information Collection; Guaranteed Farm Loan Program

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-07

... Information Collection; Guaranteed Farm Loan Program AGENCY: Farm Service Agency, USDA. ACTION: Notice... revision of a currently approved information collection associated with the Guaranteed Farm Loan Program. This information collection is used to make and service loans guaranteed by FSA to eligible farmers and...